A Method to Quantify Biofilms in Object Glass Using ImageJ

Authors

  • Arief Heru Faculty of Medicine, University of Islam Malang, Malang 65144, Indonesia
  • Reza Hakim Faculty of Medicine, University of Islam Malang, Malang 65144, Indonesia
  • Hanggia Primadita Faculty of Medicine, Brawijaya University, Malang 65145, Indonesia
  • Rio Risandiansyah Faculty of Medicine, University of Islam Malang, Malang 65144, Indonesia

DOI:

https://doi.org/10.55227/ijhet.v4i5.507

Keywords:

Biofilm, ImageJ, Direct Microscopic Observation, Quantification

Abstract

One method to observe biofilms is by inoculating bacteria on glass slides and observed for the presence of large structures (microcolonies) and small structures (clusters, aggregates, or single cells) under a microscope. Analysis of these structures using image processing software may provide a method to quantify biofilm production and degradation in glass slides. In this study, we use ImageJ to quantify the number and area percentage of microbial structures observable on a slide. This study is an experimental in vitro study. Biofilm production was done by submerging slides in petri dishes filled with Brain Heart Infusion with 2% sucrose (w/v) and inoculating it with bacteria. The petri dishes were incubated undisturbed for 48 hours at 37°C (n=3). Afterwards, the slides were removed and submerged in distilled water (Group 1) or detergent (Group 2) for 5 minutes before staining with 0.1% crystal violet and rewashed. The slides were then observed under a light microscope at 1000x and images from five fields of view were collected. ImageJ was then used to count the number of microcolonies (>15.000 μm2), aggregate cells (200 – 14.999 μm2), and single cells or cell clusters (1 – 199 μm2), and their area percentage. Welch’s T-Test was performed using JASP version 0.18.3. Observation of slides shows microcolonies to be formed in Group 1, and no or little in Group 2. Based on ImageJ calculation, slides treated with distilled water had a biofilm consisting of an average 4.60 ± 2.41 microcolony number and an average percentage area of 39.97 ± 9.99%, 120.47 ± 32.31 (8.96 ± 3.19%) cell aggregates, and 415.06 ± 139.85 (1.39 ± 0.33%) single cells and cell clusters. Detergent application possibly showed biofilm breakdown, with a significant (p<0.001) reduction in microcolony percentage area to up to 99% (0.33 ± 0.68% remaining) and increased single cell number and percentage area to 1,754.93 ± 689.52 (5.27 ± 0.49%). ImageJ can be a valuable tool to quantify biofilm production in glass slides based on the number and percentage area of microcolonies, cell aggregates, and single cells or cell clusters.

Downloads

Download data is not yet available.

References

Bakkiyaraj, D., Sritharadol, R., Padmavathi, A. R., Nakpheng, T., & Srichana, T. (2017). Anti-biofilm properties of a mupirocin spray formulation against Escherichia coli wound infections. Biofouling, 33(7), 591–600. https://doi.org/10.1080/08927014.2017.1337100

Coffey, B. M., & Anderson, G. G. (2014). Biofilm Formation in the 96-Well Microtiter Plate. In A. Filloux & J.-L. Ramos (Eds.), Pseudomonas Methods and Protocols (Vol. 1149, pp. 631–641). Springer New York. https://doi.org/10.1007/978-1-4939-0473-0_48

Dertli, E., Mayer, M. J., & Narbad, A. (2015). Impact of the exopolysaccharide layer on biofilms, adhesion and resistance to stress in Lactobacillus johnsonii FI9785. BMC Microbiology, 15, 8. https://doi.org/10.1186/s12866-015-0347-2

Dexter, A. M., & Scott, J. B. (2019). Airway management and ventilator-associated events. Respiratory Care, 64(8), 986–993. https://doi.org/10.4187/respcare.07107

Di Domenico, E. G., Oliva, A., & Guembe, M. (2022). The current knowledge on the pathogenesis of tissue and medical device-related biofilm infections. Microorganisms, 10(7), 1259. https://doi.org/10.3390/microorganisms10071259

Giordani, B., Naldi, M., Croatti, V., Parolin, C., Erdoğan, Ü., Bartolini, M., & Vitali, B. (2023). Exopolysaccharides from vaginal lactobacilli modulate microbial biofilms. Microbial Cell Factories, 22(1), 45. https://doi.org/10.1186/s12934-023-02053-x

