We would like to thank former Weiss Lab members that led or contributed to developing the poly-transfection method and its application to cell classifiers: Jeremy Gam, Bre DiAndreth, and Jin Huh; other Weiss lab members who have contributed to further method development/optimization: Wenlong Xu, Lei Wang, and Christian Cuba-Samaniego; Prof. Josh Leonard and group members, including Patrick Donahue and Hailey Edelstein, for testing poly-transfection and providing feedback; and Prof. Nika Shakiba for inviting this manuscript and providing feedback. We would also like to thank the National Institutes of Health [R01CA173712, R01CA207029, P50GM098792]; National Science Foundation [1745645]; Cancer Center Support (core) Grant [P30CCA14051, in part] from the NCI, and National Institutes of Health [P50GM098792] for funding this work.

NOTE: Table 1 and Table 2 serve as significant references for this protocol. Table 1 shows reagent scaling for reactions, and Table 2 shows DNA ratio arithmetic for an example poly-transfection described in the protocol (upper half) and for a possible follow-up experiment (lower half).
1. Preparing cells for transfection
<ol>
	<li>Ensure that the culture of human embryonic kidney (HEK293) cells is 60%-80% confluent before initiating the protocol. To do this, seed 1 x 106 cells in a 100 mm x 15 mm tissue culture Petri dish 2 days prior, and incubate at 37 &#176;C with 5% CO2. 
	NOTE:&#160;Although our protocol focuses on HEK293 cells, other cell types may be substituted.</li>
	<li>Prepare the media and cells for transfections as described below.
	<ol>
		<li>Pre-warm at least 20 mL of a solution of Dulbecco&#39;s modified eagle medium (DMEM) with 10% fetal bovine serum (FBS) and 1% non-essential amino acids (NEAA; see Table of Materials) to 37 &#176;C. Pre-warm at least 2.4 mL of Trypsin and 2.4 mL of phosphate-buffered saline (PBS) to 37 &#176;C as well. Pre-warm reduced serum medium to ~16 &#176;C. 
		NOTE: All tissue culture work should be performed with care in a biosafety cabinet.</li>
	</ol>
	</li>
	<li>Resuspend the cells in the DMEM solution as described below.
	<ol>
		<li>Aspirate and dispose of the current media. Dispense 2 mL of PBS onto the HEK293 cell culture to wash the cells. Aspirate and dispose of the PBS.</li>
		<li>Dispense 2 mL of Trypsin onto the HEK293 cell culture. Place the Petri dish in an incubator at 37 &#176;C for 3 min or until the cells no longer adhere to the dish. Return the dish to the biosafety cabinet and dilute the cell solution by dispensing 8 mL of DMEM solution into the plate.</li>
		<li>Mix the solution by gently pipetting up and down several times. Aspirate all the media and place it in a 15 mL conical tube.</li>
	</ol>
	</li>
	<li>Centrifuge the cells at 300 x g for 3 min to pellet them. Aspirate the media (taking care not to aspirate the cells) and discard it. Resuspend the cells in 5 mL of DMEM solution, mixing by gently pipetting up and down.</li>
	<li>Estimate&#160;the current cell concentration using an automated cell counter (listed in the Table of Materials). Seed six wells (in this example) in a 24-well plate with 1 x 105 cells (for a seeding density of 50,000 cells/cm2).</li>
	<li>Add the DMEM solution up to 500 &#181;L (add DMEM solution to the wells first), and then label one well per treatment as the following: no color control, mKO2 control, TagBFP control, NeonGreen control, all color control, and poly-transfection 1.&#160;TagBFP, mKO2, and NeonGreen control wells are single color controls for all fluorescent proteins included in the poly-transfection.</li>
</ol>
2. Performing transfection
<ol>
	<li>Prepare tubes for each DNA aggregate. Set aside 1.5 mL microcentrifuge tubes and label the tubes as: no color control, mKO2 control, TagBFP control, NeonGreen control, all color control, poly-transfection mix 1, and poly-transfection mix 2.
	<ol>
		<li>Add 36 &#181;L of reduced serum medium to the no color control, mKO2 control, TagBFP control, NeonGreen control, and all color control tubes. Add 18 &#181;L of reduced serum medium to each of the poly-transfection mix 1 and poly-transfection mix 2 tubes. 
		NOTE: The plasmid concentrations are assumed to be 150 ng/&#181;L.</li>
		<li>Add 600 ng of filler plasmid to the no color control tube. Add 300 ng of mKO2 and 300 ng of filler plasmid to the mKO2 color control tube. Add 300 ng of TagBFP and 300 ng of filler plasmid to the TagBFP color control tube.</li>
		<li>Add 300 ng of constitutive NeonGreen plasmid and 300 ng of filler plasmid to the NeonGreen color control tube. Add 100 ng each of mKO2, TagBFP, and constitutive NeonGreen, as well as 300 ng of filler plasmid, to the all color control tube.</li>
		<li>Add 150 ng of mKO2 to the poly-transfection mix 1 tube. Add 75 ng of reporter NeonGreen plasmid and 75 ng of filler plasmid to the poly-transfection mix 1 tube.</li>
		<li>Add 150 ng of TagBFP to the poly-transfection mix 2 tube. Add 75 ng of L7ae plasmid and 75 ng of filler plasmid to the poly-transfection mix 2 tube.</li>
	</ol>
	</li>
	<li>Create the transfection master mix in a 1.5 mL microcentrifuge tube by combining 216 &#181;L of reduced serum medium with 9.48 &#181;L of transfection reagent (see Table 1 for reagent ratios and reaction scaling). Mix well by pipetting up and down, and set aside.</li>
	<li>Add 1.58 &#181;L of enhancer reagent to each of the no color control, single color control, and all color control tubes. Add 79 &#181;L of enhancer reagent to each of the poly-transfection mix tubes. Mix each tube individually by pipetting vigorously.</li>
	<li>Add the transfection master mix to each tube containing DNA.
	<ol>
		<li>Add 37.58 &#181;L of transfection master mix to each of the no color control, single color control, and all color control tubes. Mix each tube individually by pipetting vigorously.</li>
		<li>Add 18.79 &#181;L of transfection master mix to each of the poly-transfection mix tubes. Mix each tube individually by pipetting vigorously.</li>
	</ol>
	</li>
	<li>Dispense the transfection mixes into the wells.
	<ol>
		<li>Pipette 65.97 &#181;L of each transfection mix for the no color, single color, and all color controls into the corresponding wells.</li>
		<li>Pipette 32.98 &#181;L of the poly-transfection mix 1 into the poly-transfection well and swirl the plate quickly but gently in a tight figure-eight pattern along a flat surface to distribute the complexes effectively. Then, pipette 32.98 &#181;L of the poly-transfection mix 2 into the same poly-transfection well and swirl the plate in the same fashion.</li>
	</ol>
	</li>
	<li>Place the plate in an incubator at 37 &#176;C, with 5% CO2 and without shaking, for a period of 48 h. 
	NOTE: To increase cell viability, the cell media can be replaced every 6 h following transfection (though this is not always necessary, and with HEK293 cells and its derivatives, one must be careful not to detach the cells from the plate when changing the media).</li>
</ol>
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Reagent</td>
			<td colspan="3">Amount</td>
			<td colspan="3">Scaling</td>
		</tr>
		<tr>
			<td>Reduced serum medium for DNA mixture</td>
			<td colspan="3">36 &#956;L per control tube, 18 &#956;L per poly-transfection tube&#160;</td>
