Quantitative non-invasive cell characterisation and discrimination based on 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.

Viewing early life without labels: optical approaches for imaging the early embryo†

Embryo quality is an important determinant of successful implantation and a resultant live birth. Current clinical approaches for evaluating embryo quality rely on subjective morphology assessments or an invasive biopsy for genetic testing. However, both approaches can be inherently inaccurate and crucially, fail to improve the live birth rate following the transfer of in vitro produced embryos. Optical imaging offers a potential non-invasive and accurate avenue for assessing embryo viability. Recent advances in various label-free optical imaging approaches have garnered increased interest in the field of reproductive biology due to their ability to rapidly capture images at high resolution, delivering both morphological and molecular information. This burgeoning field holds immense potential for further development, with profound implications for clinical translation. Here, our review aims to: (1) describe the principles of various imaging systems, distinguishing between approaches that capture morphological and molecular information, (2) highlight the recent application of these technologies in the field of reproductive biology, and (3) assess their respective merits and limitations concerning the capacity to evaluate embryo quality. Additionally, the review summarizes challenges in the translation of optical imaging systems into routine clinical practice, providing recommendations for their future development. Finally, we identify suitable imaging approaches for interrogating the mechanisms underpinning successful embryo 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.

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.

Oocyte and cumulus cell cooperativity and metabolic plasticity under the direction of oocyte paracrine factors

Mammalian oocytes develop and mature in a mutually dependent relationship with surrounding cumulus cells. The oocyte actively regulates cumulus cell differentiation and function by secreting soluble paracrine oocyte-secreted factors (OSFs). We characterized the molecular mechanisms by which two model OSFs, cumulin and BMP15, regulate oocyte maturation and cumulus-oocyte cooperativity. Exposure to these OSFs during mouse oocyte maturation in vitro altered the proteomic and multispectral autofluorescence profiles of both the oocyte and cumulus cells. In oocytes, cumulin significantly upregulated proteins involved in nuclear function. In cumulus cells, both OSFs elicited marked upregulation of a variety of metabolic processes (mostly anabolic), including lipid, nucleotide, and carbohydrate metabolism, whereas mitochondrial metabolic processes were downregulated. The mitochondrial changes were validated by functional assays confirming altered mitochondrial morphology, respiration, and content while maintaining ATP homeostasis. Collectively, these data demonstrate that cumulin and BMP15 remodel cumulus cell metabolism, instructing them to upregulate their anabolic metabolic processes, while routine cellular functions are minimized in the oocyte during maturation, in preparation for ensuing embryonic development.NEW & NOTEWORTHY Oocyte-secreted factors (OSFs) promote oocyte and cumulus cell cooperativity by altering the molecular composition of both cell types. OSFs downregulate protein catabolic processes and upregulate processes associated with DNA binding, translation, and ribosome assembly in oocytes. In cumulus cells, OSFs alter mitochondrial number, morphology, and function, and enhance metabolic plasticity by upregulating anabolic pathways. Hence, the oocyte via OSFs, instructs cumulus cells to increase metabolic processes on its behalf, thereby subduing oocyte metabolism.

High-speed fluorescence excitation-scanning hyperspectral imaging microscopy using thin-film tunable filters

Hyperspectral imaging (HSI) technologies have enabled a range of experimental techniques and studies in the fluorescence microscopy field. Unfortunately, a drawback of many HSI microscope platforms is increased acquisition time required to collect images across many spectral bands, as well as signal loss due to the need to filter or disperse emitted fluorescence into many discrete bands. We have previously demonstrated that an alternative approach of scanning the fluorescence excitation spectrum can greatly improve system efficiency by decreasing light losses associated with emission filtering. Our initial system was configured using an array of thin-film tunable filters (TFTFs, VersaChrome, Semrock) mounted in a tiltable filter wheel (VF-5, Sutter) that required ~150-200 ms to switch between wavelengths. Here, we present a new configuration for high-speed switching of TFTFs to allow rapid time-lapse HSI microscopy. A TFTF array was mounted in a custom holder that was attached to a piezoelectric rotation mount (ThorLabs), allowing high-speed rotation. Switching between adjacent filters was achieved using the internal optics of a DG-4 lightsource (Sutter Instrument), including a pair of off-axis parabolic mirrors and galvanometers. Output light was coupled to a liquid lightguide and into an inverted widefield fluorescence microscope (TI-2, Nikon Instruments). Initial tests indicate that the HSI system provides a 15-20 nm bandwidth tunable excitation band and ~10-20 ms wavelength switch time, allowing for high-speed HSI imaging of dynamic cellular events. This work was supported by NIH P01HL066299, R01HL169522, NIH TL1TR003106, and NSF MRI1725937.

Morphological Signal Processing for Phenotype Recognition of Human Pluripotent Stem Cells Using Machine Learning Methods

Human pluripotent stem cells have the potential for unlimited proliferation and controlled differentiation into various somatic cells, making them a unique tool for regenerative and personalized medicine. Determining the best clone selection is a challenging problem in this field and requires new sensing instruments and methods able to automatically assess the state of a growing colony ('phenotype') and make decisions about its destiny. One possible solution for such label-free, non-invasive assessment is to make phase-contrast images and/or videos of growing stem cell colonies, process the morphological parameters ('morphological portrait', or signal), link this information to the colony phenotype, and initiate an automated protocol for the colony selection. As a step in implementing this strategy, we used machine learning methods to find an effective model for classifying the human pluripotent stem cell colonies of three lines according to their morphological phenotype ('good' or 'bad'), using morphological parameters from the previously published data as predictors. We found that the model using cellular morphological parameters as predictors and artificial neural networks as the classification method produced the best average accuracy of phenotype prediction (67%). When morphological parameters of colonies were used as predictors, logistic regression was the most effective classification method (75% average accuracy). Combining the morphological parameters of cells and colonies resulted in the most effective model, with a 99% average accuracy of phenotype prediction. Random forest was the most efficient classification method for the combined data. We applied feature selection methods and showed that different morphological parameters were important for phenotype recognition via either cellular or colonial parameters. Our results indicate a necessity for retaining both cellular and colonial morphological information for predicting the phenotype and provide an optimal choice for the machine learning method. The classification models reported in this study could be used as a basis for developing and/or improving automated solutions to control the quality of human pluripotent stem cells for medical purposes.

