Creation of the video was supported by grants from the National Center for Research Resources (5P41RR011823-17) and the National Institute of General Medical Sciences (8 P41 GM103533-17) from the National Institutes of Health. This work was also supported by NSF grant 1120425. MJD is a Rita Allen Foundation Scholar. AWM is supported in part by NIH T32 HG00035. We thank Anna Sunshine for assistance with improving protocols. Additionally, we acknowledge Sara DiRienzi, Celia Payen, and Amy Sirr as early users of the ministats.

Use appropriate sterile technique throughout the protocol.
1. Assembling Parts for and Preparing the Ministat Array
<ol>
 <li>Order all parts. </li>
 <li>Clean glass tubes. Mark tubes at 20 ml volume. </li>
 <li>Make cork assemblies with air, media, and effluent ports and place them at the top of the cleaned glass culture tubes. </li>
 <li>Prepare humidifying chambers and arrange all non-autoclaved parts. </li>
 <li>Make air, effluent, and media tubing using sufficient tubing lengths and compatible couplings.</li>
 <li>Connect each type of tubing (air, media, and effluent) to the cork assemblies and foil filters and the media quick-connect to prepare them for the autoclave.</li>
 <li>Prepare a carboy for use in making sterile chemostat medium. </li>
 <li>Prepare the culture sampling bottles by inserting a two-hole rubber stopper with appropriate fittings. Foil each filter to prepare them for the autoclave.</li>
 <li>Fit the assembled array neatly into one or more autoclave trays and autoclave all parts. </li>
 <li>Make and filter chemostat media into autoclaved carboys. </li>
</ol>
2. Setting Up an Experiment
<ol>
 <li>Fill each hydration flask with 700 ml ddH2O. </li>
 <li>Place the autoclaved ministats into the heating block set at the desired temperature. </li>
 <li>Place the airlines into the 4-port manifold and turn on the air pump. </li>
 <li>Connect the effluent lines to the 100 ml collection bottles. </li>
 <li>Remove the foil from the end of the media tubing and media carboy and connect the two quick connects. Thread each length of pump tubing through a peristaltic pump cartridge and click them into place. Turn on the media pump.</li>
 <li>Let the chambers fill. Turn off the media pump. </li>
 <li>Spray the cork assemblies with 70% ethanol and inoculate the cultures using a syringe. Save a sample of the inoculum as a frozen glycerol stock if desired. Let cultures grow for 30 hr. </li>
 <li>Adjust the height of the effluent needle until the culture volume is set to 20 ml with the air flow turned off. This may take several adjustments over the course of an hour. When finished turn the air flow back on. </li>
 <li>Turn the media pump on. </li>
 <li>Empty the effluent sampling bottles, which contain media collected while setting the working culture volume, and record the time. </li>
 <li>To take a time-zero measurement place the effluent lines into sterile collection tubes for 15 min-2 hr (depending on what volume you wish to sample for DNA analysis). Also make a glycerol frozen stock for each culture at this time if desired. </li>
</ol>
3. Daily Measurements
<ol>
 <li>As with your time-zero measurement, sample on ice for 15 min-2 hr (as required for your experiment) on ice and record the time sampled for DNA and frozen stock samples. </li>
 <li>For RNA samples either collect a small volume using a syringe and 22G 5" needle from the culture or uncork each ministat to harvest the entire culture. Samples must be taken quickly, collected by filtration, and frozen immediately in liquid nitrogen. </li>
 <li>Measure the effluent collected since the last sampling for each ministat to quantify dilution rate. Adjust dilution rates if needed by readjusting the pump setting or tuning the fine adjust on individual pump lines.</li>
 <li>Replace effluent lines in empty collection bottles. </li>
 <li>Quantify cells/ml as well as other endpoints of interest and make a glycerol frozen stock. </li>
</ol>
4. Post-experiment Cleanup
<ol>
 <li>Place all tubing in separate trays and rinse excessively with ddH2O. Dry tubing using an aquarium pump.</li>
 <li>Clean the cork assemblies with ddH2O and use needle insert to clean the needles, aspirating and dispensing water in turn. Wipe the outside of the needles and cork to remove any residual media.</li>
 <li>Clean the glass tubing with water and ethanol, and remove physical contaminants with 3 balled up Kimwipes and forceps. </li>
 <li>Rinse and dry all parts again before use.</li>
</ol>

