Excited to share our fun journey through time with the amazing team @D_Birschenkaum @FlorianIngelfi1 Yonathan @kathleenabadie @AssafWeiner from the @IdoAmitLab, measuring the temporal dynamics of immune cells in the GBM!

Nothing in biology makes sense… journals.plos.org/ploscompbi…

#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

🚀 Interested in joining my group as a PhD or Postdoc? I'm mentoring for the ETH AI Center's Doctoral and Postdoc Fellowship, working on biomolecular design. If you're excited about AIxBio, I'd love to hear from you. Apply now 👉 ai.ethz.ch/apply Deadline: Oct 27, 2026

How does interferon-alpha interfere with clonal evolution in human blood stem cells? We address it here @natureGenet: nature.com/articles/s41588-0… 🎉 Congrats to our super talented students Chhiring Lama, @danielle_isakov! Wonderful collab w/ Ron Hoffman. @WCMC, @WCMCPathology 🧵⤵

CRISPR screens are great at telling you what a gene is doing inside your cells. But what if you're interested in what's happening to its neighbors? Today, I'm excited to share match-seq, a new method that deciphers cell-cell interactions using barcoded RNA transfer. 1/9

Insane paper alert! Interferon is the one therapy that can actually deplete the mutant stem cells in myeloproliferative neoplasms, the blood cancers where the marrow keeps overproducing one lineage or another. The standard explanation for how it works was fairly mechanical. It pushes the mutant cells into the cell cycle, they divide, and eventually they exhaust or lose ground. Clean enough to teach. Lama et al. pulls it apart, and it can do that because of a set of single-cell methods that read out the mutation, the transcriptome, the surface proteins and the chromatin in the same cell, so the healthy stem cells sit inside the same patient as a built-in control, right next to their mutant neighbors. What they see is that interferon does not do one thing to a stem cell, it does two opposite things at once. Part of the stem pool is driven into an inflammatory myeloid progenitor state nobody had really described before, running on AP-1 and NF-κB. Another part is pushed toward lymphoid output. That lymphoid arm is easy to overlook, but it seems to be doing the clinical work, offsetting the myeloid overproduction that defines the disease, which is likely why counts normalize even in patients whose mutant fraction barely moves. Interestingly, the result that carries the paper is a negative one. If fitness ran on proliferation, the clones cycling fastest under interferon should be the ones whose fate you could predict. But the mutant cells cycled faster than the healthy ones throughout, before treatment and during it, and that gap predicted nothing about which clones expanded and which collapsed. What predicted it was whether a clone would follow that inflammatory myeloid path out of the stem state. The ones that resisted held on or grew. The ones that went along got cleared. So the drug is not really wearing the clone down. It is holding open an exit from the stem cell state, and resistance amounts to declining to take it. The mutations tilt the cell's transcription-factor wiring, PU.1 in particular, so mutant and healthy cells read the same interferon signal differently, and the mutant ones tend to sit tighter in the stem compartment…and the same resistance signature turns up in DNMT3A clonal hematopoiesis, so it is probably not tied to one mutation or one disease. If a clone survives by refusing to differentiate, killing it is beside the point. You would have to take the exit away, so it has to leave the stem state whether it resists or not, and I don't know what that looks like yet, or how much of this same quiet sorting runs in ordinary aging marrow where no one is being treated at all. @AnnaEnim @landau_lab and many more rockstars! #MyeloproliferativeNeoplasms #Hematology #StemCellBiology #SingleCell #Interferon Nature Genetics, doi.org/10.1038/s41588-026-0…

IDH-mutant gliomas often progress slowly, but inevitably recur and progress. Are there spatial organizing principles at the level of cell states that repeat across tumours during stages of tumour progression? cell.com/cancer-cell/fulltex… Out this week in @Cancer_Cell, our work with @RouvenHoefflin, @TiroshLab, @MarioSuva, @GaliliNoam, and Christopher Mount quantitatively maps two independent axes of tumour organization, revealing how they emerge at different stages of progression and in distinct tissue contexts. We hope that understanding these recurring spatial patterns and associations will reveal new opportunities to halt tumour progression.

