Reducing target binding affinity improves the therapeutic index of anti-MET antibody-drug conjugate in tumor bearing animals.

Many oncology antibody-drug conjugates (ADCs) have failed to demonstrate efficacy in clinic because of dose-limiting toxicity caused by uptake into healthy tissues. We developed an approach that harnesses ADC affinity to broaden the therapeutic index (TI) using two anti-mesenchymal-epithelial transition factor (MET) monoclonal antibodies (mAbs) with high affinity (HAV) or low affinity (LAV) conjugated to monomethyl auristatin E (MMAE). The estimated TI for LAV-ADC was at least 3 times greater than the HAV-ADC. The LAV- and HAV-ADCs showed similar levels of anti-tumor activity in the xenograft model, while the 111In-DTPA studies showed similar amounts of the ADCs in HT29 tumors. Although the LAV-ADC has ~2-fold slower blood clearance than the HAV-ADC, higher liver toxicity was observed with HAV-ADC. While the SPECT/CT 111In- and 124I- DTPA findings showed HAV-ADC has higher accumulation and rapid clearance in normal tissues, intravital microscopy (IVM) studies confirmed HAV mAb accumulates within hepatic sinusoidal endothelial cells while the LAV mAb does not. These results demonstrated that lowering the MET binding affinity provides a larger TI for MET-ADC. Decreasing the affinity of the ADC reduces the target mediated drug disposition (TMDD) to MET expressed in normal tissues while maintaining uptake/delivery to the tumor. This approach can be applied to multiple ADCs to improve the clinical outcomes.

NISNet3D: three-dimensional nuclear synthesis and instance segmentation for fluorescence microscopy images.

The primary step in tissue cytometry is the automated distinction of individual cells (segmentation). Since cell borders are seldom labeled, cells are generally segmented by their nuclei. While tools have been developed for segmenting nuclei in two dimensions, segmentation of nuclei in three-dimensional volumes remains a challenging task. The lack of effective methods for three-dimensional segmentation represents a bottleneck in the realization of the potential of tissue cytometry, particularly as methods of tissue clearing present the opportunity to characterize entire organs. Methods based on deep learning have shown enormous promise, but their implementation is hampered by the need for large amounts of manually annotated training data. In this paper, we describe 3D Nuclei Instance Segmentation Network (NISNet3D) that directly segments 3D volumes through the use of a modified 3D U-Net, 3D marker-controlled watershed transform, and a nuclei instance segmentation system for separating touching nuclei. NISNet3D is unique in that it provides accurate segmentation of even challenging image volumes using a network trained on large amounts of synthetic nuclei derived from relatively few annotated volumes, or on synthetic data obtained without annotated volumes. We present a quantitative comparison of results obtained from NISNet3D with results obtained from a variety of existing nuclei segmentation techniques. We also examine the performance of the methods when no ground truth is available and only synthetic volumes were used for training.

Factor VIII trafficking to CD4+ T cells shapes its immunogenicity and requires several types of antigen-presenting cells.

Despite >80 years of clinical experience with coagulation factor VIII (FVIII) inhibitors, surprisingly little is known about the in vivo mechanism of this most serious complication of replacement therapy for hemophilia A. These neutralizing antidrug alloantibodies arise in ∼30% of patients. Inhibitor formation is T-cell dependent, but events leading up to helper T-cell activation have been elusive because of, in part, the complex anatomy and cellular makeup of the spleen. Here, we show that FVIII antigen presentation to CD4+ T cells critically depends on a select set of several anatomically distinct antigen-presenting cells, whereby marginal zone B cells and marginal zone and marginal metallophilic macrophages but not red pulp macrophages (RPMFs) participate in shuttling FVIII to the white pulp in which conventional dendritic cells (DCs) prime helper T cells, which then differentiate into follicular helper T (Tfh) cells. Toll-like receptor 9 stimulation accelerated Tfh cell responses and germinal center and inhibitor formation, whereas systemic administration of FVIII alone in hemophilia A mice increased frequencies of monocyte-derived and plasmacytoid DCs. Moreover, FVIII enhanced T-cell proliferation to another protein antigen (ovalbumin), and inflammatory signaling-deficient mice were less likely to develop inhibitors, indicating that FVIII may have intrinsic immunostimulatory properties. Ovalbumin, which, unlike FVIII, is absorbed into the RPMF compartment, fails to elicit T-cell proliferative and antibody responses when administered at the same dose as FVIII. Altogether, we propose that an antigen trafficking pattern that results in efficient in vivo delivery to DCs and inflammatory signaling, shape the immunogenicity of FVIII.