<ol>
	<li>Monod, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=R&#233;cherches+sur+la+Croissance+des+Cultures+Bacteriennes.">R&#233;cherches sur la Croissance des Cultures Bacteriennes.</a> Ann. I. Pasteur. 79, 390-410 (1950).</li><li>Novick, A., Szilard, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Description+of+the+chemostat.">Description of the chemostat.</a> Science. 15, 715-716 (1950).</li><li>Daran-Lapujade, P., Daran, J. -. M., van Maris, A. J. A., de Winde, J. H., Pronk, J. T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Chemostat-based+micro-array+analysis+in+baker's+yeast.">Chemostat-based micro-array analysis in baker's yeast.</a> Adv. Microb. Physiol. 54, 257-311 (2009).</li><li>ter Linde, J. J. M., Pronk, J. T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Genome-wide+transcriptional+analysis+of+aerobic+and+anaerobic+chemostat+cultures+of+Saccharomyces+cerevisiae.">Genome-wide transcriptional analysis of aerobic and anaerobic chemostat cultures of Saccharomyces cerevisiae.</a> J. Bacteriol. 181, 7409-7413 (1999).</li><li>Boer, V., de Winde, J., Pronk, J., Piper, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+genome-wide+transcriptional+responses+of+Saccharomyces+cerevisiae+grown+on+glucose+in+aerobic+chemostat+cultures+limited+for+carbon,+nitrogen,+phosphorus,+or+sulfur.">The genome-wide transcriptional responses of Saccharomyces cerevisiae grown on glucose in aerobic chemostat cultures limited for carbon, nitrogen, phosphorus, or sulfur.</a> J. Biol. Chem. 278, 3265-3274 (2003).</li><li>Wu, J., Zhang, N., Hayes, A., Panoutsopoulou, K., Oliver, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Global+analysis+of+nutrient+control+of+gene+expression+in+Saccharomyces+cerevisiae+during+growth+and+starvation.">Global analysis of nutrient control of gene expression in Saccharomyces cerevisiae during growth and starvation.</a> 101, 3148-3153 (2004).</li><li>Diderich, J. A., Kruckeberg, A. L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Glucose+Uptake+Kinetics+and+Transcription+of+HXT+Genes+in+Chemostat+Cultures+of+Saccharomyces+cerevisiae.">Glucose Uptake Kinetics and Transcription of HXT Genes in Chemostat Cultures of Saccharomyces cerevisiae.</a> J. Biol. Chem. 274, 15350-15359 (1999).</li><li>Novick, A., Szilard, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Experiments+with+the+Chemostat+on+spontaneous+mutations+of+bacteria.">Experiments with the Chemostat on spontaneous mutations of bacteria.</a> Proc. Natl. Acad. Sci. U.S.A. 36, 708-719 (1950).</li><li>Kubitschek, H. E., Bendigkeit, H. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mutation+in+continuous+cultures.+I.+Dependence+of+mutational+response+upon+growth-limiting+factors.">Mutation in continuous cultures. I. Dependence of mutational response upon growth-limiting factors.</a> Mutation Res. 1, 113-120 (1964).</li><li>Gresham, D., Dunham, M. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Repertoire+and+Dynamics+of+Evolutionary+Adaptations+to+Controlled+Nutrient-Limited+Environments+in+Yeast.">The Repertoire and Dynamics of Evolutionary Adaptations to Controlled Nutrient-Limited Environments in Yeast.</a> PLoS Genet. 4, e1000303 (2008).</li><li>Kao, K. C., Sherlock, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Molecular+characterization+of+clonal+interference+during+adaptive+evolution+in+asexual+populations+of+Saccharomyces+cerevisiae.">Molecular characterization of clonal interference during adaptive evolution in asexual populations of Saccharomyces cerevisiae.</a> Nat. Genet. 40, 1499-1504 (2008).</li><li>Kvitek, D. J., Sherlock, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Reciprocal+Sign+Epistasis+between+Frequently+Experimentally+Evolved+Adaptive+Mutations+Causes+a+Rugged+Fitness+Landscape.">Reciprocal Sign Epistasis between Frequently Experimentally Evolved Adaptive Mutations Causes a Rugged Fitness Landscape.</a> PLoS Genet. 7, e1002056 (2011).</li><li>Helling, R. B., Adams, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Evolution+of+Escherichia+coli+during+Growth+in+a+Constant+Environment.">Evolution of Escherichia coli during Growth in a Constant Environment.</a> Genetics. 116, 349-358 (1987).</li><li>Dunham, M. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Experimental+Evolution+in+Yeast:+A+Practical+Guide.">Experimental Evolution in Yeast: A Practical Guide.</a> Methods Enzymol. 470, (2010).</li><li>Hoskisson, P. A., Hobbs, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Continuous+culture+-+making+a+comeback.">Continuous culture - making a comeback.</a> Microbiology. 151, 3153-3159 (2005).</li><li>Nanchen, A., Schicker, A., Sauer, U. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Nonlinear+dependency+of+intracellular+fluxes+on+growth+rate+in+miniaturized+continuous+cultures+of+Escherichia+coli.">Nonlinear dependency of intracellular fluxes on growth rate in miniaturized continuous cultures of Escherichia coli.</a> Appl. Environ. Microbiol. 72, 1164-1172 (2006).</li><li>Klein, T., Schneider, K., Heinzle, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+system+of+miniaturized+stirred+bioreactors+for+parallel+continuous+cultivation+of+yeast+with+online+measurement+of+dissolved+oxygen+and+off-gas.">A system of miniaturized stirred bioreactors for parallel continuous cultivation of yeast with online measurement of dissolved oxygen and off-gas.</a> Biotechnol. and bioeng. , (2012).</li><li>Balagadde, F. K., You, L., Hansen, C. L., Arnold, F. H., Quake, S. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Long-term+monitoring+of+bacteria+undergoing+programmed+population+control+in+a+microchemostat.">Long-term monitoring of bacteria undergoing programmed population control in a microchemostat.</a> Science. 309, 137-140 (2005).</li><li>Groisman, A., Lobo, C., Cho, H., Campbell, J. K., Dufour, Y. S., Stevens, A. M., Levchenko, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+microfluidic+chemostat+for+experiments+with+bacterial+and+yeast+cells.">A microfluidic chemostat for experiments with bacterial and yeast cells.</a> Nat. Methods. 2, 685-689 (2005).</li><li>Brauer, M. J., Botstein, D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Homeostatic+Adjustment+and+Metabolic+Remodeling+in+Glucose-limited+Yeast+Cultures.">Homeostatic Adjustment and Metabolic Remodeling in Glucose-limited Yeast Cultures.</a> Mol. Biol. Cell. 16, 2503-2517 (2005).</li><li>Torres, E. M., Amon, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Effects+of+Aneuploidy+on+Cellular+Physiology+and+Cell+Division+in+Haploid+Yeast.">Effects of Aneuploidy on Cellular Physiology and Cell Division in Haploid Yeast.</a> Science. 317, 916-924 (2007).</li><li>Regenberg, B., Nielsen, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Growth-rate+regulated+genes+have+profound+impact+on+interpretation+of+transcriptome+profiling+in+Saccharomyces+cerevisiae.">Growth-rate regulated genes have profound impact on interpretation of transcriptome profiling in Saccharomyces cerevisiae.</a> Genome Biology. 7, R107 (2006).</li><li>Castrillo, J. I., Oliver, S. G., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Growth+control+of+the+eukaryote+cell:+a+systems+biology+study+in+yeast.">Growth control of the eukaryote cell: a systems biology study in yeast.</a> Journal of Biology. 6, 4 (2007).</li><li>Brauer, M. J., Botstein, D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Coordination+of+growth+rate,+cell+cycle,+stress+response,+and+metabolic+activity+in+yeast.">Coordination of growth rate, cell cycle, stress response, and metabolic activity in yeast.</a> Molecular Biology of the Cell. 19, 352-367 (2008).</li><li>Ferenci, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Bacterial+physiology,+regulation+and+mutational+adaptation+in+a+chemostat+environment.">Bacterial physiology, regulation and mutational adaptation in a chemostat environment.</a> Adv. Microb. Physiol. 53, 169-229 (2008).</li></ol>

The authors declare that they have no conflicts of interest.

