Autofluorescence Detection Method for Dental Plaque Bacteria

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Article Autoﬂuorescence Detection Method for Dental Plaque Bacteria Detection and Classiﬁcation: Example of Porphyromonas gingivalis, Aggregatibacter actinomycetemcomitans, and Streptococcus mutans

Yung-Jhe Yan 1 , Bo-Wen Wang 2, Chih-Man Yang 3,4 , Ching-Yi Wu 5 and Mang Ou-Yang 1,*

1 Institute of Electrical and Control Engineering, National Yang Ming Chiao Tung University, 1001 University Road, Hsinchu City 30010, Taiwan; [email protected] 2 Department of Electrical and Computer Engineering, National Yang Ming Chiao Tung University, 1001 University Road, Hsinchu City 30010, Taiwan; [email protected] 3 Department of Laboratory Medicine, National Taiwan University Hospital Hsin-Chu Branch, No. 25 Ln. 442 Jingguo Road, Hsinchu City 30010, Taiwan; [email protected] 4 Institute of Molecular Medicine and Biochemical Engineering, National Yang Ming Chiao Tung University, 1001 University Road, Hsinchu City 30010, Taiwan 5 Institute of Oral Biology, National Yang Ming Chiao Tung University, 155 Linong Street, Taipei City 11221, Taiwan; [email protected] * Correspondence: [email protected] Abstract: The use of fluorescence spectroscopy for plaque detection is a fast and effective way to Citation: Yan, Y.-J.; Wang, B.-W.; monitor oral health. At present, there is no uniform specification for the design of the excitation light Yang, C.-M.; Wu, C.-Y.; Ou-Yang, M. source of related products for generating fluorescence. To carry out experiments on dental plaque, the Autofluorescence Detection Method fluorescence spectra of three different bacterial species (Porphyromonas gingivalis, Aggregatibacter acti- for Dental Plaque Bacteria Detection nomycetemcomitans, and Streptococcus mutans) were measured by hyperspectral imaging microscopy and Classification: Example of (HIM). Three critical issues were found in the experiments. One issue was the unwanted spectrum Porphyromonas gingivalis, Aggregatibacter actinomycetemcomitans, generated from a mercury line source; two four-order low-pass filters were evaluated for eliminating and Streptococcus mutans. Dent. J. the unwanted spectrum and meet the experimental requirements. The second issue was the red 2021, 9, 74. https://doi.org/10.3390/ fluorescence generated from the microscope slide made of borosilicate glass; this could affect the dj9070074 observation of the red fluorescence from the bacteria; quartz microscope slides were found to reduce the fluorescence intensity by about 2 dB compared with the borosilicate slide. The third issue of Academic Editors: Liviu Steier and photobleaching in the fluorescence of the Porphyromonas gingivalis was studied. This study proposes Gianrico Spagnuolo a method of classifying three bacteria based on the spectral intensity ratios (510/635 and 500/635 nm) under the 405 nm excitation light was proposed in this study. The sensitivity and specificity of the Received: 13 May 2021 classification were approximately 99% and 99%, respectively. Accepted: 21 June 2021 Published: 22 June 2021 Keywords: plaque detection; dental plaque; autofluorescence; Porphyromonas gingivalis; Aggregatibac- ter actinomycetemcomitans; Streptococcus mutans Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affil- iations. 1. Introduction Dental plaque is composed of tiny food particles, mass bacteria, and waste products of bacteria on the tooth surface or other surfaces in the oral cavity. The build-up of dental plaque often causes gingivitis, periodontitis, and caries. According to a Health Promotion Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. Administration survey in 2012, the prevalence of caries in Taiwan exceeded 88%, and the This article is an open access article proportion of periodontitis and gingivitis, which are associated with periodontal disease, distributed under the terms and reached 99% [1]. If gingivitis, periodontitis, and caries diseases are not properly treated at conditions of the Creative Commons an early stage, they cause tooth loss and accompany an increasing failure rate for dental Attribution (CC BY) license (https:// implants. Due to inflammation of the mucous membrane and bone loss accompanying creativecommons.org/licenses/by/ periodontal disease, implanting a denture is like building a house on a hollow foundation, 4.0/). and it will finally fall apart. Dental plaque build-up is normally caused by poor oral

Dent. J. 2021, 9, 74. https://doi.org/10.3390/dj9070074 https://www.mdpi.com/journal/dentistry Dent. J. 2021, 9, 74 2 of 14

hygiene. As the plaque biofilm matures, the secreted acidic substances erode the teeth, decalcify the tooth surface, and form caries. In addition, lipopolysaccharide, found in the outer membrane of Gram-negative bacteria, might induce the loss of periodontal ligament and alveolar bone, causing teeth to shake and fall out. Moreover, some bacteria produce proteases to degrade host tissues. The two pathogenic factors mentioned above will continue to pose harm even if the bacteria are killed. Bacteria can be divided into two broad categories: Gram-positive bacteria and Gram- negative bacteria. The Gram staining classification method makes the Gram-positive bacteria remain purple, while Gram-negative bacteria are stained pink or red in counter- stain [2,3]. Considerable research over several decades has led to the identification of Por- phyromonas gingivalis (PG), a Gram-negative anaerobic bacterium, as the major pathogenic bacterium that contributes to the development of periodontal disease [4]. The PG was found in 87.75% of subgingival plaque samples from chronic periodontitis patients. Aggre- gatibacter actinomycetemcomitans (AA), a Gram-negative facultative anaerobic bacterium, is highly associated with localized aggressive periodontitis. It has been further implicated in various systemic diseases, including infectious endocarditis, brain abscesses, and chest wall abscesses [5]. Streptococcus mutans (SM), a Gram-positive facultative anaerobic bacterium, plays a major role in tooth decay. On the basis of the above reasons, the AA, PG, and SM were the target bacteria species in the current study. Although oral cleaning procedures can easily remove dental plaque, oral hygiene is often neglected. Various dental plaque disclosing methods have been developed to assess dental plaque levels. The traditional method is to rinse the mouth with a disclosing solution containing red pigment and erythrosine. Absorption plays an important part during this process because erythrosine preferentially binds to plaque rather than teeth. However, the result of this method is affected by the staining time and oral muscle movements. It does not have intuitive or quantitative characteristics; moreover, residual pigments can cause esthetic problems. In recent years, fluorescent imaging technology has been widely used in biomedical detection. The endogenous fluorophores were irradiated by ultraviolet light and emit visible light. The energy difference between the absorption wavelength and fluorescence wavelength is known as the Stokes shift [6]. This fluorescence characteristic can be used to detect dental plaque. The traditional method and fluorescent imaging technology are compared in Table1.

Table 1. Comparison of the plaque disclosing agent and autoﬂuorescence imaging technology in principle, speed, and issues.

