Name: gene digital circuits based on crispr-cas systems and anti-crispr proteins
Uploaded: 2022-10-18T15:00:00
Description: Watch this Scientific Journal Video about Gene Digital Circuits Based on CRISPR-Cas Systems and Anti-CRISPR Proteins at JoVE.com

We want to thank all the students of the Synthetic Biology lab-SPST, TJU-for their general help, together with Zhi Li and Xiangyang Zhang for their assistance in FACS experiments.

1. Design and construction of the sgRNA/crRNA expression cassette
NOTE: There are two kinds of sgRNA/crRNA expression cassettes: one-termed SNR5210-is composed of the RNA polymerase III-dependent SNR52 promoter, the sgRNA/crRNA sequence, and the SUP4 terminator; another-abbreviated as RGR11-consists of the RNA polymerase II-dependent ADH1 promoter, the RGR (ribozyme-guide RNA-ribozyme) structure that cont...

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The protocol showed a possible complete workflow for synthetic gene digital circuits, following the &#34;Design-Build-Test-Learn&#34; (DBTL) biological engineering cycle and concerning both dry-lab and wet-lab experiments. Here, we focused on the CRISPR-Cas system, mainly dSpCas9, denAsCas12a, dLbCas12a, and the corresponding anti-CRISPR proteins, by designing and building in S. cerevisiae small transcriptional networks. Some of them mimicked Boolean gates, which are the basic components of digital circuits. All...

