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

Transcription Attenuation in Prokaryotes02:42

Transcription Attenuation in Prokaryotes

16.1K
Transcriptional attenuation occurs when RNA transcription is prematurely terminated due to the formation of a terminator mRNA hairpin structure.  Bacteria use these hairpins to regulate the transcription process and control the synthesis of several amino acids including histidine, lysine, threonine, and phenylalanine. Transcription attenuation takes place in the non-coding regions of mRNA.
There are several different mechanisms used to attenuate transcription. In ribosome mediated...
16.1K
Bacterial RNA Polymerase00:43

Bacterial RNA Polymerase

8.9K
8.9K
Bacterial Transcription01:53

Bacterial Transcription

29.6K
RNA polymerase (RNAP) carries out DNA-dependent RNA synthesis in both bacteria and eukaryotes. Bacteria do not have a membrane-bound nucleus. So, transcription and translation occur simultaneously, on the same DNA template.
Transcription can be divided into three main stages, each involving distinct DNA sequences to guide the polymerase. These are:
29.6K
Transcription in Prokaryotes01:28

Transcription in Prokaryotes

284
Transcription is a highly regulated process that converts genetic information into RNA molecules. The transcription cycle is divided into three key stages: initiation, elongation, and termination, each driven by specific molecular mechanisms.Initiation of TranscriptionIn bacteria, transcription begins when the RNA polymerase core enzyme associates with a sigma factor to form a holoenzyme. For example, the E. coli sigma factor called σ70 forms a holoenzyme, which recognizes the -10 (Pribnow...
284
Ribosome Profiling02:24

Ribosome Profiling

3.6K
Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique...
3.6K

You might also read

Related Articles

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

Sort by
Same author

Degradation of mucin <i>O</i>-glycans by a human gut symbiont requires a complex enzyme repertoire and promotes colonization.

bioRxiv : the preprint server for biology·2026
Same author

The butyrate-producing Gram-positive human gut bacterium, Hoskinsella mucinilytica, selectively targets host mucin N-acetylhexosamines.

The Journal of biological chemistry·2026
Same author

Identification and characterization of the functional LolB ortholog in <i>Bacteroides</i>.

bioRxiv : the preprint server for biology·2026
Same author

Description of <i>Hoskinsella mucinilytica</i> gen. nov., sp. nov., a mucin-degrading isolate from human faeces, and reclassification of <i>Amedibacillus hominis</i> Abdugheni <i>et al</i>. 2023 as a later heterotypic synonym of <i>Eubacterium hominis</i> Liu <i>et al</i>. 2022 within the genus <i>Hoskinsella</i> gen. nov.

International journal of systematic and evolutionary microbiology·2026
Same author

Lung ultrasound morphology patterns predict treatment response and weaning outcomes in high-risk mechanically ventilated patients.

BMC pulmonary medicine·2025
Same author

Fe<sup>3+</sup>-assisted nitrogen-doped carbon dot fluorescence switch for ultrasensitive detection of acetyl-CoA in live microalgal cells.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy·2025
Same journal

Environmental microbes as modulators of plant volatile landscapes: Implications for plant-insect chemical communication.

Trends in microbiology·2026
Same journal

Beyond AMGs: Phage-encoded transcription and sigma factors as understudied virocell reprogramming tools.

Trends in microbiology·2026
Same journal

Cronobacter spp.

Trends in microbiology·2026
Same journal

Anaerobic lignin deconstruction: A game changer for lignocellulosic biorefineries.

Trends in microbiology·2026
Same journal

Critical role of the inflammatory rheostat in influenza-associated pulmonary aspergillosis.

Trends in microbiology·2026
Same journal

Structure-based prokaryotic transcription shapes adaptation and host-invader interplay.

Trends in microbiology·2026
See all related articles

Related Experiment Video

Updated: Sep 16, 2025

A Fast and Reliable Pipeline for Bacterial Transcriptome Analysis Case study: Serine-dependent Gene Regulation in Streptococcus pneumoniae
10:18

A Fast and Reliable Pipeline for Bacterial Transcriptome Analysis Case study: Serine-dependent Gene Regulation in Streptococcus pneumoniae

Published on: April 25, 2015

10.5K

Low biomass bacterial transcriptomics takes shape.

Qinnan Yang1, Eric C Martens1

  • 1Department of Microbiology and Immunology, University of Michigan Medical School, Ann Arbor, MI 48109-5620, USA.

Trends in Microbiology
|July 8, 2025
PubMed
Summary
This summary is machine-generated.

Researchers profiled gene expression in different sizes of Bacteroides thetaiotaomicron using a low-input bacterial RNA-sequencing (RNA-seq) method. This technique enables studying transcriptional variations in individual bacterial cells sorted by fluorescence-activated cell sorting (FACS).

More Related Videos

Purifying the Impure: Sequencing Metagenomes and Metatranscriptomes from Complex Animal-associated Samples
11:23

Purifying the Impure: Sequencing Metagenomes and Metatranscriptomes from Complex Animal-associated Samples

Published on: December 22, 2014

37.4K
Understanding the Impact of Temperate Bacteriophages on Their Lysogens Through Transcriptomics
09:23

Understanding the Impact of Temperate Bacteriophages on Their Lysogens Through Transcriptomics

Published on: January 5, 2024

2.0K

Related Experiment Videos

Last Updated: Sep 16, 2025

A Fast and Reliable Pipeline for Bacterial Transcriptome Analysis Case study: Serine-dependent Gene Regulation in Streptococcus pneumoniae
10:18

A Fast and Reliable Pipeline for Bacterial Transcriptome Analysis Case study: Serine-dependent Gene Regulation in Streptococcus pneumoniae

Published on: April 25, 2015

10.5K
Purifying the Impure: Sequencing Metagenomes and Metatranscriptomes from Complex Animal-associated Samples
11:23

Purifying the Impure: Sequencing Metagenomes and Metatranscriptomes from Complex Animal-associated Samples

Published on: December 22, 2014

37.4K
Understanding the Impact of Temperate Bacteriophages on Their Lysogens Through Transcriptomics
09:23

Understanding the Impact of Temperate Bacteriophages on Their Lysogens Through Transcriptomics

Published on: January 5, 2024

2.0K

Area of Science:

  • Microbiology
  • Genomics
  • Molecular Biology

Background:

  • Bacterial gene expression can vary within genetically identical populations.
  • Understanding these variations is crucial for studying microbial physiology and adaptation.
  • Previous methods lacked the sensitivity to profile small cell populations.

Purpose of the Study:

  • To develop and apply a low-input bacterial RNA-sequencing (RNA-seq) pipeline.
  • To transcriptionally profile distinct cell size populations of *Bacteroides thetaiotaomicron*.
  • To enable the analysis of transcriptional heterogeneity in sorted bacterial cells.

Main Methods:

  • Utilized a low-input bacterial RNA-sequencing (RNA-seq) pipeline.
  • Employed fluorescence-activated cell sorting (FACS) to isolate small, medium, and large cell populations.
  • Analyzed the transcriptome of sorted *Bacteroides thetaiotaomicron* cells.

Main Results:

  • Successfully profiled the transcriptome of small, medium, and large cell populations.
  • Demonstrated the feasibility of measuring transcriptional differences in FACS-sorted bacterial cells.
  • Identified potential transcriptional variations linked to cell size or other FACS-sortable features.

Conclusions:

  • The developed low-input RNA-seq pipeline is effective for profiling bacterial transcriptomes.
  • This approach facilitates the study of transcriptional heterogeneity in microbial populations.
  • Opens new avenues for investigating cell-to-cell variability in bacteria based on morphology or other features.