Integrated Cytometry With Machine Learning Applied to High-Content Imaging of Human Kidney Tissue for In Situ Cell Classification and Neighborhood Analysis.

The human kidney is a complex organ with various cell types that are intricately organized to perform key physiological functions and maintain homeostasis. New imaging modalities, such as mesoscale and highly multiplexed fluorescence microscopy, are increasingly being applied to human kidney tissue to create single-cell resolution data sets that are both spatially large and multidimensional. These single-cell resolution high-content imaging data sets have great potential to uncover the complex spatial organization and cellular makeup of the human kidney. Tissue cytometry is a novel approach used for the quantitative analysis of imaging data; however, the scale and complexity of such data sets pose unique challenges for processing and analysis. We have developed the Volumetric Tissue Exploration and Analysis (VTEA) software, a unique tool that integrates image processing, segmentation, and interactive cytometry analysis into a single framework on desktop computers. Supported by an extensible and open-source framework, VTEA's integrated pipeline now includes enhanced analytical tools, such as machine learning, data visualization, and neighborhood analyses, for hyperdimensional large-scale imaging data sets. These novel capabilities enable the analysis of mesoscale 2- and 3-dimensional multiplexed human kidney imaging data sets (such as co-detection by indexing and 3-dimensional confocal multiplexed fluorescence imaging). We demonstrate the utility of this approach in identifying cell subtypes in the kidney on the basis of labels, spatial association, and their microenvironment or neighborhood membership. VTEA provides an integrated and intuitive approach to decipher the cellular and spatial complexity of the human kidney and complements other transcriptomics and epigenetic efforts to define the landscape of kidney cell types.

Intravital Microscopy Reveals Unforeseen Biodistribution Within the Liver and Kidney Mechanistically Connected to the Clearance of a Bifunctional Antibody.

Bifunctional antibody (BfAb) therapeutics offer the potential for novel functionalities beyond those of the individual monospecific entities. However, combining these entities into a single molecule can have unpredictable effects, including changes in pharmacokinetics that limit the compound's therapeutic profile. A better understanding of how molecular modifications affect in vivo tissue interactions could help inform BfAb design. The present studies were predicated on the observation that a BfAb designed to have minimal off-target interactions cleared from the circulation twice as fast as the monoclonal antibody (mAb) from which it was derived. The present study leverages the spatial and temporal resolution of intravital microscopy (IVM) to identify cellular interactions that may explain the different pharmacokinetics of the two compounds. Disposition studies of mice demonstrated that radiolabeled compounds distributed similarly over the first 24 hours, except that BfAb accumulated approximately two- to -three times more than mAb in the liver. IVM studies of mice demonstrated that both distributed to endosomes of liver endothelia but with different kinetics. Whereas mAb accumulated rapidly within the first hour of administration, BfAb accumulated only modestly during the first hour but continued to accumulate over 24 hours, ultimately reaching levels similar to those of the mAb. Although neither compound was freely filtered by the mouse or rat kidney, BfAb, but not mAb, was found to accumulate over 24 hours in endosomes of proximal tubule cells. These studies demonstrate how IVM can be used as a tool in drug design, revealing unpredicted cellular interactions that are undetectable by conventional analyses. SIGNIFICANCE STATEMENT: Bifunctional antibodies offer novel therapeutic functionalities beyond those of the individual monospecific entities. However, combining these entities into a single molecule can have unpredictable effects, including undesirable changes in pharmacokinetics. Studies of the dynamic distribution of a bifunctional antibody and its parent monoclonal antibody presented here demonstrate how intravital microscopy can expand our understanding of the in vivo disposition of therapeutics, detecting off-target interactions that could not be detected by conventional pharmacokinetics approaches or predicted by conventional physicochemical analyses.

Epigenetic basis of diabetic vasculopathy.

