| 摘要(英) |
Klebsiella pneumoniae (K. pneumoniae) is a kind of gram-negative bacteria. Patients infected with this pathogen might suffer pneumonia, urinary tract infections, and intra-abdominal infections with serious symptoms, such as toxic presentation with sudden onset, high fever, and hemoptysis. Recently, matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) is an emerging technology for microbial identification. However, there have been less studies using large mass spectra dataset of K. pneumoniae to analyze multiple antibiotic resistance. Thus, we collected lots of mass spectra of K. pneumoniae and considered three antibiotics Ciprofloxacin (CIP), Cefuroxime (CXM), Ceftriaxone (CRO), and multiple antibiotic resistance or susceptibility to the three antibiotics above. After feature selection in prediction models for strains resistant or susceptible to three antibiotics above, the accuracy of independent testing can achieve 0.7858 with sensitivity 0.7289 and specificity 0.8127 using 46 features in combined dataset. The informative peaks 3657, 4341, 4519, 4709, 5070, 5409, 5921, 5939 and 6516 m/z might be the potential features for multiple antibiotic resistant K. pneumoniae and all of these peaks account for higher ratio in the resistant K. pneumoniae than in susceptible K. pneumoniae. We hope that the models for antibiotic resistance can assist doctors to evaluate the use of antibiotic in clinical. The association between resistant mechanism and informative mass spectra also needs to be further studied in the future experiment. |
| 參考文獻 |
1. Ko, W.C., et al., Community-acquired Klebsiella pneumoniae bacteremia: global differences in clinical patterns. Emerging Infectious Diseases, 2002. 8(2): p. 160-6.
2. Kim, J., et al., Assessment of antibiotic resistance in Klebsiella pneumoniae exposed to sequential in vitro antibiotic treatments. Annals of Clinical Microbiology and Antimicrobials, 2016. 15(1): p. 60.
3. Gasink, L.B., et al., Risk factors and clinical impact of Klebsiella pneumoniae carbapenemase-producing K. pneumoniae. Infection Control & Hospital Epidemiology, 2009. 30(12): p. 1180-5.
4. Chiu, S.K., et al., Carbapenem nonsusceptible Klebsiella pneumoniae in Taiwan: dissemination and increasing resistance of carbapenemase producers during 2012–2015. Scientific Reports, 2018. 8(1): p. 8468.
5. Kim, S., et al., PubChem 2019 update: improved access to chemical data. Nucleic Acids Research, 2019. 47(D1): p. D1102-9.
6. Rawat, D. and Nair D., Extended-spectrum β-lactamases in Gram negative bacteria. Journal of Global Infectious Diseases, 2010. 2(3): p. 263.
7. Wang, M., et al., Emerging plasmid-mediated quinolone resistance associated with the qnr gene in Klebsiella pneumoniae clinical isolates in the United States. Antimicrobial Agents and Chemotherapy, 2004.48(4): p.1295-9.
8. Paterson, D.L. and Bonomo R.A., Extended-spectrum beta-lactamases: a clinical update. Clinical Microbiology Reviews, 2005. 18(4): p. 657-86.
9. Khan, Z.A., Siddiqui M.F., and Park S., Current and emerging methods of antibiotic susceptibility testing. Diagnostics, 2019. 9(2): p. 49.
10. Singhal, N., et al., MALDI-TOF mass spectrometry: an emerging technology for microbial identification and diagnosis. Frontiers in Microbiology, 2015. 6: p. 791.
11. Zimmermann, S. and Burckhardt, I., Development and application of MALDI-TOF for detection of resistance mechanisms, MALDI‐TOF and Tandem MS for Clinical Microbiology. 2017. p. 231-48.
12. Angeletti, S., et al., MALDI-TOF mass spectrometry and blakpc gene phylogenetic analysis of an outbreak of carbapenem-resistant K. pneumoniae strains. New Microbiologica, 2015. 38(4): p. 541-50.
13. Flores-Trevino, S., et al., Screening of biomarkers of drug resistance or virulence in ESCAPE pathogens by MALDI-TOF mass spectrometry. Scientific Reports, 2019. 9(1): p. 18945.
14. Rocco, V.G., et al., Rapid identification of carbapenemase-producing Klebsiella pneumoniae strains by matrix-assisted laser desorption/ionization-time of flight using VitekⓇ mass spectrometry system. The Eurasian Journal of Medicine, 2019. 51(3): p. 209-13.
15. Huang, T.S., et al., Detection of carbapenem-resistant Klebsiella pneumoniae on the basis of matrix-assisted laser desorption ionization time-of-flight mass spectrometry by using supervised machine learning approach. PLoS One, 2020. 15(2): p. e0228459.
16. Lau, A.F., et al., A rapid matrix-assisted laser desorption ionization-time of flight mass spectrometry-based method for single-plasmid tracking in an outbreak of carbapenem-resistant Enterobacteriaceae. Journal of Clinical Microbiology, 2014. 52(8): p. 2804-12.
17. Bar-Meir, M., et al., The utility of MALDI-TOF MS for outbreak investigation in the neonatal intensive care unit. European Journal of Pediatrics, 2020.
18. Chambers, M.C., et al., A cross-platform toolkit for mass spectrometry and proteomics. Nature Biotechnology, 2012. 30(10): p. 918-20.
19. Gibb, S. and Strimmer K., MALDIquant: a versatile R package for the analysis of mass spectrometry data. Bioinformatics, 2012. 28(17): p. 2270-1.
20. Botev, Z.I., Grotowski, J.F., and Kroese, D.P., Kernel density estimation via diffusion. The Annals of Statistics, 2010. 38(5): p. 2916-57.
21. Pedregosa, F., et al., Scikit-learn: machine learning in python. Journal of Machine Learning Research, 2011. 12: p. 2825-30.
22. Zhang, H., The optimality of naive Bayes. American Association for Artificial Intelligence, 2004. 1(2): p. 3.
23. Chen, T. and Guestrin, C., XGBoost: a scalable tree boosting system. Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016. p. 785-94.
24. Youden, W.J., Index for rating diagnostic tests. Cancer, 1950. 3(1): p. 32-5. |
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