Abstract
Cells are basic structural and functional units of living organisms. Understanding the composition, structure and function of cells, and exploring cellular activities, are quite important for the cognition of phenomena and rules of life. Microfluidics, combined with advanced molecular, imaging and bioinformatics techniques, constitute a robust ‘toolbox’ and revolutionize the way for cell biology researches. In microfluidic systems, small amounts of fluids are manipulated using precisely designed channels with dimensions at micrometer level. Various chemical and biological processes can be transferred and integrated in a small single device, achieving multiple chemical and biological functions. Microfluidic technology displays a number of unique merits over conventional approaches, and has been extensively applied to various fields of cell research. In this chapter, we will review the recent developments and outstanding achievements of microfluidic technology in cell researches. Based on the cell study procedure, the main content is divided into four parts: cell culture, cell manipulation , cell stimulation and cell analysis. This review will also discuss the challenges and directions of microfluidic-based cell analysis, providing important references and ideas for the development of biological and medical researches and applications.
Access provided by CONRICYT-eBooks. Download chapter PDF
Similar content being viewed by others
Keywords
2.1 Introduction
Cells are basic structural and functional units of living organisms. Understanding the composition, structure and function of cells, and exploring cellular activities, are quite important for the cognition of activity rules and phenomena of life. Cells have small size, low amount of contents and diverse species. And in organisms, cells are located in complex microenvironments and subjected to multiple cues that vary in time and space, including temperature, oxygen concentration, gradients of cytokines and signaling molecules, mechanical forces, and interactions with extracellular matrix (ECM) and other cells [1,2,3]. The microenvironments are significant for maintaining cellular functions [4, 5]. Therefore, it is highly important and desirable to develop advanced technologies that enable precise cell manipulation , physiologically relevant microenvironment simulation, as well as sensitive, selective, high-throughput and reliable cell analysis.
Since the 1990s, microfluidic technology has experienced explosive developments, and gradually become an important tool for cell research. In microfluidic systems, small (10−9–10−18 L) amounts of fluids are manipulated using precisely designed channels with dimensions of tens to hundreds micrometres [6, 7]. Various chemical and biological processes, such as synthesis, reaction, separation, detection, and cell culture , cell isolation , cell lysis and cell analysis, can be integrated in a single device to achieve multiple chemical and biological functions [8,9,10]. Microfluidic technology displays a number of unique merits over conventional approaches, which promote the applications in cell researches [11,12,13]. The dimensions of microfluidic channels are comparable to the sizes of cells, thus facilitating precise cell manipulation . Microchannels reduce sample consumption, avoid sample dilution, and allow rapid mass and heat transfer [14]. These features contribute to highly sensitive cell analysis. And due to the size effect, microfluidic fluids at low flow rate are laminar, which enables precise fluid control [15], and can be applied to partitioned channel modification [16], concentration gradient establishment [17] and regional cell stimulation [18]. A variety of complex microstructures can be designed and fabricated on microfluidic devices, allowing better control of multiple biological cues and more physiologically relevant mimic of cellular microenvironments . The ability of integration is a prominent advantage of microfluidic technology. Microfluidics not only enable the assembly of multiple cell analysis units on a single device, but also can integrate with diverse cell detecting techniques (such as optical and electrical detection, mass spectrometry), thus facilitating comprehensive cell researches [19,20,21]. For example, combining microvalves , micropumps and microchambers, an automatic single-cell analysis pipeline was established on a microfluidic device, which incorporated cell culture, precise cell stimulation, live-cell microscopy, computerized cell tracking, on-chip staining of key proteins and subsequent retrieval of cells for high-throughput gene expression analysis [22]. Using droplet-based microfluidics [23, 24] or microarrays [25, 26], high throughput cell analysis can be achieved to improve research efficiency and shorten analysis time. Owing to these advantages, recently microfluidic technology has been applied to various fields of cell researches, such as cell culture [27, 28], cell sorting [29], cancer research [30], stem cell research [31], clinic diagnosis [32, 33], drug screening [34, 35] and tissue engineering [36].
In this chapter, we will introduce the recent developments and outstanding achievements of microfluidic technology in cell researches. Based on the cell study procedure, the main content is divided into four parts: cell culture, cell manipulation , cell stimulation and cell analysis. This chapter will also discuss the challenges and directions of microfluidics in cell research, providing important reference and ideas for the development of biological and medical research and application.
2.2 Cell Culture
Cell culture in vitro is the cornerstone of cell biology research. In living organisms, cells are located in complex microenvironments and subjected to multiple cues, including physicochemical properties such as temperature, oxygen concentration, pH, osmotic pressure, stimulation factors such as gradients of cytokines and signaling molecules, mechanical forces, and interactions with ECM and other cells [37]. Compared to conventional cell culture methods using petri dishes or culture plates, microfluidic devices have many unique advantages [38]. Micro-sized channels are comparable to in vivo cellular microenvironment , and enable precise regulation of cell number, cell density and spatial location; controllable fluids allow cell culture under flow condition and precise cell stimulation ; using microstructures or hydrogels , three dimensional (3D) cell culture and cell co-culture can be achieved, which maintain cell-cell, cell-ECM interactions and are more physiologically relevant; microfluidic technology also facilitates parallel and automated cell culture, improving throughput and reproducibility of cell researches [27, 39].
In microfluidic cell study, how to develop more physiologically relevant cell culture models and make subsequent biological and medical researches more realistic and reliable, is an important research topic. We will review recent progresses of cell culture on microfluidics in this section, according to three parts: 3D cell culture, cell co-culture and tissues/organs-on-chips.
2.2.1 3D Cell Culture
The majority of microfluidic cell-culture systems are 2D cell culture , in which cells are grown as a monolayer on a flat substrate surface (e.g., glass or plastic). Although it is simple to handle, the 2D systems have certain limitations in mimicking the in vivo cellular microenvironment , and lack diffusion-limited distribution of soluble factors and cell-cell, cell-ECM interactions [40]. The transition from 2D to 3D cell culture is an important step for better mimicking the in vivo microenvironment [41, 42]. Owing to the complex microstructures and well-controlled parameters, microfluidics provide a versatile platform for 3D cell culture, which offer more physiologically relevant cellular morphology and phenotype, and promote metabolic activity and cellular functionality [43, 44].
The most common strategy for microfluidic 3D cell culture is to embed cells in 3D hydrogel scaffolds, such as matrigel , collagen, agarose and synthetic hydrogels [45]. Hydrogels enable cell-ECM interactions and permit diffusive permeability of oxygen, nutrients and metabolites to encapsulated cells [46]. Sung et al. developed a microfluidic platform to examine the influence of 2D and 3D culture of human mammary fibroblasts (HMFs) on the invasive transition of breast cancer cells (MCF-DCIS) [47]. MCF-DCIS encapsulated in the mixture of collagen and matrigel were co-cultured with HMFs either embed in 3D matrix or grown on 2D surface. Results demonstrated that HMFs cultured in 3D secreted more paracrine signaling molecules and intensified the promotion of the invasive progression through the HGF/c-Met interaction. Combined with high-throughput droplet-based microfluidics, a large number of monodisperse 3D liver model were formed by controlled assembly of hepatocytes and fibroblasts in core–shell hydrogel scaffolds [48]. These droplets were able to be cultured for long periods of time and showed enhanced liver-specific functions. Advances in hydrogel materials promote the development of 3D cell culture with better in vivo relevance. Donald et al. developed an injectable, interconnected microporous gel scaffold assembled from monodisperse microgels generated by microfluidic droplet technique (Fig. 2.1a) [49]. In vitro, cells incorporated during scaffold formation proliferated and formed extensive 3D networks within 48 h. In vivo, the scaffold facilitated cell migration that resulted in rapid cutaneous-tissue regeneration and tissue-structure formation within five days. 3D cell culture can also be realized by gel-free microfluidic systems, such as hanging-drop network [50, 51], micro-well array [52] and dielectrophoretic patterning [53].
2.2.2 Cell Co-culture
Cell-cell interactions are very important for the development and function of multicellular organisms. They allow cells to communicate with each other, respond to signals in microenvironment and regulate basic cellular functions such as survival, apoptosis, migration, proliferation, and differentiation [54, 55]. Cell-cell interactions occur through multiple mechanisms, including direct cell contact, diffusion of soluble factors, electrical signal transmission and transduction of mechanical cues through ECM [56]. Efforts have been made to investigate the interaction mechanisms and their roles in physiological homeostasis and disease states. Microfluidics, as a flexible and reliable technique which is capable of co-culturing multiple cell types in precisely defined positions and delivering biochemical and biophysical stimuli in a spatiotemporal controllable manner, has been extensively developed and widely applied to cell-cell interaction study [57, 58].
Different intercellular interaction mechanisms have been investigated in various microfluidic cell co-culture systems, which can be divided into two categories: contact and non-contact approaches [59]. The non-contact microchips utilize barriers such as hydrogels [60, 61], semi-permeable membranes [62], porous films [63], pressure-controlled valves [64] and narrow channels [65] to separately culture cell in different regions. These microfluidic systems eliminate the influence of direct cell contact and can be used for the study of paracrine signaling and endocrine signaling. Contact approaches, such as microfluidic droplet co-culture [66], microcontact printing [67] and stencil-based methods [68, 69], culture cells in direct contact and are applicable to all interaction mechanisms, especially gap junction signaling and juxtacrine signaling. Selective cell adhesion on specific functionalized substrates was an alternative method for defined cell co-culture [70].
Cells in microfluidic systems can be co-cultured in 2D, 3D or single cell manner. Combining micropatterned surfaces with microfluidic channels, neurons and astrocytes were cultured in defined locations and communicated with each other through grooves [71]. Pharmacological agents were delivered through microchannels. This device analyzed neuron–astrocyte interactions under both healthy and pathophysiological conditions, and found that calcium dynamics in astrocytes could be modulated by the interactions with neurons. Shin et al. [72] developed a hydrogel-incorporating microfluidic cell culture assay, which facilitated the interaction of cells in 3D ECM scaffolds. It could be used in various applications, including angiogenesis and cancer metastasis, and provide new insights into how biochemical and biophysical factors regulate interactions between populations of different cell types (Fig. 2.1b). Dura et al. [73] described a microfluidic platform that achieved high-throughput single-cell pairing of lymphocytes with a defined contact time, enabling pairwise-correlated multiparametric profiling of lymphocyte interactions over hundreds of pairs in a single experiment. This platform was applied to characterize early activation dynamics of CD8 T cells and investigated the extent of heterogeneity in T-cell activation and the correlation of multiple readouts.
2.2.3 Tissues/Organs-on-Chips
Owing to the progress in 3D cell culture and cell co-culture , as well as the precisely controlled fluid flow and mechanical force, tissue/organ-on-chip microsystems have been extensively developed on microfluidic devices. In tissues/organs-on-chips, living cells are culture in well-organized microchambers, with well-defined physiological factors and mechanical cues, which can not only reconstitute multicellular architectures and microenvironment of living human tissues or organs, but also recapitulate their physiological functions and responses. These systems are more human relevant and cost-effective than animal models, and the optical transparency of microdevices enable the direct real-time imaging and analysis of cellular activities [74, 75]. Tissues/organs-on-chips have great potential to study basic mechanisms of organ physiology and disease such as cancers, and are highly applicable for preclinical drug discovery [76, 77].
Various tissue/organ-on-chip models have been developed, such as blood vessels [78, 79], brain [80], liver [81, 82], lung [83, 84], kidney [85, 86], heart [87, 88], bone [89] and muscle [90]. Microfluidic chip is quite suitable for the development of blood vessel-on-a-chip, because of its fluid perfusion ability which facilitates blood mimic and introduces shear stresses, and the ease of gradient generation for angiogenesis assays [44]. Zheng and co-workers [91] engineered living microvascular networks in type I collagen on a microfluidic scaffold. With long-term (one to two weeks) culture, the microvasculature-on-a-chip emerged appropriate endothelial morphology and barrier functions. This platform could be used to investigate angiogenic remodeling, interactions between endothelial cells and perivascular cells, and interactions between blood components and endothelium with flow. Reconstituting the organ-level functions is the major goal of organs-on-chips study. Ingber’s group developed a human ‘breathing’ lung-on-a-chip which reproduced key structural, functional, and mechanical properties of the human alveolar-capillary interface (Fig. 2.1c) [92, 93]. This bioinspired microdevice demonstrated complex organ-level responses to bacteria and inflammatory cytokines introduced into the alveolar space, and could be used to investigate the role of mechanical breathing motions in lung disease. In follow-up study, this group reconstituted a small airway-on-a-chip containing a differentiated, mucociliary bronchiolar epithelium and an underlying microvascular endothelium that experienced fluid flow (Fig. 2.1d) [94]. This platform achieved greater robustness and fidelity in modeling of pulmonary diseases and recapitulation of lung inflammatory responses in vitro. As complex heterogeneous diseases, cancer in vitro models have also been intensively studied [95, 96]. Alexandre et al. reported a tumor-on-a-chip system where incorporation of tumor-like spheroids into a microfluidic channel permitted real-time analysis of nanoparticle (NP) accumulation at physiological flow conditions [97]. Taking advantage of the integration feature of microfluidics, ‘human-on-a-chip’ models which interconnect different organ-on-chip compartments through microfluidic circulatory systems have been investigated currently. It can provide more complete physiological biomimicry and become an important direction in further microfluidic study [75, 98].
2.3 Cell Manipulation
Cell manipulation plays an important role in basic cell biology study, drug screening, disease diagnosis and therapy. Because of the unique advantages, microfluidics was an excellent practical technique which provides incomparable possibilities to manipulate cells in an automated, reproducible, fast and efficient way. Various microfluidic techniques have been developed to manipulate cell precisely for diverse biological researches, such as microstructures, integrated valves and pumps, droplet encapsulation, electrokinetic operations , affinity-based surface patterning and free flow manipulation [99, 100]. Different techniques can be integrated to improve performance and functionalities within a single chip. In the next three sections, we mainly focus on the microstructures, electrokinetic operations, and free flow manipulation, and provide some recent examples. Droplet-based microfluidics will be summarized in Chap. 7.
2.3.1 Microstructures
Microstructures, such as microwells, microbarriers and microtraps, can be precisely designed and applied to cell capture , pairing, patterning and subsequent cell culture as well as other biological study [101,102,103,104]. This approach is high-throughput, high-efficient and ease of operation, which has been extensively used in both multicellular and single-cell systems. Chung et al. [105] developed a microfluidic embryo-trap array that could rapidly order and vertically orient hundreds of embryos, and this platform was used to quantitatively analyze multiple morphogen gradients in the dorsoventral patterning system (Fig. 2.2a). Sarioglu et al. [106] introduced a Cluster-Chip, which contained a series of triangular pillars to differentiate CTC clusters from single cells in blood. It was used to isolate CTC clusters from unprocessed patient blood samples with high sensitivity, allowing for downstream molecular and functional assays. Integrating the microwell array with microfluidic valve and pump systems, Lecault et al. [107] developed a longer-term mammalian cell culture platform which was able to immobilize nonadherent cells during automated medium exchange and recover the cells for subsequent analysis. This platform was then applied to high-throughput investigation of hematopoietic stem cell proliferation at the single-cell level.
2.3.2 Free-Flow Manipulation
The free flow cell manipulation can be divided into passive and active strategies [108]. Passive strategies use rationally designed microfluidic structures to control cell positions, such as pinched flow [109] and deterministic lateral displacement [110]; Active strategies use actuators to manipulate cells based on their electrical, magnetic and mechanical properties, such as dielectrophoresis [111], magnetophoresis [112], acoustophoresis [113] and optical tweezers [114]. These techniques can also be integrated to improve the performance [108]. Warkiani et al. [115] developed a label-free spiral microfluidic device to allow size-based cell isolation by taking advantage of dean migration and inertial focusing in curvilinear microchannels (Fig. 2.2b). Karabacak et al. [116] presented a CTC-iChip using deterministic lateral displacement, inertial focusing and magnetophoresis to isolate rare circulating tumor cells (CTCs) from blood samples. This device achieved an average of 3.8-log depletion of white blood cells at a rate of 8 ml whole blood/h and a cancer cell yield of 97 ± 2.7%. Collins et al. [117] utilized surface acoustic waves at high frequency to create a 2D acoustic force field with an inter-nodal spacing of the same order as the cell dimensions (Fig. 2.2c). This device was applied to the patterning of multiple spatially separated single cells with one cell per acoustic well.
2.3.3 Electrokinetic Operations
Owing to the feasibility of integrating microelectrodes in microfluidic chips, electrokinetic forces stemming from the electric field have been widely applied to microfluidic cell manipulation [118]. Electrokinetic manipulations include several categories: electrophoresis [119], dielectrophoresis [120], electroosmosis [121], electroporation [122], electrofusion [123] and electric cell lysis , and these techniques have all been realized on microfluidic chips.
Dielectrophoresis (DEP) refers to the movement of cells caused by a force, generated due to polarization differences between cells and the medium under a non-uniform electric field. It has been used to move, separate and position cells [124]. Tsutsui et al. developed a quick and active method based on positive DEP traps to pattern embryonic stem cells on PEG hydrogels [53]. Mazutis et al. integrated microdroplet generation and DEP sorting on one microfluidic platform for the high-throughput analysis and sorting of single cells (Fig. 2.3a) [125]. Compartmentalization of single cells in droplets enabled the analysis of proteins secreted by cells, and fluorescence-activated droplet sorting by electrophoretic force enabled target cell enrichment.
