Genomic Characterization of an O-Antigen-Deficient, Hydrogen Sulfide-Negative Salmonella enterica Serovar Senftenberg Isolated from Cooked Mussels
Abstract
1. Introduction
2. Materials and Methods
2.1. Sample Collection and Bacterial Isolation
2.2. DNA Isolation and Quantification
2.3. Whole-Genome Sequencing
2.4. Genome Assembly and Annotation
2.5. Bioinformatic Analyses
2.5.1. In Silico Serotyping, Antimicrobial Resistance, and Virulence
2.5.2. Phylogenetic Analysis
2.5.3. Comparative Genomics
3. Results
3.1. Detection and Phenotypic Characterization of Atypical S. enterica Strain
3.2. Genome Sequencing and De Novo Assembly
3.3. In Silico Characterization and Antimicrobial Resistance Profiling
3.4. Genetic Basis for Loss of Somatic Antigen Expression

3.5. Analysis of Hydrogen Sulfide Production Pathways

3.6. Phylogenetic Relationship to Regional and Global S. Senftenberg Strains
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Tina, L.; Sudarnika, E.; Ridwan, Y.; Sudarwanto, M.B.; Pisestyani, H. Microbiological safety of smoked fish: A review of Escherichia coli and Salmonella spp. contamination in traditional markets of Kendari City, Indonesia. Int. J. Vet. Sci. 2025, 14, 771. [Google Scholar]
- European Food Safety Authority (EFSA); European Centre for Disease Prevention and Control (ECDC). The European Union One Health 2023 Zoonoses report. EFSA J. 2024, 22, e9106. [Google Scholar]
- Scallan, E.; Hoekstra, R.M.; Angulo, F.J.; Tauxe, R.V.; Widdowson, M.A.; Roy, S.L.; Jones, J.L.; Griffin, P.M. Foodborne illness acquired in the United States—Major pathogens. Emerg. Infect. Dis. 2011, 17, 7–15. [Google Scholar] [CrossRef]
- Mooijman, K.A.; Pielaatl, A.; Kuijpers, A.F.A. Validation of EN ISO 6579-1-Microbiology of the food chain—Horizontal method for the detection, enumeration and serotyping of Salmonella—Part 1 detection of Salmonella spp. Int. J. Food Microbiol. 2019, 288, 3–12. [Google Scholar] [CrossRef]
- Andrews, W.H.; Wang, H.; Jacobson, A.; Ge, B.; Zhang, G.; Hammack, T. BAM Chapter 5: Salmonella. Available online: https://www.fda.gov/food/laboratory-methods-food/bam-chapter-5-salmonella (accessed on 15 July 2025).
- European Market Observatory for Fisheries and Aquaculture Products. Case Study, Fresh Mussel in the EU. Price Structure in the Supply Chain. Focus on Denmark, Germany and Italy; Publications Office of the European Union: Luxembourg, 2019. [Google Scholar]
- Martinez-Urtaza, J.; Liebana, E. Use of pulsed-field gel electrophoresis to characterize the genetic diversity and clonal persistence of Salmonella Senftenberg in mussel processing facilities. Int. J. Food Microbiol. 2005, 105, 153–163. [Google Scholar] [CrossRef] [PubMed]
- Lozano-Leon, A.; Garcia-Omil, C.; Dalama, J.; Rodriguez-Souto, R.; Martinez-Urtaza, J.; Gonzalez-Escalona, N. Detection of colistin resistance mcr-1 gene in Salmonella enterica serovar Rissen isolated from mussels, Spain, 2012- to 2016. Euro Surveill. 2019, 24, 1900200. [Google Scholar] [CrossRef]
