Ageing and Polypharmacy in Mesenchymal Stromal Cells: Metabolic Impact Assessed by Hyperspectral Imaging of Autofluorescence.

The impact of age on mesenchymal stromal cell (MSC) characteristics has been well researched. However, increased age is concomitant with increased prevalence of polypharmacy. This adjustable factor may have further implications for the functionality of MSCs and the effectiveness of autologous MSC procedures. We applied hyperspectral microscopy of cell autofluorescence-a non-invasive imaging technique used to characterise cytometabolic heterogeneity-to identify changes in the autofluorescence signals of MSCs from (1) young mice, (2) old mice, (3) young mice randomised to receive polypharmacy (9-10 weeks of oral therapeutic doses of simvastatin, metoprolol, oxycodone, oxybutynin and citalopram), and (4) old mice randomised to receive polypharmacy. Principal Component Analysis and Logistic Regression Analysis were used to assess alterations in spectral and associated metabolic characteristics. Modelling demonstrated that cells from young mice receiving polypharmacy had less NAD(P)H and increased porphyrin relative to cells from old control mice, allowing for effective separation of the two groups (AUC of ROC curve > 0.94). Similarly, cells from old polypharmacy mice were accurately separated from those from young controls due to lower levels of NAD(P)H (p < 0.001) and higher porphyrin (p < 0.001), allowing for an extremely accurate logistic regression (AUC of ROC curve = 0.99). This polypharmacy regimen may have a more profound impact on MSCs than ageing, and can simultaneously reduce optical redox ratio (ORR) and increase porphyrin levels. This has implications for the use of autologous MSCs for older patients with chronic disease.

Label-Free Assessment of Key Biological Autofluorophores: Material Characteristics and Opportunities for Clinical Applications.

Autofluorophores are endogenous fluorescent compounds that naturally occur in the intra and extracellular spaces of all tissues and organs. Most have vital biological functions - like the metabolic cofactors NAD(P)H and FAD+, as well as the structural protein collagen. Others are considered to be waste products - like lipofuscin and advanced glycation end products - which accumulate with age and are associated with cellular dysfunction. Due to their natural fluorescence, these materials have great utility for enabling non-invasive, label-free assays with direct ties to biological function. Numerous technologies, with different advantages and drawbacks, are applied to their assessment, including fluorescence lifetime imaging microscopy, hyperspectral microscopy, and flow cytometry. Here, the applications of label-free autofluorophore assessment are reviewed for clinical and health-research applications, with specific attention to biomaterials, disease detection, surgical guidance, treatment monitoring, and tissue assessment - fields that greatly benefit from non-invasive methodologies capable of continuous, in vivo characterization.

Towards label-free non-invasive autofluorescence multispectral imaging for melanoma diagnosis.

This study focuses on the use of cellular autofluorescence which visualizes the cell metabolism by monitoring endogenous fluorophores including NAD(P)H and flavins. It explores the potential of multispectral imaging of native fluorophores in melanoma diagnostics using excitation wavelengths ranging from 340 nm to 510 nm and emission wavelengths above 391 nm. Cultured immortalized cells are utilized to compare the autofluorescent signatures of two melanoma cell lines to one fibroblast cell line. Feature analysis identifies the most significant and least correlated features for differentiating the cells. The investigation successfully applies this analysis to pre-processed, noise-removed images and original background-corrupted data. Furthermore, the applicability of distinguishing melanomas and healthy fibroblasts based on their autofluorescent characteristics is validated using the same evaluation technique on patient cells. Additionally, the study tentatively maps the detected features to underlying biological processes. This research demonstrates the potential of cellular autofluorescence as a promising tool for melanoma diagnostics.

Pancreatic Islet Viability Assessment Using Hyperspectral Imaging of Autofluorescence.

