Biofilms formed on tooth surfaces are highly complex and structured. Microbial communities enmeshed in an extracellular matrix, which are exposed to constant environmental challenges. The overall goal here is to show two specific components of an analytical toolbox designed to facilitate structural and molecular studies, considering the complex nature of oral biofilms by combining a novel fluorescence imaging technique with custom made software for data processing and analysis.
This is accomplished by first selecting specific assays for biofilm, transcriptome and structure analysis, including a new confocal imaging approach for simultaneous visualization of EPS and bacteria. The second step of the procedure is to collect the raw data from the bioassays. The third step is to process the raw data using specific software, including the newly developed duo stat for colocalization analysis.
The final step is to analyze the process data, including the use of microarray data mining and organization software microarray, data visualizer, or MDV. Ultimately, results can be obtained that show how oral pathogens change their transcriptome and the architecture of the biofilms in response to complex diet, host microbial interactions using our uniquely integrated analytical toolbox, providing a more comprehensive biofilm analysis and data interpretation. Hi, my name is Michelle Kuh, an associate professor in the center, Foral biology here at Universal of Rochester Medical Center.
Today, we present an analytical toolbox for biofilm analysis. This toolbox can help answer key questions in the field of biofilm research as how the biofilm cells are structured, arranged with extracellular matrix and how they respond to complex environmental challenges at Transcriptomic level. My name is Jean, she, I'm a postdoc fellow in Dr.Ks lab.
Today I'm going to demonstrate the imaging part of our toolbox. Hi, I'm Aise Klein. I'm research assistant professor at Dr.Ks lab.
Today, I will present the MDV software for microray data analysis. In this procedure, saliva coated hydroxy appetite discs are used as tooth surface surrogates on which biofilms are grown. First, add 2.8 milliliters of culture medium inoculated with S mutants in each well of a 24 well plate protecting the plate from light at dextrin conjugated LOR 6 47 dye to each well to a final concentration of one micromolar and pipette up and down several times to mix the dye into the culture medium.
Next, using sterile forceps dip, wash the sterile saliva coated hydroxyapatite discs twice in sterile AB buffer to remove any excess saliva or unbound salivary components. Then place the discs vertically in the dye supplemented culture medium, ensuring that each disc is fully submerged. Cover the plate in aluminum foil and incubate it at 37 degrees Celsius in a 5%carbon dioxide incubator for 20 hours to allow the biofilms to form and the conjugated texture to be incorporated into the exo polysaccharides produced by the bacterial cells.
To label the bacterial cells first, prepare a 24 well plate with 2.8 milliliters of sterile milli Q water per well. Add 1.5 microliters of cyto nine dye to each well to a final concentration of one micromolar and protect the plate from light. Once the biofilm has formed, remove the plate containing the discs from the incubator dip.
Wash each disc in a solution of 0.89%sodium chloride. Then transfer them to the new plate containing the cyto nine dye. Cover the plate in aluminum foil and incubate it for 30 minutes at room temperature.
Once the cells have been stained dip, wash the biofilms and sodium chloride as before. Then using forceps, release the biofilms from the wire into a Petri dish containing sodium chloride. Wrap the Petri dish with aluminum foil.
The biofilms are now ready for visualization by confocal microscopy using a laser scanning confocal microscope. Scan each biofilm at five to 10 randomly selected positions and generate Z series at each position. To allow 3D reconstructions, open the confocal images and process them using a mirror software.
This three dimensional rendering of confocal images produced using the program, Amira shows an S mutants biofilm formed on the apathetic surface using the demonstrated procedure. Bacterial cells and micro colonies are visible in green and are embedded in the biofilm matrix containing exo polysaccharides. In red, a closeup view of a selected area can be generated, which illustrates the specific bacteria EPS structural relationship at the micro scale.
Use the duos stat program to quantify the amount of colocalization of separate biofilm components such as the bacteria and the exo polysaccharides. First, set up the path of the newly developed duo stat in MATLAB version 5.1 and open the image folders containing the Z series images of the two biofilm components. Next, choose two channels that will be correlated and analyzed.