Chemostat cultivation in the ministats, as with any chemostat, requires attention to detail and trouble-shooting. Since contamination is of great concern in continuous culture experiments, we typically look via microscope for bacterial and fungal contamination upon inoculation and every 50 generations during long-term evolution experiments. To date we have not observed contamination across 96 evolution experiments of greater than 300 generations (data not shown). To test for cross-contamination between ministats and the potential for microbes to colonize the culture chamber by way of the effluent line we ran 16 ministats such that every other ministat was inoculated with yeast as above and the remainder were not inoculated with any culture. The cultures were sampled into a communal waste container, which was emptied every other day. Thus if it were possible for contaminants to enter through the effluent line we likely would have observed that in this experiment. During three weeks and greater than 100 generations of growth in this checkerboard pattern of inoculated and non-inoculated cultures we did not observe growth in non-inoculated ministat culture tubes, suggesting that contamination from outside yeast or other microbes is unlikely to occur in experiments of similar time frames. 
Although the ministats were designed to operate in a fashion analogous to commercial chemostats, the modular nature of this arrangement allows for optimization to fit the users' needs and budget. The peristaltic pump used in this protocol can achieve flow rates between 0.0186 vol/hr to 3.6 vol/hr (data not shown). Increased control of dilution rates could be achieved with alternative pump models. Note that operation at lower dilution rates may require substitution of a higher gauge needle to achieve the same frequency of droplet delivery. Population size is an important consideration for proper design of evolution experiments. The standard dilution rate and nutrient concentration used here provides a relatively large population size (~109 cells) of the same order of magnitude as published evolution studies.11 Larger or smaller populations could be maintained by changing the working volume or limiting nutrient concentration. Increased mutation supply could also be obtained by working with strains with elevated mutation rates.
The ministats could also be improved over our current design. For instance condensation can collect on the culture tube walls and can be greatly reduced by using a deep waterbath, incubator, or constant temperature room. Though clumping and wall growth in sulfate limited cultures appears to be relatively rare, appearing in 5/48 evolution experiments by 300 generations (data not shown), a variety of surfactants are available that may aid in decreasing or delaying this trait. In the event that clumping interferes with adequate culture mixing, increased agitation can be achieved by reducing the number of ways each air pump is divided, or by adding a stirring apparatus. Additional probes for dissolved gas concentration, pH, or other parameters could also be included, as in some other designs.17
Despite potential modifications, using the ministats as described in this protocol, we observed highly consistent experimental parameters and reproducible results when comparing our device to reported data for larger volume commercial chemostats. This included reproducibility of cellular physiology as seen through reaching steady-state equilibrium within 10-15 generations (Figure 2A) and obtaining similar culture densities at equilibrium. Gene expression patterns were consistent across three biological replicates in ministats and between ministats and commercial large-volume platforms (Figure 2B), with the exception of iron metabolism genes. These expression differences are likely caused by changes in metal content of the two devices or improvements in the quality of media ingredients. Our data suggest that ministats will be useful for physiology or competition experiments where a consistent environment is required.
To test if the ministat design is sufficient for experimental evolution applications we evolved cultures under sulfate limitation for 250 generations and used CGH to characterize amplification at the SUL1 locus - a hallmark of long-term evolution under these conditions in larger volume chemostats.10 We observed amplification of SUL1 in clones from 4/4 independent evolution experiments in sulfate-limited media (Figure 2C). Taken as a whole these data suggest that ministats are a robust platform that may be useful for a variety of traditional chemostat applications. Though we demonstrated their use in culturing budding yeast, the ministats should also be compatible with other organisms and similar designs have in fact been used for culturing bacteria and other yeast species.16,17,25 Furthermore the smaller culture volume and correlated decreased need for media may make ministats an attractive alternative for experiments requiring expensive or exotic reagents as can be the case in chemical or genetic screens.

The dynamics of microbial growth and evolution are fundamental to microbiology, ecology, genetics, and biotechnology. The most common method of culturing microbes is in batch, where cells are inoculated at low density into nutrient-rich broth and grown to saturation. Though straightforward to perform using standard laboratory equipment, batch cultures experience a fluctuating chemical environment and correspondingly changing cellular physiology. This heterogeneous growth environment can result in secondary growth and stress effects that can mask subtle physiological differences. Experimental evolution by serial batch transfer can select for complex mixtures of growth-phase specific subpopulations, complicating attempts to connect adaptations to specific selective conditions. Measurement of quantitative phenotypes can be difficult due to noise from imprecise sample timing and variation in features such as lag time. Continuous cultures provide an alternative growth regime where cells can be reproducibly cultivated in a chemically homogeneous environment at a defined growth rate to reach a physiological steady state. Because of these advantages, studies of experimental evolution and characterization of cellular state often utilize the controlled environment of continuous cultures like the chemostat.14 
Appreciation of these advantages has led to a resurgence in interest in chemostat cultures.15 Since their introduction in 1950,1,2 chemostat systems have been developed to function on a variety of scales ranging from liters to microliters and for a variety of applications.16-19 These various designs, which range from commercially produced bioreactors to glassblown vessels to custom microfluidics platforms, share general design principles. A culture chamber is stirred and aerated (usually by bubbling air through it) and the microbes contained therein are kept homogeneously dispersed throughout the culture chamber at all times. Fresh medium of defined composition is added continually and the rate of addition controls growth rate and influences the chemical environment experienced by the culture. An overflow sets the culture volume in the growth tube, and through this overflow the culture will be sampled at the same rate at which fresh medium enters. In this way cultures quickly reach a physiological steady state at which many biological parameters remain constant. Despite the advantages of chemostats and reports of these various platforms in the literature, widespread adoption has been limited by difficulties in building and operating these systems, and high costs associated with commercial options. Furthermore descriptions of how to make and use these devices can be opaque. 
We present designs and instructions for use of a small-footprint array of miniature chemostats built from readily available parts at low cost. We observe highly consistent experimental parameters and reproducible results when comparing our device to reported data for yeast cultured in larger volume commercial bioreactors. This includes reproducibility of cellular physiology as seen through reaching steady-state equilibrium within 10-15 generations and obtaining similar culture densities at equilibrium. Additionally, gene expression patterns are consistent between ministats and a commercial larger-volume platform. Stability of dilution rate, optical density and reproducibility of gene expression between three replicate cultures demonstrate the robustness of our platform. We also show that the same adaptive mutations arise over similar experimental evolution timescales as with larger volume chemostats.

