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Three Dimensional Nanocomposites: Fluidics Driven Assembly of Metal Nanoparticles on Protein Nanostructures and their Cell-Line Dependent Intracellular Trafficking Pattern Raman Srikar, Dhananjay Suresh, Sandhya Saranathan, Ajit Prakash Zambre, and Raghuraman Kannan Langmuir, Just Accepted Manuscript • DOI: 10.1021/acs.langmuir.6b00911 • Publication Date (Web): 18 Apr 2016 Downloaded from http://pubs.acs.org on May 2, 2016

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Three Dimensional Nanocomposites: Fluidics Driven Assembly of Metal Nanoparticles on Protein Nanostructures and their Cell-Line Dependent Intracellular Trafficking Pattern R Srikar, Dhananjay Suresh, Sandhya Saranathan, Ajit Zambre, and Raghuraman Kannan* Departments of Radiology and Bioengineering, University of Missouri-Columbia, Columbia, MO 65212, USA RECEIVED DATE (to be automatically inserted after your manuscript is accepted if required according to the journal that you are submitting your paper to) TITLE RUNNING HEAD “Multidimensional Nanomaterials” CORRESPONDING AUTHORS: Tel: 573-8825676; e-mail: [email protected]

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ABSTRACT. Three-dimensional nanocomposites prepared using two different families of nanomaterials holds significant relevance pertaining to biological applications. However, integration of the two distinct nanomaterials with precision to control the overall compositional homogeneity of the resulting 3D nanocomposite is a synthetic challenge. Conventional reactions result in nanocomposites with heterogeneous composition and render useless. To address this challenge, we have developed a fluidicsmediated process for controlling the interaction of nanoparticles to yield a compositional uniform multidimensional nanoparticle; as an example we demonstrated the integration of gold nanoparticles on gelatin nanoparticles. The composition of the nanocomposite is controlled by reacting predetermined number of gold nanoparticles to a known number of thiolated gelatin nanoparticles at any given time within a defined cross sectional area. Using the fluidics process, we developed nanocomposites of different composition: [gelatin nanoparticles-(gold nanoparticles)x] where xaverage = 2, 12 or 25. The nanocomposites were further surface conjugated with organic molecules such as fluorescent dye or polyethylene glycol molecules. To study the biological behavior of nanocomposite, we investigated the cellular internalization and trafficking characteristics of nnaocomposites in two human cancer cell lines. The nanocomposites exhibited a three-stage cellular release mechanism that enables the translocation of gold nanoparticles within various cellular compartments.

In summary, the three dimensional

nanocomposite serves as a novel platform for developing well defined protein-metal nanocomposites for potential drug delivery, sensory and molecular imaging applications. KEYWORDS. Gelatin, Gold Nanoparticles, Fluidics, Endosomal release, Intracellular trafficking, Multidimensional nanoconstruct, Cancer cells.


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Developing synthetic route for covalently binding different kinds of nanoparticles to form well-defined “3D nanocomposites (3DNC)” is one of the key challenges of nanotechnology1. Especially synthesizing these materials with uniform composition in each nanoparticle require accurate control of both chemical reactivity and spatial assembly of individual nanoparticles. Well-defined 3DNC with uniform composition exhibit physical and biological properties that are distinct from their individual constituents, thus, hold great promise for biomedical applications2. As the individual constituents are chemically more reactive to form intra or inter chemical bonds, developing a 3DNC with precise composition has been a synthetically challenge2, 3.

Previous studies established two fundamental

parameters govern the synthesis of 3DNC: specificity and reactivity of precursor nanoparticles.