Islets prepared for transplantation into type 1 diabetes patients are exposed to compromising intrinsic and extrinsic factors that contribute to early graft failure, necessitating repeated islet infusions for clinical insulin independence. A lack of reliable pre-transplant measures to determine islet viability severely limits the success of islet transplantation and will limit future beta cell replacement strategies. We applied hyperspectral fluorescent microscopy to determine whether we could non-invasively detect islet damage induced by oxidative stress, hypoxia, cytokine injury, and warm ischaemia, and so predict transplant outcomes in a mouse model. In assessing islet spectral signals for NAD(P)H, flavins, collagen-I, and cytochrome-C in intact islets, we distinguished islets compromised by oxidative stress (ROS) (AUC = 1.00), hypoxia (AUC = 0.69), cytokine exposure (AUC = 0.94), and warm ischaemia (AUC = 0.94) compared to islets harvested from pristine anaesthetised heart-beating mouse donors. Significantly, with unsupervised assessment we defined an autofluorescent score for ischaemic islets that accurately predicted the restoration of glucose control in diabetic recipients following transplantation. Similar results were obtained for islet single cell suspensions, suggesting translational utility in the context of emerging beta cell replacement strategies. These data show that the pre-transplant hyperspectral imaging of islet autofluorescence has promise for predicting islet viability and transplant success.

Emerging clinical applications in oncology for non-invasive multi- and hyperspectral imaging of cell and tissue autofluorescence.

Hyperspectral and multispectral imaging of cell and tissue autofluorescence is an emerging technology in which fluorescence imaging is applied to biological materials across multiple spectral channels. This produces a stack of images where each matched pixel contains information about the sample's spectral properties at that location. This allows precise collection of molecularly specific data from a broad range of native fluorophores. Importantly, complex information, directly reflective of biological status, is collected without staining and tissues can be characterised in situ, without biopsy. For oncology, this can spare the collection of biopsies from sensitive regions and enable accurate tumour mapping. For in vivo tumour analysis, the greatest focus has been on oral cancer, whereas for ex vivo assessment head-and-neck cancers along with colon cancer have been the most studied, followed by oral and eye cancer. This review details the scope and progress of research undertaken towards clinical translation in oncology.

Automated pancreatic islet viability assessment for transplantation using bright-field deep morphological signature.

Islets transplanted for type-1 diabetes have their viability reduced by warm ischemia, dimethyloxalylglycine (DMOG; hypoxia model), oxidative stress and cytokine injury. This results in frequent transplant failures and the major burden of patients having to undergo multiple rounds of treatment for insulin independence. Presently there is no reliable measure to assess islet preparation viability prior to clinical transplantation. We investigated deep morphological signatures (DMS) for detecting the exposure of islets to viability compromising insults from brightfield images. Accuracies ranged from 98 % to 68 % for; ROS damage, pro-inflammatory cytokines, warm ischemia and DMOG. When islets were disaggregated to single cells to enable higher throughput data collection, good accuracy was still obtained (83-71 %). Encapsulation of islets reduced accuracy for cytokine exposure, but it was still high (78 %). Unsupervised modelling of the DMS for islet preparations transplanted into a syngeneic mouse model was able to predict whether or not they would restore glucose control with 100 % accuracy. Our strategy for constructing DMS' is effective for the assessment of islet pre-transplant viability. If translated into the clinic, standard equipment could be used to prospectively identify non-functional islet preparations unable to contribute to the restoration of glucose control and reduce the burden of unsuccessful treatments.

Clinical applications of non-invasive multi and hyperspectral imaging of cell and tissue autofluorescence beyond oncology.

Hyperspectral and multispectral imaging of cell and tissue autofluorescence employs fluorescence imaging, without exogenous fluorophores, across multiple excitation/emission combinations (spectral channels). This produces an image stack where each pixel (matched by location) contains unique information about the sample's spectral properties. Analysis of this data enables access to a rich, molecularly specific data set from a broad range of cell-native fluorophores (autofluorophores) directly reflective of biochemical status, without use of fixation or stains. This non-invasive, non-destructive technology has great potential to spare the collection of biopsies from sensitive regions. As both staining and biopsy may be impossible, or undesirable, depending on the context, this technology great diagnostic potential for clinical decision making. The main research focus has been on the identification of neoplastic tissues. However, advances have been made in diverse applications-including ophthalmology, cardiovascular health, neurology, infection, assisted reproduction technology and organ transplantation.

