Dept. Psychology and Neuroscience, Dalhousie University, Halifax, NS B3H3X5, Canada.
Comp Biochem Physiol B Biochem Mol Biol. 2021 Aug-Sep;255:110564. doi: 10.1016/j.cbpb.2021.110564. Epub 2021 Jan 27.
An explosion of data has provided detailed information about organisms at the molecular level. For some traits, this information can accurately predict phenotype. However, knowledge of the underlying molecular networks often cannot be used to accurately predict higher order phenomena, such as the response to multiple stressors. This failure raises the question of whether methodological reductionism is sufficient to uncover predictable connections between molecules and phenotype. This question is explored in this paper by examining whether our understanding of the molecular responses to food limitation and pathogens in insects can be used to predict their combined effects. The molecular pathways underlying the response to starvation and pathogen attack in insects demonstrates the complexity of real-world physiological networks. Although known intracellular signaling pathways suggest that food restriction should enhance immune function, a reduction in food availability leads to an increase in some immune components, a decrease in others, and a complex effect on disease resistance in insects such as the caterpillar Manduca sexta. However, our inability to predict the effects of food restriction on disease resistance is likely due to our incomplete knowledge of the intra- and extracellular signaling pathways mediating the response to single or multiple stressors. Moving from molecules to organisms will require novel quantitative, integrative and experimental approaches (e.g. single cell RNAseq). Physiological networks are non-linear, dynamic, highly interconnected and replete with alternative pathways. However, that does not make them impossible to predict, given the appropriate experimental and analytical tools. Such tools are still under development. Therefore, given that molecular data sets are incomplete and analytical tools are still under development, it is premature to conclude that methodological reductionism cannot be used to predict phenotype.
数据的爆炸式增长为我们提供了关于生物体分子水平的详细信息。对于某些特征,这些信息可以准确预测表型。然而,对于潜在的分子网络的了解通常不能用于准确预测更高阶的现象,例如对多种胁迫的反应。这种失败引发了一个问题,即方法还原论是否足以揭示分子和表型之间可预测的联系。本文通过研究我们对昆虫中食物限制和病原体的分子反应的理解是否可以用于预测它们的综合效应,探讨了这个问题。昆虫对饥饿和病原体攻击的分子反应途径表明了真实生理网络的复杂性。尽管已知的细胞内信号通路表明食物限制应该增强免疫功能,但食物供应的减少会导致某些免疫成分增加,其他成分减少,并且对毛毛虫 Manduca sexta 等昆虫的疾病抵抗力产生复杂的影响。然而,我们无法预测食物限制对疾病抵抗力的影响,可能是因为我们对介导单一或多种胁迫反应的细胞内和细胞外信号通路的了解不完整。从分子到生物体的转变需要新颖的定量、综合和实验方法(例如单细胞 RNAseq)。生理网络是非线性的、动态的、高度互联的,并且充满了替代途径。然而,考虑到适当的实验和分析工具,这并不意味着它们无法预测。这些工具仍在开发中。因此,鉴于分子数据集不完整,分析工具仍在开发中,过早地得出结论认为方法还原论不能用于预测表型还为时过早。