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 Concept Videos

Population Growth00:57

Population Growth

26.2K
Population size is dynamic, increasing with birth rates and immigration, and decreasing with death rates and emigration. In ideal conditions with unlimited resources, populations can increase exponentially, which plots as a J-shaped growth rate curve of population size against time. This type of curve is characteristic of newly-introduced invasive species, or populations that have suffered catastrophic declines and are rebounding.
26.2K
Diversity of Protists IV01:27

Diversity of Protists IV

516
Amoebozoa represent a diverse group of terrestrial and aquatic protists that utilize lobe-shaped pseudopodia for locomotion and feeding. This characteristic differentiates them from the Rhizaria, which possess threadlike pseudopodia. The primary classifications within Amoebozoa include gymnamoebas, entamoebas, and the plasmodial and cellular slime molds. Phylogenetic evidence indicates that Amoebozoa diverged from a lineage that ultimately gave rise to fungi and animals.Gymnamoebas and...
516
Exponential Equations for Modeling Growth02:33

Exponential Equations for Modeling Growth

17
Exponential models are essential for describing rapid, multiplicative changes in natural systems, such as population growth. When a population doubles at regular intervals, the process can be modeled using a suitable base. For instance, a bacterial culture that doubles every three hours follows the model n(t)=n0⋅2t/3, where n(t) is the population at the time t.A more general model uses the natural base e, especially for continuous growth. This takes the form n(t)=n0⋅ert, where r is...
17
Bacterial Phylum Tenericutes01:24

Bacterial Phylum Tenericutes

186
The phylum Tenericutes, which includes the single class Mollicutes, comprises bacteria that lack cell walls. The term "Mollicutes" derives from the Latin word mollis, meaning "soft." These organisms are among the smallest known and are commonly referred to as mycoplasmas due to the prominence of the genus Mycoplasma, which includes well-known human pathogens. Despite their inability to stain gram-positively (a result of their lack of cell walls), mycoplasmas are phylogenetically related to the...
186
Diversity of Protists III01:27

Diversity of Protists III

498
Rhizaria are a diverse group of unicellular protists characterized by their threadlike cytoplasmic extensions known as pseudopodia. These structures aid in both locomotion and feeding, giving Rhizaria an amoeboid appearance. Their amoeboid morphology once led to taxonomic confusion, but molecular phylogenetics has clarified their evolutionary placement and emphasized their shared use of pseudopodia despite divergent lineages.This clade comprises diverse lineages such as Chlorarachniophyta,...
498
Gene Regulation in Microbial Communities: Quorum Sensing01:28

Gene Regulation in Microbial Communities: Quorum Sensing

169
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,...
169

You might also read

Related Articles

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

Sort by
Same author

Incidental Renal Cell Carcinoma in an Active-Duty Fighter Pilot.

Aerospace medicine and human performance·2026
Same author

Segmentation-free analysis of live-cell imaging data reveals how T cell modifications influence cancer cell aggregation dynamics.

Scientific reports·2026
Same author

Recognising intoxication in healthcare: evidence, challenges, and implications.

Addiction science & clinical practice·2026
Same author

The effect of Montmorency tart cherry consumption on athletic performance and post-exercise recovery in healthy adults: a scoping review.

Frontiers in nutrition·2026
Same author

Higher disease burden and greater small fibre impairment in women with painful diabetic neuropathy.

Pain reports·2026
Same author

Not Just Visitors: A Sibling's Story.

Nursing in critical care·2026
Same journal

Ruliological Resilience: Pattern Restoration and Robustness in Wolfram Patterns. A Basis for Regeneration, Not Just in Cone Shells?

Bio Systems·2026
Same journal

The quantum-to-classical transducer: A thermodynamic and quantum mechanical framework for the emergence of bioenergetics.

Bio Systems·2026
Same journal

Forward-backward gene expression binarization for boolean state inference over a known regulatory network.

Bio Systems·2026
Same journal

Partial-label metric ceilings for evaluating gene regulatory networks inferred from single-cell foundation models.

Bio Systems·2026
Same journal

The impedance mismatch theory: A non-equilibrium thermodynamic framework for a shared energetic stress pathway in neurodegeneration.

Bio Systems·2026
Same journal

Immune signal-status misclassification: A theoretical framework for biological status assignment and failed status resolution.

Bio Systems·2026
See all related articles

Related Experiment Video

Updated: Oct 28, 2025

Monitoring Spatial Segregation in Surface Colonizing Microbial Populations
07:40

Monitoring Spatial Segregation in Surface Colonizing Microbial Populations

Published on: October 29, 2016

11.3K

Complex population dynamics in a spatial microbial ecosystem with Physarum polycephalum.

Leo Epstein1, Zeth Dubois2, Jessica Smith2

  • 1University of Idaho, Moscow, ID, 83844, USA; Max Delbrück Center for Molecular Medicine, Berlin, 13125, Germany.

Bio Systems
|July 16, 2021
PubMed
Summary
This summary is machine-generated.

The slime mold Physarum polycephalum and red yeast exhibit inverse growth dynamics. P. polycephalum may sustain itself by using yeast as a periodic food source, creating a unique feeding strategy.

Keywords:
Microbial ecosystemPhysarum polycephalumPopulation dynamicsSlime mold

More Related Videos

Generating Controlled, Dynamic Chemical Landscapes to Study Microbial Behavior
10:07

Generating Controlled, Dynamic Chemical Landscapes to Study Microbial Behavior

Published on: January 31, 2020

6.3K
Time-lapse Imaging of Bacterial Swarms and the Collective Stress Response
06:26

Time-lapse Imaging of Bacterial Swarms and the Collective Stress Response

Published on: May 23, 2020

8.5K

Related Experiment Videos

Last Updated: Oct 28, 2025

Monitoring Spatial Segregation in Surface Colonizing Microbial Populations
07:40

Monitoring Spatial Segregation in Surface Colonizing Microbial Populations

Published on: October 29, 2016

11.3K
Generating Controlled, Dynamic Chemical Landscapes to Study Microbial Behavior
10:07

Generating Controlled, Dynamic Chemical Landscapes to Study Microbial Behavior

Published on: January 31, 2020

6.3K
Time-lapse Imaging of Bacterial Swarms and the Collective Stress Response
06:26

Time-lapse Imaging of Bacterial Swarms and the Collective Stress Response

Published on: May 23, 2020

8.5K

Area of Science:

  • Microbiology and Ecology
  • Investigating microbial interactions within a defined spatial ecosystem.

Background:

  • Understanding interspecies dynamics is crucial for ecological studies.
  • Physarum polycephalum (a slime mold) and red yeast interactions are not well-documented in spatial contexts.

Purpose of the Study:

  • To analyze the population dynamics between P. polycephalum and red yeast.
  • To quantify species interactions and growth rates over time.
  • To explore potential feeding strategies and ecological relationships.

Main Methods:

  • Week-long imaging experiments to observe species interactions.
  • Advanced image analysis using semantic segmentation for population density quantification.
  • Monitoring of growth rates and successional dynamics.

Main Results:

  • An inverse relationship was observed between the growth rates of P. polycephalum and red yeast.
  • Successional and oscillatory dynamics were captured between the two species.
  • P. polycephalum demonstrated positive growth when yeast growth was negative, and vice versa.

Conclusions:

  • P. polycephalum may employ a sustainable feeding strategy by utilizing yeast as a periodic food source via slime trails.
  • This research quantifies complex ecological dynamics in spatial ecosystems.
  • Opens new avenues for studying P. polycephalum population dynamics and interspecies relationships.