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

Comparing Mitochondrial, Chloroplast, and Prokaryotic Genomes02:16

Comparing Mitochondrial, Chloroplast, and Prokaryotic Genomes

12.3K
The present-day mitochondrial and chloroplast genomes have retained some of the characteristics of their ancestral prokaryotes and also have acquired new attributes during their evolution within eukaryotic cells. Like prokaryotic genomes, mitochondrial and chloroplast genomes neither bind with histone-like proteins nor show complex packaging into chromosome-like structures, as observed in eukaryotes. Unlike mitotic cell divisions observed in eukaryotic cells, mitochondria and chloroplasts...
12.3K
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

5.7K
Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
5.7K
Genome Size and the Evolution of New Genes03:21

Genome Size and the Evolution of New Genes

7.9K
While every living organism has a genome of some kind (be it RNA, or DNA), there is considerable variation in the sizes of these blueprints. One major factor that impacts genome size is whether the organism is prokaryotic or eukaryotic. In prokaryotes, the genome contains little to no non-coding sequence, such that genes are tightly clustered in groups or operons sequentially along the chromosome. Conversely, the genes in eukaryotes are punctuated by long stretches of non-coding sequence.
7.9K
The Evidence for Evolution02:55

The Evidence for Evolution

42.7K
Genetic variations accumulating within populations over generations give rise to biological evolution. Evolutionary changes can result in the formation of novel varieties and entire new species. These changes are responsible for the diverse forms of life inhabiting the planet. The evidence for evolution suggests that all living organisms descended from common ancestors.
42.7K
Overview of Metabolism01:40

Overview of Metabolism

29.8K
Living cells constantly carry out various chemical reactions which are necessary for their proper functioning. These reactions are interlinked to one another via multiple pathways. The collection of these chemical reactions is known as metabolism.
Plant Metabolism
Sunlight, the primary source of energy in plants, is first absorbed by the chlorophyll pigments present in their leaves. Plants then use this energy to carry out photosynthesis, where water is oxidized into oxygen and carbon dioxide...
29.8K
Gene Evolution - Fast or Slow?02:05

Gene Evolution - Fast or Slow?

7.1K
The genomes of eukaryotes are punctuated by long stretches of sequence which do not code for proteins or RNAs. Although some of these regions do contain crucial regulatory sequences, the vast majority of this DNA serves no known function. Typically, these regions of the genome are the ones in which the fastest change, in evolutionary terms, is observed, because there is typically little to no selection pressure acting on these regions to preserve their sequences.
In contrast, regions which code...
7.1K

You might also read

Related Articles

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

Sort by
Same author

Evidence of dark oxygen production at the abyssal seafloor.

Nature geoscience·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 author

hypeR-GEM: connecting metabolite signatures to enzyme-coding genes via genome-scale metabolic models.

bioRxiv : the preprint server for biology·2025
Same author

Inorganic nitrogen and organic matter jointly regulate ectomycorrhizal fungi-mediated iron acquisition.

The New phytologist·2025
Same journal

Unravelling the cause of an unprecedented harmful algal bloom in South Australia.

Nature ecology & evolution·2026
Same journal

A catastrophic marine mortality event caused by a complex algal bloom including the brevetoxin producer Karenia cristata.

Nature ecology & evolution·2026
Same journal

Rethinking temperate coral restoration beyond tropical paradigms.

Nature ecology & evolution·2026
Same journal

Observed core-to-transition biodiversity gradient may be a statistical artefact.

Nature ecology & evolution·2026
Same journal

Reply to: Observed core-to-transition biodiversity gradient may be a statistical artefact.

Nature ecology & evolution·2026
Same journal

Anolis shrevei.

Nature ecology & evolution·2026
See all related articles

Related Experiment Video

Updated: Jun 22, 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

4.3K

Metabolic complexity drives divergence in microbial communities.

Michael R Silverstein1,2, Jennifer M Bhatnagar1,3, Daniel Segrè4,5,6,7

  • 1Bioinformatics Program, Faculty of Computing and Data Science, Boston University, Boston, MA, USA.

Nature Ecology & Evolution
|July 2, 2024
PubMed
Summary
This summary is machine-generated.

Microbial communities converge in simple environments but diverge as metabolic complexity increases. This divergence-complexity effect is driven by community diversity and specialist microbes, impacting microbiome engineering.

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

27.9K
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

9.4K

Related Experiment Videos

Last Updated: Jun 22, 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

4.3K
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

27.9K
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

9.4K

Area of Science:

  • Microbiology
  • Ecology
  • Systems Biology

Background:

  • Microbial communities are influenced by environmental metabolites.
  • The principles governing community convergence or divergence are not fully understood.
  • This knowledge gap poses challenges for microbiome engineering.

Purpose of the Study:

  • To investigate the longitudinal assembly dynamics of microbial communities.
  • To understand how metabolic complexity affects community convergence and divergence.
  • To explore the feasibility of microbiome engineering.

Main Methods:

  • Studied natural microbial communities in laboratory conditions.
  • Varied environmental metabolic complexity.
  • Analyzed community composition and diversity.
  • Developed an ecological model of community dynamics.

Main Results:

  • Communities converged in metabolically simple conditions.
  • Communities diverged in composition with increasing metabolic complexity (divergence-complexity effect).
  • Divergence was driven by community diversity and specialist taxa degrading complex metabolites.
  • An ecological model successfully recapitulated experimental observations.

Conclusions:

  • The hierarchical structure of metabolism and cross-feeding are key drivers of microbial community assembly.
  • The divergence-complexity effect explains how environments can support multiple community states.
  • Findings provide insights for microbiome engineering and predicting ecosystem functions.