The DOI matches its Crossref record.
Usefulness of the MicroSeq 500 16S Ribosomal DNA-Based Bacterial Identification System for Identification of Clinically Significant Bacterial Isolates with Ambiguous Biochemical Profiles
Open accessAbstract
Due to the inadequate automation in the amplification and sequencing procedures, the use of 16S rRNA gene sequence-based methods in clinical microbiology laboratories is largely limited to identification of strains that are difficult to identify by phenotypic methods. In this study, using conventional full-sequence 16S rRNA gene sequencing as the “gold standard,” we evaluated the usefulness of the MicroSeq 500 16S ribosomal DNA (rDNA)-based bacterial identification system, which involves amplification and sequencing of the first 527-bp fragment of the 16S rRNA genes of bacterial strains and analysis of the sequences using the database of the system, for identification of clinically significant bacterial isolates with ambiguous biochemical profiles. Among 37 clinically significant bacterial strains that showed ambiguous biochemical profiles, representing 37 nonduplicating aerobic gram-positive and gram-negative, anaerobic, and Mycobacterium species, the MicroSeq 500 16S rDNA-based bacterial identification system was successful in identifying 30 (81.1%) of them. Five (13.5%) isolates were misidentified at the genus level ( Granulicatella adiacens was misidentified as Abiotrophia defectiva , Helcococcus kunzii was misidentified as Clostridium hastiforme , Olsenella uli was misidentified as Atopobium rimae , Leptotrichia buccalis was misidentified as Fusobacterium mortiferum , and Bergeyella zoohelcum was misidentified as Rimerella anatipestifer ), and two (5.4%) were misidentified at the species level ( Actinomyces odontolyticus was misidentified as Actinomyces meyeri and Arcobacter cryaerophilus was misidentified as Arcobacter butzleri ). When the same 527-bp DNA sequences of these seven isolates were compared to the known 16S rRNA gene sequences in the GenBank, five yielded the correct identity, with good discrimination between the best and second best match sequences, meaning that the reason for misidentification in these five isolates was due to a lack of the 16S rRNA gene sequences of these bacteria in the database of the MicroSeq 500 16S rDNA-based bacterial identification system. In conclusion, the MicroSeq 500 16S rDNA-based bacterial identification system is useful for identification of most clinically important bacterial strains with ambiguous biochemical profiles, but the database of the MicroSeq 500 16S rDNA-based bacterial identification system has to be expanded in order to encompass the rarely encountered bacterial species and achieve better accuracy in bacterial identification.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Vahabnezhad, E., Mochon, A. B., Wozniak, L. J., & Ziring, D. A. (2013) · Journal of Clinical Gastroenterology · doi:10.1097/mcg.0b013e318279abf0 · Cited by 156
Song, Y., Liu, C., Bolaňos, M., Lee, J., McTeague, M., & Finegold, S. M. (2005) · Journal of Clinical Microbiology · doi:10.1128/jcm.43.4.1531-1537.2005 · Cited by 43
Bioinformatic Methodologies in Assessing Gut Microbiota
Fox, J. D., Sims, A., Ross, M., Bettag, J., Wilder, A., Natrop, D., Borsotti, A., Kolli, S., Mehta, S., Verma, H., et al. (2024) · Microbiology Research · doi:10.3390/microbiolres15040170 · Cited by 15
Metadata
- Authors
- Woo, P. C. Y., Ng, K. H. L., Lau, S. K. P., Yip, K.-T., Fung, A. M. Y., Leung, K.-W., Tam, D. M. W., Que, T.-L., & Yuen, K.-Y.
- Venue
- Journal of Clinical Microbiology
- Publisher
- American Society for Microbiology
- Published
- 2003-05
- Volume
- 41
- Issue
- 5
- Pages
- 1996-2001
- ISSN
- 0095-1137 (ISSN-L)
- 1098-660X
- OpenAlex
- W2108283786
- Cited by
- 205
- References
- 0
- FWCI
- 6.32
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Usefulness of the MicroSeq 500 16S Ribosomal DNA-Based Bacterial Identification System for Identification of Clinically Significant Bacterial Isolates with Ambiguous Biochemical Profiles. https://app.cochat.ai/papers/10.1128/jcm.41.5.1996-2001.2003
- The paper
- Woo, P. C. Y., Ng, K. H. L., Lau, S. K. P., Yip, K.-T., Fung, A. M. Y., Leung, K.-W., Tam, D. M. W., Que, T.-L., & Yuen, K.-Y. (2003). Usefulness of the MicroSeq 500 16S Ribosomal DNA-Based Bacterial Identification System for Identification of Clinically Significant Bacterial Isolates with Ambiguous Biochemical Profiles. Journal of Clinical Microbiology. https://doi.org/10.1128/jcm.41.5.1996-2001.2003
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.