We thank Dr. Mitch Doktycz, Dr. Jennifer Morrel-Falvey, Dr. Amber Bible, and Dr. Brandon Razooky for helpful advice and conversations, and acknowledge Dr. Sukanya Iyer for constructing the Pet3a-EGFP plasmid used in the gene expression tests. We acknowledge support from the Center for Nanophase Materials Sciences, which is sponsored by the Scientific User Facilities Division, Office of Science, U.S. Department of Energy. SEN and PMC acknowledge support from Bredesen Center Fellowships at the University of Tennessee, Knoxville. This research was performed at Oak Ridge National Laboratory (ORNL). ORNL is managed by UT-Battelle, LLC, for the U.S. Department of Energy.

1. Optical Lithography of Device Masters
<ol>
	<li>Dehydrate clean silicon wafers on a hot plate at ~250 &#176;C for at least 1 hr. 
	NOTE: It is good practice to use more than one wafer when preparing a master, in case of user error.</li>
	<li>Prepare photoresist aliquots. Prepare aliquots of both SU-8 2015 photoresist and a dilution of SU-8 2015 photoresist in 2:1 ratio using SU-8 thinner as diluent. 
	NOTE: Approximately 1 ml of photoresist is needed for spin-coating one wafer.</li>
	<li>Prepare three mask patterns for producing these masters. For the Membrane Master, prepare two masks: one patterning the membrane channel and the other patterning the reaction chambers. For the Control Valve master, prepare only one mask pattern. 
	NOTE: For more details on lithographic techniques, including mask patterning, see Ito and Okazaki, 2000.36 See Fowlkes and Collier, 2013 for a more detailed description of device design.37</li>
	<li>Prepare the Membrane Master
	<ol>
		<li>Spin-coat 2:1 SU-8 2015 photoresist dilution on wafers at 1,000 rpm for 45 sec.</li>
		<li>Soft bake wafers at 95 &#176;C for 2 min. Using a contact aligner, expose wafers with membrane channel pattern for 10 sec, and perform a post-exposure bake for 2 min at 95 &#176;C.</li>
		<li>Develop wafers in SU-8 developer for 1 min, or until photoresist residue is removed. Rinse wafer with isopropanol, moving from top to bottom. Dry wafer with nitrogen, again moving from top to bottom. Bake wafers at 180 &#176;C for 4 min.</li>
		<li>Spin-coat patterned wafers again with 2:1 SU-8 dilution at 2,000 rpm for 45 sec.</li>
		<li>Soft bake patterned wafers for 2 min at 95 &#176;C. Using contact aligner, align patterned wafers with reaction chamber pattern, and expose for 10 sec. Perform post-exposure bake for 2 min at 95 &#176;C.</li>
		<li>Develop wafers as described in step 1.4.3. After developing and drying wafers, bake wafers at 180 &#176;C for 4 min. 
		NOTE: The wafers may be developed in the same developer that was used in the previous step.</li>
	</ol>
	</li>
	<li>Prepare the Control Valve Master
	<ol>
		<li>Spin-coat undiluted SU-8 photoresist onto clean wafers at 2,000 rpm for 45 sec.</li>
		<li>Soft bake wafer at 95 &#176;C for 6 min. Using a contact aligner, expose wafers with control valve pattern for 10 sec. Perform a post-exposure bake at 95 &#176;C for 6 min.</li>
		<li>Develop wafers in SU-8 Developer for 2 min, or until residue is removed. Rinse with isopropanol, moving from top to bottom. Dry wafer with nitrogen and bake at 180 &#176;C for 4 min.</li>
	</ol>
	</li>
</ol>
2. PDMS Device Fabrication
<ol>
	<li>Silanize all masters with ~0.2 ml trimethylchlorosilane via vapor deposition.
	<ol>
		<li>Quickly enclose the master in an airtight container at RT with a few drops of the silanizing agent. 
		NOTE: Other silanizing protocols may be acceptable.38 If performed properly, the PDMS will be easy to remove.</li>
	</ol>
	</li>
	<li>Mix a commercial poly(dimethylsiloxane) (PDMS) base and curing agent in different ratios for both the membrane and control valve layers of the device, as has been demonstrated in similar multilayer valve designs39. Use 20:1 and 5:1 ratios of base:curing agent for the membrane and control valve molds, respectively.
	<ol>
		<li>For the membrane mold, mix 10 g of base with 0.5 g of curing agent. 
		NOTE: This volume will be spin-coated onto the membrane master.</li>
		<li>For the control valve mold, mix the base and curing agent in a 5:1 ratio. The amount of PDMS necessary to mold the control valve will depend on the container used to hold the control valve master; fill the container such that the master is coated with ~1 cm of PDMS.</li>
	</ol>
	</li>
	<li>Thoroughly mix both PDMS preparations, and de-gas them in a vacuum chamber until no air bubbles are visible. Place the control valve master in a heat-resistant container, such as a glass dish. Carefully pour 5:1 ratio PDMS over the master, and de-gas the container a second time.</li>
	<li>While the control valve PDMS container is being de-gassed, spin-coat the 20:1 ratio PDMS on the membrane master by carefully pouring the PDMS mixture onto the membrane master to minimize air bubble formation, then spin-coating the master at 1,000 rpm for 45 sec.</li>
	<li>Partially cure both masters in an oven at 80 &#176;C for 6 min for the membrane master and 15 min for the control valve master. 
	NOTE: When partially cured, the PDMS should hold its form, but the material will be slightly tacky. If PDMS is not yet cured, bake again in increments of a few minutes at a time until the material holds its form when pressed.</li>
	<li>Cut rectangular PDMS molds from control valve master, peeling the molds away gently. Punch inlet holes through the molded component using a 0.75 mm hole punch. 
	NOTE: The hole may be cleaned by inserting a 23 gauge blunt tip needle, and the mold exterior may be cleaned with cellophane tape, if necessary.</li>
	<li>Using an optical microscope to locate the reaction chambers on the membrane master, align the control valve mold component with the features of the reaction chamber membrane and place the control valve component directly on top of the membrane master. Orient the control valve inlet to the bottom left corner of the device, and ensure that the reaction chambers and channel of the membrane master are visible inside the rectangular control valve.</li>
	<li>Bake the aligned mold components at 80 &#176;C for 2 hr. 
	NOTE: The membrane and control valve molds will now be sealed together, and manipulated as one mold.</li>
	<li>Cut the layered PDMS mold away from the membrane master, peeling the mold away from the master very gently so as not to perforate the membrane.</li>
	<li>Punch inlet and outlet holes for the cell extract input using a 0.75 mm hole punch. Punch holes through both layers, and clean them in the same way as described in step 2.6.</li>
	<li>Using an inductively-coupled plasma cleaner, plasma treat both the mold (membrane side up) and a No. 0 glass coverslip at 10.5 W for 20 sec. Immediately remove the coverslip and mold from the plasma cleaner and layer the components, membrane side towards the glass, attempting to minimize air pockets between the glass and the mold. Do not press directly on the membrane input channel, or the membrane may anneal to the glass, making it difficult to fill the channel with reactants.
