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Gene Expression Profiling of Infecting Microbes Using a Digital Bar-coding Platform
Published on: January 13, 2016
Genetic tools to study gene expression during bacterial pathogen infection.
1Department of Microbiology, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA.
Advances in Applied Microbiology
|February 28, 2009
Summary
In vivo expression technology (IVET) helps study bacterial gene regulation during infection. This method identifies virulence factors and regulatory events, advancing our understanding of bacterial pathogenesis and host adaptation.
Area of Science:
- Microbiology
- Molecular Biology
- Genetics
Background:
- Bacterial pathogenesis relies on regulatory mechanisms enabling adaptation to host environments.
- Transcriptional changes are crucial for bacterial survival and virulence within a host.
- Investigating bacterial gene expression in vivo is essential for understanding infection dynamics.
Purpose of the Study:
- To review in vivo expression technology (IVET) as a method for studying bacterial transcriptional changes during infection.
- To highlight the utility of IVET in identifying virulence factors and regulatory events.
- To discuss the expanding applications of IVET in microbial pathogenesis research.
Main Methods:
- In vivo expression technology (IVET) utilizes promoter-trapping with reporter constructs.
- IVET enables the isolation and analysis of bacterial genes expressed during infection.
- Various reporter systems and promoter-trapping strategies are employed.
Main Results:
- IVET has successfully catalogued virulence factors in human pathogens.
- The timing of virulence gene regulation during infection has been elucidated using IVET.
- IVET has identified transcriptional repression events, including the suppression of anti-colonization factors.
Conclusions:
- IVET is a powerful tool for probing bacterial transcriptional activities in vivo.
- Advancements in IVET reporters and strategies enhance the study of bacterial survival and disease.
- IVET significantly contributes to understanding the complex regulatory networks governing bacterial pathogenesis.
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