ABSTRACT
Ruchi, a temperate, AS1 subcluster bacteriophage isolated in Lumpkin County, Georgia using host Arthrobacter globiformis, possesses a genome of 38,571 bp and 67.7% GC. Annotation of this virus revealed 64 predicted reading frames, no predicted tRNA genes, and a close evolutionary relationship to AS1 phage Basilisk.
KEYWORDS: bacteriophage, genome annotation, arthrobacter phage, AS1
ANNOUNCEMENT
Phage therapy presents an alternative approach to the treatment of multidrug-resistant bacterial infections (1–3). A thorough understanding of phage diversity and evolution is therefore paramount. Here, we contribute to this knowledge with the annotated genome of Ruchi, a temperate AS1 subcluster bacteriophage propagated on Arthrobacter globiformis.
Ruchi was isolated in August 2022 from topsoil from the Pine Valley Recreation Center in Lumpkin County, Georgia (34.51N, 84.06W). Lab methods followed the SEA-PHAGES protocol (4). LB medium was mixed with soil and incubated at 30°C for 1 hour. Supernatant was then sterilized using 0.22 µm filtration. Phage presence was confirmed and purified by standard plaque assay using A. globiformis B-2979 and amplified to high titer via flooding of a web plate. A Wizard DNA extraction kit (Promega) was used on 6.7e−9 pfu/mL lysate to obtain 122.2 ng/µL genomic DNA. A NEBNext Ultra II FS kit was used for sequencing library construction. Illumina MiSeq sequencing yielded ~3,914× coverage from 1.1 million 150-bp single-end reads. Genome assembly used Newbler 2.9 (default settings), and the accuracy and completeness of the assembly were evaluated with Consed 29 (5). Ruchi has siphovirus morphology (Fig. 1) and is likely temperate based on plaque morphology and the presence of a tyrosine integrase gene.
DNA Master 5.23.6 (6), Glimmer 3.02 (7), GeneMark 3.26 (8), BLAST (9, 10), HHPred 2.08 (11), Phamerator 505 (12), tRNAscan SE 2.0 (13), Aragorn (14), and DeepTMHMM 1.0.24 (15) were used for genome annotation (all using default parameters). DNA Master provided first-pass analysis of open reading frames (ORFs), gaps, and ribosomal binding sites. Subsequent homology assessment using BLASTp (16) (Genbank nr database), HHPred (default pdb database; UniRef30), and Phamerator refined the annotation. Gaps larger than 25 bp were assessed for additional genes. An e value <10−4 was used as the threshold for function assignments (17).
The complete Ruchi genome (38,571 bp; 67.7% GC; 3′ overhang GAGTTGCCGGGA) contains 64 predicted ORFs [36 with ascribed function (56%)] and no predicted tRNA genes. Genes 1–24 and 35–64 are encoded on one strand, and genes 25–34 are encoded on the other. Among the predicted genes are four nucleases, endolysin, an immunity repressor (adjacent to tyrosine integrase), and an excise protein as well as RusA-like resolvase. ORFs 14 and 15 are predicted to encode overlapping tail assembly chaperones (111 and 244 aa, respectively) with ORF 14 terminated by a −1 frameshift at nucleotide position 10336. Three predicted ORFs with assigned functions (ORFs 4, 16, 24) and five with unassigned functions (ORFs 1, 21, 22, 39, 47) likely have transmembrane domains. Ruchi shares the highest nucleotide sequence similarity (98.7% identity) with Arthrobacter phage Basilisk (Genbank ON260822), which was isolated from Lumpkin County, GA, a year earlier about 20 km from Ruchi’s locale.
ACKNOWLEDGMENTS
This SEA-PHAGES project was supported by the Howard Hughes Medical Institute. EM was performed by M. Ard at the UGA Electron Microscopy facility. Illumina sequencing was performed by the Pittsburgh Bacteriophage Institute. L. Chuhran, C. Teems, and C. Whitlow assisted in phage isolation and annotation. C. Miller and A. Nesbitt assisted with laboratory components.
Contributor Information
Alison Kanak, Email: alison.kanak@ung.edu.
Kenneth M. Stedman, Portland State University, Portland, Oregon, USA
DATA AVAILABILITY
The Ruchi genome can be accessed through NCBI (Genbank OR434022) and sequencing reads can be obtained from the SRA (SRX22366555).
