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B RIEFINGS IN FUNC TIONAL GENOMICS . VOL 12. NO 4. 354 ^365 doi:10.1093/bfgp/elt009 Bacteriophage functional genomics and its role in bacterial pathogen detection Jochen Klumpp, Derrick E. Fouts and Shanmuga Sozhamannan Advance Access publication date 21 March 2013 Abstract Emerging and reemerging bacterial infectious diseases are a major public health concern worldwide. The role of bacteriophages in the emergence of novel bacterial pathogens by horizontal gene transfer was highlighted by the May 2011 Escherichia coli O104:H4 outbreaks that originated in Germany and spread to other European countries. This outbreak also highlighted the pivotal role played by recent advances in functional genomics in rapidly deciphering the virulence mechanism elicited by this novel pathogen and developing rapid diagnostics and therapeutics. However, despite a steady increase in the number of phage sequences in the public databases, boosted by the next-generation sequencing technologies, few functional genomics studies of bacteriophages have been conducted. Our definition of ‘functional genomics’ encompasses a range of aspects: phage genome sequencing, annotation and ascribing functions to phage genes, prophage identification in bacterial sequences, elucidating the events in various stages of phage life cycle using genomic, transcriptomic and proteomic approaches, defining the mechanisms of host takeover including specific bacterial ^ phage protein interactions and identifying virulence and other adaptive features encoded by phages and finally, using prophage genomic information for bacterial detection/diagnostics. Given the breadth and depth of this definition and the fact that some of these aspects (especially phage-encoded virulence/adaptive features) have been treated extensively in other reviews, we restrict our focus only on certain aspects. These include phage genome sequencing and annotation, identification of prophages in bacterial sequences and genetic characterization of phages, functional genomics of the infection process and finally, bacterial identification using genomic information. Keywords: next-generation DNA sequencing; prophage identification; genome annotation pathogen detection; reporter phage; antimicrobials INTRODUCTION Infectious diseases are a constant threat to human health and the second most frequent cause of death, with an estimated more than 10 million fatalities worldwide annually. Amongst the top five foodborne diseases worldwide, four are caused by bacterial pathogens, such as Salmonella, Clostridium, Campylobacter and Staphylococcus, and are responsible for more than 3 million infections and intoxications in the USA alone in 2011 [1]. In the European Union, foodborne infections by Salmonella, Campylobacter and Listeria account for more than 300 000 human cases of infection annually [2]. By their nature, bacteriophages (phages), viruses that infect bacteria, are ideal weapons to combat bacterial infections. They are highly species-specific, and are Corresponding author. Jochen Klumpp, Institute of Food, Nutrition and Health, ETH Zurich, Schmelzbergstrasse 7, 8092 Zurich, Switzerland. Tel.: þ41 44 632 5378; Fax: þ41 44 632 1266; E-mail: [email protected] Jochen Klumpp is a research fellow at the Institute of Food, Nutrition and Health, ETH Zurich. He is a molecular biologist and bioinformatician, and his main research interests are DNA sequencing technologies, the bacteriophage infection process, the use of bacteriophage particles and enzymes for food safety and transmission electron microscopy of viruses. Derrick E. Fouts is an associate professor at the J. Craig Venter Institute, Rockville, MD. He is a molecular microbiologist, genomicist, and bioinformaticist. His research focus is on viral and bacterial genomics, microbial pathogenesis, and community metagenomics. He has developed a number of bioinformatics software tools, including tools for prophage identification (Phage_Finder) and for ortholog detection (PanOCT). Shanmuga Sozhamannan is a molecular biologist with GoldBelt Raven, LLC providing support as the technical coordinator for the Critical Reagents Program within the Chemical Biological Medical Systems project office on Fort Detrick, MD. His research interests focus on understanding the biology of bacterial viruses and extra chromosomal elements and their roles in horizontal gene transfer and evolution of bacterial pathogens using genetic, molecular biological and genomic approaches. ß The Author 2013. Published by Oxford University Press. All rights reserved. For permissions, please email: [email protected] Bacteriophage functional genomics non-toxic to animals and plants and they are self-amplified when they infect, multiply and kill their target bacteria [3]. Bacteriophages are the most abundant biological entity on this planet and it is estimated that phages kill half of all bacteria each day and influence most of earth’s biogeochemistry through their bacterial host [4,5]. Since their discovery in 1915 and 1917 by D’Herelle and Twort [6,7], bacteriophages have been used primarily as research tools in the Western world and as antibacterial agents in the former Soviet Union countries and Eastern Europe. The discovery of antibiotics led to the complete abandonment of phage therapy by the West [8,9] and, hence, phages are not as widely used as therapeutics as one would imagine. The widespread use, and in many instances misuse, of antibiotics since the 1940s, in a variety of healthcare settings to combat bacterial infections in humans and livestock, has resulted in the current crisis with antibiotic resistant bacteria. Recently, phage therapy and biocontrol approaches have received renewed research interest. It is believed that the antibiotic potential of phages has not yet been fully realized [3,8,10–12]. The modern day phage therapy attempts of the Western world started around 1980. In a pioneering study, Smith and Huggins successfully eradicated experimentally-induced Escherichia coli infection in a mouse infection model [13]. Since then, similar studies have been conducted to cure infections of many bacteria such as Staphylococcus aureus, VancomycinResistant Enterococci (VRE), Methicillin-Resistant Staphylococcus aureus (MRSA) in animals, Acinetobacter baumanii or Pseudomonas aeruginosa and animals with local and systemic disease caused by Vibrio vulnificus, Mycobacterium avium, Mycobacterium tuberculosis in macrophages, E. coli and fish pathogens. Phages have also been used in treating non-systemic infections caused by enteropathogenic strains of E. coli in calves, pigs and lambs and ileocecitis caused by Clostridium difficile in hamsters. Phages have been shown to be effective in preventing the destruction of skin grafts by P. aeruginosa, against fish pathogens in aquaculture and bacterial wilt in vegetables [14–17]. Bacteriophages have more recently been used in various other applications to counter pathogenic bacteria. The use of bacteriophage preparations or bacteriophage-derived enzymes for detection and control of pathogens in the food chain has recently attracted intensive research (e.g. reviewed in [18,19]). Some additional examples include the detection of Listeria, Bacillus orYersinia by reporter phages carrying luciferase 355 genes, which are expressed upon infection and transcription of phage genes [20–23] and the biocontrol of pathogenic bacteria in food [24–27] (reviewed in [28]). Bacteriophages, especially