			<td colspan="3">0.05 &#956;L Reduced serum medium/ng DNA per tube, with 10-20% extra volume to account for pipetting</td>
		</tr>
		<tr>
			<td>DNA</td>
			<td colspan="3">300-600 ng per tube</td>
			<td colspan="3"></td>
		</tr>
		<tr>
			<td>P3000</td>
			<td colspan="3">1.58 &#956;L per control tube, 0.79 &#956;L per poly-transfection tube</td>
			<td colspan="3">0.0022 &#956;L P3000/ng DNA per tube, with 10-20% extra</td>
		</tr>
		<tr>
			<td>Reduced serum medium for Lipo master mix</td>
			<td colspan="3">36 &#956;L per control tube, 18 &#956;L per poly-transfection tube</td>
			<td colspan="3">0.05 &#956;L reduced serum medium/ng total DNA, with 10-20% extra volume to account for pipetting</td>
		</tr>
		<tr>
			<td>Transfection and enhancer reagent</td>
			<td colspan="3">1.58 &#956;L per control tube, 0.79 &#956;L per poly-transfection tube</td>
			<td colspan="3">0.0022 &#956;L Lipofectamine 3000/ng DNA, with 10-20% extra</td>
		</tr>
	</tbody>
</table>
Table 1:&#160;Reagent scaling for transfections. The table indicates the correct ratio of reagent to include for the DNA quantity included in a single well. This can be used to scale reactions effectively and form master mixes. Quantities of reagent have been scaled to include a 20% excess.
3. Preparing cells for flow cytometry
<ol>
	<li>Pre-warm at least 4.2 mL of the DMEM solution to 37 &#176;C. Pre-warm at least 4.2 mL of Trypsin and 4.2 mL of PBS to 37 &#176;C. Keep fluorescence-activated cell sorting (FACS) buffer solution at 4 &#176;C until ready to use.</li>
	<li>Resuspend the cells in the FACS buffer solution (PBS supplemented with 1% BSA, 5 mM ethylenediaminetetraacetic acid [EDTA], and 0.1% sodium azide [NaN3], to reduce clumping; see Table of Materials) as described below.
	<ol>
		<li>Aspirate and dispose of the current media in each well. Dispense 5 mL of PBS into each well to wash the cells. Aspirate and dispose of the PBS.</li>
		<li>Dispense 5 mL of Trypsin into each well. Place the plate in an incubator at 37 &#176;C for 3 min, or until the cells no longer adhere to the dish. Return the plate to the biosafety cabinet and dilute the cell solutions by dispensing 5 mL of DMEM solution into each well.</li>
		<li>For each well, mix the solution by gently pipetting up and down several times. For each well, aspirate all the media and place it in a 15 mL conical tube.</li>
	</ol>
	</li>
	<li>Centrifuge the cells at 300 x g for 3 min to pellet them. Aspirate the media, taking care not to aspirate the cells and discard it. In each tube, resuspend the cells in 5 mL of FACS buffer solution, mixing by gently pipetting up and down.</li>
	<li>Pass each cell suspension solution through a strainer (to remove clumps) into separate flow cytometry conical tubes. Keep these tubes on ice for no more than 1 h, and perform flow cytometry as soon as possible.</li>
</ol>
4. Performing flow cytometry
NOTE: Operating a flow cytometer requires proper training and knowledge of the necessary tasks. As software and equipment may vary and users should be trained generally, this section refers to specific operations that are useful to perform.
<ol>
	<li>First, examine the cells transfected with the filler plasmid control (no color control) to select for cell characteristics and avoid anomalies (including aggregates, debris, etc.). While there are many combinations of parameters to distinguish cells, use the following three general options as a good way to visualize distinguishing features.
	<ol>
		<li>Look at the side scatter area (log or linear scale per preference/cell type) versus the forward scatter area (linear scale).</li>
		<li>Look at the side scatter height (log scale) versus the side scatter width (linear scale).</li>
		<li>Look at the forward scatter width (linear scale) versus the forward scatter height (linear scale).</li>
	</ol>
	</li>
	<li>Next, look at the single color controls. Use the all color control to tune the instrument voltages, such that the signals from each fluorescent protein are normalized to equivalent arbitrary units (a.u.) of fluorescence. Next, run the single color controls for each fluorescent protein, which are used to set the compensation matrix, allowing for bleed-through correction. 
	NOTE: Ideally, the full dynamic range of the fluorescence values should be visible. Further normalization of fluorescent protein signals can be done via conversion to standardized units (e.g., molecules of equivalent fluorescein [MEFLs; see Beal et al.15]). To enable MEFL conversion during analysis, run rainbow calibration beads. Such calibration is also useful for reducing instrument-to-instrument and day-to-day signal variation16.</li>
	<li>Run the poly-transfection sample tube. 
	NOTE: Where possible, it is recommended to run 1,000 x 10^ (^ = mixes) cells, as higher-dimensional poly-transfections need to be subdivided into more bins during analysis, and each bin needs enough cells (ideally &#62;10) to make statistically significant comparisons.</li>
</ol>
5. Performing post-experiment analysis
<ol>
	<li>Initially, use data from the controls (and, if applicable, the beads) to ensure accurate results. Use one of the available software tools to perform live cell gating (using gates outlined above), compensation, and autofluorescence correction. 
	NOTE: We typically use either custom MATLAB code (e.g., https://github.com/jonesr18/MATLAB_Flow_Analysis or Cytoflow17), which has both a graphical user interface and a python library suitable for the pre-processing phase and for poly-transfection analysis.</li>
</ol>
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Method</td>
			<td>Complex</td>
			<td>ng Fluorescent Marker</td>
			<td>ng L7ae (fraction)</td>
			<td>ng Reporter (fraction)</td>
			<td>ng Filler DNA (fraction)</td>
			<td>Total (ng)</td>
		</tr>
		<tr>
			<td>Poly-transfection 1</td>
			<td></td>
			<td></td>
			<td></td>
			<td></td>
			<td></td>
			<td>600</td>
		</tr>
		<tr>
			<td>&#8594;</td>
			<td>1</td>
			<td>150</td>
			<td>75 (&#189;)</td>
			<td></td>
			<td>75 (&#189;)</td>
			<td>300</td>
		</tr>
		<tr>
			<td>&#8594;</td>
			<td>2</td>
			<td>150</td>
			<td></td>
			<td>75 (&#189;)</td>
			<td>75 (&#189;)</td>
			<td>300</td>
		</tr>
		<tr>
			<td>Poly-transfection 2</td>
			<td></td>
			<td></td>
			<td></td>
			<td></td>
			<td></td>
			<td>600</td>
		</tr>
		<tr>
			<td>&#8594;</td>
			<td>1</td>
			<td>150</td>
			<td>25 (1/6)</td>
			<td></td>
			<td>125 (5/6)</td>
			<td>300</td>
		</tr>
		<tr>
			<td>&#8594;</td>
			<td>2</td>
			<td>150</td>
			<td></td>
			<td>125 (5/6)</td>
			<td>25(1/6)</td>
			<td>300</td>
		</tr>
	</tbody>
</table>
Table 2:&#160;DNA amounts for poly-transfection demonstrated in the protocol, and an example follow-up experiment with tuned plasmid ratios. The upper half of the table shows the composition of plasmids used in a simple poly-transfection experiment. The lower half shows the composition of an updated experiment that adjusts the plasmid ratios to better subsample a hypothetical concentration space, where the gene expression modulator is at a more optimal 1:5 ratio relative to its reporter, yielding more transfected cells to sample around this ratio.