Plaque Disclosing Agent Autoﬂuorescent Imaging Technology Principle Adsorption Fluorescence Test duration 5−10 min Real-time < 1 ms After the test Aesthetic issues No change Gram-negative bacterial identiﬁcation No Yes Relative thickness of the plaque Yes Yes

The red fluorescence has been found in a biofilm that might be originated from porphyrins produced during bacterial metabolites [7]. The red fluorescence has been used to detect dental caries, oral malodor, and dental plaque [7–16]. Coulthwaite et al. observed the fluorescence of plaque on dentures using 366 nm excitation light sources [7]. Rechmann et al. discriminated plaque and gingival inflammation based on a SOPROCARE camera system and a 450 nm excitation light source [8]. Joseph et al. detected dental plaque in situ based on laser-induced autofluorescence spectroscopy equipped with a 404 nm excitation light source [9]. Liu et al. detected in-vitro dental plaque based on red fluorescence with a 405 nm excitation light source [10]. The wavelength of the excitation light sources in these studies seems inconsistent. Furthermore, bacteria species might produce different fluorophores that have individual fluorescent spectra induced by the specific wavelengths Dent. J. 2021, 9, x FOR PEER REVIEW 3 of 15

Dent. J. 2021, 9, 74 3 of 14 sources in these studies seems inconsistent. Furthermore, bacteria species might produce different fluorophores that have individual fluorescent spectra induced by the specific wavelengths of excitation light sources. Thus, this study aims to find the optimal fluores‐ cenceof excitation stimulation light sources. band and Thus, find this the study significant aims to spectral find the band optimal in fluorescencethree kinds of stimulation common bacteria,band and including find the significantPG, AA, and spectral SM. Caries band could in three be kindsinduced of commonby SM, and bacteria, periodontal including dis‐ easePG, AAcould, and be inducedSM. Caries by PG could and AA be; induced the identification by SM, and of bacteria periodontal species disease in dental could plaque be mightinduced help by toPG preventand AA people; the identification from developing of bacteria caries, species periodontal in dental disease, plaque and might subsequent help to derivationprevent people of systematic from developing disease. caries, Thus, periodontalthe goal of this disease, study and is to subsequent identify three derivation bacteria of systematic disease. Thus, the goal of this study is to identify three bacteria species based species based on light‐induced autofluorescence spectroscopy. on light-induced autofluorescence spectroscopy.

2. Materials Materials and and Methods Methods 2.1. Hyperspectral Hyperspectral Microscopy Microscopy System The hyperspectral hyperspectral microscopy microscopy system system (HMS) (HMS) was was developed developed in ina previous a previous study study to collectto collect the thefluorescence fluorescence spectra spectra of bacteria of bacteria [17]. The [17]. HMS The is HMS mainly is mainly composed composed of a micros of a‐ copymicroscopy system systemand a hyperspectral and a hyperspectral imaging imaging system (HIS). system The (HIS). microscopy The microscopy system consists system ofconsists an Olympus of an Olympus IX‐71 inverted IX-71 invertedmicroscope, microscope, a CCD camera, a CCD and camera, two andemission two emission light sources, light includingsources, including a halogen a source halogen and source a mercury and a mercurysource (Figure source 1a). (Figure The 1microscopea). The microscope provides anprovides eyepiece, an eyepiece,with additional with additional image output image ports output on the ports left on and the right left and sides right of the sides observa of the‐ tionobservation window. window. The left‐ Theside left-side output port output is connected port is connected to the HIS, to the and HIS, the and right the‐side right-side output portoutput is connected port is connected to the CCD. to the The CCD. halogen The halogen source was source used was in usedthe experiment in the experiment to supply to excitationsupply excitation lights in lights different in different bands. The bands. excitation The excitation band was band selected was according selected according to the spec to‐ ifiedthe specified excitation excitation filter. The filter. excitation The excitation light is reflected light is by reflected the dichromatic by the dichromatic mirror and mirrorpasses throughand passes the through objective the lens objective (OBL) lensto irradiate (OBL) to a irradiatesample. After a sample. irradiation, After irradiation, the sample the is excitedsample and is excited emits fluorescence. and emits fluorescence. The fluorescence The fluorescence passes through passes the OBL through and thethe OBLemission and filter.the emission The beams filter. splitter The beams 1 splits splitter the fluorescence 1 splits the into fluorescence two parts. intoOne twopart parts.is passed One to part the CCDis passed or the to theeyepiece CCD orand the the eyepiece other to and the the HIS. other The to HIS the HIS.is composed The HIS of is composeda relay lens, of a steppingrelay lens, motor, a stepping a spectrometer motor, a spectrometer (Specim V10E), (Specim and an V10E), electron and‐multiplying an electron-multiplying charge‐cou‐ pledcharge-coupled device (EMCCD) device camera (EMCCD) (Anode camera Luca (Anode R604). Luca The relay R604). lens The is relay composed lens is of composed multiple symmetricalof multiple symmetrical lenses to transfer lenses images to transfer from images one side from to onethe other. side to The the image other. Theis laterally image andis laterally vertically and inverted. vertically The inverted. stepping Themotor stepping controls motor the coil controls current the and coil magnetizes current and the oppositemagnetizes rotor the at opposite a certain rotor angle at to a certaincontrol anglethe position to control of the the relay position lens. of It the can relay achieve lens. the It advantagecan achieve of the precise advantage rotation. of precise The system rotation. scans The the system target scans by moving the target the by relay moving lens, theal‐ lowingrelay lens, the allowing target to the be targetmeasured to be without measured moving without the moving target theor the target system. or the The system. splitting The systemsplitting decomposes system decomposes the input the light input into light spectra into from spectra 400 from to 1000 400 tonm. 1000 It includes nm. It includes all visible all lightvisible and light part and of partthe UV of the and UV near and‐infrared near-infrared light. The light. EMCCD The EMCCD has an has electronic an electronic gain func gain‐ tionfunction that thatallows allows the thecharge charge to multiply to multiply through through the the gain gain register register and and amplify amplify the the weak signal to facilitate the collection of the weak fluorescent fluorescent signals. The spectral resolution of µ × µ thethe HIS is about 2.8 nm, and the spatial resolution isis about 3030 m  1010 m.m. Accordingly, Accordingly, thethe HIS can collect the bacteria bacteria-scale‐scale fluorescent fluorescent image over hundreds of bands.

(a) (b)

Figure 1. (a) Inverted microscope structure in the hyperspectral microscopy system. (b) Hyperspectral system equipped on the hyperspectral microscopy system.

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Dent. J. 2021, 9, 74 4 of 14 Figure 1. (a) Inverted microscope structure in the hyperspectral microscopy system. (b) Hyperspectral system equipped on the hyperspectral microscopy system.

