Faster, sharper, more precise: Automated Cluster-FLIM in preclinical testing directly identifies the intracellular fate of theranostics in live cells and tissue

Cy3-Based Nanoviscosity Determination of Mucus: Effect of Mucus Collection Methods and Antibiotics Treatment

The integrity of the protective mucus layer as a primary defense against pathogen invasion and microbial leakage into the intestinal epithelium can be compromised by the effects of antibiotics on the commensal microbiome. Changes in mucus integrity directly affect the solvent viscosity in the immediate vicinity of the mucin network, that is, the nanoviscosity, which in turn affects both biochemical reactions and selective transport. To assess mucus nanoviscosity, a reliable readout via the viscosity-dependent fluorescence lifetime of the molecular rotor dye cyanine 3 is established and nanoviscosities from porcine and murine ex vivo mucus are determined. To account for different mucin concentrations due to the removal of digestive residues during mucus collection, the power law dependence of mucin concentration on viscosity is used. The impact of antibiotics combinations (meropenem/vancomycin, gentamycin/ampicillin) on ex vivo intestinal mucus nanoviscosity is presented. The significant increase in viscosity of murine intestinal mucus after treatment suggests an effect of antibiotics on the microbiota that affects mucus integrity. This method will be a useful tool to assess how drugs, directly or indirectly, affect mucus integrity. Additionally, the method can be utilized to analyze the role of mucus nanoviscosity in health and disease, as well as in drug development.

Impact of glycan nature on structure and viscoelastic properties of glycopeptide hydrogels

Mucus is a complex biological hydrogel that acts as a barrier for almost everything entering or exiting the body. It is therefore of emerging interest for biomedical and pharmaceutical applications. Besides water, the most abundant components are the large and densely glycosylated mucins, glycoproteins of up to 20 MDa and carbohydrate content of up to 80 wt%. Here, we designed and explored a library of glycosylated peptides to deconstruct the complexity of mucus. Using the well-characterized hFF03 coiled-coil system as a hydrogel-forming peptide scaffold, we systematically probed the contribution of single glycans to the secondary structure as well as the formation and viscoelastic properties of the resulting hydrogels. We show that glycan-decoration does not affect α-helix and coiled-coil formation while it alters gel stiffness. By using oscillatory macrorheology, dynamic light scattering microrheology, and fluorescence lifetime-based nanorheology, we characterized the glycopeptide materials over several length scales. Molecular simulations revealed that the glycosylated linker may extend into the solvent, but more frequently interacts with the peptide, thereby likely modifying the stability of the self-assembled fibers. This systematic study highlights the interplay between glycan structure and hydrogel properties and may guide the development of synthetic mucus mimetics.

Label-free mapping of cetuximab in multi-layered tumor oral mucosa models by atomic force-microscopy-based infrared spectroscopy

Sensitive mapping of drugs and drug delivery systems is pivotal for the understanding and improvement of treatment options. Since labeling alters the physicochemical and potentially the pharmacological properties of the molecule of interest, its label-free detection by photothermal expansion is investigated. We report on a proof-of-concept study to map the cetuximab distribution by atomic-force microscopy-based infrared spectroscopy (AFM-IR). The monoclonal antibody cetuximab was applied to a human tumor oral mucosa model, consisting of a tumor epithelium on a lamina propria equivalent. Hyperspectral imaging in the wavenumber regime between 903 cm-1 and 1312 cm-1 and a probing distance between the data points down to 10 × 10 nm are used for determining the local drug distribution. The local distinction of cetuximab from the tissue background is gained by linear combination modeling making use of reference spectra of the drug and untreated models. The results from this approach are compared to principal component analyses, yielding comparable results. Even single molecule detection appears feasible. The results indicate that cetuximab penetrates the cytosol of tumor cells but does not bind to structures in the cell membrane. In conclusion, AFM-IR mapping of cetuximab proved to sensitively determine drug concentrations at an unprecedented spatial resolution without the need for drug labeling.

