Rapid and label-free identification of single leukemia cells from blood in a high-density microfluidic trapping array by fluorescence lifetime imaging microscopy

Advancements in phasor-based FLIM: multi-component analysis and lifetime probes in biological imaging

Fluorescence lifetime imaging microscopy (FLIM) is a reliable method that achieves imaging by detecting fluorescence lifetimes within samples. Owing to its unique temporal characteristic, it can complement fluorescence intensity measurement. Technological and methodological advancements in FLIM have broadened its applications across various domains. The processing of fluorescence lifetime data is crucial for enhancing the speed and accuracy of imaging. Thus, various lifetime fitting algorithms have been developed to improve the imaging speed. The phasor analysis (PA) method is an approach for processing fluorescence lifetime data, capable of directly converting lifetime signals into visual graphics without fitting, which outperforms traditional approaches in speed. Furthermore, lifetime probes with distinct lifetimes are readily implemented for visualization and cluster analysis combined with PA, facilitating the prediction of specific biological states or functions. This review examines various lifetime probes employed in phasor-based FLIM and discusses their roles in the PA method. The methods for multi-component PA within complex biological environments were also described. Additionally, we focused on the advantages of the phasor vector rule and the unmixing of multi-component analysis based on PA. The integration of lifetime probes with phasor-based FLIM facilitates rapid and intuitive detection methods for analyzing complex biological environments.

Ultrafast Intelligent Sensor for Integrated Biological Fluorescence Imaging and Recognition

Fluorescence imaging and recognition are core technologies in targeted medicine, pathological surgery, and biomedicine. However, current imaging and recognition systems are separate, requiring repeated data transfers for imaging and recognition that lead to delays and inefficiency, hindering the capture of rapidly changing physiological processes and biological phenomena. To address these problems, we propose an integrated intelligent sensor for biological fluorescence imaging and ultrafast recognition. This sensor integrates an imaging system based on a photodetector array and a recognition system based on neural networks on a single chip, featuring a highly compact structure, a continuously adjustable optical response, and reconfigurable electrical performance. The unified architecture of the imaging and recognition systems enables ultrafast recognition (19.63 μs) of tumor margins. Additionally, the special organic materials and bulk heterojunction structure endow the photodetector array with strong wavelength dependence, achieving high specific detectivity (3.06 × 1012 Jones) in the narrowband near-infrared range commonly used in biomedical imaging (600-800 nm). After training, the sensor can accurately recognize biological fluorescence edges in real time, even under interference from other colored light noise. Benefiting from its rapidity and high accuracy, we demonstrated a simulated surgical experiment showcasing tumor edge fluorescence imaging, recognition, and cutting. This integrated approach holds the potential to establish a novel paradigm for designing and manufacturing intelligent medical sensors.

Rapid Antibiotic Susceptibility Determination by Fluorescence Lifetime Tracking of Bacterial Metabolism

To combat the rise of antibiotic-resistance in bacteria and the resulting effects on healthcare worldwide, new technologies are needed that can perform rapid antibiotic susceptibility testing (AST). Conventional clinical methods for AST rely on growth-based assays, which typically require long incubation times to obtain quantitative results, representing a major bottleneck in the determination of the optimal antibiotic regimen to treat patients. Here, we demonstrate a rapid AST method based on the metabolic activity measured by fluorescence lifetime imaging microscopy (FLIM). Using lab strains and clinical isolates of Escherichia coli with tetracycline-susceptible and resistant phenotypes as models, we demonstrate that changes in metabolic state associated with antibiotic susceptibility can be quantitatively tracked by FLIM. Our results show that the magnitude of metabolic perturbation resulting from antibiotic activity correlates with susceptibility evaluated by conventional metrics. Moreover, susceptible and resistant phenotypes can be differentiated in as short as 10 min after antibiotic exposure. This FLIM-AST (FAST) method can be applied to other antibiotics and provides insights into the nature of metabolic perturbations inside bacterial cells resulting from antibiotic exposure with single cell resolution.

A microfluidic array enabling generation of identical biochemical stimulating signals to trapped biological cells for single-cell dynamics

Microfluidic-based analyses of single-cell dynamics in response to dynamic biochemical signals are emerging as pivotal approaches for investigating the effects of extracellular microenvironmental biochemical factors on cellular structure, function, and behavior. However, current devices often fail to consistently apply identical dynamic biochemical signals to trapped cells. In this study, we introduce a novel radially distributed single-cell trapping microfluidic array, designed to quantitatively and consistently apply identical biochemical stimulating signals to each trapped cell. Numerical simulations were employed to optimize microchannel geometry, enhancing trapping efficiency while minimizing signal distortion. Experimental validation demonstrated the trapping success rate and the single-cell trapping efficiency exceeding 99% and 85%, respectively. The microarray's capability to deliver identical dynamic biochemical stimulating signals, with various waveforms, to each unit was confirmed through fluorescein transport tests. Furthermore, we examined the intracellular calcium dynamics of U-2 OS human osteosarcoma cells in response to dynamic ATP signals, observing both single-peak calcium responses and calcium oscillations, which were modelled by a second-order system with a natural frequency of 1.6 mHz. Overall, our proposed microfluidic array offers a robust and valuable framework for advancing the understanding of single-cell dynamics.