Pterygium and Ocular Surface Squamous Neoplasia: Optical Biopsy Using a Novel Autofluorescence Multispectral Imaging Technique.

In this study, differentiation of pterygium vs. ocular surface squamous neoplasia based on multispectral autofluorescence imaging technique was investigated. Fifty (N = 50) patients with histopathological diagnosis of pterygium (PTG) and/or ocular surface squamous neoplasia (OSSN) were recruited. Fixed unstained biopsy specimens were imaged by multispectral microscopy. Tissue autofluorescence images were obtained with a custom-built fluorescent microscope with 59 spectral channels, each with specific excitation and emission wavelength ranges, suitable for the most abundant tissue fluorophores such as elastin, flavins, porphyrin, and lipofuscin. Images were analyzed using a new classification framework called fused-classification, designed to minimize interpatient variability, as an established support vector machine learning method. Normal, PTG, and OSSN regions were automatically detected and delineated, with accuracy evaluated against expert assessment by a specialist in OSSN pathology. Signals from spectral channels yielding signals from elastin, flavins, porphyrin, and lipofuscin were significantly different between regions classified as normal, PTG, and OSSN (p < 0.01). Differential diagnosis of PTG/OSSN and normal tissue had accuracy, sensitivity, and specificity of 88 ± 6%, 84 ± 10% and 91 ± 6%, respectively. Our automated diagnostic method generated maps of the reasonably well circumscribed normal/PTG and OSSN interface. PTG and OSSN margins identified by our automated analysis were in close agreement with the margins found in the H&E sections. Such a map can be rapidly generated on a real time basis and potentially used for intraoperative assessment.

Autofluorescent imprint of chronic constriction nerve injury identified by deep learning.

Our understanding of chronic pain and the underlying molecular mechanisms remains limited due to a lack of tools to identify the complex phenomena responsible for exaggerated pain behaviours. Furthermore, currently there is no objective measure of pain with current assessment relying on patient self-scoring. Here, we applied a fully biologically unsupervised technique of hyperspectral autofluorescence imaging to identify a complex signature associated with chronic constriction nerve injury known to cause allodynia. The analysis was carried out using deep learning/artificial intelligence methods. The central element was a deep learning autoencoder we developed to condense the hyperspectral channel images into a four- colour image, such that spinal cord tissue based on nerve injury status could be differentiated from control tissue. This study provides the first validation of hyperspectral imaging as a tool to differentiate tissues from nerve injured vs non-injured mice. The auto-fluorescent signals associated with nerve injury were not diffuse throughout the tissue but formed specific microscopic size regions. Furthermore, we identified a unique fluorescent signal that could differentiate spinal cord tissue isolated from nerve injured male and female animals. The identification of a specific global autofluorescence fingerprint associated with nerve injury and resultant neuropathic pain opens up the exciting opportunity to develop a diagnostic tool for identifying novel contributors to pain in individuals.

The Autofluorescence Patterns of Acanthamoeba castellanii, Pseudomonas aeruginosa and Staphylococcus aureus: Effects of Antibiotics and Tetracaine.

Acanthamoeba Keratitis (AK) can lead to substantial vision loss and morbidity among contact lens wearers. Misdiagnosis or delayed diagnosis is a major factor contributing to poor outcomes of AK. This study aimed to assess the effect of two antibiotics and one anaesthetic drug used in the diagnosis and nonspecific management of keratitis on the autofluorescence patterns of Acanthamoeba and two common bacteria that may also cause keratitis. Acanthamoeba castellanii ATCC 30868, Pseudomonas aeruginosa ATCC 9027, and Staphylococcus aureus ATCC 6538 were grown then diluted in either PBS (bacteria) or » strength Ringer's solution (Acanthamoeba) to give final concentrations of 0.1 OD at 660 nm or 104 cells/mL. Cells were then treated with ciprofloxacin, tetracycline, tetracaine, or no treatment (naïve). Excitation-emission matrices (EEMs) were collected for each sample with excitation at 270-500 nm with increments in 5 nm steps and emission at 280-700 nm at 2 nm steps using a Fluoromax-4 spectrometer. The data were analysed using MATLAB software to produce smoothed color-coded images of the samples tested. Acanthamoeba exhibited a distinctive fluorescence pattern compared to bacteria. The addition of antibiotics and anaesthetic had variable effects on autofluorescence. Tetracaine altered the fluorescence of all three microorganisms, whereas tetracycline did not show any effect on the fluorescence. Ciprofloxacin produced changes to the fluorescence pattern for the bacteria, but not Acanthamoeba. Fluorescence spectroscopy was able to differentiate Acanthamoeba from P. aeruginosa and S. aureus in vitro. There is a need for further assessment of the fluorescence pattern for different strains of Acanthamoeba and bacteria. Additionally, analysis of the effects of anti-amoebic drugs on the fluorescence pattern of Acanthamoeba and bacteria would be prudent before in vivo testing of the fluorescence diagnostic approach in the animal models.

