Ecogenomics and Genome Landscapes of Marine Pseudoalteromonas Phage H105/1
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The ISME Journal (2010), 1–15 & 2010 International Society for Microbial Ecology All rights reserved 1751-7362/10 $32.00 www.nature.com/ismej ORIGINAL ARTICLE Ecogenomics and genome landscapes of marine Pseudoalteromonas phage H105/1 Melissa Beth Duhaime1,2, Antje Wichels3, Jost Waldmann1, Hanno Teeling1 and Frank Oliver Glo¨ckner1,2 1Microbial Genomics Group, Max Planck Institute for Marine Microbiology, Celsiusstrasse 1, Bremen, Germany; 2School of Engineering and Sciences, Jacobs University, Bremen, Germany and 3Biosciences Division, Alfred Wegener Institute for Polar and Marine Research, BAH, Helgoland, Germany Marine phages have an astounding global abundance and ecological impact. However, little knowledge is derived from phage genomes, as most of the open reading frames in their small genomes are unknown, novel proteins. To infer potential functional and ecological relevance of sequenced marine Pseudoalteromonas phage H105/1, two strategies were used. First, similarity searches were extended to include six viral and bacterial metagenomes paired with their respective environmental contextual data. This approach revealed ‘ecogenomic’ patterns of Pseudoalteromo- nas phage H105/1, such as its estuarine origin. Second, intrinsic genome signatures (phylogenetic, codon adaptation and tetranucleotide (tetra) frequencies) were evaluated on a resolved intra- genomic level to shed light on the evolution of phage functional modules. On the basis of differential codon adaptation of Phage H105/1 proteins to the sequenced Pseudoalteromonas spp., regions of the phage genome with the most ‘host’-adapted proteins also have the strongest bacterial tetra signature, whereas the least ‘host’-adapted proteins have the strongest phage tetra signature. Such a pattern may reflect the evolutionary history of the respective phage proteins and functional modules. Finally, analysis of the structural proteome identified seven proteins that make up the mature virion, four of which were previously unknown. This integrated approach combines both novel and classical strategies and serves as a model to elucidate ecological inferences and evolutionary relationships from phage genomes that typically abound with unknown gene content. The ISME Journal advance online publication, 8 July 2010; doi:10.1038/ismej.2010.94 Subject Category: evolutionary genetics Keywords: ecogenomics; genome signatures; genomics; marine; phage; Pseudoalteromonas Introduction Pseudoalteromonads are ubiquitous heterotrophic members of marine bacterial communities, which, Viruses are the most abundant biological entity and as with most microbial life, are ecologically and the largest source of genetic material on the planet evolutionarily influenced by phages (Moebus, 1992; (Suttle, 2007), and are likely the major vehicle for Wichels et al., 1998, 2002; Ma¨nnisto¨ et al., 1999; gene transfer in the ocean. Considering the global Me´digue et al., 2005; Thomas et al., 2008). All three volume of seawater, the worldwide abundance of sequenced Pseudoalteromonads contain integrated marine phages and bacteria and the frequency of prophages, two of which are dominated by P2-like gene transfers per infection, virus-mediated trans- myovirus proteins (Prophinder) (Lima-Mendez et al., fers occur up to 1015 times per second in the ocean 28 2008). Pseudoalteromonas phage H105/1, the focus of (Bushman, 2002), with an extrapolated 10 bp of this study, is a member of the Siphoviridae family DNA transduced by phages per year (Paul et al., isolated from the North Sea, on Pseudoalteromonas 2002). Evidence shows that these transfers include sp. H105 (Figure 1). Phage H105/1 also infects host-derived metabolic genes central to the metabo- Pseudoalteromonas spp. H103 and H108, which were lism of the world’s oceans (Lindell et al., 2005), isolated along with H105 from the same water sample carried by the virus and expressed during infection (Wichels et al., 1998). The host, Pseudoalteromonas (Lindell et al., 2004). sp. H105, is susceptible to lysis or growth inhibition by other Helgoland and North Sea phages, including members of both the Myovridae and Siphoviridae Correspondence: MB Duhaime, Microbial Genomics, Max Planck families (Wichels et al., 1998, 2002). Institute for Marine Microbiology, Celsiusstrasse 1, Bremen Phage genomes are small (3–300 kb) compared 28359, Germany. E-mail: [email protected] with the Bacteria and Archaea they infect (1000– Received 14 January 2010; revised 4 May 2010; accepted 19 May 13 000 kb), and typically abound with unknown 2010 gene content. The majority of the open reading Marine Pseudoalteromonas phage H105/1 genome MB Duhaime et al 2 82 Pseudoalteromonas antarctica AF045560 (T) Pseudoalteromonas