- Mahmood, S.; Rasool, M.H.; Khurshid, M.; Aslam, B. Genetic outlook of colistin resistant Salmonella enterica serovar Typhimurium recovered from poultry-environment interface: A One Health standpoint. Pak. Vet. J. 2025, 45, 246–256. [Google Scholar]
- Nghiem, S.; Mai, N.; Tran, M.; Cribb, D.M.; Bulfone, L.; Andersson, P.; Zahedi, A.; Hoang, T.; Zulfiqar, T.; Ferdinand, A.; et al. The impact of integrated genomic surveillance on non-typhoidal Salmonella infection in Australia: An ecological study. Lancet Reg. Health West. Pac. 2025, 59, 101592. [Google Scholar] [CrossRef]
- Kolmogorov, M.; Yuan, J.; Lin, Y.; Pevzner, P.A. Assembly of long, error-prone reads using repeat graphs. Nat. Biotechnol. 2019, 37, 540–546. [Google Scholar] [CrossRef]
- Bolger, A.M.; Lohse, M.; Usadel, B. Trimmomatic: A flexible trimmer for Illumina sequence data. Bioinformatics 2014, 30, 2114–2120. [Google Scholar] [CrossRef] [PubMed]
- Wick, R.R.; Judd, L.M.; Gorrie, C.L.; Holt, K.E. Unicycler: Resolving bacterial genome assemblies from short and long sequencing reads. PLoS Comput. Biol. 2017, 13, e1005595. [Google Scholar] [CrossRef]
- Seemann, T. Prokka: Rapid prokaryotic genome annotation. Bioinformatics 2014, 30, 2068–2069. [Google Scholar] [CrossRef]
- Zhang, S.; den Bakker, H.C.; Li, S.; Chen, J.; Dinsmore, B.A.; Lane, C.; Lauer, A.C.; Fields, P.I.; Deng, X. SeqSero2: Rapid and improved Salmonella serotype determination using whole-genome sequencing data. Appl. Environ. Microbiol. 2019, 85, e01746-19. [Google Scholar] [CrossRef]
- Bortolaia, V.; Kaas, R.S.; Ruppe, E.; Roberts, M.C.; Schwarz, S.; Cattoir, V.; Philippon, A.; Allesoe, R.L.; Rebelo, A.R.; Florensa, A.F.; et al. ResFinder 4.0 for predictions of phenotypes from genotypes. J. Antimicrob. Chemother. 2020, 75, 3491–3500. [Google Scholar] [CrossRef] [PubMed]
- Roer, L.; Hendriksen, R.S.; Leekitcharoenphon, P.; Lukjancenko, O.; Kaas, R.S.; Hasman, H.; Aarestrup, F.M. Is the evolution of Salmonella enterica subsp. enterica linked to restriction-modification systems? mSystems 2016, 1, e00009-16. [Google Scholar] [CrossRef] [PubMed]
- Kimura, M. A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences. J. Mol. Evol. 1980, 16, 111–120. [Google Scholar] [CrossRef] [PubMed]
- Stecher, G.; Suleski, M.; Tao, Q.; Tamura, K.; Kumar, S. MEGA 12.1: Cross-Platform Release for macOS and Linux Operating Systems. J. Mol. Evol. 2026, 94, 14–18. [Google Scholar] [CrossRef]
- Fitzgerald, C.; Sherwood, R.; Gheesling, L.L.; Brenner, F.W.; Fields, P.I. Molecular analysis of the rfb O antigen gene cluster of Salmonella enterica serogroup O:6,14 and development of a serogroup-specific PCR assay. Appl. Environ. Microbiol. 2003, 69, 6099–6105. [Google Scholar] [CrossRef]
- Petrin, S.; Tiengo, A.; Longo, A.; Furlan, M.; Marafin, E.; Zavagnin, P.; Orsini, M.; Losasso, C.; Barco, L. Uncommon Salmonella Infantis variants with incomplete antigenic formula in the poultry food chain, Italy. Emerg. Infect. Dis. 2024, 30, 795–799. [Google Scholar] [CrossRef]