By

controlling these parameters, we can prevent heterogeneous self-assembly and aggregation between these particles 4. In case of specificity, biomolecules served as precursor materials to build 3DNC and the materials are largely limited to DNA, virus or proteins

5, 6, 7

. The limitations of biomolecule

mediated assembly method include weak bonding between nanomaterials, poor versatility as the core is dictated by natural arrangement of atoms, and require multiple complicated chemical transformations for modifying the core structure8. With regard to controlling the reactivity, very few examples are known in the literature in utilizing this approach for the synthesis of 3DNC. Controlling self-assembly of nanoparticles on a polymeric matrix has yielded multicompartment nanoparticles; however, the comprehensive understanding for rational design of multidimensional nanoparticle is still lacking.9 Taken together, it is evident that the advancement in this field directly depends on our ability to develop generalized synthetic methods to produce spatially well-defined 3D nanocomposites (Figure 1c). In the present study, we developed a fluidics process for controlling the reactivity of precursor nanomaterials and generated a library of protein-metal 3DNC. It is known that fluidics platform controls the kinetics of interaction of precursors offering precise control over reactivity and prevents


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aggregation between nanomaterials (Figure 1)

10, 11, 12

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. To demonstrate the utility and versatility of the

platform, we covalently integrated gold nanoparticles (AuNPs) on gelatin nanoparticles (GN) to form a library of 3DNC with general formula: [GN-(AuNP)x] x = 1-4, 9-15 or 17-30 (Figure 2). In the [GN(AuNP)x], AuNPs are bonded through thiols on to the surface of GN. The biological property of [GN(AuNP)x] synthesized in the study resembles to that of molecules fabricated using biomolecule mediated self-assembly process; however, fluidics route provides extraordinary control in developing nanomaterials with uniform composition and unique spatial arrangement. The surface of GN contains functional groups such as –NH2 and –COOH; neither of these groups forms strong covalent bonds with AuNPs

13, 14, 15

. Even though bonding between amine and AuNPs are noted

in the literature the resulting bond is weak and susceptible to cleavage in the presence of other strong electron donating, π-acceptor ligands15. Therefore, to covalently attach AuNPs to GN it is necessary to modify the surface of GN with ligands to impart selective reactivity towards AuNP for forming covalent bond (Scheme 1)16, 17, 18. Importantly, the post surface modification of GN should retain the stability and solubility to enable unfettered interaction with AuNP. Our previous studies and other studies have shown that thiol groups have shown stronger affinity towards AuNPs and form stable covalent bond19. Therefore, we focused our attention on converting amino groups on the surface of GN, using Traut’s reagent, to thiol groups, as reported previously20, 21, 22. This functional group conversion increases the reactivity of GN toward AuNP, while retaining the integrity, stability and solubility of GN. However, the high reactivity of thiol modified GN toward AuNP led to massive non-directional aggregation with precipitation (see Supporting Information: Figure SF-1). A similar aggregation trend is noted in several studies; an interesting molecular simulation study showed that reaction between AuNPs and thiolmodified polymers occur within a time-scale of 100 nanoseconds

23

. Therefore, we hypothesized that

controlling the interaction kinetics between particles to less than 100 nanosecond scale would lead to


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defined [GN-(AuNP)x]. To validate our hypothesis, we developed a fluidics-controlled reaction system to control the rate of interaction between reactants (Figure 1). It is shown in the literature that fluidics based reactions yield self-assembled nanoparticles with complicated architecture

24, 25

. In the present

study, we designed our fluidics-controlled system with channels of cross sectional diameter of 100 µm and the length was fixed as 10 cm from the mixing chamber. As these dimensions are fixed, the flow rate of the reactants could be varied so that at the given time (100 nanoseconds or less) the number of nanoparticles interacting with each other in mixing chamber is controlled. For example, the theoretical number of AuNPs interacting per GN-SH at a time scale of 100 nanoseconds was calculated to be 72 (see Supporting Information: Table ST-1). To control the number of AuNPs interacting with GN, the flow rate of constituents in the fluidics system are varied to 10 mL/hour; 20 mL/hour; and 40 mL/hour and the resultant products were analyzed. Based on this flow rate at fixed concentration of the reactants, we theoretically calculated the number of NPs flowing through the mixing chamber in μm2 cross sectional area per μs was calculated and presented in Table 1. It is worth to note that even though the mixing chamber is three-dimensional, the comparison could be better attained with two-dimensional parameters. For example, at the flow rate 40 mL/hour of reactants (6.08 GN/µsec.µm2 and 344 AuNP/µsec.µm2); the overall surface area of the particles occupying the space in the channels 1.25 µm2 exceeds the available surface area of the channel at this flow rate and leading to clogging of the fluidic channel (see Supporting Information: Figure ST-2).

