scDOT: optimal transport for mapping senescent cells in spatial transcriptomics.

Nam D Nguyen, Lorena Rosas, Timur Khaliullin, Peiran Jiang, Euxhen Hasanaj, Jose A Ovando-Ricardez, Marta Bueno, Irfan Rahman, Gloria S Pryhuber, Dongmei Li, Qin Ma, Toren Finkel, Melanie Königshoff, Oliver Eickelberg, Mauricio Rojas, Ana L Mora, Jose Lugo-Martinez, Ziv Bar-Joseph

Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA.Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA. · pubmed

Paper

Abstract

The low resolution of spatial transcriptomics data necessitates additional information for optimal use. We developed scDOT, which combines spatial transcriptomics and single cell RNA sequencing to improve the ability to reconstruct single cell resolved spatial maps and identify senescent cells. scDOT integrates optimal transport and expression deconvolution to learn non-linear couplings between cells and spots and to infer cell placements. Application of scDOT to lung spatial transcriptomics data improves on prior methods and allows the identification of the spatial organization of senescent cells, their neighboring cells and novel genes involved in cell-cell interactions that may be driving senescence.

The following analysis is generated by AI and may contain errors. It is separate from the authors’ abstract and is not peer review.

Research summary

The paper addresses the identification of senescent cells, which are known to play a role in aging and age-related diseases. By developing a method that enhances the mapping of these cells in spatial transcriptomics, the research contributes to understanding the spatial organization and interactions of senescent cells, potentially informing strategies to address the root causes of aging. However, while the findings are solid and relevant, they do not represent a major breakthrough or transformative advancement in the field of longevity research, hence the moderate impact score.

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