Type 2 diabetes mellitus (T2DM) causes peripheral vascular disease because of which several blood-borne factors, including vital nutrients fail to reach the affected tissue. Tissue epigenome is sensitive to chronic hyperglycemia and is known to cause pathogenesis of micro- and macrovascular complications. These vascular complications of T2DM may perpetuate the onset of organ dysfunction. The burden of diabetes is primarily because of a wide range of complications of which nonhealing diabetic ulcers represent a major component. Thus, it is imperative that current research help recognize more effective methods for the diagnosis and management of early vascular injuries. This review addresses the significance of epigenetic processes such as DNA methylation and histone modifications in the evolution of macrovascular and microvascular complications of T2DM.

Integration of spatial and single-cell transcriptomics localizes epithelial cell-immune cross-talk in kidney injury.

Single-cell sequencing studies have characterized the transcriptomic signature of cell types within the kidney. However, the spatial distribution of acute kidney injury (AKI) is regional and affects cells heterogeneously. We first optimized coordination of spatial transcriptomics and single-nuclear sequencing data sets, mapping 30 dominant cell types to a human nephrectomy. The predicted cell-type spots corresponded with the underlying histopathology. To study the implications of AKI on transcript expression, we then characterized the spatial transcriptomic signature of 2 murine AKI models: ischemia/reperfusion injury (IRI) and cecal ligation puncture (CLP). Localized regions of reduced overall expression were associated with injury pathways. Using single-cell sequencing, we deconvoluted the signature of each spatial transcriptomic spot, identifying patterns of colocalization between immune and epithelial cells. Neutrophils infiltrated the renal medulla in the ischemia model. Atf3 was identified as a chemotactic factor in S3 proximal tubules. In the CLP model, infiltrating macrophages dominated the outer cortical signature, and Mdk was identified as a corresponding chemotactic factor. The regional distribution of these immune cells was validated with multiplexed CO-Detection by indEXing (CODEX) immunofluorescence. Spatial transcriptomic sequencing complemented single-cell sequencing by uncovering mechanisms driving immune cell infiltration and detection of relevant cell subpopulations.

The Indiana O'Brien Center for Advanced Renal Microscopic Analysis.

The Indiana O'Brien Center for Advanced Microscopic Analysis is a National Institutes of Health (NIH) P30-funded research center dedicated to the development and dissemination of advanced methods of optical microscopy to support renal researchers throughout the world. The Indiana O'Brien Center was founded in 2002 as an NIH P-50 project with the original goal of helping researchers realize the potential of intravital multiphoton microscopy as a tool for understanding renal physiology and pathophysiology. The center has since expanded into the development and implementation of large-scale, high-content tissue cytometry. The advanced imaging capabilities of the center are made available to renal researchers worldwide via collaborations and a unique fellowship program. Center outreach is accomplished through an enrichment core that oversees a seminar series, an informational website, and a biennial workshop featuring hands-on training from members of the Indiana O'Brien Center and imaging experts from around the world.

Molecular characterization of the human kidney interstitium in health and disease.

The gene expression signature of the human kidney interstitium is incompletely understood. The cortical interstitium (excluding tubules, glomeruli, and vessels) in reference nephrectomies (N = 9) and diabetic kidney biopsy specimens (N = 6) was laser microdissected (LMD) and sequenced. Samples underwent RNA sequencing. Gene signatures were deconvolved using single nuclear RNA sequencing (snRNAseq) data derived from overlapping specimens. Interstitial LMD transcriptomics uncovered previously unidentified markers including KISS1, validated with in situ hybridization. LMD transcriptomics and snRNAseq revealed strong correlation of gene expression within corresponding kidney regions. Relevant enriched interstitial pathways included G-protein coupled receptor. binding and collagen biosynthesis. The diabetic interstitium was enriched for extracellular matrix organization and small-molecule catabolism. Cell type markers with unchanged expression (NOTCH3, EGFR, and HEG1) and those down-regulated in diabetic nephropathy (MYH11, LUM, and CCDC3) were identified. LMD transcriptomics complements snRNAseq; together, they facilitate mapping of interstitial marker genes to aid interpretation of pathophysiology in precision medicine studies.

Clinical, histopathologic and molecular features of idiopathic and diabetic nodular mesangial sclerosis in humans.

