fatimasnc.bsky.social
@fatimasnc.bsky.social
... with special mention to our amazing collaborators @kirkebylab.bsky.social Gaurav, Pedro and Charlotte 🙌
December 19, 2025 at 5:01 PM
Congratulations 👏 and huge thanks to all the authors for your essential contributions to this manuscript @akanksha-jain.bsky.social
@zhisonghe.bsky.social @jasperjanssens.bsky.social @josch1.bsky.social Ryoko, Gosia, Makiko and Benedikt...
December 19, 2025 at 5:01 PM
We’re so excited to share this work with the community🎉 and hope it can be used to optimise the design of the next generation of neural organoid models 🧠🧫
December 19, 2025 at 5:01 PM
Something we’re particularly excited about is the co-development of neural and non-neural tissues in some of our conditions 🧩

Fine-tuning these morphogen conditions and using the right patterning modalities could help us develop more complex organoids 🏗️🏙️
December 19, 2025 at 5:01 PM
Most variability came from differences between hPSC lines and neural induction strategies, not batch or sex🧐

Dual SMAD inhibition enriched for CNS fates but was much less reproducible than minimal neural induction (without SB+Noggin) across lines🔥
December 19, 2025 at 5:01 PM
Some regulons were consistent across cell lines👱🧑‍🦰🧑‍🦱 and neural induction media🧫, but others varied strongly!

This gives us an idea of which cell types may be easier or harder to achieve reproducibly in vitro 🧪☑️
December 19, 2025 at 5:01 PM
By sampling organoids right after morphogen exposure, we could quantify activation of patterning regulons - signals we usually lose as neural progenitors disappear in older organoids 🫣
December 19, 2025 at 5:01 PM
We sampled early-stage organoids to capture a rich spectrum of developmental states, from PSCs to neurons 👶➡️🧑

Our population of interest was the neural progenitors undergoing patterning🐣, which nicely complements other datasets focusing on more mature neuronal identities 🧠
December 19, 2025 at 5:01 PM
We also designed a reproducibility screen: 12 morphogens across 4 hPSC lines, 2 neural induction media and 2 technical batches 💪

Our systematic datasets are ideal for modeling approaches 💻 like CellFlow www.biorxiv.org/content/10.1...
CellFlow enables generative single-cell phenotype modeling with flow matching
High-content phenotypic screens provide a powerful strategy for studying biological systems, but the scale of possible perturbations and cell states makes exhaustive experiments unfeasible. Computatio...
www.biorxiv.org
December 19, 2025 at 5:01 PM
We used SHH, WNT, FGF8, RA, and BMP4/7 pathway modulators to probe, in an unbiased way, how morphogen timing 🕑 concentration 📶 and combinations🌀affect patterning outcomes.

For each morphogen, some factors matter more ➕ and others less➖!
December 19, 2025 at 5:01 PM
Aware of the hurdles, we tried to put an end to this suffering 🙅‍♀️

Pipette in hand, @nazbukina.bsky.social and I set out to screen for as many factors as we could to better understand how early regional patterning works in human neural organoids 🧠🧫
December 19, 2025 at 5:01 PM
We usually focus only on the "best" conditions⭐️ ignoring what happens beneath the surface: batch effects, mixed identities, heterogeneity 🥴

‼️What if, instead of avoiding it, we harnessed that heterogeneity to build more complex organoid systems?
December 19, 2025 at 5:01 PM
All regionalised organoid protocols rely on the same morphogens 🪅 SHH, RA, BMPs, FGFs, WNTs 🪅 applied at different doses and times. Each lab painstakingly optimises conditions to generate the purest CNS region-specific populations.
December 19, 2025 at 5:01 PM