A Kinetic Model of Oligonucleotide-Brush Interactions for the Rational

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A Kinetic Model of Oligonucleotide-Brush Interactions for the Rational Design of Gene Delivery Vectors Fengjin Qu, Danyang Li, Xiaoyan Ma, Fang Chen, and Julien Gautrot Biomacromolecules, Just Accepted Manuscript • DOI: 10.1021/acs.biomac.9b00155 • Publication Date (Web): 24 Apr 2019 Downloaded from http://pubs.acs.org on April 25, 2019

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Biomacromolecules

A

Kinetic

Model

of

Oligonucleotide-Brush

Interactions for the Rational Design of Gene Delivery Vectors

Fengjin Qu∥,†,§, Danyang Li†,§, Xiaoyan Ma∥, Fang Chen∥, Julien Gautrot*,†,§

∥Department of Applied Chemistry, School of Natural and Applied Sciences, Northwestern Polytechnical University, Xi’an 710072, PR China. †Institute of Bioengineering and §School of Engineering and Materials Science, Queen Mary University of London, Mile End Road, London E1 4NS, United Kingdom.

KEYWORDS Polymer brushes, oligonucleotides, surface plasmon resonance, gene delivery.

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ABSTRACT

Polymer brushes are attractive candidates for the design of gene delivery vectors as they allow the systematic study of the impact of structural (type, size and shape of nanomaterials core) and physico-chemical parameters (cationic monomer chemistry, brush thickness and grafting density) on transfection efficiency. However, relatively little is known of their interactions of oligonucleotides. To study such interactions, we use surface plasmon resonance and developed a kinetic model of brush binding and infiltration. We identify the striking impact that brush grafting density and thickness have on oligonucleotide kinetics of infiltration, binding affinity and maximum loading. Surprisingly, double stranded RNA molecules are found to load at significantly higher levels compared to DNA molecules of identical sequence (apart from uracils/thymines). Furthermore, analysis of the kinetics of adsorption of these oligonucleotides indicates that the stoichiometry of binding (the ration of amine vs. phosphate residues) is close to parity for the uptake of double stranded 20 bp RNA. Finally, nanoparticles were designed, to be used as gene transfection vectors and to quantify that the brush grafting density and thickness significantly impact transfection efficiencies in an siRNA knock down assay. Therefore, this study demonstrates the rational design of polymer brush-based nanoparticle vectors for efficient delivery. The model developed will allow to uncover how the refinement of the physico-chemical and structural properties of polymer brushes enable the tuning of RNA binding and allow the systematic study of cationic vectors efficiency for RNA delivery.


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Introduction Gene therapy has gained significant attention over the past decades as a potential method for treating diseases such as epidermolysis bullosa1, cancer2 and wound healing3. Research efforts are currently focused on designing effective carriers that compact and protect oligonucleotides for gene therapy, because free oligonucleotides are rapidly degraded by serum nucleases in the blood when injected intravenously. These carriers should also promote cellular uptake. To this aim, viral carriers have shown very promising performance4. However, viral vectors typically display significant toxicity, immunogenicity and limited scale-up potential. These drawbacks have encouraged the investigation of other potential scaffolds for the delivery of exogenous DNA or RNA into targeted cells and tissues5, 6. Indeed, in recent years, significant effort has been devoted to develop nanomaterials for gene delivery as these systems offer the possibility to design sub-micron vectors able to deliver genetic materials to targeted cells (in some cases through the circulation, after crossing the endothelial barrier). Cationic polymers such as polyethylenimine (PEI), polyallylamine (PAA), poly-L-lysine (PLL) and poly (N,N-dimethylaminoethyl methacrylate) (PDMAEMA), are typically used for such applications as they allow the complexation of nucleic acid materials and promote cellular uptake7-9. The synthesis and design of polycationic vectors has identified a number of rules and structure-property relationships that can be used for the optimisation of non-viral vectors. Gene transfection efficiency usually increases with the molecular weight of the cationic polymer used to condense oligonucleotides and plasmids, to the detriment of increased cytotoxicity10, 11.

The hydrophilicity/hydrophobicity balance of the non-viral vector is an important factor

impacting gene delivery: hydrophobic carriers enhance cell adhesion, alleviate the serum inhibition and protect oligonucleotides from enzymatic degradation, generally improving gene transfection. However hydrophilic moieties increase water solubility and stability, and reduce opsonisation, therefore regulate transfection efficiencies12. For micellar systems, this balance 3 ACS Paragon Plus Environment


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also determines the association behaviour and stability of the carrier13. Other structural and physico-chemical properties of cationic moieties, such as side chain length, strength of electrolytes and charge density, which affect the interaction between vectors and oligonucleotides also modulate transfection14. Finally, the size and shape of vectors can affect the condensation of oligonucleotides, and influence cellular uptake and transfection efficiency15. However, the generality of such structure-property relationships remains difficult to establish as it is particularly challenging to control independently chemistry and structural features (size, charge density, shape of vectors and complexes). In this context, polymer brushes are an interesting class of vectors as they potentially allow the independent design of chemistry and structure (Figure 1). Indeed, in addition to a very wide range of monomers that can be incorporated into polymer brushes via controlled surfaceinitiated polymerisations, the grafting density, thickness and core size and shape can be readily controlled, independently of each other16-20. Polymer brushes can be grafted from a wide range of nanomaterials (silica nanoparticles, nanodiamond, graphene, for example) and yet enable the control of outer surface chemistry21-23. In particular, the extremely high grafting density that can be achieved via surface-initiated controlled radical polymerisations has conferred to these coatings unique properties for their application in the biomedical field24. Indeed, such high grafting density significantly impact the ability of biomacromolecules to infiltrate within the polymer coating, through to the underlying substrate. This has important consequences for the design of protein resistant coatings and high density polymer brushes such as poly(carboxybetaine methacrylate)25, 26 and poly(hydroxypropyl methacrylamide)27 are considered the most protein resistant coatings developed to date. The restriction of biomacromolecule infiltration also impacts the ability to biofunctionalise polymer brushes as it regulates the accessibility of biomacromolecules for coupling to reactive sites28, 29. 4 ACS Paragon Plus Environment