arctica DQ787199 (T) Pseudoalteromonas haloplanktis TAC125 CR954246 Pseudoalteromonas espejiana X82143 (T) Pseudoalteromonas carrageenovora X82136 (T) Alteromonadales bacterium TW-7 AY028202 Pseudoalteromonas sp. H105 Pseudoalteromonas denitrificans X82138 (T) Alteromonadales Pseudoalteromonas citrea X82137 (T) 78 Pseudoalteromonas peptidolytica AF007286 (T) 100 Pseudoalteromonas piscicida AF297959 (T) Pseudoalteromonas mariniglutinosa AB257337 Pseudoalteromonas spongiae AY769918 (T) Pseudoalteromonas tunicata D2 Z25522 (T) 94 Pseudoalteromonas ulvae AF172987 (T) 97 95 Haemophilus influenzae BD425102 Pasturellales Providencia stuartii ATCC 25827 ABJD02000005 Enterobacteriales Vibrio cholerae MO10 DS179652 88 Listonella pelagia AJ293802 (T) Vibrionales 100 Vibrio parahaemolyticus AQ3810 AAWQ01000319 Photobacterium profundum CR378680 100 100 Shewanella oneidensis MR−1 AE014299 84 100 Shewanella sp. MR−7 CP000444 0.1 substit. 100 Shewanella sp. MR−4 CP000446 Alteromonadales 100 97 Shewanella sp. ANA−3 CP000469 GAMMA Moritella marina AB121097 100 Alteromonas macleodii Y18228 (T) 99 Pseudoalteromonas atlantica T6c CP000388 Legionella pneumophila str. Phi AE017354 Legionellales 100 Silicibacter sp. TM1040 CP000376 100 ALPHA Rhodobacterales 100 Roseobacter sp. CCS2 AAYB01000001 Cand. Pelagibacter ubique HTCC1062 CP000084 Rickettsiales 100 Staphylococcus aureus subsp. aureus L36472 (T) Listeria monocytogenes AX641671 Bacilliales FIRMICUTES 19 Figure 1 Phylogenetic characterization of host Pseudoalteromonas sp. H105 16S rRNA gene. Maximum likelihood tree calculated with 1000 bootstraps using RAxML. RefSeq accession numbers follow the organism name; (T) indicates a type strain. Background shading highlights the taxonomic classification of the organism. Bootstrap values 475 are shown on the branches; 19 sequences were used as an outgroup. Bar represents 10% estimated sequence change. ALPHA and GAMMA denote the class of Proteobacteria per cluster. frames (ORFs) (over 60%) of sequenced marine frequently swapped between phages infecting phage genomes are hypothetical proteins (unique diverse hosts (Lucchini et al., 1999; File´e et al., in public sequence databases) or conserved hypo- 2006). As such, phage genomes can be thought of as thetical proteins (similar only to other unknown veritable ‘concatenated metagenomes’, in that con- proteins). As the public sequence databases are secutive fragments can have very dissimilar origins insufficient to grasp phage protein diversity, tradi- and evolutionary pasts. Tetranucleotide (tetra) usage tional approaches to genome analysis, which rely on frequencies, a feature increasingly used to cluster similarity searches (blast (Altschul et al., 1990) sequence fragments originating from discrete organ- against NCBI-nr), or protein family classification isms of a community (Woyke et al., 2006; Andersson (Pfam (Finn et al., 2010)), reveal little about phage and Banfield, 2008; Dick et al., 2009), were evolution. We expanded the similarity searches of considered in this study as a tool to differentiate Phage H105/1 to include the Global Ocean Sampling and shed light on the evolutionary history of Phage data set (GOS) (Rusch et al., 2007) and five globally H105/1 ‘functional modules’. distributed marine viral metagenomes missing from We set out to test (a) whether the isolation habitat NCBI-nr and -env (Angly et al., 2006; McDaniel et al., of Phage H105/1 (Helgoland, North Sea), in light of 2008). Such an approach lends itself to ‘ecogenomic’ its respective environmental parameters, influences interpretations, whereby ecological inferences about the distribution of H105/1 protein sequences in the Phage H105/1 can be made on the basis of genomic currently available ‘global virome’, and (b) whether patterns and their respective environmental contex- a resolved intra-genomic (tetra) frequency signature tual data (Kottmann et al., 2010). exists, and how this may be related to host codon Further complicating phage genomics, their adaptation. These novel approaches, integrated evolution is driven by the rampant exchange with experimental characterization of the phage’s of functional genome modules (Botstein, 1980; infection dynamics and structural proteome, offer Hendrix et al., 1999; Pedulla et al., 2003) that are strategies to elucidate ecological and evolutionary The ISME Journal Marine Pseudoalteromonas phage H105/1 genome MB Duhaime et al 3 patterns and understand genomic features of (À10*Log(P), where P is the probability that the Pseudoalteromonas phage H105/1. observed match is random). Protein scores 429 were considered significant (Po0.05). Materials and methods Genome annotation Phage harvesting, DNA isolation and sequencing Genes were predicted on the basis of (i) GeneMark. Pseudoalteromonas sp. strain H105 and Pseudoalter- hmm (prokaryotic