Review of optical methods for noninvasive imaging of skin fibroblasts-From in vitro to ex vivo and in vivo visualization

Fibroblasts are among the most common cell types in the stroma responsible for creating and maintaining the structural organization of the extracellular matrix in the dermis, skin regeneration, and a range of immune responses. Until now, the processes of fibroblast adaptation and functioning in a varying environment have not been fully understood. Modern laser microscopes are capable of studying fibroblasts in vitro and ex vivo. One-photon- and two-photon-excited fluorescence microscopy, Raman spectroscopy/microspectroscopy are well-suited noninvasive optical methods for fibroblast imaging in vitro and ex vivo. In vivo staining-free fibroblast imaging is not still implemented. The exception is fibroblast imaging in tattooed skin. Although in vivo noninvasive staining-free imaging of fibroblasts in the skin has not yet been implemented, it is expected in the future. This review summarizes the state-of-the-art in fibroblast visualization using optical methods and discusses the advantages, limitations, and prospects for future noninvasive imaging.

Fluorescence Lifetime Measurements and Analyses: Protocols Using Flow Cytometry and High-Throughput Microscopy

This chapter focuses on applications and protocols that involve the measurement of the fluorescence lifetime as an informative cytometric parameter. The timing of fluorescence decay has been well-studied for cell counting, sorting, and imaging. Therefore, provided herein is an overview of the techniques used, how they enhance cytometry protocols, and the modern techniques used for lifetime analysis. The background and theory behind fluorescence decay kinetic measurements in cells is first discussed followed by the history of the development of time-resolved flow cytometry. These sections are followed by a review of applications that benefit from the quantitative nature of fluorescence lifetimes as a photophysical trait. Lastly, perspectives on the modern ways in which the fluorescence lifetime is scanned at high throughputs which include high-speed microscopy and machine learning are provided.

Visualization of Nanocarriers and Drugs in Cells and Tissue

In this chapter, the visualization of nanocarriers and drugs in cells and tissue is reviewed. This topic is tightly connected to modern drug delivery, which relies on nanoscopic drug formulation approaches and the ability to probe nanoparticulate systems selectively in cells and tissue using advanced spectroscopic and microscopic techniques. We first give an overview of the breadth of this research field. Then, we mainly focus on topical drug delivery to the skin and discuss selected visualization techniques from spectromicroscopy, such as scanning transmission X-ray microscopy and fluorescence lifetime imaging. These techniques rely on the sensitive and quantitative detection of the topically applied drug delivery systems and active substances, either by exploiting their molecular properties or by introducing environmentally sensitive probes that facilitate their detection.

Automation: A revolutionary vision of artificial intelligence in theranostics

The last two decades have witnessed an extraordinary evolution of automation and artificial intelligence (AI), which has become an integral part of our daily lives. Lately, AI has also been assimilated in the field of medicine to upgrade overall healthcare system and encourage personalized treatment. Theranostics literally meaning combination of diagnosis and therapeutics, is a targeted pharmacotherapy, based on specific targeted diagnostic tests. Numerous theranostic agents/biomarkers are available which can identify the most beneficial treatment, correct dose or predict response to a medicine, thus, maximizing drug efficacy, minimizing toxicity and providing informed treatment choice. For instance, a statistics based Cluster-FLIM technology provides precise data on drug-receptor binding behavior in biological tissues using fluorescence real experimental imaging. Automated Idylla™ qPCR System is another approach in oncology to determine the EGFR mutations at initial stage as well as during the treatment and also assists the oncologist in designing the treatment protocol. Recent incorporation of automation and AI in theranostics has brought a drastic change in early detection and treatment protocols for various diseases such as cancer and diabetes. Also, it leads to quick analysis of number of diverse experimental datum with accuracy. The approach mainly uses computer algorithms to unveil relevant and significant information from clinical data, thereby assisting in making accurate, logical and pertinent decisions. This review highlights the emerging uses/role of automation and AI in theranostics, technical difficulties and focuses on its future prospects to facilitate a patient specific, reliable and efficient pharmacotherapy.

