Abstract
Objectives
In this study, the possibilities of Fourier-transformed infrared spectroscopy (FTIR) for analysis of urine sediments and for detection of bacteria causing urinary tract infections (UTIs) were investigated.
Methods
Dried urine specimens of control subjects and patients presenting with various nephrological and urological conditions were analysed using mid-infrared spectroscopy (4,000–400 cm−1). Urine samples from patients with a UTI were inoculated on a blood agar plate. After drying of the pure bacterial colonies, FTIR was applied and compared with the results obtained by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). Chemometric data analysis was used to classify the different species.
Results
Due to the typical molecular assignments of lipids, proteins, nucleic acids and carbohydrates, FTIR was able to identify bacteria and showed promising results in the detection of proteins, lipids, white and red blood cells, as well as in the identification of crystals. Principal component analysis (PCA) allowed to differentiate between Gram-negative and Gram-positive species and soft independent modelling of class analogy (SIMCA) revealed promising classification ratios between the different pathogens.
Conclusions
FTIR can be considered as a supplementary method for urine sediment examination and for detection of pathogenic bacteria in UTI.
Funding source: Universitair Ziekenhuis Gent, Belgium
-
Research funding: None declared.
-
Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
-
Competing interests: Authors state no conflict of interest.
-
Informed consent: Informed consent was obtained from all individuals included in this study.
-
Ethical approval: The approval of this study was granted by the Ethical committee of the Ghent University Hospital (EC2019/1379) on Dec 13, 2019.
References
1. Fogazzi, GB. The urinary sediment: an integrated view. 3rd ed. Milano: Elsevier Masson; 2010:254 p.Search in Google Scholar
2. Kouri, T, Fogazzi, G, Gant, V, Hallander, H, Hofmann, W, Guder, WG. European urinalysis guidelines. Scand J Clin Lab Invest 2000;60:1–96. https://doi.org/10.1080/00365513.2000.12056993.Search in Google Scholar
3. Delanghe, JR, Kouri, TT, Huber, AR, Hannemann-Pohl, K, Guder, WG, Lun, A, et al. The role of automated urine particle flow cytometry in clinical practice. Clin Chim Acta 2000;301:1–18. https://doi.org/10.1016/s0009-8981(00)00342-9.Search in Google Scholar
4. Oyaert, M, Delanghe, J. Progress in automated urinalysis. Ann Lab Med 2019;39:15–22. https://doi.org/10.3343/alm.2019.39.1.15.Search in Google Scholar PubMed PubMed Central
5. De Bruyne, S, Speeckaert, MM, Delanghe, JR. Applications of mid-infrared spectroscopy in the clinical laboratory setting. Crit Rev Clin Lab Sci 2018;55:1–20. https://doi.org/10.1080/10408363.2017.1414142.Search in Google Scholar PubMed
6. De Koninck, A-S, Groen, L-A, Maes, H, Verstraete, AG, Stove, V, Delanghe, JR. An unusual type of kidney stone. Clin Lab 2016;62:235–9. https://doi.org/10.7754/clin.lab.2015.150605.Search in Google Scholar PubMed
7. De Bruyne, S, Speeckaert, R, Boelens, J, Hayette, M-P, Speeckaert, M, Delanghe, J. Infrared spectroscopy as a novel tool to diagnose onychomycosis. Br J Dermatol 2019;180:637–46. https://doi.org/10.1111/bjd.17199.Search in Google Scholar PubMed
8. Takamura, A, Watanabe, K, Akutsu, T, Ozawa, T. Soft and robust identification of body fluid using Fourier transform infrared spectroscopy and chemometric strategies for forensic analysis. Sci Rep 2018;8:8459. https://doi.org/10.1038/s41598-018-26873-9.Search in Google Scholar PubMed PubMed Central