<table border="1">
 <tbody>
 <tr>
 <td>Name of the reagent</td>
 <td>Company</td>
 <td>Catalogue number</td>
 <td>Comments (optional)</td>
 </tr>
 <tr>
 <td>3/32" x 7/32" silicone tubing</td>
 <td>VWR</td>
 <td>63009-260</td>
 <td>Tubing: Order: (50' coil pack) </td>
 </tr>
 <tr>
 <td>1/2" x 5/8" silicone tubing (extra large)</td>
 <td>VWR</td>
 <td>63009-299</td>
 <td>Tubing: Order: (50' coil pack)</td>
 </tr>
 <tr>
 <td>1/4" x 3/8" silicone tubing (medium)</td>
 <td>VWR</td>
 <td>63009-279</td>
 <td>Tubing: Order: (50' coil pack)</td>
 </tr>
 <tr>
 <td>Orange green marprene pump tubing</td>
 <td>Watson-Marlow</td>
 <td>978.0038.00+</td>
 <td>Tubing: Order: 6x(pack of 6)</td>
 </tr>
 <tr>
 <td>Female luer, 1/8" barb</td>
 <td>Cole Parmer</td>
 <td>HV-45500-04</td>
 <td>Connectors: Order: 4x(pack of 25)</td>
 </tr>
 <tr>
 <td>Male luer lock, 1/8" barb</td>
 <td>Cole Parmer</td>
 <td>HV-45503-04</td>
 <td>Connectors: Order: 1x (pack of 25)</td>
 </tr>
 <tr>
 <td>Reducing connector, PVDF, 1/4" to 1/8"</td>
 <td>Cole Parmer</td>
 <td>EW-30703-50</td>
 <td>Connectors: Order: 1x (pack of 10)</td>
 </tr>
 <tr>
 <td>Barbed Y connector, 1/8" ID</td>
 <td>Cole Parmer</td>
 <td>HV-30703-92</td>
 <td>Connectors: Order: 3x(pack of 10)</td>
 </tr>
 <tr>
 <td>Medium tubing clamps</td>
 <td>VWR</td>
 <td>63022-405</td>
 <td>Clamps: Order: 1x(pack of 12)</td>
 </tr>
 <tr>
 <td>Day Pinchcock (metal clamp for tubing)</td>
 <td>VWR</td>
 <td>21730-001</td>
 <td>Clamps: Order: 1x(pack of 10)</td>
 </tr>
 <tr>
 <td>Male inline valved quick-connector, Fits tubing: 1/4 in.</td>
 <td>Fisher</td>
 <td>05-112-39</td>
 <td>Connectors: Order: 1x(pack of 25)</td>
 </tr>
 <tr>
 <td>Female inline valved quick-connector, Fits tubing: 1/4 in. I.D.,Polypropylene</td>
 <td>Fisher</td>
 <td>05-112-37</td>
 <td>Connectors: Order: 1x(pack of 5)</td>
 </tr>
 <tr>
 <td>Silent Air Pumps</td>
 <td><a href="http://www.aquariumguys.com/" target="_blank">Aquarium Guys.com </a></td>
 <td>212422</td>
 <td>Air Supply: Order: 4 pumps</td>
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 <tr>
 <td> PTFE filters, 0.45 &mu;m, for air filtration</td>
 <td> Cole Parmer</td>
 <td> HV-02915-22</td>
 <td> Air Supply: Order: 1x(box of 100)</td>
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 <tr>
 <td>1L Flask with sidearm</td>
 <td>Fisher</td>
 <td>10-181F</td>
 <td>Air Supply: Order: 2x(Pack of 6)</td>
 </tr>
 <tr>
 <td>#8 silicone stopper, 3/8 in hole, for sidearm flasks</td>
 <td>Fisher</td>
 <td>K953715-0801</td>
 <td>Air Supply: Order: 8 stoppers</td>
 </tr>
 <tr>
 <td>4-Port manifold</td>
 <td>Cole Parmer</td>
 <td>EW-06464-85</td>
 <td>Air Supply: Order: 8 manifolds</td>
 </tr>
 <tr>
 <td>55 ml Screw cap culture tubes</td>
 <td>Corning Life Sciences</td>
 <td>9825-25</td>
 <td>Culture Chamber: Order: 2x(pack of 48)</td>
 </tr>
 <tr>
 <td>Regular hypodermic white hub needle, 16G, 5 in. length for effluent line</td>
 <td>Fisher</td>
 <td>14-817-105</td>
 <td>Culture Chamber: Order: 1x(pack of 100)</td>
 </tr>
 <tr>
 <td>Spinal tap needle</td>
 <td>VWR</td>
 <td>BD40836</td>
 <td>Culture Chamber: Order: 4x(pack of 10)</td>
 </tr>
 <tr>
 <td>Regular hypodermic pink needle</td>
 <td>Fisher</td>
 <td>14-817-104</td>
 <td>Culture Chamber: Order: 1x(pack of 100)</td>
 </tr>
 <tr>
 <td>Foam Silicone stopper size "2", pink</td>
 <td>Cole Parmer</td>
 <td>EW-06298-06</td>
 <td>Culture Chamber: Order: 2x(pack of 20)</td>
 </tr>
 <tr>
 <td>8-Well tube Rack</td>
 <td>VWR</td>
 <td>82024-452</td>
 <td>Culture Chamber: Order: 4 racks</td>
 </tr>
 <tr>
 <td>10L Reservoir bottle with bottom hose outlet: vacuum safe</td>
 <td>VWR</td>
 <td>89001-530</td>
 <td>Media: Order: 2 or more </td>
 </tr>
 <tr>
 <td>Yellow foam silicone stopper, non-standard size 12</td>
 <td>Cole Parmer</td>
 <td> EW-06298-22</td>
 <td>Media: Order: 2 or more</td>
 </tr>
 <tr>
 <td>Carboy Venting Filter</td>
 <td>Fisher</td>
 <td>SLFG 050 10</td>
 <td>Media: Order: 1x(pack of 10)</td>
 </tr>
 <tr>
 <td>Electrical tape, green</td>
 <td> <a href="http://Amazon.com" target="_blank">Amazon.com</a></td>
 <td>10851-BA-10</td>
 <td>Media: Order 1 roll.</td>
 </tr>
 <tr>
 <td>Bottle top filter, 1L, .2 &mu;m, 45 mm</td>
 <td>VWR</td>
 <td>29442-978</td>
 <td>Media: Order: (1 case of 12)</td>
 </tr>
 <tr>
 <td>5000 ml Reservoir bottle with bottom outlet: vacuum safe</td>
 <td>VWR</td>
 <td>89003-384</td>
 <td>Media: (Optional)</td>
 </tr>
 <tr>
 <td>Blue Foam Silicone stopper, nonstandardsize 10 1/2</td>
 <td>Cole Parmer</td>
 <td>EW-06298-18</td>
 <td>Media: (Optional)</td>
 </tr>
 <tr>
 <td>205S/CA16, 16 Cartridge pump</td>
 <td>Watson-Marlow</td>
 <td>020.3716.00A</td>
 <td>Media Pump: Order: 1</td>
 </tr>
 <tr>
 <td>16-channel 205CA Extension pump head</td>
 <td>Watson-Marlow</td>
 <td>023.1401.000</td>
 <td>Media Pump: Order: 2 extension pump heads</td>
 </tr>
 <tr>
 <td>Silicone aquarium sealer</td>
 <td>Fisher</td>
 <td>S18180B</td>
 <td>Media Pump: Order: 1</td>
 </tr>
 <tr>
 <td>6-block dry bath</td>
 <td>VWR</td>
 <td>12621-120</td>
 <td>Heatblock: Order: 2 for 32 ministats or 1 for 16.</td>
 </tr>
 <tr>
 <td>Block for drybath, 6 x 25 mm test tube per block</td>
 <td>VWR</td>
 <td>12621-120</td>
 <td>Heatblock: Order: 12 for 32 ministats or 6 for 16.</td>
 </tr>
 <tr>
 <td>Nylon Membrane Filters, 0.45 &mu;m Pore Size; Dia.: 25 mm</td>
 <td>Fisher</td>
 <td>R04SP02500</td>
 <td>Harvesting: Order: 1x(pack of 100) (optional)</td>
 </tr>
 <tr>
 <td>Nylon Membrane Filters,0.45 &mu;m Pore Size; 45 mm</td>
 <td>Fisher</td>
 <td>R04SP04700</td>
 <td>Harvesting: Order: 1x(pack of 100) (optional)</td>
 </tr>
 <tr>
 <td>47 mm, large filter apparatus</td>
 <td>Fisher</td>
 <td>XX10 047 30</td>
 <td>Harvesting: Order: 1 (optional)</td>
 </tr>
 <tr>
 <td>Glass filter holder, 25 mm, small filter apparatus</td>
 <td>VWR</td>
 <td>26316-692</td>
 <td>Harvesting: Order: 1 (optional)</td>
 </tr>
 <tr> 
 <td>Dewar flask, 1L for Liquid Nitrogen</td>
 <td>VWR</td>
 <td>63380-052</td>
 <td>Harvesting: Order: 1 (optional)</td>
 </tr>
 </tbody>
</table>

