Kevin S McFarland, Kaitlin Hegadorn, Michael J Betenbaugh, Michael W Handlogten
Chinese hamster ovary (CHO) bioprocesses, the dominant platform for therapeutic protein production, are increasingly used to produce complex multispecific proteins. Product quantity and quality are affected by intracellular conditions, but these are challenging to measure and often overlooked during process optimization studies. pH is known to impact quality attributes like protein aggregation across upstream and downstream processes, yet the effects of intracellular pH on cell culture performance are largely unknown. Recently, advances in protein biosensors have enabled investigations of intracellular environments with high spatiotemporal resolution. In this study, we integrated a fluorescent pH-sensitive biosensor into a bispecifc (bisAb)-producing cell line to investigate changes in endoplasmic reticulum pH (pHER). We then investigated how changes in lactate metabolism impacted pHER, cellular redox, and product quality in fed-batch and perfusion bioreactors. Our data show pHER rapidly increased during exponential growth to a maximum of pH 7.7, followed by a sharp drop in the stationary phase in all perfusion and fed-batch conditions. pHER decline in the stationary phase was driven by an apparent loss of cellular pH regulation that occurred despite differences in redox profiles. Finally, we found protein aggregate levels correlated most closely with pHER which provides new insights into product aggregate formation in CHO processes. An improved understanding of the intracellular changes impacting bioprocesses can ultimately help guide media optimizations, improve bioprocess control strategies, or provide new targets for cell engineering.
{"title":"Elevated endoplasmic reticulum pH is associated with high growth and bisAb aggregation in CHO cells.","authors":"Kevin S McFarland, Kaitlin Hegadorn, Michael J Betenbaugh, Michael W Handlogten","doi":"10.1002/bit.28866","DOIUrl":"10.1002/bit.28866","url":null,"abstract":"<p><p>Chinese hamster ovary (CHO) bioprocesses, the dominant platform for therapeutic protein production, are increasingly used to produce complex multispecific proteins. Product quantity and quality are affected by intracellular conditions, but these are challenging to measure and often overlooked during process optimization studies. pH is known to impact quality attributes like protein aggregation across upstream and downstream processes, yet the effects of intracellular pH on cell culture performance are largely unknown. Recently, advances in protein biosensors have enabled investigations of intracellular environments with high spatiotemporal resolution. In this study, we integrated a fluorescent pH-sensitive biosensor into a bispecifc (bisAb)-producing cell line to investigate changes in endoplasmic reticulum pH (pH<sub>ER</sub>). We then investigated how changes in lactate metabolism impacted pH<sub>ER</sub>, cellular redox, and product quality in fed-batch and perfusion bioreactors. Our data show pH<sub>ER</sub> rapidly increased during exponential growth to a maximum of pH 7.7, followed by a sharp drop in the stationary phase in all perfusion and fed-batch conditions. pH<sub>ER</sub> decline in the stationary phase was driven by an apparent loss of cellular pH regulation that occurred despite differences in redox profiles. Finally, we found protein aggregate levels correlated most closely with pH<sub>ER</sub> which provides new insights into product aggregate formation in CHO processes. An improved understanding of the intracellular changes impacting bioprocesses can ultimately help guide media optimizations, improve bioprocess control strategies, or provide new targets for cell engineering.</p>","PeriodicalId":9168,"journal":{"name":"Biotechnology and Bioengineering","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142458169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
l‐homoserine is an important platform compound of many valuable products. Construction of microbial cell factory for l‐homoserine production from glucose has attracted a great deal of attention. In this study, l‐homoserine biosynthesis pathway was divided into three modules, the glucose uptake and upstream pathway, the downstream pathway, and the energy supply module. Metabolomics of the chassis strain HS indicated that the supply of ATP was inadequate, therefore, the energy supply module was firstly modified. By balancing the ATP supply module, the l‐homoserine production increased by 66% to 12.55 g/L. Further, the results indicated that the upstream pathway was blocked, and increasing the culture temperature to 37°C could solve this problem and the l‐homoserine production reached 21.38 g/L. Then, the downstream synthesis pathways were further strengthened to balance the fluxes, and the l‐homoserine production reached the highest reported level of 32.55 g/L in shake flasks. Finally, fed‐batch fermentation in a 5‐L bioreactor was conducted, and l‐homoserine production could reach to 119.96 g/L after 92 h cultivation, with the yield of 0.41 g/g glucose and productivity of 1.31 g/L/h. The study provides a well research foundation for l‐homoserine production by microbial fermentation with the capacity for industrial application.
