Microbioreactor Systems for Accelerated Bioprocess Development

Abstract

In recent years, microbioreactor (MBR) systems have evolved towards versatile bioprocess engineering tools. They provide a unique solution to combine higher experimental throughput with extensive bioprocess monitoring and control, which is indispensable to develop economically and ecologically competitive bioproduction processes. MBR systems are based either on down-scaled stirred tank reactors or on advanced shaken microtiter plate cultivation devices. Importantly, MBR systems make use of optical measurements for non-invasive, online monitoring of important process variables like biomass concentration, dissolved oxygen, pH, and fluorescence. The application range of MBR systems can be further increased by integration into liquid handling robots, enabling automatization and, thus standardization, of various handling and operation procedures. Finally, the tight integration of quantitative strain phenotyping with bioprocess development under industrially relevant conditions greatly increases the probability of finding the right combination of producer strain and bioprocess control strategy. This review will discuss the current state of the art in the field of MBR systems and we can readily conclude that their importance for industrial biotechnology will further increase in the near future.

A model‐based framework for parallel scale‐down fed‐batch cultivations in mini‐bioreactors for accelerated phenotyping

“…For instance, Janakiraman, Kwiatkowski, Kshirsagar, Ryll, and Huang () matched the volumetric aeration rates (vvm) between parallel ambr15 TM cultivations of CHO cells and a 15,000‐L production‐scale bioreactor, whereas Velez‐Suberbie et al () used the power per unit volume (P/V) as a scale‐down criterion to compare ambr15f cultivations of E. coli with 20‐L bioreactor cultivations. Other works involving high‐throughput cultivations in complex integrated facilities have also been reported (see recent review in Hemmerich, Noack, Wiechert, & Oldiges, ). However, although these works point to the right direction in terms of high‐throughput bioprocess development, matching only one engineering criterion between scales is not necessarily the same as replicating specific environmental heterogeneities in smaller bioreactors for scale‐down studies.…”

Less Sacrifice, More Insight: Repeated Low‐Volume Sampling of Microbioreactor Cultivations Enables Accelerated Deep Phenotyping of Microbial Strain Libraries

“…These libraries can be characterized under defined conditions in a process henceforth termed quantitative microbial phenotyping. Essentially, it describes the assignment of performance indicators (PIs) to any microbial strain under investigation . Typical PIs for biotechnological purposes are: i) concentrations (titers) of biomass ( c X ) and product ( c P ); ii) specific yields relating biomass formation with substrate conversion ( Y X/S ) as well as product formation with biomass growth ( Y P/X ); and iii) specific rates for substrate consumption ( q S ), growth ( μ ) and product formation ( q P ).…”

“…Different microbioreactor (MBR) systems have been developed in the past, enabling the tight monitoring and controlling of microbial cultivation experiments at elevated throughput . Next to microtiter plate (MTP) based systems, microscale bubble‐column and stirred tank reactor‐based MBR technologies with reaction volumes in the mL‐range were developed .…”

Evolutionary engineering of Corynebacterium glutamicum

“…To overcome this limitation, several microbioreactor systems are available that are based on shaken microtiter plates (MTPs), e.g., “GrowthProfiler” (EnzyScreen), “Bioscreen C” (Oy Growth Curves) or “BioLector” (m2p‐labs), which employ (quasi)‐continuous biomass measurement via integrated image analysis, optical density, or backscatter (see Hemmerich et al for an comprehensive overview). In addition, MTPs enable a higher throughput to perform replicate ALE experiments under identical conditions and thus provide access to important quantities for analyzing the evolutionary process, e.g., in terms of beneficial mutation rates and the occurrence of fixed or converged mutations .…”