Department of Chemical Engineering, The Pennsylvania State University, University Park, PA 16801, USA.
Beijing Key Lab of Bioprocess, College of Life and Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China.
Bioinformatics. 2017 Nov 15;33(22):3603-3609. doi: 10.1093/bioinformatics/btx453.
In a genome-scale metabolic model, the biomass produced is defined to have a molecular weight (MW) of 1 g mmol-1. This is critical for correctly predicting growth yields, contrasting multiple models and more importantly modeling microbial communities. However, the standard is rarely verified in the current practice and the chemical formulae of biomass components such as proteins, nucleic acids and lipids are often represented by undefined side groups (e.g. X, R).
We introduced a systematic procedure for checking the biomass weight and ensuring complete mass balance of a model. We identified significant departures after examining 64 published models. The biomass weights of 34 models differed by 5-50%, while 8 models have discrepancies >50%. In total 20 models were manually curated. By maximizing the original versus corrected biomass reactions, flux balance analysis revealed >10% differences in growth yields for 12 of the curated models. Biomass MW discrepancies are accentuated in microbial community simulations as they can cause significant and systematic errors in the community composition. Microbes with underestimated biomass MWs are overpredicted in the community whereas microbes with overestimated biomass weights are underpredicted. The observed departures in community composition are disproportionately larger than the discrepancies in the biomass weight estimate. We propose the presented procedure as a standard practice for metabolic reconstructions.
The MALTAB and Python scripts are available in the Supplementary Material.
costas@psu.edu or joshua.chan@connect.polyu.hk.
Supplementary data are available at Bioinformatics online.
在基因组规模的代谢模型中，生物量的定义为 1 g mmol-1 的分子量。这对于正确预测生长产量、对比多个模型以及更重要的是对微生物群落进行建模至关重要。然而，在当前实践中，这一标准很少得到验证，并且生物量成分（如蛋白质、核酸和脂质）的化学公式通常由未定义的侧基（例如 X、R）表示。
我们引入了一种系统的程序来检查模型的生物量重量并确保其完全质量平衡。在检查了 64 个已发表的模型后，我们发现了显著的偏差。34 个模型的生物量重量差异为 5-50%，而 8 个模型的差异>50%。共有 20 个模型经过人工校对。通过最大化原始与校正后的生物量反应，通量平衡分析显示 12 个经过校对的模型的生长产量差异>10%。在微生物群落模拟中，生物量 MW 差异会被放大，因为它们会导致群落组成中出现显著且系统的误差。生物量 MW 被低估的微生物在群落中被过度预测，而生物量重量被高估的微生物则被低估。观察到的群落组成偏差比生物量重量估计的偏差大得多。我们建议将提出的程序作为代谢重建的标准实践。
MATLAB 和 Python 脚本可在补充材料中获得。
costas@psu.edu 或 joshua.chan@connect.polyu.hk。
补充数据可在 Bioinformatics 在线获得。
