We would like to acknowledge Molly Lazar and Ver&#243;nica Delgado for assistance in testing the protocol, Kieran Sweeney for helpful discussions and editing, and Taylor Scott, My An-adirekkun, and Stephanie Geller for critical reading of the manuscript. Megan Nicole McClean, Ph.D. holds a Career Award at the Scientific Interface from the Burroughs Wellcome Fund.

<ol>
	<li>Motta-Mena, L. B., Reade, 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=An+optogenetic+gene+expression+system+with+rapid+activation+and+deactivation+kinetics.">An optogenetic gene expression system with rapid activation and deactivation kinetics.</a> Nature chemical biology. 10 (3), 196-202 (2014).</li><li>Hughes, R. M., Bolger, S., Tapadia, H., Tucker, C. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Light-mediated+control+of+DNA+transcription+in+yeast.">Light-mediated control of DNA transcription in yeast.</a> Methods. 58 (4), 385-391 (2012).</li><li>Shimizu-Sato, S., Huq, E., Tepperman, J. M., Quail, P. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+light-switchable+gene+promoter+system.">A light-switchable gene promoter system.</a> Nature biotechnology. 20 (10), 1041-1044 (2002).</li><li>Polstein, L. R., Gersbach, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=a+Light-inducible+spatiotemporal+control+of+gene+activation+by+customizable+zinc+finger+transcription+factors.">a Light-inducible spatiotemporal control of gene activation by customizable zinc finger transcription factors.</a> J Am Chem Soc. 134 (40), 16480-16483 (2012).</li><li>Polstein, L. R., Gersbach, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=a+A+light-inducible+CRISPR-Cas9+system+for+control+of+endogenous+gene+activation.">a A light-inducible CRISPR-Cas9 system for control of endogenous gene activation.</a> Nature Chemical Biology. 11 (3), 198-200 (2015).</li><li>Yang, X., Jost, A. P. T., Weiner, O. D., Tang, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+light-inducible+organelle-targeting+system+for+dynamically+activating+and+inactivating+signaling+in+budding+yeast.">A light-inducible organelle-targeting system for dynamically activating and inactivating signaling in budding yeast.</a> Molecular biology of the cell. 24 (15), 2419-2430 (2013).</li><li>Lee, S., Park, H., 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=Reversible+protein+inactivation+by+optogenetic+trapping+in+cells.">Reversible protein inactivation by optogenetic trapping in cells.</a> Nature methods. 11 (6), 633-636 (2014).</li><li>Kennedy, M. J., Hughes, R. M., Peteya, L. A., Schwartz, J. W., Ehlers, M. D., Tucker, C. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Rapid+blue-light-mediated+induction+of+protein+interactions+in+living+cells.">Rapid blue-light-mediated induction of protein interactions in living cells.</a> Nature Methods. 7 (12), 973-975 (2010).</li><li>Yazawa, M., Sadaghiani, A. M., Hsueh, B., Dolmetsch, R. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Induction+of+protein-protein+interactions+in+live+cells+using+light.">Induction of protein-protein interactions in live cells using light.</a> Nat Biotechnol. 27 (10), 941-945 (2009).</li><li>Zoltowski, B. D., Motta-Mena, L. B., Gardner, K. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Blue+light-induced+dimerization+of+a+bacterial+LOV-HTH+DNA-binding+protein.">Blue light-induced dimerization of a bacterial LOV-HTH DNA-binding protein.</a> Biochemistry. 52 (38), 6653-6661 (2013).</li><li>Renicke, C., Schuster, D., Usherenko, S., Essen, L. O., Taxis, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+LOV2+Domain-Based+Optogenetic+Tool+to+Control+Protein+Degradation+and+Cellular+Function.">A LOV2 Domain-Based Optogenetic Tool to Control Protein Degradation and Cellular Function.</a> Chemistry &amp; Biology. 20 (4), 619-626 (2013).</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 (New York, N.Y.). 112 (2920), 715-716 (1950).</li><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=La+technique+de+culture+continue.+Th&#233;orie+et+applications.">La technique de culture continue. Th&#233;orie et applications.</a> Ann. Inst. Pasteur. 79 (4), 390-410 (1950).</li><li>Shimizu-Sato, S., Huq, E., Tepperman, J. M., Quail, P. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+light-switchable+gene+promoter+system.">A light-switchable gene promoter system.</a> Nature Biotechnology. 20, 1041-1044 (2002).</li><li>Kennedy, M. J., Hughes, R. M., Peteya, L. A., Schwartz, J. W., Ehlers, M. D., Tucker, C. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Rapid+blue-light-mediated+induction+of+protein+interactions+in+living+cells.">Rapid blue-light-mediated induction of protein interactions in living cells.</a> Nature Methods. 7, 973-975 (2010).</li><li>Olson, E. J., Tabor, J. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Optogenetic+characterization+methods+overcome+key+challenges+in+synthetic+and+systems+biology.">Optogenetic characterization methods overcome key challenges in synthetic and systems biology.</a> Nature chemical biology. 10 (7), 502-511 (2014).</li><li>Botstein, D., Fink, G. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Yeast:+An+experimental+organism+for+21st+century+biology.">Yeast: An experimental organism for 21st century biology.</a> Genetics. 189 (3), 695-704 (2011).</li><li>Galanie, S., Smolke, C. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Optimization+of+yeast-based+production+of+medicinal+protoberberine+alkaloids.">Optimization of yeast-based production of medicinal protoberberine alkaloids.</a> Microbial cell factories. 14 (1), 144 (2015).</li><li>Gerngross, T. U. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Advances+in+the+production+of+human+therapeutic+proteins+in+yeasts+and+filamentous+fungi.">Advances in the production of human therapeutic proteins in yeasts and filamentous fungi.</a> Nature biotechnology. 22 (11), 1409-1414 (2004).</li><li>van Maris, A. J. A., Abbott, D. 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=Alcoholic+fermentation+of+carbon+sources+in+biomass+hydrolysates+by+Saccharomyces+cerevisiae:+current+status.">Alcoholic fermentation of carbon sources in biomass hydrolysates by Saccharomyces cerevisiae: current status.</a> Antonie van Leeuwenhoek. 90 (4), 391-418 (2006).</li><li>Edelstein, A., Amodaj, N., Hoover, K., Vale, R., Stuurman, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Computer+control+of+microscopes+using+&#181;Manager.">Computer control of microscopes using &#181;Manager.