design and use of multiplexed chemostat arrays

Chemostats are continuous culture systems in which cells are grown in a tightly controlled, chemically constant environment where culture density is constrained by limiting specific nutrients.1,2 Data from chemostats are highly reproducible for the measurement of quantitative phenotypes as they provide a constant growth rate and environment at steady state. For these reasons, chemostats have become useful tools for fine-scale characterization of physiology through analysis of gene expression3-6 and other characteristics of cultures at steady-state equilibrium.7 Long-term experiments in chemostats can highlight specific trajectories that microbial populations adopt during adaptive evolution in a controlled environment. In fact, chemostats have been used for experimental evolution since their invention.8 A common result in evolution experiments is for each biological replicate to acquire a unique repertoire of mutations.9-13 This diversity suggests that there is much left to be discovered by performing evolution experiments with far greater throughput. 
We present here the design and operation of a relatively simple, low cost array of miniature chemostats&mdash;or ministats&mdash;and validate their use in determination of physiology and in evolution experiments with yeast. This approach entails growth of tens of chemostats run off a single multiplexed peristaltic pump. The cultures are maintained at a 20 ml working volume, which is practical for a variety of applications. It is our hope that increasing throughput, decreasing expense, and providing detailed building and operation instructions may also motivate research and industrial application of this design as a general platform for functionally characterizing large numbers of strains, species, and growth parameters, as well as genetic or drug libraries.

The ministat array described above and in (Figure 1A, B) was used to culture a haploid MATa laboratory strain of budding yeast (S288c) under sulfate-limiting conditions as described previously.10 We tested efficacy for common chemostat applications including determination of physiology and experimental evolution. To validate the ministats, we repeated several experiments previously performed in industrial fermentors modified for chemostat use.10,20,21 ATR Sixfors fermentors were run at a 300 ml working volume, over ten times the volume of the ministats, and have considerably different modes of culture aeration and agitation. We attempted to replicate equipment stability, steady state physiology, experimental evolution results, and gene expression patterns obtained with these fermentors.
Since uniformity of dilution rate and aeration are important aspects of the chemostat design, we measured the actual dilution rate across 32 ministats after 15 generations of growth and found that with a target dilution rate of 0.17 vol/hr (4-5 drops/min) we achieved an average dilution rate of 0.17208 with a standard deviation of 0.0075 across 32 replicates. This range was within our typical tolerance of +/-0.01 vol/hr difference from the target setting, beyond which large-scale changes in gene expression have been observed.22-23 Across 4 ministats the air flow rate was determined to be 307.5 ml/min with a standard deviation of 9.57 ml/min. This suggests that air-flow into the chambers is robust and evenly divided between the 4 chambers and is a value similar to that described for aeration in industrial fermentors.20 
We previously observed recurrent amplification of the high-affinity sulfur-ion transporter SUL1 in 8/8 sulfate-limited evolution experiments in yeast.10 Given the consistency of results under this condition we chose sulfate-limitation to test our system's ability. A requisite element of chemostat culture is the need to maintain a constant chemical environment. Fluctuations in the abundance of a limiting nutrient or other changes in the environment typically result in a change in the number of cells in a given culture. We measured optical density as a proxy for cell number (Figure 2A) and measured reproducibility across 16 replicate cultures, finding an average A600 of 1.12 (~109 cells) after ~15 generations of growth with a standard deviation of 0.057 units, or 5.1%. For comparison, measurements taken from 4 replicate cultures grown in the industrial fermentors showed a standard deviation of 2.5%. Cells were well-mixed in the growth chamber: measurements of OD and cell count taken from the effluent track were equivalent to samples taken directly from the culture tube (data not shown). These results demonstrate the robustness of our platform and ability to maintain a constant chemical environment within a similar tolerance as the industrial fermentor. 
As a more sensitive readout of physiology, we compared genome-wide steady state gene expression from cultures grown under sulfate limitation in the ministats and in the industrial fermentor. Gene expression in the ministats showed a high degree of similarity across three biological replicates (Figure 2B). We previously noted that for RNA derived from two replicate Sixfors chemostats and co-hybridized to a microarray, expression of 99% of genes fell within a 1.5-fold range, allowing the use of 1.5X as an empirical significance cutoff.21 Gene expression from three replicate ministats, compared pairwise, showed 99% of genes fell within a 1.5-1.7 fold range, comparable to results from the industrial fermentors. The three samples were hybridized to individual arrays and the pairwise ratios calculated afterwards, so these values include inter-array noise in addition to biological noise, potentially overestimating the variation between replicates as compared to the published, co-hybridized results. 138 genes were differentially expressed &gt;1.5-fold in all three ministat replicates as compared to a sample collected from a matched culture grown in the industrial fermentor. Genes decreased in expression in the ministats were heavily enriched for iron metabolism. This signature may reflect the different metal composition of each device configuration: the Sixfors apparatus includes a metal impeller and aeration assembly immersed in the culture, and the media carboys previously used also required metal hardware. The ministat utilizes stainless steel needles, but no other metal components. Genes with increased expression were largely associated with cell membranes, though the biological significance of this association is unclear. 
Finally, we tested experimental evolution under these conditions. After 250 generations of sulfate-limited growth, 4/4 clones tested from 4 independent evolving populations showed amplification of SUL1 as detected by array Comparative Genomic Hybridization (CGH, Figure 2C). This result is consistent with findings in larger volume chemostats over similar time intervals.10
<img src="/files/ftp_upload/50262/50262fig1.jpg" alt="Figure 1" fo:content-width="6in" fo:src="/files/ftp_upload/50262/50262fig1highres.jpg"/> 
Figure 1. A. Design and arrangement of the ministat array. B. Design of the culture chamber.
<img src="/files/ftp_upload/50262/50262fig2.jpg" alt="Figure 2" fo:content-width="5.5in" fo:src="/files/ftp_upload/50262/50262fig2highres.jpg"/> 
Figure 2. A. Experimental data showing that cultures reach equilibrium within ten generations of growth (n=16). B. Expression data for three biological replicates S1-3 sampled during steady state under sulfate limitation compared to a common reference grown in a matched sulfate-limited Sixfors chemostat. C. SUL1 amplifications recovered in ministats after 250 generations of growth in a sulfate-limited environment. Genomic DNA from each evolved clone was compared to ancestral DNA by CGH as described.21 Mean copy number was calculated for each amplified region and is shown next to each amplicon. All microarray data are deposited in the GEO database under accession GSE36691. <a href="https://www.jove.com/files/ftp_upload/50262/50262fig2large.jpg" target="_blank"> Click here to view larger figure.</a>

Watch this Scientific Journal Video about Design and Use of Multiplexed Chemostat Arrays at JoVE.com

Design and Use of Multiplexed Chemostat Arrays

We developed and validated a small-footprint array of miniature chemostats built from readily available parts for low cost. Physiological and experimental evolution results were similar to larger volume chemostats. The ministat array provides a compact, inexpensive, and accessible platform for traditional chemostat experiments, functional genomics, and chemical screening applications.

