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Related Concept Videos

Bacterial Signaling01:30

Bacterial Signaling

Bacterial signaling can occur within bacteria (intracellular) or between bacteria (intercellular). At times, a group of bacteria behaves like a community. To achieve this, they engage in quorum sensing, the perception of higher cell density that causes changes in gene expression. Quorum sensing involves both extracellular and intracellular signaling. The signaling cascade starts with a molecule called an autoinducer (AI). Individual bacteria produce AIs that move out of the bacterial cell...
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Biofilms are complex communities of microorganisms encased in a self-produced extracellular polysaccharide matrix attached to surfaces. These microbial consortia can include single or multiple species, providing enhanced survival benefits by forming organized, multilayered structures.The formation of biofilms occurs through four key stages: attachment, colonization, development, and dispersal.During attachment, free-swimming planktonic cells adhere to a surface, often facilitated by...
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Quorum sensing is a mechanism of bacterial communication that enables coordinated gene expression in response to changes in population density. This facilitates collective behaviors that enhance survival, resource acquisition, and ecological adaptation. This process relies on small signaling molecules called autoinducers that accumulate as bacterial populations grow. When a critical threshold concentration of autoinducers is reached, bacterial cells collectively modify gene expression,...
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Microbial biosensors are analytical devices that utilize living microbes to detect specific substances through measurable signals. These devices consist of two main components: biosensing organisms and signal-transducing elements. Biosensing organisms, such as Escherichia coli or Saccharomyces cerevisiae, are typically housed in multiwell plates connected to transducers, enabling rapid, real-time detection of target analytes.Signal Generation MechanismWhen a target analyte—such as...

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Unveiling bacterial communication with a MATLAB GUI implementing the diffusion-based quorum sensing model.

Urvashi Singh1, Zeeshan Saifi2, Prem Saran Tirumalai3

  • 1Department of Electrical Engineering, Indian Institute of Technology Bombay, Mumbai, India.

Scientific Reports
|June 7, 2024
PubMed
Summary

This study introduces a MATLAB GUI to explore bacterial quorum sensing (QS). The diffusion coefficient significantly impacts QS dynamics and autoinducer concentration more than cell size.

Keywords:
GUIMATLABOrganism and diffusion coefficientQuorum sensing

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Area of Science:

  • Microbiology
  • Computational Biology
  • Biophysics

Background:

  • Bacteria utilize quorum sensing (QS) for community behavior coordination.
  • Understanding QS dynamics is crucial for controlling bacterial populations.

Purpose of the Study:

  • To develop a MATLAB GUI for simulating and analyzing quorum sensing dynamics.
  • To investigate the influence of key parameters on QS initiation and behavior.

Main Methods:

  • Development of a computational framework using MATLAB GUI.
  • Simulation of quorum sensing under varying diffusion coefficients, cell dimensions, production rates, and cell concentrations.
  • Prediction of minimum biofilm thickness for QS initiation.

Main Results:

  • The diffusion coefficient critically influences autoinducer concentration and QS dynamics, more so than cell dimensions.
  • Minimum biofilm thickness required for QS initiation is dependent on the diffusion coefficient.
  • Higher production rates and cell concentrations accelerate QS.

Conclusions:

  • The developed GUI provides a versatile tool for assessing QS, parameter dependencies, and predicting QS initiation conditions.
  • This computational approach aids in understanding bacterial communication and environmental influences on QS.
  • The GUI is valuable for standardizing results and facilitating early QS assessments, particularly for non-biologists.