J. Bai
ABSTRACT
Methicillin-resistant staphylococcus aureus (MRSA) cause nosocomial and communal infections seriously. Rapid and accurate identification of MRSA is vital for prevention of human morbidity. Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS) has been widely used for identification and typing of micro-organisms. To identify MRSA based on the mass spectra of clinical S.aureus, we propose a genetic algorithm with a t-test based population seeding for wrapper feature selection, in which the t-test statistics are used as the prior information for initial population. The results of some compared experiments show that the proposed method improves the average sensitivity from 0.55 to 0.71, and the balanced accuracy is a larger value on contrast group, whose average value is 0.72. As the result, the proposed GA with prior information can identify MRSA effectively.
- Bhanot, G., Alexe, G., Venkataraghavan, B., and Levine, A. J. 2006. A robust meta-classification strategy for cancer detection from MS data. J. Proteomics, 6(2): 592--604.Google Scholar
Cross Ref
- Cotter, R. J. 1992. Time-of-flight mass spectrometry for the structural analysis of biological molecules. Anal. Chem. 64(21): 1027A--1039A.Google ScholarCross Ref
- Shan, W., Li, J., Fang, Y., Wang, X., Gu, D., and Zhang, R. 2015. Rapid identification of methicillin-resistant staphylococcus aureus (MRSA) by the vitek MS saramis system. Curr. Microbiol. 72(1): 1--4.Google Scholar
- Du, Z., Yang, R., Guo, Z., Song, Y., and Wang, J. 2002. Identification of staphylococcus aureus and determination of its methicillin resistance by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. Anal. Chem. 74(21): 5487--91.Google ScholarCross Ref
- Goodacre, R., Rooney, P. J., and Kell, D. B. 1998. Discrimination between methicillin-resistant and methicillin-susceptible Staphylococcus aureus using pyrolysis mass spectrometry and artificial neural networks. J. Antimicro. Chemo. 41(1): 27--34.Google ScholarCross Ref
- Edwards-Jones, V., Claydon, M. A., Evason, D. J., Walker, J., Fox, A. J., and Gordon, D. B. 2000. Rapid discrimination between methicillin-sensitive and methicillin-resistant Staphylococcus aureus by intact cell mass spectrometry. J. Med. Microbiol, 49, (3): 295--300.Google ScholarCross Ref
- Lauritsen, F. R., and Lloyd, D. 1994. Mass spectrometry for the characterization of microorganisms. In by C. Fenselau (American Chemical Society, Washington, DC, 1994), ACS Symp. Ser. 541:91--106.Google ScholarCross Ref
- Majcherczyk, P. A., McKenna, T., Moreillon, P., and Vaudaux, P. 2006. The discriminatory power of MALDI-TOF mass spectrometry to differentiate between isogenic teicoplanin-susceptible and teicoplanin-resistant strains of methicillin-resistant Staphylococcus aureus. FEMS. microbial. let. 255(2): 233--239.Google Scholar
- Wu, B., Abbott, T., Fishman, D., McMurray, W., Mor, G., Stone, K. and Zhao, H. 2003. Comparison of statistical methods for classification of ovarian cancer using mass spectrometry data. J. Bioinform. 19(13): 1636--43.Google ScholarCross Ref
- Zhang, T., Ding, J., Rao, X., Yu, J., Chu, M., Ren, W., ... and Xue, W. 2015. Analysis of methicillin-resistant staphylococcus aureus major clonal lineages by matrix-assisted laser desorption ionization--time of flight mass spectrometry (MALDI--TOF MS). J. Microbiol. Methods. 117: 122--127.Google ScholarCross Ref
- Li, Y., Liu, Y., and Bai, L. 2008. Genetic algorithm based feature selection for mass spectrometry data. IEEE International Conference on Bioinformatics and Bioengineering (Bibe 2008, October 8-10, 2008). Athens, Greece DBLP, 1--6.Google ScholarCross Ref