BACKGROUND: Idiopathic nodular mesangial sclerosis, also called idiopathic nodular glomerulosclerosis (ING), is a rare clinical entity with an unclear pathogenesis. The hallmark of this disease is the presence of nodular mesangial sclerosis on histology without clinical evidence of diabetes mellitus or other predisposing diagnoses. To achieve insights into its pathogenesis, we queried the clinical, histopathologic and transcriptomic features of ING and nodular diabetic nephropathy (DN). METHODS: All renal biopsy reports accessioned at Indiana University Health from 2001 to 2016 were reviewed to identify 48 ING cases. Clinical and histopathologic features were compared between individuals with ING and DN (n = 751). Glomeruli of ING (n = 5), DN (n = 18) and reference (REF) nephrectomy (n = 9) samples were isolated by laser microdissection and RNA was sequenced. Immunohistochemistry of proline-rich 36 (PRR36) protein was performed. RESULTS: ING subjects were frequently hypertensive (95.8%) with a smoking history (66.7%). ING subjects were older, had lower proteinuria and had less hyaline arteriolosclerosis than DN subjects. Butanoate metabolism was an enriched pathway in ING samples compared with either REF or DN samples. The top differentially expressed gene, PRR36, had increased expression in glomeruli 248-fold [false discovery rate (FDR) P = 5.93 × 10-6] compared with the REF and increased 109-fold (FDR P = 1.85 × 10-6) compared with DN samples. Immunohistochemistry revealed a reduced proportion of cells with perinuclear reaction in ING samples as compared to DN. CONCLUSIONS: Despite similar clinical and histopathologic characteristics in ING and DN, the uncovered transcriptomic signature suggests that ING has distinct molecular features from nodular DN. Further study is warranted to understand these relationships.

Large-scale, three-dimensional tissue cytometry of the human kidney: a complete and accessible pipeline.

The advent of personalized medicine has driven the development of novel approaches for obtaining detailed cellular and molecular information from clinical tissue samples. Tissue cytometry is a promising new technique that can be used to enumerate and characterize each cell in a tissue and, unlike flow cytometry and other single-cell techniques, does so in the context of the intact tissue, preserving spatial information that is frequently crucial to understanding a cell's physiology, function, and behavior. However, the wide-scale adoption of tissue cytometry as a research tool has been limited by the fact that published examples utilize specialized techniques that are beyond the capabilities of most laboratories. Here we describe a complete and accessible pipeline, including methods of sample preparation, microscopy, image analysis, and data analysis for large-scale three-dimensional tissue cytometry of human kidney tissues. In this workflow, multiphoton microscopy of unlabeled tissue is first conducted to collect autofluorescence and second-harmonic images. The tissue is then labeled with eight fluorescent probes, and imaged using spectral confocal microscopy. The raw 16-channel images are spectrally deconvolved into 8-channel images, and analyzed using the Volumetric Tissue Exploration and Analysis (VTEA) software developed by our group. We applied this workflow to analyze millimeter-scale tissue samples obtained from human nephrectomies and from renal biopsies from individuals diagnosed with diabetic nephropathy, generating a quantitative census of tens of thousands of cells in each. Such analyses can provide useful insights that can be linked to the biology or pathology of kidney disease. The approach utilizes common laboratory techniques, is compatible with most commercially-available confocal microscope systems and all image and data analysis is conducted using the VTEA image analysis software, which is available as a plug-in for ImageJ.

Digital Image Analysis Tools Developed by the Indiana O'Brien Center.

The scale and complexity of images collected in biological microscopy have grown enormously over the past 30 years. The development and commercialization of multiphoton microscopy has promoted a renaissance of intravital microscopy, providing a window into cell biology in vivo. New methods of optical sectioning and tissue clearing now enable biologists to characterize entire organs at subcellular resolution. New methods of multiplexed imaging support simultaneous localization of forty or more probes at a time. Exploiting these exciting new techniques has increasingly required biomedical researchers to master procedures of image analysis that were once the specialized province of imaging experts. A primary goal of the Indiana O'Brien Center has been to develop robust and accessible image analysis tools for biomedical researchers. Here we describe biomedical image analysis software developed by the Indiana O'Brien Center over the past 25 years.

In Situ Classification of Cell Types in Human Kidney Tissue Using 3D Nuclear Staining.

