Novel Organism Verification and Analysis (NOVA) study: identification of 35 clinical isolates representing potentially novel bacterial taxa using a pipeline based on whole genome sequencing
Abstract Background Reliable species identification of cultured isolates is essential in clinical bacteriology. We established a new study algorithm named NOVA – Novel Organism Verification and Analysis to systematically analyze bacterial isolates that cannot be characterized by conventional identif...
| Main Authors: | , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2024-01-01
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| Series: | BMC Microbiology |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12866-023-03163-7 |
| _version_ | 1797363594802757632 |
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| author | Veronika Muigg Helena M.B. Seth-Smith Kai-Manuel Adam Maja Weisser Vladimira Hinić Annette Blaich Tim Roloff Ulrich Heininger Hanna Schmid Maurus Kohler Lukas Graf Dylan M. Winterflood Pascal Schlaepfer Daniel Goldenberger |
| author_facet | Veronika Muigg Helena M.B. Seth-Smith Kai-Manuel Adam Maja Weisser Vladimira Hinić Annette Blaich Tim Roloff Ulrich Heininger Hanna Schmid Maurus Kohler Lukas Graf Dylan M. Winterflood Pascal Schlaepfer Daniel Goldenberger |
| author_sort | Veronika Muigg |
| collection | DOAJ |
| description | Abstract Background Reliable species identification of cultured isolates is essential in clinical bacteriology. We established a new study algorithm named NOVA – Novel Organism Verification and Analysis to systematically analyze bacterial isolates that cannot be characterized by conventional identification procedures MALDI-TOF MS and partial 16 S rRNA gene sequencing using Whole Genome Sequencing (WGS). Results We identified a total of 35 bacterial strains that represent potentially novel species. Corynebacterium sp. (n = 6) and Schaalia sp. (n = 5) were the predominant genera. Two strains each were identified within the genera Anaerococcus, Clostridium, Desulfovibrio, and Peptoniphilus, and one new species was detected within Citrobacter, Dermabacter, Helcococcus, Lancefieldella, Neisseria, Ochrobactrum (Brucella), Paenibacillus, Pantoea, Porphyromonas, Pseudoclavibacter, Pseudomonas, Psychrobacter, Pusillimonas, Rothia, Sneathia, and Tessaracoccus. Twenty-seven of 35 strains were isolated from deep tissue specimens or blood cultures. Seven out of 35 isolated strains identified were clinically relevant. In addition, 26 bacterial strains that could only be identified at the species level using WGS analysis, were mainly organisms that have been identified/classified very recently. Conclusion Our new algorithm proved to be a powerful tool for detection and identification of novel bacterial organisms. Publicly available clinical and genomic data may help to better understand their clinical and ecological role. Our identification of 35 novel strains, 7 of which appear to be clinically relevant, shows the wide range of undescribed pathogens yet to define. |
| first_indexed | 2024-03-08T16:23:24Z |
| format | Article |
| id | doaj.art-77d0a7d164a443d880e7b9327be60668 |
| institution | Directory Open Access Journal |
| issn | 1471-2180 |
| language | English |
| last_indexed | 2024-03-08T16:23:24Z |
| publishDate | 2024-01-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Microbiology |
| spelling | doaj.art-77d0a7d164a443d880e7b9327be606682024-01-07T12:14:10ZengBMCBMC Microbiology1471-21802024-01-0124111110.1186/s12866-023-03163-7Novel Organism Verification and Analysis (NOVA) study: identification of 35 clinical isolates representing potentially novel bacterial taxa using a pipeline based on whole genome sequencingVeronika Muigg0Helena M.B. Seth-Smith1Kai-Manuel Adam2Maja Weisser3Vladimira Hinić4Annette Blaich5Tim Roloff6Ulrich Heininger7Hanna Schmid8Maurus Kohler9Lukas Graf10Dylan M. Winterflood11Pascal Schlaepfer12Daniel Goldenberger13Clinical Bacteriology and Mycology, University Hospital Basel and University of BaselClinical Bacteriology and Mycology, University Hospital Basel and University of BaselDivision of Infectious Diseases and Hospital Epidemiology, University Hospital BaselDivision of Infectious Diseases and Hospital Epidemiology, University Hospital BaselClinical Bacteriology and Mycology, University Hospital Basel and University of BaselClinical Bacteriology and Mycology, University Hospital Basel and University of BaselClinical Bacteriology and Mycology, University Hospital