Indeed, experimental results at 40 mL/hour

resulted in non-tractable aggregated material. As a next step, we reduced our flow rate to 20-mL/hour lead to controlled interaction with improved particle size; however, the clogging could not be controlled with time (particles occupying ~ 65% of the available surface area).

Finally, at 10ml/hour flow rate,

controlled assembly of AuNPs to GN through convective self-integration was achieved in the connected mixing chamber. The collected 3D nanocomposite was observed to be uniformly integrated thus


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validating our hypothesis. TEM image further confirmed uniform distribution of number of AuNPs on the surface of each GN (Figure 2). Taken together, these results confirm that by controlling the rate of interaction of nanoparticles using fluidics-system designer 3D nanocomposites could be synthesized. As a next step toward our rationale synthesis of [GN-(AuNP)x] nanocomposite, we focused our attention on estimating the range of concentration ratios [GN]:[Au], at which the fluidics system would yield a well-defined 3D nanocomposite. To evaluate the ratio, it is important to understand whether the concentration of AuNP has any functional dependency in the resulting [GN-AuNP)x].

To

systematically investigate, we chose four different concentrations of both GN and AuNPs resulting in 16 combinations (see Supporting Information: Table ST-1). For example, in this experiment we treated fixed concentrations of GN with four increasing concentrations of AuNPs in a fluidics-mixing chamber. After each of these reactions, the unreacted AuNPs were separated and analyzed using UV-visible plasmon resonance and the final product was analyzed using TEM. To compare the results obtained, we calculated “Efficiency of Integration” and presented in graphical form; the efficiency can be defined as the maximum amount of AuNPs that can be covalently integrated to given concentration of GN to form well-defined 3DNC. It is expected that increase in concentration of AuNPs for a given concentration of GN, would lead to an increase in efficiency up to a saturation level beyond that the value plateaus. That means there is a limit in number of AuNPs that can be integrated with GN. Indeed, we found a functional dependency of AuNP in the precursor solution per mg of GN, defined as ratiometric value (Ŕ), on the resulting [GN-AuNP] (Figure 3). Our studies show that there was no clear correlation or behavior was observed in lower ratios (Ŕ ≤ 0.033).

In sharp contrast, at higher ratios that are when

0.05 ≤ Ŕ ≤ 0.15, a linear increase in efficiency is observed indicating that in the fluidic channel, [AuNP] of certain concentrations exhibit efficient reactivity in binding with GN. At Ŕ = 0.15 maximum number of precursor [AuNP] used in the reaction is bound with GN. We utilized Ŕ for developing the library of


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[GN-(AuNP)x]; comprising of x = 1-4, 9-15, and 18-30. Assuming equal distribution of the integrated AuNPs on the surface of the spherical GN-SH, the absolute number of gold nanoparticles would therefore be twice the observed. The maximum number of gold nanoparticles per gelatin nanoparticle at Ŕ = 0.15 would be 60 AuNPs per GN-SH. Theoretical number of AuNPs that can be bound to GNs was in close correlation to the results obtained from TEM (see Supporting Information: Table ST-1). As a next step, we investigated the ability of [GN-(AuNP)x] to encapsulate molecules within gelatin matrix and also their ability to release it with external trigger such as enzymes. For this study, we used indocyanine green (ICG) as a model encapsulant owing to their absorption at 780 nm for easy and accurate analysis.