In 2011, researchers proposed a computational method and developed a corresponding piece of software for the automatic design of digital synthetic gene circuits1. A user had to specify the number of inputs (three or four) and fill in the circuit truth table; this provided all the necessary information to derive the circuit structure using techniques from electronics. The truth table was translated into two Boolean formulae via the Karnaugh map method2. Each Boolean formula is made of clauses that describe logic operations (sum or multiplication) among (part of) the circuit inputs and their negations (the literals). Clauses, in their turn, are either summed up (OR) or multiplied (AND) to compute the circuit output. Every circuit can be realized according to any of its two corresponding formulae: one written in POS (product of sums) form and the other in SOP (sum of products) representation. The former consists of a multiplication of clauses (i.e., Boolean gates) that contain a logic sum of the literals. The latter, in contrast, is a sum of clauses where the literals are multiplied.
Electric circuits can be realized, on a breadboard, by physically wiring different gates together. The electric current permits the exchange of signals among gates, which leads to the computation of the output.
In biology, the situation is more complex. A Boolean gate can be realized as a transcription unit (TU; i.e., the sequence &#34;promoter-coding region-terminator&#34; inside eukaryotic cells), where transcription or translation (or both) are regulated. Thus, at least two kinds of molecules establish a biological wiring: the transcription factor proteins and the non-coding, antisense RNAs1.
A gene digital circuit is organized into two or three layers of gates, namely: 1) the input layer, which is made of YES (buffer) and NOT gates and converts the input chemicals into wiring molecules; 2) the internal layer, which consists of as many TUs as there are clauses in the corresponding Boolean formula. If the circuit is designed according to the SOP formula, every clause in the internal layer will produce the circuit output (e.g., fluorescence) in a so-called distributed output architecture. If the product of sum (POS) formula is used, then a 3) final layer is required, which will contain a single multiplicative gate collecting the wiring molecules from the internal layer.
Overall, in synthetic biology, many different schemes can be designed for the same circuit. They differ in the number and the kind of both TUs and wiring molecules. In order to choose the easiest solution to be implemented in yeast cells, each circuit design is associated with a complexity score S, defined as
<img alt="Equation 1" src="/files/ftp_upload/64539/64539eq01.jpg" style="margin: auto;" />
where A represents the number of activators, R represents the number of repressors, and a is the amount of antisense RNA molecules. If either activators or repressors are absent from the circuit, their contribution to S is zero. Therefore, it is more difficult to realize a circuit scheme in the lab (high S) when it requires a high number of orthogonal transcription factors. This means that new activators and repressors shall be engineered de novo in order to realize the complete wiring inside the digital circuits. In principle, novel DNA-binding proteins can be assembled by using Zinc Finger proteins3 and TAL effectors4 as templates. However, this option appears too arduous and time-consuming; therefore, one should rely mostly on small RNAs and translation regulation to finalize complex gene circuits.
Originally, this method was developed to fabricate digital circuits in bacteria. Indeed, in eukaryotic cells, instead of antisense RNAs, it is more suitable to talk of microRNAs (miRNAs) or small interfering RNAs (siRNAs)5. However, the RNAi pathway is not present in the yeast S. cerevisiae. Hence, one should opt for fully transcriptional networks. Suppose that a circuit needs five activators and five repressors; its complexity score would be S = 32. Circuit complexity can be reduced by replacing the 10 transcription factors with a single dCas96 (nuclease deficient Cas9) fused to an activation domain (AD). As shown in7, dCas9-AD works as a repressor in yeast when binding a promoter between the TATA box and the TSS (transcription start site) and as an activator when binding well upstream of the TATA box. Thus, one can replace 10 transcription factors with a single dCas9-AD fusion protein and 10 sgRNAs (single guide RNAs) for a total complexity score of S = 11. It is quick and easy to synthesize ten sgRNAs, whereas, as previously commented, the assembly of 10 proteins would demand much longer and more complicated work.
Alternatively, one might use two orthogonal dCas proteins (e.g., dCas9 and dCas12a): one to fuse to an AD, and the other bare or in combination with a repression domain. The complexity score would increase by only one unit (S = 12). Hence, CRISPR-dCas systems are the key to the construction of very intricate gene digital circuits in S. cerevisiae.
This paper deeply characterizes the efficiency of both dCas9- and dCas12a-based repressors and activators in yeast. Results show that they do not demand a high amount of sgRNA to optimize their activity, so episomal plasmids are preferentially avoided. Moreover, dCas9-based activators are far more effective when using a scaffold RNA (scRNA) that recruits copies of the VP64 AD. In contrast, dCas12a works well when fused to the strong VPR AD directly. Furthermore, a synthetic activated promoter demands a variable number of target sites, depending on the configuration of the activator (e.g., three when using dCas12a-VPR, six for dCas9-VP64, and only one with dCas9 and a scRNA). As a repressor, dCas12a appears more incisive when binding the coding region rather than the promoter.