To understand the physiology and pathology of disease, capturing the heterogeneity of cell types within their tissue environment is fundamental. In such an endeavor, the human kidney presents a formidable challenge because its complex organizational structure is tightly linked to key physiological functions. Advances in imaging-based cell classification may be limited by the need to incorporate specific markers that can link classification to function. Multiplex imaging can mitigate these limitations, but requires cumulative incorporation of markers, which may lead to tissue exhaustion. Furthermore, the application of such strategies in large scale 3-dimensional (3D) imaging is challenging. Here, we propose that 3D nuclear signatures from a DNA stain, DAPI, which could be incorporated in most experimental imaging, can be used for classifying cells in intact human kidney tissue. We developed an unsupervised approach that uses 3D tissue cytometry to generate a large training dataset of nuclei images (NephNuc), where each nucleus is associated with a cell type label. We then devised various supervised machine learning approaches for kidney cell classification and demonstrated that a deep learning approach outperforms classical machine learning or shape-based classifiers. Specifically, a custom 3D convolutional neural network (NephNet3D) trained on nuclei image volumes achieved a balanced accuracy of 80.26%. Importantly, integrating NephNet3D classification with tissue cytometry allowed in situ visualization of cell type classifications in kidney tissue. In conclusion, we present a tissue cytometry and deep learning approach for in situ classification of cell types in human kidney tissue using only a DNA stain. This methodology is generalizable to other tissues and has potential advantages on tissue economy and non-exhaustive classification of different cell types.

A multimodal and integrated approach to interrogate human kidney biopsies with rigor and reproducibility: guidelines from the Kidney Precision Medicine Project.

Comprehensive and spatially mapped molecular atlases of organs at a cellular level are a critical resource to gain insights into pathogenic mechanisms and personalized therapies for diseases. The Kidney Precision Medicine Project (KPMP) is an endeavor to generate three-dimensional (3-D) molecular atlases of healthy and diseased kidney biopsies by using multiple state-of-the-art omics and imaging technologies across several institutions. Obtaining rigorous and reproducible results from disparate methods and at different sites to interrogate biomolecules at a single-cell level or in 3-D space is a significant challenge that can be a futile exercise if not well controlled. We describe a "follow the tissue" pipeline for generating a reliable and authentic single-cell/region 3-D molecular atlas of human adult kidney. Our approach emphasizes quality assurance, quality control, validation, and harmonization across different omics and imaging technologies from sample procurement, processing, storage, shipping to data generation, analysis, and sharing. We established benchmarks for quality control, rigor, reproducibility, and feasibility across multiple technologies through a pilot experiment using common source tissue that was processed and analyzed at different institutions and different technologies. A peer review system was established to critically review quality control measures and the reproducibility of data generated by each technology before their being approved to interrogate clinical biopsy specimens. The process established economizes the use of valuable biopsy tissue for multiomics and imaging analysis with stringent quality control to ensure rigor and reproducibility of results and serves as a model for precision medicine projects across laboratories, institutions and consortia.

Sphere estimation network: three-dimensional nuclei detection of fluorescence microscopy images.

Purpose: Fluorescence microscopy visualizes three-dimensional subcellular structures in tissue with two-photon microscopy achieving deeper penetration into tissue. Nuclei detection, which is essential for analyzing tissue for clinical and research purposes, remains a challenging problem due to the spatial variability of nuclei. Recent advancements in deep learning techniques have enabled the analysis of fluorescence microscopy data to localize and segment nuclei. However, these localization or segmentation techniques would require additional steps to extract characteristics of nuclei. We develop a 3D convolutional neural network, called Sphere Estimation Network (SphEsNet), to extract characteristics of nuclei without any postprocessing steps. Approach: To simultaneously estimate the center locations of nuclei and their sizes, SphEsNet is composed of two branches to localize nuclei center coordinates and to estimate their radii. Synthetic microscopy volumes automatically generated using a spatially constrained cycle-consistent adversarial network are used for training the network because manually generating 3D real ground truth volumes would be extremely tedious. Results: Three SphEsNet models based on the size of nuclei were trained and tested on five real fluorescence microscopy data sets from rat kidney and mouse intestine. Our method can successfully detect nuclei in multiple locations with various sizes. In addition, our method was compared with other techniques and outperformed them based on object-level precision, recall, and F 1 score. Our model achieved 89.90% for F 1 score. Conclusions: SphEsNet can simultaneously localize nuclei and estimate their size without additional steps. SphEsNet can be potentially used to extract more information from nuclei in fluorescence microscopy images.

Application of Laser Microdissection to Uncover Regional Transcriptomics in Human Kidney Tissue.

