Ayan Esra, Aytekin Ali Özhan, Kati Ahmet, Demirci Hasan
Department of Molecular Biology and Genetics, Faculty of Science, Koç University, Istanbul, Türkiye.
Center for Targeted Therapy Technologies, Bogazici University, Istanbul, Türkiye.
PLoS One. 2025 Sep 8;20(9):e0329319. doi: 10.1371/journal.pone.0329319. eCollection 2025.
The increasing demand for efficient recombinant insulin production necessitates the development of scalable, high-yield, and cost-effective bioprocesses. In this study, we engineered a novel mini-proinsulin (nMPI) with enhanced expression properties by shortening the C-peptide and incorporating specific residue substitutions to eliminate the need for enzymatic cleavage. To optimize its production, we applied a hybrid approach combining microscale high-throughput cultivation using the BioLector microbioreactor and statistical modeling via response surface methodology (RSM). Critical medium components were first screened using Plackett-Burman Design (PBD) and refined through Central Composite Design (CDD), identifying glycerol as the most influential factor for yield. Among the four statistically derived formulations, Scenario III demonstrated the highest productivity in the microscale platform (13.00 g/L) and maintained strong performance upon scale-up to a 3-L bioreactor (11.5 g/L). The optimized medium balanced carbon and nitrogen sources to enhance cell viability and maximize protein expression. This study not only confirms the predictive accuracy and scalability of the hybrid optimization system but also introduces a robust production platform for nMPI that can be translated into industrial settings. The workflow presented here can serve as a model for the development of efficient expression systems for complex recombinant proteins in E. coli.
对高效重组胰岛素生产的需求不断增加,这就需要开发可扩展、高产且具有成本效益的生物工艺。在本研究中,我们通过缩短C肽并引入特定的残基替换来消除酶切需求,从而设计了一种具有增强表达特性的新型微型胰岛素原(nMPI)。为了优化其生产,我们采用了一种混合方法,该方法结合了使用BioLector微生物反应器的微尺度高通量培养和通过响应面法(RSM)进行的统计建模。首先使用Plackett-Burman设计(PBD)筛选关键培养基成分,并通过中心复合设计(CCD)进行优化,确定甘油是对产量影响最大的因素。在四种通过统计得出的配方中,方案III在微尺度平台上表现出最高的生产力(13.00 g/L),并且在放大到3-L生物反应器时保持了强劲的性能(11.5 g/L)。优化后的培养基平衡了碳源和氮源,以提高细胞活力并最大化蛋白质表达。本研究不仅证实了混合优化系统的预测准确性和可扩展性,还引入了一个强大的nMPI生产平台,该平台可转化为工业应用。这里介绍的工作流程可以作为在大肠杆菌中开发复杂重组蛋白高效表达系统的模型。