Lipid Membrane Alterations in Tumor Spheroids Revealed by Fluorescence Lifetime Microscopy Imaging

Three-dimensional (3D) cultured tumor spheroid models, as one type of in vitro model, have been proven to have more physiological similarities to in vivo animal models than cells in 2D cultures. Tumor spheroids have been widely used in preclinical experiments of anticancer drug treatments, providing reliable data in pathogenetic research. Currently, different 3D cell culture conditions, even in the same cell line, generate heterogeneous spheroids in morphology and size, resulting in different growth rates or drug-killing responses. Therefore, the measurement and evaluation of the properties of tumor spheroids have become highly demanding tasks with huge challenges. For functional characterization of tumor spheroids, the microenvironment sensitivity and quantitative properties of the fluorescence lifetime microscopy imaging (FLIM) technique have great advantages for improving the reliability of cell physiological testing. In this paper, we have proposed a FLIM-based approach to observe the lipid components labeled with Nile red of cells in both 3D and 2D cultures. The imaging data and analysis provided basic information on the sizes, morphologies, and cell membrane fluorescence lifetime values of the tumor spheroids. FLIM data showed that the microenvironment of the cell membrane in the 3D model was largely altered compared to that in the 2D culture. Next, a series of parameters that may influence the lipid components of tumor cells and tumor spheroids were tested by FLIM, including pH, viscosity, and polarity. The results showed that pH and viscosity contributed little to the change in fluorescence lifetime values, while the change in cell membrane polarity was the main cause of the alterations in fluorescence lifetime data, suggesting that cell membrane polarity should be considered a marker in distinguishing tumor spheroids from cellular physiological status. In conclusion, this FLIM-based testing process has been proven to be a quantitative method for measuring the differences between the cells of the 3D model from the 2D cultured cells with satisfactory sensitivity and accuracy, providing a high potential standard assay in the quality evaluation and control of tumor spheroids for future anticancer drug development.

QuasAr Odyssey: the origin of fluorescence and its voltage sensitivity in microbial rhodopsins

Rhodopsins had long been considered non-fluorescent until a peculiar voltage-sensitive fluorescence was reported for archaerhodopsin-3 (Arch3) derivatives. These proteins named QuasArs have been used for imaging membrane voltage changes in cell cultures and small animals. However due to the low fluorescence intensity, these constructs require use of much higher light intensity than other optogenetic tools. To develop the next generation of sensors, it is indispensable to first understand the molecular basis of the fluorescence and its modulation by the membrane voltage. Based on spectroscopic studies of fluorescent Arch3 derivatives, we propose a unique photo-reaction scheme with extended excited-state lifetimes and inefficient photoisomerization. Molecular dynamics simulations of Arch3, of the Arch3 fluorescent derivative Archon1, and of several its mutants have revealed different voltage-dependent changes of the hydrogen-bonding networks including the protonated retinal Schiff-base and adjacent residues. Experimental observations suggest that under negative voltage, these changes modulate retinal Schiff base deprotonation and promote a decrease in the populations of fluorescent species. Finally, we identified molecular constraints that further improve fluorescence quantum yield and voltage sensitivity.

The authors present an in-depth investigation of excited state dynamics and molecular mechanism of the voltage sensing in microbial rhodopsins. Using a combination of spectroscopic investigations and molecular dynamics simulations, the study proposes the voltage-modulated deprotonation of the chromophore as the key event in the voltage sensing. Thus, molecular constraints that may further improve the fluorescence quantum yield and the voltage sensitivity are presented.

uFLIM - Unsupervised analysis of FLIM-FRET microscopy data

Despite their widespread use in cell biology, fluorescence lifetime imaging microscopy (FLIM) data-sets are challenging to analyse, because each spatial position can contain a superposition of multiple fluorescent components. Here, we present a data analysis method employing all information in the available photon budget, as well as being fast. The method, called uFLIM, determines spatial distributions and temporal dynamics of multiple fluorescent components with no prior knowledge. It goes significantly beyond current approaches which either assume the functional dependence of the dynamics, e.g. an exponential decay, or require dynamics to be known, or calibrated. Its efficient non-negative matrix factorization algorithm allows for real-time data processing. We validate in silico that uFLIM is capable to disentangle the spatial distribution and spectral properties of five fluorescing probes, from only two excitation and detection channels and a photon budget of 100 detected photons per pixel. By adapting the method to data exhibiting Förster resonant energy transfer (FRET), we retrieve the spatial and transfer rate distribution of the bound species, without constrains on donor and acceptor dynamics.

