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Modulating Phagocytic Cell Sequestration by Tailoring Nanoconstruct Softness Roberto Palomba, Anna Lisa Palange, Ilaria Francesca Rizzuti, Miguel Ferreira, Antonio Cervadoro, Maria Grazia Barbato, Claudio Canale, and Paolo Decuzzi ACS Nano, Just Accepted Manuscript • DOI: 10.1021/acsnano.7b07797 • Publication Date (Web): 09 Jan 2018 Downloaded from http://pubs.acs.org on January 10, 2018
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Modulating Phagocytic Cell Sequestration by Tailoring Nanoconstruct Softness
Roberto Palomba1, Anna Lisa Palange1, Ilaria Francesca Rizzuti1, Miguel Ferreira1, Antonio Cervadoro2, Maria Grazia Barbato1, Claudio Canale3, Paolo Decuzzi1,♣
1
Laboratory of Nanotechnology for Precision Medicine, Fondazione Istituto Italiano di Tecnologia, Via Morego 30, Genoa 16163, Italy 2
3
♣
NEST, Scuola Normale Superiore di Pisa, Piazza San Silvestro, 12, 56126Pisa, Italy
Nanophysics, Fondazione Istituto Italiano di Tecnologia, Via Morego 30, Genoa 16163, Italy
To whom correspondence should be addressed: Paolo Decuzzi, PhD. Phone: +39 010 71781 941, Fax: +39 010
71781 228, E-mail:
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ABSTRACT The effect of nanoparticle size, shape and surface properties on cellular uptake has been extensively investigated for its basic science and translational implications. Recently, softness is emerging as a design parameter for modulating the interaction of nanoparticles with cells and the biological microenvironment. Here, circular, quadrangular and elliptical polymeric nanoconstructs of different sizes are realized with a Young’s modulus ranging from ∼ 100 kPa (soft) to 10 MPa (rigid). The interaction of these nanoconstructs with professional phagocytic cells is assessed via confocal microscopy and flow cytometry analyses. Regardless of the size and shape, softer nanoconstructs evade up to 5 times more efficiently cellular uptake, by bone marrow derived monocytes, as compared to rigid nanoconstructs. Soft circular and quadrangular nanoconstructs are equally uptaken by professional phagocytic cells (< 15%), soft elliptical particles are more avidly internalized (< 60%) possibly because of the larger size and elongated shape, whilst over 70% of rigid nanoconstructs of any shape and size are uptaken. Inhibition of actin polymerization via cytochalasin D reduces internalization propensity for all nanoconstruct types. High-resolution live cell microscopy documents that soft nanoconstructs mostly establish short-lived (< 30 sec) interactions with macrophages thus diminishing the likelihood of recognition and internalization. The bending stiffness is identified as a discriminating factor for internalization, whereby particles with a bending stiffness slightly higher than cells would more efficiently oppose internalization as compared to stiffer or softer particles. These results confirm that softness is a key parameter in modulating the behavior of nanoparticles and are expected to inspire the design of more efficient nanoconstructs for drug delivery, biomedical imaging and immunomodulatory therapies.
KEYWORDS: nanoparticle • internalization • deformability • immune cells • rational design
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Nanoparticles are being increasingly used for the systemic delivery of therapeutic molecules and imaging agents in cancer, cardiovascular, inflammatory and neurological diseases.1-3 Following intravascular administration, nanoparticles are transported by the blood flow and can virtually reach any vascular districts within the host. Such blood-borne nanoparticles exploit different biophysical and biochemical cues to recognize abnormal tissues and progressively deposit thereof, including the expression of specific vascular or extravascular cell receptors and the hyper-permeability of inflamed vascular beds.4-6 Generally, these cues are sufficient to enhance nanoparticle accumulation at the target site, as compared to freely administered small molecules.7-9 However, this unique ability of ‘sensing’ and exploiting vascular and tissue abnormalities is counteracted by the presence of professional phagocytic cells, which tend to clear any foreign objects, including blood-borne nanoparticles, from the circulation. This mostly happens in filtering organs where nanoparticles tend to be directly exposed to the hepatic Kupffer cells, splenic and pulmonary intravascular macrophages.10, 11 As a consequence, the majority of systemically injected nanoparticles still tend to accumulate within such filtering organs, thus reducing the percentage of therapeutic cargo successfully lodging within the diseased tissue.
The size, shape and surface properties of nanoparticles have been modified in order to modulate recognition and subsequent internalization by phagocytic cells. Upon injection into the bloodstream, the surface of nanoparticles is coated by a multitude of different molecules, generally known as opsonins.10, 12 These blood molecules adsorb on the nanoparticle surface and mediate the recognition, and subsequent sequestration by immune system cells. In order to improve nanoparticle camouflage, the most commonly used strategy still relies on decorating the surfaces with synthetic and natural polymeric chains. These are either adsorbed or grafted on the surface of nanoparticles and are supposed to limit the adsorption of opsonins and generate sufficient repulsive colloidal forces against the
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phagocytes’ membrane. These polymers include polyethylene glycol (PEG) or PEG-containing copolymer chains13, 14, hyaluronic acid (HA)15, 16, and others.17 Surface decoration is known to affect cell uptake depending on the density and length of these polymeric chains. Notably, the effectiveness of this camouflage tends to reduce with time as the surface decoration deteriorates and the polymeric chains fall off.