As a drawback, however, CRISPR-dCas9/dCas12a do not interact with chemicals directly. Therefore, they might be of no use in the input layer. For this reason, alternative Boolean gate designs containing anti-CRISPR proteins (Acrs) have been investigated. Acrs act on (d)Cas proteins and inhibit their working8. Hence, they are a means to modulate the activity of CRISPR-(d)Cas systems. This paper thoroughly analyzes the interactions between type II Acrs and (d)Cas9, as well as type V Acrs and (d)Cas12a in S. cerevisiae. Since Acrs are much smaller than Cas proteins, a NOT gate responsive to the estrogen &#946;-estradiol was built by fusing the hormone-binding domain of the human estrogen receptor9-HBD(hER)-to AcrIIA4. Besides, a handful of YES and NOT gates that expressed dCas12a(-AD) constitutively and AcrVAs upon induction with galactose were realized. At present, these gates serve only as a proof of concept. However, they also represent the first step toward a deep rethinking of the algorithm to carry out the computational automatic design of synthetic gene digital circuits in yeast cells.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>0.1 mL PCR 8-strip tubes</td>
			<td>NEST</td>
			<td>403112</td>
			<td></td>
		</tr>
		<tr>
			<td>0.2 mL PCR tubes</td>
			<td>Axygen</td>
			<td>PCR-02-C</td>
			<td></td>
		</tr>
		<tr>
			<td>1.5 mL Microtubes</td>
			<td>Axygen</td>
			<td>MCT-150-C</td>
			<td></td>
		</tr>
		<tr>
			<td>15 mL Centrifuge tubes&#160;</td>
			<td>BIOFIL</td>
			<td>CFT011150</td>
			<td></td>
		</tr>
		<tr>
			<td>2 mL Microtubes</td>
			<td>Axygen</td>
			<td>MCT-200-C&#160;</td>
			<td></td>
		</tr>
		<tr>
			<td>50 mL Centrifuge tubes&#160;</td>
			<td>BIOFIL</td>
			<td>CFT011500</td>
			<td></td>
		</tr>
		<tr>
			<td>Agarose-molecular biology grade</td>
			<td>Invitrogen</td>
			<td>75510-019</td>
			<td></td>
		</tr>
		<tr>
			<td>Ampicillin sodium salt</td>
			<td>Solarbio</td>
			<td>69-52-3</td>
			<td></td>
		</tr>
		<tr>
			<td>Applied biosystems veriti 96-well thermal cycler</td>
			<td>Thermo Fisher Scientific</td>
			<td>4375786</td>
			<td></td>
		</tr>
		<tr>
			<td>AxyPrep DNA gel extraction kit</td>
			<td>Axygen</td>
			<td>AP-GX-250</td>
			<td></td>
		</tr>
		<tr>
			<td>BD FACSuite CS&#38;T research beads</td>
			<td>BD</td>
			<td>650621</td>
			<td>Fluorescent beads</td>
		</tr>
		<tr>
			<td>BD FACSVerse flow cytometer&#160;</td>
			<td>BD</td>
			<td>-</td>
			<td></td>
		</tr>
		<tr>
			<td>Centrifuge</td>
			<td>Eppendorf</td>
			<td>5424</td>
			<td></td>
		</tr>
		<tr>
			<td>Centrifuge Sorvall ST 16R</td>
			<td>Thermo Fisher Scientific</td>
			<td>75004380</td>
			<td></td>
		</tr>
		<tr>
			<td>E. coli competent cells (Strain DH5&#945;)</td>
			<td>Life Technologies</td>
			<td>18263-012</td>
			<td></td>
		</tr>
		<tr>
			<td>ECL select Western Blotting detection reagent</td>
			<td>GE Healthcare</td>
			<td>RPN2235</td>
			<td></td>
		</tr>
		<tr>
			<td>Electrophoresis apparatus</td>
			<td>Beijing JUNYI Electrophoresis Co., Ltd</td>
			<td>JY300C</td>
			<td></td>
		</tr>
		<tr>
			<td>Flat 8-strip caps</td>
			<td>NEST</td>
			<td>406012</td>
			<td></td>
		</tr>
		<tr>
			<td>Gene synthesis company</td>
			<td>Azenta Life Sciences</td>
			<td></td>
			<td>https://web.azenta.com/zh-cn/azenta-life-sciences</td>
		</tr>
		<tr>
			<td>Goat anti-Mouse IgG (H+L) cross-adsorbed secondary antibody Alexa Fluor 568</td>
			<td>Invitrogen</td>
			<td>A-11004</td>
			<td></td>
		</tr>
		<tr>
			<td>HiFiScript cDNA synthesis kit</td>
			<td>CWBIO</td>
			<td>CW2569M</td>
			<td>Kit used in step 6.2.2.1</td>
		</tr>
		<tr>
			<td>Lysate solution (Zymolyase)</td>
			<td>zymoresearch</td>
			<td>E1004-A</td>
			<td></td>
		</tr>
		<tr>
			<td>Nikon Eclipse 80i fluorescence microscope</td>
			<td>Nikon</td>
			<td>-</td>
			<td>Fluorescence microscope</td>
		</tr>
		<tr>
			<td>Pipet tips&#8212;10 &#956;L</td>
			<td>Axygen</td>
			<td>T-300-R-S</td>
			<td></td>
		</tr>
		<tr>
			<td>Pipet tips&#8212;1000 &#956;L</td>
			<td>Axygen</td>
			<td>T-1000-B-R-S</td>
			<td></td>
		</tr>
		<tr>
			<td>Pipet tips&#8212;200 &#956;L</td>
			<td>Axygen</td>
			<td>T-200-Y-R-S</td>
			<td></td>
		</tr>
		<tr>
			<td>pRSII403</td>
			<td>Addgene</td>
			<td>35436</td>
			<td></td>
		</tr>
		<tr>
			<td>pRSII404</td>
			<td>Addgene</td>
			<td>35438</td>
			<td></td>
		</tr>
		<tr>
			<td>pRSII405</td>
			<td>Addgene</td>
			<td>35440</td>
			<td></td>
		</tr>
		<tr>
			<td>pRSII406</td>
			<td>Addgene</td>
			<td>35442</td>
			<td></td>
		</tr>
		<tr>
			<td>pRSII424</td>
			<td>Addgene</td>
			<td>35466</td>
			<td></td>
		</tr>
		<tr>
			<td>pTPGI_dSpCas9_VP64&#160;</td>
			<td>Addgene</td>
			<td>49013</td>
			<td></td>
		</tr>
		<tr>
			<td>Q5 High-fidelity DNApolymerase</td>
			<td>New England Biolabs</td>
			<td>M0491</td>
			<td></td>
		</tr>
		<tr>
			<td>Restriction enzyme-Acc65I</td>
			<td>New England Biolabs</td>
			<td>R0599</td>
			<td></td>
		</tr>
		<tr>
			<td>Restriction enzyme-BamHI</td>
			<td>New England Biolabs</td>
			<td>R0136</td>
			<td></td>
		</tr>
		<tr>
			<td>Restriction enzyme-SacI-HF</td>
			<td>New England Biolabs</td>
			<td>R3156</td>
			<td></td>
		</tr>
		<tr>
			<td>Restriction enzyme-XhoI</td>
			<td>New England Biolabs</td>
			<td>R0146</td>
			<td></td>
		</tr>
		<tr>
			<td>Roche LightCycler 96&#160;</td>
			<td>Roche</td>
			<td>-</td>
			<td>Real-Time PCR Instrument</td>
		</tr>
		<tr>
			<td>S. cerevisiae CEN.PK2-1C</td>
			<td>-</td>
			<td>-</td>
			<td>The parent strain. The genotype is: MATa; his3D1; leu2-3_112; ura3-52; trp1-289; 
			MAL2-8c; SUC2</td>
		</tr>
		<tr>
			<td>Stem-Loop Kit</td>
			<td>SparkJade</td>
			<td>AG0502</td>
			<td>Kit used in step 6.2.1.3</td>
		</tr>
		<tr>
			<td>T100 Thermal Cycler</td>
			<td>BIO-RAD</td>
			<td>186-1096</td>
			<td></td>
		</tr>
		<tr>
			<td>T4 DNA ligase</td>
			<td>New England Biolabs</td>
			<td>M0202</td>
			<td></td>
		</tr>
		<tr>
			<td>T5 Exonuclease</td>
			<td>New England Biolabs</td>
			<td>M0363</td>
			<td></td>
		</tr>
		<tr>
			<td>Taq DNA ligase</td>
			<td>New England Biolabs</td>
			<td>M0208</td>
			<td></td>
		</tr>
		<tr>
			<td>Taq DNA polymerase</td>
			<td>New England Biolabs</td>
			<td>M0495</td>
			<td></td>
		</tr>
		<tr>
			<td>TB Green Premix Ex Taq II (Tli RNaseH Plus)(2x) (SYBR Green I dye)</td>
			<td>Takara</td>
			<td>RR820Q</td>
			<td></td>
		</tr>
		<tr>
			<td>YeaStar RNA kit</td>
			<td>Zymo Research</td>
			<td>R1002</td>
			<td></td>
		</tr>
		<tr>
			<td>&#946;-estradiol</td>
			<td>Sigma-Aldrich</td>
			<td>E8875</td>
			<td></td>
		</tr>
	</tbody>
</table>

