Background: Rhamnolipids are potent biosurfactants with high potential for industrial applications. However, rhamnolipids are currently produced with the opportunistic pathogen Pseudomonas aeruginosa during growth on hydrophobic substrates such as plant oils. The heterologous production of rhamnolipids entails two essential advantages: Disconnecting the rhamnolipid biosynthesis from the complex quorum sensing regulation and the opportunity of avoiding pathogenic production strains, in particular P. aeruginosa. In addition, separation of rhamnolipids from fatty acids is difficult and hence costly. Results: Here, the metabolic engineering of a rhamnolipid producing Pseudomonas putida KT2440, a strain certified as safety strain using glucose as carbon source to avoid cumbersome product purification, is reported. Notably, P. putida KT2440 features almost no changes in growth rate and lag-phase in the presence of high concentrations of rhamnolipids (> 90 g/L) in contrast to the industrially important bacteria Bacillus subtilis, Corynebacterium glutamicum, and Escherichia coli. P. putida KT2440 expressing the rhlAB-genes from P. aeruginosa PAO1 produces mono-rhamnolipids of P. aeruginosa PAO1 type (mainly C₁₀:C₁₀). The metabolic network was optimized in silico for rhamnolipid synthesis from glucose. In addition, a first genetic optimization, the removal of polyhydroxyalkanoate formation as competing pathway, was implemented. The final strain had production rates in the range of P. aeruginosa PAO1 at yields of about 0.15 g/g_glucose corresponding to 32% of the theoretical optimum. What's more, rhamnolipid production was independent from biomass formation, a trait that can be exploited for high rhamnolipid production without high biomass formation. Conclusions: A functional alternative to the pathogenic rhamnolipid producer P. aeruginosa was constructed and characterized. P. putida KT24C1 pVLT31_rhlAB featured the highest yield and titer reported from heterologous rhamnolipid producers with glucose as carbon source. Notably, rhamnolipid production was uncoupled from biomass formation, which allows optimal distribution of resources towards rhamnolipid synthesis. The results are discussed in the context of rational strain engineering by using the concepts of synthetic biology like chassis cells and orthogonality, thereby avoiding the complex regulatory programs of rhamnolipid production existing in the natural producer P. aeruginosa.

Technical bulk enzymes represent a huge market, and the extracellular production of such enzymes is favorable due to lowered cost for product recovery. Protein secretion can be achieved via general secretion (Sec) pathway. Specific sequences, signal peptides (SPs), are necessary to direct the target protein into the translocation machinery. For example, >150 Sec-specific SPs have been identified for Bacillus subtilis alone. As the best SP for a target protein of choice cannot be predicted a priori, screening of homologous SPs has been shown to be a powerful tool for different expression organisms. While SP libraries between closely related species were successfully applied to optimize recombinant protein secretion, this was not investigated for distantly related species. Therefore, in this study a Sec SP library from low-GC firmicutes B. subtilis is investigated to optimize protein secretion in high-GC actinobacterium Corynebacterium glutamicum using cutinase from Fusarium solani pisi as model protein. A homologous SP library (~150 SP) for recombinant cutinase secretion in B. subtilis was successfully transferred to C. glutamicum as alternative secretion host. Cutinase secretion in C. glutamicum was quantified using an automated micro scale cultivation system for online growth monitoring, cell separation and cutinase activity determination. Secretion phenotyping results were correlated to those from a previous study, in which the same SP library was used to optimize secretion of the same cutinase but using B. subtilis as host. Strikingly, behavior of specific SP-cutinase combinations was changed dramatically between B. subtilis and C. glutamicum. Some SPs showed comparable cutinase secretion performances in both hosts, whereas other SPs caused diametrical extracellular cutinase activities. The optimal production strain for a specific target protein of choice still cannot be designed in silico. Not only the best SP for a target protein has to be evaluated each time from scratch, the expression host also affects which SP is best. Thus, (heterologous) SP library screening using high-throughput methods is considered to be crucial to construct an optimal production strain for a target protein.

In Pichia pastoris bioprocess engineering, classic approaches for clone selection and bioprocess optimization at small/micro scale using the promoter of the alcohol oxidase 1 gene (P AOX1 ), induced by methanol, present low reproducibility leading to high time and resource consumption.

With modern genetic engineering tools, high number of potentially improved production strains can be created in a short time. This results in a bottleneck in the succeeding step of bioprocess development, which can be handled by accelerating quantitative microbial phenotyping. Miniaturization and automation are key technologies to achieve this goal. In this study, a novel workflow for repeated low‐volume sampling of BioLector‐based cultivation setups is presented. Six samples of 20 μL each can be taken automatically from shaken 48‐well microtiter plates without disturbing cell population growth. The volume is sufficient for quantification of substrate and product concentrations by spectrophotometric‐based enzyme assays. From transient concentration data and replicate cultures, valid performance indicators (titers, rates, yields) are determined through process modeling and random error propagation analysis. Practical relevance of the workflow is demonstrated with a set of five genome‐reduced Corynebacterium glutamicum strains that are engineered for Sec‐mediated heterologous cutinase secretion. Quantitative phenotyping of this strain library led to the identification of a strain with a 1.6‐fold increase in cutinase yield. The prophage‐free strain carries combinatorial deletions of three gene clusters (Δ3102‐3111, Δ3263‐3301, and Δ3324‐3345) of which the last two likely contain novel target genes to foster rational engineering of heterologous cutinase secretion in C. glutamicum.

The production of bulk enzymes used in food industry or organic chemistry constitutes an important part of industrial biotechnology. The development of production processes for novel proteins comprises a variety of biological engineering and bioprocess reaction engineering factors. The combinatorial explosion of these factors can be effectively countered by combining high‐throughput experimentation with advanced algorithms for data analysis and experimental design. We present an experimental optimization strategy that merges three different techniques: (1) advanced microbioreactor systems, (2) lab automation, and (3) Kriging‐based experimental analysis and design. This strategy is demonstrated by maximizing product titer of secreted green fluorescent protein (GFP), synthesized by Corynebacterium glutamicum, through systematic variation of CgXII minimal medium composition. First, relevant design parameters are identified in an initial fractional factorial screening experiment. Then, the functional relationship between selected media components and protein titer is investigated more detailed in an iterative procedure. In each iteration, Kriging interpolations are used for formulating hypotheses and planning the next round of experiments. For the optimized medium composition, GFP product titer was more than doubled. Hence, Kriging‐based experimental analysis and design has been proven to be a powerful tool for efficient process optimization.