</a> Curr Protoc Mol Biol. , (2010).</li><li>Edelstein, A. D., Tsuchida, M. A., Amodaj, N., Pinkard, H., Vale, R. D., Stuurman, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Advanced+methods+of+microscope+control+using+&#181;Manager+software.">Advanced methods of microscope control using &#181;Manager software.</a> Journal of biological methods. 1 (2), (2014).</li><li>Schindelin, J., Arganda-Carreras, I., 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=Fiji:+an+open-source+platform+for+biological-image+analysis.">Fiji: an open-source platform for biological-image analysis.</a> Nature methods. 9 (7), 676-682 (2012).</li><li>Bhattacharya, S., Datta, A., Berg, J. M., Gangopadhyay, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Studies+on+surface+wettability+of+poly(dimethyl)+siloxane+(PDMS)+and+glass+under+oxygen-plasma+treatment+and+correlation+with+bond+strength.">Studies on surface wettability of poly(dimethyl) siloxane (PDMS) and glass under oxygen-plasma treatment and correlation with bond strength.</a> Journal of Microelectromechanical Systems. 14 (3), 590-597 (2005).</li><li>Saldanha, A. J., Brauer, M. J., Botstein, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Nutritional+homeostasis+in+batch+and+steady-state+culture+of+yeast.">Nutritional homeostasis in batch and steady-state culture of yeast.</a> Molecular Biology of the Cell. 15, 4089-4104 (2004).</li><li>Boer, V. M., Tai, S. 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=Transcriptional+responses+of+Saccharomyces+cerevisaie+to+preferred+and+nonpreferred+nitrogen+sources+in+glucose-limited+chemostat+cultures.">Transcriptional responses of Saccharomyces cerevisaie to preferred and nonpreferred nitrogen sources in glucose-limited chemostat cultures.</a> FEMS Yeast Research. 7, 604-620 (2007).</li><li>Boer, V. M., Amini, S., Botstein, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Influence+of+genotype+and+nutrition+on+survival+and+metabolism+of+starving+yeast.">Influence of genotype and nutrition on survival and metabolism of starving yeast.</a> Proceedings of the National Academy of Sciences. 105, 6930-6935 (2008).</li><li>Brauer, M. J., Huttenhower, C., 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>Gresham, D., 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=The+enduring+utility+of+continuous+culturing+in+experimental+evolution.">The enduring utility of continuous culturing in experimental evolution.</a> Genomics. 104 (6), 399-405 (2014).</li><li>Liu, H., Yu, X., 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=Photoexcited+CRY2+interacts+with+CIB1+to+regulate+transcription+and+floral+initiation+in+Arabidopsis.">Photoexcited CRY2 interacts with CIB1 to regulate transcription and floral initiation in Arabidopsis.</a> Science (New York, N.Y.). 322 (5907), 1535-1539 (2008).</li><li>McIsaac, R. S., Oakes, B. L., Wang, X., Dummit, K. A., Botstein, D., Noyes, M. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Synthetic+gene+expression+perturbation+systems+with+rapid,+tunable,+single-gene+specificity+in+yeast.">Synthetic gene expression perturbation systems with rapid, tunable, single-gene specificity in yeast.</a> Nucleic Acids Research. 41 (4), 1-10 (2013).</li><li>McIsaac, R. S., Petti, A. A., Bussemaker, H. J., Botstein, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Perturbation-based+analysis+and+modeling+of+combinatorial+regulation+in+the+yeast+sulfur+assimilation+pathway.">Perturbation-based analysis and modeling of combinatorial regulation in the yeast sulfur assimilation pathway.</a> Molecular biology of the cell. 23 (15), 2993-3007 (2012).</li><li>McIsaac, R. S., Silverman, S. 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=Fast-acting+and+nearly+gratuitous+induction+of+gene+expression+and+protein+depletion+in+Saccharomyces+cerevisiae.">Fast-acting and nearly gratuitous induction of gene expression and protein depletion in Saccharomyces cerevisiae.</a> Molecular biology of the cell. 22 (22), 4447-4459 (2011).</li><li>Melendez, J., Patel, M., Oakes, B. L., Xu, P., Morton, P., McClean, M. N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Real-time+optogenetic+control+of+intracellular+protein+concentration+in+microbial+cell+cultures.">Real-time optogenetic control of intracellular protein concentration in microbial cell cultures.</a> Integrative biology quantitative biosciences from nano to macro. 6 (3), 366-372 (2014).</li><li>Brauer, M. J., Huttenhower, C., 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 (1), 352-367 (2008).</li><li>Boer, V. M., Crutchfield, C. A., Bradley, P. H., Botstein, D., Rabinowitz, J. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Growth-limiting+intracellular+metabolites+in+yeast+growing+under+diverse+nutrient+limitations.">Growth-limiting intracellular metabolites in yeast growing under diverse nutrient limitations.</a> Molecular biology of the cell. 21 (1), 198-211 (2010).</li><li>Markham, B. E., Byrne, W. J., Methods, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Uptake,+storage+and+utilization+of+phosphate+by+yeast.">Uptake, storage and utilization of phosphate by yeast.</a> Journal of the Institute of Brewing. 73, 271-273 (1967).</li><li>Kazemi Seresht, A., Palmqvist, E. A., Olsson, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+impact+of+phosphate+scarcity+on+pharmaceutical+protein+production+in+S.+cerevisiae:+linking+transcriptomic+insights+to+phenotypic+responses.">The impact of phosphate scarcity on pharmaceutical protein production in S. cerevisiae: linking transcriptomic insights to phenotypic responses.</a> Microbial cell factories. 10 (1), 104 (2011).</li><li>Shimizu, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Regulation+Systems+of+Bacteria+such+as+Escherichia+coli+in+Response+to+Nutrient+Limitation+and+Environmental+Stresses.">Regulation Systems of Bacteria such as Escherichia coli in Response to Nutrient Limitation and Environmental Stresses.</a> Metabolites. 4 (1), 1-35 (2013).</li><li>Olson, E. J., Hartsough, L. A., Landry, B. P., Shroff, R., Tabor, J. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Characterizing+bacterial+gene+circuit+dynamics+with+optically+programmed+gene+expression+signals.">Characterizing bacterial gene circuit dynamics with optically programmed gene expression signals.</a> Nature methods. 11 (4), 449-455 (2014).</li></ol>

