Next Article in Journal
Transcriptomic Analysis of the Campylobacter jejuni Response to T4-Like Phage NCTC 12673 Infection
Next Article in Special Issue
Bacteriophages of Myxococcus xanthus, a Social Bacterium
Previous Article in Journal
Viral Determinants of Virulence in Tick-Borne Flaviviruses
Previous Article in Special Issue
Analysis of 19 Highly Conserved Vibrio cholerae Bacteriophages Isolated from Environmental and Patient Sources Over a Twelve-Year Period
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Viruses
Volume 10
Issue 6
10.3390/v10060331
viruses-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Pseudomonas PB1-Like Phages: Whole Genomes from Metagenomes Offer Insight into an Abundant Group of Bacteriophages

by
Siobhan C. Watkins
1,†,
Emily Sible
1,‡ and
Catherine Putonti
1,2,3,*
1
Department of Biology, Loyola University Chicago, Chicago, IL 60660, USA
2
Department of Computer Science, Loyola University Chicago, Chicago, IL 60660, USA
3
Bioinformatics Program, Loyola University Chicago, Chicago, IL 60660, USA
*
Author to whom correspondence should be addressed.
†
Current Address: Biology Department, New Mexico Institute of Mining and Technology, Socorro, NM 87801, USA.
‡
Current Address: Biology Department, City University of New York, New York, NY 10031, USA.
Viruses 2018, 10(6), 331; https://doi.org/10.3390/v10060331
Submission received: 15 May 2018 / Revised: 11 June 2018 / Accepted: 11 June 2018 / Published: 16 June 2018
(This article belongs to the Special Issue Bacteriophage Genomes and Genomics: News from the Wild)
Browse Figures
Versions Notes

Abstract

:
Despite the abundance, ubiquity and impact of environmental viruses, their inherent genomic plasticity and extreme diversity pose significant challenges for the examination of bacteriophages on Earth. Viral metagenomic studies have offered insight into broader aspects of phage ecology and repeatedly uncover genes to which we are currently unable to assign function. A combined effort of phage isolation and metagenomic survey of Chicago’s nearshore waters of Lake Michigan revealed the presence of Pbunaviruses, relatives of the Pseudomonas phage PB1. This prompted our expansive investigation of PB1-like phages. Genomic signatures of PB1-like phages and Pbunaviruses were identified, permitting the unambiguous distinction between the presence/absence of these phages in soils, freshwater and wastewater samples, as well as publicly available viral metagenomic datasets. This bioinformatic analysis led to the de novo assembly of nine novel PB1-like phage genomes from a metagenomic survey of samples collected from Lake Michigan. While this study finds that Pbunaviruses are abundant in various environments of Northern Illinois, genomic variation also exists to a considerable extent within individual communities.

1. Introduction

Research on bacterial viruses (bacteriophages) has progressed remarkably over the last 100 years [1], and phages are now regarded as ubiquitous engineers of bacterial community structure and metabolism [2,3,4,5]. Despite this, the quantity of phage-related information stored in biological sequence repositories is meager. To date there are less than 2000 distinct species represented in GenBank, which is largely a reflection of the many challenges of working with phages in the laboratory [6]. High-throughput sequencing platforms have been instrumental in advancing current understanding of microbial community diversity [7]. Viral metagenomic studies of phage communities have significantly improved our ability to examine and understand viral diversity in the wild [8,9,10]. Meta-analyses have expanded the viral catalogue postulating new branches of the evolutionary tree for viruses [11,12,13]. Furthermore, metagenomics has permitted a glimpse into viral biogeography (e.g., [11,14,15,16]; see review [17]).
Methods for molecular [18,19,20] and computational [21,22,23] assessment of viral communities are being continuously developed and refined. The aforementioned methods, as well as other approaches employed in studies (e.g., clustering contigs based upon nucleotide usage and/or coverage (see review [24]), have resulted in the generation of numerous complete or near complete genomes of uncultivated prokaryotes [25,26,27,28,29,30,31,32,33,34,35,36,37] and viruses [11,28,30,34,38,39,40]. Additionally, complete phage genomes have been assembled from viral metagenomes through manual curation and BLAST searches [11,15,33,41,42,43,44,45,46,47,48]. Given the advances in DNA sequencing technology throughput, high-quality genomes derived solely from metagenomes are anticipated to become commonplace, challenging the way in which we classify new viruses [49]. Nevertheless, with the recent assemblies of the largest phage genome to date [11] and the first genomes of freshwater Actinobacteria-infecting phages [48], metagenomics has greatly expanded our understanding of phage genomic diversity.
The study presented here was initially informed by our previous work, in which four Pseudomonas aeruginosa-infecting PB1-like phages (genus: Pbunavirus) were isolated from the nearshore waters of Lake Michigan [50]. Other members of this genus have been isolated from freshwater, sewage and soil and predominately infect Pseudomonas species [51]. While Pseudomonas phage PB1 is the type species for Pbunavirus, over 40 members of this genus have been suggested on the basis of homology assessments [52]. Currently there are 31 Pbunavirus species with RefSeq genomes publicly available. These dsDNA viruses have a genome ~66 Kbp in length with 88 to 97 predicted coding regions. Given its lack of a recognizable integrase, it is presumed to be obligately lytic [53]. Recently, PB1-related phages have been isolated from sewage samples in Germany [54], Poland [55], and Portugal [56], wastewater in France [57], and river water in Brazil [58].
While Pseudomonas is a truly multi-faceted microorganism and is generally regarded as having a high presence in the aquatic environment, it is not a dominant member of freshwater habitats [59,60], from which we previously isolated four PB1-like phages [50]. Nevertheless, Pbunaviruses have been found in a variety of ecological niches across the globe [51,54,55,56,57,58]. This parallels observations for several marine phages that have been found across large geographic distances [11,13,61]. This led us to hypothesize that Pbunaviruses are widespread in nature. Integrating molecular and computational methods, the presence and abundance of PB1-like phages was assessed in soil, freshwater, and sewage samples.

2. Materials and Methods

2.1. Samples

Samples were collected from three bodies of freshwater: (1) Lake Defiance (42°19′19.4″ N 88°13′37.5″ W) in Moraine Hills State Park (McHenry, IL, USA) is an isolated lake/bog; (2) Grass Lake/Fox River (42°26′46.4″ N 88°10′50.2″ W) in the Chain O’Lakes State Park (Spring Grove, IL, USA) is located within a large interconnected chain of lakes and waterways; and (3) Lake Michigan’s Hartigan Beach Park (42°00′06.3″ N 87°39′22.3″ W). Two biological replicates, each 4 L, were collected from Lake Defiance and Grass Lake in August 2015. Five temporal replicates, each 4 L, were collected from the Hartigan Beach site (June–August 2015). Additionally, four samples of activated sludge, in triplicate (50 mL) were collected from the aeration basins of O’Brien Water Reclamation Plant (Skokie, IL, USA) in October 2014. Four replicate soil samples (50 g) were collected from the Loyola Lakeshore campus in August 2015. Each sample of activated sludge and soil were diluted with 500 mL phosphate buffered saline (PBS), agitated in a shaking incubator overnight. Sample locations are shown in Figure S1.

