METAPHOR: Metabolic evaluation through phasor-based hyperspectral imaging and organelle recognition for mouse blastocysts and oocytes.

Only 30% of embryos from in vitro fertilized oocytes successfully implant and develop to term, leading to repeated transfer cycles. To reduce time-to-pregnancy and stress for patients, there is a need for a diagnostic tool to better select embryos and oocytes based on their physiology. The current standard employs brightfield imaging, which provides limited physiological information. Here, we introduce METAPHOR: Metabolic Evaluation through Phasor-based Hyperspectral Imaging and Organelle Recognition. This non-invasive, label-free imaging method combines two-photon illumination and AI to deliver the metabolic profile of embryos and oocytes based on intrinsic autofluorescence signals. We used it to classify i) mouse blastocysts cultured under standard conditions or with depletion of selected metabolites (glucose, pyruvate, lactate); and ii) oocytes from young and old mouse females, or in vitro-aged oocytes. The imaging process was safe for blastocysts and oocytes. The METAPHOR classification of control vs. metabolites-depleted embryos reached an area under the ROC curve (AUC) of 93.7%, compared to 51% achieved for human grading using brightfield imaging. The binary classification of young vs. old/in vitro-aged oocytes and their blastulation prediction using METAPHOR reached an AUC of 96.2% and 82.2%, respectively. Finally, organelle recognition and segmentation based on the flavin adenine dinucleotide signal revealed that quantification of mitochondria size and distribution can be used as a biomarker to classify oocytes and embryos. The performance and safety of the method highlight the accuracy of noninvasive metabolic imaging as a complementary approach to evaluate oocytes and embryos based on their physiology.

A single-shot hyperspectral phasor camera for fast, multi-color fluorescence microscopy.

Hyperspectral fluorescence imaging improves multiplexed observations of biological samples by utilizing multiple color channels across the spectral range to compensate for spectral overlap between labels. Typically, spectral resolution comes at a cost of decreased detection efficiency, which both hampers imaging speed and increases photo-toxicity to the samples. Here, we present a high-speed, high-efficiency snapshot spectral acquisition method, based on optical compression of the fluorescence spectra via Fourier transform, that overcomes the challenges of discrete spectral sampling: single-shot hyperspectral phasor camera (SHy-Cam). SHy-Cam captures fluorescence spatial and spectral information in a single exposure with a standard scientific CMOS camera, with photon efficiency of over 80%, easily and with acquisition rates exceeding 30 datasets per second, making it a powerful tool for multi-color in vivo imaging. Its simple design, using readily available optical components, and its easy integration provide a low-cost solution for multi-color fluorescence imaging with increased efficiency and speed.

HyU: Hybrid Unmixing for longitudinal in vivo imaging of low signal-to-noise fluorescence.

The expansion of fluorescence bioimaging toward more complex systems and geometries requires analytical tools capable of spanning widely varying timescales and length scales, cleanly separating multiple fluorescent labels and distinguishing these labels from background autofluorescence. Here we meet these challenging objectives for multispectral fluorescence microscopy, combining hyperspectral phasors and linear unmixing to create Hybrid Unmixing (HyU). HyU is efficient and robust, capable of quantitative signal separation even at low illumination levels. In dynamic imaging of developing zebrafish embryos and in mouse tissue, HyU was able to cleanly and efficiently unmix multiple fluorescent labels, even in demanding volumetric timelapse imaging settings. HyU permits high dynamic range imaging, allowing simultaneous imaging of bright exogenous labels and dim endogenous labels. This enables coincident studies of tagged components, cellular behaviors and cellular metabolism within the same specimen, providing more accurate insights into the orchestrated complexity of biological systems.

FRaeppli: a multispectral imaging toolbox for cell tracing and dense tissue analysis in zebrafish.

Visualizing cell shapes and interactions of differentiating cells is instrumental for understanding organ development and repair. Across species, strategies for stochastic multicolour labelling have greatly facilitated in vivo cell tracking and mapping neuronal connectivity. Yet integrating multi-fluorophore information into the context of developing zebrafish tissues is challenging given their cytoplasmic localization and spectral incompatibility with common fluorescent markers. Inspired by Drosophila Raeppli, we developed FRaeppli (Fish-Raeppli) by expressing bright membrane- or nuclear-targeted fluorescent proteins for efficient cell shape analysis and tracking. High spatiotemporal activation flexibility is provided by the Gal4/UAS system together with Cre/lox and/or PhiC31 integrase. The distinct spectra of the FRaeppli fluorescent proteins allow simultaneous imaging with GFP and infrared subcellular reporters or tissue landmarks. We demonstrate the suitability of FRaeppli for live imaging of complex internal organs, such as the liver, and have tailored hyperspectral protocols for time-efficient acquisition. Combining FRaeppli with polarity markers revealed previously unknown canalicular topologies between differentiating hepatocytes, reminiscent of the mammalian liver, suggesting common developmental mechanisms. The multispectral FRaeppli toolbox thus enables the comprehensive analysis of intricate cellular morphologies, topologies and lineages at single-cell resolution in zebrafish.