Chemostats are continuous culture systems in which cells are grown in a tightly controlled, chemically constant environment where culture density is ...

design-and-use-of-multiplexed-chemostat-arrays

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23.1K Views.  University of Washington. We developed and validated a small-footprint array of miniature chemostats built from readily available parts for low cost. Physiological and experimental evolution results were similar to larger volume chemostats. The ministat array provides a compact, inexpensive, and accessible platform for traditional chemostat experiments, functional genomics, and chemical screening applications.

Video: Design and Use of Multiplexed Chemostat Arrays

Microfluidic Chips Controlled with Elastomeric Microvalve Arrays

Miniaturized microfluidic systems provide simple and effective solutions for low-cost point-of-care diagnostics and high-throughput biomedical assays. Robust flow control and precise fluidic volumes are two critical requirements for these applications. We have developed microfluidic chips featuring elastomeric polydimethylsiloxane (PDMS) microvalve arrays that: 1) need no extra energy source to close the fluidic path, hence the loaded device is highly portable; and 2) allow for microfabricating deep (up to 1 mm) channels with vertical sidewalls and resulting in very precise features.

The PDMS microvalves-based devices consist of three layers: a fluidic layer containing fluidic paths and microchambers of various sizes, a control layer containing the microchannels necessary to actuate the fluidic path with microvalves, and a middle thin PDMS membrane that is bound to the control layer. Fluidic layer and control layers are made by replica molding of PDMS from SU-8 photoresist masters, and the thin PDMS membrane is made by spinning PDMS at specified heights. The control layer is bonded to the thin PDMS membrane after oxygen activation of both, and then assembled with the fluidic layer. The microvalves are closed at rest and can be opened by applying negative pressure (e.g., house vacuum). Microvalve closure and opening are automated via solenoid valves controlled by computer software.

Here, we demonstrate two microvalve-based microfluidic chips for two different applications. The first chip allows for storing and mixing precise sub-nanoliter volumes of aqueous solutions at various mixing ratios. The second chip allows for computer-controlled perfusion of microfluidic cell cultures.

The devices are easy to fabricate and simple to control. Due to the biocompatibility of PDMS, these microchips could have broad applications in miniaturized diagnostic assays as well as basic cell biology studies.

We demonstrate protocols for manufacturing and automating elastomeric polydimethylsiloxane (PDMS)-based microvalve arrays that need no extra energy to close and feature photolithographically defined precise volumes. A parallel subnanoliter-volume mixer and an integrated microfluidic perfusion system are presented.

Miniaturized microfluidic systems provide simple and effective solutions for low-cost point-of-care diagnostics and high-throughput biomedical assays.  ...

Profiling of Pre-micro RNAs and microRNAs using Quantitative Real-time PCR (qPCR) Arrays

Quantitative real-time PCR (QPCR) has emerged as an accurate and valuable tool in profiling gene expression levels.  One of its many advantages is a lower detection limit compared to other methods of gene expression profiling while using smaller amounts of input for each assay.  Automated qPCR setup has improved this field by allowing for greater reproducibility.  Its convenient and rapid setup allows for high-throughput experiments, enabling the profiling of many different genes simultaneously in each experiment.  This method along with internal plate controls also reduces experimental variables common to other techniques.  
We recently developed a qPCR assay for profiling of pre-microRNAs  (pre-miRNAs) using a set of 186 primer pairs.  MicroRNAs have emerged as a novel class of small, non-coding RNAs with the ability to regulate many mRNA targets at the post-transcriptional level.  These small RNAs are first transcribed by RNA polymerase II as a primary miRNA (pri-miRNA) transcript, which is then cleaved into the precursor miRNA (pre-miRNA).  Pre-miRNAs are exported to the cytoplasm where Dicer cleaves the hairpin loop to yield mature miRNAs.  Increases in miRNA levels can be observed at both the precursor and mature miRNA levels and profiling of both of these forms can be useful.  There are several commercially available assays for mature miRNAs; however, their high cost may deter researchers from this profiling technique.  Here, we discuss a cost-effective, reliable, SYBR-based qPCR method of profiling pre-miRNAs.  Changes in pre-miRNA levels often reflect mature miRNA changes and can be a useful indicator of mature miRNA expression.  However, simultaneous profiling of both pre-miRNAs and mature miRNAs may be optimal as they can contribute nonredundant information and provide insight into microRNA processing.  Furthermore, the technique described here can be expanded to encompass the profiling of other library sets for specific pathways or pathogens.

Profiling of Pre-micro RNAs and microRNAs using Quantitative Real-time PCR qPCR Arrays

We will demonstrate the setup and analysis of pre-microRNA 96-well arrays for QPCR using a robot as well as by hand with a Thermo Scientific Matrix multichannel pipette.

Quantitative real-time PCR (QPCR) has emerged as an accurate and valuable tool in profiling gene expression levels.  One of its many advantages is a lower ...

Multiplexed Fluorometric ImmunoAssay Testing Methodology and Troubleshooting

To ensure the quality of animal models used in biomedical research we have developed a number of diagnostic testing strategies and methods to determine if animals have been exposed to adventitious infectious agents (viruses, mycoplasma, and other fastidious microorganisms). Infections of immunocompetent animals are generally transient, yet serum antibody responses to infection often can be detected within days to weeks and persist throughout the life of the host. Serology is the primary diagnostic methodology by which laboratory animals are monitored. Historically the indirect enzyme-linked immunosorbent assay (ELISA) has been the main screening method for serosurveillance. The ELISA is performed as a singleplex, in which one microbial antigen-antibody reaction is measured per well. In comparison the MFIA is performed as a multiplexed assay. Since the microspheres come in 100 distinct color sets, as many as 100 different assays can be performed simultaneously in a single microplate well. This innovation decreases the amount of serum, reagents and disposables required for routine testing while increasing the amount of information obtained from a single test well. In addition, we are able to incorporate multiple internal control beads to verify sample and system suitability and thereby assure the accuracy of results. These include tissue control and IgG anti-test serum species immunoglobulin (&alpha;Ig) coated bead sets to evaluate sample suitability. As in the ELISA and IFA, the tissue control detects non-specific binding of serum immunoglobulin. The &alpha;Ig control (Serum control) confirms that serum has been added and contains a sufficient immunoglobulin concentration while the IgG control bead (System Suitability control), coated with serum species immunoglobulin, demonstrates that the labeled reagents and Luminex reader are functioning properly.

Using Luminex Corporation&#x2019;s xMAP microsphere technology, we have developed the Multiplexed Fluorometric ImmunoAssay (MFIA) for serosurveillance of various laboratory animal species. The MFIA is a suspension microarray where antigen, tissue control or immunoglobulins are covalently linked to color-coded polystyrene microspheres. The MFIA testing method as well as various troubleshooting topics is addressed.