2.2. Viral DNA Extraction

Virus-like particles were purified from the collected samples through successive filtration: initially, through a sterile 0.45 μm bottle-top cellulose acetate membrane filter (Corning Inc., Corning, NY, USA) to remove plant matter, sand, debris, and eukaryotic cells, then through a 0.22 μm polyethersulfone membrane filter (MO BIO Laboratories, Carlsbad, CA, USA) to remove bacterial cells. The filtrate was then filtered and concentrated using a 0.10 μm polypropylene filter (EMD Millipore Corp, Billerica, MA, USA) with the Labscale™ tangential flow filtration (TFF) system (EMD Millipore Corp, Billerica, MA, USA) according to the manufacturer’s instructions. DNA was extracted from the TFF fraction using the MO BIO Laboratories UltraClean® DNA Isolation Kit (Carlsbad, CA, USA). The protocol recommended by the manufacturer was followed with the exception of an additional heat treatment at 70 °C for 20 min prior to initial vortexing.

2.3. PCR Amplification and Amplicon Analysis

PCR primers were designed to target conserved regions among the Pbunaviruses within the DNA of the collected samples. Primers and their expected amplicons (within the PB1 genome, GenBank: NC_011810) were queried against the nr/nt database. Five primer pairs were selected given their specificity for Pbunaviruses (Table 1). PCR primers were obtained from Eurofins MWG (Louisville, KY, USA). Thermal cycling conditions were designed based upon the individual primer pair’s Tm and expected amplicon size. PCR amplicons were purified (E.Z.N.A.® Cycle Pure Kit, Omega Bio-tek, Norcross, GA, USA) and sequenced in both directions via Sanger sequencing (Genewiz, South Plainfield, NJ, USA). Consensus sequences were queried via BLASTn. Sequences were aligned in Geneious, and consensus sequences were assessed for phylogenetic relatedness, visualized via a neighbor-joining tree created with the Geneious Tree Builder tool (v 8.0.5, Biomatters Limited, Auckland, NZ) using the Jukes-Cantor distance model with bootstrap resampling (100 replicates).

2.4. Determination of the Presence of PB1 and Pbunaviruses in Publicly Available Metagenomic Datasets

Raw sequence reads (fasta or fastq format) for publicly available viral metagenomes from freshwater, hot springs, wastewater, and soil samples were collected from the SRA database. Table S1 lists the datasets. Additional marine viromes were downloaded from the iMicrobe project (data.imicrobe.us), and datasets collected from open sea sampling expeditions, including raw read data from the Pacific Ocean Virome study [62], the Global Ocean Sampling Expedition [63], the Broad Marine Phage Sequencing Project (https://www.broadinstitute.org/annotation/viral/phage/home.html), and the Ocean Viruses project [64]. For each individual sample, sequence reads were assembled using Velvet [65] with a hash size of 31. A local BLAST database was created for each dataset and again the PB1 amino acid sequences were compared via blastx.
The highest scoring hit (with respect to both sequence identity and query coverage, bitscore) for each PB1 gene and individual viral metagenome assemblage was next compared to the threshold of similarity for Pbunaviruses generated in our prior work [66]. Briefly, each PB1 gene was compared to all other Pbunavirus genomes and all non-Pbunavirus phage genomes via BLAST. Intragenus and intergenus sequence similarity scores (again assessed via the BLAST bitscore) were calculated to ascertain the “informativity” of a PB1 gene. PB1 genes exhibiting sequence similarity on par with or greater than that of its most distant Pbunavirus relative (BcepF1) were deemed “uninformative” as signatures for PB1 and Pbunavirus genomes. Each viral metagenome’s sequence similarity to PB1 informative genes are represented in the atlas as the average of the query coverage and sequence identity values.

2.5. Assembly and Annotation of Uncultivated PB1-Like Genomes

Each of the Chicago area Lake Michigan viral metagenomic datasets [67] was assembled individually using the Geneious assembler (Geneious (v 8.0.5), Biomatters Ltd., Auckland, NZ), the SPAdes assembler [68] using the “meta” flag for metagenomic samples, and the Velvet assembler [65]. Geneious assemblies repeatedly produced greater N50 scores and were selected for further analysis. Contigs of length ≥ 20 Kbp were queried against the complete nr/nt database via the BLAST web interface. Contigs returning high sequence similarity (e-value < 0.00001) to PB1 (GenBank: NC_011810) or other Pbunaviruses were investigated further. From this pool, each contig was then used as a “reference genome” to which the raw reads for individual viral metagenomic samples were mapped using Bowtie2 [69]. This additional second stage mapping process served to quantify genome coverage and in some cases extend contigs. At no time was the RefSeq PB1 genome or any other published Pbunavirus genome used to “fish” for reads: assembly to complete full genomes were generated a priori. Furthermore, in several cases the complete genome was produced during the initial assembly. All genomes were then manually inspected, and coverage was computed using BBMap (sourceforge.net/projects/bbmap/). Genomes from five viral metagenomic datasets were removed from further consideration as they contained regions (≥100 bp) of low coverage (<5 paired end reads). Annotations were generated, using Geneious, according to the most recent PB1 annotation (GenBank: NC_011810), and manually inspected again. Genome sequences were deposited in GenBank, Accession numbers KT372690 through KT272698.

2.6. Comparative Genomics

The nine uncultivated Lake Michigan PB1-like genome sequences were adjusted to the same frame as the PB1 RefSeq sequence. Genome alignments were performed using the progressive Mauve algorithm [70] and visualized in Geneious. These nine genomes were compared to other available Pseudomonas-infecting Pbunavirus genomes: phages LMA2 (GenBank: NC_011166), SN (GenBank: NC_011756), 14-1 (GenBank: NC_0111703), F8 (GenBank: NC_007810), PB1 (GenBank: NC_011810), LBL3 (GenBank: NC_011165), φVader (GenBank: KT254130), φMoody (GenBank: KT254131), φHabibi (GenBank: KT254132), and φFenriz (GenBank: KT254133). A neighbor-joining phylogenetic tree was created for the publicly available genomes, including the four Lake Michigan isolates [50], and the nine uncultivated PB1-like genomes based upon this alignment. This tree was created with the Geneious Tree Builder tool using the Jukes-Cantor distance model with bootstrap resampling (100 replicates).