	<ol>
		<li>Take special care when handling the assembled devices to avoid breaking the glass layer. Use thin glass coverslips as the device must be imaged through the glass coverslip using high magnification oil-immersion objectives &#8212; if the glass is too thick, the device features may not be visible.</li>
	</ol>
	</li>
	<li>Finally, cure the completed devices at 80 &#176;C for 2 hr.</li>
</ol>
3. Experimental Setup for Cell-free Protein Synthesis Reaction
<ol>
	<li>Hydrate a device by boiling it in deionized water for 1 hr. 
	NOTE: Device should have a cloudy appearance when completely hydrated. Device may also be left O/N in sterile water at RT in order to hydrate it.</li>
	<li>Using an inverted microscope with an incubation chamber, set the ambient temperature to 30 &#176;C. 
	NOTE: This temperature was chosen to optimize expression of GFP with a T7 promoter, so optimal temperatures for other reactions may vary40.</li>
	<li>Mount device to microscope stage holder with cellophane tape and wrap edges of device with wet tissue paper in order to maintain local hydration.</li>
	<li>Use two high precision closed-loop voltage-pressure transducers to modulate nitrogen gas pressure for control valve actuation and reagent input. 
	NOTE: This protocol has only been tested with low-purity nitrogen, though other inert gases may be used.
	<ol>
		<li>Connect the first transducer by 24-gauge PTFE tubing to a water reservoir held in a 4 ml glass vial with a septum lid. Connect the reservoir to the control valve inlet using a second tube terminated by a 23 gauge blunt tip needle. 
		NOTE: Both tubes penetrate the reservoir septum with two sharp 23 gauge needles.</li>
		<li>Connect the second transducer by 24-gauge PTFE tubing connected to a male-to-male Luer-lok connector. Attach this to a Luer-lok 23 gauge needle connected by tubing with another 23 gauge blunt tip needle, which is assembled individually for each device. This needle connects to the membrane reaction channel; use it to flush water from the reaction channel and input reagents.</li>
	</ol>
	</li>
	<li>Using a cell-free protein expression system, assemble the components for the CFPS reaction on ice, according to manufacturer&#8217;s instructions. Minimize the time spent holding CFPS reagents on ice and place the reaction into the device immediately after assembly. 
	NOTE: This device has been used with a commercial E. coli extract protein expression kit and a plasmid constitutively expressing GFP. The total reaction volume was scaled to 25 &#181;l &#8212; it may be possible to use an even lower volume for reactants, if desired. As CFPS reagents tend to be sensitive to freeze-thaw cycles, it may be helpful to make aliquots of the reagents at the appropriate volume prior to the experiment. Other reagents may be added to the reaction mixture, but the reaction must be fully assembled before being applied to the device.
	<ol>
		<li>Assemble the reaction, adding the DNA input last. 
		NOTE: Once assembled in an Eppendorf tube, the CFPS reaction will begin if not held on ice. Since the time taken to apply the reagents to the device and begin the experiment may vary, it is helpful to start a timer once the reaction is assembled and mixed &#8212; this will keep the timescale between experiments consistent, and aid in troubleshooting.</li>
	</ol>
	</li>
	<li>Using the tubing and needle connector described in Step 3.4.2, withdraw the assembled reaction into the tube using a 1 ml syringe. Insert the blunt tip needle into the reaction chamber inlet. Detach the needle connector from the syringe and attach it to the male-to-male connector used for the reaction chamber transducer.</li>
	<li>Apply pressure (&#60;10 psi) to the CFPS reactants to fill the channel. Remove the needle when the reaction is filled.</li>
	<li>Insert the blunt tube from the other transducer into the control valve inlet. Do not pressurize the control valve yet.</li>
	<li>Place the mounted device on the stage. Using brightfield imaging, locate the reaction chambers with a 100X oil-immersion objective.</li>
	<li>Actuate the control valve by pressurizing the control valve transducer to 20 psi; a visible change in the membrane will be evident when the control valve is actuated. Focus on the bottoms of the reaction chambers.</li>
	<li>Begin the image acquisition; growth in fluorescence will be visible in the interior and around the exterior of the reaction chambers, though it will likely not be evident in the early stages of the reaction. Capture images every 1-3 min until the reaction reaches a steady state fluorescence. If an automatically focusing stage is not available, briefly refocus each image prior to the images being taken. 
	NOTE: While some photobleaching will occur, the effects on relative fluorescence due to photobleaching may be accounted for as long as the rate of photobleaching is known. This photobleaching rate may be estimated by exposing a fluorescent standard, such as a known concentration of GFP or a fluorophore mixture, to constant photobleaching over a period of time.</li>
	<li>Record the time elapsed from the reaction assembly to the first image acquired. 
	NOTE: This typically takes 4-5 min.</li>
</ol>
4. Image Analysis and Data Processing
<ol>
	<li>Using an image analysis software such as ImageJ, select the interior of the reaction chambers as an ROI. Acquire the mean fluorescence intensity value of the ROI for all images. 
	NOTE: This is the raw fluorescence intensity trace.
	<ol>
		<li>Perform this task in ImageJ using the Time Series Analyzer and ROI Manager plugins &#8212; Use Time Series Analyzer to choose regions of interest around the interior of each reaction chamber. Set &#8220;AutoROIProperties&#8221; to an area which corresponds to the interior of each reaction chamber, check &#8220;Add On Click&#8221;, and select each chamber. 
		NOTE: This step may also be done using the ellipse tool to draw an ROI around the fluorescent chamber. This ROI size usually corresponds to a 30 x 30 pixel ellipse for a 10 &#181;m diameter chamber viewed with a 100X objective.</li>
		<li>Highlight all ROIs in the ROI Manager. Use the &#8220;Multi Measure&#8221; function to determine the fluorescence intensity mean of each ROI through the entire image stack. 
		NOTE: A plugin named StackReg may be used to align the image stack, if necessary.</li>
	</ol>
	</li>
	<li>After acquiring the raw fluorescence intensity traces for all chambers in an experiment, determine the deterministic component of the reaction by taking an inter-experimental average across all traces, and subtracting the average from individual raw traces. Use data analysis software such as IGOR or MS Excel for this analysis. 
	NOTE: This provides noise traces for each reaction chamber.</li>
	<li>Analyze the gene expression noise from these reaction chambers using the same methods used to analyze gene expression noise derived from cells25.</li>
</ol>

The authors have nothing to disclose.

