Destruction-free procedure for the isolation of bacteria from sputum samples for Raman spectroscopic analysis
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Lower respiratory tract infections are the fourth leading cause of death worldwide. Here, a timely identification of the causing pathogens is crucial to the success of the treatment. Raman spectroscopy allows for quick identification of bacterial cells without the need for time-consuming cultivation steps, which is the current gold standard to detect pathogens. However, before Raman spectroscopy can be used to identify pathogens, they have to be isolated from the sample matrix, i.e., sputum in case of lower respiratory tract infections. In this study, we report an isolation protocol for single bacterial cells from sputum samples for Raman spectroscopic identification. Prior to the isolation, a liquefaction step using the proteolytic enzyme mixture Pronase E is required in order to deal with the high viscosity of sputum. The extraction of the bacteria was subsequently performed via different filtration and centrifugation steps, whereby isolation ratios between 46 and 57 % were achieved for sputa spiked with 6·107 to 6·104 CFU/mL of Staphylococcus aureus. The compatibility of such a liquefaction and isolation procedure towards a Raman spectroscopic classification was shown for five different model species, namely S. aureus, Staphylococcus epidermidis, Streptococcus pneumoniae, Klebsiella pneumoniae, and Pseudomonas aeruginosa. A classification of single-cell Raman spectra of these five species with an accuracy of 98.5 % could be achieved on the basis of a principal component analysis (PCA) followed by a linear discriminant analysis (LDA). These classification results could be validated with an independent test dataset, where 97.4 % of all spectra were identified correctly.
KeywordsRaman spectroscopy Single-cell pathogen identification Sputum Isolation
Funding of the research projects FastDiagnosis (13N11350) and “JBCI 2.0” (03IPT513Y—Unternehmen Region, InnoProfile Transfer) from the Federal Ministry of Education and Research, Germany (BMBF) and FastTB (2013FE9057) from Free State of Thuringia and the European Union (EFRE) are gratefully acknowledged. We thank Prof. Dr. Wolfgang Pfister from the Institute of Medical Microbiology (University Hospital Jena) for providing the used bacterial strains. The authors thank Bernd Kampe for the help with the program GnuR and Prof. Dr. Michael Schmitt, Dr. Susann Meisel, and Dr. Stephan Stöckel for the critical reading of the present manuscript.
- 1.Engel C, Brunkhorst F, Bone H-G, Brunkhorst R, Gerlach H, Grond S, Gruendling M, Huhle G, Jaschinski U, John S, Mayer K, Oppert M, Olthoff D, Quintel M, Ragaller M, Rossaint R, Stuber F, Weiler N, Welte T, Bogatsch H, Hartog C, Loeffler M, Reinhart K (2007) Epidemiology of sepsis in Germany: results from a national prospective multicenter study. Intensive Care Med 33(4):606–618CrossRefGoogle Scholar
- 2.(WHO) WHO (2014) Global Health Estimates 2014. World Health Organization (WHO);. http://www.who.int/healthinfo/global_burden_disease/en/. Accessed 23.01.2015
- 6.Bogaerts P, Hamels S, de Mendonca R, Huang T-D, Roisin S, Remacle J, Markine-Goriaynoff N, de Longueville F, Plüster W, Denis O, Glupczynski Y (2013) Analytical validation of a novel high multiplexing real-time PCR array for the identification of key pathogens causative of bacterial ventilator-associated pneumonia and their associated resistance genes. J Antimicrob Chemother 68(2):340–347CrossRefGoogle Scholar
- 9.Aydemir O, Aydemir Y, Ozdemir M (2014) The role of multiplex PCR test in identification of bacterial pathogens in lower respiratory tract infections. Pak J Med Sci 30(5):1011–1016Google Scholar
- 11.Stöckel S, Meisel S, Elschner M, Melzer F, Rösch P, Popp J (2015) Raman spectroscopic detection and identification of Burkholderia mallei and Burkholderia pseudomallei in feedstuff. Anal Bioanal Chem 407(4):787–794Google Scholar
- 21.Bosch A, Miñán A, Vescina C, Degrossi J, Gatti B, Montanaro P, Messina M, Franco M, Vay C, Schmitt J, Naumann D, Yantorno O (2008) Fourier transform infrared spectroscopy for rapid identification of nonfermenting gram-negative bacteria isolated from sputum samples from cystic fibrosis patients. J Clin Microbiol 46(8):2535–2546CrossRefGoogle Scholar
- 23.R Development Core Team (2011) R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, AustriaGoogle Scholar
- 27.Dörfer T, Bocklitz T, Tarcea N, Schmitt M, Popp J (2011) Checking and improving calibration of Raman spectra using chemometric approaches. Z Phys Chem 225(6-7):753–764Google Scholar