3. Results

3.1. Hunting for Pbunaviruses in Soil, Freshwater and Activated Sludge

In our previous work, we evaluated the coding sequences of PB1 and Pbunaviruses to identify genes (called “informative genes”) that can be used as signatures of PB1 strains as well as other Pbunaviruses [66]. We designed primer pairs targeting five genomic regions (see Methods; Table 1). These genomic regions target genes encoding hypothetical proteins as well as the annotated helicase (primer pair 3 in Table 1). Primer sequences as well as expected amplicon sequences (using the PB1 genome, GenBank: NC_011810) were queried using BLASTn; resulting hits were only to Pbunavirus species. Replicate samples of soil, activated sludge, and freshwater were collected from locations throughout northern Illinois (see Methods). Samples were filtered and concentrated, and the community DNA extracted and amplified with each of the primer sets (see Methods). DNA isolated from three Lake Michigan collections, made the year prior (2014) and within our existing collection, were amplified as well. Sanger sequencing of the resulting amplicons confirmed specific amplification of genes belonging to the Pbunaviruses; sequences were found to have a coverage >99% and sequence identity >99% to a Pbunavirus sequence in GenBank. Sequenced amplicons produced by primer pair 5 (amplifying genes encoding hypothetical proteins PB1_gp84, 85, 86) were using to construct a neighbor joining phylogenetic tree (Figure 1).

3.2. Searching for PB1 in Soil, Freshwater, and Activated Sludge Viral Metagenomes

In total, 104 DNA viral metagenomes (from various environments) were inspected for the presence of PB1-like phages, including 40 from Lake Michigan nearshore waters (nine from collections made in 2013 [71] and 31 from 2014 [67]), 12 from hot springs, 38 from other freshwater sources, 12 from sewage, and two from soil (Table S1). Raw data was gathered for all data samples and assembled individually (see Methods). First, a purely BLAST-based approach was evaluated; all 104 viral metagenome samples produced high-quality hits to currently annotated PB1 genes (Figure S2). The 104 metagenomes were next re-evaluated considering only ORFs informative of PB1 genes listed in Figure 2. These genes are present within PB1 strains and do not exhibit sequence similarity to gene sequences within non-Pbunaviruses. As can be seen in Figure 2, many of metagenomes do not produce a signal (shown in gray) signifying that the viral metagenome did not include a sequence similar to the annotated gene sequences of PB1-like phages. Nevertheless, informative genes are detected within two hot spring samples, 47 freshwater samples, 11 sewage samples, and one soil sample. With the exception of the Lake Michigan samples, many of the samples identified only one informative gene. It is worth noting that comparable analyses were conducted for viral metagenome sets from marine environments, although no signal of the presence of PB1 was detected. To date, no Pseudomonas-infecting Pbunaviruses have been collected from marine/oceanic samples.

3.3. Unique PB1-Like Phage Genomes Can Be Assembled and Closed from Viral Metagenome Data Generated from Lake Michigan

Given the abundance of informative genes within the 31 Lake Michigan datasets collected during 2014 (Figure 2), each was analyzed to determine the presence of complete or near-complete PB1-like phage genomes. De novo assemblies were performed for these 31 paired-end sequence datasets [67], exploring numerous different assemblers and parameters (see Methods). High-quality contigs were then queried via BLAST for the presence of PB1 genes. Hits were identified within contigs for 14 of these data sets. Further examination revealed that nine contained single contigs representative of complete, high coverage (15 to 220×) genomes of PB1-like phages. The five other datasets were excluded because of low coverage. The nine genomes ranged in size from 65,762 to 66,283 bp in length, each comprising 85–89 annotated genes (Table 2). Overall, the nine genomes had high nucleotide sequence identity to each other—greater than 99% (Table S2). In addition, each genome was assembled from a different water sample, either collected on different dates, at different locations or found within a different biological replicate (Table 2). Assembly did not require a subsequent laboratory-based effort to extend or close the genomes; rather each genome was fully assembled based on metagenomic data alone.
Comparing the uncultured PB1-like genomes to the PB1 RefSeq genome record revealed collinear blocks common to all, as well as open reading frames (ORFs) (all homologous to annotated hypothetical proteins) which were absent throughout the entire cohort (Figure 3a). The ORFs absent from or disturbed (often by a frameshift mutation or large indel) from one or more of the uncultivated Lake Michigan PB1-like viruses can be found in Table S3. A phylogenetic comparison of the candidate phages against other Pseudomonas-infecting members of the Pbunaviruses and the genomes of four PB1-like phages previously isolated from Lake Michigan [50] was performed (Figure 3b). The nine uncultivated Lake Michigan PB1-like viral genomes demonstrated closest similarities to PB1 and the previously isolated Lake Michigan phages and exhibited marked differences from the genomes of the other Pbunaviruses.

