Optically Modulated and Optically Activated Delayed Fluorescent Proteins through Dark State Engineering.

Modulating fluorescent protein emission holds great potential for increasing readout sensitivity for applications in biological imaging and detection. Here, we identify and engineer optically modulated yellow fluorescent proteins (EYFP, originally 10C, but renamed EYFP later, and mVenus) to yield new emitters with distinct modulation profiles and unique, optically gated, delayed fluorescence. The parent YFPs are individually modulatable through secondary illumination, depopulating a long-lived dark state to dynamically increase fluorescence. A single point mutation introduced near the chromophore in each of these YFPs provides access to a second, even longer-lived modulatable dark state, while a different double mutant renders EYFP unmodulatable. The naturally occurring dark state in the parent YFPs yields strong fluorescence modulation upon long-wavelength-induced dark state depopulation, allowing selective detection at the frequency at which the long wavelength secondary laser is intensity modulated. Distinct from photoswitches, however, this near IR secondary coexcitation repumps the emissive S1 level from the long-lived triplet state, resulting in optically activated delayed fluorescence (OADF). This OADF results from secondary laser-induced, reverse intersystem crossing (RISC), producing additional nanosecond-lived, visible fluorescence that is delayed by many microseconds after the primary excitation has turned off. Mutation of the parent chromophore environment opens an additional modulation pathway that avoids the OADF-producing triplet state, resulting in a second, much longer-lived, modulatable dark state. These Optically Modulated and Optically Activated Delayed Fluorescent Proteins (OMFPs and OADFPs) are thus excellent for background- and reference-free, high sensitivity cellular imaging, but time-gated OADF offers a second modality for true background-free detection. Our combined structural and spectroscopic data not only gives additional mechanistic details for designing optically modulated fluorescent proteins but also provides the opportunity to distinguish similarly emitting OMFPs through OADF and through their unique modulation spectra.

A practical methodology to measure unbiased gas chromatographic retention factor vs. temperature relationships.

Compound identification continues to be a major challenge. Gas chromatography-mass spectrometry (GC-MS) is a primary tool used for this purpose, but the GC retention information it provides is underutilized because existing retention databases are experimentally restrictive and unreliable. A methodology called "retention projection" has the potential to overcome these limitations, but it requires the retention factor (k) vs. T relationship of a compound to calculate its retention time. Direct methods of measuring k vs. T relationships from a series of isothermal runs are tedious and time-consuming. Instead, a series of temperature programs can be used to quickly measure the k vs. T relationships, but they are generally not as accurate when measured this way because they are strongly biased by non-ideal behavior of the GC system in each of the runs. In this work, we overcome that problem by using the retention times of 25 n-alkanes to back-calculate the effective temperature profile and hold-up time vs. T profiles produced in each of the six temperature programs. When the profiles were measured this way and taken into account, the k vs. T relationships measured from each of two different GC-MS instruments were nearly as accurate as the ones measured isothermally, showing less than two-fold more error. Furthermore, temperature-programmed retention times calculated in five other laboratories from the new k vs. T relationships had the same distribution of error as when they were calculated from k vs. T relationships measured isothermally. Free software was developed to make the methodology easy to use. The new methodology potentially provides a relatively fast and easy way to measure unbiased k vs. T relationships.