those featuring a temperate lifestyle, are also the major driving force of horizontal gene exchange and bacterial evolution [29–31]. Many bacterial genomes carry either complete and fully functional prophages or defective remnants of prophages indicative of prior infections. In many cases, they account for a significant proportion of the bacterial genomic content. For example, Streptococcus pyogenes features a genome with more than 10% phage-related sequences [32], and in E. coli O157:H7 strain Sakai, prophage elements account for 16% of the total genome [33]. In many instances, the prophages confer adaptive features to their host; these include genes related to bacterial virulence, antibiotic resistance cassettes or toxin genes in a variety of organisms [29,32]. For example, CTX phage of Vibrio cholerae [34,35] or shiga-toxin carrying lambdoid prophages of pathogenic E. coli, such as the serotype O104:H4, responsible for the recent outbreak in Germany [36]. In the classical sense, bacteriophage functional genomics includes DNA sequencing of phage genomes, annotation and attribution of functions based on in silico approaches and or biochemical or genetic studies and identifying prophage regions in bacterial sequences. With the recent expansion of ‘omics’ areas, it can also include the elucidation of various stages of phage infection process using genomic, transcriptomic and proteomic approaches, specific mechanisms that phages adopt to shut down and take over host macromolecular machinery for their own reproduction and growth, and the study of the interaction between specific bacterial and phage proteins. For this review, we focus on three specific areas: (i) recent advances in bacterial and phage genomics, tools for identifying prophage regions and genetic characterization of phages; (ii) functional genomics of the infection process and (iii) using phage genomic data for bacterial identification in clinical and non-clinical samples. Bacteriophage genome sequencing Obtaining the complete genome sequence of a bacteriophage is an essential prerequisite for any type of functional genomics study as well as for regulatory approval for phage-based biocontrol and therapy applications in food industry and medicine. Recent 356 Klumpp et al. advances in second- and third-generation DNA sequencing technologies have led to an increasing number of phage genomic sequences, either from purified virus particles or as a result of bacterial genome sequencing in the form of prophage sequences [37]. Conventional Sanger sequencing has been rivaled by a number of second-generation high throughput short-read sequencing technologies (e.g. 454, Illumina, SOLiD and Ion Torrent) and lately by a third-generation single-molecule longread sequencing technology (e.g. PacBio RS by Pacific Biosciences), all of which produce more than enough data to reliably assemble phage genomes. Although the short-read sequencing technologies produce large amounts of short, accurate reads, they also produce context-specific errors, which make error correction by the same method difficult. In addition, because of the short read length, repetitive genome sequences are difficult to assemble. Recent improvements in chemistry and device design are targeted to address these problems. For example, single read lengths of up to 1000 bp can be achieved using the latest FLX plus chemistry of the Roche 454 sequencing platform. Other approaches include the generation of paired-end long insert libraries, which provide scaffolding information [37]. However, single-molecule sequencing using third-generation PacBio RS technology produces by far the longest read lengths, although the individual reads are error prone and feature single-pass accuracies of only around 87%. Since the primary error model consists of truly random single nucleotide indels, these reads can be corrected by an increase in sequencing coverage either by circular consensus sequencing or with data from other sequencing platforms, e.g. Illumina data for error correction [37–39]. Error correction by deep sequencing is an especially attractive option, as it requires only one long-insert library and a single sequencing run. Thus, reliable bacteriophage whole genome sequencing, regardless of the technology used, is possible and competitively priced. Nextgeneration sequencing technologies have also brought about the democratization of whole genome sequencing because of the smaller foot print needed in terms of cost, space and manpower. Hence, generating sequence data is within any researcher’s reach. However, data handling, storage and analysis are not trivial [37]. In addition to more than 1700 bacteriophage genomes, the above described advances in DNA sequencing technologies have enabled the generation of more than 3500 complete and 11 000 incomplete bacterial genome sequences (Gold genomes database, November 2012). In many genome-sequencing projects, the presence of integrated genomes of temperate phages (prophage) in the host chromosome is overlooked or not assessed. Conservative estimates show the presence of prophages in nearly 50% of all sequenced bacterial strains, with prophages contributing up to 20% of a bacterial genome [40]. Thus, the phage gene pool is larger and more diverse than the rest of the chromosome. Bacteriophage genome annotation More than 50% of in silico predicted phage gene products are hypothetical and do not have an assigned function due to a lack of experimental data. For instance, phage T4 (one of the most extensively characterized bacteriophages) genome has about 300 probable genes (168 903 bp genome size) and almost half of these still do not have an assigned function [41]. Several approaches have been put forth to solve the problem of assigning functions to hypothetical gene products (encoded by predicted open reading frames with no homology to any known gene) in all phage genomes. Recently developed bioinformatic tools, such as the structure/function prediction tool HHPred [42] make use of Hidden Markov Models (HMMs) and protein profiles to deduce putative protein functions and identify functional domains in larger proteins. Comparative genomic approaches using closely related phages from different host organisms can fill another gap in protein function assignment. Some information can be deduced from the genetic context or location of genes of interest, because phage genomes are organized in a modular fashion [31,43] and mosaicism (i.e. the exchange of genetic modules between phages) is very common. The recent surge of interest in phage-based antimicrobials has led to more studies being published describing the experimental characterization of specific phage proteins, e.g. tail adhesins [44–47], host takeover genes [48,49], core genes with therapeutic potential [50] or lysins (see below). Many of the hypothetical phage proteins are likely involved in host recognition and, disruption of host metabolism; hence, are potential candidates for bacterial detection and antimicrobial target selection, respectively. This reasoning is best illustrated by a pioneering study on drug discovery through phage genomics, in which investigators at PhageTech Inc. Bacteriophage functional genomics used 27 S. aureus phage genome sequences to screen potential drug targets. Screening a total of 964 ORFs for abolition of bacterial growth produced 34 distinct families of growth-inhibitory proteins (3.5%) [10,51]. This screen excluded the obvious growth inhibitory proteins such as holins, lysins or