gene digital circuits based on crispr-cas systems and anti-crispr proteins

Synthetic gene Boolean gates and digital circuits have a broad range of applications, from medical diagnostics to environmental care. The discovery of the CRISPR-Cas systems and their natural inhibitors-the anti-CRISPR proteins (Acrs)-provides a new tool to design and implement in vivo gene digital circuits. Here, we describe a protocol that follows the idea of the "Design-Build-Test-Learn" biological engineering cycle and makes use of dCas9/dCas12a together with their corresponding Acrs to establish small transcriptional networks, some of which behave like Boolean gates, in Saccharomyces cerevisiae. These results point out the properties of dCas9/dCas12a as transcription factors. In particular, to achieve maximal activation of gene expression, dSpCas9 needs to interact with an engineered scaffold RNA that collects multiple copies of the VP64 activation domain (AD). In contrast, dCas12a shall be fused, at the C terminus, with the strong VP64-p65-Rta (VPR) AD. Furthermore, the activity of both Cas proteins is not enhanced by increasing the amount of sgRNA/crRNA in the cell. This article also explains how to build Boolean gates based on the CRISPR-dCas-Acr interaction. The AcrIIA4 fused hormone-binding domain of the human estrogen receptor is the core of a NOT gate responsive to &#946;-estradiol, whereas AcrVAs synthesized by the inducible GAL1 promoter permits to mimic both YES and NOT gates with galactose as an input. In the latter circuits, AcrVA5, together with dLbCas12a, showed the best logic behavior.

sgRNA/crRNA expression by an RNA polymerase III-type promoter 
First, this work addressed the engineering of the transcriptional activation circuit (circuit 1) shown in Figure 1A. It contained three basic components: 1) the gene encoding for yEGFP (the reporter), which was preceded by a series of different synthetic promoters that provided target sites for dCas9/dCas12a-AD; 2) a yeast codon-optimized version of dCas9 or dCas12a fused to an activation domain (VP64 and VP...

Watch this Scientific Journal Video about Gene Digital Circuits Based on CRISPR-Cas Systems and Anti-CRISPR Proteins at JoVE.com

Gene Digital Circuits Based on CRISPR-Cas Systems and Anti-CRISPR Proteins

CRISPR-Cas systems and anti-CRISPR proteins were integrated into the scheme of Boolean gates in Saccharomyces cerevisiae. The new small logic circuits showed good performance and deepened the understanding of both dCas9/dCas12a-based transcription factors and the properties of anti-CRISPR proteins.

Synthetic gene Boolean gates and digital circuits have a broad range of applications, from medical diagnostics to environmental care. The discovery of the ...