Exposing a cell to a strong electric field pulses results in electroporation—the formation of nanoscale aqueous pores in the cell membrane. These permeable structures provide a pathway for diffusive transport of molecules which are physiologically membrane impermeable [126]. Electroporation on microfluidics alleviates heat effect, allows real-time monitoring of cellular response and enables single-cell manipulation [127]. These devices have been applied to cell transfection. Garcia et al. introduced a rapid microfluidic assay to determine the critical electric field threshold required for inducing bacterial electroporation [128]. Qu et al. utilized a droplet electroporation microfluidic platform for nuclear transformation of microalgae, which showed a remarkably higher transformation efficiency than bulk phase electroporation [129]. Kang et al. presented a microfluidic device that coupled long-term cell culture on the device and repeated temporal transfection by localized electroporation (Fig. 2.3b) [130]. This platform enabled on-chip differentiation of neural stem cells and transfection of postmitotic neurons with a green fluorescent protein plasmid.
Cell fusion is an important method to achieve nucleus transfer, hybridoma and epigenetic reprograming of somatic cells [131]. Due to the ability of precisely controlling cell positions, electrofusion in microfluidic devices shows remarkable advantages [132]. Skelleyet al. [133] presented a microfluidic device containing a dense array of weir-based passive hydrodynamic cell traps, which could immobilize and pair thousands of cells at once (Fig. 2.3c). The device is compatible with both chemical and electrical fusion protocols, with better performance of electrical fusion. 50% properly paired and fused cells were achieved over the entire device, fivefold greater than the commercial electrofusion chamber . This platform was successfully applied to the reprogramming in hybrids between mouse embryonic stem cells and mouse embryonic fibroblasts.
2.4 Cell Stimulation
In cellular microenvironment, cells are subject to multiple cues that vary in time and space, including physical conditions such as temperature, oxygen, pH, gradients of cytokines and secreted proteins from neighboring cells, and mechanical forces. Investigating cellular responses to multiple stimulations will facilitate better understanding of biological pathways, cell-fate decisions and tissue functionalities. Microfluidics is a robust technology that enables controlled perturbation of the cellular environment spatiotemporally in vitro. By precise flow control and well-defined microstructures, it is easy to build concentration gradients and mechanical conditions in microfluidic devices. In this section, we will discuss the recent developments of cell stimulation studies in microfluidics, from three aspects: flow control, gradient generation and mechanical stimuli.
2.4.1 Flow Control
Microfluidic devices facilitate precise flow control, owing to the unique features of flow at micrometer length scale and the feasible integration of valves and pumps. The microfluidic flows are always laminar, allowing for highly predictable fluid dynamics and molecular diffusion kinetics . Laminar flow can route different fluid to specific region in a well-ordered manner, which can alter liquid-phase environment over distances and be applied to controlled cell stimulation in a high spatial and temporal resolution [15]. Lucchetta et al. used microfluidic laminar flow to create temperature differences by flowing two converging aqueous streams around an embryo, each at a controlled temperature (Fig. 2.4a) [18]. This platform was applied to differentially control the rate of development in the anterior and posterior halves of the embryo. Similar microfluidic chips were used to deliver small molecules to selected subcellular microdomains [134], for the study of mitochondrial movement [135] or neurite injury [136].
Integrated valves or pumps, which are feasible to be incorporated into elastomeric microfluidic devices, lead to flexible, automated and high-throughput flow control with unparalleled temporal and spatial precision [137,138,139]. Diverse microfluidic designs with valves and pumps have been developed for various biological researches, including the precisely controlled cell stimulation . For example, Shen et al. reported a microfluidic device that integrated with pneumatic valves and peristaltic pumps to control fluid exchange parallelly and pump conditioned mediums towards the cells that exposed to toxin (Fig. 2.4b) [140]. This platform was used to investigate the roles of Dickkopf-1 in cell susceptibility to anthrax toxin. Taylor et al. developed a microfluidic platform that combined programmable on-chip mixing and perfusion with high-throughput image acquisition and processing [141]. Single-cell network responses under hundreds of combined genetic perturbations and time-varying stimulant sequences were investigated on this platform for dynamic analysis of MAPK signaling.
2.4.2 Gradient Generation
In cellular microenvironment, cells are always exposed to concentration gradients of biochemical signals such as growth factors, hormones and chemokines, which regulate many biological processes including cell differentiation, cell migration , immune responses, angiogenesis and cancer metastasis [142]. Thanks to the ability of accurate and precise flow control, it is convenient to establish concentration gradients in microfluidic systems to mimic the stimulations in microenvironment and study cellular behaviors [143]. Recently, a number of microfluidics-based gradient devices have been developed and used for different cellular studies. These devices can be categorized into two groups: flow-based gradient generators and free-diffusion-based gradient generators [144].
Flow-based gradient generators utilize laminar flows in microfluidic channels and can be divided into two design mechanisms. In Y-junction, T-junction or flow splitter microfluidic devices, streams of fluids composed of different chemical species or concentrations are brought together where the solutes diffuse across the interface as they flow down the microchannel, thus concentration gradients perpendicular to the flow direction can be established [145]. Lin et al. developed a ‘‘Y’’ type microfluidic device to generate concentration gradients of chemokine CCL19 and CXCL12 for T cell chemotaxis investigation [146]. In the other design mechanism, which refers to “Christmas tree”, solutions of different concentrations are introduced from the inlet, and then repeatedly split, mixed in serpentine channel regions and recombined to produce multiple streams of mixed solutions having different proportions of input solutions. These streams can be brought together into a single wide channel to generate a gradient across the channel or introduced into separate channels for parallel cell stimulation with defined concentration gradients [145]. Jeon et al. used “Christmas tree” device to generate linear or complex gradients of interleukin-8 in a single channel to investigate neutrophil chemotaxis [17]. Similar devices were also utilized to study bacterial chemotaxis [147], to investigate neural stem cell differentiation [148], and to generate gradients of substrate-bound laminin to orient axonal specification of neurons [149]. Our group [150] developed an integrated microfluidic device for high-throughput drug screening with an online mass spectrometry analysis (Fig. 2.5a). “Christmas tree” mixer network was used to generate drug gradient, and cells in the culture chambers were stimulated with different drug concentrations separately. Drug absorption and cytotoxicity were then characterized on this platform.
In free-diffusion-based gradient generators, a gradient across a given area is established as the molecules diffuse from high concentration “source” to low concentration “sink” [151]. Porous materials such as hydrogels and semi-permeable membranes are often used to form concentration gradients between sources and sinks [152]. For example, Haessler et al. developed a microfluidic device that allowed rapid establishment of stable gradients in 3D matrices to show that dendritic cells chemotaxis in 3D could respond to CCR7 ligand gradients (Fig. 2.5b) [153]. Nguyen et al. designed blood vessels-on-a-chip by lining endothelial cells in a cylindrical channel encapsulated within a 3D collagen hydrogel [154]. Emanating from a parallel source channel, gradients of angiogenic factors were established in hydrogel and used to stimulate endothelial cells and recapitulate the angiogenic sprouting in vitro. Apart from porous gels, gradient can also be formed across a region that connects to the source and sink with microchannels . The interconnecting channels have low height, narrow width and long length, thus creating a high fluidic resistance while minimizing convective flow [152]. Chabaud et al. presented a microfluidic device composed of two fluidic chambers connected by migration microchannels [155]. Perpendicular drug gradients along migration channels were established and applied to investigate the migration and antigen capture processes of dendritic cells. Boneschansker et al. employed two large-scale arrays of microchannels to connect the central main channel with two side channels (Fig. 2.5c) [156]. Cell traps were integrated in the central channel to load precise numbers of leukocytes. Chemokine gradients were developed in the main channel by filling one side channel with chemokines and the other with buffer. This device facilitated the quantification of leukocyte migration patterns at single-cell level.
2.4.3 Mechanical Stimuli
Apart from physical and biochemical signals, cells in vivo are also subject to multiple mechanical cues in microenvironment, including shear stress, interstitial flow, substrate strain, confinement, compression and matrix stiffness. These mechanical processes are important for cell growth, migration, differentiation, apoptosis, and dysfunctional mechanotransduction can lead to numerous diseases [157, 158].
Microfluidics offers an excellent strategy for the study of cellular responses to mechanical stimuli. As blood flows through a vessel, it exerts shear stress on endothelial cells. The control of fluidic flow in microfluidics allows to study the impacts of shear stress on cellular morphology, behavior and functions [159, 160]. Sundd et al. integrated a microfluidic device with quantitative dynamic footprinting microscopy to study the mechanisms of neutrophil rolling at high shear stress [161, 162]. They indicated that step-wise peeling of “slings” at the front of rolling cells is responsible for the rolling of neutrophils. Miura et al. fabricated a multilayer microfluidic device to study the microvilli formation in placental transfer process (Fig. 2.6a) [163]. Abroad range of fluid shear stress was applied to placental barrier cells, and cellular responses were monitored. Results showed that the fluid shear stress serves as a trigger for microvilli formation in human placental trophoblastic cells, and the molecular mechanisms were also intensively investigated.
Substrate strain is another crucial mechanical force that can manipulate cellular alignment and tissue functions [164]. By incorporating flexible substrates into microfluidic platforms, devices have been developed to study the effect of mechanical stretch on the cells cultured on the deformable substrate. Hsieh et al. developed microfluidic chip which consisted of a concentric circular hydrogel pattern and a flexible PDMS membrane (Fig. 2.6b) [165]. A range of gradient static strains on cells can be generated by compressing the cell-laden hydrogels with the membrane, and cells were elongated with the increase of strain. In previously introduced example, by applying and releasing vacuum in two larger, lateral microchambers, PDMS membrane with the adherent tissue layers were stretched and recoiled [93]. This “breathing” human lung-on-a-chip could replicate the dynamic mechanical distortion of the alveolar-capillary interface caused by breathing movements.
Compressive stress on cells was also realized in microfluidic devices. Kollmannsperger et al. utilized the compression-induced cell deformation for rapid and efficient transfer of trisNTA probe into living cells (Fig. 2.6c) [166]. Cells were compressed through micrometre constrictions in a microfluidic device, causing the formation of transient holes in the plasma membrane. Si et al. developed an air-driven microfluidic device to apply a compressive force on Escherichia coli cells [167]. With compression, cells no longer retained their rod-like shapes but grew and divided with a flat pancake-like geometry.
The mechanical stiffness of extracellular matrix has proven to be a crucial regulator for cell growth, differentiation, movement and functions [168]. Microfluidics offer versatile platforms for the study of cellular responses to matrix stiffness. Sundararaghavan et al. designed and developed a microfluidic device to investigate the neurites growth under stiffness gradients [169]. An “H”-shaped, source–sink network was utilized to generate a gradient of genipin (a collagen crosslinker) in type I collagen solution. After self-assembly, hydrogel with a gradient of mechanical stiffness, linearly ranging from 57 to 797 Pa, was formed in the device. Chick dorsal root ganglia was introduced into the gradient and results shown that the neurites extended preferentially down the stiffness gradient. García et al. presented a robust microfluidic device that generated a stable, linear and diffusive chemical gradient over a biocompatible hydrogel with a well-defined stiffness gradient (Fig. 2.6d) [170]. Matrix stiffness was regulated by UV exposure level of the polyacrylamide hydrogel. This device was then used to study the cell scattering in response to perpendicular gradients of hepatocyte growth factor and substrate stiffness.
Except for the mimicking of cellular mechanical environments, microfluidic techniques can also be used to measure mechanical forces generated by cells [171]. Christopher S. Chen group has developed micrometre-sized elastomer post arrays to manipulate and measure mechanical interactions between cells and their underlying substrates. Cells attached to, spread across, and deflected multiple posts. And the deflections of the posts directly reported the subcellular distribution of traction forces. Values of the forces could be measure according to the geometry change. By controlling cell adhesion on these micromechanical sensors, it showed that cell morphology regulated the magnitude of traction force generated by cells. Unspread cells did not contract in response to stimulation by serum or lysophosphatidic acid, whereas spread cells did [172]. Similar micro-fabricated device has also been utilized for mapping mechanical forces during epithelial cell migration [173]. Besides, by alternating the post heights or pillar diameters, the stiffness of substrates could be regulated, and their effects on cell morphology, focal adhesions, cytoskeletal contractility and stem cell differentiation were then investigated [174, 175]. The mechanosensing mechanism for cellular adaptation to substrate stiffness was also intensively studied (Fig. 2.6e) [176].
2.5 Cell Analysis
In native cellular microenvironment, cells are surrounded with multiple biophysical and biochemical cues and also respond to the various stimuli. Thus analyzing cells, including the cell morphology, cellular contents, cell signaling and cell secretion, is crucial for intensive understanding of biological processes and mechanisms. Owing to the unique merits, including flexible design, low sample consumption, high throughput, ease of integration and automation, microfluidic technology has been regarded as a robust and promising tool for cell analysis [11, 31, 177]. Almost every analytical tool available in a conventional biology lab has an equivalent microfabricated counterpart on microfluidic devices. And the microfluidic chips are also feasible to integrate with diverse analytical instruments, such as microscopy, electronic operation, mass spectrometry and nuclear magnetic resonance, to analyze cells for various purposes [21]. In this section, we will introduce the recent developments of cell analysis on microfluidics, both in sample preparation and analytical systems.
2.5.1 Sample Preparation
2.5.1.1 Cell Sorting
Isolating and sorting cells from complex, heterogeneous cell mixtures is a critical preparatory step in many biological and medical assays, enabling the enrichment of cell samples into well-defined populations or the isolation of rare cells such as circulating tumor cells (CTCs) and hematopoietic stem cells (HSCs) from much larger population of background cells [178]. It enhances the efficiency in biological researches and diagnosis, and facilitates the understanding of accurate underlying biochemical information of specific cell types in a mixture. Recent advances in microfluidics promote high-throughput cell sorting, and this has led to various novel diagnostic and therapeutic applications that are difficult to implement using conventional technologies [179]. Microfluidic cell sorting techniques are either based on the inherent physical properties of cells, such as cell size, morphology, electrical properties and cell-fluid interactions, or on account of the differences after affinity labeling [180, 181]. And depending on the utilization of external forces, microfluidic cell sorting can also be classified as passive and active strategies. Passive sorting relies on the channel geometry (pillar and weir structures, microfilters), hydrodynamic forces (pinched flow fractionation, hydrodynamic filtration, inertial separation) and surface modification (affinity-based separation) for functionality. While active sorting applies external forces such as electric, magnetic, acoustic and optical forces for cell separation [182]. Detailed examples are listed in Table 2.1 [183].
Affinity ligands for cell surface markers can be used either to provide a force for separation, such as in cell affinity separation and capture, or as labels in fluorescence activated cell sorting (FACS) and magnetic activated cell sorting (MACS) . It improves the selectivity and are quite suitable for cell types that are physically similar to the background cell populations. In cell affinity separation, affinity ligands such as antibodies, aptamers and proteins are modified on chip surface. Cells with specific markers can be selectively captured in channel through the ligand-receptor interactions, while other cell types are passed through the device. The large surface to volume ratio of microfluidic channels significantly increases the possibility of cell-to-surface interactions and leads to a better isolation performance [180, 184]. The geometry of the channel can affect the cell flow and cell capture efficiency. Stott et al. demonstrated a herringbone-chip (HB-chip) that allowed passive mixing of blood cells through the generation of microvortices to significantly increase the number of interactions between target CTCs and the antibody-coated chip surface (Fig. 2.7a) [185]. The HB-chip was used for CTC separations, identifying CTCs in 93% of patients with metastatic disease. The low shear flow properties enabled the isolation of previously unappreciated microclusters of CTCs, facilitating the investigation of the association between expression of mesenchymal markers and CTC clusters [186]. Chen et al. developed a microfluidic chip with a microwell array that was encoded with cell-recognizable aptamer [187]. Single tumor cells were isolated with 88.2% single-cell occupancy, and various cellular carboxylesterases were studied by time-course measurements of cellular fluorescence kinetics at individual-cell level. Recovery of captured cells can be achieved by using specific enzymes for antibodies or aptamers digestion or photocleavable linkers for ligand immobilization.
In FACS, cells are labeled by antibodies conjugated to fluorophores and selected according to their fluorescence signals. Traditional FACS has been thoroughly developed and widely applied in biological and pharmaceutical researches and industries [188]. More recently, FACS has been implemented in microfluidic devices, achieving high separation purity, high efficiency and low sample consumption. Microfluidic FACS generally operates by ordering cells in flow streams for: (i) serial interrogation by laser light, (ii) real-time classification, and (iii) rapid, command-driven sorting [29]. Sorting process can be driven by electrokinetic mechanisms (including electrophoresis, dielectrophoresis and electroosmotic flow) , acoustophoresis, optical manipulations and mechanical forces [189,190,191,192,193,194]. However, the throughput of microfluidic FACS is not high enough to compete with the commercial, large-scale instruments systems. Thus further efforts should be made to improve the throughput, for example by using a pulsed laser triggered sorting to reduce the switching time [195] or by building a parallel array of microfluidic sorting units for simultaneous operation.