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More recently, we reported that the uniquely high grafting density of cationic polymer brushes enables the strong binding of small RNA molecules, such as siRNA, and their loading at particularly high levels30. Hence a four-fold increase in grafting density (from 0.12 to 0.5 chains/nm2) results in a similar level of increase in the binding of oligonucleotides. As a result, polymer brush-functionalised nanoparticles display high transfection efficiencies for gene silencing. In this respect, it is interesting to note that the chain density of most systems typically achieved via grafting to approaches, or via the self-assembly of block-copolymer structures, is controlled by steric hindrance and electrostatic repulsion, and falls below 0.1 chains/nm2. In addition, it was identified that the binding of nucleic acid molecules is strongly affected by the brush grafting density. Hence plasmid DNA bound to relatively low levels to polymer brushes, with relatively little impact of grafting density, indicating weak infiltration within the polymer brush and only surface adsorption30, 31. In contrast, small (10 bp) DNA molecules resulted in rapid desorption from low grafting density polymer brushes. However, a systematic study of the impact of polymer brush grafting density and thickness on the binding of oligonucleotides with different molecular weights, and how this impacts gene delivery efficacy, is still lacking. In this work, the binding of oligonucleotides by poly (N,N-dimethylaminoethyl methacrylate) (PDMAEMA) brushes, cationic polyelectrolytes with a pKa close to 7.0, is studied. We vary the grafting density and thickness of PDMAEMA brushes, and quantify oligonucleotide binding by surface plasmon resonance. We report a model of the kinetics of oligonucleotide absorption that accounts for the impact of brush grafting density, thickness and oligonucleotide molecular weight on oligonucleotide binding. In turn, we correlate binding affinity and transfection efficacy, using a knock down assay.



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Experimental Section Materials. 2-(Dimethylamino)ethyl methacrylate (DMAEMA,  = 1.318 g/cm3), copper chloride (Cu(I)Cl), copper bromide (Cu(II)Br2), 2,2′-bipyridyl (bipy), anhydrous toluene, triethylamine (Et3N), trimethoxy(propyl)silane and 1-undecanethiol were purchased from Sigma-Aldrich and used as received. All chemicals and solvents were analytical grades unless otherwise stated. Cu(I)Cl was kept under a vacuum until used. Silicon wafers (100 mm diameter, ⟨100⟩ orientation, polished on one side/reverse etched) were purchased from Compart Technology Ltd. and cleaned in a Henniker Plasma Cleanser (HPT-200, air plasma) for 10 min. Gold-coated substrates were obtained through the evaporation of a chromium layer (20 nm) on silicon wafer followed by the evaporation of a gold layer (~200 nm) using an Edwards Auto 500 evaporator. Silica particles (unfunctionalized) were purchased from Bangs Laboratories (supplied as aqueous suspension, mean diameter of 300 nm). The thiol initiator ωmercaptoundecyl bromoisobutyrate was synthesized according to the literature19. The silane initiator, (3-trimethoxysilyl)propyl 2-bromo-2-methylpropionate, was purchased from Gelest. Surface plasmon resonance (SPR) chips (10 × 12 × 0.3 mm) were purchased from Ssens. Triton X-100, gelatin, phallodin–tetramethylrhodamine B isothiocyanate, paraformaldehyde (PFA), 4,6-diamidino-2-phenylindole (DAPI), and phosphate-buffered saline (PBS, 150 mM) were purchased from Sigma-Aldrich. Dulbecco’s modified Eagle medium (DMEM), Opti-MEM medium, trypsin, versene, penicillin-streptomycin, L-glutamine, DNA fragments and 20 bp RNA were from Thermo-Fisher. 20 bp RNA were designed with the same sequence as the 20 DNA fragment, with the exception of uracils instead of thymines. Collagen type I was from BD Bioscience. GFP siRNA (target sequence CGGCAAGCTGACCCTGAAGTTCAT) and negative control (NC) siRNA (detailed sequence not available) were purchased from Qiagen. 6-FAM labelled siRNA (green fluorescence) were purchased from Sigma-Aldrich.


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Deposition of Initiators on Flat Substrates. Polymer brushes were grown from the corresponding bromo initiator-functionalized substrates using a “grafting from” method, via atom transfer radical polymerization (ATRP). For the deposition of the ATRP silane initiator on silicon wafers, a plasma-oxidized silicon chip (1 cm2) was immersed in a solution of silane initiator (30 μL), Et3N (50 μL), and anhydrous toluene (30 mL) and incubated at room temperature overnight. For sparse brushes, a mixture of silane initiator with trimethoxy(propyl)silane at different ratios of 1:0, 1:4, 1:9 and 1:19 was used, depending on the grafting density targeted (100, 20, 10, 5%), to reduce the surface density of initiator. Then, the wafer was rinsed with ethanol and dried under a nitrogen stream. Initiator-coated wafers were kept in a dry and dust-free nitrogen box until used. The dry thickness of silane initiator layers was near 2 nm as measured via spectroscopic ellipsometry. For the deposition of ATRP thiol initiator on gold substrates, gold silicon and SPR chips were first plasma-oxidized and immersed in 5 mM of thiol initiator ethanolic solutions containing ω-mercaptoundecyl bromoisobutyrate and 1-undecanethiol, at different ratios of 1:0, 1:4, 1:9 and 1:19, depending on the targeted grafting densities of brushes. The chips were incubated at room temperature overnight and then washed with ethanol and dried under nitrogen. The thiol initiatorfunctionalized chips were directly used to grow polymer brushes. The dry thickness of thiol initiator layers was near 2 nm, as measured via ellipsometry. Synthesis of PDMAEMA Brushes from Flat Substrates. To study PDMAEMA brush growth and the evolution of its thickness as a function of time, a solution of CuBr2 (18 mg, 80 μmol), bipy (320 mg, 2.05 mmol), and DMAEMA (42 mmol, 6.6 g) in water/ethanol (3:2 (v/v), 30 mL) was degassed using argon bubbling for 30 min. CuCl (82 mg, 828 μmol) was then added to this solution quickly, and the resulting mixture was sonicated to ensure full dissolution of CuCl and further degassed for 30 min before polymerization. Initiator-coated silicon/gold substrates (∼1 × 1 cm2 each) were placed in reaction vessels and degassed via four cycles of 7 ACS Paragon Plus Environment


