Photodynamic therapy (PDT) is an established treatment which uses a photosensitiser drug and light source to destroy superficial lesions. This therapy is not applicable to deep-seated tumours due to limited light penetration. Recently, it has been found that replacing light in PDT with X-rays (thus named radiodynamic therapy (RDT)) can stimulate nano formulated photosensitiser drugs including Verteporfin and generate reactive oxygen species to kill the cancer cells. Herein, we investigated aspects of cellular metabolic processes after RDT in comparison with PDT and radiotherapy using label-free hyperspectral autofluorescence microscopy and image analysis. Biochemical signatures of metabolically relevant fluorophores (NAD(P)H, flavins, and optical-redox-ratio) were identified by developing a semi-unsupervised unmixing method combining supervised and unsupervised unmixing in a novel way.
Reactive oxygen species (ROS) play an essential role as cellular messengers, functioning as redox regulators under normal physiological conditions. However, the excessive production of ROS in cells and organs due to disorders such as diabetes mellitus, inflammation, cardiovascular, cancer, and neurodegenerative disease leads to oxidative stress, which may be an early indication of progressive pathology . Currently, ROS -specific indicators which requires labelling are used for ROS quantification. Therefore, a label-free imaging technique is desirable for assessing the level of ROS. In this work, we introduced a novel imaging method to quantitatively identify ROS in cells and tissues named autofluorescence multispectral imaging (AFMI). This technique involved a custom-built spectral imaging system with 18 spectral channels with distinctive excitation and emission wavelength spanning specific excitation (365 nm-495 nm) and emission (420 nm-700 nm) wavelength ranges. Such a system can extract rich spectral information related to the ROS present in cells and tissue. We correlated the spectral information obtained from AFMI to the level of ROS acquired from CellROX imaging, which served the reference ROS value in this study. Further, our analyses were repeated for UV sensitive applications where an excitation spectrum less than 400nm was avoided. Quantitative analysis of the spectral images showed a strong multispectral signature correlating the spectral variable with the ROS level in the cells and tissue. Our results showed that ROS levels can be determined non-invasively using AFMI, which potentially can be translated to future clinical applications where ROS are known to correlate with progressive disease.
Pain is currently assessed using subjective measurements, often not aligning with clinical symptoms. Therefore, objective pain level assessments, using minimally-invasive and molecular methods, are needed to assess disease activity and response to treatment in osteoarthritis and rheumatoid arthritis. We report sophisticated quantitative biochemical “signatures” from the label-free hyperspectral imaging (HSI) of cartilage tissue for the characterization of molecular composition, structure and functional status. Further study on sinuvium tissue provides evidence that HSI could be used as a novel technique to delineate disease state. Additionally, HSI could be used to objectively separate individuals based on pain severity providing molecular correlates of pain.
Type 1 diabetes occurs when insulin secreting beta cells in pancreatic islets are destroyed leading to elevated glucose and ill health. Islet transplantation is an effective therapy, but islets are often damaged by the isolation process resulting in numerous, repeated transplants to achieve insulin independence. We have applied hyperspectral microscopy to damaged islets and have shown through the assessment of native cell autofluorescence we can detect heterogenous forms of damage (elevated ROS, inflammatory signalling and warm ischemia) in mouse islets. This approach has great potential to be translated clinically to minimise the burden of suboptimal islet transplantations.
Automated and unbiased methods of non-invasive cell monitoring able to deal with complex biological heterogeneity are fundamentally important for biological research and medical diagnostics. Label-free cell imaging provides information about endogenous autofluorescent metabolites, enzymes and cofactors in cells. However, extracting high content information from autofluorescence imaging has been hitherto impossible. Here, we developed a multispectral fluorescence imaging technique which allows precise quantification of the native fluorophores in cells and tissues. With that approach we are now able to non-invasively image the aspects of biomolecular composition of cells and tissues; where many of these fluorophores (NADH, flavins, cytochrome C) are relevant to metabolism. We will discuss label-free detection of reactive oxygen species (ROS) and the cell cycle. Cell cycle and metabolism have a tight, bidirectional relationship, with the ability of the cell to commit to growth depending on the availability of metabolites, and the molecular mechanisms of the cell-cycle being linked to the regulation of metabolic networks. Cells entering the cell cycle increase glycolysis as they go from G1-phase into S-phase, this results in accumulation of the NADH relative to FAD which is also fluorescent.
