Phosphorylated Peptide Functionalization of Lanthanide

Mar 1, 2016 - Advanced Cytometry Laboratories, ARC Centre of Excellence for Nanoscale BioPhotonics (CNBP), Macquarie University, Sydney, New South ...
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Phosphorylated Peptides Functionalization of Lanthanide Upconversion Nanoparticles for Tuning the Nanomaterial-Cell Interaction Chi Yao, Caiyi Wei, Zhi Huang, Yiqing Lu, Ahmed Mohamed ElToni, Dianwen Ju, Xiangmin Zhang, Wenning Wang, and Fan Zhang ACS Appl. Mater. Interfaces, Just Accepted Manuscript • DOI: 10.1021/acsami.6b01085 • Publication Date (Web): 01 Mar 2016 Downloaded from http://pubs.acs.org on March 2, 2016

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Phosphorylated

Peptides

Functionalization

of

Lanthanide

Upconversion Nanoparticles for Tuning the Nanomaterial-Cell Interaction Chi Yao†┴, Caiyi Wei†┴, Zhi Huang‡, Yiqing Lu∫, Ahmed Mohamed El-Toni║╪, Dianwen Ju§, Xiangmin Zhang‡, Wenning Wang†* and Fan Zhang†* †

Department of Chemistry, Collaborative Innovation Center of Chemistry for Energy

Materials, State Key Laboratory of Molecular Engineering of Polymers, Fudan University, Shanghai 200433, P. R. China. ‡

§

Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, P. R. China. School of pharmacy, Fudan University, Shanghai 201203, P. R. China.



Advanced Cytometry Laboratories, ARC Centre of Excellence for Nanoscale

BioPhotonics (CNBP), Macquarie University, Sydney, New South Wales 2109, Australia. ║

King Abdullah Institute for Nanotechnology, King Saud University, Riyadh 11451,

Saudi Arabia ╪

Central Metallurgical Research and Development Institute, CMRDI, Helwan 11421,

Cairo, Egypt ┴

These two authors contributed equally for this work.

KEYWORD: lanthanide upconversion nanoparticles, peptide, phosphorylation, cancer target, autophagy

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ABSTRACT Peptide modification of nanoparticles with high efficiency is critical in determining the properties and bioapplications of nanoparticles, but the methodology remains a challenging task. Here, by using the phosphorylated linear and cyclic peptide with the arginine–glycine–aspartic acid (RGD) targeting motifs as typical examples, the peptides binding efficiency for the inorganic metal compound nanoparticles were increased significantly after the phosphorylation treatment, and the modification allows improving the selectivity and signal-to-noise ratio for the cancer targeting and reducing the toxicity derived from non-specific interactions of nanoparticles with cells owing to the higher binding amount of phosphopeptide. In addition, molecular dynamics (MD) simulations of various peptides on inorganic metal compound surfaces revealed that the peptide adsorption on surface is mainly driven by electrostatic interactions between phosphate oxygen and the polarized interfacial water layer, consistent with the experimental observation of strong binding propensity of phosphorylated peptides. Significantly, with the RGD phosphopeptide surface modification, these nanoparticles provide a versatile tool for tuning material-cell interactions to achieve the desired level of autophagy, and may prove useful for the various diagnostic and therapeutic applications.

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INTRODUCTION Surface functionalization of hydrophobic inorganic nanoparticles (INPs) is prerequisite for biomedical applications, not only to render them reasonably water-stable and biocompatible but also to provide active sites for subsequent functional conjugation with biological or chemical moieties.1-8 When conjugated with biomolecular targeting ligands, especially peptides, these nanoparticles have been used to alter the nanomaterial-cell interaction.9-13 However, the design of high efficiency and affinity peptide functionalization method for the nanoparticles remains a challenge. The peptide functionalization of nanoparticles are currently mainly based on the 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide (EDC) coupling reaction, which is somewhat a long-time tedious method with low conjugation efficiency (the coupling efficiency depending on carboxylic acid activation, usually less than 10 %).14 On the other hand, compared with EDC coupling, non-covalent surface engineering with high-affinity binding peptides is particularly noteworthy due to its unparalleled versatility, biocompatibility, simplicity and scalability, but the mechanism by which non-covalent surface engineering of peptides operates remains unclear. What’s more, peptides show an intrinsic limitation regarding their metal-ion binding ability if only natural amino acids are used because these amino acids bear only simple oxygen ligands that exhibit moderate affinity for metal-ion binding. Recently, we demonstrated that non-covalent surface engineering of peptides for inorganic metal compound-based nanoparticles can be efficiently realized by

