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Bacteriophages are being widely harnessed as an alternative to antibiotics due to the global emergence of drug-resistant pathogens. To guide the usage of these bactericidal agents, characterization of their host specificity is vital—however, host range information remains limited for many bacteriophages. This is particularly the case for bacteriophages infecting the Microbacterium genus, despite their importance in agriculture, biomedicine, and biotechnology. Here, we elucidate the phylogenomic relationships between 125 Microbacterium cluster EA bacteriophages—including members from 11 sub-clusters (EA1 to EA11)—and infer their putative host ranges using insights from codon usage bias patterns as well as predictions from both exploratory and confirmatory computational methods. Our computational analyses suggest that cluster EA bacteriophages have a shared infection history across the Microbacterium clade. Interestingly, bacteriophages of all sub-clusters exhibit codon usage preference patterns that resemble those of bacterial strains different from ones used for isolation, suggesting that they might be able to infect additional hosts. Furthermore, host range predictions indicate that certain sub-clusters may be better suited in prospective biotechnological and medical applications such as phage therapy.

Bacteriophages infecting bacteria of the genus Gordonia have increasingly gained interest in the scientific community for their diverse applications in agriculture, biotechnology, and medicine, ranging from biocontrol agents in wastewater management to the treatment of opportunistic pathogens in pulmonary disease patients. However, due to the time and costs associated with experimental isolation and cultivation, host ranges for many bacteriophages remain poorly characterized, hindering a more efficient usage of bacteriophages in these areas. Here, we perform a series of computational genomic inferences to predict the putative host ranges of all Gordonia cluster DR bacteriophages known to date. Our analyses suggest that BiggityBass (as well as several of its close relatives) is likely able to infect host bacteria from a wide range of genera—from Gordonia to Nocardia to Rhodococcus, making it a suitable candidate for future phage therapy and wastewater treatment strategies.

Increased antibiotic resistance has prompted the development of bacteriophage agents for a multitude of applications in agriculture, biotechnology, and medicine. A key factor in the choice of agents for these applications is the host range of a bacteriophage, i.e., the bacterial genera, species, and strains a bacteriophage is able to infect. Although experimental explorations of host ranges remain the gold standard, such investigations are inherently limited to a small number of viruses and bacteria amendable to cultivation. Here, we review recently developed bioinformatic tools that offer a promising and high-throughput alternative by computationally predicting the putative host ranges of bacteriophages, including those challenging to grow in laboratory environments.

AbstractBacteriophages infecting pathogenic hosts play an important role in medical research, not only as potential treatments for antibiotic-resistant infections but also offering novel insights into pathogen genetics and evolution. A prominent example is cluster K mycobacteriophages infecting Mycobacterium tuberculosisM. tuberculosisMycobacterium smegmatisM. tuberculosisMycobacterium lepraeMycobacterium abscessusMycobacterium marinum—