Discrimination of periodontal pathogens using Raman spectroscopy combined with machine learning algorithms

[in Chinese]; [in Chinese]; [in Chinese]; [in Chinese]; [in Chinese]; [in Chinese]; [in Chinese]; [in Chinese]; [in Chinese]

doi:10.1142/s1793545822400016

[1] J. H. Meurman, A. Bascones-Martinez, "Oral infections and systemic health - More than just links to cardiovascular diseases," Oral Health Prev. Dent. 19(1), 441–448 (2021), https://doi.org/10.3290/j.ohpd.b1993965.

[2] D. F. Kinane, P. G. Stathopoulou, P. N. Papapanou, "Periodontal diseases," Nat. Rev. Dis. Primers. 3, 17038 (2017), https://doi.org/10.1038/nrdp.2017.38.

[3] T. J. Oh, R. Eber, H. L. Wang, "Periodontal diseases in the child and adolescent," J. Clin. Periodontol.29(5), 400–410 (2002), https://doi.org/10.1034/j.1600-051x.2002.290504.x.

[4] X. Li, K. M. Kolltveit, L. Tronstad, I. Olsen, "Systemic diseases caused by oral infection," Clin. Microbiol. Rev. 13(4), 547–558 (2000), https://doi.org/10.1128/CMR.13.4.547.

[5] S. Jepsen, J. Blanco, W. Buchalla et al., "Prevention and control of dental caries and periodontal diseases at individual and population level: Consensus report of group 3 of joint EFP/ORCA workshop on the boundaries between caries and periodontal diseases," J. Clin. Periodontol. 44 (Suppl 18), S85–S93 (2017), https://doi.org/10.1111/jcpe.12687.

[6] J. Meyle, I. Chapple, "Molecular aspects of the pathogenesis of periodontitis," Periodontol 2000. 69(1), 7–17 (2015), https://doi.org/10.1111/prd.12104.

[7] E. Koonoonen, M. Gursoy, U. K. Gursoy, Periodontitis: A multifaceted disease of tooth-supporting tissues, J. Clin. Med. 8(8), 1135 (2019), https://doi.org/10.3390/jcm8081135.

[8] P. I. Eke, L. Wei, G. O. Thornton-Evans et al., "Risk indicators for periodontitis in US adults: NHANES 2009 to 2012," J. Periodontol. 87(10), 1174–1185 (2016), https://doi.org/10.1902/jop.2016.160013.

[9] R. J. Genco, W. S. Borgnakke, "Risk factors for periodontal disease," Periodontol 2000. 62(1), 59–94(2013), https://doi.org/10.1111/j.1600-0757.2012.00457.x.

[10] E. H. Kim, S. Kim, H. J. Kim et al., "Prediction of chronic periodontitis severity using machine learning models based on salivary bacterial copy number," Front. Cell Infect. Microbiol. 10, 571515 (2020), https://doi.org/10.3389/fcimb.2020.571515.

[11] Y. W. Han, X. Wang, "Mobile microbiome: Oral bacteria in extra-oral infections and inflammation," J. Dent. Res. 92(6), 485–491 (2013), https://doi.org/10.1177/0022034513487559.

[12] J. Sakalauskiene, R. Kubilius, A. Gleiznys, A. Vitkauskiene, E. Ivanauskiene, V. Saferis, "Relationship of clinical and microbiological variables in patients with type 1 diabetes mellitus and periodontitis," Med. Sci. Monit. 20, 1871–1877 (2014), https://doi.org/10.12659/MSM.890879.

[13] L. Forner, T. Larsen, M. Kilian, P. Holmstrup, "Incidence of bacteremia after chewing, tooth brushing and scaling in individuals with periodontal inflammation," J. Clin. Periodontol. 33(6), 401–407 (2006), https://doi.org/10.1111/j.1600-051X.2006.00924.x.

[14] L. Paturel, J. P. Casalta, G. Habib, M. Nezri, D. Raoult, "Actinobacillus actinomycetemcomitans endocarditis," Clin. Microbiol. Infect. 10(2), 98–118 (2004), https://doi.org/10.1111/j.1469-0691.2004.00794.x.

