Microscale technologies for stem cell culture

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Microscale technologies for stem cell culture

DOI: 10.1533/9781908818300.143 Abstract: Microscale technologies provide powerful experimental tools for a wide range of relevant applications in stem cell research, including high-throughput screening of large numbers of test samples. Miniaturization increases assay throughput, while reducing reagent consumption and the number of cells required, which makes these platforms attractive for a wide range of applications in drug discovery, toxicology and stem cell research. In this chapter we provide an overview of the emerging technologies that can be used to generate different microscale devices, in addition to highlighting significant advances in the field. This emerging and multidisciplinary approach offers new opportunities for the design and control of stem cells in tissue engineering and cellular therapies, and promises to accelerate drug discovery in the biotechnology and pharmaceutical industries. Key words: microscale technologies, cellular microarrays, microfluidics, high-throughput screening platforms.

5.1 Introduction The past decades have produced significant progress in the biomedical field. In the pharmaceutical industry the rational use of combinatorial synthesis together with increased access to natural product sources facilitated the rapid synthesis and identification of new compounds with clinical potential (Kwon et al. 2007). This has resulted in a growing awareness of the potential of cell therapies and drug discovery, and there Published by Woodhead Publishing Limited, 2013

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has been a significant increase in the number of screenable drug candidates available to the pharmaceutical industry (Geysen et al. 2003). Stem cells in particular offer a potentially unlimited source of different cell types and, due to their unique properties (e.g. capacity for self-renewal and ability to differentiate into specialized cell types), are starting to be used as alternative sources of mature cells for cellular therapies (Klimanskaya et al. 2008) and drug discovery (McNeish 2004; Sartipy et al. 2007). The development of in vitro high-throughput screening methods for evaluating the effect of new growth factors and culture conditions in such cellular models might assist in the rapid and cost-effective development of novel drugs, as well as advancing our understanding of the conditions that selectively control cell fate. Cell-based assays thus present an opportunity to carry out screens of chemical libraries for molecules that modulate a broad range of biological events. The conventional approach is to use antibody labeling to follow cellfate decisions using known markers (Xu et al. 2008), but the cost of highcontent cell-based screening using conventional well-plate formats can be unreasonable. Moreover, these standard methods often lack the ability to present quantitative information on cell functions. Therefore, microscale technologies are emerging as interesting alternatives for tissue engineering and biological studies (Khademhosseini et al. 2006b), as well as for drug discovery applications (Bhadriraju and Chen 2002). In particular, cellular microarrays and microfluidic platforms can provide more information from smaller sample volumes, while enabling the incorporation of low-cost, high-throughput assays in the drug discovery process (Castel et al. 2006). With the advent of robotic spotting technology and microfabrication, it is now possible to distribute nanoliter volumes of different chemicals, biomolecules and cells in a spatially addressable footprint (Chin et al. 2004; Falsey et al. 2001; MacBeath and Schreiber 2000; Yamazoe and Iwata 2005). Therefore, cell-based microscale platforms are especially suited for high-throughput screening of large numbers of very small samples (Howbrook et al. 2003; Nicholson et al. 2007). In this chapter we focus on the potential of microscale technologies to develop new platforms that permit analysis of the effect of perturbing cells with drugs, genes and other molecular cues (such as extracellular matrix (ECM) proteins, biopolymers or RNA interference (RNAi)). The range of applications is remarkably broad and it includes protein therapeutic and drug candidate evaluation, enzyme activity and inhibition assays, and toxicity screening. Moreover, this growing field promises to impact the design and control of stem cells for regenerative medicine and biological studies, as well as guide researchers and bioengineers in the development of new bioprocesses for stem cell expansion and controlled differentiation.

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5.2 Types of microscale technologies ‘Microscale technologies’ is a generic term associated with a wide range of methods that can be employed to produce platforms with various two- and three-dimensional (3-D) microscale features, allowing the recreation of an environment with appropriate biological and mechanical cues. In addition, these technologies permit the investigation of a vast number of possible combinations of different interactions, providing extensive information on a given biological issue. Different fabrication techniques have been developed, including adaptation of a large number of methods from the microelectronics industry. The most successful methods involve the use of photolithography and soft lithography to produce substrates with microscale features relevant for biological studies. Modifications of these techniques and advances in robotic spotting have facilitated the development of other platforms that provide substantial insights into the cell biology and complexity of a given biological system. These techniques are not exclusive and may be used sequentially to produce the desired outcome.

5.2.1 Soft lithography and replica molding Soft lithography refers to a group of techniques for fabricating or replicating structures in elastomeric materials using molds or customized photomasks (Rogers and Nuzzo 2005). Soft lithography is generally used to construct features measured on the micrometer to nanometer scale (Xia and Whitesides 1998). Patterns are first created on a silicon wafer using photolithography, and are then transferred to an elastomeric mold. These techniques offer many advantages since they provide simple, inexpensive and reliable solutions for applications in biotechnology and tissue engineering (Peters and Brey 2009). Poly(dimethylsiloxane) (PDMS) is the most commonly used material in soft lithography due to its soft and flexible nature, its transparency to ultraviolet and visible light and its permeability to oxygen, making it suitable for cell culture (Wheeldon et al. 2011). Furthermore, it is easy to prepare and it is inexpensive, thus it is a simple solution to common cell biology laboratories that are not equipped with photolithography equipment and clean-room facilities (McDonald et al. 2000). Other materials, such as polyethylene glycols (PEGs), have also been successfully used in soft lithography applications (Kobel and Lutolf 2012). PEGs are very useful since they can readily form hydrogels that are mostly inert to protein Published by Woodhead Publishing Limited, 2013

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adsorption, and thus resist cell adhesion (Lutolf et al. 2009b). Additionally, they can also be easily chemically functionalized with proteins of interest. Replica molding is thus the process of transferring a microfeature into an elastomeric material, such as PDMS, based on a master mold or template. This template is first produced using photolithography in a silicon wafer, but other template materials can be used, including PDMS. In photolithography, light is used to transfer a geometric pattern from a photomask to a light-sensitive chemical photoresist. After the pattern is created, the elastomer is peeled off from the master mold after crosslinking, resulting in a negative pattern of the original template (Figure 5.1). These approaches allow fabricating microscale structures for microfluidic devices, stamps for microcontact printing, microwell arrays

Figure 5.1

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Replica molding using soft lithography approaches. The process consists of three sequential steps. First, a topographically patterned master is created, usually by photolithography techniques in a silicon wafer. Poly(dimethylsiloxane) (PDMS) is then poured onto the master mold and allowed to cure. The pattern is thus transferred from the master into PDMS by solidifying the liquid precursor. Finally, the PDMS is removed from the mold to yield a negative replica of the template Published by Woodhead Publishing Limited, 2013

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for cell culture in confined spaces, and many other structures that are used to force constrains and geometric control of the cell culture environment (Wheeldon et al. 2011).