Use of high frequency electrorotation to identify cytoplasmic changes in cells non-disruptively

In this paper we demonstrate how the use of frequencies ranging from 50 kHz to 5 GHz in the analysis of cells by electrorotation can open the path to the identification of differences not detectable by conventional set-ups. Earlier works usually reported electrorotation devices operating below 20 MHz, limiting the response obtained to properties associated with the cell membrane. Those devices are thus unable to resolve the physiological properties in the cytoplasm. We used microwave-based technology to extend the frequency operation to 5 GHz. At high frequencies (from tens of MHz to GHz), the electromagnetic signal passes through the membrane and allows probing the cytoplasm. This enables several applications, such as cell classification, and viability analysis. Additionally, the use of conventional microfabrication techniques reduces the cost and complexity of analysis, compared to other non-invasive methods. We demonstrated the potential of this set-up by identifying two different populations of T-lymphocytes not distinguishable through visual assessment. We also assessed the effect of calcein on cell cytoplasmic properties and used it as a controlled experiment to demonstrate the possibility of this method to detect changes happening predominantly in the cytoplasm.

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.

Making and selecting the best embryo in the laboratory

Over the past 4 decades our ability to maintain a viable human embryo in vitro has improved dramatically, leading to higher implantation rates. This has led to a notable shift to single blastocyst transfer and the ensuing elimination of high order multiple gestations. Future improvements to embryo culture systems will not only come from new improved innovative media formulations (such as the inclusion of antioxidants), but plausibly by moving away from static culture to more dynamic perfusion-based systems now made a reality owing to the breakthroughs in three-dimensional printing technology and micro fabrication. Such an approach has already made it feasible to create high resolution devices for intracytoplasmic sperm injection, culture, and cryopreservation, paving the way not only for improvements in outcomes but also automation of assisted reproductive technology. Although improvements in culture systems can lead to further increases in pregnancy outcomes, the ability to quantitate biomarkers of embryo health and viability will reduce time to pregnancy and decrease pregnancy loss. Currently artificial intelligence is being used to assess embryo development through image analysis, but we predict its power will be realized through the creation of selection algorithms based on the integration of information related to metabolic functions, cell-free DNA, and morphokinetics, thereby using vast amounts of different data types obtained for each embryo to predict outcomes. All of this will not only make assisted reproductive technology more effective, but it will also make it more cost effective, thereby increasing patient access to infertility treatment worldwide.

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.

Volumetric live-cell autofluorescence imaging using Fourier light-field microscopy

This study introduces a rapid, volumetric live-cell imaging technique for visualizing autofluorescent sub-cellular structures and their dynamics by employing high-resolution Fourier light-field microscopy. We demonstrated this method by capturing lysosomal autofluorescence in fibroblasts and HeLa cells. Additionally, we conducted multicolor imaging to simultaneously observe lysosomal autofluorescence and fluorescently-labeled organelles such as lysosomes and mitochondria. We further analyzed the data to quantify the interactions between lysosomes and mitochondria. This research lays the foundation for future exploration of native cellular states and functions in three-dimensional environments, effectively reducing photodamage and eliminating the necessity for exogenous labels.

Progress in Nano-Biosensors for Non-Invasive Monitoring of Stem Cell Differentiation

Non-invasive, non-destructive, and label-free sensing techniques are required to monitor real-time stem cell differentiation. However, conventional analysis methods, such as immunocytochemistry, polymerase chain reaction, and Western blot, involve invasive processes and are complicated and time-consuming. Unlike traditional cellular sensing methods, electrochemical and optical sensing techniques allow non-invasive qualitative identification of cellular phenotypes and quantitative analysis of stem cell differentiation. In addition, various nano- and micromaterials with cell-friendly properties can greatly improve the performance of existing sensors. This review focuses on nano- and micromaterials that have been reported to improve sensing capabilities, including sensitivity and selectivity, of biosensors towards target analytes associated with specific stem cell differentiation. The information presented aims to motivate further research into nano-and micromaterials with advantageous properties for developing or improving existing nano-biosensors to achieve the practical evaluation of stem cell differentiation and efficient stem cell-based therapies.

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.

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.

Experimentally unsupervised deconvolution for light-sheet microscopy with propagation-invariant beams

Deconvolution is a challenging inverse problem, particularly in techniques that employ complex engineered point-spread functions, such as microscopy with propagation-invariant beams. Here, we present a deep-learning method for deconvolution that, in lieu of end-to-end training with ground truths, is trained using known physics of the imaging system. Specifically, we train a generative adversarial network with images generated with the known point-spread function of the system, and combine this with unpaired experimental data that preserve perceptual content. Our method rapidly and robustly deconvolves and super-resolves microscopy images, demonstrating a two-fold improvement in image contrast to conventional deconvolution methods. In contrast to common end-to-end networks that often require 1000-10,000s paired images, our method is experimentally unsupervised and can be trained solely on a few hundred regions of interest. We demonstrate its performance on light-sheet microscopy with propagation-invariant Airy beams in oocytes, preimplantation embryos and excised brain tissue, as well as illustrate its utility for Bessel-beam LSM. This method aims to democratise learned methods for deconvolution, as it does not require data acquisition outwith the conventional imaging protocol.

Reproductive biology research down under: highlights from the Australian and New Zealand Annual Meeting of the Society for Reproductive Biology, 2021

Against the backdrop of a global pandemic, the Society for Reproductive Biology (SRB) 2021 meeting reunited the Australian and New Zealand reproductive research community for the first time since 2019 and was the first virtual SRB meeting. Despite the recent global research disruptions, the conference revealed significant advancements in reproductive research, the importance of which span human health, agriculture, and conservation. A core theme was novel technologies, including the use of medical microrobots for therapeutic and sperm delivery, diagnostic hyperspectral imaging, and hydrogel condoms with potential beyond contraception. The importance of challenging the contraceptive status quo was further highlighted with innovations in gene therapies, non-hormonal female contraceptives, epigenetic semen analysis, and in applying evolutionary theory to suppress pest population reproduction. How best to support pregnancies, particularly in the context of global trends of increasing maternal age, was also discussed, with several promising therapies for improved outcomes in assisted reproductive technology, pre-eclampsia, and pre-term birth prevention. The unique insights gained via non-model species was another key focus and presented research emphasised the importance of studying diverse systems to understand fundamental aspects of reproductive biology and evolution. Finally, the meeting highlighted how to effectively translate reproductive research into policy and industry practice.

