A hybrid FLIM-elastic net platform for label free profiling of breast cancer

Label-Free Monitoring of Coculture System Dynamics: Probing Probiotic and Cancer Cell Interactions via Infrared Spectroscopic Imaging

Evaluating the dynamic interaction of microorganisms and mammalian cells is challenging due to the lack of suitable platforms for examining interspecies interactions in biologically relevant coculture conditions. In this work, we demonstrate the interaction between probiotic bacteria (Lactococcus lactis and Escherichia coli) and A498 human cancer cells in vitro, utilizing a hydrogel-based platform in a label-free manner by infrared spectroscopy. The L. lactis strain recapitulated in the compartment system secretes polypeptide molecules such as nisin, which has been reported to trigger cell apoptosis. We propose a mid-infrared (IR) spectroscopic imaging approach to monitor the variation of biological components utilizing kidney cells (A498) as a model system cocultured with bacteria. We characterized the biochemical composition (i.e., nucleic acids, protein secondary structures, and lipid conformations) label-free using an unbiased measurement. Several IR spectral features, including unsaturated fatty acids, β-turns in protein, and nucleic acids, were utilized to predict cellular response. These features were then applied to establish a quantitative relationship through a multivariate regression model to predict cellular dynamics in the coculture system to assess the effect of nisin on A498 kidney cancer cells cocultured with bacteria. Overall, our study sheds light on the potential of using IR spectroscopic imaging as a label-free tool to monitor complex microbe-host cell interactions in biological systems. This integration will enable mechanistic studies of interspecies interactions with insights into their underlying physiological processes.

Early Detection of Cervical Cancer by Fluorescence Lifetime Imaging Microscopy Combined with Unsupervised Machine Learning

Cervical cancer has high morbidity and mortality rates, affecting hundreds of thousands of women worldwide and requiring more accurate screening for early intervention and follow-up treatment. Cytology is the current dominant clinical screening approach, and though it has been used for decades, it has unsatisfactory sensitivity and specificity. In this work, fluorescence lifetime imaging microscopy (FLIM) was used for the imaging of exfoliated cervical cells in which an endogenous coenzyme involved in metabolism, namely, reduced nicotinamide adenine dinucleotide (phosphate) [NAD(P)H], was detected to evaluate the metabolic status of cells. FLIM images from 71 participants were analyzed by the unsupervised machine learning method to build a prediction model for cervical cancer risk. The FLIM method combined with unsupervised machine learning (FLIM-ML) had a sensitivity and specificity of 90.9% and 100%, respectively, significantly higher than those of the cytology approach. One cancer recurrence case was predicted as high-risk several months earlier using this method as compared to using current clinical methods, implying that FLIM-ML may be very helpful for follow-up cancer care. This study illustrates the clinical applicability of FLIM-ML as a detection method for cervical cancer screening and a convenient tool for follow-up cancer care.

Longitudinal monitoring of cell metabolism in biopharmaceutical production using label-free fluorescence lifetime imaging microscopy

Chinese hamster ovary (CHO) cells are routinely used in the biopharmaceutical industry for production of therapeutic monoclonal antibodies (mAbs). Although multiple offline and time-consuming measurements of spent media composition and cell viability assays are used to monitor the status of culture in biopharmaceutical manufacturing, the day-to-day changes in the cellular microenvironment need further in-depth characterization. In this study, two-photon fluorescence lifetime imaging microscopy (2P-FLIM) was used as a tool to directly probe into the health of CHO cells from a bioreactor, exploiting the autofluorescence of intracellular nicotinamide adenine dinucleotide phosphate (NAD(P)H), an enzymatic cofactor that determines the redox state of the cells. A custom-built multimodal microscope with two-photon FLIM capability was utilized to monitor changes in NAD(P)H fluorescence for longitudinal characterization of a changing environment during cell culture processes. Three different cell lines were cultured in 0.5 L shake flasks and 3 L bioreactors. The resulting FLIM data revealed differences in the fluorescence lifetime parameters, which were an indicator of alterations in metabolic activity. In addition, a simple principal component analysis (PCA) of these optical parameters was able to identify differences in metabolic progression of two cell lines cultured in bioreactors. Improved understanding of cell health during antibody production processes can result in better streamlining of process development, thereby improving product titer and verification of scale-up. To our knowledge, this is the first study to use FLIM as a label-free measure of cellular metabolism in a biopharmaceutically relevant and clinically important CHO cell line.

Epigenetic Process Monitoring in Live Cultures with Peptide Biosensors

Acetyltransferase is a member of the transferase group responsible for transferring an acetyl group from acetyl-CoA to amino group of a histone lysine residue. Past efforts on histone acetylation monitoring involved biochemical analysis that do not provide spatiotemporal information in a dynamic format. We propose a novel approach to monitor acetyltransferase acetylation in live single cells using time correlated single photon counting fluorescence lifetime imaging (TCSPC-FLIM) with peptide biosensors. Utilizing 2D and 3D cultures we show that the peptide sensor has a specific response to acetyltransferase enzyme activity in a fluorescence lifetime dependent manner ( P < 0.001). Our FLIM biosensor concept enables real-time longitudinal measurement of acetylation activity with high spatial and temporal resolution in live single cells to monitor cell function or evaluate drug effects to treat cancer or neurological diseases.