The two image stacks must have identical pixel sizes in all dimensions and the same number of images in each stack. Set the thresholds for each channel and follow the instructions in the software interface and input the data into the data processing file for analysis. This figure shows how duo stack quantitatively interprets the spatial relationship between bacteria and DBS.
Within the biofilm Duo stack calculates the vertical distribution of bacteria and DPS from disc surface to fluid phase as seen here in the green line for bacteria and the red line for EPS. It also calculates the colocalization of bacteria and DPS across the biofilm thickness. As shown in the yellow line, the data show higher proportions of EPS than bacteria across the biofilm depth, and most of the bacterial cells are associated with EPS, especially from the middle layers and up Duo stat with 3D rendering provides enhanced understanding of the structural organization and interaction of bacteria and DPS in biofilms.
In order to ensure that high quality RNA is obtained from biofilms, we recommend that RNA extraction be performed according to the biofilm specific protocol described in the article by Curian KU published in 2007. In the journal, analytical biochemistry standard protocols are used for CD NA microarray preparation and quantitative realtime PCR assays. In order to facilitate analysis of the large data sets generated by microarray experiments, we have designed a data mining and organization software, the microarray data visualizer or MDV, which is available online at www.oralgen.anl.gov.
Before submitting the data to MDV carry out statistical analysis like a paired T-test with random variance model using the BRB array tool software available online with a cutoff P value of 0.001 for class comparison. In this example analysis of s mutton's, biofilms grown in three distinct sugar concentrations and four time points were performed. Paired comparisons were performed originating three BRB files condition a 0.5%sucrose plus 1%starch versus 1%sucrose condition B 0.5%sucrose plus 1%starch versus 0.5%sucrose and condition C 0.5%sucrose versus 1%sucrose.
This panel represents the number of genes detected as differentially expressed in each condition and time point evaluated by standard class comparison using the BRB array tool, which results in a large number of genes named BRB raw data. For demonstration of MDV, we will focus on time point 30 hours using Excel. Convert the BRB raw data into MDV tab limited text files.
Be sure to remove all letters that come with the gene locus tab number, for example in the name SMU dot 1432 C.Delete the letter C, open MDV. Open the file menu and choose select annotation source. Select the flat file option when a dialogue box appears.
Use the browse buttons to choose the files that contain annotations for gene ontology number pathway functional classification data and gene name. Go to file and import each of the files converted into the MDV format. Each file represents an experimental condition.
Compare the genes expressed in each experimental condition A versus B versus C.In this example, using the Venn diagram feature. For this demonstration, we focus on differentially expressed genes that are uniquely related to influences of sucrose and starch in combination. The Venn diagram based feature is used to visualize the number of unique and shared genes expressed under these different conditions and assists us in identifying those to be selected for further analysis.
Here we select only the genes differentially expressed that are unique in condition A and or B, but not those detected in C as shown in gray as shown here. MDV greatly reduced the total number of genes to be analyzed, and at the same time filtered out the non-relevant genes for the experimental case. From the file menu, choose the export option to save the data.
As tab limited files, the files may then be opened in Excel where the data output can be organized and converted into the desired graphical displays. The data organization in Excel allows the graphical display of MDV output. This graph shows an overview of the differential expression of unique functional subsets of genes that are affected by the combination of starch and sucrose at distinct stages of biofilm development.
The influences on the S mutants transcriptome are more pronounced at 30 hours of biofilm development than at other time points. The output helped us to identify precisely specific functional subsets of genes that are relevant for our working hypothesis, considering the temporal effects which facilitated the gene selection and further validation process. Following this procedure, biochemical and proteomic methods can be also performed to answer additional questions such as what are the specific physiological and metabolic responses of the organisms within biofilms.
Such a comprehensive and integrated analysis would certainly help to further understand how the biofilms modulate pathogenicity in indoor cavity, a highly dynamic and complex environment. For more details, please check the PDF file attached to this video article.