FLUTE: A Python GUI for interactive phasor analysis of FLIM data

Fluorescence lifetime imaging microscopy (FLIM) is a powerful technique used to probe the local environment of fluorophores. The fit-free phasor approach to FLIM data is increasingly being used due to its ease of interpretation. To date, no open-source graphical user interface (GUI) for phasor analysis of FLIM data is available in Python, thus limiting the widespread use of phasor analysis in biomedical research. Here, we present Fluorescence Lifetime Ultimate Explorer (FLUTE), a Python GUI that is designed to fill this gap. FLUTE simplifies and automates many aspects of the analysis of FLIM data acquired in the time domain, such as calibrating the FLIM data, performing interactive exploration of the phasor plot, displaying phasor plots and FLIM images with different lifetime contrasts simultaneously, and calculating the distance from known molecular species. After applying desired filters and thresholds, the final edited datasets can be exported for further user-specific analysis. FLUTE has been tested using several FLIM datasets including autofluorescence of zebrafish embryos and in vitro cells. In summary, our user-friendly GUI extends the advantages of phasor plotting by making the data visualization and analysis easy and interactive, allows for analysis of large FLIM datasets, and accelerates FLIM analysis for non-specialized labs.

Single-cell characterization of deformation and dynamics of mesenchymal stem cells in microfluidic systems: A computational study

Understanding the homing dynamics of individual mesenchymal stem cells (MSCs) in physiologically relevant microenvironments is crucial for improving the efficacy of MSC-based therapies for therapeutic and targeting purposes. This study investigates the passive homing behavior of individual MSCs in micropores that mimic interendothelial clefts through predictive computational simulations informed by previous microfluidic experiments. Initially, we quantified the size-dependent behavior of MSCs in micropores and elucidated the underlying mechanisms. Subsequently, we analyzed the shape deformation and traversal dynamics of each MSC. In addition, we conducted a systematic investigation to understand how the mechanical properties of MSCs impact their traversal process. We considered geometric and mechanical parameters, such as reduced cell volume, cell-to-nucleus diameter ratio, and cytoskeletal prestress states. Furthermore, we quantified the changes in the MSC traversal process and identified the quantitative limits in their response to variations in micropore length. Taken together, the computational results indicate the complex dynamic behavior of individual MSCs in the confined microflow. This finding offers an objective way to evaluate the homing ability of MSCs in an interendothelial-slit-like microenvironment.

Lab-on-a-chip systems for cancer biomarker diagnosis

Lab-on-a-chip (LOC) or micro total analysis system is one of the microfluidic technologies defined as the adaptation, miniaturization, integration, and automation of analytical laboratory procedures into a single instrument or "chip". In this article, we review developments over the past five years in the application of LOC biosensors for the detection of different types of cancer. Microfluidics encompasses chemistry and biotechnology skills and has revolutionized healthcare diagnosis. Superior to traditional cell culture or animal models, microfluidic technology has made it possible to reconstruct functional units of organs on chips to study human diseases such as cancer. LOCs have found numerous biomedical applications over the past five years, including integrated bioassays, cell analysis, metabolomics, drug discovery and delivery systems, tissue and organ physiology and disease modeling, and personalized medicine. This review provides an overview of the latest developments in microfluidic-based cancer research, with pros, cons, and prospects.

Label-free microfluidic cell sorting and detection for rapid blood analysis

Blood tests are considered as standard clinical procedures to screen for markers of diseases and health conditions. However, the complex cellular background (>99.9% RBCs) and biomolecular composition often pose significant technical challenges for accurate blood analysis. An emerging approach for point-of-care blood diagnostics is utilizing "label-free" microfluidic technologies that rely on intrinsic cell properties for blood fractionation and disease detection without any antibody binding. A growing body of clinical evidence has also reported that cellular dysfunction and their biophysical phenotypes are complementary to standard hematoanalyzer analysis (complete blood count) and can provide a more comprehensive health profiling. In this review, we will summarize recent advances in microfluidic label-free separation of different blood cell components including circulating tumor cells, leukocytes, platelets and nanoscale extracellular vesicles. Label-free single cell analysis of intrinsic cell morphology, spectrochemical properties, dielectric parameters and biophysical characteristics as novel blood-based biomarkers will also be presented. Next, we will highlight research efforts that combine label-free microfluidics with machine learning approaches to enhance detection sensitivity and specificity in clinical studies, as well as innovative microfluidic solutions which are capable of fully integrated and label-free blood cell sorting and analysis. Lastly, we will envisage the current challenges and future outlook of label-free microfluidics platforms for high throughput multi-dimensional blood cell analysis to identify non-traditional circulating biomarkers for clinical diagnostics.