4. Discussion

Given the ubiquity of Pseudomonas, it is not surprising that Pbunaviruses have been previously isolated from a vast array of environments [50,51,54,55,56,57,58]. By targeting a collection of species and genus specific genes, Pbunaviruses were detected within soil, freshwater, and activated sludge samples collected here. Comparison of these amplicon sequences revealed sequence diversity; contrary to our initial expectations, samples collected from the same geographical location or source (soil, freshwater, activated sludge) did not clade together. While the amplicon sequences indicate that Pbunaviruses (or very close relatives) are present in northern Illinois, the phylogenetic tree suggests genetic variation amongst the samples that is not dictated by the type of environment sampled. Comprehensive analysis determined that the PB1-like phages, are, in fact, very well represented throughout datasets collected from Lake Michigan (Figure 2). The samples sequenced from collections made in the summer of 2014 [67] included more “informative genes” than the sequences from the samples collected in the summer of 2013. Nevertheless, these are the same sites from which the PB1-like phages φVader, φMoody, φHabibi, and φFenriz were isolated during the summer of 2013 [50].
The evidence for the presence of Pbunaviruses in other freshwaters, soils, wastewater, and hot springs metagenomes, is however, tenuous (Figure 2). This may be a result of differences in the sample sites themselves (e.g., oligotrophy, season, depth, etc.), sample preparation, sequencing depth and/or technology, or PB1 abundance within the particular sample. Interestingly, PB1 gp05 (128 amino acids in length) and gp74 (150 amino acids in length), both annotated as hypothetical proteins, are detected—often at very high levels—within these samples. Both of these genes were found to be Pbunavirus-specific, not present in any other sequenced phage genome. Furthermore, each was queried (tBLASTn) against the complete nr/nt database; all hits returned were to Pbunaviruses. BLASTp analysis confirmed that gp05 is exclusively found with Pbunavirus sequences and PB1′s gp74 amino acid sequence exhibited only modest sequence homology (57% query coverage and 42% sequence identity) to a hypothetical protein within the T4-like Pseudomonas putida-infecting phage pf16 [72]. These proteins are of particular interest with regards to characterizing their function. The detection of these two hypothetical proteins in other viral metagenomic samples can be the result of: (1) the presence of distant Pbunavirus relatives; (2) evidence of prior gene sharing between Pbunaviruses and other viral species; or (3) these similar sequences originating independently.
During examination of a viral metagenomic survey of Lake Michigan, we were able to assemble nine separate PB1-like genomes, de novo from the data generated. Variation was observed between the uncultivated assembled viruses including size. Three of the genomes, Kraken, Kula and Nemo, came from biological replicates collected from the same site (Calumet Beach) on 5 August 2014. From the pairwise assembly of the genomes of Kula and Nemo, 529 nucleotide differences were observed (Table S2). This suggests that even within a niche (as replicates were collected within a 5 m area [67]), significant viral microdiversity exists. Interestingly, a complete PB1-like genome was unable to be assembled from the fourth biological replicate collected. Variation was also observed among the nine genomes with respect to the number of ORFs identified. It is important to note that reading frames and predicted functions were determined based upon the PB1 genome annotation. Regions which are missing/disrupted in the new uncultivated viral genomes were predominantly PB1 annotated hypothetical proteins (Figure 3A; Table S3). Nevertheless, disruptions were observed in all 9 genomes for the minor head protein (PB1 gp18) and helicase (PB1 gp77). Nevertheless, the genomes of all nine uncultivated viruses were more similar to PB1-like viruses than other members of the genus.
Significant sequence coverage suggests that these phages were present in the Lake Michigan samples in high abundance. The nine genomes essentially fell out of the data, providing a more genuine representation of viral abundance than the number of hits alone. Luo et al. [73] estimated genomes may be assembled most accurately from metagenomes with a coverage of 20×—the coverage of many of the genomes examined in this study far exceeded this measure (Table 2). As with the discovery of crAssphage, ubiquitous in human fecal metagenomes [39], ultimately the efficacy of assembling entire genomes from complex environmental datasets is reliant on the initial high abundance of the organism, or an alternative factor which effectively places it as the low hanging fruit in that data. However, as generating complete genomes of other characterized phage genomes from our data was not possible, the former is likely the case here.
We were unable to produce a complete genome assembly of a PB1-like virus from the nine viral metagenomic dataset from Lake Michigan collected the year before and hits to informative genes in the PB1 genome were low throughout (Figure 2). This suggests that the incidence of PB1-like viruses was considerably higher, for whatever reason, during the 2014 sampling effort, and that the presence of this group of viruses is likely to be, unsurprisingly, dynamic. Nevertheless, we are confident that PB1 viruses were present during 2013 as four were isolated and characterized from these very same samples [50]. The results of culture-independent and culture-dependent methods further supports the presence of a dynamic community.
Although culture-based studies of phages can provide multiple key aspects of a phage’s ecology, the many challenges with working with phages in the laboratory [6] limit our understanding of their genetic diversity. Viral metagenomic studies, however, have the potential to uncover far more than just a phage’s genome [21]. Through comparative viral metagenomics we were able to identify samples for which PB1-like viruses were present as well as abundant, thereby providing insight into the phage’s ecology. Hypothesis-driven data mining coupled with experimental work, such as the approach presented here for the investigation of PB1-like viruses, has significant potential to greatly expand our understanding of phage ecology.

Supplementary Materials

The following are available online at https://www.mdpi.com/1999-4915/10/6/331/s1, Figure S1: Map of collection sites for this study. Figure S2: PB1 BLAST genome atlas. Bitscore values of BLAST queries for each PB1 gene in each metagenome is indicated. Table S1: Information about the viral metagenomic data sets evaluated for the presence of Pseudomonas phage PB1. Table S2: Sequence similarity between the nine uncultivated genomes assembled in this study. Table S3: List of coding sequences missing or disrupted genes in the nine uncultivated genomes.

Author Contributions

Conceptualization, S.C.W. and C.P.; Formal Analysis, S.C.W., E.S. and C.P., Data Curation, E.S. and C.P.; Writing, S.C.W. and C.P.

