Microbial Transcriptomics
One-Sentence Definition
Microbial transcriptomics (RNA-seq) measures which genes a microbe is expressing under a given condition, revealing regulation that genome sequence alone cannot show.
Simple Explanation
The genome says what a cell can do; the transcriptome says what it is doing right now.
Detailed Scientific Explanation
Workflow: RNA extraction → rRNA depletion (bacteria lack polyA selection) → library → sequencing → QC → mapping/pseudo-alignment → counts → normalization (TPM/CPM) → differential expression (DESeq2, edgeR).
Specialized variants:
- Dual RNA-seq — pathogen and host transcripts simultaneously
- Single-cell / scRNA-seq of host immune cells during infection
- Term-seq / dRNA-seq — transcript boundaries, operons
- Nanopore direct RNA — native modifications
Interpretation: fold changes need biological replicates; expression ≠ protein level (Proteomics and MALDI Bioinformatics).
Mechanism
Counting reads per feature, modeling counts with negative binomial distributions, and controlling false discovery across thousands of genes.
Clinical Importance
- Explains induced resistance (efflux pump upregulation, ampC induction) that gene detection misses
- Host response signatures for sepsis discrimination feed AI Diagnostics in Microbiology
Research Importance
- Regulatory networks, stress responses, biofilm and persister states
Diagnostic Relevance
- Host transcriptomic signatures (bacterial vs viral) are an emerging diagnostic class
AMR Relevance
- Efflux/porin regulation is expression-level — a key gap in genotype-only prediction (Machine Learning for AMR Prediction)
Related MOCs
Active Recall Questions
- Why can’t you use polyA selection for bacterial mRNA?
- Which resistance mechanisms are visible only in expression data?
- What is dual RNA-seq?