polypeptides with transmembrane domains. With an increase in the number of genes with assigned functions, future comparative genomic studies will likely yield more accurate prediction of phage gene functions. Thus, functional genomics approaches, either in silico or experimental, present a vast potential for improving phage annotation and facilitating development of tools for food safety and medicine. Prophage identification and using prophages as markers for bacterial identification Assuming an average of three prophage regions per genome [52], there is a potential for as many as 42 000 prophage genomes available for data mining in the currently available bacterial genome sequences— 22 times the number of currently sequenced bacteriophage genomes. Even without prophage identification, genes encoding enzymes of interest, such as phage lysins (see below) can easily be identified using HMMs or BLAST searches. If, however, the objective of a study is to generate phage tail-based molecular diagnostic tools or tail-based bacteriocins (see below), prophage identification is needed. The same holds true if the study objective is to generate a synthetic phage genome for detection or eradication of specific bacterial taxa, as homology of tail proteins can be too low for HMM or BLAST detection and the nucleotide sequence of the entire prophage is needed to construct synthetic variants. A number of bioinformatic tools have been developed for prophage identification in bacterial sequences, including Phage_Finder, one of the first automated prophage-finding open source programs developed. Since the publication of Phage_Finder [52], there have been at least five other prophagefinding tools described in the literature [53–56]. Phage_Finder is written in PERL and uses BLASTP matches to a curated phage database and HMM matches to phage-specific models to define the rough location of a prophage region followed by heuristic decision making to extend the region based on annotation. Putative attachment (att) sites are found using one of many different local alignment options. Prophinder [54], also written in PERL also 357 uses BLASTP matches to a database, but chooses regions based on probability statistics rather than heuristics. PHAST [55] is a web server that also uses homology to identify prophage regions, but is unique in that it does not require an annotated genome as input. Prophages have also been identified based on nucleotide differences [53], training of artificial neural networks [57] or using a combination of AT/GC skew, protein length, gene directionality, homology and k-mer frequencies using a random forest classification algorithm [56]. Though each publication claims their software to be better than the previously reported programs at finding a set of ‘known’ prophage regions, the value of these comparisons is unclear, since each group has a different definition of what constitutes a true prophage. As modified from a previous review on bacteriophage bioinformatics [58], a prophage region is defined as ‘a cluster or stretch of genes, possibly encoding proteins with bacteriophage-like core functions (i.e. terminase, portal, capsid), interspersed with genes of unknown function or functions other than phage replication, morphogenesis, packaging, immunity or lysis of the host’. Ultimately, a true prophage is inducible, whereas defective prophages are the non-inducible remnants of formerly functional temperate bacteriophages. In addition, some comparisons may have been skewed since Phage_Finder can run under two different stringency modes, producing radically different results. PhiSpy [56] uses a training set based on known prophages in closely related organisms to train the random forest classification algorithm implemented in the R statistical package, which by definition should produce better results than other programs because the training set is highly related to the prophages being identified. Phage-Finder does more than just finding prophage regions—it takes advantage of the power of HMMs to identify, with high confidence, specific phage genes of interest. Lysins, toxins and tail components can be mined for applications in bacterial detection or destruction (see below). In addition, HMM matches to family-specific proteins can be used to characterize the prophage region (e.g. Mu-like or P2-like prophage). These in silico approaches to prophage identification are also successful at identifying cryptic, defective prophages or remnants of prophages. One such class of defective prophages is the phage tail-like bacteriocins (PTLBs), for which the P. aeruginosa R-type or F-type pyocins are the prototypes [59]. PTLB 358 Klumpp et al. regions are defective prophages which are different from prophage regions in that they primarily contain genes for tail fibers and tail appendages, regulators and lysis genes, but lack genes for packaging and head morphogenesis. PTLB particles can kill bacteria of similar species by disrupting the membrane of the target bacteria [60]. The bacteriocins are referred to by many different names based on the bacterium that produces it (monocin for Listeria monocytogenes, pestisin for Yersinia pestis, cerecin for Bacillus cereus, colicins for E. coli, staphylococcin for Staphylococcus and diffocin for C. difficile) [61]. Like bacteriophage, the bacteriocins have proven useful for the typing/ identification of pathogenic bacterial strains [62,63]. The presence of prophages can be used to detect and type bacterial pathogens and define their roles in gene regulation and pathogenicity of their host bacteria [64,65]. Newly emerging V. cholerae variants can be discriminated by PCR targeted to mobile genetic elements and phages [66]. Prophage polymorphism has been employed to detect and differentiate exfoliative toxin A-producing S. aureus strains [67]. Likewise, the chromosomal insertion sites of Shiga toxin-producing E. coli define the three major genotypes (clusters 1–3) among clinical isolates of E. coli O157:H7 [68]. In addition, it has been found that prophage regions are critical for competitiveness of P. aeruginosa strains [69]. Prophages also provide unique signatures for bacterial identification. For example, Bacillus anthracis genome encodes four prophages and the collective presence of all four is a unique feature of B. anthracis and can be exploited for developing a multiplex PCR assay for B. anthracis [70]. Similarly, the recent German outbreak strains can be distinguished from their near neighbor E. coli O104:H4 strains by prophage content [71]. Experimental approaches to identify prophages in bacterial chromosomes rely on the induction of prophages by UV irradiation or chemical DNA damaging agents [72]. However, this approach is only applicable to intact prophages that can undergo excision from the chromosome and undergo the lytic life cycle to be detected as plaques on a bacterial lawn. In some pathogens, such as V. cholerae, only subpopulations of bacteria undergo lysis and produce toxin. Studies of these subpopulations require a method to isolate cells that are normally killed by the prophage after induction [73]. Methods such as recombination-based in vivo expression technology and selective in vivo expression technology have been developed for this purpose [73–75]. Functional genomics of the phage infection process and the use of phage and phage proteins for pathogen control and detection Phages are found in nearly every environment where they have been searched for and they can