bioRxivCell BiologyPreprint
Same-section spatial metabolo-transcriptomics using Stereo-meta-seq reveals DHA-driven kidney maturation
Roan H van ScheppingeniD, Baihua WuiD, Yumeng Zhang, Sytske Schep, Ulli Winter, Fengxiang WangiD, Yilong ZouiD, Susana M. Chuva de Sousa LopesiD, David L. SilveriD, И. В. СидоровiD, Martin A. GieraiD, Bernard M. van den BergiD, Cathelijne W. van den BergiD, Lijian HuiiD, Ton J. RabelinkiD, Gangqi WangiD
Abstract
A central unresolved question in developmental biology is whether local metabolites merely accompany, or actively instruct, tissue maturation. Addressing this question requires direct spatial coupling of metabolic states with genome-wide transcriptional programs in situ at high spatial resolution, which existing approaches do not readily achieve. Here, we introduce Stereo-meta-seq, a workflow that integrates quantitative MALDI-MSI with Stereo-seq spatial transcriptomics within a single tissue section. A conductive adapter was designed to overcome the electrical incompatibility of non-conductive Stereo-seq chips with vacuum MALDI platforms, improving efficiency of MSI detection that preserves RNA integrity. MALDI laser-ablation marks are retained in downstream Stereo-seq data and serve as intrinsic fiducials for direct co-registration at 10 m or 20 m resolution, enabling fine grained spatial metabolite-transcript integration. Applying Stereo-meta-seq to human kidney development, we uncover selective enrichment of docosahexaenoic acid (DHA) in maturing proximal tubules. Functional studies in human kidney organoids demonstrate that DHA activates PPAR-and HNF4-driven transcriptional programs and promotes proximal tubule maturation in vitro and after transplantation in vivo. These findings identify lipid metabolism as an instructive regulator of human nephrogenesis and establish Stereo-meta-seq as a practical platform for dissecting metabolite-gene coupling and tissue heterogeneity in situ.
- organism: human
- assay: spatial transcriptomics
- assay: metabolomics
- research focus: cell type annotation
- research focus: spatial domain detection
- approach: experimental assay
- Citations
- 0
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Unified Mass Imaging Maps the Lipidome of Vertebrate Development
Halima Hannah Schede, Leila Haj Abdullah Alieh, … Gioele La Manno·Nature MethodsPeer-reviewed·Sep 1, 2025
- Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball patterned arrays
- OpenFISH enables integrated high-resolution spatial transcriptomics and metabolomics on a single tissue section
Xinyang Li, Yuan Huang, … Lihui Duan·bioRxiv·Aug 19, 2025
- Single-embryo metabolomics reveals developmental metabolism in the early Drosophila embryo
J. Eduardo Pérez-Mojica, Zachary Madaj, … Adelheid M. Lempradl·bioRxiv·Apr 17, 2024
- Spatial quantitative metabolomics enables identification of remote and sustained ipsilateral cortical metabolic reprogramming after stroke
Gangqi Wang, Bernard M. van den Berg, … Ton J. Rabelink·Nature MetabolismPeer-reviewed·Aug 5, 2025
- Characterization of metabolic compartmentalization in the liver using spatially resolved metabolomics
J. van der Reest, S. A. Stopka, … N. Y. R. Agar·bioRxiv·Dec 13, 2021