Acknowledgments

The authors thank Joy Watts for her comments on an early version of the manuscript. This work was funded by the NSF (1149387) (C.P.). E.S. was supported by a Mulcahy Research Fellowship from Loyola University Chicago.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Salmond, G.P.C.; Fineran, P.C. A century of the phage: Past, present and future. Nat. Rev. Microbiol. 2015, 13, 777–786. [Google Scholar] [CrossRef] [PubMed]
  2. Suttle, C.A. Viruses in the sea. Nature 2005, 437, 356–361. [Google Scholar] [CrossRef] [PubMed]
  3. Rohwer, F.; Thurber, R.V. Viruses manipulate the marine environment. Nature 2009, 459, 207–212. [Google Scholar] [CrossRef] [PubMed]
  4. Balcazar, J.L. Bacteriophages as vehicles for antibiotic resistance genes in the environment. PLoS Pathog. 2014, 10, e1004219. [Google Scholar] [CrossRef] [PubMed]
  5. Hargreaves, K.R.; Kropinski, A.M.; Clokie, M.R. Bacteriophage behavioral ecology: How phages alter their bacterial host’s habits. Bacteriophage 2014, 4, e29866. [Google Scholar] [CrossRef] [PubMed]
  6. Breitbart, M. Marine viruses: Truth or dare. Ann. Rev. Mar. Sci. 2012, 4, 425–448. [Google Scholar] [CrossRef] [PubMed]
  7. Hug, L.A.; Baker, B.J.; Anantharaman, K.; Brown, C.T.; Probst, A.J.; Castelle, C.J.; Butterfield, C.N.; Hernsdorf, A.W.; Amano, Y.; Ise, K.; et al. A new view of the tree of life. Nat. Microbiol. 2016, 1, 16048. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  8. Bruder, K.; Malki, K.; Cooper, A.; Sible, E.; Shapiro, J.W.; Watkins, S.C.; Putonti, C. Freshwater Metaviromics and Bacteriophages: A Current Assessment of the State of the Art in Relation to Bioinformatic Challenges. Evol. Bioinform. 2016, 12, 25–33. [Google Scholar] [CrossRef] [PubMed]
  9. Perez Sepulveda, B.; Redgwell, T.; Rihtman, B.; Pitt, F.; Scanlan, D.J.; Millard, A. Marine phage genomics: The tip of the iceberg. FEMS Microbiol. Lett. 2016, 363, fnw158. [Google Scholar] [CrossRef] [PubMed]
  10. Pratama, A.A.; van Elsas, J.D. The “Neglected” Soil Virome–Potential Role and Impact. Trends Microbiol. 2018. [Google Scholar] [CrossRef] [PubMed]
  11. Paez-Espino, D.; Eloe-Fadrosh, E.A.; Pavlopoulos, G.A.; Thomas, A.D.; Huntemann, M.; Mikhailova, N.; Rubin, E.; Ivanova, N.N.; Kyrpides, N.C. Uncovering Earth’s virome. Nature 2016, 536, 425–430. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  12. Roux, S.; Hallam, S.J.; Woyke, T.; Sullivan, M.B. Viral dark matter and virus–host interactions resolved from publicly available microbial genomes. eLife 2015, 4, e08490. [Google Scholar] [CrossRef] [PubMed]
  13. Coutinho, F.H.; Silveira, C.B.; Gregoracci, G.B.; Thompson, C.C.; Edwards, R.A.; Brussaard, C.P.D.; Dutilh, B.E.; Thompson, F.L. Marine viruses discovered via metagenomics shed light on viral strategies throughout the oceans. Nat. Commun. 2017, 8, 15955. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  14. Clokie, M.R.; Millard, A.D.; Letarov, A.V.; Heaphy, S. Phages in nature. Bacteriophage 2011, 1, 31–45. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  15. Labonté, J.M.; Suttle, C.A. Metagenomic and whole-genome analysis reveals new lineages of gokushoviruses and biogeographic separation in the sea. Front. Microbiol. 2013, 4, 404. [Google Scholar] [CrossRef] [PubMed]
  16. Hanson, C.A.; Marston, M.F.; Martiny, J.B.H. Biogeographic Variation in Host Range Phenotypes and Taxonomic Composition of Marine Cyanophage Isolates. Front. Microbiol. 2016, 7, 983. [Google Scholar] [CrossRef] [PubMed]
  17. Chow, C.-E.T.; Suttle, C.A. Biogeography of Viruses in the Sea. Annu. Rev. Virol. 2015, 2, 41–66. [Google Scholar] [CrossRef] [PubMed]
  18. Chow, C.-E.T.; Winget, D.M.; White, R.A.; Hallam, S.J.; Suttle, C.A. Combining genomic sequencing methods to explore viral diversity and reveal potential virus-host interactions. Front. Microbiol. 2015, 6, 265. [Google Scholar] [CrossRef] [PubMed]
  19. Martinez-Hernandez, F.; Fornas, O.; Gomez, M.L.; Bolduc, B.; de La Cruz Peña, M.J.; Martínez, J.M.; Anton, J.; Gasol, J.M.; Rosselli, R.; Rodriguez-Valera, F.; et al. Single-virus genomics reveals hidden cosmopolitan and abundant viruses. Nat. Commun. 2017, 8, 15892. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  20. De La Cruz Peña, M.J.; Martinez-Hernandez, F.; Garcia-Heredia, I.; Lluesma Gomez, M.; Fornas, Ò.; Martinez-Garcia, M. Deciphering the human virome with single-virus genomics and metagenomics. Viruses 2018, 10, 113. [Google Scholar] [CrossRef] [PubMed]
  21. Hurwitz, B.L.; Westveld, A.H.; Brum, J.R.; Sullivan, M.B. Modeling ecological drivers in marine viral communities using comparative metagenomics and network analyses. Proc. Natl. Acad. Sci. USA 2014, 111, 10714–10719. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  22. Roux, S.; Enault, F.; Hurwitz, B.L.; Sullivan, M.B. VirSorter: Mining viral signal from microbial genomic data. PeerJ 2015, 3, e985. [Google Scholar] [CrossRef] [PubMed]
  23. Ren, J.; Ahlgren, N.A.; Lu, Y.Y.; Fuhrman, J.A.; Sun, F. VirFinder: A novel K-MER based tool for identifying viral sequences from assembled metagenomic data. Microbiome 2017, 5, 69. [Google Scholar] [CrossRef] [PubMed]
  24. Garza, D.R.; Dutilh, B.E. From cultured to uncultured genome sequences: Metagenomics and modeling microbial ecosystems. Cell Mol. Life Sci. 2015, 72, 4287–4308. [Google Scholar] [CrossRef] [PubMed]
  25. Iverson, V.; Morris, R.M.; Frazar, C.D.; Berthiaume, C.T.; Morales, R.L.; Armbrust, E.V. Untangling genomes from metagenomes: Revealing an uncultured class of marine Euryarchaeota. Science 2012, 335, 587–590. [Google Scholar] [CrossRef] [PubMed]
  26. Wrighton, K.C.; Thomas, B.C.; Sharon, I.; Miller, C.S.; Castelle, C.J.; VerBerkmoes, N.C.; Wilkins, M.J.; Hettich, R.L.; Lipton, M.S.; Williams, K.H.; et al. Fermentation, Hydrogen, and Sulfur Metabolism in Multiple Uncultivated Bacterial Phyla. Science 2012, 337, 1661–1665. [Google Scholar] [CrossRef] [PubMed]
