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Genome alignment of the strain described in this study (purple) with the M. smegmatis (orange) and M. <t>wolinskyi</t> (green) reference genomes. Genomic islands (cyan) were predicted using IslandPath-DIMOB prediction method in IslandViewer 4 , whereas phage regions (magenta and brown) were predicted using the PHASTEST tool in Proksee. Antibiotic resistance markers predicted by the CARD Resistance Gene Identifier are indicated as well as efflux pumps are highlighted in red and purple, respectively. All features, as well as the complete image, were generated using Proksee. The average nucleotide identity (ANI) compared with M. smegmatis strain Jucho and M. wolisnkyi ATCC 700010 was 82.62% and 97.49%, respectively.
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Genome alignment of the strain described in this study (purple) with the M. smegmatis (orange) and M. <t>wolinskyi</t> (green) reference genomes. Genomic islands (cyan) were predicted using IslandPath-DIMOB prediction method in IslandViewer 4 , whereas phage regions (magenta and brown) were predicted using the PHASTEST tool in Proksee. Antibiotic resistance markers predicted by the CARD Resistance Gene Identifier are indicated as well as efflux pumps are highlighted in red and purple, respectively. All features, as well as the complete image, were generated using Proksee. The average nucleotide identity (ANI) compared with M. smegmatis strain Jucho and M. wolisnkyi ATCC 700010 was 82.62% and 97.49%, respectively.
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Genome alignment of the strain described in this study (purple) with the M. smegmatis (orange) and M. <t>wolinskyi</t> (green) reference genomes. Genomic islands (cyan) were predicted using IslandPath-DIMOB prediction method in IslandViewer 4 , whereas phage regions (magenta and brown) were predicted using the PHASTEST tool in Proksee. Antibiotic resistance markers predicted by the CARD Resistance Gene Identifier are indicated as well as efflux pumps are highlighted in red and purple, respectively. All features, as well as the complete image, were generated using Proksee. The average nucleotide identity (ANI) compared with M. smegmatis strain Jucho and M. wolisnkyi ATCC 700010 was 82.62% and 97.49%, respectively.
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Genome alignment of the strain described in this study (purple) with the M. smegmatis (orange) and M. wolinskyi (green) reference genomes. Genomic islands (cyan) were predicted using IslandPath-DIMOB prediction method in IslandViewer 4 , whereas phage regions (magenta and brown) were predicted using the PHASTEST tool in Proksee. Antibiotic resistance markers predicted by the CARD Resistance Gene Identifier are indicated as well as efflux pumps are highlighted in red and purple, respectively. All features, as well as the complete image, were generated using Proksee. The average nucleotide identity (ANI) compared with M. smegmatis strain Jucho and M. wolisnkyi ATCC 700010 was 82.62% and 97.49%, respectively.

Journal: ASM Case Reports

Article Title: Mycobacterium wolinskyi as an emerging cause of pacemaker pocket infection and lead endocarditis: a case report and genomic characterization

doi: 10.1128/asmcr.00146-25

Figure Lengend Snippet: Genome alignment of the strain described in this study (purple) with the M. smegmatis (orange) and M. wolinskyi (green) reference genomes. Genomic islands (cyan) were predicted using IslandPath-DIMOB prediction method in IslandViewer 4 , whereas phage regions (magenta and brown) were predicted using the PHASTEST tool in Proksee. Antibiotic resistance markers predicted by the CARD Resistance Gene Identifier are indicated as well as efflux pumps are highlighted in red and purple, respectively. All features, as well as the complete image, were generated using Proksee. The average nucleotide identity (ANI) compared with M. smegmatis strain Jucho and M. wolisnkyi ATCC 700010 was 82.62% and 97.49%, respectively.

Article Snippet: Because of discrepant 16S rRNA sequencing results and low ANI percentage compared with the M. wolinskyi reference genome (strain ATCC 700010), a phylogenetic analysis was performed.

Techniques: Generated

Genome alignment of the strain described in this study (purple) with the M. smegmatis (orange) and M. wolinskyi (green) reference genomes. Genomic islands (cyan) were predicted using IslandPath-DIMOB prediction method in IslandViewer 4 , whereas phage regions (magenta and brown) were predicted using the PHASTEST tool in Proksee. Antibiotic resistance markers predicted by the CARD Resistance Gene Identifier are indicated as well as efflux pumps are highlighted in red and purple, respectively. All features, as well as the complete image, were generated using Proksee. The average nucleotide identity (ANI) compared with M. smegmatis strain Jucho and M. wolisnkyi ATCC 700010 was 82.62% and 97.49%, respectively.

Journal: ASM Case Reports

Article Title: Mycobacterium wolinskyi as an emerging cause of pacemaker pocket infection and lead endocarditis: a case report and genomic characterization

doi: 10.1128/asmcr.00146-25

Figure Lengend Snippet: Genome alignment of the strain described in this study (purple) with the M. smegmatis (orange) and M. wolinskyi (green) reference genomes. Genomic islands (cyan) were predicted using IslandPath-DIMOB prediction method in IslandViewer 4 , whereas phage regions (magenta and brown) were predicted using the PHASTEST tool in Proksee. Antibiotic resistance markers predicted by the CARD Resistance Gene Identifier are indicated as well as efflux pumps are highlighted in red and purple, respectively. All features, as well as the complete image, were generated using Proksee. The average nucleotide identity (ANI) compared with M. smegmatis strain Jucho and M. wolisnkyi ATCC 700010 was 82.62% and 97.49%, respectively.

Article Snippet: Further alignment of the genome of the mycobacterial isolate with reference genomes of M. smegmatis (strain Jucho) and M. wolinskyi (strain ATCC 700010) using Proksee ( ) showed a closer relationship to M. wolinskyi than to M. smegmatis , despite having only an average nucleotide identity (ANI) of about 97.49% compared with M. wolinskyi , which is above the cut-off of 95%–96% proposed by Richter & Rossello-Mora to classify bacteria as the same species, but below the cut-off of 98% that is generally used to distinguish between subspecies ( ) ( ).

Techniques: Generated