Alternative strategies have been focusing on changing the geometrical properties of nanoparticles. Among the first, the group of Chan performed a systematic analysis on the cell uptake of gold nanoparticles with different sizes and shapes.18 On HeLa cells, it was demonstrated that, for spherical nanoparticles, there is a critical diameter that would maximize the rate of internalization; whereas rodshaped nanoparticles are less efficiently uptaken as compared to spherical presenting the same characteristic size. These observations were further confirmed and extended by DeSimone’s group who reported that rod-like particles resist internalization more than spherical over a wide size range, spanning from a few to several hundreds of nanometers.19 At the micrometer scale, the seminal work of Mitragotri and collaborators on rat and mouse macrophages quantitatively demonstrated that elongated particles pointing with their major axis at the cell membrane are more rapidly uptaken than those laying along the major axis on the cell membrane.20 Similar conclusions were derived for endothelial cells exposed to discoidal mesoporous silicon microparticles.21
More recently, the capacity of polymeric nanoconstructs to deform (softness) is emerging as an additional parameter to fine tune and modulate their behavior. The authors and others have shown that soft nano- and micro-particles can circulate longer and more efficiently accumulate into hyperpermeable and tortuous vasculatures.22-24 However, at authors’ knowledge, no comprehensive analysis has been performed on the effect of particles softness on macrophage internalization. In this
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work, discoidal polymeric nanoconstructs (DPNs) with various shapes, including circular, elliptical and quadrangular; characteristic sizes, ranging from 1,000 to 2,000 nm; and Young’s modulus, varying from 100 kPa to 10 MPa; are realized and incubated with phagocytic cells. A mouse macrophage cell line and primary rat bone marrow-derived monocytes are considered. After characterizing the physical properties of DPNs via optical, electron and atomic force microscopies, the propensity towards cellular uptake is quantitatively analyzed as a function of their geometry and mechanical properties.
RESULTS/DISCUSSION Synthesis of Discoidal Polymeric Nanoconstructs. Discoidal Polymeric Nanoconstructs (DPNs) with different characteristic sizes, ranging between 1,000 and 2,000 nm; shapes, including circular, quadrangular and elliptical; and softness, with a Young’s modulus varying from about 100 kPa up to 10 MPa; were synthesized following a top-down fabrication process. This is schematically shown in Figure.1a and results from the combination of lithographic techniques, replica molding and polymer chemistry.22, 25 First, a master template made out of silicon was fabricated using a direct laser writing lithographic technique (DLW), which allowed to scribe rapidly and accurately multiple arrays of discoidal wells with circular, elliptical or quadrangular bases. Then, this geometrical pattern was precisely replicated into an intermediate template, made out of polydimethylsiloxane (PDMS), and subsequently into a sacrificial template of poly(vinyl alcohol) (PVA). A polymeric mixture, containing the constituting ingredients of the final discoidal nanoconstructs, was spread over the sacrificial template (PVA) carefully filling up the wells while avoiding the formation of a superficial ‘backing’ layer (Figure.1a). Sacrificial templates with differently shaped wells and filled with a mixture of poly(lactic acid-co-glycolic acid) (PLGA), poly(ethylene glycol) diacrylate (PEG-DA) and lipidRhodamine B (lipid-RhB) are shown in Figure.1b. On the top rows, nanoconstructs (red, lipid-RhB) appear orderly dispersed within PVA templates (purple, colored PVA template by distributed Cy5 dye
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molecules); on the lower rows, two separate images for the PVA template and the nanoconstructs are provided. After exposing the filled PVA templates to UV light for crosslinking the PEG-DA chains, DPNs were released in water upon continuous dissolution of the sacrificial template. The resulting DPNs were collected via centrifugation and resulted into micrometric, hydrogel nanoconstructs with precise geometrical and mechanical properties. A cartoon of the DPN cross-section is shown in Figure.1c, together with the constituting ingredients.
