{"title":"DeepLabCut-based automated system reveals diverse temperature tolerance among medaka strains and related Oryzias species.","authors":"Yoshiya Matsuo, Takuya Kato, Kiyoshi Naruse, Takashi Yoshimura, Tatsuhito Hasegawa, Tomoya Nakayama","doi":"10.1038/s41598-026-66712-w","DOIUrl":null,"url":null,"abstract":"<p><p>Temperature is a critical environmental factor influencing the physiology and behavior of ectothermic animals, yet conventional methods for evaluating thermal tolerance in fish rely on subjective manual observation of loss of equilibrium (LOE), limiting experimental throughput and introducing observer bias. Here, we developed an automated temperature tolerance evaluation system integrating DeepLabCut-based pose estimation with custom image processing algorithms to objectively quantify the timing of LOE during thermal stress tests. Our system incorporated region partitioning and color transformation preprocessing to improve keypoint detection accuracy, followed by a classification model combining ResNet34-based frame features with keypoint coordinates to objectively determine the timing of LOE without manual observation. Validation against manual annotation showed that the automated system achieved an accuracy comparable to the natural variability between trained investigators, and outperformed naive human observers, supporting its validity as an objective and reproducible alternative to manual scoring. Using this system, we characterized cold and heat tolerance across six medaka strains (Oryzias latipes: d-rR/TOKYO, HB11A, OK-Cab, HO5 and HdrR-II1; O. sakaizumii: HNI-II). Cold and heat tolerance assessment revealed inter-strain variation, with HdrR-II1 among the most cold- and heat-tolerant strains and HNI-II the least tolerant of both cold and heat stress. We further evaluated cold tolerance in medaka-related species (O. sinensis, O. cabaranensis, O. curvinotus, O. luzonensis, O. celebensis, and O. javanicus) and zebrafish (Danio rerio), revealing substantial interspecific variation that broadly corresponded with latitudinal distribution. O. latipes, distributed at the highest latitudes among the tested species, exhibited the greatest cold tolerance, whereas O. celebensis, O. javanicus, and other tropical or low-latitude species showed comparatively low cold tolerance. Our automated system provides a robust, high-throughput platform for thermal tolerance evaluation and, combined with the genetic and genomic resources available in medaka, establishes a foundation for elucidating the molecular mechanisms underlying temperature adaptation in fish.</p>","PeriodicalId":21811,"journal":{"name":"Scientific Reports","volume":"16 1","pages":""},"PeriodicalIF":4.9000,"publicationDate":"2026-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13562581/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scientific Reports","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1038/s41598-026-66712-w","RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Temperature is a critical environmental factor influencing the physiology and behavior of ectothermic animals, yet conventional methods for evaluating thermal tolerance in fish rely on subjective manual observation of loss of equilibrium (LOE), limiting experimental throughput and introducing observer bias. Here, we developed an automated temperature tolerance evaluation system integrating DeepLabCut-based pose estimation with custom image processing algorithms to objectively quantify the timing of LOE during thermal stress tests. Our system incorporated region partitioning and color transformation preprocessing to improve keypoint detection accuracy, followed by a classification model combining ResNet34-based frame features with keypoint coordinates to objectively determine the timing of LOE without manual observation. Validation against manual annotation showed that the automated system achieved an accuracy comparable to the natural variability between trained investigators, and outperformed naive human observers, supporting its validity as an objective and reproducible alternative to manual scoring. Using this system, we characterized cold and heat tolerance across six medaka strains (Oryzias latipes: d-rR/TOKYO, HB11A, OK-Cab, HO5 and HdrR-II1; O. sakaizumii: HNI-II). Cold and heat tolerance assessment revealed inter-strain variation, with HdrR-II1 among the most cold- and heat-tolerant strains and HNI-II the least tolerant of both cold and heat stress. We further evaluated cold tolerance in medaka-related species (O. sinensis, O. cabaranensis, O. curvinotus, O. luzonensis, O. celebensis, and O. javanicus) and zebrafish (Danio rerio), revealing substantial interspecific variation that broadly corresponded with latitudinal distribution. O. latipes, distributed at the highest latitudes among the tested species, exhibited the greatest cold tolerance, whereas O. celebensis, O. javanicus, and other tropical or low-latitude species showed comparatively low cold tolerance. Our automated system provides a robust, high-throughput platform for thermal tolerance evaluation and, combined with the genetic and genomic resources available in medaka, establishes a foundation for elucidating the molecular mechanisms underlying temperature adaptation in fish.
温度是影响恒温动物生理和行为的关键环境因素,但传统的评估鱼类热耐受性的方法依赖于主观的人工观察平衡损失(LOE),限制了实验吞吐量并引入了观察者偏差。在这里,我们开发了一个自动化的温度耐受性评估系统,该系统集成了基于deeplabcut的姿态估计和自定义图像处理算法,以客观地量化热应力测试中LOE的时间。我们的系统采用区域划分和颜色变换预处理来提高关键点检测精度,然后结合基于resnet34的帧特征和关键点坐标的分类模型,在不需要人工观察的情况下客观地确定LOE的时间。对人工标注的验证表明,自动化系统达到了与训练有素的调查人员之间的自然变异性相当的准确性,并且优于幼稚的人类观察者,支持其作为人工评分的客观和可重复替代方案的有效性。利用该系统对6个medaka菌株(Oryzias latipes: d-rR/TOKYO、HB11A、okc - cab、HO5和HdrR-II1; O. sakaizumii: HNI-II)的耐寒性和耐热性进行了表征。耐寒性和耐热性评估显示了品系间的差异,HdrR-II1是最耐寒和耐热的品系,而HNI-II是最不耐寒和耐热的品系。我们进一步评估了medkaka相关物种(O. sinensis, O. cabaranensis, O. curvinotus, O. luzonensis, O. celebensis和O. javanicus)和斑马鱼(Danio rerio)的耐寒性,揭示了大量的种间差异,与纬度分布大致一致。分布在高纬度地区的O. latipes的耐寒性最强,而O. celebensis、O. javanicus和其他热带或低纬度物种的耐寒性相对较低。我们的自动化系统为热耐受性评估提供了一个强大的、高通量的平台,并结合medaka的遗传和基因组资源,为阐明鱼类温度适应的分子机制奠定了基础。
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