Using highly efficient nonlinear experimental design methods for optimization of Lactococcus lactis fermentation in chemically defined media

Challenges in developing cell culture media using machine learning

Microbial and mammalian cells are widely used in the food, pharmaceutical, and medical industries. Developing or optimizing culture media is essential to improve cell culture performance as a critical technology in cell culture engineering. Methodologies for media optimization have been developed to a great extent, such as the approaches of one-factor-at-a-time (OFAT) and response surface methodology (RSM). The present review introduces the emerging machine learning (ML) technology in cell culture engineering by combining high-throughput experimental technologies to develop highly efficient and effective culture media. The commonly used ML algorithms and the successful applications of employing ML in medium optimization are summarized. This review highlights the benefits of ML-assisted medium development and guides the selection of the media optimization method appropriate for various cell culture purposes.

Multi-objective Bayesian algorithm automatically discovers low-cost high-growth serum-free media for cellular agriculture application

In this work, we applied a multi-information source modeling technique to solve a multi-objective Bayesian optimization problem involving the simultaneous minimization of cost and maximization of growth for serum-free C2C12 cells using a hyper-volume improvement acquisition function. In sequential batches of custom media experiments designed using our Bayesian criteria, collected using multiple assays targeting different cellular growth dynamics, the algorithm learned to identify the trade-off relationship between long-term growth and cost. We were able to identify several media with > 100 % more growth of C2C12 cells than the control, as well as a medium with 23% more growth at only 62.5% of the cost of the control. These algorithmically generated media also maintained growth far past the study period, indicating the modeling approach approximates the cell growth well from an extremely limited data set.

A review of algorithmic approaches for cell culture media optimization

Cell culture media composition and culture conditions play a crucial role in product yield, quality and cost of production. Culture media optimization is the technique of improving media composition and culture conditions to achieve desired product outcomes. To achieve this, there have been many algorithmic methods proposed and used for culture media optimization in the literature. To help readers evaluate and decide on a method that best suits their specific application, we carried out a systematic review of the different methods from an algorithmic perspective that classifies, explains and compares the available methods. We also examine the trends and new developments in the area. This review provides recommendations to researchers regarding the suitable media optimization algorithm for their applications and we hope to also promote the development of new cell culture media optimization methods that are better suited to existing and upcoming challenges in this biotechnology field, which will be essential for more efficient production of various cell culture products.

Optimization of muscle cell culture media using nonlinear design of experiments

Optimizing media for biological processes, such as those used in tissue engineering and cultivated meat production, is difficult due to the extensive experimentation required, number of media components, nonlinear and interactive responses, and the number of conflicting design objectives. Here we demonstrate the capacity of a nonlinear design-of-experiments (DOE) method to predict optimal media conditions in fewer experiments than a traditional DOE. The approach is based on a hybridization of a coordinate search for local optimization with dynamically adjusted search spaces and a global search method utilizing a truncated genetic algorithm using radial basis functions to store and model prior knowledge. Using this method, we were able to reduce the cost of muscle cell proliferation media while maintaining cell growth 48 hours after seeding using 30 common components of typical commercial growth medium in fewer experiments than a traditional DOE (70 vs 103). While we clearly demonstrated that the experimental optimization algorithm significantly outperforms conventional DOE, due to the choice of a 48 hour growth assay weighted by medium cost as an objective function, these findings were limited to performance at a single passage, and did not generalize to growth over multiple passages. This underscores the importance of choosing objective functions that align well with process goals. This article is protected by copyright. All rights reserved.

Considerations for the development of cost-effective cell culture media for cultivated meat production

Innovation in cultivated meat development has been rapidly accelerating in recent years because it holds the potential to help attenuate issues facing production of dietary protein for a growing world population. There are technical obstacles still hindering large-scale commercialization of cultivated meat, of which many are related to the media that are used to culture the muscle, fat, and connective tissue cells. While animal cell culture media has been used and refined for roughly a century, it has not been specifically designed with the requirements of cultivated meat in mind. Perhaps the most common industrial use of animal cell culture is currently the production of therapeutic monoclonal antibodies, which sell for orders of magnitude more than meat. Successful production of cultivated meat requires media that is food grade with minimal cost, can regulate large-scale cell proliferation and differentiation, has acceptable sensory qualities, and is animal ingredient-free. Much insight into strategies for achieving media formulations with these qualities can be obtained from knowledge of conventional culture media applications and from the metabolic pathways involved in myogenesis and protein synthesis. In addition, application of principles used to optimize media for large-scale microbial fermentation processes producing lower value commodity chemicals and food ingredients can also be instructive. As such, the present review shall provide an overview of the current understanding of cell culture media as it relates to cultivated meat.