Geometrical characterization of Discoidal Polymeric Nanoconstructs. First, the geometrical properties of DPNs were characterized using multiple, different techniques including confocal fluorescent microscopy (FM) (Figure.2a); transmission electron microscopy (TEM) (Figure.2b); multisizer coulter counting (Figure.2c), and dynamic light scattering (DLS) (Figure.2d). Tridimensional images of DPNs loaded with lipid-RhB chains (RhB-DPNs) were generated using confocal microscopy imaging and surface rendering. Figure.2a shows top and side views of all four differently shaped DPNs: two circular nanoconstructs (CPNs) with diameters of 1,000 and 2,000 nm and heights of 400 nm and 600 nm, respectively; an ellipsoidal nanoconstruct (EPN) with a major axis of ∼ 2,100 nm, minor axis of ∼ 1,400 nm, and height of 400 nm; a quadrangular nanoconstruct (QPN) with a side length of 1,000 nm and height of 400 nm. DPN characteristic dimensions were confirmed by the fluorescent images and are in close agreement with the geometrical features originally realized in the silicon master templates (Figure.1). All nanoconstructs were made of the same PLGA:PEG:lipid-RhB mixture. Tridimensional movies with rotations around the x-axis and reconstructions along the z-axis are available as Supporting Information. TEM images of individual DPNs are presented in Figure.2b, as top and tilted views. The latter offers details of the nanoconstruct edges demonstrating the precise replica of the original template geometry. The analysis with the multisizer, coulter counter system (Figure.2c) allowed us to quantify precisely ACS Paragon Plus Environment
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the number of nanoconstructs as well as returning a characteristic size for the differently shaped DPNs. Note that, given the non-spherical shape of DPNs, a size distribution was returned with a sharp peak, which represents the characteristic geometrical dimension of DPNs for that instrument. This is a very powerful tool to assess the quality and reproducibility of the nanoconstruct geometrical features, and for precisely counting the number of particles. Similar observations can also be extended to the DLS profiles provided in Supporting Figure.1. The characteristic size, resulting from the multisizer and DLS machines, are summarized in the table of Figure.2d together with the ζ-potential measurements. The last column lists values for the spherical polymeric nanoconstructs (SPNs). These were made out of the same materials as per DPNs but were obtained via an emulsion/nanoprecipitation approach returning a spherical shape with a diameter of 172.4 ± 0.1 nm (PDI = 0.115 ± 0.03) and ζ = -44.6 ± 1.14 mV (see Supporting Figure.2).26-28 Note that the peaks became sharper as the characteristic size and aspect ratio (base /height) of the nanoconstruct increases. This is nicely shown in Figure.2c for 2,000 nm CPNs and QPNs. Less clear peaks can be observed for EPNs, where the two peaks should be ascribed to the minor and major axes of the elliptical base (∼ 1,400 and ∼ 2,100 nm, respectively), and the 1,000 nm CPN where the 600 nm peak is close to the lower detection limit of the instrument. All DPNs present a similar surface electrostatic potential ζ ∼ - 25 mV, which has to be related to the carboxylic terminations of the PLGA chains. Notably, the different geometrical properties do not affect the surface electrostatic potential.
Mechanical characterization of Discoidal Polymeric Nanoconstructs. Atomic force microscopy (AFM) analysis was used to determine the morphological and mechanical properties of DPNs (Figure.3). The DPN morphology was assessed using an AFM quantitative imaging mode under wet conditions. Figure.3a shows the size and shape of 1,000 × 400 nm circular CPNs, 1,000 × 400 nm square QPNs, and 2,100 × 1,400 × 400 nm elliptical EPNs. The geometry of DPNs properly resemble ACS Paragon Plus Environment
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that of the original silicon template. Still using atomic force microscopy, the Young’s modulus of DPNs was estimated directly from multiple (> 100) force-displacement curves, generated on over 10 particles per experimental group. In particular, the histograms in Figure.3b report the Young’s modulus distributions for three differently shaped DPNs (1,000 nm CPNs, QPNs and EPNs) and DPNs with different mechanical properties (soft – sCPNs; rigid – rCPNs, and rigid-rigid – rrCPNs). The Young’s modulus E = 185 ± 35 kPa for the 1,000 nm sCPNs; 195 ± 16 kPa for the 1,000 nm QPNs; 56 ± 6 kPa for the 2,000 nm sCPNs; and 476 ± 110 kPa for EPNs. Therefore, regardless of the size and shape, all soft DPNs returned a Young’s modulus close to ∼ 100 kPa. Only EPNs present a slightly larger Young’s modulus, which might be associated with its elongated shape and different polymerization rates. As the percentage of PEG in the original polymeric paste reduces, DPNs became stiffer and the Young’s modulus grew correspondingly. Therefore, for rigid DPNs, it follows E = 737 ± 28 kPa for the 1,000 nm rCPNs and 1,606 ± 177 kPa for the 2,000 nm rCPNs; and, for rigid-rigid DPNs, it results E = 1,907 ± 162 kPa for the 1,000 nm rrCPNs and 5,172 ± 902 kPa for the 2,000 nm rrCPNs. As summarized in the bar chart of Figure.3b, the Young’s modulus grows steadily moving from soft, to rigid and rigid-rigid DPNs, regardless of their size. Interestingly, the change in rigidity of DPNs is also reflected in size distribution measurements performed with the multisizer coulter counter (Figure.3c). Note that, in this instrument, particles dispersed within an isotonic solution are forced to flow across a small 20 µm capillary where each single passage is counted as an event. Rigid and rigidrigid DPNs present a smaller variation in size distribution exhibiting quite sharp peaks and less broad distributions as compared to soft DPNs. This could be related to the DPN deformability under flow, whereby softer particles would deform more and take different orientations in the flow thus leading to a broader size distribution as compared to stiffer particles. Potentially, this could be used as a highthroughput approach to qualitatively assess the nanoconstruct deformability. Indeed, under static and
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quasi-static conditions, the size and shape of DPNs stay as that provided by FM, TEM and AFM analyses of Figure.2a,b and Figure.3a.