The authors have nothing to disclose.

We designed this apparatus with flexibility in mind. All the code used is free and open-source. The default image analysis process to segment cells is simple and runs quickly. Custom analysis could be implemented by recording user input while analyzing a representative image with the FIJI graphic user interface, converting the input to a beanshell script, and then setting the plugin to call the script. When it is called, this script will be sent a String array called &#34;images&#34; containing the file paths to the most recent set of background-subtracted images. Images and data are saved as they are collected so that they are not lost if an experiment ends abruptly. A blue LED array was chosen for inducing our optogenetic system but it could be replaced with LEDs of different colors. There are additional input and output pins available on the microcontroller as well as through-holes for an additional MOSFET switch and relay switch on the PCB that make it easy for this system to be adapted for more complex purposes. For example, to make this apparatus operate as a turbidostat, use the additional pins on the microcontroller to power an LED and read values from a light-sensor strapped to the culturing vessel, and then modify the software to measure turbidity and dilute the vessel accordingly.
Care must be taken to ensure that the culture is not contaminated, to protect sensitive microscopy equipment, and to ensure that the fluid flow rates are consistent. Contaminations prior to when the culturing vessel is intentionally inoculated can be detected by waiting a few days before inoculating the vessel and verifying that there is no growth inside. To avoid spilling cell culture on the microscope objective, check that the microfluidic device will not leak by first pumping cell culture through it over an absorbent cloth. If the flow of media into the culturing vessel is inconsistent, it is usually because the tube around the rollers of the peristaltic pump has become too loose. If the flow of air from the aquarium pump is inconsistent, ensure that there are no U-shaped bends in the effluent tube where liquid may pool and inconsistently resist air flow. If tubing becomes clogged after an experiment because media has dried up inside of it, soak the clogged tubes in a hot water bath to dissolve the clog.
There are intrinsic limitations to this protocol to consider when planning an experiment or analyzing results. Depending on the dilution rate and length of tube used, there is a delay of roughly 10 min during which the cell culture is pumped from the culturing vessel to the microscope. Therefore, it is not well suited to studying events occurring over shorter timescales. Also, while an experiment can run continuously for about ten days, limited only by the volume of media, the evolution of the cell culture must be considered as the duration of the experiment increases. The limiting nutrient of the media has profound effects on metabolism and gene expression35,36,37,38,39 and should therefore be determined based on the aspect of physiology under study. When analyzing results, the images-especially the images from outlying data points-should be reviewed for errors in the way that ROIs were identified by the image analysis routine. It is possible for bubbles or artifacts to be mistaken for cells, thereby skewing the measured fluorescence. One simple way to eliminate such erroneous measurements is to discard all ROIs with fluorescence intensities below the auto-fluorescence intensity.
This protocol will be useful for measuring fluorescence intensity and/or cellular morphology of effluent cell culture in response to light in organisms that can grow in continuous culture, settle to a consistent focal plane when not stirred, and be automatically identified by an image analysis algorithm. The default cell identification algorithm used here will be most directly applicable to roughly spherical microbes that resemble budding yeast. One alternative40 to this protocol is to grow microbes in a set of batch cultures, and then sample one batch for each time point and characterize the sample by flow cytometry. However, the advantages of the protocol described here are that samples are taken from the same culture, many samples can be taken, and the process is automated. This protocol also improves upon a similar method in which optogenetic yeast were continuously cultured and imaged under a microscope34 by acquiring multiple images quickly and not biasing ROIs identification by fluorescence. A great advantage of this protocol is that many measurements of individual cells can be regularly acquired over several days without user input. After measuring the response of the microbial culture to light exposure, a next step may be to implement in silico closed-loop control of the response.

Optogenetic systems use light to control a growing list of cellular processes including gene expression,1,2,3,4,5 protein localization,6 protein activity,6,7,8 protein binding,8,9,10 and protein degradation.11 A method for culturing cells in a controlled environment with programmed optical stimulation and for measuring their response over biologically relevant timescales is necessary to exploit the potential of these tools for research in cell biology and biotechnology. Our method takes advantage of chemostasis to maintain a constant cell growth rate in a well-mixed, aerated, and temperature-controlled glass culturing vessel12,13 that is exposed to programmed illumination. We image individual cells in the culture effluent with an inverted microscope to measure the response of the culture to programmed illumination. The culturing, sampling, imaging, and image analysis are fully automated so that the fluorescence intensity and cellular morphology of the effluent cell culture can be measured over multiple days without user input.
This protocol can be implemented in most labs familiar with growing cell culture and microscopy, and the apparatus used is inexpensive and made of readily available components. A transparent culturing vessel is placed above a matrix of light emitting diodes (LEDs) capable of emitting 1 &#181;W/cm2-10 mW/cm2 of light. Microbes are grown in the culturing vessel continuously; one peristaltic pump is used to add media at the dilution rate, another is used to withdraw culture at a lesser rate to the microscope, and the difference escapes through an overflow outlet. A heating pad maintains the temperature. Air is continually pumped into the culturing vessel to maintain a positive pressure as well as to mix and aerate the culture. Except for the air pump, power to these devices is regulated by a microcontroller that also receives input from a thermometer and a connected desktop computer. The effluent cell culture is pumped to a microfluidic device on the stage of an inverted microscope. Non-fluorescent and fluorescent images are automatically acquired. The cells in the images are characterized by an algorithm that locates each cell as a region of interest (ROI) and measures the properties of each ROI.
To demonstrate an application of this protocol, we measured the response to varying light intensities of Saccharomyces cerevisiae cells engineered with a blue-light responsive optogenetic system which controls the transcription of fluorescent protein. S. cerevisiae, commonly known as baker&#39;s yeast, was selected because multiple optogenetic systems for controlling gene expression in this system already exist14,15,16. Furthermore, this model organism is commonly used for studies in systems biology17 and as a chassis for biotechnological applications18,19,20. Our representative results demonstrate that this protocol can be used to control transcription of a culture over multiple days by varying input light intensities and measuring the production of a fluorescent reporter.

