ABSTRACT
Here, we report the complete genome sequence of nitric oxide (NO)-producing Limosilactobacillus fermentum strain DM075, which was isolated from human tongue coating samples from healthy donors in South Korea. The complete genome sequence of DM075 comprises a single circular 2,204,022-bp genome, with a GC content of 51.0%, and lacks antimicrobial resistance genes.
ANNOUNCEMENT
The relationship between oral microbiota and their production of nitric oxide (NO) has recently gained much attention (1–6). To isolate NO-producing Lactobacillus strains, we obtained tongue coating samples from healthy donors from South Korea, measured nitrate-reducing activity using a double agar overlay method based on the Griess reaction (4), and identified DM075 by complete 16S rRNA gene sequencing in February 2022.
For long-read sequencing, DM075 was anaerobically and statically cultivated in MRS broth for 24 h at 37°C. Genomic DNA (gDNA) was extracted using the Maxwell RSC system (Promega, USA) and sheared to 7 to 12 kb using the Megaruptor 3 system (Diagenode, USA), and small fragments (<3 kb) were removed using AMPure PB beads (Pacific Biosciences [PacBio], USA). The sequencing library was constructed using 3 μg of gDNA with the SMRTbell Express template preparation kit v2.0 (PacBio). The library was sequenced using the Sequel system (PacBio), yielding a total of 78,320 subreads (N50, 10,359 bp) with an average length of 8,323 bp. The data were assembled according to the Microbial Assembly protocol in SMRT Link v10.1.0.119588 (PacBio), including read quality control, error correction, adapter filtering, circularity checking, and overlap trimming (7), which produced a single circular oriC-rotated genome. For short-read sequencing, 100 ng of gDNA was sheared using Adaptive Focused Acoustics technology (Covaris, USA), and an ~350-bp sequencing library was prepared using the TruSeq Nano DNA high-throughput library preparation kit (Illumina, USA). The HiSeq X Ten platform (Illumina) was used for the sequencing, which resulted in a total of 17,586,382 quality-filtered 2 × 151-bp paired-end reads (with ≥90% of bases having Phred quality scores of >30). The Illumina reads were then mapped to the PacBio-assembled genome using BWA-MEM v0.7.17 (8) after adapter and quality trimming with Trimmomatic v0.38 (9). The final error correction was conducted three times with Pilon v1.21 (10) with a default minDepth value of 0.01, resulting in a single circular 2,204,022-bp chromosome (Table 1).
TABLE 1.
Summary of assembly and annotation statistics for L. fermentum DM075
| Parameter | Finding |
|---|---|
| Genetic element | Chromosome |
| Length (bp) | 2,204,022 |
| GC content (%) | 51.0 |
| No. of coding sequences | 2,129 |
| No. of rRNAs | 15 |
| No. of tRNAs | 58 |
| Sequencing depth (×) | 259.2 |
| GenBank accession no. | CP100352 |
The average nucleotide identity (ANI) was analyzed using OrthoANI (11), which yielded 99.28% sequence similarity with Limosilactobacillus fermentum CBA7106 (GenBank accession number CP021964.1). The genome annotation by the NCBI Prokaryotic Genome Annotation Pipeline (PGAP) v6.1 (12) predicted 2,129 protein-coding genes, 15 rRNA genes, and 58 tRNA genes. Additional annotations were conducted using Prokka v1.14.6 (13), InterProScan v5.30-69.0 (14), and eggNOG DB v4.5 (15), which suggested the highest incidence of genes for DNA metabolism (16.5%), followed by amino acid metabolism (8.6%) and translation (6.5%). The absence of antibiotic resistance genes, one of the key prerequisites for strain safety, was verified using ResFinder v4.1 (16) and the Comprehensive Antibiotic Resistance Database (CARD) v3.2.3 (17). All tools were run with default parameters unless otherwise specified.
The biospecimens used for this study were provided by the Biobank of Apple Tree Dental Hospital, a member of the Korea Biobank Network, after approval from the public institutional review board (http://public.irb.or.kr) (approval number P01-202111-31-002).
Data availability.
The accession numbers for the 16S rRNA partial sequence and the genome sequence and raw sequencing reads for DM075 are as follows: GenBank, OP579185.1 and CP100352; BioProject, PRJNA853106; BioSample, SAMN29360653; SRA, SRX15901026 and SRX15901027.
ACKNOWLEDGMENT
This work was supported in part by the grant from the KBN (KBN4-A04-03). We thank Macrogen, Inc. (Seoul, Korea) for 16S rRNA and genome sequencing.
Contributor Information
Inseong Hwang, Email: his@docsmedi.kr.