Quantifying internalization of Discoidal Polymeric Nanoconstructs into professional phagocytic cells. The propensity of DPNs with different geometrical and mechanical properties to resist internalization by professional phagocytic cells was assessed using two different cell types, namely a conventional macrophage cell line (RAW 264.7) and primary cells directly extracted from rats (Bone Marrow Derived Monocytes – BMDMs). Two different and complementary biological assays were used for quantifying DPN internalization, including confocal fluorescent microscopy (FM) and flow cytometry analysis (FC). DPNs were incubated with phagocytic cells for 24h at a 1:10 cell:DPN ratio. Representative FM images, reporting the maximum intensity profiles from multiple z-stack acquisitions, are shown in Figure.4 and in the Supporting Information for BMDMs and RAW cells, respectively (Supporting Figure.3). These images undoubtedly show that DPN uptake grows as their size and stiffness increases. Both 1,000 and 2,000 nm soft circular nanoconstructs (sCPN) are poorly internalized by BMDMs, as compared to controls (Figure.4a). Also, rCPNs and rrCPNs are from two to four times more avidly uptaken by phagocytic cells (Figure.4b). Notably, CPNs, QPNs and EPNs with a characteristic size of about 1,000 nm appeared to present similar internalization rates. EPNs showed a slightly higher propensity to be uptaken possibly due to the overall larger size and shape anisotropy, which are known to favor cellular uptake (Figure.4c).20 As a positive control, BMDMs are also incubated with 1.5 µg/mL SPNs which appear to be massively internalized (Figure.4b) at levels comparable with rrCPNs. Indeed, cell internalization is affected by size too, as already documented by several authors.29-32 Similar conclusions are obtained by performing the same internalization analyses upon incubation of DPNs with RAW 267.4 cells (Supporting Figure.3 and 4). In particular, Supporting Figure.4 shows tri-dimensional reconstruction of cells associated with DPNs confirming
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their intracellular localization. In the first and second column, 3D images and surface reconstructions of macrophages internalizing CPNs are reported. In the third column, a cut slice of the surface reconstruction is shown. For all images, the macrophage cytoskeleton (actin) is stained in green and the nuclei are stained in blue. The largest majority of cell-associated nanoconstructs are clearly observed to reside inside the macrophages. As a complementary and more quantitative assay, a flow cytometry analysis (FC) was performed for the same experimental groups. Results expressed in terms of percentage of cells associated with RhBDPNs are summarized in Figure.5a-b for the case of BMDMs and in Figure.5c-d for the case of RAW 267.4 cells. The FC results confirm the overall picture that has emerged through the confocal microscopy studies: larger and stiffer DPNs are more easily internalized as compared to smaller and softer DPNs. More specifically, for BMDMs, only 11.7 ± 9.9% of cells are associated with 1,000 nm sCPN. This percentage grows to 54 ± 11.6% and 46 ± 12.4% for respectively 1,000 nm rCPN and rrCPNs. The difference is not statistically significant between the two more rigid CPNs but, as compared to sCPNs, there is about a 5-fold increase in cell internalization. For the larger 2,000 nm sCPN, the percentage of associated cells grows to 28.2 ± 16%, which is almost a 3-fold increase as compared to 1,000 nm sCPNs. The percentage grows even larger for the rigid nanoconstructs, specifically 67.9 ± 23.5% and 67.3 ± 16.1% of for the 2,000 nm rCPN and rrCPNs, respectively. Even in this case there is no significant difference in cell association for the more rigid nanoconstructs, but a 2.5-fold increase is again observed moving from soft to rigid CPNs. The fact that the association percentage does no change significantly as moving from rigid to rigid-rigid DPNs, for both the 1,000 and 2,000 nm nanoconstructs, could imply that softness affects internalization up to a certain threshold (about 1 MPa in the present case) beyond which all nanoconstructs are seen from the cells as rigid particles. Anyway, confocal microscopy images (Figure.4d) also showed a steadily growing amount of DPNs associated with cells as moving from rigid to rigid-rigid nanoconstructs. ACS Paragon Plus Environment
