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Page 4 of 17 Wottrich et al. Microbiome Res Rep 2024;3:27 https://dx.doi.org/10.20517/mrr.2023.42

Table 1. C. acnes bacteriophages used in this study
Phage name GenBank Accession No. Bacterial host Experiments
Aquarius a MF919491 Cutibacterium acnes All experiments
a
Lauchelly NC_027628 Cutibacterium acnes Cross spotting; bioinformatics
a
BruceLethal NC_031084 Cutibacterium acnes Cross spotting
a
QueenBey NC_031005 Cutibacterium acnes Cross spotting
b
ATCC 29399B_C JX262225 Cutibacterium acnes Cross spotting; escape mutant isolation
P100A c JX262221 Cutibacterium acnes Cross spotting
c
P100D NC_018852 Cutibacterium acnes Cross spotting
P104A c NC_018845 Cutibacterium acnes Cross spotting
c
P105 NC_018849 Cutibacterium acnes Cross spotting
TP-J34 d HE861935 Streptococcus thermophilus; Lactococcus lactis Bioinformatics
e
TP-778L HG380752 Streptococcus thermophilus; Lactococcus lactis Bioinformatics
a [26] b
Source: UCLA Advanced Research in Virology Undergraduate Laboratory Curriculum ; Source: Clear/lytic (C) plaque isolated by Marinelli
et al. (2012) from a mixed population of clear and turbid plaques observed from C. acnes phage stock ATCC 29399B originally described by
[3,27] c [3] d [28] e [23]
Webster and Cummins (1978) ; Source: Marinelli et al. (2012) ; Source: Neve et al. (2003) ; Source: Ali et al. (2014) . UCLA:
University of California, Los Angeles.

Genome annotation and comparative analysis
Preliminary annotation of the genome was conducted via the prokaryotic gene protein-coding potential
prediction software tools Glimmer and GeneMark, in conjunction with DNA Master as the point source for
genomic edits and organization [30-32] . Refining of the locations of the auto-called genes was performed using
a set of bioinformatics tools, including Starterator, Phamerator, and the NCBI BLAST suite [33,34] . Following
confirmation of all gene locations, functional assignments were performed for each gene using a variety of
bioinformatics tools, including the domain predicting tool HHPred, the Conserved Domain Database
(CDD), Phamerator, the NCBI BLAST suite, Phagesdb (local) BLAST, and the Protein Database (PDB) [34-38] .

Gene Content Similarity (GCS) for the C. acnes phages used in this study was calculated using the Explore
Gene Content tool embedded in the Acinobacteriophage Database (https://phagesdb.org/genecontent/).
GCS is calculated by identifying the number of phams (gene “phamilies” with a high degree of alignment)
that are present in both phages and dividing that number by the total number of phams present in each
phage, then averaging the two values . Phamerator.org was used to generate comparative genomic maps
[34]
for the C. acnes phages [34,38] . The streptococcus phages were not included in these analyses because the
Phagesdb and Phamerator databases are limited to actinobacteriophages. Pairwise comparisons of the
genome nucleotide sequences for all phages in Table 1, including the streptococcus phages, were conducted
using the Genome-BLAST Distance Phylogeny (GBDP) method under settings recommended for
[39]
prokaryotic viruses . The resulting intergenomic distances were used to infer a balanced minimum
[40]
evolution tree with branch support via FASTME including SPR postprocessing for the D0 formula.
[41]
Branch support was inferred from 100 pseudo-bootstrap replicates each. Trees were rooted at the
[42]
midpoint and visualized with iTOL .
[43]
SIR testing
Lawns of C. acnes ATCC 6919 and three clinical isolates [strains 060PA1, 110PA3, and 020PA1, described
by Fitz-Gibbon et al. (2013)] were spot inoculated with phage lysates and observed for bacterial regrowth
within the plaques . Putative pseudolysogens were collected by taking five samples of bacteria that grew in
[1]
the centers of areas of clearing, three from a host range assay and two from a phage lysate plate. These
samples were inoculated in RCM and incubated for three days at 37 °C under anaerobic conditions. The
-1
-9
putative pseudolysogens were plated on A Media and 10-fold dilutions (ranging from 10 to 10 ) of phage