Campylobacter spp. are commensal organisms in avian species and are one of the leading causes of bacterial foodborne human diarrheal disease worldwide. We report the draft genome sequences of Campylobacter volucris, C. lari, and C. jejuni strains isolated from California gull (Larus californicus) excreta collected from a California beach.
ABSTRACT
Campylobacter spp. are commensal organisms in avian species and are one of the leading causes of bacterial foodborne human diarrheal disease worldwide. We report the draft genome sequences of Campylobacter volucris, C. lari, and C. jejuni strains isolated from California gull (Larus californicus) excreta collected from a California beach.
ANNOUNCEMENT
Campylobacter species are Gram-negative spiral rods, non-spore-forming chemoorganotrophs, and members of the Epsilonproteobacteria class, which grow under microaerobic conditions (1). Several Campylobacter species are recognized as a leading cause of bacterial foodborne infection diseases worldwide and are common inhabitants of the intestine of many wild and domestic avian species (2–4). A previous study documented the presence of a diverse and abundant population of campylobacters in the excreta of California gulls (Larus californicus) from California beaches (5). Although the risk from water impacted by California gulls is low for the community, advances in genomic analysis of potentially human infectious Campylobacter spp. in gull excreta may provide additional information for estimating the risks posed by nonsewage fecal sources (6).
Four strains (CaG_5A, CaG_58BB, CaG_63A, and CaG_70BB) were isolated from gull excreta collected in the summer of 2012 from Hobie Beach (Oxnard, CA, USA) following Waldenström et al. (7). The four colonies were transferred to individual Bolton enrichment agar plates (without antibiotics) and incubated at 42°C under microaerophilic conditions (10% CO2, 5% O2, and 85% N2) for 24 h. All colonies were isolated separately, and their genomic DNA was extracted from a single colony using the MasterPure DNA extraction kit (Epicentre, Madison, WI) and purified with the DNA Clean & Concentrator kit (Zymo Research, Irvine, CA) following the manufacturer’s instructions. Genomic libraries were prepared using the TruSeq library kit followed by rapid mode sequencing (2 × 100 bp) on the HiSeq 2000 platform (Illumina, Inc., San Diego, CA).
A total of 39,770,374 reads were generated. Prior to assembly, the libraries were cleaned of adapters and phiX artifacts, error corrected, normalized (≤100×), and filtered to a minimum length of 80 nucleotides using the software package BBMap v38.22 (with the following settings: ktrim=r k=23 mink=11 hdist=1 tbo tpe maxns=0 trimq=10 qtrim=r maq=12 minlength=100 ecco=t eccc=t ecct=t target=100) (8). A reference-assisted de novo assembly approach was used to assemble the processed reads using Unicycler v0.4.7 (9). Average nucleotide identity (ANI), an index of similarity between two genomes (10), was calculated using FastANI v1.1 (11). The in silico multilocus sequence type (MLST) based on seven alleles (aspA, glnA, gltA, glyA, pgm, tkt, and uncA) was obtained using mlst v2.16.1 (12, 13), genes were assessed for antibiotic resistance with ResFinder v3.1 (14), and chromosomal point mutations were determined with PointFinder v3.1 (15). Default parameters were used for all software unless otherwise specified. The genome quality and statistics were estimated with BBMap and annotated with Prokka v1.13.1 (16) (Table 1).
TABLE 1.
Summary statistics of whole-genome assemblies
Strain | Coverage (×) | No. of contigs | Assembly size (bp) | Contig N50 (bp) | G+C content (%) | Gene annotation data (no.) |
STb | Taxonomic affiliation |
Reference genome | GenBank accession no. | ||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Genes | CDSa | rRNAs | tRNAs | Genus | Species | |||||||||
CaG_5A | 238 | 28 | 1,547,878 | 313,244 | 28.45 | 1,598 | 1,552 | 4 | 41 | NA | Campylobacter | volucris | GCF_000816345 | SMTU00000000 |
CaG_58BB | 231 | 50 | 1,537,596 | 170,866 | 29.50 | 1,553 | 1,513 | 2 | 37 | NA | Campylobacter | lari | GCA_000816385 | SMTT00000000 |
CaG_63A | 197 | 45 | 1,687,991 | 219,579 | 30.46 | 1,773 | 1,729 | 3 | 40 | 2654 | Campylobacter | jejuni | GCA_000737085 | SMTS00000000 |
CaG_70BB | 228 | 19 | 1,569,087 | 436,706 | 28.41 | 1,631 | 1,585 | 4 | 41 | NA | Campylobacter | volucris | GCA_000816345 | SMTR00000000 |
CDS, coding sequences.
ST, sequence type (in silico MLST; aspA, glnA, gltA, glyA, pgm, tkt, uncA); NA, not assigned.
ANI calculations revealed an average genome similarity of 98.38% between strains CaG_5A and CaG_70BB, which were both distantly related to CaG_58BB and CaG_63A with 79.00% and 81.36% similarity, respectively. Taxonomic affiliation analysis based on the ANI between genomes (17) shows that both CaG_5A and CaG_70BB were closely related to Campylobacter volucris LMG 24379 with 98.16% similarity, CaG_58BB to C. lari CCUG 22395 with 93.51% similarity, and CaG_63A to C. jejuni subsp. jejuni MTVDSCj20 with 98.10% similarity. Only strain CaG_63A was assigned to a sequence type (ST2654), which was previously detected in recreational beaches and environmental waters in France (18). Genome analysis using the Web tool PointFinder (15) confirmed the absence of known chromosomal point mutations or genes associated with antimicrobial resistance except for blaOXA-466 in strain CaG_63A, potentially conferring resistance to β-lactams.