- Alessiani, A.; La Bella, G.; Donatiello, A.; Occhiochiuso, G.; Faleo, S.; Didonna, A.; D’Attoli, L.; Selicato, P.; Pedarra, C.; La Salandra, G.; et al. Occurrence of a new variant of Infantis lacking somatic antigen. Microorganisms 2023, 11, 2274. [Google Scholar] [CrossRef]
- Rump, L.V.; Feng, P.C.; Fischer, M.; Monday, S.R. Genetic analysis for the lack of expression of the O157 antigen in an O Rough:H7 Escherichia coli strain. Appl. Environ. Microbiol. 2010, 76, 945–947. [Google Scholar] [CrossRef]
- Rump, L.V.; Beutin, L.; Fischer, M.; Feng, P.C. Characterization of a gne::IS629 O rough:H7 Escherichia coli strain from a hemorrhagic colitis patient. Appl. Environ. Microbiol. 2010, 76, 5290–5291. [Google Scholar] [CrossRef]
- Drauch, V.; Palmieri, N.; Spergser, J.; Hummel, K.; Brandstetter, M.; Kornschober, C.; Hess, M.; Hess, C. Comprehensive phenotyping combined with multi-omics of Salmonella Infantis and its H(2)S negative variant—Resolving adaption mechanisms to environmental changes. Food Microbiol. 2025, 129, 104744. [Google Scholar] [CrossRef]
- Bentum, K.E.; Kuufire, E.; Nyarku, R.; Woods, C.; Ale, K.; McKie, L.; McKenzie, D.; Jackson, C.R.; Adesiyun, A.; Opoku-Agyemang, T.; et al. Detection of a hydrogen sulfide-negative Salmonella Typhimurium from cattle feces in a cross-sectional study of cow-calf herds in the Southeastern United States. Front. Vet. Sci. 2025, 12, 1619880. [Google Scholar] [CrossRef]
- Yi, S.; Xie, J.; Liu, N.; Li, P.; Xu, X.; Li, H.; Sun, J.; Wang, J.; Liang, B.; Yang, C.; et al. Emergence and prevalence of non-H2S-producing Salmonella enterica serovar Senftenberg isolates belonging to novel sequence type 1751 in China. J. Clin. Microbiol. 2014, 52, 2557–2565. [Google Scholar] [CrossRef] [PubMed]
- Bentum, K.E.; Jackson, C.R.; Nyarku, R.; Kuufire, E.; Samuel, T.; Abebe, W. Hydrogen sulfide negative and their implication for standard culture-based identification. J. Food Prot. 2025, 88, 100549. [Google Scholar] [CrossRef] [PubMed]
- Patel, A.; Wolfram, A.; Desin, T.S. Advancements in detection methods for Salmonella in food: A comprehensive review. Pathogens 2024, 13, 1075. [Google Scholar] [CrossRef]
- Gonzalez-Escalona, N.; Hammack, T.S.; Russell, M.; Jacobson, A.P.; De Jesus, A.J.; Brown, E.W.; Lampel, K.A. Detection of live Salmonella sp. cells in produce by a TaqMan-based quantitative reverse transcriptase real-time PCR targeting invA mRNA. Appl. Environ. Microbiol. 2009, 75, 3714–3720. [Google Scholar] [CrossRef] [PubMed]
- Timme, R.E.; Strain, E.; Baugher, J.D.; Davis, S.; Gonzalez-Escalona, N.; Sanchez Leon, M.; Allard, M.W.; Brown, E.W.; Tallent, S.; Rand, H. Phylogenomic Pipeline Validation for Foodborne Pathogen Disease Surveillance. J. Clin. Microbiol. 2019, 57, e01816-18. [Google Scholar] [CrossRef]
- Allard, M.W.; Bell, R.; Ferreira, C.M.; Gonzalez-Escalona, N.; Hoffmann, M.; Muruvanda, T.; Ottesen, A.; Ramachandran, P.; Reed, E.; Sharma, S.; et al. Genomics of foodborne pathogens for microbial food safety. Curr. Opin. Biotechnol. 2018, 49, 224–229. [Google Scholar] [CrossRef]