transduce genetic markers between related host bacteria. As alluded to in an earlier section, phage-mediated horizontal gene transfer between intestinal bacteria and autochthonous bacteria is of interest with respect to bacterial pathogenicity [76]. For example, the presence of prophages enables Clostridium botulinum and C. difficile toxin production [77,78], increases Salmonella virulence [79] and influences gene expression within the Staphylococcus pathogenicity islands [80]. Phages with transduction or lysogenic potential are generally not desired in any biotechnological application and identification of such phages or of genes contributing to lysogeny in a phage is critical before embarking on any whole phage based therapeutic application. [81]. Also, temperate phages often possess a narrow host range which limits their utility as biocontrol agents but may be useful as diagnostic tools [82]. Due to a general lack of functional annotation of many phage gene products and the enormous diversity seen in the strategies adopted by phages, our understanding of the mechanism of the phage infection process is rather sketchy at best. In general, functional data, which could bolster in silico prediction of protein function based on sequence homology, are lacking. Only a few model phages have been studied in detail with respect to their life cycle (mostly infecting Gram-negative organisms) and structure/ functions of only a few phage proteins have been determined. The infection of a bacterial cell by a bacteriophage is initiated by a highly specific and irreversible interaction of the phage particle associated protein to cell surface receptors, such as outer membrane proteins or LPS structures in Gram-negative bacteria or teichoic acids or the peptidoglycan backbone in Gram-positive bacteria. This binding is mediated by highly specific receptor binding protein (RBP) of the phage that is very difficult to predict simply based on sequence homology. Besides a trial-and-error cloning strategy of candidate receptor genes, genomics approaches such as structure prediction and identification of conserved domains play an important role in the discovery of RBP proteins. The three-dimensional (3D) atomic RBP structures of three Lactococcus siphoviruses Bacteriophage functional genomics (p2, bIL170 and TP901-1) have been solved by X-ray crystallography and Cryo-EM techniques [44–47]. General saccharide and phosphoglycerol binding has been demonstrated for some RBPs [44,83,84]. The baseplate of Lactococcal phage Tuc2009 has been shown to possess a 6-fold symmetry with six RBP trimers attached around the baseplate and a tail-associated lysin located in the middle of the base plate [83]. Bacteriophages of two other organisms have been subject to intensive research recently. Streptococcus thermophilus is an important organism in industrial fermentation. The RBP of the small Siphovirus DT1 of S. thermophilus is encoded by gp18 [85]. The receptors for S. thermophilus phages are most likely glucosamine, N-acetylglucosamine or rhamnose [86,87]. Other phages of Streptococcus have been investigated for identifying the host receptor [87,88]. Bacillus subtilis Siphovirus SPP1 has been the focus of intensive structural studies. Besides 3D structures of the virion and details of DNA packaging, the baseplate proteins (gp 22–24.1) have been investigated [89–91]. The baseplate proteins have been shown to be essential for binding of the host cell and hence may have utility in bacterial detection assays. Cell wall teichoic acids have been proposed as the major target of SPP1 reversible initial binding, followed by binding to the membrane receptor YueB. Adsorption to cell wall teichoic acids has been shown to accelerate irreversible binding to YueB [92]. Thus, these functional genomic approaches lay the foundation for modeling based structural prediction of phage encoded RBPs. Following adsorption, the phage must penetrate the rigid cell wall and inject its DNA into the host cytosol. Specialized tail-located lytic proteins mediate localized cell wall degradation and allow DNA translocation. The potential application of lytic structural proteins (LSPs) in biocontrol is exemplified by the identification of improved adsorption of the SPO1-related phage EF34C infecting Enterococcus faecalis [93,94] due to a spontaneous point mutation in a putative long tail fiber protein encoded by ORF31 [95], using a functional genomics approach. With the exception of well-studied enteric phages such as bacteriophage P22 [96], little is known about the molecular details of DNA transport across cell membranes, especially in phages infecting Gram-positive bacteria [97]. Localized cell wall hydrolysis is mediated by tail tip-associated lytic proteins (LPs) [98–100]. It is believed that LSPs are 359 commonly found among all phages [101–103]. In Lactococcus phage Tuc2009, a tail-tip associated protein (Tal2009) has been found to feature cell wall degrading activity [101,104]. The presence of LSP proteins in phages infecting other Firmicutes has been demonstrated [103,105,106]. The LSP of Staphylococcus phage MR11 could be located at the tail tip [107], whereas in mycobacteriophage TM4, the lytic activity lies in the tape measure protein [108]. Recently, a tail-associated muralytic enzyme was described for Staphylococcus phage K and its activity demonstrated [103]. Infection of a bacterial host by a bacteriophage is usually accompanied by dramatic rearrangements in bacterial gene expression and changes in cell physiology and metabolism. Understanding these steps using functional genomics approaches may lead to development of rapid diagnostics and therapeutics against bacteria. After an initial takeover phase, the virus down-regulates cellular functions and reprograms the bacterial cell for virus progeny production. Later in the life cycle, virion proteins and progeny DNAs are produced, packaged and virions are assembled, finally resulting in cell lysis and release of progeny phage particles. In case of temperate bacteriophages, the infection process can be stalled at an early stage and the phage genome is integrated in the host chromosome, resulting in some cases, host gene disruption and possible effects on gene expression (e.g. as recently shown for comK disruption in Listeria by phage A118 [65]). Once induced by stress signals, temperate phages enter into a lytic cycle and take over host cell functions. Many studies have focused on only certain stages of the infection process, although in some phages, the entire life cycle has been investigated. Escherichia coli phage T4 is one such example that has been extensively studied in using microarrays [109] and proteomics (described in [41,98] and many more). Host modification and takeover functions have been described for some phages [110,111]. Many studies have focused on the changes in gene expression and cell physiology during virus infection [112,113]. Other authors have demonstrated the complete shutoff of macromolecular synthesis in the infected host [114,115]. Such functional genomic approaches reveal specific phage–bacterial interactions in shutting down and take over of host machinery and also possibly provide new drug targets. The identification of DnaI (the helicase loader) as a target for ORF 104 of a S. aureus phage 77, led to the development of novel small molecule antimicrobial 360 Klumpp et al. compounds that mimic the phage protein (ORF 104 product) activity (69). More such studies are needed to unravel the