2.2.2.2. Specific Specific Consideration Consideration for for Eliminating Eliminating the the Excitation Excitation Light Light AA few few narrowband narrowband wavelengths wavelengths in inthe the mercury mercury line line were were used used as the as theexcitation excitation light light inin the the experiments. experiments. The The 365 365 nm nm filter filter was was installed installed in in front of thethe mercurymercury lightlight source,source, and andfive five narrow narrow band-pass band‐pass filters filters with with center center wavelengths wavelengths of of 375, 375, 394, 394, 405, 405, 420, 420, andand 430430 nm nmwere were equipped. equipped. Each Each filter filter had had a photon a photon attenuation attenuation (absorption (absorption and and scattering) scattering) or optical or opticaldensity density (OD) (OD) that resulted that resulted in an in exponential an exponential decay decay of intensity of intensity of anyof any given given optical optical field, field,as it as penetrated it penetrated deep deep into into tissue tissue and and limited limited the the penetration penetration depth depth achievable achievable for for deep deeptissue tissue imaging. imaging. Unexpectedly,Unexpectedly, the the EMCCD EMCCD-acquired‐acquired image image contained contained green green light. light. Therefore, Therefore, all the all the spectraspectra of of the the excitation excitation lights lights filtered filtered by by the the six six band band-pass‐pass filters filters were checked. The resultsre‐ sults in Figure 2a show that the filters were correctly designed because each filter has only in Figure2a show that the filters were correctly designed because each filter has only one one narrow peak at the specified band. The penetration rate α is the emitted light divided narrow peak at the specified band. The penetration rate α is the emitted light divided by by the incident light, and it satisfies Equation (1). To counteract the intensity of the unde‐ the incident light, and it satisfies Equation (1). To counteract the intensity of the undesired sired green light, two 450 nm low‐pass filters with the order (OD) of 4, with the same effect green light, two 450 nm low-pass filters with the order (OD) of 4, with the same effect of of one 450 nm low‐pass filters with the order (OD) of 8, were positioned in front of all the one 450 nm low-pass filters with the order (OD) of 8, were positioned in front of all the narrowband filters. The spectra of the excitation light source coupled with and without narrowband filters. The spectra of the excitation light source coupled with and without the the 450 nm low‐pass filter are shown in Figure 2b. These low‐pass filters dramatically 450 nm low-pass filter are shown in Figure2b. These low-pass filters dramatically reduced reduced the intensity of the unexpected green light. the intensity of the unexpected green light. 𝛼10 (1) α = 10−OD (1)

(a) (b)

FigureFigure 2. 2. (a()a Spectrum) Spectrum of of the the excitation excitation light light source source filtered filtered by by 365 365-,‐, 375 375-,‐, 394 394-,‐, 405 405-,‐, 420 420-,‐, and and 430 430 nm nmband-pass band‐pass filters. filters. (b ()b Spectrum) Spectrum of of the the excitation excitation light light source source with with and and without without twotwo 450450 nm (OD = 4) = 4) low‐pass filter. OD is the order of the penetration rate. low-pass filter. OD is the order of the penetration rate.

2.3.2.3. Object Object Slide Slide of ofMicroscope Microscope Necessary Necessary for for Autofluorescence Autofluorescence Measurement Measurement AtAt the the beginning beginning of of the the experiment, experiment, the the spectrum spectrum of each of each sample sample was was characterized characterized byby a aweak weak red red fluorescence fluorescence with with a peak a peak wavelength wavelength of ofabout about 650 650700−700 nm. nm. To determine To determine thethe source source of ofthe the red red fluorescence, fluorescence, the sample the sample and filter and sets filter were sets removed were removed first, and first, only and oneonly or onefour or microscope four microscope slides were slides equipped were equipped on the microscope. on the microscope. The corresponding The corresponding spec‐ traspectra are shown are shown in Figure in Figure 3. The3. Thered intensity red intensity of the of thespectrum spectrum was was higher higher with with the thefour four microscopemicroscope slides slides than than with with the the one microscopemicroscope slide.slide. Notably,Notably, the the general general microscope microscope slide slideis made is made of borosilicate of borosilicate glass, glass, which which was foundwas found to generate to generate red fluorescence red fluorescence when excitedwhen at excited445 nm at [ 18445]. nm Therefore, [18]. Therefore, it is reasonable it is reasonable to infer thatto infer the that microscope the microscope slide generated slide gener the‐ red atedfluorescence. the red fluorescence. It was essential It was to eliminateessential to the eliminate red fluorescence the red becausefluorescence its intensity because is its close intensityto that of is the close bacteria to that and of the could bacteria affect and the analysis.could affect Quartz the analysis. slides presented Quartz slides an alternative pre‐ sentedto borosilicate an alternative glass. to Figureborosilicate3 displays glass. the Figure spectrum 3 displays obtained the spectrum with the obtained quartz slide.with It shows a much lower intensity of red fluorescence compared to borosilicate glass. The intensity at a 700 nm wavelength for quartz is reduced by 2 dB compared to borosilicate glass. For accurate measurements, the subsequent experiments used quartz slides instead of borosilicate glass. Dent. J. 2021, 9, x FOR PEER REVIEW 5 of 15

the quartz slide. It shows a much lower intensity of red fluorescence compared to borosil‐ Dent. J. 2021, 9, 74 icate glass. The intensity at a 700 nm wavelength for quartz is reduced by 2 dB compared5 of 14 to borosilicate glass. For accurate measurements, the subsequent experiments used quartz slides instead of borosilicate glass.

Figure 3. SpectrumSpectrum obtained obtained with with the the four four borosilicate borosilicate slides, slides, one borosilicate one borosilicate slide, slide,and one and quartz one quartzslide. slide.

