A protocol for the concurrent quantification and comparison of three cellular and extracellular components within biofilms is presented. The methodology involves the use of confocal laser scanning microscopy, biofilm structural analysis and visualization software, and statistical analysis software.
Confocal laser scanning microscopy (CLSM) is a powerful tool for investigation of biofilms. Very few investigations have successfully quantified concurrent distribution of more than two components within biofilms because: 1) selection of fluorescent dyes having minimal spectral overlap is complicated, and 2) quantification of multiple fluorochromes poses a multifactorial problem. Objectives: Report a methodology to quantify and compare concurrent 3-dimensional distributions of three cellular/extracellular components of biofilms grown on relevant substrates. Methods: The method consists of distinct, interconnected steps involving biofilm growth, staining, CLSM imaging, biofilm structural analysis and visualization, and statistical analysis of structural parameters. Biofilms of Streptococcus mutans (strain UA159) were grown for 48 hr on sterile specimens of Point 4 and TPH3 resin composites. Specimens were subsequently immersed for 60 sec in either Biotène PBF (BIO) or Listerine Total Care (LTO) mouthwashes, or water (control group; n=5/group). Biofilms were stained with fluorochromes for extracellular polymeric substances, proteins and nucleic acids before imaging with CLSM. Biofilm structural parameters calculated using ISA3D image analysis software were biovolume and mean biofilm thickness. Mixed models statistical analyses compared structural parameters between mouthwash and control groups (SAS software; α=0.05). Volocity software permitted visualization of 3D distributions of overlaid biofilm components (fluorochromes). Results: Mouthwash BIO produced biofilm structures that differed significantly from the control (p<0.05) on both resin composites, whereas LTO did not produce differences (p>0.05) on either product. Conclusions: This methodology efficiently and successfully quantified and compared concurrent 3D distributions of three major components within S. mutans biofilms on relevant substrates, thus overcoming two challenges to simultaneous assessment of biofilm components. This method can also be used to determine the efficacy of antibacterial/antifouling agents against multiple biofilm components, as shown using mouthwashes. Furthermore, this method has broad application because it facilitates comparison of 3D structures/architecture of biofilms in a variety of disciplines.
Biofilms are structured microbial communities that are encapsulated in a self-produced extracellular matrix, and are attached to biological or inert surfaces1. Biofilms represent a common lifestyle for many bacteria, and form by transitioning in stages from free-floating (planktonic) cells to complex multispecies communities. The inherent resistance of biofilms to antimicrobial agents is at the root of many persistent and chronic bacterial infections1,2, as demonstrated by oral biofilms (dental plaque). Cariogenic microorganisms such as mutans streptococci process sucrose and other carbohydrates to produce an extracellular matrix and generate acids that can demineralize tooth structure and cause dental caries. Most biofilm matrices are biopolymers consisting of cellular and extracellular components such as exopolysaccharides (EPS), proteins, and nucleic acids3,4.
Confocal laser scanning microscopy (CLSM), the most widely used technique for fluorescence imaging, has radically transformed optical imaging in biology because it has the ability to collect 3D images of hydrated biological structures without fixation5,6,7. This nondestructive technique involves collecting images of thin sections within a region of interest on the specimen in such a manner that the contribution of out-of-focus light is removed. The quality and resolution of images captured by CLSM is beyond what is achievable using widefield fluorescence microscopy. One major drawback of CLSM is that scanning of images occurs at a slower rate than with widefield microscopy techniques, in which entire images are collected simultaneously5. However, with a widening selection of fluorochromes, lasers, and filters, CLSM has become one of the prevailing techniques for multispectral imaging5,7.
Previous studies have shown CLSM to be a useful tool for examining the structure or architecture of biofilms by using one or two fluorescent tags or stains to provide a better understanding of the distribution of EPS and cells within biofilms, and especially within the extracellular matrix7,8. In theory, fluorescent staining/labeling of multiple components is desirable for exploring the detailed structure and colocalization of cellular and extracellular components within biofilms. However, concurrent analysis of various components within biofilms can be challenging because: 1) selection of fluorescent dyes having minimal spectral overlap is complicated, and 2) quantification of multiple fluorochromes poses a multifactorial problem. Colocalization using multiple fluorochromes requires the use of highly specific stains with minimal spectral interference to avoid any bleed-through effects, which occurs when two fluorochromes have significant overlap in their spectral peak, causing one to be more strongly excited than the other9. Ideally, fluorochromes having excitation spectra that do not overlap would provide the best results, however it is very difficult to find stains that meet this criterion. Instead, the selection of stains is optimized by choosing fluorochromes whose emission spectra have minimal overlap, allowing the stains to be viewed one by one within a limited observation wavelength band9.