5.2.2 Microcontact printing and surface patterning Microcontact printing is a particular type of soft lithography and replica molding procedure. In this process, an ink solution is transferred from an elastomeric mold, or stamp, to a substrate surface. The stamp is produced using soft lithography approaches and the ink solution is typically composed of proteins, protein mixtures or small molecules. After pouring the stamping solution onto the stamp, the transfer occurs at the interface of the stamp and the target substrate (Figure 5.2). This process yields a pattern of inked material on the surface of the target substrate, allowing the pattern and deposition of geometrically defined and spatially addressable materials onto flat surfaces.

Figure 5.2

Microcontact printing involves the production of an elastomeric stamp using soft lithography. After inking the stamp with the material solution, the deposition occurs by direct contact of the stamp with the surface of the substrate (PDMS, poly(dimethylsiloxane) Published by Woodhead Publishing Limited, 2013

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Microcontact printing has been used to create microscale patterns of adhesive biomolecules, like collagen and fibronectin among others, in cell-repellent substrates (Wheeldon et al. 2011). This results in cellular arrays in which cell growth is restricted to the islands of adhesive materials (Peerani et al. 2009a). Thus, in vitro culture of geometrically organized cell communities is possible using such patterning techniques.

5.2.3

Robotic spotting and printing

This technology consists of spotting nanoliter size spots onto designated locations in flat treated surfaces using robotic-assisted apparatus. Typically a solution containing the desired material is printed onto a suitably modified surface by dipping pin-tips into the solutions of interest. The tips are filled by capillary force and spots are printed as the tip approaches the substrate surface at the designated locations (Figure 5.3).

Figure 5.3

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In robotic spotting, a pin or tip controlled by a robotic arm is dipped into the solution of interest, and the desired material is deposited at designated locations on the surface of the array. The resulting microarrays are therefore customized for each experiment, because it is possible to select different combinations of materials and printing locations on the arrays Published by Woodhead Publishing Limited, 2013

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Spot sizes are dependent on different parameters such as the viscosity of the printing solution and the diameter of the printing tip (Wheeldon et al. 2011). Robotic spotting, or printing, was first used to produce DNA microarrays for genomic analysis and quantitative gene expression measurement (Howbrook et al. 2003). Since then it has also been widely used to develop protein microarrays for different high-throughput applications, like screening for protein–protein interactions, identifying the substrates of protein kinases, and identifying the protein targets of small molecules (MacBeath and Schreiber 2000). More recently, printing technologies have been adapted to cell biology applications to study the interaction of cells with different biomaterials and proteins of the extracellular matrix (Anderson et al. 2005; Flaim et al. 2005). Very low volumes, typically 20–60 nL, can be obtained using these dispensing approaches (Gepp et al. 2009). In addition, this technique can be used to create arrays of 3-D cell-culture hydrogels (Fernandes et al. 2010), where the 3-D printing process allows structuring alginate into tissue-like assemblies capable of supporting live cells (Pataky et al. 2011).

5.3 Microscale platforms for cell culture 5.3.1 Microwell arrays and microfluidic devices Soft lithography can be used to fabricate arrays of microwells with defined dimensions, allowing the control of cellular aggregate sizes (Figure 5.4). In addition to PDMS, other types of materials like PEG or hyaluronic acid have been employed to generate microwells for stem cell culture (Karp et al. 2007; Khademhosseini et al. 2006a). The microwell arrays then serve as templates for directing the formation of cellular aggregates such as embryoid bodies (EBs) (Khademhosseini et al. 2006a; Mohr et al. 2006). Using this approach it is possible to control parameters like aggregate size, shape and homogeneity, and further improvements have been made in material composition of the microwells, cell seeding procedures and retrieval of cellular aggregates from microwells since the first development of these platforms (Moeller et al. 2008). Both spatial organization of different cell types and control of pattern geometry can be achieved with microwells of different shapes (Tekin et al. 2012). Microwell arrays can then be used to rapidly study thousands of

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Figure 5.4

Microwell arrays for controlling the size of cellular aggregates. (A) Schematic representation of a microwell platform. (B) The microwell array is produced when poly(dimethylsiloxane) (PDMS) or another material is molded on a silicon master to produce microwell-patterned surfaces. Surfaces are then treated with cell-repellant material and the array is seeded with a cell suspension. Seeded cells will be confined to the inside of the microwells, where they can form cellular aggregates. Unconfined cells are washed out during periodical medium change

individual stem cell samples, using low reagent volumes, in a wide range of applications including differentiation assays and screening of reprograming factors, opening up considerable opportunities in the stem cell field (Lindstrom et al. 2009). Microfluidic devices that enable cell cultivation and cell analysis in parallel have also been developed using soft lithography approaches (Kang et al. 2008). Fully automated and quantitative cell culture can thus be performed in microfluidic chip-based arrays (Gómez-Sjöberg et al. 2007; Hung et al. 2005). These microscale approaches allow investigating the complex biology of stem cell responses, including the effects of soluble biochemical factors, extracellular matrix interactions, cell–cell signaling,

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physical cues (e.g. oxygen tension) and mechanical forces (e.g. shear stress) (Gupta et al. 2010). In one example, continuous perfusion of medium inside parallel culture chambers allowed the evaluation of a wide range of transient stimulation schedules on the proliferation, differentiation and motility of human mesenchymal stem cells (MSCs) (Gómez-Sjöberg et al. 2007). Interestingly, platforms combining the benefits of microwell confinement and microfluidic perfusion have also been developed (Okuyama et al. 2010). This allows control of cellular localization and generation of different concentration gradients within microchannels. Therefore, such microfluidic cell culture systems offer attractive solutions for a wide range of applications in high-throughput, cell-based screening and quantitative cell biology (Fernandes et al. 2009). These bioengineered platforms may combine microenvironmental control with specific signaling (Vunjak-Novakovic and Scadden 2011) and some recent applications are summarized in Table 5.1.

