Shichkova Polina, Coggan Jay S, Markram Henry, Keller Daniel
Blue Brain Project, École Polytechnique Fédérale de Lausanne, Geneva, Switzerland.
Laboratory of Neural Microcircuitry, Brain Mind Institute, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
Front Mol Neurosci. 2021 Nov 10;14:604559. doi: 10.3389/fnmol.2021.604559. eCollection 2021.
Accurate molecular concentrations are essential for reliable analyses of biochemical networks and the creation of predictive models for molecular and systems biology, yet protein and metabolite concentrations used in such models are often poorly constrained or irreproducible. Challenges of using data from different sources include conflicts in nomenclature and units, as well as discrepancies in experimental procedures, data processing and implementation of the model. To obtain a consistent estimate of protein and metabolite levels, we integrated and normalized data from a large variety of sources to calculate Adjusted Molecular Concentrations. We found a high degree of reproducibility and consistency of many molecular species across brain regions and cell types, consistent with tight homeostatic regulation. We demonstrated the value of this normalization with differential protein expression analyses related to neurodegenerative diseases, brain regions and cell types. We also used the results in proof-of-concept simulations of brain energy metabolism. The standardized Brain Molecular Atlas overcomes the obstacles of missing or inconsistent data to support systems biology research and is provided as a resource for biomolecular modeling.
准确的分子浓度对于生化网络的可靠分析以及分子生物学和系统生物学预测模型的创建至关重要,然而此类模型中使用的蛋白质和代谢物浓度往往受到的限制不足或不可重复。使用来自不同来源的数据面临的挑战包括命名法和单位的冲突,以及实验程序、数据处理和模型实施方面的差异。为了获得蛋白质和代谢物水平的一致估计,我们整合并标准化了来自各种来源的数据,以计算调整后的分子浓度。我们发现许多分子种类在脑区和细胞类型之间具有高度的可重复性和一致性,这与严格的稳态调节一致。我们通过与神经退行性疾病、脑区和细胞类型相关的差异蛋白质表达分析证明了这种标准化的价值。我们还将结果用于脑能量代谢的概念验证模拟。标准化的脑分子图谱克服了数据缺失或不一致的障碍,以支持系统生物学研究,并作为生物分子建模的资源提供。