Tajparast Mohammad, Frigon Dominic
Microbial Community Engineering Laboratory, Department of Civil Engineering and Applied Mechanics, McGill University, 817 Sherbrooke Street West, Montreal, QC, H3A 0C3, Canada.
BMC Syst Biol. 2015 Aug 7;9:43. doi: 10.1186/s12918-015-0190-y.
Rhodococcus jostii RHA1 growing on different substrates is capable of accumulating simultaneously three types of carbon storage compounds: glycogen, polyhydroxyalkanoates (PHA), and triacylglycerols (TAG). Under nitrogen-limited (N-limited) condition, the level of storage increases as is commonly observed for other bacteria. The proportion of each storage compound changes with substrate, but it remains unclear what modelling approach should be adopted to predict the relative composition of the mixture of the storage compounds. We analyzed the growth of R. jostii RHA1 under N-limited conditions using a genome-scale metabolic modelling approach to determine which global metabolic objective function could be used for the prediction.
The R. jostii RHA1 model (iMT1174) produced during this study contains 1,243 balanced metabolites, 1,935 unique reactions, and 1,174 open reading frames (ORFs). Seven objective functions used with flux balance analysis (FBA) were compared for their capacity to predict the mixture of storage compounds accumulated after the sudden onset of N-limitation. Predictive abilities were determined using a Bayesian approach. Experimental data on storage accumulation mixture (glycogen, polyhydroxyalkanoates, and triacylglycerols) were obtained for batch cultures grown on glucose or acetate. The best FBA simulation results were obtained using a novel objective function for the N-limited condition which combined the maximization of the storage fluxes and the minimization of metabolic adjustments (MOMA) with the preceding non-limited conditions (max storage + environmental MOMA). The FBA solutions for the non-limited growth conditions were simply constrained by the objective function of growth rate maximization. Measurement of central metabolic fluxes by (13)C-labelling experiments of amino acids further supported the application of the environmental MOMA principle in the context of changing environment. Finally, it was found that the quantitative predictions of the storage mixture during N-limited storage accumulation were fairly sensitive to the biomass composition, as expected.
The genome-scale metabolic model analysis of R. jostii RHA1 cultures suggested that the intracellular reaction flux profile immediately after the onset of N-limited condition are impacted by the values of the same fluxes during the period of non-limited growth. PHA turned out to be the main storage pool of the mixture in R. jostii RHA1.
约氏红球菌RHA1在不同底物上生长时能够同时积累三种类型的碳储存化合物:糖原、聚羟基脂肪酸酯(PHA)和三酰甘油(TAG)。在氮限制(N限制)条件下,储存水平会升高,这在其他细菌中也很常见。每种储存化合物的比例会随底物而变化,但尚不清楚应采用何种建模方法来预测储存化合物混合物的相对组成。我们使用基因组规模代谢建模方法分析了约氏红球菌RHA1在N限制条件下的生长情况,以确定可用于预测的全局代谢目标函数。
本研究构建的约氏红球菌RHA1模型(iMT1174)包含1243种平衡代谢物、1935种独特反应和1174个开放阅读框(ORF)。比较了用于通量平衡分析(FBA)的七种目标函数预测N限制突然开始后积累的储存化合物混合物的能力。使用贝叶斯方法确定预测能力。获得了在葡萄糖或乙酸盐上生长的分批培养物中储存积累混合物(糖原、聚羟基脂肪酸酯和三酰甘油)的实验数据。使用一种针对N限制条件的新型目标函数获得了最佳的FBA模拟结果,该目标函数将储存通量最大化和代谢调整最小化(MOMA)与之前的非限制条件(最大储存量 + 环境MOMA)相结合。非限制生长条件下的FBA解仅受生长速率最大化目标函数的约束。通过氨基酸的(13)C标记实验对中心代谢通量的测量进一步支持了环境MOMA原理在变化环境中的应用。最后,发现N限制储存积累期间储存混合物的定量预测对生物量组成相当敏感,正如预期的那样。
约氏红球菌RHA1培养物的基因组规模代谢模型分析表明,N限制条件开始后立即出现的细胞内反应通量分布受非限制生长期间相同通量值的影响。结果表明,PHA是约氏红球菌RHA1中混合物的主要储存库。