Our protocol explains how to design, build, and analyze yeast gene digital circuits that make use of type two and type five CRISPR dCas systems and the corresponding anti-CRISPR proteins. It's assembly stay because it gathers zero standard procedures to assemble and test synthetic transcriptional networks in services. To begin, prepare a reaction mixture containing 20 to 40 nanograms of DNA template, one microliter of forward primer, one microliter of reverse primer, five microliters of DNTP mix, 0.5 microliters of DNA polymerase, 10 microliters of 5x DNA polymerase reaction buffer, and double distilled water up to a total volume of 50 microliters.Amplify the DNA sequences using the touchdown PCR program on a thermocycler as described in the manuscript. Isolate the PCR products via gel electrophoresis and dilute the DNA sequences from the agarose gel via a DNA gel extraction kit. Using the Gibson assembly method, insert the purified PCR products into the cut-open shuttle vector by letting in the equimolar DNA mixture at 50 degrees Celsius for one hour.Construct the dCas12a accepter vector via touchdown PCR and the Gibson assembly method as demonstrated previously. Insert the yeast codon optimized dCas12a proteins into the two newly constructed acceptor vectors via digestion with BamH1 and Xhol1 and ligation with T4 DNA ligase. Similarly, construct the plasmids based on the pRS2403 shuttle vector to express the anti-CRISPR proteins via touchdown PCR and the Gibson assembly method.To perform microscopy cell detection, place two microliters of the cell solution on a glass slide and cover it with a cover slip. Observe the cells under a fluorescence microscope by turning on the fluorescent light source, microscope, and computer. After writing down the fluorescent light source number, open the microscope software on the computer.Put the slide on the microscope stage and choose the 40x objective lens while observing the cells under the green light. Move the course focus knob until the contour of yeast cells appears and the fine focus knob to focus the cells. To detect the cells, after closing the microscope field of view switch to the computer screen and click on live.Wait for three to five seconds. Click on capture to take a picture and save the picture. Next, turn off the computer, microscope, and fluorescent light source.Switch on the FACS machine 20 minutes before the measurements to warm up the laser and mix 20 microliters of the cell culture with 300 microliters of double distilled water. Run the FACS software on the computer connected to the FACS machine and create a new experiment. Then set the measurement parameters.Next, select the filter according to the excitation and emission wavelengths of the samples and set the acquisition cell number to 10, 000. Adjust the FITC filter voltage by measuring the intensity of fluorescent beads, ensuring that the relative difference in the intensity of the beads between two consecutive experiments does not exceed 5%Wash the machine with double distilled water for a few seconds to remove any possible excess beads. Measure the sample fluorescence intensity and click on preview while waiting for three to five seconds for sample injection stability.Finally click on acquire. Measure the beads again at the end of the experiment. After checking whether the relative difference between the two beads measurements exceeds 5%Export the FACS data as FCS files.Open R studio and load the script BDverse_analysis. R to analyze the FCS files. Set the experiment name as ename, the directory path where the FCS files are stored as dir_d and the result files will be created as dir_r.Next, set the fluorescence channel. Set the number of samples that were measured. The dimensions of dot plots and the maximal length of the x and y axis for bar plots and box plots.Choose the grading method by removing the hashtag from the corresponding lines. Select the flowSet object gated corresponding to the chosen gating method and the dot plot resolution, which should be at least equal to 256. Uncomment the two filtering instructions to remove measurements where fluorescence is negative and to remove outliers due to other experiments as described in the manuscript.Press source and run the script. All the files containing the results from the analysis are created in dir_r. The best activation efficiency of dSpCas9-VP64 was achieved when there were six lexOp target sites on the synthetic promoter.While for dCas12a-VPR highest activation efficiency when three copies of lexOp were inserted into the synthetic promoter. The activation by CRISPR RNA and single guide RNA located on an integrative plasmid were 1.4 to 2.4, and 1.1 to 1.5 fold higher than when placed on an episomal plasmid. RT-qPCR results showed that an episomal vector produced a much higher level of single guide RNA CRISPR RNA than the integrative vector, irrespective of the expression system.The activation efficiency of the complex dSpCas9 and scaffold RNA recruiting MCP-VP64 was tested. The scaffold RNA containing a single wild type and F6MS2 hairpin gave a 5.27 and a 4.3 fold activation respectively. However, the combination of the two hairpins resulted in 7.54 fold with the highest activation efficiency.Four different promoters were used to drive the expression of three kinds of type two anti CRISPR showing that they worked in a dose dependent manner. A strong promoter reduced the fluorescence level to 0.21, 0.11, and 0.13 of its value respectively. The titration curve shows that the circuit behaves like a knot gait with an on to off ratio approaching 2.3.The type five anti-CRISPR A one reduces the fluorescence expression of both denAS-Cas12a and dLB-Cas12a as activators from 19%to 71%The relation between activators and repressors was studied where the Acr-VA one displayed big fluctuations in its performance when produced by pGAL1 under pTEF1 and genetic CYC1t-pCYC1noTata type five anti-CRISPR-A1 showed some repression on the bare dLB Cas12a only. The FACS machine is frail, therefore it shall be handled carefully. Cell solution should never be too dense and the machine shall be kept clean.

