美国斯坦福大学Markus W. Covert小组在研究中取得进展。他们利用机械模拟同时对异质性大肠杆菌数据集进行了交叉评估。2020年7月24日，《科学》发表了这一成果。

大肠杆菌大规模机制模型的建立使研究人员能够基于数十年来各个研究组报道的测量结果，对庞大的异构数据集进行集成和交叉评估。研究人员在数据中发现了与功能性结果不一致的地方，例如数据揭示的核糖体和RNA聚合酶的总产量与测量得到的细胞复制倍增时间不一致，所测得的代谢参数既不与各自完全匹配也不与总体生长相匹配，并且在细胞周期过程中缺少必需的蛋白质，而细胞对于这种缺乏反应灵敏。

最后，从整体上考虑这些数据可以成功预测新的实验结果，正如本文中的例子：蛋白质的半衰期。

据介绍，生物数据的广泛异质性给数据分析和解释带来了挑战。

附：英文原文

Title: Simultaneous cross-evaluation of heterogeneous E. coli datasets via mechanistic simulation

Author: Derek N. Macklin, Travis A. Ahn-Horst, Heejo Choi, Nicholas A. Ruggero, Javier Carrera, John C. Mason, Gwanggyu Sun, Eran Agmon, Mialy M. DeFelice, Inbal Maayan, Keara Lane, Ryan K. Spangler, Taryn E. Gillies, Morgan L. Paull, Sajia Akhter, Samuel R. Bray, Daniel S. Weaver, Ingrid M. Keseler, Peter D. Karp, Jerry H. Morrison, Markus W. Covert

Issue&Volume: 2020/07/24

Abstract: The extensive heterogeneity of biological data poses challenges to analysis and interpretation. Construction of a large-scale mechanistic model of Escherichia coli enabled us to integrate and cross-evaluate a massive, heterogeneous dataset based on measurements reported by various groups over decades. We identified inconsistencies with functional consequences across the data, including that the total output of the ribosomes and RNA polymerases described by data are not sufficient for a cell to reproduce measured doubling times, that measured metabolic parameters are neither fully compatible with each other nor with overall growth, and that essential proteins are absent during the cell cycle—and the cell is robust to this absence. Finally, considering these data as a whole leads to successful predictions of new experimental outcomes, in this case protein half-lives.

DOI: 10.1126/science.aav3751

Source: https://science.sciencemag.org/content/369/6502/eaav3751