To ensure the quality of animal models used in biomedical research we have developed a number of diagnostic testing strategies and methods to determine if ...

Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays

Phenotypes are determined by a complex series of physical (e.g. protein-protein) and functional (e.g. gene-gene or genetic) interactions (GI)1. While physical interactions can indicate which bacterial proteins are associated as complexes, they do not necessarily reveal pathway-level functional relationships1. GI screens, in which the growth of double mutants bearing two deleted or inactivated genes is measured and compared to the corresponding single mutants, can illuminate epistatic dependencies between loci and hence provide a means to query and discover novel functional relationships2. Large-scale GI maps have been reported for eukaryotic organisms like yeast3-7, but GI information remains sparse for prokaryotes8, which hinders the functional annotation of bacterial genomes. To this end, we and others have developed high-throughput quantitative bacterial GI screening methods9, 10.
Here, we present the key steps required to perform quantitative E. coli Synthetic Genetic Array (eSGA) screening procedure on a genome-scale9, using natural bacterial conjugation and homologous recombination to systemically generate and measure the fitness of large numbers of double mutants in a colony array format. Briefly, a robot is used to transfer, through conjugation, chloramphenicol (Cm) - marked mutant alleles from engineered Hfr (High frequency of recombination) 'donor strains' into an ordered array of kanamycin (Kan) - marked F- recipient strains. Typically, we use loss-of-function single mutants bearing non-essential gene deletions (e.g. the 'Keio' collection11) and essential gene hypomorphic mutations (i.e. alleles conferring reduced protein expression, stability, or activity9, 12, 13) to query the functional associations of non-essential and essential genes, respectively. After conjugation and ensuing genetic exchange mediated by homologous recombination, the resulting double mutants are selected on solid medium containing both antibiotics. After outgrowth, the plates are digitally imaged and colony sizes are quantitatively scored using an in-house automated image processing system14. GIs are revealed when the growth rate of a double mutant is either significantly better or worse than expected9. Aggravating (or negative) GIs often result between loss-of-function mutations in pairs of genes from compensatory pathways that impinge on the same essential process2. Here, the loss of a single gene is buffered, such that either single mutant is viable. However, the loss of both pathways is deleterious and results in synthetic lethality or sickness (i.e. slow growth). Conversely, alleviating (or positive) interactions can occur between genes in the same pathway or protein complex2 as the deletion of either gene alone is often sufficient to perturb the normal function of the pathway or complex such that additional perturbations do not reduce activity, and hence growth, further. Overall, systematically identifying and analyzing GI networks can provide unbiased, global maps of the functional relationships between large numbers of genes, from which pathway-level information missed by other approaches can be inferred9.

Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays

Systematic, large-scale synthetic genetic (gene-gene or epistasis) interaction screens can be used to explore genetic redundancy and pathway cross-talk. Here, we describe a high-throughput quantitative synthetic genetic array screening technology, termed eSGA that we developed for elucidating epistatic relationships and exploring genetic interaction networks in Escherichia coli.

Phenotypes  are determined by a complex series of physical (e.g. protein-protein) and  functional (e.g. gene-gene or genetic) interactions (GI)1. While ...

Fabrication and Use of MicroEnvironment microArrays (MEArrays)

The interactions between cells and their surrounding microenvironment have functional consequences for cellular behaviour. On the single cell level, distinct microenvironments can impose differentiation, migration, and proliferation phenotypes, and on the tissue level the microenvironment processes as complex as morphogenesis and tumorigenesis1. Not only do the cell and molecular contents of microenvironments impact the cells within, but so do the elasticity2 and geometry3 of the tissue. Defined as the sum total of cell-cell, -ECM, and -soluble factor interactions, in addition to physical characteristics, the microenvironment is complex. The phenotypes of cells within a tissue are partially due to their genomic content and partially due to the combinatorial interactions with the microenviroment. A major challenge is to link specific combinations of microenvironmental components with distinctive behaviours.
Here, we present the microenvironment microarray (MEArray) platform for cell-based functional screening of interactions with combinatorial microenvironments4. The method allows for simultaneous control of the molecular composition and the elastic modulus, and combines the use of widely available microarray and micropatterning technologies. MEArray screens require as few as 10,000 cells per array, which facilitates functional studies of rare cell types such as adult progenitor cells. A limitation of the technology is that entire tissue microenvironments cannot be completely recapitulated on MEArrays. However, comparison of responses in the same cell type to numerous related microenvironments, for instance pairwise combinations of ECM proteins that characterize a given tissue, will provide insights into how microenvironmental components elicit tissue-specific functional phenotypes.
MEArrays can be printed using a wide variety of recombinant growth factors, cytokines, and purified ECM proteins, and combinations thereof. The platform is limited only by the availability of specific reagents. MEArrays are amenable to time-lapsed analysis, but most often are used for end point analyses of cellular functions that are measureable with fluorescent probes. For instance, DNA synthesis, apoptosis, acquisition of differentiated states, or production of specific gene products are commonly measured. Briefly, the basic flow of an MEArray experiment is to prepare slides coated with printing substrata and to prepare the master plate of proteins that are to be printed. Then the arrays are printed with a microarray robot, cells are allowed to attach, grow in culture, and then are chemically fixed upon reaching the experimental endpoint. Fluorescent or colorimetric assays, imaged with traditional microscopes or microarray scanners, are used to reveal relevant molecular and cellular phenotypes (Figure 1).

Fabrication and Use of MicroEnvironment microArrays MEArrays

A combinatorial functional screening method for gaining insights into the impacts of the molecular composition of microenvironments on cellular functions is described. The method takes advantage of existing microarray-based technologies to generate arrays of defined combinatorial microenvironments that support cell adhesion and functional analysis.

The interactions between cells and their surrounding microenvironment have functional consequences for cellular behaviour. On the single cell level, ...

Assembly of Nucleosomal Arrays from Recombinant Core Histones and Nucleosome Positioning DNA

Core histone octamers that are repetitively spaced along a DNA molecule are called nucleosomal arrays. Nucleosomal arrays are obtained in one of two ways: purification from in vivo sources, or reconstitution in vitro from recombinant core histones and tandemly repeated nucleosome positioning DNA. The latter method has the benefit of allowing for the assembly of a more compositionally uniform and precisely positioned nucleosomal array. Sedimentation velocity experiments in the analytical ultracentrifuge yield information about the size and shape of macromolecules by analyzing the rate at which they migrate through solution under centrifugal force. This technique, along with atomic force microscopy, can be used for quality control, ensuring that the majority of DNA templates are saturated with nucleosomes after reconstitution. Here we describe the protocols necessary to reconstitute milligram quantities of length and compositionally defined nucleosomal arrays suitable for biochemical and biophysical studies of chromatin structure and function.

A method is presented for the reconstitution of model nucleosomal arrays from recombinant core histones and tandemly repeated nucleosome positioning DNA. We also describe how sedimentation velocity experiments in the analytical ultracentrifuge, and atomic force microscopy (AFM) are used to monitor the extent of nucleosomal array saturation after reconstitution.