<ol>
	<li>Prochazka, L., Benenson, Y., Zandstra, P. W. <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+circuits+and+cellular+decision-making+in+human+pluripotent+stem+cells.">Synthetic gene circuits and cellular decision-making in human pluripotent stem cells.</a> Current Opinion in Systems Biology. 5, 93-103 (2017).</li><li>Sayeg, M. K., 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=Rationally+designed+microRNA-based+genetic+classifiers+target+specific+neurons+in+the+brain.">Rationally designed microRNA-based genetic classifiers target specific neurons in the brain.</a> ACS Synthetic Biology. 4 (7), 788-795 (2015).</li><li>Zhen, X., Wroblewska, L., Prochazka, L., Weiss, R., Benenson, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Multi-Input+RNAi-based+logic+circuit+for+identification+of+specific+cancer+cells.">Multi-Input RNAi-based logic circuit for identification of specific cancer cells.</a> Science. 333 (6047), 1307-1311 (2011).</li><li>Nissim, 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=Synthetic+RNA-based+immunomodulatory+gene+circuits+for+cancer+immunotherapy.">Synthetic RNA-based immunomodulatory gene circuits for cancer immunotherapy.</a> Cell. 171 (5), 1138-1150 (2017).</li><li>Nissim, L., Bar-Ziv, R. 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+tunable+dual-promoter+integrator+for+targeting+of+cancer+cells.">A tunable dual-promoter integrator for targeting of cancer cells.</a> Molecular Systems Biology. 6, 444 (2010).</li><li>Mohammadi, P., Castel, S. E., Brown, A. A., Lappalainen, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantifying+the+regulatory+effect+size+of+cis-acting+genetic+variation+using+allelic+fold+change.">Quantifying the regulatory effect size of cis-acting genetic variation using allelic fold change.</a> Genome Research. 27 (11), 1872-1884 (2017).</li><li>Prochazka, 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=Discrete-to-analog+signal+pluripotent+stem+cells+conversion+in+human.">Discrete-to-analog signal pluripotent stem cells conversion in human.</a> BioRxiv. , (2021).</li><li>Del Vecchio, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Modularity,+context-dependence,+and+insulation+in+engineered+biological+circuits.">Modularity, context-dependence, and insulation in engineered biological circuits.</a> Trends in Biotechnology. 33 (2), 111-119 (2015).</li><li>Shakiba, N., Jones, R. D., Weiss, R., Del Vecchio, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Context-aware+synthetic+biology+by+controller+design:+Engineering+the+mammalian+cell.">Context-aware synthetic biology by controller design: Engineering the mammalian cell.</a> Cell Systems. 12 (6), 561-592 (2021).</li><li>Gam, J. J., DiAndreth, B., Jones, R. D., Huh, J., Weiss, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+'poly-transfection'+method+for+rapid,+one-pot+characterization+and+optimization+of+genetic+systems.">A 'poly-transfection' method for rapid, one-pot characterization and optimization of genetic systems.</a> Nucleic Acids Research. 47 (18), 106 (2019).</li><li>Jones, R. 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=Robust+and+tunable+signal+processing+in+mammalian+cells+via+engineered+covalent+modification+cycles.">Robust and tunable signal processing in mammalian cells via engineered covalent modification cycles.</a> Nature Communications. 13 (1), 1720 (2022).</li><li>Jones, R. 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=An+endoribonuclease-based+feedforward+controller+for+decoupling+resource-limited+genetic+modules+in+mammalian+cells.">An endoribonuclease-based feedforward controller for decoupling resource-limited genetic modules in mammalian cells.</a> Nature Communications. 11 (1), 5690 (2020).</li><li>DiAndreth, B., Wauford, N., Hu, E., Palacios, S., Weiss, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=PERSIST+platform+provides+programmable+RNA+regulation+using+CRISPR+endoRNases.">PERSIST platform provides programmable RNA regulation using CRISPR endoRNases.</a> Nature Communications. 13 (1), 2582 (2022).</li><li>Frei, 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=Characterization+and+mitigation+of+gene+expression+burden+in+mammalian+cells.">Characterization and mitigation of gene expression burden in mammalian cells.</a> Nature Communications. 11 (1), 4641 (2020).</li><li>Beal, J., Weiss, R., Yaman, F., Adler, A., Davidsohn, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+method+for+fast,+high-precision+characterization+of+synthetic+biology+devices.+Computer+Science+and+Artificial+Intelligence+Laboratory+Technical+Report.">A method for fast, high-precision characterization of synthetic biology devices. Computer Science and Artificial Intelligence Laboratory Technical Report.</a> Massachusetts institute of technology. , (2012).</li><li>Beal, 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=Meeting+measurement+precision+requirements+for+effective+engineering+of+genetic+regulatory+networks.">Meeting measurement precision requirements for effective engineering of genetic regulatory networks.</a> ACS Synthetic Biology. 11 (3), 1196-1207 (2022).</li><li>Teague, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Cytoflow:+A+Python+toolbox+for+flow+cytometry.">Cytoflow: A Python toolbox for flow cytometry.</a> bioRxiv. , (2022).</li><li>Ferreira, J. P., Overton, K. W., Wang, 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=Tuning+gene+expression+with+synthetic+upstream+open+reading+frames).">Tuning gene expression with synthetic upstream open reading frames).</a> Proceedings of the National Academy of Sciences. 110 (28), 11284-11289 (2013).</li><li>Michaels, Y. S., 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=Precise+tuning+of+gene+expression+levels+in+mammalian+cells.">Precise tuning of gene expression levels in mammalian cells.</a> Nature Communications. 10 (1), 818 (2019).</li><li>Saito, 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=Synthetic+translational+regulation+by+an+L7Ae-kink-turn+RNP+switch.">Synthetic translational regulation by an L7Ae-kink-turn RNP switch.</a> Nature Chemical Biology. 6 (1), 71-78 (2010).</li><li>Wroblewska, 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=Mammalian+synthetic+circuits+with+RNA+binding+proteins+for+RNA-only+delivery.">Mammalian synthetic circuits with RNA binding proteins for RNA-only delivery.</a> Nature Biotechnology. 33 (8), 839-841 (2015).</li><li>Wagner, T. E., 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=Small-molecule-based+regulation+of+RNA-delivered+circuits+in+mammalian+cells.">Small-molecule-based regulation of RNA-delivered circuits in mammalian cells.</a> Nature Chemical Biology. 14 (11), 1043-1050 (2018).</li><li>Sekuklu, S. D., Donoghue, M. T. A., Spillane, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=miR-21+as+a+key+regulator+of+oncogenic+processes.">miR-21 as a key regulator of oncogenic processes.</a> Biochemical Society Transactions. 37, 918-925 (2009).</li><li>Stanton, B. 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=Genomic+mining+of+prokaryotic+repressors+for+orthogonal+logic+gates.">Genomic mining of prokaryotic repressors for orthogonal logic gates.</a> Nature Chemical Biology. 10 (2), 99-105 (2014).</li><li>Stanton, B. 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=Systematic+transfer+of+prokaryotic+sensors+and+circuits+to+mammalian+cells.">Systematic transfer of prokaryotic sensors and circuits to mammalian cells.</a> ACS Synthetic Biology. 3 (12), 880-891 (2014).</li></ol>