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vacuum/nitrogen. Subsequently, 1 mL of DMAEMA solution was transferred to reaction vessels under an inert atmosphere, via a syringe. The polymerization was stopped at different time points (from 5 to 180 min) by immersing the coated substrates in deionized water followed by washing with copious amounts of ethanol and drying under a nitrogen stream. The dry thickness of the PDMAEMA brush was subsequently determined via ellipsometry. The swelling and collapse of brushes in different conditions was studied via in-situ ellipsometry. Synthesis of Polymer Brush-Coated Silica Nanoparticles (SiO2-PDMAEMA). For initiator deposition, silica particles in aqueous suspensions were centrifuged at 4000 rpm for 15 min to remove water. Dry ethanol was used to resuspend the particles by sonication, and then removed after centrifugation. To remove traces of water in suspension more thoroughly, the sonication and centrifugation process was repeated three times. Anhydrous toluene (4 mL) kept under nitrogen was added to 200 mg of silica nanoparticles associated with sonication until the suspension turned cloudy and homogeneous. Toluene was then aspirated out after centrifugation and particles were resuspended in anhydrous toluene to remove final traces of ethanol. After washing particles with toluene three times, the particles were finally dispersed in 4 mL of anhydrous toluene. The initiator grafting process was carried out by adding 200 μL of Et3N and 40 μL of silane initiator to the 4 mL of silica dispersion and stirred overnight. Then, the silica particles with silane initiator (SiO2-silane) were washed with 4 mL of ethanol three times and stored in a final water/ethanol (3:2 (v/v), 10 mL) solution at 5oC, until needed for polymerization. For the synthesis of PDMAEMA-grafted silica nanoparticles (SiO2PDMAEMA), a polymerisation solution was prepared as described previously by dissolving DMAEMA (6.6 g, 42 mmol), bipy (320 mg, 2.05 mmol), CuBr2 (80 mmol), and CuCl (0.082 g, 828 μmol) in half of the total polymerization solvent (water/ethanol 3:2 (v/v), 15 mL). 10 mL of SiO2-silane dispersion were degassed for 30 min with argon bubbling while stirring. An equal volume of DMAEMA monomer solution was added to the SiO2-silane suspension. 8 ACS Paragon Plus Environment

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Polymerization was allowed to proceed under argon at room temperature. To terminate the polymerization, the particle suspension was diluted using deionized water and bubbled with air until the colour changed from dark brown to blue (oxidization of CuCl). The particles were recovered via centrifugation and washed successively with water and ethanol to remove the catalysts and residual monomer, during which sonication was applied to reduce aggregation. Finally, the particles were dispersed in 10 mL of deionized water and stored at 5oC. Ellipsometry Measurements. Ellipsometry Measurements were carried out with an α-SE instrument from J. A. Woolam, at an incidence angle of 70o. For dry samples, a simple silicon substrate/Cauchy film model was used. For wet samples, substrates were placed in an in-housebuilt chamber fitted with quartz windows normal to the laser beam path. Measurements were carried out in triplicate. Swelling ratios are given as swollen height/dry height. It is worth noting that we only refer to the values of dry thickness of brushes in this work to prevent confusion, unless otherwise stated in the text. Light Scattering and -Potential Measurement. The size of particles and their -potentials were measured with a Malvern zetasizer nano ZS. Samples were prepared by dispersing particles in water, PBS, 0.15 M pH 4 NaCl and 0.15 M pH 10 NaCl until obtaining lightly cloudy solution (5 g/mL) and then sonicated for 30 min with shaking at regular intervals. Each sample was measured in triplicate (three independent samples from at least two batches of particles) at 25 °C. Thermogravimetric Analysis (TGA). Using TGA, the dry mass of polymer on silica nanoparticles was determined. TGA was performed in air using a TA Instruments Q500. All samples were heated from room temperature to 1000 °C at a heating rate of 10 °C/min and dried under a vacuum at room temperature prior to TGA runs. It was assumed that the mass change from 100 to 900 °C was due to the burning of the organic polymer brush coating and



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that the remainder was non-combustible silica particles. The polymer brush thickness on silica nanoparticles was then calculated according to TGA results. Determination of grafting densities on silica nanoparticles. To calculate the density of polymer brushes on SiO2, the molecular weight of polymer brushes was measured by gel permeation chromatography (GPC). Briefly, 5 mL of SiO2-PDMAEMA suspension (20 mg/mL) was added to 25 mL 10% hydrofluoric acid solution and stirred at room temperature for 4 h. Then, the solution was transferred to a 3.5 kD Spetra/Por dialysis bag, dialysed with deionized water and freeze dried afterwards. GPC measurements were carried out with an Agilent 1260 infinity system operating in dimethylformamide (DMF, HPLC grade) with 5 mM ammonium tetrafluoroborate at 50 C and equipped with refractive index detectors and variable wavelength detectors. The instrument was calibrated with linear narrow polystyrene standards in a range of 550 to 46,890 g/mol. 2 mg of PDMAEMA cleaved from silica nanoparticles was dissolved in 2 mL of DMF (HPLC grade) completely and filtered before GPC characterisation. The PDMAEMA chain density on SiO2 was found to be 0.45, 0.23, 0.16, 0.11 chain/nm2 for the full initiator density (100 %), 20 %, 10 % and 5 % initiator density, respectively. The density of brushes with 100 % concentration of initiator is close to the dense brushes achieved on flat silicon substrates in this work (0.48 chain/nm2). Thus, dense PDMAEMA brush-coated silica nanoparticles were prepared for further siRNA knockdown studies. Equation 1 was used to determine the brush thickness on silica nanoparticles

30,

where

𝑊PDMAEMA is the weight loss percentage corresponding to the decomposition of the polymer brush component, 𝑊SiO2 the residual weight percentage, PDMAEMA the mass density of the polymer brush (1.318 g cm-3), SiO2 the density of bulk SiO2 (2.4 g cm-3), and 𝑅SiO2 is the radius of SiO2 (150 nm).


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(

ℎ = 𝑅SiO2

𝑊PDMAEMASiO2 𝑊SiO2PDMAEMA

13

)

+1

― 𝑅SiO2 (1)

Equation 2 was used to determine the PDMAEMA brush density on silica nanoparticles, where 𝑊PDMAEMA is the weight loss percentage corresponding to the decomposition of PDMAEMA, 𝑊SiO2 the residual weight percentage, SiO2 the density of bulk SiO2 (2.4 g/cm3), 𝑉SiO2 the volume of SiO2 nanoparticles calculated from the average diameter of SiO2 (300 nm), 𝑁A Avogadro’s number, 𝑀n the molecular weight of PDMAEMA cleaved from SiO2, and 𝐴SiO2 is the surface area of SiO2 nanoparticles, calculated from the average diameter of the SiO2 particles used in our study (300 nm).

=

𝑊PDMAEMA SiO2𝑉SiO2𝑁A 𝑊SiO 2

𝑀n𝐴SiO2

(2)

Surface Plasmon Resonance (SPR). SPR was used to quantify interactions between nucleic acid molecules of different sizes (10 bp DNA, 15 bp DNA, 20 bp DNA, 75 bp DNA, 100 bp DNA, 20 bp RNA and 22 bp GFP-siRNA) and polymer brushes with a Biacore 3000. SPR chips were coated with polymer brushes prior to mounting on a substrate holder. Mounted chips were docked, primed with PBS, and equilibrated with PBS at 10 μL/min flow rate until a stable baseline was obtained. Then, 50 μL of nucleic acid solutions (DNA or RNA) were injected at 10 μg/mL. Once the injection was finished, washing with PBS was continued at a 10 μL/ min flow rate. The nucleic acid adsorption level was measured after washing with PBS for 1200 s. Nucleic acid adsorption studies via SPR were carried out with chips coated with PDMAEMA brushes with various thicknesses at grafting densities of 100%, 20%, 10% and 5% (referring to the ratio of initiator to ATRP-inactive molecule in the corresponding monolayers). To carry out SPR experiments with different concentrations of DNA on the same brush, a low concentration of DNA was first injected and washed with PBS for 1200s, followed by washing