- Jeffries, N. O. 2004. Performance of a genetic algorithm for mass spectrometry proteomics. BMC. Bioinform, 5(1): 1--13.Google ScholarCross Ref
- Yu, J. S., Ongarello, S., Fiedler, R., Chen, X. W., Toffolo, G., Cobelli, C., and Trajanoski, Z. 2005. Ovarian cancer identification based on dimensionality reduction for high-throughput mass spectrometry data. J. Bioinform, 21(10): 2200--2209. Google ScholarDigital Library
- Vapnik, V. N. and Vapnik, V. 1998. Statistical learning theory. New York: Wiley, 1998.Google Scholar
- Mather, C. A., Werth, B. J., Sivagnanam, S., SenGupta, D. J., and Butler-Wu, S. M. 2016. Rapid detection of vancomycin-intermediate Staphylococcus aureus by matrix-assisted laser desorption ionization--time of flight mass spectrometry. J. Clin. Microbiol. 54(4):883--890.Google ScholarCross Ref
- Ge, J. K., Qiu, Y. H., Wu, C. M., and Pu, G. L. 2008. Summary of genetic algorithms research. Application Research of Computers, 10: 2911--2916.Google Scholar
- Zhang, X., Lu, X., Shi, Q., Xu, X. Q., Hon-chiu, E. L., Harris, L. N., ... and Wong, W. H. 2006. Recursive SVM feature selection and sample classification for mass-spectrometry and microarray data. BMC bioinformatics, 7:197.Google Scholar
- Wang, Y. R., Qian, C. H. E. N., Cui, S. H., and Li, F. Q. 2013. Characterization of Staphylococcus aureus Isolated from Clinical Specimens by Matrix Assisted Laser Desorption/Ionization Time-of-flight Mass Spectrometry. Biomed. Environ. Sci, 26(6): 430--436.Google Scholar
- Paul, P. V., Ramalingam, A., Baskaran, R., Dhavachelvan, P., Vivekanandan, K., and Subramanian, R. 2014. A new population seeding technique for permutation-coded Genetic Algorithm: Service transfer approach. J. Comput. Sci. 5(2): 277--297.Google ScholarCross Ref
- Jackson, K. A., Edwards-Jones, V., Sutton, C. W., and Fox, A. J. 2005. Optimisation of intact cell MALDI method for fingerprinting of methicillin-resistant Staphylococcus aureus. J. Microbial. methods, 62(3): 273--284.Google Scholar
Index Terms
- Classification of Methicillin-Resistant and Methicillin-Susceptible Staphylococcus Aureus Using an Improved Genetic Algorithm for Feature Selection Based on Mass Spectra
Recommendations
Improved Random Forest Algorithm to Classify Methicillin-Resistant and Methicillin-Susceptible Staphylococcus Aureus on Mass Spectra
ICBBT '17: Proceedings of the 9th International Conference on Bioinformatics and Biomedical TechnologyMass spectrometry (MS) method has been one of the most popular subjects in the field of microbial identification by the reason of its rapid identification and variety application. However, the biomarker of Methicillin-resistant and methicillin-...
Analysis of methicillin-resistant staphylococcus aureus using Apriori, DBSCAN, and K-means algorithms
ICBBE '16: Proceedings of the 3rd International Conference on Biomedical and Bioinformatics EngineeringKnown as the most virulent "super-bacteria," methicillin-resistant staphylococcus aureus (MRSA) is a bacterium that has developed a multi-resistance to standard types of antibiotics, including the penicillins and cephalosporins. Such difficulty to treat ...
Ugi efficient synthesis of novel N–alkylated lipopeptides, antimicrobial properties and computational studies in Staphylococcus aureus via MurD antibacterial target
AbstractLipopeptides are medicinally essential building blocks with strong hemolytic, antifungal and antibiotic potential. In the present research article, we are presenting our findings regarding the synthesis of N–alkylated lipopeptides via ...
Graphical AbstractDisplay Omitted
Highlights- Novel lipopeptides were synthesized in high yields through the Ugi-4CR reaction.
Comments