Alotaibi Najla, Aldahlawi Alia, Zaher Kawther, Basingab Fatemah, Alrahimi Jehan
Department of Biological Sciences, Faculty of Sciences, King Abdulaziz University, Jeddah, Saudi Arabia.
Immunology Unit, King Fahad Medical Research Center, King Abdulaziz University, Jeddah, Saudi Arabia.
J Genet Eng Biotechnol. 2023 Nov 29;21(1):144. doi: 10.1186/s43141-023-00597-4.
Factorial design is a simple, yet elegant method to investigate the effect of multiple factors and their interaction on a specific response simultaneously. Hence, this type of study design reaches the best optimization conditions of a process. Although the interaction between the variables is widely prevalent in cell culture procedures, factorial design per se is infrequently utilized in improving cell culture output. Therefore, we aim to optimize the experimental conditions for generating mature bone marrow-derived dendritic cells (BMDCs). Two different variables were investigated, including the concentrations of the inducing factors and the starting density of the bone marrow mononuclear cells. In the current study, we utilized the design of experiments (DoE), a statistical approach, to systematically assess the impact of factors with varying levels on cell culture outcomes. Herein, we apply a two-factor, two-level (2) factorial experiment resulting in four conditions that are run in triplicate. The two variables investigated here are cytokines combinations with two levels, granulocyte-macrophage colony-stimulating factor (GM-CSF) alone or with interleukin-4 (IL4). The other parameter is cell density with two different concentrations, 2 × 10 and 4 × 10 cells/mL. Then, we measured cell viability using the trypan blue exclusion method, and a flow cytometer was used to detect the BMDCs expressing the markers FITC-CD80, CD86, CD83, and CD14. BMDC marker expression levels were calculated using arbitrary units (AU) of the mean fluorescence intensity (MFI).
The current study showed that the highest total viable cells and cells yield obtained were in cell group seeded at 2 × 10 cells/mL and treated with GM-CSF and IL-4. Importantly, the expression of the co-stimulatory molecules CD83 and CD80/CD86 were statistically significant for cell density of 2 × 10 cells/mL (P < 0.01, two-way ANOVA). Bone marrow mononuclear cells seeded at 4 × 10 in the presence of the cytokine mix less efficiently differentiated and matured into BMDCs. Statistical analysis via two-way ANOVA revealed an interaction between cell density and cytokine combinations.
The analysis of this study indicates a substantial interaction between cytokines combinations and cell densities on BMDC maturation. However, higher cell density is not associated with optimizing DC maturation. Notably, applying DoE in bioprocess designs increases experimental efficacy and reliability while minimizing experiments, time, and process costs.
析因设计是一种简单而精巧的方法，可同时研究多个因素及其相互作用对特定反应的影响。因此，这种研究设计能够达到一个过程的最佳优化条件。尽管变量之间的相互作用在细胞培养过程中广泛存在，但析因设计本身在提高细胞培养产量方面却很少被使用。因此，我们旨在优化生成成熟骨髓来源树突状细胞（BMDCs）的实验条件。我们研究了两个不同的变量，包括诱导因子的浓度和骨髓单个核细胞的起始密度。在本研究中，我们采用实验设计（DoE）这一统计方法，系统地评估不同水平的因素对细胞培养结果的影响。在此，我们进行了一个双因素、两水平（2²）析因实验，产生四种条件，并重复进行三次。这里研究的两个变量是具有两个水平的细胞因子组合，单独的粒细胞 - 巨噬细胞集落刺激因子（GM - CSF）或与白细胞介素 - 4（IL4）组合。另一个参数是具有两种不同浓度（2×10⁶和4×10⁶个细胞/mL）的细胞密度。然后，我们使用台盼蓝排斥法测量细胞活力，并使用流式细胞仪检测表达标记物FITC - CD80、CD86、CD83和CD14的BMDCs。BMDC标记物表达水平使用平均荧光强度（MFI）的任意单位（AU）进行计算。
本研究表明，接种密度为2×10⁶个细胞/mL并接受GM - CSF和IL - 4处理的细胞组获得的总活细胞数和细胞产量最高。重要的是，对于接种密度为2×10⁶个细胞/mL的细胞，共刺激分子CD83和CD80/CD86的表达具有统计学意义（P < 0.01，双向方差分析）。在细胞因子混合物存在下，接种密度为4×10⁶个细胞/mL的骨髓单个核细胞分化和成熟为BMDCs的效率较低。通过双向方差分析进行的统计分析揭示了细胞密度和细胞因子组合之间的相互作用。
本研究分析表明，细胞因子组合与细胞密度在BMDC成熟过程中存在显著相互作用。然而，较高的细胞密度与优化DC成熟无关。值得注意的是，在生物过程设计中应用DoE可提高实验效率和可靠性，同时最大限度地减少实验、时间和过程成本。
