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Image sensors capable of capturing individual photons have made tremendous progress in recent years. However, this technology faces a major limitation. Because they capture scene information at the individual photon level, the raw data is sparse and noisy. Here we propose CASPI: Collaborative Photon Processing for Active Single-Photon Imaging, a technology-agnostic, application-agnostic, and training-free photon processing pipeline for emerging high-resolution single-photon cameras. By collaboratively exploiting both local and non-local correlations in the spatio-temporal photon data cubes, CASPI estimates scene properties reliably even under very challenging lighting conditions. We demonstrate the versatility of CASPI with two applications: LiDAR imaging over a wide range of photon flux levels, from a sub-photon to high ambient regimes, and live-cell autofluorescence FLIM in low photon count regimes. We envision CASPI as a basic building block of general-purpose photon processing units that will be implemented on-chip in future single-photon cameras. The sparse, noisy, and distorted raw photon data captured by single-photon cameras make it difficult to estimate scene properties under challenging illumination conditions. Here, the authors present Collaborative photon processing for Active Single-Photon Imaging (CASPI), a technology-agnostic, application-agnostic, and training-free photon processing pipeline for high-resolution single-photon cameras.

The delivery of therapeutics to the central nervous system remains a major challenge in part due to the presence of the blood–brain barrier (BBB). Recently, cell-derived vesicles, particularly exosomes, have emerged as an attractive vehicle for targeting drugs to the brain, but whether or how they cross the BBB remains unclear. Here, we investigated the interactions between exosomes and brain microvascular endothelial cells (BMECs) in vitro under conditions that mimic the healthy and inflamed BBB in vivo . Transwell assays revealed that luciferase-carrying exosomes can cross a BMEC monolayer under stroke-like, inflamed conditions (TNF- α activated) but not under normal conditions. Confocal microscopy showed that exosomes are internalized by BMECs through endocytosis, co-localize with endosomes, in effect primarily utilizing the transcellular route of crossing. Together, these results indicate that cell-derived exosomes can cross the BBB model under stroke-like conditions in vitro . This study encourages further development of engineered exosomes as drug delivery vehicles or tracking tools for treating or monitoring neurological diseases.

The rise of antibiotic resistance requires the development of new strategies to combat bacterial infection and pathogenesis. A major direction has been the development of drugs that broadly target virulence. However, few targets have been identified due to the species-specific nature of many virulence regulators. The lack of a virulence regulator that is conserved across species has presented a further challenge to the development of therapeutics. Here, we identify that NADH activity has an important role in the induction of virulence in the pathogen P. aeruginosa . This finding, coupled with the ubiquity of NADH in bacterial pathogens, opens up the possibility of targeting enzymes that process NADH as a potential broad antivirulence approach. The availability of energy has significant impact on cell physiology. However, the role of cellular metabolism in bacterial pathogenesis is not understood. We investigated the dynamics of central metabolism during virulence induction by surface sensing and quorum sensing in early-stage biofilms of the multidrug-resistant bacterium Pseudomonas aeruginosa . We established a metabolic profile for P. aeruginosa using fluorescence lifetime imaging microscopy (FLIM), which reports the activity of NADH in live cells. We identified a critical growth transition period during which virulence is activated. We performed FLIM measurements and direct measurements of NADH and NAD + concentrations during this period. Here, planktonic (low-virulence) and surface-attached (virulence-activated) populations diverged into distinct metabolic states, with the surface-attached population exhibiting FLIM lifetimes that were associated with lower levels of enzyme-bound NADH and decreasing total NAD(H) production. We inhibited virulence by perturbing central metabolism using citrate and pyruvate, which further decreased the enzyme-bound NADH fraction and total NAD(H) production and suggested the involvement of the glyoxylate pathway in virulence activation in surface-attached populations. In addition, we induced virulence at an earlier time using the electron transport chain oxidase inhibitor antimycin A. Our results demonstrate the use of FLIM to noninvasively measure NADH dynamics in biofilms and suggest a model in which a metabolic rearrangement accompanies the virulence activation period. IMPORTANCE The rise of antibiotic resistance requires the development of new strategies to combat bacterial infection and pathogenesis. A major direction has been the development of drugs that broadly target virulence. However, few targets have been identified due to the species-specific nature of many virulence regulators. The lack of a virulence regulator that is conserved across species has presented a further challenge to the development of therapeutics. Here, we identify that NADH activity has an important role in the induction of virulence in the pathogen P. aeruginosa . This finding, coupled with the ubiquity of NADH in bacterial pathogens, opens up the possibility of targeting enzymes that process NADH as a potential broad antivirulence approach.