- Xavier, B.B.; Mysara, M.; Bolzan, M.; Ribeiro-Goncalves, B.; Alako, B.T.F.; Harrison, P.; Lammens, C.; Kumar-Singh, S.; Goossens, H.; Carrico, J.A.; et al. BacPipe: A Rapid, User-Friendly Whole-Genome Sequencing Pipeline for Clinical Diagnostic Bacteriology. iScience 2020, 23, 100769. [Google Scholar] [CrossRef]
- Quijada, N.M.; Rodriguez-Lazaro, D.; Eiros, J.M.; Hernandez, M. TORMES: An automated pipeline for whole bacterial genome analysis. Bioinformatics 2019, 35, 4207–4212. [Google Scholar] [CrossRef] [PubMed]
- Sserwadda, I.; Mboowa, G. rMAP: The Rapid Microbial Analysis Pipeline for ESKAPE bacterial group whole-genome sequence data. Microb. Genom. 2021, 7, 000583. [Google Scholar] [CrossRef] [PubMed]
- Liu, B.; Zheng, D.; Jin, Q.; Chen, L.; Yang, J. VFDB 2019: A comparative pathogenomic platform with an interactive web interface. Nucleic Acids Res. 2019, 47, D687–D692. [Google Scholar] [CrossRef]
- Konganti, K.; Kase, J.A.; Gonzalez-Escalona, N. Centriflaken: An automated data analysis pipeline for assembly and in silico analyses of foodborne pathogens from metagenomic samples. PLoS ONE 2025, 20, e0329425. [Google Scholar] [CrossRef] [PubMed]
- Pillai, C.A.; Thirunavukkarasu, N.; Gonzalez-Escalona, N.; Melka, D.; Curry, P.; Binet, R.; Tallent, S.; Brown, E.; Sharma, S. Closed genome sequence of Clostridium botulinum type B1 strain isolated from an infant botulism case in the United States. Microbiol. Resour. Announc. 2024, 13, e0085423. [Google Scholar] [CrossRef]
- Gonzalez-Escalona, N.; Kwon, H.J.; Chen, Y. Nanopore sequencing allows recovery of high-quality completely closed genomes of all Cronobacter species from powdered infant formula overnight enrichments. Microorganisms 2024, 12, 2389. [Google Scholar] [CrossRef]
- Buytaers, F.E.; Verhaegen, B.; Van Nieuwenhuysen, T.; Roosens, N.H.C.; Vanneste, K.; Marchal, K.; De Keersmaecker, S.C.J. Strain-level characterization of foodborne pathogens without culture enrichment for outbreak investigation using shotgun metagenomics facilitated with nanopore adaptive sampling. Front. Microbiol. 2024, 15, 1330814. [Google Scholar] [CrossRef]
- Martinez-Urtaza, J.; Saco, M.; Hernandez-Cordova, G.; Lozano, A.; Garcia-Martin, O.; Espinosa, J. Identification of Salmonella serovars isolated from live molluscan shellfish and their significance in the marine environment. J. Food Prot. 2003, 66, 226–232. [Google Scholar] [CrossRef]
- Martinez-Urtaza, J.; Saco, M.; de Novoa, J.; Perez-Pineiro, P.; Peiteado, J.; Lozano-Leon, A.; Garcia-Martin, O. Influence of environmental factors and human activity on the presence of Salmonella serovars in a marine environment. Appl. Environ. Microbiol. 2004, 70, 2089–2097. [Google Scholar] [CrossRef]
- Martinez-Urtaza, J.; Lozano-Leon, A.; Varela-Pet, J.; Trinanes, J.; Pazos, Y.; Garcia-Martin, O. Environmental determinants of the occurrence and distribution of Vibrio parahaemolyticus in the rias of Galicia, Spain. Appl. Environ. Microbiol. 2008, 74, 265–274. [Google Scholar] [CrossRef] [PubMed]
