Temperature-Dependent Expression of a CFP-YFP FRET Diacylglycerol Sensor Enables Multiple-Read Screening for Compounds That Affect C1 Domains

Biosensor-Based Directed Evolution of Methanol Dehydrogenase from Lysinibacillus xylanilyticus

Methanol dehydrogenase (Mdh), is a crucial enzyme for utilizing methane and methanol as carbon and energy sources in methylotrophy and synthetic methylotrophy. Engineering of Mdh, especially NAD-dependent Mdh, has thus been actively investigated to enhance methanol conversion. However, its poor catalytic activity and low methanol affinity limit its wider application. In this study, we applied a transcriptional factor-based biosensor for the direct evolution of Mdh from Lysinibacillus xylanilyticus (Lxmdh), which has a relatively high turnover rate and low K_M value compared to other wild-type NAD-dependent Mdhs. A random mutant library of Lxmdh was constructed in Escherichia coli and was screened using formaldehyde-detectable biosensors by incubation with low methanol concentrations. Positive clones showing higher fluorescence were selected by fluorescence-activated cell sorting (FACS) system, and their catalytic activities toward methanol were evaluated. The successfully isolated mutants E396V, K318N, and K46E showed high activity, particularly at very low methanol concentrations. In kinetic analysis, mutant E396V, K318N, and K46E had superior methanol conversion efficiency, with 79-, 23-, and 3-fold improvements compared to the wild-type, respectively. These mutant enzymes could thus be useful for engineering synthetic methylotrophy and for enhancing methanol conversion to various useful products.

Z' Does Not Need to Be > 0.5

The assay metric Z' has come to play a critical gatekeeping role in determining whether high-throughput assays can be performed. While Z' is commonly required to be > 0.5, this expectation is not well supported. Requiring Z' > 0.5 likely prevents many potentially useful phenotypic and cell-based screens from being conducted, and causes other assays to be conducted under extreme conditions that may prevent activity from being found. We used power analysis and a novel numerical simulation approach to determine how Z' reflects assay performance under a variety of conditions. Our results show that assays with Z' > 0.5 perform better than assays with lower Z', but when an appropriate threshold is selected, assays with Z' < 0.5 can almost always find useful compounds without generating too many false positives. We provide a method that will allow researchers to estimate how to set an appropriate threshold for their assay. We suggest that instead of always requiring Z' > 0.5, assays with Z' < 0.5 should be performed when they can be justified in terms of the importance of the target and the limitations of alternate assay formats.

The National Cancer Institute's Plated Compound Sets Can Be a Valuable Resource for Academic Researchers

Academic researchers looking for material to screen may benefit from plated compound collections provided at no cost except shipping by the U.S. National Cancer Institute (NCI). Four plated sets are available, two of which comprise diverse synthetic compounds. These collections, of ~900 and ~1500 compounds, are a convenient size to screen without automated equipment, and a great deal of data about the compounds is available that increases their usefulness. Despite these positive attributes, the collections contain a relatively large number of compounds that are pan-assay interfering and nonspecific (PAINS) or may have other chemical liabilities. Our experience with the compound collections suggests that, perhaps because they contain PAINS and other compounds with liabilities, the collections will yield hits in many assays. This makes them a valuable resource for testing primary screens and follow-up workflows, but by the same token means that hits might not be attractive leads for further development. The NCI sets have a great deal of value for academic researchers as a source of material for early screening. It might be possible, however, to create a better collection specifically for this purpose. One possibility is to pool ~5000-10,000 carefully selected lead-like compounds into ~1000 wells. A collection like this might also generate hits in a wide variety of assays but avoid the downside of those hits often having liabilities.

C1 Compound Biosensors: Design, Functional Study, and Applications

The microbial assimilation of one-carbon (C1) gases is a topic of interest, given that products developed using this pathway have the potential to act as promising substrates for the synthesis of valuable chemicals via enzymatic oxidation or C–C bonding. Despite extensive studies on C1 gas assimilation pathways, their key enzymes have yet to be subjected to high-throughput evolution studies on account of the lack of an efficient analytical tool for C1 metabolites. To address this challenging issue, we attempted to establish a fine-tuned single-cell–level biosensor system constituting a combination of transcription factors (TFs) and several C1-converting enzymes that convert target compounds to the ligand of a TF. This enzymatic conversion broadens the detection range of ligands by the genetic biosensor systems. In this study, we presented new genetic enzyme screening systems (GESSs) to detect formate, formaldehyde, and methanol from specific enzyme activities and pathways, named FA-GESS, Frm-GESS, and MeOH-GESS, respectively. All the biosensors displayed linear responses to their respective C1 molecules, namely, formate (1.0–250 mM), formaldehyde (1.0–50 μM), and methanol (5–400 mM), and they did so with high specificity. Consequently, the helper enzymes, including formaldehyde dehydrogenase and methanol dehydrogenase, were successfully combined to constitute new versatile combinations of the C1-biosensors.