This preprint closes a long development phase…
but opens a new frontier: morphology as a quantitative, molecularly anchored measurement modality.
If this resonates with your work, we’d love to connect.
Thanks again to the entire team and looking forward to exciting new IRIS adventures 🚀!

IRIS also revealed that subtle nuclear morphologies correspond to distinct molecular states, including the previously puzzling T cell stripy nuclear phenotype (collab. w/ @BerendSnijder's lab; Hale et al., Science, 2024), now shown to map to a specific transcriptomic program.

We also show that IRIS enables prediction of transcriptomes directly from images (#ML). Models trained on IRIS data recover gene-level variation, cell-cycle phase, and cell identity from morphology alone.

We uncovered phase-specific TF activity, revealing how DREAM complex repression, FUCCI intensity, and cell-cycle speed are linked. IRIS detects quiescence-primed vs fully quiescent states & shows that slowly cycling cells display stronger DREAM-mediated repression, insights missed by RNA-only tools.

As a 1st application, we used IRIS to profile >5k FUCCI-3T3 cells, reconstructing the full continuous #cell-cycle from morphology + RNA; identifying 670 cycling genes. IRIS’s morphology-anchored cell-cycle angle aligns with Seurat/Tricycle but provides smoother, higher-resolution structure.

IRIS solves a long-standing gap: #imaging and droplet-based sequencing were never truly connected at single-cell resolution. Here, every cell is imaged first (BF + 4 fluorescent channels) → then deterministically barcoded → then sequenced, enabling single cell #phenomics.

🧵2/ Across 384 TFs and ~40,000 cells, we found:
– Nonlinear, dose-sensitive reprogramming responses
– TFs triggering different fates at low vs high dose
– Same dose, different outcome = hidden complexity
– TF pairs flipping between synergy & antagonism based on dose ratio

Fantastic work by Camille Lambert, Guido van Mierlo, Orane Guillaume-Gentil and Johannes Bues. For a related review on 'The evolution of DNA sequencing with microfluidics', pls also see: www.nature.com/articles/s41...

Sounds very exciting, very much looking forward!

Happy to be part of the feed Erik, thanks for the initiative. scholar.google.ch/citations?us...