In Vitro Models of Biological Barriers for Nanomedical Research

Nanoconstructs developed for biomedical purposes must overcome diverse biological barriers before reaching the target where playing their therapeutic or diagnostic function. In vivo models are very complex and unsuitable to distinguish the roles plaid by the multiple biological barriers on nanoparticle biodistribution and effect; in addition, they are costly, time-consuming and subject to strict ethical regulation. For these reasons, simplified in vitro models are preferred, at least for the earlier phases of the nanoconstruct development. Many in vitro models have therefore been set up. Each model has its own pros and cons: conventional 2D cell cultures are simple and cost-effective, but the information remains limited to single cells; cell monolayers allow the formation of cell–cell junctions and the assessment of nanoparticle translocation across structured barriers but they lack three-dimensionality; 3D cell culture systems are more appropriate to test in vitro nanoparticle biodistribution but they are static; finally, bioreactors and microfluidic devices can mimicking the physiological flow occurring in vivo thus providing in vitro biological barrier models suitable to reliably assess nanoparticles relocation. In this evolving context, the present review provides an overview of the most representative and performing in vitro models of biological barriers set up for nanomedical research.

Comparison of fluorescence lifetime and multispectral imaging for quantitative multiplexing in biological tissue

Fluorescence lifetime (FLT) multiplexing and multispectral imaging (MSI) are both frequently employed for in vitro and ex vivo biological studies. In vivo applications of MSI for deep seated fluorophores require consideration of diffusive light propagation in biological tissue. We have previously shown that a well-known redshift of fluorescence spectra in diffusive medium induces a fluorophore cross-talk, which cannot be accounted for even with known optical properties of the medium. In contrast, FLT measurements remain largely unaffected by light propagation in tissue, enabling zero cross-talk and accurate relative quantification. While a fully quantitative estimation of fluorophore concentrations requires depth resolved tomographic imaging, this is often not possible due to the difficulty of estimating tissue optical properties and modelling light propagation in complex tissue geometries. Here, we experimentally investigate the performance of planar (non-tomographic) MSI and FLT multiplexing for the quantitative recovery of multiple near-infrared fluorophores embedded in 4-8 mm thick tissue. We show that FLT multiplexing provides a superior quantification accuracy (error < 10%) compared to MSI (error = 20-107%) in tissue. The error rates for MSI increased with tissue thickness and can be directly attributed to the spectral redshift induced cross-talk between emission spectra. Our data indicate that planar FLT multiplexing can provide high quantification accuracy in thick biological tissue without a need for optical property estimation, thereby offering an important validation tool for rapid quantification of fluorophore concentrations in bulk tissue.

Improved fluorescent phytochromes for in situ imaging

Modern biology investigations on phytochromes as near-infrared fluorescent pigments pave the way for the development of new biosensors, as well as for optogenetics and in vivo imaging tools. Recently, near-infrared fluorescent proteins (NIR-FPs) engineered from biliverdin-binding bacteriophytochromes and cyanobacteriochromes, and from phycocyanobilin-binding cyanobacterial phytochromes have become promising probes for fluorescence microscopy and in vivo imaging. However, current NIR-FPs typically suffer from low fluorescence quantum yields and short fluorescence lifetimes. Here, we applied the rational approach of combining mutations known to enhance fluorescence in the cyanobacterial phytochrome Cph1 to derive a series of highly fluorescent variants with fluorescence quantum yield exceeding 15%. These variants were characterised by biochemical and spectroscopic methods, including time-resolved fluorescence spectroscopy. We show that these new NIR-FPs exhibit high fluorescence quantum yields and long fluorescence lifetimes, contributing to their bright fluorescence, and provide fluorescence lifetime imaging measurements in E.coli cells.