<table><tbody><tr><td>Extensive lab manual</td><td>GitHub</td><td>NA</td><td>An extensive, regularly updated lab manual is available in the &amp;ldquo;Optogenetic Chemostat Files&amp;rdquo; GitHub repository (https://github.com/McCleanResearch/Optogenetic-Chemostat-Files). This also includes a description of the microfluidic mold used to generate the representative results.</td></tr><tr><td>Fritzing Design Viewer</td><td>Fritzing</td><td>NA</td><td>The free, open-sourced software to view and edit the .fzz type circuit board designs is available at &quot;http://fritzing.org/download/&quot;</td></tr><tr><td>Arduino Uno R3 (Atmega328 - assembled)</td><td>Adafruit</td><td>50</td><td>Microcontroller. 1 required.</td></tr><tr><td>Arduino Stackable Header Kit</td><td>SparkFun Electronics</td><td>10007</td><td>Female pin headers for connecting PCB to microcontroller. 1 required.</td></tr><tr><td>Adjustable 30W 110V soldering iron - XY-258 110V</td><td>Adafruit</td><td>180</td><td>For making electrical connections to the PCB. 1 required.</td></tr><tr><td>Soldering iron stand</td><td>Adafruit</td><td>150</td><td>For making electrical connections to the PCB. 1 required.</td></tr><tr><td>Mini Solder spool - 60/40 lead rosin-core solder 0.031&quot; diameter - 100g</td><td>Adafruit</td><td>145</td><td>For making electrical connections to the PCB. 1 required.</td></tr><tr><td>0.1 &amp;mu;F capacitor</td><td>SparkFun Electronics</td><td>COM-08375</td><td>Stabilizes voltage in PCB. 1 required.</td></tr><tr><td>10 &amp;mu;F capacitor</td><td>SparkFun Electronics</td><td>COM-00523</td><td>Stabilizes voltage in PCB. 1 required.</td></tr><tr><td>MAX7219CNG LED Matrix/Digit Display Driver - MAX7219</td><td>Maxim</td><td>MAX7219CNG</td><td>LED driver. 1 required.</td></tr><tr><td>8 pin IC Socket</td><td>Mouser Electronics</td><td>575-144308</td><td>16 required. These will be stacked on top of each other to support the culture vessel above the LED matrix.</td></tr><tr><td>24 Pin IC socket</td><td>Mouser Electronics</td><td>535-24-3518-10</td><td>Optional. Use this to reversibly attach the MAXIM 7219CNG driver to the PCB.</td></tr><tr><td>Digital multimeter</td><td>Adafruit</td><td>2034</td><td>For troubleshooting electronics. 1 required.</td></tr><tr><td>Break Away Headers - 40-pin Male (Long Centered, PTH, 0.1&quot;)</td><td>SparkFun Electronics</td><td>PRT-12693</td><td>Male pin headers for connected LED matrix to printed circuit board. Ends can be trimmed with wire cutters. 1 set required.&amp;nbsp;</td></tr><tr><td>Flush diagonal wire cutters</td><td>Adafruit</td><td>152</td><td>For trimming long pin headers and cutting power cables. 1 required.</td></tr><tr><td>Premium Female/Female Jumper Wires - 40 x 12&quot; (300mm)</td><td>Adafruit</td><td>793</td><td>Wire ribbon for connecting breadboard to LED matrix. Can be connected end-to-end with male pin-headers to be longer. 1 required.</td></tr><tr><td>Half-size breadboard</td><td>Adafruit</td><td>64</td><td>The LED matrix will connect to this and the culturing vessel will rest above it.</td></tr><tr><td>Miniature 8x8 Blue LED Matrix</td><td>Adafruit</td><td>956</td><td>Light source. Dominant wavelength is 470nm (blue). 1 required. Alternative miniature LED matrices from the same vendor are available with dominant wavelengths: 624 nm (red), 588 nm (yellow), 525 nm (green), 572 nm (yellow-green), and white.</td></tr><tr><td>Stackable header-3 pin</td><td>SparkFun Electronics</td><td>13875</td><td>8 required.</td></tr><tr><td>Resistor Kit - 1/4W (500 total)</td><td>SparkFun Electronics</td><td>10969</td><td>For electronics. 1 required.</td></tr><tr><td>&amp;nbsp;IRL520N MOSFET</td><td>International Rectifier</td><td>IRL520N</td><td>Voltage regulating switch for controlling DC current. 4 required.</td></tr><tr><td>Hook-Up Wire - Assortment (Solid Core, 22 AWG)</td><td>SparkFun Electronics</td><td>PRT 11367</td><td>Wire for electronics. 1 required.</td></tr><tr><td>5V 2A (2000mA) switching power supply - UL Listed</td><td>Adafruit</td><td>276</td><td>Power supply for the heating pad and Arduino. 2 required.</td></tr><tr><td>12 VDC 1000mA regulated switching power adapter - UL listed</td><td>Adafruit</td><td>798</td><td>For peristaltic pumps. 2 required.</td></tr><tr><td>Electric Heating Pad - 10cm x 5cm</td><td>Adafruit</td><td>1481</td><td>For heating the bioreactor. 1 required.</td></tr><tr><td>Low flow variable flow peristaltic pump</td><td>Fisher Scientific</td><td>13-876-1</td><td>For pumping media. 1 required</td></tr><tr><td>Medium flow variable flow peristaltic pump</td><td>Fisher Scientific</td><td>13-876-2</td><td>For pumping culture. 1 required.</td></tr><tr><td>9 VDC 1000mA regulated switching power adapter - UL listed</td><td>Adafruit</td><td>63</td><td>For microcontroller power supply. Order 1.</td></tr><tr><td>High Temp Waterproof DS18B20 Digital temperature sensor + extras</td><td>Adafruit</td><td>642</td><td>Thermometer for the bioreactor. 1 required.</td></tr><tr><td>Micromanager</td><td>Micromanager</td><td>NA</td><td>The free, open-sourced microscope control software is available at &quot;https://micro-manager.org/wiki/Download_Micro-Manager_Latest_Release&quot;</td></tr><tr><td>FIJI</td><td>ImageJ</td><td>NA</td><td>The free, open-sourced image analysis software is available at &quot;http://fiji.sc/&quot;</td></tr><tr><td>Arduino Integrated Development Environment</td><td>Arduino</td><td>NA</td><td>The free, open-sourced IDE is available at &quot;https://www.arduino.cc/en/Main/Software&quot;</td></tr><tr><td>Custom code</td><td>GitHub</td><td>NA</td><td>The custom microcontroller code and &quot;Bioreactor Controller&quot; plugin are available in the &amp;ldquo;Optogenetic Chemostat Files&amp;rdquo; GitHub repository (https://github.com/McCleanResearch/Optogenetic-Chemostat-Files).</td></tr><tr><td>USB Cable A to B - 6 Foot</td><td>SparkFun Electronics</td><td>CAB-00512</td><td>Used to download data to microcontroller. 1 required.