Computational Prediction of Bacteriophage Host Ranges

Versoza, Cyril J; Pfeifer, Susanne

doi:10.3390/microorganisms10010149

Cited by 25 publications

(24 citation statements)

References 55 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This gap is slowly filled with new laboratory methods of high-throughput identification of virus-host interactions (including proximity ligation, viral tagging, phageFISH, and XRM-Seq) but these methods still require a careful interpretation by an expert and thus the paste of the discovery lags the deluge of metagenomic data ( Coclet and Roux, 2021 ; Smith et al, 2022 ). These issues have prompted the development of bioinformatics tools that predict the potential host(s) based on the virus genome sequence and may select candidates for experimental verification of the interaction ( Versoza and Pfeifer, 2022 ). Some of the most promising approaches to phage-host predictions are based on machine learning (ML) algorithms ( Wang et al, 2020 ; Coutinho et al, 2021 ).…”

Section: Discussionmentioning

confidence: 99%

“…Some of the most promising approaches to phage-host predictions are based on machine learning (ML) algorithms ( Wang et al, 2020 ; Coutinho et al, 2021 ). As has been recently highlighted ( Coclet and Roux, 2021 ; Versoza and Pfeifer, 2022 ), there is a pressing need to establish robust, comprehensive, and balanced sets suitable for training and testing ML algorithms. PHD can aid developers in constructing custom sets meeting specific criteria such as taxonomic affiliations of viruses and hosts, quality of the genome assemblies, and source databases.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Daily Reports on Phage-Host Interactions

Albrycht

Rynkiewicz²,

Harasymczuk³

et al. 2022

Front. Microbiol.

View full text Add to dashboard Cite

Understanding phage-host relationships is crucial for the study of virus biology and the application of phages in biotechnology and medicine. However, information concerning the range of hosts for bacterial and archaeal viruses is scattered across numerous databases and is difficult to obtain. Therefore, here we present PHD (Phage & Host Daily), a web application that offers a comprehensive, up-to-date catalog of known phage-host associations that allows users to select viruses targeting specific bacterial and archaeal taxa of interest. Our service combines the latest information on virus-host interactions from seven source databases with current taxonomic classification retrieved directly from the groups and institutions responsible for its maintenance. The web application also provides summary statistics on host and virus diversity, their pairwise interactions, and the host range of deposited phages. PHD is updated daily and available at http://phdaily.info or http://combio.pl/phdaily.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Daily Reports on Phage-Host Interactions

Albrycht

Rynkiewicz²,

Harasymczuk³

et al. 2022

Front. Microbiol.

View full text Add to dashboard Cite

show abstract

“…Following the best practices suggested by Versoza and Pfeifer (2022) , both exploratory and confirmatory methods were used to computationally predict host ranges for 40 closely related cluster P mycobacteriophages ( Supplementary Table 1 ). First, the exploratory tool PHERI v.0.2 ( Baláž et al 2020 ) was used to predict bacterial host genera.…”

Section: Methodsmentioning

confidence: 99%

Phylogenomic analyses and host range prediction of cluster P mycobacteriophages

Howell

Versoza

Cerna

et al. 2022

G3 Genes|Genomes|Genetics

Self Cite

View full text Add to dashboard Cite

Bacteriophages, infecting bacterial hosts in every environment on our planet, are a driver of adaptive evolution in bacterial communities. At the same time, the host range of many bacteriophages—and thus one of the selective pressures acting on complex microbial systems in nature—remains poorly characterized. Here, we computationally inferred the putative host ranges of 40 cluster P mycobacteriophages, including members from six sub-clusters (P1-P6). A series of comparative genomic analyses revealed that mycobacteriophages of sub-cluster P1 are restricted to the Mycobacterium genus, whereas mycobacteriophages of sub-clusters P2 to P6 are likely also able to infect other genera, several of which are commonly associated with human disease. Further genomic analysis highlighted that the majority of cluster P mycobacteriophages harbor a conserved integration-dependent immunity system, hypothesized to be the ancestral state of a genetic switch that controls the shift between lytic and lysogenic life cycles—a temperate characteristic that impedes their usage in anti-bacterial applications.

show abstract

“…There are some tools available online to identify these features, such as VirHostMatcher, which identifies host range based on oligonucleotide frequency in a k-mer length [ 103 ]. Lastly, the advancement of high-throughput sequencing technology allows prediction of host range based on sequence features, CpG bias, and CG bias through machine learning algorithms [ 104 , 105 ].…”

Section: Engineering Strategies Of Phage Tail Fiber For Reprogramming...mentioning

confidence: 99%

Understanding Bacteriophage Tail Fiber Interaction with Host Surface Receptor: The Key “Blueprint” for Reprogramming Phage Host Range

Mourosi

Awe

Guo

et al. 2022

IJMS

View full text Add to dashboard Cite

Bacteriophages (phages), as natural antibacterial agents, are being rediscovered because of the growing threat of multi- and pan-drug-resistant bacterial pathogens globally. However, with an estimated 1031 phages on the planet, finding the right phage to recognize a specific bacterial host is like looking for a needle in a trillion haystacks. The host range of a phage is primarily determined by phage tail fibers (or spikes), which initially mediate reversible and specific recognition and adsorption by susceptible bacteria. Recent significant advances at single-molecule and atomic levels have begun to unravel the structural organization of tail fibers and underlying mechanisms of phage–host interactions. Here, we discuss the molecular mechanisms and models of the tail fibers of the well-characterized T4 phage’s interaction with host surface receptors. Structure–function knowledge of tail fibers will pave the way for reprogramming phage host range and will bring future benefits through more-effective phage therapy in medicine. Furthermore, the design strategies of tail fiber engineering are briefly summarized, including machine-learning-assisted engineering inspired by the increasingly enormous amount of phage genetic information.

show abstract

Computational Prediction of Bacteriophage Host Ranges

Cited by 25 publications

References 55 publications

Daily Reports on Phage-Host Interactions

Daily Reports on Phage-Host Interactions

Phylogenomic analyses and host range prediction of cluster P mycobacteriophages

Understanding Bacteriophage Tail Fiber Interaction with Host Surface Receptor: The Key “Blueprint” for Reprogramming Phage Host Range

Contact Info

Product

Resources

About