Data availability.
This whole-genome shotgun project has been deposited in DDBJ/ENA/GenBank under the accession numbers listed in Table 1. The raw sequence reads have been submitted to the NCBI SRA under the accession numbers SRR8715499, SRR8715500, SRR8715501, and SRR8715502. The versions described in this paper are the first versions.
ACKNOWLEDGMENTS
This research was supported by EPA Office of Research and Development's Safe and Sustainable Water Resources Program 3.02A.
The opinions expressed are those of the authors and do not necessarily reflect the official positions and policies of the U.S. EPA. Any mention of product or trade names does not constitute recommendation for use by the U.S. EPA.
REFERENCES
- 1.On SLW. 2001. Taxonomy of Campylobacter, Arcobacter, Helicobacter and related bacteria: current status, future prospects and immediate concerns. J Appl Microbiol 90:1S–15S. doi: 10.1046/j.1365-2672.2001.01349.x. [DOI] [PubMed] [Google Scholar]
- 2.Frasao BS, Marin VA, Conte‐Junior CA. 2017. Molecular detection, typing, and quantification of Campylobacter spp. in foods of animal origin. Compr Rev Food Sci Food Saf 16:721–734. doi: 10.1111/1541-4337.12274. [DOI] [PubMed] [Google Scholar]
- 3.Kaakoush NO, Castaño-Rodríguez N, Mitchell HM, Man SM. 2015. Global epidemiology of Campylobacter infection. Clin Microbiol Rev 28:687–720. doi: 10.1128/CMR.00006-15. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Silva J, Leite D, Fernandes M, Mena C, Gibbs PA, Teixeira P. 2011. Campylobacter spp. as a foodborne pathogen: a review. Front Microbiol 2:200. doi: 10.3389/fmicb.2011.00200. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Lu J, Ryu H, Santo Domingo JW, Griffith JF, Ashbolt N. 2011. Molecular detection of Campylobacter spp. in California gull (Larus californicus) excreta. Appl Environ Microbiol 77:5034–5039. doi: 10.1128/AEM.00018-11. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Schoen ME, Ashbolt NJ. 2010. Assessing pathogen risk to swimmers at non-sewage impacted recreational beaches. Environ Sci Technol 44:2286–2291. doi: 10.1021/es903523q. [DOI] [PubMed] [Google Scholar]
- 7.Waldenström J, Broman T, Carlsson I, Hasselquist D, Achterberg RP, Wagenaar JA, Olsen B. 2002. Prevalence of Campylobacter jejuni, Campylobacter lari, and Campylobacter coli in different ecological guilds and taxa of migrating birds. Appl Environ Microbiol 68:5911–5917. doi: 10.1128/aem.68.12.5911-5917.2002. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Bushnell B. 2016. BBMap short read aligner, and other bioinformatic [sic] tools. http://sourceforge.net/projects/bbmap/.
- 9.Wick RR, Judd LM, Gorrie CL, Holt KE. 2017. Unicycler: resolving bacterial genome assemblies from short and long sequencing reads. PLoS Comput Biol 13:e1005595. doi: 10.1371/journal.pcbi.1005595. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Goris J, Konstantinidis KT, Klappenbach JA, Coenye T, Vandamme P, Tiedje JM. 2007. DNA-DNA hybridization values and their relationship to whole-genome sequence similarities. Int J Syst Evol Microbiol 57:81–91. doi: 10.1099/ijs.0.64483-0. [DOI] [PubMed] [Google Scholar]
- 11.Jain C, Rodriguez-R LM, Phillippy AM, Konstantinidis KT, Aluru S. 2018. High throughput ANI analysis of 90K prokaryotic genomes reveals clear species boundaries. Nat Commun 9:5114. doi: 10.1038/s41467-018-07641-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Seemann T. 2019. mlst. https://github.com/tseemann/mlst.
- 13.Jolley KA, Maiden MC. 2010. BIGSdb: scalable analysis of bacterial genome variation at the population level. BMC Bioinformatics 11:595. doi: 10.1186/1471-2105-11-595. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.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]
- 15.Zankari E, Allesøe R, Joensen KG, Cavaco LM, Lund O, Aarestrup FM. 2017. PointFinder: a novel Web tool for WGS-based detection of antimicrobial resistance associated with chromosomal point mutations in bacterial pathogens. J Antimicrob Chemother 72:2764–2768. doi: 10.1093/jac/dkx217. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Seemann T. 2014. Prokka: rapid prokaryotic genome annotation. Bioinformatics 30:2068–2069. doi: 10.1093/bioinformatics/btu153. [DOI] [PubMed] [Google Scholar]
- 17.Figueras MJ, Beaz-Hidalgo R, Hossain MJ, Liles MR. 2014. Taxonomic affiliation of new genomes should be verified using average nucleotide identity and multilocus phylogenetic analysis. Genome Announc 2:e00927-14. doi: 10.1128/genomeA.00927-14. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Thépault A, Méric G, Rivoal K, Pascoe B, Mageiros L, Touzain F, Rose V, Béven V, Chemaly M, Sheppard SK. 2017. Genome-wide identification of host-segregating epidemiological markers for source attribution in Campylobacter jejuni. Appl Environ Microbiol 83:e03085-16. doi: 10.1128/AEM.03085-16. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
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Data Availability Statement
This whole-genome shotgun project has been deposited in DDBJ/ENA/GenBank under the accession numbers listed in Table 1. The raw sequence reads have been submitted to the NCBI SRA under the accession numbers SRR8715499, SRR8715500, SRR8715501, and SRR8715502. The versions described in this paper are the first versions.