Light-sheet autofluorescence lifetime imaging with a single-photon avalanche diode array.

Significance: 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. Aim: We aim to design, validate, and demonstrate a proof-of-concept light-sheet system for NAD(P)H FLIM. Approach: 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. Results: 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 in vivo 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 30× to 6× acquisition speed advantage for the light sheet compared to the laser scanning geometry. Conclusions: 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.

Light sheet autofluorescence lifetime imaging with a single photon avalanche diode array.

Single photon avalanche diode (SPAD) array sensors can increase the imaging speed for fluorescence lifetime imaging microscopy (FLIM) by transitioning from laser scanning to widefield geometries. While a SPAD camera in epi-fluorescence geometry enables widefield FLIM of fluorescently labeled samples, label-free imaging of single-cell autofluorescence is not feasible in an epi-fluorescence geometry because background fluorescence from out-of-focus features masks weak cell autofluorescence and biases lifetime measurements. Here, we address this problem by integrating the SPAD camera in a light sheet illumination geometry to achieve optical sectioning and limit out-of-focus contributions, enabling fast label-free FLIM of single-cell NAD(P)H autofluorescence. The feasibility of this NAD(P)H light sheet FLIM system was confirmed with time-course imaging of metabolic perturbations in pancreas cancer cells with 10 s integration times, and in vivo NAD(P)H light sheet FLIM was demonstrated with live neutrophil imaging in a 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 30X to 6X frame rate advantage for the light sheet compared to the laser scanning geometry. This light sheet system provides faster frame rates for 3D NAD(P)H FLIM for live cell imaging applications such as monitoring single cell metabolism and immune cell migration throughout an entire living organism.

Hardware-software co-design of an open-source automatic multimodal whole slide histopathology imaging system.

Significance: 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. Aim: 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. Approach: 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. Results: 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. Conclusions: The system integrates the acquisition pipeline and data analysis pipeline into a single workflow that improves the throughput and reproducibility of multimodal histopathological imaging.

Optical imaging of collagen fiber damage to assess thermally injured human skin.

Surgery is the definitive treatment for burn patients who sustain full-thickness burn injuries. Visual assessment of burn depth is made by the clinician early after injury but is accurate only up to 70% of the time among experienced surgeons. Collagen undergoes denaturation as a result of thermal injury; however, the association of collagen denaturation and cellular death in response to thermal injury is unknown. While gene expression assays and histologic staining allow for ex vivo identification of collagen changes, these methods do not provide spatial or integrity information in vivo. Thermal effects on collagen and the role of collagen in wound repair have been understudied in human burn models due to a lack of methods to visualize both intact and denatured collagen. Hence, there is a critical need for a clinically applicable method to discriminate between damaged and intact collagen fibers in tissues. We present two complementary candidate methods for visualization of collagen structure in three dimensions. Second harmonic generation imaging offers a label-free, high-resolution method to identify intact collagen. Simultaneously, a fluorophore-tagged collagen-mimetic peptide can detect damaged collagen. Together, these methods enable the characterization of collagen damage in human skin biopsies from burn patients, as well as ex vivo thermally injured human skin samples. These combined methods could enhance the understanding of the role of collagen in human wound healing after thermal injury and potentially assist in clinical decision-making.

Optimization of interstrand interactions enables burn detection with a collagen-mimetic peptide.

Collagen is an abundant component of the extracellular matrix and connective tissues. Some collagen-mimetic peptides (CMPs) that do not form homotrimers can anneal to damaged tissue. Here, through a computational screen, we identify (flpHypGly)7 as an optimal monomeric CMP for heterotrimer formation. We find that (flpHypGly)7 forms stable triple helices with (ProProGly)7 but not with itself. The nonnatural amino acid HflpOH, which is (2S,4S)-4-fluoroproline, is not toxic to human fibroblasts or keratinocytes. Conjugation of (flpHypGly)7 to a fluorescent dye enables the facile detection of burned collagenous tissue with high specificity. The ubiquity of collagen and the prevalence of injuries and diseases that disrupt endogenous collagen suggests widespread utility for this approach.

NAD(P)H fluorescence lifetime measurements in fixed biological tissues.

