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Hydrophobic Nanoparticles Modify the Thermal Release Behavior of Liposomes Matthew Ryan Preiss, Ashley E Hart, Christopher L. Kitchens, and Geoffrey D. Bothun J. Phys. Chem. B, Just Accepted Manuscript • Publication Date (Web): 25 Apr 2017 Downloaded from http://pubs.acs.org on April 30, 2017

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The Journal of Physical Chemistry

Hydrophobic Nanoparticles Modify the Thermal Release Behavior of Liposomes

Matthew Ryan Preiss1, Ashley Hart2, Christopher Kitchens2, and Geoffrey D. Bothun1,* 1

Department of Chemical Engineering, University of Rhode Island, 51 Lower College Road,

Kingston, RI 02881 2

Department of Chemical and Biomolecular Engineering, Clemson University, 130 Earle Hall,

Clemson, SC 29634 *Corresponding author: [email protected], +1-401-874-9518

1 ACS Paragon Plus Environment

The Journal of Physical Chemistry 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Abstract Understanding the effect of embedded nanoparticles on the characteristics and behavior of lipid bilayers is critical to the development of lipid-nanoparticle assemblies (LNAs) for biomedical applications. In this work we investigate the effect of hydrophobic nanoparticle size and concentration on liposomal thermal release behavior. Decorated LNAs (D-LNAs) were formed by embedding 2 nm (GNP2) and 4 nm (GNP4) dodecanethiol-capped gold nanoparticles into DPPC liposomes at lipid to nanoparticle ratios (L:N) of 25,000:1, 10,000:1, and 5,000:1. D-LNA structure was investigated by cryogenic transmission electron microscopy, and lipid bilayer permeability and phase behavior were investigated based on the leakage of a model drug, carboxyfluorescein, and by differential scanning calorimetry, respectively. The presence of bilayer nanoparticles caused changes in the lipid bilayer release and phase behavior compared to pure lipid controls at very low nanoparticle to bilayer volume fractions (0.3%-4.6%). Arrhenius plots of the thermal leakage show that GNP2 lead to greater increases in the leakage energy barrier compared to GNP4, consistent with GNP4 causing greater bilayer disruption due to their size relative to the bilayer thickness. Embedding hydrophobic nanoparticles as permeability modifiers is a unique approach to controlling liposomal leakage based on nanoparticle size and concentration.


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Introduction Liposomes are well-established biocompatible carriers capable of protecting, transporting, and delivering hydrophobic (contained within the lipid bilayer) and/or hydrophilic cargo (contained within the aqueous core) for biomedical applications.1-3 Liposomal drug delivery systems can increase therapeutic effectiveness, increase stability, target diseased sites, and control release while reducing overall toxicity and side effects. As of 2013, the U.S. FDA has approved thirteen lipid-based products for clinical use to treat cancers (such as breast, ovarian, Kaposi's sarcoma, and acute lymphoblastic leukemia), meningitis, and other ailments. They have also been approved as an anesthetic, to treat fungal infections, and for menopausal therapy. Clinical trials of lipid-based therapies are expanding especially for treatment of cancers, including colorectal, gastric, pancreatic, colon, lung, and liver cancers.1, 2 One approach to controlling liposomal delivery and imparting additional functionality is through the addition of nanoparticles to form lipid-nanoparticle assemblies (LNAs).4-10 LNAs are liposome structures with bilayer-embedded, encapsulated or surface-adsorbed nanoparticles. Decorated LNAs (D-LNAs) formed with hydrophobic nanoparticles, with sizes similar to the lipid bilayer thickness (4-5 nm),11, 12 embedded in the acyl tail region of the lipid bilayer represent a unique hybrid structure where the nanoparticles add functionality and can be used to manipulate the physical and mechanical properties of the bilayer. D-LNAs have been formed with iron oxide,13, 14 quantum dot (CdSe and ZnS),15-19 gold,19-23 silver,24, 25 silicon,26 C60 fullerene,27, 28 and cobalt ferrite29 nanoparticles providing a range of stimuli-responsive release and imaging capabilities. The stability and function of D-LNAs derive from their structure. Recent work has examined the effect of nanoparticle concentration, nanoparticle size, and nanoparticle 3 ACS Paragon Plus Environment


