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Area of Science:

  • Molecular Biology
  • Synthetic Biology
  • Microbial Genetics

Background:

  • Understanding cellular heterogeneity requires tracking transcriptional dynamics within individual cells.
  • Existing methods struggle to capture the historical transcriptional state of single cells.

Purpose of the Study:

  • To develop a novel system for recording and analyzing transcriptional history in living bacterial cells.
  • To enable the quantification of gene expression and single-nucleotide variations over time within single cells.

Main Methods:

  • Utilized reprogrammed tracrRNAs (Rptrs) to sense cellular transcripts and convert them into guide RNAs.
  • Employed a Cas9 base editor system guided by Rptrs to create DNA edits corresponding to RNA sequences.
  • Developed the TIGER (transcribed RNAs inferred by genetically encoded records) system for DNA-based RNA recording and subsequent sequencing analysis.

Main Results:

  • Successfully recorded heterologous and endogenous transcripts in individual bacterial cells using TIGER.
  • Demonstrated TIGER's capability to quantify relative expression, differentiate single-nucleotide variations, and simultaneously record multiple transcripts.
  • Applied TIGER to study metabolic bet hedging, antibiotic resistance, and bacterial host cell invasion in real-time.

Conclusions:

  • TIGER provides a powerful tool for linking current and past cellular states through RNA recording.
  • This technology facilitates the deciphering of complex cellular responses and behaviors at the single-cell level.
  • TIGER opens new avenues for studying microbial dynamics and gene expression in heterogeneous populations.