In MACS, cells are first labeled by magnetic beads coated with affinity ligands, and a strong magnetic field is used to isolate the magnetic beads that are attached to the desired cell population. The immunomagnetic-based separation is highly specific, biocompatible and high-throughput. Enrichment of up to 1011 cells in less than 30 min has been reported [184]. Many macroscale MACS separations have been adapted in microfluidic systems, which have the advantages of low sample costs, fluid flow condition and parallel operations [29, 196]. Among these approaches, continuous separation by means of magnetophoresis has been well-studied and applied to cell separation. For example, Hoshino et al. developed an immunomagnetic microchip for CTC detection [197]. As the blood sample flowed through the microchannel closely above arrayed magnets, cancer cells labeled with magnetic nanoparticles were captured and separated from blood flow. CTCs with low cancer cell to blood cell ratios (about 1:107 to 109) were detected, at a fast screening speed (10 mL/h). Xia et al. developed a lateral magnetophoresis for cell separation (Fig. 2.7b) [198]. This method used a horizontal magnetic field to drag labeled target cells from the sample flow into the buffer flow. Living E. coli bacteria bound to magnetic nanoparticles were efficiently removed from flowing solutions containing densities of red blood cells similar to that found in blood. Similar design was also utilized in CTC separation, which isolates about 90% of spiked CTCs in human peripheral blood with a purity of 97%. The overall isolation procedure was completed within 15 min for 200 μL of blood [199].
2.5.1.2 Cell Lysis
Cell lysis is an essential step for the analysis of cellular contents such as proteins and nucleic acids. Microfluidic cell lysis has several advantages over conventional approaches. The unique geometries and precise dimensions allow for finely tuned mechanical or chemical cell perturbation. Micrometer length scale minimizes lysate dilution. And laminar flow limits the convective transport of lysate. These properties facilitate the increase of analyzing sensitivity [200, 201]. Microfluidic cell lysis approaches can be categorized into four major groups: mechanical lysis, thermal lysis, chemical lysis and electrical lysis [202]. In this section, we will discuss these four cell lysis approaches and provide some recent examples.
Mechanical cell lysis tears or punctures cell membranes by mechanical forces, which include shear stress, collision with sharp features, friction forces and compressive stress. In this way, cell structures are disrupted and intracellular components are released [201]. Yun et al. presented a handheld mechanical cell lysis chip with ultra-sharp nano-blade arrays (Fig. 2.8a) [203]. Cells bumped into the blades were easily ruptured by these ultra-sharp nanostructures. This chip can be directly connected to a commercial syringe, and the protein concentration obtained by this chip is quantitatively comparable to the conventional chemical lysis method. Kim et al. developed a microfluidic CD (Compact Disc) platform for cell lysis [204]. Cells were mixed with granular particles, and the solution was placed into an annular channel on the chip. When the disc was rotated at high speeds around a horizontal axis, cells were broken up by the frictions and collisions between the cells and particles. Mammalian cells, bacteria and yeast cells could all be effectively lysed and the lysis efficiency relative to a conventional lysis protocol was approximately 65%. Combining a magnetically actuated bead-beating system with this CD chip could further improve the lysis efficiency [205]. These platforms were utilized in nucleic acid extraction from clinical samples. Mechanical lysis can relatively minimize the protein damage and avoid detergent interferences. However, it requires additional instrumentation or operation for activation, and the cell debris produced in mechanical lysis may hinder subsequent extraction.
In electrical cell lysis, cells are exposed to strong electric fields. The membranes are destabilized and pores are formed. As the osmotic pressure between the cytosol and the surrounding media becomes unbalanced, cells swell, rupture and eventually lyse. The electric field can be tuned for rapid cell lysis without denaturing target biomolecules. And considering difference between trans cell-membrane potential and trans organelle-membrane potentials, appropriate electric field strength and exposure time can selectively rupture the cell membrane while leave organelles intact [2, 201]. Electrical cell lysis is well suitable for microfluidics applications. Mellors et al. developed a microfluidic device for automated real-time analysis of individual cells using capillary electrophoresis (CE ) and electrospray ionization mass spectrometry (ESI-MS) [206]. Cell lysis occured at a channel intersection using a combination of rapid buffer exchange and an increase in electric field strength (4 kV). The cell lysis rate is 0.2 cells per second. Jokilaakso et al. reported a microfluidic device which positioned individual cells on silicon nanowire biological field effect transistors by manipulating magnetic beads using external magnetic fields (Fig. 2.8b) [207]. Ultra-rapid cell lysis was subsequently performed by applying 600–900 mVpp at 10 MHz for as little as 2 ms across the transistor channel and the bulk substrate. This system was used to study the single cell variation within a population.
Thermal cell lysis utilizes high temperature to denature the proteins within cell membranes, thus irreparably damaging the cells and releasing the cytoplasmic contents. This method is commonly used in nucleic acid preparation, combining with PCR-based assays. Thermal lysis can be performed by ohmic heating, induction heating or heat generated by irradiating nanoparticles. For example, Lee et al. presented an automated microfluidic chip capable of performing thermal cell lysis, electrokinetic sample/reagent transportation and mixing, and DNA amplification (PCR) (Fig. 2.8c) [208]. Two sets of micro-heaters and micro temperature sensors were integrated in cell lysis reactor and PCR chamber, to regulate and monitor the temperature. Cells could be lysed within 2 min at a constant temperature of 95 °C and PCR amplification of a 273 bp Streptococcus pneumoniae were demonstrated. Thermal lysis is a simple method and has been well-established for nucleic acid analysis. However, the thermal damage of proteins restricts its application in immunoassays.
Chemical cell lysis uses lytic agents to break down the cell wall and/or membrane. There are various chemical reagents which are chosen based on the cell types and target molecules. Detergents such as sodium dodecyl sulfate (SDS) and Triton X-100 disrupt cell membranes by solubilizing membrane proteins and lipids and creating pores. Ammonium chloride can only lyse the erythrocytes. For bacterial lysis, enzymatic degradation step such as lysozyme treatment is essential to destroy the cell wall. Chaotropic salts such as guanidinium thiocyanate and guanidinium chloride lyse cell membranes by disrupting protein intermolecular forces. They are most commonly used in nucleic acid preparations [200]. Chemical cell lysis is easily incorporated in microfluidic chips. Sarkar et al. presented a microfluidic probe that chemically lysed single adherent cells from standard tissue culture using commercial lysis buffer and captured the contents to perform single-cell biochemical assays (Fig. 2.8d) [209]. This device was applied to measure kinase and housekeeping protein activities from single human hepatocellular carcinoma cells in adherent culture. Chemical cell lysis is simple to implement and needs only mixing for activation. However, the chemical reagents in lysis buffer may interfere subsequent extraction and detection, for example when target molecules are analyzed by mass spectrometry. Thus additional separation steps will be required to remove the regents.
2.5.1.3 Sample Separation
Preconcentration and separation of biomolecules (nucleic acids, proteins, metabolites etc.) from complex cell lysate are quite important for sensitive detection and successful downstream processing. Microfluidics offer unique advantages for sample separation compared to conventional bench-top methods [32]. Microscale channels reduce sample and reagent consumption. The ease of integration on microfluidic devices enables the coupling of multiple separation techniques, which improves the separation efficiency. The separation step can also be integrated with lysis and analysis steps in an automatic manner, and this can minimize manual sample handling and preserve sample integrity, thereby improving the accuracy and reproducibility [210].
Many separation techniques can be operated in microfluidic devices, including chromatography, electrokinetic separation, solid-phase extraction (SPE) , liquid-liquid extraction and filtration [211]. Each method has its own merits and applicative analytes. These separation techniques can also be integrated in one device to develop multidimensional separations works, which increase the capacity, throughput and efficiency.
Microfluidic electrokinetic separation, such as microchip capillary electrophoresis (MCE ), gel electrophoresis, electrochromatography, isoelectric focusing (IEF) and isotachophoresis (ITP), are more commonly used for biomolecule fractionation and enrichment [212,213,214]. In microchip electrophoresis, charged molecules are separated based on their electrophoretic mobility under an electric field. Liu et al. developed a portable lab-on-a-chip system comprising a PCR reactor and a 7-cm-long separation channel for capillary electrophoretic analysis (Fig. 2.9a) [215]. This device was utilized in real-time forensic short tandem repeat (STR) analysis . Alleles which differed by 1 bp could be separated, and the CE separation process was completed in 8 min. Lin et al. presented a multiplex protein assay based on tunable aptamer by MCE [216]. Different lengths of aptamers could modulate the electrophoretic mobility of proteins, allowing the proteins to be effectively separated. This method was applied to analyze the PDGF-BB and VEGF165 from cell secretions. ITP uses a heterogeneous buffer system consisting of high-mobility ions in the leading electrolyte (LE) and low-mobility ions in the terminating electrolyte (TE); an applied electric potential separates the ionic species based on their electrophoretic mobility, thus focusing the analytes at the LE/TE interface [217]. Schoch et al. demonstrated an on-chip ITP for the simultaneous extraction, isolation, preconcentration and quantitation of small RNAs from cell lysate [218]. It separated small RNAs from precursor miRNAs in less than 3 min, and the minimal cell number for small RNA extraction and detection is 900 (from a 5 mL sample volume).
In microchip chromatography system, stationary phase plays a critical role in molecules separation. There are a variety of stationary phase materials, including chromatography resins, monoliths and nanowires. In addition, surface functionalized microchannels (open channel system) and “pillar structured” microchannels are also studied as stationary phases [219, 220]. Several companies have launched nanoLC systems with integrated liquid chromatography (LC) microchips for chip-based LC-MS analysis. The cHiPLC-nanoflex system from Eksigent Technologies, Trizaic UPLC nanoTile system from Waters and Chip Cube from Agilent are currently commercially available and have been used in various fields of bioanalytical applications including proteomics , glycomics , and clinical and pharmaceutical studies [221]. Chen et al. coupled the cHiPLCnanoflex system to an Orbitrap spectrometer [222]. After multistep sample preparation, peptide mixtures were separated in cHiPLC-nanoflex equipped with a 15 cm × 75 cm C18 column. high peptide coverage for 12 γ-aminobutyric acid type A receptor (GABAA receptor) subunits was obtained from 2 pmol of affinity-purified GABAA receptors from rat brain neocortex.
Microchip solid-phase extraction is also a widely used method for sample preconcentration and clean-up. In microchip SPE, sample is retained on a solid phase, allowing the matrix to be rinsed away, and then the retained analytes was eluted for analysis [211]. Various solid phases, including packed-bead columns [223], monolith columns [224] and affinity columns [225] have been incorporated in microfluidic devices. Our group has developed a series of microfluidic systems which integrated drug injection , cell culture chambers and micro-SPE column in one device and coupled to mass spectrometry . The micro-SPE was used for desalination and extraction of cell metabolites. These devices have been applied to study drug metabolism in cell co-culture systems [150, 226,227,228]. Hagan et al. utilized chitosan-coated silica as a solid phase for RNA purification in a microfluidic device [229]. The effectiveness of the chitosan phase was demonstrated by the successful purification of RNA from cancer cells, with 3.5-fold greater extraction efficiencies than that purified by the simple silica phase.
Multidimensional separation is a significant advantage for microfluidic separation techniques. Various multidimensional microfluidic systems have been developed, such as micellar electrokinetic chromatography (MEKC)-CE, IEF-CE, ITP-CE, IEF-free-flow electrophoresis (FFE) [210, 230]. Emrich et al. developed a microfluidic separation system to perform two-dimensional differential gel electrophoretic separations of complex protein mixtures (Fig. 2.9b) [231]. This two-layer borosilicate glass microdevice consisted of a single 3.75 cm long channel for IEF, which was sampled in parallel by 20 channels effecting a second-dimension separation by native CE. The connection between the orthogonal separation systems was much shallower, narrower channels, which could prevented media leakage between the two dimensions and enabled facile loading of discontinuous gel systems in each dimension. Reproducible separations of both purified proteins and complex protein mixtures produced by E. coli were performed with minimal run-to-run variation.
2.5.2 Cell Analysis
Microfluidic devices are feasible to integrate with diverse analytical techniques, including optical detector, electrical analysis , mass spectrometry and nuclear magnetic resonance, to perform both qualitative and quantitative cell analysis for various purposes [21]. Optical detection, such as absorbance , fluorescence, infrared (IR) and surface plasmon resonance (SPR) , are the most widely used techniques in microfluidics for cell analysis [232,233,234]. Owing to the transparency of microfluidic chips, various types of microscopy can be integrated to imaging the cell morphology, structure, movements, as well as specifically labeled cellular contents. Optical detector such as absorbance , laser-induce fluorescence (LIF ), chemiluminescence (CL) can also be coupled with microfluidic separation channels, for the detection and quantification of fractionated biomolecules [235]. Electrical analysis, such as amperometry, electrochemical impedance spectroscopy (EIS), or patch-clamp, can be incorporated in microdevice to monitor cell secretion, cell morphology and migration, cell monolayer permeability, cell membrane electrophysiologic activity, and so on [236,237,238,239]. Mass spectrometry, as a powerful analytical technique, is commonly coupled with microfluidics for the analysis of cellular contents (DNA, protein, glycan etc .) and metabolites [240,241,242]. Integrating with these analytical techniques, microfluidic systems enable rapid, sensitive, reproducible and high-throughput cell analysis, which promotes the development of both basic biological researches and clinic diagnosis and therapy [243, 244]. In this section, we will introduce cell analysis using microfluidic devices integrated with diverse analytical techniques, according to the analysis objects. Some recent examples are also reviewed here.
2.5.2.1 Cell Morphology and Movement
In cellular microenvironment, cells are surrounded with multiple physical and biochemical cues. Cell morphology and movement are the most intuitionistic parameters that can reflect cellular responses to the diverse stimuli. By integrating biomimetic cell culture systems with various types of microscopy or electrical techniques, microfluidics offers a robust platform for real-time monitoring of cell morphology alteration and cell movements.
Fluorescence imaging are the most commonly used technique for cell observation. Cells cultured in microchannels are labeled by fluorescent dyes or proteins and visualized under fluorescence microscopy. Giobbe et al. described a multistage microfluidics-based approach for the differentiation of human pluripotent stem cells [245]. Cell morphology changed during factor stimulation and cell differentiation were observed by immunofluorescent staining of F-actin. And with the increase of acetaminophen concentration, morphology of human embryonic stem cell was disrupted, especially at 25 mM with almost complete loss of cell structure and function. Cell movement can also be altered under external stimuli, which is a pivotal step in angiogenesis, cancer invasion and metastasis [246,247,248]. Kim et al. proposed a microfluidic platform that could monitor and quantify cellular behaviors, including morphological changes, cell migration and formation of angiogenic sprouts, under the treatment of anti-angiogenic drug (Fig. 2.10a) [249]. Results showed that cells rapidly and actively migrated from the endothelial channel into the 3D hydrogel scaffolds toward the VEGF-supplemented media channel, and this process could be inhibited by anti-angiogenic drug bortezomib.
Electrical techniques can also be incorporated in microfluidic devices for cell morphology analysis. Haandbæk et al. demonstrated a microfluidic single cell impedance cytometer capable of dielectric characterization of single cells at frequencies up to 500 MHz (Fig. 2.10b) [250]. The increased frequency range allowed for characterization of subcellular morphology, such as vacuoles and cell nuclei, in addition to the properties detectable at lower frequencies. This device could discriminate wild-type yeast cells from those with a mutant, which differed in size and distribution of vacuoles in the intracellular fluid.
2.5.2.2 Genetic Analysis
Genetic analysis is one of the most extensively developed field in microfluidic cell analysis. Since the amount of the nucleic acids extracted from cells is relatively small, nucleic acid amplification processes play a critical role in sensitive detection and quantification [251]. Polymerase chain reaction (PCR) is the most widely used non-isothermal amplification technique, which performs thermal cycling to amplify a few copies of DNA across several orders of magnitude, generating thousands to millions of copies of a particular DNA sequence. Quantification of RNA can be achieved by performing reverse-transcription PCR (RT-PCR). There are also various isothermal amplification techniques, such as strand displacement amplification (SDA), nucleic acid sequence based amplification (NASBA), rolling circle amplification (RCA), and loop mediated isothermal amplification (LAMP) [252]. Both isothermal and non-isothermal amplification have been successfully performed in microfluidic devices, with advantages including faster reaction times, low sample consumption, precise temperature distribution and the ease of integrating with separation techniques [253, 254]. Zhang et al. developed a targeted RNA sequencing method that coupled microfluidics-based multiplex PCR with deep sequencing [255]. This system could uniformly and simultaneously amplify up to 960 loci in 48 samples on a single microfluidic chip independent of their gene expression levels. Resulting PCR amplicons were barcoded for each sample and then subjected to deep sequencing to obtain high coverage allowing accurate measurement of allelic ratios. Fang et al. demonstrated a portable microchip-based LAMP platform, which performed rapid DNA release, exponential signal amplification and naked-eye result read-out in single or multiplex format [256]. This device was successfully used for point-of-care identification of bacteria.
Microfluidic techniques have been applied to various areas of genetic analysis , including sequencing, gene expression analysis [257], pathogen detection [258], and forensic STR typing [259]. High-throughput single-cell transcriptome sequencing (RNA-Seq) offers an unbiased approach for understanding the extent, basis and function of gene expression variation between seemingly identical cells. Currently, several microfluidic-based single-cell RNA-Seq platforms have been developed and applied to study transcriptional heterogeneity of cancer [260, 261], immune [262] and stem cells [263]. Streetsv et al. [264] presented a microfluidic-based system to perform single-cell whole-transcriptome sequencing (Fig. 2.11a). Single cells were captured and lysed in a microfluidic device, where mRNAs with poly(A) tails were reverse-transcribed into cDNA. Double-stranded cDNA was then collected and sequenced using a next generation sequencing platform. This technique enabled the identification and quantification of biological variation in a population of mouse embryonic stem cells at the single-cell level. Shalek et al. used a commercially available microfluidic device (C1 single-cell Auto Prep System, Fluidigm) and a transposase-based library preparation strategy to help prepare over 1700 single-cell RNA-seq libraries along time courses of bone-marrow derived dendritic cells responding to different stimuli [265]. Transcriptome-wide changes in single-cell expression variation across a variety of conditions was tracked and how both antiviral and inflammatory response modules in dendritic cells were controlled by positive and negative intercellular paracrine signaling were illustrated.