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with a high ionic strength salt solution (2M NaCl) to induce the detachment of oligonucleotides. After confirming that the signal was back to the baseline level, the injection of oligonucleotides with higher concentrations was carried out. All measurements were carried out in triplicate (three separate chips freshly prepared). Transmission electron microscopy (TEM). TEM measurements were carried out using a JEOL 2010 transmission electron microscope with a LaB6 filament, operated at 200 kV. Samples were prepared by dropping the diluted brush coated silica nanoparticle suspension on a copper grid with porous carbon film and drying at room temperature. Fluorescence Microscopy. To characterize the binding of RNA from thicker polymer brushes (which thickness is such that the signal obtained for SPR is beyond the detection range), fluorescence-labelled RNA was used. Brush-coated silicon chips were incubated in 10 ng/μL of 6-FAM labelled siRNA for 10 min, then washed with PBS and water thoroughly, and dried in a steam of nitrogen. Fluorescence measurements were carried out immediately. HaCaT-GFP Cell Culture and Passage. A stable HaCaT cell line expressing EGFP-actin, generated by transfection with linearized plasmids for EGFP-actin (Clontech, Mountain View, CA) as previously described32, was used to quantify transfection efficacy. DMEM media supplied with 10% FBS, 1% penicillin-streptomycin (P/S), and 1% glutamine was used to culture HaCaT-GFP cells in a 37 °C/5% CO2 incubator. For harvesting, HaCaT cells (T75) were washed twice with pre-warmed PBS solutions and then detached from the flask by trypsinization (versene/trypsin, 4:1 v/v, 5 mL, 37 °C). 15 mL DMEM medium were then added to the flask to quench the trypsin. Cells were transferred to a 50 mL centrifuge tube and centrifuged at 1200 rpm for 5 min. After discarding the supernatant solution, the pellet was resuspended in 10 mL of FAD medium, and the concentration of cells was measured with a hematocytometer.


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Knockdown Assay with SiO2-PDMAEMA and lipofectamine. HaCaT-GFP cells were seeded at a density of 50000/ well on glass coverslips pretreated with collagen in 24-well plates 24 h prior to the transfection assay. A final siRNA concentration of 50 nM/well was used for all transfection assays described in this report. Serum-free OPTI-MEM medium was used as diluent both for the siRNA and SiO2-PDMAEMA solutions. The siRNA was then added to the SiO2-PDMAEMA solution dropwise and the resulting solution was mixed gently to afford the corresponding siRNA/SiO2-PDMAEMA complexes at N/P = 10. After removing the DMEM medium, cells were washed twice with prewarmed serum-free OPTI-MEM medium, and another 400 μL was added. Then, 100 μL of siRNA complexes were then added dropwise to each well and mixed by shaking gently. Cells were incubated with siRNA complexes for 4 h in the incubator, and the medium was then replaced by 500 μL of normal DMEM medium for a further 24 h of incubation. Lipofectamine 2000 (Thermo Fisher) complexed with GFP siRNA/negative control (NC) siRNA (protocol according to the manufacturer’s instruction with a final siRNA concentration of 50 nM/ well) was used as a positive/negative control. The transfected cells were washed with PBS three times, fixed in paraformaldehyde (PFA, 4%, 10 min), and permeabilized with Triton X-100 (0.2%, 5 min). Cells were then stained with TRITCphalloidin (1:1000) and 4,6-diamidino-2-phenylindole (DAPI, 1:1000) in blocking buffer (10% FBS and 0.25% gelatin from cold water fish skin, Sigma-Aldrich) and kept at room temperature for 1 h. Coverslips with fixed cells were mounted on glass slides before imaging with a Leica DMI4000 fluorescence microscope. Statistics. Data are reported as averages ± standard deviation for groups of at least three replicates. An unpaired two-tailed Student’s t test was used for assessing statistical significance (*p < 0.05, **p < 0.01, ***p < 0.001).



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Results and Discussion Controlled Polymer Brush Growth at Different Grafting Densities. The ATRP polymerisation of PDMAEMA brushes was first investigated to confirm the control of brush growth on both silicon and gold substrates. The kinetics of the polymerization was monitored by measuring the dry brush thickness via ellipsometry (Figure 2A and S1). The polymerization rate, which can be controlled by varying the monomer concentration, the ratio of Cu(I) to Cu(II) complexes, the nature of the ligands, and solvent composition was selected based on previous work30. We found that a ratio of ethanol/water of 3/2 (v/v) resulted in a relatively controlled rate of polymerization within the time range tested, with a linear increase in dry brush thickness. A minor initial jump at early time points is typically observed for polymer brushes grown in aqueous conditions30,

33,

and thought to be associated with some early chain

recombination. The grafting density of brushes can be manipulated relatively readily by using a nonreactive analogue (trimethoxy(propyl)silane for silicone substrates and 1-undecanethiol for gold substrates). This resulted in a steady reduction in brush thickness at all time points and a gradual reduction in the slope of increase in dry thickness as a function of time (Figure 2A). We then selected polymerization times that ensured that the dry thickness of polymer brushes was kept constant (10 nm), whilst grafting densities were varied. We compared these sparse brushes to the equivalent brushes grown for the same time from 100 % ATRP initiator monolayers. The densities of the PDMAEMA brushes generated was calculated according to the equation:

=

ℎdryDMAEMA𝑁A 𝑀n

(3)


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where ℎdry is the dry thickness of the brushes, DMAEMA the density of DMAEMA (1.318 g/cm3), 𝑁A Avogadro’s number, and 𝑀n is the molecular weight of the tethered polymer chains, as determined by GPC. A density for brushes with full initiator density (100 %) of 0.48 chains/nm2 was calculated, which is consistent with the previously reported density of 0.50 chains/ nm2 for PDMAEMA in similar conditions30. For lower grafting density brushes, we calculated chain densities of 0.28, 0.20 and 0.12 chains/nm2 for brushes grown from 20, 10 and 5 % initiator monolayers, respectively. Hence we achieved a 4-fold reduction in brush grafting density. Table 1 gathers characterisation of the different brushes that will be studied in the rest of this manuscript, as well as the nomenclature used in figures. The solution morphology of PDMAEMA brushes of various thicknesses and densities was probed by ellipsometry to further study and confirm their impact on the pH-responsiveness of these brushes (Figure 2B). Changes in the ellipsometric thickness of brushes were first measured in air, then deionised water, in a 0.15 M NaCl solution, in PBS, in pH 4 and 10 solutions of 0.15 M NaCl and finally after drying. In deionized water, brush swelling increased to 2.4-4.8 depending on the density. Whereas swelling ratios (swollen height/dry height) very moderately decreased (from 2.4 to 2.1) as the brush thickness increased, the swelling ratio was particularly sensitive to the grafting density. This is in good agreement with the Alexander-de Gennes theory and the swelling behavior of neutral and polyelectrolyte brushes34, 35, expected to vary as a function of grafting density with an exponent in the range of 0.5-0.66, depending on the monomer charge, degree of dissociation (for a weak polyelectrolyte) and bulkiness36-38. This is in very good agreement with the trends observed in our results (exponents in the range of 0.499 and 0.527 – plots not shown). Therefore, the increased length of individual polymer chains required to generate sparse brushes displaying identical thicknesses to those generated from 100 % initiator density would be expected to lead to increased swelling ratios. Indeed, if polymer brushes are grown for identical times via a controlled radical polymerization process, 15 ACS Paragon Plus Environment


