Application of Biomass Monitoring in Microbial (Cell) Efficacy Evaluation/Strain Screening

    In a previous tweet, we introduced WIGGENS's CGQ biomass online monitoring system to monitor the growth stage of microorganisms or cells. In this issue, we introduce the application of biomass monitoring to microbial (cell) efficacy evaluation/strain screening.
First, let's look at a published literature on monitoring biomass using the CGQ system.
Bruder et al. (2016): Parallelised online biomass monitoring in shake flasks enabling efficient strain and carbon source dependent growth characterisation of Saccharomyces cerevisia (Microbial Cell Factories).

Bruder monitors high-efficiency strains (CEN.PK2-1C) and carbon-dependent growth characteristics of Saccharomyces cerevisiae.

The biomass curve (OD value) in the above figure is a real-time online measurement of the CGQ system. Glucose concentration and alcohol concentration were measured by real-time online monitoring using an online biochemical analyzer.
From the data curve in the above figure, we can clearly see the correlation between the amount of biological growth and the glucose concentration and alcohol production in the medium. The bacteria that are desired to be used in the fermentation process are more efficient in converting substrates such as sugars into alcohol. The potency ratio of substrate to product is the most direct assessment of the efficacy of S. cerevisiae strains.
      The online monitoring of CGQ and biochemical analyzers allows for an intuitive evaluation of the overall efficacy of the strain.
Mutant studies of microorganisms or cells are an effective means of finding efficient strains. A comparative study of mutants and wild type for efficacy evaluation of mutants.

    Pictured above is the most Grafswald University in Germany (founded in 1456), using the CGQ system for Staphylococcus aureus (S. aureus) wild-type and mutant biomass analysis.
As a powerful tool for strain screening, the CGQ system can monitor the biomass under the same culture conditions or under different culture conditions in real time, and provide data support for strain screening based on the monitoring data of biomass.
The CGQ and the biochemical analyzer can be used simultaneously to comprehensively evaluate the multi-parameter correlation, effectively expanding the scope of application, and comprehensively evaluating the microbial efficacy through multi-parameter changes.

For more CGQ biomass monitoring applications, please refer to the following documents:
[1] Tripp et al (2017): Establishing a yeast-based screening system for discovery of human GLUT5inhibitors and activators (Nature – Scientific Reports)

[2] Bruder, S. & Boles, E. (2017): Improvement of the yeast based (R)-phenylacetylcarbinol production process via reduction of by-product formation (Biochemical EngineeringJournal).

[3] Gottardi et al. (2017): De novo biosynthesis of trans-cinnamic acid derivatives in Saccharomyces cerevisiae (Applied Microbiology and Biotechnology).

[4] Bracharz et al. (2017): The effects of TORC signal interference on lipogenesis in the oleaginous yeast Trichosporonoleaginosus (BMCBiotechnology).

[5] Bruder et al. (2016): Parallelised online biomass monitoring in shake flasks efficient strain and carbon source dependent growth characterisation of Saccharomyces cerevisia (Microbial Cell Factories).