5.3.2 Cellular microarrays A cellular microarray platform can be described as a solid substrate where small volumes of different biomolecules and cells can be deposited in defined locations, allowing the multiplexed interrogation of living cells and the analysis of cellular responses (e.g. changes in phenotype) (Chen and Davis 2006). A wide range of different molecules (small molecules, polymers, antibodies, other proteins, etc.) can be arrayed using robotic spotting technology or soft lithography (Doh and Irvine 2006; How et al. 2004; Orner et al. 2004; Soen et al. 2003), and the strategy of choice in the conception of these platforms is related to the type of application and problem under study (Table 5.2). For example, surfaces on which cells interact are important for maintaining cellular functions, and the features of these surfaces often act as signals that influence cellular behavior (Hubbel 2004; Jang and Schaffer 2006). Microarrays can be used to dissect the crucial features of polymer–cell interactions and to unravel key features of specific cellular responses using robotic dispensing systems (Anderson et al. 2005). Optimized protocols have been developed that allow the high-throughput examination of the multiple effects of different extracellular components in a combinatorial manner on any cell type of interest (Brafman et al. 2012). Due to the complexity of the in vivo niche, such bioengineering approaches allow for combinatorial analysis of different components of the microenvironment, and are useful for deconstructing basic molecular Published by Woodhead Publishing Limited, 2013

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Table 5.1

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Microscale platforms fabricated using soft lithographic methods, and their application in stem cell culture and combinatorial screening

Device design and function

Examples

Microfluidic cell culture platforms for high-throughput cell-based assays

Hung et al. 2005 Wada et al. 2008 Chen et al. 2011

Miniaturized multiwell culture platform for drug development

Khetani and Bhatia 2008

Protein surface arrays for modulation of cell responses and stem cell fate studies

Derda et al. 2007 Doh and Irvine 2006 Konagaya et al. 2011 Nakajima et al. 2007 Orner et al. 2004 Ruiz et al. 2008 Yamazoe and Iwata 2005 Ashton et al. 2007

Microwell arrays for single-cell analysis and stem cell culture

Azarin et al. 2012 Bauwens et al. 2011 Chin et al. 2004 Cordey et al. 2008 Gobaa et al. 2011 Hwang et al. 2009 Karp et al. 2007 Khademhosseini et al. 2006a Khademhosseini et al. 2006b Lindstrom et al. 2009 Lutolf et al. 2009a Moeller et al. 2008 Mohr et al. 2006 Mohr et al. 2010 Ochsner et al. 2007

Microfluidic cell culture platforms for stem cell research

Blagovic et al. 2011 Cimetta et al. 2010 Faley et al. 2009 Figallo et al. 2007 Gómez-Sjöberg et al. 2007 Hattori et al. 2011 Kim et al. 2006 Kobel et al. 2010 Przybyla and Voldman 2012 Toh and Voldman 2011 Tumarkin et al. 2011 Zhong et al. 2008

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Table 5.2

Microscale platforms fabricated using robotic spotting approaches, and their application in stem cell culture and combinatorial screening

Device design and function

Examples

Cellular microarrays for highthroughput toxicology assays

Lee et al. 2008 Lee et al. 2005 Meli et al. 2012 Wu et al. 2011

Cellular microarrays for highthroughput compound screening

Bailey et al. 2004 Fernandes et al. 2008 Gopalakrishnan et al. 2003 Bailey et al. 2006 Yoshikawa et al. 2004 Zhang et al. 2012

Transfection microarrays for gene function assays

Falsey et al. 2001

Peptide and small-molecule microarrays for high-throughput cell-adhesion assays

Soen et al. 2003

Cellular microarrays for the identification and characterization of antigen-specific populations of cells

Anderson et al. 2004 Anderson et al. 2005 Derda et al. 2010 Mei et al. 2010 Yang et al. 2010

Biomaterial microarrays for testing stem cell-biomaterial interactions

Brafman et al. 2012 Brafman et al. 2009 Fernandes et al. 2010

Microarrayed cellular microenvironments for stem cell studies

Flaim et al. 2005 Flaim et al. 2008 LaBarge et al. 2009

Cellular microarrays of artificial niches for adult stem cell differentiation

Phillippi et al. 2008 Soen et al. 2006

mechanisms in human tissues (LaBarge et al. 2009). These approaches are thus very useful in furthering our understanding of how cells interact with their environment, and will potentially lead to the development of new material-based platforms that control cell behavior in vitro (Kim and Hayward 2012; Marklein and Burdick 2010). Published by Woodhead Publishing Limited, 2013