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the degree of polymerization achieved should be comparable, regardless of their starting grafting density. Brush swelling further increased in PBS and when the pH was reduced to 4.0. Upon switching to alkaline solutions (pH = 10.0), brushes collapsed. However, this collapse was dependent on brush thickness. Whereas thin brushes of all grafting densities fully collapsed back to their dry thickness at pH 10.0, thicker brushes at 100 % initiator density only partially collapsed (but we confirmed that they fully collapsed when dried again). This indicates that collapse of thick brushes is not homogenous, possibly resulting in a hydrophobic shell in the upper brush compartment that prevents further diffusion of water molecules and protons, therefore preventing the full collapse of PDMAEMA brushes at a pH where polymer chains should be fully deprotonated. A similar behavior was observed in the case of poly(2(diethylamino)ethyl methacrylate)39 and the confinement of phase separation was perhaps best evidenced in the case of temperature sensitive poly(di(ethyleneglycol) methyl ether methacrylate)40. Overall, our results are in excellent agreement with the proposed control of the polymer brush thickness and grafting density. In addition, the marked differences in swelling behaviors observed suggested that molecular infiltration could be sensitive to the brush characteristic thickness and grafting density. Oligonucleotide Adsorption to PDMAEMA Brushes. The interaction of oligonculeotides (double-stranded DNA and RNA) with PDMAEMA brushes was quantified via surface plasmon resonance (SPR). We first studied the impact of the oligonucleotide size (double stranded DNA in the range of 10-100 bp) and type (20 bp double stranded RNA with identical sequence as the 20 bp DNA, except for uracils instead of thymines) on binding to 10 nm full density (100 % initiator; 0.48 chains/nm2) PDMAEMA brushes (Figure 3A). Upon exposure to oligonucleotide solutions, adsorption to the brush surface increased in all cases, reaching a plateau near (7000 RU, corresponding to 700 ng/cm2). The level of binding was not significantly altered by the size of the oligonucleotide, but 20 bp RNA was found to adsorb at 16 ACS Paragon Plus Environment

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a level of 13,800 RU, a 2-fold increase compared to the DNA probes tested. Although it is not clear why RNAs adsorbs significantly more than DNA molecules of similar sizes, this observation is in agreement with our previous report30. This effect could be due to the difference in nucleobase composition between the two types of oligonucleotides, and the presence of an additional hydroxyl on nucleotides of the RNA molecules. Although the maximum binding level was insensitive to DNA size, there was a clear trend in their rate of adsorption, with larger oligonucleotides adsorbing at slower rates. In addition, the shorter 10 bp DNA displayed a fast saturation of the surface and some level of desorption upon exposure to PBS, indicating that equilibrium saturation of brush binding sites have been reached for these short oligonucleotides. With increasing polymer brush thicknesses, the level of adsorption of all oligonucleotides generally increased, indicating that the ultimate surface density of oligonucleotides is regulated by the surface density of cationic moieties (Figures 3 and S2). In the case of 20 bp RNA, this resulted in a surface density of 2,900 ng/cm2, for a 29 nm brush, again a two-fold increase compared to DNA molecules. At higher brush thicknesses, the adsorption kinetics was also more clearly affected by the size of the oligonucleotides, resulting in sub-saturation surface densities and an apparent decrease in the ultimate binding density as the molecular weight of DNA molecules increased (Figure 3B and 4). However, it was clear that adsorption had not reached a plateau for the largest DNA probes. The impact of polymer brush grafting density on oligonucleotide adsorption was next examined. Strikingly, the adsorption level of oligonucleotides was reduced as the grafting density of brushes decreased (Figures 3C and S2), but also became insensitive to the size of DNA molecules (for example, comparing 11 nm 0.48 chain/nm2 brushes to 9 nm 0.12 chain/nm2 chains). The kinetics of adsorption also gradually became less sensitive to molecular size (or at least, this could not be resolved in this experimental set up). Finally, the adsorption 17 ACS Paragon Plus Environment


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of 20 bp RNA followed a similar trend (reduced from 1380 ng/cm2 at for 0.48 chain/nm2 brushes to 960 ng/cm2 for 0.12 chain/nm2 brushes), although retaining a 2-fold increase compared to DNA molecules of similar size (20 bp). Overall, these results indicate that oligonucleotides can complex the surface and infiltrate cationic polymer brushes, irrespective of their size. However molecular diffusion through the brush presumably restricts absorption and is sensitive to oligonucleotide size, conformational freedom and brush grafting density (Figure 4). Experimental and theoretical work had previously identified that, in order for molecular diffusion to occur within polymer brushes (in the case of weakly interacting molecules and brushes), the size of molecules (specifically, their radius of gyration) should be small compared to the dimensions of the brush (equivalent radius of gyration, determined by their thickness and grafting density)41-44. Therefore, it is well established that weakly attracted large macromolecules poorly infiltrate dense polymer brushes. However, for stronger brushmolecule interactions, adsorption to the brush surface will occur regardless of the grafting density44. This may result in adsorption restricted at the brush-solution interface. However, if free molecules (and brushes) display sufficient conformational freedom, deeper infiltration may occur, although restricted, aided by the formation of hairpin inclusions45. Therefore, our observation of substantial molecular diffusion of strongly interacting oligonucleotides within cationic polymer brushes is in good agreement with these molecular dynamics simulations. We also observe that the level of adsorption of oligonucleotides to polymer brushes is regulated by the strength of complexation between the oppositely charged polyelectrolytes, resulting in saturation levels insensitive to molecular size, providing complexation strength is comparable. This suggests that the complexation strength and therefore the binding energy associated with the capture of RNA molecules is higher than for DNA. We next quantified the adsorption of oligonucleotides at the surface of thicker brushes (35-59 nm, 100 % initiator density), to investigate whether infiltration would be limited in this range 18 ACS Paragon Plus Environment

