Colony Biofilm
Colony Biofilm - Related Videos
03:54
Preparation of Bacterial Biofilm Colonies for Morphological Analysis
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2026
Source: Bucher, T., et. al., Methodologies for Studying B. subtilis Biofilms as a Model for Characterizing Small Molecule Biofilm Inhibitors. J. Vis. Exp.(2016)This video demonstrates the preparation of mature bacterial biofilm colonies for high-resolution imaging. It covers fixation, dehydration, mounting, and metal coating steps to preserve and visualize biofilm morphology.
11:17
A Semi-quantitative Approach to Assess Biofilm Formation Using Wrinkled Colony Development
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Cited by 32 •
2012
We provide a simple, semi-quantitative method to investigate biofilm formation in vitro. This method takes advantage of the Zeiss stemi 2000-C Dissecting Microscope (with camera attachment) to monitor both the timing and pattern of biofilm formation, as assessed by the development of wrinkled colonies.
07:16
Development of a Polymicrobial Colony Biofilm Model to Test Antimicrobials in Cystic Fibrosis
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Cited by 3 •
2024
This methodology allows for the establishment of a polymicrobial biofilm model in cystic fibrosis for antimicrobial sensitivity testing in research and clinical laboratories. This model provides accurate and reliable results over a range of outputs.
10:17
Methodologies for Studying B. subtilis Biofilms as a Model for Characterizing Small Molecule Biofilm Inhibitors
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Cited by 28 •
2016
This study presents the development of reproducible methodologies to study biofilm inhibitors and their effects on Bacillus subtilis multicellularity.
09:03
Growth of Mycobacterium tuberculosis Biofilms
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Cited by 79 •
2012
Mycobacterium tuberculosis forms drug tolerant biofilms when cultured in certain conditions. Here we describe methods for culturing M. tuberculosis biofilms and determining the frequency of drug tolerant persisters. These protocols will be useful for further studies into the mechanisms of drug tolerance in M. tuberculosis.
FAQs
As the colony grows, restricted diffusion produces chemical and physiological gradients rather than uniform conditions. Cells in different locations therefore experience distinct local environments, which can alter gene expression across the community. This spatial variation helps researchers examine how the same microbial population displays different genetic responses within one structured system.
Matrix production and cell-to-cell signaling help shape the conditions in which neighboring cells grow and respond. Genetic changes affecting either process can influence adhesion, community organization, or stress responses. Studying these components allows researchers to connect regulatory networks with traits that emerge at the level of the entire microbial community.
Researchers compare how mutations alter traits such as adhesion, matrix production, stress responses, or antibiotic tolerance. These comparisons link particular genetic changes with measurable community-level effects. The approach also helps distinguish the contributions of individual genes from broader regulatory networks that coordinate behavior as cells grow together.
Spatial gene expression shows where particular genetic programs are active within the colony, rather than treating all cells as equivalent. Researchers can use these patterns to relate local conditions and physiological gradients to regulatory responses. This reveals how position within the community contributes to functional differences among genetically related cells.
Such experiments can connect genotype with community-level traits and identify how regulatory networks influence organized growth. They may also reveal spatial patterns of expression, changes in stress responses, and differences in antibiotic tolerance. Together, these outcomes show how genetic variation affects both individual cellular behavior and the properties of the population.
Researchers examine whether mutations or regulatory changes alter the community's response to antibiotics and whether tolerance varies across spatially distinct regions. Because limited diffusion and local physiological conditions influence gene expression, the system helps relate genetic control to uneven stress responses. This supports broader studies of antimicrobial resistance and population adaptation.
Their structured organization lets researchers study how microbial populations respond to changing conditions while linking those responses to genetic regulation. Findings can clarify how community traits develop in infection-related settings, how stress responses are organized, and how populations adapt over time. The model therefore connects molecular genetics with clinically and ecologically relevant behavior.