Fluorescence lifetime image microscopy prediction with convolutional neural networks for cell detection and classification in tissues

Convolutional neural networks (CNNs) and other deep-learning models have proven to be transformative tools for the automated analysis of microscopy images, particularly in the domain of cellular and tissue imaging. These computer-vision models have primarily been applied with traditional microscopy imaging modalities (e.g. brightfield and fluorescence), likely due to the availability of large datasets in these regimes. However, more advanced microscopy imaging techniques could, potentially, allow for improved model performance in various computational histopathology tasks. In this work, we demonstrate that CNNs can achieve high accuracy in cell detection and classification without large amounts of data when applied to histology images acquired by fluorescence lifetime imaging microscopy (FLIM). This accuracy is higher than what would be achieved with regular single or dual-channel fluorescence images under the same settings, particularly for CNNs pretrained on publicly available fluorescent cell or general image datasets. Additionally, generated FLIM images could be predicted from just the fluorescence image data by using a dense U-Net CNN model trained on a subset of ground-truth FLIM images. These U-Net CNN generated FLIM images demonstrated high similarity to ground truth and improved accuracy in cell detection and classification over fluorescence alone when used as input to a variety of commonly used CNNs. This improved accuracy was maintained even when the FLIM images were generated by a U-Net CNN trained on only a few example FLIM images.

Phasor Analysis of Fluorescence Lifetime Enables Quantitative Multiplexed Molecular Imaging of Three Probes

The excited-state lifetime is an intrinsic property of fluorescent molecules that can be leveraged for multiplexed imaging. An advantage of fluorescence lifetime-based multiplexing is that signals from multiple probes can be gathered simultaneously, whereas traditional spectral fluorescence imaging typically requires multiple images at different excitation and emission wavelengths. Additionally, lifetime and spectra could both be utilized to expand the multiplexing capacity of fluorescence. However, resolving exogenous molecular probes based exclusively on the fluorescence lifetime has been limited by technical challenges in analyzing lifetime data. The phasor approach to lifetime analysis offers a simple, graphical solution that has increasingly been used to assess endogenous cellular autofluorescence to quantify metabolic factors. In this study, we employed the phasor analysis of FLIM to quantitatively resolve three exogenous, antibody-targeted fluorescent probes with similar spectral properties based on lifetime information alone. First, we demonstrated that three biomarkers that were spatially restricted to the cell membrane, cytosol, or nucleus could be accurately distinguished using FLIM and phasor analysis. Next, we successfully resolved and quantified three probes that were all targeted to cell surface biomarkers. Finally, we demonstrated that lifetime-based quantitation accuracy can be improved through intensity matching of various probe-biomarker combinations, which will expand the utility of this technique. Importantly, we reconstructed images for each individual probe, as well as an overlay of all three probes, from a single FLIM image. Our results demonstrate that FLIM and phasor analysis can be leveraged as a powerful tool for simultaneous detection of multiple biomarkers with high sensitivity and accuracy.

Label-free detection and enumeration of rare circulating tumor cells by bright-field image cytometry and multi-frame image correlation analysis

Identification and enumeration of circulating tumor cells (CTCs) in peripheral blood are proved to correlate with the progress of metastatic cancer and can provide valuable information for diagnosis and monitoring of cancer. Here, we introduce a bright-field image cytometry (BFIC) technique, assisted by a multi-frame image correlation (MFIC) algorithm, as a label-free approach for tumor cell detection in peripheral blood. For this method, images of flowing cells in a wide channel were continuously recorded and cell types were determined simultaneously using a deep neural network of YOLO-V4 with an average precision (AP) of 98.63%, 99.04%, and 98.95% for cancer cell lines HT29, A549, and KYSE30, respectively. The use of the wide microfluidic channel (400 μm width) allowed for a high throughput of 50 000 cells per min without clogging. Then erroneous or missed cell classifications caused by imaging angle differences or accidental misinterpretations in single frames were corrected by the multi-frame correlation analysis. This further improved the AP to 99.40%, 99.52%, and 99.47% for HT29, A549, and KYSE30, respectively. Meanwhile, cell counting was also accomplished in this dynamic process. Moreover, our imaging cytometry method can readily detect as few as 10 tumor cells from 100 000 white blood cells and was unaffected by the EMT process. Furthermore, CTCs from 8 advanced-stage cancer clinical samples were also successfully detected, while none for 6 healthy control subjects. Although this method is implemented for CTCs, it can also be used for the detection of other rare cells.

Electrodeformation of White Blood Cells Enriched with Gold Nanoparticles

The elasticity of white blood cells (WBCs) provides valuable insight into the condition of the cells themselves, the presence of some diseases, as well as immune system activity. In this work, we describe a novel process of refined control of WBCs’ elasticity through a combined use of gold nanoparticles (AuNPs) and the microelectrode array device. The capture and controlled deformation of gold nanoparticles enriched white blood cells in vitro are demonstrated and quantified. Gold nanoparticles enhance the effect of electrically induced deformation and make the DEP-related processes more controllable.

Acoustic Standing Wave Aided Multiparametric Photoacoustic Imaging Flow Cytometry

Photoacoustic imaging reveals great potential for the study of individual cells due to the rich imaging contrast for both label-free and labeled cells. However, previously reported photoacoustic imaging flow cytometry configuration suffers from inadequate imaging quality and challenge to distinguish multiple cells. In order to solve such issues, we propose a novel acoustic standing wave aided multiparametric photoacoustic imaging flow cytometry (MPAFC) system. The acoustic standing wave is introduced to improve the imaging quality and speed. Multispectral illumination along with cell geometry, photoacoustic amplitude, and acoustic frequency spectrum enables the proposed system to precisely identify multiple types of cells with one scanning. On the basis of the identification, elimination of melanoma cells, and targeted labeled glioma cells have been performed with an elimination efficiency of >95%. Additionally, the MPAFC system is able to image and capture melanoma cells at a lowest concentration of 100 cells mL^-1 in pure blood. Current results suggest that the proposed MPAFC may provide a precise and efficient tool for cell detection, manipulation, and elimination in both fundamental and clinical studies.

