Bioprocess monitoring: minimizing sample matrix effects for total protein quantification with bicinchoninic acid assay

Author:

Reichelt Wieland N1,Waldschitz Daniel1,Herwig Christoph12,Neutsch Lukas2

Affiliation:

1. grid.5329.d 0000000123484034 Christian Doppler Laboratory for Mechanistic and Physiological Methods for Improved Bioprocesses, Institute of Chemical Engineering Vienna University of Technology Getreidemarkt 9/166 1060 Vienna Austria

2. grid.5329.d 0000000123484034 Research Division Biochemical Engineering, Institute of Chemical Engineering Vienna University of Technology Gumpendorfer Strasse 1A/166-4 1060 Vienna Austria

Abstract

Abstract Determining total protein content is a routine operation in many laboratories. Despite substantial work on assay optimization interferences, the widely used bicinchoninic acid (BCA) assay remains widely recognized for its robustness. Especially in the field of bioprocess engineering the inaccuracy caused by interfering substances remains hardly predictable and not well understood. Since the introduction of the assay, sample pre-treatment by trichloroacetic acid (TCA) precipitation has been indicated as necessary and sufficient to minimize interferences. However, the sample matrix in cultivation media is not only highly complex but also dynamically changing over process time in terms of qualitative and quantitative composition. A significant misestimation of the total protein concentration of bioprocess samples is often observed when following standard work-up schemes such as TCA precipitation, indicating that this step alone is not an adequate means to avoid measurement bias. Here, we propose a modification of the BCA assay, which is less influenced by sample complexity. The dynamically changing sample matrix composition of bioprocessing samples impairs the conventional approach of compensating for interfering substances via a static offset. Hence, we evaluated the use of a correction factor based on an internal spike measurement for the respective samples. Using protein spikes, the accuracy of the BCA protein quantification could be improved fivefold, taking the BCA protein quantification to a level of accuracy comparable to other, more expensive methods. This will allow reducing expensive iterations in bioprocess development to due inaccurate total protein analytics. Graphical abstract

Publisher

Oxford University Press (OUP)

Subject

Applied Microbiology and Biotechnology,Biotechnology,Bioengineering

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