Predicting Gene Silencing Through the Spatiotemporal Control of siRNA Release from Photo-responsive Polymeric Nanocarriers

Summary

We present a novel method that uses photo-responsive block copolymers for more efficient spatiotemporal control of gene silencing with no detectable off-target effects. Additionally, changes in gene expression can be predicted using straightforward siRNA release assays and simple kinetic modeling.

Abstract

New materials and methods are needed to better control the binding vs. release of nucleic acids for a wide range of applications that require the precise regulation of gene activity. In particular, novel stimuli-responsive materials with improved spatiotemporal control over gene expression would unlock translatable platforms in drug discovery and regenerative medicine technologies. Furthermore, an enhanced ability to control nucleic acid release from materials would enable the development of streamlined methods to predict nanocarrier efficacy a priori, leading to expedited screening of delivery vehicles. Herein, we present a protocol for predicting gene silencing efficiencies and achieving spatiotemporal control over gene expression through a modular photo-responsive nanocarrier system. Small interfering RNA (siRNA) is complexed with mPEG-b-poly(5-(3-(amino)propoxy)-2-nitrobenzyl methacrylate) (mPEG-b-P(APNBMA)) polymers to form stable nanocarriers that can be controlled with light to facilitate tunable, on/off siRNA release. We outline two complementary assays employing fluorescence correlation spectroscopy and gel electrophoresis for the accurate quantification of siRNA release from solutions mimicking intracellular environments. Information gained from these assays was incorporated into a simple RNA interference (RNAi) kinetic model to predict the dynamic silencing responses to various photo-stimulus conditions. In turn, these optimized irradiation conditions allowed refinement of a new protocol for spatiotemporally controlling gene silencing. This method can generate cellular patterns in gene expression with cell-to-cell resolution and no detectable off-target effects. Taken together, our approach offers an easy-to-use method for predicting dynamic changes in gene expression and precisely controlling siRNA activity in space and time. This set of assays can be readily adapted to test a wide variety of other stimuli-responsive systems in order to address key challenges pertinent to a multitude of applications in biomedical research and medicine.

Introduction

Small interfering RNAs (siRNAs) mediate post-transcriptional gene silencing through a catalytic RNAi pathway that is highly specific, potent, and tailorable to virtually any target gene¹. These promising characteristics have enabled siRNA therapeutics to advance in human clinical trials for the treatment of numerous diseases, including metastatic melanoma and hemophilia^2,3. However, significant delivery issues persist that have hindered translation⁴. In particular, delivery vehicles must remain stable and protect siRNAs from extracellular degradation, yet also release the payload into the cytoplasm⁵. Furthermore, many RNAi applications require improved methods to regulate gene silencing in space and time⁶, which will reduce side effects in siRNA therapeutics⁷ and enable transformative advances in applications ranging from cell microarrays for drug discovery⁸ to modulation of cell responses in regenerative scaffolds⁹. These challenges highlight the need for new materials and methods to better control binding vs. release in siRNA nanocarriers.

One of the most promising strategies for controlling siRNA release and enhancing spatiotemporal regulation is the use of stimuli-responsive materials¹⁰. For example, a wide variety of biomaterials have been engineered with changeable nucleic acid binding affinity in response to altered redox potential or pH, or applied magnetic fields, ultrasound, or light¹¹. Although many of these systems demonstrate improved control over nucleic acid activity, the use of light as a trigger is particularly advantageous due to its instantaneous temporal response, precise spatial resolution, and ease of tunability¹². Moreover, the potential of photo-sensitive technologies for regulating gene expression has been demonstrated by state-of-the-art inducible promoter and optogenetic regulator systems; however, these systems suffer from numerous challenges including limited capacities to regulate endogenous genes, safety concerns such as immunogenicity, and difficulties in delivering multi-component assemblies^13,14,15. Photo-responsive siRNA nanocarriers are ideally suited to overcome these drawbacks and provide a simpler and more robust approach to spatiotemporally modulate gene expression^16,17,18. Unfortunately, methods to accurately predict the resulting protein knockdown response remain elusive.