various strategies that phages adopt to tame their host. All stages in the bacteriophage life cycle can be harnessed for pathogen detection and for the development of novel antimicrobials. Bacterial detection can be achieved either by manipulation of the genomes of virulent phages to give a detectable signal during the infection process (reporter phages) or by the use of the highly specific phage binding proteins, either RBPs or the anchoring domain of endolysins [84,116–118] for specific tagging and/or immobilization of bacteria. Phage tail lysins [102] and endolysins [119,120] represent a novel class of lytic protein (enzybiotics) for pathogen control. Another pathogen detection approach, which follows the genomics to protein function path, is the use or reporter bacteriophages. Reporter phages are usually virulent phages containing a genetically modified genome in which a reporter gene is expressed under the transcriptional control of phage promoters. Expression of the reporter gene upon infection of the susceptible host generates a detectable response. The advantage of such an approach is that only viable target cells are detected, as the expression of the reporter gene relies on successful infection and initiation of phage gene expression. Construction of such reporter phages requires functional genomic knowledge of the gene expression profiles and location of promoters and appropriate insertion sites for the reporter genes and the effect of reporter gene insertion on the overall phage gene expression and a productive life cycle. One of the early approaches involved cloning of the luxAB genes from Vibrio harveyi or Vibrio fischeri behind a strong late phase phage promoter of Listeria phage A511 [20]. This type of reporter assay has subsequently been developed for a number of other bacterium–phage pairs (i.e. Bacillus [23], Salmonella [121] or Yersinia [22]). In principle, nearly every available reporter gene can be used for diagnostic purposes (e.g. luc, ina, beta-galactosidase or fluorescent molecules [122–124]). Recently, a hyperthermostable glycosidase reporter gene cloned into phage A511 was used for the detection of Listeria. The assay offers flexibility in the use of fluorescent, chemilumnescent or chromogenic substrates for pathogen detection [125]. The reporter-phage assay is highly specific, yields no false-positive results and is easy to conduct in a standard laboratory setting by lab personnel with little specialized experience or expertise. The assay detects only viable, phage-sensitive bacteria and is also somewhat dependent on correct folding of the reporter protein (which should be chosen accordingly) and incubation temperature [125]. Recently, phage genomes have been manipulated to express biotin-binding peptide on the capsid surface, which were subsequently captured upon adsorption to cognate bacteria using streptavidin coated quantum dots for high sensitive detection of bacteria [126,127]. Other approaches to pathogen detection harness the function of bacteriophage encoded enzymes. Phage genomes usually encode at least two types of highly specific cellular binding proteins. Tail proteins feature binding domains, which mediate the initial contact with the host cell surface (RBP proteins, see above). These are highly strain- or even serovarspecific and can be used for pathogen detection. They feature a single binding-site and are in this respect superior to antibodies, because no agglutination is triggered. The final stage of a successful infection is marked by the release of the progeny virus particles. Phageencoded cell wall hydrolytic enzymes lyse the bacterial cell from within [119]. These enzymes are also very useful for pathogen detection and control. Large libraries of lytic enzyme-encoding genes identified by either genome sequencing, prophage identification or functional (meta-) genomics approaches [128] are available for different bacterial species, e.g. Streptococcus and Staphylococcus [120]. Phage lysins are composed of an enzymatic active domain(s) and a cell wall-binding domain(s) (CBDs), directing the enzyme to its target structure [119]. CBDs have efficiently been used to target and selectively decorate bacteria in several matrices and media [117,129– 131]. CBD domains can be fused to reporter molecules, such as Green Fluorescent Protein (GFP), for easy readout of the signal upon binding to the target bacteria. Different CBD molecules, tagged with different fluorophores can be used to simultaneously identify several different bacterial species or serovariants in a one-step multiplex assay [117]. CBDs feature equilibrium constants in the picomolar range and are highly species specific and more sensitive than conventional antibodies [117,131]. Recently, CBD domains have been used in combination with gold screen-printed electrodes to develop a biosensor for Listeria [132]. Because of the usefulness of these small phage proteins in combination with powerful detection methods, we expect many more such Bacteriophage functional genomics biosensor platforms targeting many different bacteria to be developed in the near future. In general, CBD proteins are not as effective for detection of Gram-negative cells, as the outer membrane precludes binding to the cell wall receptor structure. For Gram-negative bacteria, phage-tail based affinity molecules are much better suited for immobilization and detection. Moreover, these proteins exhibit similar desirable features as CBD molecules, such as high affinity, high specificity and a single binding site. Besides specific cell decoration, both CBDs and tail adhesins can also be used to immobilize bacterial cells, for example to paramagnetic beads. Enrichment of a specific pathogen from a complex matrix is possible with this technique in a matter of minutes, compared to hours or even days when using conventional enrichment methods [131]. Similar to methods employing whole phage particles, coupling of these phage proteins to specific surfaces for detection applications, paves the way for the development of a new class of biosensor based on phage proteins [133,134]. In conclusion, bacteriophage functional genomics offers exciting new possibilities for detection and control of bacterial pathogens. The high specificity of phages and some phage proteins to their bacterial hosts, combined with the absence of undesired side effects and the relatively straightforward discovery and large-scale production of phages make them ideal tools for food industry and medical applications. However, our knowledge of phage-encoded gene functions, and their influence on the bacterial host gene expression and our general understanding of the molecular diversity of phage life cycle are rather limited. Recent advances in genome sequencing, comparative genomics combined with functional genomic studies will undoubtedly play a major role in filling this knowledge gap and increase our understanding of phage biology for better utilization of these organisms for bacterial detection and therapeutics. Functional genomic studies addressing all stages of the bacteriophage infection cycle can be manipulated in developing methods for pathogen detection. Acknowledgements J.K. is grateful to Martin J. Loessner for providing the research environment which enabled the bacteriophage functional genomics studies mentioned in this manuscript. The views expressed in this article are those of the authors and do not necessarily reflect the official policy or position of the JPEO-CBDCBMS-BSV-CRP, Department of Defense, nor the US Government. References 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. Key points Bacteriophages offer exciting possibilities for the detection and biocontrol of bacterial pathogens. Next-generation sequencing technologies have boosted the number of complete phage genomic sequences available for functional genomic studies. Prophage identification by in silico or experimental methods is mandatory to understand pathogen biology and evolution and can be used for pathogen detection purposes. 