Bioinspired glycosaminoglycan hydrogels via click chemistry for 3D dynamic cell encapsulation

Cell encapsulation within 3D hydrogels is an attractive approach to develop effective cell-based therapies. However, little is known about how cells respond to the dynamic microenvironment resulting from hydrogel gelation-based cell encapsulation. Here, a tunable biomimetic hydrogel system that possesses alterable gelation kinetics and biologically relevant matrix stiffness is developed to study 3D dynamic cellular responses during encapsulation. Hydrogels are synthesized by cross-linking thiolated hyaluronic acid and thiolated chondroitin sulfate with polyethylene glycol diacrylate under cell-compatible conditions. Hydrogel properties are tailored by altering thiol substitution degrees of glycosaminoglycans or molecular weights of cross-linkers. Encapsulation of human mesenchymal stem cells through hydrogel gelation reveals high cell viability as well as a three-stage gelation-dependent cellular response in real-time focal adhesion kinase (FAK) phosphorylation in live single cells. Furthermore, stiffer hydrogels result in higher equilibrium FAK activity and enhanced actin protrusions. Our results demonstrate the promise of hydrogel-mediated cellular responses during cell encapsulation.

Autofluorescence lifetime imaging of cellular metabolism: Sensitivity toward cell density, pH, intracellular, and intercellular heterogeneity

Autofluorescence imaging (AFI) has greatly accelerated in the last decade, way past its origins in detecting endogenous signals in biological tissues to identify differences between samples. There are many endogenous fluorescence sources of contrast but the most robust and widely utilized have been those associated with metabolism. The intrinsically fluorescent metabolic cofactors nicotinamide adenine dinucleotide (NAD+ /NADH) and flavin adenine dinucleotide (FAD/FADH2 ) have been utilized in a number of AFI applications including basic research, clinical, and pharmaceutical studies. Fluorescence lifetime imaging microscopy (FLIM) has emerged as one of the more powerful AFI tools for NADH and FAD characterization due to its unique ability to noninvasively detect metabolite bound and free states and quantitate cellular redox ratio. However, despite this widespread biological use, many standardization methods are still needed to extend FLIM-based AFI into a fully robust research and clinical diagnostic tools. FLIM is sensitive to a wide range of factors in the fluorophore microenvironment, and there are a number of analysis variables as well. To this end, there has been an emphasis on developing imaging standards and ways to make the image acquisition and analysis more consistent. However, biological conditions during FLIM-based AFI imaging are rarely considered as key sources of FLIM variability. Here, we present several experimental factors with supporting data of the cellular microenvironment such as confluency, pH, inter-/intracellular heterogeneity, and choice of cell line that need to be considered for accurate quantitative FLIM-based AFI measurement of cellular metabolism. © 2018 International Society for Advancement of Cytometry.

Analysis of time-correlated single photon counting data: a comparative evaluation of deterministic and probabilistic approaches

We review various methods for analysing time-resolved fluorescence data acquired using the time-correlated single photon counting method in an attempt to evaluate their benefits and limitations. We have applied these methods to both experimental and simulated data. The relative merits of using deterministic approaches, such as the commonly used iterative reconvolution method, and probabilistic approaches, such as the smoothed exponential series method, the maximum entropy method and recently proposed basis pursuit denoising (compressed sensing) method, are outlined. In particular, we show the value of using multiple methods to arrive at the most appropriate choice of model. We show that the use of probabilistic analysis methods can indicate whether a discrete component or distribution analysis provides the better representation of the data.

Real-Time Multiplex Kinase Phosphorylation Sensors in Living Cells

Phosphorylation is an important post-translational modification implicated in cellular signaling and regulation. However, current methods to study protein phosphorylation by various kinases lack spatiotemporal resolution or the ability to simultaneously observe in real time the activity of multiple kinases in live cells. We present a peptide biosensor strategy with time correlated single photon counting-fluorescence lifetime imaging (TCSPC-FLIM) to interrogate the spatial and temporal dynamics of VEGFR-2 and AKT phosphorylation activity in real time in live 2D and 3D cell culture models at single cell resolution. By recording the increase in fluorescence lifetime due to a change in the solvatochromic environment of the sensor upon phosphorylation, we demonstrate that spatiotemporal maps of protein kinase activity can be obtained. Our results suggest that fluorescence lifetime imaging of peptide biosensors can be effectively and specifically used to monitor and quantify phosphorylation of multiple kinases in live cells.

Monitoring focal adhesion kinase phosphorylation dynamics in live cells

Focal adhesion kinase (FAK) is a cytoplasmic non-receptor tyrosine kinase essential for a diverse set of cellular functions. Current methods for monitoring FAK activity in response to an extracellular stimulus lack spatiotemporal resolution and/or the ability to perform multiplex detection. Here we report on a novel approach to monitor the real-time kinase phosphorylation activity of FAK in live single cells by fluorescence lifetime imaging.

Inside single cells: quantitative analysis with advanced optics and nanomaterials

Single-cell explorations offer a unique window to inspect molecules and events relevant to mechanisms and heterogeneity constituting the central dogma of biology. A large number of nucleic acids, proteins, metabolites, and small molecules are involved in determining and fine-tuning the state and function of a single cell at a given time point. Advanced optical platforms and nanotools provide tremendous opportunities to probe intracellular components with single-molecule accuracy, as well as promising tools to adjust single-cell activity. To obtain quantitative information (e.g., molecular quantity, kinetics, and stoichiometry) within an intact cell, achieving the observation with comparable spatiotemporal resolution is a challenge. For single-cell studies, both the method of detection and the biocompatibility are critical factors as they determine the feasibility, especially when considering live-cell analysis. Although a considerable proportion of single-cell methodologies depend on specialized expertise and expensive instruments, it is our expectation that the information content and implication will outweigh the costs given the impact on life science enabled by single-cell analysis.