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

AutoMitoNetwork: Software for analyzing mitochondrial networks in autofluorescence images to enable label-free cell classification

High-resolution mitochondria imaging in combination with image analysis tools have significantly advanced our understanding of cellular function in health and disease. However, most image analysis tools for mitochondrial studies have been designed to work with fluorescently labeled images only. Additionally, efforts to integrate features describing mitochondrial networks with machine learning techniques for the differentiation of cell types have been limited. Herein, we present AutoMitoNetwork software for image-based assessment of mitochondrial networks in label-free autofluorescence images using a range of interpretable morphological, intensity, and textural features. To demonstrate its utility, we characterized unstained mitochondrial networks in healthy retinal cells and in retinal cells exposed to two types of treatments: rotenone, which directly inhibited mitochondrial respiration and ATP production, and iodoacetic acid, which had a milder impact on mitochondrial networks via the inhibition of anaerobic glycolysis. For both cases, our multi-dimensional feature analysis combined with a support vector machine classifier distinguished between healthy cells and those treated with rotenone or iodoacetic acid. Subtle changes in morphological features were measured including increased fragmentation in the treated retinal cells, pointing to an association with metabolic mechanisms. AutoMitoNetwork opens new options for image-based machine learning in label-free imaging, diagnostics, and mitochondrial disease drug development.

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.

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.

Diagnostic and prognostic biomarkers for tubulointerstitial fibrosis

Renal fibrosis is the final common pathophysiological pathway in chronic kidney disease (CKD) regardless of the underlying cause of kidney injury. Tubulointerstitial fibrosis (TIF) is considered to be the key pathological predictor of CKD progression. Currently, the gold-standard tool to identify TIF is kidney biopsy, an invasive method that carries risks. Non-invasive diagnostics rely on an estimation of glomerular filtration rate and albuminuria to assess kidney function, but these fail to diagnose early CKD accurately or to predict progressive decline in kidney function. In this review, we summarize the current and emerging molecular biomarkers that have been studied in various clinical settings and in animal models of kidney disease and that are correlated with the degree of TIF. We examine the potential of these biomarkers to diagnose TIF non-invasively and to predict disease progression. We also examine the potential of new technologies and non-invasive diagnostic approaches in assessing TIF. Limitations of current and potential biomarkers are discussed and knowledge gaps identified.

Non-invasive assessment of oocyte developmental competence

Oocyte quality is a key factor influencing IVF success. The oocyte and surrounding cumulus cells, known collectively as the cumulus oocyte complex (COC), communicate bi-directionally and regulate each other's metabolic function to support oocyte growth and maturation. Many studies have attempted to associate metabolic markers with oocyte quality, including metabolites in follicular fluid or 'spent medium' following maturation, gene expression of cumulus cells and measuring oxygen consumption in medium surrounding COCs. However, these methods fail to provide spatial metabolic information on the separate oocyte and cumulus cell compartments. Optical imaging of the autofluorescent cofactors - reduced nicotinamide adenine dinucleotide (phosphate) [NAD(P)H] and flavin adenine dinucleotide (FAD) - has been put forward as an approach to generate spatially resolved measurements of metabolism within individual cells of the COC. The optical redox ratio (FAD/[NAD(P)H+FAD]), calculated from these cofactors, can act as an indicator of overall metabolic activity in the oocyte and cumulus cell compartments. Confocal microscopy, fluorescence lifetime imaging microscopy (FLIM) and hyperspectral microscopy may be used for this purpose. This review provides an overview of current optical imaging techniques that capture the inner biochemistry within cells of the COC and discusses the potential for such imaging to assess oocyte developmental competence.