361 14. 15. Centers for Disease Control and Prevention. CDC Estimates of Foodborne Illness in the United States. http://www.cdc. gov/foodborneburden/2011-foodborne-estimates.html (27 February 2013, date last accessed). European Food Safety Authority, E.C.f.D.P.a.C The European Union summary report on trends and sources of zoonoses, zoonotic agents and food-borne outbreaks in 2009. EFSA J 2011;9:1–378. Summers WC. Bacteriophage therapy. Annu Rev Microbiol 2001;55:437–51. Abedon ST. Kinetics of phage-mediated biocontrol of bacteria. Foodborne Pathog Dis 2009;6:807–15. Rohwer F, Edwards R. The Phage Proteomic Tree: a genome-based taxonomy for phage. J Bacteriol 2002;184: 4529–35. D’Herelle F. Sur un microbe invisible antagoniste des bacilles dysentériques. C R Hebd Seances Acad Sci D 1917; 165:373–5. Twort F. An investigation on the nature of ultramicroscopic viruses. Lancet 1915;11:1241. Summers W. Bacteriophage research: early history. In: Kutter E, Sulakvelidze A (eds). Bacteriophages: Biology and Applications. Boca Raton, FL: CRC Press, 2005. Summers WC. The strange history of phage therapy. Bacteriophage 2012;2:130–3. Projan S. Phage-inspired antibiotics? Nat Biotechnol 2004;22: 167–8. Sulakvelidze A. Phage therapy: an attractive option for dealing with antibiotic-resistant bacterial infections. Drug Discov Today 2005;10:807–9. Brussow H. What is needed for phage therapy to become a reality in Western medicine? Virology 2012;434:138–42. Smith HW, Huggins MB. Successful treatment of experimental Escherichia coli infections in mice using phage: its general superiority over antibiotics. J Gen Microbiol 1982; 128:307–18. Merril CR, Scholl D, Adhya SL. The prospect for bacteriophage therapy in Western medicine. Nat Rev Drug Discov 2003;2:489–97. Stenholm AR, Dalsgaard I, Middelboe M. Isolation and characterization of bacteriophages infecting the fish pathogen Flavobacterium psychrophilum. Appl Environ Microbiol 2008;74:4070–8. 362 Klumpp et al. 16. Walakira JK, Carrias AA, Hossain MJ, et al. Identification and characterization of bacteriophages specific to the catfish pathogen, Edwardsiella ictaluri. J Appl Microbiol 2008;105: 2133–42. 17. Fujiwara A, Fujisawa M, Hamasaki R, et al. Biocontrol of Ralstonia solanacearum by treatment with lytic bacteriophages. Appl Environ Microbiol 2011;77:4155–62. 18. Callewaert L, Walmagh M, Michiels CW, et al. Food applications of bacterial cell wall hydrolases. Curr Opin Biotechnol 2011;22:164–71. 19. Fenton M, Ross P, McAuliffe O, et al. Recombinant bacteriophage lysins as antibacterials. Bioeng Bugs 2010;1: 9–16. 20. Loessner MJ, Rees CE, Stewart GS, et al. Construction of luciferase reporter bacteriophage A511::luxAB for rapid and sensitive detection of viable Listeria cells. Appl Environ Microbiol 1996;62:1133–40. 21. Loessner MJ, Rudolf M, Scherer S. Evaluation of luciferase reporter bacteriophage A511::luxAB for detection of Listeria monocytogenes in contaminated foods. Appl Environ Microbiol 1997;63:2961–5. 22. Schofield DA, Molineux IJ, Westwater C. Diagnostic bioluminescent phage for detection of Yersinia pestis. J Clin Microbiol 2009;47:3887–94. 23. Schofield DA, Westwater C. Phage-mediated bioluminescent detection of Bacillus anthracis. J Appl Microbiol 2009;107: 1468–78. 24. Guenther S, Herzig O, Fieseler L, et al. Biocontrol of Salmonella Typhimurium in RTE foods with the virulent bacteriophage FO1-E2. IntJ Food Microbiol 2012;154:66–72. 25. Guenther S, Huwyler D, Richard S, et al. Virulent bacteriophage for efficient biocontrol of Listeria monocytogenes in ready-to-eat foods. Appl Environ Microbiol 2009;75: 93–100. 26. Hooton SP, Atterbury RJ, Connerton IF. Application of a bacteriophage cocktail to reduce Salmonella Typhimurium U288 contamination on pig skin. Int J Food Microbiol 2011; 151:157–63. 27. Connerton PL, Timms AR, Connerton IF. Campylobacter bacteriophages and bacteriophage therapy. J Appl Microbiol 2011;111:255–65. 28. Amalaradjou MA, Bhunia AK. Modern approaches in probiotics research to control foodborne pathogens. Adv Food Nutr Res 2012;67:185–239. 29. Brussow H, Canchaya C, Hardt WD. Phages and the evolution of bacterial pathogens: from genomic rearrangements to lysogenic conversion. Microbiol Mol Biol Rev 2004;68: 560–602. 30. Casjens SR. Comparative genomics and evolution of the tailed-bacteriophages. Curr Opin Microbiol 2005;8:451–8. 31. Hendrix RW, Hatfull GF, Smith MC. Bacteriophages with tails: chasing their origins and evolution. Res Microbiol 2003; 154:253–7. 32. Beres SB, Sylva GL, Barbian KD, et al. Genome sequence of a serotype M3 strain of group A Streptococcus: phage-encoded toxins, the high-virulence phenotype, and clone emergence. Proc Natl Acad Sci U S A 2002;99: 10078–83. 33. Hayashi T, Makino K, Ohnishi M, et al. Complete genome sequence of enterohemorrhagic Escherichia coli O157:H7 and genomic comparison with a laboratory strain K-12. DNA Res 2001;8:11–22. 34. Faruque SM, Mekalanos JJ. Phage-bacterial interactions in the evolution of toxigenic Vibrio cholerae. Virulence 2012;3: 1–10. 35. Waldor MK, Mekalanos JJ. Lysogenic conversion by a filamentous phage encoding cholera toxin. Science 1996;272: 1910–4. 36. Muniesa M, Hammerl JA, Hertwig S, et al. Shiga toxin-producing Escherichia coli O104:H4: a new challenge for microbiology. Appl Environ Microbiol 2012;78:4065–73. 37. Klumpp J, Fouts DE, Sozhamannan S. Next-generation sequencing technologies and the changing landscape of phage genomics. Bacteriophage 2012;2:190–9. 38. Carneiro MO, Russ C, Ross MG, et al. Pacific biosciences sequencing technology for genotyping and variation discovery in human data. BMC Genomics 2012;13:375. 39. Quail MA, Smith M, Coupland P, et al. A tale of three next generation sequencing platforms: comparison of Ion Torrent, Pacific Biosciences and Illumina MiSeq sequencers. BMC Genomics 2012;13:341. 40. Casjens S. Prophages and bacterial genomics: what have we learned so far? Mol Microbiol 2003;49:277–300. 41. Miller ES, Kutter E, Mosig G, et al. Bacteriophage T4 genome. Microbiol Mol Biol Rev 2003;67:86–156. 42. Hildebrand A, Remmert M, Biegert A, et al. Fast and accurate automatic structure prediction with HHpred. Proteins 2009;77(Suppl. 9):128–32. 43. Hendrix RW, Lawrence JG, Hatfull GF, et al. The origins and ongoing evolution of viruses. Trends Microbiol 2000;8: 504–8. 44. Ricagno S, Campanacci V, Blangy S, et al. Crystal structure of the receptor-binding protein head domain from Lactococcus lactis phage bIL170. J Virol 2006;80:9331–5. 45. Spinelli S, Campanacci V, Blangy S, et al. Modular structure of the receptor binding proteins of Lactococcus lactis phages. The RBP structure of the temperate phage TP901-1. J Biol Chem 2006;281:14256–62. 46. Spinelli S, Desmyter A, Verrips CT, et al. Lactococcal bacteriophage p2 receptor-binding protein structure suggests a common ancestor gene with bacterial and mammalian viruses. Nat Struct Mol Biol 2006;13:85–9. 