Yangteng Ou

Check out our latest paper on droplet microfluidics and biomaterials design. @zexianghan @ShenglinC @ZToprakcioglu @janheck_ @KnowlesLabCamb @ChemCambridge

Not fully completed; but if someone is interested in the #rheology of granular hydrogels, I have made some interesting findings: chemrxiv.org/doi/full/10.26…

New issue alert👉cell.com/cell/current Yoshida et al. present 3D, single-cell-resolution atlases of multiple adult mouse organs and of the entire neonatal mouse. The artwork reimagines Klimt's decorative motifs to reflect the organization and vast scale of individual cells.

Once largely a basic science discipline, mechanobiology has evolved into the field of mechanomedicine, shaping new approaches to disease detection, targeted therapies and tissue repair Read our new Editorial: go.nature.com/4bsb6aL

Excellent review in which Solé et al. explore how physical/mathematical constraints may determine what subset of biological systems could theoretically evolve in the universe. Link "Fundamental constraints to the logic of living systems": doi.org/10.1098/rsfs.2…

Excited to share our new work. Over the past decade, single-cell genomics has transformed our ability to map cellular systems. But a major question remains: Can we predict how perturbations reshape cellular trajectories over time? In 2018, we first showed that it is possible to predict cellular responses to perturbations — ranging from disease signals to chemical treatments — even in unseen contexts. In 2022, we introduced CPA (MSB 2022; NeurIPS 2022), extending this idea to predict responses to unseen chemical and genetic perturbations, including their combinations. Since then, the field of perturbation modeling has grown enormously. The community has pushed the space forward with many creative ideas and powerful models. It’s exciting to see how fast things are moving — even though many fundamental challenges remain. One of the biggest is that cells are not static. They move through trajectories during development, immune responses, and disease. Yet most current models still predict perturbation effects within a single state, rather than how early perturbations propagate across future states and reshape downstream outcomes. To address this, we developed PerturbGen, a trajectory-aware generative AI model that predicts how genetic perturbations reshape downstream cellular states. Huge credit to the people who made this work possible. Thanks to co-first authors @lifeisscience_5, @Adib_m_, @Tomo_Isobe, @Amirhossein Vahidi, @delshadveghari & Anthony Rostron. Special recognition to @lifeisscience_5 and @Adib_m_ for driving this work over the finish line. Grateful for our outstanding collaborators from @HaniffaLab, @BertieGottgens lab @GosiaTrynka and many others — a true cross-institute effort across @SCICambridge, @OpenTargets ,@sangerinstitute and @Cambridge_Uni.🎉 PerturbGen learns transcriptional dynamics across cellular trajectories. By introducing perturbations at an early source state, it can simulate how these effects propagate into future states along differentiation trajectories. Scaling this across genes enables the creation of dynamic in silico perturbation atlases — maps of how perturbations reshape biological trajectories over time. We explored this idea across three biological questions. First, in a human in vivo LPS immune challenge, PerturbGen predicted that perturbing a transient IL1B signal dampens downstream inflammatory programs in myeloid cells, with pathway changes reversing signatures observed in an independent IL-1β stimulation experiment. Second, in human hematopoiesis, PerturbGen predicted transcriptional responses to CRISPR transcription factor knockouts and enabled construction of perturbation atlases revealing lineage- and age-specific regulatory programs. These programs could also be linked to human genetics and blood diseases, including recapitulation of signatures associated with ETV6-related thrombocytopenia. Finally, we asked whether perturbation modeling could help improve complex tissue models. We built a dynamic perturbation atlas of human skin organoids to identify perturbations that could guideorganoid cells towardhuman fetal skin states. PerturbGen prioritized activation of Wnt signaling via GSK3β inhibition. Experimental validation confirmed the prediction: treatment with CHIR99021 induced stromal gene programs and shifted organoid fibroblasts toward transcriptional states observed in fetal skin stroma. Together, these results show how trajectory-aware perturbation modeling can connect gene perturbations to developmental programs, human genetics, disease mechanisms, and experimental interventions. More broadly, we think these point toward a future where single-cell atlases become predictive systems. As atlases expand across tissues, developmental windows, and modalities, models like PerturbGen could enable dynamic, virtual perturbation atlases— allowing us to simulate interventions, generate hypotheses, and design experiments before stepping into the lab. Preprint shorturl.at/EkisP Code github.com/Lotfollahi-lab… Excited to see how the community builds on this work.

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meanwhile in science

New publication alert! We use theory and experiment to demonstrate that glassy adhesion dynamics can predict anomalous migration on viscoelastic substrates. Grateful to have worked with Vivek Sharma, Ze Gong, @theChaudhurilab, and Vivek B Shenoy 🙏 ! #Abs1" target="_blank" rel="nofollow noopener">nature.com/articles/s4146…

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🔬 pertpy: a unified, scalable framework for single-cell perturbation analysis, now out in Nature Methods Designed for modern perturbation data - CRISPR, drug screens, patient treatments - scaling to millions of cells and 1000s of conditions. 👉 nature.com/articles/s4159…

Mechanomedicine bit.ly/4aHOCE2

Mapping the metabolic effects of drugs helps define their mode of action go.nature.com/3CreANg rdcu.be/eUK7o

Stereo-cell is a DNA nanoball array-based method that enables scalable, spatially resolved single-cell RNA sequencing across diverse cell types and sizes with multimodal integration capabilities. #NBThighlight science.org/doi/10.1126/sc…

Science today reports a hydrogel that functions over a temperature range from −115° to 143°C. science.org/doi/10.1126/sc…

Wanderer above the Sea of Fog

Experiments and simulations of DNA nanostar hydrogels reveal that microscopic topology determines macroscale elasticity in amorphous networks. @Dmichiel1 nature.com/articles/s4156…