[15] J. Choi, S. Y. Lee, K. Kim, B. K. Choi, "Identification of immunoreactive epitopes of the Porphyromonas gingivalis heat shock protein in periodontitis and atherosclerosis," J. Periodontal. Res. 46(2), 240–245 (2011), https://doi.org/10.1111/j.1600-0765.2010.01339.x.

[16] B. Lorenz, C. Wichmann, S. Stoockel, P. Roosch, J. Popp, "Cultivation-free Raman spectroscopic investigations of bacteria," Trends Microbiol. 25(5), 413–424 (2017), https://doi.org/10.1016/j.tim.2017.01.002.

[17] K. Kong, C. Kendall, N. Stone, I. Notingher, "Raman spectroscopy for medical diagnostics -From in-vitro biofluid assays to in-vivo cancer detection," Adv. Drug Deliv. Rev. 89, 121–134(2015), https://doi.org/10.1016/j.addr.2015.03.009.

[18] E. Witkowska, D. Korsak, A. Kowalska, A. Janeczek, A. Kamińska, "Strain-level typing and identification of bacteria - a novel approach for SERS active plasmonic nanostructures," Anal. Bioanal. Chem. 410(20), 5019–5031 (2018), https://doi.org/10.1007/s00216-018-1153-0.

[19] Y. Bao, Y. Li, L. Ling et al., "Label-free and highly sensitive detection of native proteins by Ag IANPs via surface-enhanced Raman spectroscopy," Anal. Chem. 92(21), 14325–14329 (2020), https://doi.org/10.1021/acs.analchem.0c03165.

[20] M. I. Jordan, T. M. Mitchell, "Machine learning: Trends, perspectives, and prospects," Science 349 (6245), 255–260 (2015), https://doi.org/10.1126/science.aaa8415.

[21] S. Meisel, S. Stoockel, P. Roosch, J. Popp, "Identification of meat-associated pathogens via Raman microspectroscopy," Food Microbiol. 38, 36–43 (2014), https://doi.org/10.1016/j.fm.2013.08.007.

[22] S. B. Rodriguez, M. A. Thornton, R. J. Thornton, "Discrimination of wine lactic acid bacteria by Raman spectroscopy," J. Ind. Microbiol. Biotechnol. 44(8), 1167–1175 (2017), https://doi.org/10.1007/s10295-017-1943-y.

[23] T. Yamamoto, J. N. Taylor, S. Koseki, K. Koyama, "Classification of food spoilage bacterial species and their sodium chloride, sodium acetate and glycine tolerance using chemometrics analysis and Raman spectroscopy," J. Microbiol. Meth. 190, 106326 (2021), https://doi.org/10.1016/j.mimet.2021.106326.

[24] S. Kloss, B. Kampe, S. Sachse et al., "Culture independent Raman spectroscopic identification of urinary tract infection pathogens: A proof of principle study," Anal. Chem. 85(20), 9610–9616 (2013), https://doi.org/10.1021/ac401806f.

[25] B. Lorenz, P. Roosch, J. Popp, "Isolation mattersprocessing blood for Raman microspectroscopic identification of bacteria," Anal. Bioanal. Chem. 411(21), 5445–5454 (2019), https://doi.org/10.1007/s00216-019-01918-8.

[26] C. G. Ryan, E. Clayton, W. L. Gri±n, S. H. Sie, D. R. Cousens, "SNIP, a statistics-sensitive background treatment for the quantitative-analysis of PIXE spectra in geoscience applications," Nucl. Instrum. Meth. B 34(3), 396–402 (1988), https://doi.org/10.1016/0168-583X(88)90063-8.

[27] M. Wacker, H. Witte, "Adaptive phase extraction: Incorporating the Gabor transform in the matching pursuit algorithm," IEEE Trans. Biomed. Eng. 58(10), 2844–2851 (2011), https://doi.org/10.1109/TBME.2011.2160636.

[28] N. Ortigosa, ó. Cano, G. Ayala, A. Galbis, C. Fernandez, "Atrial fibrillation subtypes classification using the general Fourier-family transform," Med. Eng. Phys. 36(4), 554–560 (2014), https://doi.org/10.1016/j.medengphy.2013.12.005.