R.W. is a co-founder of Strand Therapeutics and Replay Bio; R.W. and R.J. filed a provisional patent related to a cell type classifier.

Rapid prototyping methods such as computer-aided design (CAD), breadboarding, and 3D printing have revolutionized mechanical, electrical, and civil engineering disciplines. The ability to quickly search through many possible solutions to a given challenge greatly accelerates progress in a field. We believe that poly-transfection is an analogous technology for biological engineering, enabling rapid prototyping of genetic circuits. Additionally, other rapid prototyping technologies require hands-on sequential iteration of ...

The field of mammalian synthetic biology has rapidly progressed, from developing simple sense-and-respond parts in cultured cell lines to the optimization of complex networks of genes to address real-world challenges in diagnostics and therapeutics1. These sophisticated circuits are capable of sensing biological inputs from microRNA profiles to cytokines to small molecule drugs, and implementing logic processing circuits including transistors, band-pass filters, toggle switches, and oscillators. They have also shown promising results in animal models of diseases like cancer, arthritis, diabetes, and many more1,2,3,4,5. However, as the complexity of a circuit grows, optimizing the levels of each of its components becomes increasingly challenging.
One particularly useful type of genetic circuit is a cell classifier, which can be programmed to sense and respond to cellular states. Selective production of protein or RNA outputs in specific cellular states is a powerful tool to guide and program differentiation of cells and organoids, identify and destroy diseased cells and/or undesirable cell types, and regulate the function of therapeutic cells1,2,3,4,5. However, creating circuits in mammalian cells that can accurately classify cell states from multiple cellular RNA and/or protein species has been highly challenging.
One of the most time-consuming steps of developing a cell classification circuit is to optimize the relative expression levels of individual component genes, such as sensors and processing factors, within the circuit. To speed up circuit optimization and allow for the construction of more sophisticated circuits, recent work has used mathematical modeling of cell classifier circuits and their components to predict optimal compositions and topologies6,7. While this has shown powerful results so far, mathematical analysis is limited by the need to systematically characterize the input-output behavior of component genes in the circuit, which is time-consuming. Further, a myriad of context-dependent problems can emerge in complex genetic circuits, causing the behavior of a full circuit to defy predictions based on individual part characterizations8,9.
To more rapidly develop and test complex mammalian circuits such as cell state classifiers, our lab developed a technique called poly-transfection10, an evolution of plasmid co-transfection protocols. In co-transfection, multiple plasmid DNA species are complexed together with a positively charged lipid or polymer reagent, then delivered to cells in a correlated manner (Figure 1A). In poly-transfection, plasmids are separately complexed with the reagent, such that the DNA from each transfection complex is delivered to cells in a de-correlated manner (Figure 1B). Using this method, cells within the transfected population are exposed to numerous combinations of ratios of two or more DNA payloads carrying different circuit components.
To measure the ratios of circuit components delivered to each cell, each transfection complex within a poly-transfection contains a constitutively expressed fluorescent reporter that serves as a proxy for cellular uptake of the complex. Filler DNA that does not contain any elements active within a mammalian cell is used to tune the relative amount of the fluorescent reporter and circuit components delivered to a cell in a single transfection complex and is discussed in more detail in the discussion. An example of filler DNA used in the Weiss lab is a plasmid containing a terminator sequence, but no promotor, coding sequence, etc. Cells with different ratios of circuit components can then be compared to find optimal ratios for gene circuit function. This in turn yields useful predictions for choosing promoters and other circuit elements to achieve optimal gene expression levels when combining circuit components into a single vector for genetic integration (e.g., a lentivirus, transposon, or landing pad). Thus, instead of choosing ratios between circuit components based on intuition or via a time-consuming trial and error process, poly-transfection evaluates a wide range of stoichiometries between genetic parts in a single-pot reaction.
In our lab, poly-transfection has enabled the optimization of many genetic circuits, including cell classifiers, feedback and feedforward controllers, and bistable motifs. This simple but powerful method significantly speeds up design cycles for complex genetic circuits in mammalian cells. Poly-transfection has since been used to characterize several genetic circuits to reveal their multi-dimensional input-output transfer functions at high resolution10, optimize an alternate circuit topology for cell state classification11, and accelerate various published12,13 and ongoing projects.
Here we describe and depict the workflow for using poly-transfection to rapidly optimize a genetic circuit (Figure 2). The protocol shows how to generate high-quality poly-transfection data and avoid several common errors in the poly-transfection protocol and data analysis (Figure 3). It then demonstrates how to use poly-transfection to characterize simple circuit components and, in the process, benchmark poly-transfection results against co-transfection (Figure 4). Finally, the results of poly-transfection show optimization of the cancer classifier circuit (Figure 5).