Chromatin immunoprecipitation coupled with deep sequencing (ChIP-seq) has also been successfully operated on microfluidics for the examining of in vivo genome-wide chromatin modifications (Fig. 2.11b) [266]. Magnetic beads coated with a ChIP antibody were flowed into the microfluidic chamber and form a packed bed. It facilitated rapid and high-efficiency adsorption of target chromatin fragments, and the nonspecific adsorption was removed by effective oscillatory washing. These target chromatin samples were then purified and sequenced. Using this technology, many new enhancers and super enhancers in hematopoietic stem and progenitor cells were uncovered, suggesting that enhancer activity was highly dynamic during early hematopoiesis.
Even genetically identical cells with seemingly identical cell histories and environmental conditions can have significant differences in gene expression levels, due largely to the alteration of mRNA production by random fluctuations or complex molecular switches. Thus quantitative analysis of gene expression at single-cell level is important for the understanding of basic biological mechanism and disease onset and progression [267]. Toriello et al. developed an integrated microdevice for the analysis of gene expression in single cells (Fig. 2.11c) [268]. This device consisted of integrated nanoliter metering pumps, a 200 nL RT-PCR reactor with a single-cell capture pad, and an affinity capture matrix that was coupled to a microchip capillary electrophoresis separation channel for product purification and analysis. It was used to measure siRNA knockdown of the GAPDH gene in individual Jurkat cells and indicated the presence of 2 distinct populations of cells with moderate or complete silencing. Busch et al. developed a high-throughput microfluidic device in which 64 Arabidopsis thaliana seedlings could be grown and their roots were imaged by confocal microscopy over several days without manual intervention (Fig. 2.11d) [269]. This device was used to quantify expression patterns of 12 reporter genes in roots growing in different conditions and identified several cases of transient or heterogeneous expression.
2.5.2.3 Protein Analysis
Proteins are one of basic component of cells, which perform and regulate various cellular functions. Owing to the low abundance and high complexity, the development of sensitive and reliable protein analysis techniques are highly desirable. Microfluidics offer rapid, sensitive, reproducible and high-throughput platforms for protein analysis. Various aspects, including protein species, amounts, activity, as well as protein interaction with other biomolecules, can be analyzed using microfluidic devices, with tremendous advantages over conventional methods [270]. In this section, we will review the main microfluidic-based protein analysis methods, with some recently developed examples.
Cellular staining assays are commonly used methods which are easy to be applied in microfluidic devices for protein analysis. Proteins in cells are specifically labeled by tags or fluorescent antibodies, and their locations and expressions can be imaged using microscopies. Sun et al. reported a microfluidic image cytometry which was capable of quantitative, single-cell proteomic analysis (Fig. 2.12a) [271]. Simultaneous measurement of four critical signaling proteins (EGFR, PTEN, phospho-Akt, and phospho-S6) within the oncogenic signaling pathway in human brain tumor biopsies was performed by multicolor analysis of fluorescent antibody-labeled cytoplasmic proteins . This platform required much smaller amounts of reagents (∼ 2 μL/channel) and samples (< 3000 cells) than that for flow cytometry , and results were in good correlation with the clinical immunohistochemistry method. In previously mentioned example, native proteins were genetically encoded with oligohistidine sequence (His6–10), which could interacted with a fluorescent multivalent chelator head trisNTA, leading to high-affinity protein labelling in living cells [166]. And the transfer of trisNTA probe into cells was facilitated by microfluidic cell squeezing. Multiplexed protein labeling as well as super-resolution (nanometer precision) tracing of target proteins in live mammalian cells were achieved using this technique.
Another important microfluidic protein analysis technique is surface-based immunoassay . Proteins are specifically captured by affinity ligands modified on microchannel or microbead surface, and sandwich immunoassays are then performed. This method enables high level of multiplexing and quantitation, and intracellular, membrane, and secreted proteins can all be analyzed from the same single cell [270]. Love’s group developed a microengraved single-cell proteomics chip which employed an array of microfabricated subnanoliter wells to isolate and culture single cells (Fig. 2.12b) [272]. This microwell array was capped with an antibody-coated microengraved substrate, and proteins secreted by single cells were captured and then characterized using sandwich ELISAs . This devices were used to analyze the antibody production behavior of B cells collected from both a healthy mouse and a mouse model with autoimmune disorder. Microfluidic barcode chip developed by Heath group was also a versatile and robust tool for proteomic analysis (Fig. 2.12c). Single cells, or defined numbers of cells, were isolated within microchambers, each of which contained a full barcode array. Each barcode stripe was initially patterned with a unique ssDNA oligomer, and the barcode was converted into an antibody array using a cocktail of antibodies labeled with complementary ssDNA oligomers (DNA-encoded antibody library, DEAL) [273], just prior to running an assay. This platform could be used to capture and detect secreted proteins from living cells, or proteins, nucleic acids and metabolites from lysed cells, using ELISA or fluoroimmunoassy (FIA) coupled with a standard array scanner [274]. This technique was quantitative, sensitive, highly multiplexed and high-throughput, and has been applied to study single-cell proteomics , cell signaling and cell-cell interaction [275, 276].
Recently, protein immunoblotting assay has been operated on microfluidic devices, overcomes several limitations associated with conventional immunoblotting, including multiple steps requiring manual intervention, low throughput and substantial consumption of reagents [277, 278]. Polyacrylamide (PA ) gels in glass microfluidic devices were regional photo-patterned and served as a platform for rapid and automated protein immunoblotting . All assay stages were programmably controlled by a high-voltage power supply and monitored by an epifluorescence microscope equipped with a charge-coupled device camera. Microfluidic single-cell western blotting (scWestern) has also been developed by the same group (Fig. 2.13a) [279, 280]. PA gels were photo-patterned to form a microwell array, in which single cells were settled and lysed in situ. Gel electrophoresis was then performed, and separated proteins were immobilized by photoinitiated blotting and detected by antibody probing. This scWestern method enabled multiplexed analysis of 11 protein targets per single cell with detection thresholds of < 30,000 molecules. It was applied to monitor single-cell differentiation of rat neural stem cells and their responses to mitogen stimulation.
Protein activity, and the interactions between protein and other biomolecules, can also been analyzed on microfluidics. In previously mentioned example, Sarkar et al. presented a microfluidic probe that lysed single adherent cells from standard tissue culture and captured the contents to perform single-cell assays [209]. Kinase and housekeeping protein activities were measured simultaneously or separately by mixing them with assay reagents in nanolitre scale integrated chambers , and imaging over time for fluorescence . This approach was used to elucidate the biological heterogeneity in Akt kinase activity levels among cells under insulin stimulation. Lee et al. presented a magneto-nanosensor platform integrated with a microfluidic chip that allowed measurement of low-affinity protein–protein interactions (Fig. 2.13b) [281]. Prey proteins were pre-conjugated to magnetic nanoparticles (MNPs), and then introduced into microchannels and specifically interacted with magneto-nanosensors modified with bait proteins. The magneto-nanosensors produced signals proportional to the number of bound complexes, and real-time binding curves were measured and kinetic parameters were calculated. This platform was used to characterize the binding affinities of the PD-1—PD-L1/PD-L2 co-inhibitory receptor system, and discovered an unexpected interaction between the two known PD-1 ligands, PD-L1 and PD-L2.
Coupled with mass spectrometry (MS), microfluidic technique offers a robust platform for proteomic analysis [282, 283]. A commercially available HPLC-chip/MS system has been developed by Agilent Technologies, which uses a multilayer polyimide chip consisting of preparation channels and an integrated electrospray tip [284]. Trypsin-digested proteins are introduced into the HPLC-chip, concentrated on a small volume (40 nL) enrichment column and separated in the analytical nanochannel. Eluting compounds are directly sprayed into the MS instrument with the electrospray tip. This system was combined with strong cation exchange chromatography and applied to the analysis of the nucleolar proteome, resulting in the identification of more than 200 proteins which corresponded to 2024 unique tryptic peptides. Microfluidic devices can also be integrated with matrix-assisted laser desorption and ionization mass spectrometry (MALDI-MS), in either off-line or on-line manner [285]. Lee et al. constructed an automated proteolytic digestion bioreactor and continuous deposition system in a plastic microfluidic device for off-line interfacing to MALDI-TOF MS (Fig. 2.13c) [286]. Proteins were digested by trypsin immobilized on an array of micropost structures in bioreactor, and the obtained peptides were continuously deposited onto a MALDI plate modified with nitrocellulose solution containing a matrix by a 50 mm capillary tube attached to the end of the bioreactor. Various proteins were analyzed in this platform with good sequence coverage.
2.5.2.4 Metabolite Analysis
The intracellular levels and spatial localizations of metabolites reflect the state of a cell and its relationship to its surrounding environment [287]. Microfluidic device is an ideal platform for cellular metabolite profiling both in physiological environment and under drug treatment, owing to the ability of integrating cell culture, stimulation, metabolite enrichment and detection on a single chip coupled with various analytical instruments [288].
Among diverse analytical techniques, MS is the most powerful and promising tool for cell metabolite analysis , because of its broad detection range, high sensitivity, high mass resolution, rapid operation, and the ability for multiplexed analysis . Microfluidic devices can integrate with different types of MS, including ESI-MS, MALDI-MS and paper-spray ionization MS [289]. Recently, our group has developed a series of chip-MS platforms for cell metabolites analysis. Functional sections including cell medium/drug introducing channels, cell culture chambers , micro-SPE columns were integrated in one microchip, and coupled to ESI-MS via capillaries [150, 226,227,228, 290,291,292]. Chen et al. developed a stable isotope labeling assisted microfluidic chip electrospray ionization mass spectrometry (SIL-chip—ESI-MS) platform for qualitative and quantitative analysis of cell metabolism (Fig. 2.14a) [293]. MCF-7 cells were cultivated in vitro and exposed in anticancer agent (genistein ) for cell-based drug assay. A dual-isotopic labeling was presented for effective qualitative analysis of multiplex metabolites. Three coeluting pairs of isotopomers could be easily recognized and identified. This chip-MS technique can also be extended to study cell-cell communication . Zhuang et al. [294] designed a membrane integrated microfluidic device to achieve the co-culture of PC12 cells and 293 cells to study nephrocyte-neurocyte interaction. The neuro-like differentiated PC12 cells induced by mNGF released neurotransmitter acetylcholine, which stimulated the 293 cells and led to the secretion of hormone epinephrine. Secreted epinephrine could be detected by ESI-MS, providing a chemical insight into the understanding of cellular interaction.
Optical detecting technique can also be integrated with microfluidic device for cell metabolite analysis . Wang et al. presented a flexible high-throughput approach that used microfluidics to compartmentalize individual cells for growth and analysis in monodisperse nanoliter aqueous droplets surrounded by an immiscible fluorinated oil phase (Fig. 2.14b) [295]. Fluorescent assay system was used to measure the concentration of the metabolites (oxidase enzymes), and the assay reaction started when a cell-containing droplet coalesced with an assay droplet. Based on the cellular metabolism behavior, this system was able to identify xylose-overconsuming Saccharomyces cerevisiae cells from a population containing one such cell per 104 cells and enrich L-lactate-producing Escherichia coli clones 5800 × from a population containing one L-lactate producer per 104 D-lactate producers.
2.6 Conclusion and Perspective
Microfluidics, combined with advanced molecular, imaging and bioinformatics techniques, constitute a robust ‘toolbox’ and revolutionize the way for cell biology researches. Multiple processes including cell culture, cell manipulation , cell stimulation and cell analysis can be transferred and integrated in a small single microfluidic device, promoting the development of cell researches. Owing to the unique advantages of microfluidic technology, it has been applied to various biological fields, such as single-cell analysis, cancer research, drug discovery and screening, clinical diagnostics, stem cell research, intra- and inter-cellular signaling, tissue models and microbiology. These applications have been partially introduced in previous sections and will be reviewed in detail in the following chapters in this book.
Despite the rapid development and significant progress of microfluidic technology in recent years, there are still challenges and hurdles that should be addressed for microfluidic cell analysis. One pivotal challenge is the low adoption of novel microfluidic techniques in mainstream biology researches. Most microfluidic-based techniques for cell biology applications recently are only iterative improvements on methods that already exist. And owing to the gaps in expertise between microfluidic engineers and biologists, it is not easy for biologists to handle complex microfluidic systems. Thus the superiority and particularity of microfluidic techniques over traditional methods are not obvious, and biologists will generally prefer to use conventional macroscale methods than to learn and adopt the new microfluidic techniques. To address this challenge, efforts can be made from different directions. First, collaborations between multidisciplinary researchers (physicists, chemists, engineers, molecular and cell biologists, and clinicians) should be further strengthened, which can make the microfluidic-based techniques more biologically compatible, allow direct interaction and feedback between designers and end-users, and accelerate the applications of newly developed techniques. Second, more attentions should be payed to research areas in which microfluidic technology shows unique advantages and irreplaceable roles, such as diagnostic devices for low-resource settings, rapidly assaying biofluids for research and clinical applications, and development of more physiologically relevant in vitro models. Third, simplifying microfluidic devices and operation processes is an effective way to lower the barrier to entry for biologists and expand practical applications. In addition, developing automated microfluidic systems with diverse functions can also improve the adoption of microfluidic technology in mainstream cell researches [7, 15].
In summary, with twenty-year development, microfluidic technology has become one of the most powerful and promising tool for the study of cell biology and cell analysis. It has been extensively utilized in various fields of cell research and is still in rapid progression. We believe that with further advance and maturation, this versatile and robust technology will continue to introduce new paradigm for cell study, and make contributions to the deep cognition and development of both basic biological research and clinic applications.
