Excitation spectral microscopy for highly multiplexed fluorescence imaging and quantitative biosensing

Hyperspectral imaging and dynamic region of interest tracking approaches to quantify localized cAMP signals

Cyclic adenosine monophosphate (cAMP) is a ubiquitous second messenger known to orchestrate a myriad of cellular functions over a wide range of timescales. In the last 20 years, a variety of single-cell sensors have been developed to measure second messenger signals including cAMP, Ca2+, and the balance of kinase and phosphatase activities. These sensors utilize changes in fluorescence emission of an individual fluorophore or Förster resonance energy transfer (FRET) to detect changes in second messenger concentration. cAMP and kinase activity reporter probes have provided powerful tools for the study of localized signals. Studies relying on these and related probes have the potential to further revolutionize our understanding of G protein-coupled receptor signaling systems. Unfortunately, investigators have not been able to take full advantage of the potential of these probes due to the limited signal-to-noise ratio of the probes and the limited ability of standard epifluorescence and confocal microscope systems to simultaneously measure the distributions of multiple signals (e.g. cAMP, Ca2+, and changes in kinase activities) in real time. In this review, we focus on recently implemented strategies to overcome these limitations: hyperspectral imaging and adaptive thresholding approaches to track dynamic regions of interest (ROI). This combination of approaches increases signal-to-noise ratio and contrast, and allows identification of localized signals throughout cells. These in turn lead to the identification and quantification of intracellular signals with higher effective resolution. Hyperspectral imaging and dynamic ROI tracking approaches offer investigators additional tools with which to visualize and quantify multiplexed intracellular signaling systems.

3D Amplified Single-Cell RNA and Protein Imaging Identifies Oncogenic Transcript Subtypes in B-Cell Acute Lymphoblastic Leukemia

Simultaneous in situ detection of transcript and protein markers at the single-cell level is essential for gaining a better understanding of tumor heterogeneity and for predicting and monitoring treatment responses. However, the limited accessibility to advanced 3D imaging techniques has hindered their rapid implementation. Here, we present a 3D single-cell imaging technique, termed 3D digital rolling circle amplification (4DRCA), capable of the multiplexed and amplified simultaneous digital quantification of single-cell RNAs and proteins using standard fluorescence microscopy and off-the-shelf reagents. We generated spectrally distinguishable DNA amplicons from molecular markers through an integrative protocol combining single-cell RNA and protein assays and directly enumerated the amplicons by leveraging an open-source algorithm for 3D deconvolution with a custom-built automatic gating algorithm. With 4DRCA, we were able to simultaneously quantify surface protein markers and cytokine transcripts in T-lymphocytes. We also show that 4DRCA can distinguish BCR-ABL1 fusion transcript positive B-cell acute lymphoblastic leukemia cells with or without CD19 protein expression. The accessibility and extensibility of 4DRCA render it broadly applicable to other cell-based diagnostic workflows, enabling sensitive and accurate single-cell RNA and protein profiling.

High-speed fluorescence excitation-scanning hyperspectral imaging microscopy using thin-film tunable filters

Hyperspectral imaging (HSI) technologies have enabled a range of experimental techniques and studies in the fluorescence microscopy field. Unfortunately, a drawback of many HSI microscope platforms is increased acquisition time required to collect images across many spectral bands, as well as signal loss due to the need to filter or disperse emitted fluorescence into many discrete bands. We have previously demonstrated that an alternative approach of scanning the fluorescence excitation spectrum can greatly improve system efficiency by decreasing light losses associated with emission filtering. Our initial system was configured using an array of thin-film tunable filters (TFTFs, VersaChrome, Semrock) mounted in a tiltable filter wheel (VF-5, Sutter) that required ~150-200 ms to switch between wavelengths. Here, we present a new configuration for high-speed switching of TFTFs to allow rapid time-lapse HSI microscopy. A TFTF array was mounted in a custom holder that was attached to a piezoelectric rotation mount (ThorLabs), allowing high-speed rotation. Switching between adjacent filters was achieved using the internal optics of a DG-4 lightsource (Sutter Instrument), including a pair of off-axis parabolic mirrors and galvanometers. Output light was coupled to a liquid lightguide and into an inverted widefield fluorescence microscope (TI-2, Nikon Instruments). Initial tests indicate that the HSI system provides a 15-20 nm bandwidth tunable excitation band and ~10-20 ms wavelength switch time, allowing for high-speed HSI imaging of dynamic cellular events. This work was supported by NIH P01HL066299, R01HL169522, NIH TL1TR003106, and NSF MRI1725937.