Gene expression in cells is inherently noisy due to small cellular volumes and low copy numbers of important reactants. Noise biology often focuses on the sources, processing, and biological consequences of fluctuations in the populations, concentrations, positions, or states of molecules that control gene circuits and networks44. The vast majority of this work has been performed in cellular systems, which has the advantage of viewing the noise of a gene circuit within the natural context of the genetic networks within the cell. However, cell-free systems allow the characterization of the intrinsic fluctuations of an individual gene circuit without the confounding extrinsic effects18 &#160;that cannot be avoided in cellular systems. Analysis of noise can offer important physical insights into how genetic circuits are structured and how they function, and has been used in cellular systems to characterize negative25 and positive27 autoregulation, extrinsic and intrinsic contributions to expression noise18 , and transcriptional bursting45,46. Here we describe the study of a cell-free expression system in microfluidic devices that enable the simultaneous control of reactor size and reaction initiation times, in order to better understand the roles that confinement and crowding47,48 have on intrinsic protein expression noise without the complications associated with living cells.
The key enabling feature of the design is the integration of arrays of femtoliter-volume (micron-scale) reaction chambers used for confining the reactants of a cell-free protein expression system, with an elastomeric &#8220;control valve&#8221; membrane in PDMS that traps the reactants at a well-defined, &#8220;time zero&#8221; for reaction initiation (Figure 1). This control allows the kinetics of the reactions involved in protein synthesis to be followed in real time with high precision. As such, it is important to manage cell-free reactants so that inter-experimental variability is minimized as much as possible. This control allows us to evaluate noise structure of cell-free genetic circuits in a manner that is analogous to techniques previously used to evaluate gene expression in living cells.
As reactants used in CFPS systems can be sensitive to freeze-thaw cycles, it is important to keep the reactants cold and minimize the time the reactants spend thawing on ice. It is good practice to periodically test the expression of the CFPS system in bulk in order to identify changes in expression levels over time &#8212; this may be done in a 10-15 &#181;l reaction in an Eppendorf tube, or in a device like a microplate reader, which performs multiple reads over time to capture reaction kinetics. Noting the age and thaw times of the reactants for every experiment will help when troubleshooting low expression levels. Furthermore, when assembling CFPS reagents, it is important to note that the reaction will begin once it is fully assembled and removed from the ice. In order to maintain a consistent &#8220;time zero&#8221;, it is helpful to record the time following the initiation of the CFPS reaction after the final addition of the DNA input, and to apply the reaction as quickly as possible to the incubated device. This process should take about 4-5 min, and fluorescence should not yet be visible within the reaction chambers. This control assures that the time available to visualize the growth portion of the reaction curve is maximized.
Before running CFPS reactions on the device, it is advisable to run quality-control tests to verify there is no leakage from the chambers. A FRAP test can be performed (as in Figure 2D) by applying a fluorophore to the device and exposing an individual well until the well is completely bleached. If the chambers are well-sealed, no recovery should be visible inside the well &#8212; there should be a stark contrast between the walls of the compartment and the interior and exterior spaces. If fluorescence recovery is apparent or the walls of the reaction chamber are not well defined, the pressure on the control valve should be increased or the device should be checked for leakage or delamination from the glass slide.
This protocol has been tested with CFPS reagents from a commercial E. coli cell-free protein expression kit (scaled to 25 &#181;l), though other robust CFPS systems may be used. It is possible to use volumes much lower than 25 &#181;l when applying reactions to the device, which may be helpful when reagent cost is a limiting factor in experiments. Once reactants are added to the device and the reaction chambers are sealed, it is not possible to add reactants to the solution without de-actuating the control valve &#8212; thus this device is not suitable for reactions which require the addition of reagents during the course of the reaction. This device is also not optimized for observing CFPS reactions which may run longer than 3 hr &#8212; the effects of dehydration and drying of the device after this time period have not been evaluated. If longer reaction times are desired, these effects may be mitigated by sealing the device to prevent evaporation, changing the incubation temperature, or by using a humidity chamber. Modifications to the device design, such as nanoporous structures in the chamber walls49,50 or the inclusion of a porous membrane layer, represent a few methods which could allow reagent exchange and thus lengthen reaction timescales.
Microfabricated reaction compartments of uniform volume are valuable for maintaining consistent dimensions across experiments and highly suitable for investigation into &#8220;side reactions&#8221; with the compartment walls. Unlike methods using non-microfabricated techniques, these reactions must be evaluated in small numbers, and do not provide dimensional flexibility during experiments. However, the controllable design for these reaction chambers is highly suitable for time-lapse microscopy, and may be an illuminating complement to a high-throughput method of confinement.

Cell-free systems offer a simplified and flexible platform for viewing biological reactions free from complicating factors such as fitness, division, and mutation that are unavoidable in the study of living cells. Such approaches have been employed to study cellular systems including the characterization of membrane proteins1, the probing of protein interactions2, and the exploration of fundamental aspects of translation3-7. Recently cell-free systems have begun to gain a foothold as viable platforms for synthetic biology8-10. The appeal of such approaches is that they free synthetic biology from the resource sharing and &#8216;extrinsic noise&#8217; that affects reaction dynamics in living cells. However questions remain as to how the physical environment in which cell-free reactions are embedded affects the progression and outcome of the reaction. Cell-free reaction environments &#8212; particularly confined environments that approach cell-relevant volumes &#8212; remain poorly characterized. Cell-Free Protein Synthesis (CFPS) is conventionally thought of as being &#8216;scale-free,&#8217; exhibiting equivalent kinetics across a range of microliter to liter-scale reaction volumes11. Nonetheless, confining reactions to cellular scale volumes has been shown to significantly affect protein expression rates12.
The stochastic nature of cell-free reactions &#8212; especially as these systems approach or even go below femtoliter volumes &#8212; may be of particular importance. Noise in gene expression is a property greatly influenced by confinement as small cell volumes and high densities of components force many of the important molecules to very low population levels &#8212; for example, Escherichia coli confines within a 1 fl volume as many as 4,300 different polypeptides under the inducible control of several hundred different promoters13. This inherent noise has been implicated as a central driving force in numerous biological processes including chemotaxis14, the HIV decision between active replication and latency15, the &#955; phage decision between lysis and lysogeny16,17, and the Bacillus subtillus decision between competence and sporulation17. Cell-free synthetic biology then provides both an opportunity to explore the stochastic properties of cellular gene circuits and networks, and manipulate these behaviors to achieve specific technological goals. While the noise behavior of cellular systems has been well-studied18-27, there has been little exploration of the fundamental noise behavior of cell-free systems8, particularly at the cellular scale.
Here we present a platform for the study of stochastic effects in cell-free synthetic biology. This microfabricated platform contains femtoliter-scale reaction chambers which may be quickly transitioned between open (free diffusion in and out of the chamber) and closed (reactants confined within the chamber) states. In the closed state, we confine Cell-Free Protein Synthesis (CFPS) reactants expressing a green fluorescent protein (GFP), and follow gene expression using time-lapse fluorescence microscopy28 (Figure 1). We characterize this cell-free environment by measuring the structure of the stochastic fluctuations in gene expression in a manner directly analogous to those used to characterize cells25. Non-microfabrication methods for confining cell-free reactions include vesicles and liposomes29-32, water-in-oil emulsions12, and porous media33. However, while these methods can provide control over the size distribution of the confined volumes34, microfabrication methods create highly replicable features with tightly specified dimensions, even on the nanoscale. Moreover, these rigid structures can be easily tracked over time without being susceptible to evaporation or changes in the external environment. Microfabricated container designs used in previous work8,35 cannot quickly seal the reaction chambers following reaction initiation, complicating the clear assignment of the time when the reaction was initiated (time zero). Using the method presented here, only 4-5 min&#160;are needed between initiation and visualization of the reaction on the device, thereby providing a well-defined &#8220;time zero&#8221;. The following protocols describe the methods for fabricating and testing this device, including optical lithography, device assembly, device testing, and methods for image analysis.