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>15mL Corning Falcon conical tubes</td>
			<td>ThermoFisher Scientific</td>
			<td>14-959-53A</td>
			<td></td>
		</tr>
		<tr>
			<td>24-well petri dish</td>
			<td>Any company of choice</td>
			<td></td>
			<td>(Non-pyrogenic, Sterile, RNase, DNase, DNA and Pyrogen Free)</td>
		</tr>
		<tr>
			<td>Bovine serum albumin</td>
			<td>NEB</td>
			<td>B9000S</td>
			<td></td>
		</tr>
		<tr>
			<td>Centrifuge</td>
			<td>Any company of choice</td>
			<td></td>
			<td>Capable of exposing 15mL Falcon tubes to 300 rcf</td>
		</tr>
		<tr>
			<td>Countess 3 Automated Cell Counter</td>
			<td>ThermoFisher Scientific</td>
			<td>AMQAX2000</td>
			<td></td>
		</tr>
		<tr>
			<td>Countess Cell Counting Chamber Slides</td>
			<td>ThermoFisher Scientific</td>
			<td>C10228</td>
			<td></td>
		</tr>
		<tr>
			<td>Cytoflow</td>
			<td>Non-commercial software package</td>
			<td></td>
			<td>https://cytoflow.readthedocs.io/en/stable/#&#160;</td>
		</tr>
		<tr>
			<td>DMEM</td>
			<td>VWR</td>
			<td>10-013-CV</td>
			<td>Use the correct media for your cell type</td>
		</tr>
		<tr>
			<td>EDTA&#160;</td>
			<td>ThermoFisher Scientific</td>
			<td>03690-100ML</td>
			<td></td>
		</tr>
		<tr>
			<td>Fetal bovine serum</td>
			<td>Sigma Aldrich</td>
			<td>F4135</td>
			<td></td>
		</tr>
		<tr>
			<td>HEK cells</td>
			<td>ATCC</td>
			<td>CRL-1573</td>
			<td>Use the relevant cell type for your experiments. HEK cells tend to transfect very efficiently.</td>
		</tr>
		<tr>
			<td>HeLa cells</td>
			<td>ATCC</td>
			<td>CRL-12401</td>
			<td>Use the relevant cell type for your experiments.</td>
		</tr>
		<tr>
			<td>Lipofectamine 3000 and P3000 enhancer</td>
			<td>ThermoFisher Scientific</td>
			<td>L3000001</td>
			<td>Use the correct reagent for your cell type; transfection and enhancer reagent</td>
		</tr>
		<tr>
			<td>LSRFortessa flow cytometer</td>
			<td>BD Biosciences</td>
			<td>N/A</td>
			<td></td>
		</tr>
		<tr>
			<td>MEM Non-Essential Amino Acids Solution</td>
			<td>Gibco</td>
			<td>11140050</td>
			<td></td>
		</tr>
		<tr>
			<td>Microcentrifuge Tubes, 1.5 mL</td>
			<td>Any company of choice</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Opti-MEM</td>
			<td>ThermoFisher Scientific</td>
			<td>31985070</td>
			<td>reduced serum medium</td>
		</tr>
		<tr>
			<td>Phosphate buffered saline</td>
			<td>ThermoFisher Scientific</td>
			<td>70011044</td>
			<td></td>
		</tr>
		<tr>
			<td>Rainbow calibration beads</td>
			<td>Spherotech</td>
			<td>URCP-100-2H</td>
			<td></td>
		</tr>
		<tr>
			<td>Sodium azide</td>
			<td>Sigma Aldrich</td>
			<td>S2002</td>
			<td></td>
		</tr>
		<tr>
			<td>Trypsin</td>
			<td>VWR</td>
			<td>25-053-CI</td>
			<td></td>
		</tr>
	</tbody>
</table>

rapid development of cell state identification circuits with poly-transfection

Mammalian genetic circuits have demonstrated the potential to sense and treat a wide range of disease states, but optimization of the levels of circuit components remains challenging and labor-intensive. To accelerate this process, our lab developed poly-transfection, a high-throughput extension of traditional mammalian transfection. In poly-transfection, each cell in the transfected population essentially performs a different experiment, testing the behavior of the circuit at different DNA copy numbers and allowing users to analyze a large number of stoichiometries in a single-pot reaction. So far, poly-transfections that optimize ratios of three-component circuits in a single well of cells have been demonstrated; in principle, the same method can be used for the development of even larger circuits. Poly-transfection results can be easily applied to find optimal ratios of DNA to co-transfect for transient circuits or to choose expression levels for circuit components for the generation of stable cell lines.
Here, we demonstrate the use of poly-transfection to optimize a three-component circuit. The protocol begins with experimental design principles and explains how poly-transfection builds upon&#160;traditional co-transfection methods. Next, poly-transfection of cells is carried out and followed by flow cytometry a few days later. Finally, the data is analyzed by examining slices of the single-cell flow cytometry data that correspond to subsets of cells with certain component ratios. In the lab, poly-transfection has been used to optimize cell classifiers, feedback and feedforward controllers, bistable motifs, and many more. This simple but powerful method speeds up design cycles for complex genetic circuits in mammalian cells.