References
Barthes J, Ozcelik H, Hindie M, Ndreu-Halili A, Hasan A, Vrana NE (2014) Cell microenvironment engineering and monitoring for tissue engineering and regenerative medicine: the recent advances. Biomed Res Int 2014:921905. doi:10.1155/2014/921905
El-Ali J, Sorger PK, Jensen KF (2006) Cells on chips. Nature 442(7101):403–411. doi:10.1038/nature05063
Gattazzo F, Urciuolo A, Bonaldo P (2014) Extracellular matrix: a dynamic microenvironment for stem cell niche. Biochim Biophys Acta 1840(8):2506–2519. doi:10.1016/j.bbagen.2014.01.010
Quail DF, Joyce JA (2013) Microenvironmental regulation of tumor progression and metastasis. Nat Med 19(11):1423–1437. doi:10.1038/nm.3394
Sun Y, Chen CS, Fu J (2012) Forcing stem cells to behave: a biophysical perspective of the cellular microenvironment. Annu Rev Biophys 41:519–542. doi:10.1146/annurev-biophys-042910-155306
Whitesides GM (2006) The origins and the future of microfluidics. Nature 442(7101):368–373. doi:10.1038/nature05058
Sackmann EK, Fulton AL, Beebe DJ (2014) The present and future role of microfluidics in biomedical research. Nature 507(7491):181–189. doi:10.1038/nature13118
Mark D, Haeberle S, Roth G, von Stetten F, Zengerle R (2010) Microfluidic lab-on-a-chip platforms: requirements, characteristics and applications. Chem Soc Rev 39(3):1153–1182. doi:10.1039/b820557b
Nge PN, Rogers CI, Woolley AT (2013) Advances in microfluidic materials, functions, integration, and applications. Chem Rev 113(4):2550–2583. doi:10.1021/cr300337x
Livak-Dahl E, Sinn I, Burns M (2011) Microfluidic chemical analysis systems. Annu Rev Chem Biomol Eng 2:325–353. doi:10.1146/annurev-chembioeng-061010-114215
Salieb-Beugelaar GB, Simone G, Arora A, Philippi A, Manz A (2010) Latest developments in microfluidic cell biology and analysis systems. Anal Chem 82(12):4848–4864. doi:10.1021/ac1009707
Zhuang Q-C, Ning R-Z, Ma Y, Lin J-M (2016) Recent developments in microfluidic chip for in vitro cell-based research. Chin J Anal Chem 44(4):522–532. doi:10.1016/s1872-2040(16)60919-2
Andersson H, van den Berg A (2003) Microfluidic devices for cellomics: a review. Sens Actuators B: Chem 92(3):315–325. doi:10.1016/s0925-4005(03)00266-1
Xiong B, Ren K, Shu Y, Chen Y, Shen B, Wu H (2014) Recent developments in microfluidics for cell studies. Adv Mater 26(31):5525–5532. doi:10.1002/adma.201305348
Duncombe TA, Tentori AM, Herr AE (2015) Microfluidics: reframing biological enquiry. Nat Rev Mol Cell Biol 16(9):554–567. doi:10.1038/nrm4041
Priest C (2010) Surface patterning of bonded microfluidic channels. Biomicrofluidics 4(3):32206. doi:10.1063/1.3493643
Li Jeon N, Baskaran H, Dertinger SK, Whitesides GM, Van de Water L, Toner M (2002) Neutrophil chemotaxis in linear and complex gradients of interleukin-8 formed in a microfabricated device. Nat Biotechnol 20(8):826–830. doi:10.1038/nbt712
Lucchetta EM, Lee JH, Fu LA, Patel NH, Ismagilov RF (2005) Dynamics of Drosophila embryonic patterning network perturbed in space and time using microfluidics. Nature 434(7037):1134–1138. doi:10.1038/nature03509
Araci IE, Brisk P (2014) Recent developments in microfluidic large scale integration. Curr Opin Biotechnol 25:60–68. doi:10.1016/j.copbio.2013.08.014
Melin J, Quake SR (2007) Microfluidic large-scale integration: the evolution of design rules for biological automation. Annu Rev Biophys Biomol Struct 36:213–231. doi:10.1146/annurev.biophys.36.040306.132646
Wu J, He Z, Chen Q, Lin J-M (2016) Biochemical analysis on microfluidic chips. TrAC Trends Anal Chem 80:213–231. doi:10.1016/j.trac.2016.03.013
Kellogg RA, Gomez-Sjoberg R, Leyrat AA, Tay S (2014) High-throughput microfluidic single-cell analysis pipeline for studies of signaling dynamics. Nat Protoc 9(7):1713–1726. doi:10.1038/nprot.2014.120
Shembekar N, Chaipan C, Utharala R, Merten CA (2016) Droplet-based microfluidics in drug discovery, transcriptomics and high-throughput molecular genetics. Lab Chip 16(8):1314–1331. doi:10.1039/c6lc00249h
Joensson HN, Andersson Svahn H (2012) Droplet microfluidics—a tool for single-cell analysis. Angew Chem Int Ed Engl 51(49):12176–12192. doi:10.1002/anie.201200460
Rothbauer M, Wartmann D, Charwat V, Ertl P (2015) Recent advances and future applications of microfluidic live-cell microarrays. Biotechnol Adv 33(6 Pt 1):948–961. doi:10.1016/j.biotechadv.2015.06.006
Willaert R, Goossens K (2015) Microfluidic bioreactors for cellular microarrays. Fermentation 1(1):38–78. doi:10.3390/fermentation1010038
Mehling M, Tay S (2014) Microfluidic cell culture. Curr Opin Biotechnol 25:95–102. doi:10.1016/j.copbio.2013.10.005
Halldorsson S, Lucumi E, Gomez-Sjoberg R, Fleming RM (2015) Advantages and challenges of microfluidic cell culture in polydimethylsiloxane devices. Biosens Bioelectron 63:218–231. doi:10.1016/j.bios.2014.07.029
Shields CW, Reyes CD, Lopez GP (2015) Microfluidic cell sorting: a review of the advances in the separation of cells from debulking to rare cell isolation. Lab Chip 15(5):1230–1249. doi:10.1039/c4lc01246a
Pappas D (2016) Microfluidics and cancer analysis: cell separation, cell/tissue culture, cell mechanics, and integrated analysis systems. Analyst 141(2):525–535. doi:10.1039/c5an01778e
Ertl P, Sticker D, Charwat V, Kasper C, Lepperdinger G (2014) Lab-on-a-chip technologies for stem cell analysis. Trends Biotechnol 32(5):245–253. doi:10.1016/j.tibtech.2014.03.004
Mach AJ, Adeyiga OB, Di Carlo D (2013) Microfluidic sample preparation for diagnostic cytopathology. Lab Chip 13(6):1011–1026. doi:10.1039/c2lc41104k
Eicher D, Merten CA (2011) Microfluidic devices for diagnostic applications. Expert Rev Mol Diagn 11(5):505–519. doi:10.1586/ERM.11.25
Dittrich PS, Manz A (2006) Lab-on-a-chip: microfluidics in drug discovery. Nat Rev Drug Discov 5(3):210–218. doi:10.1038/nrd1985
Neuzi P, Giselbrecht S, Lange K, Huang TJ, Manz A (2012) Revisiting lab-on-a-chip technology for drug discovery. Nat Rev Drug Discov 11(8):620–632. doi:10.1038/nrd3799
Choi NW, Cabodi M, Held B, Gleghorn JP, Bonassar LJ, Stroock AD (2007) Microfluidic scaffolds for tissue engineering. Nat Mater 6(11):908–915. doi:10.1038/nmat2022
Young EW, Beebe DJ (2010) Fundamentals of microfluidic cell culture in controlled microenvironments. Chem Soc Rev 39(3):1036–1048. doi:10.1039/b909900j
Tehranirokh M, Kouzani AZ, Francis PS, Kanwar JR (2013) Microfluidic devices for cell cultivation and proliferation. Biomicrofluidics 7(5):51502. doi:10.1063/1.4826935
Gao D, Liu H, Jiang Y, Lin J-M, Gao D, Liu H, Jiang Y (2012) Recent developments in microfluidic devices for in vitro cell culture for cell-biology research. TrAC Trends Anal Chem 35:150–164. doi:10.1016/j.trac.2012.02.008
Gupta N, Liu JR, Patel B, Solomon DE, Vaidya B, Gupta V (2016) Microfluidics-based 3D cell culture models: utility in novel drug discovery and delivery research. Bioeng Transl Med 1(1):63–81. doi:10.1002/btm2.10013
Shamir ER, Ewald AJ (2014) Three-dimensional organotypic culture: experimental models of mammalian biology and disease. Nat Rev Mol Cell Biol 15(10):647–664. doi:10.1038/nrm3873
Ravi M, Paramesh V, Kaviya SR, Anuradha E, Solomon FD (2015) 3D cell culture systems: advantages and applications. J Cell Physiol 230(1):16–26. doi:10.1002/jcp.24683
Edmondson R, Broglie JJ, Adcock AF, Yang L (2014) Three-dimensional cell culture systems and their applications in drug discovery and cell-based biosensors. Assay Drug Dev Technol 12(4):207–218. doi:10.1089/adt.2014.573
van Duinen V, Trietsch SJ, Joore J, Vulto P, Hankemeier T (2015) Microfluidic 3D cell culture: from tools to tissue models. Curr Opin Biotechnol 35:118–126. doi:10.1016/j.copbio.2015.05.002
Lee DH, Bae CY, Kwon S, Park JK (2015) User-friendly 3D bioassays with cell-containing hydrogel modules: narrowing the gap between microfluidic bioassays and clinical end-users’ needs. Lab Chip 15(11):2379–2387. doi:10.1039/c5lc00239g
Li XJ, Valadez AV, Zuo P, Nie Z (2012) Microfluidic 3D cell culture: potential application for tissue-based bioassays. Bioanalysis 4(12):1509–1525. doi:10.4155/bio.12.133
Sung KE, Su X, Berthier E, Pehlke C, Friedl A, Beebe DJ (2013) Understanding the impact of 2D and 3D fibroblast cultures on in vitro breast cancer models. PLoS ONE 8(10):e76373. doi:10.1371/journal.pone.0076373
Chen Q, Utech S, Chen D, Prodanovic R, Lin JM, Weitz DA (2016) Controlled assembly of heterotypic cells in a core-shell scaffold: organ in a droplet. Lab Chip 16(8):1346–1349. doi:10.1039/c6lc00231e
Griffin DR, Weaver WM, Scumpia PO, Di Carlo D, Segura T (2015) Accelerated wound healing by injectable microporous gel scaffolds assembled from annealed building blocks. Nat Mater 14(7):737–744. doi:10.1038/nmat4294
Frey O, Misun PM, Fluri DA, Hengstler JG, Hierlemann A (2014) Reconfigurable microfluidic hanging drop network for multi-tissue interaction and analysis. Nat Commun 5:4250. doi:10.1038/ncomms5250
Misun PM, Rothe J, Schmid YRF, Hierlemann A, Frey O (2016) Multi-analyte biosensor interface for real-time monitoring of 3D microtissue spheroids in hanging-drop networks. Microsyst Nanoeng 2:16022. doi:10.1038/micronano.2016.22
Chen YC, Lou X, Zhang Z, Ingram P, Yoon E (2015) High-throughput cancer cell sphere formation for characterizing the efficacy of photo dynamic therapy in 3D cell cultures. Sci Rep 5:12175. doi:10.1038/srep12175
Tsutsui H, Yu E, Marquina S, Valamehr B, Wong I, Wu H, Ho CM (2010) Efficient dielectrophoretic patterning of embryonic stem cells in energy landscapes defined by hydrogel geometries. Ann Biomed Eng 38(12):3777–3788. doi:10.1007/s10439-010-0108-1
Physiology in perspective: cell-cell interactions: the physiological basis of communication (2014) Physiology (Bethesda) 29(4):220–221. doi:10.1152/physiol.00031.2014
Kim SH, Turnbull J, Guimond S (2011) Extracellular matrix and cell signalling: the dynamic cooperation of integrin, proteoglycan and growth factor receptor. J Endocrinol 209(2):139–151. doi:10.1530/JOE-10-0377
Zervantonakis IK, Kothapalli CR, Chung S, Sudo R, Kamm RD (2011) Microfluidic devices for studying heterotypic cell-cell interactions and tissue specimen cultures under controlled microenvironments. Biomicrofluidics 5(1):13406. doi:10.1063/1.3553237
Guo F, French JB, Li P, Zhao H, Chan CY, Fick JR, Benkovic SJ, Huang TJ (2013) Probing cell-cell communication with microfluidic devices. Lab Chip 13(16):3152–3162. doi:10.1039/c3lc90067c
Delamarche E, Tonna N, Lovchik RD, Bianco F, Matteoli M (2013) Pharmacology on microfluidics: multimodal analysis for studying cell-cell interaction. Curr Opin Pharmacol 13(5):821–828. doi:10.1016/j.coph.2013.07.005
Nahavandi S, Tang SY, Baratchi S, Soffe R, Nahavandi S, Kalantar-zadeh K, Mitchell A, Khoshmanesh K (2014) Microfluidic platforms for the investigation of intercellular signalling mechanisms. Small 10(23):4810–4826. doi:10.1002/smll.201401444
Jeon JS, Bersini S, Gilardi M, Dubini G, Charest JL, Moretti M, Kamm RD (2015) Human 3D vascularized organotypic microfluidic assays to study breast cancer cell extravasation. Proc Natl Acad Sci U S A 112(1):214–219. doi:10.1073/pnas.1417115112
Zervantonakis IK, Hughes-Alford SK, Charest JL, Condeelis JS, Gertler FB, Kamm RD (2012) Three-dimensional microfluidic model for tumor cell intravasation and endothelial barrier function. Proc Natl Acad Sci U S A 109(34):13515–13520. doi:10.1073/pnas.1210182109
Kimura H, Yamamoto T, Sakai H, Sakai Y, Fujii T (2008) An integrated microfluidic system for long-term perfusion culture and on-line monitoring of intestinal tissue models. Lab Chip 8(5):741–746. doi:10.1039/b717091b
Chen Q, Wu J, Zhuang Q, Lin X, Zhang J, Lin JM (2013) Microfluidic isolation of highly pure embryonic stem cells using feeder-separated co-culture system. Sci Rep 3:2433. doi:10.1038/srep02433
Liu W, Li L, Wang X, Ren L, Wang X, Wang J, Tu Q, Huang X, Wang J (2010) An integrated microfluidic system for studying cell-microenvironmental interactions versatilely and dynamically. Lab Chip 10(13):1717–1724. doi:10.1039/c001049a
Lin X, Chen Q, Liu W, Zhang J, Wang S, Lin Z, Lin JM (2015) Oxygen-induced cell migration and on-line monitoring biomarkers modulation of cervical cancers on a microfluidic system. Sci Rep 5:9643. doi:10.1038/srep09643
Tumarkin E, Tzadu L, Csaszar E, Seo M, Zhang H, Lee A, Peerani R, Purpura K, Zandstra PW, Kumacheva E (2011) High-throughput combinatorial cell co-culture using microfluidics. Integr Biol (Camb) 3(6):653–662. doi:10.1039/c1ib00002k
Ricoult SG, Goldman JS, Stellwagen D, Juncker D, Kennedy TE (2012) Generation of microisland cultures using microcontact printing to pattern protein substrates. J Neurosci Methods 208(1):10–17. doi:10.1016/j.jneumeth.2012.04.016
Khetani SR, Bhatia SN (2008) Microscale culture of human liver cells for drug development. Nat Biotechnol 26(1):120–126. doi:10.1038/nbt1361
Cho CH, Park J, Tilles AW, Berthiaume F, Toner M, Yarmush ML (2010) Layered patterning of hepatocytes in co-culture systems using microfabricated stencils. Biotechniques 48(1):47–52. doi:10.2144/000113317
Edahiro J, Sumaru K, Ooshima Y, Kanamori T (2009) Selective separation and co-culture of cells by photo-induced enhancement of cell adhesion (PIECA). Biotechnol Bioeng 102(4):1278–1282. doi:10.1002/bit.22124
Gao Y, Broussard J, Haque A, Revzin A, Lin T (2016) Functional imaging of neuron–astrocyte interactions in a compartmentalized microfluidic device. Microsyst Nanoeng 2:15045. doi:10.1038/micronano.2015.45
Shin Y, Han S, Jeon JS, Yamamoto K, Zervantonakis IK, Sudo R, Kamm RD, Chung S (2012) Microfluidic assay for simultaneous culture of multiple cell types on surfaces or within hydrogels. Nat Protoc 7(7):1247–1259. doi:10.1038/nprot.2012.051
Dura B, Dougan SK, Barisa M, Hoehl MM, Lo CT, Ploegh HL, Voldman J (2015) Profiling lymphocyte interactions at the single-cell level by microfluidic cell pairing. Nat Commun 6:5940. doi:10.1038/ncomms6940
Bhatia SN, Ingber DE (2014) Microfluidic organs-on-chips. Nat Biotechnol 32(8):760–772. doi:10.1038/nbt.2989
Huh D, Hamilton GA, Ingber DE (2011) From 3D cell culture to organs-on-chips. Trends Cell Biol 21(12):745–754. doi:10.1016/j.tcb.2011.09.005
Lee E, Song HG, Chen CS (2016) Biomimetic on-a-chip platforms for studying cancer metastasis. Curr Opin Chem Eng 11:20–27. doi:10.1016/j.coche.2015.12.001
Esch EW, Bahinski A, Huh D (2015) Organs-on-chips at the frontiers of drug discovery. Nat Rev Drug Discov 14(4):248–260. doi:10.1038/nrd4539
Chrobak KM, Potter DR, Tien J (2006) Formation of perfused, functional microvascular tubes in vitro. Microvasc Res 71(3):185–196. doi:10.1016/j.mvr.2006.02.005
Tsai M, Kita A, Leach J, Rounsevell R, Huang JN, Moake J, Ware RE, Fletcher DA, Lam WA (2012) In vitro modeling of the microvascular occlusion and thrombosis that occur in hematologic diseases using microfluidic technology. J Clin Invest 122(1):408–418. doi:10.1172/JCI58753
Cho H, Seo JH, Wong KH, Terasaki Y, Park J, Bong K, Arai K, Lo EH, Irimia D (2015) Three-dimensional blood-brain barrier model for in vitro studies of neurovascular pathology. Sci Rep 5:15222. doi:10.1038/srep15222