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Soft lithography using elastomeric materials has also been used to generate microbioreactor arrays for high-throughput experiments using human embryonic stem cells (ESCs) (Figallo et al. 2007) and patterned surfaces for the growth of neural stem cells (NSCs) (Ruiz et al. 2008). PDMS is biocompatible silicone rubber that has been used to generate substrates for the culture of single cells with 3-D cell-shape control (Ochsner et al. 2007); micropatterning of hydrogels, such as hyaluronic acid or agarose, can also serve as an alternative means of generating arrays of cells for high-throughput screening applications (Khademhosseini et al. 2006a; Schurdak et al. 2001). Fabrication parameters like substrate and protein solution requirements, surface passivation strategies (e.g. bovine serum albumin treatment to minimize non-specific binding) and cell culture conditions, have been shown to critically influence microarray quality, and should be optimized for further use in stem cell culture (Rodríguez-Seguí et al. 2009). This tight control of process parameters results in the ability to manipulate cellular input, like signaling thresholds regulated by local microenvironmental stimuli, and therefore allows extracting more meaningful data from cell-based assays (Peerani et al. 2009b). Cells can also be directly spotted onto functionalized glass surfaces using robotic fluid-dispensing devices. With this strategy, it is possible to generate patterns of cells encapsulated in 3-D hydrogel matrices (e.g. collagen or alginate), which support cell growth on the microscale. One example advanced by Lee and colleagues (Lee et al. 2008) involves the use of glass slides that are spin-coated with a polymeric material (poly[styrene-co-maleic anhydride], or PS-MA) to increase the hydrophobicity of the surface while providing reactive functional groups to attach a hydrogel matrix. A mixture of poly-l-lysine (PLL) and barium chloride (BaCl2) is first spotted onto glass slides coated with PS-MA. The positively charged PLL serves as a substrate to bind Ba2+ ions and assist the attachment of the negatively charged alginate. The Ba2+ ions also cause essentially immediate alginate gelation to give rise to 3-D cell-containing matrix spots possessing volumes as low as 20 nL. Other dispensing procedures have also been used to create micropatterned culture platforms for stem cell differentiation (Lee et al. 2009; Tuleuova et al. 2010). Instead of supplementing culture media with soluble growth factors, these molecules have been printed onto silane-modified glass surfaces. Stem cells seeded on top of different growth factor combinations exhibited different features and degrees of lineage commitment. Hepatic differentiation, in particular, is further

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enhanced by co-culture with hepatic stellate cells. Thus, a combination of co-culture and optimal protein stimulation was found to induce endoderm and hepatic phenotype earlier and to a much greater extent than growth factor stimulation or co-culture alone. In conclusion, micropatterned cultures of different stem cells show significant promise for driving stem cell differentiation towards specific phenotypes. In the future, these cell culture platforms will be further enhanced to enable efficient progression of cells through more committed stages.

5.4 High-throughput and combinatorial screening applications 5.4.1 Microtechnologies for drug discovery High-throughput, cell-based screening assays are routinely performed in the pharmaceutical industry and utilize 96- or 384-well microtiter plates with 2-D cell monolayer cultures (Kasibhatla et al. 2004; Mueller et al. 2004). However, this multiwell plate format has several limitations, including inefficient removal of reagents from the wells, and thus the difficulty of washing out chemicals from the cell monolayer (Dunn and Feygin 2000). Furthermore, high-throughput, cell-based screening using such microtiter-plate platforms is expensive because relatively large amounts of high-cost reagents and cells are needed, particularly when 96-well plates are used. Miniaturization of cell-based assays in a microarray format, which would also increase parallelism of cell analysis, offers an attractive solution. Moreover (as will be described in detail below) this technology can be used to evaluate the effects of drug leads in cells, to identify targets for drugs of unknown mechanism and to study the in vitro toxicology of drug, agricultural and cosmetic candidates. One particularly promising application is the integration of cell image-based analysis with highthroughput capabilities, the so-called high-content screening (Xia and Wong 2012). This enables the acquisition of profounder information at a single-cell resolution, so that more complex biological systems can be studied in greater detail. This approach is particularly appropriate for all aspects of contemporary drug discovery, and more recently for stem cell research (Zanella et al. 2010). Published by Woodhead Publishing Limited, 2013

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5.4.2 Devices for high-throughput toxicology studies The number of approvals of new drugs per year by the regulatory agencies has not increased significantly in the past decade, especially when compared with the growing investment in pharmaceutical research and development. Although there are numerous causes for this low productivity, including the complexity of biological systems as related to drug targets within the cell (Hopkins 2008), one particularly troubling cause is an unacceptably high rate of toxicity among drug candidates in the late clinical stages. Miniaturized cell-based assays with highthroughput capability can be used to identify potentially toxic compounds much earlier in the drug development process, thereby removing these compounds from further consideration and saving significant financial resources. Moreover, this cellular chip-based technology will serve as an important linkage between in vitro and in vivo studies, reducing the demand for animal studies, and making clinical trials more effective (Sung and Shuler 2010). Lee and colleagues developed miniaturized, high-throughput systems that mimic the effects of human liver metabolism and simultaneously evaluate cytotoxicity of small molecules and their metabolites (Lee et al. 2005; 2008). These methods combine enzyme catalysis with cell-based screening on a microscale biochip platform. Test compounds are added to the chip, which contain about 2000 combinations of human cytochrome P450 (CYP450) isoforms, and are then stamped onto a complementary 3-D cellular microarray for high-throughput screening of test compounds and their CYP450-generated metabolites (Lee et al. 2008). This methodology provided half maximal inhibitory concentration (IC50) values for nine compounds and their metabolites. The values were generated from the individual cytochrome P450 isoforms CYP1A2, CYP2-D6, CYP3A4, and a mixture of these three P450s designed to emulate the human liver. Despite an almost 2000-fold miniaturization, similar results were obtained when compared with conventional 96-well plate assays, demonstrating that scale reduction of this order does not influence the cytotoxicity response (Meli et al. 2012). A similar microarray sandwich system was also used to evaluate cell viability after chemical exposure to potentially toxic compounds (Wu et al. 2011). The efficacy of the system was demonstrated by generating four hits from toxicology screens towards MCF-7 human breast cancer cells. In addition to these systems, microfluidic sensor cell-based chips have also been proposed to detect cytotoxic reagents in a sensitive and 156

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high-throughput fashion (Wada et al. 2008). By using microfluidic cell culture systems in combination with sensor cells (e.g. cells transfected with reporter plasmids encoding green fluorescent protein, GFP), the authors were able to demonstrate that cytotoxic reagents can be quantitatively detected in a rapid, sensitive and dose-responsive manner. Overall, these strategies exemplify the potential of microscale highthroughput screening approaches for toxicity studies. Establishing stem cells and their committed progenitors as an innovative platform for toxicity studies in drug screening might be the next logical step in developing unique in vitro models for predicting the toxicity of drug candidates and chemicals in humans (reviewed in Davila et al. 2004). Therefore, the development of miniaturized stem cell-based assays represents a promising and innovative strategy for early efficiency in toxicity screening, allowing an improved selection of lead candidates and the reduction of adverse outcomes in later stages of drug development.