2.4. Culture the Bacteria Three speciesspecies ofof bacteria (PG,, AA and SM) were obtained from Bioresource Collection andand ResearchResearch Center, Center, Hsinchu Hsinchu City, City, Taiwan. Taiwan. The The bacteria bacteria were were stored stored in a stock in a with stock TYHK with mediumTYHK medium composed composed of trypticase of trypticase soy broth soy (30 broth g/L), (30 yeast g/L), extract yeast (5 extract g/L), hemin (5 g/L), (1 heminµg/mL), (1 vitaminμg/mL), K3vitamin (1 µg/mL), K3 (1 μ andg/mL), brain and heart brain infusion heart infusion with 10% with glycerol. 10% glycerol. The bacteria The bacteria were culturedwere cultured and stocked and stocked in the in biosafety the biosafety level level two (BSL-2)two (BSL laboratory‐2) laboratory at National at National Taiwan Tai‐ Universitywan University Hospital Hospital Hsin-Chu Hsin‐ Branch,Chu Branch, Hsinchu Hsinchu City, City, Taiwan. Taiwan. The bacteria The bacteria were were cultured cul‐ intured a suitable in a suitable environment, environment, Petri dish, Petri and dish, medium. and Specifically,medium. Specifically, CDC anaerobic CDC blood anaerobic agar ◦ wasblood used agar to was facilitate used to the facilitate cultivation the cultivation of the PG and of the the PGAA andat 37the AAC in at an 37 anaerobic °C in an anaer tank,‐ and tryptic soy agar with 5% sheep blood agar was used to facilitate the cultivation of the obic tank,◦ and tryptic soy agar with 5% sheep blood agar was used to facilitate the culti‐ SMvationat 37 of theC in SM an at aerobic 37 °C tank.in an Theaerobic two tank. agars The were two manufactured agars were manufactured by Dr. Plate Co. by The Dr. bacteriaPlate Co. were The bacteria first stocked were infirst Bacterial stocked Freezing in Bacterial medium Freezing tubes. medium After tubes. removing After some remov of‐ eaching some bacterial of each species bacterial from species the Bacterial from the Freezing Bacterial medium Freezing tubes medium using sterile tubes loops, using itsterile was smeared on the four regions of the agar using the streaking method. PG and AA were loops, it was smeared on the four regions of the agar using the streaking method. PG and cultured for 2–3 weeks and SM was cultured for 3–4 days before the exiting and scanning AA were cultured for 23 weeks and SM was cultured for 34 days before the exiting and processes using the HMS. In the experiment, six plates of PG, six plates of AA, and 15 plates scanning processes using the HMS. In the experiment, six plates of PG, six plates of AA, of SM were cultured. and 15 plates of SM were cultured. 3. Results and Analysis 3.1.3. Results Photobleaching and Analysis of PG 3.1. PhotobleachingPhotobleaching of describesPG the photochemical alteration of a fluorophore in such a way that itPhotobleaching permanently loses describes its ability the tophotochemical fluorescence [alteration19,20]. The of phenomenon, a fluorophore though in such not a yetway fully that understood,it permanently is irreversibleloses its ability because to fluorescence a covalent [19,20]. bond in The a fluorophore phenomenon, molecule though thatnot yet transits fully fromunderstood, the singlet is irreversible state to the because triplet state. a covalent Some bond fluorescent in a fluorophore materials molecule undergo bleachingthat transits as from soon the as they singlet are state excited, to the while triplet some state. may Some experience fluorescent thousands materials or millionsundergo ofbleaching fluorescent as soon cycles as beforethey are bleaching excited, [while19,20]. some The lossmay of experience fluorescence thousands in photobleaching or millions followsof fluorescent an exponential cycles before decay. bleaching The protoporphyrin [19,20]. The loss IX of was fluorescence detected in inPG photobleaching[21], and the fluorescentfollows an spectrumexponential of thedecay. porphyrins The protoporphyrin was consistent IX with was the detected fluorescent in PG spectrum [21], and of thethe PGfluorescent in this study spectrum [22,23 of]. the Thus, porphyrins the protoporphyrin was consistent IX might with bethe the fluorescent main contribution spectrum ofof thethe fluorescentPG in this study spectrum [22,23]. in PG Thus,. Figure the 4protoporphyrin shows the porphyrin IX might structure be the and main the contribution structures ofof parentthe fluorescent porphyrin spectrum [23–27]. in PG. Figure 4 shows the porphyrin structure and the struc‐ turesOne of parent feature porphyrin of exponential [23–27]. decay is the half-life (t1/2), which refers to the time it takes for a certain concentration of a substance to be reduced to half of its initial concentration after a certain reaction. The t1/2 is defined as follows:

−λt N(t) = N0 e , (2)

ln2 t1/2 = , (3) λ Dent. J. 2021, 9, 74 6 of 14

where N0 is the initial intensity, N(t) is the intensity at time t, and λ is the reaction rate constant. As the ﬂuorescence is generated not only from porphyrin but also from bacteria and other substances, the offset of parameter M should be added as compensation in Dent. J. 2021, 9, x FOR PEER REVIEW Equation (4). 6 of 15 −λt N(t) = M + N0 e . (4)

(a) (b) (c)

(d) (e)

FigureFigure 4. 4. (a()a Chemical) Chemical structure structure of ofporphyrin, porphyrin, (b) (tetraphenylporphyrin,b) tetraphenylporphyrin, (c) octaethylporphyrin, (c) octaethylporphyrin, (d) protoporphyrin(d) protoporphyrin IX, and IX, and(e) heme. (e) heme.

OneThe feature fluorescence of exponential decay complicates decay is the the half quantitative‐life (t1/2), which analysis refers of to the the hyperspectral time it takes formeasuring a certain data. concentration The different of a positions substance of to the be sample reduced must to half be measured of its initial at differentconcentration times afterbecause a certain the hyperspectral reaction. The t system1/2 is defined measures as follows: a narrow slot area of a sample at one time, referred to as the line scan, and the sample area is normally larger than the slot of the HMS. 𝑁𝑡 𝑁 𝑒 , (2) Furthermore, because the whole sample was excited at the same time in the experiments, fluorescence decay may also start at the same time. These reasons caused the variance of 𝑡 , the spectrum measurement position with increased/ durations of bleaching. (3) Photobleaching occurred in the initial fluorescence experiment of PG. To further where N0 is the initial intensity, N(t) is the intensity at time t, and λ is the reaction rate observe the fluorescence decay exhibited by PG at different excitation wavelengths, two constant. As the fluorescence is generated not only from porphyrin but also from bacteria plates of PG and six excitation wavelengths, including 365, 375, 394, 405, 420, and 430 nm, and other substances, the offset of parameter M should be added as compensation in were used. At first, the bacteria-free quartz slide was scanned to measure the background Equation (4). signal. Some PG was removed from the Petri dish using a sterile loop and was smeared onto the quartz slide for excitation and𝑁𝑡 scanning. 𝑀𝑁 To 𝑒 observe. the fluorescence decay under(4) the same intensity of the excitation wavelengths for the two PG samples, the same position of theThePG fluorescencesamples in a decay slot range complicates was scanned the quantitative several times analysis for a fixed of the scanning hyperspectral duration measuringand exposure data. time. The The different fluorescence positions emission of the sample spectra must of PG beshowed measured a peak at different wavelength times at becauseabout 635 the nm hyperspectral at the different system excitation measures wavelengths a narrow (Figure slot area5). Theof a highestsample fluorescenceat one time, referredintensity to was as observedthe line scan, at the and 405 the nm sample excitation area wavelength. is normally The larger photobleaching than the slot of ofPG theat HMS.the 405 Furthermore, nm excitation because wavelength, the whole as seen sample in the was experimental excited at results, the same was time further in the analyzed. exper‐ iments, fluorescence decay may also start at the same time. These reasons caused the var‐ iance of the spectrum measurement position with increased durations of bleaching. Photobleaching occurred in the initial fluorescence experiment of PG. To further ob‐ serve the fluorescence decay exhibited by PG at different excitation wavelengths, two plates of PG and six excitation wavelengths, including 365, 375, 394, 405, 420, and 430 nm, were used. At first, the bacteria‐free quartz slide was scanned to measure the background signal. Some PG was removed from the Petri dish using a sterile loop and was smeared onto the quartz slide for excitation and scanning. To observe the fluorescence decay under the same intensity of the excitation wavelengths for the two PG samples, the same position of the PG samples in a slot range was scanned several times for a fixed scanning duration and exposure time. The fluorescence emission spectra of PG showed a peak wavelength

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at about 635 nm at the different excitation wavelengths (Figure 5). The highest fluores‐ at about 635 nmcence at intensitythe different was observedexcitation at wavelengths the 405 nm excitation(Figure 5). wavelength. The highest The fluores photobleaching‐ of cence intensityPG was at theobserved 405 nm at excitationthe 405 nm wavelength, excitation wavelength. as seen in the The experimental photobleaching results, of was further Dent. J. 2021, 9, 74 7 of 14 PG at the 405 analyzed.nm excitation wavelength, as seen in the experimental results, was further analyzed.