</td></tr><tr><td>bioreactorTimecourse_example.csv</td><td>GitHub</td><td>NA</td><td>The advantage of loading LED matrix values from a CSV file is that a program can be called by the plugin to update those values based on image analysis results, and those values can be reloaded to the microcontroller, enabling feed-back control. It is available from the &amp;ldquo;Optogenetic Chemostat Files&amp;rdquo; GitHub repository (https://github.com/McCleanResearch/Optogenetic-Chemostat-Files).</td></tr><tr><td>Tota-frost gels (diffusion paper)</td><td>B&amp;amp;H</td><td>B&amp;amp;H # LOFSFTL&lt;br/&gt; MFR # T1-72</td><td>For LED matrix. 1 required.</td></tr><tr><td>Kitting Sheet Crosslink 1/4x12x24in</td><td>Grainger, inc</td><td>20JL37</td><td>Black foam for culturing vessel enclosure. 4 required.</td></tr><tr><td>Standard Photodiode Power Sensor, Si, 200 - 1100 nm, 50 mW&amp;nbsp;</td><td>Thorlabs</td><td>S120VC</td><td>For measuring light intensity. 1 required.</td></tr><tr><td>Labelling Tape</td><td>Fisher Scientific</td><td>159015N</td><td>For labelling and securing loose components. 1 required.</td></tr><tr><td>Compact Power and Energy Meter Console, Digital 4&quot; LCD</td><td>Thorlabs</td><td>PM100D</td><td>For measuring light intensity. 1 required.</td></tr><tr><td>100mL GL45 hybridization glass bottle</td><td>Bellco Glass, Inc.</td><td>(7910-40150)</td><td>Bioreactor vessel. 1 required.</td></tr><tr><td>Six port assembly</td><td>Bellco Glass, Inc.</td><td>Custom&amp;nbsp;</td><td>For the bioreactor vessel. Tubing Specs: .125&quot; OD x .055&quot;ID. Port A: 1.0&quot; long above cap slug and to bottom of tube. Ports B,C,E,F: 1.0&quot; long above cap slug, 33 mm long below. Port D: 1.0&quot; long above cap slug, 65 mm&amp;nbsp; long below. 1 required. Includes 45 mm diameter polypropylene open top screw cap and a white silicone gasket to ensure a tight seal between the cap and the vessel.&amp;nbsp;</td></tr><tr><td>Scotch Magic Tape 3105, 3/4 x 300 Inches, Pack of 3</td><td>Amazon</td><td>B0009F3P3U</td><td>Clear scotch tape. This is available from many other vendors. It is used to cover markings on the culturing vessel and to secure the coverglass with the PDMS channel to the aluminum support frame.</td></tr><tr><td>1/16&quot; ID x 3/16&quot; OD x 1/16&quot; Wall Tygon Sanitary Silicone Tubing</td><td>United States Plastic Corp.</td><td>57288</td><td>Tubing. ~25&#039; required.</td></tr><tr><td>Cole-Parmer Twistit white rubber stopper, size 10</td><td>Cole-Parmer</td><td>EW-62992-32</td><td>Media flask stopper and effluent flask stopper. 2 required.</td></tr><tr><td>2L Laboratory Flask</td><td>Pyrex</td><td>4980</td><td>Media flask and effluent flask. 2 required.</td></tr><tr><td>Day pinchcock</td><td>Fisher Scientific</td><td>5867</td><td>For pinching tubes shut. 3 required.</td></tr><tr><td>Replacement tubing assembly 1/16&quot; ID</td><td>Traceable Products</td><td>3372</td><td>The peristaltic pumps come with a set of tubes, but they wear out after weeks of use.</td></tr><tr><td>Replacement tubing assembly 1/50&quot; ID</td><td>Traceable Products</td><td>3371</td><td>The peristaltic pumps come with a set of tubes, but they wear out after weeks of use.</td></tr><tr><td>Male luer with lock ring x 1/16&quot; hose barb, Nylon, 25/pk</td><td>Cole-Parmer</td><td>EW-45505-00</td><td>Connectors. ~10 luers are required.</td></tr><tr><td>Male luer with lock ring x 1/8&quot; hose barb, Nylon, 25/pk</td><td>Cole-Parmer</td><td>EW-45505-04</td><td>Connectors. 5 required, one for each rubber stopper hole to fill with tubing.</td></tr><tr><td>Female luer x 1/16&quot; hose barb adapter, Nylon, 25/pk</td><td>Cole-Parmer</td><td>EW-45502-00</td><td>Connectors. ~10 luers required.</td></tr><tr><td>Female luer x 3/16&quot; hose barb adapter</td><td>Cole-Parmer</td><td>EW-45502-08</td><td>Connectors. ~10 luers required.</td></tr><tr><td>Cole-Parmer Luer Accessory, Female Luer Cap, Nylon, 25/Pk</td><td>Cole-Parmer</td><td>SC-45502-28</td><td></td></tr><tr><td>Cole-Parmer Luer Accessory, Male Luer Lock Plug, Nylon, 25/Pk</td><td>Cole-Parmer</td><td>EW-45505-56</td><td></td></tr><tr><td>Microbore PTFE Tubing, 0.022&quot;ID x 0.042&quot;OD, 100 ft/roll</td><td>Cole-Parmer</td><td>EW-06417-21</td><td>Tubing. 1 roll required.</td></tr><tr><td>Masterflex platinum-cured silicone tubing, L/S 13, 25 ft</td><td>Cole-Parmer</td><td>EW-96410-13</td><td>Tubing. ~25&#039; required.</td></tr><tr><td>3/16&quot; ID x 1/4&quot; OD x 1/32&quot; Wall Tygon Sanitary Silicone Tubing</td><td>United States Plastic Corp.</td><td>57293</td><td>Tubing. ~1&#039; required.</td></tr><tr><td>Vacuum filter</td><td>Fisher Scientific</td><td>974107</td><td>Nalgene vacuum filter for sterile filtering media.</td></tr><tr><td>Aquel Oxy-Boost 200</td><td>Rena Aquatic Supply</td><td>AP200</td><td>Dual diaphram adjustable flow air pump for aerating and mixing media. 1 required.&amp;nbsp;</td></tr><tr><td>0.2 &amp;mu;m pore syringe filter</td><td>Corning International</td><td>431229</td><td>This ensures that air from the aquarium pump does not contaminate the apparatus. 1 required.</td></tr><tr><td>Slygard 184 Silicone Elastomer Kit</td><td>Dow Corning</td><td>Slygard 184</td><td>For microfluidic device. 1 required.</td></tr><tr><td>American Safety Razor GEM Scientific Single-Edge Razor Blades</td><td>Fisher Scientific</td><td>17989000</td><td>For cutting tubes and PDMS. 1 blade required.</td></tr><tr><td>Harris Uni-Core hole puncher 1.2mm ID</td><td>Sigma-Aldrich</td><td>WHAWB100028 ALDRICH</td><td>For punching inlet/outlet in microfluidic device. 1 required.</td></tr><tr><td>Microscope cover glass 22x60-1.5</td><td>Fisher Scientific</td><td>12-544-G</td><td>For microfluidic device. 1 required.</td></tr><tr><td>Rectangular aluminum frame with a square window</td><td>Custom</td><td>Custom</td><td>To support the microfluidic channel. Outer dimensions: 3 inches x 1.25 inches.&lt;br/&gt; Inner dimmensions (cut out portion): 7/8 inches x 7/8 inches&lt;br/&gt; Thickness: ~1/32 inches</td></tr></tbody></table>