Basel and University of BaselInfectious Diseases and Vaccinology, University of Basel Children’s HospitalInfectious Diseases and Vaccinology, University of Basel Children’s HospitalKantonsspital Baselland (Bruderholz, Liestal, Laufen)Ear, Nose and Throat Department, University Hospital BaselClinical Bacteriology and Mycology, University Hospital Basel and University of BaselLaboratory Medicine, University Hospital Basel and University of BaselClinical Bacteriology and Mycology, University Hospital Basel and University of BaselAbstract Background Reliable species identification of cultured isolates is essential in clinical bacteriology. We established a new study algorithm named NOVA – Novel Organism Verification and Analysis to systematically analyze bacterial isolates that cannot be characterized by conventional identification procedures MALDI-TOF MS and partial 16 S rRNA gene sequencing using Whole Genome Sequencing (WGS). Results We identified a total of 35 bacterial strains that represent potentially novel species. Corynebacterium sp. (n = 6) and Schaalia sp. (n = 5) were the predominant genera. Two strains each were identified within the genera Anaerococcus, Clostridium, Desulfovibrio, and Peptoniphilus, and one new species was detected within Citrobacter, Dermabacter, Helcococcus, Lancefieldella, Neisseria, Ochrobactrum (Brucella), Paenibacillus, Pantoea, Porphyromonas, Pseudoclavibacter, Pseudomonas, Psychrobacter, Pusillimonas, Rothia, Sneathia, and Tessaracoccus. Twenty-seven of 35 strains were isolated from deep tissue specimens or blood cultures. Seven out of 35 isolated strains identified were clinically relevant. In addition, 26 bacterial strains that could only be identified at the species level using WGS analysis, were mainly organisms that have been identified/classified very recently. Conclusion Our new algorithm proved to be a powerful tool for detection and identification of novel bacterial organisms. Publicly available clinical and genomic data may help to better understand their clinical and ecological role. Our identification of 35 novel strains, 7 of which appear to be clinically relevant, shows the wide range of undescribed pathogens yet to define.https://doi.org/10.1186/s12866-023-03163-7Clinical isolatesDifficult to identify strainsWhole genome sequencing (WGS)Novel bacteriaClinical significanceType (strain) genome server (TYGS) |
| spellingShingle | Veronika Muigg Helena M.B. Seth-Smith Kai-Manuel Adam Maja Weisser Vladimira Hinić Annette Blaich Tim Roloff Ulrich Heininger Hanna Schmid Maurus Kohler Lukas Graf Dylan M. Winterflood Pascal Schlaepfer Daniel Goldenberger Novel Organism Verification and Analysis (NOVA) study: identification of 35 clinical isolates representing potentially novel bacterial taxa using a pipeline based on whole genome sequencing BMC Microbiology Clinical isolates Difficult to identify strains Whole genome sequencing (WGS) Novel bacteria Clinical significance Type (strain) genome server (TYGS) |
| title | Novel Organism Verification and Analysis (NOVA) study: identification of 35 clinical isolates representing potentially novel bacterial taxa using a pipeline based on whole genome sequencing |
| title_full | Novel Organism Verification and Analysis (NOVA) study: identification of 35 clinical isolates representing potentially novel bacterial taxa using a pipeline based on whole genome sequencing |
| title_fullStr | Novel Organism Verification and Analysis (NOVA) study: identification of 35 clinical isolates representing potentially novel bacterial taxa using a pipeline based on whole genome sequencing |
| title_full_unstemmed | Novel Organism Verification and Analysis (NOVA) study: identification of 35 clinical isolates representing potentially novel bacterial taxa using a pipeline based on whole genome sequencing |
| title_short | Novel Organism Verification and Analysis (NOVA) study: identification of 35 clinical isolates representing potentially novel bacterial taxa using a pipeline based on whole genome sequencing |
| title_sort | novel organism verification and analysis nova study identification of 35 clinical isolates representing potentially novel bacterial taxa using a pipeline based on whole genome sequencing |
| topic | Clinical isolates Difficult to identify strains Whole genome sequencing (WGS) Novel bacteria Clinical significance Type (strain) genome server (TYGS) |
| url | https://doi.org/10.1186/s12866-023-03163-7 |
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