Moreover, metabolic dysregulation is common across the spectrum of diseases, this next-generation methodology is able to detect major health conditions including neurodegeneration and cancer. This work also reports on approaches for early diagnosis of motor neurone disease (MND) and localisation of cancer margins for ocular surface squamous neoplasia. Our optimal discrimination approach (extracted features for treatment monitoring in MND and melanoma) enables statistical hypothesis testing and intuitive visualisations where previously undetectable differences become clearly apparent.
Cytokines play critical roles in homeostatic control of health and they are integral for the creation and maintenance of a myriad of disease states. Their ultra-low concentration, often in the picomolar range, and extremely dynamic transient secretion process place stringent demands on cytokine quantification. We developed a nanoparticle-based strategy to detect trace cytokine secretion from individual, single live cells, for which we coined the term “OnCELISA”. Using a capture surface on the cell membrane and fluorescent magnetic nanoparticles as assay reporters, our universal OnCELISA assay achieved the sensitivity 0.1 pg mL-1, an over 10-fold enhancement, compared to state-of-the-art. The sensitive OnCELISA cell labelling made it possible to select and sort different cell types to determine highly cytokine - secreting cell subpopulations . The capture surfaces on cell membranes did not show noticeable effect on cell viability and their subsequent proliferation. The capability to specifically select such highly cytokine-secreting cells and purify their populations is pivotal for their use in multicellular pathologies such as atherosclerosis. Accordingly, we used this new approach to label cytokine secretion from vascular tissues of apolipoprotein E-/- mice; an in vivo model of atherosclerosis. In response to lipopolysaccharide, we observed increased capture of cytokine using this model. With the capacity of monitoring multiple cytokine secretions (IL-6 and IL-1β)), our OnCELISA method is able to probe how the individual cells and tissues secrete cytokines as they respond in real time to the surrounding signals.
Pancreatic cancer is a highly lethal malignancy and a leading cause of cancer death in the world. Patients are either treated by surgery or by means of radiation therapy or by means of chemotherapy or by combining radiation and chemotherapy together depends upon the status of the pancreatic cancer. All these current treatments have limited efficacy as well as significant toxicity. Photodynamic therapy (PDT) is relatively free from side effects, but it is currently not applicable to pancreatic cancer due to its location in deep tissue. Herein, we developed a PDT system which uses poly (D, L-lactide-co-glycolide) (PLGA) polymeric nanoparticles incorporating a photosensitizer, verteporfin, to generate cytotoxic reactive oxygen species (ROS) by X-ray radiation of 6 MeV. The use of X-ray as the source of energy to trigger verteporfin avoids the limitation of poor penetration depth in conventional PDT. In addition, TAT peptide, a targeting moiety conjugated to the surface of the PLGA nanoconstructs facilitates the targeting of nanoparticles towards the nucleus of the cancer cells. The physiochemical characterisation as well as ROS generation capabilities of the nanoconstructs were studied under 6 MeV X-rays. We believe that the X-ray-induced ROS generation from Verteporfin molecules may be due to Cerenkov radiation (CR) and/or generation of energetic electron by the 6 MeV X-rays which then produce a cascade of ROSs. The cellular experiments carried out in Panc-1 cancer cell line suggest that an improved therapeutic effects can be achieved with the nanoconstructs triggered with X-ray radiation, compared with radiation alone.
Degradation of cartilage, occurring in osteoarthritis and other conditions leads to pain and reduced mobility. Current treatments beyond anti-inflammatories include intra-articular injections of hyaluronan or preparations based on adult mesenchymal stem cells (MSC), the latter shown to aid cartilage regeneration which requires the assessment of the cartilage, best on a molecular level and in a minimally invasive way. However, the conventional methods are invasive, destroying and can only provide a snapshot of a tissue structure and functional state on a sample-by-sample basis, while the continuous monitoring and high-throughput assays require low-invasive biopsy-free approach. As a first step to address this problem, in current work, we explored the potential of label-free multispectral imaging of endogenous tissue fluorescence to characterise the molecular composition, structure and functional status of ex vivo healthy bovine and osteoarthritic (OA) human knee articular cartilage followed by monitoring the effects of experimental treatment of OA cartilage performed ex vivo.