Gene expression analysis of human kidney tissue is an important tool to understand homeostasis and disease pathophysiology. Increasing the resolution and depth of this technology and extending it to the level of cells within the tissue is needed. Although the use of single nuclear and single cell RNA sequencing has become widespread, the expression signatures of cells obtained from tissue dissociation do not maintain spatial context. Laser microdissection (LMD) based on specific fluorescent markers would allow the isolation of specific structures and cell groups of interest with known localization, thereby enabling the acquisition of spatially-anchored transcriptomic signatures in kidney tissue. We have optimized an LMD methodology, guided by a rapid fluorescence-based stain, to isolate five distinct compartments within the human kidney and conduct subsequent RNA sequencing from valuable human kidney tissue specimens. We also present quality control parameters to enable the assessment of adequacy of the collected specimens. The workflow outlined in this manuscript shows the feasibility of this approach to isolate sub-segmental transcriptomic signatures with high confidence. The methodological approach presented here may also be applied to other tissue types with substitution of relevant antibody markers.

Mitochondrial depolarization and repolarization in the early stages of acetaminophen hepatotoxicity in mice.

Mitochondrial injury and depolarization are primary events in acetaminophen hepatotoxicity. Previous studies have shown that restoration of mitochondrial function in surviving hepatocytes, which is critical to recovery, is at least partially accomplished via biogenesis of new mitochondria. However, other studies indicate that mitochondria also have the potential to spontaneously repolarize. Although repolarization was previously observed only at a sub-hepatotoxic dose of acetaminophen, we postulated that mitochondrial repolarization in hepatocytes outside the centrilobular regions of necrosis might contribute to recovery of mitochondrial function following acetaminophen-induced injury. Our studies utilized longitudinal intravital microscopy of millimeter-scale regions of the mouse liver to characterize the spatio-temporal relationship between mitochondrial polarization and necrosis early in acetaminophen-induced liver injury. Treatment of male C57BL/6J mice with a single intraperitoneal 250 mg/kg dose of acetaminophen resulted in hepatotoxicity that was apparent histologically within 2 h of treatment, leading to 20 and 60-fold increases in serum aspartate aminotransferase and alanine aminotransferase, respectively, within 6 h. Intravital microscopy of the livers of mice injected with rhodamine123, TexasRed-dextran, propidium iodide and Hoechst 33342 detected centrilobular foci of necrosis within extended regions of mitochondrial depolarization within 2 h of acetaminophen treatment. Although regions of necrosis were more apparent 6 h after acetaminophen treatment, the vast majority of hepatocytes with depolarized mitochondria did not progress to necrosis, but rather recovered mitochondrial polarization within 6 h. Recovery of mitochondrial function following acetaminophen hepatotoxicity thus involves not only biogenesis of new mitochondria, but also repolarization of existing mitochondria. These studies also revealed a spatial distribution of necrosis and mitochondrial depolarization whose single-cell granularity is inconsistent with the hypothesis that communication between neighboring cells plays an important role in the propagation of necrosis during the early stages of APAP hepatotoxicity. Small islands of healthy, intact cells were frequently found surrounded by necrotic cells, and small islands of necrotic cells were frequently found surrounded by healthy, intact cells. Time-series studies demonstrated that these "islands", consisting in some cases of single cells, are persistent; over a period of hours, injury does not spread from individual necrotic cells to their neighbors.

PIE-FLIM Measurements of Two Different FRET-Based Biosensor Activities in the Same Living Cells.

We report the use of pulsed interleaved excitation (PIE)-fluorescence lifetime imaging microscopy (FLIM) to measure the activities of two different biosensor probes simultaneously in single living cells. Many genetically encoded biosensors rely on the measurement of Förster resonance energy transfer (FRET) to detect changes in biosensor conformation that accompany the targeted cell signaling event. One of the most robust ways of quantifying FRET is to measure changes in the fluorescence lifetime of the donor fluorophore using FLIM. The study of complex signaling networks in living cells demands the ability to track more than one of these cellular events at the same time. Here, we demonstrate how PIE-FLIM can separate and quantify the signals from different FRET-based biosensors to simultaneously measure changes in the activity of two cell signaling pathways in the same living cells in tissues. The imaging system described here uses selectable laser wavelengths and synchronized detection gating that can be tailored and optimized for each FRET pair. Proof-of-principle studies showing simultaneous measurement of cytosolic calcium and protein kinase A activity are shown, but the PIE-FLIM approach is broadly applicable to other signaling pathways.