Excitation-Scanning Hyperspectral Imaging Microscopy to Efficiently Discriminate Fluorescence Signals

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.

Multifaceted mirror array illuminator for fluorescence excitation-scanning spectral imaging microscopy

SIGNIFICANCE

Hyperspectral imaging (HSI) technologies offer great potential in fluorescence microscopy for multiplexed imaging, autofluorescence removal, and analysis of autofluorescent molecules. However, there are also associated trade-offs when implementing HSI in fluorescence microscopy systems, such as decreased acquisition speed, resolution, or field-of-view due to the need to acquire spectral information in addition to spatial information. The vast majority of HSI fluorescence microscopy systems provide spectral discrimination by filtering or dispersing the fluorescence emission, which may result in loss of emitted fluorescence signal due to optical filters, dispersive optics, or supporting optics, such as slits and collimators. Technologies that scan the fluorescence excitation spectrum may offer an approach to mitigate some of these trade-offs by decreasing the complexity of the emission light path.

AIM

We describe the development of an optical technique for hyperspectral imaging fluorescence excitation-scanning (HIFEX) on a microscope system.

APPROACH

The approach is based on the design of an array of wavelength-dependent light emitting diodes (LEDs) and a unique beam combining system that uses a multifurcated mirror. The system was modeled and optimized using optical ray trace simulations, and a prototype was built and coupled to an inverted microscope platform. The prototype system was calibrated, and initial feasibility testing was performed by imaging multilabel slide preparations.

RESULTS

We present results from optical ray trace simulations, prototyping, calibration, and feasibility testing of the system. Results indicate that the system can discriminate between at least six fluorescent labels and autofluorescence and that the approach can provide decreased wavelength switching times, in comparison with mechanically tuned filters.

CONCLUSIONS

We anticipate that LED-based HIFEX microscopy may provide improved performance for time-dependent and photosensitive assays.

Combined hyperspectral imaging, monolayer stress microscopy, and S8 image analysis approaches for simultaneously interrogating cellular signals and biomechanics

Second messenger signals, e.g., Ca2+ and cyclic nucleotides, orchestrate a wide range of cellular events. The methods by which second messenger signals determine specific physiological responses are complex. Recent studies point to the importance of temporal and spatial encoding in determining signal specificity. Studies also indicate the importance of mechanical stimuli, substrate stiffness, and mechanical responses - the "mechanosome" - in regulating physiology. Hence, approaches that probe both chemical and mechanical signals are needed. Here, we report preliminary efforts to combine hyperspectral imaging for second messenger signal measurements, monolayer stress microscopy for mechanical force measurements, and S8 analysis software for quantifying localized signals - specifically, Ca2+ dynamics and mechanical forces in human airway smooth muscle cells (HASMCs). HASMCs were prepared as confluent monolayers on 11 kPa gels with embedded fluorescent microparticles that serve as fiducial markers as well as smaller microparticles to measure deformation (strain). Imaging was performed using a custom excitation-scanning hyperspectral microscope. Hyperspectral images were unmixed to identify signals from cellular fluorescent labels (e.g., CAL 590-AM) and fluorescent microparticles. Images were analyzed to quantify localized force dynamics through monolayer stress microscopy. S8 software was used to identify, track, and quantify spatially-localized Ca2+ activity. Results indicate that localized and transient cellular signals and forces can be quantified and mapped within cell populations. Importantly, these results establish a method for simultaneous interrogation of cellular signals and mechanical forces that may play synergistic roles in regulating downstream cellular physiology in confluent monolayers. This work was supported by NIH P01HL066299, R01HL137030, R01HL058506, and NSF MRI1725937. Drs. Leavesley and Rich disclose financial interest in a university start-up company, SpectraCyte LLC, to commercialize spectral imaging technologies.

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.

Application of Microspectral Imaging in Motor and Sensory Nerve Classification

Objective

It aimed to explore the application of the microscopic hyperspectral technique in motor and sensory nerve classification.

Methods

The self-developed microscopic hyperspectral acquisition system was applied to collect the data of anterior and posterior spinal cord sections of white rabbits. The joint correction algorithm was employed to preprocess the collected data, such as noise reduction. On the basis of pure linear light source index, a new pixel purification algorithm based on cross contrast was proposed to extract more regions of interest, which was used for feature extraction of motor and sensory nerves. Besides, the ML algorithm was employed to classify motor and sensory nerves based on feature extraction results.

Results

The joint correction algorithm was adopted to preprocess the data collected by the microscopic hyperspectral technique, so as to eliminate the influence of the incident light source and the system and improve the classification accuracy. The axon and myelin spectrum curves of the two kinds of nerves in the stained specimens had the same trend, but the values of all kinds of spectrum of sensory nerves were higher than those of motor nerves. However, the myelin sheath spectrum curves of motor nerves in the unstained specimens were greatly different from the curves of sensory nerves. The axon spectrum curves had the same trend, but the axon spectrum values of sensory nerves were higher than those of motor nerves. The ML algorithm had high accuracy and fast speed in motor and sensory nerve classification, and the classification effect of stained specimens was better than that of unstained specimens.

Conclusion

The microscopic hyperspectral technique had high feasibility in sensory and motor nerve classification and was worthy of further research and promotion.

Multi-aperture system approach for snapshot multispectral imaging applications

We present an ultra-compact system approach for snapshot, multispectral imaging. It is based on a slanted linear variable spectral filter mounted in close proximity to the entrance pupil of a micro-optical, multi-aperture imaging system. A compact demonstration setup with a size of only 60 × 60 × 28 mm³ is developed, which enables the acquisition of 66 spectral channels in a single shot and offers a linear spectral sampling of approximately six nanometers over an extended wavelength range of 450-850 nm. The spatial sampling of each channel covers up to 400 × 400 pixels. First, the concept, the optical design and the fabrication are detailed. After the optical performance characterization, a comprehensive calibration strategy is developed and applied. An experimental demonstration is performed by acquiring the spatial and the spectral information of an imaged test scene.

Comparison of spectral FRET microscopy approaches for single-cell analysis

Förster resonance energy transfer (FRET) is a valuable tool for measuring molecular distances and the effects of biological processes such as cyclic nucleotide messenger signaling and protein localization. Most FRET techniques require two fluorescent proteins with overlapping excitation/emission spectral pairing to maximize detection sensitivity and FRET efficiency. FRET microscopy often utilizes differing peak intensities of the selected fluorophores measured through different optical filter sets to estimate the FRET index or efficiency. Microscopy platforms used to make these measurements include wide-field, laser scanning confocal, and fluorescence lifetime imaging. Each platform has associated advantages and disadvantages, such as speed, sensitivity, specificity, out-of-focus fluorescence, and Z-resolution. In this study, we report comparisons among multiple microscopy and spectral filtering platforms such as standard 2-filter FRET, emission-scanning hyperspectral imaging, and excitation-scanning hyperspectral imaging. Samples of human embryonic kidney (HEK293) cells were grown on laminin-coated 28 mm round gridded glass coverslips (10816, Ibidi, Fitchburg, Wisconsin) and transfected with adenovirus encoding a cAMP-sensing FRET probe composed of a FRET donor (Turquoise) and acceptor (Venus). Additionally, 3 FRET "controls" with fixed linker lengths between Turquoise and Venus proteins were used for inter-platform validation. Grid locations were logged, recorded with light micrographs, and used to ensure that whole-cell FRET was compared on a cell-by-cell basis among the different microscopy platforms. FRET efficiencies were also calculated and compared for each method. Preliminary results indicate that hyperspectral methods increase the signal-to-noise ratio compared to a standard 2-filter approach.