Improved itaconic acid production by Aspergillus niveus using blended algal biomass hydrolysate and glycerol as substrates

Superfluous algal biomass hydrolysate and purified glycerol obtained from biodiesel production were utilized for the production of itaconic acid by Aspergillus niveus. The lipid extracted Gracilaria edulis algal biomass residual was subjected to a pretreatment for the enhanced production of itaconic acid. Glycerol acquired from biodiesel production was pretreated and utilized as a substrate for itaconic acid production. The effect of individual and combined substrate concentration on itaconic acid production was investigated. Ultrasonication combined with the acid pretreated algal biomass produces higher itaconic acid due to the higher level of the total carbohydrate content (58.47 ± 2.57% w/v). After 168 h of incubation, A. niveus utilizes algal biomass hydrolysate and purified glycerol as substrate and produced 31.55 ± 1.25 g/L of itaconic acid and the dry cell weight is 18.24 ± 0.23 g/L respectively. Glycerol and algal biomass hydrolysate was a potential substrate for itaconic acid production by fungal species.

Switching industrial production processes from complex to defined media: method development and case study using the example of Penicillium chrysogenum

BACKGROUND

Filamentous fungi are versatile cell factories and widely used for the production of antibiotics, organic acids, enzymes and other industrially relevant compounds at large scale. As a fact, industrial production processes employing filamentous fungi are commonly based on complex raw materials. However, considerable lot-to-lot variability of complex media ingredients not only demands for exhaustive incoming components inspection and quality control, but unavoidably affects process stability and performance. Thus, switching bioprocesses from complex to defined media is highly desirable.

RESULTS

This study presents a strategy for strain characterization of filamentous fungi on partly complex media using redundant mass balancing techniques. Applying the suggested method, interdependencies between specific biomass and side-product formation rates, production of fructooligosaccharides, specific complex media component uptake rates and fungal strains were revealed. A 2-fold increase of the overall penicillin space time yield and a 3-fold increase in the maximum specific penicillin formation rate were reached in defined media compared to complex media.

CONCLUSIONS

The newly developed methodology enabled fast characterization of two different industrial Penicillium chrysogenum candidate strains on complex media based on specific complex media component uptake kinetics and identification of the most promising strain for switching the process from complex to defined conditions. Characterization at different complex/defined media ratios using only a limited number of analytical methods allowed maximizing the overall industrial objectives of increasing both, method throughput and the generation of scientific process understanding.

Multi-omics approach to study the growth efficiency and amino acid metabolism in Lactococcus lactis at various specific growth rates

Background

Lactococcus lactis is recognised as a safe (GRAS) microorganism and has hence gained interest in numerous biotechnological approaches. As it is fastidious for several amino acids, optimization of processes which involve this organism requires a thorough understanding of its metabolic regulations during multisubstrate growth.

Results

Using glucose limited continuous cultivations, specific growth rate dependent metabolism of L. lactis including utilization of amino acids was studied based on extracellular metabolome, global transcriptome and proteome analysis. A new growth medium was designed with reduced amino acid concentrations to increase precision of measurements of consumption of amino acids. Consumption patterns were calculated for all 20 amino acids and measured carbon balance showed good fit of the data at all growth rates studied. It was observed that metabolism of L. lactis became more efficient with rising specific growth rate in the range 0.10 - 0.60 h^-1, indicated by 30% increase in biomass yield based on glucose consumption, 50% increase in efficiency of nitrogen use for biomass synthesis, and 40% reduction in energy spilling. The latter was realized by decrease in the overall product formation and higher efficiency of incorporation of amino acids into biomass. L. lactis global transcriptome and proteome profiles showed good correlation supporting the general idea of transcription level control of bacterial metabolism, but the data indicated that substrate transport systems together with lower part of glycolysis in L. lactis were presumably under allosteric control.

Conclusions

The current study demonstrates advantages of the usage of strictly controlled continuous cultivation methods combined with multi-omics approach for quantitative understanding of amino acid and energy metabolism of L. lactis which is a valuable new knowledge for development of balanced growth media, gene manipulations for desired product formation etc. Moreover, collected dataset is an excellent input for developing metabolic models.