Toh YC, Lim TC, Tai D, Xiao G, van Noort D, Yu H (2009) A microfluidic 3D hepatocyte chip for drug toxicity testing. Lab Chip 9(14):2026–2035. doi:10.1039/b900912d
Carraro A, Hsu WM, Kulig KM, Cheung WS, Miller ML, Weinberg EJ, Swart EF, Kaazempur-Mofrad M, Borenstein JT, Vacanti JP, Neville C (2008) In vitro analysis of a hepatic device with intrinsic microvascular-based channels. Biomed Microdevices 10(6):795–805. doi:10.1007/s10544-008-9194-3
Huh D, Fujioka H, Tung YC, Futai N, Paine R 3rd, Grotberg JB, Takayama S (2007) Acoustically detectable cellular-level lung injury induced by fluid mechanical stresses in microfluidic airway systems. Proc Natl Acad Sci U S A 104(48):18886–18891. doi:10.1073/pnas.0610868104
Huh D, Leslie DC, Matthews BD, Fraser JP, Jurek S, Hamilton GA, Thorneloe KS, McAlexander MA, Ingber DE (2012) A human disease model of drug toxicity-induced pulmonary edema in a lung-on-a-chip microdevice. Sci Transl Med 4(159):159ra147. doi:10.1126/scitranslmed.3004249
Jang KJ, Suh KY (2010) A multi-layer microfluidic device for efficient culture and analysis of renal tubular cells. Lab Chip 10(1):36–42. doi:10.1039/b907515a
Wilmer MJ, Ng CP, Lanz HL, Vulto P, Suter-Dick L, Masereeuw R (2016) Kidney-on-a-chip technology for drug-induced nephrotoxicity screening. Trends Biotechnol 34(2):156–170. doi:10.1016/j.tibtech.2015.11.001
Agarwal A, Goss JA, Cho A, McCain ML, Parker KK (2013) Microfluidic heart on a chip for higher throughput pharmacological studies. Lab Chip 13(18):3599–3608. doi:10.1039/c3lc50350j
Grosberg A, Alford PW, McCain ML, Parker KK (2011) Ensembles of engineered cardiac tissues for physiological and pharmacological study: heart on a chip. Lab Chip 11(24):4165–4173. doi:10.1039/c1lc20557a
Park SH, Sim WY, Min BH, Yang SS, Khademhosseini A, Kaplan DL (2012) Chip-based comparison of the osteogenesis of human bone marrow- and adipose tissue-derived mesenchymal stem cells under mechanical stimulation. PLoS ONE 7(9):e46689. doi:10.1371/journal.pone.0046689
Grosberg A, Nesmith AP, Goss JA, Brigham MD, McCain ML, Parker KK (2012) Muscle on a chip: in vitro contractility assays for smooth and striated muscle. J Pharmacol Toxicol Methods 65(3):126–135. doi:10.1016/j.vascn.2012.04.001
Zheng Y, Chen J, Craven M, Choi NW, Totorica S, Diaz-Santana A, Kermani P, Hempstead B, Fischbach-Teschl C, Lopez JA, Stroock AD (2012) In vitro microvessels for the study of angiogenesis and thrombosis. Proc Natl Acad Sci U S A 109(24):9342–9347. doi:10.1073/pnas.1201240109
Huh D, Kim HJ, Fraser JP, Shea DE, Khan M, Bahinski A, Hamilton GA, Ingber DE (2013) Microfabrication of human organs-on-chips. Nat Protoc 8(11):2135–2157. doi:10.1038/nprot.2013.137
Huh D, Matthews BD, Mammoto A, Montoya-Zavala M, Hsin HY, Ingber DE (2010) Reconstituting organ-level lung functions on a chip. Science 328(5986):1662–1668. doi:10.1126/science.1188302
Benam KH, Villenave R, Lucchesi C, Varone A, Hubeau C, Lee HH, Alves SE, Salmon M, Ferrante TC, Weaver JC, Bahinski A, Hamilton GA, Ingber DE (2016) Small airway-on-a-chip enables analysis of human lung inflammation and drug responses in vitro. Nat Methods 13(2):151–157. doi:10.1038/nmeth.3697
Young EW (2013) Cells, tissues, and organs on chips: challenges and opportunities for the cancer tumor microenvironment. Integr Biol (Camb) 5(9):1096–1109. doi:10.1039/c3ib40076j
Fan Y, Nguyen DT, Akay Y, Xu F, Akay M (2016) Engineering a brain cancer chip for high-throughput drug screening. Sci Rep 6:25062. doi:10.1038/srep25062
Albanese A, Lam AK, Sykes EA, Rocheleau JV, Chan WC (2013) Tumour-on-a-chip provides an optical window into nanoparticle tissue transport. Nat Commun 4:2718. doi:10.1038/ncomms3718
Zheng F, Fu F, Cheng Y, Wang C, Zhao Y, Gu Z (2016) Organ-on-a-chip systems: microengineering to biomimic living systems. Small 12(17):2253–2282. doi:10.1002/smll.201503208
Yi C, Li C-W, Ji S, Yang M (2006) Microfluidics technology for manipulation and analysis of biological cells. Anal Chim Acta 560(1–2):1–23. doi:10.1016/j.aca.2005.12.037
Mu X, Zheng W, Sun J, Zhang W, Jiang X (2013) Microfluidics for manipulating cells. Small 9(1):9–21. doi:10.1002/smll.201200996
Yarmush ML, King KR (2009) Living-cell microarrays. Annu Rev Biomed Eng 11:235–257. doi:10.1146/annurev.bioeng.10.061807.160502
Jonczyk R, Kurth T, Lavrentieva A, Walter JG, Scheper T, Stahl F (2016) Living cell microarrays: an overview of concepts. Microarrays (Basel) 5(2). doi:10.3390/microarrays5020011
Chung J, Kim YJ, Yoon E (2011) Highly-efficient single-cell capture in microfluidic array chips using differential hydrodynamic guiding structures. Appl Phys Lett 98(12):123701. doi:10.1063/1.3565236
Lin L, Chu YS, Thiery JP, Lim CT, Rodriguez I (2013) Microfluidic cell trap array for controlled positioning of single cells on adhesive micropatterns. Lab Chip 13(4):714–721. doi:10.1039/c2lc41070b
Chung K, Kim Y, Kanodia JS, Gong E, Shvartsman SY, Lu H (2011) A microfluidic array for large-scale ordering and orientation of embryos. Nat Methods 8(2):171–176. doi:10.1038/nmeth.1548
Sarioglu AF, Aceto N, Kojic N, Donaldson MC, Zeinali M, Hamza B, Engstrom A, Zhu H, Sundaresan TK, Miyamoto DT, Luo X, Bardia A, Wittner BS, Ramaswamy S, Shioda T, Ting DT, Stott SL, Kapur R, Maheswaran S, Haber DA, Toner M (2015) A microfluidic device for label-free, physical capture of circulating tumor cell clusters. Nat Methods 12(7):685–691. doi:10.1038/nmeth.3404
Lecault V, Vaninsberghe M, Sekulovic S, Knapp DJ, Wohrer S, Bowden W, Viel F, McLaughlin T, Jarandehei A, Miller M, Falconnet D, White AK, Kent DG, Copley MR, Taghipour F, Eaves CJ, Humphries RK, Piret JM, Hansen CL (2011) High-throughput analysis of single hematopoietic stem cell proliferation in microfluidic cell culture arrays. Nat Methods 8(7):581–586. doi:10.1038/nmeth.1614
Novo P, Dell’Aica M, Janasek D, Zahedi RP (2016) High spatial and temporal resolution cell manipulation techniques in microchannels. Analyst 141(6):1888–1905. doi:10.1039/c6an00027d
Dudani JS, Gossett DR, Tse HT, Di Carlo D (2013) Pinched-flow hydrodynamic stretching of single-cells. Lab Chip 13(18):3728–3734. doi:10.1039/c3lc50649e
McGrath J, Jimenez M, Bridle H (2014) Deterministic lateral displacement for particle separation: a review. Lab Chip 14(21):4139–4158. doi:10.1039/c4lc00939h
Qian C, Huang H, Chen L, Li X, Ge Z, Chen T, Yang Z, Sun L (2014) Dielectrophoresis for bioparticle manipulation. Int J Mol Sci 15(10):18281–18309. doi:10.3390/ijms151018281
Lim B, Reddy V, Hu X, Kim K, Jadhav M, Abedini-Nassab R, Noh YW, Lim YT, Yellen BB, Kim C (2014) Magnetophoretic circuits for digital control of single particles and cells. Nat Commun 5:3846. doi:10.1038/ncomms4846
Ahmed D, Ozcelik A, Bojanala N, Nama N, Upadhyay A, Chen Y, Hanna-Rose W, Huang TJ (2016) Rotational manipulation of single cells and organisms using acoustic waves. Nat Commun 7:11085. doi:10.1038/ncomms11085
Zhang H, Liu KK (2008) Optical tweezers for single cells. J R Soc Interface 5(24):671–690. doi:10.1098/rsif.2008.0052
Warkiani ME, Khoo BL, Wu L, Tay AK, Bhagat AA, Han J, Lim CT (2016) Ultra-fast, label-free isolation of circulating tumor cells from blood using spiral microfluidics. Nat Protoc 11(1):134–148. doi:10.1038/nprot.2016.003
Karabacak NM, Spuhler PS, Fachin F, Lim EJ, Pai V, Ozkumur E, Martel JM, Kojic N, Smith K, Chen PI, Yang J, Hwang H, Morgan B, Trautwein J, Barber TA, Stott SL, Maheswaran S, Kapur R, Haber DA, Toner M (2014) Microfluidic, marker-free isolation of circulating tumor cells from blood samples. Nat Protoc 9(3):694–710. doi:10.1038/nprot.2014.044
Collins DJ, Morahan B, Garcia-Bustos J, Doerig C, Plebanski M, Neild A (2015) Two-dimensional single-cell patterning with one cell per well driven by surface acoustic waves. Nat Commun 6:8686. doi:10.1038/ncomms9686
Voldman J (2006) Electrical forces for microscale cell manipulation. Annu Rev Biomed Eng 8:425–454. doi:10.1146/annurev.bioeng.8.061505.095739
Yasukawa T, Nagamine K, Horiguchi Y, Shiku H, Koide M, Itayama T, Shiraishi F, Matsue T (2008) Electrophoretic cell manipulation and electrochemical gene-function analysis based on a yeast two-hybrid system in a microfluidic device. Anal Chem 80(10):3722–3727. doi:10.1021/ac800143t
Park K, Suk HJ, Akin D, Bashir R (2009) Dielectrophoresis-based cell manipulation using electrodes on a reusable printed circuit board. Lab Chip 9(15):2224–2229. doi:10.1039/b904328d
Glawdel T, Ren CL (2009) Electro-osmotic flow control for living cell analysis in microfluidic PDMS chips. Mech Res Commun 36(1):75–81. doi:10.1016/j.mechrescom.2008.06.015
Geng T, Lu C (2013) Microfluidic electroporation for cellular analysis and delivery. Lab Chip 13(19):3803–3821. doi:10.1039/c3lc50566a
Wu W, Qu Y, Hu N, Zeng Y, Yang J, Xu H, Yin ZQ (2015) A cell electrofusion chip for somatic cells reprogramming. PLoS ONE 10(7):e0131966. doi:10.1371/journal.pone.0131966
Pethig R (2010) Review article-dielectrophoresis: status of the theory, technology, and applications. Biomicrofluidics 4(2). doi:10.1063/1.3456626
Mazutis L, Gilbert J, Ung WL, Weitz DA, Griffiths AD, Heyman JA (2013) Single-cell analysis and sorting using droplet-based microfluidics. Nat Protoc 8(5):870–891. doi:10.1038/nprot.2013.046
Yarmush ML, Golberg A, Sersa G, Kotnik T, Miklavcic D (2014) Electroporation-based technologies for medicine: principles, applications, and challenges. Annu Rev Biomed Eng 16:295–320. doi:10.1146/annurev-bioeng-071813-104622
Movahed S, Li D (2010) Microfluidics cell electroporation. Microfluid Nanofluid 10(4):703–734. doi:10.1007/s10404-010-0716-y
Garcia PA, Ge Z, Moran JL, Buie CR (2016) Microfluidic screening of electric fields for electroporation. Sci Rep 6:21238. doi:10.1038/srep21238
Qu B, Eu YJ, Jeong WJ, Kim DP (2012) Droplet electroporation in microfluidics for efficient cell transformation with or without cell wall removal. Lab Chip 12(21):4483–4488. doi:10.1039/c2lc40360a
Kang W, Giraldo-Vela JP, Nathamgari SS, McGuire T, McNaughton RL, Kessler JA, Espinosa HD (2014) Microfluidic device for stem cell differentiation and localized electroporation of postmitotic neurons. Lab Chip 14(23):4486–4495. doi:10.1039/c4lc00721b
Ogle BM, Cascalho M, Platt JL (2005) Biological implications of cell fusion. Nat Rev Mol Cell Biol 6(7):567–575. doi:10.1038/nrm1678
Hu N, Yang J, Joo SW, Banerjee AN, Qian S (2013) Cell electrofusion in microfluidic devices: a review. Sens Actuators B: Chem 178:63–85. doi:10.1016/j.snb.2012.12.034
Skelley AM, Kirak O, Suh H, Jaenisch R, Voldman J (2009) Microfluidic control of cell pairing and fusion. Nat Methods 6(2):147–152. doi:10.1038/nmeth.1290
Takayama S, Ostuni E, LeDuc P, Naruse K, Ingber DE, Whitesides GM (2001) Subcellular positioning of small molecules. Nature 411(6841):1016. doi:10.1038/35082637
Takayama S, Ostuni E, LeDuc P, Naruse K, Ingber DE, Whitesides GM (2003) Selective chemical treatment of cellular microdomains using multiple laminar streams. Chem Biol 10(2):123–130. doi:10.1016/s1074-5521(03)00019-x
Lee CY, Romanova EV, Sweedler JV (2013) Laminar stream of detergents for subcellular neurite damage in a microfluidic device: a simple tool for the study of neuroregeneration. J Neural Eng 10(3):036020. doi:10.1088/1741-2560/10/3/036020
Au AK, Lai H, Utela BR, Folch A (2011) Microvalves and micropumps for BioMEMS. Micromachines 2(4):179–220. doi:10.3390/mi2020179
Ogden S, Klintberg L, Thornell G, Hjort K, Bodén R (2013) Review on miniaturized paraffin phase change actuators, valves, and pumps. Microfluid Nanofluid 17(1):53–71. doi:10.1007/s10404-013-1289-3
Iverson BD, Garimella SV (2008) Recent advances in microscale pumping technologies: a review and evaluation. Microfluid Nanofluid 5(2):145–174. doi:10.1007/s10404-008-0266-8
Shen J, Cai C, Yu Z, Pang Y, Zhou Y, Qian L, Wei W, Huang Y (2015) A microfluidic live cell assay to study anthrax toxin induced cell lethality assisted by conditioned medium. Sci Rep 5:8651. doi:10.1038/srep08651
Taylor RJ, Falconnet D, Niemisto A, Ramsey SA, Prinz S, Shmulevich I, Galitski T, Hansen CL (2009) Dynamic analysis of MAPK signaling using a high-throughput microfluidic single-cell imaging platform. Proc Natl Acad Sci U S A 106(10):3758–3763. doi:10.1073/pnas.0813416106
Nguyen EH, Schwartz MP, Murphy WL (2011) Biomimetic approaches to control soluble concentration gradients in biomaterials. Macromol Biosci 11(4):483–492. doi:10.1002/mabi.201000448
Dhumpa R, Roper MG (2012) Temporal gradients in microfluidic systems to probe cellular dynamics: a review. Anal Chim Acta 743:9–18. doi:10.1016/j.aca.2012.07.006
Chung BG, Choo J (2010) Microfluidic gradient platforms for controlling cellular behavior. Electrophoresis 31(18):3014–3027. doi:10.1002/elps.201000137
Toh AGG, Wang ZP, Yang C, Nguyen N-T (2013) Engineering microfluidic concentration gradient generators for biological applications. Microfluid Nanofluid 16(1–2):1–18. doi:10.1007/s10404-013-1236-3
Lin F, Butcher EC (2006) T cell chemotaxis in a simple microfluidic device. Lab Chip 6(11):1462–1469. doi:10.1039/b607071j
Englert DL, Manson MD, Jayaraman A (2010) Investigation of bacterial chemotaxis in flow-based microfluidic devices. Nat Protoc 5(5):864–872. doi:10.1038/nprot.2010.18
Chung BG, Flanagan LA, Rhee SW, Schwartz PH, Lee AP, Monuki ES, Jeon NL (2005) Human neural stem cell growth and differentiation in a gradient-generating microfluidic device. Lab Chip 5(4):401–406. doi:10.1039/b417651k
Dertinger SK, Jiang X, Li Z, Murthy VN, Whitesides GM (2002) Gradients of substrate-bound laminin orient axonal specification of neurons. Proc Natl Acad Sci U S A 99(20):12542–12547. doi:10.1073/pnas.192457199
Gao D, Li H, Wang N, Lin JM (2012) Evaluation of the absorption of methotrexate on cells and its cytotoxicity assay by using an integrated microfluidic device coupled to a mass spectrometer. Anal Chem 84(21):9230–9237. doi:10.1021/ac301966c
Wu J, Wu X, Lin F (2013) Recent developments in microfluidics-based chemotaxis studies. Lab Chip 13(13):2484–2499. doi:10.1039/c3lc50415h
Kim S, Kim HJ, Jeon NL (2010) Biological applications of microfluidic gradient devices. Integr Biol (Camb) 2(11–12):584–603. doi:10.1039/c0ib00055h
Haessler U, Pisano M, Wu M, Swartz MA (2011) Dendritic cell chemotaxis in 3D under defined chemokine gradients reveals differential response to ligands CCL21 and CCL19. Proc Natl Acad Sci U S A 108(14):5614–5619. doi:10.1073/pnas.1014920108
Nguyen DH, Stapleton SC, Yang MT, Cha SS, Choi CK, Galie PA, Chen CS (2013) Biomimetic model to reconstitute angiogenic sprouting morphogenesis in vitro. Proc Natl Acad Sci U S A 110(17):6712–6717. doi:10.1073/pnas.1221526110
Chabaud M, Heuze ML, Bretou M, Vargas P, Maiuri P, Solanes P, Maurin M, Terriac E, Le Berre M, Lankar D, Piolot T, Adelstein RS, Zhang Y, Sixt M, Jacobelli J, Benichou O, Voituriez R, Piel M, Lennon-Dumenil AM (2015) Cell migration and antigen capture are antagonistic processes coupled by myosin II in dendritic cells. Nat Commun 6:7526. doi:10.1038/ncomms8526