5.4.3 Devices for small molecule screening The use of microscale technologies to engineer the cellular environment for drug development has already shown some promise (Khetani and Bhatia 2008) and represents an emerging opportunity for small molecule screening. In fact, one major goal is to develop biologically relevant models of human tissues and organs-on-a-chip for disease modeling and drug testing (Ghaemmaghami et al. 2012). To this end, one of the first systems developed for screening small molecules in mammalian cells consisted of discs of 200 µm diameter composed of a biodegradable poly(d),(l)-lactide/glycolide copolymer in which each compound was impregnated (Bailey et al. 2004). Cells were seeded on top of these discs and compounds slowly diffused out, affecting proximal cells. A similar strategy was used for the identification of G protein-coupled receptor (GPCR) agonists (Gopalakrishnan et al. 2003). Human embryonic kidney cells expressing a human dopamine receptor and a chimeric G protein, together with a fluorescent calcium indicator (Fluo4), were incorporated into an agarose sheet and then placed on top of a polyester sheet, which contained over 8500 spotted test compounds that were able to diffuse into the gel. Binding of the test compounds to the dopamine receptor increased calcium ion levels, thereby resulting in binding to the reporter Fluo-4 and enhanced fluorescence. Due to their importance in many physiological or disease-related processes, miniaturization of GPCR-based live-cell screening assays was Published by Woodhead Publishing Limited, 2013

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among the first examples of microscale approaches for drug discovery (Martins et al. 2012). However, such systems suffer from region-toregion contamination caused by lateral diffusion of the spotted test compounds. An alternative format is a 3-D cell-based array, in which cells are printed onto a solid surface, as described above. An example of this approach is the development of an in-cell, on-chip immunofluorescence technique (Fernandes et al. 2008), which was used to demonstrate smallmolecule activation and deregulation of hypoxia-inducible factor 1α (Hif-1α) – a transcription factor expressed under hypoxic cellular conditions and related to a series of pathologies, including several types of cancer. Levels of the Hif-1α subunit in human pancreatic tumor cells were measured on-chip (Fernandes et al. 2008). Cells were cultured either under normoxic (control) conditions that suppress Hif-1α expression or under induced hypoxia, where Hif-1α expression is upregulated. In both cases, the expected expression levels of Hif-1α were observed. This technique allowed the rapid assessment of effects of inhibitors on protein expression levels. For example, different concentrations of the Hif-1α inhibitor 2-methoxyoestradiol (2ME2) were added to reduce the levels of the target protein in the microarray, and thereby provide dose–response information. Thus, rapid identification of small-molecule inhibitors of Hif-1α could be achieved in the future. Such an approach might be performed using different cell types and protein targets, as well as a range of small-molecule inhibitors, activators or modifiers. In fact, microwell arrays with complementary micropillar arrays were created to function as on-chip cell-based assays to identify epidermal growth factor receptor (EGFR) activity inhibitors in a high-throughput and high-content manner (Chen et al. 2011). The micropillar array serves as drug carrier device to topically apply drugs to cells cultured in the microwell array. Other applications include the use of high-throughput screening approaches to evaluate potential selective inhibitors of cancer stem cells (Gupta et al. 2009), screening for drugs that alter energy metabolism (Gohil et al. 2010), and screening assays for the discovery of anti-angiogenesis agents using endothelial cells (Truskey 2010). These examples illustrate the potential of microscale technologies in drug discovery settings (Foong et al. 2012), and further improvements have been made towards the evaluation of the effects of different molecules in 3-D microenvironments (Chen et al. 2010; Gidrol et al. 2009). Cellular microarrays can also be used with genetically modified cells to mimic a particular genetic disease or condition. For example, lentivirus-

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infected cell-based microarrays have been created for the high-throughput screening of gene function (Bailey et al. 2006). To provide proof-ofconcept, Bailey and colleagues (Bailey et al. 2006) spotted arrays with lentiviruses encoding short interfering RNA (siRNA) or DNA. Cells seeded on top of this pattern became infected, creating a living array of stably transduced cell clusters. Thousands of distinct parallel infections on a single glass slide were performed, including the transfection of primary cells (human fibroblasts and mouse dendritic cells) with GFPexpressing lentiviruses. In the future, screening drugs in the presence of different siRNAs might be used to assess whether the loss of function of one particular gene sensitizes cells to specific agents that can trigger different cell responses. This approach has obvious implications for cancer research and developmental biology (Perrimon and MatheyPrevot 2007).

5.5 Stem cell research Owing to their unique characteristics of unlimited self-renewal capacity and potential to generate fully differentiated, mature cells (Smith 2001), stem cells are at the forefront of potential regenerative medicine therapies and they might also provide an unlimited source of highly uniform cell types for pharmaceutical applications, especially when compared with genetically abnormal transformed or tumor cell lines (Klimanskaya et al. 2008; Pouton and Haynes 2005). However, several major challenges hinder the transition from fundamental science to functional technologies, including a need to identify the signals and conditions that regulate and influence cell function and the application of this information to the design of stem cell bioprocesses and therapies (Kirouac and Zandstra 2008). Conventional cell culture methods are unable to meet the demands of increased throughput, therefore the ability to track stem cell fate decisions and to quantify specific stem cell markers on microarray platforms has the potential to increase our understanding of the cellular mechanisms involved (Yang et al. 2009). This fundamental information will then facilitate the development of high-throughput cellbased screening devices for fast and effective identification of small molecules and other signals that can be used to direct cellular responses; these include engineered peptide and protein materials with tunable properties that are suitable for use as in vitro neural stem cell niche mimics, and in vivo central nervous system repair (Lampe and Heilshorn 2012). Published by Woodhead Publishing Limited, 2013

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Other applications include automated, high-throughput methods for synthesizing and screening combinatorial libraries of biomaterials, as well as methods for creating and screening local microenvironments of soluble factors, such as small molecules, siRNAs and other signaling molecules. Deconstructing the complexity of signals that control stem cell fate is thus the major objective of these studies, and rational, combinatorial analysis of different cues is attained using microscale approaches (Krause and Scadden 2012). For example, small molecules targeting specific signaling pathways are powerful tools for manipulating stem cells for desired outcomes (Brey et al. 2011; Firestone and Chen 2010; Li et al. 2012). The effects of these signals on stem cell fate can then be evaluated and the resulting information translated into improved bioprocesses for cell-based therapies or drug discovery programs. Microscale platforms are thus becoming increasingly important in probing the fundamental mechanisms of stem cell biology and facilitating the translation of fundamental knowledge into therapeutic approaches for regenerative medicine.