Machine learning reveals mesenchymal breast carcinoma cell adaptation in response to matrix stiffness.

Epithelial-mesenchymal transition (EMT) and its reverse process, mesenchymal-epithelial transition (MET), are believed to play key roles in facilitating the metastatic cascade. Metastatic lesions often exhibit a similar epithelial-like state to that of the primary tumour, in particular, by forming carcinoma cell clusters via E-cadherin-mediated junctional complexes. However, the factors enabling mesenchymal-like micrometastatic cells to resume growth and reacquire an epithelial phenotype in the target organ microenvironment remain elusive. In this study, we developed a workflow using image-based cell profiling and machine learning to examine morphological, contextual and molecular states of individual breast carcinoma cells (MDA-MB-231). MDA-MB-231 heterogeneous response to the host organ microenvironment was modelled by substrates with controllable stiffness varying from 0.2kPa (soft tissues) to 64kPa (bone tissues). We identified 3 distinct morphological cell types (morphs) varying from compact round-shaped to flattened irregular-shaped cells with lamellipodia, predominantly populating 2-kPa and >16kPa substrates, respectively. These observations were accompanied by significant changes in E-cadherin and vimentin expression. Furthermore, we demonstrate that the bone-mimicking substrate (64kPa) induced multicellular cluster formation accompanied by E-cadherin cell surface localisation. MDA-MB-231 cells responded to different substrate stiffness by morphological adaptation, changes in proliferation rate and cytoskeleton markers, and cluster formation on bone-mimicking substrate. Our results suggest that the stiffest microenvironment can induce MET.

Maternal Particulate Matter Exposure Impairs Lung Health and Is Associated with Mitochondrial Damage.

Relatively little is known about the transgenerational effects of chronic maternal exposure to low-level traffic-related air pollution (TRAP) on the offspring lung health, nor are the effects of removing such exposure before pregnancy. Female BALB/c mice were exposed to PM2.5 (PM2.5, 5 µg/day) for 6 weeks before mating and during gestation and lactation; in a subgroup, PM was removed when mating started to model mothers moving to cleaner areas during pregnancy to protect their unborn child (Pre-exposure). Lung pathology was characterised in both dams and offspring. A subcohort of female offspring was also exposed to ovalbumin to model allergic airways disease. PM2.5 and Pre-exposure dams exhibited airways hyper-responsiveness (AHR) with mucus hypersecretion, increased mitochondrial reactive oxygen species (ROS) and mitochondrial dysfunction in the lungs. Female offspring from PM2.5 and Pre-exposure dams displayed AHR with increased lung inflammation and mitochondrial ROS production, while males only displayed increased lung inflammation. After the ovalbumin challenge, AHR was increased in female offspring from PM2.5 dams compared with those from control dams. Using an in vitro model, the mitochondria-targeted antioxidant MitoQ reversed mitochondrial dysfunction by PM stimulation, suggesting that the lung pathology in offspring is driven by dysfunctional mitochondria. In conclusion, chronic exposure to low doses of PM2.5 exerted transgenerational impairment on lung health.

Radiodynamic Therapy Using TAT Peptide-Targeted Verteporfin-Encapsulated PLGA Nanoparticles.