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of brush dimensions. However, at such high dry thicknesses (35-59 nm), SPR measurements indicated a gradual reduction in oligonucleotide uptake, compared to 29 nm brushes (Figure S3A). This is likely to be due to the high swelling of corresponding brushes, extending beyond the limit of detection range of the SPR (150 nm; RU levels were close to saturation in these cases)46, therefore making detection of oligonucleotide binding in this range inaccurate. To address this issue, we used a tagged RNA probe and monitored its adsorption to thick polymer brushes via fluorescence microscopy (Figure S3B). Upon exposure to 10 ng/μL of taggedRNA, the fluorescence intensity at the brush surface, after washing with PBS, gradually increased by a factor of 1.69 (for 59 nm brushes, compared to 29 nm brushes). This has to be compared to the 2.1 factor measured when increasing the brush thickness from 10 to 29 nm, indicating relatively substantial infiltration of oligonucleotides within thick brush (comparable to thinner brushes). Therefore, our results indicate that oligonucleotides infiltrate well within cationic polymer brushes, despite their expected complexation, the associated local collapse and impaired molecular diffusion. Development of a Kinetics Model of Oligonucleotide Absorption within Polymer Brushes. To gain further insight into the parameters controlling oligonucleotide absorption and the strength of their binding, we monitored binding at different concentrations of oligonucleotides, via SPR (Figures 5 and S4). In order to carry out adsorption kinetics on the same brush at different oligonucleotide concentrations, brushes were regenerated by washing with 2M NaCl solutions, and injections were carried out starting with the lowest concentrations of oligonucleotides (0.520 ng/μL; Figure S5). We confirmed that the regeneration process completely desorbed oligonucleotides and that subsequent exposure to a freshly prepared oligonucleotide solution led to comparable (within error) levels of adsorption. In all cases, except for the absorption of 100 bp DNA to dense brushes (0.48 chains/nm2) with a thickness of 29 nm, loading saturation was reached at high concentrations of oligonucleotides. The rate of absorption systematically 19 ACS Paragon Plus Environment


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increased with the oligonucleotide concentration and very little desorption was observed upon washing substrates with PBS. Therefore, this indicates a high binding affinity of oligonucelotides for PDMAEMA brushes in the conditions tested, as binding affinities in the range of mM-1 to M-1 typically lead to fast desorption kinetics47. This is presumably due to the high charge, and therefore binding site, density resulting in strong desorption re-adsorption effects, as in the capture of histidine-tagged proteins by nitrilotriacetic acid (NTA)functionalised brushes48. The only exception to this behavior was for 10 bp DNA molecules, which showed significant desorption at 10 and 20 ng/μL, and for 20 bp RNA molecules (although the binding level was significantly higher overall). In order to quantify some of the parameters controlling the absorption of oligonucleotides to polymer brushes, we developed a simple kinetics model based on a two-stage process, adapting a previously reported model of polyelectrolyte adsorption49. In the present model, a first reversible adsorption equilibrium allows oligonucleotides to bind to the surface of polymer brushes, prior to their subsequent diffusion within the core of the brush (Figure 6). Therefore, this models differs from previous adsorption models of protein binding to surfaces (typically used to model SPR data) and of polyelectrolyte adsorption to charged interfaces by assuming a fast exchange between bulk and surface free molecules (therefore ignoring the initial free diffusion step) and by introducing an infiltration step modelled by the diffusion of oligonucleotides within the brush. The rate of adsorption of oligonucleotides at the surface of the brush is determined by: 𝑑Γ 𝑑𝑡

= 𝑘𝑎𝐶𝑆[𝐵𝑟] ― 𝑘𝑑𝐶𝐵𝑂

(4)

where Γ is the mass of molecules adsorbed per surface area, 𝑘𝑎 and 𝑘𝑑 are the surface adsorption and desorption rate constants, 𝐶𝑆 is the solution concentration of oligonucleotides (which is assumed to be equal to the sub-surface concentration of oligonucleotides), 𝐶𝐵𝑂 is the surface 20 ACS Paragon Plus Environment

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concentration of oligonucleotides in the outer brush layer and [Br] is the surface concentration of free (not occupied by oligonucleotides) binding sites on the brush. Hence the change in surface-bound mass is solely determined by the rates of adsorption and desorption of oligonucleotides. A full description of the mathematical development of the model can be found in the Supplementary Information. Assuming a steady state between surface adsorption from the bulk solution and infiltration through the brush, we can derive the following profile of adsorption, after integration: Γ = Γ𝑚𝑎𝑥(1 ― 𝑒 ― 𝑘𝑎𝑝𝑝𝑡)

(5)

where Γ𝑚𝑎𝑥 and 𝑘𝑎𝑝𝑝 are the maximum surface density of oligonucleotide, at saturation, and an apparent rate constant, respectively (see the Supplementary Information for the full expression of these constants). It follows that the binding affinity Ka (defined by 𝐾𝑎 =

𝑘𝑎

) and the binding

𝑘𝑑

factor  can be derived from the following equation, by plotting the corresponding evolution of 1/Γ𝑚𝑎𝑥 as a function of 1/𝐶𝑆. The binding factor  defines the number of oligonucleotides 𝐵𝑟 of molecular weight 𝑀𝑂𝑁 𝑛 that can be bound per polymer brush chain of molecular weight 𝑀𝑛 , 𝑀𝐵𝑟 𝑛

as 𝛼 𝑀𝑂𝑁. 𝑛

1

Γ𝑚𝑎𝑥 =

𝛼 𝑀𝑂𝑁 𝑛 ℎ𝜌

+

𝛼 𝑀𝑂𝑁 1 1 𝑛 ℎ 𝜌 𝐾𝑎𝐶𝑆

(6)

where 𝑀𝑂𝑁 𝑛 is the molecular weight of oligonucleotides, ℎ the dry height of polymer brush and 𝜌 the dry density of the polymer brush. For each absorption trace, we extracted the saturation surface density Γ𝑚𝑎𝑥 and plotted against the oligonucleotide solution concentration, according to equation 6 (Figure 7A-C), enabling us to extract the associated affinity constant Ka and binding factor  (Figure 7D). In most cases, linear regressions for the entire data set (for concentrations of oligonucleotides) gave good fits, 21 ACS Paragon Plus Environment


