As promised, a 🧵 on our recent article now out in @NatureSMB! Co-led with @AbbyBartlett_ @Pagliarini_Lab @JudithSimcox, we find ACAD10/11 are NOT like other acyl-CoA dehydrogenases and instead catabolize atypical lipids called 4-hydroxy acids 🤯#lipidtime doi.org/10.1038/s41594-025-0…

Have you ever wanted to talk to your molecules? Now you can with Chat with PyMOL! We built this in the Romero Lab to make PyMOL more accessible to our BME undergrads, but quickly found it’s simply a better way to interact with molecular structures. (1/2)

#lipidtime: It's a lipid universe. Today in Nature we publish the Lipid Brain Atlas, the first map of membrane lipid composition across the entire mouse brain, a layer of organisation that cell-type and transcript maps had left out. #lipidomics #neuroscience #BrainAtlas

An extraordinary @Nature paper has just landed from the lab of @Sergiu_P_Pasca at @Stanford - led by Konstantin Kaganovsky. They have found a way to create "xenocortical mice" which have ~92% of their cortex occupied by a cortical organoid derived from human stem cells. This human-derived cortical graft integrates deeply with the host nervous system, supporting organised neural activity and behaviour. This study is a milestone in synthetic biology and chimera research. It has the potential to generate multiple medical breakthroughs by providing an enhanced biological model of human brain tissue that allows behavioural as well as neural and genetic assays. The Stanford team have been exceptionally thorough and proactive in addressing ethical concerns that comes from this frontier work. But their pioneering work nonetheless raises many open questions: are the xenocortical mice conscious? Do they have any human-like properties of consciousness or cognition? @NitaFarahany and I will be addressing some of these questions in a forthcoming commentary - where we'll also offer an ethically-informed roadmap to guide this important research as it progresses. In this context, "pacing the frontier" really does make sense 😉 Read the Stanford @nature paper here, and buckle up. It's wild. nature.com/articles/s41586-0…

Our Tabula Sapiens 2.0 is online at @CellCellPress! We doubled our dataset to >1.1M cells across 28 tissues, mapped expression of human transcription factors, and analyzed cellular senescence programs. The atlas is open access. Read the paper here: cell.com/cell/fulltext/S0092…

I guess it is possible to be surprised and not at all surprised at the same time... wow 2 big fails in a row on genetically validated CV targets

I am very excited to share that our latest work on spatial lineage-tracing in the KP lung adenocarcinoma model has been published in @NatureGenet today! This is the latest work from my lab at @MITBiology @kochinstitute @MIT_IMES. Thread below👇

Big congrats to grad student @AnnaMBarbeau of @mvh_lab on their review of the current understanding and considerations of how diet influences cancer progression/therapy. So important and timely! Check out here: annualreviews.org/content/jo…

Always a great time at @CSHL presenting some new findings and meeting old and new friends at the mechanisms and models of cancer meeting!

The 2026 @arcinstitute Virtual Cell Challenge just launched. The grand prize is $100,000, sponsored by @NVIDIA, @10xGenomics, and @UltimaGenomics. There's a lot of interest in virtual cells these days: ML models of cells that can complement wet lab experiments. (You'll always need the wet lab to validate results, of course. But ML models can in principle search far more efficiently.) A practical challenge in the field is that benchmarking is quite difficult: cells are very complicated, and it's not a priori obvious how to compare two different models. So, inspired by the CASP protein folding contest, we're running the Virtual Cell Challenge to create a standardized way for teams around the world to compare the efficacy of different approaches, to spread awareness of what works, and ultimately -- we hope -- to support faster progress overall. arcinstitute.org/news/virtua…

Claude Science is an amazing tool. But, as @pdhsu has pointed out, these binders weren’t designed by Claude, but rather by domain-specific models, most of which are publicly available, like RFdiffusion. Maybe this is a good time to explain the whole science behind this a bit, as well as the history of these models. A “binder” in this case is simply a protein or a fragment of a protein engineered to stick tightly and selectively to another protein. One example is a molecule that can latch onto a receptor and prevent it from interacting with its normal partner, thus blocking its function. Optimising "binders" is just one small part of the drug discovery pipeline. We already have AI models that are very good at the task of binder design. These models have been extensively trained on relevant domain specific data: int his case, protein structure data. One example is RFdiffusion, a de novo protein design model which was published in 2023. Unlike AlphaFold, which predicts existing protein structure from sequence, RFDiffusion can generate new candidate protein structures, including structures shaped to bind a specified patch on another protein. RFDiffusion was built by taking RoseTTAFold, a protein-structure-prediction model, (so similar in nature to AlphaFold, which was released in 2021, and retraining it as a diffusion model. What researchers did in practice was take experimentally determined protein structures from the Protein Data Bank, added noise to their coordinates, and taught the model to reconstruct them. The original RFdiffusion paper was already demonstrating experimentally validated binders with nanomolar affinities and a 19% hit rate on several test targets. So the core of this technology was not created through Claude. The key models for protein design are now three to five years old. What Claude adds is still amazing useful and labour saving (I've written about how I'm excited about it before), but imo it acts more like a very useful interface and orchestrator.

It is NOA day! 🎉 I feel blessed and excited to receive the K99/R00 from NIH NIGMS! Thanks to everyone who has supported me and continues to support me on this journey. I appreciate you all! 🙏🏾✨🧪@UofUBiochem @RutterLab

New paper from my group at @kochinstitute @MIT_IMES @MITBiology! I am thrilled to share that our paper describing scAmp, a new method for analyzing extrachromosomal DNA amplifications at single-cell resolution, has been published in @NatureComms. Thread below 👇

I'm glad to share the publication of new work carried from my postdoc with @weaverbird45 to my new laboratory @sbpdiscovery! Major implications for the relationship between immune oncology and metabolic syndrome. I'm deeply grateful to my co-authors! science.org/doi/10.1126/scia…

Thrilled to share our new work, co-developed w/Adrian Salic's lab: #bioorthogonal probes for PE, a multifunctional membrane lipid and source of several protein modifications. Congrats to @YuanTingCho1, @BrittMW08 , Jade Xia & Cindy Jao! onlinelibrary.wiley.com/doi/… #lipidtime

Hot off the press in Nature! After 10 years, 2,780 patients and 300+ scientists, we announce the Human Cancer Models Initiative (HCMI) release of 665 organoids and other next-generation models! All available to accelerate cancer drug discovery! rdcu.be/fx3I3

3 papers in @Nature today reflecting large scale efforts at mapping dependencies and multimodal molecular profiling data from a large panel of patient-derived 3D cancer models. This is DepMap on steroids! nature.com/articles/s41586-0… nature.com/articles/s41586-0… nature.com/articles/s41586-0…

To help, we created the Lipid Interactome Repository, an open-access platform that centralizes and standardizes proteomics data on lipid–protein interactions. lipidinteractome.org/

To understand what a lipid does, we need to know its partners. Which proteins bind lipids and how can we capture those interactions? Our new Nature Protocols paper provides a practical, step-by-step guide to identifying lipid-binding proteins. 🧵

Excited to share our new preprint! biorxiv.org/content/10.64898… We know that mitochondria make contacts with organelles, but determining whether these contacts establish functionally distinct mitochondrial populations has been challenging.

Identification of lipid specificity in membrane organizing protein complexes | bioRxiv biorxiv.org/content/10.64898…