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Nanoliter cell culture array with tunable chemical gradients Jonathan Avesar, Yaron Blinder, Hadar Aktin, Ariel Szklanny, Dekel Rosenfeld, Yonatan Savir, Moran Bercovici, and Shulamit Levenberg Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.8b01017 • Publication Date (Web): 17 May 2018 Downloaded from http://pubs.acs.org on May 17, 2018
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Analytical Chemistry
Nanoliter Cell Culture Array with Tunable Chemical Gradients Jonathan Avesara, Yaron Blindera, Hadar Aktinb, Ariel Szklannya, Dekel Rosenfelda†, Yonatan Savirb, Moran Bercovicic, and Shulamit Levenberga,d* a
Faculty of Biomedical Engineering, Technion—Israel Institute of Technology, Haifa, 3200003 Israel. Department of Physiology, Biophysics and Systems Biology, Faculty of Medicine, Technion, Haifa, 3109601 Israel c Faculty of Mechanical Engineering, Technion—Israel Institute of Technology, Haifa, 3200003 Israel. d Russell Berrie Nanotechnology Institute, Technion—Israel Institute of Technology, Haifa, 3200003 Israel. b
Supporting Information available: Appendix 1, Movie S1. See DOI: 10.1039/x0xx00000x ABSTRACT: A multitude of cell screening assays for diagnostic and research applications rely on quantitative measurements of a sample in the presence of different reagent concentrations. Standard methods rely on microtiter plates of varying well density, which provide simple and standardized sample addressability. However, testing hundreds of chemical dilutions requires complex automation, and typical well volumes of microtiter plates are incompatible with the analysis of a small number of cells. Here, we present a microfluidic device for creating a high resolution chemical gradient spanning 200 nanoliter wells. Using air-based shearing, we show that the individual wells can be compartmentalized without altering the concentration gradient, resulting in a large set of isolated nanoliter cell culture wells. We provide an analytical and numerical model for predicting the concentration within each culture chamber and validate it against experimental results. We apply our system for the investigation of yeast cell metabolic gene regulation in the presence of different ratios of galactose/glucose concentrations and successfully resolve the nutrient threshold at which the cells activate the galactose pathway.
A large number of cell analysis studies rely on testing the response of cells to a range of reagent concentrations. The microtiter plate has been the most widely used format for performing such studies, providing a standard format for addressing up to hundreds or thousands of individual test chambers, with volumes as low as a few microliters. Such compartmentalization is key in ensuring that the contents of each well remain isolated from its neighbors, yielding a large set of independent experiments. In addition, microtiter plates support the culture of both cells in suspension, and of adherent cells attached to a tissue culture surface. Despite these advantages, microtiter well volumes are still relatively large for single cell analysis applications where volumes must be small enough to yield a detectable concentration of the analyte of interest. In addition, testing hundreds of reagent concentrations using microtiter plates can be laborious or require the use of complex and expensive robotics. This, together with often limited volume of precious samples led to the development of microfluidic based solutions1–3. Perhaps the most widely used microfluidic single cell encapsulation technique is droplet microfluidics, where large number of nanoliter water-in-oil droplets can be produced at a high rate4,5. The contents of the droplets can be easily modulated by adjusting the relative flow rates between two merging aqueous solutions of different chemical compositions6. How-
ever, the use of droplets brings along complexity in droplet tracking, indexing, data collection and in culture of adherent cells3. For this reason, various microfluidic techniques which compartmentalize samples in a stationary format have been developed 3,7–10. Kim et al coupled a “christmas tree” gradient generator design to an array of chambers which can be actively compartmentalized using valves11. While brached dilution designs allow for robust gradient production independently of analyte properties, the geometry defines the achievable gradients such that changing sampling resolution requires designing and fabricating new device designs12. Sun et al developed a method which does not require active valving, and instead relies on sequential dilution to form discrete gradients9, followed by compartmentalization using oil. Guermonprez et al8 leveraged the concentration gradient formed by a Y-junction13 as the source for a network of chambers which were also compartmentalized using oil. Using a computational model, they demonstrated that the concentration gradient can be controlled by flow parameters. In previous work from our group, we reported a highly multiplexed device providing 600 compartmentalized nanoliter chambers in a single loading step3. These nanoliter chambers are interfaced with a substrate of choice and support the culture of both adherent and non-adherent cells. This device was