[29] M. Feurer, A. Klein, K. Eggensperger, J. T. Springenberg, M. Blum, F. Hutter, "Auto-sklearn: E±cient and robust automated machine learning," Autom. Mach. Learn. Methods, Systems, Challenges (Springer International Publishing, Cham, 2019), pp. 113–134, https://doi.org/10.1007/978-3-030-05318-5 6.

[30] C. E. Metz, "Basic principles of ROC analysis," Semin. Nucl. Med. 8(4), 283–298 (1978), https://doi.org/10.1016/s0001-2998(78)80014-2.

[31] W. E. Huang, M. Li, R. M. Jarvis, R. Goodacre, S. A. Banwart, "Shining light on the microbial world the application of Raman microspectroscopy," Adv. Appl. Microbiol. 70, 153–186 (2010), https://doi.org/10.1016/S0065-2164(10)70005-8.

[32] K. M. Davis, R. R. Isberg, "Defining heterogeneity within bacterial populations via single cell approaches," Bioessays 38(8), 782–790 (2016), https://doi.org/10.1002/bies.201500121.

[33] Z. Movasaghi, S. Rehman, I. U. Rehman, "Raman spectroscopy of biological tissues," Appl. Spectrosc. Rev. 42(5), 493–541 (2007), https://doi.org/10.1080/05704920701551530.

[34] G. Socrates, Infrared and Raman Characteristic Group Frequencies: Tables and Charts (Wiley, Chichester, 2004).

[35] M. Harz, P. Roosch, K. D. Peschke, O. Ronneberger, H. Burkhardt, J. Popp, "Micro-Raman spectroscopic identification of bacterial cells of the genus Staphylococcus and dependence on their cultivation conditions," Analyst 130(11), 1543–1550 (2005), https://doi.org/10.1039/b507715j.

[36] J. C. Baritaux, A. C. Simon, E. Schultz, C. Emain, P. Laurent, J. M. Dinten, "A study on identification of bacteria in environmental samples using single-cell Raman spectroscopy: Feasibility and reference libraries," Environ. Sci. Poll. Res. 23(9), 8184–8191 (2016), https://doi.org/10.1007/s11356-015-5953-x.

[37] E. Harikrishna, K. A. Reddy, Real Perspective of Fourier Transforms and Current Developments in Superconductivity (IntechOpen, London, 2021).

[38] C. Garcia-Timermans, P. Rubbens, F. M. Kerckhof et al., "Label-free Raman characterization of bacteria calls for standardized procedures," J. Microbiol. Meth. 151, 69–75 (2018), https://doi.org/10.1016/j.mimet.2018.05.027.

[39] C. Wichmann, M. Chhallani, T. Bocklitz, P. Roosch, J. Popp, "Simulation of transportation and storage and their influence on Raman spectra of bacteria," Anal. Chem. 91(21), 13688–13694 (2019), https://doi.org/10.1021/acs.analchem.9b02932.

[40] P. Aemaimanan, P. Amimanan, S. Taweechaisupapong, "Quantification of key periodontal pathogens in insulin-dependent type 2 diabetic and nondiabetic patients with generalized chronic periodontitis," Anaerobe 22, 64–68 (2013), https://doi.org/10.1016/j.anaerobe.2013.06.010.

[41] V. I. Haraszthy, J. J. Zambon, M. Trevisan, M. Zeid, R. J. Genco, "Identification of periodontal pathogens in atheromatous plaques," J. Periodontol. 71(10), 1554–1560 (2000), https://doi.org/10.1902/jop.2000.71.10.1554.

[42] S. Yan, S. Wang, J. Qiu et al., "Raman spectroscopy combined with machine learning for rapid detection of food-borne pathogens at the single-cell level," Talanta 226, 122195 (2021), https://doi.org/10.1016/j.talanta.2021.122195.

[43] W. Lu, X. Chen, L. Wang, H. Li, Y. V. Fu, "Combination of an artificial intelligence approach and laser tweezers Raman spectroscopy for microbial identification," Anal. Chem. 92(9), 6288–6296 (2020), https://doi.org/10.1021/acs.analchem.9b04946.