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modifying the hydroxyl functional group of a side grafted serine peptides into a phosphate group (phosphorylation) with one-step exchange approach.15 However, the amount of conjugated peptides was difficult to quantify, thus compromise the bio-application of the modified nanoparticles, such as tuning the autophagy of the tumor cells. In the present work, by using synthetic Arg-Gly-Asp-Ser (RGDS) and Cyclo(Arg-Gly-Asp-d-Phe-Lys)-Ser(c(RGDfK)S)

peptides

combined

with

“ligand-free” lanthanide-based upconversion nanoparticles (UCNPs)16-24 as a model system (Figure 1a), we studied metal binding in detail and showed that the phosphorylation of specific serine sidechains of the RGDS and c(RGDfK)S peptides to

phosphorylated

RGDS

(RGDS(p))

and

phosphorylated

c(RGDfK)S

(c(RGDfK)S(p)) dramatically enhanced their metal ion affinity without affecting their original target recognition performance. Furthermore, Molecular dynamics (MD) simulations for gadolinium-based nanoparticle surface and (non-)phosphorylated peptides system elucidated that phosphopeptide adsorption on surface is driven by electrostatic interaction between phosphate oxygen and interfacial water. The higher binding percentages of phosphopeptides in 30 ns simulations than that of non-phosphorylated peptides provided further support to the experimental results. We also demonstrated that phosphorylation of the peptides could significantly increase their capacity to bind to most of the transition metal nanoparticles besides the lanthanides materials. The high binding efficiency promised efficient cancer targeting performance of the phosphopeptide-coated UCNPs. Significantly, with the RGD

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phosphopeptide surface modification, these nanoparticles also provide a versatile tool for tuning material-cell interactions to achieve the desired level of autophagy. RESULTS AND DISCUSSION Phosphopeptide

surface

Phosphopeptides

with

modification

specific

for

sequences

the can

lanthanide be

easily

nanoparticles. synthesized

by

phosphorylating the hydroxyl of side-grafted serine-containing amino acids (Figure S1). Monodispersed 18-nm NaGdF4:18 %Yb3+/2 %Er3+@NaGdF4 hexagonal UCNPs were synthesized using oleic acid as the capping agent (Figure 1b,i).25,26 After a simple acid treatment process to remove oleate ligands from the surfaces of oleic acid (OA)-capped

UCNPs,27

We

used

designed

RGDS(p)

and

c(RGDfK)S(p)

phosphopeptides to modify the ligand-free UCNPs through coordinating interactions (Figure 1a). Representative TEM (Figure 1b, iii, iv) of the resulting RGDS(p) and c(RGDfK)S(p)

phosphopeptide-modified

UCNPs

(RGDS(p)-UCNPs

and

c(RGDfK)S(p)-UCNPs) show that these nanoparticles are well-dispersed in water and their shape is unchanged from that of the OA-capped hydrophobic UCNPs (Figure 1b, i). Binding properties of phosphopeptide to the lanthanide nanoparticles. To further demonstrate the necessity of peptide phosphorylation for enhancing the binding of peptides to metal compound-based nanoparticles, phosphorylated RGDS(p), c(RGDfK)S(p) and original non-phosphorylated RGDS, RGD, c(RGDfK)D peptides (Figure S1) were allowed to interact with the ligand-free UCNPs at constant concentration (Figure 2a). The amount of non-bound peptide was measured using