REFERENCES
- 1. Jones JD, Varghese D, Pabary R, Langley RJ. 2022. The potential of bacteriophage therapy in the treatment of paediatric respiratory infections. Paediatr Respir Rev 44:70–77. doi: 10.1016/j.prrv.2022.02.001 [DOI] [PubMed] [Google Scholar]
- 2. Marongiu L, Burkard M, Lauer UM, Hoelzle LE, Venturelli S. 2022. Reassessment of historical clinical trials supports the effectiveness of phage therapy. Clin Microbiol Rev 35:e0006222. doi: 10.1128/cmr.00062-22 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3. Vandamme EJ, Mortelmans K. 2019. A century of bacteriophage research and applications: impacts on biotechnology, health, ecology and the economy!: a century of bacteriophage research and applications. J Chem Tech Biotech 94:323–342. doi: 10.1002/jctb.5810 [DOI] [Google Scholar]
- 4. Jordan TC, Burnett SH, Carson S, Caruso SM, Clase K, DeJong RJ, Dennehy JJ, Denver DR, Dunbar D, Elgin SCR, et al. 2014. A broadly implementable research course in phage discovery and genomics for first-year undergraduate students. mBio 5:e01051-13. doi: 10.1128/mBio.01051-13 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5. Russell DA. 2018. Sequencing, assembling, and finishing complete bacteriophage genomes. Methods Mol Biol 1681:109–125. doi: 10.1007/978-1-4939-7343-9_9 [DOI] [PubMed] [Google Scholar]
- 6. Lawrence J. 2021. DNA master version 5.23.6 (Build 2705; 24 Oct 2021)
- 7. Delcher AL, Bratke KA, Powers EC, Salzberg SL. 2007. Identifying bacterial genes and endosymbiont DNA with glimmer. Bioinformatics 23:673–679. doi: 10.1093/bioinformatics/btm009 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8. Besemer J, Lomsadze A, Borodovsky M. 2001. GeneMarkS: a self-training method for prediction of gene starts in microbial genomes. implications for finding sequence motifs in regulatory regions. Nucleic Acids Res 29:2607–2618. doi: 10.1093/nar/29.12.2607 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9. National Center for Biotechnology Information (NCBI) [Internet] . 2023. Bethesda (MD) National library of medicine (US), National center for biotechnology information [1988]. Available from: https://www.ncbi.nlm.nih.gov/
- 10. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. 1990. Basic local alignment search tool. J Mol Biol 215:403–410. doi: 10.1016/S0022-2836(05)80360-2 [DOI] [PubMed] [Google Scholar]
- 11. Söding J, Biegert A, Lupas AN. 2005. The HHpred interactive server for protein homology detection and structure prediction. Nucleic Acids Res 33:W244–W248. doi: 10.1093/nar/gki408 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12. Cresawn SG, Bogel M, Day N, Jacobs-Sera D, Hendrix RW, Hatfull GF. 2011. Phamerator: a bioinformatic tool for comparative bacteriophage genomics. BMC Bioinformatics 12:395. doi: 10.1186/1471-2105-12-395 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13. Chan PP, Lin BY, Mak AJ, Lowe TM. 2021. tRNAscan-SE 2.0: improved detection and functional classification of transfer RNA genes. Nucleic Acids Res 49:9077–9096. doi: 10.1093/nar/gkab688 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14. Laslett D, Canback B. 2004. ARAGORN, a program to detect tRNA genes and tmRNA genes in nucleotide sequences. Nucleic Acids Res 32:11–16. doi: 10.1093/nar/gkh152 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15. Hallgren J, Tsirigos KD, Pedersen MD, Almagro Armenteros JJ, Marcatili P, Nielsen H, Krogh A, Winther O. 2022. DeepTMHMM predicts alpha and beta transmembrane proteins using deep neural networks. Bioinformatics. doi: 10.1101/2022.04.08.487609 [DOI]
- 16. Gish W, States DJ. 1993. Identification of protein coding regions by database similarity search. Nat Genet 3:266–272. doi: 10.1038/ng0393-266 [DOI] [PubMed] [Google Scholar]
- 17. Colston LE, Segura-Totten M, Shanks RA. 2020. Characterization and genome sequence of the mycobacteriophage Donny. Microbiol Resour Announc 9:e00373-20. doi: 10.1128/MRA.00373-20 [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The Ruchi genome can be accessed through NCBI (Genbank OR434022) and sequencing reads can be obtained from the SRA (SRX22366555).