We encapsulated ICG (20mg/g of GN) within the gelatin and followed the similar

procedure as described for making 3DNC. Encapsulation of ICG within gelatin nanoparticles was performed as per previous reports20. Briefly, the amino groups on the surface of GN(ICG) was converted to thiol and covalently conjugated with AuNPs using fluidics process to yield [GN(ICG) AuNP]. It is worth to note that encapsulated ICG was retained with no release through out the different chemical modifications. The encapsulation and loading content of our system was determined to be ~40% and ~5% (w/w); this value is comparable to other literature values known for both polymeric or gelatin nanoparticles synthesized through solution phase

20, 26, 27, 28

. We studied the release

characteristics of ICG from [GN(ICG)-(AuNP)x] under different biological media; the results show that ICG is intact within the nanoparticle and only less than 10% released during 48 hours of study period conforming to previous studies that have also indicated that the diffusion mediated release from gelatin saturates at ~15%

29, 30

. This result prompted us to investigate whether we can release ICG in the

presence of external trigger such as enzymes. It has been previously reported that MMP-2, a gelatinase capable of degrading gelatin and its analogues, was detected in the cytoplasm of cancer cells in 75.6% cases (102 cases) 31. We investigated the percent of release of ICG from [GN(ICG) -AuNP] in presence


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of external trigger matrix metalloproteinases (MMP-2), after incubating for 15 hours at 37 oC. For example, at MMP-2 concentrations of 1µg cumulative ICG release was 7 fold higher (72% release) than with no MMP-2 conditions (Figure 4). Our investigations further revealed that the concentration of the enzyme is a prime factor for degradation.

To confirm whether further the release of ICG from

[GN(ICG) -(AuNP)x] is mediated by enzymes or other factors, we performed semi-empirical calculations (see Supporting Information: Table ST-3) and focused on calculating desorption enthalpy of the nanoconstruct. The importance of desorption enthalpy is to elucidate that in the absence of any degradation agent; the encapsulated compound would remain intact within 3D nanocomposite. Previous studies have shown that desorption enthalpy would provide the ability of the system to release the encapsulated material

32, 33

. The system with higher desorption enthalpy showed lower release of the

encapsulated material; for example, a system with a desorption enthalpy of 45kJ/mol released only 1.4% at 1400 hours while another system with 37kJ/mol released 65% of the encapsulated compound within 100 hours

32

. Assuming desorption of molecules from nanoparticles is comparable to that from the

nanopores of nanofibers, the desorption enthalpy of GN used in synthesizing [GN(ICG) -AuNP] of interest was calculated using a previously reported desorption equation and clapeyron-like desorption law. Effective diffusion, Deff was calculated assuming the length as 200nm. Desorption enthalpy for [GN(ICG) -(AuNP)x] was estimated approximately 43KJ/mol. As desorption enthalpy is higher, it is evident that release of ICG from 3DNC is mediated only by enzymes. It is also important to note that the desorption enthalpy value of 43KJ/mol is only for ICG encapsulated within [GN-(AuNP)x] and should be recalculated for different encapsulants. It is fair to assume that any drug release would have unique [GN-(AuNP)x] interaction and alter the desorption enthalpy. However, the value once established for a particular system would stand valid irrespective of the loading percentage or concentration of drug/gelatin. This further strengthens our claims that the chosen gelatin for [GN-


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(AuNP)x] would degrade under active enzymes such as MMPs. Our studies further indicate that AuNPs present on the surface of [GN-(AuNP)x] still provide the stereospecific access for MMP-2 to disintegrate gelatin. To investigate the cellular uptake, trafficking, and intracellular release behavior of [GN-(AuNP)x], we used both transmission electron microscopy (TEM) and confocal microscopy for analysis. Our studies are aimed to establish the ability of [GN-(AuNP)x] to release from endosomes based on their charge reversal capabilities (also known as proton sponge effect) (see Supporting Information: Figure SF-3) 34. The charge of [GN-(AuNP)x] reverse upon varying the pH of solution with minimal change in size. Amines and carboxylate groups present on GN mediate the charge reversal with no disruption to the overall structure. In acidic pH (3-5) the zeta potential of the [GN-(AuNP)x] was positive; whereas, at neutral and basic pH (6-8) the zeta potential changes to negative. At the late endosomal pH (4.5-5.5), the charge of the [GN-(AuNP)x] reverses (see Supporting Information: Figure SF-3)

35

. Such charge

reversal within endosomes is always accompanied with huge intake of water molecules from cytoplasm to maintain the endosomal pH triggering the disruption of endosomal membrane with subsequent release of nanoparticles to cytoplasm

36, 37

.