Bioassay Guided Fractionation Protocol for Determining Novel Active Compounds in Selected Australian Flora

A large variety of unique and distinct flora of Australia have developed exceptional survival methods and phytochemicals and hence may provide a significant avenue for new drug discovery. This study proposes a bioassay guided fractionation protocol that maybe robust and efficient in screening plants with potential bioactive properties and isolating lead novel compounds. Hence, five native Australian plants were selected for this screening process, namely Pittosporum angustifolium (Gumbi gumbi), Terminalia ferdinandiana (Kakadu plum, seeds (KPS), and flesh (KPF)), Cupaniopsis anacardioides (Tuckeroo, seeds (TKS) and flesh (TKF)), Podocarpus elatus (Illawarra plum, seeds (IPS) and flesh (IPF)) and Pleiogynium timoriense (Burdekin plum, seeds (BPS) and flesh (BPF)). The methanolic extracts of the plants samples were analysed for Total phenolic content (TPC) and antioxidant capacity measure by FRAP. The highest values were found in the KPF which were 12,442 ± 1355 mg GAE/ 100 g TPC and 16,670 ± 2275 mg TXE/100 g antioxidant capacity. Extracts of GGL was deemed to be most potent with complete cell inhibition in HeLa and HT29, and about 95% inhibition in HuH7 cells. Comparative activity was also seen for KPS extract, where more than 80% cell inhibition occurred in all tested cell lines. Dose-dependent studies showed higher SI values (0.72-1.02) in KPS extracts than GGL (0.5-0.73). Microbial assays of the crude extracts were also performed against five bacterial strains commonly associated with causing food poisoning diseases were selected (Gram positive-Staphylococcus aureus and Gram negative-Escherichia coli, Salmonella typhi and Pseudomonas aeruginosa bacteria). KPF extracts were effective in suppressing microbial growth of all tested bacterial strains except for P. aeruginosa, while TKS and TKF were only slightly effective against S. aureus. Due to the potential of the GGL crude extract to completely inhibit the cells compared to KPS, it was further fractionated and tested against the cell lines. HPLC phenolic profiling of the crude extracts were performed, and numerous peak overlaps were evident in the fruit extracts. The KPF extracts demonstrated the strongest peaks which was coherent with the fact that it had the highest TPC and antioxidant capacity values. A high occurrence of t-ferulic acid in the GGL extracts was found which may explain the cytotoxic activity of GGL extracts. Peaks in KPS and KPF extracts were tentatively identified as gallic acid, protocatechuic acid, 4-hydroxybenzoic acid and syringic acid and possibly ellagic acid. HPLC time-based fractionation of the GGL extract (F1-F5) was performed and Dose dependent cytotoxic effects were determined. It was construed that F1, having the highest SI value for HeLa, HT29 and HuH7 (1.60, 1.41 and 1.67, respectively) would be promising for further fractionation and isolation process.

Exfoliated Kidney Cells from Urine for Early Diagnosis and Prognostication of CKD: The Way of the Future?

Chronic kidney disease (CKD) is a global health issue, affecting more than 10% of the worldwide population. The current approach for formal diagnosis and prognostication of CKD typically relies on non-invasive serum and urine biomarkers such as serum creatinine and albuminuria. However, histological evidence of tubulointerstitial fibrosis is the 'gold standard' marker of the likelihood of disease progression. The development of novel biomedical technologies to evaluate exfoliated kidney cells from urine for non-invasive diagnosis and prognostication of CKD presents opportunities to avoid kidney biopsy for the purpose of prognostication. Efforts to apply these technologies more widely in clinical practice are encouraged, given their potential as a cost-effective approach, and no risk of post-biopsy complications such as bleeding, pain and hospitalization. The identification of biomarkers in exfoliated kidney cells from urine via western blotting, enzyme-linked immunosorbent assay (ELISA), immunofluorescence techniques, measurement of cell and protein-specific messenger ribonucleic acid (mRNA)/micro-RNA and other techniques have been reported. Recent innovations such as multispectral autofluorescence imaging and single-cell RNA sequencing (scRNA-seq) have brought additional dimensions to the clinical application of exfoliated kidney cells from urine. In this review, we discuss the current evidence regarding the utility of exfoliated proximal tubule cells (PTC), podocytes, mesangial cells, extracellular vesicles and stem/progenitor cells as surrogate markers for the early diagnosis and prognostication of CKD. Future directions for development within this research area are also identified.