5.5.1 Exploring the stem cell microenvironment Signals emanating from the stem cell microenvironment, or niche, are crucial in regulating stem cell fate. These signals include physical cues such as matrix elasticity (Engler et al. 2006), cell–cell and cell–ECM interactions, and soluble factors such as growth factors and small molecules; fate can also be determined by the 3-D architecture that supports cell growth and differentiation (Even-Ram et al. 2006). Smallscale, high-throughput microarray systems thus provide optimal environments for unveiling such complex interactions. The functional immobilization of signaling molecules on a surface has been shown to direct stem cell fate (Alberti et al. 2008). Consequently, ECM microarray platforms were developed to facilitate screening of ECM molecules and their effects on stem cells in a combinatorial and parallel fashion. With the aid of robotic spotting devices, specific ECM components, such as collagen I, collagen III, collagen IV, laminin and fibronectin, were immobilized on hydrogel surfaces and screened in different combinations (Flaim et al. 2005). The commitment of mouse ESCs towards an early hepatic fate was evaluated, leading to the identification of several combinations of ECM components that synergistically impact differentiation of ESCs and hepatocyte function.

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This platform was further advanced to probe experimentally the interactions between ECM components and soluble growth factors on stem cell fate (Flaim et al. 2008), resulting in the analysis of 1200 simultaneous experimental endpoints on 240 unique signaling microenvironments. These studies were consistent with those previously reported in the literature, which resulted in the discovery of hitherto unknown and less-intuitive interactions between growth factors and ECM molecules. For example, this type of strategy yielded chemically defined, xeno-free, feeder-free synthetic substrates that are able to support robust self-renewal of fully dissociated human pluripotent stem cells (PSCs) (Mei et al. 2010). Similar work has also been conducted using human ESCs, and has led to the identification of novel peptide surfaces that support human ESC growth and self-renewal (Derda et al. 2007; Derda et al. 2010). In addition to ESCs, robotic spotting techniques can also be used to study the effects of signaling molecules and growth factors in adult stem cell populations. For example, combinations of ECM molecules, growth factors and other signaling proteins were spotted onto arrays to evaluate their effects on the proliferation and differentiation of human adult neural precursor cells (Soen et al. 2006). Quantitative single-cell analysis revealed significant effects of some of these signals on the extent and direction of differentiation into neuronal or glial fate. Similarly, the spatial patterning of bone morphogenetic protein 2 (BMP-2) on fibrincoated surfaces was used to study the osteogenic or myogenic differentiation of muscle-derived stem cells using a single chip (Phillippi et al. 2008), thus demonstrating the utility of this approach in the study of complex cell–ECM interactions. Mimicking in vivo conditions is a major motivation of these studies, and in the case of hematopoietic stem cells (HSCs) it appears to be a fundamental step for their in vitro expansion, while retaining the selfrenewal and proliferative capacity undamaged. The first step in such biomimetic approaches is to systematically study the natural architecture of the hematopoietic niche, while uncovering the essential factors for HSC expansion (Lee-Thedieck and Spatz 2012). It will then be possible to recreate the necessary physiological conditions in an artificial HSC culture system. This workflow has also been customized to neural stem cells (NSCs), enabling the adaptation of different neuronal cell models to high-throughput screening settings, while recapitulating physiological events occurring in the central nervous system (Garavaglia et al. 2010). Similarly, synthetic ECM hydrogels based on peptide self-assembly enabled multifactorial experimental designs for investigating interactions Published by Woodhead Publishing Limited, 2013

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between these ligands, and for determining a multi-peptide matrix formulation that maximized endothelial cell growth (Jung et al. 2011). Synthetic polymers can also be arranged in a site-specific, combinatorial fashion using photo-assisted patterning. High-throughput, miniaturized arrays for the rapid synthesis and screening of combinatorial libraries of photopolymerizable biomaterials were used to identify biomaterial compositions that influence human ESC attachment, growth and differentiation (Anderson et al. 2004). Over 1700 cell–biomaterial interactions were screened, revealing several unexpected cell–polymer interactions, including materials that support high levels of growth and differentiation into epithelial cells. It is also possible to immobilize both growth factors and synthetic matrices together in the same array (Nakajima et al. 2007). In this case, substrates can be loaded with growth factors known to have neurotrophic activities to expand undifferentiated NSCs or to induce differentiation of NSCs into specific lineages. Once again, this array-based method was able to identify favorable composite materials for the growth and differentiation of stem cell populations. The analysis of different combinations of biomaterials and growth factors in a microarray platform can provide valuable insights into the mechanisms regulating stem cell fate. Furthermore, by integrating 3-D cell culture with sensitive immunofluorescence detection in a microarray platform, potential stem cell fates can be assessed at high-throughput, while maintaining the cells in a more in vivo like microenvironment (Fernandes et al. 2010). As a result, it should be possible to identify parameters that regulate stem cell fate faster and more efficiently, and provide important information for the development and design of scaffolds for cell-based therapies.