<table><tbody><tr><td>SU-8 2015</td><td>Microchem</td><td>SU-8 2000 series</td><td>Toxic. Handle with care. Wear chemical goggles, chemical gloves and suitable protective clothing when handling SU-8 2000 resists. Do not get into eyes, or onto skin or clothing.</td></tr><tr><td>SU-8 Thinner</td><td>Microchem</td><td>SU-8 2000 series</td><td>Handle with care. Wear chemical goggles, chemical gloves and suitable protective clothing when handling SU-8 2000 resists. Do not get into eyes, or onto skin or clothing.</td></tr><tr><td>SU-8 Developer</td><td>Microchem</td><td>SU-8 2000 series</td><td>Handle with care. Wear chemical goggles, chemical gloves and suitable protective clothing when handling SU-8 2000 resists. Do not get into eyes, or onto skin or clothing.</td></tr><tr><td>Chlorotrimethylsilane</td><td>Sigma Aldrich</td><td>92360 FLUKA</td><td>Hazardous. Corrosive to the respiratory tract., Reacts violently with water.</td></tr><tr><td>Sylgard 184 PDMS</td><td>Dow Corning</td><td>SYLGARD 184</td><td></td></tr><tr><td>0.75 mm hole-puncher</td><td>Ted Pella Inc.</td><td>15072</td><td>Harris Uni-Core</td></tr><tr><td>23 gauge needles blunt tip</td><td>Component Supply Co.</td><td>/NE-231PL-25</td><td></td></tr><tr><td>#0 glass coverslip</td><td>Ted Pella Inc.</td><td>260366</td><td>Gold Seal</td></tr><tr><td>Plasma Cleaner</td><td>Harrick Plasma</td><td>PDC-001</td><td></td></tr><tr><td>Microscope</td><td>Nikon Instruments</td><td>Eclipse TE 300</td><td></td></tr><tr><td>CCD camera</td><td>Roper Scientific</td><td>CoolSNAP-HQ</td><td></td></tr><tr><td>Shutter</td><td>Shutter Insturment</td><td>Lambda SC</td><td></td></tr><tr><td>Light Source</td><td>Nikon</td><td>Intensilight C-HGFI</td><td></td></tr><tr><td>Color Filters</td><td>Chroma Technology Corp.</td><td>ZET 532/106 excitation, ZT 532rdc dichroic, ET 595/50m emission</td><td></td></tr><tr><td>100X oil-immersion objective</td><td>Nikon</td><td>N.A. 1.4</td><td></td></tr><tr><td>Temperature Regulator</td><td>Oko Lab</td><td>H201-T</td><td></td></tr><tr><td>Metamorph</td><td>Universal Imaging Corp.</td><td>Version 7.8.3.0</td><td></td></tr><tr><td>Marsh Bellofram transducers</td><td>Marsh Bellofram</td><td>T2000</td><td></td></tr><tr><td>24 gauge PTFE tubing</td><td>Component Supply Co.</td><td>/SWTT-24-C</td><td></td></tr><tr><td>Septum vials</td><td>National Scientific</td><td>C4015- 17W</td><td></td></tr><tr><td>Power Supply</td><td>Hewlett Packard</td><td>6205B Dual DC Power Supply</td><td></td></tr><tr><td>Sharp 23 gauge needles</td><td>Precision Glide</td><td>305129</td><td></td></tr><tr><td>Male-to-male luer lock adapters</td><td>Qosina</td><td>20024</td><td>Polycarbonate</td></tr><tr><td>Stainless Steel Blunt Needle 23 gauge</td><td>Component Supply Co.</td><td>/NE-232PL-5C</td><td>Polypropylene</td></tr><tr><td>S30 &lt;em&gt;E. coli&lt;/em&gt; protein expression system</td><td>Promega</td><td>L1110</td><td></td></tr><tr><td>Pet3a-GFP vector/protein</td><td>Novagen</td><td>69418-3</td><td>Assembled in-house. Inserted EGFP gene in Pet3a.</td></tr><tr><td>Quantum Prep Plasmid Midiprep Kit</td><td>Biorad</td><td>#732-6120</td><td></td></tr><tr><td>QIAquick PCR Purification Kit</td><td>Qiagen</td><td>28106</td><td></td></tr><tr><td>Kimwipes</td><td>Kimberly-Clark</td><td>34155</td><td></td></tr><tr><td>Alexa Fluor 555</td><td>Molecular Probes</td><td>AF555</td><td>http://www.lifetechnologies.com</td></tr><tr><td>ImageJ</td><td>National Institutes of Health</td><td>Version 1.46r</td><td></td></tr><tr><td>Plugin: Time Series Analyzer</td><td>Balaji J Dept. of Neurobiology, UCLA</td><td>Version 3.0</td><td></td></tr><tr><td>Plugin: StackReg/TurboReg</td><td>Ecole Polytechnique F&amp;eacute;d&amp;eacute;rale de Lausanne Biomedical Imaging Group</td><td>Distribution is dated July 7, 2011</td><td></td></tr><tr><td>Plugin: ROI Manager Tools</td><td>Tiago Ferreira</td><td>12/15/2013 Version</td><td></td></tr></tbody></table>

sealable femtoliter chamber arrays for cell-free biology

Cell-free systems provide a flexible platform for probing specific networks of biological reactions isolated from the complex resource sharing (e.g., global gene expression, cell division) encountered within living cells. However, such systems, used in conventional macro-scale bulk reactors, often fail to exhibit the dynamic behaviors and efficiencies characteristic of their living micro-scale counterparts. Understanding the impact of internal cell structure and scale on reaction dynamics is crucial to understanding complex gene networks. Here we report a microfabricated device that confines cell-free reactions in cellular scale volumes while allowing flexible characterization of the enclosed molecular system. This multilayered poly(dimethylsiloxane) (PDMS) device contains femtoliter-scale reaction chambers on an elastomeric membrane which can be actuated (open and closed). When actuated, the chambers confine Cell-Free Protein Synthesis (CFPS) reactions expressing a fluorescent protein, allowing for the visualization of the reaction kinetics over time using time-lapse fluorescent microscopy. Here we demonstrate how this device may be used to measure the noise structure of CFPS reactions in a manner that is directly analogous to those used to characterize cellular systems, thereby enabling the use of noise biology techniques used in cellular systems to characterize CFPS gene circuits and their interactions with the cell-free environment.

