Quantification of Adeno-Associated Viral Genomes in Purified Vector Samples by Digital Droplet Polymerase Chain Reaction

Adeno-associated virus (AAV) is a non-pathogenic virus used as a delivery vehicle to transfer therapeutic genes into patients. Accurate quantification of ...

KU Leuven

The crystal structure of the on-state of PDM1-4, a single-mutation variant of the photochromic fluorescent protein Dronpa, is reported at 1.95 Å resolution. PDM1-4 is a Dronpa variant that possesses a slower off-switching rate than Dronpa and thus can effectively increase the image resolution in subdiffraction optical microscopy, although the precise molecular basis for this change has not been elucidated. This work shows that the Lys145Asn mutation in PDM1-4 stabilizes the interface available for dimerization, facilitating oligomerization of the protein. No significant changes were observed in the chromophore environment of PDM1-4 compared with Dronpa, and the ensemble absorption and emission properties of PDM1-4 were highly similar to those of Dronpa. It is proposed that the slower off-switching rate in PDM1-4 is caused by a decrease in the potential flexibility of certain β-strands caused by oligomerization along the AC interface.

Structural basis for the influence of a single mutation K145N on the oligomerization and photoswitching rate of Dronpa.

Advanced imaging techniques crucially depend on the labels used. In this work, we present the structure-guided design of a fluorescent protein that displays both reversibly photochromic and green-to-red photoconversion behavior. We first designed ffDronpa, a mutant of the photochromic fluorescent protein Dronpa that matures up to three times faster while retaining its interesting photochromic features. Using a combined evolutionary and structure-driven rational design strategy, we developed a green-to-red photoconvertible ffDronpa mutant, called pcDronpa, and explored different optimization strategies that resulted in its improved version, pcDronpa2. This fluorescent probe combines a high brightness with low photobleaching and photoblinking. We herein show that, despite its tetrameric nature, pcDronpa2 allows for multimodal subdiffraction imaging by sequentially imaging a given sample using both super-resolution fluctuation imaging and localization microscopy.

Green-to-red photoconvertible Dronpa mutant for multimodal super-resolution fluorescence microscopy.

Reversibly photoswitchable fluorescent proteins (RSFPs) are highly useful probes for a range of applications including diffraction-unlimited fluorescence microscopy. It was previously shown that reversible photoswitching not only involves cis-trans isomerization and protonation-deprotonation of the chromophore but also results in a marked difference in β-barrel flexibility. In this work, we performed flexibility profiling and functional mode analysis (FMA) using molecular dynamics calculations to study how the flexibility of the RSFP β-barrel influences the photoswitching properties of several fluorescent proteins. We also used Partial Least-Squared (PLS) FMA to detect promising mutation sites for the modulation of photoswitching properties of RSFPs. Our results show that the flexibility of RSFP does depend on its state with a systematically higher flexibility in the dark state compared to the bright state. In particular our method highlights the importance of Val157 in Dronpa, which upon mutation yields a striking difference in the collective motions of the two mutants. Overall, we show that PLS-FMA yields information, complementary to static structures, that can guide the rational design of fluorescent proteins.

Molecular Dynamic Indicators of the Photoswitching Properties of Green Fluorescent Proteins.

Super-resolution fluorescence imaging techniques allow optical imaging of specimens beyond the diffraction limit of light. Super-resolution optical fluctuation imaging (SOFI) relies on computational analysis of stochastic blinking events to obtain a super-resolved image. As with some other super-resolution methods, this strong dependency on computational analysis can make it difficult to gauge how well the resulting images reflect the underlying sample structure. We herein report SOFIevaluator, an unbiased and parameter-free algorithm for calculating a set of metrics that describes the quality of super-resolution fluorescence imaging data for SOFI. We additionally demonstrate how SOFIevaluator can be used to identify fluorescent proteins that perform well for SOFI imaging under different imaging conditions.

SOFIevaluator: a strategy for the quantitative quality assessment of SOFI data.

