MIR transmission spectroscopy – a new method to monitor bacterial fed-batch cultures?

Written by Eva Arnold Posted in Think out of the box

Microbial production of recombinant proteins has become one of the most important tools in modern biotechnology and drug discovery. The production of the drug insulin is probably the best-known example.

In developing and optimizing a recombinant protein production system, it is important to ensure that sufficient nutrients are supplied to ensure good bacterial growth. Unfortunately, it doesn’t help simply providing an excess of nutrients, as in Escherichia coli this results in the production of growth-inhibiting side-products, which negatively impacts protein yield. Therefore, goal is to maintain a sufficient nutrient supply without triggering the production of growth-inhibiting products. Like this, a high cell density and, consequently, a good protein yield will be reached.

To properly dose the nutrient and buffer supply to create ideal cell growth conditions, a system is needed that simultaneously with the cultivation of the bacteria measures the concentration of nutrients, side-products and other factors such as the pH.

One of the growth-inhibiting side-products is acetate, which E.coli is releasing in case of a glucose concentration being too high. Due to the lack of on-line analysis systems for acetate, it has not yet been possible to directly adjust the glucose supply to the acetate concentration. Now, the scientists of Prof. Dr. med. Richard Biener’s group from the University of Esslingen suggest a method that can resolve this problem (Hofmann J et al. (2017) Acetatmessung mit MIR-Transmissionsspektroskopie bei der E.coli-Kultur. BIOspektrum 3:273-275).

In collaboration with an external company, they developed a special mid-infrared (MIR) spectroscopic device for on-line analysis of aqueous samples. Using MIR spectroscopy to analyze aqueous samples is a challenge, as water in the mid-infrared range exhibits high intrinsic absorption, making it difficult to quantify substances dissolved in water. To overcome this problem, the scientists developed a flow cell that allows the analysis of aqueous samples within minutes due to a cell length of less than 10 μm. They were able to reliably quantify acetate in concentrations starting from 5 mg/L, which corresponds to the lower ppm range.

As a model organism, the scientists used a proline auxotrophic E.coli strain for recombinant production of green fluorescent proteins (GFP). In addition to acetate, the concentrations of other metabolites such as pyruvate, succinate and lactate as well as important components of the medium such as glucose, proline, ammonium, sulfate and citrate were determined using the MIR spectroscopy method. Interestingly, the data analysis was done using database-based algorithms, which saves time and money because calibration is no longer necessary. The agreement of the data from the MIR spectroscopy method with classically measured (enzymatically, colorimetrically) values for glucose, acetate and phosphate largely confirms the consistency of the algorithm. But it should be noted that a comparison of the values for the seven remaining substances is not mentioned.

The method presented in this article promises short measurement times, a small evaluation effort and good potential for fully automating fed-batch cultures. According to the scientists, the MIR spectroscopy method can also be used to determine protein structure and conformation, thereby enabling quality control of the proteins at the same time as growth control. A statement about the yield of the produced GFP is missing.

Using MIR spectroscopy, many substances can be detected, identified and quantified in parallel. The possibility presented here of applying MIR spectroscopy to aqueous samples creates a wide range of new application fields. This method is expected to be of great interest for rapid quality control during a production process in pharmaceutical companies and especially for effective screenings during process development. Complex HPLC methods might be replaced by the new method, which could save time and resources. However, it should be noted that the algorithm used to evaluate the data must be specifically tailored to the process. It remains to be shown to what extent this method will prove it’s worth in the application fields mentioned above.