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.

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.

Multispectral autofluorescence characteristics of reproductive aging in old and young mouse oocytes

Increasing age has a major detrimental impact on female fertility, which, with an ageing population, has major sociological implications. This impact is primarily mediated through deteriorating quality of the oocyte. Deteriorating oocyte quality with biological age is the greatest rate-limiting factor to female fertility. Here we have used label-free, non-invasive multi-spectral imaging to identify unique autofluorescence profiles of oocytes from young and aged animals. Discriminant analysis demonstrated that young oocytes have a distinct autofluorescent profile which accurately distinguishes them from aged oocytes. We recently showed that treatment with the nicotinamide adenine dinucleotide (NAD+) precursor nicotinamide mononucleotide (NMN) restored oocyte quality and fertility in aged animals, and when our analysis was applied to oocytes from aged animals treated with NMN, 85% of these oocytes were classified as having the autofluorescent signature of young animals. Spectral unmixing using the Robust Dependent Component Analysis (RoDECA) algorithm demonstrated that NMN treatment altered the metabolic profile of oocytes, increasing free NAD(P)H, protein bound NAD(P)H, redox ratio and the ratio of bound to free NAD(P)H. The frequency of oocytes with simultaneously high NAD(P)H and flavin content was also significantly increased in mice treated with NMN. Young and Aged + NMN oocytes had a smoother spectral distribution, with the distribution of NAD(P)H in young oocytes specifically differing from that of aged oocytes. Identifying the multispectral profile of oocyte autofluorescence during aging could have utility as a non-invasive and sensitive measure of oocyte quality.

Excitation–emission matrix fluorescence spectroscopy for cell viability testing in UV-treated cell culture

Monitoring of cells viability is essential in a number of biomedical applications, including cell-based sensors, cell-based microsystems, and cell-based assays. The use of spectroscopic techniques for such purposes is especially advantageous since they are non-invasive, label-free, and non-destructive. However, such an approach must include chemometric analysis of the data to assess the information on cells viability. In the presented article we demonstrate, that excitation–emission matrix (EEM) fluorescence spectroscopy can be applied for reliable determination of cells viability due to the high correlation of EEM fluorescence data with the MTT test data. A375 cells (malignant melanoma) were exposed to UV radiation as a physical stress factor, resulting in a decrease of viability up to ca. 20%, confirmed by the standard MTT test. They were also characterized by means of EEM fluorescence spectroscopy coupled with unfolded partial least squares (UPLS) regression. Statistical evaluation revealed high accordance of the two methods of viability testing in terms of accuracy, precision, and correlation. The presented results are very promising for the development of spectroscopic soft sensors that can be applied for drug screening, biocompatibility testing, tissue engineering, and pharmacodynamic studies.

Excitation-emission matrix fluorescence spectroscopy can be applied for label-free and non-destructive determination of cells viability, which is promising methodology for drug screening, biocompatibility testing, or pharmacodynamic studies.

Non-invasive, label-free optical analysis to detect aneuploidy within the inner cell mass of the preimplantation embryo

STUDY QUESTION

Can label-free, non-invasive optical imaging by hyperspectral autofluorescence microscopy discern between euploid and aneuploid cells within the inner cell mass (ICM) of the mouse preimplantation embryo?

SUMMARY ANSWER

Hyperspectral autofluorescence microscopy enables discrimination between euploid and aneuploid ICM in mouse embryos.

WHAT IS KNOWN ALREADY

Euploid/aneuploid mosaicism affects up to 17.3% of human blastocyst embryos with trophectoderm biopsy or spent media currently utilized to diagnose aneuploidy and mosaicism in clinical in vitro fertilization. Based on their design, these approaches will fail to diagnose the presence or proportion of aneuploid cells within the foetal lineage ICM of some blastocyst embryos.

STUDY DESIGN, SIZE, DURATION

The impact of aneuploidy on cellular autofluorescence and metabolism of primary human fibroblast cells and mouse embryos was assessed using a fluorescence microscope adapted for imaging with multiple spectral channels (hyperspectral imaging). Primary human fibroblast cells with known ploidy were subjected to hyperspectral imaging to record native cell fluorescence (4-6 independent replicates, euploid n = 467; aneuploid n = 969). For mouse embryos, blastomeres from the eight-cell stage (five independent replicates: control n = 39; reversine n = 44) and chimeric blastocysts (eight independent replicates: control n = 34; reversine n = 34; 1:1 (control:reversine) n = 30 and 1:3 (control:reversine) n = 37) were utilized for hyperspectral imaging. The ICM from control and reversine-treated embryos were mechanically dissected and their karyotype confirmed by whole genome sequencing (n = 13 euploid and n = 9 aneuploid).

PARTICIPANTS/MATERIALS, SETTING, METHODS

Two models were employed: (i) primary human fibroblasts with known karyotype and (ii) a mouse model of embryo aneuploidy where mouse embryos were treated with reversine, a reversible spindle assembly checkpoint inhibitor, during the four- to eight-cell division. Individual blastomeres were dissociated from control and reversine-treated eight-cell embryos and either imaged directly or used to generate chimeric blastocysts with differing ratios of control:reversine-treated cells. Individual blastomeres and embryos were interrogated by hyperspectral imaging. Changes in cellular metabolism were determined by quantification of metabolic co-factors (inferred from their autofluorescence signature): NAD(P)H and flavins with the subsequent calculation of the optical redox ratio (ORR: flavins/[NAD(P)H + flavins]). Autofluorescence signals obtained from hyperspectral imaging were examined mathematically to extract features from each cell/blastomere/ICM. This was used to discriminate between different cell populations.