Temporally multiplexed imaging of dynamic signaling networks in living cells

Molecular signals interact in networks to mediate biological processes. To analyze these networks, it would be useful to image many signals at once, in the same living cell, using standard microscopes and genetically encoded fluorescent reporters. Here, we report temporally multiplexed imaging (TMI), which uses genetically encoded fluorescent proteins with different clocklike properties-such as reversibly photoswitchable fluorescent proteins with different switching kinetics-to represent different cellular signals. We linearly decompose a brief (few-second-long) trace of the fluorescence fluctuations, at each point in a cell, into a weighted sum of the traces exhibited by each fluorophore expressed in the cell. The weights then represent the signal amplitudes. We use TMI to analyze relationships between different kinase activities in individual cells, as well as between different cell-cycle signals, pointing toward broad utility throughout biology in the analysis of signal transduction cascades in living systems.

AutoUnmix: an autoencoder-based spectral unmixing method for multi-color fluorescence microscopy imaging

Multiplexed fluorescence microscopy imaging is widely used in biomedical applications. However, simultaneous imaging of multiple fluorophores can result in spectral leaks and overlapping, which greatly degrades image quality and subsequent analysis. Existing popular spectral unmixing methods are mainly based on computational intensive linear models, and the performance is heavily dependent on the reference spectra, which may greatly preclude its further applications. In this paper, we propose a deep learning-based blindly spectral unmixing method, termed AutoUnmix, to imitate the physical spectral mixing process. A transfer learning framework is further devised to allow our AutoUnmix to adapt to a variety of imaging systems without retraining the network. Our proposed method has demonstrated real-time unmixing capabilities, surpassing existing methods by up to 100-fold in terms of unmixing speed. We further validate the reconstruction performance on both synthetic datasets and biological samples. The unmixing results of AutoUnmix achieve the highest SSIM of 0.99 in both three- and four-color imaging, with nearly up to 20% higher than other popular unmixing methods. For experiments where spectral profiles and morphology are akin to simulated data, our method realizes the quantitative performance demonstrated above. Due to the desirable property of data independency and superior blind unmixing performance, we believe AutoUnmix is a powerful tool for studying the interaction process of different organelles labeled by multiple fluorophores.

Single-Molecule Displacement Mapping Unveils Sign-Asymmetric Protein Charge Effects on Intraorganellar Diffusion

Using single-molecule displacement/diffusivity mapping (SMdM), an emerging super-resolution microscopy method, here we quantify, at nanoscale resolution, the diffusion of a typical fluorescent protein (FP) in the endoplasmic reticulum (ER) and mitochondrion of living mammalian cells. We thus show that the diffusion coefficients D in both organelles are ∼40% of that in the cytoplasm, with the latter exhibiting higher spatial inhomogeneities. Moreover, we unveil that diffusions in the ER lumen and the mitochondrial matrix are markedly impeded when the FP is given positive, but not negative, net charges. Calculation shows most intraorganellar proteins as negatively charged, hence a mechanism to impede the diffusion of positively charged proteins. However, we further identify the ER protein PPIB as an exception with a positive net charge and experimentally show that the removal of this positive charge elevates its intra-ER diffusivity. We thus unveil a sign-asymmetric protein charge effect on the nanoscale intraorganellar diffusion.

Single-molecule displacement mapping unveils sign-asymmetric protein charge effects on intraorganellar diffusion

Using single-molecule displacement/diffusivity mapping (SM d M), an emerging super-resolution microscopy method, here we quantify, at nanoscale resolution, the diffusion of a typical fluorescent protein (FP) in the endoplasmic reticulum (ER) and mitochondrion of living mammalian cells. We thus show that the diffusion coefficients D in both organelles are ~40% of that in the cytoplasm, with the latter exhibiting higher spatial inhomogeneities. Moreover, we unveil that diffusions in the ER lumen and the mitochondrial matrix are markedly impeded when the FP is given positive, but not negative, net charges. Calculation shows most intraorganellar proteins as negatively charged, thus a mechanism to impede the diffusion of positively charged proteins. However, we further identify the ER protein PPIB as an exception with a positive net charge, and experimentally show that the removal of this positive charge elevates its intra-ER diffusivity. We thus unveil a sign-asymmetric protein charge effect on the nanoscale intraorganellar diffusion.