Label-free sensing of cells with fluorescence lifetime imaging: The quest for metabolic heterogeneity

Molecular, morphological, and physiological heterogeneity is the inherent property of cells which governs differences in their response to external influence. Tumor cell metabolic heterogeneity is of a special interest due to its clinical relevance to tumor progression and therapeutic outcomes. Rapid, sensitive, and noninvasive assessment of metabolic heterogeneity of cells is a great demand for biomedical sciences. Fluorescence lifetime imaging (FLIM), which is an all-optical technique, is an emerging tool for sensing and quantifying cellular metabolism by measuring fluorescence decay parameters of endogenous fluorophores, such as NAD(P)H. To achieve accurate discrimination between metabolically diverse cellular subpopulations, appropriate approaches to FLIM data collection and analysis are needed. In this paper, the unique capability of FLIM to attain the overarching goal of discriminating metabolic heterogeneity is demonstrated. This has been achieved using an approach to data analysis based on the nonparametric analysis, which revealed a much better sensitivity to the presence of metabolically distinct subpopulations compared to more traditional approaches of FLIM measurements and analysis. The approach was further validated for imaging cultured cancer cells treated with chemotherapy. These results pave the way for accurate detection and quantification of cellular metabolic heterogeneity using FLIM, which will be valuable for assessing therapeutic vulnerabilities and predicting clinical outcomes.

Deep learning in macroscopic diffuse optical imaging

SIGNIFICANCE

Biomedical optics system design, image formation, and image analysis have primarily been guided by classical physical modeling and signal processing methodologies. Recently, however, deep learning (DL) has become a major paradigm in computational modeling and has demonstrated utility in numerous scientific domains and various forms of data analysis.

AIM

We aim to comprehensively review the use of DL applied to macroscopic diffuse optical imaging (DOI).

APPROACH

First, we provide a layman introduction to DL. Then, the review summarizes current DL work in some of the most active areas of this field, including optical properties retrieval, fluorescence lifetime imaging, and diffuse optical tomography.

RESULTS

The advantages of using DL for DOI versus conventional inverse solvers cited in the literature reviewed herein are numerous. These include, among others, a decrease in analysis time (often by many orders of magnitude), increased quantitative reconstruction quality, robustness to noise, and the unique capability to learn complex end-to-end relationships.

CONCLUSIONS

The heavily validated capability of DL's use across a wide range of complex inverse solving methodologies has enormous potential to bring novel DOI modalities, otherwise deemed impractical for clinical translation, to the patient's bedside.

BODIPY derivatives as fluorescent reporters of molecular activities in living cells

Fluorescent compounds have become indispensable tools for imaging molecular activities in the living cell. 4,4-Difluoro-4-bora-3a,4a-diaza-s-indacene (BODIPY) is currently one of the most popular fluorescent reporters due to its unique photophysical properties. This review provides a general survey and presents a summary of recent advances in the development of new BODIPY-based cellular biomarkers and biosensors. The review starts with the consideration of the properties of BODIPY derivatives required for their application as cellular reporters. Then review provides examples of the design of sensors for different biologically important molecules, ions, membrane potential, temperature and viscosity defining the live cell status. Special attention is payed to BODPY-based phototransformable reporters.

The bibliography includes 339 references.

Development of a rapid and sensitive quantum dot nanobead-based double-antigen sandwich lateral flow immunoassay and its clinical performance for the detection of SARS-CoV-2 total antibodies

Owing to the over-increasing demands in resisting and managing the coronavirus disease 2019 (COVID-19) pandemic, development of rapid, highly sensitive, accurate, and versatile tools for monitoring total antibody concentrations at the population level has been evolved as an urgent challenge on measuring the fatality rate, tracking the changes in incidence and prevalence, comprehending medical sequelae after recovery, as well as characterizing seroprevalence and vaccine coverage. To this end, herein we prepared highly luminescent quantum dot nanobeads (QBs) by embedding numerous quantum dots into polymer matrix, and then applied it as a signal-amplification label in lateral flow immunoassay (LFIA). After covalently linkage with the expressed recombinant SARS-CoV-2 spike protein (RSSP), the synthesized QBs were used to determine the total antibody levels in sera by virtue of a double-antigen sandwich immunoassay. Under the developed condition, the QB-LFIA can allow the rapid detection of SARS-CoV-2 total antibodies within 15 min with about one order of magnitude improvement in analytical sensitivity compared to conventional gold nanoparticle-based LFIA. In addition, the developed QB-LFIA performed well in clinical study in dynamic monitoring of serum antibody levels in the whole course of SARS-CoV-2 infection. In conclusion, we successfully developed a promising fluorescent immunological sensing tool for characterizing the host immune response to SARS-CoV-2 infection and confirming the acquired immunity to COVID-19 by evaluating the SRAS-CoV-2 total antibody level in the crowd.

