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

Microbial Nutrition01:28

Microbial Nutrition

71
Organisms exhibit remarkable metabolic diversity, categorized based on how they acquire energy and carbon. These strategies enable survival in various ecological niches and are essential for maintaining energy flow and nutrient cycling within ecosystems.Energy and Carbon SourcesOrganisms are classified as phototrophs or chemotrophs based on energy acquisition. Phototrophs use light as their energy source, while chemotrophs rely on oxidizing chemical compounds. Further differentiation arises...
71
Diversity of Archaea I01:30

Diversity of Archaea I

34
Archaea, a domain of single-celled microorganisms, are classified into five major phyla based on genetic and biochemical characteristics: Euryarchaeota, Crenarchaeota, Thaumarchaeota, Korarchaeota, and Nanoarchaeota. Among these, the phylum Euryarchaeota is notable for its remarkable diversity in morphology, metabolism, and ecological adaptations.Morphological and Metabolic DiversityMembers of Euryarchaeota exhibit a variety of cellular shapes, including rods and cocci. Their metabolic pathways...
34
Applications of Molecular Taxonomy01:20

Applications of Molecular Taxonomy

41
Molecular taxonomy has revolutionized the understanding and classification of bacteria, providing precise insights into their diversity, evolutionary relationships, and ecological roles. By utilizing molecular techniques such as DNA sequencing and fingerprinting, researchers have made significant strides in various fields related to bacterial studies.Resolving Taxonomic AmbiguitiesMolecular taxonomy has been instrumental in distinguishing closely related bacterial species initially thought to...
41
Microbial Morphologies01:29

Microbial Morphologies

47
Bacterial and archaeal cells exhibit remarkable diversity in shape and structure, critical in their adaptability and functionality. Among bacteria, the most commonly observed shapes include cocci and bacilli. Cocci are spherical and may exist singly or in groupings such as pairs (diplococci), chains (streptococci), clusters (staphylococci), or tetrads. Bacilli, in contrast, are rod-shaped and can also occur as single cells, in pairs, or chains, depending on their environmental and genetic...
47
Metabolism of Chemolithotrophs01:15

Metabolism of Chemolithotrophs

45
Chemolithotrophs are microorganisms that obtain energy by oxidizing inorganic molecules such as hydrogen gas (H₂), ammonia (NH₃), reduced sulfur compounds (H₂S, S²⁻), and ferrous iron (Fe²⁺). Unlike heterotrophic organisms that rely on organic carbon, chemolithotrophs transfer electrons from these inorganic donors to the electron transport chain (ETC), generating a proton motive force (PMF) that drives ATP synthesis through oxidative phosphorylation.
45
Modern Molecular Taxonomy01:29

Modern Molecular Taxonomy

52
Advancements in molecular biology have revolutionized the identification and characterization of bacteria, with multiple methods leveraging DNA sequencing for enhanced precision. As sequencing technologies improve and costs decline, these approaches are increasingly used in clinical, environmental, and evolutionary studies.Multilocus Sequence Typing (MLST) examines several housekeeping genes, essential chromosomal genes encoding cellular functions, to distinguish strains. Approximately...
52

You might also read

Related Articles

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

Sort by
Same author

Collaborative Care Model for Perinatal Wellness Support Services - Population-Level Upstream Systems Change (COMPASS+): A Hybrid Type 2 Cluster Randomized Trial.

Contemporary clinical trials·2026
Same author

Evidence of dark oxygen production at the abyssal seafloor.

Nature geoscience·2026
Same author

Reproducible Tools and Enhanced Computational Workflows for Batch Effect Evaluation of High-Throughput Data Using BatchQC.

bioRxiv : the preprint server for biology·2026
Same author

Metabolic blueprints of monocultures enable prediction and design of synthetic microbial consortia.

bioRxiv : the preprint server for biology·2026
Same author

Dynamic metabolic modelling of ATP allocation during viral infection.

Journal of the Royal Society, Interface·2026
Same author

Reduced methane emissions in transgenic rice genotypes are associated with altered rhizosphere microbial hydrogen cycling.

Nature communications·2026
Same journal

A human-specific genetic modifier reconfigures large-scale cortical network dynamics underlying behavioral performance.

bioRxiv : the preprint server for biology·2026
Same journal

<i>Staphylococcus aureus</i> uses a eukaryotic-like uridyltransferase to make UDP-GlcNAc for cell wall synthesis.

bioRxiv : the preprint server for biology·2026
Same journal

Dynamic redistribution of eIF4F controls cap-dependent translation initiation.

bioRxiv : the preprint server for biology·2026
Same journal

When does additional information improve accuracy of RNA secondary structure prediction?

bioRxiv : the preprint server for biology·2026
Same journal

Normative brain-state trajectories reveal deviation from healthy aging in Alzheimer's disease.

bioRxiv : the preprint server for biology·2026
Same journal

Noradrenergic infraslow rhythm during sleep is the critical link between heart-rate dynamics and memory consolidation.

bioRxiv : the preprint server for biology·2026
See all related articles

Related Experiment Video

Updated: Jul 19, 2025

Divergence of Root Microbiota in Different Habitats based on Weighted Correlation Networks
09:49

Divergence of Root Microbiota in Different Habitats based on Weighted Correlation Networks

Published on: September 25, 2021

4.4K

Metabolic complexity drives divergence in microbial communities.

Michael Silverstein1,2, Jennifer M Bhatnagar1,3, Daniel Segrè1,2,3,4

  • 1Bioinformatics Program, Boston University, Boston, MA.

Biorxiv : the Preprint Server for Biology
|August 14, 2023
PubMed
Summary
This summary is machine-generated.

Microbial communities converge in simple environments but diverge as complexity increases, a phenomenon called the divergence-complexity effect. This finding is key for microbiome engineering and understanding ecosystem functions.

More Related Videos

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing
11:22

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing

Published on: October 15, 2019

28.3K
Workflow Based on the Combination of Isotopic Tracer Experiments to Investigate Microbial Metabolism of Multiple Nutrient Sources
12:47

Workflow Based on the Combination of Isotopic Tracer Experiments to Investigate Microbial Metabolism of Multiple Nutrient Sources

Published on: January 22, 2018

9.5K

Related Experiment Videos

Last Updated: Jul 19, 2025

Divergence of Root Microbiota in Different Habitats based on Weighted Correlation Networks
09:49

Divergence of Root Microbiota in Different Habitats based on Weighted Correlation Networks

Published on: September 25, 2021

4.4K
Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing
11:22

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing

Published on: October 15, 2019

28.3K
Workflow Based on the Combination of Isotopic Tracer Experiments to Investigate Microbial Metabolism of Multiple Nutrient Sources
12:47

Workflow Based on the Combination of Isotopic Tracer Experiments to Investigate Microbial Metabolism of Multiple Nutrient Sources

Published on: January 22, 2018

9.5K

Area of Science:

  • Microbial Ecology
  • Systems Biology
  • Metabolic Engineering

Background:

  • Microbial community composition is influenced by environmental metabolites.
  • Principles governing community convergence or divergence are not fully understood.
  • This knowledge gap impacts the feasibility of microbiome engineering.

Conclusions:

  • The hierarchical structure of metabolism is fundamental to community assembly.
  • The divergence-complexity effect explains community assembly principles.
  • Understanding this effect aids microbiome engineering by identifying environments supporting desired ecosystem functions.