Abstract
Pichia pastoris (Komagataella phaffii) is widely used for industrial production of heterologous proteins due to high secretory capabilities but selection of highly productive engineered strains remains a limiting step. Despite availability of a comprehensive molecular toolbox for construct design and gene integration, there is high clonal variability among transformants due to frequent multi-copy and off-target random integration. Therefore, functional screening of several hundreds of transformant clones is essential to identify the best protein production strains. Screening methods are commonly based on deep-well plate cultures with analysis by immunoblotting or enzyme activity assays of post-induction samples, and each heterologous protein produced may require development of bespoke assays with multiple sample processing steps. In this work, we developed a generic system based on a P. pastoris strain that uses a protein-based biosensor to identify highly productive protein secretion clones from a heterogeneous set of transformants. The biosensor uses a split green fluorescent protein where the large GFP fragment (GFP1-10) is fused to a sequence-specific protease from Tobacco Etch Virus (TEV) and is targeted to the endoplasmic reticulum. Recombinant proteins targeted for secretion are tagged with the small fragment of the split GFP (GFP11). Recombinant protein production can be measured by monitoring GFP fluorescence, which is dependent on interaction between the large and small GFP fragments. The reconstituted GFP is cleaved from the target protein by TEV protease, allowing for secretion of the untagged protein of interest and intracellular retention of the mature GFP. We demonstrate this technology with four recombinant proteins (phytase, laccase, β-casein and β-lactoglobulin) and show that the biosensor directly reports protein production levels that correlate with traditional assays. Our results confirm that the split GFP biosensor can be used for facile, generic, and rapid screening of P. pastoris clones to identify those with the highest production levels.