In cytoplasm, [GN-(AuNP)x] will encounter several

proteases including MMP-2 that are present in within cancer cells to facilitate local proteolysis Subsequently, gelatin portion of [GN-(AuNP)x]

38

.

will undergo enzymatic cleavage mediated by

gelatinases, resulting in complete degradation of the particles. We have shown in previous section that [GN-(AuNP)x] readily undergo enzymatic cleavage in presence of gelatinase (MMP-2). In order to understand the cell uptake of [GN-(AuNP)x] in microscopy, we attached a fluorescent dye fluorescein 5 maleimide (Fl5M) to thiol groups present in the construct (see Supporting Information: Figure SF-4). The fluorescent dye enables us to track the localization of GN within cancer cells. However, owing to the very small size (2-5 nm) of AuNP, their intracellular location was observed using TEM. As a first


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study, we incubated Fl5M, [GN], [Fl5M-GN-(AuNP)x], and [Fl5M-GN-(AuNP)x-PEG] with human lung cancer cells A549 for 4 hours and monitored the cellular release using fluorescent microscopy (Figure 5). We analyzed the fluorescent microcopy images to quantify the presence of fluorescein within cellular boundaries using image analysis (see Supporting Information: Table ST-4). It is anticipated that cells incubated with [Fl5M-GN-(AuNP)x] should exhibit higher fluorescence within cells than other nanoparticles and free dye. Indeed, fluorescence quantification of these molecules exhibited the following increasing trend: Fl5M < [Fl5M-GN-(AuNP)x-PEG] < [GN] < [Fl5M-GN(AuNP)x] (Figure SF-5). Based on the data it is evident that the nanoparticles internalize effectively within cells. In addition, the quantification proves that [GN-(AuNP)x] internalizes more compared to free [GN]. The data is also consistent with previous literature studies wherein PEGylated nanoparticles showed poor internalization capabilities39.

Therefore, the fluorescence intensity is low in cells

incubated with [Fl5M-GN-(AuNP)x-PEG]. To monitor the cellular localization, we performed TEM analysis of cells incubated with [Fl5M-GN-(AuNP)x]. To ensure that contrasting spots of AuNP is visualized without interference, the cells were not stained (in conventional procedure, cell staining is a routine to reveal cellular boundaries). Earlier studies using naked gold nanoparticles have revealed upon cellular internalization, the AuNPs reside trapped within endosomes (see Supporting Information: Figure SF-6) 40, 41. In the case of [GN-(AuNP)x], AuNPs escaped from endosomes and localized within cytosol. Interestingly, some of the AuNPs were also trafficked to the nucleus of the cells (Figure 6). It is known that imparting positive surface charge to a negatively charged molecule can enable delivery to nucleus 40, 42. For example, conjugation of negatively charged DNA with cationic polymers for delivery to nucleus has been a norm for several decades

43

. El-sayed and coworkers have shown that gold

nanoparticles conjugated with nuclear localization signal peptide selectively transported to nucleus of cancer cells.44 In a similar fashion, gold nanoclusters conjugated with Herceptin has shown nuclear


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localization capabilities.45 In our study, while no specific mechanism can be associated for such phenomenon; one possible reason could be in-situ surface layer coating of degrading gelatin matrix of 3DNC on the surface of liberating AuNPs within the cells. The gelatin nanoparticles, which are inherently positive, form a thin layer coating on the surface of the negatively charged AuNPs. The coating could possible impart sufficient surface modification to enable delivery to nucleus. To understand whether degraded GN reattaches with AuNP, we performed the following experiment. In this experiment, naked AuNPs were added to gelatin and subjected to enzymatic degradation. The particles were then centrifuged @ 20,000g for 20 minutes. In the case of naked AuNP (with protease), the centrifugation destabilized AuNP causing change in color from red to dark purple with significant change in UV-Vis absorption spectrum of AuNP indicating agglomeration as reported in previous literatures

46, 47

. However, in the case of GN-AuNP, no significant change in color was observed (see

Supporting Information: Figure SF-7). Also, the shift in the plasmon resonance of AuNP was negligible indicating degraded gelatin stabilized AuNP through surface coating, a possible phenomenon that takes place within the cell in our case, to traffic AuNPs to the nucleus.