  27. Inskeep, W.P.; Jay, Z.J.; Herrgard, M.J.; Kozubal, M.A.; Rusch, D.B.; Tringe, S.G.; Macur, R.E.; Boyd, E.S.; Spear, J.R.; Roberto, F.F. Phylogenetic and Functional Analysis of Metagenome Sequence from High-Temperature Archaeal Habitats Demonstrate Linkages between Metabolic Potential and Geochemistry. Front. Microbiol. 2013, 4, 95. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  28. Sharon, I.; Banfield, J.F. Genomes from Metagenomics. Science 2013, 342, 1057–1058. [Google Scholar] [CrossRef] [PubMed]
  29. Handley, K.M.; Bartels, D.; O’Loughlin, E.J.; Williams, K.H.; Trimble, W.L.; Skinner, K.; Gilbert, J.A.; Desai, N.; Glass, E.M.; Paczian, T.; et al. The complete genome sequence for putative H2- and S-oxidizer Candidatus Sulfuricurvum sp., assembled de novo from an aquifer-derived metagenome. Environ. Microbiol. 2014, 16, 3443–3462. [Google Scholar] [CrossRef] [PubMed]
  30. Nielsen, H.B.; Almeida, M.; Juncker, A.S.; Rasmussen, S.; Li, J.; Sunagawa, S.; Plichta, D.R.; Gautier, L.; Pedersen, A.G.; Le Chatelier, E.; et al. Identification and assembly of genomes and genetic elements in complex metagenomic samples without using reference genomes. Nat. Biotechnol. 2014, 32, 822–828. [Google Scholar] [CrossRef] [PubMed]
  31. Brown, C.T. Strain recovery from metagenomes. Nat. Biotechnol. 2015, 33, 1041–1043. [Google Scholar] [CrossRef] [PubMed]
  32. Spang, A.; Saw, J.H.; Jørgensen, S.L.; Zaremba-Niedzwiedzka, K.; Martijn, J.; Lind, A.E.; van Eijk, R.; Schleper, C.; Guy, L.; Ettema, T.J.G. Complex archaea that bridge the gap between prokaryotes and eukaryotes. Nature 2015, 521, 173–179. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  33. Anantharaman, K.; Breier, J.A.; Dick, G.J. Metagenomic resolution of microbial functions in deep-sea hydrothermal plumes across the Eastern Lau Spreading Center. ISME J. 2016, 10, 225–239. [Google Scholar] [CrossRef] [PubMed]
  34. Gupta, A.; Kumar, S.; Prasoodanan, V.P.K.; Harish, K.; Sharma, A.K.; Sharma, V.K. Reconstruction of Bacterial and Viral Genomes from Multiple Metagenomes. Front. Microbiol. 2016, 7, 469. [Google Scholar] [CrossRef] [PubMed]
  35. Haroon, M.F.; Thompson, L.R.; Parks, D.H.; Hugenholtz, P.; Stingl, U. A catalogue of 136 microbial draft genomes from Red Sea metagenomes. Sci. Data 2016, 3, 160050. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  36. Laczny, C.C.; Muller, E.E.L.; Heintz-Buschart, A.; Herold, M.; Lebrun, L.A.; Hogan, A.; May, P.; de Beaufort, C.; Wilmes, P. Identification, Recovery, and Refinement of Hitherto Undescribed Population-Level Genomes from the Human Gastrointestinal Tract. Front. Microbiol. 2016, 7, 884. [Google Scholar] [CrossRef] [PubMed]
  37. Svartström, O.; Alneberg, J.; Terrapon, N.; Lombard, V.; de Bruijn, I.; Malmsten, J.; Dalin, A.-M.; EL Muller, E.; Shah, P.; Wilmes, P.; et al. Ninety-nine de novo assembled genomes from the moose (Alces alces) rumen microbiome provide new insights into microbial plant biomass degradation. ISME J. 2017, 11, 2538–2551. [Google Scholar] [CrossRef] [PubMed]
  38. Roux, S.; Krupovic, M.; Poulet, A.; Debroas, D.; Enault, F. Evolution and Diversity of the Microviridae Viral Family through a Collection of 81 New Complete Genomes Assembled from virome reads. PLoS ONE 2012, 7, e40418. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  39. Dutilh, B.E.; Cassman, N.; McNair, K.; Sanchez, S.E.; Silva, G.G.Z.; Boling, L.; Barr, J.J.; Speth, D.R.; Seguritan, V.; Aziz, R.K.; et al. A highly abundant bacteriophage discovered in the unknown sequences of human faecal metagenomes. Nat. Commun. 2014, 5, 4498. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  40. Smits, S.L.; Bodewes, R.; Ruiz-González, A.; Baumgärtner, W.; Koopmans, M.P.; Osterhaus, A.D.M.E.; Schürch, A.C. Recovering full-length viral genomes from metagenomes. Front. Microbiol. 2015, 6, 1069. [Google Scholar] [CrossRef] [PubMed]
  41. Andersson, A.F.; Banfield, J.F. Virus population dynamics and acquired virus resistance in natural microbial communities. Science 2008, 320, 1047–1050. [Google Scholar] [CrossRef] [PubMed]
  42. Labonté, J.M.; Suttle, C.A. Previously unknown and highly divergent ssDNA viruses populate the oceans. ISME J. 2013, 7, 2169–2177. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  43. Mizuno, C.M.; Rodriguez-Valera, F.; Garcia-Heredia, I.; Martin-Cuadrado, A.-B.; Ghai, R. Reconstruction of novel cyanobacterial siphovirus genomes from Mediterranean metagenomic fosmids. Appl. Environ. Microbiol. 2013, 79, 688–695. [Google Scholar] [CrossRef] [PubMed]
  44. Mizuno, C.M.; Rodriguez-Valera, F.; Kimes, N.E.; Ghai, R. Expanding the marine virosphere using metagenomics. PLoS Genet. 2013, 9, e1003987. [Google Scholar] [CrossRef] [PubMed]
  45. Bellas, C.M.; Anesio, A.M.; Barker, G. Analysis of virus genomes from glacial environments reveals novel virus groups with unusual host interactions. Front. Microbiol. 2015, 6, 656. [Google Scholar] [CrossRef] [PubMed]
  46. Skvortsov, T.; de Leeuwe, C.; Quinn, J.P.; McGrath, J.W.; Allen, C.C.R.; McElarney, Y.; Watson, C.; Arkhipova, K.; Lavigne, R.; Kulakov, L.A. Metagenomic characterisation of the viral community of Lough Neagh, the largest freshwater lake in Ireland. PLoS ONE 2016, 11, e0150361. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  47. Voorhies, A.A.; Eisenlord, S.D.; Marcus, D.N.; Duhaime, M.B.; Biddanda, B.A.; Cavalcoli, J.D.; Dick, G.J. Ecological and genetic interactions between cyanobacteria and viruses in a low-oxygen mat community inferred through metagenomics and metatranscriptomics: Cyanobacteria-virus interactions in a low-O2 mat community. Environ. Microbiol. 2016, 18, 358–371. [Google Scholar] [CrossRef] [PubMed]
  48. Ghai, R.; Mehrshad, M.; Mizuno, C.M.; Rodriguez-Valera, F. Metagenomic recovery of phage genomes of uncultured freshwater actinobacteria. ISME J. 2017, 11, 304–308. [Google Scholar] [CrossRef] [PubMed]