Steven R. Gill, University of Rochester School of Medicine and Dentistry
REFERENCES
- 1.Rosier BT, Buetas E, Moya-Gonzalvez EM, Artacho A, Mira A. 2020. Nitrate as a potential prebiotic for the oral microbiome. Sci Rep 10:12895. doi: 10.1038/s41598-020-69931-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Vanhatalo A, L'Heureux JE, Kelly J, Blackwell JR, Wylie LJ, Fulford J, Winyard PG, Williams DW, van der Giezen M, Jones AM. 2021. Network analysis of nitrate-sensitive oral microbiome reveals interactions with cognitive function and cardiovascular health across dietary interventions. Redox Biol 41:101933. doi: 10.1016/j.redox.2021.101933. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Xu J, Verstraete W. 2001. Evaluation of nitric oxide production by lactobacilli. Appl Microbiol Biotechnol 56:504–507. doi: 10.1007/s002530100616. [DOI] [PubMed] [Google Scholar]
- 4.Doel JJ, Benjamin N, Hector MP, Rogers M, Allaker RP. 2005. Evaluation of bacterial nitrate reduction in the human oral cavity. Eur J Oral Sci 113:14–19. doi: 10.1111/j.1600-0722.2004.00184.x. [DOI] [PubMed] [Google Scholar]
- 5.Bhusal A, Muriana PM. 2021. Isolation and characterization of nitrate reducing bacteria for conversion of vegetable-derived nitrate to ‘natural nitrite.’ Appl Microbiol 1:11–23. doi: 10.3390/applmicrobiol1010002. [DOI] [Google Scholar]
- 6.Sato-Suzuki Y, Washio J, Wicaksono DP, Sato T, Fukumoto S, Takahashi N. 2020. Nitrite-producing oral microbiome in adults and children. Sci Rep 10:16652. doi: 10.1038/s41598-020-73479-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Chin CS, Alexander DH, Marks P, Klammer AA, Drake J, Heiner C, Clum A, Copeland A, Huddleston J, Eichler EE, Turner SW, Korlach J. 2013. Nonhybrid, finished microbial genome assemblies from long-read SMRT sequencing data. Nat Methods 10:563–569. doi: 10.1038/nmeth.2474. [DOI] [PubMed] [Google Scholar]
- 8.Li H. 2013. Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. arXiv 1303.3997. doi: 10.48550/arXiv.1303.3997. [DOI]
- 9.Bolger AM, Lohse M, Usadel B. 2014. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30:2114–2120. doi: 10.1093/bioinformatics/btu170. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Walker BJ, Abeel T, Shea T, Priest M, Abouelliel A, Sakthikumar S, Cuomo CA, Zeng Q, Wortman J, Young SK, Earl AM. 2014. Pilon: an integrated tool for comprehensive microbial variant detection and genome assembly improvement. PLoS One 9:e112963. doi: 10.1371/journal.pone.0112963. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Yoon SH, Ha SM, Lim J, Kwon S, Chun J. 2017. A large-scale evaluation of algorithms to calculate average nucleotide identity. Antonie Van Leeuwenhoek 110:1281–1286. doi: 10.1007/s10482-017-0844-4. [DOI] [PubMed] [Google Scholar]
- 12.Tatusova T, DiCuccio M, Badretdin A, Chetvernin V, Nawrocki EP, Zaslavsky L, Lomsadze A, Pruitt KD, Borodovsky M, Ostell J. 2016. NCBI Prokaryotic Genome Annotation Pipeline. Nucleic Acids Res 44:6614–6624. doi: 10.1093/nar/gkw569. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Seemann T. 2014. Prokka: rapid prokaryotic genome annotation. Bioinformatics 30:2068–2069. doi: 10.1093/bioinformatics/btu153. [DOI] [PubMed] [Google Scholar]
- 14.Jones P, Binns D, Chang HY, Fraser M, Li W, McAnulla C, McWilliam H, Maslen J, Mitchell A, Nuka G, Pesseat S, Quinn AF, Sangrador-Vegas A, Scheremetjew M, Yong SY, Lopez R, Hunter S. 2014. InterProScan 5: genome-scale protein function classification. Bioinformatics 30:1236–1240. doi: 10.1093/bioinformatics/btu031. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Huerta-Cepas J, Szklarczyk D, Forslund K, Cook H, Heller D, Walter MC, Rattei T, Mende DR, Sunagawa S, Kuhn M, Jensen LJ, von Mering C, Bork P. 2016. eggNOG 4.5: a hierarchical orthology framework with improved functional annotations for eukaryotic, prokaryotic and viral sequences. Nucleic Acids Res 44:D286–D293. doi: 10.1093/nar/gkv1248. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Zankari E, Hasman H, Cosentino S, Vestergaard M, Rasmussen S, Lund O, Aarestrup FM, Larsen MV. 2012. Identification of acquired antimicrobial resistance genes. J Antimicrob Chemother 67:2640–2644. doi: 10.1093/jac/dks261. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Alcock BP, Raphenya AR, Lau TTY, Tsang KK, Bouchard M, Edalatmand A, Huynh W, Nguyen AV, Cheng AA, Liu S, Min SY, Miroshnichenko A, Tran HK, Werfalli RE, Nasir JA, Oloni M, Speicher DJ, Florescu A, Singh B, Faltyn M, Hernandez-Koutoucheva A, Sharma AN, Bordeleau E, Pawlowski AC, Zubyk HL, Dooley D, Griffiths E, Maguire F, Winsor GL, Beiko RG, Brinkman FSL, Hsiao WWL, Domselaar GV, McArthur AG. 2020. CARD 2020: antibiotic resistome surveillance with the Comprehensive Antibiotic Resistance Database. Nucleic Acids Res 48:D517–D525. doi: 10.1093/nar/gkz935. [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 accession numbers for the 16S rRNA partial sequence and the genome sequence and raw sequencing reads for DM075 are as follows: GenBank, OP579185.1 and CP100352; BioProject, PRJNA853106; BioSample, SAMN29360653; SRA, SRX15901026 and SRX15901027.