Further studies are warranted to

confirm the nuclear localization and mechanism of transport of these particles to different cellular compartments. To understand whether [GN-(AuNP)x] possess similar intracellular release characteristics in other cancer cells, we incubated the nanocomposite in PC3 cells for 24 hours and intracellular localization of AuNPs were analyzed using TEM. We analyzed the TEM images and observed that the nanocomposite undergo a three-stage process of release from endosomes (Figure 7 and Figure 8). In stage 1, the charge reversal property enable the endosomal release of [GN-(AuNP)x] allowing it to enter the cytoplasm of the cells wherein, they interact with various components of cytoplasm including gelatinases (Figure 8b). In stage 2, the enzymes initiate the degradation of 3DNC; AuNPs, present on


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the surface of 3DNC, detach from [GN-(AuNP)x] due to the surface degradation of the gelatin component and cluster together within the cytoplasm (Figure 8c). In stage 3, transmigration of AuNPs to different location within cytoplasm including endoplasmic reticulum and near the nucleus boundary occurs, while the gelatin component of the 3DNC undergoes complete degradation (Figure 8 d, e and f). However, in the case of PC3 cells, not many AuNPs were observed within the nucleus relative to the results from A549 cells, which could be attributed to cell line dependent transfection and intracellular trafficking, which is well known 48. For example, Douglas et al. had shown fluorescein labeled chitosan upon incubation within various cell lines (293T, COS7 and CHO cells), had distinct transfection and trafficking pattern depending upon the cell line, explaining why the fate of the components of 3DNC varied between PC3 and A549 cells 49. Taken together, we have shown that 3DNC possess the potential for endosomal escape and to release its components to various regions of the cells. However, the fate of 3DNC components’ cytoplasmic transmigration would be cell-line dependent. In conclusion, we hypothesized that fluidics driven platform would control the interaction between individual nanoparticles, important for covalent integration of nanoparticles to form multidimensional nanoparticles with uniform composition. Subsequent to validation of the hypothesis, we used our platform to synthesize a library of well-defined 3D nanocomposites. We systematically investigated the synthetic conditions of the platform and estimated two important parameters that control the covalent integration of nanoparticles: ratiometric value and efficiency of integration. The ratiometric value provides the upper and lower limits of the boundary concentrations for the platform, outside which, the integration of particles would not be optimal. The efficiency of integration provided a value for concentration of nanoparticles that is required for integrating different classes of nanoparticles into a single component. Also, our results confirmed that the nanocomposite is stable in biological media and is a versatile platform to load chemical and biological entities and that, the release


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from the nanocomposite is dominated through degradation assisted release while Fickian diffusion or desorption mediated release is negligible.

Uniting two different nanoparticles into a single

nanocomposite provides excellent cellular internalization and delivery to various compartments of the cell owing to its unique surface properties. Overall, we believe that the platform designed in this study provides attractive opportunities to design novel 3D nanocomposites for various biomedical applications.

ACKNOWLEDGMENT. RK kindly acknowledges the “Michael J and Sharon R Bukstein Chair in Cancer Research” for financial support. Authors also acknowledge financial support from UM-Fast Track Funding, Mizzou Advantage Funding, and Coulter Translational Partnership Grants. SUPPORTING INFORMATION PARAGRAPH. Detailed experimental section is provided. Additional characterization, TEM images, tables, and figures are included. This material is available free of charge via the Internet at http://pubs.acs.org


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TOC


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FIGURES

Figure 1. Fluidics platform for synthesis for 3D nanocomposites with uniform composition: (a) Schematic illustration of fluidics platform for controlled interaction of AuNP on GN; (b) Experimental setup developed in our study for controlling the interaction of nanoparticles in nanosecond scales; (c) Schematic representation of 3D nanocomposite synthesized in our study, inset shows the TEM image of [GN-(AuNP)x].