A key challenge is that quantitative evaluations of siRNA release are rare^19,20, and even when these evaluations are performed, they have not been coupled to analyses of siRNA/protein turnover dynamics. Both the amount of siRNA released and its persistence/lifetime are important determinants of the resulting gene silencing dynamics; hence, a lack of such information is a major disconnect that precludes accurate prediction of dose-response in RNAi²¹. Addressing this challenge would expedite the formulation of the appropriate structure-function relationships in nanocarriers and better inform biomaterial designs²². Furthermore, such approaches would enable development of more effective siRNA dosing protocols. In an attempt to understand the dynamic silencing response, several groups have investigated mathematical models of RNAi^23,24,25. These frameworks were successful in providing insights into siRNA-mediated changes in gene expression and identifying rate-limiting steps²⁶. However, these models have been applied only to commercial gene delivery systems (e.g., Lipofectamine and polyethylenimine (PEI)) that are not capable of controlled siRNA release, and the complexity of the models has severely limited their utility²⁷. These shortcomings highlight an unmet need for new materials capable of precisely tunable siRNA release combined with streamlined and easy-to-use predictive kinetic models.

Our method addresses all of these challenges through the integration of a light-sensitive nanocarrier platform with coupled methods to quantify free siRNA and model RNAi dynamics. In particular, our platform's precisely controlled siRNA release²⁸ is monitored by two complementary methods for accurately quantifying encapsulated vs. unbound siRNA. The experimental data from these assays are entered into a simple kinetic model to predict gene silencing efficiencies a priori²⁹. Finally, the on/off nature of the nanocarriers is easily exploited to generate cell patterns in gene expression with spatial control on the cellular length scale. Thus, this method provides an easily adaptable method to control and predict gene silencing in a variety of applications that would benefit from spatiotemporal regulation of cell behavior.

Protocol

1. Formulation of siRNA Nanocarriers

1. Prepare separate solutions of siRNA and mPEG-b-P(APNBMA) with equal volumes diluted in 20 mM 4-(2-hydroxyethyl)piperazine-1-ethanesulfonic acid (HEPES) buffer at pH 6.0.
   1. Add siRNA at a concentration of 32 µg/mL to 20 mM HEPES solution.
      NOTE: The siRNA was a non-targeted, universal negative control sequence; however, the siRNA can be designed to target any gene of interest.
   2. Dissolve mPEG-b-P(APNBMA) polymers into a 20 mM HEPES solution. Add an appropriate amount of mPEG-b-P(APNBMA) to make a 220 µg/mL solution so that the N/P ratio (N, amine groups on mPEG-b-P(APNBMA); P, phosphate groups on siRNA) is 4.
      NOTE: The synthetic protocol for the mPEG-b-P(APNBMA) polymers is reported elsewhere³⁰.
2. Add the mPEG-b-P(APNBMA) solution dropwise to an equal volume of the siRNA solution while gently mixing on a vortex machine. Continue to vortex for 30 s following polymer addition. Incubate the samples in the dark at room temperature for 30 min.