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As per the effect of shape, 1,000 nm square nanoconstructs (sQPNs) exhibited internalization percentages comparable with sCPNs, namely 12.9 ± 2.6%. Differently, the elliptical nanoconstructs (sEPNs) presented a much larger percentage of internalization 59.5 ± 4.7%. This appears to be following the notion that the larger EPNs (2,100 × 1,400 × 400 nm) together with their elongated shape and slightly higher rigidity could favor association and internalization by phagocytic cells.20 Similar results were obtained upon incubation of the polymeric nanoconstructs with RAW 267.4 cells (Figure.5c-d). Overall, RAW 267.4 cells appeared to internalize less avidly as compared to primary BMDMs. Also, when comparing soft particles of 1,000 and 2,000 nm (Figure.5c), the size parameter seems to be less relevant compared to what observed with BMDMs. Specifically, 15.4 ±10.8% of Raw 264.7 cells internalize 1,000 nm sCPN, 22.7± 8.0% and 22.5± 13.0% of cells internalize respectively 1,000 nm rCPN by and 1,000 nm rrCPN. Moreover, the 12.1± 5.7% of cells internalize 2,000 nm sCPN; whereas 38.9±10.5% and 55.3±8.7% of cells internalize, respectively, 2,000 nm rCPN and rrCPN. Regarding the differently shaped particles, 23.5±8.4% and 39.6±4.7% of cells internalize respectively sQPN and sEPN. Quadrangular and ellipsoidal particles are thus internalized by RAW cell at a similar extent of 1,000 nm rCPN and rrCPNs and 2,000 nm rCPN. p-values for the FC and confocal microscopy analyses are shown in the Supporting Information. In both experiments, SPNs are used as a control. The percentage of cells which are positive to SPN internalization are shown in the two bar charts where differently shaped nanoconstructs are also directly compared (Figure.5b,d) For all analyses, the internalization activity of non-inhibited cells was considered equal to 100%. As expected, a massive amount of cells internalizes SPNs: 78±3.6% for BMDMs and 96.8±0.9% for RAW 267.4. Given the characteristic size of DPNs, phagocytosis is expected to be the dominant mechanism of internalization, whereby actin fibers would be responsible for wrapping the cell membrane and
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dragging a foreign body inside the cell. Cytochalasin D is commonly used as an actin polymerization inhibitor. By treating the phagocytic cells with this compound, it is observed, on average, a 50% reduction in internalization propensity for all tested conditions, regardless of the size, shape and softness (Figure.5e). A higher inhibition activity is reached for the BMDMs possibly because of their higher ‘avidity’.
Monitoring the interaction of individual Discoidal Polymeric Nanoconstructs with professional phagocytic cells. In the attempt to unravel the mechanisms modulating the differential DPN uptake, time lapse microscopy experiments were performed on RAW 267.4 cells upon incubation with fluorescently labelled particles. Multiple movies were acquired and analyzed to monitor single DPNcell interactions over time. Representative movies are available as Supporting Information. Considering that there is no statistically significant difference between rCPN and rrCPN in terms of internalization, a direct comparison was only performed between 1,000 nm sCPN and rrCPN. The experiment is schematically described in Figure.6a: the trajectory of DPNs, the separation distance between the DPN and the cell membrane, and the time spent by the DPN next to the cell membrane are derived upon post-processing the continuously acquired microscopy images. Of these three physical quantities, the most interesting one is the time spent by DPNs in close proximity with the cell membrane (separation distance ≤ 1,000 nm). Based on this definition, DPNs–cell interactions were classified as short-lived, which are those lasting less than 30 seconds; and long-lived, which are those lasting more than 30 seconds. From movie post processing, it resulted that sCPNs mostly establish short-lived interactions, whereas rrCPNs tend to spend a longer time next to the cell membrane establishing long-lived interactions. This is shown in Figure.6b for CPNs of different sizes (1,000 and 2,000 nm); and in Figure.6c, for DPNs of different shapes (1,000 nm CPNs, QPNs, and EPNs). The bar chart in Figure.6b documents that ACS Paragon Plus Environment
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moving progressively from soft 1,000 and 2,000 nm CPNs to rigid 1,000 and 2,000 nm CPNs the percentage of long-lived interactions steadily grows from 27±11.3% to 74.2±9.8%. Importantly, soft CPNs with different sizes and shapes all presented similarly short-lived interactions with the cell membrane: only 30% of the soft DPN interactions with cells are longer than 30 seconds (Figure.6c). Specifically, 31.4% of EPN, 28.3% of QPN and 27% of sCPN exhibit long-lived interactions with cells. Additional data on the duration of DPN-cell interactions are provided in the pie charts of Supporting Figure.5.