5.5.2 Microwell and microfluidic arrays in stem cell research The merging of microfabrication with advanced biomaterial technologies has also been used to develop functional artificial niches capable of recapitulating extrinsic stem cell regulation in vitro and on a single-cell level (Kobel and Lutolf 2010). Particularly, the combination of hydrogel matrix technology with microscale engineering has been used to develop a microwell array platform on which the fate of NSCs and neurosphere formation can be followed, starting from a single founding cell (Cordey et al. 2008). Compared with conventional neurosphere culture methods on plastic dishes, the viability of single NSCs was increased two-fold

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using this platform, and an effective confinement of single proliferating cells to the microwells led to the formation of neurospheres of controlled size. Similarly, microwell-mediated control of cellular aggregate size regulates ESC cardiogenesis (Hwang et al. 2009), and the process was driven by differential expression of WNTs, particularly the non-canonical WNT pathway, according to aggregate size. Additionally, microwell microarrays can also be used for parallel and quantitative analysis of single cells, so the study of clonal stem cells can be conducted more efficiently with microwells than with time-consuming microtiter-well-plate formats. Clonal microarrays can be constructed by seeding a population of cells at clonal density on micropatterned surfaces that have been generated using soft lithographic microfabrication techniques. Clones of interest can be isolated after they have been assayed in parallel for various cellular processes and functions, including proliferation, signal transduction and differentiation (Ashton et al. 2007). Moreover, microscale platforms comprised of soft hydrogel microwell arrays with modular stiffness have been tested to evaluate the effect of cell–cell interactions on adipogenic differentiation of human MSCs and the effect of substrate stiffness on osteogenic MSC differentiation (Gobaa et al. 2011). A similar approach was used to enhance our understanding of the signals that control NSC fate (Roccio et al. 2012), whereby microwell arrays were used to expose NSCs, cultured either as neurospheres or as adherent clones, to PEG hydrogel substrates functionalized with selected signaling molecules. This allowed verification of the signaling moieties that increased cell survival, proliferation, and clonogenic potential of NSCs. These examples show the importance of probing the effect of key microenvironmental factors on the fate of different stem cell populations at a single-cell resolution and in highthroughput fashion (Hope and Bhatia 2011). Microfluidic technology also offers the potential to influence stem cell research, particularly for high-throughput analysis of signals that affect stem cell fate. Microfluidic channels are normally formed through the casting of PDMS over a pre-fabricated mold. Using this method, a microfluidic device was developed to analyze ESC cultures in parallel (Kim et al. 2006). A logarithmic range of flow rates within channels was tested, and flow rate was shown to significantly influence colony formation. In another example, a microbioreactor array, containing twelve independent micro-bioreactors perfused with culture medium, was fabricated using soft lithography. This system supported the cultivation of cells, either attached to substrates or encapsulated in hydrogels, at variable levels of hydrodynamic shear, and automated Published by Woodhead Publishing Limited, 2013

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image analysis detected the expression of cell differentiation markers (Figallo et al. 2007). Various conditions and configurations were validated for different cell types, including a mouse myoblast cell line, primary rat cardiac myocytes and human ESCs. In another example, a microfluidic approach was used to analyze gene expression of human ESCs at the single-cell level (Zhong et al. 2008). Total mRNA from individual single-cells could be extracted and complementary DNA (cDNA) synthesized on a single device with a high efficiency of generating cDNA from messenger RNA (mRNA), thereby making it possible to profile single-cell gene expression on a large scale. Finally, a platform combining microfluidic perfusion culture with discrete microchambers composed of different microenvironments (i.e. combinations of soluble factors and ECM) enabled the combinatorial and simultaneous study of soluble and matrix-associated stimuli in mammalian cells (Hattori et al. 2011).

5.5.3 High-throughput DNA and RNA systems for stem cell studies High-throughput DNA and small interference RNA (siRNA) systems have also been developed, creating an efficient screen for the effect of genetic control elements on stem cell behavior. In an effort to study ESC function, a subtractive library approach was used to identify the multiple genes (e.g. zinc finger protein 42, or Zfp42; also known as Rex-1) involved in the regulation of expression of the master embryonic transcription factor octamer 4 (Oct-4) and of self-renewal (Zhang et al. 2006). This study indicated that RNA interference (RNAi) screening is a feasible and efficient approach to identify genes involved in stem cell selfrenewal and differentiation. Microscale methodologies thus enable higher throughput and require less reagent than traditional microtiter well-plates. To that end, transfection microarrays have been developed that allow studies using limited numbers of cells, not only for large-scale functional analysis, but also reporter-based time-lapse cellular event evaluation (Miyake et al. 2009). In one example demonstrating these advantages, human MSCs were cultivated on-chip and transfected with previously arrayed plasmid DNA with high efficiency and spatial resolution. The ECM protein, fibronectin, was found to be an essential factor for the efficient on-chip transfection of these cells (Yoshikawa et al. 2004). Furthermore, the delivery of both siRNA and plasmid DNA could be performed in parallel,

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and a dose–response gene knockdown was observed. Concomitant with the development of small-molecule platforms, high-throughput RNAi screens are similarly emerging as important tools in cell and developmental biology, particularly in stem cell research (Yoshikawa et al. 2004). In fact, screening and detection approaches have been described that provide useful data elucidating mechanisms that govern the delivery of RNA molecules to effector cells (Nguyen et al. 2009). Such assays have also been developed in high-throughput 3-D settings using both viral and non-viral delivery systems (Zhang et al. 2012; Zoldan et al. 2011). Again, 3-D cultures have shown to more closely mimic the in vivo cellular milieu, thus providing cellular responses to genetic manipulation that are more like the in vivo situation than 2-D cultures (Zhang et al. 2012).

5.6 Conclusions and future trends The miniaturization of cell-based assays promises to have a profound impact on high-throughput screening of compounds by minimizing the consumption of reagents and cells. To achieve routine adoption of highthroughput cellular microscale platforms, future development will most certainly need to focus on automated, high-throughput methods for the study of cellular microenvironments and growth conditions in 3-D environments (Jongpaiboonkit et al. 2008). In this regard, array-based formats have been developed that have proved useful as enhancedthroughput platforms for 3-D culture of various cell types (Gottwald et al. 2007; Liu and Roy 2005), and much effort is now being directed towards cell culture models that better reflect in vivo function. For example, multiple cell types can be spatially organized in defined 3-D architectures (Sala et al. 2011; Tekin et al. 2012), which have been shown to better control cell fate decisions during in vitro culture (Giobbe et al. 2012). Furthermore, cell–cell and cell–ECM interactions are important factors that control cell behavior, and the 3-D architecture of the cellular niche has also been shown to improve the quality of information obtained from in vitro assays (Horning et al. 2008). In fact, cells respond in vivo in the context of complex microenvironmental cues, comprising heterologous cell types, signaling molecules, extracellular matrix, biophysical forces, and metabolic substrates (Krause and Scadden 2012). Therefore, the scientific community is developing significant efforts in order to build high-throughput microdevices for the investigation of microenvironmental Published by Woodhead Publishing Limited, 2013

