Directed Evolution of a Bright Variant of mCherry: Suppression of Nonradiative Decay by Fluorescence Lifetime Selections.

The approximately linear scaling of fluorescence quantum yield (ϕ) with fluorescence lifetime (τ) in fluorescent proteins (FPs) has inspired engineering of brighter fluorophores based on screening for increased lifetimes. Several recently developed FPs such as mTurquoise2, mScarlet, and FusionRed-MQV which have become useful for live cell imaging are products of lifetime selection strategies. However, the underlying photophysical basis of the improved brightness has not been scrutinized. In this study, we focused on understanding the outcome of lifetime-based directed evolution of mCherry, which is a popular red-FP (RFP). We identified four positions (W143, I161, Q163, and I197) near the FP chromophore that can be mutated to create mCherry-XL (eXtended Lifetime: ϕ = 0.70; τ = 3.9 ns). The 3-fold higher quantum yield of mCherry-XL is on par with that of the brightest RFP to date, mScarlet. We examined selected variants within the evolution trajectory and found a near-linear scaling of lifetime with quantum yield and consistent blue-shifts of the absorption and emission spectra. We find that the improvement in brightness is primarily due to a decrease in the nonradiative decay of the excited state. In addition, our analysis revealed the decrease in nonradiative rate is not limited to the blue-shift of the energy gap and changes in the excited state reorganization energy. Our findings suggest that nonradiative mechanisms beyond the scope of energy-gap models such the Englman-Jortner model are suppressed in this lifetime evolution trajectory.

Directed evolution of excited state lifetime and brightness in FusionRed using a microfluidic sorter.

Green fluorescent proteins (GFP) and their blue, cyan and red counterparts offer unprecedented advantages as biological markers owing to their genetic encodability and straightforward expression in different organisms. Although significant advancements have been made towards engineering the key photo-physical properties of red fluorescent proteins (RFPs), they continue to perform sub-optimally relative to GFP variants. Advanced engineering strategies are needed for further evolution of RFPs in the pursuit of improving their photo-physics. In this report, a microfluidic sorter that discriminates members of a cell-based library based on their excited state lifetime and fluorescence intensity is used for the directed evolution of the photo-physical properties of FusionRed. In-flow measurements of the fluorescence lifetime are performed in a frequency-domain approach with sub-millisecond sampling times. Promising clones are sorted by optical force trapping with an infrared laser. Using this microfluidic sorter, mutants are generated with longer lifetimes than their precursor, FusionRed. This improvement in the excited state lifetime of the mutants leads to an increase in their fluorescence quantum yield up to 1.8-fold. In the course of evolution, we also identified one key mutation (L177M), which generated a mutant (FusionRed-M) that displayed ∼2-fold higher brightness than its precursor upon expression in mammalian (HeLa) cells. Photo-physical and mutational analyses of clones isolated at the different stages of mutagenesis reveal the photo-physical evolution towards higher in vivo brightness.

High-speed multiparameter photophysical analyses of fluorophore libraries.

There is a critical need for high-speed multiparameter photophysical measurements of large libraries of fluorescent probe variants for imaging and biosensor development. We present a microfluidic flow cytometer that rapidly assays 10(4)-10(5) member cell-based fluorophore libraries, simultaneously measuring fluorescence lifetime and photobleaching. Together, these photophysical characteristics determine imaging performance. We demonstrate the ability to resolve the diverse photophysical characteristics of different library types and the ability to identify rare populations.

Transcriptome responses to combinations of stresses in Arabidopsis.

Biotic and abiotic stresses limit agricultural yields, and plants are often simultaneously exposed to multiple stresses. Combinations of stresses such as heat and drought or cold and high light intensity have profound effects on crop performance and yields. Thus, delineation of the regulatory networks and metabolic pathways responding to single and multiple concurrent stresses is required for breeding and engineering crop stress tolerance. Many studies have described transcriptome changes in response to single stresses. However, exposure of plants to a combination of stress factors may require agonistic or antagonistic responses or responses potentially unrelated to responses to the corresponding single stresses. To analyze such responses, we initially compared transcriptome changes in 10 Arabidopsis (Arabidopsis thaliana) ecotypes using cold, heat, high-light, salt, and flagellin treatments as single stress factors as well as their double combinations. This revealed that some 61% of the transcriptome changes in response to double stresses were not predic from the responses to single stress treatments. It also showed that plants prioritized between potentially antagonistic responses for only 5% to 10% of the responding transcripts. This indicates that plants have evolved to cope with combinations of stresses and, therefore, may be bred to endure them. In addition, using a subset of this data from the Columbia and Landsberg erecta ecotypes, we have delineated coexpression network modules responding to single and combined stresses.

Optimization of the BLASTN substitution matrix for prediction of non-specific DNA microarray hybridization.

DNA microarray measurements are susceptible to error caused by non-specific hybridization between a probe and a target (cross-hybridization), or between two targets (bulk-hybridization). Search algorithms such as BLASTN can quickly identify potentially hybridizing sequences. We set out to improve BLASTN accuracy by modifying the substitution matrix and gap penalties. We generated gene expression microarray data for samples in which 1 or 10% of the target mass was an exogenous spike of known sequence. We found that the 10% spike induced 2-fold intensity changes in 3% of the probes, two-third of which were decreases in intensity likely caused by bulk-hybridization. These changes were correlated with similarity between the spike and probe sequences. Interestingly, even very weak similarities tended to induce a change in probe intensity with the 10% spike. Using this data, we optimized the BLASTN substitution matrix to more accurately identify probes susceptible to non-specific hybridization with the spike. Relative to the default substitution matrix, the optimized matrix features a decreased score for A-T base pairs relative to G-C base pairs, resulting in a 5-15% increase in area under the ROC curve for identifying affected probes. This optimized matrix may be useful in the design of microarray probes, and in other BLASTN-based searches for hybridization partners.