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except for 20 bp DNA adsorbing to sparse brushes. Such behavior is due to the steady state assumption made in our model, which fails as brushes are reaching saturation. In these cases, we retained the data points for which saturation was not reached (at lower concentration of oligonucleotide). Analysis of our kinetics data (Figure 7D) indicated that Ka decreased with increasing size of DNA molecules, with constants in the 106-107 M-1 range, slightly below the range typically observed for antibody-antigen interactions, but above many protein-protein and proteinpolysaccharide affinities. Ka was sensitive to the brush height, decreasing for thicker brushes, and decreased significantly for 20 bp RNA. The grafting density had a bimodal impact on Ka, indicating that affinities are maximised at intermediate grafting densities, in which polymer chains may offer an optimal spacing for the stable binding of oligonucleotides. In contrast, the binding factor  was insensitive to the thickness of brushes and increased at lower grafting density, indicating that the stoichiometry of association (balance of positive to negative charges) was increased at lower grafting densities (more amines were needed to stabilise each phosphate group). In addition, although the size of DNA molecules had a moderate impact on , the binding of 20 bp RNA was associated with a significantly reduced binding factor (0.37±0.23). This indicates that the number of positively charged amines required to stabilise RNA molecules was significantly reduced, close to stoichiometry. Overall, our results indicate that dense polymer brushes are able to stabilise oligonucleotides with a lower amine/phosphate ratio than sparse brushes, leading to higher loading levels. In addition, this stoichiometry is further improved for the binding of double stranded RNA molecules. Considering the similar charge densities and conformations of double stranded DNA and RNA molecules, it is therefore likely that uracils are better stabilised by amine residues on PDMAEMA chains than thymines, or that the additional hydroxyl found on RNA molecules significantly contributes to their stabilisation by PDMAEMA chains. However, this reduction in the number of amine 22 ACS Paragon Plus Environment

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moieties stabilising each base pair is also associated with a reduction in the overall affinity constant of the brush and associated kinetics of adsorption and desorption. This is therefore likely to alter the dynamics of oligonucleotides within the brush and their rates of loading and, importantly, release. However, we note that our model does not allow a full derivation of the rate constants associated with oligonucleotide adsorption and infiltration (and their desorption). Therefore, the kinetics analysis it provides remains qualitative, although it allows quantification of equilibrium parameters (affinity constant and binding factor). Synthesis and Characterization of PDMAEMA Brush-Coated Silica Nanoparticles. The high binding capacity (low binding factor) measured for RNA molecules adsorbing to PDMAEMA brushes suggested their use for siRNA delivery and the regulation of gene expression. Indeed, such behavior would ensure the high loading of vectors with RNA molecules and their stable retention to promote specific cytosolic delivery. To explore the impact of polymer brush thickness on transfection efficiency, we generated a series of polymer brush-coated silica nanoparticles, with controlled PDMAEMA brush shell thickness. The thickness of the resulting polymer brush coatings was characterised by transmission electron microscope (TEM, Figure S6). A layer of organic coating was clearly observed surrounding the silica core and its thickness increased with polymerization time. In addition, the thickness of this shell remained relatively constant for brushes grown from different densities of ATRP initiator monolayers, for which the polymerization time had been adjusted to achieve comparable dry brush thicknesses (see Figure 2A). In addition, thermogravimetric analysis (TGA) confirmed the increase in brush thickness with increasing polymerization time and the preserved brush thickness at different grafting densities (Figure S7 and Table 2), in excellent agreement with TEM data and the ellipsometry data obtained for flat interfaces. Based on the difference in weight loss between initiator-coated and bare silica particles (3 wt% at 800 °C), the density of the ATRP initiator immobilized on nanoparticles was estimated to be 23 ACS Paragon Plus Environment


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7.08 initiator/nm2 29. This value agrees with those reported in the literature for silica particles of similar diameters (300 nm)29. Considering that the surface hydroxyl density of silica is ∼5 OH/nm2 37, a dense initiator layer was successfully deposited on silica particles. Finally, the increase in molecular weight of polymer brushes observed at increasing polymerization times (for decreasing grafting densities of initiators) was confirmed by size exclusion chromatography, after cleavage of brushes (Figure S8). The solution behavior of the resulting polymer brush-coated nanoparticles was characterized by dynamic light scattering and electrophoretic light scattering (Figure S9). A clear increase in hydrodynamic diameter was observed with an increase in polymerization time, in all conditions, confirming the control of the polymer brush thickness. In all cases, the -potential of the corresponding nanoparticles was found to be positive (> 20 mV), in agreement with the literature30. In addition, similarly to what was measured on flat surfaces by in situ ellipsometry (Figure 2B), we measured a systematic increase in hydrodynamic diameter when increasing the ionic strength of the medium and at low pH. In contrast, when the pH was increased to 10, the brush collapsed, consistent with their neutralization, and the zeta potential was reduced. The hydrodynamic diameter of nanoparticles with polymer brushes grafted at low densities also increased with lower initiator densities, consistent with the increased polymerization time and therefore chain molecular weight that was necessary to achieve comparable dry polymer brush thicknesses (this is also consistent with the in situ ellipsometry data in Figure 2B). Overall, our data confirms the excellent control of the polymer brush thickness and grafting density from silica nanoparticles, with comparable characteristics and solution behavior to brushes generated from flat substrates and used to study oligonucleotide interactions. Impact of Polymer Brush Thickness and Grafting Density on Knockdown Efficiency. We next quantified the impact of brush thickness and grafting density on knockdown efficiency. A keratinocyte cell line expressing actin-GFP was selected for the accurate quantification of 24 ACS Paragon Plus Environment

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knockdown efficiency, allowing simultaneous imaging of endogenous and GFP-tagged actin after phalloidin staining. Knockdown levels were determined for an N/P ratio of 10 for all vectors, previously identified as optimal for PDMAEMA brush vectors30, and compared to lipofectamine 2000, as positive control. Following transfection with a GFP-siRNA, the ratio of fluorescence intensities of GFP-actin (green)/phalloidin (red) was measured and compared with the ratio of non-transfected cells to determine the knockdown efficiency. Importantly, in all experiments, the total amount of RNA transfected was kept constant. Therefore, as the polymer brush thickness was increased, the total number of particles was reduced (since the N/P ratio was kept constant). With increasing brush thicknesses, a clear gradual increase in knock down efficiencies can be observed (Figures 8 and S10). Cells transfected with the thickest PDMAEMA brush decorated particles (29 nm brushes) displayed stress fibers constituted of endogenous actin, as observed on control non transfected cells and those transfected with a non-targeting RNA sequence, but the level of GFP-actin expressed was significantly reduced (to similar levels to cells transfected with lipofectamine 2000). In contrast, reducing the grafting density of brushes induced a strong reduction in transfection efficiencies, down to levels comparable with the negative control and non-transfected cells. Hence our results clearly demonstrate that the thickness of polymer brushes and their grafting density have a significant impact on transfection efficiencies and suggest that decreasing the binding factor associated with a brush coating, and therefore increasing the binding factor  and associated total loading level that can be achieved, should improve transfection efficiencies, irrespective of binding affinities (Ka).



