Univ. Lille, CNRS, Inserm, CHU Lille, Institut Pasteur de Lille, UMR9020-U1277 - CANTHER - Cancer Heterogeneity Plasticity and Resistance to Therapies, F-59000, Lille, France.
Univ. Lille, CNRS, UMR 8523 - PhLAM - Physique des Lasers Atomes et Molécules, F-59000, Lille, France.
Metab Eng. 2023 Jan;75:100-109. doi: 10.1016/j.ymben.2022.11.001. Epub 2022 Nov 17.
Carbon isotope labeling method is a standard metabolic engineering tool for flux quantification in living cells. To cope with the high dimensionality of isotope labeling systems, diverse algorithms have been developed to reduce the number of variables or operations in metabolic flux analysis (MFA), but lacks generalizability to non-stationary metabolic conditions. In this study, we present a stochastic simulation algorithm (SSA) derived from the chemical master equation of the isotope labeling system. This algorithm allows to compute the time evolution of isotopomer concentrations in non-stationary conditions, with the valuable property that computational time does not scale with the number of isotopomers. The efficiency and limitations of the algorithm is benchmarked for the forward and inverse problems of 13C-DMFA in the pentose phosphate pathways, and is compared with EMU-based methods for NMFA and MFA including the central carbon metabolism. Overall, SSA constitutes an alternative class to deterministic approaches for metabolic flux analysis that is well adapted to comprehensive dataset including parallel labeling experiments, and whose limitations associated to the sampling size can be overcome by using Monte Carlo sampling approaches.
碳同位素标记方法是一种标准的代谢工程工具，用于量化活细胞中的通量。为了应对同位素标记系统的高维性，已经开发了多种算法来减少代谢通量分析（MFA）中的变量或操作数，但缺乏对非稳态代谢条件的通用性。在这项研究中，我们提出了一种基于同位素标记系统的化学主方程的随机模拟算法（SSA）。该算法允许在非稳态条件下计算同位素质谱浓度的时间演化，具有计算时间不随同位素质谱数增加而增加的宝贵特性。我们对标了正向和反向 13C-DMFA 在戊糖磷酸途径中的问题，并与基于 EMU 的 NMFA 和 MFA 方法进行了比较，包括中心碳代谢。总的来说，SSA 构成了代谢通量分析的确定性方法的替代方法，它非常适合包括平行标记实验在内的综合数据集，并且可以通过使用蒙特卡罗抽样方法克服与抽样大小相关的限制。