MAIN RESULTS AND THE ROLE OF CHANCE

An increase in the relative abundance of NAD(P)H and decrease in flavins led to a significant reduction in the ORR for aneuploid cells in primary human fibroblasts and reversine-treated mouse blastomeres (P < 0.05). Mathematical analysis of endogenous cell autofluorescence achieved separation between (i) euploid and aneuploid primary human fibroblast cells, (ii) control and reversine-treated mouse blastomeres cells, (iii) control and reversine-treated chimeric blastocysts, (iv) 1:1 and 1:3 chimeric blastocysts and (v) confirmed euploid and aneuploid ICM from mouse blastocysts. The accuracy of these separations was supported by receiver operating characteristic curves with areas under the curve of 0.97, 0.99, 0.87, 0.88 and 0.93, respectively. We believe that the role of chance is low as mathematical features separated euploid from aneuploid in both human fibroblasts and ICM of mouse blastocysts.

LARGE SCALE DATA

N/A.

LIMITATIONS, REASONS FOR CAUTION

Although we were able to discriminate between euploid and aneuploid ICM in mouse blastocysts, confirmation of this approach in human embryos is required. While we show this approach is safe in mouse, further validation is required in large animal species prior to implementation in a clinical setting.

WIDER IMPLICATIONS OF THE FINDINGS

We have developed an original, accurate and non-invasive optical approach to assess aneuploidy within the ICM of mouse embryos in the absence of fluorescent tags. Hyperspectral autofluorescence imaging was able to discriminate between euploid and aneuploid human fibroblast and mouse blastocysts (ICM). This approach may potentially lead to a new diagnostic for embryo analysis.

STUDY FUNDING/COMPETING INTEREST(S)

K.R.D. is supported by a Mid-Career Fellowship from the Hospital Research Foundation (C-MCF-58-2019). This study was funded by the Australian Research Council Centre of Excellence for Nanoscale Biophotonics (CE140100003) and the National Health and Medical Research Council (APP2003786). The authors declare that there is no conflict of interest.

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.

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.

NAD+ Repletion Rescues Female Fertility during Reproductive Aging

Reproductive aging in female mammals is an irreversible process associated with declining oocyte quality, which is the rate-limiting factor to fertility. Here, we show that this loss of oocyte quality with age accompanies declining levels of the prominent metabolic cofactor nicotinamide adenine dinucleotide (NAD⁺). Treatment with the NAD⁺ metabolic precursor nicotinamide mononucleotide (NMN) rejuvenates oocyte quality in aged animals, leading to restoration in fertility, and this can be recapitulated by transgenic overexpression of the NAD⁺-dependent deacylase SIRT2, though deletion of this enzyme does not impair oocyte quality. These benefits of NMN extend to the developing embryo, where supplementation reverses the adverse effect of maternal age on developmental milestones. These findings suggest that late-life restoration of NAD⁺ levels represents an opportunity to rescue female reproductive function in mammals.

Declining oocyte quality is considered an irreversible feature of aging and is rate limiting for human fertility. Bertoldo et al. show that reversing an age-dependent decline in NAD(P)H restores oocyte quality, embryo development, and functional fertility in aged mice. These findings may be relevant to reproductive medicine.

Optical imaging of cleavage stage bovine embryos using hyperspectral and confocal approaches reveals metabolic differences between on-time and fast-developing embryos

The assessment of embryo quality aims to enhance subsequent pregnancy and live birth outcomes. Metabolic analysis of embryos has immense potential in this regard. As a step towards this goal, here we assess the metabolism of bovine embryos using label-free optical imaging. We compared embryos defined as either on-time or fast-developing, as fast dividing embryos are more likely to develop to the blastocyst stage. Specifically, bovine embryos at 48 (Day 2) and 96 (Day 4) hours post fertilization were fixed and separated based on morphological assessment: on-time (Day 2: 2 cell; Day 4: 5-7 cell) or fast-developing (Day 2: 3-7 cell; Day 4: 8-16 cell). Embryos with different developmental rates on Day 2 and Day 4 were correlated with metabolic activity and DNA damage. Confocal microscopy was used to assess metabolic activity by quantification of cellular autofluorescence specific for the endogenous fluorophores NAD(P)H and FAD with a subsequent calculation of the optical redox ratio. Separately, hyperspectral microscopy was employed to assess a broader range of endogenous fluorophores. DNA damage was determined using γH2AX immunohistochemistry. Hyperspectral imaging showed significantly lower abundance of endogenous fluorophores in fast-developing compared to on-time embryos on Day 2, indicating a lower metabolic activity. On Day 4 of development there was no difference in the abundance of FAD between on-time and fast-developing embryos. There was, however, significantly higher levels of NAD(P)H in fast-developing embryos leading to a significantly lower optical redox ratio when compared to on-time embryos. Collectively, these results demonstrate that fast-developing embryos present a 'quiet' metabolic pattern on Day 2 and Day 4 of development, compared to on-time embryos. There was no difference in the level of DNA damage between on-time and fast-developing embryos on either day of development. To our knowledge, this is the first collective use of confocal and hyperspectral imaging in cleavage-stage bovine embryos in the absence of fluorescent tags.

Metabolic co-dependence of the oocyte and cumulus cells: essential role in determining oocyte developmental competence

BACKGROUND

Within the antral follicle, the oocyte is reliant on metabolic support from its surrounding somatic cells. Metabolism plays a critical role in oocyte developmental competence (oocyte quality). In the last decade, there has been significant progress in understanding the metabolism of the cumulus-oocyte complex (COC) during its final stages of growth and maturation in the follicle. Certain metabolic conditions (e.g. obesity) or ART (e.g. IVM) perturb COC metabolism, providing insights into metabolic regulation of oocyte quality.

OBJECTIVE AND RATIONALE

This review provides an update on the progress made in our understanding of COC metabolism, and the metabolic conditions that influence both meiotic and developmental competence of the oocyte.

SEARCH METHODS

The PubMed database was used to search for peer-reviewed original and review articles. Searches were performed adopting the main terms 'oocyte metabolism', 'cumulus cell metabolism', 'oocyte maturation', 'oocyte mitochondria', 'oocyte metabolism', 'oocyte developmental competence' and 'oocyte IVM'.