Radiodynamic therapy (RDT) is a recent extension of conventional photodynamic therapy, in which visible/near infrared light irradiation is replaced by a well-tolerated dose of high-energy X-rays. This enables greater tissue penetration to allow non-invasive treatment of large, deep-seated tumors. We report here the design and testing of a drug delivery system for RDT that is intended to enhance intra- or peri-nuclear localization of the photosensitizer, leading to DNA damage and resulting clonogenic cell kill. This comprises a photosensitizer (Verteporfin, VP) incorporated into poly (lactic-co-glycolic acid) nanoparticles (PLGA NPs) that are surface-functionalized with a cell-penetrating HIV trans-activator of transcription (TAT) peptide. In addition to a series of physical and photophysical characterization studies, cytotoxicity tests in pancreatic (PANC-1) cancer cells in vitro under 4 Gy X-ray exposure from a clinical 6 MV linear accelerator (LINAC) showed that TAT targeting of the nanoparticles markedly enhances the effectiveness of RDT treatment, particularly when assessed by a clonogenic, i.e., DNA damage-mediated, cell kill.

Non-invasive assessment of exfoliated kidney cells extracted from urine using multispectral autofluorescence features.

Optimally preserved urinary exfoliated renal proximal tubule cells were assessed by multispectral imaging of cell autofluorescence. We demonstrated different multispectral autofluorescence signals in such cells extracted from the urine of patients with healthy or diseased kidneys. Using up to 10 features, we were able to differentiate cells from individuals with heathy kidneys and impaired renal function (indicated by estimated glomerular filtration rate (eGFR) values) with the receiver operating characteristic area under the curve (AUC) of 0.99. Using the same method, we were also able to discriminate such urine cells from patients with and without renal fibrosis on biopsy, where significant differences in multispectral autofluorescence signals (AUC = 0.90) were demonstrated between healthy and diseased patients (p < 0.05). These findings show that multispectral assessment of the cell autofluorescence in urine exfoliated proximal tubule kidney cells has the potential to be developed as a sensitive, non-invasive diagnostic method for CKD.

Non-invasive real-time imaging of reactive oxygen species (ROS) using auto-fluorescence multispectral imaging technique: A novel tool for redox biology.

Detecting reactive oxygen species (ROS) that play a critical role as redox modulators and signalling molecules in biological systems currently requires invasive methods such as ROS -specific indicators for imaging and quantification. We developed a non-invasive, real-time, label-free imaging technique for assessing the level of ROS in live cells and thawed cryopreserved tissues that is compatible with in-vivo imaging. The technique is based on autofluorescence multispectral imaging (AFMI) carried out in an adapted fluorescence microscope with an expanded number of spectral channels spanning specific excitation (365 nm-495 nm) and emission (420 nm-700 nm) wavelength ranges. We established a strong quantitative correlation between the spectral information obtained from AFMI and the level of ROS obtained from CellROX staining. The results were obtained in several cell types (HeLa, PANC1 and mesenchymal stem cells) and in live kidney tissue. Additioanly,two spectral regimes were considered: with and without UV excitation (wavelengths > 400 nm); the latter being suitable for UV-sensitive systems such as the eye. Data were analyzed by linear regression combined with an optimization method of swarm intelligence. This allowed the calibration of AFMI signals to the level of ROS with excellent correlation (R = 0.84, p = 0.00) in the entire spectral range and very good correlation (R = 0.78, p = 0.00) in the limited, UV-free spectral range. We also developed a strong classifier which allowed us to distinguish moderate and high levels of ROS in these two regimes (AUC = 0.91 in the entire spectral range and AUC = 0.78 for UV-free imaging). These results indicate that ROS in cells and tissues can be imaged non-invasively, which opens the way to future clinical applications in conditions where reactive oxygen species are known to contribute to progressive disease such as in ophthalmology, diabetes, kidney disease, cancer and neurodegenerative diseases.

PGRMC1 effects on metabolism, genomic mutation and CpG methylation imply crucial roles in animal biology and disease.

