Application of direct stochastic optical reconstruction microscopy (dSTORM) to the histological analysis of human glomerular disease.

Electron microscopy (EM) following immunofluorescence (IF) imaging is a vital tool for the diagnosis of human glomerular diseases, but the implementation of EM is limited to specialised institutions and it is not available in many countries. Recent progress in fluorescence microscopy now enables conventional widefield fluorescence microscopes to be adapted at modest cost to provide resolution below 50 nm in biological specimens. We show that stochastically switched single-molecule localisation microscopy can be applied to clinical histological sections stained with standard IF techniques and that such super-resolved IF may provide an alternative means to resolve ultrastructure to aid the diagnosis of kidney disease where EM is not available. We have implemented the direct stochastic optical reconstruction microscopy technique with human kidney biopsy frozen sections stained with clinically approved immunofluorescent probes for the basal laminae and immunoglobulin G deposits. Using cases of membranous glomerulonephritis, thin basement membrane lesion, and lupus nephritis, we compare this approach to clinical EM images and demonstrate enhanced imaging compared to conventional IF microscopy. With minor modifications in established IF protocols of clinical frozen renal biopsies, we believe the cost-effective adaptation of conventional widefield microscopes can be widely implemented to provide super-resolved image information to aid diagnosis of human glomerular disease.

Quantitative in vivo optical tomography of cancer progression & vasculature development in adult zebrafish.

We describe a novel approach to study tumour progression and vasculature development in vivo via global 3-D fluorescence imaging of live non-pigmented adult zebrafish utilising angularly multiplexed optical projection tomography with compressive sensing (CS-OPT). This "mesoscopic" imaging method bridges a gap between established ~µm resolution 3-D fluorescence microscopy techniques and ~mm-resolved whole body planar imaging and diffuse tomography. Implementing angular multiplexing with CS-OPT, we demonstrate the in vivo global imaging of an inducible fluorescently labelled genetic model of liver cancer in adult non-pigmented zebrafish that also present fluorescently labelled vasculature. In this disease model, addition of a chemical inducer (doxycycline) drives expression of eGFP tagged oncogenic K-RASV12 in the liver of immune competent animals. We show that our novel in vivo global imaging methodology enables non-invasive quantitative imaging of the development of tumour and vasculature throughout the progression of the disease, which we have validated against established methods of pathology including immunohistochemistry. We have also demonstrated its potential for longitudinal imaging through a study of vascular development in the same zebrafish from early embryo to adulthood. We believe that this instrument, together with its associated analysis and data management tools, constitute a new platform for in vivo cancer studies and drug discovery in zebrafish disease models.

Rapid global fitting of large fluorescence lifetime imaging microscopy datasets.

Fluorescence lifetime imaging (FLIM) is widely applied to obtain quantitative information from fluorescence signals, particularly using Förster Resonant Energy Transfer (FRET) measurements to map, for example, protein-protein interactions. Extracting FRET efficiencies or population fractions typically entails fitting data to complex fluorescence decay models but such experiments are frequently photon constrained, particularly for live cell or in vivo imaging, and this leads to unacceptable errors when analysing data on a pixel-wise basis. Lifetimes and population fractions may, however, be more robustly extracted using global analysis to simultaneously fit the fluorescence decay data of all pixels in an image or dataset to a multi-exponential model under the assumption that the lifetime components are invariant across the image (dataset). This approach is often considered to be prohibitively slow and/or computationally expensive but we present here a computationally efficient global analysis algorithm for the analysis of time-correlated single photon counting (TCSPC) or time-gated FLIM data based on variable projection. It makes efficient use of both computer processor and memory resources, requiring less than a minute to analyse time series and multiwell plate datasets with hundreds of FLIM images on standard personal computers. This lifetime analysis takes account of repetitive excitation, including fluorescence photons excited by earlier pulses contributing to the fit, and is able to accommodate time-varying backgrounds and instrument response functions. We demonstrate that this global approach allows us to readily fit time-resolved fluorescence data to complex models including a four-exponential model of a FRET system, for which the FRET efficiencies of the two species of a bi-exponential donor are linked, and polarisation-resolved lifetime data, where a fluorescence intensity and bi-exponential anisotropy decay model is applied to the analysis of live cell homo-FRET data. A software package implementing this algorithm, FLIMfit, is available under an open source licence through the Open Microscopy Environment.