In Figure 1, we compare co-transfection to poly-transfection. In a co-transfection, all plasmids are delivered in the same transfection mix, resulting in high correlation between the amount of each plasmid any single cell receives (Figure 1A). While the number of total plasmids delivered to each cell varies significantly, the fluorescence of the two reporter proteins in the individual cells across the population is well-correlated, indicating that the two plasmi...

Watch this Scientific Journal Video about Rapid Development of Cell State Identification Circuits with Poly-Transfection at JoVE.com

Rapid Development of Cell State Identification Circuits with Poly-Transfection

Complex genetic circuits are time-consuming to design, test, and optimize. To facilitate this process, mammalian cells are transfected in a way that allows the testing of multiple stoichiometries of circuit components in a single well. This protocol outlines the steps for experimental planning, transfection, and data analysis.

Mammalian genetic circuits have demonstrated the potential to sense and treat a wide range of disease states, but optimization of the levels of circuit ...

rapid-development-cell-state-identification-circuits-with-poly

Universidad de Cartagena UDEC

Research

JoVE Journal

Bioengineering

1.3K Views.  Massachusetts Institute of Technology. Complex genetic circuits are time-consuming to design, test, and optimize. To facilitate this process, mammalian cells are transfected in a way that allows the testing of multiple stoichiometries of circuit components in a single well. This protocol outlines the steps for experimental planning, transfection, and data analysis. 

Video: Rapid Development of Cell State Identification Circuits with Poly-Transfection

Monitoring Protein Adsorption with Solid-state Nanopores

Solid-state nanopores have been used to perform measurements at the single-molecule level to examine the local structure and flexibility of nucleic acids 1-6, the unfolding of proteins 7, and binding affinity of different ligands 8. By coupling these nanopores to the resistive-pulse technique 9-12, such measurements can be done under a wide variety of conditions and without the need for labeling 3. In the resistive-pulse technique, an ionic salt solution is introduced on both sides of the nanopore. Therefore, ions are driven from one side of the chamber to the other by an applied transmembrane potential, resulting in a steady current. The partitioning of an analyte into the nanopore causes a well-defined deflection in this current, which can be analyzed to extract single-molecule information. Using this technique, the adsorption of single proteins to the nanopore walls can be monitored under a wide range of conditions 13. Protein adsorption is growing in importance, because as microfluidic devices shrink in size, the interaction of these systems with single proteins becomes a concern. This protocol describes a rapid assay for protein binding to nitride films, which can readily be extended to other thin films amenable to nanopore drilling, or to functionalized nitride surfaces. A variety of proteins may be explored under a wide range of solutions and denaturing conditions. Additionally, this protocol may be used to explore more basic problems using nanopore spectroscopy.

A method of using solid-state nanopores to monitor the non-specific adsorption of proteins onto an inorganic surface is described. The method employs the resistive-pulse principle, allowing for the adsorption to be probed in real-time and at the single-molecule level. Because the process of single protein adsorption is far from equilibrium, we propose the employment of parallel arrays of synthetic nanopores, enabling for the quantitative determination of the apparent first-order reaction rate constant of protein adsorption as well as and the Langmuir adsorption constant.

Solid-state nanopores have been used to perform measurements at the single-molecule level to examine the local structure and flexibility of nucleic acids ...

Ratiometric Biosensors that Measure Mitochondrial Redox State and ATP in Living Yeast Cells

Mitochondria have roles in many cellular processes, from energy metabolism and calcium homeostasis to control of cellular lifespan and programmed cell death. These processes affect and are affected by the redox status of and ATP production by mitochondria. Here, we describe the use of two ratiometric, genetically encoded biosensors that can detect mitochondrial redox state and ATP levels at subcellular resolution in living yeast cells. Mitochondrial redox state is measured using redox-sensitive Green Fluorescent Protein (roGFP) that is targeted to the mitochondrial matrix. Mito-roGFP contains cysteines at positions 147 and 204 of GFP, which undergo reversible and environment-dependent oxidation and reduction, which in turn alter the excitation spectrum of the protein. MitGO-ATeam is a F&ouml;rster resonance energy transfer (FRET) probe in which the &epsilon; subunit of the FoF1-ATP synthase is sandwiched between FRET donor and acceptor fluorescent proteins. Binding of ATP to the &epsilon; subunit results in conformation changes in the protein that bring the FRET donor and acceptor in close proximity and allow for fluorescence resonance energy transfer from the donor to acceptor.

We describe the use of two ratiometric, genetically encoded biosensors, which are based on GFP, to monitor mitochondrial redox state and ATP levels at subcellular resolution in living yeast cells.

Mitochondria have roles in many cellular processes, from energy metabolism and calcium homeostasis to control of cellular lifespan and programmed cell ...

Sensing of Barrier Tissue Disruption with an Organic Electrochemical Transistor

The gastrointestinal tract is an example of barrier tissue that provides a physical barrier against entry of pathogens and toxins, while allowing the passage of necessary ions and molecules. A breach in this barrier can be caused by a reduction in the extracellular calcium concentration. This reduction in calcium concentration causes a conformational change in proteins involved in the sealing of the barrier, leading to an increase of the paracellular flux. To mimic this effect the calcium chelator ethylene glycol-bis(beta-aminoethyl ether)-N,N,N&#39;,N&#39;-tetra acetic acid (EGTA) was used on a monolayer of cells known to be representative of the gastrointestinal tract. Different methods to detect the disruption of the barrier tissue already exist, such as immunofluorescence and&#160;permeability assays. However, these methods are time-consuming and costly and not suited to dynamic or high-throughput measurements. Electronic methods for measuring barrier tissue integrity also exist for measurement of the transepithelial resistance (TER), however these are often costly and complex. The development of rapid, cheap, and sensitive methods is urgently needed as the integrity of barrier tissue is a key parameter in drug discovery and pathogen/toxin diagnostics. The organic electrochemical transistor (OECT) integrated with barrier tissue forming cells has been shown as a new device capable of dynamically monitoring barrier tissue integrity. The device is able to measure minute variations in ionic flux with unprecedented temporal resolution and sensitivity, in real time, as an indicator of barrier tissue integrity. This new method is based on a simple device that can be compatible with high throughput screening applications and fabricated at low cost.