In the field of fluorescence microscopy, there is continued demand for dynamic technologies that can exploit the complete information from every pixel of an image. One imaging technique with proven ability for yielding additional information from fluorescence imaging is Fluorescence Lifetime Imaging Microscopy (FLIM). FLIM allows for the measurement of how long a fluorophore stays in an excited energy state, and this measurement is affected by changes in its chemical microenvironment, such as proximity to other fluorophores, pH, and hydrophobic regions. This ability to provide information about the microenvironment has made FLIM a powerful tool for cellular imaging studies ranging from metabolic measurement to measuring distances between proteins. The increased use of FLIM has necessitated the development of computational tools for integrating FLIM analysis with image and data processing. To address this need, we have created FLIMJ, an ImageJ plugin and toolkit that allows for easy use and development of extensible image analysis workflows with FLIM data. Built on the FLIMLib decay curve fitting library and the ImageJ Ops framework, FLIMJ offers FLIM fitting routines with seamless integration with many other ImageJ components, and the ability to be extended to create complex FLIM analysis workflows. Building on ImageJ Ops also enables FLIMJ’s routines to be used with Jupyter notebooks and integrate naturally with science-friendly programming in, e.g., Python and Groovy. We show the extensibility of FLIMJ in two analysis scenarios: lifetime-based image segmentation and image colocalization. We also validate the fitting routines by comparing them against industry FLIM analysis standards.

Fluoro-Gold is a fluorescent neuronal tracer suitable for targeted deep imaging of the nervous system. Widefield fluorescence microscopy enables visualization of Fluoro-Gold, but lacks depth discrimination. Though scanning laser confocal microscopy yields volumetric data, imaging depth is limited, and optimal single-photon excitation of Fluoro-Gold requires an unconventional ultraviolet excitation line. Two-photon excitation microscopy employs ultrafast pulsed infrared lasers to image fluorophores at high-resolution at unparalleled depths in opaque tissue. Deep imaging of Fluoro-Gold-labeled neurons carries potential to advance understanding of the central and peripheral nervous systems, yet its two-photon spectral and temporal properties remain uncharacterized. Herein, we report the two-photon excitation spectrum of Fluoro-Gold between 720 and 990 nm, and its fluorescence decay rate in aqueous solution and murine brainstem tissue. We demonstrate unprecedented imaging depth of whole-mounted murine brainstem via two-photon excitation microscopy of Fluoro-Gold labeled facial motor nuclei. Optimal two-photon excitation of Fluoro-Gold within microscope tuning range occurred at 720 nm, while maximum lifetime contrast was observed at 760 nm with mean fluorescence lifetime of 1.4 ns. Whole-mount brainstem explants were readily imaged to depths in excess of 450 µm via immersion in refractive-index matching solution.

Fluorescence properties of a molecule can be used to study the structural and functional nature of biological processes. Physical properties, including fluorescence lifetime, emission spectrum, emission polarization, and others, help researchers probe a molecule, produce desired effects, and infer causes and consequences. Correlative imaging techniques such as hyperdimensional imaging microscopy (HDIM) combine the physical properties and biochemical states of a fluorophore. Here we present a fiber-based imaging system that can generate hyper-dimensional contrast by combining multiple fluorescence properties into a single fluorescence lifetime decay curve. Fluorescence lifetime imaging microscopy (FLIM) with controlled excitation polarization and temporally dispersed emission can generate a spectrally coded, polarization-filtered lifetime distribution for a pixel. This HDIM scheme generates a better contrast between different molecules than that from individual techniques. This setup uses only a single detector and is simpler to implement, modular, cost-efficient, and adaptable to any existing FLIM microscope. We present higher contrast data from Arabidopsis thaliana epidermal cells based on intrinsic anthocyanin emission properties under multiphoton excitation. This work lays the foundation for an alternative hyperdimensional imaging system and demonstrates that contrast-based imaging is useful to study cellular heterogeneity in biological samples.

