Rapid Identification of Oral Pathogens Microorganism Based on Single-cell Raman

doi:10.13701/j.cnki.kqyxyj.2021.09.006

Abstract

Abstract: Objective: To evaluate the efficiency of single-cell Raman technique for rapid classification of three kinds of oral pathogens microorganism. Methods: Streptococcus mutans UA159, Candida albicans ATCC10231, and Enterococcus faecalis ATCC29212 were cultured in each medium respectively until the stationary phase. Cells were sampled and treated as below: (1) inoculated culture was monitored by the optical density at 600 nm to measure bacterial growth. (2) inoculated culture was sampled at logarithmic and stationary phase respectively to measure the Raman spectra. Results: Firstly, the logarithmic phase and stationary phase of three strains could be rapidly distinguished by Raman technique. And the classification accuracy rates of random forest were 99.6%, 99.86%, and 99.60%. Secondly, Raman based method could discriminate different oral microbes in stationary phase, and the specificity in classification was 99.68%. Lastly, Raman biomarkers for the classification were 1126-1128 cm^-1 (protein), 736-744 cm^-1 (thymine), 1330-1440 cm^-1 (lipid), 778-785 cm^-1 (cytosine, uracil), 1001-1003 cm^-1 (phenylalanine), and 1431-1481 cm^-1 (Marker protein 1451), respectively. Conclusion: Single-cell Raman could be used to differentiate between growth phases of a single species and strain types of difference species.

Key words: single-cell raman spectroscopy, oral pathogens microorganism, identification, random forest, PCA

LI Shanshan, SUN Yanfei, GUO Yi, YANG Fang. Rapid Identification of Oral Pathogens Microorganism Based on Single-cell Raman[J]. Journal of Oral Science Research, 2021, 37(9): 794-799.

References

[1] 张志民,程博群.口腔微生物与消化系统癌症关系的研究进展[J].口腔医学研究,2020,36(2): 93-97.
[2] 孙同正,杨芳.基于实时荧光定量聚合酶链反应技术预测龋病发生的研究进展[J].口腔医学研究,2019,35(1): 13-15.
[3] Zhang D, Bi H, Liu B, et al. Detection of pathogenic microorganisms by microfluidics based analytical methods [J]. Anal Chem, 2018, 90(9):5512-5520.
[4] Kumar S, Gopinathan R, Chandra GK, et al. Rapid detection of bacterial infection and viability assessment with high specificity and sensitivity using Raman microspectroscopy [J]. Anal Bioanal Chem, 2020, 412(11):2505-2516.
[5] Lorenz B, Wichmann C, Stckel S, et al. Cultivation-Free Raman Spectroscopic Investigations of Bacteria [J]. Trends Microbiol, 2017, 25(5):413-424.
[6] 张俊岭.分子生物学技术在病原微生物检验中的应用[J].临床医药文献电子杂志,2018, 5(13):182.
[7] 朱玉娟,焦康礼,周建业,等.常用分子检测技术在儿童龋病微生物多样性研究中的应用[J].口腔医学研究,2016,32(2): 202-204.
[8] 李玲,杨丽玮.病原微生物检验中分子生物学技术的应用效果分析[J].临床检验杂志,2019,8(3):173.
[9] Ho CS, Jean N, Hogan CA, et al. Rapid identification of pathogenic bacteria using Raman spectroscopy and deep learning [J]. Nat Commun, 2019, 10(1):4927.
[10] Liu Y, Xu J, Tao Y, et al. Rapid and accurate identification of marine microbes with single-cell Raman spectroscopy [J]. Analyst, 2020, 145(9):3297-3305.
[11] Kloss S, Kampe B, Sachse S, et al. Culture independent Raman spectroscopic identification of urinary tract infection pathogens: a proof of principle study [J]. Anal Chem, 2013, 85(20):9610-9616.
[12] Montanari LB, Sartori FG, Ribeiro DBM, et al. Yeast isolation and identification in water used in a Brazilian hemodialysis unit by classic microbiological techniques and Raman spectroscopy [J]. J Water Health, 2018, 16(2):311-320.
[13] Wang Y, Song Y, Tao Y, et al. Reverse and multiple stable isotope probing to study bacterial metabolism and interactions at the single cell level [J]. Anal Chem, 2016, 88(19):9443-9450.
[14] Uzunbajakava N, Lenferink A, Kraan Y, et al. Nonresonant confocal Raman imaging of DNA and protein distribution in apoptotic cells [J]. Biophys J, 2003, 84(6):3968-3981.
[15] Jyothi Lakshmi R, Kartha VB, Murali Krishna C, et al. Tissue Raman spectroscopy for the study of radiation damage: brain irradiation of mice [J]. Radiat Res, 2002, 157(2):175-182.
[16] Váradi L, Luo JL, Hibbs DE, et al. Methods for the detection and identification of pathogenic bacteria: past, present, and future [J]. Chem Soc Rev, 2017, 46(16):4818-4832.
[17] Maurer FP, Christner M, Hentschke M, et al. Advances in rapid identification and susceptibility testing of bacteria in the clinical microbiology laboratory: implications for patient care and antimicrobial stewardship programs [J].Infect Dis Rep, 2017, 9(1):6839.
[18] Stöckel S, Kirchhoff J, Neugebauer U, et al. The application of Raman spectroscopy for the detection and identification of microorganisms [J]. Raman Spectrosc, 2015, 47(1): 89-109.
[19] Wang Y, Xu J, Kong L, et al. Raman-activated sorting of antibiotic-resistant bacteria in human gut microbiota [J]. Environ Microbiol, 2020, 22(7):2613-2624.
[20] Lynk TP, Sit CS, Brosseau CL. Electrochemical surface-enhanced Raman spectroscopy as a platform for bacterial detection and identification [J]. Anal Chem, 2018, 90(21):12639-12646.