Discussion. The mechanical properties of the discoidal polymeric nanoconstructs (DPNs) can be modulated by changing either the relative ratio of the two constituting polymers (PLGA and PEG) or the overall particle geometry. As per the polymers, the higher is the relative concentration of PEG and the higher is the particle softness. For instance, considering solely the 1,000 × 400 nm CPNs, particle softness decreases as the PEG concentration reduces from soft (E = 185 ± 35 kPa) to rigid (E = 737 ± 28 kPa) and rigid-rigid (E = 1,907 ± 162 kPa), without changing the nanoconstruct geometry. A similar observation applies for the 2,000 × 600 nm CPNs. On the other hand, moving from 1,000 nm soft CPNs to 1,000 nm QPNs and 2,000 nm soft CPNs, the particle geometry changes significantly while the Young’s modulus only moderately varies, staying around 100 kPa. Particle phagocytosis is known to be associated with an extensive, localized reorganization of the actin filaments, which alter locally the shape of the cell membrane and the structure of the cytoskeleton. During this process, multiple adhesive interactions are established at the particle/cell interface through which mechanical forces are directly applied on the particle itself from the morphing membrane. These forces guide membrane wrapping as well as serve to orient, twist and bend the particle in order to favor its final internalization.20,
33
Within this context, discoidal polymeric nanoconstructs could be
approximatively considered as thin plates.34 As such, the resistance to deformation under external ACS Paragon Plus Environment
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forces can be quantified via the bending rigidity Eh3, where h is the thickness of the particle. For geometrically identical DPNs, Eh3 grows linearly with the Young’s modulus thus possibly explaining the difference in internalization behaviors observed among soft, rigid and rigid-rigid CPNs. More interesting is the case of 1,000 nm soft CPNs, 2,000 nm soft CPNs and 1,000 nm soft QPNs, which present similar internalization propensities, both with BMDMs and RAW cells (Figure.5) (p < 0.05). For the 1,000 nm soft CPNs and 1,000 nm soft QPNs, this is easy to realize in that the two particles have identical thickness (400 nm) and very similar Young’s modulii (E = 185 ± 35 and 195 ± 16 kPa, respectively), thus returning a bending stiffness Eh3 ∼ 3.0×106kBT (kBT = 4.11×10-21 J). For the 2,000 nm soft CPNs, with E = 56 ± 6 kPa and h = 600 nm, the bending stiffness Eh3 equals 2.9×106kBT, which is indeed very close to that deduced for the two other particles. Therefore, discoidal polymeric nanoconstructs with similar bending stiffness would exhibit also similar internalization behaviors. Differently, for EPNs, the Young’s modulus is close to 500 kPa returning a bending factor Eh3 = 7.4×106kBT, which is significantly higher than that of the other soft particles. The rigid and rigid-rigid CPNs return Eh3 values of 1.15×107 kBT and 3.0×107 kBT, for the 1,000 nm; and 8.4×107kBT and 2.7×108kBT, for the 2,000 nm. This data would suggest that particles with bending stiffness higher than ∼ 107kBT would be seen all as rigid particles from phagocytic cells. A similar behavior, with the appearance of a plateau in internalization behavior, was also recently documented by other authors.35 Recently, using a layer-by-layer technique, Garapaty and Champion have produced 3 µm spherical particles and capsules, and 12 × 2.5 µm rod-shaped particles and capsules.33 Then, the internalization behavior of these particles in a murine macrophage cell line was assessed. The study demonstrates that rod-shaped capsules are uptaken as avidly as the spherical particles and capsules, and significantly more avidly than solid rod-shaped particles. This higher internalization of the slender and empty rodshaped capsules would most likely be explained by their higher capacity to be bent, twisted and re-
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oriented by the cell membrane. In another recent paper by the group of Caruso, 3 µm spherical hyaluronic acid capsules were obtained via a mesoporous silica templating approach.36 The capsule deformability was modulated by changing the number of polymeric layers, returning a capsule thickness ranging from 4.4 nm to 19.4 nm. Even in this case, it was shown that softer capsules are more easily uptaken by HeLa cells. Assuming a Young’s modulus of 10 kPa, the bending stiffness parameter for this microcapsules would range between 0.21 and 17.7kBT. Even in this paper, a plateau was observed for high values of stiffness. Finally, in the work of Hartmann et al., ∼ 4 µm spherical polyelectrolyte capsules were used to analyze the effect of particle stiffness on intracellular trafficking, from the outer cellular membrane to the lysosomal compartments.37 In this case, it was shown that, upon internalization in HeLa cells, softer capsules evolve more rapidly through the different intracellular compartments. This behavior, occurring post particle internalization, should be most likely ascribed to the ability of capsules to more easily conform to the membrane of intracellular vesicles. No specific information was provided on the thickness of the capsule and Young’s modulus of the membrane. It is here important to observe that typical values for the bending stiffness of a red blood cells lie in the range of 100kBT
38
, whereas neutrophils and endothelial cells, that possess a more extensive
cytoskeleton, return values close to 103kBT.39 Therefore, the estimated bending stiffness of above described microcapsules would be 1 to 3 orders of magnitude lower than that of cells and comparable with that of extracellular vesicles (∼ 14kBT).40 On the other hand, the softest discoidal polymeric nanoconstructs would exhibit a Eh3 factor which is about 3 orders of magnitude higher than that of cells (106kBT). This would become at least 4 orders of magnitude higher in the case of rigid DPNs. Considering the above numbers, one could argue that microcapsules, softer than cells, would readily conform to external and internal cell membranes favoring internalization and intracellular transport, just like extracellular vesicles do. Differently, soft DPNs would be sufficiently deformable to evade cell ACS Paragon Plus Environment
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embracing and, yet, sufficiently rigid to avoid conforming to biological membranes. Finally, rigid DPNs would be far more easily manipulated and re-oriented by the cell membrane thus facilitating internalization.
