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验证小型陆生昆虫高温耐受性不同测量方法的自动化。

Validating the automation of different measures of high temperature tolerance of small terrestrial insects.

机构信息

Department of Biology, Aarhus University, Ny Munkegade 114, Bldg. 1540, 8000 Aarhus C, Denmark.

Department of Biology, Aarhus University, Ny Munkegade 114, Bldg. 1540, 8000 Aarhus C, Denmark.

出版信息

J Insect Physiol. 2022 Feb-Mar;137:104362. doi: 10.1016/j.jinsphys.2022.104362. Epub 2022 Jan 31.

Abstract

Accurately phenotyping numerous test subjects is essential for most experimental research. Collecting such data can be tedious or time-consuming, and it can be biased or limited using manual observations. The thermal tolerance of small ectotherms is a good example of this type of phenotypic data, and it is widely used to investigate thermal adaptation, acclimation capacity and climate change resilience of small ectotherms. Here, we present the results of automatically generated thermal tolerance data using motion-tracking software on video recordings. The automatization was applied to two different heat tolerance assays, in two Drosophila species and used temperature acclimation to create variation in thermal tolerances. We find similar effect sizes of acclimation and hardening responses between manual and automated approaches, but different absolute tolerance estimates. This discrepancy likely reflects both technical differences in the assay conditions as well as the measured end-points of the assays. We conclude that both methods generate biological meaningful results, which reflect different aspects of the thermal biology, find no evidence of inflated variance in the manually scored assays, but find that automation can increase throughput several times without compromising quality. Further we show that the method can be applied to a wide range of arthropod taxa. We suggest that this automated method is a useful example of high throughput phenotyping. Further, we suggest this approach might be applied to other tedious laboratory traits, such as desiccation or starvation tolerance, with similar benefits to throughput but caution that the interpretation and potential comparison to results using different methodology rely on thorough validation of the assay and the involved biological mechanism.

摘要

准确地表征大量的实验对象对于大多数实验研究至关重要。收集此类数据可能既繁琐又耗时,如果使用手动观察,数据可能会存在偏差或受限。小型变温动物的耐热性就是这种表型数据的一个很好的例子,它被广泛用于研究小型变温动物的热适应、驯化能力和对气候变化的恢复能力。在这里,我们展示了使用视频记录中的运动跟踪软件自动生成热耐受数据的结果。该自动化方法应用于两种不同的耐热性测定方法,在两种果蝇物种中,并使用温度驯化来产生热耐受的变化。我们发现,在手动和自动方法之间,驯化和硬化反应的效应大小相似,但绝对耐受估计值不同。这种差异可能反映了测定条件的技术差异以及测定终点的不同。我们得出的结论是,两种方法都产生了具有生物学意义的结果,这些结果反映了热生物学的不同方面,没有发现手动评分测定中存在方差膨胀的证据,但发现自动化可以在不影响质量的情况下将通量提高数倍。此外,我们还表明,该方法可以应用于广泛的节肢动物类群。我们建议这种自动化方法是高通量表型的一个有用示例。此外,我们建议这种方法可以应用于其他繁琐的实验室特征,如干燥或饥饿耐受性,具有类似的通量优势,但需要注意的是,对测定和涉及的生物学机制进行彻底验证对于解释和潜在比较使用不同方法学获得的结果是至关重要的。

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