Multiphoton multispectral fluorescence lifetime tomography for the evaluation of basal cell carcinomas.

We present the first detailed study using multispectral multiphoton fluorescence lifetime imaging to differentiate basal cell carcinoma cells (BCCs) from normal keratinocytes. Images were acquired from 19 freshly excised BCCs and 27 samples of normal skin (in & ex vivo). Features from fluorescence lifetime images were used to discriminate BCCs with a sensitivity/specificity of 79%/93% respectively. A mosaic of BCC fluorescence lifetime images covering >1 mm(2) is also presented, demonstrating the potential for tumour margin delineation. Using 10,462 manually segmented cells from the image data, we quantify the cellular morphology and spectroscopic differences between BCCs and normal skin for the first time. Statistically significant increases were found in the fluorescence lifetimes of cells from BCCs in all spectral channels, ranging from 19.9% (425-515 nm spectral emission) to 39.8% (620-655 nm emission). A discriminant analysis based diagnostic algorithm allowed the fraction of cells classified as malignant to be calculated for each patient. This yielded a receiver operator characteristic area under the curve for the detection of BCC of 0.83. We have used both morphological and spectroscopic parameters to discriminate BCC from normal skin, and provide a comprehensive base for how this technique could be used for BCC assessment in clinical practice.

Quantification of cellular autofluorescence of human skin using multiphoton tomography and fluorescence lifetime imaging in two spectral detection channels.

We explore the diagnostic potential of imaging endogenous fluorophores using two photon microscopy and fluorescence lifetime imaging (FLIM) in human skin with two spectral detection channels. Freshly excised benign dysplastic nevi (DN) and malignant nodular Basal Cell Carcinomas (nBCCs) were excited at 760 nm. The resulting fluorescence signal was binned manually on a cell by cell basis. This improved the reliability of fitting using a double exponential decay model and allowed the fluorescence signatures from different cell populations within the tissue to be identified and studied. We also performed a direct comparison between different diagnostic groups. A statistically significant difference between the median mean fluorescence lifetime of 2.79 ns versus 2.52 ns (blue channel, 300-500 nm) and 2.08 ns versus 1.33 ns (green channel, 500-640 nm) was found between nBCCs and DN respectively, using the Mann-Whitney U test (p < 0.01). Further differences in the distribution of fluorescence lifetime parameters and inter-patient variability are also discussed.

Angiogenesis: an improved in vitro biological system and automated image-based workflow to aid identification and characterization of angiogenesis and angiogenic modulators.

Angiogenesis is a general term describing formation of new tube-like microvessel sprouts that are the size of capillary blood vessels. Angiogenesis is fundamental in key stages of embryonic development, organ formation, and wound repair and is also involved in the development and progression of a variety of pathological conditions, including cancer (tumor growth and metastasis), cardiovascular disease, diabetic retinopathy, age-related macular degeneration, atherosclerosis, and rheumatoid arthritis. Because of its diverse roles in key physiological and pathological processes, angiogenesis is an important area of medical research, with a considerable number of angiogenic and anti-angiogenic drugs currently undergoing clinical trials. Cost-effective and efficient screening for potential lead compounds is therefore of prime importance. However, screening methodologies vary in their physiological relevance depending on how faithfully critical aspects of angiogenesis are represented. Cell-based in vitro angiogenesis assays are important tools for screening, which in many cases rely on imaging microscopy to ascertain drug effects. Unfortunately, such screens can be hampered by poorly defined biology, slow image acquisition by manual or semiautomated hardware, and slow data analysis by non-dedicated software. This article describes use of a 96-well microplate in vitro angiogenesis screening system as part of an integrated workflow, comprising (1) setting up the biology in a three-dimensional physiologically relevant system, (2) acquiring a series of image slices ("stacks") using an automated z-stage instrument, (3) collapsing the image stack series into sets of two-dimensional images, (4) segmenting objects of interest, and (5) analyzing the segmentation patterns in order to obtain statistically relevant data.