Boneschansker L, Yan J, Wong E, Briscoe DM, Irimia D (2014) Microfluidic platform for the quantitative analysis of leukocyte migration signatures. Nat Commun 5:4787. doi:10.1038/ncomms5787
Vanapalli SA, Duits MH, Mugele F (2009) Microfluidics as a functional tool for cell mechanics. Biomicrofluidics 3(1):12006. doi:10.1063/1.3067820
Tee SY, Bausch AR, Janmey PA (2009) The mechanical cell. Curr Biol 19(17):R745–R748. doi:10.1016/j.cub.2009.06.034
Polacheck WJ, Li R, Uzel SG, Kamm RD (2013) Microfluidic platforms for mechanobiology. Lab Chip 13(12):2252–2267. doi:10.1039/c3lc41393d
Jain A, Graveline A, Waterhouse A, Vernet A, Flaumenhaft R, Ingber DE (2016) A shear gradient-activated microfluidic device for automated monitoring of whole blood haemostasis and platelet function. Nat Commun 7:10176. doi:10.1038/ncomms10176
Sundd P, Gutierrez E, Koltsova EK, Kuwano Y, Fukuda S, Pospieszalska MK, Groisman A, Ley K (2012) ‘Slings’ enable neutrophil rolling at high shear. Nature 488(7411):399–403. doi:10.1038/nature11248
Sundd P, Gutierrez E, Pospieszalska MK, Zhang H, Groisman A, Ley K (2010) Quantitative dynamic footprinting microscopy reveals mechanisms of neutrophil rolling. Nat Methods 7(10):821–824. doi:10.1038/nmeth.1508
Miura S, Sato K, Kato-Negishi M, Teshima T, Takeuchi S (2015) Fluid shear triggers microvilli formation via mechanosensitive activation of TRPV6. Nat Commun 6:8871. doi:10.1038/ncomms9871
Humphrey JD, Dufresne ER, Schwartz MA (2014) Mechanotransduction and extracellular matrix homeostasis. Nat Rev Mol Cell Biol 15(12):802–812. doi:10.1038/nrm3896
Hsieh HY, Camci-Unal G, Huang TW, Liao R, Chen TJ, Paul A, Tseng FG, Khademhosseini A (2014) Gradient static-strain stimulation in a microfluidic chip for 3D cellular alignment. Lab Chip 14(3):482–493. doi:10.1039/c3lc50884f
Kollmannsperger A, Sharei A, Raulf A, Heilemann M, Langer R, Jensen KF, Wieneke R, Tampe R (2016) Live-cell protein labelling with nanometre precision by cell squeezing. Nat Commun 7:10372. doi:10.1038/ncomms10372
Si F, Li B, Margolin W, Sun SX (2015) Bacterial growth and form under mechanical compression. Sci Rep 5:11367. doi:10.1038/srep11367
Wells RG (2008) The role of matrix stiffness in regulating cell behavior. Hepatology 47(4):1394–1400. doi:10.1002/hep.22193
Sundararaghavan HG, Monteiro GA, Firestein BL, Shreiber DI (2009) Neurite growth in 3D collagen gels with gradients of mechanical properties. Biotechnol Bioeng 102(2):632–643. doi:10.1002/bit.22074
Garcia S, Sunyer R, Olivares A, Noailly J, Atencia J, Trepat X (2015) Generation of stable orthogonal gradients of chemical concentration and substrate stiffness in a microfluidic device. Lab Chip 15(12):2606–2614. doi:10.1039/c5lc00140d
Polacheck WJ, Chen CS (2016) Measuring cell-generated forces: a guide to the available tools. Nat Methods 13(5):415–423. doi:10.1038/nmeth.3834
Tan JL, Tien J, Pirone DM, Gray DS, Bhadriraju K, Chen CS (2003) Cells lying on a bed of microneedles: an approach to isolate mechanical force. Proc Natl Acad Sci U S A 100(4):1484–1489. doi:10.1073/pnas.0235407100
du Roure O, Saez A, Buguin A, Austin RH, Chavrier P, Silberzan P, Ladoux B (2005) Force mapping in epithelial cell migration. Proc Natl Acad Sci U S A 102(7):2390–2395. doi:10.1073/pnas.0408482102
Fu J, Wang YK, Yang MT, Desai RA, Yu X, Liu Z, Chen CS (2010) Mechanical regulation of cell function with geometrically modulated elastomeric substrates. Nat Methods 7(9):733–736. doi:10.1038/nmeth.1487
Ghassemi S, Meacci G, Liu S, Gondarenko AA, Mathur A, Roca-Cusachs P, Sheetz MP, Hone J (2012) Cells test substrate rigidity by local contractions on submicrometer pillars. Proc Natl Acad Sci U S A 109(14):5328–5333. doi:10.1073/pnas.1119886109
Trichet L, Le Digabel J, Hawkins RJ, Vedula SR, Gupta M, Ribrault C, Hersen P, Voituriez R, Ladoux B (2012) Evidence of a large-scale mechanosensing mechanism for cellular adaptation to substrate stiffness. Proc Natl Acad Sci U S A 109(18):6933–6938. doi:10.1073/pnas.1117810109
Zare RN, Kim S (2010) Microfluidic platforms for single-cell analysis. Annu Rev Biomed Eng 12:187–201. doi:10.1146/annurev-bioeng-070909-105238
Chen Y, Li P, Huang PH, Xie Y, Mai JD, Wang L, Nguyen NT, Huang TJ (2014) Rare cell isolation and analysis in microfluidics. Lab Chip 14(4):626–645. doi:10.1039/c3lc90136j
Autebert J, Coudert B, Bidard FC, Pierga JY, Descroix S, Malaquin L, Viovy JL (2012) Microfluidic: an innovative tool for efficient cell sorting. Methods 57(3):297–307. doi:10.1016/j.ymeth.2012.07.002
Gao Y, Li W, Pappas D (2013) Recent advances in microfluidic cell separations. Analyst 138(17):4714–4721. doi:10.1039/c3an00315a
Gossett DR, Weaver WM, Mach AJ, Hur SC, Tse HT, Lee W, Amini H, Di Carlo D (2010) Label-free cell separation and sorting in microfluidic systems. Anal Bioanal Chem 397(8):3249–3267. doi:10.1007/s00216-010-3721-9
Plouffe BD, Murthy SK (2014) Perspective on microfluidic cell separation: a solved problem? Anal Chem 86(23):11481–11488. doi:10.1021/ac5013283
Bhagat AA, Bow H, Hou HW, Tan SJ, Han J, Lim CT (2010) Microfluidics for cell separation. Med Biol Eng Comput 48(10):999–1014. doi:10.1007/s11517-010-0611-4
Warkiani ME, Wu L, Tay AK, Han J (2015) Large-volume microfluidic cell sorting for biomedical applications. Annu Rev Biomed Eng 17:1–34. doi:10.1146/annurev-bioeng-071114-040818
Stott SL, Hsu CH, Tsukrov DI, Yu M, Miyamoto DT, Waltman BA, Rothenberg SM, Shah AM, Smas ME, Korir GK, Floyd FP Jr, Gilman AJ, Lord JB, Winokur D, Springer S, Irimia D, Nagrath S, Sequist LV, Lee RJ, Isselbacher KJ, Maheswaran S, Haber DA, Toner M (2010) Isolation of circulating tumor cells using a microvortex-generating herringbone-chip. Proc Natl Acad Sci U S A 107(43):18392–18397. doi:10.1073/pnas.1012539107
Yu M, Bardia A, Wittner BS, Stott SL, Smas ME, Ting DT, Isakoff SJ, Ciciliano JC, Wells MN, Shah AM, Concannon KF, Donaldson MC, Sequist LV, Brachtel E, Sgroi D, Baselga J, Ramaswamy S, Toner M, Haber DA, Maheswaran S (2013) Circulating breast tumor cells exhibit dynamic changes in epithelial and mesenchymal composition. Science 339(6119):580–584. doi:10.1126/science.1228522
Chen Q, Wu J, Zhang Y, Lin Z, Lin JM (2012) Targeted isolation and analysis of single tumor cells with aptamer-encoded microwell array on microfluidic device. Lab Chip 12(24):5180–5185. doi:10.1039/c2lc40858a
Herzenberg LA, Parks D, Sahaf B, Perez O, Roederer M, Herzenberg LA (2002) The history and future of the fluorescence activated cell sorter and flow cytometry: a view from Stanford. Clin Chem 48(10):1819–1827
Lenshof A, Laurell T (2010) Continuous separation of cells and particles in microfluidic systems. Chem Soc Rev 39(3):1203–1217. doi:10.1039/b915999c
Yao B, Luo GA, Feng X, Wang W, Chen LX, Wang YM (2004) A microfluidic device based on gravity and electric force driving for flow cytometry and fluorescence activated cell sorting. Lab Chip 4(6):603–607. doi:10.1039/b408422e
Baret JC, Miller OJ, Taly V, Ryckelynck M, El-Harrak A, Frenz L, Rick C, Samuels ML, Hutchison JB, Agresti JJ, Link DR, Weitz DA, Griffiths AD (2009) Fluorescence-activated droplet sorting (FADS): efficient microfluidic cell sorting based on enzymatic activity. Lab Chip 9(13):1850–1858. doi:10.1039/b902504a
Sun Y, Lim CS, Liu AQ, Ayi TC, Yap PH (2007) Design, simulation and experiment of electroosmotic microfluidic chip for cell sorting. Sens Actuators A: Phys 133(2):340–348. doi:10.1016/j.sna.2006.06.047
Austin Suthanthiraraj PP, Piyasena ME, Woods TA, Naivar MA, Lomicronpez GP, Graves SW (2012) One-dimensional acoustic standing waves in rectangular channels for flow cytometry. Methods 57(3):259–271. doi:10.1016/j.ymeth.2012.02.013
Johansson L, Nikolajeff F, Johansson S, Thorslund S (2009) On-chip fluorescence-activated cell sorting by an integrated miniaturized ultrasonic transducer. Anal Chem 81(13):5188–5196. doi:10.1021/ac802681r
Wu TH, Chen Y, Park SY, Hong J, Teslaa T, Zhong JF, Di Carlo D, Teitell MA, Chiou PY (2012) Pulsed laser triggered high speed microfluidic fluorescence activated cell sorter. Lab Chip 12(7):1378–1383. doi:10.1039/c2lc21084c
Yung CW, Fiering J, Mueller AJ, Ingber DE (2009) Micromagnetic-microfluidic blood cleansing device. Lab Chip 9(9):1171–1177. doi:10.1039/b816986a
Hoshino K, Huang YY, Lane N, Huebschman M, Uhr JW, Frenkel EP, Zhang X (2011) Microchip-based immunomagnetic detection of circulating tumor cells. Lab Chip 11(20):3449–3457. doi:10.1039/c1lc20270g
Xia N, Hunt TP, Mayers BT, Alsberg E, Whitesides GM, Westervelt RM, Ingber DE (2006) Combined microfluidic-micromagnetic separation of living cells in continuous flow. Biomed Microdevices 8(4):299–308. doi:10.1007/s10544-006-0033-0
Kim S, Han SI, Park MJ, Jeon CW, Joo YD, Choi IH, Han KH (2013) Circulating tumor cell microseparator based on lateral magnetophoresis and immunomagnetic nanobeads. Anal Chem 85(5):2779–2786. doi:10.1021/ac303284u
Brown RB, Audet J (2008) Current techniques for single-cell lysis. J R Soc Interface 5(Suppl 2):S131–S138. doi:10.1098/rsif.2008.0009.focus
Nan L, Jiang Z, Wei X (2014) Emerging microfluidic devices for cell lysis: a review. Lab Chip 14(6):1060–1073. doi:10.1039/c3lc51133b
Hosic S, Murthy SK, Koppes AN (2016) Microfluidic sample preparation for single cell analysis. Anal Chem 88(1):354–380. doi:10.1021/acs.analchem.5b04077
Yun SS, Yoon SY, Song MK, Im SH, Kim S, Lee JH, Yang S (2010) Handheld mechanical cell lysis chip with ultra-sharp silicon nano-blade arrays for rapid intracellular protein extraction. Lab Chip 10(11):1442–1446. doi:10.1039/b925244d
Kim J, Hee Jang S, Jia G, Zoval JV, Da Silva NA, Madou MJ (2004) Cell lysis on a microfluidic CD (compact disc). Lab Chip 4(5):516–522. doi:10.1039/b401106f
Siegrist J, Gorkin R, Bastien M, Stewart G, Peytavi R, Kido H, Bergeron M, Madou M (2010) Validation of a centrifugal microfluidic sample lysis and homogenization platform for nucleic acid extraction with clinical samples. Lab Chip 10(3):363–371. doi:10.1039/b913219h
Mellors JS, Jorabchi K, Smith LM, Ramsey JM (2010) Integrated microfluidic device for automated single cell analysis using electrophoretic separation and electrospray ionization mass spectrometry. Anal Chem 82(3):967–973. doi:10.1021/ac902218y
Jokilaakso N, Salm E, Chen A, Millet L, Guevara CD, Dorvel B, Reddy B Jr, Karlstrom AE, Chen Y, Ji H, Chen Y, Sooryakumar R, Bashir R (2013) Ultra-localized single cell electroporation using silicon nanowires. Lab Chip 13(3):336–339. doi:10.1039/c2lc40837f
Lee C-Y, Lee G-B, Lin J-L, Huang F-C, Liao C-S (2005) Integrated microfluidic systems for cell lysis, mixing/pumping and DNA amplification. J Micromech Microeng 15(6):1215–1223. doi:10.1088/0960-1317/15/6/011
Sarkar A, Kolitz S, Lauffenburger DA, Han J (2014) Microfluidic probe for single-cell analysis in adherent tissue culture. Nat Commun 5:3421. doi:10.1038/ncomms4421
Yang W, Woolley AT (2010) Integrated multi-process microfluidic systems for automating analysis. JALA Charlottesv Va 15(3):198–209. doi:10.1016/j.jala.2010.01.008
Cui F, Rhee M, Singh A, Tripathi A (2015) Microfluidic sample preparation for medical diagnostics. Annu Rev Biomed Eng 17:267–286. doi:10.1146/annurev-bioeng-071114-040538
Wu D, Qin J, Lin B (2008) Electrophoretic separations on microfluidic chips. J Chromatogr A 1184(1–2):542–559. doi:10.1016/j.chroma.2007.11.119
Cong H, Xu X, Yu B, Yuan H, Peng Q, Tian C (2015) Recent progress in preparation and application of microfluidic chip electrophoresis. J Micromech Microeng 25(5):053001. doi:10.1088/0960-1317/25/5/053001
Karlinsey JM (2012) Sample introduction techniques for microchip electrophoresis: a review. Anal Chim Acta 725:1–13. doi:10.1016/j.aca.2012.02.052
Liu P, Yeung SH, Crenshaw KA, Crouse CA, Scherer JR, Mathies RA (2008) Real-time forensic DNA analysis at a crime scene using a portable microchip analyzer. Forensic Sci Int Genet 2(4):301–309. doi:10.1016/j.fsigen.2008.03.009
Lin X, Chen Q, Liu W, Yi L, Li H, Wang Z, Lin JM (2015) Assay of multiplex proteins from cell metabolism based on tunable aptamer and microchip electrophoresis. Biosens Bioelectron 63:105–111. doi:10.1016/j.bios.2014.07.013
Smejkal P, Bottenus D, Breadmore MC, Guijt RM, Ivory CF, Foret F, Macka M (2013) Microfluidic isotachophoresis: a review. Electrophoresis 34(11):1493–1509. doi:10.1002/elps.201300021
Schoch RB, Ronaghi M, Santiago JG (2009) Rapid and selective extraction, isolation, preconcentration, and quantitation of small RNAs from cell lysate using on-chip isotachophoresis. Lab Chip 9(15):2145–2152. doi:10.1039/b903542g
Tetala KK, Vijayalakshmi MA (2016) A review on recent developments for biomolecule separation at analytical scale using microfluidic devices. Anal Chim Acta 906:7–21. doi:10.1016/j.aca.2015.11.037
Wu R, Hu L, Wang F, Ye M, Zou H (2008) Recent development of monolithic stationary phases with emphasis on microscale chromatographic separation. J Chromatogr A 1184(1–2):369–392. doi:10.1016/j.chroma.2007.09.022
Lin SL, Lin TY, Fuh MR (2014) Microfluidic chip-based liquid chromatography coupled to mass spectrometry for determination of small molecules in bioanalytical applications: an update. Electrophoresis 35(9):1275–1284. doi:10.1002/elps.201300415
Chen ZW, Fuchs K, Sieghart W, Townsend RR, Evers AS (2012) Deep amino acid sequencing of native brain GABAA receptors using high-resolution mass spectrometry. Mol Cell Proteomics 11(1):M111 011445
Hwang KY, Kwon SH, Jung SO, Namkoong K, Jung WJ, Kim JH, Suh KY, Huh N (2012) Solid phase DNA extraction with a flexible bead-packed microfluidic device to detect methicillin-resistant Staphylococcus aureus in nasal swabs. Anal Chem 84(18):7912–7918. doi:10.1021/ac3016533
Kumar S, Sahore V, Rogers CI, Woolley AT (2016) Development of an integrated microfluidic solid-phase extraction and electrophoresis device. Analyst 141(5):1660–1668. doi:10.1039/c5an02352a
Ramsey JD, Collins GE (2005) Integrated microfluidic device for solid-phase extraction coupled to micellar electrokinetic chromatography separation. Anal Chem 77(20):6664–6670. doi:10.1021/ac0507789
Mao S, Zhang J, Li H, Lin JM (2013) Strategy for signaling molecule detection by using an integrated microfluidic device coupled with mass spectrometry to study cell-to-cell communication. Anal Chem 85(2):868–876. doi:10.1021/ac303164b
Zhang J, Wu J, Li H, Chen Q, Lin JM (2015) An in vitro liver model on microfluidic device for analysis of capecitabine metabolite using mass spectrometer as detector. Biosens Bioelectron 68:322–328. doi:10.1016/j.bios.2015.01.013
Gao D, Liu H, Lin JM, Wang Y, Jiang Y (2013) Characterization of drug permeability in Caco-2 monolayers by mass spectrometry on a membrane-based microfluidic device. Lab Chip 13(5):978–985. doi:10.1039/c2lc41215b