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termed the stationary nanoliter droplet array (SNDA). Chemical gradients were produced by flowing a concentrated sample for a finite amount of time, thereby subjecting upstream chambers to longer diffusion time of the solute as compared to downstream chambers3. However, this gradient production method requires precise timing to form repeatable gradients, thus making it sensitive to user error. In this work, we introduce a method for producing stable and repeatable digitized chemical gradients along hundreds of nanoliter cell culture compartments. Using ~2 microliters, the equivalent sample volume of a single well of a 1536-well plate, 200 culture chambers can be created using our system, each with a varying chemical composition. By combining the SNDA with an upstream Y-junction source, we demonstrate the ability to create a large number of individual nanoliter cell culture chambers, each with a different ratio of chemical compositions. This platform allows for configurable gradient profiles solely by controlling relative flow rates, without the need to alter the geometry of the chip. Since the gradient profile is reached under steady state conditions, the system is more robust as it is insensitive to precise timing or variability in user operation. Furthermore, we provide a closed form analytical solution to the gradient profile, allowing prediction of the concentration in each culture chamber. We validate the model against a numerical simulation as well as a set of controlled experiments. We demonstrate that the traditional use of oil for compartmentalization of the cell culture chambers can be replaced with air-based shearing, with little or no effect on the gradient profile. This results in a single liquid phase array which is simpler to use and can potentially be readdressed. Incubating a small number of yeast cells in each of the chambers and providing each with a different ratio of glucose/galactose, we demonstrate the applicability of our platform for studying the decision-making pathways of yeast in complex nutritional environments. Results A 3D depiction of the Gradient-SNDA system is presented in Figure 1a. We utilize a modified version of the stationary nanoliter droplet array (SNDA)3 device which consists of 200 wells of 8 nL each branching off a main channel. Well dimensions are 400µm × 200µm × 100µm (L × W × H) and the main channel is 300µm × 100µm (W × H). Figure 1b illustrates the process of assay execution for a simplified 8 well device. The process involves first loading the cells, then delivering reagents for gradient production, and lastly “shearing” the gradient for well compartmentalization and subsequent incubation. The mechanism behind gradient production in the gradientSNDA system is illustrated in Figure 2a. With this method, two parallel inflows merge at the main channel, one containing the upper concentration limit of the solute ( ) and the other containing the lower concentration limit ( ). As the liquid
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convects down the main channel, the solute is allowed to diffuse along the channel width while advecting along the length, a balance which is described by the non-dimensional Péclet () number. The flow is maintained until the gradient is fully developed, reaching a steady state. As a result, each well discretely samples the concentration in the section of the main channel that it is in contact with. The wells on the side sample concentrations from high to medium (proximal to distal) and wells on the side sample concentrations from low to medium (proximal to distal) (Figure 2b). The fully developed profile is maintained as long as the flow persists.
Figure 1. 3D depiction and concept illustration. (a) The gradientSNDA system consists of a microfluidic device reversibly sealed to a glass slide. The device contains three inlets, each connected to 1 mm tubing: two delivering respective reagents for gradient production and one used to deliver air for gradient shearing. An aluminium frame surrounds the device and is hermetically sealed to the slide using vacuum grease. This frame serves as a humid chamber once gradient production is completed and the tubing is disconnected by adding a small volume of water and an additional glass coverslip atop to seal the chamber (not shown). (b) The process of assay execution involves three main steps: loading the cells from the outlet, delivering reagents for gradient production, and shearing the gradient for nanoliter well compartmentalization and subsequent incubation. Note: only 8 wells are shown here for simplicity.
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Analytical Chemistry
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Figure 2. Gradient mechanism and computational model. (a) Illustration of gradient production in the SNDA. (b) A time-dependant concentration study of gradient production in the SNDA shown at steady state with = 0.5. (c) Comparison of concentrations within the
channel with the concentrations at the far edges of the wells at = 0.5 at three different characteristic times (c(i)) /, (c(ii)) +
,
(c(iii)) + illustrate the development of the gradient profile prior to reaching steady state. (d) Comparison of the analytical model with the computational model at steady state for = 0.5 showing very good agreement. (e) Different gradient profiles plotted using the computational model at steady state at various numbers. (f) A flow study in the SNDA geometry reveals recirculating flow with velocity of an order of magnitude slower than that in the main channel with no convective flux between the wells and the channel.
Analytical Model Consider a straight channel of length and half width . We assume a fully developed steady unidirectional flow field with a cross-section average velocity . In a stationary frame of reference, the transport of a solute , " with diffusion coefficient D can be described by the 2D advection-diffusion equation
tions
#$
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#( $
#) (
subjected to the boundary condi-
= 0, " = − ,-" − − -" − 2 / + #$
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= 0,
where -" is the Heavyside step function. Our gradient generation method requires axial advection to
be on the same scale as lateral diffusion
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while being dominant relative to axial diffusion 1. The equation then reduces to
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