design and implementation of an automated illuminating, culturing, and sampling system for microbial optogenetic applications

Optogenetic systems utilize genetically-encoded proteins that change conformation in response to specific wavelengths of light to alter cellular processes. There is a need for culturing and measuring systems that incorporate programmed illumination and stimulation of optogenetic systems. We present a protocol for building and using a continuous culturing apparatus to illuminate microbial cells with programmed doses of light, and automatically acquire and analyze images of cells in the effluent. The operation of this apparatus as a chemostat allows the growth rate and the cellular environment to be tightly controlled. The effluent of the continuous cell culture is regularly sampled and the cells are imaged by multi-channel microscopy. The culturing, sampling, imaging, and image analysis are fully automated so that dynamic responses in the fluorescence intensity and cellular morphology of cells sampled from the culture effluent are measured over multiple days without user input. We demonstrate the utility of this culturing apparatus by dynamically inducing protein production in a strain of Saccharomyces cerevisiae engineered with an optogenetic system that activates transcription.

This apparatus was used to stimulate a culture of S. cerevisiae expressing yellow fluorescent protein (YFP) in response to blue-light via an inducible optogenetic transcription system based on the CRY2/CIB1 protein pair30. Cells were grown chemostatically in phosphate-limited media with an average dilution rate of 0.2 &#177; 0.008. Phosphate limitation is commonly used in S. cerevisiae chemostat experiments to control growth rate and the effects of phosphate limitation are well characterized.31,32,33 Effluent from the continuously-diluted culturing vessel was sampled to a microfluidic device on an inverted microscope. The images were automatically analyzed as shown in Figure 8. Individual cells were identified in background-subtracted phase-contrast images and their YFP concentration was estimated from their fluorescence as measured from the background-subtracted fluorescent images.
The fluorescence of 169,677 cells was analyzed from 33,600 images of effluent acquired from 28 locations in the microfluidic device over the 70 h of the experiment. We used an inverted microscope equipped with a fluorescence illumination system and a CMOS camera. The YFP images were acquired with a 500/20 nm excitation filter, a 535/30 nm emission filter, and a T515lp dichroic. Images were taken with a 40X phase contrast objective, under K&#246;hler illumination. Images were recorded in 16-bit color depth with 87 pixels per micrometer squared. The culture was exposed to varying intensities of blue light for 6 h intervals, followed by complete darkness for 6 h intervals. The culture had been exposed to light prior to the first measurement, which is why its fluorescence intensity is decreasing during the first dark period.
Figure 9 shows the fluorescence due to YFP production upon activation of the optogenetic system in response to illuminating the culturing vessel. It demonstrates the utility of single cell measurements of fluorescence over a population average-single-cell measurements reveal the population distribution of fluorescence intensity. Note the outlier at 42 h 26 min. After reviewing the corresponding images, it was apparent that there were clumps of cells in the majority of the images used to generate the composite image of the background, resulting in artifacts that resembled cells in the background-subtracted image. Also, a bubble from the culturing vessel was pumped to the microfluidic channel and parts of its edges were mistaken as cells by the image analysis algorithm. Since neither the bubble nor the artifacts from subtracting the background corresponded to actual cells, their measured fluorescence intensity is lower than the auto-fluorescence of the cells. This figure demonstrates the quality of data that can be automatically acquired over 3 d. <a href="https://cloudflare-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/54894/54894fig9large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 8" src="/files/ftp_upload/54894/54894fig8.jpg" /> 
Figure 8: Visual depiction of the image analysis algorithm. These images have been cropped and expanded for ease of viewing. (A) Six images are acquired to generate the background-subtracted phase contrast image of the cell culture. After the main image is acquired, five additional images are acquired with the effluent-sampling pump briefly turned on between each acquisition to ensure that cells are displaced. A composite image of the background is generated from the five component images. The value of each pixel in the background image is the median value of that same pixel across the 5 component images. (B) The background-subtracted image is then converted to a binary. The binary is then dilated and the holes within continuous sections of the binary are filled. The yellow outlines correspond to selected regions of interest (ROI), based on size and circularity criteria. (C) Those ROI are mapped onto the fluorescent image, where the fluorescence of each cell is measured as the value of the brightest pixel within the ROI. <a href="https://cloudflare-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/54894/54894fig8large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 9" src="/files/ftp_upload/54894/54894fig9.jpg" /> 
Figure 9: Population distribution of fluorescence intensities over time. In these subfigures the logarithm of measured fluorescence is displayed, following standard practice in flow cytometry. The line in A and B indicates the intensity of light absorbed or diffracted by the culture, which is measured as the difference in intensity between light transmitted through sterile media and light transmitted through cell culture in the culturing vessel. It is plotted against the second ordinate axis. (A) A box and whisker plot (5th percentile, 25th percentile, median, 75th percentile, 95th percentile) of the logarithm of the measured fluorescence of the population over time. (B) A 2-dimensional histogram of the same data, where color corresponds to the normalized frequency of cells with a measured fluorescence in the range of the corresponding bin. The colors were scaled to the range of data without the outlier at 42 h 26 min included. The normalized frequency of the outlier in the lowest fluorescence bin is 0.7. (C) One dimensional histograms of the logarithm of the measured fluorescence of the population before the first recorded exposure to light and after the greatest exposure to light. It demonstrates that the light-induced expression of YFP in this strain is bimodal. <a href="https://cloudflare-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/54894/54894fig9large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Watch this Scientific Journal Video about Design and Implementation of an Automated Illuminating, Culturing, and Sampling System for Microbial Optogenetic Applications at JoVE.com

Design and Implementation of an Automated Illuminating, Culturing, and Sampling System for Microbial Optogenetic Applications

We designed a continuous culturing apparatus for use with optogenetic systems to illuminate cultures of microbes and regularly image cells in the effluent with an inverted microscope. The culturing, sampling, imaging, and image analysis are fully automated so that dynamic responses to illumination can be measured over several days.

Optogenetic systems utilize genetically-encoded proteins that change conformation in response to specific wavelengths of light to alter cellular ...

design-implementation-an-automated-illuminating-culturing-sampling

Universidad San Sebastian

Research

JoVE Journal

Bioengineering

9.6K Views.  University of Wisconsin-Madison. We designed a continuous culturing apparatus for use with optogenetic systems to illuminate cultures of microbes and regularly image cells in the effluent with an inverted microscope. The culturing, sampling, imaging, and image analysis are fully automated so that dynamic responses to illumination can be measured over several days.

Video: Design and Implementation of an Automated Illuminating, Culturing, and Sampling System for Microbial Optogenetic Applications

An Optogenetic Method to Control and Analyze Gene Expression Patterns in Cell-to-cell Interactions

Cells should respond properly to temporally changing environments, which are influenced by various factors from surrounding cells. The Notch signaling pathway is one of such essential molecular machinery for cell-to-cell communications, which plays key roles in normal development of embryos. This pathway involves a cell-to-cell transfer of oscillatory information with ultradian rhythms, but despite the progress in molecular biology techniques, it has been challenging to elucidate the impact of multicellular interactions on oscillatory gene dynamics. Here, we present a protocol that permits optogenetic control and live monitoring of gene expression patterns in a precise temporal manner. This method successfully revealed that intracellular and intercellular periodic inputs of Notch signaling entrain intrinsic oscillations by frequency tuning and phase shifting at the single-cell resolution. This approach is applicable to the analysis of the dynamic features of various signaling pathways, providing a unique platform to test a functional significance of dynamic gene expression programs in multicellular systems.

Here, we present a protocol to analyze cell-to-cell transfer of oscillatory information by optogenetic control and live monitoring of gene expression. This approach provides a unique platform to test a functional significance of dynamic gene expression programs in multicellular systems.

Cells should respond properly to temporally changing environments, which are influenced by various factors from surrounding cells. The Notch signaling ...

Genetics

In vivo Optogenetic Stimulation of the Rodent Central Nervous System

The ability to probe defined neural circuits in awake, freely-moving animals with cell-type specificity, spatial precision, and high temporal resolution has been a long sought tool for neuroscientists in the systems-level search for the neural circuitry governing complex behavioral states. Optogenetics is a cutting-edge tool that is revolutionizing the field of neuroscience and represents one of the first systematic approaches to enable causal testing regarding the relation between neural signaling events and behavior. By combining optical and genetic approaches, neural signaling can be bi-directionally controlled through expression of light-sensitive ion channels (opsins) in mammalian cells. The current protocol describes delivery of specific wavelengths of light to opsin-expressing cells in deep brain structures of awake, freely-moving rodents for neural circuit modulation. Theoretical principles of light transmission as an experimental consideration are discussed in the context of performing in vivo optogenetic stimulation. The protocol details the design and construction of both simple and complex laser configurations and describes tethering strategies to permit simultaneous stimulation of multiple animals for high-throughput behavioral testing.