However, strong autofluorescence of collagens (especially from collagen type II, which is the structural backbone of collagen fibrils) from various cartilage layers presents a challenge, because this signal tends to overpower the fluorescence from chondrocytes. We have managed to use Robust Dependent Component Analysis (RoDECA) to observe the detailed metabolic information with a proper account of intrinsic cellular heterogeneity, which signifies the sophisticated quantitative biochemical analysis. This work reports on the “signatures” of the healthy articular cartilage for superficial and transitional layer, define the “healthy range” of each fluorophore’s abundance and localization of chondrocytes non-invasively as well as identify the changes of the signatures in OA cartilage of real patients and observe the reaction of the OA cartilage on 2 types of experimental treatments.
Adipose-derived stem cells (ADSC) based therapies have the potential to treat cartilage disorders such as osteoarthritis in both animals and humans. The current opinion points to secretions from stem cells in the proximity of the diseased joints as key agents in these new regenerative treatments. In this work, biological insights are derived from native fluorescence by using hyperspectral imaging technique. This approach allows to noninvasively monitor the relative levels of individual biochemicals in the tissue, at a cellular level. In this work, we used hyperspectral imaging and unsupervised unmixing to characterize the effects of specific cytokine treatments on different cartilage layers. These layers are composed of various types of collagen, elastin as well as chondrocytes. Strong autofluorescence of the cartilage chip especially from collagen type II presents a significant challenge for the hyperspectral unmixing analysis because the background signal from the collagen tends to dominate the autofluorescence from the chondrocytes. The latter is used for therapy monitoring, and it allows to compare the merits of specific regenerative treatments of cartilage.
The unsupervised hyperspectral unmixing approach developed in this work, Robust Dependent Component Analysis (RoDECA) provides a robust and detailed biochemical information from the examined cells and tissues, with a proper account of intrinsic cellular heterogeneity. With appropriate hardware adjustment and software modification in this cartilage chip model study, it was possible to analyze the biochemical effects of the stem cell based treatments. Most importantly, collagen I and collagen II have been distinguished for the first time in a label- free manner, which gives a new way of observing the regenerative treatments of the articular cartilage. This method can be extended in the future to the analysis of optically thick tissue.
The main objective of our work was to design a light source which should be capable to collect and illuminate light of LEDs at the smaller aperture of cone (9mm) which could be either coupled with secondary optics of a microscope or utilized independently for hyperspectral studies.
Optimized performance of cone was assessed for different substrates (diffused glass silica, Alumina, Zerodur glass, acrylic plastic) and coating surfaces (white diffused, flat white paint, standard mirror) using a simulation software. The parameters optimized for truncated cone include slanting length and Top Major R (Larger diameter of cone) which were also varied from 10 to 350 mm and 10 to 80 mm respectively. In order to see affect of LED positions on cone efficiency, the positions of LED were varied from central axis to off-axis. Similarly, interLED distance was varied from 2 mm to 6 mm to reckon its effect on the performance of cone.
The optimized Slant length (80 mm) and Top Major R (50 mm) were determined for substrates (glass zerodur or acrylic plastic) and coating surface (standard mirror). The output profile of truncated source was found non uniform, which is a typical presentation of non imaging optics problem. The maximum efficiency of cone has been found for LED at the centre and it was found decreasing as LED moves away from the central axis. Moreover, shorter the interLED distance, better is the performance of cone.
The primary optics of cone shaped light source is capable to lit visible and UV LEDs in practical design. The optimum parameters obtained through simulations could be implemented in the fabrication procedure if the reflectance of source would have been maintained upto finish level of a standard mirror.
Fluorescence-based bio-imaging methods have been extensively used to identify molecular changes occurring in biological samples in various pathological adaptations. Auto-fluorescence generated by endogenous fluorescent molecules within these samples can interfere with signal to background noise making positive antibody based fluorescent staining difficult to resolve. Hyperspectral imaging uses spectral and spatial imaging information for target detection and classification, and can be used to resolve changes in endogenous fluorescent molecules such as flavins, bound and free NADH and retinoids that are involved in cell metabolism. Hyperspectral auto-fluorescence imaging of spinal cord slices was used in this study to detect metabolic differences within pain processing regions of non-pain versus sciatic chronic constriction injury (CCI) animals, an established animal model of peripheral neuropathy. By using an endogenous source of contrast, subtle metabolic variations were detected between tissue samples, making it possible to distinguish between animals from non-injured and injured groups. Tissue maps of native fluorophores, flavins, bound and free NADH and retinoids unveiled subtle metabolic signatures and helped uncover significant tissue regions with compromised mitochondrial function. Taken together, our results demonstrate that hyperspectral imaging provides a new non-invasive method to investigate central changes of peripheral neuropathic injury and other neurodegenerative disease models, and paves the way for novel cellular characterisation in health, disease and during treatment, with proper account of intrinsic cellular heterogeneity.