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Figure 2. TEM images of library of 3D nanocomposite [GN-(AuNP)x] synthesized in our study. (a) x =1-4 AuNP; (b) x = 9-15 AuNP; and (c) x = 17-30 AuNP.


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Figure 3. (a) Efficiency of Integration (EOI) determined by varying the concentration of GN and AuNP. Increasing AuNP concentration yielded increased EOI (max EOI of 84% at 0.5mg/ml GN and 0.075mM AuNP); (b) Graphical representation of EOI of AuNP normalized to per mg of GN. The f(EOI) represented in the graph is independent of each individual concentrations of AuNP integrated per GN. A characteristic exponential profile of EOI with respect to mole of AuNP per mg of GN with asymptotic limit at approximately 85% was determined suggesting EOI is a dependent function of AuNP concentration per GN concentration.


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(a)

(b)

Figure 4. (a) MMP-2 assisted degradation of MDN (1mg/ml) and release of ICG after 15 hours of incubation at 37 oC, and representative NIR images of ICG released from degraded 3DNC(ICG) at various concentration of MMP-2 (0ng, 250ng, 500ng and 1000ng), inset represents pristine GN(ICG) and 3DNC(ICG); WL- white light, NIRL: Near infrared light; (b) Absorption spectra of GN (no peaks), GN(ICG) (780nm peak corresponding to ICG), and 3DNC (780nm corresponding to ICG and 520nm corresponding to AuNP)


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Figure 5. 3DNC conjugate [GN-(AuNP)x-Fluorescein], [GN-(AuNP)x], or [GN-Fluorescein] were incubated with A549 cells, cellular internalization was studied using dark field and fluorescence microscope images at 40X magnification. These images show co-internalization of nanocomposite with fluorescein within A549 Cells. [GN-(AuNP)x-Fluorescein] with A549 cells: (a1) DAPI stained nucleus of cells; (a2) dark field images showing clustered gold nanoparticles as bright white spots; (a3) fluorescence microscopy image showing green fluorescence emanating from the conjugated fluorescein and devoid of bright AuNP spots and (a4) overlay of (a1), (a2) and (a3); [GN-(AuNP)x] with A549 cells: b(1-4) showing absence of fluorescein and presence of AuNPs; [GN- fluorescein] with A549 cells: c(1-4) showing absence of AuNPs and presence of fluorescein.


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Figure 6. TEM images of A549 cells after incubation with [GN-(AuNP)x]. (top) Clustered AuNPs localized within nucleus were observed at several locations within cells. (bottom) Arrows indicate AuNPs present within nucleus of A549 cells.


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Figure 7. Schematic representation of intracellular trafficking of 3DNC in human cancer cells.


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Figure 8. TEM images showing various stages intracellular trafficking mechanism of [GN-(AuNP)x] within PC3 cancer cells. (a) various stages of 3DNC captured within a single cancer cell revealing the transformation and trafficking pattern; (b) Stage 1: The gelatin component of 3DNC starts degrading from outermost surface liberating its surface component i.e. AuNP; (c) Stage 2: The gelatin particles undergo complete surface degradation and partial overall degradation. The liberated AuNPs cluster together; (d) Stage 3: AuNP are trafficked to various locations of the cells and GN undergo complete degradation; (e) AuNPs are transported to the cytoplasm; and (f) AuNPs selectively localized near the endoplasmic reticulum of the cells.


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Scheme 1. Synthesis of homogenous multidimensional nanoconstruct using fluidics as platform. Size distribution with PDI and zeta potential with standard deviation are provided in the supplementary information


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Table 1. Number of nanoparticles interacting at given time in fluidics mixing chamber. Flow Rate (ml/hr)

AuNP (Particle/µsec.µm2)

GN (Particle/µsec.µm2)

Area of NPs with respect to available area in mixing chamber (%)

10

86

1.52

32

20

172

3.04

65

40

344

6.08

125


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