The distinct advantage of this microfabricated platform is in the application of the controllable elastomeric &#8220;control valve&#8221; which is independently actuated in order to confine CFPS reactions (Figure 2A). When the device is actuated, the membrane chambers are pressed against the glass slide to confine fluorescent reagents into an array of reaction chambers (Figure 2C). In order to verify that the chambers reliably confine the reaction through the duration of the experiment, a basic FRAP (Fluorescence Recovery After Photobleaching) test was conducted37. A fluorophore (AF 555) was applied to the device, and the control valve was actuated; using the shutter aperture of the microscope, a single well confining the fluorophore was isolated and photobleached individually (Figure 2D). The chosen well became dark and did not recover in brightness until the control valve was depressurized 20 min&#160;later, releasing the chamber from the glass. This test verifies that these reaction chambers remain well-sealed for the duration of the experiment.
In optimal conditions, a CFPS reaction expressing an easily visualized protein (such as GFP or Luciferase) expresses detectable protein within a few minutes of being applied to this device. Over the lifetime of the reaction, protein synthesis in the interior and exterior of the reaction chambers is imaged and quantified by measuring units of fluorescence intensity within each chamber (Figure 3A). Fluorescence intensity, corresponding to protein concentration, may be mapped over time for each reaction chamber (Figure&#160;3D).
Gene expression is an inherently stochastic process that introduces fluctuations (noise) at every molecular step (synthesis, degradation, protein-DNA binding, etc.)20. One branch of noise biology focuses on the probative value of gene circuit noise41 . Expression in cell-free systems will have extrinsic noise effects that arise from interactions between the molecular machinery of expression and the surfaces that define the boundaries of the reaction vessels. These extrinsic effects will likely become more pronounced as cell-free reactions are confined into even smaller reaction chambers. The ability to perform time-lapse imaging of multiple confined CFPS reactions then enables the careful analysis of noise structure (magnitude and dynamics) in confined cell-free systems in a way directly analogous to methods that have been reported for cellular systems25. Figure 3C and 3D show the time courses of constitutive GFP expression from a T7 promoter in a standard 384-well microplate with a well volume of 15 &#181;l, compared to in PDMS reaction chambers 10 &#181;m in diameter, corresponding to volumes of only about 300 fl, about seven orders of magnitude less. The variability in protein expression rates in the 10 &#181;m reaction chambers is much higher than in the well-plate measurements, approaching those seen in cells.
Multiplexed reactions performed on the device exhibit similar kinetics to CFPS reactions performed in bulk on a microplate reader (Figure&#160;3B), where there is a swift increase in fluorescence which plateaus, often assumed to be caused by resource limitation within the reaction volume42,43. This deterministic growth behavior, though fluctuating, is generally consistent across all reaction chambers, and between experiments &#8212; by averaging traces between chambers across experiments, the deterministic trend may be subtracted from trace values, leaving only the noise components of the reaction (Figure&#160;4A). Figure 4B shows the GFP expression noise after removal of the deterministic, transient component (top), and the autocorrelation of the noise (bottom), while Figure 4A shows the corresponding traces in the 10 &#181;m reaction chambers. The distribution in the half-times of the autocorrelation traces gives the frequency dependence of the noise while the zero lag time of the autocorrelation traces gives the magnitudes of the noise, as the variance.
<img alt="Figure 1" src="/files/ftp_upload/52616/52616fig1.jpg" /> 
Figure 1. Cell-Free Protein Synthesis reactants are confined in femtoliter scale reaction chambers for the purpose of measuring gene expression noise. Reactants from a commercial cell-free protein expression system are used to constitutively express GFP inside confined PDMS reaction chambers. An array of these chambers may be visualized with time-lapse fluorescence microscopy in order to characterize protein expression and gene expression noise. The fluorescence intensity of each reaction chamber over time may be plotted as an individual trace. <a href="https://www.jove.com/files/ftp_upload/52616/52616fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" src="/files/ftp_upload/52616/52616fig2.jpg" /> 
Figure 2. Fabrication of two-layer microfluidic device with sealable femtoliter-scale chambers.&#160;(A) Layout and exploded view of device layers. The device is composed of two PDMS layers and a glass coverslip. The PDMS membrane, sealed between the glass and control valve layers, holds the reaction chambers. (B) SEM image of PDMS reaction chamber. The interior diameter is 10 &#181;m. (C) Schematic of input channels in device. Cell-Free Protein Synthesis (CFPS) reagents are flown through the reaction channel. Water is pressurized in the control valve to compress the reaction chambers against the glass slide, sealing the chambers37. Reproduced from Ref. 37 with permission from The Royal Society of Chemistry. (D) Fluorescence Recovery After Photobleaching (FRAP) test on a single well using FITC indicates chamber is well-sealed against external environment. The fluorophore was captured in the chambers (upper image) and a single well was photobleached (lower image). No fluorescence recovery was seen in the photobleached chamber until the control valve was released. <a href="https://www.jove.com/files/ftp_upload/52616/52616fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" src="/files/ftp_upload/52616/52616fig3.jpg" /> 
Figure 3. EGFP Expression in Confined Cell-Free Reaction. (A) Fluorescence images of sealed reaction chambers at chosen time points in the reaction. Protein production can be seen both inside the reaction chambers and outside the chambers in the main channel. (B) EGFP was cloned into a Pet3a vector, providing a T7 polymerase promoter and terminator and a strong ribosome binding site (RBS). (C) Normalized fluorescence measurements of constitutive expression of EGFP in a bulk cell-free reaction performed in a microplate reader. CFPS reactions usually produce protein quickly before slowing to a &#39;steady state&#39; fluorescence &#8212; this is associated with resource limitation43. Black dashes indicate the average trace. (D) Normalized fluorescence of 51 raw fluorescence intensity traces read from 51 reaction chambers over several experiments. Black dashes indicate the average trace over several experiments, which illustrate the deterministic component of the protein expression. <a href="https://www.jove.com/files/ftp_upload/52616/52616fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" src="/files/ftp_upload/52616/52616fig4.jpg" /> 
Figure 4. Individual Noise Traces and Noise Autocorrelation of a Cellular and Cell-Free System. (A) From Austin et al., 2006. Noise in GFP expression (top) and normalized autocorrelation functions (bottom) acquired from tracking GFP production in living bacteria25. Reprinted by permission from Macmillan Publishers Ltd: [Nature] 25 (Vol. 439), copyright (2006). (B) Noise in GFP expression (top) and normalized autocorrelation functions (bottom) acquired from GFP production in cell-free system, tracked in microfluidic device reaction chambers. <a href="https://www.jove.com/files/ftp_upload/52616/52616fig4highres.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Watch this Scientific Journal Video about Sealable Femtoliter Chamber Arrays for Cell-free Biology at JoVE.com

Sealable Femtoliter Chamber Arrays for Cell-free Biology

A microfabricated device with sealable femtoliter-volume reaction chambers is described. This report includes a protocol for sealing cell-free protein synthesis reactants inside these chambers for the purpose of understanding the role of crowding and confinement in gene expression.