Tetra-color superresolution microscopy based on excitation spectral demixing

Multicolor imaging allows protein colocalizations and organelle interactions to be studied in biological research, which is especially important for single-molecule localization microscopy (SMLM). Here, we propose a multicolor method called excitation-resolved stochastic optical reconstruction microscopy (ExR-STORM). The method, which is based on the excitation spectrum of fluorescent dyes, successfully separated four spectrally very close far-red organic fluorophores utilizing three excitation lasers with cross-talk of less than 3%. Dyes that are only 5 nm apart in the emission spectrum were resolved, resulting in negligible chromatic aberrations. This method was extended to three-dimensional (3D) imaging by combining the astigmatic method, providing a powerful tool for resolving 3D morphologies at the nanoscale.

Super-multiplexing excitation spectral microscopy with multiple fluorescence bands

Fluorescence microscopy, with high molecular specificity and selectivity, is a valuable tool for studying complex biological systems and processes. However, the ability to distinguish a large number of distinct subcellular structures in a single sample is impeded by the broad spectra of molecular fluorescence. We have recently shown that excitation spectral microscopy provides a powerful means to unmix up to six fluorophores in a single fluorescence band. Here, by working with multiple fluorescence bands, we extend this approach to the simultaneous imaging of up to ten targets, with the potential for further expansions. By covering the excitation/emission bandwidth across the full visible range, an ultra-broad 24-wavelength excitation scheme is established through frame-synchronized scanning of the excitation wavelength from a white lamp via an acousto-optic tunable filter (AOTF), so that full-frame excitation-spectral images are obtained every 24 camera frames, offering superior spectral information and multiplexing capability. With numerical simulations, we validate the concurrent imaging of 10 fluorophores spanning the visible range to achieve exceptionally low (∼0.5%) crosstalks. For cell imaging experiments, we demonstrate unambiguous identification of up to eight different intracellular structures labeled by common fluorophores of substantial spectral overlap with minimal color crosstalks. We thus showcase an easy-to-implement, cost-effective microscopy system for visualizing complex cellular components with more colors and lower crosstalks.

Spectrally Tunable Förster Resonance Energy Transfer-Based Biosensors Using Organic Dye Grafting

Biosensors based on Förster resonance energy transfer (FRET) have revolutionized cellular biology by allowing the direct measurement of biochemical processes in situ. Many genetically encoded sensors make use of fluorescent proteins that are limited in spectral versatility and that allow few ways to change the spectral properties once the construct has been created. In this work, we developed genetically encoded FRET biosensors based on the chemigenetic SNAP and HaloTag domains combined with matching organic fluorophores. We found that the resulting constructs can display comparable responses, kinetics, and reversibility compared to their fluorescent protein-based ancestors, but with the added advantage of spectral versatility, including the availability of red-shifted dye pairs. However, we also find that the introduction of these tags can alter the sensor readout, showing that careful validation is required before applying such constructs in practice. Overall, our approach delivers an innovative methodology that can readily expand the spectral variety and versatility of FRET-based biosensors.

Excitation modalities for enhanced micro and nanoparticle imaging in a smartphone coupled 3D printed fluorescent microscope

