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Page 2 of 21               O’Connell et al. Microbiome Res Rep 2023;2:21  https://dx.doi.org/10.20517/mrr.2023.17

               Conclusion: The link between genus and subcluster classifications appears robust, as most subclusters can be
               assigned a single genus and vice versa. By relating the taxonomic and clustering classification systems, they can be
               easily kept up to date to best reflect MP diversity, which could aid the rapid selection of related (or diverse) phages
               for research, therapeutic and diagnostic purposes.

               Keywords: Mycobacteriophage, taxonomy, ICTV, actinobacteriophage database, novel genera, novel subclusters



               INTRODUCTION
               The frequency of antibiotic resistance (AR) is increasing at a worrying rate. There has been an increase in
                                                                                               [1,2]
               resistant nontuberculosis mycobacteria (NTM) infections, demonstrating varying levels of AR . Although
               NTM are typically opportunistic pathogens, treatment failure may lead to stubborn colonisation . For
                                                                                                     [2]
               example, Mycobacterium avium sbsp. paratuberculosis (MAP) causes chronic gastroenteritis (i.e., Johne’s
               disease) in ruminant animals . In order to address the challenges of AR-related mycobacterial infections,
                                        [3]
               alternatives  to  traditional  antibiotic  regimens  are  actively  being  explored.  One  alternative  is
               mycobacteriophage (MP) therapy . Recently, human case studies involving effective MP therapy were
                                             [4]
               described, the first being the successful treatment of a young cystic fibrosis patient with a chronic AR
               Mycobacterium abscessuss pulmonary infection . As the number of isolated and sequenced phages
                                                          [5,6]
               increases, greater opportunity to create robust MP therapy will arise, either through identifying or
               engineering phages capable of infecting NTM.

               As the genomics era progresses, sequencing and annotation of phage genomes have become as routine and
               vital as phenotypic characterisation (e.g., host range, burst size, and adsorption assays). The ever-increasing
               volume of available genomic information and sequence analysis software allows for more in-depth in silico
               analyses that may provide valuable insights regarding the potential functionality and taxonomy of phages, as
               suggested by Lawrence et al. . By exploring the genomic data further, it may be possible to identify other
                                       [7]
               characteristics (e.g., host range, pH tolerance, heat tolerance) shared by phages belonging to the same
               taxonomic groups (e.g., those belonging to the same genus, subfamily, or family group) that may greatly aid
               the design of phage therapies and diagnostics. However, assumptions made while characterising a new
                                                                                                   [8,9]
               isolate based on their supposed taxonomy can only be trusted if phage taxonomy is well maintained .

               The latest software to be introduced for identifying phage taxonomic relationships is VIRIDIC, which
               calculates intergenomic similarities between viral genomes in a pairwise manner, as well as their length ratio
               and the aligned genome fraction . The output of the algorithm includes a hierarchical heatmap of the
                                            [10]
               similarity scores, which places the most similar genomes together. This heatmap is accompanied by a cluster
               table that indicates genus- and species-level relationships based on pre-set thresholds of genomic
                       [10]
               similarity . The default settings of VIRIDIC are set to identify genome groups based on the latest
               taxonomic demarcations, i.e., genus threshold of ≥ 70% and species threshold of ≥ 95% [10,11] . During its
               development, it was noted that VIRIDIC produced results that most closely supported those of the
               traditional BLASTN algorithm, while outperforming other bioinformatic tools with regard to estimating the
               relatedness between more distally related genomes . The use of VIRIDIC to identify unknown or outdated
                                                          [10]
               phage taxonomy has become commonplace (e.g., classifying phages targeting Pseudomonas, Salmonella,
               Vibrio, and Bacillus) since its development in 2020, as systems move toward sequence-based classifications,
               as predicted by Lawrence et al. in 2002 [7,10,12-17] . With this in mind, the existing taxonomy of publicly available
               MP was interrogated to determine whether the current classifications remain accurate or require revisions.
               Thus far, global efforts have isolated almost 12,000 MP, and over 2,100 have been fully sequenced, largely as
               part of the SEA-PHAGES program. The program initially involved undergrad students undertaking massive
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