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parameters that direct stem cell differentiation (Burdick and Watt 2011). Many of these efforts are focused on advanced fabrication methodologies for cellular microarray production (Hook et al. 2009). Additionally, incorporating biosensing elements alongside the cell culture has been used for local detection of secreted cellular products, which further enhances the utility of cellular microarrays. This concept was demonstrated using hepatocytes and their secretion of liver proteins (albumin and α1-antitrypsin) as a model system (Jones et al. 2008). Liver-specific proteins secreted by hepatocytes were captured on antibody domains immobilized in the immediate vicinity of the cells, detected with an immunofluorescence assay and quantified using a microarray scanner. By using these tools, among others, to create more in vivo-like cultures and more sensitive detection methods, cell-based drug discovery and target validation is likely to be improved, and the ability of in vitro assays to predict the in vivo response will become more reliable. Importantly, computational approaches and systems-level understanding of complex cellular niches would greatly enhance our ability to mimic physiological conditions (Bajikar and Janes 2012). Different modeling methodologies would focus on defining relationships between perturbations in microenvironmental factors and the resulting changes in intracellular signaling networks and stem cell fate decisions (Ashton et al. 2011). Furthermore, as technology permits the generation of complex artificial niches (Toh et al. 2010), models of population dynamics and intercellular interactions will become increasingly important for predicting spatial and temporal perturbations in cellular microenvironments during tissue formation. Such improvements are expected to lead to increased adoption and greater importance of microscale cell-based platforms throughout biotechnology.

5.7 References Alberti K, Davey R E, Onishi K, George S, Salchert K et al. (2008), ‘Functional immobilization of signaling proteins enables control of stem cell fate’, Nat Methods, 5: 645–50. Anderson D G, Levenberg S and Langer R (2004), ‘Nanoliter-scale synthesis of arrayed biomaterials and application to human embryonic stem cells’, Nat Biotechnol, 22: 863–6. Anderson D G, Putnam D, Lavik E B, Mahmood T A and Langer R (2005), ‘Biomaterial microarrays: rapid, microscale screening of polymer–cell interaction’, Biomaterials, 26: 4892–7.

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Flaim C J, Teng D, Chien S and Bhatia S N (2008), ‘Combinatorial signaling microenvironments for studying stem cell fate’, Stem Cells Dev. 17: 29–39. Foong Y, Fu J, Yao S and Uttamchandani M (2012), ‘Current advances in peptide and small molecule microarray technologies’, Curr Opin Chem Biol, 16(1–2): 234–42. Garavaglia A, Moiana A, Camnasio S, Bolognini D, Papait R et al. (2010), ‘Adaptation of NS cells growth and differentiation to high-throughput screening-compatible plates’, BMC Neurosci, 11: 7. Gepp M, Ehrhart F, Shirley S, Howitz S and Zimmermann H (2009), ‘Dispensing of very low volumes of ultra high viscosity alginate gels: a new tool for encapsulation of adherent cells and rapid prototyping of scaffolds and implants’, BioTechniques, 46(1): 31. Geysen H M, Schoenen F, Wagner D and Wagner R (2003), ‘Combinatorial compound libraries for drug discovery: an ongoing challenge’, Nat Rev Drug Discovery, 2: 222–30. Ghaemmaghami A, Hancock M, Harrington H, Kaji H and Khademhosseini A (2012), ‘Biomimetic tissues on a chip for drug discovery’, Drug Discov Today, 17(3–4): 173–81. Gidrol X, Fouqué B, Ghenim L, Haguet V, Picollet-D’hahan N and Schaack B (2009), ‘2D and 3D cell microarrays in pharmacology’, Curr Opin Pharmacol, 9(5): 664–8. Giobbe G, Zagallo M, Riello M, Serena E, Masi G et al. (2012), ‘Confined, 3D microenvironment regulates early differentiation in human pluripotent stem cells’, Biotechnol Bioeng. DOI (ahead of print) doi:10.1002/bit.24571. Gobaa S, Hoehnel S, Roccio M, Negro A, Kobel S and Lutolf M (2011), ‘Artificial niche microarrays for probing single stem cell fate in high throughput’, Nat Methods, 8(11): 949–55. Gohil V, Sheth S, Nilsson R, Wojtovich A, Lee J et al. (2010), ‘Nutrient-sensitized screening for drugs that shift energy metabolism from mitochondrial respiration to glycolysis’, Nat Biotechnol, 28(3): 249–55. Gómez-Sjöberg R, Leyrat A A, Pirone D M, Chen C S and Quake S R (2007), ‘Versatile, fully automated, microfluidic cell culture system’, Anal Chem 79: 8557–63. Gopalakrishnan S M, Moreland R B, Kofron J L, Helfrich R J, Gubbins E et al. (2003), ‘A cell-based microarrayed compound screening format for identifying agonists of G-protein-coupled receptors’, Anal Biochem 321: 192–201. Gottwald E, Giselbrecht S, Augspurger C, Lahni B, Dambrowsky N et al. (2007), ‘A chip-based platform for the in vitro generation of tissues in threedimensional organization’, Lab Chip, 7: 777–85. Gupta K, Kim D H, Ellison D, Smith C, Kundu A et al. (2010), ‘Lab-on-a-chip devices as an emerging platform for stem cell biology’, Lab Chip, 10(16): 2019–31. Gupta P, Onder T, Jiang G, Tao K, Kuperwasser C et al. (2009), ‘Identification of selective inhibitors of cancer stem cells by high-throughput screening’, Cell, 138(4): 645–59. Hattori K, Sugiura S and Kanamori T (2011), ‘Microenvironment array chip for cell culture environment screening’, Lab Chip, 11(2): 212–14.

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