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Unit 1

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SCIENTISTS IN ACTION

Three-dimensional Cell Culture Model for Measuring the Effects of Interstitial Fluid Flow on Tumor Cell Invasion

The growth and progression of most solid tumors depend on the initial transformation of the cancer cells and their response to stroma-associated signaling in the tumor microenvironment 1. Previously, research on the tumor microenvironment has focused primarily on tumor-stromal interactions 1-2. However, the tumor microenvironment also includes a variety of biophysical forces, whose effects remain poorly understood. These forces are biomechanical consequences of tumor growth that lead to changes in gene expression, cell division, differentiation and invasion3. Matrix density 4, stiffness 5-6, and structure 6-7, interstitial fluid pressure 8, and interstitial fluid flow 8 are all altered during cancer progression.
Interstitial fluid flow in particular is higher in tumors compared to normal tissues 8-10. The estimated interstitial fluid flow velocities were measured and found to be in the range of 0.1-3 &mu;m s-1, depending on tumor size and differentiation 9, 11. This is due to elevated interstitial fluid pressure caused by tumor-induced angiogenesis and increased vascular permeability 12. Interstitial fluid flow has been shown to increase invasion of cancer cells 13-14, vascular fibroblasts and smooth muscle cells 15. This invasion may be due to autologous chemotactic gradients created around cells in 3-D 16 or increased matrix metalloproteinase (MMP) expression 15, chemokine secretion and cell adhesion molecule expression 17. However, the mechanism by which cells sense fluid flow is not well understood. In addition to altering tumor cell behavior, interstitial fluid flow modulates the activity of other cells in the tumor microenvironment. It is associated with (a) driving differentiation of fibroblasts into tumor-promoting myofibroblasts 18, (b) transporting of antigens and other soluble factors to lymph nodes 19, and (c) modulating lymphatic endothelial cell morphogenesis 20.
The technique presented here imposes interstitial fluid flow on cells in vitro and quantifies its effects on invasion (Figure 1). This method has been published in multiple studies to measure the effects of fluid flow on stromal and cancer cell invasion 13-15, 17. By changing the matrix composition, cell type, and cell concentration, this method can be applied to other diseases and physiological systems to study the effects of interstitial flow on cellular processes such as invasion, differentiation, proliferation, and gene expression.

Interstitial fluid flow is elevated in solid tumors and can modulate tumor cell invasion. Here we describe a technique to apply interstitial fluid flow to cells embedded in a matrix and then measure its effects on cell invasion. This technique can be easily adapted to study other systems.

The growth and progression of most solid tumors depend on the initial transformation of the cancer cells and their response to stroma-associated signaling ...

Investigating Receptor-ligand Systems of the Cellulosome with AFM-based Single-molecule Force Spectroscopy

Cellulosomes are discrete multienzyme complexes used by a subset of anaerobic bacteria and fungi to digest lignocellulosic substrates. Assembly of the enzymes onto the noncatalytic scaffold protein is directed by interactions among a family of related receptor-ligand pairs comprising interacting cohesin and dockerin modules. The extremely strong binding between cohesin and dockerin modules results in dissociation constants in the low picomolar to nanomolar range, which may hamper accurate off-rate measurements with conventional bulk methods. Single-molecule force spectroscopy (SMFS) with the atomic force microscope measures the response of individual biomolecules to force, and in contrast to other single-molecule manipulation methods (i.e.&#160;optical tweezers), is optimal for studying high-affinity receptor-ligand interactions because of its ability to probe the high-force regime (&#62;120 pN). Here we present our complete protocol for studying cellulosomal protein assemblies at the single-molecule level. Using a protein topology derived from the native cellulosome, we worked with enzyme-dockerin and carbohydrate binding module-cohesin (CBM-cohesin) fusion proteins, each with an accessible free thiol group at an engineered cysteine residue. We present our site-specific surface immobilization protocol, along with our measurement and data analysis procedure for obtaining detailed binding parameters for the high-affinity complex. We demonstrate how to quantify single subdomain unfolding forces, complex rupture forces, kinetic off-rates, and potential widths of the binding well. The successful application of these methods in characterizing the cohesin-dockerin interaction responsible for assembly of multidomain cellulolytic complexes is further described.