Katsipis, G., Tsalouxidou, V., Halevas, E., Geromichalou, E., Geromichalos, G., & Pantazaki, A. A. (2021). In vitro and in silico evaluation of the inhibitory effect of a curcumin-based oxovanadium (IV) complex on alkaline phosphatase activity and bacterial biofilm formation. Applied Microbiology and Biotechnology, 105(1), 147–168. https://doi.org/10.1007/s00253-020-11004-0

Mombeshora, M., Chi, G. F., & Mukanganyama, S. (2021). Antibiofilm activity of extract and a compound isolated from Triumfetta welwitschii against Pseudomonas aeruginosa. Biochemistry Research International, 2021(1). https://doi.org/10.1155/2021/9946183

Osland, A. M., Oastler, C., Konrat, K., Nesse, L. L., Brook, E., Richter, A. M., Gosling, R. J., Arvand, M., & Vestby, L. K. (2023). Evaluation of disinfectant efficacy against biofilm-residing wild-type Salmonella from the porcine industry. Antibiotics, 12(7), 1189. https://doi.org/10.3390/antibiotics12071189

Paula, A. J., Hwang, G., & Koo, H. (2020). Dynamics of bacterial population growth in biofilms resemble spatial and structural aspects of urbanization. Nature Communications, 11(1), 1354. https://doi.org/10.1038/s41467-020-15165-4

Raissa, G., Waturangi, D. E., & Wahjuningrum, D. (2020). Screening of antibiofilm and anti-quorum sensing activty of Actinomycetes isolates extracts against aquaculture pathogenic bacteria. BMC Microbiology, 20(1), 343. https://doi.org/10.1186/s12866-020-02022-z

Rubi, H., Mudey, G., & Kunjalwar, R. (2022). Catheter-associated urinary tract infection (CAUTI). Cureus, 14(10), e30385. https://doi.org/10.7759/cureus.30385

Rueden, C. T., Schindelin, J., Hiner, M. C., DeZonia, B. E., Walter, A. E., Arena, E. T., & Eliceiri, K. W. (2017). ImageJ2: ImageJ for the next generation of scientific image data. BMC Bioinformatics, 18(1), 529. https://doi.org/10.1186/s12859-017-1934-z

Ruhal, R., & Kataria, R. (2021). Biofilm patterns in gram-positive and gram-negative bacteria. Microbiological Research, 251, 126829. https://doi.org/10.1016/j.micres.2021.126829

Schilcher, K., & Horswill, A. R. (2020). Staphylococcal biofilm development: structure, regulation, and treatment strategies. Microbiology and Molecular Biology Reviews, 84(3), e00026-19. https://doi.org/10.1128/MMBR.00026-19

Schulze, K., López, D. A., Tillich, U. M., & Frohme, M. (2011). A simple viability analysis for unicellular cyanobacteria using a new autofluorescence assay, automated microscopy, and ImageJ. BMC Biotechnology, 11(1), 118. https://doi.org/10.1186/1472-6750-11-118

JASP, T. (2024). JASP. https://jasp-stats.org/

Vandeplassche, E., Coenye, T., & Crabbé, A. (2017). Developing selective media for quantification of multispecies biofilms following antibiotic treatment. PLOS ONE, 12(11), e0187540. https://doi.org/10.1371/journal.pone.0187540

Yan, J., & Bassler, B. L. (2019). Surviving as a community: antibiotic tolerance and persistence in bacterial biofilms. Cell Host & Microbe, 26(1), 15–21. https://doi.org/10.1016/j.chom.2019.06.002

Young, K., & Morrison, H. (2018). Quantifying microglia morphology from photomicrographs of immunohistochemistry prepared tissue using ImageJ. Journal of Visualized Experiments, 136, e57648. https://doi.org/10.3791/57648-v

Downloads

Published

2026-01-28

How to Cite

Heru, A., Hakim, R., Primadita, H., & Risandiansyah, R. (2026). A Method to Quantify Biofilms in Object Glass Using ImageJ. International Journal of Health Engineering and Technology, 4(5). https://doi.org/10.55227/ijhet.v4i5.507