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

FLIMB: fluorescence lifetime microendoscopy for metabolic and functional imaging of femoral marrow at subcellular resolution

Intravital imaging of bone marrow provides a unique opportunity to study cellular dynamics and their interaction with the tissue microenvironment, which governs cell functions and metabolic profiles. To optically access the deep marrow of long bones, we previously developed a microendoscopy system for longitudinal two-photon fluorescence imaging of the murine femur. However, this does not provide information on cell functions or metabolism, for which quantification fluorescence lifetime imaging (FLIM) has proven to be a versatile tool. We present and characterize FLIMB, an adapted GRIN-based microendoscopic system capable of performing reliable, co-registered TCSPC-based two-photon excited FLIM and fluorescence imaging in the femur of fluorescent reporter mice, at sub-cellular resolution. Using FLIMB, we demonstrate metabolic imaging via NAD(P)H-FLIM and intracellular Ca2+ signaling via FRET-FLIM in immune cell subsets, in the femoral marrow. This method retains the power to study molecular mechanisms underlying various cell functions in tissue context thus providing new insights into bone biology.

Multi-color two-laser super-resolution structured illumination microscopy for the visualization of multi-organelle in living cells

In this study, we introduced a novel dual-laser multi-color imaging system. Integrated with a multi-channel filter wheel, this system compared three spectral decontamination algorithms (nonnegative matrix factorization [NMF], RCAN, and PICASSO) showcasing its efficacy in achieving four-color imaging with only two laser sources. Combined with a reliable image reconstruction algorithm, the spatial resolution of four channels super-resolution four-color images reached 130, 125, 133, and 132 nm, respectively. Lipid droplets, mitochondria, lysosomes, and nuclei from the mouse hepatocytes (AML12), human neuroblastoma cells (SH-SY5Y), mouse hippocampal neuronal cells (HT-22), and immortalized murine bone marrow-derived macrophages were imaged. At the same time, the chromatin condensation, nuclear contraction, DNA fragmentation, apoptotic body formation, as well as the fusion of Mito and Lyso involved in mitochondrial autophagy were observed in HT-22 and SH-SY5Y cells suffering oxidative stress. Our multi-color SIM imaging system establishes a powerful platform for dynamic organelle studies and other high-resolution investigations in live cells.

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.

Two-photon autofluorescence lifetime assay of rabbit photoreceptors and retinal pigment epithelium during light-dark visual cycles in rabbit retina

Two-photon excited fluorescence (TPEF) is a powerful technique that enables the examination of intrinsic retinal fluorophores involved in cellular metabolism and the visual cycle. Although previous intensity-based TPEF studies in non-human primates have successfully imaged several classes of retinal cells and elucidated aspects of both rod and cone photoreceptor function, fluorescence lifetime imaging (FLIM) of the retinal cells under light-dark visual cycle has yet to be fully exploited. Here we demonstrate a FLIM assay of photoreceptors and retinal pigment epithelium (RPE) that reveals key insights into retinal physiology and adaptation. We found that photoreceptor fluorescence lifetimes increase and decrease in sync with light and dark exposure, respectively. This is likely due to changes in all-trans-retinol and all-trans-retinal levels in the outer segments, mediated by phototransduction and visual cycle activity. During light exposure, RPE fluorescence lifetime was observed to increase steadily over time, as a result of all-trans-retinol accumulation during the visual cycle and decreasing metabolism caused by the lack of normal perfusion of the sample. Our system can measure the fluorescence lifetime of intrinsic retinal fluorophores on a cellular scale, revealing differences in lifetime between retinal cell classes under different conditions of light and dark exposure.

