Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Predicting Escherichia coli's chemotactic drift under exponential gradient.

Sibendu Samanta1, Ritwik Layek1, Shantimoy Kar2

  • 1Department of Electronics and Electrical Communication Engineering, Indian Institute of Technology, Kharagpur WB-721302, India.

Physical Review. E
|January 20, 2018
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Toll-Like Receptor-Mediated Neuroinflammation and Its Role in Neurocognitive Functions.

Current reviews in clinical and experimental pharmacology·2026
Same author

Capillarity in swelling porous media emerges from the local heterogeneities.

Journal of colloid and interface science·2026
Same author

Endocrine-metabolic regulation during the transition period in dairy cows: mechanisms, biomarkers, and emerging diagnostics for subclinical ketosis.

Frontiers in endocrinology·2026
Same author

Breaking the capillary limit: jet-controlled ultrafast droplet rebound on superhydrophobic meshes.

Journal of colloid and interface science·2026
Same author

Exploring composition fluctuations and their dynamics in binary mixtures using coarse-grained molecular dynamics.

The Journal of chemical physics·2026
Same author

Field-Unmasked Surface Charge Enables Programmable Nanofluidics.

Small (Weinheim an der Bergstrasse, Germany)·2026
Same journal

Erratum: Low-dimensional model for adaptive networks of spiking neurons [Phys. Rev. E 111, 014422 (2025)].

Physical review. E·2026
Same journal

Disentangling the effects of many-body forces on depletion interactions.

Physical review. E·2026
Same journal

Charge transport and mode transition in dual-energy electron beam diodes.

Physical review. E·2026
Same journal

Optimization of multisite reactions in complex compartmentalized media.

Physical review. E·2026
Same journal

Origin of geometric cohesion in nonconvex granular materials: Interplay between interdigitation and rotational constraints enhancing frictional stability.

Physical review. E·2026
Same journal

Interaction of walkers with a standing Faraday wave.

Physical review. E·2026
See all related articles

This study presents a robust theoretical model for bacterial chemotaxis, validating it with experiments on Escherichia coli. The model accurately predicts bacterial drift velocity and movement patterns in nutrient gradients.

Area of Science:

  • Microbiology
  • Biophysics
  • Theoretical Biology

Background:

  • Bacteria exhibit chemotaxis, directed movement influenced by chemical signals.
  • Existing models for bacterial chemotaxis show discrepancies with experimental data.
  • Understanding bacterial movement is crucial for various biological and medical applications.

Purpose of the Study:

  • To develop and validate a robust theoretical model for chemotaxis in peritrichous bacteria.
  • To investigate bacterial chemotactic drift under an exponential nutrient gradient.
  • To improve the alignment between theoretical predictions and experimental observations of bacterial motion.

Main Methods:

  • Development of a novel theoretical model for bacterial chemotaxis.
  • Utilizing an exponential nutrient gradient to simulate environmental conditions.

Related Experiment Videos

  • Experimental validation and computational simulations of bacterial movement.

    • Main Results:

    • The proposed theoretical model accurately predicts bacterial chemotactic drift.
    • Experimental and simulation results validate the model's estimations.
    • The model successfully delineates bacterial run time, trajectory, and drift velocity.

    Conclusions:

    • The developed model offers a more accurate framework for understanding bacterial chemotaxis.
    • This research bridges the gap between theoretical knowledge and experimental findings in bacterial motility.
    • The validated model can be applied to predict bacterial behavior in complex chemical environments.