OUTCOMES

Metabolism is a major determinant of oocyte quality. Glucose is an essential requirement for both meiotic and cytoplasmic maturation of the COC. Glucose is the driver of cumulus cell metabolism and is essential for energy production, extracellular matrix formation and supply of pyruvate to the oocyte for ATP production. Mitochondria are the primary source of ATP production within the oocyte. Recent advances in real-time live cell imaging reveal dynamic fluctuations in ATP demand throughout oocyte maturation. Cumulus cells have been shown to play a central role in maintaining adequate oocyte ATP levels by providing metabolic support through gap junctional communication. New insights have highlighted the importance of oocyte lipid metabolism for oocyte oxidative phosphorylation for ATP production, meiotic progression and developmental competence. Within the last decade, several new strategies for improving the developmental competence of oocytes undergoing IVM have emerged, including modulation of cyclic nucleotides, the addition of precursors for the antioxidant glutathione or endogenous maturation mediators such as epidermal growth factor-like peptides and growth differentiation factor 9/bone morphogenetic protein 15. These IVM additives positively alter COC metabolic endpoints commonly associated with oocyte competence. There remain significant challenges in the study of COC metabolism. Owing to the paucity in non-invasive or in situ techniques to assess metabolism, most work to date has used in vitro or ex vivo models. Additionally, the difficulty of measuring oocyte and cumulus cell metabolism separately while still in a complex has led to the frequent use of denuded oocytes, the results from which should be interpreted with caution since the oocyte and cumulus cell compartments are metabolically interdependent, and oocytes do not naturally exist in a naked state until after fertilization. There are emerging tools, including live fluorescence imaging and photonics probes, which may provide ways to measure the dynamic nature of metabolism in a single oocyte, potentially while in situ.

WIDER IMPLICATIONS

There is an association between oocyte metabolism and oocyte developmental competence. Advancing our understanding of basic cellular and biochemical mechanisms regulating oocyte metabolism may identify new avenues to augment oocyte quality and assess developmental potential in assisted reproduction.

Reducing time to pregnancy and facilitating the birth of healthy children through functional analysis of embryo physiology†

An ever-increasing number of couples rely on assisted reproductive technologies (ART) in order to conceive a child. Although advances in embryo culture have led to increases in the success rates of clinical ART, it often takes more than one treatment cycle to conceive a child. Ensuring patients conceive as soon as possible with a healthy embryo is a priority for reproductive medicine. Currently, selection of embryos for transfer relies predominantly on the morphological assessment of the preimplantation embryo; however, morphology is not an absolute link to embryo physiology, nor the health of the resulting child. Non-invasive quantitation of individual embryo physiology, a key regulator of both embryo viability and health, could provide valuable information to assist in the selection of the most viable embryo for transfer, hence reducing the time to pregnancy. Further, according to the Barker Hypothesis, the environment to which a fetus is exposed to during gestation affects subsequent offspring health. If the environment of the preimplantation period is capable of affecting metabolism, which in turn will affect gene expression through the metaboloepigenetic link, then assessment of embryo metabolism should represent an indirect measure of future offspring health. Previously, the term viable embryo has been used in association with the potential of an embryo to establish a pregnancy. Here, we propose the term healthy embryo to reflect the capacity of that embryo to lead to a healthy child and adult.

Ageing human bone marrow mesenchymal stem cells have depleted NAD(P)H and distinct multispectral autofluorescence

Stem cell exhaustion plays a major role in the ageing of different tissues. Similarly, in vitro cell ageing during expansion prior to their use in regenerative medicine can severely compromise stem cell quality through progressive declines in differentiation and growth capacity. We utilized non-destructive multispectral assessment of native cell autofluorescence to investigate the metabolic mechanisms of in vitro mesenchymal stem cell (MSC) ageing in human bone marrow MSCs over serial passages (P2-P10). The spectral signals for NAD(P)H, flavins and protein-bound NAD(P)H were successfully isolated using Robust Dependent Component Analysis (RoDECA). NAD(P)H decreased over the course of hMSC ageing in absolute terms as well as relative to flavins (optical redox ratio). Relative changes in other fluorophore levels (flavins, protein-bound NAD(P)H) suggested that this reduction was due to nicotinamide adenine dinucleotide depletion rather than a metabolic shift from glycolysis to oxidative phosphorylation. Using multispectral features, which are determined without cell fixation or fluorescent labelling, we developed and externally validated a reliable, linear model which could accurately categorize the age of culture-expanded hMSCs. The largest shift in spectral characteristics occurs early in hMSC ageing. These findings demonstrate the feasibility of applying multispectral technology for the non-invasive monitoring of MSC health in vitro.

Dark-field hyperspectral imaging for label free detection of nano-bio-materials

Nanomaterials are playing an increasingly important role in cancer diagnosis and treatment. Nanoparticle (NP)-based technologies have been utilized for targeted drug delivery during chemotherapies, photodynamic therapy, and immunotherapy. Another active area of research is the toxicity studies of these nanomaterials to understand the cellular uptake and transport of these materials in cells, tissues, and environment. Traditional techniques such as transmission electron microscopy, and mass spectrometry to analyze NP-based cellular transport or toxicity effect are expensive, require extensive sample preparation, and are low-throughput. Dark-field hyperspectral imaging (DF-HSI), an integration of spectroscopy and microscopy/imaging, provides the ability to investigate cellular transport of these NPs and to quantify the distribution of them within bio-materials. DF-HSI also offers versatility in non-invasively monitoring microorganisms, single cell, and proteins. DF-HSI is a low-cost, label-free technique that is minimally invasive and is a viable choice for obtaining high-throughput quantitative molecular analyses. Multimodal imaging modalities such as Fourier transform infrared and Raman spectroscopy are also being integrated with HSI systems to enable chemical imaging of the samples. HSI technology is being applied in surgeries to obtain molecular information about the tissues in real-time. This article provides brief overview of fundamental principles of DF-HSI and its application for nanomaterials, protein-detection, single-cell analysis, microbiology, surgical procedures along with technical challenges and future integrative approach with other imaging and measurement modalities. This article is categorized under: Diagnostic Tools > in vitro Nanoparticle-Based Sensing Diagnostic Tools > in vivo Nanodiagnostics and Imaging Implantable Materials and Surgical Technologies > Nanoscale Tools and Techniques in Surgery.