l-高丝氨酸是许多有价值产品的重要平台化合物。构建以葡萄糖为原料生产 l-高丝氨酸的微生物细胞工厂引起了广泛关注。本研究将 l-高丝氨酸的生物合成途径分为三个模块,即葡萄糖摄取及上游途径、下游途径和能量供应模块。基质菌株 HS 的代谢组学研究表明 ATP 供应不足,因此首先对能量供应模块进行了改造。通过平衡 ATP 供应模块,l-高丝氨酸的产量增加了 66%,达到 12.55 克/升。此外,结果表明上游途径受阻,将培养温度提高到 37°C 可以解决这一问题,l-高丝氨酸产量达到 21.38 克/升。然后,进一步加强下游合成途径以平衡通量,在摇瓶中,l-高丝氨酸的产量达到了所报道的最高水平,即 32.55 克/升。最后,在 5 升生物反应器中进行饲料批量发酵,经过 92 h 的培养,l-高丝氨酸产量达到 119.96 g/L,葡萄糖产量为 0.41 g/g,生产率为 1.31 g/L/h。该研究为微生物发酵法生产 l-高丝氨酸提供了良好的研究基础,并具有工业应用能力。
{"title":"Adjustment of the main biosynthesis modules to enhance the production of l‐homoserine in Escherichia coli W3110","authors":"Kun Niu, Rui Zheng, Miao Zhang, Mao‐Qin Chen, Yi‐Ming Kong, Zhi‐Qiang Liu, Yu‐Guo Zheng","doi":"10.1002/bit.28861","DOIUrl":"https://doi.org/10.1002/bit.28861","url":null,"abstract":"<jats:sc>l</jats:sc>‐homoserine is an important platform compound of many valuable products. Construction of microbial cell factory for <jats:sc>l</jats:sc>‐homoserine production from glucose has attracted a great deal of attention. In this study, <jats:sc>l</jats:sc>‐homoserine biosynthesis pathway was divided into three modules, the glucose uptake and upstream pathway, the downstream pathway, and the energy supply module. Metabolomics of the chassis strain HS indicated that the supply of ATP was inadequate, therefore, the energy supply module was firstly modified. By balancing the ATP supply module, the <jats:sc>l</jats:sc>‐homoserine production increased by 66% to 12.55 g/L. Further, the results indicated that the upstream pathway was blocked, and increasing the culture temperature to 37°C could solve this problem and the <jats:sc>l</jats:sc>‐homoserine production reached 21.38 g/L. Then, the downstream synthesis pathways were further strengthened to balance the fluxes, and the <jats:sc>l</jats:sc>‐homoserine production reached the highest reported level of 32.55 g/L in shake flasks. Finally, fed‐batch fermentation in a 5‐L bioreactor was conducted, and <jats:sc>l</jats:sc>‐homoserine production could reach to 119.96 g/L after 92 h cultivation, with the yield of 0.41 g/g glucose and productivity of 1.31 g/L/h. The study provides a well research foundation for <jats:sc>l</jats:sc>‐homoserine production by microbial fermentation with the capacity for industrial application.","PeriodicalId":9168,"journal":{"name":"Biotechnology and Bioengineering","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142449589","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ruby Sedgwick, John P. Goertz, Molly M. Stevens, Ruth Misener, Mark van der Wilk
With the rise in engineered biomolecular devices, there is an increased need for tailor-made biological sequences. Often, many similar biological sequences need to be made for a specific application meaning numerous, sometimes prohibitively expensive, lab experiments are necessary for their optimization. This paper presents a transfer learning design of experiments workflow to make this development feasible. By combining a transfer learning surrogate model with Bayesian optimization, we show how the total number of experiments can be reduced by sharing information between optimization tasks. We demonstrate the reduction in the number of experiments using data from the development of DNA competitors for use in an amplification-based diagnostic assay. We use cross-validation to compare the predictive accuracy of different transfer learning models, and then compare the performance of the models for both single objective and penalized optimization tasks.