Smartphone fluorescent microscopes (SFM) offer many functional characteristics similar to their benchtop counterparts at a fraction of the cost and have been shown to work for biomarker detection in many biomedical applications. However, imaging and quantification of bioparticles in the sub-micron and nanometer range remains challenging as it requires aggressive robustness and high-performance metrics of the building blocks of SFM. Here, we explored multiple excitation modalities and their performance on the imaging capability of an SFM. Employing spatial positional variations of the excitation source with respect to the imaging sample plane (i.e., parallel, perpendicular, oblique), we developed three distinct SFM variants. These SFM variants were tested using green-fluorescent beads of four different sizes (8.3, 2, 1, 0.8 μm). Optimal excitation voltage range was determined by imaging these beads at multiple excitation voltages to optimize for no data loss and acceptable noise levels for each SFM variant. The SFM with parallel excitation was able to only image 8.3 μm beads while the SFM variants with perpendicular and oblique excitation were able to image all four bead sizes. Relative performance of the SFM variants was quantified by calculating signal difference to noise ratio (SDNR) and contrast to noise ratio (CNR) from the captured images. SFM with oblique excitation generated the highest SDNR and CNR values, whereas, for power consumption, SFM with perpendicular excitation generated the best results. This study sheds light on significant findings related to performance of SFM systems and their potential utility in biomedical applications involving sub-micron imaging. Similarly, findings of this study are translatable to benchtop microscopy instruments as well as to enhance their imaging performance metrics.

Pushing the colorimetry camera-based fluorescence microscopy to low light imaging by denoising and dye combination

Colorimetry camera-based fluorescence microscopy (CCFM) is a single-frame imaging method for observing multiple biological events simultaneously. Compared with the traditional multi-color fluorescence microscopy methods based on sequential excitation or spectral splitting, the CCFM method simplifies multi-color fluorescence imaging experiments, while keeping a high spatial resolution. However, when the level of the detected fluorescence signal decreases, the image quality, the demosaicking algorithm precision, and the discrimination of fluorescence channels on the colorimetry camera will also decrease. Thus, CCFM has a poor color resolution under a low signal level. For example, the crosstalk will be higher than 10% when the signal is less than 100 photons/pixel. To solve this problem, we developed a new algorithm that combines sCMOS noise correction with demosaicking, and a dye selection method based on the spectral response characteristics of the colorimetry camera. By combining the above two strategies, low crosstalk can be obtained with 4 ∼ 6 fold fewer fluorescence photons, and low light single-frame four-color fluorescence imaging was successfully performed on fixed cos-7 cells. This study expands the power of the CCFM method, and provides a simple and efficient way for various bioimaging applications in low-light conditions.

Microscopy is better in color: development of a streamlined spectral light path for real-time multiplex fluorescence microscopy

Spectroscopic image data has provided molecular discrimination for numerous fields including: remote sensing, food safety and biomedical imaging. Despite the various technologies for acquiring spectral data, there remains a trade-off when acquiring data. Typically, spectral imaging either requires long acquisition times to collect an image stack with high spectral specificity or acquisition times are shortened at the expense of fewer spectral bands or reduced spatial sampling. Hence, new spectral imaging microscope platforms are needed to help mitigate these limitations. Fluorescence excitation-scanning spectral imaging is one such new technology, which allows more of the emitted signal to be detected than comparable emission-scanning spectral imaging systems. Here, we have developed a new optical geometry that provides spectral illumination for use in excitation-scanning spectral imaging microscope systems. This was accomplished using a wavelength-specific LED array to acquire spectral image data. Feasibility of the LED-based spectral illuminator was evaluated through simulation and benchtop testing and assessment of imaging performance when integrated with a widefield fluorescence microscope. Ray tracing simulations (TracePro) were used to determine optimal optical component selection and geometry. Spectral imaging feasibility was evaluated using a series of 6-label fluorescent slides. The LED-based system response was compared to a previously tested thin-film tunable filter (TFTF)-based system. Spectral unmixing successfully discriminated all fluorescent components in spectral image data acquired from both the LED and TFTF systems. Therefore, the LED-based spectral illuminator provided spectral image data sets with comparable information content so as to allow identification of each fluorescent component. These results provide proof-of-principle demonstration of the ability to combine output from many discrete wavelength LED sources using a double-mirror (Cassegrain style) optical configuration that can be further modified to allow for high speed, video-rate spectral image acquisition. Real-time spectral fluorescence microscopy would allow monitoring of rapid cell signaling processes (i.e., Ca²⁺ and other second messenger signaling) and has potential to be translated to clinical imaging platforms.