Non-invasive and label-free identification of human natural killer cell subclasses by biophysical single-cell features in microfluidic flow

Natural killer (NK) cells are indicated as favorite candidates for innovative therapeutic treatment and are divided into two subclasses: immature regulatory NK CD56^bright and mature cytotoxic NK CD56^dim. Therefore, the ability to discriminate CD56^dim from CD56^bright could be very useful because of their higher cytotoxicity. Nowadays, NK cell classification is routinely performed by cytometric analysis based on surface receptor expression. Here, we present an in-flow, label-free and non-invasive biophysical analysis of NK cells through a combination of light scattering and machine learning (ML) for NK cell subclass classification. In this respect, to identify relevant biophysical cell features, we stimulated NK cells with interleukine-15 inducing a subclass transition from CD56^bright to CD56^dim. We trained our ML algorithm with sorted NK cell subclasses (≥86% accuracy). Next, we applied our NK cell classification algorithm to cells stimulated over time, to investigate the transition of CD56^bright to CD56^dim and their biophysical feature changes. Finally, we tested our approach on several proband samples, highlighting the potential of our measurement approach. We show a label-free way for the robust identification of NK cell subclasses based on biophysical features, which can be applied in both cell biology and cell therapy.

A Review of Advanced Impedance Biosensors with Microfluidic Chips for Single-Cell Analysis

Electrical impedance biosensors combined with microfluidic devices can be used to analyze fundamental biological processes for high-throughput analysis at the single-cell scale. These specialized analytical tools can determine the effectiveness and toxicity of drugs with high sensitivity and demonstrate biological functions on a single-cell scale. Because the various parameters of the cells can be measured depending on methods of single-cell trapping, technological development ultimately determine the efficiency and performance of the sensors. Identifying the latest trends in single-cell trapping technologies afford opportunities such as new structural design and combination with other technologies. This will lead to more advanced applications towards improving measurement sensitivity to the desired target. In this review, we examined the basic principles of impedance sensors and their applications in various biological fields. In the next step, we introduced the latest trend of microfluidic chip technology for trapping single cells and summarized the important findings on the characteristics of single cells in impedance biosensor systems that successfully trapped single cells. This is expected to be used as a leading technology in cell biology, pathology, and pharmacological fields, promoting the further understanding of complex functions and mechanisms within individual cells with numerous data sampling and accurate analysis capabilities.

Autofluorescence of blood and its application in biomedical and clinical research

Autofluorescence of blood has been explored as a label free approach for detection of cell types, as well as for diagnosis and detection of infection, cancer, and other diseases. Although blood autofluorescence is used to indicate the presence of several physiological abnormalities with high sensitivity, it often lacks disease specificity due to use of a limited number of fluorophores in the detection of several abnormal conditions. In addition, the measurement of autofluorescence is sensitive to the type of sample, sample preparation, and spectroscopy method used for the measurement. Therefore, while current blood autofluorescence detection approaches may not be suitable for primary clinical diagnosis, it certainly has tremendous potential in developing methods for large scale screening that can identify high risk groups for further diagnosis using highly specific diagnostic tests. This review discusses the source of blood autofluorescence, the role of spectroscopy methods, and various applications that have used autofluorescence of blood, to explore the potential of blood autofluorescence in biomedical research and clinical applications.

FLIM as a Promising Tool for Cancer Diagnosis and Treatment Monitoring

Fluorescence lifetime imaging microscopy (FLIM) has been rapidly developed over the past 30 years and widely applied in biomedical engineering. Recent progress in fluorophore-dyed probe design has widened the application prospects of fluorescence. Because fluorescence lifetime is sensitive to microenvironments and molecule alterations, FLIM is promising for the detection of pathological conditions. Current cancer-related FLIM applications can be divided into three main categories: (i) FLIM with autofluorescence molecules in or out of a cell, especially with reduced form of nicotinamide adenine dinucleotide, and flavin adenine dinucleotide for cellular metabolism research; (ii) FLIM with Förster resonance energy transfer for monitoring protein interactions; and (iii) FLIM with fluorophore-dyed probes for specific aberration detection. Advancements in nanomaterial production and efficient calculation systems, as well as novel cancer biomarker discoveries, have promoted FLIM optimization, offering more opportunities for medical research and applications to cancer diagnosis and treatment monitoring. This review summarizes cutting-edge researches from 2015 to 2020 on cancer-related FLIM applications and the potential of FLIM for future cancer diagnosis methods and anti-cancer therapy development. We also highlight current challenges and provide perspectives for further investigation.

