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Gene Expression Profiling of Infecting Microbes Using a Digital Bar-coding Platform
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Gene Expression Profiling of Infecting Microbes Using a Digital Bar-coding Platform.

Wenjie Xu1, Norma V Solis2, Scott G Filler2

  • 1Department of Biological Sciences, Carnegie Mellon University; wxu7206@gmail.com.

Journal of Visualized Experiments : Jove
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PubMed
Summary
This summary is machine-generated.

We developed a sensitive protocol for profiling gene expression in pathogens like Candida albicans during infection. This method overcomes challenges in quantifying low-abundance pathogen RNA from host tissues.

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Area of Science:

  • Microbiology
  • Molecular Biology
  • Infectious Diseases

Background:

  • Quantifying pathogen gene expression in infected tissues is challenging due to low pathogen RNA levels.
  • Existing microarray and RNAseq methods struggle with weakly expressed pathogen genes and mutant strains.

Purpose of the Study:

  • To develop a sensitive, reproducible, and rapid in vivo gene expression profiling protocol for pathogens.
  • To investigate dynamic gene expression of Candida albicans during murine kidney infection.

Main Methods:

  • Developed a novel in vivo gene expression profiling protocol.
  • Applied the protocol to a murine model of hematogenously disseminated candidiasis.
  • Analyzed gene expression of Candida albicans in infected kidney tissues.

Main Results:

  • The protocol is fast, highly sensitive, and reproducible for pathogen gene expression analysis.
  • Documented dynamic gene expression changes of C. albicans during kidney infection.
  • Observed unexpected gene expression responses to antifungal drug treatment in vivo.

Conclusions:

  • The new protocol enables accurate quantification of pathogen gene transcripts from infected tissues.
  • Provides novel insights into Candida albicans gene regulation during infection and drug treatment.
  • Facilitates the study of gene expression for challenging pathogen strains and experimental conditions.