Development of a rapid and sensitive quantum dot nanobead-based double-antigen sandwich lateral flow immunoassay and its clinical performance for the detection of SARS-CoV-2 total antibodies

Owing to the over-increasing demands in resisting and managing the coronavirus disease 2019 (COVID-19) pandemic, development of rapid, highly sensitive, accurate, and versatile tools for monitoring total antibody concentrations at the population level has been evolved as an urgent challenge on measuring the fatality rate, tracking the changes in incidence and prevalence, comprehending medical sequelae after recovery, as well as characterizing seroprevalence and vaccine coverage. To this end, herein we prepared highly luminescent quantum dot nanobeads (QBs) by embedding numerous quantum dots into polymer matrix, and then applied it as a signal-amplification label in lateral flow immunoassay (LFIA). After covalently linkage with the expressed recombinant SARS-CoV-2 spike protein (RSSP), the synthesized QBs were used to determine the total antibody levels in sera by virtue of a double-antigen sandwich immunoassay. Under the developed condition, the QB-LFIA can allow the rapid detection of SARS-CoV-2 total antibodies within 15 min with about one order of magnitude improvement in analytical sensitivity compared to conventional gold nanoparticle-based LFIA. In addition, the developed QB-LFIA performed well in clinical study in dynamic monitoring of serum antibody levels in the whole course of SARS-CoV-2 infection. In conclusion, we successfully developed a promising fluorescent immunological sensing tool for characterizing the host immune response to SARS-CoV-2 infection and confirming the acquired immunity to COVID-19 by evaluating the SRAS-CoV-2 total antibody level in the crowd.

A Dual Fluorescence-Spin Label Probe for Visualization and Quantification of Target Molecules in Tissue by Multiplexed FLIM-EPR Spectroscopy

Simultaneous visualization and concentration quantification of molecules in biological tissue is an important though challenging goal. The advantages of fluorescence lifetime imaging microscopy (FLIM) for visualization, and electron paramagnetic resonance (EPR) spectroscopy for quantification are complementary. Their combination in a multiplexed approach promises a successful but ambitious strategy because of spin label-mediated fluorescence quenching. Here, we solved this problem and present the molecular design of a dual label (DL) compound comprising a highly fluorescent dye together with an EPR spin probe, which also renders the fluorescence lifetime to be concentration sensitive. The DL can easily be coupled to the biomolecule of choice, enabling in vivo and in vitro applications. This novel approach paves the way for elegant studies ranging from fundamental biological investigations to preclinical drug research, as shown in proof-of-principle penetration experiments in human skin ex vivo.

A Nomogram Based on a Collagen Feature Support Vector Machine for Predicting the Treatment Response to Neoadjuvant Chemoradiotherapy in Rectal Cancer Patients

BACKGROUND

The relationship between collagen features (CFs) in the tumor microenvironment and the treatment response to neoadjuvant chemoradiotherapy (nCRT) is still unknown. This study aimed to develop and validate a perdition model based on the CFs and clinicopathological characteristics to predict the treatment response to nCRT among locally advanced rectal cancer (LARC) patients.

METHODS

In this multicenter, retrospective analysis, 428 patients were included and randomly divided into a training cohort (299 patients) and validation cohort (129 patients) [7:3 ratio]. A total of 11 CFs were extracted from a multiphoton image of pretreatment biopsy, and a support vector machine (SVM) was then used to construct a CFs-SVM classifier. A prediction model was developed and presented with a nomogram using multivariable analysis. Further validation of the nomogram was performed in the validation cohort.