CONCLUSIONS In addition to size, shape and surface properties, softness was identified as to be a fourth parameter for modulating the interaction between immune cells and particles. For three different shapes (circular, elliptical and quadrangular); two characteristic sizes (1,000 and 2,000 nm); and a Young’s modulus varying over two orders of magnitude (from 100 kPa to 10 MPa), professional phagocytic cells were observed to engulf more avidly rigid as compared to soft nanoconstructs. This was verified both for a conventional murine cell line – RAW 246.7 – and for primary rat monocytes – Bone Marrow Derived Monocytes. Interestingly, the internalization behavior appears to be related to the particle bending stiffness Eh3 and, in the present case, a threshold has been identified (Eh3 ∼ 7×106 kBT) above which nanoconstruct internalization becomes independent of the mechanical properties. In other words, discoidal nanoconstructs stiffer than 7×106 kBT would always be seen as rigid particles by phagocytic cells. 1,000 nm discoidal and quadrangular polymeric nanoconstructs were far less internalized than soft elliptical nanoconstructs and rigid nanoconstructs, of any shape. Conventional, 150 nm spherical polymeric nanoparticles, coated with PEG chains, were documented to be internalized 8 times more avidly than soft 1,000 nm discoidal nanoconstructs. Upon a critical analysis of the presented results and data published by other authors, three different internalization regimens were identified based on the bending stiffness ratios between particles and cells: Eh3 lower than cells would facilitate internalization; Eh3 slightly higher than cells would oppose internalization; Eh3 much higher than cells would favor again internalization.
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The ability to modulate the recognition and sequestration of particles by immune cells has multiple biomedical implications. For instance, softer particles would be taken up less efficiently by resident, tissue specific macrophages, such as the hepatic Kupffer cells and the splenic macrophages, thus circulate longer and eventually reach in a larger number the original biological target. Moreover, the ability to precisely tune the softness of particles favoring adhesion, but not internalization, over macrophages could help developing immunomodulatory therapies and more efficiently use circulating monocytes as natural carriers. All this is expected to enhance the therapeutic and imaging performance of systemically injected soft particles.
METHODS/EXPERIMENTAL Fabrication of Discoidal Polymeric Nanoconstructs. Discoidal Polymeric Nanoconstructs (DPNs) were synthesized by employing a top-down fabrication process.22 Briefly, this involves the use of the Direct Laser Writer lithographic technique to fabricate a silicon master template presenting an array of discoidal holes with circular, elliptical and quadrangular base and fixed size. This pattern is then replicated into PDMS (Sylgard ® 184, Dow Corniging, USA) and subsequently poly(vinyl alcohol) (PVA) (Sigma Aldrich, USA) templates, by using soft lithography. Once the holes of the sacrificial template (PVA) are filled with the polymeric mixture, composed by the hydrophobic (poly(lactic acidco-glycolic acid) (PLGA) (Sigma Aldrich, USA) and hydrophilic poly(ethylene glycol) diacrylate (PEG diacrylate) chains, the PVA is dissolved in water to collect the resulting particles. Lipid Rhodamine-B (Avanti Polar Lipids, USA) is added to the polymeric paste composing the DPNs. DPN concentration and size distribution profiles were performed through Multisizer (Beckman Coulter, USA). The zeta potential was calculated using dynamic light scattering (DLS) (Malvern, UK). Morphological analysis of DPNs was also determined by Transmission Electron Microscopy (TEM)
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(JEOL, Japan). The sample were prepared by the drop casting method over a carbon coated grid. The samples were sputtered with 10 nm of carbon and analyzed operating at an acceletation voltage of 100kV. Confocal images of particle were obtained using an A1-Nikon confocal microscope (Nikon Corporation, Japan ) as detailed below.
Atomic Force Microscopy imaging and mechanical analyses. The morphological and mechanical analysis of DPNs was performed by using
a Nanowizard III AFM system (JPK Instruments,
Germany), mounted on an AxioObserver D1 (Zeiss, Germany). Silicon nitride triangular cantilevers (DNP, Bruker, USA), with a nominal spring constant of 0.06 N/m, were employed. The typical radius of curvature of the tip was 20-60 nm. The actual spring constant of each cantilever was determined by using the thermal noise method (Hutter & Bechhoefer, 1993). 10 µL of solution containing particles, spotted on Poly-L-Lysine coated glass substrates (HistoBond + 76 × 26 × 1 mm; Marienfeld), were dried at room temperature in air and subsequently rehydrated in milliQ water, for at least 3 h before the acquisition of the AFM data. Quantitative imaging (QI) mode was used for the morphological analysis. QI mode is based on the acquisition of a large set of force–distance (FD) curves and on the reconstruction of sample topography from the tip position at the specific force load. QI data set were acquired in milliQ water, by applying maximum forces load of 1 nN. QI images were obtained collecting 256 × 256 FD curves. FD curves length was maintained constant for each data collection, ranging from 200 to 500 nm, the tip was always moved at a constant velocity of 20 µm/s. The mechanical analysis was obtained from FD curves acquired at a lower tip velocity (3 µm/s). Over 10 particles per experimental groups were considered. For each particle, force-displacement curves were determined in at least 100 different points. A statistically relevant number of curves (> 100) was acquire per DNPs. FD curves were analyzed by using the JPK Data Processing software (JPK Instruments, Germany). Each FD curve of the QI map was converted into force-indentation (FI) curve ACS Paragon Plus Environment
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and fitted with the Hertz model, by using a Poisson’s ratio of 0.5. The AFM tip was approximated as a quadratic pyramid indenter.
