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Related Concept Videos

Cystic Fibrosis: Pathogenesis01:23

Cystic Fibrosis: Pathogenesis

532
Cystic fibrosis (CF), an autosomal recessive disorder, significantly affects the function of exocrine glands. This genetically inherited disease is characterized by the production of thick and sticky mucus, which can severely affect various organs and systems in the body.
CF is primarily caused by a genetic mutation in a chromosome 7 gene coding for the cystic fibrosis transmembrane conductance regulator (CFTR) protein. The most common gene mutation leading to CF is the ΔF508 mutation,...
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Cystic Fibrosis: Management01:24

Cystic Fibrosis: Management

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Cystic fibrosis (CF) is an autosomal recessive disorder that predominantly affects individuals of Northern European descent, occurring at a rate of 1 in 3500. It is caused by a genetic mutation in a gene on chromosome 7, most commonly the ΔF508 mutation, that codes for the cystic fibrosis transmembrane conductance regulator (CFTR) protein. This results in thicker mucus secretions and obstruction pathologies in multiple organs, including the lungs and sinuses.
Sinus disease and chronic...
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Growing a Cystic Fibrosis-Relevant Polymicrobial Biofilm to Probe Community Phenotypes
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One versus Many: Polymicrobial Communities and the Cystic Fibrosis Airway.

Fabrice Jean-Pierre1, Arsh Vyas2, Thomas H Hampton1

  • 1Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire, USA.

Mbio
|March 17, 2021
PubMed
Summary

Chronic lung infections in cystic fibrosis (CF) patients involve complex microbial communities. Computational modeling can create in vitro models to study these polymicrobial infections and find new treatments.

Keywords:
antibioticsbiofilmschronic infectioncystic fibrosismetabolic modelingmicrobial communitiesmicrobiome

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Area of Science:

  • Microbiology
  • Computational Biology
  • Infectious Diseases

Background:

  • Chronic lung infections in cystic fibrosis (CF) are polymicrobial, not caused by single species.
  • Interactions within CF airway polymicrobial communities influence clinical outcomes.
  • Existing 16S rRNA gene studies provide insights but cannot fully explain clinical diversity.

Purpose of the Study:

  • To advocate for in silico approaches to build clinically relevant in vitro models of CF polymicrobial communities.
  • To enable experimental validation of computationally generated hypotheses.
  • To enhance understanding of microbial community function and identify novel therapeutics.

Main Methods:

  • Utilizing in silico (computational) approaches to design polymicrobial communities.
  • Developing in vitro models based on computational predictions.
  • Integrating computational and experimental methodologies.

Main Results:

  • In silico methods can guide the construction of realistic polymicrobial communities for CF lung infections.
  • This integrated approach facilitates hypothesis testing and validation.
  • The combined strategy advances understanding of microbial dynamics and therapeutic targets.

Conclusions:

  • Computational approaches are crucial for developing in vitro models of CF polymicrobial infections.
  • Integrating in silico and experimental methods enhances the study of microbial community function.
  • This synergy promises to accelerate the discovery of new treatments for CF lung infections.