The DOI matches its Crossref record; 66 of the 66 references it cites were found in a registry or an index.
Rapid pathogen detection by metagenomic next-generation sequencing of infected body fluids
Open accessAbstract
We developed a metagenomic next-generation sequencing (mNGS) test using cell-free DNA from body fluids to identify pathogens. The performance of mNGS testing of 182 body fluids from 160 patients with acute illness was evaluated using two sequencing platforms in comparison to microbiological testing using culture, 16S bacterial PCR and/or 28S–internal transcribed ribosomal gene spacer (28S–ITS) fungal PCR. Test sensitivity and specificity of detection were 79 and 91% for bacteria and 91 and 89% for fungi, respectively, by Illumina sequencing; and 75 and 81% for bacteria and 91 and 100% for fungi, respectively, by nanopore sequencing. In a case series of 12 patients with culture/PCR-negative body fluids but for whom an infectious diagnosis was ultimately established, seven (58%) were mNGS positive. Real-time computational analysis enabled pathogen identification by nanopore sequencing in a median 50-min sequencing and 6-h sample-to-answer time. Rapid mNGS testing is a promising tool for diagnosis of unknown infections from body fluids. A universal method enables high-specificity, unbiased pathogen detection from diverse body fluids using metagenomic sequencing and may accelerate clinical decisions.
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Altschul, S. F., Gish, W., Miller, W., Myers, E. W., & Lipman, D. J. (1990) · Journal of Molecular Biology · doi:10.1006/jmbi.1990.9999 · Cited by 98,669
Cook, R. J., Dickens, B. M., & Fathalla, M. F. (2003) · Reproductive Health and Human Rights · doi:10.1093/acprof:oso/9780199241323.003.0025 · Cited by 10,769
Klindworth, A., Pruesse, E., Schweer, T., Peplies, J., Quast, C., Horn, M., & Glöckner, F. O. (2013) · Nucleic Acids Research · doi:10.1093/nar/gks808 · Cited by 8,850
Kumar, A., Roberts, D., Wood, K. E., Light, B., Parrillo, J. E., Sharma, S., Suppes, R., Feinstein, D., Zanotti, S., Taiberg, L., et al. (2006) · Critical Care Medicine · doi:10.1097/01.ccm.0000217961.75225.e9 · Cited by 6,109
Janda, J. M., & Abbott, S. L. (2007) · Journal of Clinical Microbiology · doi:10.1128/jcm.01228-07 · Cited by 2,216
Llor, C., & Bjerrum, L. (2014) · Therapeutic Advances in Drug Safety · doi:10.1177/2042098614554919 · Cited by 2,079
Chiu, C. Y., & Miller, S. A. (2019) · Nature Reviews Genetics · doi:10.1038/s41576-019-0113-7 · Cited by 1,620
Self-citationClinical Metagenomic Next-Generation Sequencing for Pathogen Detection
Gu, W., Miller, S., & Chiu, C. Y. (2019) · Annual Review of Pathology: Mechanisms of Disease · doi:10.1146/annurev-pathmechdis-012418-012751 · Cited by 1,458
Self-citationReal-time, portable genome sequencing for Ebola surveillance
Quick, J., Loman, N. J., Duraffour, S., Simpson, J. T., Severi, E., Cowley, L., Bore, J. A., Koundouno, R., Dudas, G., Mikhail, A., et al. (2016) · Nature · doi:10.1038/nature16996 · Cited by 1,448
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Chai, X., Wang, J., Li, H., Gao, C., Li, S., Wei, C., Huang, J., Tian, Y., Yuan, J., Lu, J., et al. (2023) · Gut Microbes · doi:10.1080/19490976.2022.2156255 · Cited by 152
Molecular diagnostics in cerebrospinal fluid for the diagnosis of central nervous system infections
Olie, S. E., Andersen, C. Ø., van de Beek, D., & Brouwer, M. C. (2024) · Clinical Microbiology Reviews · doi:10.1128/cmr.00021-24 · Cited by 38
“In contrast to most sequencing platforms, with turnaround times of 48–72 hours, nanopore technology performed on the MinIOn sequencer has a total turnaround time of less than 6 hours (315).”
Distinguishing community-acquired bacterial and viral meningitis: Microbes and biomarkers
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Metadata
- Authors
- Gu, W., Deng, X., Lee, M., Sucu, Y. D., Arevalo, S., Stryke, D., Federman, S., Gopez, A., Reyes, K., Zorn, K., Sample, H., Yu, G., Ishpuniani, G., Briggs, B., Chow, E. D., Berger, A., Wilson, M. R., Wang, C., Hsu, E., Miller, S., DeRisi, J. L., & Chiu, C. Y.
- Venue
- Nature Medicine
- Published
- 2020-11-09
- Volume
- 27
- Issue
- 1
- Pages
- 115-124
- ISSN
- 1078-8956 (ISSN-L)
- 1546-170X
- OpenAlex
- W3099584446
- Cited by
- 689
- References
- 66
- FWCI
- 43.66
- Type
- journal article
- Language
- en
- Open access
- green
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- Gu, W., Deng, X., Lee, M., Sucu, Y. D., Arevalo, S., Stryke, D., Federman, S., Gopez, A., Reyes, K., Zorn, K., Sample, H., Yu, G., Ishpuniani, G., Briggs, B., Chow, E. D., Berger, A., Wilson, M. R., Wang, C., Hsu, E., . . . Chiu, C. Y. (2021). Rapid pathogen detection by metagenomic next-generation sequencing of infected body fluids. Nature Medicine. https://doi.org/10.1038/s41591-020-1105-z
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