Cell Culturing. Raw 267.4 cells from were cultured in DMEM Hi Glucose (ATCC, USA), with 10% FBS (Gibco, Thermo Fisher Scientific, USA) and 1% Penicillin/Streptomycin (Sigma Aldrich, USA) at 37 °C in a humidified 5% CO2 atmosphere. Bone marrow derived monocytes (BMDMs) from rats were isolated based on the following procedures. Briefly after scarifying the animal, femurs were isolated, cleaned from surrounding tissues and washed in PBS (Thermo Fisher Scientific, USA), a cut was performed at both ends. PBS was used to flush the cavities, cells were harvested and plated in media supplemented with macrophage colony-stimulating factor (mCSF) (10 ng mL−1) (Sigma Aldrich, USA). The procedure were conducted following the guidelines of the Institutional Animal Care and Use Committee of IIT.
Confocal Fluorescent Microscopy imaging. Confocal images of DPNs were obtained using an Nikon-A1 confocal microscope (Nikon Corporation, Japan). Lipid Rhodamine-B (Avanti Polar Lipids, USA) was used in the fabrication step to allow particle visualization. Particles were suspended in PBS (Thermo Fisher Scientific, USA) and a single drop was seeded on a microscopy slide and covered using a coverslip. For cells imaging (Fig.3), 2,0000 cells (either Raw267.4 or BMDM) were seeded into each well of a Nunc™ Lab-Tek™ II Chamber Slide™ System (Thermo Fisher Scientific, USA) maintaining culturing conditions, as described above. Cells were treated with CPN of different level of softness and with DPN of different geometries using a cell particle rate equals to 1:10. In order to favor the homogenous distribution of the particles among different samples and run, all the treatment were performed suspending the particles in an adequate volume of culturing media in order to replace the media without particles with the media with particles. This procedure allows for an homogeneous
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distribution of particles within the well. After 24h culturing media was removed and cells were washed in PBS (Thermo Fisher Scientific, USA). Fixation was performed using a 3.7% solution of paraformaldehyde (Sigma Aldrich, USA) for 5 minutes. Actin was stained in green using Alexa Fluor™ 488 Phalloidin (Thermo Fisher Scientific, USA) and nuclei using DAPI (Thermo Fisher Scientific, USA) following vendors indications. A z-stack section was acquired using a60X objective (≥12 steps of 1,000 nm each were acquired per image) the maximum intensity profile is presented in Figure 4 and Supporting Figure 3. A particle was considered internalized when its edges were fully included in the cell body as from the lateral projection planes (x-z, z-y) and 3D surface reconstructions. Surface reconstruction of macrophages with sagittal cuts are presented in the Supporting Figure 4. Analyses were performed on over 40 cells per experimental group (multiple and different regions within the well were considered, in a random fashion).
Flow Cytometry Analysis. Flow cytometry was performed using a FACS ARIA (Becton Dickinson, USA). 200,000 cells (either Raw or BMDM) were seeded into each well of a 12 well plate maintaining culturing conditions indicated in cell culturing section. Cells were treated for 24h with CPN of different stiffness and with DPN of different geometries using a cell particle rate equals to 1:10. After treatment cells were washed using cold PBS in order to ease the scraping procedures. Cold DMEM, high glucose, no glutamine, no phenol red (Thermo Fisher Scientific, USA) was added and cells were harvested by gentle scraping the plastic bottom (a volume of 200 µl of was used). Samples were immediately stored in ice and vortexed right before the analysis. A random sample from each 12 well plate was used to assess cell viability by trypan blue staining, Flow Cytometry analyses (FCs) were not considered for viabilities lower than 95%. For Cytochalasin D (Sigma Aldrich, USA) treatment, cells were treated using 0.3 µg/ml of the compound was added to the media 30 minutes before DPN incubation.
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Data analysis: cell population was selected setting a scatter gate excluding the negligible amount of debris and aggregates present in the samples and taking in account the side scatter (SSC) shift due to internal complexity changes caused by internalized particles. The population of cell positive for internalization was selected considering the basal level of fluorescence in untreated cells.
Time Lapse Microscopy Analysis. For time lapse microscopy experiment 10,000 Raw 267.4 cells were seeded into a Nunc™ Lab-Tek™ II Chamber Slide™ System (Thermo Fisher Scientific, USA). A Nikon Eclipse-Ti-E microscope (Nikon Corporation, Japan) was used for this analysis. The following day, RhB-DPN were added and time lapse movies were acquired in bright field and tritc channels starting from the treatment up to 4h. During the acquisitions cells were kept in controlled environmental condition: 37 °C in a humidified 5% CO2 atmosphere, DMEM, high glucose, no glutamine, no phenol red (Thermo Fisher Scientific, USA) was used to eliminate any possible fluorescence background. Movies were acquired at a frame rate of 12 fpm using a 100X objective. 4 to 6 fields per condition were acquired and statistical analyses were performed considering continuous Cell-DPN interaction event of single particle as single events.
Statistical Analysis. Statistical analyses were performed using ANOVA. P values of