Superimposition of fluorescence images is probably the most widely used method for evaluating concurrent distribution of fluorochromes. Colocalization of the various components appears as an overlap of different colors through multiple channels created by the fluorochromes being examined10. The tools for displaying multiple-channel fluorescence images as merged color images are available in most CLSM software and biological image analysis software. Although superimposition of images is useful for spatial evaluation of colocalization, the images can only be examined qualitatively by visual analysis. This provides a limited amount of information, as these representations are generally not helpful for quantifying colocalization under different experimental conditions nor do they determine whether the colocalization exceeds random coincidence11. Very few investigations so far have used quantitative methods to analyze the 3-dimensional structure of biofilms and biofilm components, and even fewer have quantified the effect of antibacterial treatments or antifouling measures on biofilm components.
The objective of this study was to report a methodology for quantification and comparison of the concurrent 3-dimensional distributions of three cellular and extracellular components of biofilms. The method consists of distinct but interconnected steps involving biofilm growth, staining, CLSM imaging of biofilms, biofilm structural analysis and visualization, and statistical analysis of structural parameters. The biofilm growth assay permits biofilm growth on relevant substrates, and produces biofilm structures that are reproducible. The combination of novel simultaneous staining of EPS, proteins and nucleic acid components with the measurement of 3D biofilm structural parameters results in quantifiable distributions of components within biofilms. Statistical analysis of the biofilm structural parameters facilitates evaluation of biofilms under specific experimental conditions (e.g. after treatment with mouthwashes), as will be described in the next section.
1. Preparation of Media and Reagents
2. Specimen Fabrication
3. Biofilm Growth
4. Antibacterial/Mouthwash Treatments
5. Staining
6. Imaging Using Confocal Laser Scanning Microscopy
7. Biofilm Structural Analysis
8. Visualization of Biofilm Structure
9. Statistical Analysis
Representative results for the treatments (mouthwashes) and untreated control group are shown in Table 2, and Figures 1 and 2. Table 2 displays the mean and standard deviation values of biofilm structural parameters biovolume (μm3) and mean biofilm thickness (μm) that were calculated using ISA3D software. Structural parameters of biofilms treated with mouthwash that differed significantly from those of biofilms in the control group (p<0.05) have mean and standard deviation values highlighted in red. The results of the mixed models statistical analyses demonstrated that mouthwash BIO produced biofilm structures that differed significantly from the control (p<0.05) on both resin composites, whereas mouthwash LTO did not produce significant differences (p>0.05) on either resin composite. The results clearly show that the cellular and extracellular biofilm components remaining after the two mouthwash treatments differed. It should also be noted that the S. mutans biofilms grown on the two substrates (PF and TP) differed in 3D structure even though they were grown under similar conditions and both substrates were polished with similar abrasives.
The concurrent distribution of EPS, proteins and nucleic acid within biofilms can be visualized via the 3D reconstructions generated using Volocity software. Figures 1 and 2 demonstrate representative reconstructions of control group biofilms grown on PF and TP resin composites, respectively. The blue stain represents EPS within S. mutans biofilms, the green stain demonstrates nucleic acids, and the red stain shows proteins. The intervening space may be occupied by water or other nonfluorescently labeled biofilms components.
Figure 1. A representative 3D reconstruction of S. mutans biofilm grown on PF resin composite in the control group (not treated with mouthwash). Concurrent overlay of the three stains within a single biofilm permits the simultaneous visualization of EPS (blue stain), nucleic acid (green stain), and protein (red stain) components within S. mutans biofilms. (1 Unit = 24 μm). Click here to view larger figure.
Figure 2. A representative 3D reconstruction of S. mutans biofilm grown on TP resin composite in the control group (not treated with mouthwash). Concurrent overlay of the three stains within a single biofilm permits the simultaneous visualization of EPS (blue stain), nucleic acid (green stain), and protein (red stain) components within S. mutans biofilms. (1 Unit = 24 μm). Click here to view larger figure.
Resin composite | Point 4 | TPH3 | |||
Mouthwash | Component | BV (μm3) | MT (μm) | BV (μm3) | MT (μm) |
Biotène PBF | Nucleic Acids | 279,517±53,291 | 9.32±2.80 | 195,033±42,014 | 7.45±3.70 |
EPS | 344,902±56,386 | 35.22±17.19 | 197,840±62,351 | 9.83±7.26 | |
Proteins | 298,796±62,868 | 54.21±21.65 | 216,033±66,654 | 24.33±39.64 | |
Listerine Total Care | Nucleic Acids | 355,707±110,444 | 26.45±14.21 | 273,296±47,323 | 13.43±2.89 |
EPS | 494,099±180,592 | 64.90± 26.68 | 329,150±47,145 | 34.35±30.32 | |
Proteins | 348,416±161,316 | 58.68±47.28 | 303,150±54,705 | 34.18±41.46 | |
Control (untreated) | Nucleic Acids | 388,375±42,152 | 51.15±40.66 | 327,809±39,400 | 17.08±1.65 |
EPS | 660,448±173,197 | 91.37±74.84 | 363,850±67,612 | 28.33± 15.07 | |
Proteins | 517,274±119,475 | 127.96±73.84 | 353,161±56,518 | 21.17±4.41 |
Table 2. Mean and standard deviation values of Biovolume (BV) and Mean biofilm thickness (MT) of biofilms treated with BIO or LTO, or left untreated (control group). Structural parameters of biofilms treated with mouthwashes that differed significantly from those of biofilms in the control group (p<0.05) have mean and standard deviation values highlighted in red.