Figure 5. Spectra of the fluorescence of Porphyromonas gingivalis by six excitation lights, including Figure 5.5. SpectraSpectrathe ofof center the the fluorescence fluorescence wavelengths of of Porphyromonasof Porphyromonas 365, 375, 394, gingivalis 405,gingivalis 420,by and by six 430six excitation excitationnm. lights, lights, including including the centerthe center wavelengths wavelengths of 365, of 365, 375, 375, 394, 394, 405, 405, 420, 420, and and 430 nm.430 nm. The photobleaching of the PG samples at 405 nm excitation light is shown in Figure The photobleachingphotobleaching6a. The fluorescence of of the thePG PG samplesintensity samples at atat 405 about405 nm nm excitation635 excitation nm wavelength light light is shownis shownwas in decaying Figurein Figure6 a.when the HMS The6a. The fluorescence fluorescencewas intensity continuously intensity at about at scanning.about 635 nm635 The wavelengthnm wavelengthfluorescence was was decaying spectra decaying at when the when theline HMS positionthe HMS was of 552 and at continuouslywas continuously scanning.different scanning. times, The fluorescence Theincluding fluorescence 19, spectra 80, 155,spectra at the 232, line at and the position 289 line s, positionare of 552 further and of atshown552 different and in at Figure 6b. The times,different including times,spectra including 19, 80, illustrate 155, 19, 232, 80, that 155, and the 232, 289 fluorescence s,and are 289 further s, ofare PG shown further decayed in shown Figure at the in6b. wavelengthsFigure The spectra 6b. The of 635 and 702 illustratespectra illustrate thatnm. the that fluorescence the fluorescence of PG decayed of PG atdecayed the wavelengths at the wavelengths of 635 and of 702 635 nm. and 702 nm.

(a) (b) (a) (b) Figure 6. (a) Figurethree‐dimensional 6. (a) three-dimensional plot of the fluorescence plot of the fluorescence decay of Porphyromonas decay of Porphyromonas gingivalis at gingivalis635 nm underat 635 405 nm nm excita‐ Figure 6. (a) threetion‐dimensional light. (bunder) Spectra plot 405 ofof nm thethe excitation fluorescencefluorescence light. decay (b) Spectra ofat thePorphyromonas same of the position fluorescence gingivalis at different decay at 635 times. at nm the under sameTo determine position405 nm excita at the different ‐consistency of tion light. (b) Spectrathe photobleaching, of the times.fluorescence To the determine decay fluorescence at the the consistency same‐decay position curves of at the different of photobleaching, the PG times. samples To thedetermine were fluorescence-decay fitted the to consistency an exponential curves of of the curve. Half the photobleaching,of the thedifference fluorescencePG samples between were‐decay the fitted curves maximum to an of exponential the and PG minimumsamples curve. Halfwere values of fitted the of difference to the an decayedexponential between fluorescence the curve. maximum Half intensities and was 1/2 1/2 of the differenceconsidered between minimumas the t .maximum Based values on of Equationand the decayed minimum (3), fluorescence the values λ can intensities ofbe thederived decayed was by considered the fluorescence known as t1/2 t . .intensities Based The simulated on Equation was curves (3), were 1/2 1/2 considered ascalculated t . Based andtheon λEquation plottedcan be derived according (3), the by λ the tocan known Equation be derivedt1/2. (4) The by simulated MATLAB™.the known curves t The were. The fluorescence calculated simulated and curvesdecay plotted ofwere according two PG samples calculated andat plotted 635 nm according atto two Equation line to positions (4)Equation by MATLAB fitted (4) by to™ MATLAB™. .the The exponential fluorescence The curve decayfluorescence is of shown two PG decay insamples Figure of two at 7. 635 PG nm samples at two line at 635 nm at two line positionspositions fitted fitted to to the the exponential exponential curvecurve is is shown shown in in Figure Figure7. 7.

The simulated curves in Figure7a,b are similar to the experimental curves. However, t1/2 of one sample at the different spatial positions was not identical. This phenomenon may be caused by variations in the thickness of the bacteria at different spatial positions. The thickness variation may lead to a variation in the fluorescence processing time. Considering that the bacteria in the samples were excited from the bottom to the top, the fluorescence reaction also started from the bottom to the top. Although the whole sample was uniformly excited, the different thicknesses of the bacteria led to differences in the fluorescence t1/2 values. Furthermore, the reason for the thickness variation is the limited control over the number and uniform thickness of the bacteria in the different positions during the experiments. If there were a way to stabilize the number of bacteria, the experiments could be further carried out to obtain various light intensities corresponding to various quantities. Dent. J. 2021, 9, x FOR PEER REVIEW 8 of 15

Dent. J. 2021, 9, 74 Dent. J. 2021, 9, x FOR PEER REVIEW 8 of 14 8 of 15

(a) (b) Figure 7. (a) Simulated and experimental results of the photobleaching at 635 nm excited by 405 nm at the spatial position of 552; (b) Simulated and experimental results of the photobleaching at 635 nm excited by 405 nm at the spatial position of 488.

orescence reaction also started from the bottom to the top. Although the whole sample

was uniformly excited, the different thicknesses of the bacteria led to differences in the (a) (b) fluorescence t1/2 values. Furthermore, the reason for the thickness variation is the limited Figure 7. (aFigurecontrol) Simulated 7. over(a) and Simulated the experimental number and experimentaland results uniform of the results photobleaching thickness of the of photobleaching the at 635 bacteria nm excited atin 635 the by nm 405different excited nm at the bypositions 405spatial nm position of 552; (b) Simulatedatduring the spatial the and experiments. position experimental of 552; If results ( bthere) Simulated of were the photobleaching a and way experimental to stabilize at 635 results the nm number ofexcited the photobleaching byof 405bacteria, nm at thethe at 635spatialexper nm ‐position of 488. excitediments bycould 405 nm be atfurther the spatial carried position out ofto 488. obtain various light intensities corresponding to various quantities. The simulated curves in Figure 7a,b are similar to the experimental curves. However, Maturely, the sample sample has has continuous continuous thickness thickness variation variation across across the the positions, positions, and and the t1/2 of one sample at the different spatial positions was not identical. This phenomenon theexcitation excitation light light intensity intensity is continuous is continuous in a nearby in a nearby location. location. Therefore, Therefore, the t1/2 of the thet1/2 fluoof‐ may be caused by variations in the thickness of the bacteria at different spatial positions. therescence ﬂuorescence must continuously must continuously vary with vary the withpositions. the positions. To prove To this prove phenomenon, this phenomenon, the t1/2 of The thickness variation may lead to a variation in the fluorescence processing time. Con‐ the t1/2 of the ﬁrst sample in the region from 450 to 1003 was calculated and plotted in the first samplesidering in the region that the from bacteria 450 to in 1003 the samples was calculated were excited and plotted from the in bottomFigure 8.to Thethe top, the flu‐ Figure8. The results showed that the t was a continuous curve, making the inference results showedorescence that the treaction1/2 was a also continuous started1/2 from curve, the making bottom the to inferencethe top. Although more convinc the whole‐ sample more convincing. ing. was uniformly excited, the different thicknesses of the bacteria led to differences in the fluorescence t1/2 values. Furthermore, the reason for the thickness variation is the limited control over the number and uniform thickness of the bacteria in the different positions during the experiments. If there were a way to stabilize the number of bacteria, the exper‐ iments could be further carried out to obtain various light intensities corresponding to various quantities. Maturely, the sample has continuous thickness variation across the positions, and the excitation light intensity is continuous in a nearby location. Therefore, the t1/2 of the fluo‐ rescence must continuously vary with the positions. To prove this phenomenon, the t1/2 of the first sample in the region from 450 to 1003 was calculated and plotted in Figure 8. The results showed that the t1/2 was a continuous curve, making the inference more convinc‐ ing.