Live-cell imaging of glucose-induced metabolic coupling of β and α cell metabolism in health and type 2 diabetes

Type 2 diabetes is characterized by β and α cell dysfunction. We used phasor-FLIM (Fluorescence Lifetime Imaging Microscopy) to monitor oxidative phosphorylation and glycolysis in living islet cells before and after glucose stimulation. In healthy cells, glucose enhanced oxidative phosphorylation in β cells and suppressed oxidative phosphorylation in α cells. In Type 2 diabetes, glucose increased glycolysis in β cells, and only partially suppressed oxidative phosphorylation in α cells. FLIM uncovers key perturbations in glucose induced metabolism in living islet cells and provides a sensitive tool for drug discovery in diabetes.

Label-free identification of human coronary atherosclerotic plaque based on a three-dimensional quantitative assessment of multiphoton microscopy images

The rupture of coronary atherosclerotic plaque (CAP) and the resulting intracoronary thrombosis account for most acute coronary syndromes. Thus, the early identification and risk assessment of CAP is crucial for timely medical intervention. In this study, we propose a quantitative and label-free method for human CAP identification using multiphoton microscopy (MPM) and three-dimensional (3D) image analysis techniques. By detecting the intrinsic MPM signals, the microstructures of collagen and elastin fibers within normal and CAP-lesioned human coronary artery walls were imaged. Using a 3D gray level co-occurrence matrix method and 3D weighted vector summation algorithm, quantitative indicators that characterize the spatial texture and orientation features of the fibers were extracted. We demonstrate that these indicators show superior accuracy and repeatability over 2D texture features in CAP discrimination. Furthermore, by combining the 3D microstructural indicators, a support vector machine model that classifies CAP from the normal arterial wall with an accuracy of >97% was established. In conjunction with advances in multiphoton endoscopy, the proposed method shows great potential in providing a quantitative, label-free, and real-time tool for the early identification and risk assessment of CAP in the future.

A microfluidic single-cell array for in situ laminar-flow-based comparative culturing of budding yeast cells

To facilitate in situ comparative culturing of budding yeast cells in a precisely controlled microenvironment, we developed a microfluidic single-cell array (MiSCA) with 96 traps (16 rows × 6 columns) for single-cell immobilization. Through optimization of the distances between neighboring traps and the applied flow rates by using a hydraulic equivalent circuit of the fluidic network, yeast cells were delivered to each column of the array by laminar focused flows and reliably captured at the traps by hydrodynamic forces with about 90% efficiency of cell immobilization. Immobilized cells in different columns within the same device can then be cultured in parallel while being exposed to different media and compounds delivered by laminar flows. For biological validation of the comparative cell-culturing device, we used budding yeast that can express yellow fluorescent protein upon the addition of β-estradiol in cell-culturing medium. Experimental results show successful induction of fluorescence in cells immobilized in desired columns that have been dosed with β-estradiol. The MiSCA system allows for performing sets of experiments and control experiments in parallel in the same device, or for executing comparative experiments under well-defined laminar-perfusion conditions with different media, as well as in situ monitoring of dynamic cellular responses upon different analytical compounds or reagents for single-cell analysis.

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.

Fluorescence lifetime imaging with a megapixel SPAD camera and neural network lifetime estimation

Fluorescence lifetime imaging microscopy (FLIM) is a key technology that provides direct insight into cell metabolism, cell dynamics and protein activity. However, determining the lifetimes of different fluorescent proteins requires the detection of a relatively large number of photons, hence slowing down total acquisition times. Moreover, there are many cases, for example in studies of cell collectives, where wide-field imaging is desired. We report scan-less wide-field FLIM based on a 0.5 MP resolution, time-gated Single Photon Avalanche Diode (SPAD) camera, with acquisition rates up to 1 Hz. Fluorescence lifetime estimation is performed via a pre-trained artificial neural network with 1000-fold improvement in processing times compared to standard least squares fitting techniques. We utilised our system to image HT1080-human fibrosarcoma cell line as well as Convallaria. The results show promise for real-time FLIM and a viable route towards multi-megapixel fluorescence lifetime images, with a proof-of-principle mosaic image shown with 3.6 MP.

The label-free separation and culture of tumor cells in a microfluidic biochip

Circulating tumor cells (CTCs) from liquid biopsy have shown a strong correlation to the clinical outcome of cancer patients. The enumeration and cytological analysis of CTCs have attracted increasing efforts for cancer disease management amid immunotherapy and personalized medicine. However, both enumeration and cytological analysis are challenging due to the rarity of CTCs and the lack of integrated solutions for the minimal risk of cell loss in the course of CTC procurement. We report a simple microfluidic chip permitting a one-stop solution for streamlining the on-chip cell separation, capture, immunofluorescence assay and/or in situ culture of isolated cells devoid of risky manual steps. Our results showed effective trapping of single cells, doublets and cell lumps isolated from blood in the same device. On-chip immunostaining revealed normal cell morphology and the characterization of cell expansion uncovered an altered cell growth curve with a reduced lag phase as compared to the conventional culture despite closely matching cell growth rates. The cells were viable and functional for as long as 11 days inside our chip and cell migration was also readily observed, with lumps showing greater aggressiveness than single cells. With these results, we expect promising applications of our one-stop solution for liquid biopsy via CTCs.