Cellulosomes are multienzyme complexes designed for digesting cellulose. AFM-based SMFS was used to study the mechanical properties and folding configuration of cellulosome-associated protein assemblies. We present a complete workflow for protein immobilization, data acquisition, and data analysis to study the interactions of individual receptor-ligand complexes involved in cellulosome assembly.

Cellulosomes are discrete multienzyme complexes used by a subset of anaerobic bacteria and fungi to digest lignocellulosic substrates. Assembly of the ...

Patterning Bioactive Proteins or Peptides on Hydrogel Using Photochemistry for Biological Applications

There are many biological stimuli that can influence cell behavior and stem cell differentiation. General cell culture approaches rely on soluble factors within the medium to control cell behavior. However, soluble additions cannot mimic certain signaling motifs, such as matrix-bound growth factors, cell-cell signaling, and spatial biochemical cues, which are common influences on cells. Furthermore, biophysical properties of the matrix, such as substrate stiffness, play important roles in cell fate, which is not easily manipulated using conventional cell culturing practices. In this method, we describe a straightforward protocol to provide patterned bioactive proteins on synthetic polyethylene glycol (PEG) hydrogels using photochemistry. This platform allows for the independent control of substrate stiffness and spatial biochemical cues. These hydrogels can achieve a large range of physiologically relevant stiffness values. Additionally, the surfaces of these hydrogels can be photopatterned with bioactive peptides or proteins via thiol-ene click chemistry reactions. These methods have been optimized to retain protein function after surface immobilization. This is a versatile protocol that can be applied to any protein or peptide of interest to create a variety of patterns. Finally, cells seeded onto the surfaces of these bioactive hydrogels can be monitored over time as they respond to spatially specific signals.

In this method, we use photopolymerization and click chemistry techniques to create protein or peptide patterns on the surface of polyethylene glycol (PEG) hydrogels, providing immobilized bioactive signals for the study of cellular responses in vitro.

There are many biological stimuli that can influence cell behavior and stem cell differentiation. General cell culture approaches rely on soluble factors ...

Agarose-based Tissue Mimicking Optical Phantoms for Diffuse Reflectance Spectroscopy

This protocol describes how to make agarose-based tissue-mimicking phantoms and demonstrates how to determine their optical properties using a conventional optical system with an integrating sphere. Measuring systems for the acquisition of the diffuse reflectance and total transmittance spectra are constructed with a broadband white light source, a light guide, an achromatic lens, an integrating sphere, a sample holder, an optical fiber probe, and a multi-channel spectrometer. An acrylic mold consisting of two rectangular acrylic pieces and a U-shaped acrylic piece is constructed to create an epidermal phantom and a dermal phantom with whole blood. The application of a sodium dithionite (Na2S2O4) solution to the dermal phantom enables the researcher to deoxygenate hemoglobin in red blood cells distributed in the dermal phantom. The inverse Monte Carlo simulation with the diffuse reflectance and total transmittance spectra measured by a spectrometer with an integrating sphere is performed to determine the absorption coefficient spectrum &#181;a(&#955;) and the reduced scattering coefficient spectrum &#181;s&#39;(&#955;) of each layer phantom. A two-layered phantom mimicking the diffuse reflectance of human skin tissue is also demonstrated by piling up the epidermal phantom on the dermal phantom.

Here, we demonstrate how agarose-based tissue-mimicking optical phantoms are made and how their optical properties are determined using a conventional optical system with an integrating sphere.

This protocol describes how to make agarose-based tissue-mimicking phantoms and demonstrates how to determine their optical properties using a ...

A Droplet-Based Microfluidic Approach and Microsphere-PCR Amplification for Single-Stranded DNA Amplicons

Droplet-based microfluidics enable the reliable production of homogeneous microspheres in the microfluidic channel, providing controlled size and morphology of the obtained microsphere. A microsphere copolymerized with an acrydite-DNA probe was successfully fabricated. Different methods such as asymmetric PCR, exonuclease digestion, and isolation on streptavidin-coated magnetic beads can be used to synthesize single-stranded DNA (ssDNA). However, these methods cannot efficiently use large amounts of highly purified ssDNA. Here, we describe a microsphere-PCR protocol detailing how ssDNA can be efficiently amplified and separated from dsDNA simply by pipetting from a PCR reaction tube. The amplification of ssDNA can be applied as potential reagents for the DNA microarray and DNA-SELEX (Systematic evolution of ligands by exponential enrichment) processes.

This work provides a method for the fabrication of droplet-based microfluidic platforms and the application of polyacrylamide microspheres for microsphere-PCR amplification. The microsphere-PCR method makes it possible to obtain single-stranded DNA amplicons without separating double-stranded DNA.