47. Tremblay DM, Tegoni M, Spinelli S, et al. Receptor-binding protein of Lactococcus lactis phages: identification and characterization of the saccharide receptor-binding site. J Bacteriol 2006;188:2400–10. 48. Stewart CR, Casjens SR, Cresawn SG, etal. The genome of Bacillus subtilis bacteriophage SPO1. J Mol Biol 2009;388: 48–70. 49. Stewart CR, Gaslightwala I, Hinata K, et al. Genes and regulatory sites of the ‘‘host-takeover module’’ in the terminal redundancy of Bacillus subtilis bacteriophage SPO1. Virology 1998;246:329–40. 50. Oakley BB, Talundzic E, Morales CA, et al. Comparative genomics of four closely related Clostridium perfringens bacteriophages reveals variable evolution among core genes with therapeutic potential. BMC Genomics 2011;12:282. 51. Liu J, Dehbi M, Moeck G, et al. Antimicrobial drug discovery through bacteriophage genomics. Nat Biotechnol 2004; 22:185–91. 52. Fouts DE. Phage_Finder: automated identification and classification of prophage regions in complete bacterial genome sequences. Nucleic Acids Res 2006;34:5839–51. Bacteriophage functional genomics 53. Srividhya KV, Alaguraj V, Poornima G, et al. Identification of prophages in bacterial genomes by dinucleotide relative abundance difference. PLoS One 2007;2:e1193. 54. Lima-Mendez G, Van Helden J, Toussaint A, et al. Prophinder: a computational tool for prophage prediction in prokaryotic genomes. Bioinformatics 2008;24:863–5. 55. Zhou Y, Liang Y, Lynch KH, et al. PHAST: a fast phage search tool. Nucleic Acids Res 2011;39:W347–52. 56. Akhter S, Aziz RK, Edwards RA. PhiSpy: a novel algorithm for finding prophages in bacterial genomes that combines similarity- and composition-based strategies. Nucleic Acids Res 2012;40:e126. 57. Seguritan V, Alves N, Jr, Arnoult M, et al. Artificial neural networks trained to detect viral and phage structural proteins. PLoS Comput Biol 2012;8:e1002657. 58. Fouts DE. Bacteriophage bioinformatics. In: Fraser CM, Read TD, Nelson KE (eds). Microbial Genomes. Totowa, NJ: Humana Press Inc, 2004. 59. Nakayama K, Takashima K, Ishihara H, et al. The R-type pyocin of Pseudomonas aeruginosa is related to P2 phage, and the F-type is related to lambda phage. Mol Microbiol 2000; 38:213–31. 60. Uratani Y, Hoshino T. Pyocin R1 inhibits active transport in Pseudomonas aeruginosa and depolarizes membrane potential. J Bacteriol 1984;157:632–6. 61. Daw MA, Falkiner FR. Bacteriocins: nature, function and structure. Micron 1996;27:467–79. 62. Rampling A, Whitby JL. Preparation of phage-free pyocin extracts for use in the typing of Pseudomonas aeruginosa. J Med Microbiol 1972;5:305–12. 63. Jones LF, Zakanycz JP, Thomas ET, et al. Pyocin typing of Pseudomonas aeruginosa: a simplified method. Appl Microbiol 1974;27:400–6. 64. Busby B, Kristensen DM, Koonin EV. Contribution of phage-derived genomic islands to the virulence of facultative bacterial pathogens. Environ Microbiol 2013;15: 307–12. 65. Rabinovich L, Sigal N, Borovok I, et al. Prophage excision activates Listeria competence genes that promote phagosomal escape and virulence. Cell 2012;150:792–802. 66. Spagnoletti M, Ceccarelli D, Colombo MM. Rapid detection by multiplex PCR of Genomic Islands, prophages and Integrative Conjugative Elements in V. cholerae 7th pandemic variants. J Microbiol Methods 2012;88:98–102. 67. Holochova P, Ruzickova V, Dostalova L, et al. Rapid detection and differentiation of the exfoliative toxin A-producing Staphylococcus aureus strains based on phiETA prophage polymorphisms. Diagn Microbiol Infect Dis 2010;66: 248–52. 68. Besser TE, Shaikh N, Holt NJ, et al. Greater diversity of Shiga toxin-encoding bacteriophage insertion sites among Escherichia coli O157:H7 isolates from cattle than in those from humans. Appl Environ Microbiol 2007;73:671–9. 69. Winstanley C, Langille MG, Fothergill JL, et al. Newly introduced genomic prophage islands are critical determinants of in vivo competitiveness in the Liverpool Epidemic Strain of Pseudomonas aeruginosa. Genome Res 2009;19:12–23. 70. Sozhamannan S, Chute MD, McAfee FD, et al. The Bacillus anthracis chromosome contains four conserved, excision-proficient, putative prophages. BMC Microbiol 2006;6:34. 363 71. Ahmed SA, Awosika J, Baldwin C, et al. Genomic comparison of Escherichia coli O104:H4 isolates from 2009 and 2011 reveals plasmid, and prophage heterogeneity, including shiga toxin encoding phage stx2. PloS One 2012;7:e48228. 72. Loessner MJ, Goeppl S, Busse M. Comparative inducibility of bacteriophage in naturally lysogenic and lysogenized strains of Listeria spp. by U.V. light and Mitomycin C. Lett Appl Microbiol 1991;12:196–9. 73. Livny J, Larock CN, Friedman DI. Identification and isolation of lysogens with induced prophage. Methods Mol Biol 2009;501:253–65. 74. Camilli A, Mekalanos JJ. Use of recombinase gene fusions to identify Vibrio cholerae genes induced during infection. Mol Microbiol 1995;18:671–83. 75. Livny J, Friedman DI. Characterizing spontaneous induction of Stx encoding phages using a selectable reporter system. Mol Microbiol 2004;51:1691–704. 76. Muniesa M, Imamovic L, Jofre J. Bacteriophages and genetic mobilization in sewage and faecally polluted environments. Microb Biotechnol 2011;4:725–34. 77. Sekulovic O, Meessen-Pinard M, Fortier LC. Prophagestimulated toxin production in Clostridium difficile NAP1/ 027 lysogens. J Bacteriol 2011;193:2726–34. 78. Sakaguchi Y, Hayashi T, Kurokawa K, et al. The genome sequence of Clostridium botulinum type C neurotoxinconverting phage and the molecular mechanisms of unstable lysogeny. Proc Natl Acad Sci U S A 2005;102:17472–7. 79. Zou QH, Li QH, Zhu HY, et al. SPC-P1: a pathogenicity-associated prophage of Salmonella paratyphi C. BMC Genomics 2010;11:729. 80. Tormo-Mas MA, Mir I, Shrestha A, et al. Moonlighting bacteriophage proteins derepress staphylococcal pathogenicity islands. Nature 2010;465:779–82. 81. Waddell TE, Franklin K, Mazzocco A, et al. Generalized transduction by lytic bacteriophages. Methods Mol Biol 2009;501:293–303. 82. Hagens S, Loessner MJ. Bacteriophage for biocontrol of foodborne pathogens: calculations and considerations. Curr Pharma Biotechnol 2010;11:58–68. 83. Sciara G, Blangy S, Siponen M, etal. A topological model of the baseplate of lactococcal phage Tuc2009. J Biol Chem 2008;283:2716–23. 84. Siponen M, Spinelli S, Blangy S, et al. Crystal structure of a chimeric receptor binding protein constructed from two lactococcal phages. J Bacteriol 2009;191:3220–5. 85. Duplessis M, Moineau S. Identification of a genetic determinant responsible for host specificity in Streptococcus thermophilus bacteriophages. Mol Microbiol 2001;41:325–36. 86. Duplessis M, Levesque CM, Moineau S. Characterization of Streptococcus thermophilus host range phage mutants. Appl Environ Microbiol 2006;72:3036–41. 87. Shibata Y, Yamashita Y, van der Ploeg JR. The serotype-specific glucose side chain of rhamnose-glucose polysaccharides is essential for adsorption of bacteriophage M102 to Streptococcus mutans. FEMS Microbiol Lett 2009;294: 68–73. 88. Tiwari R, Timoney JF. Streptococcus equi bacteriophage SeP9 binds to group C carbohydrate but is not infective for the closely related S. zooepidemicus. Vet Microbiol 2009;135:304–7. 89. Goulet A, Lai-Kee-Him J, Veesler D, et al. The opening of the SPP1 bacteriophage tail, a prevalent mechanism in 364 Klumpp et al. Gram-positive-infecting siphophages. J Biol Chem 2011;286: 25397–405. 90. Veesler D, Blangy S, Spinelli S, et al. Crystal structure of Bacillussubtilis SPP1 phage gp22 shares fold similarity with a domain of lactococcal phage p2 RBP. Protein Sci 2010;19: 1439–43. 