Liquid biopsy technologies for hematological diseases

Since the discovery of circulating tumor cells in 1869, technological advances in studying circulating biomarkers from patients' blood have made the diagnosis of nonhematologic cancers less invasive. Technological advances in the detection and analysis of biomarkers provide new opportunities for the characterization of other disease types. When compared with traditional biopsies, liquid biopsy markers, such as exfoliated bladder cancer cells, circulating cell-free DNA (cfDNA), and extracellular vesicles (EV), are considered more convenient than conventional biopsies. Liquid biopsy markers undoubtedly have the potential to influence disease management and treatment dynamics. Our main focuses of this review will be the cell-based, gene-based, and protein-based key liquid biopsy markers (including EV and cfDNA) in disease detection, and discuss the research progress of these biomarkers used in conjunction with liquid biopsy. First, we highlighted the key technologies that have been broadly adopted used in hematological diseases. Second, we introduced the latest technological developments for the specific detection of cardiovascular disease, leukemia, and coronavirus disease. Finally, we concluded with perspectives on these research areas, focusing on the role of microfluidic technology and artificial intelligence in point-of-care medical applications. We believe that the noninvasive capabilities of these technologies have great potential in the development of diagnostics and can influence treatment options, thereby advancing precision disease management.

The up-to-date strategies for the isolation and manipulation of single cells

Due to the large cellular heterogeneity, the strategies for the isolation and manipulation of single cells have been pronounced indispensable in the fields of disease diagnostics, drug delivery, and cancer biology at the single-cell resolution. Herein, an overview of the up-to-date techniques for precise manipulation/separation and analysis of single-cell is accomplished, these include the various approaches for the isolation and detection of individual cells in flow cytometry, microfluidic systems, micromodule systems, and others. In addition, the advanced application of these protocols is discussed. In particular, a few designs are highlighted for visualization, non-invasion, and intelligentization in single cell analysis, i.e., imaging flow cytometry, label-free microfluidic platform, single-cell capillary probe, and other related techniques. At the present, the main barriers in the various schemes for single cell manipulation which limited their practical applications are their cumbersome construction and single-functionality. The future opportunities and outstanding challenges in the isolation/manipulation of single cells are depicted.

Microfluidic systems for hydrodynamic trapping of cells and clusters

Microfluidic devices have been widely applied to trapping and isolation of cells and clusters for controllable intercellular environments and high-throughput analysis, triggering numerous advances in disease diagnosis and single-cell analysis. Passive hydrodynamic cell trapping is one of the simple and effective methods that has been gaining attention in recent years. Our aim here is to review the existing passive microfluidic trapping approaches, including microposts, microfiltration, microwells, and trapping chambers, with emphasis on design principles and performance. We summarize the remarkable advances that hydrodynamic trapping methods offer, as well as the existing challenges and prospects for development. Finally, we hope that an improved understanding of hydrodynamic trapping approaches can lead to sophisticated and useful platforms to advance medical and biological research.

Nanoelectrochemical biosensors for monitoring ROS in cancer cells

Compared with normal cells, cancer or tumor cells have a specific microenvironment and apparently possess a relatively large amount of ROS/RNS, and their overexpression is one of the important reasons for tumor development and deterioration. Therefore, monitoring the changes of intracellular ROS/RNS can improve the awareness of the clinical manifestations of the disease, which will be beneficial for the early diagnosis of cancer and improving treatment efficiency. Herein, in this study we have exploited and constructed a novel strategy based on the SiC@C nanowire electrode for intracellular electrochemical analysis to monitor ROS levels in cancer or tumor cells. Firstly, the SiC@C nanowire electrode was utilized to detect the intracellular ROS radical changes involved in the relevant biological processes of cancer cells where fluorescent zinc nanoclusters were biosynthesized in situ in target cancer cells by using the intracellular microenvironment and specificity of these cancer cells. By combining a confocal fluorescence microscopy study simultaneously, our observations illustrate that accompanied by the apparent change of the intracellular ROS, these in situ biosynthesized fluorescent nanoclusters gradually accumulate inside the cytosolic area with the increase of the reaction time. Moreover, it is evident that the size of the SiC@C nanoelectrodes can match the single cell dimensions, and its unique high spatial resolution provides the possibility of relevant intracellular molecular detection. These nanoelectrochemical biosensors can be adopted to quantitatively determine the change of the ROS content in target single cells in the relevant biological microenvironment or during the in situ biosynthesis process, and are also beneficial for understanding the related mechanism of some specific biological processes including the in situ synthesis at the single cell level.

CD4+ versus CD8+ T-lymphocyte identification in an integrated microfluidic chip using light scattering and machine learning

T lymphocytes are a group of cells representing the main effectors of human adaptive immunity. Characterization of the most representative T-lymphocyte subclasses, CD4+ and CD8+, is challenging, but has a significant impact on clinical decisions. Up to now, T lymphocytes have been identified by quite complex cytometric assays, which are based on antibody labeling. However, a label-free approach based on pure biophysical evaluation at a single-cell level could enable the ability to distinguish between these subclasses. Here, we report a light-scattering approach, supported by accurate data mining, to evaluate cell biophysical properties on an integrated microfluidic chip. In order to perform single-cell optical analysis in viscoelastic fluids, such a chip is composed of mixing, alignment, readout and collection sections. In particular, we measured the cell dimensions, the refractive index of the cell nucleus, the refractive index of the cytosol, and the nucleus-to-cytosol ratio. Combining measurement of biophysical properties and machine learning allows us to both distinguish and count human CD4+ and CD8+ cells with an accuracy of 79%. An enhanced identification accuracy of 88% can be achieved by stimulating the cells with a selective anti-apoptotic protein, which results in increased biophysical differences between CD4+ and CD8+ cells. This approach has been successfully validated by analysis of samples that recapitulate physiological and pathological scenarios (CD4+/CD8+ ratios). The results are encouraging for the possible application of our approach in hematological clinical routines, as well as in diagnosis and follow-up of specific pathologies, such as human immunodeficiency virus (HIV) progression.