The Organic Electrochemical Transistor is integrated with live cells and used to monitor ion flux across the gastrointestinal epithelial barrier. In this study, an increase in ion flux, related to disruption of tight junctions, induced by the presence of the calcium chelator EGTA (ethylene glycol-bis(beta-aminoethyl ether)-N,N,N',N'-tetra acetic acid), is measured.

The gastrointestinal tract is an example of barrier tissue that provides a physical barrier against entry of pathogens and toxins, while allowing the ...

In Vitro Model of Physiological and Pathological Blood Flow with Application to Investigations of Vascular Cell Remodeling

Vascular disease is a common cause of death within the United States. Herein, we present a method to examine the contribution of flow dynamics towards vascular disease pathologies. Unhealthy arteries often present with wall stiffening, scarring, or partial stenosis which may all affect fluid flow rates, and the magnitude of pulsatile flow, or pulsatility index. Replication of various flow conditions is the result of tuning a flow pressure damping chamber downstream of a blood pump. Introduction of air within a closed flow system allows for a compressible medium to absorb pulsatile pressure from the pump, and therefore vary the pulsatility index. The method described herein is simply reproduced, with highly controllable input, and easily measurable results. Some limitations are recreation of the complex physiological pulse waveform, which is only approximated by the system. Endothelial cells, smooth muscle cells, and fibroblasts are affected by the blood flow through the artery. The dynamic component of blood flow is determined by the cardiac output and arterial wall compliance. Vascular cell mechano-transduction of flow dynamics may trigger cytokine release and cross-talk between cell types within the artery. Co-culture of vascular cells is a more accurate picture reflecting cell-cell interaction on the blood vessel wall and vascular response to mechanical signaling. Contribution of flow dynamics, including the cell response to the dynamic and mean (or steady) components of flow, is therefore an important metric in determining disease pathology and treatment efficacy. Through introducing an in vitro co-culture model and pressure damping downstream of blood pump which produces simulated cardiac output, various arterial disease pathologies may be investigated.

In Vitro Model of Physiological and Pathological Blood Flow with Application to Investigations of Vascular Cell Remodeling

This protocol replicates physiological or pathological blood flow in vitro to aid in determining cell response in disease pathologies. By introducing a pressure damping chamber downstream of a blood pump, blood flow across the vasculature can be recapitulated and imposed on a monolayer of vascular endothelium or a mimetic co-culture.

Vascular disease is a common cause of death within the United States. Herein, we present a method to examine the contribution of flow dynamics towards ...

Qualitative Characterization of the Aqueous Fraction from Hydrothermal Liquefaction of Algae Using 2D Gas Chromatography with Time-of-flight Mass Spectrometry

Two-dimensional gas chromatography coupled with time-of-flight mass spectrometry is a powerful tool for identifying and quantifying chemical components in complex mixtures. It is often used to analyze gasoline, jet fuel, diesel, bio-diesel and the organic fraction of bio-crude/bio-oil. In most of those analyses, the first dimension of separation is non-polar, followed by a polar separation. The aqueous fractions of bio-crude and other aqueous samples from biofuels production have been examined with similar column combinations. However, sample preparation techniques such as derivatization, solvent extraction, and solid-phase extraction were necessary prior to analysis. In this study, aqueous fractions obtained from the hydrothermal liquefaction of algae were characterized by two-dimensional gas chromatography coupled with time-of-flight mass spectrometry without prior sample preparation techniques using a polar separation in the first dimension followed by a non-polar separation in the second. Two-dimensional plots from this analysis were compared with those obtained from the more traditional column configuration. Results from qualitative characterization of the aqueous fractions of algal bio-crude are discussed in detail. The advantages of using a polar separation followed by a non-polar separation for characterization of organics in aqueous samples by two-dimensional gas chromatography coupled with time-of-flight mass spectrometry are highlighted.

A two-dimensional gas chromatography-time-of-flight mass spectrometry method is described for characterization of the aqueous fraction of bio-crude produced from hydrothermal liquefaction of algae. This protocol can also be employed to analyze the aqueous fraction of liquid products from fast pyrolysis, catalytic fast pyrolysis, catalytic deoxygenation and hydro-treating.

Two-dimensional gas chromatography coupled with time-of-flight mass spectrometry is a powerful tool for identifying and quantifying chemical components in ...

Rapid Subtractive Patterning of Live Cell Layers with a Microfluidic Probe

The microfluidic probe (MFP) facilitates performing local chemistry on biological substrates by confining nanoliter volumes of liquids. Using one particular implementation of the MFP, the hierarchical hydrodynamic flow confinement (hHFC), multiple liquids are simultaneously brought in contact with a substrate. Local chemical action and liquid shaping using the hHFC, is exploited to create cell patterns by locally lysing and removing cells. By utilizing the scanning ability of the MFP, user-defined patterns of cell monolayers are created. This protocol enables rapid, real-time and spatially controlled cell patterning, which can allow selective cell-cell and cell-matrix interaction studies.

We present a protocol to perform subtractive patterning of live cell monolayers on a surface. This is achieved by local and selective lysis of adherent cells using a microfluidic probe (MFP). The cell lysate retrieved from local regions can be used for downstream analysis, enabling molecular profiling studies.

The microfluidic probe (MFP) facilitates performing local chemistry on biological substrates by confining nanoliter volumes of liquids. Using one ...

A Rapid and Chemical-free Hemoglobin Assay with Photothermal Angular Light Scattering

Photo-thermal angular light scattering (PT-AS) is a novel optical method for measuring the hemoglobin concentration ([Hb]) of blood samples. On the basis of the intrinsic photothermal response of hemoglobin molecules, the sensor enables high-sensitivity, chemical-free measurement of [Hb]. [Hb] detection capability with a limit of 0.12 g/dl over the range of 0.35 - 17.9 g/dl has been demonstrated previously. The method can be readily implemented using inexpensive consumer electronic devices such as a laser pointer and a webcam. The use of a micro-capillary tube as a blood container also enables the hemoglobin assay with a nanoliter-scale blood volume and a low operating cost. Here, detailed instructions for the PT-AS optical setup and signal processing procedures are presented. Experimental protocols and representative results for blood samples in anemic conditions ([Hb] = 5.3, 7.5, and 9.9 g/dl) are also provided, and the measurements are compared with those from a hematology analyzer. Its simplicity in implementation and operation should enable its wide adoption in clinical laboratories and resource-limited settings.

