Plasmid DNA fermentation strategies: influence on plasmid stability and cell physiology

A machine learning-based approach for improving plasmid DNA production in Escherichia coli fed-batch fermentations

Artificial Intelligence (AI) technology is spearheading a new industrial revolution, which provides ample opportunities for the transformational development of traditional fermentation processes. During plasmid fermentation, traditional subjective process control leads to highly unstable plasmid yields. In this study, a multi-parameter correlation analysis was first performed to discover a dynamic metabolic balance among the oxygen uptake rate, temperature, and plasmid yield, whilst revealing the heating rate and timing as the most important optimization factor for balanced cell growth and plasmid production. Then, based on the acquired on-line parameters as well as outputs of kinetic models constructed for describing process dynamics of biomass concentration, plasmid yield, and substrate concentration, a machine learning (ML) model with Random Forest (RF) as the best machine learning algorithm was established to predict the optimal heating strategy. Finally, the highest plasmid yield and specific productivity of 1167.74 mg L-1 and 8.87 mg L-1/OD600 were achieved with the optimal heating strategy predicted by the RF model in the 50 L bioreactor, respectively, which was 71% and 21% higher than those obtained in the control cultures where a traditional one-step temperature upshift strategy was applied. In addition, this study transformed empirical fermentation process optimization into a more efficient and rational self-optimization method. The methodology employed in this study is equally applicable to predict the regulation of process dynamics for other products, thereby facilitating the potential for furthering the intelligent automation of fermentation processes.

The persistence potential of transferable plasmids

Conjugative plasmids can mediate the spread and maintenance of diverse traits and functions in microbial communities. This role depends on the plasmid's ability to persist in a population. However, for a community consisting of multiple populations transferring multiple plasmids, the conditions underlying plasmid persistence are poorly understood. Here, we describe a plasmid-centric framework that makes it computationally feasible to analyze gene flow in complex communities. Using this framework, we derive the 'persistence potential': a general, heuristic metric that predicts the persistence and abundance of any plasmids. We validate the metric with engineered microbial consortia transferring mobilizable plasmids and with quantitative data available in the literature. We believe that our framework and the resulting metric will facilitate a quantitative understanding of natural microbial communities and the engineering of microbial consortia.

Plasmid DNA production with Escherichia coli GALG20, a pgi-gene knockout strain: fermentation strategies and impact on downstream processing

The market development of plasmid biopharmaceuticals for gene therapy and DNA vaccination applications is critically dependent on the availability of cost-effective manufacturing processes capable of delivering large amounts of high-quality plasmid DNA (pDNA) for clinical trials and commercialization. The producer host strain used in these processes must be designed to meet the upstream and downstream processing challenges characteristic of large scale pDNA production. The goal of the present study was to investigate the effect of different glucose feeding strategies (batch and fed-batch) on the pDNA productivity of GALG20, a pgi Escherichia coli strain potentially useful in industrial fermentations, which uses the pentose phosphate pathway (PPP) as the main route for glucose metabolism. The parental strain, MG1655ΔendAΔrecA, and the common laboratory strain, DH5α, were used for comparison purposes and pVAX1GFP, a ColE1-type plasmid, was tested as a model. GALG20 produced 3-fold more pDNA (∼141 mg/L) than MG1655ΔendAΔrecA (∼48 mg/L) and DH5α (∼40 mg/L) in glucose-based fed-batch fermentations. The amount of pDNA in lysates obtained from these cells was also larger for GALG20 (41%) when compared with MG1655ΔendAΔrecA (31%) and DH5α (26%). However, the final quality of pDNA preparations obtained with a process that explores precipitation, hydrophobic interaction chromatography and size exclusion was not significantly affected by strain genotype. Finally, high cell density fed-batch cultures were performed with GALG20, this time using another ColE1-type plasmid, NTC7482-41H-HA, in pre-industrial facilities using glucose and glycerol. These experiments demonstrated the ability of GALG20 to produce high pDNA yields of the order of 2100-2200 mg/L.

In situ pH management for microbial culture in shake flasks and its application to increase plasmid yield

Shake flasks are widely used to culture microorganisms, but they do not allow for pH control without additional infrastructure. In the presence of a carbon source like glucose, culture pH typically decreases due to overflow metabolism and can limit the growth of microorganisms in shake flasks. In this study, we demonstrate the use of magnesium hydroxide-loaded pH managing hydrogels (m-pHmH) for in situ base release to counter the decrease in culture pH in shake flasks using Escherichia coli as a model organism, in both complex and mineral salts medium. Base release from m-pHmH is shown to increase with decreasing pH (22-fold increase in release rate from pH 8 to 5), thus providing feedback from culture pH. The addition of m-pHmH resulted in better pH maintenance and higher biomass yields of E. coli K12 in media containing glucose as a carbon source. The use of m-pHmH with additional buffer resulted in pH being maintained above 6.9 while pH decreases below 5 without m-pHmH. We demonstrate one application of such in situ pH management to increase the volumetric plasmid yield from E. coli in shake flask culture. In situ glucose release through a hydrogel to mimic fed-batch culture along with the addition of m-pHmH resulted in a 395 % increase in volumetric plasmid yield to 38 μg/ml in shake flask culture.