碳酸氢钠体系中基于pH特征的聚球藻生长模型构建与验证

Growth-pH Coupling Mechanism and Prediction Model for Synechococcus in Sodium Bicarbonate Culture System

摘要

针对聚球藻培养过程中pH波动引发生长受限、生长状态难以实时精准预测的问题，提出了基于在线pH信号的多因子耦合生长预测模型。设置不同初始接种浓度（以730 nm波长下的光密度OD₇₃₀表示，记为A（无量纲），其取值范围为0.1～1.3）、光照强度（14～181 μmol·m^-2·s^-1）和碳酸氢钠物质的量浓度（25～125 mmol/L），监测聚球藻的生物量与pH动态变化数据；在无机碳形态转换机理分析基础上，采用Logistic模型定量表征生物量与pH的响应关系，并进一步构建多因子耦合生长预测模型。研究结果表明，生物量积累与培养液pH上升高度同步，生长限制主要由pH升高促使HCO₃^-向CO₃^2-转化，导致可利用无机碳不足引起；Logistic模型在15组条件下拟合优度R²均大于0.98，拐点pH为9.5～9.8，且与碳源可利用性转折节点高度吻合；生长预测模型在两组独立实验中预测拟合优度R²_pred分别为0.987 9、0.885 8，平均绝对误差E分别为0.043 9、0.118 1。营养代谢试验证实无机碳消耗与硝态氮消耗呈显著正相关；脂质的质量分数（以细胞干质量为基准）为13.0%～18.7%，脂肪酸以棕榈酸和棕榈油酸为主要组分，二者合计占总脂肪酸的75%～85%。经多目标优化得到最优培养条件为：光照强度为97 μmol·m^-2·s^-1、初始接种浓度为0.1～0.4、碳酸氢钠物质的量浓度为25～50 mmol/L。该模型可依托现场pH在线监测，实现聚球藻培养过程精准预判与精细化调控。

Abstract

To address the growth limitation caused by pH fluctuations during Synechococcus cultivation and the difficulty in accurate real-time prediction,a multifactor-coupled growth prediction model based on online pH signals is proposed.Experiments are conducted at different initial inoculation concentrations (expressed as optical density at 730 nm,OD₇₃₀,denoted by A,ranging from 0.1 to 1.3),light intensities (14—181 μmol·m^-2·s^-1),and sodium bicarbonate concentrations (25—125 mmol/L) to obtain dynamic biomass and pH data.Based on an analysis of inorganic carbon speciation,a logistic model is used to quantify the biomass-pH relationship,and a multifactor-coupled growth prediction model is further established.It is shown that biomass accumulation is highly synchronized with the increase in culture-medium pH,and that growth limitation is mainly caused by the pH-driven conversion of HCO₃ ^- to CO₃ ^2-,resulting in insufficient available inorganic carbon.R² values above 0.98 are obtained by the Logistic model under all 15 conditions,with inflection-point pH values of 9.5—9.8,which closely correspond to the transition points of carbon-source availability.In two independent experiments,predicted determination coefficients R² _pred values of 0.987 9 and 0.885 8 and mean absolute error E of 0.043 9 and 0.118 1 are obtained by the growth prediction model,respectively.A significant positive correlation between inorganic carbon consumption and nitrate-nitrogen consumption is confirmed by nutrient metabolism experiments.The dry cell mass-based lipid mass fraction ranges from 13.0% to 18.7%,and palmitic acid and palmitoleic acid are the main fatty acids,together accounting for 75%—85% of the total fatty acids.The optimal culture conditions are determined through multi-objective optimization as a light intensity of 97 μmol·m^-2·s^-1,an initial inoculation concentration of 0.1—0.4,and a sodium bicarbonate concentration of 25—50 mmol/L.Accurate prediction and refined regulation of Synechococcus cultivation can be achieved using the model based on online pH monitoring.

关键词

聚球藻 / pH波动 / 生长预测模型 / 营养代谢 / 脂肪酸

Key words

Synechococcus / pH fluctuations / growth prediction model / nutrient metabolism / fatty acids

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基金资助

国家自然科学基金资助项目(52488201)