A photo-thermal angular light scattering (PT-AS) sensor enables the rapid and chemical-free hemoglobin assay of nanoliter-scale blood samples. Here, details of the PT-AS setup and a measurement protocol for the hemoglobin concentration in blood are provided. Representative results for anemic blood samples are also presented.

Photo-thermal angular light scattering (PT-AS) is a novel optical method for measuring the hemoglobin concentration ([Hb]) of blood samples. On the basis ...

Synthesis of Biocompatible Liquid Crystal Elastomer Foams as Cell Scaffolds for 3D Spatial Cell Cultures

Here, we present a step-by-step preparation of a 3D, biodegradable, foam-like cell scaffold. These scaffolds were prepared by cross-linking star block co-polymers featuring cholesterol units as side-chain pendant groups, resulting in smectic-A (SmA) liquid crystal elastomers (LCEs). Foam-like scaffolds, prepared using metal templates, feature interconnected microchannels, making them suitable as 3D cell culture scaffolds. The combined properties of the regular structure of the metal foam and of the elastomer result in a 3D cell scaffold that promotes not only higher cell proliferation compared to conventional porous templated films, but also better management of mass transport (i.e., nutrients, gases, waste, etc.). The nature of the metal template allows for the easy manipulation of foam shapes (i.e., rolls or films) and for the preparation of scaffolds of different pore sizes for different cell studies while preserving the interconnected porous nature of the template. The etching process does not affect the chemistry of the elastomers, preserving their biocompatible and biodegradable nature. We show that these smectic LCEs, when grown for extensive time periods, enable the study of clinically relevant and complex tissue constructs while promoting the growth and proliferation of cells.

This study presents a methodology to prepare 3D, biodegradable, foam-like cell scaffolds based on biocompatible side-chain liquid crystal elastomers (LCEs). Confocal microscopy experiments show that foam-like LCEs allow for cell attachment, proliferation, and the spontaneous alignment of C2C12s myoblasts.

Here, we present a step-by-step preparation of a 3D, biodegradable, foam-like cell scaffold. These scaffolds were prepared by cross-linking star block ...

Rapid Assembly of Multi-Gene Constructs using Modular Golden Gate Cloning

The Golden Gate cloning method enables the rapid assembly of multiple genes in any user-defined arrangement. It utilizes type IIS restriction enzymes that cut outside of their recognition sites and create a short overhang. This modular cloning (MoClo) system uses a hierarchical workflow in which different DNA parts, such as promoters, coding sequences (CDS), and terminators, are first cloned into an entry vector. Multiple entry vectors then assemble into transcription units. Several transcription units then connect into a multi-gene plasmid. The Golden Gate cloning strategy is of tremendous advantage because it allows scar-less, directional, and modular assembly in a one-pot reaction. The hierarchical workflow typically enables the facile cloning of a large variety of multi-gene constructs with no need for sequencing beyond entry vectors. The use of fluorescent protein dropouts enables easy visual screening. This work provides a detailed, step-by-step protocol for assembling multi-gene plasmids using the yeast modular cloning (MoClo) kit. We show optimal and suboptimal results of multi-gene plasmid assembly and provide a guide for screening for colonies. This cloning strategy is highly applicable for yeast metabolic engineering and other situations in which multi-gene plasmid cloning is required.

The goal of this protocol is to provide a detailed, step-by-step guide for assembling multi-gene constructs using the modular cloning system based on Golden Gate cloning. It also gives recommendations on critical steps to ensure optimal assembly based on our experiences.

The Golden Gate cloning method enables the rapid assembly of multiple genes in any user-defined arrangement. It utilizes type IIS restriction enzymes that ...

3D Printing of In Vitro Hydrogel Microcarriers by Alternating Viscous-Inertial Force Jetting

Microcarriers are beads with a diameter of 60-250 &#181;m and a large specific surface area, which are commonly used as carriers for large-scale cell cultures. Microcarrier culture technology has become one of the main techniques in cytological research and is commonly used in the field of large-scale cell expansion. Microcarriers have also been shown to play an increasingly important role in in vitro tissue engineering construction and clinical drug screening. Current methods for preparing microcarriers include microfluidic chips and inkjet printing, which often rely on complex flow channel design, an incompatible two-phase interface, and a fixed nozzle shape. These methods face the challenges of complex nozzle processing, inconvenient nozzle changes, and excessive extrusion forces when applied to multiple bioink. In this study, a 3D printing technique, called alternating viscous-inertial force jetting, was applied to enable the construction of hydrogel microcarriers with a diameter of 100-300 &#181;m. Cells were subsequently seeded on microcarriers to form tissue engineering modules. Compared to existing methods, this method offers a free nozzle tip diameter, flexible nozzle switching, free control of printing parameters, and mild printing conditions for a wide range of bioactive materials.

3D Printing of In Vitro Hydrogel Microcarriers by Alternating Viscous-Inertial Force Jetting

Presented here is a mild 3D printing technique driven by alternating viscous-inertial forces to enable the construction of hydrogel microcarriers. Homemade nozzles offer flexibility, allowing easy replacement for different materials and diameters. Cell binding microcarriers with a diameter of 50-500 &#181;m can be obtained and collected for further culturing.

Microcarriers are beads with a diameter of 60-250 &#181;m and a large specific surface area, which are commonly used as carriers for large-scale cell ...

Rapid Development of Cell State Identification Circuits with Poly-Transfection

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Monitoring Protein Adsorption with Solid-state Nanopores

Ratiometric Biosensors that Measure Mitochondrial Redox State and ATP in Living Yeast Cells

Sensing of Barrier Tissue Disruption with an Organic Electrochemical Transistor

In Vitro Model of Physiological and Pathological Blood Flow with Application to Investigations of Vascular Cell Remodeling

Qualitative Characterization of the Aqueous Fraction from Hydrothermal Liquefaction of Algae Using 2D Gas Chromatography with Time-of-flight Mass Spectrometry

Rapid Subtractive Patterning of Live Cell Layers with a Microfluidic Probe

A Rapid and Chemical-free Hemoglobin Assay with Photothermal Angular Light Scattering

Synthesis of Biocompatible Liquid Crystal Elastomer Foams as Cell Scaffolds for 3D Spatial Cell Cultures

Rapid Assembly of Multi-Gene Constructs using Modular Golden Gate Cloning

3D Printing of In Vitro Hydrogel Microcarriers by Alternating Viscous-Inertial Force Jetting