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Related Concept Videos

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High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions
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A highly multiplexed and sensitive RNA-seq protocol for simultaneous analysis of host and pathogen transcriptomes.

Roi Avraham1, Nathan Haseley1, Amy Fan1

  • 1Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.

Nature Protocols
|July 22, 2016
PubMed
Summary
This summary is machine-generated.

This study presents a new RNA sequencing (RNA-seq) protocol for simultaneously analyzing host and bacterial gene expression during infection. This method offers a sensitive and generalizable approach for in-depth pathogen-host interaction studies.

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Gene Expression Profiling of Infecting Microbes Using a Digital Bar-coding Platform
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Area of Science:

  • Microbiology
  • Genomics
  • Molecular Biology

Background:

  • Simultaneous characterization of bacterial and host expression is crucial for understanding infection dynamics.
  • Existing RNA sequencing (RNA-seq) protocols face limitations in profiling both host and pathogen transcripts concurrently.
  • Advances in RNA-seq are needed to overcome these limitations in mixed samples.

Purpose of the Study:

  • To provide a detailed protocol for the simultaneous analysis of host and bacterial transcripts using RNA-seq.
  • To enable comprehensive studies of pathogen-host interactions by profiling both transcriptomes from a single sample.
  • To offer a sensitive, facile, and generalizable method for infection models.

Main Methods:

  • Development of a protocol for efficient host and bacteria lysis.
  • Implementation of sample barcoding and advanced preparation techniques for low-yield inputs.
  • Establishment of a computational pipeline for analyzing mixed mammalian and microbial RNA-seq data.
  • Streamlined workflow from cultured cells to pooled libraries in 3 days, with 1 day for data analysis.

Main Results:

  • Successful simultaneous profiling of host and bacterial transcripts from mixed samples.
  • Demonstration of a sensitive and facile approach suitable for large-scale studies.
  • Validation of a computational pipeline for accurate analysis of mixed RNA-seq data.

Conclusions:

  • The presented RNA-seq protocol enables in-depth analysis of host-pathogen interactions.
  • This method facilitates a comprehensive understanding of infection mechanisms by characterizing both organisms' expression programs.
  • The protocol is generalizable and suitable for diverse infection models and large-scale research.