@erturklab
AI and tissue clearing-based technologies for health. Director at Helmholtz Munich, Full professor at LMU Munich, and CEO of Deep Piction (@deeppiction.bsky.social) We’re🇩🇪🇹🇷🇭🇷🇨🇳🇮🇹🇮🇳🇸🇮🇴🇲🇨🇱🇭🇺🇧🇬🇺🇦🇷🇴🇦🇹🇹🇼🏳🌈
In this recent Nature Methods Perspective, I outline how tissue clearing, spatial-omics, and AI converge to create deep 3D histology, enabling unbiased, organism-scale biology and next-generation digital pathology. www.nature.com/articles/s41...
A new preprint introduces aDISCO, a DISCO-based clearing approach that makes whole archival FFPE human tissues transparent and antibody-compatible, enabling true 3D light-sheet histology across brain & multiple organs at cellular resolution. Aguzzi & Helmchen teams.
www.biorxiv.org/content/10.1...
We’re hiring – Computer Science PhD at iBIO (Helmholtz Munich / LMU).
Build AI-driven, whole-body multi-omics atlases by combining scRNA-seq, spatial transcriptomics, proteomics & 3D imaging.
Looking for strong omics data analysis skills with ML/DL.
Apply or share:
www.linkedin.com/jobs/view/43...
This is going to be fun! I promise!
My team at Deep Piction (Munich) is hiring a Senior Director, Drug Discovery (Long Covid) to build and lead our early discovery engine. If you have 10+ years in early-stage biotech/pharma, let’s talk.
www.linkedin.com/jobs/view/43...
Most transcriptomics studies sample ~0.001% of a mouse. Which region do we choose? Often: we guess.
Meet DISCO-seq 🤗 flipping the order: RNA-preserving clearing → whole-organ/whole-body 3D imaging → pick ROIs in 3D → unbiased scRNA-seq.
Preprint: www.biorxiv.org/content/10.6...
Single cell transcriptomics from cleared tissue? Impossible you say? Check out our latest preprint!
Very cool paper in NBT from the Dietz and Erturk labs @erturklab.bsky.social @markuselsner.bsky.social go.nature.com/4gNLjeC
✨ DISCO-seq bridges 3D anatomy and single-cell genomics.
Unbiased, imaging-guided, whole-organ transcriptomics—from brain tumors to infection biology.
Take-home: most spatial biology still starts from 2D slices + predefined ROIs/genes.
DISCO-seq changes the paradigm: whole-organ/whole-body 3D first → unbiased single-cell transcriptomics second.
Spike S1 induces region- and condition-specific gene programs, highlighting spatial immune specialization along the gut.
Small intestine scRNA-seq preserves cell-type diversity across conditions/regions (PBS vs S1; duodenum vs ileum) with expected epithelial, immune, and stromal populations.
Whole-body application: 3D DISCO imaging maps organ-specific SARS-CoV-2 Spike S1 tropism.
In the gut, we see distinct enrichment patterns (duodenum vs ileum), enabling unbiased ROI selection.
DISCO-seq resolves region- and cell-type-specific programs in GBM: neurons and microglia show distinct states across core vs remote niches.
Imaging-guided ROI selection enables spatially resolved transcriptomics: tumor core vs remote rostral/caudal ROIs within the intact brain.
3D quantification maps tumor burden across annotated brain regions, distinguishing small blobs, clusters, and large lesions—revealing region-specific heterogeneity
Glioblastoma: whole-brain 3D imaging reveals dissemination beyond the primary lesion.
Satellite tumors + contralateral spread become visible in 3D—often missed in 2D or standard clinical imaging.
Workflow in one line:
RNA-preserving clearing → probe hybridization & partitioning → library construction → sequencing → analysis.
Cell-type composition and gene detection are well preserved.
Platform-agnostic: strong libraries across technologies (single cells and nuclei).
Decrosslinking is critical—markedly improves fragment size and library quality.
Key challenge: solvent-based clearing usually destroys RNA.
DISCO-seq systematically optimized clearing chemistries (THF/DCM + controlled rehydration) to preserve RNA integrity comparable to fresh/fixed tissue.
Spatial methods often rely on thin sections or predefined gene panels.
DISCO-seq keeps the global 3D context and lets you select ROIs anatomically—then profile them at single-cell resolution.
Most transcriptomics studies sample ~0.001% of a mouse. Which region do we choose? Often: we guess.
Meet DISCO-seq 🤗 flipping the order: RNA-preserving clearing → whole-organ/whole-body 3D imaging → pick ROIs in 3D → unbiased scRNA-seq.
Preprint: www.biorxiv.org/content/10.6...
Congratulations to our scientist, Laurent Simons, for earning his PhD in quantum physics at just 15—an exceptional achievement.
In our lab, Laurent’s work focuses on in silico biology to accelerate treatment of devastating diseases. We’re thrilled to have him on the team.
Hiring: PostDoc in Tissue Clearing & 3D Histopathology 🧪🖥️
My lab at Helmholtz Munich is seeking a highly motivated PostDoc/Scientist to strengthen our efforts in advanced imaging of cancer tissues.
More info: www.linkedin.com/posts/ali-ma...
Be your own advocate. Share your preprint on social media. Write a short thread explaining the key findings. If you're not at a top-tier institution, you have to be even more proactive. Create your own audience. It shows confidence and initiative.
Post to a preprint server (e.g., bioRxiv). The fear of being scooped is mostly a myth now. A preprint plants your flag, establishes priority, and gets your work seen by reviewers in your field early. It’s free advertising.
Finally, don't wait for publication day to create visibility. The work starts months earlier.
"We developed a method to do X, which for the first time allows us to solve problem Y." No jargon.
Focus on the Story, Not Just Data: Editors are looking for a compelling narrative along with great science. What is the problem? What was the breakthrough? Why does it matter to a broad audience?
Also, master your pitch!
Once you get that face-to-face meeting, you have about 60 seconds to make an impact. Don't waste it.
Nail the One-Liner: Start with a single, clear sentence that states your main finding and its importance.
Don't just do great science and hope it gets noticed. Be strategic, be human, and actively create your opportunities.
What else would you suggest to the young generation that their papers get published well?