In vivo Optogenetic Stimulation of the Rodent Central Nervous System

Optogenetics has become a powerful tool for use in behavioral neuroscience experiments. This protocol offers a step-by-step guide to the design and set-up of laser systems, and provides a full protocol for carrying out multiple and simultaneous in vivo optogenetic stimulations compatible with most rodent behavioral testing paradigms.

The ability to probe defined neural circuits in awake, freely-moving animals with cell-type specificity, spatial precision, and high temporal resolution ...

Neuroscience

Investigating Development with Optogenetic Signaling Manipulation in Zebrafish

Optogenetic Signaling Activation in Zebrafish Embryos

Signaling pathways orchestrate fundamental biological processes, including development, regeneration, homeostasis, and disease. Methods to experimentally manipulate signaling are required to understand how signaling is interpreted in these wide-ranging contexts. Molecular optogenetic&#160;tools can provide reversible, tunable manipulations of signaling pathway activity with a high degree of spatiotemporal control and have been applied in vitro, ex vivo, and in vivo. These tools couple light-responsive protein domains, such as the blue light homodimerizing light-oxygen-voltage sensing (LOV) domain, with signaling effectors to confer light-dependent experimental control over signaling. This protocol provides practical guidelines for using the LOV-based bone morphogenetic protein (BMP) and Nodal signaling activators bOpto-BMP and bOpto-Nodal in the optically accessible early zebrafish embryo. It describes two control experiments: A quick phenotype assay to determine appropriate experimental conditions, and an immunofluorescence assay to directly assess signaling. Together, these control experiments can help establish a pipeline for using optogenetic tools in early zebrafish embryos. These strategies provide a powerful platform to investigate the roles of signaling in development, health, and physiology.

Author Spotlight: Manipulating Signaling in Zebrafish Embryos to Decode Cell Fate Decisions 

Optogenetic manipulation of signaling pathways can be a powerful strategy to investigate how signaling is decoded in development, regeneration, homeostasis, and disease. This protocol provides practical guidelines for using light-oxygen-voltage sensing domain-based Nodal and bone morphogenic protein (BMP) signaling activators in the early zebrafish embryo.

Signaling pathways orchestrate fundamental biological processes, including development, regeneration, homeostasis, and disease. Methods to experimentally ...

Developmental Biology

Building a Simple and Versatile Illumination System for Optogenetic Experiments

Controlling biological processes using light has increased the accuracy and speed with which researchers can manipulate many biological processes. Optical control allows for an unprecedented ability to dissect function and holds the potential for enabling novel genetic therapies. However, optogenetic experiments require adequate light sources with spatial, temporal, or intensity control, often a bottleneck for researchers. Here we detail how to build a low-cost and versatile LED illumination system that is easily customizable for different available optogenetic tools. This system is configurable for manual or computer control with adjustable LED intensity. We provide an illustrated step-by-step guide for building the circuit, making it computer-controlled, and constructing the LEDs. To facilitate the assembly of this device, we also discuss some basic soldering techniques and explain the circuitry used to control the LEDs. Using our open-source user interface, users can automate precise timing and pulsing of light on a personal computer (PC) or an inexpensive tablet. This automation makes the system useful for experiments that use LEDs to control genes, signaling pathways, and other cellular activities that span large time scales. For this protocol, no prior expertise in electronics is required to build all the parts needed or to use the illumination system to perform optogenetic experiments.

This protocol describes how to perform optogenetic experiments for controlling gene expression with red and far-red light using PhyB and PIF3. Included are step-by-step instructions for building a simple and flexible illumination system, which enables the control of gene expression or other optogenetics with a computer.

Controlling biological processes using light has increased the accuracy and speed with which researchers can manipulate many biological processes. Optical ...

Reliably Engineering and Controlling Stable Optogenetic Gene Circuits in Mammalian Cells

Reliable gene expression control in mammalian cells requires tools with high fold change, low noise, and determined input-to-output transfer functions, regardless of the method used. Toward this goal, optogenetic gene expression systems have gained much attention over the past decade for spatiotemporal control of protein levels in mammalian cells. However, most existing circuits controlling light-induced gene expression vary in architecture, are expressed from plasmids, and utilize variable optogenetic equipment, creating a need to explore characterization and standardization of optogenetic components in stable cell lines. Here, the study provides an experimental pipeline of reliable gene circuit construction, integration, and characterization for controlling light-inducible gene expression in mammalian cells, using a negative feedback optogenetic circuit as a case example. The protocols also illustrate how standardizing optogenetic equipment and light regimes can reliably reveal gene circuit features such as gene expression noise and protein expression magnitude. Lastly, this paper may be of use for laboratories unfamiliar with optogenetics who wish to adopt such technology. The pipeline described here should apply for other optogenetic circuits in mammalian cells, allowing for more reliable, detailed characterization and control of gene expression at the transcriptional, proteomic, and ultimately phenotypic level in mammalian cells.

Reliably controlling light-responsive mammalian cells requires the standardization of optogenetic methods. Toward this goal, this study outlines a pipeline of gene circuit construction, cell engineering, optogenetic equipment operation, and verification assays to standardize the study of light-induced gene expression using a negative-feedback optogenetic gene circuit as a case study.

Reliable gene expression control in mammalian cells requires tools with high fold change, low noise, and determined input-to-output transfer functions, ...

Light-Controlled Fermentations for Microbial Chemical and Protein Production

Microbial cell factories offer a sustainable alternative for producing chemicals and recombinant proteins from renewable feedstocks. However, overburdening a microorganism with genetic modifications can reduce host fitness and productivity. This problem can be overcome by using dynamic control: inducible expression of enzymes and pathways, typically using chemical- or nutrient-based additives, to balance cellular growth and production. Optogenetics offers a non-invasive, highly tunable, and reversible method of dynamically regulating gene expression. Here, we describe how to set up light-controlled fermentations of engineered Escherichia coli and Saccharomyces cerevisiae for the production of chemicals or recombinant proteins. We discuss how to apply light at selected times and dosages to decouple microbial growth and production for improved fermentation control and productivity, as well as the key optimization considerations for best results. Additionally, we describe how to implement light controls for lab-scale bioreactor experiments. These protocols facilitate the adoption of optogenetic controls in engineered microorganisms for improved fermentation performance.

Optogenetic control of microbial metabolism offers flexible dynamic control over fermentation processes. The protocol here shows how to set up blue light-regulated fermentations for chemical and protein production at different volumetric scales.

Microbial cell factories offer a sustainable alternative for producing chemicals and recombinant proteins from renewable feedstocks. However, ...