9. Barth, A. Infrared spectroscopy of proteins. Biochim biophys acta 2007;1767:1073–101. https://doi.org/10.1016/j.bbabio.2007.06.004.Search in Google Scholar PubMed
10. Perez-Guaita, D, Richardson, Z, Heraud, P, Wood, B. Quantification and identification of microproteinuria using ultrafiltration and ATR-FTIR spectroscopy. Anal Chem 2020;92:2409–16. https://doi.org/10.1021/acs.analchem.9b03081.Search in Google Scholar PubMed
11. Bourbeau, PP, Swartz, BL. First evaluation of the WASP, a new automated microbiology plating instrument. J Clin Microbiol 2009;47:1101–6. https://doi.org/10.1128/jcm.01963-08.Search in Google Scholar PubMed PubMed Central
12. Singhal, N, Kumar, M, Kanaujia, PK, Virdi, JS. MALDI-TOF mass spectrometry: an emerging technology for microbial identification and diagnosis. Front Microbiol 2015;6:791. https://doi.org/10.3389/fmicb.2015.00791.Search in Google Scholar PubMed PubMed Central
13. Allain, CC, Poon, LS, Chan, CS, Richmond, W, Fu, PC. Enzymatic determination of total serum cholesterol. Clin Chem 1974;20:470–5. https://doi.org/10.1093/clinchem/20.4.470.Search in Google Scholar
14. Custers, D, Cauwenbergh, T, Bothy, JL, Courselle, P, De Beer, JO, Apers, S, et al. ATR-FTIR spectroscopy and chemometrics: an interesting tool to discriminate and characterize counterfeit medicines. J Pharm Biomed Anal 2015;112:181–9. https://doi.org/10.1016/j.jpba.2014.11.007.Search in Google Scholar PubMed
15. Eriksson, L, Byrne, T, Johansson, E, Trygg, J, Vikström, C. Multi-and megavariate data analysis, 3rd revised ed. Malmö, Sweden: MKS Umetrics AB; 2013:490 p.Search in Google Scholar
16. Pretini, V, Koenen, MH, Kaestner, L, Fens, MHAM, Schiffelers, RM, Bartels, M, et al. Red blood cells: chasing interactions. Front Physiol 2019;10:945. https://doi.org/10.3389/fphys.2019.00945.Search in Google Scholar PubMed PubMed Central
17. Li, H, Lykotrafitis, G. Erythrocyte membrane model with explicit description of the lipid bilayer and the spectrin network. Biophys J 2014;107:642–53. https://doi.org/10.1016/j.bpj.2014.06.031.Search in Google Scholar PubMed PubMed Central
18. Hesse, A, Sanders, G. Infrarotspektren-Atlas zur Harnsteinanalyse = Atlas of infrared spectra for the analysis of urinary concrements. Stuttgart: Georg Thieme Verlag; 1988:192 p.Search in Google Scholar
19. Covarelli, C, Primiano, A, Garigali, G, Caselli, E, Gervasoni, J, Baroni, S, et al. Other very rare and poorly known uric acid crystals for the first time also shown by polarized light and definitively identified by infrared spectroscopy. Clin Chim Acta 2018;484:148–9. https://doi.org/10.1016/j.cca.2018.05.052.Search in Google Scholar PubMed
20. Klahr, S, Tripathy, K, Bolanos, O. Qualitative and quantitative analysis of urinary lipids in the nephrotic syndrome. J Clin Invest 1967;46:1475–81. https://doi.org/10.1172/jci105639.Search in Google Scholar PubMed PubMed Central
21. Beveridge, TJ. Use of the gram stain in microbiology. Biotech Histochem 2001;76:111–8. https://doi.org/10.1080/bih.76.3.111.118.Search in Google Scholar
22. Biancolillo, A, Marini, F. Chemometric methods for spectroscopy-based pharmaceutical analysis. Front Chem 2018;6:576. https://doi.org/10.3389/fchem.2018.00576.Search in Google Scholar PubMed PubMed Central
23. Filip, Z, Hermann, S, Demnerova, K. FT-IR spectroscopic characteristics of differently cultivated Escherichia coli. Czech J Food Sci 2009;26:458–63. https://doi.org/10.17221/14/2008-cjfs.Search in Google Scholar
© 2020 Walter de Gruyter GmbH, Berlin/Boston