Figure 8. Half-lifeHalf‐life in spatial position from 450 to 1003.

3.2. ClassificationClassification of PG/AA/SM For the classification,classification, the bacteria and part ofof thethe agaragar containingcontaining thethe bacteriabacteria werewere placed onon the quartz slide and scanned. Part of the bacteria-freebacteria‐free agar was measured asas thethe background. The spectrum data were normalized against thethe maximummaximum intensityintensity ofof eacheach spectrum. TheThe normalized normalized fluorescence fluorescence spectra spectra of ofPG PG, AA, AAand andSM SMat 405 at nm405 excitation nm excitation light are shown in Figure9. After subtracting the background, the spectrum of PG had a valley with a negative value at about 500 nm. This is due to the composition variation in the agar during culturing. AA and SM had a positive value; this was significantly different from

PG. Thus, the negative peak at 500 nm was used to differentiate PG from the others. The fluorescent spectrumFigure 8. of HalfAA‐lifeand in SMspatialhad position the same from peak 450 to at 1003. 500 nm but differed at 635 nm. To classify AA and SM, the ratio of intensity at 635 ± 1 nm to the highest peak intensity at 3.2. Classification of PG/AA/SM around 510 ± 1 nm of AA and 500 ± 1 nm of SM, respectively, was considered to identify the correspondingFor bacteria. the classification, Figure 10 shows the bacteria the flow and chart part ofof thethe classificationagar containing criteria. the bacteria were For each bacterialplaced species, on the the quartz ratio slide of one and point scanned. was calculated Part of the asbacteria a simple‐free reference. agar was Themeasured as the results are shownbackground. in Figure The 11. spectrum It is worthy data of were mentioning normalized that against the peak the intensity maximum of intensity the of each experimental rawspectrum. data was The larger normalized than 10,000; fluorescence overexposure spectra occurred, of PG, AA and and the SM data at 405 were nm excitation excluded from the analysis. In Figure 11, the SM7-1 had a peak intensity larger than 10,000.

Dent. J. 2021, 9, x FOR PEER REVIEW 9 of 15

light are shown in Figure 9. After subtracting the background, the spectrum of PG had a valley with a negative value at about 500 nm. This is due to the composition variation in the agar during culturing. AA and SM had a positive value;value; this was significantly different from PG. Thus, the negative peak at 500 nm was used to differentiate PG from the others. The fluorescent spectrum of AA and SM had the same peak at 500 nm but differed at 635 nm. To classify AA and SM, the ratio of intensityintensity at 635635 ± 1 nm to the highest peak intensity at around 510510 ± 1 nm of AA and 500500 ± 1 nm of SM, respectively, was considered to identify the corresponding bacteria. Figure 10 shows the flow chart of the classification criteria. Dent. J. 2021, 9, 74 For each bacterial species, the ratio of one point was calculated as a simple reference.9 of The 14 results are shown in Figure 11.11. It is worthy of mentioning that the peak intensity of the experimental raw data was larger than 10,000; overexposure occurred,occurred, and the data were excluded from the analysis. In Figure 11, the SM7‐-1 had a peak intensity larger than 10,000. The SM7-1 data were excluded because the EMCCD was overexposed to measure this The SM7‐-1 data were excluded because the EMCCD was overexposed to measure this data. A total of 6 and 15 groups of AA and SM were recruited, respectively. The ratio at data. A total of 6 and 15 groups of AA and SM were recruited, respectively. The ratio at approximately 0.33 was the standard to distinguish between AA and SM. If the ratio was approximately 0.33 was the standard to distinguish between AA and SM. If the ratio was higher than 0.33, the sample was identiﬁed as AA. If the ratio of the sample was lower than higher than 0.33,0.33, the sample was identified as AA. If the ratio of the sample was lower 0.33, the sample was identiﬁed as SM. than 0.33, the sample was identified as SM.

FigureFigure 9.9. NormalizedNormalized spectralspectral curvecurve of PorphyromonasPorphyromonas gingivalisgingivalis ((PGPG),),), AggregatibacterAggregatibacter actinomycetem-actinomycetemactinomycetem-‐ comitanscomitans ((AAAA),),), andand Streptococcus Streptococcus mutans mutans( (SMSM).).).

Dent. J. 2021, 9, xFigure FigureFOR PEER 10.10. REVIEW Flow chart chart of of the the classification classiﬁcation in in PorphyromonasPorphyromonas gingivalis gingivalis (PG(PG),), Aggregatibacter), Aggregatibacter actinomyactinomy- actino-‐ 10 of 15

mycetemcomitanscetemcomitans (AA(AA),), and), and StreptococcusStreptococcus mutans mutans (SM(SM).). ).

Figure 11.Figure Peak intensity, 11. Peak intensity,the intensity the intensityat 635 nm, at and 635 the nm, ratio and theof the ratio intensity of the intensityat 635 nm at to 635 the nm peak to theintensity peak of every group. intensity of every group.

For further optimizationFor further andoptimization validation, and the validation, data were the groupeddata were as grouped training as andtraining and vali‐ validation sets.dation The sample sets. The points sample of the points training of the set training and the set validation and the validation set of PG setwere of 6PG were 6 and 180 points, respectively. The sample points of the training set and the validation set of AA were 6 and 210 points, respectively. The sample points of the training set and the valida‐ tion set of SM were 15 and 450 points, respectively. The training set was used to find the optimal threshold using the receiver‐operating characteristic curve (ROC) method. The validation set was used to verify the optimized threshold. At first, it is necessary to deter‐ mine the distribution model of the training set. The process of classification is shown in Figure 12. Statistically, the three bacteria were independent and not paired. Considering that the sample numbers of each type of bacterium were less than 30, the distribution models of the samples were checked for normal distribution using Minitab. If the p‐value was >0.05, the sample distribution was similar to the normal distribution.

Figure 12. Determine the distribution model.

After confirming that the distribution of the three data sets was similar to the Stu‐ dent’s t‐distribution, each data set was fitted by Equation (5), where Г is a gamma func‐ tion, and ν is the sample number minus one. As shown in Figure 13, the ratio value of the cross point of the SM and AA data distribution curves was about 0.33. According to the ROC curve in Figure 14, the ratio was the optimal threshold for classifying the bacteria as SM or AA. The sensitivity and specificity of the ratio were over 99%, respectively.