Droplet-based microfluidics enable the reliable production of homogeneous microspheres in the microfluidic channel, providing controlled size and ...

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

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

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

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

Methods for In Vivo Biomechanical Testing on Brachial Plexus in Neonatal Piglets

Neonatal brachial plexus palsy (NBPP) is a stretch injury that occurs during the birthing process in nerve complexes located in the neck and shoulder regions, collectively referred to as the brachial plexus (BP). Despite recent advances in obstetrical care, the problem of NBPP continues to be a global health burden with an incidence of 1.5 cases per 1,000 live births. More severe types of this injury can cause permanent paralysis of the arm from the shoulder down. Prevention and treatment of NBPP warrants an understanding of the biomechanical and physiological responses of newborn BP nerves when subjected to stretch. Current knowledge of the newborn BP is extrapolated from adult animal or cadaveric BP tissue instead of in vivo neonatal BP tissue. This study describes an in vivo mechanical testing device and procedure to conduct in vivo biomechanical testing in neonatal piglets. The device consists of a clamp, actuator, load cell, and camera system that apply and monitor in vivo strains and loads until failure. The camera system also allows monitoring of the failure location during rupture. Overall, the presented method allows for a detailed biomechanical characterization of neonatal BP when subjected to stretch.

Methods for In Vivo Biomechanical Testing on Brachial Plexus in Neonatal Piglets

Presented here are methods to perform in vivo biomechanical testing on brachial plexus in a neonatal piglet model.

Neonatal brachial plexus palsy (NBPP) is a stretch injury that occurs during the birthing process in nerve complexes located in the neck and shoulder ...

Electrowetting-based Digital Microfluidics Platform for Automated Enzyme-linked Immunosorbent Assay

Electrowetting is the effect by which the contact angle of a droplet exposed to a surface charge is modified. Electrowetting-on-dielectric (EWOD) exploits the dielectric properties of thin insulator films to enhance the charge density and hence boost the electrowetting effect. The presence of charges results in an electrically induced spreading of the droplet which permits purposeful manipulation across a hydrophobic surface. Here, we demonstrate EWOD-based protocol for sample processing and detection of four categories of antigens, using an automated surface actuation platform, via two variations of an Enzyme-Linked Immunosorbent Assay (ELISA) methods. The ELISA is performed on magnetic beads with immobilized primary antibodies which can be selected to target a specific antigen. An antibody conjugated to HRP binds to the antigen and is mixed with H2O2/Luminol for quantification of the captured pathogens. Assay completion times of between 6 and 10 min were achieved, whilst minuscule volumes of reagents were utilized.

Electrowetting-based digital microfluidic is a technique that utilizes a voltage-driven change in the apparent contact angle of a microliter-volume droplet to facilitate its manipulation. Combining this with functionalized magnetic beads enables the integration of multiple laboratory unit operations for sample preparation and identification of pathogens using Enzyme-linked Immunosorbent Assay (ELISA).

Electrowetting is the effect by which the contact angle of a droplet exposed to a surface charge is modified. Electrowetting-on-dielectric (EWOD) exploits ...

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, ...

Reconstitution of Actin-Based Motility with Commercially Available Proteins

Many cell movements and shape changes and certain types of intracellular bacterial and organelle motility are driven by the biopolymer actin that forms a dynamic network at the surface of the cell, organelle, or bacterium. The biochemical and mechanical basis of force production during this process can be studied by reproducing actin-based movement in an acellular manner on inert surfaces such as beads that are functionalized and incubated with a controlled set of components. Under the appropriate conditions, an elastic actin network assembles at the bead surface and breaks open due to the stress generated by network growth, forming an "actin comet" that propels the bead forward. However, such experiments require the purification of a host of different actin-binding proteins, often putting them beyond the reach of non-specialists. This article details a protocol for reproducibly obtaining actin comets and motility of beads using commercially available reagents. Bead coating, bead size, and motility mixture can be altered to observe the effect on bead speed, trajectories, and other parameters. This assay can be used for testing the biochemical activities of different actin-binding proteins, and for performing quantitative physical measurements that shed light on active matter properties of actin networks. This will be a useful tool for the community, enabling the study of in vitro actin-based motility without expert knowledge in actin-binding protein purification.

This protocol describes how to produce actin comets on the surfaces of beads using commercially available protein ingredients. Such systems mimic the protrusive structures found in cells, and can be used to examine physiological mechanisms of force production in a simplified way.

Many cell movements and shape changes and certain types of intracellular bacterial and organelle motility are driven by the biopolymer actin that forms a ...