Advances in neural engineering have brought about a number of implantable devices for improved brain stimulation and recording. Unfortunately, many of these micro-implants have not been adopted due to issues of signal loss, deterioration, and host response to the device. While glial scar characterization is critical to better understand the mechanisms that affect device functionality or tissue viability, analysis is frequently hindered by immunohistochemical tissue processing methods that result in device shattering and tissue tearing artifacts. Devices are commonly removed prior to sectioning, which can itself disturb the quality of the study. In this methods implementation study, we use the label free, optical sectioning method of second harmonic generation (SHG) to examine brain slices of various implanted intracortical electrodes and demonstrate collagen fiber distribution not found in normal brain tissue. SHG can easily be used in conjunction with multiphoton microscopy to allow direct intrinsic visualization of collagen-containing glial scars on the surface of cortically implanted electrode probes without imposing the physical strain of tissue sectioning methods required for other high resolution light microscopy modalities. Identification and future measurements of these collagen fibers may be useful in predicting host immune response and device signal fidelity.

Background/Objectives: Despite the role of metabolism in breast cancer metastasis, we still cannot predict which breast tumors will progress to distal metastatic lesions or remain dormant. This work uses metabolic imaging to study breast cancer cell lines (4T1, 4T07, and 67NR) with differing metastatic potential in a 3D collagen gel bioreactor system. Methods: Within the bioreactor, hyperpolarized magnetic resonance spectroscopy (HP-MRS) is used to image lactate/pyruvate ratios, while fluorescence lifetime imaging microscopy (FLIM) of endogenous metabolites measures metabolism at the cellular scale. Results: HP-MRS results showed no lactate peak for 67NR and a comparatively large lactate/pyruvate ratio for both 4T1 and 4T07 cell lines, suggestive of greater pyruvate utilization with greater metastatic potential. Similar patterns were observed using FLIM with significant increases in FAD intensity, redox ratio, and NAD(P)H lifetime. The lactate/pyruvate ratio was strongly correlated to NAD(P)H lifetime, consistent with the role of NADH as an electron donor for the glycolytic pathway, suggestive of an overall upregulation of metabolism (both glycolytic and oxidative), for the 4T07 and 4T1 cell lines compared to the non-metastatic 67NR cell line. Conclusions: These findings support a complementary role for HP-MRS and FLIM enabled by a novel collagen gel bioreactor system to investigate metastatic potential and cancer metabolism.

Fluorescence lifetime imaging microscopy (FLIM) of the metabolic co-enzyme nicotinamide adenine dinucleotide (phosphate) [NAD(P)H] is a popular method to monitor single-cell metabolism within unperturbed, living 3D systems. However, FLIM of NAD(P)H has not been performed in a light-sheet geometry, which is advantageous for rapid imaging of cells within live 3D samples. We aim to design, validate, and demonstrate a proof-of-concept light-sheet system for NAD(P)H FLIM. A single-photon avalanche diode camera was integrated into a light-sheet microscope to achieve optical sectioning and limit out-of-focus contributions for NAD(P)H FLIM of single cells. An NAD(P)H light-sheet FLIM system was built and validated with fluorescence lifetime standards and with time-course imaging of metabolic perturbations in pancreas cancer cells with 10 s integration times. NAD(P)H light-sheet FLIM was demonstrated with live neutrophil imaging in a larval zebrafish tail wound also with 10 s integration times. Finally, the theoretical and practical imaging speeds for NAD(P)H FLIM were compared across laser scanning and light-sheet geometries, indicating a to acquisition speed advantage for the light sheet compared to the laser scanning geometry. FLIM of NAD(P)H is feasible in a light-sheet geometry and is attractive for 3D live cell imaging applications, such as monitoring immune cell metabolism and migration within an organism.

Advanced digital control of microscopes and programmable data acquisition workflows have become increasingly important for improving the throughput and reproducibility of optical imaging experiments. Combinations of imaging modalities have enabled a more comprehensive understanding of tissue biology and tumor microenvironments in histopathological studies. However, insufficient imaging throughput and complicated workflows still limit the scalability of multimodal histopathology imaging. We present a hardware-software co-design of a whole slide scanning system for high-throughput multimodal tissue imaging, including brightfield (BF) and laser scanning microscopy. The system can automatically detect regions of interest using deep neural networks in a low-magnification rapid BF scan of the tissue slide and then conduct high-resolution BF scanning and laser scanning imaging on targeted regions with deep learning-based run-time denoising and resolution enhancement. The acquisition workflow is built using Pycro-Manager, a Python package that bridges hardware control libraries of the Java-based open-source microscopy software Micro-Manager in a Python environment. The system can achieve optimized imaging settings for both modalities with minimized human intervention and speed up the laser scanning by an order of magnitude with run-time image processing. The system integrates the acquisition pipeline and data analysis pipeline into a single workflow that improves the throughput and reproducibility of multimodal histopathological imaging.