Hiring in life sciences? Share your open positions with our professional community. Read more Close

Advertisement

RainBar: Optical Barcoding for Pooled Live-Cell Imaging with Single-Cell Resolution

Created on 06 Nov 2025

Authors

Mosadeghi, R., Foyt, D., Sharp, L., Taylor, C. A., Tay, N., Oberlin, S., Fan, J., Bourke, S., Kattah, M. G., Huang, B. Q., McManus, M. T.

Abstract

High-throughput pooled screening has advanced functional genomics, but most existing methods rely on endpoint sequencing and are blind to dynamic, time-resolved phenotypes. We developed RainBar (Rainbow Barcodes), an optical barcoding system that supports pooled live-cell imaging with single-cell resolution. RainBar uses lentiviral co-delivery of spectrally distinct nuclear and cytoplasmic fluorescent proteins to encode up to 64 unique perturbations per well. To mitigate barcode recombination and improve decoding accuracy, we employed single-template viral production, codon diversification, and a ratio-based spectral unmixing pipeline tailored to overlapping fluorophores. An inverted cytoplasmic segmentation approach and multilayer perceptron classifier enabled accurate barcode identification in both arrayed and pooled formats. As a proof of concept, we applied RainBar to dissect NF-{kappa}B signaling dynamics in epithelial cells. Live imaging of RelA translocation uncovered stimulus-specific kinetics: IL-1{beta} triggered rapid recovery, while TNF induced prolonged nuclear localization. In pooled CRISPRi screens, RainBar recovered known NF-{kappa}B regulators (e.g., IL1R1, MYD88, TNFRSF1A) and highlighted additional modulators, including the Ino80 chromatin remodeling complex subunits and KAT2A acetyltransferase. Together, these results position RainBar as a flexible platform for multiplexed, image-based functional genomics, with potential to reveal dynamic signaling architectures across diverse cellular contexts in live cells.

Preprint server: bioRxiv
The authors list and abstract were imported from bioRxiv on 06 Nov 2025.

Advertisement

Stats

  • Community rating n/a 0 votes
  • Your rating

1-terrible, 9-excellent. How would you rate this preprint? Sign in in to submit your rating.

  • Recommendations n/a n/a positive of 0 vote(s)
  • Views 45
  • Comments 0

Recommended by

  • No recommendations yet.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.

Advertisement