Cell-free systems provide a flexible platform for probing specific networks of biological reactions isolated from the complex resource sharing (e.g., ...

sealable-femtoliter-chamber-arrays-for-cell-free-biology

Research

JoVE Journal

Bioengineering

9.4K Views.  University of Tennessee, Knoxville. A microfabricated device with sealable femtoliter-volume reaction chambers is described. This report includes a protocol for sealing cell-free protein synthesis reactants inside these chambers for the purpose of understanding the role of crowding and confinement in gene expression.

Video: Sealable Femtoliter Chamber Arrays for Cell-free Biology

Counting Proteins in Single Cells with Addressable Droplet Microarrays

Often cellular behavior and cellular responses are analyzed at the population level where the responses of many cells are pooled together as an average result masking the rich single cell behavior within a complex population. Single cell protein detection and quantification technologies have made a remarkable impact in recent years. Here we describe a practical and flexible single cell analysis platform based on addressable droplet microarrays. This study describes how the absolute copy numbers of target proteins may be measured with single cell resolution. The tumor suppressor p53 is the most commonly mutated gene in human cancer, with more than 50% of total cancer cases exhibiting a non-healthy p53 expression pattern. The protocol describes steps to create 10 nL droplets within which single human cancer cells are isolated and the copy number of p53 protein is measured with single molecule resolution to precisely determine the variability in expression. The method may be applied to any cell type including primary material to determine the absolute copy number of any target proteins of interest.

Here we present addressable droplet microarrays (ADMs), a droplet array based method able to determine absolute protein abundance in single cells. We demonstrate the capability of ADMs to characterize the heterogeneity in expression of the tumor suppressor protein p53 in a human cancer cell line.

Often cellular behavior and cellular responses are analyzed at the population level where the responses of many cells are pooled together as an average ...

Cancer Research

High Throughput Single-cell and Multiple-cell Micro-encapsulation

Microfluidic encapsulation methods have been previously utilized to capture cells in picoliter-scale aqueous, monodisperse drops, providing confinement from a bulk fluid environment with applications in high throughput screening, cytometry, and mass spectrometry. We describe a method to not only encapsulate single cells, but to repeatedly capture a set number of cells (here we demonstrate one- and two-cell encapsulation) to study both isolation and the interactions between cells in groups of controlled sizes. By combining drop generation techniques with cell and particle ordering, we demonstrate controlled encapsulation of cell-sized particles for efficient, continuous encapsulation. Using an aqueous particle suspension and immiscible fluorocarbon oil, we generate aqueous drops in oil with a flow focusing nozzle. The aqueous flow rate is sufficiently high to create ordering of particles which reach the nozzle at integer multiple frequencies of the drop generation frequency, encapsulating a controlled number of cells in each drop. For representative results, 9.9 &mu;m polystyrene particles are used as cell surrogates. This study shows a single-particle encapsulation efficiency Pk=1 of 83.7% and a double-particle encapsulation efficiency Pk=2 of 79.5% as compared to their respective Poisson efficiencies of 39.3% and 33.3%, respectively. The effect of consistent cell and particle concentration is demonstrated to be of major importance for efficient encapsulation, and dripping to jetting transitions are also addressed. 
Introduction 
Continuous media aqueous cell suspensions share a common fluid environment which allows cells to interact in parallel and also homogenizes the effects of specific cells in measurements from the media. High-throughput encapsulation of cells into picoliter-scale drops confines the samples to protect drops from cross-contamination, enable a measure of cellular diversity within samples, prevent dilution of reagents and expressed biomarkers, and amplify signals from bioreactor products. Drops also provide the ability to re-merge drops into larger aqueous samples or with other drops for intercellular signaling studies.1,2 The reduction in dilution implies stronger detection signals for higher accuracy measurements as well as the ability to reduce potentially costly sample and reagent volumes.3 Encapsulation of cells in drops has been utilized to improve detection of protein expression,4 antibodies,5,6 enzymes,7 and metabolic activity8 for high throughput screening, and could be used to improve high throughput cytometry.9 Additional studies present applications in bio-electrospraying of cell containing drops for mass spectrometry10 and targeted surface cell coatings.11 Some applications, however, have been limited by the lack of ability to control the number of cells encapsulated in drops. Here we present a method of ordered encapsulation12 which increases the demonstrated encapsulation efficiencies for one and two cells and may be extrapolated for encapsulation of a larger number of cells.
To achieve monodisperse drop generation, microfluidic "flow focusing" enables the creation of controllable-size drops of one fluid (an aqueous cell mixture) within another (a continuous oil phase) by using a nozzle at which the streams converge.13 For a given nozzle geometry, the drop generation frequency f and drop size can be altered by adjusting oil and aqueous flow rates Qoil and Qaq. As the flow rates increase, the flows may transition from drop generation to unstable jetting of aqueous fluid from the nozzle.14 
When the aqueous solution contains suspended particles, particles become encapsulated and isolated from one another at the nozzle. For drop generation using a randomly distributed aqueous cell suspension, the average fraction of drops Dk containing k cells is dictated by Poisson statistics, where Dk = &lambda;k exp(-&lambda;)/(k!) and &lambda; is the average number of cells per drop. The fraction of cells which end up in the "correctly" encapsulated drops is calculated using Pk = (k x Dk)/&Sigma;(k' x Dk'). The subtle difference between the two metrics is that Dk relates to the utilization of aqueous fluid and the amount of drop sorting that must be completed following encapsulation, and Pk relates to the utilization of the cell sample. As an example, one could use a dilute cell suspension (low &lambda;) to encapsulate drops where most drops containing cells would contain just one cell. While the efficiency metric Pk would be high, the majority of drops would be empty (low Dk), thus requiring a sorting mechanism to remove empty drops, also reducing throughput.15
Combining drop generation with inertial ordering provides the ability to encapsulate drops with more predictable numbers of cells per drop and higher throughputs than random encapsulation. Inertial focusing was first discovered by Segre and Silberberg16 and refers to the tendency of finite-sized particles to migrate to lateral equilibrium positions in channel flow. Inertial ordering refers to the tendency of the particles and cells to passively organize into equally spaced, staggered, constant velocity trains. Both focusing and ordering require sufficiently high flow rates (high Reynolds number) and particle sizes (high Particle Reynolds number).17,18 Here, the Reynolds number Re =uDh/&nu; and particle Reynolds number Rep =Re(a/Dh)2, where u is a characteristic flow velocity, Dh [=2wh/(w+h)] is the hydraulic diameter, &nu; is the kinematic viscosity, a is the particle diameter, w is the channel width, and h is the channel height. Empirically, the length required to achieve fully ordered trains decreases as Re and Rep increase. Note that the high Re and Rep requirements (for this study on the order of 5 and 0.5, respectively) may conflict with the need to keep aqueous flow rates low to avoid jetting at the drop generation nozzle. Additionally, high flow rates lead to higher shear stresses on cells, which are not addressed in this protocol. The previous ordered encapsulation study demonstrated that over 90% of singly encapsulated HL60 cells under similar flow conditions to those in this study maintained cell membrane integrity.12 However, the effect of the magnitude and time scales of shear stresses will need to be carefully considered when extrapolating to different cell types and flow parameters. The overlapping of the cell ordering, drop generation, and cell viability aqueous flow rate constraints provides an ideal operational regime for controlled encapsulation of single and multiple cells.
Because very few studies address inter-particle train spacing,19,20 determining the spacing is most easily done empirically and will depend on channel geometry, flow rate, particle size, and particle concentration. Nonetheless, the equal lateral spacing between trains implies that cells arrive at predictable, consistent time intervals. When drop generation occurs at the same rate at which ordered cells arrive at the nozzle, the cells become encapsulated within the drop in a controlled manner. This technique has been utilized to encapsulate single cells with throughputs on the order of 15 kHz,12 a significant improvement over previous studies reporting encapsulation rates on the order of 60-160 Hz.4,15 In the controlled encapsulation work, over 80% of drops contained one and only one cell, a significant efficiency improvement over Poisson (random) statistics, which predicts less than 40% efficiency on average.12
In previous controlled encapsulation work,12 the average number of particles per drop &lambda; was tuned to provide single-cell encapsulation. We hypothesize that through tuning of flow rates, we can efficiently encapsulate any number of cells per drop when &lambda; is equal or close to the number of desired cells per drop. While single-cell encapsulation is valuable in determining individual cell responses from stimuli, multiple-cell encapsulation provides information relating to the interaction of controlled numbers and types of cells. Here we present a protocol, representative results using polystyrene microspheres, and discussion for controlled encapsulation of multiple cells using a passive inertial ordering channel and drop generation nozzle.

