Measurement Techniques to Resolve and Control Population Dynamics of Mixed-Culture Processes

Abstract

Microbial mixed cultures are gaining increasing attention as biotechnological production systems, since they offer a large but untapped potential for future bioprocesses. Effects of secondary metabolite induction and advantages of labor division for the degradation of complex substrates offer new possibilities for process intensification. However, mixed cultures are highly complex, and, consequently, many biotic and abiotic parameters are required to be identified, characterized, and ideally controlled to establish a stable bioprocess. In this review, we discuss the advantages and disadvantages of existing measurement techniques for identifying, characterizing, monitoring, and controlling mixed cultures and highlight promising examples. Moreover, existing challenges and emerging technologies are discussed, which lay the foundation for novel analytical workflows to monitor mixed-culture bioprocesses.

Keywords: bioprocess characterization; microbial co-culture; mixed culture.

Figure I. Schematic Illustration of Offline, Atline and Online Measurement Technologies for Bioprocess Control.

Figure 1. The four levels are identification, characterization, process development, and process control.

Key Figure Four Main Levels of Information to Investigate a Mixed or Co-Culture of Microorganisms

Figure 2. Differentiating between Co-Culture Members.

(A) Natural and synthetic cellular characteristics, which can be analyzed; (B) fluorescence image of a co-culture of Aspergillus terreus GFP1 (green) and Trichoderma reesei RFP1 (red) grown on cellulose (blue autofluorescence). Scale bar = 50 μm. Reproduced, with permission, from Ivan Schlembach.

Figure 3

Optical Measurement Principles and Output of (A) Absorbance, (B) Scattered Light, and (C) (Auto)Fluorescence to Resolve Co-Culture Compositions and Dynamics. Abbreviation: PLS, partial least square.