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Conclusion Overall, this study clearly demonstrates the striking impact of brush grafting density and thickness on the absorption profile of oligonucleotides. Small oligonucleotides infiltrate relatively rapidly polymer brushes of all grafting densities but with a relatively low binding affinity and moderate binding factor (and loading level). This contrast with the infiltration of larger oligonucleotides, hindered by high density brushes, and displaying reduced loading levels, although with higher affinities. Remarkably, double stranded RNA molecules of identical size and composition as DNA molecules (apart from their difference in base type and hydroxylation) bound to dense brushes at significantly higher levels and with reduced binding affinities. Such observations correlate well with the performance of dense and thick PDMAEMA brushes for siRNA transfection and associated knock down efficiency. Therefore, this work and the adsorption model it proposes constitute an important milestone for the rational design of polymer brush-based vectors for RNA delivery. However, several important questions remain to be answered. Indeed, the origin of the dense loading of RNA compared to DNA is not clear. The impact of subtle changes in brush chemical structure on RNA loading and binding affinity are also unexplored, yet may significantly impact transfection efficiencies. In addition, the ability to design polymer brushes with more complex structures, such as block copolymers, may further alter the adsorption dynamics and release kinetics of associated vectors, potentially allowing to confer additional properties (such as reduced cytotoxicity and cell targeting). Finally, the mechanism of desorption of RNA molecules within the cell cytoplasm remains unclear. Indeed, RNA should remain particularly strongly bound to polymer brushes at cytoplasmic and endosomal pH and must be regulated by other processes.


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Supporting Information. Additional ellipsometry data, kinetics of absorption of oligonucleotides monitored by SPR, characterisation of RNA absorption within thick brushes by fluorescence microscopy, quantification of brush regeneration by SPR, TEM characterisation of brushes grown from nanoparticles, thermogravimetric analysis, size exclusion chromatography, dynamic light scattering and electrophoretic light scattering and additional fluorescence microscopy of transfected cells.

Acknowledgement. We thank the Nanovison Centre at Queen Mary, University of London for assisting with the TEM images in this article. Fengjin Qu thanks the funding from the China Scholarship Council (No. 201706290160), and the support by the National Natural Science Foundation of China (No: 51772248).



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Figure 1. The independent design of polymer brushes structure and chemistry.


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Figure 2. (A) Dry ellipsometric thickness of PDMAEMA brushes grown from silicon substrates with silane monolayers with different densities of ATRP initiators (5, 10, 20 and 100 %). (B) Evolution of the ellipsometric thickness of PDMAEMA brushes on silicon wafers in dry conditions and in different aqueous solutions.



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Table 1. Characterisation of PDMAEMA brushes Name 100%-10 nm 100%-14 nm 100%-19 nm 100%-29 nm 20%-10 nm 10%-10 nm

Polymerisation time (min)

10 15 22 39 15 22 39

Initiator density (%) 100%

Brush densitya (chain/nm2) 0.48±0.01

Dry thickness (nm)b 10.8±0.2

Thickness at pH 4 (nm)c 35.8±0.4

100%

0.48±0.01

14.0±0.9

45.5±0.3

100%

0.48±0.01

18.6±0.4

58.8±1.4

100%

0.48±0.01

28.7±0.3

85.8±1.0

20%

0.28±0.01

9.3±0.2

46.3±1.8

10%

0.21±0.01

9.5±0.3

53.6±1.9

5%-10 nm 5% 0.12±0.01 9.1±0.4 78.5±2.7 a Calculated from equation 3. b, c Dry and swollen thicknesses (at pH 4.0). Averages of at least three replicates measured by (in situ) ellipsometry, with standard deviations.


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Figure 3. Interaction between 10 ng/μL of oligonucleotides (10, 15, 20, 75, 100 bp DNA and 20 bp RNA) and PDMAEMA brushes monitored by SPR. SPR traces recorded for (A) 100%-10 nm, (B) 100%-29 nm and (C) 10%-10 nm PDMAEMA brushes. Step1: exposure to oligonucleotide solution in the running buffer (PBS). Step 2: exposure to the running buffer.



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Figure 4. Schematic illustration of nucleic acid molecules interacting with different PDMAEMA brushes (chain length and grafting density).


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Figure 5. Adsorption/desorption kinetics of nucleic acid on PDMAEMA brushes. SPR traces of different concentrations (0.5-20 ng/L) of 20 bp DNA interacted with (A) 100%-10 nm, (B) 100%-29 nm and (C) 10%-10 nm PDMAEMA brushes. Step1: exposure to a certain concentration of DNA solution in a running buffer (PBS). Step 2: exposure to a running buffer.



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Figure 6. Model of adsorption kinetics of oligonucleotides to polymer brushes.


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Figure 7. Relationship between 1/Γ𝑚𝑎𝑥 and 1/C𝑠 for 20 bp DNA absorbing within polymer brushes with different thicknesses (A) and grafting densities (B), and (C) for different oligonucleotides absorbing on a 100 % initiator (0.48 chain/nm2) 29 nm PDMAEMA brush. (D) Corresponding extracted 𝐾𝑎 and 𝛼.



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Figure 8. Impact of PDMAEMA brush thickness on knockdown efficiency of GFP siRNA in HaCaTactin-GFP cells. (A) Fluorescence microscopy images (scale bars, 50 μm). (B) Corresponding quantification.


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Table 2. PDMAEMA Content and Dry Thickness on Silica Nanoparticles SiO2 (w %) 95

Initiator (w %) 0

PDMAEMA (w %) 0

Dry thickness (nm)a 0

SiO2-initiator

92

3

0

0

SiO2-PDMAEMA-5%-10 nm

85

3

7

7


85

3

7

7


84

3

8

8


83

3

9

9


80

3

12

13


76

3

16

17


68

3

24

27

Sample bare SiO2

SiO2-PDMAEMA-100%-35 nm 64 3 28 32 a Calculated on the basis of TGA weight loss with reference to initiator-coated silica nanoparticles. Thicknesses in the sample names correspond to dry thicknesses of brushes grown in identical conditions from flat silicon substrates.



Figure 2

ACS Paragon Plus Environment

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Figure 7



Figure 8


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Figure 3



Figure 5


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Biomacromolecules

A

Kinetic

Model

of

Oligonucleotide-Brush

Interactions for the Rational Design of Gene Delivery Vectors

Fengjin Qu∥,†,§, Danyang Li†,§, Xiaoyan Ma∥, Fang Chen∥, Julien Gautrot*,†,§

∥Department of Applied Chemistry, School of Natural and Applied Sciences, Northwestern Polytechnical University, Xi’an 710072, PR China.

†Institute of Bioengineering and §School of Engineering and Materials Science, Queen Mary University of London, Mile End Road, London E1 4NS, United Kingdom.

TOC Figure

Design of polymer brushes

Kinetic model of oligonucleotidebrush interactions

Effective gene delivery


A Kinetic Model of Oligonucleotide-Brush Interactions for the Rational

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