2. Measuring siRNA Release Using Gel Electrophoresis

1. Formulate the nanocarriers according to steps 1.1-1.2, and scale the volumes to accommodate the number of samples desired.
2. Mix the nanocarrier with sodium dodecyl sulfate (SDS).
   1. Prepare a 1 mg/mL solution of SDS in water. Aliquot out the amount of SDS solution needed to produce solutions with an S/P ratio (S, sulfate groups on SDS; P, phosphate groups on siRNA) of 15.
      NOTE: If the polyplex solution contains 1 µg of siRNA, 13 µg of SDS must be added to achieve an S/P ratio of 15.
   2. Add the SDS solution to each nanocarrier solution dropwise while gently mixing on a vortex machine. Continue to vortex for 30 s following SDS addition.
   3. Centrifuge the samples at 3,000 x g for 5 s. Incubate the samples in the dark at room temperature for 30 min.
3. Calibrate and set a UV laser with a 365 nm filter to an intensity of 200 W/m. Ensure that the light intensity is measured from the location at which the bottom of the sample solution will be seated.
4. Load the nanocarrier/SDS solution into a glass chamber comprised of glass slides separated by a rubber gasket.
   1. Pre-wash glass slides in a 7:3 (v/v) ethanol/water solution in water and dry completely. Cut a hole (~2 x 3 cm rectangle) into a rubber gasket. Place the rubber gasket onto a glass slide.
   2. Pipette the nanocarrier/SDS solution onto the glass slide inside the hole of the rubber gasket. Load an excess of solution (20 µL in surplus) onto the glass slide while avoiding contact with the rubber gasket.
      NOTE: Some liquid will be lost during the subsequent steps.
   3. Place the second glass slide on top of the slide-gasket. To avoid air bubble generation, place one end of the slide down first and then slowly lower the other end.
   4. Attach binder clips to each side of the glass chamber to hold it closed.
5. Irradiate the samples for the desired length of time (e.g., 0-60 min) using the UV laser with a 365 nm filter at an intensity of 200 W/m. Remove the binder clips and open the chamber.
6. Pipette 25 µL of the irradiated nanocarrier/SDS samples into a microcentrifuge tube. Incubate the solutions in the dark at room temperature for 30 min.
7. Prepare a 2 wt% agarose gel pre-stained with 0.5 µg/mL ethidium bromide in Tris/Borate/EDTA (TBE) buffered solution according to standard protocols³¹. Prepare a loading buffer comprised of 3:7 (v/v) glycerol/water.
8. Add 5 µL of the loading buffer solution to 25 µL of each nanocarrier/SDS sample. Incubate the samples in the dark at room temperature for 10 min.
9. Load 30 µL of each nanocarrier/SDS sample into the 2% agarose gel. Run the gel in the dark at 100 V for 30 min. Image the gel using a gel imaging system with ethidium bromide filters. Save the gel image files and proceed to step 2.10 for band intensity quantification. Ensure that the band intensities are bright enough to clearly visualize but not too bright that the signals are saturated.
10. Quantify the band intensities using publicly available ImageJ software³².
    1. Using the ROI tool of ImageJ, determine the fluorescence intensity of the free siRNA bands in each lane by drawing a rectangle around each band. Plot the intensity curves of each lane, and integrate the area under the curves by drawing a horizontal line across the intensity curves and clicking the tracing wand inside the enclosed areas.
    2. Compute the relative intensity of each lane by dividing the area under the curve of each sample by the area under the curve of the siRNA positive control (no mPEG-b-P(APNBMA) added and no SDS added). Report the percentage of siRNA released as the normalized band intensity of each sample.

3. Measuring siRNA Release Using Fluorescence Correlation Spectroscopy (FCS)

1. Obtain siRNA labelled with a single fluorophore at the 5' end of the sense strand.
   NOTE: The siRNA can be purchased pre-annealed with the labels conjugated in the desired location. The fluorophore should be photo-stable and absorb/emit between 450 and 750 nm to avoid UV light quenching and energy transfer with mPEG-b-P(APNBMA).
2. Formulate the nanocarriers according to steps 1.1-1.2 using the labelled siRNA. Scale the volumes to accommodate the number of samples desired.
3. Incubate the solutions in SDS and irradiate for the desired length of time according to steps 2.2-2.6.
4. Preparation of FCS sample chamber.
   1. Wash a glass slide with a 7:3 (v/v) ethanol/water solution and completely dry the glass using a wipe and an air stream.
   2. Remove the pieces of paper from a double-sided adhesive spacer to expose the double-sided adhesive spacer. Attach the spacer to a glass coverslip.
   3. Pipette the nanocarrier/SDS solution onto the cover slip in the middle of the hole from the adhesive spacer.
   4. Place the glass slide on top of the coverslip. Push on the glass slide to ensure that the glass slide and coverslip are well attached and form a seal.
5. Use a confocal microscope for FCS measurements³³. Use a 40X water immersion apochromat objective with a numerical aperture of 1.2. Use the appropriate excitation laser channel (488 nm) to collect at least 30 measurements of 10 s each per sample³⁴. Ensure that the laser intensity and detector alignment remain the same for each sample.
   1. In addition to the experimental samples, measure controls including: a blank sample without labelled siRNA; and a free siRNA sample with labelled siRNA but no mPEG-b-P(APNBMA).
6. Analyze the data using FCS-specific software. Identify the baseline count rate of each sample by determining the stable count rate during a time when no nanocarriers are passing through the confocal volume²⁹.
   1. Subtract the count rate of the blank sample from every sample baseline count rate value. Normalize the resulting values to the free siRNA control to calculate the percent of free siRNA³⁵.

