Hi-throughput gene expression analysis at the level of single proteins using a microfluidic turbidostat and automated cell tracking
G. Ullman, M. Wallden, E. G. Marklund, A. Mahmutovic, I. Razinkov, J., Elf

TL;DR
This paper introduces a microfluidic and microscopy-based method for high-throughput, single-protein gene expression analysis in live bacteria, enabling detailed cell cycle and molecular dynamics studies.
Contribution
It presents a novel integrated approach combining microfluidics, microscopy, and automated analysis for real-time single-protein gene expression in bacteria.
Findings
Able to observe over 3000 cell cycles per experiment
Counted non-specific DNA binding molecules of LacI-Venus
Discovered gene expression increases at cell cycle start
Abstract
We have developed a method combining microfluidics, time-lapsed single-molecule microscopy and automated image analysis allowing for the observation of an excess of 3000 complete cell cycles of exponentially growing Escherichia coli cells per experiment. The method makes it possible to analyze the rate of gene expression at the level of single proteins over the bacterial cell cycle. We also demonstrate that it is possible to count the number of non-specifically DNA binding LacI-Venus molecules using short excitation light pulses. The transcription factors are localized on the nucleoids in the cell and appear to be uniformly distributed on chromosomal DNA. An increase of the expression of LacI is observed at the beginning of the cell cycle, possibly because some gene copies are de-repressed as a result of partitioning inequalities at cell division. Finally, observe a size-growth rate…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsCell Image Analysis Techniques · Advanced Fluorescence Microscopy Techniques · Single-cell and spatial transcriptomics