Science convergence applied to psychoneuroimmunology: The future of measurement and imaging

The future of psychoneuroimmunology requires breakthrough technology discoveries. These next generation technologies need to address the unique challenges that are raised by imaging and measuring the activity of the neuroimmune interface in health and disease. The complexity of this challenge is centred around the multidimensionality of the neuroimmune system. These include novel challenges of capturing potent and rare biological signals over long times and vast anatomical distances. Here is a summary of the outcomes of the investments made by the Australian Research Council Centre of Excellence for Nanoscale BioPhotonics which was presented as part of the PNIRSAsia-Pacific symposium at the 2019 International Brain Research Organization.

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.

PGRMC1 phosphorylation affects cell shape, motility, glycolysis, mitochondrial form and function, and tumor growth

BACKGROUND

Progesterone Receptor Membrane Component 1 (PGRMC1) is expressed in many cancer cells, where it is associated with detrimental patient outcomes. It contains phosphorylated tyrosines which evolutionarily preceded deuterostome gastrulation and tissue differentiation mechanisms.

RESULTS

We demonstrate that manipulating PGRMC1 phosphorylation status in MIA PaCa-2 (MP) cells imposes broad pleiotropic effects. Relative to parental cells over-expressing hemagglutinin-tagged wild-type (WT) PGRMC1-HA, cells expressing a PGRMC1-HA-S57A/S181A double mutant (DM) exhibited reduced levels of proteins involved in energy metabolism and mitochondrial function, and altered glucose metabolism suggesting modulation of the Warburg effect. This was associated with increased PI3K/AKT activity, altered cell shape, actin cytoskeleton, motility, and mitochondrial properties. An S57A/Y180F/S181A triple mutant (TM) indicated the involvement of Y180 in PI3K/AKT activation. Mutation of Y180F strongly attenuated subcutaneous xenograft tumor growth in NOD-SCID gamma mice. Elsewhere we demonstrate altered metabolism, mutation incidence, and epigenetic status in these cells.

CONCLUSIONS

Altogether, these results indicate that mutational manipulation of PGRMC1 phosphorylation status exerts broad pleiotropic effects relevant to cancer and other cell biology.

Oocyte and embryo evaluation by AI and multi-spectral auto-fluorescence imaging: Livestock embryology needs to catch-up to clinical practice

A highly accurate 'non-invasive quantitative embryo assessment for pregnancy' (NQEAP) technique that determines embryo quality has been an elusive goal. If developed, NQEAP would transform the selection of embryos from both Multiple Ovulation and Embryo Transfer (MOET), and even more so, in vitro produced (IVP) embryos for livestock breeding. The area where this concept is already having impact is in the field of clinical embryology, where great strides have been taken in the application of morphokinetics and artificial intelligence (AI); while both are already in practice, rigorous and robust evidence of efficacy is still required. Even the translation of advances in the qualitative scoring of human IVF embryos have yet to be translated to the livestock IVP industry, which remains dependent on the MOET-standardised 3-point scoring system. Furthermore, there are new ways to interrogate the biochemistry of individual embryonic cells by using new, light-based methodologies, such as FLIM and hyperspectral microscopy. Combinations of these technologies, in particular combining new imaging systems with AI, will lead to very accurate NQEAP predictive tools, improving embryo selection and recipient pregnancy success.

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.

Autofluorescence spectroscopy in redox monitoring across cell confluencies

Patient-specific therapies require that cells be manufactured in multiple batches of small volumes, making it a challenge for conventional modes of quality control. The added complexity of inherent variability (even within batches) necessitates constant monitoring to ensure comparable end products. Hence, it is critical that new non-destructive modalities of cell monitoring be developed. Here, we study, for the first time, the use of optical spectroscopy in the determination of cellular redox across cell confluencies by exploiting the autofluorescence properties of molecules found natively within cells. This was achieved through a simple retrofitting of a standard inverted fluorescence microscope with a spectrometer output and an appropriate fluorescence filter cube. Through spectral decomposition on the acquired autofluorescence spectra, we are able to further discern the relative contributions of the different molecules, namely flavin adenine dinucleotide (FAD) and reduced nicotinamide adenine dinucleotide (NADH). This is then quantifiable as redox ratios (RR) that represent the extent of oxidation to reduction based upon the optically measured quantities of FAD and NADH. Results show that RR decreases with increasing cell confluency, which we attribute to several inter-related cellular processes. We validated the relationship between RR, metabolism and cell confluency through bio-chemical and viability assays. Live-dead and DNA damage studies were further conducted to substantiate that our measurement process had negligible effects on the cells. In this study, we demonstrate that autofluorescence spectroscopy-derived RR can serve as a rapid, non-destructive and label-free surrogate to cell metabolism measurements. This was further used to establish a relationship between cell metabolism and cellular redox across cell confluencies, and could potentially be employed as an indicator of quality in cell therapy manufacturing.

Dynamic biospeckle analysis, a new tool for the fast screening of plant nematicide selectivity

BACKGROUND

Plant feeding, free-living nematodes cause extensive damage to plant roots by direct feeding and, in the case of some trichodorid and longidorid species, through the transmission of viruses. Developing more environmentally friendly, target-specific nematicides is currently impeded by slow and laborious methods of toxicity testing. Here, we developed a bioactivity assay based on the dynamics of light 'speckle' generated by living cells and we demonstrate its application by assessing chemicals' toxicity to different nematode trophic groups.

RESULTS

Free-living nematode populations extracted from soil were exposed to methanol and phenyl isothiocyanate (PEITC). Biospeckle analysis revealed differing behavioural responses as a function of nematode feeding groups. Trichodorus nematodes were less sensitive than were bacterial feeding nematodes or non-trichodorid plant feeding nematodes. Following 24 h of exposure to PEITC, bioactivity significantly decreased for plant and bacterial feeders but not for Trichodorus nematodes. Decreases in movement for plant and bacterial feeders in the presence of PEITC also led to measurable changes to the morphology of biospeckle patterns.

CONCLUSIONS

Biospeckle analysis can be used to accelerate the screening of nematode bioactivity, thereby providing a fast way of testing the specificity of potential nematicidal compounds. With nematodes' distinctive movement and activity levels being visible in the biospeckle pattern, the technique has potential to screen the behavioural responses of diverse trophic nematode communities. The method discriminates both behavioural responses, morphological traits and activity levels and hence could be used to assess the specificity of nematicidal compounds.