随着工程生物分子设备的增多,对定制生物序列的需求也在增加。通常情况下,需要为特定应用制作许多类似的生物序列,这意味着需要进行大量的实验室实验来优化这些序列,有时实验成本之高令人望而却步。本文介绍了一种转移学习实验设计工作流程,使这一开发变得可行。通过将迁移学习代用模型与贝叶斯优化相结合,我们展示了如何通过在优化任务之间共享信息来减少实验总数。我们利用开发用于基于扩增的诊断检测的 DNA 竞争对手的数据,展示了实验数量的减少。我们使用交叉验证来比较不同迁移学习模型的预测准确性,然后比较这些模型在单一目标和惩罚优化任务中的表现。
{"title":"Transfer learning Bayesian optimization for competitor DNA molecule design for use in diagnostic assays","authors":"Ruby Sedgwick, John P. Goertz, Molly M. Stevens, Ruth Misener, Mark van der Wilk","doi":"10.1002/bit.28854","DOIUrl":"https://doi.org/10.1002/bit.28854","url":null,"abstract":"With the rise in engineered biomolecular devices, there is an increased need for tailor-made biological sequences. Often, many similar biological sequences need to be made for a specific application meaning numerous, sometimes prohibitively expensive, lab experiments are necessary for their optimization. This paper presents a transfer learning design of experiments workflow to make this development feasible. By combining a transfer learning surrogate model with Bayesian optimization, we show how the total number of experiments can be reduced by sharing information between optimization tasks. We demonstrate the reduction in the number of experiments using data from the development of DNA competitors for use in an amplification-based diagnostic assay. We use cross-validation to compare the predictive accuracy of different transfer learning models, and then compare the performance of the models for both single objective and penalized optimization tasks.","PeriodicalId":9168,"journal":{"name":"Biotechnology and Bioengineering","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142440695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
To reduce carbon emissions and address environmental concerns, the aviation industry is exploring the use of sustainable aviation fuel (SAF) as an alternative to traditional fossil fuels. In this context, bio‐alkane is considered a potentially high‐value solution. The present study focuses on the enzymes acyl‐acyl carrier protein [ACP] reductase (AAR) and aldehyde‐deformylating oxygenase (ADO), which are crucial enzymes for alka(e)ne biosynthesis. By using protein engineering techniques, including semi‐rational design and site‐directed mutagenesis, we aimed to enhance the substrate specificity of AAR and improve alkane production efficiency. The co‐expression of a modified AAR (Y26G/Q40M mutant) with wild‐type ADO in Escherichia coli significantly increased alka(e)ne production from 28.92 mg/L to 167.30 mg/L, thus notably demonstrating a 36‐fold increase in alkane yield. This research highlights the potential of protein engineering in optimizing SAF production, thereby contributing to the development of more sustainable and efficient SAF production methods and promoting greener air travel.
{"title":"Reshaping the substrate‐binding pocket of acyl‐ACP reductase to enhance the production of sustainable aviation fuel in Escherichia coli","authors":"Jiahu Han, Takuya Matsumoto, Ryosuke Yamada, Hiroyasu Ogino","doi":"10.1002/bit.28863","DOIUrl":"https://doi.org/10.1002/bit.28863","url":null,"abstract":"To reduce carbon emissions and address environmental concerns, the aviation industry is exploring the use of sustainable aviation fuel (SAF) as an alternative to traditional fossil fuels. In this context, bio‐alkane is considered a potentially high‐value solution. The present study focuses on the enzymes acyl‐acyl carrier protein [ACP] reductase (AAR) and aldehyde‐deformylating oxygenase (ADO), which are crucial enzymes for alka(e)ne biosynthesis. By using protein engineering techniques, including semi‐rational design and site‐directed mutagenesis, we aimed to enhance the substrate specificity of AAR and improve alkane production efficiency. The co‐expression of a modified AAR (Y26G/Q40M mutant) with wild‐type ADO in <jats:italic>Escherichia coli</jats:italic> significantly increased alka(e)ne production from 28.92 mg/L to 167.30 mg/L, thus notably demonstrating a 36‐fold increase in alkane yield. This research highlights the potential of protein engineering in optimizing SAF production, thereby contributing to the development of more sustainable and efficient SAF production methods and promoting greener air travel.","PeriodicalId":9168,"journal":{"name":"Biotechnology and Bioengineering","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142444008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jimmy Boman, Tjaša Marušič, Tina Vodopivec Seravalli, Janja Skok, Fredrik Pettersson, Kristina Šprinzar Nemec, Henrik Widmark, Rok Sekirnik
The cover image is based on the Article Quality by design approach to improve quality and decrease cost of in vitro transcription of mRNA using design of experiments by Jimmy Boman and Tjaša Marušič et al., https://doi.org/10.1002/bit.28806.