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Figure 11. Peak intensity, the intensity at 635 nm, and the ratio of the intensity at 635 nm to the peak intensity of every Dent. J.group.2021, 9, 74 10 of 14

For further optimization and validation, the data were grouped as training and vali‐ dation sets. The sample points of the training set and the validation set of PG were 6 and and180 180points, points, respectively. respectively. The Thesample sample points points of the of training the training set and set the and validation the validation set of setAA ofwereAA 6were and 6210 and points, 210 points, respectively. respectively. The sample The sample points pointsof the training of the training set and set the and valida the‐ validationtion set of setSM of wereSM 15were and 15 450 and points, 450 points, respectively. respectively. The training The training set was set used was to usedfind the to findoptimal the optimal threshold threshold using the using receiver the receiver-operating‐operating characteristic characteristic curve curve (ROC) (ROC) method. method. The Thevalidation validation set was set was used used to verify to verify the optimized the optimized threshold. threshold. At first, At first,it is necessary it is necessary to deter to‐ determinemine the distribution the distribution model model of the of thetraining training set. set. The The process process of ofclassification classification is isshown shown in inFigure Figure 12. 12 Statistically,. Statistically, the the three three bacteria bacteria were were independent andand notnot paired.paired. Considering Considering thatthat thethe samplesample numbersnumbers ofof eacheach type type of of bacterium bacterium were were less less than than 30, 30, the the distribution distribution modelsmodels of of the the samples samples were were checked checked for for normal normal distribution distribution using using Minitab. Minitab. If If the thep p-value‐value waswas >0.05, >0.05, the the sample sample distribution distribution was was similar similar to to the the normal normal distribution. distribution.

FigureFigure 12. 12.Determine Determine the the distribution distribution model. model.

AfterAfter confirming confirming that that the the distribution distribution of theof the three three data data sets wassets similarwas similar to the to Student’s the Stu‐ tdent’s-distribution, t‐distribution, each data each set wasdata fitted set was by Equationfitted by Equation (5), where (5),Γ is where a gamma Г is function, a gamma and funcν‐ istion, the and sample ν is number the sample minus number one. Asminus shown one. in As Figure shown 13 ,in the Figure ratio 13, value the of ratio the value cross pointof the Dent. J. 2021, 9, x FOR PEER REVIEW 11 of 15 ofcross the SMpointand ofAA thedata SM and distribution AA data curves distribution was about curves 0.33. was According about 0.33. to the According ROC curve to the in FigureROC curve 14, the in ratio Figure was 14, the the optimal ratio was threshold the optimal for classifying threshold the for bacteria classifying as SM theor bacteriaAA. The as sensitivitySM or AA. and The specificity sensitivity of and the specificity ratio were of over the 99%, ratio respectively.were over 99%, respectively. v+1 / 𝑓𝑡Γ 2 1 𝑡 /𝑣−(v+1)/2, (5) √ 2 f (t) = √ v 1 + t /v , (5) vπΓ 2

Figure 13. Student’sStudent’s tt‐-distributiondistribution of the training training set of StreptococcusStreptococcus mutans (SM) and Aggregatibacter actinomycetemcomitans (AA).

Figure 14. Receiver‐operating characteristic (ROC) curve of the training set of Streptococcus mutans and Aggregatibacter actinomycetemcomitans.

To further verify the ratio as an optimal identification method, 30 points from each group were used. The data are shown in Figures 15 and 16. In the AA groups, only 2 of 210 points were misidentified. In the SM groups, only 1 of 450 points was misidentified. The results appropriately fit the evaluation method. As all AA and SM data at 500 ± 1 nm were positive, the intensities of PG at 500 ± 1 nm are shown in Figure 17. The sensitivity and specificity were each 100% because the intensities were all negative. If the intensity of the bacteria at 500 nm was negative, it was classified as PG. Otherwise, the ratio of the intensity at 635 nm to a peak value was calculated for the next classification. If the ratio was higher than 0.33, the bacterium was classified as AA. Vice versa, if the ratio was lower than 0.33, it was classified as SM. This method has a sensitivity and specificity of approx‐ imately 99%, respectively.

Dent. J. 2021, 9, x FOR PEER REVIEW 11 of 15

/ 𝑓𝑡 1 𝑡 /𝑣 , (5) √

Dent. J. 2021, 9, 74 11 of 14 Figure 13. Student’s t‐distribution of the training set of Streptococcus mutans (SM) and Aggregatibacter actinomycetemcomitans (AA).

Figure 14. Receiver‐operating characteristic (ROC) curve of the training set of Streptococcus mutans Figure 14. Receiver-operating characteristic (ROC) curve of the training set of Streptococcus mutans and Aggregatibacter actinomycetemcomitans. and Aggregatibacter actinomycetemcomitans.

ToTo further further verify verify the the ratio ratio as as an an optimal optimal identification identification method, method, 30 30 points points from from each each groupgroup were were used. used. TheThe datadata areare shown shown in in Figures Figures 15 15 and and 16 16.. In In the theAA AAgroups, groups, only only 2 2 of of 210210 points points were were misidentified. misidentified. InIn thethe SMSM groups,groups, onlyonly 11 of of 450 450 points points was was misidentified. misidentified. TheThe results results appropriately appropriately fit fit the the evaluation evaluation method. method. As As all allAA AAand andSM SMdata data at at 500 500± ±1 1 nm nm werewere positive, positive, the the intensities intensities of ofPG PGat at 500 500± ± 11 nmnm are are shown shown in in Figure Figure 17 17.. The The sensitivity sensitivity andand specificity specificity werewere eacheach 100% because the the intensities intensities were were all all negative. negative. If If the the intensity intensity of ofthe the bacteria bacteria at at 500 500 nm nm was was negative, negative, it it was was classified classified as PG. Otherwise,Otherwise, thethe ratioratio of of the the intensityintensity at at 635 635 nm nm to to a peaka peak value value was was calculated calculated for thefor nextthe next classification. classification. If the If ratio the wasratio higherwas higher than 0.33,than the0.33, bacterium the bacterium was classified was classified as AA as. Vice AA. versa, Vice versa, if the ratioif the was ratio lower was lower than Dent. J. 2021, 9, x FOR PEER REVIEW0.33,than it 0.33, was it classified was classified as SM .as This SM method. This method has a sensitivity has a sensitivity and specificity and specificity of approximately of12 approxof 15 ‐ Dent. J. 2021, 9, x FOR PEER REVIEW 12 of 15 99%,imately respectively. 99%, respectively.

Figure 15. Ratios in the Aggregatibacter actinomycetemcomitans (AA) groups. Figure 15. RatiosRatios in in the the AggregatibacterAggregatibacter actinomycetemcomitans actinomycetemcomitans (AA(AA) groups.) groups.

Figure 16. Ratios in the Streptococcus mutans (SM) groups. Figure 16. Ratios in the Streptococcus mutans (SM) groups. Figure 16. Ratios in the Streptococcus mutans (SM) groups.