Label-free characterization of white blood cells using fluorescence lifetime imaging and flow-cytometry: molecular heterogeneity and erythrophagocytosis [Invited]

Blood cell analysis is one of the standard clinical tests. Despite the widespread use of exogenous markers for blood cell quantification, label-free optical methods are still of high demand due to their possibility for in vivo application and signal specific to the biochemical state of the cell provided by native fluorophores. Here we report the results of blood cell characterization using label-free fluorescence imaging techniques and flow-cytometry. Autofluorescence parameters of different cell types - white blood cells, red blood cells, erythrophagocytic cells - are assessed and analyzed in terms of molecular heterogeneity and possibilities of differentiation between different cell types in vitro and in vivo.

Liquid-core waveguide TCSPC sensor for high-accuracy fluorescence lifetime analysis

Liquid-core waveguide (LCW) has many advantages such as the elimination of optical artifacts typically exhibited in systems employing lenses and filters. However, due to the effect of temporal dispersion, LCWs are typically employed in steady-state fluorescence detection microsystems rather than in fluorescence lifetime measurement (FLM) systems. In this paper, we present a compact liquid-core waveguide time-correlated single-photon counting (LCW-TCSPC) sensor for FLM. The propagation of excitation within the LCW is analyzed both analytically and in simulations, with results in agreement with experimental characterization. Results reveal an optimal region within the LCW for highly accurate FLM. The proposed prototype achieves excellent excitation rejection and low temporal dispersion as a result of optimization of the propagation length of the excitation within the LCW. The prototype achieves a detection limit of 5 nM for Coumarin 6 in dimethyl sulfoxide with < 3% lifetime error. The techniques proposed for analyzing the LCW for TCSPC based FLM and prototype demonstration pave the way for developing high-performance fluorescence lifetime measurement for microfluidics and point-of-care applications. Graphical abstract A compact liquid-core waveguide time-correlated single-photon counting (LCW-TCSPC) sensor for fluorescence lifetime measurement (FLM) is presented. Results reveal an optimal propagation length region within the LCW for highly accurate FLM. The prototype achieves a detection limit of 5 nM for Coumarin 6 in dimethyl sulfoxide with < 3% lifetime error.

A microfluidic platform integrated with field-effect transistors for enumeration of circulating tumor cells

Circulating tumor cells (CTCs) are one of the promising cancer biomarkers whose concentrations are measured not only in the initial diagnostic stages, but also as treatment progresses. However, the existing methods for CTC detection are relatively time-consuming and labor-intensive. In this study, a new microfluidic platform integrated with field-effect transistors (FETs) and chambers for the trapping of CTCs was developed. This novel design could not only trap CTCs from whole blood samples, but also enumerate them via FET sensing of CTC-specific aptamer-CTC complexes. The FET output signal was experimentally found to increase with the increasing number of captured CTCs. More importantly, the enumeration of spiked CTCs in blood samples could be achieved in accordance with the signals measured on the FET devices. We therefore believe that this automated system could be a useful tool for enumeration of CTCs.

Label-Free Metabolic Classification of Single Cells in Droplets Using the Phasor Approach to Fluorescence Lifetime Imaging Microscopy

Characterization of single cell metabolism is imperative for understanding subcellular functional and biochemical changes associated with healthy tissue development and the progression of numerous diseases. However, single-cell analysis often requires the use of fluorescent tags and cell lysis followed by genomic profiling to identify the cellular heterogeneity. Identifying individual cells in a noninvasive and label-free manner is crucial for the detection of energy metabolism which will discriminate cell types and most importantly critical for maintaining cell viability for further analysis. Here, we have developed a robust assay using the droplet microfluidic technology together with the phasor approach to fluorescence lifetime imaging microscopy to study cell heterogeneity within and among the leukemia cell lines (K-562 and Jurkat). We have extended these techniques to characterize metabolic differences between proliferating and quiescent cells-a critical step toward label-free single cancer cell dormancy research. The result suggests a droplet-based noninvasive and label-free method to distinguish individual cells based on their metabolic states, which could be used as an upstream phenotypic platform to correlate with genomic statistics. © 2018 International Society for Advancement of Cytometry.