BACKGROUND: Progesterone receptor membrane component 1 (PGRMC1) is often elevated in cancers, and exists in alternative states of phosphorylation. A motif centered on PGRMC1 Y180 was evolutionarily acquired concurrently with the embryological gastrulation organizer that orchestrates vertebrate tissue differentiation. RESULTS: Here, we show that mutagenic manipulation of PGRMC1 phosphorylation alters cell metabolism, genomic stability, and CpG methylation. Each of several mutants elicited distinct patterns of genomic CpG methylation. Mutation of S57A/Y180/S181A led to increased net hypermethylation, reminiscent of embryonic stem cells. Pathways enrichment analysis suggested modulation of processes related to animal cell differentiation status and tissue identity, as well as cell cycle control and ATM/ATR DNA damage repair regulation. We detected different genomic mutation rates in culture. CONCLUSIONS: A companion manuscript shows that these cell states dramatically affect protein abundances, cell and mitochondrial morphology, and glycolytic metabolism. We propose that PGRMC1 phosphorylation status modulates cellular plasticity mechanisms relevant to early embryological tissue differentiation.

Autofluorescence excitation-emission matrices as a quantitative tool for the assessment of meat quality.

Commercially produced meat is currently graded by a complex and partly subjective multiparameter methodology; a quantitative method of grading, using small samples would be desirable. Here, we investigate the correlation between commercial grades of beef and spectral signatures of native fluorophores in such small samples. Beef samples of different commercial grades were characterized by fluorescence spectroscopy complemented by biochemical and histological assessment. The excitation-emission matrices of the specimens reveal five prominent native autofluorescence signatures in the excitation range from 250 to 350 nm, derived mainly from tryptophan and intramuscular fat. We found that these signatures reflect meat grade and can be used for its determination.

Non-destructive, label free identification of cell cycle phase in cancer cells by multispectral microscopy of autofluorescence.

BACKGROUND: Cell cycle analysis is important for cancer research. However, available methodologies have drawbacks including limited categorisation and reliance on fixation, staining or transformation. Multispectral analysis of endogenous cell autofluorescence has been shown to be sensitive to changes in cell status and could be applied to the discrimination of cell cycle without these steps. METHODS: Cells from the MIA-PaCa-2, PANC-1, and HeLa cell lines were plated on gridded dishes and imaged using a multispectral fluorescence microscope. They were then stained for proliferating cell nuclear antigen (PCNA) and DNA intensity as a reference standard for their cell cycle position (G1, S, G2, M). The multispectral data was split into training and testing datasets and models were generated to discriminate between G1, S, and G2 + M phase cells. A standard decision tree classification approach was taken, and a two-step system was generated for each line. RESULTS: Across cancer cell lines accuracy ranged from 68.3% (MIA-PaCa-2) to 73.3% (HeLa) for distinguishing G1 from S and G2 + M, and 69.0% (MIA-PaCa-2) to 78.0% (PANC1) for distinguishing S from G2 + M. Unmixing the multispectral data showed that the autofluorophores NADH, FAD, and PPIX had significant differences between phases. Similarly, the redox ratio and the ratio of protein bound to free NADH were significantly affected. CONCLUSIONS: These results demonstrate that multispectral microscopy could be used for the non-destructive, label free discrimination of cell cycle phase in cancer cells. They provide novel information on the mechanisms of cell-cycle progression and control, and have practical implications for oncology research.

A Nanoparticle-Based Affinity Sensor that Identifies and Selects Highly Cytokine-Secreting Cells.

We developed a universal method termed OnCELISA to detect cytokine secretion from individual cells by applying a capture technology on the cell membrane. OnCELISA uses fluorescent magnetic nanoparticles as assay reporters that enable detection on a single-cell level in microscopy and flow cytometry and fluorimetry in cell ensembles. This system is flexible and can be modified to detect different cytokines from a broad range of cytokine-secreting cells. Using OnCELISA we have been able to select and sort highly cytokine-secreting cells and identify cytokine-secreting expression profiles of different cell populations in vitro and ex vivo. We show that this system can be used for ultrasensitive monitoring of cytokines in the complex biological environment of atherosclerosis that contains multiple cell types. The ability to identify and select cell populations based on their cytokine expression characteristics is valuable in a host of applications that require the monitoring of disease progression.