4. Kinetic Modeling to Predict Gene Silencing

1. Create scripts in a mathematical programming language using the simple set of ordinary differential equations to predict gene silencing²⁹.
   NOTE: Scripts can be made available upon request.
   1. Write the set of ordinary differential equations as:
           (1)
           (2)
           (3)
      NOTE: For equations 1−3, the terms k_mRNA, k_siRNA, and k_prot are the rate constants for the production of mRNA, siRNA, and protein, respectively. The terms k_m,deg, k_s,deg, and k_p,deg are the rate constants for the degradation of mRNA, siRNA, and protein, respectively. Degradation rate constants are computed on the basis of the component half-lives, and production rate constants are fit to ensure that mRNA and protein steady-state values are reached in the absence of siRNA.
      1. Determine the half-lives of the mRNA and protein for the gene(s) of interest, either experimentally as described in reference ³⁶ or from the literature (see the Discussion). Also, determine the doubling time for the cell line. Input these values into the appropriate degradation rate expressions.
      2. Tune the production rate constants so that gene expression levels remain steady at a normalized value of 100 if no siRNA is introduced. Specifically, set [siRNA] to zero and vary the values of the k_mRNA, k_siRNA, and k_prot production rate constants until [mRNA] and [protein] remain within 1% of the initial normalized value of 100% for the duration of the simulation.
      3. Using the relative amounts of siRNA released from the previously described gel electrophoresis and FCS assays as estimates, adjust the initial relative concentration of siRNA in the script. Specifically, vary [siRNA] to be proportional to the relative amount of released siRNA, with a value of 100 corresponding to the maximum amount²⁹.

5. Cell Culture and In Vitro siRNA Delivery

1. Culture NIH/3T3 murine embryonic fibroblasts according to the protocols from the supplier.
   1. Grow the cells in growth medium (Dulbecco's Modified Eagle Medium (DMEM) supplemented with 10% heat-inactivated fetal bovine serum and 1% penicillin-streptomycin). Maintain the cells at 37 °C in a humidified environment with 5% CO₂.
2. Seed the cells in 6-well tissue culture treated plates.
   1. Follow the recommended subculturing procedure from the supplier. Count the cells using a hemocytometer. Dilute the cells in supplemented growth media to a concentration of 75,000 cells/mL.
   2. Add 2 mL of cell suspension (75,000 cells/mL) to each well of the 6-well plate. Let the cells adhere and recover for 24 h in the incubator.
3. Prepare the cells for transfection by washing with phosphate-buffered saline (PBS) and adding 1.5 mL of serum- and antibiotic-free transfection medium (see the Table of Materials) to each well.
4. Formulate the siRNA nanocarriers according to steps 1.1-1.2. Add 25 µL of nanocarrier solution containing 30 pmol of siRNA to each well. Gently pipette the media up and down to mix. Place the cells in the incubator for 3 h.
5. Remove the transfection media and wash each well with PBS. Add 1 mL of supplemented growth media and place the cells in the incubator to recover for 30 min.
6. To prepare the cells for treatment with a photo-stimulus, remove the supplemented growth media. Add 1 mL of transfection media (without phenol red) to each well.
   NOTE: Ensure that the transfection media does not contain phenol red.
7. Calibrate and set a UV laser with a 365 nm filter to an intensity of 200 W/m. Ensure that the light intensity is measured from the location at which the bottom of the cell plate will be seated.
8. Place the cells on a hot plate set to 37 °C. Remove the plate cover of the cells. Irradiate the cells from above the plate for the desired time (up to 20 min) using the UV laser with a 365 nm filter at an intensity of 200 W m^-2.
9. Remove the transfection media and add 2 mL of supplemented growth media. Place in incubator until further analysis (e.g., 24 h for qPCR and 48 h for Western blotting).
   1. Measure changes in gene expression using a variety of techniques such as Western blotting³⁷ and qPCR.³⁸ For genes with visible signals, such as GFP, use fluorescence microscopy²⁹.
      NOTE: These techniques are suggested due to their ease of use and accuracy in quantifying gene expression