- Maguire, M.; Ramachandran, P.; Tallent, S.; Mammel, M.K.; Brown, E.W.; Allard, M.W.; Musser, S.M.; Gonzalez-Escalona, N. Precision metagenomics sequencing for food safety: Hybrid assembly of Shiga toxin-producing Escherichia coli in enriched agricultural water. Front. Microbiol. 2023, 14, 1221668. [Google Scholar] [CrossRef]
- Rolon, M.L.; Tan, X.; Chung, T.; Gonzalez-Escalona, N.; Chen, Y.; Macarisin, D.; LaBorde, L.F.; Kovac, J. The composition of environmental microbiota in three tree fruit packing facilities changed over seasons and contained taxa indicative of L. monocytogenes contamination. Microbiome 2023, 11, 128. [Google Scholar] [CrossRef] [PubMed]
- Commichaux, S.; Javkar, K.; Ramachandran, P.; Nagarajan, N.; Bertrand, D.; Chen, Y.; Reed, E.; Gonzalez-Escalona, N.; Strain, E.; Rand, H.; et al. Evaluating the accuracy of Listeria monocytogenes assemblies from quasimetagenomic samples using long and short reads. BMC Genom. 2021, 22, 389. [Google Scholar] [CrossRef] [PubMed]
- Maguire, M.; Kase, J.A.; Roberson, D.; Muruvanda, T.; Brown, E.W.; Allard, M.; Musser, S.M.; Gonzalez-Escalona, N. Precision long-read metagenomics sequencing for food safety by detection and assembly of Shiga toxin-producing Escherichia coli in irrigation water. PLoS ONE 2021, 16, e0245172. [Google Scholar] [CrossRef]
- Grützke, J.; Malorny, B.; Hammerl, J.A.; Busch, A.; Tausch, S.H.; Tomaso, H.; Deneke, C. Fishing in the soup—Pathogen detection in food safety using metabarcoding and metagenomic sequencing. Front. Microbiol. 2019, 10, 1805. [Google Scholar] [CrossRef]


| Contig | Size | a GC% | Genes |
|---|---|---|---|
| 1 | 4,883,048 | 52.0 | 4834 |
| 2 | 71,607 | 53.2 | 82 |
| 3 | 50,564 | 53.7 | 57 |
| 4 | 7539 | 49.0 | 10 |
| 5 | 3506 | 51.3 | 3 |
| 6 | 2295 | 50.5 | 3 |
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© 2026 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.
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Lamas, A.; Lozano-León, A.; Garrido-Maestu, A.; Gonzalez-Escalona, N. Genomic Characterization of an O-Antigen-Deficient, Hydrogen Sulfide-Negative Salmonella enterica Serovar Senftenberg Isolated from Cooked Mussels. Microorganisms 2026, 14, 1284. https://doi.org/10.3390/microorganisms14061284
Lamas A, Lozano-León A, Garrido-Maestu A, Gonzalez-Escalona N. Genomic Characterization of an O-Antigen-Deficient, Hydrogen Sulfide-Negative Salmonella enterica Serovar Senftenberg Isolated from Cooked Mussels. Microorganisms. 2026; 14(6):1284. https://doi.org/10.3390/microorganisms14061284
Chicago/Turabian StyleLamas, Alexandre, Antonio Lozano-León, Alejandro Garrido-Maestu, and Narjol Gonzalez-Escalona. 2026. "Genomic Characterization of an O-Antigen-Deficient, Hydrogen Sulfide-Negative Salmonella enterica Serovar Senftenberg Isolated from Cooked Mussels" Microorganisms 14, no. 6: 1284. https://doi.org/10.3390/microorganisms14061284
APA StyleLamas, A., Lozano-León, A., Garrido-Maestu, A., & Gonzalez-Escalona, N. (2026). Genomic Characterization of an O-Antigen-Deficient, Hydrogen Sulfide-Negative Salmonella enterica Serovar Senftenberg Isolated from Cooked Mussels. Microorganisms, 14(6), 1284. https://doi.org/10.3390/microorganisms14061284