Combining monodisperse drop generation with inertial ordering of cells and particles, we describe a method to encapsulate a desired number of cells or particles in a single drop at kHz rates. We demonstrate efficiencies twice exceeding those of unordered encapsulation for single- and double-particle drops.

Microfluidic encapsulation methods have been previously utilized to capture cells in picoliter-scale aqueous, monodisperse drops, providing confinement ...

A Microfluidic Chip for the Versatile Chemical Analysis of Single Cells

We present a microfluidic device that enables the quantitative determination of intracellular biomolecules in multiple single cells in parallel. For this purpose, the cells are passively trapped in the middle of a microchamber. Upon activation of the control layer, the cell is isolated from the surrounding volume in a small chamber. The surrounding volume can then be exchanged without affecting the isolated cell. However, upon short opening and closing of the chamber, the solution in the chamber can be replaced within a few hundred milliseconds. Due to the reversibility of the chambers, the cells can be exposed to different solutions sequentially in a highly controllable fashion, e.g. for incubation, washing, and finally, cell lysis. The tightly sealed microchambers enable the retention of the lysate, minimize and control the dilution after cell lysis. Since lysis and analysis occur at the same location, high sensitivity is retained because no further dilution or loss of the analytes occurs during transport. The microchamber design therefore enables the reliable and reproducible analysis of very small copy numbers of intracellular molecules (attomoles, zeptomoles) released from individual cells. Furthermore, many microchambers can be arranged in an array format, allowing the analysis of many cells at once, given that suitable optical instruments are used for monitoring. We have already used the platform for proof-of-concept studies to analyze intracellular proteins, enzymes, cofactors and second messengers in either relative or absolute quantifiable manner.

In this article we present a microfluidic chip for single cell analysis. It allows the quantification of intracellular proteins, enzymes, cofactors, and second messengers by means of fluorescent assays or immunoassays.&#160;

We present a microfluidic device that enables the quantitative determination of intracellular biomolecules in multiple single cells in parallel. For this ...

Formation of Biomembrane Microarrays with a Squeegee-based Assembly Method

Lipid bilayer membranes form the plasma membranes of cells and define the boundaries of subcellular organelles. In nature, these membranes are heterogeneous mixtures of many types of lipids, contain membrane-bound proteins and are decorated with carbohydrates. In some experiments, it is desirable to decouple the biophysical or biochemical properties of the lipid bilayer from those of the natural membrane. Such cases call for the use of model systems such as giant vesicles, liposomes or supported lipid bilayers (SLBs). Arrays of SLBs are particularly attractive for sensing applications and mimicking cell-cell interactions. Here we describe a new method for forming SLB arrays. Submicron-diameter SiO2 beads are first coated with lipid bilayers to form spherical SLBs (SSLBs). The beads are then deposited into an array of micro-fabricated submicron-diameter microwells. The preparation technique uses a "squeegee" to clean the substrate surface, while leaving behind SSLBs that have settled into microwells. This method requires no chemical modification of the microwell substrate, nor any particular targeting ligands on the SSLB. Microwells are occupied by single beads because the well diameter is tuned to be just larger than the bead diameter. Typically, more 75% of the wells are occupied, while the rest remain empty. In buffer SSLB arrays display long-term stability of greater than one week. Multiple types of SSLBs can be placed in a single array by serial deposition, and the arrays can be used for sensing, which we demonstrate by characterizing the interaction of cholera toxin with ganglioside GM1. We also show that phospholipid vesicles without the bead supports and biomembranes from cellular sources can be arrayed with the same method and cell-specific membrane lipids can be identified.

Supported lipid bilayers and natural membrane particles are convenient systems that can approximate the properties of cell membranes and be incorporated in a variety of analytical strategies. Here we demonstrate a method for preparing microarrays composed of supported lipid bilayer-coated SiO2 beads, phospholipid vesicles or natural membrane particles.

Lipid bilayer membranes form the plasma membranes of cells and define the boundaries of subcellular organelles. In nature, these membranes are ...

A Pipette-Tip Based Method for Seeding Cells to Droplet Microfluidic Platforms

Amongst various microfluidic platform designs frequently used for cellular analysis, droplet-microfluidics provides a robust tool for isolating and analyzing cells at the single-cell level by eliminating the influence of external factors on the cellular microenvironment. Encapsulation of cells in droplets is dictated by the Poisson distribution as a function of the number of cells present in each droplet and the average number of cells per volume of droplet. Primary cells, especially immune cells, or clinical specimens can be scarce and loss-less encapsulation of cells remains challenging. In this paper, we present a new methodology that uses pipette-tips to load cells to droplet-based microfluidic devices without the significant loss of cells. With various cell types , we demonstrate efficient cell encapsulation in droplets that closely corresponds to the encapsulation efficiency predicted by the Poisson distribution. Our method ensures loss-less loading of cells to microfluidic platforms and can be easily adapted for downstream single cell analysis, e.g., to decode cellular interactions between different cell types.

This article presents a protocol for seeding scarce population of cells using pipette-tips to droplet microfluidic devices in order to provide higher encapsulation efficiency of cells in droplets.

Amongst various microfluidic platform designs frequently used for cellular analysis, droplet-microfluidics provides a robust tool for isolating and ...