Hagan KA, Meier WL, Ferrance JP, Landers JP (2009) Chitosan-coated silica as a solid phase for RNA purification in a microfluidic device. Anal Chem 81(13):5249–5256. doi:10.1021/ac900820z
Tia S, Herr AE (2009) On-chip technologies for multidimensional separations. Lab Chip 9(17):2524–2536. doi:10.1039/b900683b
Emrich CA, Medintz IL, Chu WK, Mathies RA (2007) Microfabricated two-dimensional electrophoresis device for differential protein expression profiling. Anal Chem 79(19):7360–7366. doi:10.1021/ac0711485
Choi JR, Song H, Sung JH, Kim D, Kim K (2016) Microfluidic assay-based optical measurement techniques for cell analysis: a review of recent progress. Biosens Bioelectron 77:227–236. doi:10.1016/j.bios.2015.07.068
Chrimes AF, Khoshmanesh K, Stoddart PR, Mitchell A, Kalantar-Zadeh K (2013) Microfluidics and Raman microscopy: current applications and future challenges. Chem Soc Rev 42(13):5880–5906. doi:10.1039/c3cs35515b
Perro A, Lebourdon G, Henry S, Lecomte S, Servant L, Marre S (2016) Combining microfluidics and FT-IR spectroscopy: towards spatially resolved information on chemical processes. React Chem Eng. doi:10.1039/c6re00127k
Kuswandi B, Nuriman, Huskens J, Verboom W (2007) Optical sensing systems for microfluidic devices: a review. Anal Chim Acta 601(2):141–155. doi:10.1016/j.aca.2007.08.046
Rackus DG, Shamsi MH, Wheeler AR (2015) Electrochemistry, biosensors and microfluidics: a convergence of fields. Chem Soc Rev 44(15):5320–5340. doi:10.1039/c4cs00369a
Kiilerich-Pedersen K, Rozlosnik N (2012) Cell-Based biosensors: electrical sensing in microfluidic devices. Diagnostics (Basel) 2(4):83–96. doi:10.3390/diagnostics2040083
D’hahan NP (2011) Live cell analysis: when electric detection interfaces microfluidics. J Biochips Tissue Chips 01(01). doi:10.4172/2153-0777.s1-001
Rossier J, Reymond F, Michel PE (2002) Polymer microfluidic chips for electrochemical and biochemical analyses. Electrophoresis 23(6):858–867. doi:10.1002/1522-2683(200203)23:6<858:AID-ELPS858>3.0.CO;2-3
Wang X, Yi L, Mukhitov N, Schrell AM, Dhumpa R, Roper MG (2015) Microfluidics-to-mass spectrometry: a review of coupling methods and applications. J Chromatogr A 1382:98–116. doi:10.1016/j.chroma.2014.10.039
Gao D, Liu H, Jiang Y, Lin JM (2013) Recent advances in microfluidics combined with mass spectrometry: technologies and applications. Lab Chip 13(17):3309–3322. doi:10.1039/c3lc50449b
Feng X, Liu BF, Li J, Liu X (2015) Advances in coupling microfluidic chips to mass spectrometry. Mass Spectrom Rev 34(5):535–557. doi:10.1002/mas.21417
Mao X, Huang TJ (2012) Microfluidic diagnostics for the developing world. Lab Chip 12(8):1412–1416. doi:10.1039/c2lc90022j
Chen J, Li J, Sun Y (2012) Microfluidic approaches for cancer cell detection, characterization, and separation. Lab Chip 12(10):1753–1767. doi:10.1039/c2lc21273k
Giobbe GG, Michielin F, Luni C, Giulitti S, Martewicz S, Dupont S, Floreani A, Elvassore N (2015) Functional differentiation of human pluripotent stem cells on a chip. Nat Methods 12(7):637–640. doi:10.1038/nmeth.3411
Lewis DM, Gerecht S (2016) Microfluidics and biomaterials to study angiogenesis. Curr Opin Chem Eng 11:114–122. doi:10.1016/j.coche.2016.02.005
Huang Y, Agrawal B, Sun D, Kuo JS, Williams JC (2011) Microfluidics-based devices: new tools for studying cancer and cancer stem cell migration. Biomicrofluidics 5(1):13412. doi:10.1063/1.3555195
Chung S, Sudo R, Vickerman V, Zervantonakis IK, Kamm RD (2010) Microfluidic platforms for studies of angiogenesis, cell migration, and cell-cell interactions. Ann Biomed Eng 38(3):1164–1177. doi:10.1007/s10439-010-9899-3
Kim C, Kasuya J, Jeon J, Chung S, Kamm RD (2015) A quantitative microfluidic angiogenesis screen for studying anti-angiogenic therapeutic drugs. Lab Chip 15(1):301–310. doi:10.1039/c4lc00866a
Haandbaek N, Burgel SC, Heer F, Hierlemann A (2014) Characterization of subcellular morphology of single yeast cells using high frequency microfluidic impedance cytometer. Lab Chip 14(2):369–377. doi:10.1039/c3lc50866h
Kim J, Johnson M, Hill P, Gale BK (2009) Microfluidic sample preparation: cell lysis and nucleic acid purification. Integr Biol (Camb) 1(10):574–586. doi:10.1039/b905844c
Chang CM, Chang WH, Wang CH, Wang JH, Mai JD, Lee GB (2013) Nucleic acid amplification using microfluidic systems. Lab Chip 13(7):1225–1242. doi:10.1039/c3lc41097h
Wu J, Kodzius R, Cao W, Wen W (2013) Extraction, amplification and detection of DNA in microfluidic chip-based assays. Microchim Acta 181(13–14):1611–1631. doi:10.1007/s00604-013-1140-2
Mauk MG, Liu C, Song J, Bau HH (2015) Integrated microfluidic nucleic acid isolation, isothermal amplification, and amplicon quantification. Microarrays (Basel) 4(4):474–489. doi:10.3390/microarrays4040474
Zhang R, Li X, Ramaswami G, Smith KS, Turecki G, Montgomery SB, Li JB (2014) Quantifying RNA allelic ratios by microfluidic multiplex PCR and sequencing. Nat Methods 11(1):51–54. doi:10.1038/nmeth.2736
Fang X, Chen H, Xu L, Jiang X, Wu W, Kong J (2012) A portable and integrated nucleic acid amplification microfluidic chip for identifying bacteria. Lab Chip 12(8):1495–1499. doi:10.1039/c2lc40055c
Liu P, Mathies RA (2009) Integrated microfluidic systems for high-performance genetic analysis. Trends Biotechnol 27(10):572–581. doi:10.1016/j.tibtech.2009.07.002
Foudeh AM, Fatanat Didar T, Veres T, Tabrizian M (2012) Microfluidic designs and techniques using lab-on-a-chip devices for pathogen detection for point-of-care diagnostics. Lab Chip 12(18):3249–3266. doi:10.1039/c2lc40630f
Horsman KM, Bienvenue JM, Blasier KR, Landers JP (2007) Forensic DNA analysis on microfluidic devices: a review. J Forensic Sci 52(4):784–799. doi:10.1111/j.1556-4029.2007.00468.x
Zheng GX, Lau BT, Schnall-Levin M, Jarosz M, Bell JM, Hindson CM, Kyriazopoulou-Panagiotopoulou S, Masquelier DA, Merrill L, Terry JM, Mudivarti PA, Wyatt PW, Bharadwaj R, Makarewicz AJ, Li Y, Belgrader P, Price AD, Lowe AJ, Marks P, Vurens GM, Hardenbol P, Montesclaros L, Luo M, Greenfield L, Wong A, Birch DE, Short SW, Bjornson KP, Patel P, Hopmans ES, Wood C, Kaur S, Lockwood GK, Stafford D, Delaney JP, Wu I, Ordonez HS, Grimes SM, Greer S, Lee JY, Belhocine K, Giorda KM, Heaton WH, McDermott GP, Bent ZW, Meschi F, Kondov NO, Wilson R, Bernate JA, Gauby S, Kindwall A, Bermejo C, Fehr AN, Chan A, Saxonov S, Ness KD, Hindson BJ, Ji HP (2016) Haplotyping germline and cancer genomes with high-throughput linked-read sequencing. Nat Biotechnol 34(3):303–311. doi:10.1038/nbt.3432
Ting DT, Wittner BS, Ligorio M, Vincent Jordan N, Shah AM, Miyamoto DT, Aceto N, Bersani F, Brannigan BW, Xega K, Ciciliano JC, Zhu H, MacKenzie OC, Trautwein J, Arora KS, Shahid M, Ellis HL, Qu N, Bardeesy N, Rivera MN, Deshpande V, Ferrone CR, Kapur R, Ramaswamy S, Shioda T, Toner M, Maheswaran S, Haber DA (2014) Single-cell RNA sequencing identifies extracellular matrix gene expression by pancreatic circulating tumor cells. Cell Rep 8(6):1905–1918. doi:10.1016/j.celrep.2014.08.029
Kimmerling RJ, Lee Szeto G, Li JW, Genshaft AS, Kazer SW, Payer KR, de Riba Borrajo J, Blainey PC, Irvine DJ, Shalek AK, Manalis SR (2016) A microfluidic platform enabling single-cell RNA-seq of multigenerational lineages. Nat Commun 7:10220. doi:10.1038/ncomms10220
Sanchez-Freire V, Ebert AD, Kalisky T, Quake SR, Wu JC (2012) Microfluidic single-cell real-time PCR for comparative analysis of gene expression patterns. Nat Protoc 7(5):829–838. doi:10.1038/nprot.2012.021
Streets AM, Zhang X, Cao C, Pang Y, Wu X, Xiong L, Yang L, Fu Y, Zhao L, Tang F, Huang Y (2014) Microfluidic single-cell whole-transcriptome sequencing. Proc Natl Acad Sci U S A 111(19):7048–7053. doi:10.1073/pnas.1402030111
Shalek AK, Satija R, Shuga J, Trombetta JJ, Gennert D, Lu D, Chen P, Gertner RS, Gaublomme JT, Yosef N, Schwartz S, Fowler B, Weaver S, Wang J, Wang X, Ding R, Raychowdhury R, Friedman N, Hacohen N, Park H, May AP, Regev A (2014) Single-cell RNA-seq reveals dynamic paracrine control of cellular variation. Nature 510(7505):363–369. doi:10.1038/nature13437
Cao Z, Chen C, He B, Tan K, Lu C (2015) A microfluidic device for epigenomic profiling using 100 cells. Nat Methods 12(10):959–962. doi:10.1038/nmeth.3488
Bennett MR, Hasty J (2009) Microfluidic devices for measuring gene network dynamics in single cells. Nat Rev Genet 10(9):628–638. doi:10.1038/nrg2625
Toriello NM, Douglas ES, Thaitrong N, Hsiao SC, Francis MB, Bertozzi CR, Mathies RA (2008) Integrated microfluidic bioprocessor for single-cell gene expression analysis. Proc Natl Acad Sci U S A 105(51):20173–20178. doi:10.1073/pnas.0806355106
Busch W, Moore BT, Martsberger B, Mace DL, Twigg RW, Jung J, Pruteanu-Malinici I, Kennedy SJ, Fricke GK, Clark RL, Ohler U, Benfey PN (2012) A microfluidic device and computational platform for high-throughput live imaging of gene expression. Nat Methods 9(11):1101–1106. doi:10.1038/nmeth.2185
Yu J, Zhou J, Sutherland A, Wei W, Shin YS, Xue M, Heath JR (2014) Microfluidics-based single-cell functional proteomics for fundamental and applied biomedical applications. Annu Rev Anal Chem (Palo Alto Calif) 7:275–295. doi:10.1146/annurev-anchem-071213-020323
Sun J, Masterman-Smith MD, Graham NA, Jiao J, Mottahedeh J, Laks DR, Ohashi M, DeJesus J, Kamei K, Lee KB, Wang H, Yu ZT, Lu YT, Hou S, Li K, Liu M, Zhang N, Wang S, Angenieux B, Panosyan E, Samuels ER, Park J, Williams D, Konkankit V, Nathanson D, van Dam RM, Phelps ME, Wu H, Liau LM, Mischel PS, Lazareff JA, Kornblum HI, Yong WH, Graeber TG, Tseng HR (2010) A microfluidic platform for systems pathology: multiparameter single-cell signaling measurements of clinical brain tumor specimens. Cancer Res 70(15):6128–6138. doi:10.1158/0008-5472.CAN-10-0076
Nguyen CQ, Ogunniyi AO, Karabiyik A, Love JC (2013) Single-cell analysis reveals isotype-specific autoreactive B cell repertoires in Sjogren’s syndrome. PLoS ONE 8(3):e58127. doi:10.1371/journal.pone.0058127
Bailey RC, Kwong GA, Radu CG, Witte ON, Heath JR (2007) DNA-encoded antibody libraries: a unified platform for multiplexed cell sorting and detection of genes and proteins. J Am Chem Soc 129(7):1959–1967. doi:10.1021/ja065930i
Xue M, Wei W, Su Y, Kim J, Shin YS, Mai WX, Nathanson DA, Heath JR (2015) Chemical methods for the simultaneous quantitation of metabolites and proteins from single cells. J Am Chem Soc 137(12):4066–4069. doi:10.1021/jacs.5b00944
Ma C, Fan R, Ahmad H, Shi Q, Comin-Anduix B, Chodon T, Koya RC, Liu CC, Kwong GA, Radu CG, Ribas A, Heath JR (2011) A clinical microchip for evaluation of single immune cells reveals high functional heterogeneity in phenotypically similar T cells. Nat Med 17(6):738–743. doi:10.1038/nm.2375
Poovathingal SK, Kravchenko-Balasha N, Shin YS, Levine RD, Heath JR (2016) Critical points in Tumorigenesis: a carcinogen-initiated phase transition analyzed via single-cell proteomics. Small 12(11):1425–1431. doi:10.1002/smll.201501178
He M, Herr AE (2010) Automated microfluidic protein immunoblotting. Nat Protoc 5(11):1844–1856. doi:10.1038/nprot.2010.142
Hughes AJ, Herr AE (2012) Microfluidic Western blotting. Proc Natl Acad Sci U S A 109(52):21450–21455. doi:10.1073/pnas.1207754110
Hughes AJ, Spelke DP, Xu Z, Kang CC, Schaffer DV, Herr AE (2014) Single-cell western blotting. Nat Methods 11(7):749–755. doi:10.1038/nmeth.2992
Kang CC, Yamauchi KA, Vlassakis J, Sinkala E, Duncombe TA, Herr AE (2016) Single cell-resolution western blotting. Nat Protoc 11(8):1508–1530. doi:10.1038/nprot.2016.089
Lee JR, Bechstein DJ, Ooi CC, Patel A, Gaster RS, Ng E, Gonzalez LC, Wang SX (2016) Magneto-nanosensor platform for probing low-affinity protein-protein interactions and identification of a low-affinity PD-L1/PD-L2 interaction. Nat Commun 7:12220. doi:10.1038/ncomms12220
Lee J, Soper SA, Murray KK (2009) Microfluidic chips for mass spectrometry-based proteomics. J Mass Spectrom 44(5):579–593. doi:10.1002/jms.1585
Chao TC, Hansmeier N (2013) Microfluidic devices for high-throughput proteome analyses. Proteomics 13(3–4):467–479. doi:10.1002/pmic.201200411
Vollmer M, Hörth P, Rozing G, Couté Y, Grimm R, Hochstrasser D, Sanchez J-C (2006) Multi-dimensional HPLC/MS of the nucleolar proteome using HPLC-chip/MS. J Sep Sci 29(4):499–509. doi:10.1002/jssc.200500334
Lee J, Soper SA, Murray KK (2009) Microfluidics with MALDI analysis for proteomics—a review. Anal Chim Acta 649(2):180–190. doi:10.1016/j.aca.2009.07.037
Lee J, Soper SA, Murray KK (2011) A solid-phase bioreactor with continuous sample deposition for matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. Rapid Commun Mass Spectrom 25(6):693–699. doi:10.1002/rcm.4921
Rubakhin SS, Romanova EV, Nemes P, Sweedler JV (2011) Profiling metabolites and peptides in single cells. Nat Methods 8(4 Suppl):S20–S29. doi:10.1038/nmeth.1549
Kraly JR, Holcomb RE, Guan Q, Henry CS (2009) Review: microfluidic applications in metabolomics and metabolic profiling. Anal Chim Acta 653(1):23–35. doi:10.1016/j.aca.2009.08.037
Lin L, Lin JM (2015) Development of cell metabolite analysis on microfluidic platform. J Pharm Anal 5(6):337–347. doi:10.1016/j.jpha.2015.09.003
He X, Chen Q, Zhang Y, Lin JM (2014) Recent advances in microchip-mass spectrometry for biological analysis. TrAC Trends Anal Chem 53:84–97. doi:10.1016/j.trac.2013.09.013
Liu W, Wang N, Lin X, Ma Y, Lin JM (2014) Interfacing microsampling droplets and mass spectrometry by paper spray ionization for online chemical monitoring of cell culture. Anal Chem 86(14):7128–7134. doi:10.1021/ac501678q
Mao S, Gao D, Liu W, Wei H, Lin JM (2012) Imitation of drug metabolism in human liver and cytotoxicity assay using a microfluidic device coupled to mass spectrometric detection. Lab Chip 12(1):219–226. doi:10.1039/c1lc20678h
Chen Q, Wu J, Zhang Y, Lin JM (2012) Qualitative and quantitative analysis of tumor cell metabolism via stable isotope labeling assisted microfluidic chip electrospray ionization mass spectrometry. Anal Chem 84(3):1695–1701. doi:10.1021/ac300003k
Zhuang Q, Wang S, Zhang J, He Z, Li H, Ma Y, Lin JM (2015) Nephrocyte-neurocyte interaction and cellular metabolic analysis on membrane-integrated microfluidic device. Sci China Chem 59(2):243–250. doi:10.1007/s11426-015-5453-3
Wang BL, Ghaderi A, Zhou H, Agresti J, Weitz DA, Fink GR, Stephanopoulos G (2014) Microfluidic high-throughput culturing of single cells for selection based on extracellular metabolite production or consumption. Nat Biotechnol 32(5):473–478. doi:10.1038/nbt.2857
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Singapore Pte Ltd.
About this chapter
Cite this chapter
He, Z., Lin, JM. (2018). Recent Development of Cell Analysis on Microfludics. In: Lin, JM. (eds) Cell Analysis on Microfluidics. Integrated Analytical Systems. Springer, Singapore. https://doi.org/10.1007/978-981-10-5394-8_2
Download citation
DOI: https://doi.org/10.1007/978-981-10-5394-8_2
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-5393-1
Online ISBN: 978-981-10-5394-8
eBook Packages: Chemistry and Materials ScienceChemistry and Material Science (R0)