RESULTS

The CFs-SVM classifier, which integrated collagen area, straightness, and crosslink density, was significantly associated with treatment response. Predictors contained in the nomogram included the CFs-SVM classifier and clinicopathological characteristics by multivariable analysis. The CFs nomogram demonstrated good discrimination, with area under the receiver operating characteristic curves (AUROCs) of 0.834 in the training cohort and 0.854 in the validation cohort. Decision curve analysis indicated that the CFs nomogram was clinically useful. Moreover, compared with the traditional clinicopathological model, the CFs nomogram showed more powerful discrimination in determining the response to nCRT.

CONCLUSIONS

The CFs-SVM classifier based on CFs in the tumor microenvironment is associated with treatment response, and the CFs nomogram integrating the CFs-SVM classifier and clinicopathological characteristics is useful for individualized prediction of the treatment response to nCRT among LARC patients.

Phasor-based image segmentation: machine learning clustering techniques

The phasor approach is a well-established method for data visualization and image analysis in spectral and lifetime fluorescence microscopy. Nevertheless, it is typically applied in a user-dependent manner by manually selecting regions of interest on the phasor space to find distinct regions in the fluorescence images. In this paper we present our work on using machine learning clustering techniques to establish an unsupervised and automatic method that can be used for identifying populations of fluorescent species in spectral and lifetime imaging. We demonstrate our method using both synthetic data, created by sampling photon arrival times and plotting the distributions on the phasor plot, and real live cells samples, by staining cellular organelles with a selection of commercial probes.

Luminescence lifetime imaging of three-dimensional biological objects

A major focus of current biological studies is to fill the knowledge gaps between cell, tissue and organism scales. To this end, a wide array of contemporary optical analytical tools enable multiparameter quantitative imaging of live and fixed cells, three-dimensional (3D) systems, tissues, organs and organisms in the context of their complex spatiotemporal biological and molecular features. In particular, the modalities of luminescence lifetime imaging, comprising fluorescence lifetime imaging (FLI) and phosphorescence lifetime imaging microscopy (PLIM), in synergy with Förster resonance energy transfer (FRET) assays, provide a wealth of information. On the application side, the luminescence lifetime of endogenous molecules inside cells and tissues, overexpressed fluorescent protein fusion biosensor constructs or probes delivered externally provide molecular insights at multiple scales into protein-protein interaction networks, cellular metabolism, dynamics of molecular oxygen and hypoxia, physiologically important ions, and other physical and physiological parameters. Luminescence lifetime imaging offers a unique window into the physiological and structural environment of cells and tissues, enabling a new level of functional and molecular analysis in addition to providing 3D spatially resolved and longitudinal measurements that can range from microscopic to macroscopic scale. We provide an overview of luminescence lifetime imaging and summarize key biological applications from cells and tissues to organisms.

A Review of New High-Throughput Methods Designed for Fluorescence Lifetime Sensing From Cells and Tissues

Though much of the interest in fluorescence in the past has been on measuring spectral qualities such as wavelength and intensity, there are two other highly useful intrinsic properties of fluorescence: lifetime (or decay) and anisotropy (or polarization). Each has its own set of unique advantages, limitations, and challenges in detection when it comes to use in biological studies. This review will focus on the property of fluorescence lifetime, providing a brief background on instrumentation and theory, and examine the recent advancements and applications of measuring lifetime in the fields of high-throughput fluorescence lifetime imaging microscopy (HT-FLIM) and time-resolved flow cytometry (TRFC). In addition, the crossover of these two methods and their outlooks will be discussed.

Multiplexed non-invasive tumor imaging of glucose metabolism and receptor-ligand engagement using dark quencher FRET acceptor