Single-shot multi-color fluorescence microscopy via a colorimetry camera

Multi-color fluorescence microscopy presents highly detailed biological samples interactively. However, current multi-color methods suffer from an intricate optical setup, complicated image analysis, or a long acquisition time. To address these issues, here we develop a simple multi-color method based on a customized colorimetry camera to enable the detection of multiple structures from single-shot acquisition. The unfiltered channel (W pixels) and color channels (R, G, B, and NIR pixels) in this customized camera simultaneously provide a broad detection wavelength range and high detection sensitivity. We built a simple optical setup by replacing the monochrome camera in a basic fluorescence microscopy system with a colorimetry camera, and developed effective image analysis procedures to reconstruct a multi-color image from a single frame of a raw image. We demonstrated single-shot four-color wide-field fluorescence imaging on fixed cos-7 cells with < 5% cross talk, which is comparable to the best reported values. Our method greatly simplifies both the optical system and image analysis in the widely used method of multi-color fluorescence microscopy, thus offering an effective and easy way to study multiple objects at the same time.

PICASSO allows ultra-multiplexed fluorescence imaging of spatially overlapping proteins without reference spectra measurements

Ultra-multiplexed fluorescence imaging requires the use of spectrally overlapping fluorophores to label proteins and then to unmix the images of the fluorophores. However, doing this remains a challenge, especially in highly heterogeneous specimens, such as the brain, owing to the high degree of variation in the emission spectra of fluorophores in such specimens. Here, we propose PICASSO, which enables more than 15-color imaging of spatially overlapping proteins in a single imaging round without using any reference emission spectra. PICASSO requires an equal number of images and fluorophores, which enables such advanced multiplexed imaging, even with bandpass filter-based microscopy. We show that PICASSO can be used to achieve strong multiplexing capability in diverse applications. By combining PICASSO with cyclic immunofluorescence staining, we achieve 45-color imaging of the mouse brain in three cycles. PICASSO provides a tool for multiplexed imaging with high accessibility and accuracy for a broad range of researchers.

Ultra-multiplexed fluorescence imaging is currently difficult. Here the authors report PICASSO which enables 15-colour imaging of spatially overlapping proteins in a single-round of imaging; they combine it with cyclic immunofluorescence to achieve 45-colour imaging of the mouse brain in 3 cycles.

Live-cell fluorescence spectral imaging as a data science challenge

Live-cell fluorescence spectral imaging is an evolving modality of microscopy that uses specific properties of fluorophores, such as excitation or emission spectra, to detect multiple molecules and structures in intact cells. The main challenge of analyzing live-cell fluorescence spectral imaging data is the precise quantification of fluorescent molecules despite the weak signals and high noise found when imaging living cells under non-phototoxic conditions. Beyond the optimization of fluorophores and microscopy setups, quantifying multiple fluorophores requires algorithms that separate or unmix the contributions of the numerous fluorescent signals recorded at the single pixel level. This review aims to provide both the experimental scientist and the data analyst with a straightforward description of the evolution of spectral unmixing algorithms for fluorescence live-cell imaging. We show how the initial systems of linear equations used to determine the concentration of fluorophores in a pixel progressively evolved into matrix factorization, clustering, and deep learning approaches. We outline potential future trends on combining fluorescence spectral imaging with label-free detection methods, fluorescence lifetime imaging, and deep learning image analysis.

A Snapshot Infrared Imaging Fourier Transform Spectrometer for Dynamic Target Detection

Infrared imaging spectrometry is utilized to detect and identify targets by collecting spectral images. In some cases, the infrared spectral images of dynamic targets need to be detected accurately, such as during remote sensing target tracking and engine tail flame detection applications. However, it is difficult to obtain reliable measurement results when using a traditional infrared imaging spectrometer with a scanning structure because of motion artifacts. This work proposes a snapshot infrared imaging Fourier transform spectrometer (SIIFTS) based on stepped micromirrors and a lens array. Two micromirrors sample the spectral information, and the lens array can realize multi-aperture snapshot imaging. The spectrometer is capable of collecting three-dimensional (3D) datasets during a single measurement period, and its absence of motion artifacts and its ability to work without moving parts is very important for dynamic target detection. The achromatic optical design of the SIIFTS is completed, and two front imaging systems for remote sensing and tail flame detection applications are designed for selection. A SIIFTS prototype was built, and flame detection tests were conducted in a laboratory environment. The experimental results show that the SIIFTS developed here can accurately and stably obtain real-time image and spectral information from dynamic targets.

