An enzyme-based biosensor for monitoring and engineering protein stability in vivo

Protein stability affects the physiological functions of proteins and is also a desirable trait in many protein engineering tasks, yet improving protein stability is challenging because of limitations in methods for directly monitoring protein stability in cells. Here, we report an in vivo stability biosensor wherein a protein of interest (POI) is inserted into a microbial enzyme (CysG^A) that catalyzes the formation of endogenous fluorescent compounds, thereby coupling POI stability to simple fluorescence readouts. We demonstrate the utility of the biosensor in directed evolution to obtain stabilized, less aggregation-prone variants of two POIs (including nonamyloidogenic variants of human islet amyloid polypeptide). Beyond engineering applications, we exploited our biosensor in deep mutational scanning for experimental delineation of the stability-related contributions of all residues throughout the catalytic domain of a histone H3K4 methyltransferase, thereby revealing its scientifically informative stability landscape. Thus, our highly accessible method for in vivo monitoring of the stability of diverse proteins will facilitate both basic research and applied protein engineering efforts.

Protein stability affects myriad aspects of biochemical and biological research and often appears as a challenge for the application of protein technologies. Most natural proteins are only marginally stable, having free energy values for unfolding as low as 5 to 10 kcal/mol, a level comparable to the energy needed to break only a few hydrogen bonds (1). Although these marginal stabilities enable proteins to be flexible and thereby support their diverse functions, there is a need for at least a minimal stability threshold to support adequately high enough protein folding efficiency for cell survival (2). Evolutionarily, this apparent tension has established a tight balance between increased functionality through accumulation of mutations and the ability to maintain an adequate level of stability (2). Because this balance is delicate, environmental and cellular disturbances—for example, elevated temperature or a limited pool of ligands—can often tip the balance and turn an active protein into a nonfunctional or misfolded, aggregated state (3).It is increasingly appreciated that protein instability is often a major causative factor in human diseases (4). For example, destabilized mutations of the cellular tumor antigen p53 (5) or antioxidative superoxide dismutase 1 (SOD1) (6) are known to cause multiple human diseases. Misfolding or aggregation of specific proteins is also the hallmark of many neurodegenerative diseases, such as amyloid β peptide in Alzheimer''s disease (7), α-synuclein in Parkinson’s disease (8), and polyglutamine in Huntington’s disease (9). Moreover, protein instability is very often a limiting factor in the development of protein technologies including biocatalysts, therapeutic proteins, and de novo protein design. Consider, for example, that natural enzymes cannot usually be directly deployed as biocatalysts; these tools must remain active under continuous stresses like high temperature, high ionic strength, and extreme pH during the industrial process (10) and must retain activity for days or even weeks in some cell-free applications (11). Similarly, therapeutic proteins often suffer from short half-lives in the human body and/or have a highly restricted shelf life (12). Finally, protein design based on the thermodynamic principles is often constrained by poor stability of the target: for example, 34% of the originally designed monomeric fluorescence-activating β-barrel structures were found to be insoluble, 37% were not expressed, and 7% were found to be toxic when expressed (13).Regardless of widespread academic and industrial interest in stabilizing proteins, tools available for improving protein stability remain quite limited. Although computational stability design can be used to predict stabilizing mutations, its accuracy still needs to be substantially improved due to inadequacies in the quality of experimental results in public databases, in the accuracy of functional annotation information, and in the overall performance of the stability predicting algorithms themselves (14). Directed evolution represents another approach to obtain stabilized proteins, but a profound bottleneck for this approach is to establish high-throughput selection or screening strategies to rapidly monitor protein stability in vivo. The current widely used library-based display technologies rely on functional assays, which are by nature only indirect readouts of the stability of an analyte protein (15).By contrast, protein stability biosensors offer a way to directly monitor protein stability in vivo (16–18). Although they have been successfully deployed in various protein stability evolution applications, the available technologies are not universal solutions (i.e., suitable for all proteins). As an example, our recent attempts to distinguish and evolve the in vivo stability of two members of the histone H3 lysine 4 (H3K4) methyltransferase family failed when using several well-established biosensors, including a green fluorescent protein (GFP)-based biosensor (16), an aminoglycoside 3″-adenylyltransferase–based biosensor (17), and a chloramphenicol acetyltransferase–based biosensor (18) (SI Appendix, Fig. S1). These failures in our own work highlight the need to expand the toolbox of high-throughput selection and screening strategies for the directed evolution of protein stability and served as the fundamental motivation for our work.Here, we developed an enzyme-based fluorescent biosensor to monitor and evolve protein stability in vivo. Our strategy is based on insertion of a protein of interest (POI) between two halves of the Escherichia coli uroporphyrinogen-III methyltransferase CysG^A protein (19), which catalyzes the formation of endogenous red fluorescent compounds. Linking protein folding to the activity of CysG^A allows accurate and sensitive measurement of POI stability and solubility. Our biosensor does not require exogenous substrates or any prior structural knowledge or biophysical information about the POI, therefore engendering its use as a general screen for directed evolution of protein stability. We successfully applied our biosensor to identify stabilizing mutations of muscle acylphosphatase and nonamyloidogenic mutants of the human islet amyloid peptide. Combining this biosensor with deep mutational scanning, we systematically profiled the site-specific mutational tolerance and stability of MLL3_SET, the catalytic domain of the H3K4 methyltransferase MLL3 (a member of the mixed lineage leukemia [MLL] family), therefore experimentally characterizing its stability landscape. At a fundamental level, the ability to dissect the molecular basis of protein stability allows the profile of residues that dictate stability to be generated and the stabilization hotspots in proteins to be mapped. Our study demonstrates the utility of our biosensor as a highly accessible, rapid, flexible, and robust tool for monitoring, evolving, and dissecting protein stability in vivo, allowing the improvement in the ability to engineer customized protein and a greater understanding of the relationship between sequence and stability.