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Domain-specific AI segmentation of IMPDH2 rod/ring structures in mouse embryonic stem cells

Lookup NU author(s): Emeritus Professor Neil PerkinsORCiD

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).

Abstract

© The Author(s) 2025.Background: Inosine monophosphate dehydrogenase 2 (IMPDH2) is an enzyme that catalyses the rate-limiting step of guanine nucleotides. In mouse embryonic stem cells (ESCs), IMPDH2 forms large multi-protein complexes known as rod-ring (RR) structures that dissociate when ESCs differentiate. Manual analysis of RR structures from confocal microscopy images, although possible, is not feasible on a large scale due to the quantity of RR structures present in each field of view. To address this analysis bottleneck, we have created a fully automatic RR image classification pipeline to segment, characterise and measure feature distributions of these structures in ESCs. Results: We find that this model can automatically segment images with a Dice score of over 80% for both rods and rings for in-domain images compared to expert annotation, with a slight drop to 70% for datasets out of domain. Important feature measurements derived from these segmentations show high agreement with the measurements derived from expert annotation, achieving an R2 score of over 90% for counting the number of RRs over the dataset. Conclusions: We have established for the first time a quantitative baseline for RR distribution in pluripotent ESCs and have made a pipeline available for training to be applied to other models in which RR remain an open topic of study.

Publication metadata

Author(s): Ball STM, Hennessy MJ, Tan Y, Hoettges KF, Perkins ND, Wilkinson DJ, White MRH, Zheng Y, Turner DA

Publication type: Article

Publication status: Published

Journal: BMC Biology

Year: 2025

Volume: 23

Issue: 1

Online publication date: 12/05/2025

Acceptance date: 28/04/2025

Date deposited: 27/05/2025

ISSN (electronic): 1741-7007

Publisher: BioMed Central Ltd

DOI: 10.1186/s12915-025-02226-7

Data Access Statement: All software and code generated during this study are included in this published article’s additional information files and have been deposited in Zenodo https://doi.org/10.5281/zenodo.15268276 [30] and github [https://github. com/gastruloids/gandalf].

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