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reversed phase liquid chromatography (RPLC), and the amount of bound peptide was considered the binding capacity under this condition. RGDS(p) exhibited the highest binding capacity for differently sized UCNPs (Figure 2c) among the five kinds of peptides (14.54, 6.6 and 4.04 µg per 20 µg of the 4-, 18- and 40-nm UCNPs, respectively). In comparison to the non-phosphorylated RGDS, the binding capacities of RGDS(p) were increased approximately 5.6, 7.3 and 4.5 times on the 4-, 18- and 40-nm UCNPs, respectively. The strong coordination effect of the phosphate group in the c(RGDfK)S(p) cyclic phosphopeptide increased the binding efficiency compared to the non-phosphorylated c(RGDfK)D; the binding capacities were increased approximately 4.9, 18.3 and 5.0 times for 4-, 18- and 40-nm UCNPs, respectively. However, the binding capacities of c(RGDfK)S(p) (8.65, 1.83 and 0.50 µg per 20 µg of the 4-, 18- and 40-nm UCNPs) were obviously lower than those of the RGDS(p) for the UCNPs, indicating that steric hindrance hindered the coordination of the cyclic peptide on the nanoparticle surface, thereby decreasing the binding efficiency of the cyclic peptide compared with the linear peptide. Furthermore, as the particle size increased from 4 to 40 nm, the RGDS(p) binding capacity decreased gradually from 14.54 to 4.04 µg per 20 µg of UCNPs, indicating that the higher specific surface areas of the smaller nanoparticles generally increase the peptide binding capacity. Moreover, the binding of the phosphopeptides to the UCNPs was highly stable; for example, the RGDS(p)-UCNPs (18 nm) conjugate exhibited less than 2.0 % dissociation over a 48-h period at 37 °C (Figure 2b). Furthermore, the cyclic c(RGDfK)S(p) (6.1 %

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dissociation) presented higher binding stability compared to c(RGDfK)D (15.2 % dissociation). Significantly, the binding capacity of the phosphopeptides was much higher than that of the original non-phosphorylated peptides over a range of pH values (Figure 2e). In acid solution, the carboxyl or phosphate moieties might be partially ionized and dissociated, whereas in alkaline solution, the lanthanide ions on the UCNP surface might be partially blocked by hydroxide;28 in both cases, peptide binding might be decreased. Moreover, the binding capacity of the phosphopeptides was almost unaffected by ionic concentration, even in a high ionic concentration (0.5 M) NaCl solution (Figure 2f). Besides the results obtained for the UCNPs described above, we also demonstrated that phosphorylation of the peptides could significantly increase their capacity to bind to most of the lanthanide and transition metal nanoparticles; for example, the binding capacities of the RGDS(p) were approximately 1.9 to 8.5 times those of the RGDS for TiO2, Fe2O3, Y2O3, CeO2, Nd2O3, Eu2O3, Gd2O3, Tb2O3, Ho2O3, Er2O3, Tm2O3 and Yb2O3 nanoparticles (Figure 2d). MD simulations of the peptide modification on nanoparticles. To investigate the binding mechanism of the peptides on the lanthanides UCNPs at atomic level, MD simulations

were

performed

for

NaGdF4 crystal

surface

with

RGDS(p),

c(RGDfK)S(p), RGDS, c(RGDfK)D or RGD peptides in aquaous solution, respectively. In each system, a peptide was randomly positioned in the bulk water at a distance away from the surface. According to experimental information, (100) and

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(001) surfaces of NaGdF4 were modeled with periodical boundary conditions and solvated in water box to mimic the exposed surfaces of UCNP in solvent. All the titratable side chains of the peptides were set at their standard protonation states in neutral pH environment. For each peptide system, 30 ns MD simulations were conducted. During the 30 ns simulation time, equilibrium has been reached in all five systems, i.e., the peptide bound and unbound the surface for many times. To quantify the binding affinities of the peptides, average percentages of time with peptide bound on the surface was calculated for each system. RGDS(p) adsorbs on (100) and (001) surface in about 45 % and 12 % of the simulation time (Figure 3a), while RGD and RGDS are hardly bound with either surfaces with average adsorption probabilities less than 3 %. The binding probabilities of c(RGDfK)S(p) are 36% and 15% on (100) and (001) surfaces, respectively, much higher than that of c(RGDfK)D. The data is in agreement with the above experimental observations that the two phosphopeptides have significantly higher binding affinities than the non-phosphorylated peptides, indicating that phosphorylation largely improves the efficiency of UCNPs recognition of the peptides. Moreover, the fact that both RGDS(p) and c(RGDfK)S(p) bind to (100) surface better than (001) surface supports the deduction that peptide bindings have surface selectivity, which may account for the increasing binding capacity in smaller nanoparticles. We then analyzed the movement of functional groups of the peptides toward (100) crystal surface during the simulations to explore the origin of peptide binding affinity. Figure 3b-f depict the distribution of each group along the normal distance

