Discrimination of urinary tract infection pathogens by means of their growth profiles using surface enhanced Raman scattering
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Urinary tract infection (UTI) is a widespread infection and affects millions of people around the globe. The gold standard for identification of microorganisms causing infection is urine culture. However, current methods require at least 24 h for the results. In clinical settings, identification and discrimination of bacteria with less time-consuming and cheaper methods are highly desired. In recent years, the power of surface-enhanced Raman scattering (SERS) for fast identification of bacteria and biomolecules has been demonstrated. In this study, we show discrimination of urinary tract infection causative pathogens within 1 h of incubation using principal component analysis (PCA) of SERS spectra of seven different UTI causative bacterial species. In addition, we showed differentiation of them at their different growth phases. We also analyzed origins of bacterial SERS spectra and demonstrated the highly dynamic structure of the bacteria cell wall during their growth.
KeywordsUrinary tract infection Bacteria Growth phase Surface-enhanced Raman scattering Principal component analysis
The authors gratefully acknowledge the financial support of Yeditepe University and Technological Research Council of Turkey (TUBITAK) for this study. The authors also acknowledge the contribution Associate Prof. Çağatay Acuner and Prof. Dr. Gülden Yılmaz of Yeditepe University Medical School for providing some of the bacteria species.
Conflict of interest
The authors declare that there is no conflict of interest.
- 4.Schmiemann G, Kniehl E, Gebhardt K, Matejczyk MM, Hummers-Pradier E (2010) The diagnosis of urinary tract infection. Dtsch Arztebl Int 107:361–367Google Scholar
- 7.Liao JC, Mastali M, Gau V, Suchard MA, Møller AK, Bruckner DA, Babbitt JT, Li Y, Gornbein J, Landaw EM, McCabe ER, Churchill BM, Haake DA (2006) Use of electrochemical DNA biosensors for rapid molecular identification of uropathogens in clinical urine specimens. J Clin Microbiol 44:561–570CrossRefGoogle Scholar
- 8.Ferreira L, Sánchez-Juanes F, Muñoz-Bellido JL, González-Buitrago JM (2011) Rapid method for direct identification of bacteria in urine and blood culture samples by matrix-assisted laser desorption ionization time-of-flight mass spectrometry: intact cell vs. extraction method. Clin Microbiol Infect 17:1007–1012CrossRefGoogle Scholar
- 13.Bispo JAM, De Sousa Vieira EE, Silveira L, Fernandes AB (2013) Correlating the amount of urea, creatinine, and glucose in urine from patients with diabetes mellitus and hypertension with the risk of developing renal lesions by means of Raman spectroscopy and principal component analysis. J Biomed Opt 8:087004CrossRefGoogle Scholar
- 25.Premasiri WR, Lemler P, Chen Y, Gebregziabher Y, Ziegler LD (2014) SERS analysis of bacteria, human blood and cancer cells: a metabolomic and diagnostic tool. In: Ozaki Y, Kneipp K, Aroca R (eds) Frontiers of surface-enhanced Raman scattering: single-nanoparticles and single cells, 1st edn. Wiley, Chichester, pp 255–282Google Scholar
- 34.Typas A, Banzhaf M, Gross CA, Vollmer W (2011) From the regulation of peptidoglycan synthesis to bacterial growth and morphology. Nat Rev Microbiol 10:123–136Google Scholar
- 49.Huang R, Yang H-T, Cui L, Wu D-Y, Ren B, Tian Z-Q (2013) Structural and charge sensitivity of surface-enhanced Raman spectroscopy of adenine on silver surface: a quantum chemical study. J Phys Chem B 117:23730–23737Google Scholar