Pre-processing visualization of hyperspectral fluorescent data with Spectrally Encoded Enhanced Representations.

Hyperspectral fluorescence imaging is gaining popularity for it enables multiplexing of spatio-temporal dynamics across scales for molecules, cells and tissues with multiple fluorescent labels. This is made possible by adding the dimension of wavelength to the dataset. The resulting datasets are high in information density and often require lengthy analyses to separate the overlapping fluorescent spectra. Understanding and visualizing these large multi-dimensional datasets during acquisition and pre-processing can be challenging. Here we present Spectrally Encoded Enhanced Representations (SEER), an approach for improved and computationally efficient simultaneous color visualization of multiple spectral components of hyperspectral fluorescence images. Exploiting the mathematical properties of the phasor method, we transform the wavelength space into information-rich color maps for RGB display visualization. We present multiple biological fluorescent samples and highlight SEER's enhancement of specific and subtle spectral differences, providing a fast, intuitive and mathematical way to interpret hyperspectral images during collection, pre-processing and analysis.

Using enhanced number and brightness to measure protein oligomerization dynamics in live cells.

Protein dimerization and oligomerization are essential to most cellular functions, yet measurement of the size of these oligomers in live cells, especially when their size changes over time and space, remains a challenge. A commonly used approach for studying protein aggregates in cells is number and brightness (N&B), a fluorescence microscopy method that is capable of measuring the apparent average number of molecules and their oligomerization (brightness) in each pixel from a series of fluorescence microscopy images. We have recently expanded this approach in order to allow resampling of the raw data to resolve the statistical weighting of coexisting species within each pixel. This feature makes enhanced N&B (eN&B) optimal for capturing the temporal aspects of protein oligomerization when a distribution of oligomers shifts toward a larger central size over time. In this protocol, we demonstrate the application of eN&B by quantifying receptor clustering dynamics using electron-multiplying charge-coupled device (EMCCD)-based total internal reflection microscopy (TIRF) imaging. TIRF provides a superior signal-to-noise ratio, but we also provide guidelines for implementing eN&B in confocal microscopes. For each time point, eN&B requires the acquisition of 200 frames, and it takes a few seconds up to 2 min to complete a single time point. We provide an eN&B (and standard N&B) MATLAB software package amenable to any standard confocal or TIRF microscope. The software requires a high-RAM computer (64 Gb) to run and includes a photobleaching detrending algorithm, which allows extension of the live imaging for more than an hour.

Fiber pattern removal and image reconstruction method for snapshot mosaic hyperspectral endoscopic images.

Hyperspectral endoscopic imaging has the potential to enhance clinical diagnostics and outcome. Most commercial endoscopes utilize imaging fiber bundles to transmit the collected signal from the patient to the medical operator. These bundles consist of several fiber cores surrounded by a cladding layer creating comb structure-like artifacts, which complicate further analysis, both spatially and spectrally. Here we present an optical fiber pattern removal algorithm which we applied to hyperspectral bronchoscopic images robustly and quantitatively without the need for specific optical or electrical hardware. We validate the performance of the pattern removal by using a novel hyperspectral phasor approach. This algorithm can be generalized to all forms of fiber bundle hyperspectral endoscopy.

Nanopatterns of Surface-Bound EphrinB1 Produce Multivalent Ligand-Receptor Interactions That Tune EphB2 Receptor Clustering.

Here we present a nanostructured surface able to produce multivalent interactions between surface-bound ephrinB1 ligands and membrane EphB2 receptors. We created ephrinB1 nanopatterns of regular size (<30 nm in diameter) by using self-assembled diblock copolymers. Next, we used a statistically enhanced version of the Number and Brightness technique, which can discriminate-with molecular sensitivity-the oligomeric states of diffusive species to quantitatively track the EphB2 receptor oligomerization process in real time. The results indicate that a stimulation using randomly distributed surface-bound ligands was not sufficient to fully induce receptor aggregation. Conversely, when nanopatterned onto our substrates, the ligands effectively induced a strong receptor oligomerization. This presentation of ligands improved the clustering efficiency of conventional ligand delivery systems, as it required a 9-fold lower ligand surface coverage and included faster receptor clustering kinetics compared to traditional cross-linked ligands. In conclusion, nanostructured diblock copolymers constitute a novel strategy to induce multivalent ligand-receptor interactions leading to a stronger, faster, and more efficient receptor activation, thus providing a useful strategy to precisely tune and potentiate receptor responses. The efficiency of these materials at inducing cell responses can benefit applications such as the design of new bioactive materials and drug-delivery systems.

Eph-ephrin signaling modulated by polymerization and condensation of receptors.