🧵1/ Happy to share our new study: "Spatial analysis reveals the evolving organization of IDH-mutant glioma" We asked: How is spatial organization established in glioma before the hypoxic architecture of advanced disease emerges? cell.com/cancer-cell/fulltex…

Spatially instructed checkpoints in antitumor NK cell immunity dlvr.it/TVTN1K #immunology

Tumors don’t evolve alone. 📣 New @GenomeBiology Collection on the Tumor Microenvironment: single-cell, spatial & multi-omic studies of how the TME shapes tumor evolution and therapy response. Guest eds: @IamLinghua @kchenken & me 🗓️ until 19 May 2027 link.springer.com/collection…

Millions of PBMCs have been analyzed by scRNA-seq. Have we seen it all ? We profiled thousands of single PBMCs — proteomes and transcriptomes side by side — and uncovered functional coordination undetectable in the deepest scRNA-seq we could perform. biorxiv.org/content/10.64898… 1/

This #PostdocAppreciationWeek, we celebrate the early-career scientists whose bold ideas are helping shape the future of cancer treatment. Meet the 2025–2026 CRI Postdoctoral Fellows helping build a world immune to cancer: bit.ly/3UC0e5z

A privilege today to host Dr Linghua Wang at @NYUGSOM_Path ! Thanks @Aiims1742 for inviting her!

Heading across the river tomorrow for the Harvard Systems Biology Seminar at noon. I'll definitely discuss this paper and some nifty unpublished things. hope to see folks there! @harvardmed @HMS_SynBioHIVE @HMS_SysBio @baym @NoahOlsman

MIT published a brutally honest report on what AI is doing to students. A committee of professors and students spent five months studying how AI changed learning on campus, and the findings read like a warning to every university on the planet. Study groups are disappearing. Office hours are emptying out. Problem sets and take-home exams no longer prove anything, because AI can produce credible solutions to almost any written assignment in the undergraduate curriculum. Students who lean on chatbots lose mastery and confidence, and some slip into what the report calls cognitive surrender, reaching for AI at the first hint of struggle. The numbers are rough. 46 percent of surveyed MIT undergrads use LLMs daily. 90 percent worry about their own overreliance. Undergrads who feel AI makes them replaceable now outnumber those who feel it makes them capable. The committee's answer surprised me. They refused to fight AI with surveillance. The report calls AI detectors unreliable, says lockdown browsers feel like spying, and warns that policing students builds a classroom atmosphere of mutual distrust. Instead, MIT wants to rebuild education around the things AI can't replace. That means oral exams, semester portfolios, in-person project work, and a required social component in every subject. The report even floats the idea of rethinking grades entirely, since without a GPA to optimize, much of the incentive to cheat with AI evaporates. The committee warns professors against replacing undergrad research assistants with AI agents just because they're cheaper, because a university exists to grow people, not output. The most famous tech school on earth admitted the machines broke its way of teaching. Its answer is more humans, not more software.

4/ To peer into the interplay between enhancer and gene, we co-visualized eRNA and mRNA transcription in cis. We find that gene activation coincides with a drop in enhancer transcription and that optimal gene activation seems to be achieved at low levels of enhancer activity

🚨 New collaborative paper with the Thompson lab in @CellCellPress! Mitochondrial ATP shapes T cell fate by fueling chromatin remodeling. Congrats to 1st author Charles Ng & Craig—and to @Korbinian_NK, who led the @KlebanoffLab contribution! cell.com/cell/fulltext/S0092…

🧬🧪🔬Why are enhancers transcribed? How does it impact gene regulation? I’m excited to share our new paper in @ScienceMagazine showing that ncRNAs control the timing of gene activation in embryos. w/Mike Levine #ScienceResearch #RNA A few highlights 🧵👇 science.org/doi/10.1126/scie…

Mechanistic modeling reveals a configurable AP-1 network governing cell-state heterogeneity and adaptive plasticity in melanoma cells dlvr.it/TVR5pc

Plasticity of human microglia and brain perivascular macrophages in aging and Alzheimer’s disease nature.com/articles/s41588-0…