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

Non-classical protein secretion in bacteria.

Jannick D Bendtsen1, Lars Kiemer, Anders Fausbøll

  • 1Center for Biological Sequence Analysis, BioCentrum-DTU, Building 208, Technical University of Denmark, DK-2800 Lyngby, Denmark. jannick@cbs.dtu.dk

BMC Microbiology
|October 11, 2005
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

Genome-wide meta-analysis identifies genetic drivers of bile acid metabolism in intrahepatic cholestasis of pregnancy.

Nature communications·2026
Same author

The role of genetic liability for psychiatric disorders and personality traits in post covid syndrome: data from three Nordic population cohorts.

EClinicalMedicine·2026
Same author

Detection of young-onset type 2 diabetes using deep learning across primary and secondary care: a nationwide, retrospective cohort study.

The Lancet. Digital health·2026
Same author

Genomic analyses implicate hormonal and metabolic dysregulation in polycystic ovary syndrome.

Nature genetics·2026
Same author

Opportunistic Screening: 2026 Status Update and Future Outlook.

AJR. American journal of roentgenology·2026
Same author

A biological-systems-based analysis using proteomic and metabolic network inference reveals mechanistic insights into hepatic steatosis.

Metabolism: clinical and experimental·2026
Same journal

Factors associated with drug-resistant tuberculosis among patients at a tertiary referral hospital in Tanzania.

BMC microbiology·2026
Same journal

Synthesis of zinc oxide nanoparticles and their effect on biofilm of methicillin-resistant Staphylococcus aureus isolates.

BMC microbiology·2026
Same journal

A population-based retrospective machine learning study of COVID-19 severity using integrated clinical and viral genomic data in Jiangsu Province, China.

BMC microbiology·2026
Same journal

Bacillus-based probiotic supplementation reshapes rumen bacterial and fungal communities and enhances carbohydrate-degrading functional capacity in weaned yaks.

BMC microbiology·2026
Same journal

Genome-to-function integrated exploration of polyethylene biodegradation by Rhodococcus opacus R7.

BMC microbiology·2026
Same journal

Overcoming the bottleneck in Treponema pallidum quantification: a novel flow cytometric assay for rapid, precise, and cost-effective detection.

BMC microbiology·2026
See all related articles

Researchers developed a novel method to identify bacterial proteins secreted without signal peptides, aiding in the discovery of new secretion pathways and moon-lightning proteins.

Area of Science:

  • Microbiology
  • Protein Secretion
  • Bioinformatics

Background:

  • Bacterial non-classical secretion pathways are signal peptide-independent.
  • Extracellular proteins lacking signal peptides are identified.
  • Some non-classically secreted proteins exhibit moon-lighting functions.

Purpose of the Study:

  • To develop a prediction method for identifying bacterial proteins secreted via non-classical pathways.
  • To analyze characteristics distinguishing non-classically secreted proteins from other cellular proteins.

Main Methods:

  • Literature search to compile known non-classically secreted proteins.
  • Pattern finding methods to identify secretion signals or motifs.
  • Analysis of amino acid composition, secondary structure, and disordered regions.

Related Experiment Videos

  • Artificial neural networks for prediction model development.

    • Main Results:

    • No common signal or motif found for the majority of non-classically secreted proteins.
    • Non-classically secreted proteins are distinguishable by distinct properties, including higher structural disorder.
    • A prediction method was constructed using protein features.

    Conclusions:

    • A publicly available prediction tool can identify novel non-classically secreted proteins.
    • Candidate proteins for non-classical secretion in E. coli and B. subtilis are proposed.
    • The prediction method is accessible online.