Autofluorescence based fluorescence lifetime imaging microscopy (AF-FLIM) techniques have come a long way from early studies on cancer characterization and have now been widely employed in several cellular and animal studies covering a wide range of diseases. The majority of research in autofluorescence imaging (AFI) study metabolic fluxes in live biological samples. However, tissues from clinical or scientific studies are often chemically fixed for preservation and stabilization of tissue morphology. Fixation is particularly crucial for enzymatic, functional, or histopathology studies. Interpretations of metabolic imaging such as optical redox intensity imaging and AF-FLIM, have often been viewed as potentially unreliable in a fixed sample due to lack of studies in this field. In this study, we carefully evaluate the possibility of extracting microenvironment information in fixed tissues using reduced nicotinamide adenine dinucleotide (phosphate) (NAD(P)H) endogenous fluorescence. The ability to distinguish changes such as metabolism and pH using intrinsic fluorescence in fixed tissues has great pathological value. In this work, we show that the lifetime based metabolic contrast in a sample is preserved after chemical fixation. The fluorescence lifetime of a sample increases with an additive fixative like formaldehyde; however, the fixed tissues retain metabolic signatures even after fixation. This study presents an opportunity to successfully image archived unstained histopathology tissues, and generate useful AF-FLIM signatures. We demonstrate the capability to draw metabolic interpretations in fixed tissues even after long periods of storage.

Autofluorescence lifetime imaging of cellular metabolism: Sensitivity toward cell density, pH, intracellular, and intercellular heterogeneity.

Autofluorescence imaging (AFI) has greatly accelerated in the last decade, way past its origins in detecting endogenous signals in biological tissues to identify differences between samples. There are many endogenous fluorescence sources of contrast but the most robust and widely utilized have been those associated with metabolism. The intrinsically fluorescent metabolic cofactors nicotinamide adenine dinucleotide (NAD+ /NADH) and flavin adenine dinucleotide (FAD/FADH2 ) have been utilized in a number of AFI applications including basic research, clinical, and pharmaceutical studies. Fluorescence lifetime imaging microscopy (FLIM) has emerged as one of the more powerful AFI tools for NADH and FAD characterization due to its unique ability to noninvasively detect metabolite bound and free states and quantitate cellular redox ratio. However, despite this widespread biological use, many standardization methods are still needed to extend FLIM-based AFI into a fully robust research and clinical diagnostic tools. FLIM is sensitive to a wide range of factors in the fluorophore microenvironment, and there are a number of analysis variables as well. To this end, there has been an emphasis on developing imaging standards and ways to make the image acquisition and analysis more consistent. However, biological conditions during FLIM-based AFI imaging are rarely considered as key sources of FLIM variability. Here, we present several experimental factors with supporting data of the cellular microenvironment such as confluency, pH, inter-/intracellular heterogeneity, and choice of cell line that need to be considered for accurate quantitative FLIM-based AFI measurement of cellular metabolism. © 2018 International Society for Advancement of Cytometry.

Viral highway to nucleus exposed by image correlation analyses.

Parvoviral genome translocation from the plasma membrane into the nucleus is a coordinated multistep process mediated by capsid proteins. We used fast confocal microscopy line scan imaging combined with image correlation methods including auto-, pair- and cross-correlation, and number and brightness analysis, to study the parvovirus entry pathway at the single-particle level in living cells. Our results show that the endosome-associated movement of virus particles fluctuates from fast to slow. Fast transit of single cytoplasmic capsids to the nuclear envelope is followed by slow movement of capsids and fast diffusion of capsid fragments in the nucleoplasm. The unique combination of image analyses allowed us to follow the fate of intracellular single virus particles and their interactions with importin ß revealing previously unknown dynamics of the entry pathway.

Mechanoresponsive stem cells to target cancer metastases through biophysical cues.

Despite decades of effort, little progress has been made to improve the treatment of cancer metastases. To leverage the central role of the mechanoenvironment in cancer metastasis, we present a mechanoresponsive cell system (MRCS) to selectively identify and treat cancer metastases by targeting the specific biophysical cues in the tumor niche in vivo. Our MRCS uses mechanosensitive promoter-driven mesenchymal stem cell (MSC)-based vectors, which selectively home to and target cancer metastases in response to specific mechanical cues to deliver therapeutics to effectively kill cancer cells, as demonstrated in a metastatic breast cancer mouse model. Our data suggest a strong correlation between collagen cross-linking and increased tissue stiffness at the metastatic sites, where our MRCS is specifically activated by the specific cancer-associated mechano-cues. MRCS has markedly reduced deleterious effects compared to MSCs constitutively expressing therapeutics. MRCS indicates that biophysical cues, specifically matrix stiffness, are appealing targets for cancer treatment due to their long persistence in the body (measured in years), making them refractory to the development of resistance to treatment. Our MRCS can serve as a platform for future diagnostics and therapies targeting aberrant tissue stiffness in conditions such as cancer and fibrotic diseases, and it should help to elucidate mechanobiology and reveal what cells "feel" in the microenvironment in vivo.