Assessment of unmixing approaches for the quantitation of SERS nanoparticles in highly multiplexed spectral images

Surface-enhanced Raman scattering nanoparticles (SERS NPs) offer powerful optical contrast features for imaging assays. Their gold core enhances the inelastic scattering cross section, allowing highly sensitive and rapid detection, and their characteristic sets of narrow spectral bands give them unsurpassed multiplexing capabilities. Multiplexed hyperspectral images are commonly unmixed using a compensation matrix of reference spectra to produce quantitative image channels illustrating the distribution of each material. It is these unmixed channels that are fit for interpretation from assays utilizing SERS NP contrast agents. Some factors that may impact SERS NP quantitative and dynamic range capabilities may include endogenous background heterogeneity, the ability of unmixing algorithms to account for signal variances, and linear system conditioning imposed by contrast agent signals. We report on hyperspectral Raman imaging of mixtures of SERS NPs from an expanded library of contrast agents. We study increasing plexity and varying degrees of system conditioning as inputs to a diverse set of classical, non-negatively constrained, and regularized regression algorithms to investigate which signal features and unmixing methods deliver the most promising quantitation performance with the least error. Raman imaging of SERS NP mixtures is performed on controlled substrates and representative biological specimens, and experimental results are compared against ground truth data. We evaluate spectral fitting fidelity, quantitation, and specificity correlations with system conditioning. Spectral unmixing with a regularized hybrid of least squares regression with principal component analysis (HLP) algorithm approximated spectra with 3.5× better fitting fidelity and 3× better quantitation robustness with tissue background compared with simpler unmixing routines.

More than double the fun with two-photon excitation microscopy

For generations researchers have been observing the dynamic processes of life through the lens of a microscope. This has offered tremendous insights into biological phenomena that span multiple orders of time- and length-scales ranging from the pure magic of molecular reorganization at the membrane of immune cells, to cell migration and differentiation during development or wound healing. Standard fluorescence microscopy techniques offer glimpses at such processes in vitro, however, when applied in intact systems, they are challenged by reduced signal strengths and signal-to-noise ratios that result from deeper imaging. As a remedy, two-photon excitation (TPE) microscopy takes a special place, because it allows us to investigate processes in vivo, in their natural environment, even in a living animal. Here, we review the fundamental principles underlying TPE aimed at basic and advanced microscopy users interested in adopting TPE for intravital imaging. We focus on applications in neurobiology, present current trends towards faster, wider and deeper imaging, discuss the combination with photon counting technologies for metabolic imaging and spectroscopy, as well as highlight outstanding issues and drawbacks in development and application of these methodologies.

BINGO: a blind unmixing algorithm for ultra-multiplexing fluorescence images

MOTIVATION

Spectral imaging is often used to observe different objects with multiple fluorescent labels to reveal the development of the biological event. As the number of observed objects increases, the spectral overlap between fluorophores becomes more serious, and obtaining a "pure" picture of each fluorophore becomes a major challenge. Here, we propose a blind spectral unmixing algorithm called BINGO (Blind unmixing via SVD-based Initialization Nmf with project Gradient descent and spare cOnstrain), which can extract all kinds of fluorophores more accurately from highly overlapping multichannel data, even if the spectra of the fluorophores are extremely similar or their fluorescence intensity varies greatly.

RESULTS

BINGO can isolate up to 10 fluorophores from spectral imaging data for a single excitation. nine-color living HeLa cells were visualized distinctly with BINGO. It provides an important algorithmic tool for multiplex imaging studies, especially in intravital imaging. BINGO shows great potential in multicolor imaging for biomedical sciences.

AVAILABILITY AND IMPLEMENTATION

The source code used for this paper is available with the test data at https://github.com/Xinyuan555/BINGO_unmixing.