Introduction to Immunohistochemistry: From to Evolving Science to Timeless Art

Immunohistochemistry and all techniques that use antibodies and fluorescence are widespread, essential and irreplaceable tools used in both research laboratory settings and diagnostic pathology laboratories. The field was born approximately 80 years ago, with the idea that antibodies could be tagged with fluorescent substances and used to detect antigens in cells and microorganisms, and has vertiginously evolved since; these advances have come in all aspects of the methodology, tissue fixation, generation of antibodies, monoclonal antibodies, signal amplification, antigen retrieval, signal amplification, microscopy and have become increasingly sophisticated, from in situ hybridization, in situ proximity ligation assay, flow cytometry, comet assay, to multiplexing and green fluorescent protein reconstitution, yielding Nobel Prizes along the way and generating invaluable scientific and diagnostic advances as well as timeless beautiful images.

Single Molecules Are Your Quanta: A Bottom-Up Approach toward Multidimensional Super-resolution Microscopy

The rise of single-molecule localization microscopy (SMLM) and related super-resolution methods over the past 15 years has revolutionized how we study biological and materials systems. In this Perspective, we reflect on the underlying philosophy of how diffraction-unlimited pictures containing rich spatial and functional information may gradually emerge through the local accumulation of single-molecule measurements. Starting with the basic concepts, we analyze the uniqueness of and opportunities in building up the final picture one molecule at a time. After brief introductions to the more established multicolor and three-dimensional measurements, we highlight emerging efforts to extend SMLM to new dimensions and functionalities as fluorescence polarization, emission spectra, and molecular motions, and discuss rising opportunities and future directions. With single molecules as our quanta, the bottom-up accumulation approach provides a powerful conduit for multidimensional microscopy at the nanoscale.

Combination of Structured Illumination Microscopy with Hyperspectral Imaging for Cell Analysis

Existing structured illumination microscopy (SIM) allows super-resolution live-cell imaging in few color channels that provide merely morphological information but cannot acquire the sample spectrum that is strongly relevant to the underlying physicochemical property. We develop hyperspectral SIM which enables high-speed spectral super-resolution imaging in SIM for the first time. Through optically mapping the three-dimensional (x, y, and λ) datacube of the sample to the detector plane, hyperspectral SIM allows snapshot spectral imaging of the SIM raw image, detecting the sample spectrum while retaining the high-speed and super-resolution characteristics of SIM. We demonstrate hyperspectral SIM imaging and reconstruct a datacube containing 31 super-resolution images of different wavelengths from only 9 exposures, achieving a 15 nm spectral resolution. We show time-lapse hyperspectral SIM imaging that achieves an imaging speed of 2.7 s per datacube-31-fold faster than the existing wavelength scanning strategy. To demonstrate the great prospects for further combining hyperspectral SIM with various spectral analysis methods, we also perform spectral unmixing of the hyperspectral SIM result while imaging the spectrally overlapped sample.

Super-multiplex imaging of cellular dynamics and heterogeneity by integrated stimulated Raman and fluorescence microscopy

Observing multiple molecular species simultaneously with high spatiotemporal resolution is crucial for comprehensive understanding of complex, dynamic, and heterogeneous biological systems. The recently reported super-multiplex optical imaging breaks the “color barrier” of fluorescence to achieve multiplexing number over six in living systems, while its temporal resolution is limited to several minutes mainly by slow color tuning. Herein, we report integrated stimulated Raman and fluorescence microscopy with simultaneous multimodal color tunability at high speed, enabling super-multiplex imaging covering diverse molecular contrasts with temporal resolution of seconds. We highlight this technique by demonstrating super-multiplex time-lapse imaging and image-based cytometry of live cells to investigate the dynamics and cellular heterogeneity of eight intracellular components simultaneously. Our technique provides a powerful tool to elucidate spatiotemporal organization and interactions in biological systems.

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Integrated SRS and fluorescence microscopy with fast tunability has been developed

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Eight-color live-cell imaging can be conducted with a temporal resolution of seconds

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Super-multiplex time-lapse imaging reveals complex organelle interactions

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Super-multiplex image-based cytometry accesses high-dimensional heterogeneity