Eph receptor signaling plays key roles in vertebrate tissue boundary formation, axonal pathfinding, and stem cell regeneration by steering cells to positions defined by its ligand ephrin. Some of the key events in Eph-ephrin signaling are understood: ephrin binding triggers the clustering of the Eph receptor, fostering transphosphorylation and signal transduction into the cell. However, a quantitative and mechanistic understanding of how the signal is processed by the recipient cell into precise and proportional responses is largely lacking. Studying Eph activation kinetics requires spatiotemporal data on the number and distribution of receptor oligomers, which is beyond the quantitative power offered by prevalent imaging methods. Here we describe an enhanced fluorescence fluctuation imaging analysis, which employs statistical resampling to measure the Eph receptor aggregation distribution within each pixel of an image. By performing this analysis over time courses extending tens of minutes, the information-rich 4D space (x, y, oligomerization, time) results were coupled to straightforward biophysical models of protein aggregation. This analysis reveals that Eph clustering can be explained by the combined contribution of polymerization of receptors into clusters, followed by their condensation into far larger aggregates. The modeling reveals that these two competing oligomerization mechanisms play distinct roles: polymerization mediates the activation of the receptor by assembling monomers into 6- to 8-mer oligomers; condensation of the preassembled oligomers into large clusters containing hundreds of monomers dampens the signaling. We propose that the polymerization-condensation dynamics creates mechanistic explanation for how cells properly respond to variable ligand concentrations and gradients.

Hyperspectral phasor analysis enables multiplexed 5D in vivo imaging.

Time-lapse imaging of multiple labels is challenging for biological imaging as noise, photobleaching and phototoxicity compromise signal quality, while throughput can be limited by processing time. Here, we report software called Hyper-Spectral Phasors (HySP) for denoising and unmixing multiple spectrally overlapping fluorophores in a low signal-to-noise regime with fast analysis. We show that HySP enables unmixing of seven signals in time-lapse imaging of living zebrafish embryos.

Intracellular kinetics of the androgen receptor shown by multimodal Image Correlation Spectroscopy (mICS).

The androgen receptor (AR) pathway plays a central role in prostate cancer (PCa) growth and progression and is a validated therapeutic target. In response to ligand binding AR translocates to the nucleus, though the molecular mechanism is not well understood. We therefore developed multimodal Image Correlation Spectroscopy (mICS) to measure anisotropic molecular motion across a live cell. We applied mICS to AR translocation dynamics to reveal its multimodal motion. By integrating fluorescence imaging methods we observed evidence for diffusion, confined movement, and binding of AR within both the cytoplasm and nucleus of PCa cells. Our findings suggest that in presence of cytoplasmic diffusion, the probability of AR crossing the nuclear membrane is an important factor in determining the AR distribution between cytoplasm and the nucleus, independent of functional microtubule transport. These findings may have implications for the future design of novel therapeutics targeting the AR pathway in PCa.

Spectral Phasor approach for fingerprinting of photo-activatable fluorescent proteins Dronpa, Kaede and KikGR.

The phasor global analysis algorithm is common for fluorescence lifetime applications, but has only been recently proposed for spectral analysis. Here the phasor representation and fingerprinting is exploited in its second harmonic to determine the number and spectra of photo-activated states as well as their conversion dynamics. We follow the sequence of photo-activation of proteins over time by rapidly collecting multiple spectral images. The phasor representation of the cumulative images provides easy identification of the spectral signatures of each photo-activatable protein.

Spectral phasor approach for fingerprinting of photo-activatable fluorescent proteins Dronpa, Kaede and KikGR.

The phasor global analysis algorithm is common for fluorescence lifetime applications, but has only been recently proposed for spectral analysis. Here the phasor representation and fingerprinting is exploited in its second harmonic to determine the number and spectra of photo-activated states as well as their conversion dynamics. We follow the sequence of photo-activation of proteins over time by rapidly collecting multiple spectral images. The phasor representation of the cumulative images provides easy identification of the spectral signatures of each photo-activatable protein.

Inclined selective plane illumination microscopy adaptor for conventional microscopes.

Driven by the biological sciences, there is an increased need for imaging modalities capable of live cell imaging with high spatial and temporal resolution. To achieve this goal in a comprehensive manner, three-dimensional acquisitions are necessary. Ideal features of a modern microscope system should include high imaging speed, high contrast ratio, low photo-bleaching and photo-toxicity, good resolution in a 3D context, and mosaic acquisition for large samples. Given the importance of collecting data in live sample further increases the technical challenges required to solve these issues. This work presents a practical version of a microscopy method, Selective Plane Illumination Microscopy re-introduced by Huisken et al. (Science2004,305,1007-1009). This method is gaining importance in the biomedical field, but its use is limited by difficulties associated with unconventional microscope design which employs two objectives and a particular kind of sample preparation needed to insert the sample between the objectives. Based on the selective plane illumination principle but with a design similar to the Total Internal Reflection Fluorescence microscope, Dunsby (Dunsby, Opt Express 2008,16,20306-20316) demonstrated the oblique plane microscope (OPM) using a single objective which uses conventional sample preparation protocols. However, the Dunsby instrument was not intended to be part of a commercial microscope. In this work, we describe a system with the advantages of OPM and that can be used as an adaptor to commonly used microscopes, such as IX-71 Olympus, simplifying the construction of the OPM and increasing performance of a conventional microscope. We named our design inclined selective plane illumination microscope (iSPIM).