localization and mobility on D-LNA structure.13, 20, 21, 30-33 However, few studies have examined the effects of embedded nanoparticles on lipid phase behavior and the thermal release or permeability behavior. Embedded nanoparticles can stabilize or destabilize lipid ordering and phase behavior, which are characteristic properties of liposomes and govern thermal release behavior. Oh et al.22, 24 and Bothun et al.25 have shown that the membrane fluidity of dipalmitoylphosphatidylcholine (DPPC) liposomes increased with increased loading of 4 nm and 5.7 nm silver nanoparticles, respectively, consistent with liposome destabilization (i.e. reduced lipid ordering). In contrast, liposome stabilization was observed by Chen et al.13 where 5 nm maghemite nanoparticles increased lipid ordering and reduced membrane leakage. Stabilization was also observed by Von White et al.20 where 3.9 nm gold nanoparticles increased lipid ordering and thickened the bilayer. In this work we have investigated the effect of hydrophobic nanoparticle size and concentration on the structure, leakage, and phase behavior of D-LNAs formed with DPPC and dodecanthiol-coated gold nanoparticles (GNPs) with average diameters of 2 nm or 4 nm. The two GNP diameters chosen to provide nanoparticles that were smaller than or similar to the thickness of the lipid bilayer, respectively. Critical to this study was the ability to obtain discrete GNP sizes, which was achieved by fractionating synthesized GNPs using a high-pressure carbon dioxide-based antisolvent process. D-LNA structure was examined by cryogenic transmission electron microscopy (cryo-TEM); and membrane leakage and phase behavior were examined by fluorescent spectroscopy and differential scanning calorimetry (DSC), respectively. Our results show that GNP size and concentration lead to modest changes in the phase behavior of DPPC liposomes, but significant changes in the thermal release behavior.


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Experimental Materials DPPC in chloroform (25 mg/mL) was purchased from Avanti Polar Lipids (Alabaster, AL). 5,6Carboxyfluorescein (CF) and Triton X-100 were purchased from Sigma Aldrich (St. Louis, MO) and phosphate buffered saline 1X solution (PBS) was purchased from Fisher Scientific (Suwanee, GA). All materials were used as-received. Sterile deionized ultrafiltered (DI) water at 18.2 mΩ was used from a Millipore Direct-Q3 UV purification system (Billerica, MA).

Gold Nanoparticle Synthesis Dodecanethiol (DDT)-stabilized GNPs were synthesized via an arrested precipitation method previous described for silver34 and modified for gold21 Briefly, 330 mg of gold chloride trihydrate (Acros Organics, 99%) was dissolved in 20 mL of DI water and 6 g of tetraoctylammonium bromide, TOAB, (Chem-Impex Int’l Inc, 99.35%) was dissolved in 80 mL of chloroform (Alfa Aesar, HPLC grade 99.5%). The two solutions were then combined and stirred vigorously for 1 h until the chloroform phase become an orange/red color. The aqueous phase was discarded and 600 µL of DDT (Tokyo Chemical Industry, >95%) was added to the gold/chloroform solution and stirred for 30 min. To this solution, 20 mL of 0.5 M sodium borohydride was added and stirred for 12 h. The aqueous phase was then discarded and the GNP solution was washed with methanol (Burdick & Jackson, HPLC grade), to remove any excess DDT and TOAB, and then resuspended in neat toluene (BDH, 99.5%).



Nanoparticle Fractionation The GNP synthesis process resulted in a polydisperse sample comprised of GNPs with diameters ranging from 1-10 nm. Fractionation using a solvent/antisolvent centrifugation method (as described in Korgel et al.21) to separate the GPNs by size. During the fractionation process, the largest nanoparticles and aggregates precipitate out first during centrifugation with the supernatant comprised of the smaller nanoparticles without the addition of an antisolvent. Fractionations were performed with different volume percentages of antisolvent (methanol). The first fractionation was performed with 40% antisolvent. After vortexing, the methanol/Au NP mixture was centrifuged at 14500 rpm for 10 min and the precipitate (with GNPs ~4-10 nm in diameter) was resuspended in toluene or chloroform. The supernatant was transferred to a new centrifuge tube and the process was repeated with 70% antisolvent. The precipitate (GNPs ~4 nm in diameter) was resuspended in toluene or chloroform, and a final fractionation was performed with 90% antisolvent to collect ~2 nm GNPs. For each fractionation the solvent/antisolvent mixture was removed after centrifugation by rotary evaporation.

Nanoparticle Characterization Transmission electron microscopy (TEM) was used to determine the size distribution of each nanoparticle fraction. After fractionation and resuspension in neat solvent, a drop of the GNP solution was placed on a 400 mesh Formvar/carbon coated copper grid (Electron Microscopy Sciences) and dried in air. The size distributions were analyzed using ImageJ software. For GNP2, size was determined by manually measuring 50 random particles. For GNP4, size was determined by the automatic measurement of 500–1000 particles.


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Liposome and DLNA Preparation DPPC liposomes and D-LNAs with lipid molecule to nanoparticle (L:N) ratios of 25000:1, 10000:1, and 5000:1 were formed by thin film hydration at 10 mM DPPC. The L:N ratios are similar to those typically reported for D-LNAs,13, 15, 16, 19, 20, 23, 27 and were selected to keep the lipids the major component. DPPC and GNPs in chloroform were mixed in a 25 mL round bottom flask and the chloroform was removed by rotoary evaporation at 50oC (greater than the melting temperature of DPPC) at 300 mbar for 30 min and then 50 mbar for 10 min. Residual chloroform was removed from the thin film in a vacuum chamber. For release studies, the thin film was rehydrated with 1X PBS containing 50 mM CF. The solution was bath sonicated (Branson Ultrasonics 1510, Danbury, CT, USA) a 50oC for 60 min. Unencapsulated CF was removed by a modified size exclusion chromatography technique.35 Chromatography columns were prepared with 0.5 g of Sephadex G-50 mixed in 1X PBS. Columns were centrifuged at 1000g for 3 min (Fisher Scientific Heraeus Megafuge 16R Waltham, MA), removing the PBS and leaving a chromatography column packed with Sephadex. Liposome or DLNA samples with unencapsulated CF were added to the column and centrifuged for 100g for 10 min, and then 1000g for 3 min. This process was repeated twice.

Fluorescence Leakage Studies CF leakage experiments were conducted using a PerkinElmer LS55 fluorescence spectrometer with a PTP 1 Peltier holder for temperature control (Waltham, MA). The excitation and emission wavelengths were 492 nm and 517 nm, respectively, and the excitation and emission slit widths were set at 5 nm. Fluorescence intensities reported are the average collected over a 10 s integration time. The procedure for measuring CF leakage is depicted in Figure 1. A 2 µL sample



was added to 3 mL of 1X PBS in a quartz cuvette and the solution was continuously mixed with a magnetic stir bar. CF intensity readings of the samples were taken as a function of temperature between 25oC and 47oC at increments, or ∆T(i) = T(i)-T(i-1), of 1 oC (Figure 1a, b). At each increment the temperature was maintained at T(i) for 5 min. The CF intensity after 5 min reflects the total CF release caused by ∆T(i), which was confirmed by a plateau in the transient leakage curves (results not shown). At the end of the experiment (T(i) > 47oC), 10 µL of 2% Triton X-100 was added to the cuvette and the cuvette was sonicated to lyse the liposomes or DLNAs. The percentage of CF leakage was calculated from the following equation: % = 100 ×

() − −

where I(T(i)) was the CF intensity at temperature T(i), I0 was the initial CF intensity, and If was the CF intensity after lysing. All leakage studies were performed in triplicate and standard errors are reported. An example is shown for CF leakage from DPPC liposomes as a function of T(i) in Figure 1c, which will be discussed in more detail. T(i-1)

PBS+CF

∆Ti

PBS

PBS+CF

(b)

∆T(i)=T(i)-T(i-1)

Leakage

(a)

(c) Leakage (%)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Ti

Leakage (%) Time

8 6 4 2 0 25 30 35 40 45 T(i) (oC)


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Figure 1. CF leakage measurements. (a) Schematic of CF leakage associated with a increase in temperature from T(i-1) to T(i). CF intensity increases due to an increase in CF concentration in the bulk phase and a reduction in CF quenching within the D-LNA. (b) Generic depiction of leakage vs. time and the point (5 min) at which I(T(i)) was recorded. (c) CF leakage from DPPC liposomes as a function of T(i) (shown as an example). Standard error bars are shown for n = 3.

Differential Scanning Calorimetry Lipid phase behavior was investigated with a TA Instruments Nano DSC (New Castle, DE). DPPC and D-LNA samples were diluted in 1X PBS to 0.5 mM lipid. Samples were degassed and loaded into 0.76 mL capillary cells. The DSC cell was pressurized to 3 atm and equilibrated at 20oC. Heat capacity was measured during heating cycles from 20-50oC at scan rate of 1oC min-1.

Cryogenic Transmission Electron Microscopy (Cryo-TEM) DPPC liposome and D-LNA sizes and structures were examined by cryo-TEM. Specimens were prepared using ~5 µL of sample deposited on a Quantifoil grid with 2 µm lay carbon holes (Electron Microscopy Sciences, Hatfield, PA). Grids were robotically vitrified in liquid ethane using a Vitrobot (FEI Company). Prior to imaging, the vitrified grid was transferred and stored in liquid nitrogen. Imaging was performed in a liquid nitrogen cooled stage (Model 915, Gatan Inc., Pleasanton, CA) at 200 kV using a JEOL JEM-2100F TEM (Peabody, MA). Size analysis was performed using ImageJ software36 and the average diameters and standard deviations reported were based on 92 randomly selected liposomes or D-LNAs.



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Results and Discussion Nanoparticle and D-LNA characterization D-LNAs were prepared with two different size fractions of GNPs; GNP2 had an average diameter of 2 ± 0.5 nm and GNP4 had an average diameter of 4 ± 0.8 nm based on TEM analysis (Figure S1). GNP concentrations and calculated volume fractions within the D-LNAs at L:N ratios of 25,000:1, 10,000:1, and 5,000:1 are provided in Table 1.

Table 1. Concentration and volume fraction of GNPs loaded into D-LNAs. GNP fraction

GNP2 (1.99 ± 0.5 nm)

GNP4 (4.01 ± 0.8 nm) a

Concentration

L:N

GNP Volume Fractionc

(mg/ml)

(mM)b

Geld

Fluidd

25,000:1

0.02

0.10

0.4 ± 0.1%

0.4 ± 0.1%

10,000:1

0.05

0.25

1.1 ± 0.3%

1.0 ± 0.3%

5,000:1

0.10

0.50

2.2 ± 0.6%

2.0 ± 0.6%

25,000:1

0.16

0.8

1.1 ± 0.4%

1.0 ± 0.4%

10,000:1

0.40

2.0

2.8 ± 1.0%

2.5 ± 0.9%

5,000:1

0.79

4.0

5.6 ± 2.0%

5.1 ± 1.8%

L:N is the number of lipid molecules per nanoparticle.

b

c

a

Atomic gold concentrations.

Based on nanoparticle diameter with 1.8 nm (fully extended) DDT ligands.37

d

Based on volume fraction in the hydrocarbon acyl region of gel phase (825 Å3/lipid) or fluid

phase (913 Å3/lipid) DPPC bilayers.38

DPPC liposomes were spherical unilamellar structures with an average diameter of 101 ± 45 nm (Figure 2a). D-LNAs formed with GNP2 and GNP4 had average diameters of 56 ± 21 nm (Figure 2b, c) and 69 ± 36 nm (Figures 2d-g), respectively. In addition to reducing the liposome diameter, GNP loading led to faceted edges and thicker bilayers. GNP4 yielded liposomes 10 ACS Paragon Plus Environment

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containing GNP clusters within the bilayers; this likely also occurred for GNP2 based on previous work,21 however, we could not confirm this. It should be noted that direct evidence of GNP loading was difficult to obtain at the high L:N ratios used. As demonstrated by recent DLNA studies, nanoparticle loading can be more easily observed at significantly lower L:N ratios or higher nanoparticle concentrations.14, 15, 21, 27, 30, 31, 33 Furthermore, the structures were heterogeneous, with some D-LNAs containing GNP clusters that are clearly visible (Figure 2d, f, g) and others were GNPs were not directly observed. There were also ‘darker’ D-LNAs that suggest they were loaded with GNPs, but the individual GNPs could not be resolved. We believe that the difficulty in identifying bilayer-embedded GNPs stems in part from the limitations experienced during cryo-TEM imaging. This is depicted in Figure 2f-g where a D-LNA with a ‘dark spot’ is observed, but only when the TEM is over-focused do we see that this spot is comprised of a GNP cluster. This does not mean that all structures in the D-LNA samples contained embedded GNPs – it is plausible that there were also ‘empty’ liposomes present.



Figure 2. Representative cryo-TEM micrographs of (a) DPPC liposomes, (b, c) D-LNAs prepared with GNP2, and (d-g) D-LNAs prepared with GNP4. The L:N ratio is shown on each micrograph. (f, g) Micrographs of the same region with different focus, which was able to identify the individual GNPs that comprised the GNP aggregate contained within the D-LNA bilayer. White arrows identify the location of embedded nanoparticles that can be viewed directly.

Additional analyses were performed on D-LNAs prepared with GNP4 at a higher L:N ratio of 1,000:1 to confirm that GNPs were loaded into the bilayers. CF leakage was not examined at this higher L:N ratio. D-LNAs loaded with GNPs were easily visible by cryo-TEM analysis (Figure 3a, b). Magnified images of D-LNAs with slight over-focusing revealed that the GNPs were disordered within the bilayers (Figure 3c, d). 12 ACS Paragon Plus Environment

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Figure 3. Representative cryo-TEM micrographs of D-LNAs prepared with GNP4 at L:N = 1,000:1. Magnified and over-focused regions from (a) and (b) are shown in (c) and (d), respectively.

Thermal release (leakage) behavior CF leakage was examined as a function of temperature from 26 oC to 47 oC. This temperature range spanned the gel to rippled-gel pretransition (Tp = 34.4 oC ) and the rippled-gel to fluid melting transition (Tm = 41.3 oC ) of DPPC.39 DPPC liposomes showed increases in CF leakage between 32 oC and 36 oC, corresponding to pretransition (Lβ ➛Pβ’; region (i)➛(ii) in Figure 4a), and between 38 oC and 41 oC, corresponding to the melting transition (Pβ’ ➛Lα; region (ii)➛(iii) in Figure 4a). The CF leakage behavior reflects the two lipid bilayer phase transitions that occur within the temperature range examined. Comparatively, little change in CF leakage was observed 13 ACS Paragon Plus Environment


when the liposomes were in their gel (< 32 oC) or fluid (> 41 oC; region (iii) in Figure 4a) phases, consistent with previous studies.40

Figure 4. Cumulative carboxyfluorecein (CF) leakage as a function of temperature and L:N for DPPC liposomes and D-LNAs prepared with nanoparticle fractions (a, b) GNP2 and (c, d) GNP4. The error bars represent standard deviations of n = 3. Three distinct regions of CF leakage are shown reflecting the gel-rippled gel pretransition, (i)➛(ii) (blue); the rippled gel-fluid transition, (ii)➛(iii) (black); and the fluid phase (iii) (red). Normalized activation energies, Ea,NP/Ea,DPPC, for (b) GNP2 and (d) GNP4 determined from Arrhenius plots as a function of L:N corresponding to the lipid transitions or phase. Ea,NP/Ea,DPPC > 1 reflects greater resistance to CF leakage compared to DPPC. 14 ACS Paragon Plus Environment

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CF leakage from D-LNAs prepared with GNP2 exhibited a ‘temperature lag’ where leakage shifted to higher temperatures and the total amount of CF leakage at 47 °C was reduced by roughly 50% when compared to DPPC (Figure 4a). CF leakage increased between 35oC and 42oC, after which a modest linear increase in CF leakage was observed above 41oC (< 5%). This is further reflected in the normalized activation energies, EA,GNP/EA,DPPC, based on Arrhenius plots (Figure 4b). EA,GNP/EA,DPPC > 1 corresponds to a greater energy barrier for D-LNA leakage compared to DPPC. The leakage barrier was significant for temperatures spanning the rippledgel to fluid melting transition (35 to 42oC) and within the fluid phase (> 42oC), indicating that GNP2 altered the lipid phase behavior and, in turn, the leakage behavior. For temperatures spanning the gel phase and gel to rippled-gel pretransition, the barrier for D-LNA leakage was similar to DPPC. However, the ‘temperature lag’ suggests that greater energy was needed to initiate release. D-LNAs prepared with GNP4 exhibited different CF leakage behavior compared to GNP2. At the two lower GNP loadings (L:N = 25,000:1 and 10,000:1), increases in CF leakage were observed between 34 oC and 36 oC, and between 39 oC and 42 oC (Figure 4c). The ‘temperature lag’ for CF leakage was reduced with the larger GNPs (compared to GNP2). At L:N = 5,000:1 there was no ‘temperature lag’ and CF leakage increased linearly from 26 oC to 40 o

C, with no additional leakage above 43 oC. Results for EA,GNP/EA,DPPC indicate that GNP4

increased the leakage barrier corresponding to the rippled-gel to fluid melting transition and the fluid phase, relative to DPPC, but reduced the barrier corresponding to the gel phase and the gel to rippled-gel pretransition (Figure 4d). The exception here is that the highest loading, GNP4 also reduced the leakage barrier in the fluid phase.



The effect of GNP size on leakage is evident from the EA,GNP/EA,DPPC results. The leakage barrier for GNP4 is lower than that for GNP2 at all temperature regions and L:N ratios, consistent with less liposome stabilization when larger GNPs are embedded. The diameter of GNP4 is similar to the thickness of the lipid bilayer, and the energy penalty for accommodating larger particles is greater. The effects of this energy penalty, which reduced liposome stability against leakage, can be seen in the decrease in EA,GNP/EA,DPPC with increasing GNP4 loading. Hence, GNP2 had a greater effect on stabilizing the bilayer and reducing bilayer permeability compared to GNP4, which is consistent with the ability of liposome bilayers to accommodate smaller nanoparticles.

Combined leakage and phase behavior Results from CF leakage suggest that the leakage behavior is dependent upon bilayer phase behavior and the degree to which this changes in the presence of the GNPs. To examine this more closely we show the change in CF leakage, expressed as the numerical derivative of CF leakage as a function of temperature (∆leakage/∆T), relates to the thermotropic phase behavior determined by DSC. DSC results are summarized in Table 2. The pretransition and melting transitions appear as peaks in the excess heat capacity (cp; Figure 5 and 6).38, 39, 41

Table 2. DPPC and D-LNA lipid phase behavior and CF leakage temperatures. L:N DPPC GNP2b 25,000:1 10,000:1 5,000:1 GNP4b 25,000:1 10,000:1 5,000:1

Tp (°C)a Tm, on (°C)b Tm (°C) a 35.8 40.4 41.1 35.9 40.6 41.1 36.0 40.7 41.2 36.3 40.6 41.2 35.6e 39.4 40.8 e 35.6 39.1 40.6 37.0e 40.2 41.5

TCF (°C)c ∆T1/2 (°C)d 34.5, 39.5 0.9 40.5 0.9 40.5 0.9 35.5, 38.5 1.0 32.5, 40.5 1.6 33.5, 38.5 1.8 31.5, 37.5 1.5


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a

Tp and Tm correspond to maximum cp.

b

The melting onset temperature (Tm, on) is the temperature at which the rippled gel to fluid main

transition begins. c

TCF is the temperature corresponding to maxima (peaks) in the ∆leakage/∆T results. Dual peaks

reflecting Tp and Tm are shown, where applicable, and the greater of the 2 peaks are boldfaced. d

∆T1/2 is the width of the main transition curve at half-height of the peak.

e

Pretransition peak merged with melting transition peak. For L:N = 5,000:1 the pretransition was

not observed.

DPPC liposomes exhibited maximum changes in CF leakage at temperatures corresponding to the pretransition (exothermic peak at 35.7oC) and the melting transition (exothermic peak at 41.1 oC) (Figure 5a). There is remarkable agreement between the leakage and phase transition peaks. When the pretransition peak emerged between 30-31oC, the large ∆leakage/∆T peak also emerged. When this peak plateaued between 37-38oC the ∆leakage/∆T peak also plateaued. This same trend was found for the melting transition. Gel phase lipids are ordered with fully extended acyl tails in the trans conformation, whereas fluid phase lipids are disordered in the gauche conformation and exhibit a thinner bilayer.38 The rippled-gel phase, while not completely understood, is defined as a gel phase lipid bilayer with periodic domains of fluid phase lipids. The bilayer ripples are caused by the differences in gel and fluid phase bilayer thickness and hydration.41, 42 Changes in CF leakage are greatest during these transitions because they represent co-existing phase domains within the bilayers where transient leakage is high at the interface between the domains. Our results show that the change in CF leakage was greatest during the pretransition where gel and fluid phases coexisted.



Figure 5. Excess heat capacity (cp, solid line) and changes in CF leakage with temperature (∆leakage/∆T, symbols and dashed lines) and for DPPC (a) and D-LNAs formed with GNP2 (ac) with decreasing L:N ratio (increasing GNP loading). Standard error bars shown for n = 3. The vertical dashed lines correspond to the pretransition (Tp) and melting (Tm) temperatures for DPPC liposomes.


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D-LNAs formed with GNP2 do not exhibit pretransition or melting temperatures that are significantly different than that of DPPC based on the position of the peaks (Figure 5b-d, Table 2). However, the changes in CF leakage measured for the D-LNAs are considerably different. For DPPC, the greatest change in CF leakage occurred during the pretransition. In comparison, the change in CF leakage for the D-LNAs corresponding to the pretransition was much smaller, and the change in CF leakage corresponding to melting was larger. The effects of GNP loading on the bilayer phase transitions and associated CF leakage is more pronounced when D-LNAs were prepared with GNP4, though the behavior is different than that for GNP2. In this case, changes in CF leakage are observed at temperatures corresponding to the pretransition despite the fact that increasing GNP4 loading reduced or eliminated this transition (Figure 6a-c). The change in CF leakage was shifted to lower temperatures and at the highest GNP4 loading (L:N = 5,000:1) and significant CF leakage occurred between 26oC and 38oC.



Figure 6. Excess heat capacity (cp, solid line) and changes in CF leakage with temperature (∆leakage/∆T, symbols and dashed lines) and for D-LNAs formed with GNP4 with decreasing L:N ratio (increasing GNP loading). Standard error bars shown for n = 3. The vertical dashed lines correspond to the pretransition (Tp) and melting (Tm) temperatures for DPPC liposomes.

GNP4 loading also had a much larger effect on the interaction of bilayer lipids during main phase transition based on ∆T1/2 (Table 2). ∆T1/2 is the width of the main transition curve at half the height of the peak. This parameter relates to the cooperativity of neighboring lipids when undergoing the rippled gel to fluid phase transition.43 For a first-order lipid phase transition, the peak theoretically should be infinitely sharp because all the lipids would undergo the phase transition as a single unit. Broadening of the main transition peak is caused by the occurrence of


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lipids in multiple melting domains and phase states.44, 45 For GNP2, only at L:N = 5,000:1 can a change in ∆T1/2 be observed. Loading of GNP4 showed a 68-93% change in ∆T1/2. Analyzing the CF leakage results in Figures 5 and 6 suggests that the GNPs influence the thermal release behavior (bilayer permeability) by hindering or altering the bilayer phase behavior. Cryo-TEM results further show that the GNPs alter the D-LNA size and shape, relative to DPPC liposomes, which would also influence the release behavior (i.e. CF leakage represents a mass flowrate after time t, which is proportional to the bilayer permeability × total liposome surface area). This depicts an exciting yet complicated relationship between bilayer permeability and D-LNA structure, where GNP size and loading can be used to control the release behavior in a temperature-dependent manner. What is striking is that the changes in CF leakage and lipid phase behavior occurred at such low volume fractions of GNPs within the bilayer (Table 1). Multiple mechanisms could be at work including (i) changes in lipid phase behavior and stabilization or destabilization of lipid phase domains during phase transitions (inferred by this and previous work);13, 20, 25, 46, 47 (ii) changes in bilayer structure and mechanics such as thickness and elasticity, respectively;14, 20-22, 24 and (iii) changes in liposome size and structure, (also inferred by this and previous work) and the formation of non-bilayer structures.13 These mechanisms are interrelated and likely occur simultaneously, necessitating additional work to determine the how these mechanisms contribute to the release behavior. For example, bilayer permeability has been shown to increase with liposome curvature (decrease in liposome size).48, 49

However, in this work the smaller D-LNAs, relative to liposomes, exhibit lower CF leakage.

CF leakage behavior is more dependent on how GNPs alter lipid bilayer phase behavior and structure than on how they alter liposome size.



Additional insight can be gained by considering the kinetics associated lipid phase transitions. The characteristic time of a pretransition has been reported as 5 ± 2 min.50 With a DSC scan rate of 1oC min-1, results for DPPC show that the pretransition peak present over a 3oC temperature range is consistent with this characteristic time. In addition to GNPs disrupting lipid organization, either locally or globally within the bilayer, the GNPs would also exhibit low translational diffusion times within the bilayers that would impact the kinetics associated with lipid re-organization. This was apparent during the D-LNA pretransitions, where they were suppressed or merged with the melting transition at higher temperatures, and the greatest for GNP4, which occupy more space within the bilayer and are less mobile than GNP2. Given that CF leakage is greatest at the interface between phase domains, the net effect of inhibiting or delaying a phase transition would be lower CF leakage or an apparent temperature lag.

Conclusions As shown for the GNP D-LNAs, the permeability and phase behavior of liposomes can be manipulated by the size and concentration of embedded nanoparticles at low volume fractions within the bilayers. A lipid bilayer is approximately 4-5 nm thick, and nanoparticles that were smaller than the bilayer thickness (GNP2) affected the bilayer differently than nanoparticles that were closer to the bilayer thickness (GNP4). GNP2 caused the pretransition and main transition to merge while maintaining similar phase transition temperatures observed for DPPC liposomes. Unlike DPPC liposomes, which exhibited the greatest leakage at the pretransition temperature, the merger of pretransition and main transition caused by GNP2 corresponded to the merger of the thermal leakage curves associated with these transitions. These smaller nanoparticles demonstrated the ability to reduce spontaneous leakage at lower temperatures by providing 22 ACS Paragon Plus Environment

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greater bilayer stability. In contrast, GNP4 suppressed the pretransition while broadening the main transition, and maximum leakage was observed near the pretransition temperature or at lower temperatures. These findings demonstrate that liposome leakage and stability can be manipulated by the size of embedded nanoparticles even at low loadings. Thus, embedded nanoparticles could be used to engineer D-LNAs with desired release characteristics for therapeutic applications. The nanoparticles also influence the thermal leakage behavior, allowing temperature to be used as a triggered release mechanism.

Supporting Information Transmission electron microscopy characterization of gold nanoparticle size distribution.

Acknowledgements This material is based upon work supported by the National Science Foundation under Grant Nos. CBET-1055652 and CBET-1337061. We gratefully acknowledge Yanjing Chen and Richard Kingsley for their assistance with cryo-TEM, Everett Crisman for his assistance with FE-SEM, and Arijit Bose, Yanina Breakiron, and Fiaz Mohammed for their assistance, advice, and support on this research. Electron microscopy facilities were provided through the RI Consortium for Nanoscience and Nanotechnology.

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