Engineering and Characterization of an Optogenetic Model of the Human Neuromuscular Junction

Many neuromuscular diseases, such as myasthenia gravis (MG), are associated with dysfunction of the neuromuscular junction (NMJ), which is difficult to characterize in animal models due to physiological differences between animals and humans. Tissue engineering offers opportunities to provide in vitro models of functional human NMJs that can be used to diagnose and investigate NMJ pathologies and test potential therapeutics. By incorporating optogenetic proteins into induced pluripotent stem cells (iPSCs), we generated neurons that can be stimulated with specific wavelengths of light. If the NMJ is healthy and functional, a neurochemical signal from the motoneuron results in muscle contraction. Through the integration of optogenetics and microfabrication with tissue engineering, we established an unbiased and automated methodology for characterizing NMJ function using video analysis. A standardized protocol was developed for NMJ formation, optical stimulation with simultaneous video recording, and video analysis of tissue contractility. Stimulation of optogenetic motoneurons by light to induce skeletal muscle contractions recapitulates human NMJ physiology and allows for repeated functional measurements of NMJ over time and in response to various inputs. We demonstrate this platform&#39;s ability to show functional improvements in neuromuscular connectivity over time and characterize the damaging effects of patient MG antibodies or neurotoxins on NMJ function.

We describe a reproducible, automated, and unbiased imaging system for characterizing neuromuscular junction function using human engineered skeletal muscle tissue and optogenetic motoneurons. This system allows for the functional quantification of neuromuscular connectivity over time and detects diminished neuromuscular function caused by neurotoxins and myasthenia gravis patient serum.

Many neuromuscular diseases, such as myasthenia gravis (MG), are associated with dysfunction of the neuromuscular junction (NMJ), which is difficult to ...

Yeast Optogenetic Response Analysis Using the Lustro Automation Technique

High-Throughput Optogenetics Experiments in Yeast Using the Automated Platform Lustro

Optogenetics offers precise control over cellular behavior by utilizing genetically encoded light-sensitive proteins. However, optimizing these systems to achieve the desired functionality often requires multiple design-build-test cycles, which can be time-consuming and labor-intensive. To address this challenge, we have developed Lustro, a platform that combines light stimulation with laboratory automation, enabling efficient high-throughput screening and characterization of optogenetic systems.
Lustro utilizes an automation workstation equipped with an illumination device, a shaking device, and a plate reader. By employing a robotic arm, Lustro automates the movement of a microwell plate between these devices, allowing for the stimulation of optogenetic strains and the measurement of&#160;their response. This protocol provides a step-by-step guide on using Lustro to characterize optogenetic systems for gene expression control in the budding yeast Saccharomyces cerevisiae. The protocol covers the setup of Lustro&#39;s components, including the integration of the illumination device with the automation workstation. It also provides detailed instructions for programming the illumination device, plate reader, and robot, ensuring smooth operation and data acquisition throughout the experimental process.

Author Spotlight: Advancing Optogenetics Research Using Lustro 

This protocol outlines the steps for utilizing the automated platform Lustro to perform high-throughput characterization of optogenetic systems in yeast.

Optogenetics offers precise control over cellular behavior by utilizing genetically encoded light-sensitive proteins. However, optimizing these systems to ...

Optrode Array for Simultaneous Optogenetic Modulation and Electrical Neural Recording

During the last decade, optogenetics has become an essential tool for the investigation of neural signaling due to its unique capability of selective neural modulation or monitoring. As specific types of neuronal cells can be genetically modified to express opsin proteins, optogenetics enables optical stimulation or inhibition of the selected neurons. There have been several technological advances in the optical system for optogenetics. Recently, it was proposed to combine the optical waveguide for light delivery with electrophysiological recording to simultaneously monitor the neural responses to optogenetic stimulation or inhibition. In this study, an implantable optrode array (2x2 optical fibers) was developed with embedded multichannel electrodes. 
A light-emitting diode (LED) was employed as a light source, and a microfabricated microlens array was integrated to provide sufficient light power at the tip of the optical fibers. The optrode array system comprises the disposable part and the reusable part. The disposable part has optical fibers and electrodes, while the reusable part has the LED and electronic circuitry for light control and neural signal processing. The novel design of the implantable optrode array system is introduced in the accompanying video in addition to the procedure of the optrode implantation surgery, optogenetic light stimulation, and the electrophysiological neural recording. The results of in vivo experiments successfully showed time-locked neural spikes evoked by the light stimuli from hippocampal excitatory neurons of mice.

Here, we present the fabrication method of an optrode system with optical fibers for light delivery and an electrode array for neural recording. In vivo experiments with transgenic mice expressing channelrhodopsin-2 show the feasibility of the system for simultaneous optogenetic stimulation and electrophysiological recording.

During the last decade, optogenetics has become an essential tool for the investigation of neural signaling due to its unique capability of selective ...

A Light-Stimulation Grid Approach to Study Cellular Optogenetic Protein

Mapping the Cellular Distribution of an Optogenetic Protein Using a Light-Stimulation Grid

Our goal was to accurately track the cellular distribution of an optogenetic protein and evaluate its functionality within a specific cytoplasmic location. To achieve this, we co-transfected cells with nuclear-targeted cAMP sensors and our laboratory-developed optogenetic protein, bacterial photoactivatable adenylyl cyclase-nanoluciferase (bPAC-nLuc). bPAC-nLuc, when stimulated with 445 nm light or luciferase substrates, generates adenosine 3&#39;,5&#39;-cyclic monophosphate (cAMP). We employed a solid-state laser illuminator connected to a point scanning system that allowed us to create a grid/matrix pattern of small illuminated spots (~1 &#181;m2) throughout the cytoplasm of HC-1 cells. By doing so, we were able to effectively track the distribution of nuclear-targeted bPAC-nLuc and generate a comprehensive cAMP response map. This map accurately represented the cellular distribution of bPAC-nLuc, and its response to light stimulation varied according to the amount of protein in the illuminated spot. This innovative approach contributes to the expanding toolkit of techniques available for investigating cellular optogenetic proteins. The ability to map its distribution and response with high precision has far-reaching potential and could advance various fields of research.

This protocol involves transfecting cAMP sensors and bPAC-nLuc, an optogenetic protein, to accurately track its cellular distribution and response to light stimulation. The innovative approach of creating a cAMP response map using a point scanning system holds the potential for advancing research with optogenetic proteins in different fields.

Design and Implementation of an Automated Illuminating, Culturing, and Sampling System for Microbial Optogenetic Applications

Podsumowanie

Przeglądaj więcej filmów

Rozdziały w tym wideo

An Optogenetic Method to Control and Analyze Gene Expression Patterns in Cell-to-cell Interactions

In vivo Optogenetic Stimulation of the Rodent Central Nervous System

Optogenetic Signaling Activation in Zebrafish Embryos

Building a Simple and Versatile Illumination System for Optogenetic Experiments

Reliably Engineering and Controlling Stable Optogenetic Gene Circuits in Mammalian Cells

Light-Controlled Fermentations for Microbial Chemical and Protein Production

Engineering and Characterization of an Optogenetic Model of the Human Neuromuscular Junction

High-Throughput Optogenetics Experiments in Yeast Using the Automated Platform Lustro

Optrode Array for Simultaneous Optogenetic Modulation and Electrical Neural Recording

Mapping the Cellular Distribution of an Optogenetic Protein Using a Light-Stimulation Grid