High-throughput microfluidic single-cell trapping arrays for biomolecular and imaging analysis

Single-cell analysis is of critical importance in revealing population heterogeneity, identifying minority sub-populations of interest, as well as discovering unique characteristics of individual cells. Microfluidic platforms work at the scale comparable to cell diameter and is suitable for single-cell manipulation. Here we present a microfluidic trapping array which is able to rapidly and deterministically trap single-cells in highly-packed microwells. This chapter first describes the design and fabrication protocols of the trapping array, and then presents its two representative applications: single-cell mRNA probing when integrated with a dielectrophoretic nanotweezer (DENT), and live-cell real-time imaging when combined with fluorescence lifetime imaging microscopy (FLIM). As the single-cell trapping efficiency is determined by the channel design instead of the flow rate, this trapping array can be coupled with different microfluidic sample processing units with different flow rates for various single-cell analyses.

Fluorescence lifetime shifts of NAD(P)H during apoptosis measured by time-resolved flow cytometry

Autofluorescence from the intracellular metabolite, NAD(P)H, is a biomarker that is widely used and known to reliably screen and report metabolic activity as well as metabolic fluctuations within cells. As a ubiquitous endogenous fluorophore, NAD(P)H has a unique rate of fluorescence decay that is altered when bound to coenzymes. In this work we measure the shift in the fluorescence decay, or average fluorescence lifetime (1–3 ns), of NAD(P)H and correlate this shift to changes in metabolism that cells undergo during apoptosis. Our measurements are made with a flow cytometer designed specifically for fluorescence lifetime acquisition within the ultraviolet to violet spectrum. Our methods involved culture, treatment, and preparation of cells for cytometry and microscopy measurements. The evaluation we performed included observations and quantification of the changes in endogenous emission owing to the induction of apoptosis as well as changes in the decay kinetics of the emission measured by flow cytometry. Shifts in NAD(P)H fluorescence lifetime were observed as early as 15 min post‐treatment with an apoptosis inducing agent. Results also include a phasor analysis to evaluate free to bound ratios of NAD(P)H at different time points. We defined the free to bound ratios as the ratio of ‘short‐to‐long’ (S/L) fluorescence lifetime, where S/L was found to consistently decrease with an increase in apoptosis. With a quantitative framework such as phasor analysis, the short and long lifetime components of NAD(P)H can be used to map the cycling of free and bound NAD(P)H during the early‐to‐late stages of apoptosis. The combination of lifetime screening and phasor analyses provides the first step in high throughput metabolic profiling of single cells and can be leveraged for screening and sorting for a range of applications in biomedicine. © 2018 The Authors. Cytometry Part A published by Wiley Periodicals, Inc. on behalf of International Society for Advancement of Cytometry.

An integrated microfluidic platform for size-selective single-cell trapping of monocytes from blood

Reliable separation and isolation of target single cells from bodily fluids with high purity is of great significance for an accurate and quantitative understanding of the cellular heterogeneity. Here, we describe a fully integrated single-blood-cell analysis platform capable of size-selective cell separation from a population containing a wide distribution of sizes such as diluted blood sample and highly efficient entrapment of single monocytes. The spiked single U937 cells (human monocyte cell line) are separated in sequence by two different-sized microfilters for removing large cell clumps, white blood cells, and red blood cells and then discriminated by dielectrophoretic force and isolated individually by downstream single-cell trapping arrays. When 2% hematocrit blood cells with a final ratio of 1:1000 U937 cells were introduced under the flow rate of 0.2 ml/h, 400 U937 cells were trapped sequentially and deterministically within 40 s with single-cell occupancy of up to 85%. As a proof-of-concept, we also demonstrated single monocyte isolation from diluted blood using the integrated microfluidic device. This size-selective, label-free, and live-cell enrichment microfluidic single blood-cell isolation platform for the processing of cancer and blood cells has a myriad of applications in areas such as single-cell genetic analysis, stem cell biology, point-of-care diagnostics, and cancer diagnostics.

A simple microdevice for single cell capture, array, release, and fast staining using oscillatory method

Microchips that perform single cell capture, array, and identification have become powerful tools for single cell studies, which can reveal precise underlying mechanisms among bulk cell populations. However, current single cell capture and on-chip immunostaining methods consume more time and reagent than desired. To optimize this technology, we designed a novel trap structure for single cell capture, array, and release, and meanwhile an oscillatory method was used to perform rapid on-chip cell immunostaining. The trap structure array used equal distribution of lateral flow to achieve single cell array in high velocity flows and decrease the risk of clogging. A length of glass capillary with a sealed bubble was inserted into the outlet so that it could act in a manner analogous to that of a capacitor in an RC circuit. By applying one periodic air pressure to the inlet, oscillation motion was generated, which significantly enhanced the on-chip reaction efficiency. In addition, the oscillation performance could be easily regulated by changing the length of the capillary. The trapped cells could maintain their positions during oscillation; hence, they were able to be tracked in real time. Through our trap microchip, 12 μm microbeads were successfully trapped to form a microarray with a capture efficiency of ∼92.7% and 2 μm microbeads were filtered. With an optimized oscillation condition (P_push = 0.03 MPa, f = 1 Hz, L = 3 cm), fast on-chip immunostaining was achieved with the advantages of less time (5 min) and reagent (2 μl) consumption. The effectiveness of this method was demonstrated through quantitative microbead and qualitative Caco-2 cell experiments. The device is simple, flexible, and efficient, which we believe provides a promising approach to single cell heterogeneity studies, drug screening, and clinical diagnosis.