Rapid Label-Free Analysis of Brain Tumor Biopsies by Near Infrared Raman and Fluorescence Spectroscopy-A Study of 209 Patients

In brain surgery, novel technologies are continuously developed to achieve better tumor delineation and maximize the extent of resection. Raman spectroscopy is an optical method that enables to retrieve a molecular signature of tissue biochemical composition in order to identify tumor and normal tissue. Here, the translation of Raman spectroscopy to the surgical practice for discerning a variety of different tumor entities from non-neoplastic brain parenchyma was investigated. Fresh unprocessed biopsies obtained from brain tumor surgery were analyzed over 1.5 years including all patients that gave consent. Measurements were performed with a Raman microscope by medical personnel as routine activity. The Raman and fluorescence signals of the acquired spectra were analyzed by principal component analysis, followed by supervised classification to discriminate non-tumor tissue vs. tumor and distinguish tumor entities. Histopathology of the measured biopsies was performed as reference. Classification led to the correct recognition of all non-neoplastic biopsies (7/7) and of 97% of the investigated tumor biopsies (195/202). For instance, GBM was recognized as tumor with a correct rate of 94% if primary, and of 100% if recurrent. Astrocytoma and oligodendroglioma were recognized as tumor with correct rates of 86 and 90%, respectively. All brain metastases, meningioma and schwannoma were correctly recognized as tumor and distinguished from non-neoplastic brain tissue. Furthermore, metastases were discerned from glioma with correct rate of 90%. Oligodendroglioma and astrocytoma IDH1-mutant, which differ in the presence of 1p/19q codeletion, were discerned with a correct rate of 81%. These results demonstrate the feasibility of rapid brain tumors recognition and extraction of diagnostic information by Raman spectroscopy, using a protocol that can be easily included in the routine surgical workflow.

Intra- and Interspecies Variability of Single-Cell Innate Fluorescence Signature of Microbial Cell

A cell’s innate fluorescence signature is an assemblage of fluorescence signals emitted by diverse biomolecules within a cell. It is known that the innate fluoresce signature reflects various cellular properties and physiological statuses; thus, they can serve as a rich source of information in cell characterization as well as cell identification. However, conventional techniques focus on the analysis of the innate fluorescence signatures at the population level but not at the single-cell level and thus necessitate a clonal culture. In the present study, we developed a technique to analyze the innate fluorescence signature of a single microbial cell. Using this novel method, we found that even very similarly shaped cells differ noticeably in their autofluorescence features, and the innate fluorescence signature changes dynamically with growth phases. We also demonstrated that the different cell types can be classified accurately within a mixed population under a microscope at the resolution of a single cell, depending solely on the innate fluorescence signature information. We suggest that single-cell autofluoresce signature analysis is a promising tool to directly assess the taxonomic or physiological heterogeneity within a microbial population, without cell tagging.

Here we analyzed the innate fluorescence signature of the single microbial cell, within both clonal and mixed populations of microorganisms. We found that even very similarly shaped cells differ noticeably in their autofluorescence features and that the innate fluorescence signatures change dynamically with growth phases. We demonstrated that machine learning models can be trained with a data set of single-cell innate fluorescence signatures to annotate cells according to their phenotypes and physiological status, for example, distinguishing a wild-type Aspergillus nidulans cell from its nitrogen metabolism mutant counterpart and log-phase cells from stationary-phase cells of Pseudomonas putida. We developed a minimally invasive method (confocal reflection microscopy-assisted single-cell innate fluorescence [CRIF] analysis) to optically extract and catalog the innate cellular fluorescence signatures of each of the individual live microbial cells in a three-dimensional space. This technique represents a step forward from traditional techniques which analyze the innate fluorescence signatures at the population level and necessitate a clonal culture. Since the fluorescence signature is an innate property of a cell, our technique allows the prediction of the types or physiological status of intact and tag-free single cells, within a cell population distributed in a three-dimensional space. Our study presents a blueprint for a streamlined cell analysis where one can directly assess the potential phenotype of each single cell in a heterogenous population by its autofluorescence signature under a microscope, without cell tagging.

IMPORTANCE A cell’s innate fluorescence signature is an assemblage of fluorescence signals emitted by diverse biomolecules within a cell. It is known that the innate fluoresce signature reflects various cellular properties and physiological statuses; thus, they can serve as a rich source of information in cell characterization as well as cell identification. However, conventional techniques focus on the analysis of the innate fluorescence signatures at the population level but not at the single-cell level and thus necessitate a clonal culture. In the present study, we developed a technique to analyze the innate fluorescence signature of a single microbial cell. Using this novel method, we found that even very similarly shaped cells differ noticeably in their autofluorescence features, and the innate fluorescence signature changes dynamically with growth phases. We also demonstrated that the different cell types can be classified accurately within a mixed population under a microscope at the resolution of a single cell, depending solely on the innate fluorescence signature information. We suggest that single-cell autofluoresce signature analysis is a promising tool to directly assess the taxonomic or physiological heterogeneity within a microbial population, without cell tagging.

Novel automated non invasive detection of ocular surface squamous neoplasia using multispectral autofluorescence imaging

PURPOSE

Diagnosing Ocular surface squamous neoplasia (OSSN) using newly designed multispectral imaging technique.

METHODS

Eighteen patients with histopathological diagnosis of Ocular Surface Squamous Neoplasia (OSSN) were recruited. Their previously collected biopsy specimens of OSSN were reprocessed without staining to obtain auto fluorescence multispectral microscopy images. This technique involved a custom-built spectral imaging system with 38 spectral channels. Inter and intra-patient frameworks were deployed to automatically detect and delineate OSSN using machine learning methods. Different machine learning methods were evaluated, with K nearest neighbor and Support Vector Machine chosen as preferred classifiers for intra- and inter-patient frameworks, respectively. The performance of the technique was evaluated against a pathological assessment.