  49. Simmonds, P.; Adams, M.J.; Benkő, M.; Breitbart, M.; Brister, J.R.; Carstens, E.B.; Davison, A.J.; Delwart, E.; Gorbalenya, A.E.; Harrach, B.; et al. Virus taxonomy in the age of metagenomics: Consensus statement. Nat. Rev. Microbiol. 2017, 15, 161–168. [Google Scholar] [CrossRef] [PubMed]
  50. Malki, K.; Kula, A.; Bruder, K.; Sible, E.; Hatzopoulos, T.; Steidel, S.; Watkins, S.C.; Putonti, C. Bacteriophages isolated from Lake Michigan demonstrate broad host-range across several bacterial phyla. Virol. J. 2015, 12, 164. [Google Scholar] [CrossRef] [PubMed]
  51. Ceyssens, P.-J.; Miroshnikov, K.; Mattheus, W.; Krylov, V.; Robben, J.; Noben, J.-P.; Vanderschraeghe, S.; Sykilinda, N.; Kropinski, A.M.; Volckaert, G.; et al. Comparative analysis of the widespread and conserved PB1-like viruses infecting Pseudomonas aeruginosa. Environ. Microbiol. 2009, 11, 2874–2883. [Google Scholar] [CrossRef] [PubMed]
  52. Krylov, V.N.; Tolmachova, T.O.; Akhverdian, V.Z. DNA homology in species of bacteriophages active on Pseudomonas aeruginosa. Arch. Virol. 1993, 131, 141–151. [Google Scholar] [CrossRef] [PubMed]
  53. Lavigne, R.; Darius, P.; Summer, E.J.; Seto, D.; Mahadevan, P.; Nilsson, A.S.; Ackermann, H.W.; Kropinski, A.M. Classification of Myoviridae bacteriophages using protein sequence similarity. BMC Microbiol. 2009, 9, 224. [Google Scholar] [CrossRef] [PubMed]
  54. Garbe, J.; Wesche, A.; Bunk, B.; Kazmierczak, M.; Selezska, K.; Rohde, C.; Sikorski, J.; Rohde, M.; Jahn, D.; Schobert, M. Characterization of JG024, a pseudomonas aeruginosa PB1-like broad host range phage under simulated infection conditions. BMC Microbiol. 2010, 10, 301. [Google Scholar] [CrossRef] [PubMed]
  55. Danis-Wlodarczyk, K.; Olszak, T.; Arabski, M.; Wasik, S.; Majkowska-Skrobek, G.; Augustyniak, D.; Gula, G.; Briers, Y.; Jang, H.B.; Vandenheuvel, D.; et al. Characterization of the Newly Isolated Lytic Bacteriophages KTN6 and KT28 and Their Efficacy against Pseudomonas aeruginosa Biofilm. PLoS ONE 2015, 10, e0127603. [Google Scholar] [CrossRef] [Green Version]
  56. Pires, D.P.; Sillankorva, S.; Kropinski, A.M.; Lu, T.K.; Azeredo, J. Complete Genome Sequence of Pseudomonas aeruginosa Phage vB_PaeM_CEB_DP1. Genome Announc. 2015, 3, e00918-15. [Google Scholar] [CrossRef] [PubMed]
  57. Pourcel, C.; Midoux, C.; Latino, L.; Petit, M.-A.; Vergnaud, G. Complete Genome Sequences of Pseudomonas aeruginosa Phages vB_PaeP_PcyII-10_P3P1 and vB_PaeM_PcyII-10_PII10A. Genome Announc. 2016, 4, e00916-16. [Google Scholar] [CrossRef] [PubMed]
  58. Neves, P.R.; Cerdeira, L.T.; Mitne-Neto, M.; Oliveira, T.G.M.; McCulloch, J.A.; Sampaio, J.L.M.; Mamizuka, E.M.; Levy, C.E.; Sato, M.I.Z.; Lincopan, N. Complete Genome Sequence of an F8-Like Lytic Myovirus (SPM-1) That Infects Metallo-Lactamase-Producing Pseudomonas aeruginosa. Genome Announc. 2014, 2, e00061-14. [Google Scholar] [CrossRef] [PubMed]
  59. Zwart, G.; Crump, B.; Kamst-van Agterveld, M.; Hagen, F.; Han, S. Typical freshwater bacteria: An analysis of available 16S rRNA gene sequences from plankton of lakes and rivers. Aquat. Microb. Ecol. 2002, 28, 141–155. [Google Scholar] [CrossRef]
  60. Newton, R.J.; Jones, S.E.; Eiler, A.; McMahon, K.D.; Bertilsson, S. A Guide to the natural history of freshwater lake bacteria. Microbiol. Mol. Biol. Rev. 2011, 75, 14–49. [Google Scholar] [CrossRef] [PubMed]
  61. Brum, J.R.; Ignacio-Espinoza, J.C.; Roux, S.; Doulcier, G.; Acinas, S.G.; Alberti, A.; Chaffron, S.; Cruaud, C.; de Vargas, C.; Gasol, J.M.; et al. Ocean plankton. Patterns and ecological drivers of ocean viral communities. Science 2015, 348, 1261498. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  62. Hurwitz, B.L.; Sullivan, M.B. The Pacific Ocean Virome (POV): A Marine Viral Metagenomic Dataset and Associated Protein Clusters for Quantitative Viral Ecology. PLoS ONE 2013, 8, e57355. [Google Scholar] [CrossRef] [PubMed]
  63. Yutin, N.; Suzuki, M.T.; Teeling, H.; Weber, M.; Venter, J.C.; Rusch, D.B.; Béjà, O. Assessing diversity and biogeography of aerobic anoxygenic phototrophic bacteria in surface waters of the Atlantic and Pacific Oceans using the Global Ocean Sampling expedition metagenomes. Environ. Microbiol. 2007, 9, 1464–1475. [Google Scholar] [CrossRef] [PubMed]
  64. Angly, F.; Rodriguez-Brito, B.; Bangor, D.; McNairnie, P.; Breitbart, M.; Salamon, P.; Felts, B.; Nulton, J.; Mahaffy, J.; Rohwer, F. PHACCS, an online tool for estimating the structure and diversity of uncultured viral communities using metagenomic information. BMC Bioinform. 2005, 6, 41. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  65. Zerbino, D.R.; Birney, E. Velvet: Algorithms for de novo short read assembly using de Bruijn graphs. Genome Res. 2008, 18, 821–829. [Google Scholar] [CrossRef] [PubMed]
  66. Watkins, S.C.; Putonti, C. The use of informativity in the development of robust viromics-based examinations. PeerJ 2017, 5, e3281. [Google Scholar] [CrossRef] [PubMed]
  67. Sible, E.; Cooper, A.; Malki, K.; Bruder, K.; Watkins, S.C.; Fofanov, Y.; Putonti, C. Survey of viral populations within Lake Michigan nearshore waters at four Chicago area beaches. Data Brief 2015, 5, 9–12. [Google Scholar] [CrossRef] [PubMed]
  68. Bankevich, A.; Nurk, S.; Antipov, D.; Gurevich, A.A.; Dvorkin, M.; Kulikov, A.S.; Lesin, V.M.; Nikolenko, S.I.; Pham, S.; Prjibelski, A.D.; et al. SPAdes: A new genome assembly algorithm and its applications to single-cell sequencing. J. Comput. Biol. 2012, 19, 455–477. [Google Scholar] [CrossRef] [PubMed]
  69. Langmead, B.; Salzberg, S.L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 2012, 9, 357–359. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  70. Darling, A.C.E.; Mau, B.; Blattner, F.R.; Perna, N.T. Mauve: Multiple alignment of conserved genomic sequence with rearrangements. Genome Res. 2004, 14, 1394–1403. [Google Scholar] [CrossRef] [PubMed]