91. Veesler D, Robin G, Lichiere J, et al. Crystal structure of bacteriophage SPP1 distal tail protein (gp19.1): a baseplate hub paradigm in gram-positive infecting phages. J Biol Chem 2010;285:36666–73. 92. Baptista C, Santos MA, Sao-Jose C. Phage SPP1 reversible adsorption to Bacillus subtilis cell wall teichoic acids accelerates virus recognition of membrane receptor YueB. J Bacteriol 2008;190:4989–96. 93. Uchiyama J, Rashel M, Maeda Y, et al. Isolation and characterization of a novel Enterococcus faecalis bacteriophage phiEF24C as a therapeutic candidate. FEMS Microbiol Lett 2008;278:200–6. 94. Uchiyama J, Rashel M, Takemura I, et al. In silico and in vivo evaluation of bacteriophage phiEF24C, a candidate for treatment of Enterococcus faecalis infections. Appl Environ Microbiol 2008;74:4149–63. 95. Uchiyama J, Takemura I, Satoh M, et al. Improved adsorption of an Enterococcus faecalis bacteriophage WEF24C with a spontaneous point mutation. PLOS One 2011;6:1–13. 96. Perez GL, Huynh B, Slater M, et al. Transport of phage P22 DNA across the cytoplasmic membrane. J Bacteriol 2009;191:135–40. 97. Archibald AR, Hancock IC, Harwood CR. Metabolism and Structure of Gram-positive Cell Walls. Bacillus subtilis and Other Gram-Positive Bacteria: Biochemistry, Physiology and Molecular Genetics. Washington: ASM Press, 1993. 98. Arisaka F. Assembly and infection process of bacteriophage T4. Chaos 2005;15:047502. 99. Lavigne R, Briers Y, Hertveldt K, et al. Identification and characterization of a highly thermostable bacteriophage lysozyme. Cell Mol Life Sci 2004;61:2753–9. 100. Letellier L, Boulanger P, Plancon L, et al. Main features on tailed phage, host recognition and DNA uptake. FrontBiosci 2004;9:1228–339. 101. Kenny JG, McGrath S, Fitzgerald GF, et al. Bacteriophage Tuc2009 encodes a tail-associated cell wall-degrading activity. J Bacteriol 2004;186:3480–91. 102. Moak M, Molineux IJ. Peptidoglycan hydrolytic activities associated with bacteriophage virions. Mol Microbiol 2004; 51:1169–83. 103. Paul VD, Rajagopalan SS, Sundarrajan S, et al. A novel bacteriophage Tail-Associated Muralytic Enzyme (TAME) from Phage K and its development into a potent antistaphylococcal protein. BMC Microbiol 2011;11:226. 104. Mc Grath S, Neve H, Seegers JF, et al. Anatomy of a lactococcal phage tail. J Bacteriol 2006;188:3972–82. 105. McGrath S, Fitzgerald GF, van Sinderen D. The impact of bacteriophage genomics. Curr Opin Biotechnol 2004;15: 94–9. 106. Volozhantsev NV, Verevkin VV, Bannov VA, et al. The genome sequence and proteome of bacteriophage PhiCPV1 virulent for Clostridium perfringens. Virus Res 2011;155:433–9. 107. Rashel M, Uchiyama J, Takemura I, et al. Tail-associated structural protein gp61 of Staphylococcus aureus phage phi 108. 109. 110. 111. 112. 113. 114. 115. 116. 117. 118. 119. 120. 121. 122. 123. 124. 125. MR11 has bifunctional lytic activity. FEMS Microbiol Lett 2008;284:9–16. Piuri M, Hatfull GF. A peptidoglycan hydrolase motif within the mycobacteriophage TM4 tape measure protein promotes efficient infection of stationary phase cells. Mol Microbiol 2006;62:1569–85. Luke K, Radek A, Liu X, et al. Microarray analysis of gene expression during bacteriophage T4 infection. Virology 2002;299:182–91. Stewart CR, Yip TK, Myles B, et al. Roles of genes 38, 39, and 40 in shutoff of host biosyntheses during infection of Bacillus subtilis by bacteriophage SPO1. Virology 2009;392: 271–4. Hinton DM, Pande S, Wais N, et al. Transcriptional takeover by sigma appropriation: remodelling of the sigma70 subunit of Escherichia coli RNA polymerase by the bacteriophage T4 activator MotA and co-activator AsiA. Microbiology 2005;151:1729–40. Poranen MM, Ravantti JJ, Grahn AM, etal. Global changes in cellular gene expression during bacteriophage PRD1 infection. J Virol 2006;80:8081–8. Lindell D, Jaffe JD, Coleman ML, et al. Genome-wide expression dynamics of a marine virus and host reveal features of co-evolution. Nature 2007;449:83–6. Koerner JF, Snustad DP. Shutoff of host macromolecular synthesis after T-even bacteriophage infection. Microbiol Rev 1979;43:199–223. Schachtele CF, De Sain CV, Hawley LA, et al. Transcription during the development of bacteriophage phi 29: production of host- and phi 29-specific ribonucleic acid. J Virol 1972;10:1170–8. Schmelcher M, Donovan DM, Loessner MJ. Bacteriophage endolysins as novel antimicrobials. Future Microbiol 2012;7:1147–71. Schmelcher M, Shabarova T, Eugster MR, et al. Rapid multiplex detection and differentiation of Listeria cells by use of fluorescent phage endolysin cell wall binding domains. Appl Environ Microbiol 2010;76:5745–56. Veesler D, Spinelli S, Mahony J, et al. Structure of the phage TP901-1 1.8 MDa baseplate suggests an alternative host adhesion mechanism. Proc Natl Acad Sci U S A 2012; 109:8954–8. Loessner MJ. Bacteriophage endolysins—current state of research and applications. Curr Opin Microbiol 2005;8: 480–7. Nelson DC, Schmelcher M, Rodriguez-Rubio L, et al. Endolysins as antimicrobials. Adv Virus Res 2012;83: 299–365. Kuhn J, Suissa M, Wyse J, et al. Detection of bacteria using foreign DNA: the development of a bacteriophage reagent for Salmonella. IntJ Food Microbiol 2002;74:229–38. Willford J, Goodridge LD. An integrated assay for rapid detection of Escherichia coli O157:H7 on beef samples. Food ProtTrends 2008;28:468–72. Wolber PK, Green RL. Detection of bacteria by transduction of ice nucleation genes. TrendsBiotechnol 1990;8:276–9. Cox CR. Bacteriophage-based methods of bacterial detection and identification. In: Abedon ST, Hyman P (eds). Bacteriophages in Health and Disease. Cambridge: CABI, 2012. Hagens S, de Wouters T, Vollenweider P, et al. Reporter bacteriophage A511::celB transduces a hyperthermostable Bacteriophage functional genomics 126. 127. 128. 129. glycosidase from Pyrococcus furiosus for rapid and simple detection of viable Listeria cells. Bacteriophage 2011;1: 143–51. Edgar R, McKinstry M, Hwang J, et al. High-sensitivity bacterial detection using biotin-tagged phage and quantum-dot nanocomplexes. Proc Natl Acad Sci U S A 2006;103:4841–5. Yim PB, Clarke ML, McKinstry M, et al. Quantitative characterization of quantum dot-labeled lambda phage for Escherichia coli detection. Biotechnol Bioeng 2009;104: 1059–67. Schmitz JE, Schuch R, Fischetti VA. Identifying active phage lysins through functional viral metagenomics. Appl Environ Microbiol 2010;76:7181–7. Briers Y, Schmelcher M, Loessner MJ, et al. The high-affinity peptidoglycan binding domain of Pseudomonas phage endolysin KZ144. Biochem Biophys Res Commun 2009;383:187–91. 365 130. Schmelcher M, Tchang VS, Loessner MJ. Domain shuffling and module engineering of Listeria phage endolysins for enhanced lytic activity and binding affinity. Microb Biotechnol 2011;4:651–62. 131. Kretzer JW, Lehmann R, Schmelcher M, et al. Use of high-affinity cell wall-binding domains of bacteriophage endolysins for immobilization and separation of bacterial cells. Appl Environ Microbiol 2007;73:1992–2000. 132. Tolba M, Ahmed MU, Tlili C, et al. A bacteriophage endolysin-based electrochemical impedance biosensor for the rapid detection of Listeria cells. Analyst 2012;137: 5749–56. 133. Tolba M, Minikh O, Brovko LY, et al. Oriented immobilization of bacteriophages for biosensor applications. Appl Environ Microbiol 2010;76:528–35. 134. Arya SK, Singh A, Naidoo R, et al. Chemically immobilized T4-bacteriophage for specific Escherichia coli detection using surface plasmon resonance. Analyst 2011;136:486–92.