Multiplexed imaging in live cells using pulsed interleaved excitation spectral FLIM

Multiplexed fluorescence detection has become increasingly important in the fields of biosensing and bioimaging. Although a variety of excitation/detection optical designs and fluorescence unmixing schemes have been proposed to allow for multiplexed imaging, rapid and reliable differentiation and quantification of multiple fluorescent species at each imaging pixel is still challenging. Here we present a pulsed interleaved excitation spectral fluorescence lifetime microscopic (PIE-sFLIM) system that can simultaneously image six fluorescent tags in live cells in a single hyperspectral snapshot. Using an alternating pulsed laser excitation scheme at two different wavelengths and a synchronized 16-channel time-resolved spectral detector, our PIE-sFLIM system can effectively excite multiple fluorophores and collect their emission over a broad spectrum for analysis. Combining our system with the advanced live-cell labeling techniques and the lifetime/spectral phasor analysis, our PIE-sFLIM approach can well unmix the fluorescence of six fluorophores acquired in a single measurement, thus improving the imaging speed in live-specimen investigation.

Multidimensional quantitative characterization of basal cell carcinoma by spectral- and time-resolved two-photon microscopy

Basal cell carcinoma (BCC) is a common type of skin cancer. Conventional approaches to BCC diagnosis often involve invasive histological examinations that can distort or even destroy information derived from the biomolecules in the sample. Therefore, a non-invasive, label-free examination method for the clinical diagnosis of BCC represents a critical advance. This study combined spectral- and time-resolved two-photon microscopy with a spectral phasor to extract rich biochemical information describing macroscopic tumor morphology and microscopic tumor metabolism. The proposed optical imaging technique achieved the rapid and efficient separation of tumor structures in systematic research conducted on normal and BCC human skin tissues. The results demonstrate that a combination of multidimensional data (e.g., fluorescence intensity, spectrum, and lifetime) with a spectral phasor can accurately identify tumor boundaries and achieve rapid separation. This label-free, real-time, multidimensional imaging technique serves as a complement to the conventional tumor diagnostic toolbox and demonstrates significant potential for the early diagnosis of BCC and wider applications in intraoperative auxiliary imaging.

Assessment of Essential Information in the Fourier Domain to Accelerate Raman Hyperspectral Microimaging

In the context of multivariate curve resolution (MCR) and spectral unmixing, essential information (EI) corresponds to the most linearly dissimilar rows and/or columns of a two-way data matrix. In recent works, the assessment of EI has been revealed to be a very useful practical tool to select the most relevant spectral information before MCR analysis, key features being speed and compression ability. However, the canonical approach relies on the principal component analysis to evaluate the convex hull that encapsulates the data structure in the normalized score space. This implies that the evaluation of the essentiality of each spectrum can only be achieved after all the spectra have been acquired by the instrument. This paper proposes a new approach to extract EI in the Fourier domain (EIFD). Spectral information is transformed into Fourier coefficients, and EI is assessed from a convex hull analysis of the data point cloud in the 2D phasor plots of a few selected harmonics. Because the coordinate system of a phasor plot does not depend on the data themselves, the evaluation of the essentiality of the information carried by each spectrum can be achieved individually and independently from the others. As a result, time-consuming operations like Raman spectral imaging can be significantly accelerated exploiting a chemometric-driven (i.e., based on the EI content of a spectral pixel) procedure for data acquisition and targeted sampling. The usefulness of EIFD is shown by analyzing Raman hyperspectral microimaging data, demonstrating a potential 50-fold acceleration of Raman acquisition.

Quantitative assessment of near-infrared fluorescent proteins

Recent progress in fluorescent protein development has generated a large diversity of near-infrared fluorescent proteins (NIR FPs), which are rapidly becoming popular probes for a variety of imaging applications. However, the diversity of NIR FPs poses a challenge for end-users in choosing the optimal one for a given application. Here we conducted a systematic and quantitative assessment of intracellular brightness, photostability, oligomeric state, chemical stability and cytotoxicity of 22 NIR FPs in cultured mammalian cells and primary mouse neurons and identified a set of top-performing FPs including emiRFP670, miRFP680, miRFP713 and miRFP720, which can cover a majority of imaging applications. The top-performing proteins were further validated for in vivo imaging of neurons in Caenorhabditis elegans, zebrafish, and mice as well as in mice liver. We also assessed the applicability of the selected NIR FPs for multicolor imaging of fusions, expansion microscopy and two-photon imaging.