6. Controlling Gene Silencing in a Spatiotemporal Manner

1. Culture, seed, and transfect cells according to steps 5.1-5.7.
2. Prepare a photomask that completely blocks 365 nm light and minimizes reflections.
   NOTE: In this case, 10 x 10 cm pieces of aluminum foil and black construction paper were used to block the light and to reduce reflections, respectively. The aluminum foil and construction paper were glued together to form a single unit.
   1. Cut/punch/machine the desired shape into the photomask. For example, use a sharp-edged blade and a hole-puncher to form a straight-line pattern (~5 cm long) and a circular pattern (~7 mm diameter) in the photomask, respectively.
3. Glue the photomask to the bottom of the 6-well plate with the pattern centered under the well containing the cells with the anti-reflective side (e.g., black construction paper) facing the plate. Ensure that the glue is not placed near the edge (within ~3 mm) of the pattern.
4. Set up two ring stands approximately 25 cm apart and attach a platform to each ring stand so that the platforms are of equal height. Suspend the cell plate between the two stands by resting the plate on top of the platforms. Ensure that the plate is level.
5. Irradiate the cells from below the sample for the desired time (up to 20 min) using the UV laser with a 365 nm filter at an intensity of 200 W/m².
6. Remove the transfection media and add 2 mL of supplemented growth media. Place in incubator to recover for at least 24 h. Image the cells using fluorescence microscopy as described²⁹.

Results

Following the formulation of the nanocarriers, siRNA release assays were conducted to inform the irradiation conditions to be used in the in vitro transfections. Various dosages of light were applied to determine the percent of siRNA that was released. The first assay used gel electrophoresis to separate the free siRNA molecules from the siRNA molecules still complexed/associated with the polymer. Nanocarriers that were not treated with light remained stable and did not release a...

Discussion

There are a few steps in the method that are particularly critical. When formulating the nanocarriers, the order of component addition and mixing speed are two important parameters influencing efficacy³⁹. This protocol requires that the cationic component, mPEG-b-P(APNBMA), is added to the anionic component, siRNA, in a dropwise fashion while vortexing. Depending on the total formulation volume, this mixing process takes 3-6 s. To test if the nanocarriers were formed properly, measure the...

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
siRNA	Sigma-Aldrich	SIC001	non-targeted, universal negative control
mPEG-b-P(APNBMA)	synthesized in our lab	N/A	photo-responsive polymer
HEPES	Fisher Scientific	BP310-100
sodium dodecyl sulfate	Sigma-Aldrich	436143
rubber gasket	McMaster-Carr	3788T21	0.5 mL thick
UV laser	Excelitas Technologies	Omnicure S2000	collimating lens and 365 nm filter used
agarose	Fisher Scientific	BP160-100
ethidium bromide	Fisher Scientific	BP1302-10
siRNA labelled with Dy547	GE Healthcare Dharmacon, Inc.	custom order	fluorophore conjugated to 5’ end of sense strand
microscope slide	Fisher Scientific	12-550-A3	pre-cleaned glass
Secure-Seal Spacer	Life Technologies	S24735	double-sided adhesive
LSM 780	Carl Zeiss	N/A	confocal microscope
ZEN 2010	Carl Zeiss	N/A	FCS analysis software
MATLAB	MathWorks	N/A	programming language
NIH/3T3 cells	ATCC	ATCC CRL-1658
DMEM	Mediatech	10-013-CV	growth media
fetal bovine serum	Mediatech	35-011-CV	heat-inactivated
penicillin-streptomycin	Mediatech	30-002-CI
6-well plates	Fisher Scientific	08-772-1B
Opti-MEM	Life Technologies	11058021	transfection media