Engineering

Fluorescence Biomembrane Force Probe: Concurrent Quantitation of Receptor-ligand Kinetics and Binding-induced Intracellular Signaling on a Single Cell

Membrane receptor-ligand interactions mediate many cellular functions. Binding kinetics and downstream signaling triggered by these molecular interactions are likely affected by the mechanical environment in which binding and signaling take place. A recent study demonstrated that mechanical force can regulate antigen recognition by and triggering of the T-cell receptor (TCR). This was made possible by a new technology we developed and termed fluorescence biomembrane force probe (fBFP), which combines single-molecule force spectroscopy with fluorescence microscopy. Using an ultra-soft human red blood cell as the sensitive force sensor, a high-speed camera and real-time imaging tracking techniques, the fBFP is of ~1 pN (10-12 N), ~3 nm and ~0.5 msec in force, spatial and temporal resolution. With the fBFP, one can precisely measure single receptor-ligand binding kinetics under force regulation and simultaneously image binding-triggered intracellular calcium signaling on a single live cell. This new technology can be used to study other membrane receptor-ligand interaction and signaling in other cells under mechanical regulation.

We describe a technique for concurrently measuring force-regulated single receptor-ligand binding kinetics and real-time imaging of calcium signaling in a single T lymphocyte.

Membrane receptor-ligand interactions mediate many cellular functions. Binding kinetics and downstream signaling triggered by these molecular interactions ...

A Microfluidic Platform for High-throughput Single-cell Isolation and Culture

Studying the heterogeneity of single cells is crucial for many biological questions, but is technically difficult. Thus, there is a need for a simple, yet high-throughput, method to perform single-cell culture experiments. Here, we report a microfluidic chip-based strategy for high-efficiency single-cell isolation (~77%) and demonstrate its capability of performing long-term single-cell culture (up to 7 d) and cellular heterogeneity analysis using clonogenic assay. These applications were demonstrated with KT98 mouse neural stem cells, and A549 and MDA-MB-435 human cancer cells. High single-cell isolation efficiency and long-term culture capability are achieved by using different sizes of microwells on the top and bottom of the microfluidic channel. The small microwell array is designed for precisely isolating single-cells, and the large microwell array is used for single-cell clonal culture in the microfluidic chip. This microfluidic platform constitutes an attractive approach for single-cell culture applications, due to its flexibility of adjustable cell culture spaces for different culture strategies, without decreasing isolation efficiency.

Here, we present a protocol for isolating and culturing single cells with a microfluidic platform, which utilizes a new microwell design concept to allow for high-efficiency single cell isolation and long-term clonal culture.

Studying the heterogeneity of single cells is crucial for many biological questions, but is technically difficult. Thus, there is a need for a simple, yet ...

A Femtoliter Droplet Array for Massively Parallel Protein Synthesis from Single DNA Molecules

Advances in spatial resolution and detection sensitivity of scientific instrumentation make it possible to apply small reactors for biological and chemical research. To meet the demand for high-performance microreactors, we developed a femtoliter droplet array (FemDA) device and exemplified its application in massively parallel cell-free protein synthesis (CFPS) reactions. Over one million uniform droplets were readily generated within a finger-sized area using a two-step oil-sealing protocol. Every droplet was anchored in a femtoliter microchamber composed of a hydrophilic bottom and a hydrophobic sidewall. The hybrid hydrophilic-in-hydrophobic structure and the dedicated sealing oils and surfactants are crucial for stably retaining the femtoliter aqueous solution in the femtoliter space without evaporation loss. The femtoliter configuration and the simple structure of the FemDA device allowed minimal reagent consumption. The uniform dimension of the droplet reactors made large-scale quantitative and time-course measurements convincing and reliable. The FemDA technology correlated the protein yield of the CFPS reaction with the number of DNA molecules in each droplet. We streamlined the procedures about the microfabrication of the device, the formation of the femtoliter droplets, and the acquisition and analysis of the microscopic image data. The detailed protocol with the optimized low running cost makes the FemDA technology accessible to everyone who has standard cleanroom facilities and a conventional fluorescence microscope in their own place.

The overall goal of the protocol is to prepare over one million ordered, uniform, stable, and biocompatible femtoliter droplets on a 1 cm2 planar substrate that can be used for cell-free protein synthesis.

Advances in spatial resolution and detection sensitivity of scientific instrumentation make it possible to apply small reactors for biological and ...

Chemistry

An Ultrahigh-throughput Microfluidic Platform for Single-cell Genome Sequencing

Sequencing technologies have undergone a paradigm shift from bulk to single-cell resolution in response to an evolving understanding of the role of cellular heterogeneity in biological systems. However, single-cell sequencing of large populations has been hampered by limitations in processing genomes for sequencing. In this paper, we describe a method for single-cell genome sequencing (SiC-seq) which uses droplet microfluidics to isolate, amplify, and barcode the genomes of single cells. Cell encapsulation in microgels allows the compartmentalized purification and tagmentation of DNA, while a microfluidic merger efficiently pairs each genome with a unique single-cell oligonucleotide barcode, allowing &gt;50,000 single cells to be sequenced per run. The sequencing data is demultiplexed by barcode, generating groups of reads originating from single cells. As a high-throughput and low-bias method of single-cell sequencing, SiC-seq will enable a broader range of genomic studies targeted at diverse cell populations.

Single-cell sequencing reveals genotypic heterogeneity in biological systems, but current technologies lack the throughput necessary for the deep profiling of community composition and function. Here, we describe a microfluidic workflow for sequencing &gt;50,000 single-cell genomes from diverse cell populations.

Sequencing technologies have undergone a paradigm shift from bulk to single-cell resolution in response to an evolving understanding of the role of ...

A Multilayer Microfluidic Platform for the Conduction of Prolonged Cell-Free Gene Expression

The limitations of cell-based synthetic biology are becoming increasingly apparent as researchers aim to develop larger and more complex synthetic genetic regulatory circuits. The analysis of synthetic genetic regulatory networks in vivo is time consuming and suffers from a lack of environmental control, with exogenous synthetic components interacting with host processes resulting in undesired behavior. To overcome these issues, cell-free characterization of novel circuitry is becoming more prevalent. In vitro transcription and translation (IVTT) mixtures allow the regulation of the experimental environment and can be optimized for each unique system. The protocols presented here detail the fabrication of a multilayer microfluidic device that can be utilized to sustain IVTT reactions for prolonged durations. In contrast to batch reactions, where resources are depleted over time and (by-) products accumulate, the use of microfluidic devices allows the replenishment of resources as well as the removal of reaction products. In this manner, the cellular environment is emulated by maintaining an out-of-equilibrium environment in which the dynamic behavior of gene circuits can be investigated over extended periods of time. To fully exploit the multilayer microfluidic device, hardware and software have been integrated to automate the IVTT reactions. By combining IVTT reactions with the microfluidic platform presented here, it becomes possible to comprehensively analyze complex network behaviors, furthering our understanding of the mechanisms that regulate cellular processes.

The fabrication process of a PDMS-based, multilayer, microfluidic device that allows in vitro transcription and translation (IVTT) reactions to be performed over prolonged periods is described. Furthermore, a comprehensive overview of the hardware and software required to automate and maintain these reactions for prolonged durations is provided.

The limitations of cell-based synthetic biology are becoming increasingly apparent as researchers aim to develop larger and more complex synthetic genetic ...