Super-resolution fluorescence microscopy techniques allow imaging fluorescently labelled structures with a resolution that surpasses the diffraction limit of light (approx. 200nm). The quality and, thus, reliability of each of these techniques is strongly dependent on (1) the quality of the optics, (2) the fitness of the specific fluorescent label for the given technique and (3) the algorithms being used. Of these, the fitness of the labels is most subjective, as fitness metrics are scarce, and generating samples with different labels and imaging them is laborious. This prevent rigorous fitness assessment of fluorescent labels. We have developed a mathematical framework for assessing the quality of SOFI data [1], [2], which we used to assess the fitness of 20 different fluorescent protein labels for SOFI imaging. Here, we report this dataset of 2240 image sequences, representing 10 fields of view each of transfected Cos7 cells expressing each of the 20 different fluorescent proteins under 4-12 imaging conditions. The labels span the visible spectrum and include non-photo-transforming and photo-transforming fluorescent proteins. The imaging conditions consist of 4 different excitation powers, each with three different powers of 405 nm light added (except for the blue labels that are excited with 405 nm light). Though this data was in essence generated to assess which labels are best suited for SOFI imaging, it can be used as a benchmark for further development of the SOFI algorithm, or for the development of other super-resolution imaging modalities that benefit from similar input data.

A comprehensive dataset of image sequences covering 20 fluorescent protein labels and 12 imaging conditions for use in super-resolution imaging.

Genetically encoded biosensors are indispensable tools for visualizing the spatiotemporal dynamics of analytes or processes in living cells in vitro and in vivo. Their widespread adaptation has gone hand in hand with the development of sensors for new analytes or processes and improved functionality and robustness. In this review, we highlight some of the recent advances in genetically encoded biosensor development, with a special focus on novel and innovative scaffolds that will lead to new possibilities in the future.

Genetically encoded biosensors based on innovative scaffolds.

Spectrally separated fluorophores allow the observation of multiple targets simultaneously inside living cells, leading to a deeper understanding of the molecular interplay that regulates cell function and fate. Chemogenetic systems combining a tag and a synthetic fluorophore provide certain advantages over fluorescent proteins since there is no requirement for chromophore maturation. Here, we present the engineering of a set of spectrally orthogonal fluorogen-activating tags based on the fluorescence-activating and absorption shifting tag (FAST) that are compatible with two-color, live-cell imaging. The resulting tags, greenFAST and redFAST, demonstrate orthogonality not only in their fluorogen recognition capabilities, but also in their one- and two-photon absorption profiles. This pair of orthogonal tags allowed the creation of a two-color cell cycle sensor capable of detecting very short, early cell cycles in zebrafish development and the development of split complementation systems capable of detecting multiple protein-protein interactions by live-cell fluorescence microscopy.

Orthogonal fluorescent chemogenetic reporters for multicolor imaging.

Genetically-encoded biosensors based on a single fluorescent protein are widely used to visualize analyte levels or enzymatic activities in cells, though usually to monitor relative changes rather than absolute values. We report photochromism-enabled absolute quantification (PEAQ) biosensing, a method that leverages the photochromic properties of biosensors to provide an absolute measure of the analyte concentration or activity. We develop proof-of-concept photochromic variants of the popular GCaMP family of Ca biosensors, and show that these can be used to resolve dynamic changes in the absolute Ca concentration in live cells. We also develop intermittent quantification, a technique that combines absolute aquisitions with fast fluorescence acquisitions to deliver fast but fully quantitative measurements. We also show how the photochromism-based measurements can be expanded to situations where the absolute illumination intensities are unknown. In principle, PEAQ biosensing can be applied to other biosensors with photochromic properties, thereby expanding the possibilities for fully quantitative measurements in complex and dynamic systems.

Absolute measurement of cellular activities using photochromic single-fluorophore biosensors and intermittent quantification.

Reversibly switchable monomeric Cherry (rsCherry) is a photoswitchable variant of the red fluorescent protein mCherry. We report that this protein gradually and irreversibly loses its red fluorescence in the dark over a period of months at 4 °C and a few days at 37 °C. We also find that its ancestor, mCherry, undergoes a similar fluorescence loss but at a slower rate. X-ray crystallography and mass spectrometry reveal that this is caused by the cleavage of the p-hydroxyphenyl ring from the chromophore and the formation of two novel types of cyclic structures at the remaining chromophore moiety. Overall, our work sheds light on a new process occurring within fluorescent proteins, further adding to the chemical diversity and versatility of these molecules.

Benjamien Moeyaert

Trellis Research Group,
Department of Cellular and Molecular Medicine,
Department of Microbiology,
Immunology and Transplantation,
Trellis Research Group, Department of Cellular and Molecular Medicine, Department of Microbiology, Immunology and Transplantation

KU Leuven

Quantification of Adeno-Associated Viral Genomes in Purified Vector Samples by Digital Droplet Polymerase Chain Reaction