Core histone octamers that are repetitively spaced along a DNA molecule  are called nucleosomal arrays. Nucleosomal arrays are obtained in one of two  ...

Design and Analysis of Temperature Preference Behavior and its Circadian Rhythm in Drosophila

The circadian clock regulates many aspects of life, including sleep, locomotor activity, and body temperature (BTR) rhythms1,2. We recently identified a novel Drosophila circadian output, called the temperature preference rhythm (TPR), in which the preferred temperature in flies rises during the day and falls during the night 3. Surprisingly, the TPR and locomotor activity are controlled through distinct circadian neurons3. Drosophila locomotor activity is a well&#160;known circadian behavioral output and has provided strong contributions to the discovery of many conserved mammalian circadian clock genes and mechanisms4. Therefore, understanding TPR will lead to the identification of hitherto unknown molecular and cellular circadian mechanisms. Here, we describe how to perform and analyze the TPR assay. This technique not only allows for dissecting the molecular and neural mechanisms of TPR, but also provides new insights into the fundamental mechanisms of the brain functions that integrate different environmental signals and regulate animal behaviors. Furthermore, our recently published data suggest that the fly TPR shares features with the mammalian BTR3. Drosophila are ectotherms, in which the body temperature is typically behaviorally regulated. Therefore, TPR is a strategy used to generate a rhythmic body temperature in these flies5-8. We believe that further exploration of Drosophila TPR will facilitate the characterization of the mechanisms underlying body temperature control in animals.

Design and Analysis of Temperature Preference Behavior and its Circadian Rhythm in Drosophila

We recently identified a novel Drosophila circadian output, temperature preference rhythm (TPR), in which the preferred temperature in flies rises during the day and falls during the night. TPR is regulated independently from another circadian output, locomotor activity. Here&#160;we describe the design and analysis of TPR in Drosophila.

The circadian clock regulates many aspects of life, including sleep, locomotor activity, and body temperature (BTR) rhythms1,2. We recently identified a ...

Identifying Protein-protein Interaction Sites Using Peptide Arrays

Protein-protein interactions mediate most of the processes in the living cell and control homeostasis of the organism. Impaired protein interactions may result in disease, making protein interactions important drug targets. It is thus highly important to understand these interactions at the molecular level. Protein interactions are studied using a variety of techniques ranging from cellular and biochemical assays to quantitative biophysical assays, and these may be performed either with full-length proteins, with protein domains or with peptides. Peptides serve as excellent tools to study protein interactions since peptides can be easily synthesized and allow the focusing on specific interaction sites. Peptide arrays enable the identification of the interaction sites between two proteins as well as screening for peptides that bind the target protein for therapeutic purposes. They also allow high throughput SAR studies. For identification of binding sites, a typical peptide array usually contains partly overlapping 10-20 residues peptides derived from the full sequences of one or more partner proteins of the desired target protein. Screening the array for binding the target protein reveals the binding peptides, corresponding to the binding sites in the partner proteins, in an easy and fast method using only small amount of protein.
In this article we describe a protocol for screening peptide arrays for mapping the interaction sites between a target protein and its partners. The peptide array is designed based on the sequences of the partner proteins taking into account their secondary structures. The arrays used in this protocol were Celluspots arrays prepared by INTAVIS Bioanalytical Instruments. The array is blocked to prevent unspecific binding and then incubated with the studied protein. Detection using an antibody reveals the binding peptides corresponding to the specific interaction sites between the proteins.

Peptide array screening is a high throughput assay for identifying protein-protein interaction sites. This allows mapping multiple interactions of a target protein and can serve as a method for identifying sites for inhibitors that target a protein. Here we describe a protocol for screening and analyzing peptide arrays.

Protein-protein interactions mediate most of the processes in the living cell and control homeostasis of the organism. Impaired protein interactions may ...

Specificity Analysis of Protein Lysine Methyltransferases Using SPOT Peptide Arrays

Lysine methylation is an emerging post-translation modification and it has been identified on several histone and non-histone proteins, where it plays crucial roles in cell development and many diseases. Approximately 5,000 lysine methylation sites were identified on different proteins, which are set by few dozens of protein lysine methyltransferases. This suggests that each PKMT methylates multiple proteins, however till now only one or two substrates have been identified for several of these enzymes. To approach this problem, we have introduced peptide array based substrate specificity analyses of PKMTs. Peptide arrays are powerful tools to characterize the specificity of PKMTs because methylation of several substrates with different sequences can be tested on one array. We synthesized peptide arrays on cellulose membrane using an Intavis SPOT synthesizer and analyzed the specificity of various PKMTs. Based on the results, for several of these enzymes, novel substrates could be identified. For example, for NSD1 by employing peptide arrays, we showed that it methylates K44 of H4 instead of the reported H4K20 and in addition H1.5K168 is the highly preferred substrate over the previously known H3K36. Hence, peptide arrays are powerful tools to biochemically characterize the PKMTs.

Peptide arrays synthesized by the SPOT method can be used to analyze the substrate specificity of Protein lysine methyltransferases (PKMTs) and to define the substrate spectrum of PKMTs to understand their biological role. This protocol describes how to synthesize peptide arrays, methylate them with PKMTs, and analyze the results.

Lysine methylation is an emerging post-translation modification and it has been identified on several histone and non-histone proteins, where it plays ...

Genetic Barcoding with Fluorescent Proteins for Multiplexed Applications

Fluorescent proteins, fluorescent dyes and fluorophores in general have revolutionized the field of molecular cell biology. In particular, the discovery of fluorescent proteins and their genes have enabled the engineering of protein fusions for localization, the analysis of transcriptional activation and translation of proteins of interest, or the general tracking of individual cells and cell populations. The use of fluorescent protein genes in combination with retroviral technology has further allowed the expression of these proteins in mammalian cells in a stable and reliable manner. Shown here is how one can utilize these genes to give cells within a population of cells their own biosignature. As the biosignature is achieved with retroviral technology, cells are barcoded &#180;indefinitely&#180;. As such, they can be individually tracked within a mixture of barcoded cells and utilized in more complex biological applications. The tracking of distinct populations in a mixture of cells is ideal for multiplexed applications such as discovery of drugs against a multitude of targets or the activation profile of different promoters. The protocol describes how to elegantly develop and amplify barcoded mammalian cells with distinct genetic fluorescent markers, and how to use several markers at once or one marker at different intensities. Finally, the protocol describes how the cells can be further utilized in combination with cell-based assays to increase the power of analysis through multiplexing.

Since the discovery of the green fluorescent protein gene, fluorescent proteins have impacted molecular cell biology. This protocol describes how expression of distinct fluorescent proteins through genetic engineering is used for barcoding individual cells. The procedure enables tracking distinct populations in a cell mixture, which is ideal for multiplexed applications.

Fluorescent proteins, fluorescent dyes and fluorophores in general have revolutionized the field of molecular cell biology. In particular, the discovery ...