RESULTS

Quantitative analysis of the spectral images provided a strong multispectral signature of a relative difference between neoplastic and normal tissue both within each patient (at p < 0.0005) and between patients (at p < 0.001). Our fully automated diagnostic method based on machine learning produces maps of the relatively well circumscribed neoplastic-non neoplastic interface. Such maps can be rapidly generated in quasi-real time and used for intraoperative assessment. Generally, OSSN could be detected using multispectral analysis in all patients investigated here. The cancer margins detected by multispectral analysis were in close and reasonable agreement with the margins observed in the H&E sections in intra- and inter-patient classification, respectively.

CONCLUSIONS

This study shows the feasibility of using multispectral auto-fluorescence imaging to detect and find the boundary of human OSSN. Fully automated analysis of multispectral images based on machine learning methods provides a promising diagnostic tool for OSSN which can be translated to future clinical applications.

Non-Invasive Monitoring of Functional State of Articular Cartilage Tissue with Label-Free Unsupervised Hyperspectral Imaging

Damage and degradation of articular cartilage leads to severe pain and loss of mobility. The development of new therapies for cartilage regeneration for monitoring their effect requires further study of cartilage, ideally at a molecular level and in a minimally invasive way. Hyperspectral microscopy is a novel technology which utilises endogenous fluorophores to non-invasively assess the molecular composition of cells and tissue. In this study, we applied hyperspectral microscopy to healthy bovine articular cartilage and osteoarthritic human articular cartilage to investigate its capacity to generate informative molecular data and characterise disease state and treatment effects. We successfully demonstrated label-free fluorescence identification of collagen type I and II - isolated in cartilage here for the first time and the co-enzymes free NADH and FAD which together give the optical redox ratio that is an important measure of metabolic activity. The intracellular composition of chondrocytes was also examined. Differences were observed in the molecular ratios within the superficial and transitional zones of the articular cartilage which appeared to be influenced by disease state and treatment. These findings show that hyperspectral microscopy could be useful for investigating the molecular underpinnings of articular cartilage degradation and repair. As it is non-invasive and non-destructive, samples can be repeatedly assessed over time, enabling true time-course experiments with in-depth molecular data. Additionally, there is potential for the hyperspectral approach to be adapted for patient examination to allow the investigation of cartilage state. This could be of advantage for assessment and diagnosis as well as treatment monitoring.

Label-free classification of neurons and glia in neural stem cell cultures using a hyperspectral imaging microscopy combined with machine learning

Due to a growing demand for a viable label-free observation method in the biomedical field, many techniques, such as quantitative phase imaging and Raman spectroscopy, have been studied, and a complementary approach, hyperspectral imaging, has also been introduced. We developed a high-speed hyperspectral imaging microscopy imaging method with commercially available apparatus, employing a liquid crystal tunable bandpass filter combined with a pixel-wise machine learning classification. Next, we evaluated the feasibility of the application of this method for stem cell research utilizing neural stem cells. Employing this microscopy method, with a 562 × 562 μm² field of view, 2048 × 2048 pixel resolution images containing 63 wavelength pixel-wise spectra could be obtained in 30 seconds. The neural stem cells were differentiated into neurons and astroglia (glia), and a four-class cell classification evaluation (including neuronal cell body, glial cell body, process and extracellular region) was conducted under co-cultured conditions. As a result, an average of 88% of the objects of interest were correctly classified, with an average precision of 94%, and more than 99% of the extracellular pixels were correctly segregated. These results indicated that the proposed hyperspectral imaging microscopy is feasible as a label-free observation method for stem cell research.

NADH Autofluorescence-A Marker on its Way to Boost Bioenergetic Research

More than 60 years ago, the idea was introduced that NADH autofluorescence could be used as a marker of cellular redox state and indirectly also of cellular energy metabolism. Fluorescence lifetime imaging microscopy of NADH autofluorescence offers a marker-free readout of the mitochondrial function of cells in their natural microenvironment and allows different pools of NADH to be distinguished within a cell. Despite its many advantages in terms of spatial resolution and in vivo applicability, this technique still requires improvement in order to be fully useful in bioenergetics research. In the present review, we give a summary of technical and biological challenges that have so far limited the spread of this powerful technology. To help overcome these challenges, we provide a comprehensible overview of biological applications of NADH imaging, along with a detailed summary of valid imaging approaches that may be used to tackle many biological questions. This review is meant to provide all scientists interested in bioenergetics with support on how to embed successfully NADH imaging in their research. © 2018 International Society for Advancement of Cytometry.

Single-Cell Analysis Using Hyperspectral Imaging Modalities

Almost a decade ago, hyperspectral imaging (HSI) was employed by the NASA in satellite imaging applications such as remote sensing technology. This technology has since been extensively used in the exploration of minerals, agricultural purposes, water resources, and urban development needs. Due to recent advancements in optical re-construction and imaging, HSI can now be applied down to micro- and nanometer scales possibly allowing for exquisite control and analysis of single cell to complex biological systems. This short review provides a description of the working principle of the HSI technology and how HSI can be used to assist, substitute, and validate traditional imaging technologies. This is followed by a description of the use of HSI for biological analysis and medical diagnostics with emphasis on single-cell analysis using HSI.

Statistically strong label-free quantitative identification of native fluorophores in a biological sample

Bioimaging using endogenous cell fluorescence, without any external biomarkers makes it possible to explore cells and tissues in their original native state, also in vivo. In order to be informative, this label-free method requires careful multispectral or hyperspectral recording of autofluorescence images followed by unsupervised extraction (unmixing) of biochemical signatures. The unmixing is difficult due to the scarcity of biochemically pure regions in cells and also because autofluorescence is weak compared with signals from labelled cells, typically leading to low signal to noise ratio. Here, we solve the problem of unsupervised hyperspectral unmixing of cellular autofluorescence by introducing the Robust Dependent Component Analysis (RoDECA). This approach provides sophisticated and statistically robust quantitative biochemical analysis of cellular autofluorescence images. We validate our method on artificial images, where the addition of varying known level of noise has allowed us to quantify the accuracy of our RoDECA analysis in a way that can be applied to real biological datasets. The same unsupervised statistical minimisation is then applied to imaging of mouse retinal photoreceptor cells where we establish the identity of key endogenous fluorophores (free NADH, FAD and lipofuscin) and derive the corresponding molecular abundance maps. The pre-processing methodology of image datasets is also presented, which is essential for the spectral unmixing analysis, but mostly overlooked in the previous studies.