Rationale: Following an ever-increased focus on personalized medicine, there is a continuing need to develop preclinical molecular imaging modalities to guide the development and optimization of targeted therapies. Near-Infrared (NIR) Macroscopic Fluorescence Lifetime Förster Resonance Energy Transfer (MFLI-FRET) imaging offers a unique method to robustly quantify receptor-ligand engagement in live intact animals, which is critical to assess the delivery efficacy of therapeutics. However, to date, non-invasive imaging approaches that can simultaneously measure cellular drug delivery efficacy and metabolic response are lacking. A major challenge for the implementation of concurrent optical and MFLI-FRET in vivo whole-body preclinical imaging is the spectral crowding and cross-contamination between fluorescent probes. Methods: We report on a strategy that relies on a dark quencher enabling simultaneous assessment of receptor-ligand engagement and tumor metabolism in intact live mice. Several optical imaging approaches, such as in vitro NIR FLI microscopy (FLIM) and in vivo wide-field MFLI, were used to validate a novel donor-dark quencher FRET pair. IRDye 800CW 2-deoxyglucose (2-DG) imaging was multiplexed with MFLI-FRET of NIR-labeled transferrin FRET pair (Tf-AF700/Tf-QC-1) to monitor tumor metabolism and probe uptake in breast tumor xenografts in intact live nude mice. Immunohistochemistry was used to validate in vivo imaging results. Results: First, we establish that IRDye QC-1 (QC-1) is an effective NIR dark acceptor for the FRET-induced quenching of donor Alexa Fluor 700 (AF700). Second, we report on simultaneous in vivo imaging of the metabolic probe 2-DG and MFLI-FRET imaging of Tf-AF700/Tf-QC-1 uptake in tumors. Such multiplexed imaging revealed an inverse relationship between 2-DG uptake and Tf intracellular delivery, suggesting that 2-DG signal may predict the efficacy of intracellular targeted delivery. Conclusions: Overall, our methodology enables for the first time simultaneous non-invasive monitoring of intracellular drug delivery and metabolic response in preclinical studies.

A multilayered epithelial mucosa model of head neck squamous cell carcinoma for analysis of tumor-microenvironment interactions and drug development

Pharmacotherapy of head and neck squamous cell carcinoma (HNSCC) often fails due to the development of chemoresistance and severe systemic side effects of current regimens limiting dose escalation. Preclinical models comprising all major elements of treatment resistance are urgently needed for the development of new strategies to overcome these limitations. For model establishment, we used tumor cells from patient-derived HNSCC xenografts or cell lines (SCC-25, UM-SCC-22B) and characterized the model phenotype. Docetaxel and cetuximab were selected for comparative analysis of drug-related effects at topical and systemic administration. Cetuximab cell binding was mapped by cluster-based fluorescence lifetime imaging microscopy.The tumor oral mucosa (TOM) models displayed unstructured, hyper-proliferative, and pleomorphic cell layers, reflecting well the original tumor morphology and grading. Dose- and time-dependent effects of docetaxel on tumor size, apoptosis, hypoxia, and interleukin-6 release were observed. Although the spectrum of effects was comparable, significantly lower doses were required to achieve similar docetaxel-induced changes at topical compared to systemic application. Despite displaying anti-proliferative effects in monolayer cultures, cetuximab treatment showed only minor effects in TOM models. This was not due to inefficient cetuximab uptake or target cell binding but likely mediated by microenvironmental components.We developed multi-layered HNSCC models, closely reflecting tumor morphology and displaying complex interactions between the tumor and its microenvironment. Topical application of docetaxel emerged as promising option for HNSCC treatment. Aside from the development of novel strategies for topical drug delivery, our tumor model might help to better understand key regulators of drug-tumor-interactions.

Skin Barriers in Dermal Drug Delivery: Which Barriers Have to Be Overcome and How Can We Measure Them?

Although, drugs are required in the various skin compartments such as viable epidermis, dermis, or hair follicles, to efficiently treat skin diseases, drug delivery into and across the skin is still challenging. An improved understanding of skin barrier physiology is mandatory to optimize drug penetration and permeation. The various barriers of the skin have to be known in detail, which means methods are needed to measure their functionality and outside-in or inside-out passage of molecules through the various barriers. In this review, we summarize our current knowledge about mechanical barriers, i.e., stratum corneum and tight junctions, in interfollicular epidermis, hair follicles and glands. Furthermore, we discuss the barrier properties of the basement membrane and dermal blood vessels. Barrier alterations found in skin of patients with atopic dermatitis are described. Finally, we critically compare the up-to-date applicability of several physical, biochemical and microscopic methods such as transepidermal water loss, impedance spectroscopy, Raman spectroscopy, immunohistochemical stainings, optical coherence microscopy and multiphoton microscopy to distinctly address the different barriers and to measure permeation through these barriers in vitro and in vivo.