The acquisition of CLSM images has to be performed in the manner and format necessary for the quantification of biofilms and for colocalization analysis, such that the distribution of signal intensity in each image is a reliable representation of the distribution of each fluorochrome in the biofilm stack. The signal intensity should be distinguishable from noise and background10,11, unaffected by autofluorescence from the substrate, and having minimal bleed-through due to spectral interference between the fluorochromes used11. Noise is an inevitable limitation of fluorescence microscopy11, and image quality can sometimes be limited for technical or logistical reasons. Identification of fluorochromes with minimal spectral overlap is critical to the success of this method, but can be complicated. Furthermore, the quantification of multiple fluorochromes poses a multifactorial problem. Therefore, it is not surprising that very few investigations have successfully quantified the concurrent distribution of more than two components within the structures of biofilms.
The objective of this study was to report a methodology consisting of distinct but interconnected steps for the quantification and comparison of the concurrent 3-dimensional distributions of three cellular and extracellular components within biofilms. The biofilm growth assay described permits biofilm growth on relevant substrates and produces biofilm structures that are reproducible, as demonstrated by the results reported in Table 1. The combination of novel simultaneous staining of EPS, proteins and nucleic acid components with the measurement of 3D biofilm structural parameters results in quantifiable distributions of components within biofilms. Qualitative visual analysis of the concurrent distribution of EPS, proteins and nucleic acid within the biofilms is possible via the reconstruction of overlaid stains within each biofilm. The ISA3D software12 contains several unique structural parameters such as fractal dimension, homogeneity, and biofilm roughness coefficient in addition to traditionally-measured parameters such as porosity and biofilm thickness to enhance quantification of the 3D structures of biofilms. Statistical analysis of the biofilm structural parameters facilitates relevant comparisons of biofilms under specific experimental conditions such as antibacterial/antifouling efficacy (e.g. after treatment with mouthwashes) or over time (temporal effects).
This methodology efficiently and successfully quantified and compared the concurrent 3D distributions of three major components within S. mutans biofilms that were grown on relevant substrates, thus overcoming two challenges to the simultaneous assessment of biofilm components. This method can also be used to determine the efficacy of antibacterial treatments or antifouling measures against multiple biofilm components, as shown using mouthwashes in this study. Furthermore, the majority of the protocols described above can be replaced with protocols for the fabrication of relevant substrates and biofilm growth assays of relevant microorganisms. Therefore, this method has broad application because it facilitates comparison of 3D structures/architecture of in vitro and in vivo biofilms in a variety of disciplines including the medical, dental, geological and marine sciences.
The authors have nothing to disclose.
Funding for this study was provided by the National Institutes of Health/NIDCR grant 1R15DE019566-01A1. Dr. Jim Henthorn (OUHSC Flow and Image Cytometry Laboratory) is acknowledged for providing technical assistance with confocal laser scanning microscopy. Dr. Fernando Esteban Florez (Department of Dental Materials) is acknowledged for providing technical assistance during the filming of this video.
Name of Reagent | Company | Catalog Number | Comments |
Bacto Agar | Becton, Dickinson and Company | 214010 | |
Bacto Todd Hewitt Broth | Becton, Dickinson and Company | 249240 | |
Yeast Extract, Granulated | EMD Millipore | 1.03753.0500 | |
Bacto Tryptone | Becton, Dickinson and Company | 211705 | |
OmniPur Sucrose | EMD Millipore | 8510 | |
Potassium Chloride, ACS reagent, 99.0-100.5% | Sigma-Aldrich | P3911-500G | |
Potassium Phosphate, monobasic, ≥99.0%, ACS reagent | Sigma-Aldrich | P0662-500G | |
Sodium Chloride | Sigma-Aldrich | S9888-500G | |
Sodium Phosphate, Monobasic, Monohydrate | EMD Millipore | SX0710-1 | |
Tris(hydroxymethyl)aminomethane, 99.8+%, ACS reagent | Sigma-Aldrich | 252859-500G | |
Concanavalin A, Alexa Fluor 647 Conjugate | Invitrogen | C21421 | |
Syto 9 | Invitrogen | S34854 | |
Sypro Red | Invitrogen | S12012 or S6653 | |
Biotène PBF Oral Rinse | GlaxoSmithKline | N/A | |
Listerine Total Care | McNeil-PPC, Inc. | N/A |