Figure 17. The 500 ± 1‐nm data of Porphyromonas gingivalis (PG) groups. Figure 17. The 500 ± 1‐nm data of Porphyromonas gingivalis (PG) groups. 4. Discussion and Conclusions 4. Discussion and Conclusions The fluorescent spectrum of the PG under 405 nm excitations had a peak at about 635 nm andThe afluorescent secondary spectrum peak at about of the 705PG undernm. The 405 result nm excitations was consistent had a withpeak theat about previous 635 nmstudies and thata secondary found the peak red fluorescentat about 705 in nm.PG [7,28],The result since wasthe protoporphyrinconsistent with IXthe and previous copro‐ studiesporphyrin that were found found the red in PGfluorescent [21] and inthe PG fluorescent [7,28], since spectrum the protoporphyrin of these porphyrins IX and coprois sim‐‐ porphyrinilar to that wereof the found PG [22,23]. in PG [21]Thus, and the the fluorescent fluorescent spectrum spectrum of ofthe these PG couldporphyrins be attributed is sim‐ ilarto the to thatprotoporphyrin of the PG [22,23]. IX and Thus, coproporphyrin. the fluorescent The spectrum fluorescent of the spectrum PG could of thebe attributedSM under to405 the nm protoporphyrin excitations had IX a andpeak coproporphyrin. at about 500 nm The with fluorescent a long tail spectrum extending of toward the SM the under red 405wavelength nm excitations region. had This a peak green at aboutspectrum 500 nmwas with found a long in tailrelative extending Streptococci toward thespecies red wavelength region. This green spectrum was found in relative Streptococci species

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Figure 15. Ratios in the Aggregatibacter actinomycetemcomitans (AA) groups.

Dent. J. 2021, 9, 74 12 of 14

Figure 16. Ratios in the Streptococcus mutans (SM) groups.

FigureFigure 17.17. The 500 ± 11-nm‐nm data data of of PorphyromonasPorphyromonas gingivalis gingivalis (PG(PG) groups.) groups.

4.4. DiscussionDiscussion and Conclusions TheThe fluorescent fluorescent spectrum spectrum of of the the PGPG underunder 405 405 nm nm excitations excitations had hada peak a peakat about at about 635 635nm nmand and a secondary a secondary peak peak at about at about 705 nm. 705 nm.The Theresult result was wasconsistent consistent with withthe previous the previ- ousstudies studies that thatfound found the red the fluorescent red fluorescent in PG [7,28], in PG since[7,28 ],the since protoporphyrin the protoporphyrin IX and copro IX and‐ coproporphyrinporphyrin were found were found in PG [21] in PG and[21 the] and fluorescent the fluorescent spectrum spectrum of these ofporphyrins these porphyrins is sim‐ isilar similar to that to of that the PG of the[22,23].PG Thus,[22,23 ].the Thus, fluorescent the fluorescent spectrum of spectrum the PG could of the bePG attributedcould be attributedto the protoporphyrin to the protoporphyrin IX and coproporphyrin. IX and coproporphyrin. The fluorescent The spectrum fluorescent of the spectrum SM under of the405SM nm underexcitations 405 nmhad excitations a peak at about had a500 peak nm at with about a long 500 tail nm extending with a long toward tail extending the red towardwavelength the red region. wavelength This green region. spectrum This green was spectrum found in was relative found inStreptococci relative Streptococci species species [7,15,29]. The fluorescent spectrum of the AA under 405 nm excitations had a peak of nearly 500 nm and a second peak at nearly 635 nm. The color of this spectrum could be yellow to orange [30]. The fluorescent spectrum of the SM and AA might originate from flavin adenine dinucleotide and flavins that are the product of bacteria cell energy metabolism [31,32]. The spectral band at 500 nm to 510 nm and 635 nm was used to identify three bacteria species. These spectral bands were also found to be used to detect dental caries and dental plaque in different grades [9,12]. Obviously, the significant spectral bands of fluorescence in cultured bacteria and in-vivo dental plaque were cognate because the autofluorescence might originate from the same endogenous fluorophores, including NADH, flavins, and porphyrins. This study indicated that the fluorescent profiles of these three pathogenic bacteria, PG, AA, and SM, were unique under certain growth conditions and could present a potential risk assessment tool for identifying these key pathogens for periodontal disease or caries. Indeed, the interaction between different oral bacteria is likely to change the fluorescent profile. However, the fluorescent spectrum in a dual-species biofilm could still reflect the presence of PG [33]. While uncertainty remains in the case of multi-species biofilms, the ability of fluorescent spectra in bacterial differentiation needs to study further using multi-species biofilms or freshly collected dental plaque combined with microbiome analyses. In summary, this study comprehensively explored the application of light-induced autofluorescence microscopy to microbiology. First, the excitation light source for the HMS was equipped with narrowband filters. The filters require an OD of at least eight. This helped to eliminate the unwanted excitation light and meet the experimental requirements. Second, the material of the slide was one of the important issues because of the difference in the intensity of the red fluorescence associated with different glass materials. The quartz microscope slides were found to reduce the fluorescence intensity by about 2 dB compared with the borosilicate slide. Third, photobleaching occurred, particularly in PG. This phenomenon manifested as an irreversible exponential decay in the fluorescence spectra. Finally, a method for identifying dental plaque bacteria, including PG, AA, and Dent. J. 2021, 9, 74 13 of 14

SM, was proposed in this study. The sensitivity and specificity of the method were over 99.8% based on the simulated data, and approximately 99% based on the experimental data. However, fluorescence decay is worthy of further study and improvement. If the bacteria amounts could be quantified and the sample was more uniform, the results would be able to evaluate the consistent t1/2 of the fluorescence decay.

Author Contributions: Conceptualization, C.-M.Y., C.-Y.W., and M.O.-Y.; methodology, Y.-J.Y., and M.O.-Y.; software, B.-W.W.; analysis, B.-W.W.; investigation, B.-W.W. and Y.-J.Y.; resource, C.-M.Y., and C.-Y.W.; data curation, B.-W.W.; writing—original draft preparation, Y.-J.Y.; writing—review and editing, Y.-J.Y., and M.O.-Y.; visualization, Y.-J.Y.; supervision, C.-M.Y., C.-Y.W., and M.O.-Y.; project administration, Y.-J.Y., and M.O.-Y.; funding acquisition, M.O.-Y. All authors have read and agreed to the published version of the manuscript. Funding: This research was partially financially funded by the Ministry of Science and Technology of Taiwan (MOST) (MOST 104-2622-E-009-015-CC2, MOST 105-2623-E-009-008-D, MOST 105-2221-E- 009-082-, MOST 109-2321-B-009-008-), National Chiao Tung University, National Yang Ming Chiao Tung University, and National Taiwan University Hospital Hsin-Chu Branch. Institutional Review Board Statement: Aggregatibacter actinomycetemcomitans, Porphyromonas gingivalis, and Streptococcus mutans were obtained from Bioresource Collection and Research Center, Hsinchu, Taiwan. Informed Consent Statement: Not applicable. Data Availability Statement: The data presented in this study are available on request from the corresponding author. The data are not publicly available due to their containing information that could compromise the privacy of research participants. Conflicts of Interest: The authors declare no conflict of interest.

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