  71. Watkins, S.C.; Kuehnle, N.; Ruggeri, C.A.; Malki, K.; Bruder, K.; Elayyan, J.; Damisch, K.; Vahora, N.; O’Malley, P.; Ruggles-Sage, B.; et al. Assessment of a metaviromic dataset generated from nearshore Lake Michigan. Mar. Freshw. Res. 2016, 67, 1700–1708. [Google Scholar] [CrossRef]
  72. Magill, D.J.; Krylov, V.N.; Shaburova, O.V.; McGrath, J.W.; Allen, C.C.R.; Quinn, J.P.; Kulakov, L.A. Pf16 and phiPMW: Expanding the realm of Pseudomonas putida bacteriophages. PLoS ONE 2017, 12, e0184307. [Google Scholar] [CrossRef] [PubMed]
  73. Luo, C.; Tsementzi, D.; Kyrpides, N.C.; Konstantinidis, K.T. Individual genome assembly from complex community short-read metagenomic datasets. ISME J. 2012, 6, 898–901. [Google Scholar] [CrossRef] [PubMed]
Viruses 10 00331 g001 550
Figure 1. Phylogenetic comparison of PCR amplicons of the genes encoding hypothetical proteins PB1_gp84, 85, 86 generated from environmental DNA. Neighbor-joining tree was generated based on the Jukes-Cantor distance method.
Figure 1. Phylogenetic comparison of PCR amplicons of the genes encoding hypothetical proteins PB1_gp84, 85, 86 generated from environmental DNA. Neighbor-joining tree was generated based on the Jukes-Cantor distance method.
Viruses 10 00331 g001
Viruses 10 00331 g002 550
Figure 2. PB1 genome atlas, demonstrating quality hits to the PB1 genome across environmental viral metagenomes. Genes for which no hit was detected are indicated by grey. The bar graph at the top of the figure represents amount of data collected for that sample.
Figure 2. PB1 genome atlas, demonstrating quality hits to the PB1 genome across environmental viral metagenomes. Genes for which no hit was detected are indicated by grey. The bar graph at the top of the figure represents amount of data collected for that sample.
Viruses 10 00331 g002
Viruses 10 00331 g003 550
Figure 3. (a) Genome map of PB1-like genomes. CDS regions which are missing/disrupted in the new uncultivated viral genomes are indicated (A = All 9 genomes; G = Gallinipper; J = Jollyroger; K = Kraken; L = Kula; M = Nemo; N = Nessie; P = Poseidon; S = Smee; T = Triton). (b) Phylogenetic comparison of uncultivated Lake Michigan PB1-like viruses (red) to Pseudomonas-infecting Pbunaviruses. PB1 strains indicated in blue font are phages previously cultured and isolated from Lake Michigan [50].
Figure 3. (a) Genome map of PB1-like genomes. CDS regions which are missing/disrupted in the new uncultivated viral genomes are indicated (A = All 9 genomes; G = Gallinipper; J = Jollyroger; K = Kraken; L = Kula; M = Nemo; N = Nessie; P = Poseidon; S = Smee; T = Triton). (b) Phylogenetic comparison of uncultivated Lake Michigan PB1-like viruses (red) to Pseudomonas-infecting Pbunaviruses. PB1 strains indicated in blue font are phages previously cultured and isolated from Lake Michigan [50].
Viruses 10 00331 g003
Table
Table 1. PCR primers used in this study. Expectation of amplification determined by querying the primer sequences via BLASTn to nr/nt database. HP = hypothetical protein.
Table 1. PCR primers used in this study. Expectation of amplification determined by querying the primer sequences via BLASTn to nr/nt database. HP = hypothetical protein.
Primer PairForward Primer (5′–3′)Reverse Primer (3′–5′)Annotated Coding Sequence (CDS) in AmpliconStrains/Species Expected to Amplify
1CTACGGCCGTGCAGACCTCCATGTGTGGCATCCPB1 gp10 (HP), PB1 gp11 (HP)SPM-1, PB1, F8
2ACCTTCTTCGGCATCCTCTGTGGTCACCGTATTCCAPB1 gp23 (HP), PB1 gp24 (HP)DL60, DL52, vB_PaeM_C1-14_Ab28, SPM-1, PB1, F8
3CGCCATAATAGGCTCCAACGAGACATTCGCTGATGAPB1 gp55 (helicase)SPM-1, PB1, F8
4ACCGACTCACGACGATGGCGGCAAGGTGTTCGCTTAPB1 gp68 (HP), PB1 gp69 (HP)PB1
5CGTCGAGGATGCTGATGGGGCAGGTCCGAAGGCTACPB1 gp84 (HP), PB1 gp85 (HP), PB1 gp86 (HP)vB_PaeM_LS1, vB_PaeM_E215, KPP22M1, vB_PaeM_E217, NP3, phiKTN6, KPP22M3, KPP22M2, KP22, vB_Pae_PS44, LMA2, vB_PaeM_CEB_DP1, vB_PaeM_PAO1_Ab29, vB_PaeM_PAO1_Ab27, KPP12, NH-4, PB1
Table
Table 2. Descriptive information for the nine uncultivated PB1-like genomes from Lake Michigan samples.
Table 2. Descriptive information for the nine uncultivated PB1-like genomes from Lake Michigan samples.
PhageIsolation (Beach/Date)Coverage (Average)Length (bp)# Annotated GenesAccession NumberSRA Accession (Raw Reads)
Gallinipper95th Street/10 June 20143065,91789KT372690SRX956318
Jollyroger57th Street/8 July 201420065,79590KT372691SRX995828
Kraken95th Street/5 August 2014
(Biological Replicate 1)		1565,76288KT372692SRX995836
Kula95th Street/5 August 2014
(Biological Replicate 2)		2065,76289KT372693SRX995836
Nemo95th Street/5 August 2014
(Biological Replicate 3)		2066,28388KT372694SRX995836
NessieWilmette/13 May 201422065,76289KT372695SRX995816
PoseidonWilmette/5 August 201413065,76288KT372696SRX995833
SmeeMontrose/8 July 201411566,27889KT372697SRX995827
Triton57th/5 August 201412565,76285KT372698SRX995835

Share and Cite

MDPI and ACS Style

Watkins, S.C.; Sible, E.; Putonti, C. Pseudomonas PB1-Like Phages: Whole Genomes from Metagenomes Offer Insight into an Abundant Group of Bacteriophages. Viruses 2018, 10, 331. https://doi.org/10.3390/v10060331

AMA Style

Watkins SC, Sible E, Putonti C. Pseudomonas PB1-Like Phages: Whole Genomes from Metagenomes Offer Insight into an Abundant Group of Bacteriophages. Viruses. 2018; 10(6):331. https://doi.org/10.3390/v10060331

Chicago/Turabian Style

Watkins, Siobhan C., Emily Sible, and Catherine Putonti. 2018. "Pseudomonas PB1-Like Phages: Whole Genomes from Metagenomes Offer Insight into an Abundant Group of Bacteriophages" Viruses 10, no. 6: 331. https://doi.org/10.3390/v10060331

APA Style

Watkins, S. C., Sible, E., & Putonti, C. (2018). Pseudomonas PB1-Like Phages: Whole Genomes from Metagenomes Offer Insight into an Abundant Group of Bacteriophages. Viruses, 10(6), 331. https://doi.org/10.3390/v10060331

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop