Spatiotemporal modeling of molecular holograms

Quantifying spatiotemporal dynamics during embryogenesis is crucial for understanding congenital diseases. We developed Spateo (https://github.com/aristoteleo/spateo-release), a 3D spatiotemporal modeling framework, and applied it to a 3D mouse embryogenesis atlas at E9.5 and E11.5, capturing eight million cells. Spateo enables scalable, partial, non-rigid alignment, multi-slice refinement, and mesh correction to create molecular holograms of whole embryos. It introduces digitization methods to uncover multi-level biology from subcellular to whole organ, identifying expression gradients along orthogonal axes of emergent 3D structures, e.g., secondary organizers such as midbrain-hindbrain boundary (MHB). Spateo further jointly models intercellular and intracellular interaction to dissect signaling landscapes in 3D structures, including the zona limitans intrathalamica (ZLI). Lastly, Spateo introduces "morphometric vector fields" of cell migration and integrates spatial differential geometry to unveil molecular programs underlying asymmetrical murine heart organogenesis and others, bridging macroscopic changes with molecular dynamics. Thus, Spateo enables the study of organ ecology at a molecular level in 3D space over time.

Authors

Institutions

Publication Details

Journal
Cell
Published
2024-11-11
DOI
https://doi.org/10.1016/j.cell.2024.10.011
Citations
74
Primary Topic
Photoreceptor and optogenetics research
Type
article
Field-Weighted Citation Impact
19.85
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Spatiotemporal modeling of molecular holograms

David Ellison, Sha Liao, Lulu Zuo, Shijie Hao et al.
74 citations
Cell
Photoreceptor and optogenetics research
19.85
article

Spatiotemporal modeling of molecular holograms

David Ellison, Sha Liao, Lulu Zuo, Shijie Hao, Yiwei Lai, Shiping Liu, Jonathan S. Weissman, Yinqi Bai, Zehua Jing, Longqi Liu, Hailin Pan, Jiajun Yao, Jiayi Ma, Shuai Wang, S. B. King, Xiaojie Qiu, Xinchao Wu, Zhencheng Tu, Zhuoxuan Yang, Ying Gu, Huiwen Zheng, Jinpei Lin, Daniel Y. Zhu, Kyung Hoi Min, Ao Chen, Mei Li, Yuxiang Li, Chao Liu, Yong Zhang, Xun Xu, Liang Wu, Qingquan Zhang, Zhewei Zhang, Siyang Yu, Qi Fang, Mengnan Cheng, Yifan Lu, Mingyue Wang
article en
74 citations

Abstract

Quantifying spatiotemporal dynamics during embryogenesis is crucial for understanding congenital diseases. We developed Spateo (https://github.com/aristoteleo/spateo-release), a 3D spatiotemporal modeling framework, and applied it to a 3D mouse embryogenesis atlas at E9.5 and E11.5, capturing eight million cells. Spateo enables scalable, partial, non-rigid alignment, multi-slice refinement, and mesh correction to create molecular holograms of whole embryos. It introduces digitization methods to uncover multi-level biology from subcellular to whole organ, identifying expression gradients along orthogonal axes of emergent 3D structures, e.g., secondary organizers such as midbrain-hindbrain boundary (MHB). Spateo further jointly models intercellular and intracellular interaction to dissect signaling landscapes in 3D structures, including the zona limitans intrathalamica (ZLI). Lastly, Spateo introduces "morphometric vector fields" of cell migration and integrates spatial differential geometry to unveil molecular programs underlying asymmetrical murine heart organogenesis and others, bridging macroscopic changes with molecular dynamics. Thus, Spateo enables the study of organ ecology at a molecular level in 3D space over time.

CellVol. 187(26)
BGI Group (China) (CN), Lucile Packard Children's Hospital (US), Southern University of Science and Technology (CN), University of California San Diego (US), Wuhan University (CN), Northwest University (CN), E-Techco Group (China) (CN), Shenzhen Bay Laboratory (CN), Ginkgo Bioworks, Inc. (United States) (US), R2M Solution (Italy) (IT), Botswana Geoscience Institute (BW), Sanya University (CN), Whitehead Institute for Biomedical Research (US), University of Chinese Academy of Sciences (CN), BGI Research (CN), Massachusetts Institute of Technology (US), Stanford University (US)
Openalex Percentile: Top 0%
Photoreceptor and optogenetics research
19.85
DOIOpen Access PDFOpenAlex
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.