8/ Enjoyed two exciting weeks with the teams of Philipp Mallm and Rene Jackstadt, diving into the Atera data, and we are looking forward to more of that. Our spatial transcriptomics work is supported by SATURN3/BMFTR and the MULTI-SPACE platform @mspacealliance.bsky.social.
7/ Adding immune cells to the picture: fetal-like cancer stem cells and CD4+ memory T cells co-localize at the invasive front while CD8+ effectors are excluded. Stem cell plasticity coupled to immune evasion. Everything visualized on one tissue section.
6/ The two stem cell poles sit in different compartments. Normal LGR5+ stem cells: crypt bases. Fetal-like cancer stem cells (IRC high): invasive front. At least five stem cell types could be resolved in total. This was not possible in our previous Xenium analysis.
5/ Ezgi Sen, a great PhD student in the Rippe and Stegle labs, led the downstream analysis: Atera clearly resolved 15 main cell clusters on one CRC section. Non-malignant epithelium splits into absorptive and secretory lineages with LGR5+ stem cells at the crypt bases.
4/ Building on Rene Jackstadt's CRC biology expertise, the interplay between two stemness poles is mapped: LGR5+ cancer stem cells expand the tumor. Fetal-like cancer stem cells are chemo-resistant, seed metastases and interconvert. Detecting them on FFPE was out of reach for us.
3/ In our work in the SATURN3 consortium on tumor heterogeneity saturn3.org, a crucial question is emerging: how can we resolve the different normal and cancer stem cell types together with immune cells at single-cell resolution?
2/ Atera maps ~18,000 genes in single cells on FFPE tissue with 2-3x higher sensitivity and a broader dynamic range than Xenium 5k in our hands. Having the whole transcriptome at this coverage matters when you are looking for expression signatures and low-abundance markers.
1/ Philipp Mallm from the @dkfz.bsky.social Single-cell Open Lab just broke the news at #AACR26: the first results on colorectal cancer (CRC) tissue analysis with the new Atera spatial transcriptomics platform from @10xgenomics.bsky.social. Is it "making the impossible possible?" 🧵
8/ 🤘 For those about to rock (around the Christmas tree), we salute you 🎸🎄: Isabelle Seufert & our team from @dkfz.bsky.social & BioQuant & @akispapantonis.bsky.social, Philipp Mallm, @s-anders.bsky.social & Petros Kolovos labs with support from @spp2202.bsky.social & @mspacealliance.bsky.social.
7/ 🌟 The broad applicability of our RWireX framework was shown in different cellular systems. In human blood cells, cell-type-specific regulatory programs could be distinguished, e.g., the DCs at the CD22 and the TBX21 loci had highest activity in B cells and mature CD8+ T cells, respectively.
6/ 🎯 Our AC/DC framework reveals how cells achieve precise gene control. TRGs with TF promoter binding show fastest induction. DCs enable coordinated burst-size increases, while ACs allow fine-tuned gene-specific regulation—working together to support complex programs.
5/ ⛰️ DCs are larger contiguous regions of simultaneously accessible chromatin sites. These domains exhibit locally increased transcription factor binding activity and may represent the genomic footprints of TF hubs.
4/ 🔗 ACs denote interactions between separated regulatory sites at ATAC peaks. We observed differences between rare and frequently occurring ACs, suggesting distinct roles of stochastic vs. architectural links.
3/ 💻 Using our new RWireX software (github.com/RippeLab/RWi...), we distinguish two regulatory chromatin modules: ACs (autonomous links of co-accessibility between separated sites of 1 kb size) and DCs (domains of contiguous co-accessibility of ~200 kb) that both can co-exist.
2/ 🔍 We investigated the proinflammatory response to TNF in primary human cells using #scRNA and #scATAC sequencing and fluorescence microscopy. We identified ~1,500 TNF-regulated genes (TRGs) that often clustered in the genome and exhibited induced co-expression.
1/ 🎄 We got our Christmas present today: "Two distinct chromatin modules regulate proinflammatory gene expression" is now published @natcellbio.nature.com doi.org/10.1038/s415.... Our study introduces a scATAC-seq-based framework for genome-wide analysis of gene regulation features.
Happy to report that the Xenium system for spatial transcriptomics in the Single Cell Open Lab www.dkfz.de/en/single-ce... @dkfz.bsky.social was the first one worldwide to pass the mark of 100 runs according to @10xgenomics.bsky.social. And it keeps on running with another one, so stay tuned...
"In our view, it [hexanediol] should thus be avoided and not be used as evidence for the formation of an assembly via phase separation or the fluid-like nature of a condensate in vitro or in vivo." doi.org/10.1038/s414...
These features allow it to predict immunotherapy response and point to potential universal T cell based therapies. Great multi-group effort led by Mirco Friedrich together with @michael-platten.bsky.social, @raabms.bsky.social, @stefaneichmueller.bsky.social, and many more collaborators.
Glad that the preprint on identifying and characterizing rare tumor-reactive T cells in multiple myeloma & AML patients is out now doi.org/10.1101/2025.... Single-cell TCR and transcriptome profiling & immunopeptidomics revealed conserved programs and shared non-canonical antigens.
Liquid-liquid phase separation of HP1? Not in our mouse fibroblasts… This paper by the Fabian Erdel group offers a fresh perspective on how this can be reconciled with seemingly conflicting reports: The phase separation propensity of HP1 decreases from yeast → fly → mouse. doi.org/10.1038/s414...
3/ Great joint effort with Philipp Mallm and the Single Cell Open Lab @dkfz.bsky.social, led by Anne Rademacher, Alik Huseynov, and Michele Bortolomeazzi, with key contributions from our colleagues at KiTZ Heidelberg, supported by the @mspacealliance.bsky.social program of @hlsalliance.bsky.social.
2/ Using medulloblastoma cryosections, we analyzed sensitivity, specificity, and spatial signal patterns to distinguish background from rare-cell signals. We also show how reimaging slides improves cell segmentation—and enables additional transcript and protein readouts from the same section.
1/ Spatial transcriptomics technologies are rapidly evolving. We compared five methods—Visium, RNAscope HiPlex, Molecular Cartography, Merscope, and Xenium—and developed technology-agnostic quality control metrics to guide their use: doi.org/10.1186/s130...
How do transcription compartments form — and does phase separation drive gene expression? I enjoyed discussing these questions with @akispapantonis.bsky.social a lot, and we put our thoughts together for @naturerevgenet.bsky.social, now out at rdcu.be/erP1u
From enhancer hijacking to ecDNA and onco-condensates – we review how changes in nuclear architecture drive oncogenic gene expression by disrupting enhancer–promoter communication. doi.org/10.1002/ijc..... Kudos to Isabelle Seufert, @claire-vrgs.bsky.social and Sina Wille 👏
Thanks to the Wissenschaftsrat @wissrat.bsky.social — the German Science and Humanities Council — for their clear statement expressing solidarity with US research institutions and scientists and defending academic freedom. www.wissenschaftsrat.de/SharedDocs/P...
“We all rely on science.” U.S. scientists are speaking out for scientific integrity and academic freedom. What they’re doing matters. We owe them our solidarity and a clear stand beside them.
www.nytimes.com/2025/03/31/s...
A mechanism for maintaining and spreading H3K9me3 in heterochromatin from the Fejes Toth and Aravin labs that depends on the local H3K9me3 density: HP1 dimers recruit SetDB1 to chromatin by simultaneously binding H3K9me3 on histone H3 and auto-methylated SetDB1. www.biorxiv.org/content/10.1...