To examine the process of endothelial cell aging we utilised hyperspectral imaging to collect broad autofluorescence emission at the individual cellular level and mathematically isolate the characteristic spectra of nicotinamide and flavin adenine dinucleotides (NADH and FAD, respectively). Quantitative analysis of this data provides the basis for a non-destructive spatial imaging method for cells and tissue.
FAD and NADH are important factors in cellular metabolism and have been shown to be involved with the redox state of the cell; with the ratio between the two providing the basis for an ‘optical redox ratio’.
Automated and unbiased methods of non-invasive cell monitoring able to deal with complex biological heterogeneity are fundamentally important for biology and medicine. Label-free cell imaging provides information about endogenous fluorescent metabolites, enzymes and cofactors in cells. However extracting high content information from imaging of native fluorescence has been hitherto impossible. Here, we quantitatively characterise cell populations in different tissue types, live or fixed, by using novel image processing and a simple multispectral upgrade of a wide-field fluorescence microscope. Multispectral intrinsic fluorescence imaging was applied to patient olfactory neurosphere-derived cells, cell model of a human metabolic disease MELAS (mitochondrial myopathy, encephalomyopathy, lactic acidosis, stroke-like syndrome). By using an endogenous source of contrast, subtle metabolic variations have been detected between living cells in their full morphological context which made it possible to distinguish healthy from diseased cells before and after therapy. Cellular maps of native fluorophores, flavins, bound and free NADH and retinoids unveiled subtle metabolic signatures and helped uncover significant cell subpopulations, in particular a subpopulation with compromised mitochondrial function. The versatility of our method is further illustrated by detecting genetic mutations in cancer, non-invasive monitoring of CD90 expression, label-free tracking of stem cell differentiation, identifying stem cell subpopulations with varying functional characteristics, tissue diagnostics in diabetes, and assessing the condition of preimplantation embryos. Our optimal discrimination approach enables statistical hypothesis testing and intuitive visualisations where previously undetectable differences become clearly apparent.
Extracting biochemical information from tissue autofluorescence is a promising approach to non-invasively monitor disease treatments at a cellular level, without using any external biomarkers. Our recently developed unsupervised hyperspectral unmixing by Dependent Component Analysis (DECA) provides robust and detailed metabolic information with proper account of intrinsic cellular heterogeneity. Moreover this method is compatible with established methods of fluorescent biomarker labelling.
Recently adipose-derived stem cell (ADSC) – based therapies have been introduced for treating different diseases in animals and humans. ADSC have been shown promise in regenerative treatments for osteoarthritis and other bone and joint disorders. One of the mechanism of their action is their anti-inflammatory effects within osteoarthritic joints which aid the regeneration of cartilage. These therapeutic effects are known to be driven by secretions of different cytokines from the ADSCs. We have been using the hyperspectral unmixing techniques to study in-vitro the effects of ADSC-derived cytokine-rich secretions with the cartilage chip in both human and bovine samples. The study of metabolic effects of different cytokine treatment on different cartilage layers makes it possible to compare the merits of those treatments for repairing cartilage.
Measurement of endogenous free and bound NAD(P)H relative concentrations in living cells is a useful method for monitoring aspects of cellular metabolism, because the NADH/NAD+ reduction-oxidation pair is crucial for electron transfer through the mitochondrial electron transport chain. Variations of free and bound NAD(P)H ratio are also implicated in cellular bioenergetic and biosynthetic metabolic changes accompanying cancer. This study uses two-photon fluorescence lifetime imaging microscopy (FLIM) to investigate metabolic changes in MCF10A premalignant breast cancer cells treated with a range of glycolysis inhibitors: namely, 2 deoxy-D-glucose, oxythiamine, lonidamine, and 4-(chloromethyl) benzoyl chloride, as well as the mitochondrial membrane uncoupling agent carbonyl cyanide m-chlorophenylhydrazone. Through systematic analysis of FLIM data from control and treated cancer cells, we observed that all glycolytic inhibitors apart from lonidamine had a slightly decreased metabolic rate and that the presence of serum in the culture medium generally marginally protected cells from the effect of inhibitors. Direct production of glycolytic L-lactate was also measured in both treated and control cells. The combination of these two techniques gave valuable insights into cell metabolism and indicated that FLIM was more sensitive than traditional biochemical methods, as it directly measured metabolic changes within cells as compared to quantification of lactate secreted by metabolically active cells.
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