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away from the solid surface. It is clear that phosphate groups of RGDS(p) and c(RGDfK)S(p) are distributed in the region closest to the surfaces, indicating strong interactions between phosphate and the surface (Figure 3b,c). In addition, termini COO- and sidechain of Asp residue in RGDS(p), as well as the sidechain of Asp in c(RGDfK)S(p) are also found in the area near (100) surface, with their negatively charged oxygen atoms pointing to surface (see the presentative structures of peptide in Figure 3b and c). This scenario implies that the driving force of phosphopeptide binding with NaGdF4 is the interactions between the negatively charged groups and the surface. However, in non-phosphorylated peptides, all the carboxylate groups display random distribution with no obvious binding propensties (Figure 3d-f). Therefore we can conclude that the specific interaction between phosphate groups and surface is essential to peptides binding. Another interesting observation in the simulation is that phosphorylated peptides do not interact with the metal atoms directly, but forming hydrogen bonds with the water molecules gathered at the interface between solid surfcae and bulk water, in majority of the simulation time (Figure 4a). In Figure 4b, the charge distribution of water reveals that water layer adjacent to solid surface is polarized due to the charged atoms at surface. Therefore we believe that the absorption process of phosphopeptide on UCNP is driven by the electrostatic interaction between phosphate group and the polarized interfacial water layer. Efficient specific cancer targeting of nanoparticles by phosphopeptide modification. After demonstrating that this general and efficient peptide

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phosphorylation method can significantly increase the capacity of the peptides to bind to the lanthanide nanoparticles as a model system, we then explored the performance of the phosphopeptide-modified UCNPs for cancer targeting using human glioblastoma U87MG cells (which express high levels of integrin αvβ3)29 (Figure 5). The membrane and cytoplasm of U87MG cells that had been treated with the RGDS(p)-UCNPs showed distinct green and red luminescent signals under 980-nm laser excitation because they were more specifically targeted by the RGDS(p)-UCNPs than by other RGD peptide- modified UCNPs (Figure 5). Whereas the c(RGDfK)S(p)-UCNPs-labeled cells exhibited slightly weaker signals than the RGDS(p)-labeled cells due to the lower binding capacity of c(RGDfK)S(p) on UCNPs, stronger luminescence signals were observed in comparison to those seen when other non-phosphorylated linear or cyclic peptides were used, further demonstrating the improved specific cancer cell-targeting ability provided by the phosphopeptide modification. Enhancement of autophagy induction by phosphopeptide modification. We then studied the cellular autophagic response of HeLa cells to RGDS(p)-UCNPs, and compared it with the response to non-phosphorylated peptides modified UCNPs and uncoated UCNPs. Autophagy was detected using the Cyto-ID Green Dye kit due to its selectivity for phagosomes, autophagosomes and autolysosomes in living cells. Cells that had been treated with RGDS(p)-UCNPs displayed more fluorescence dots than those treated with uncoated UCNPs, RGD-UCNPs or RGDS-UCNPs (Figure 6a), indicating significant enhancement of the UCNP-induced autophagic response by the

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RGDS(p)-UCNPs. Autophagosomes were observed using TEM (Figure 6b, i and ii). In contrast, no obvious autophagy occurred in HeLa cells that were not subjected to nanoparticle treatment (Figure 6c, right). Furthermore, as the concentration of RGDS(p)-UCNPs was increased, the number of fluorescence dots and the intensity of the punctuate fluorescence increased (Figure 6a). As the particle size increased from 18 to 200 nm, images of the affected cells showed more fluorescence dots and higher fluorescence intensity, which was caused by enhanced UCNP-induced autophagy (Figure 6c); this finding is consistent with the reduced cell viability (Figure S2). These results demonstrate that phosphorylated RGDS(p) represents an efficient tool for tuning material-cell interactions to achieve a desired level of autophagy, thus enabling the nanoparticles to reach target cells and perform the intended diagnostic or therapeutic tasks.

CONCLUSION In summary, we demonstrated that phosphopeptides obtained by phosphorylating specific serine sidechains dramatically enhanced the affinity of these peptides to nanoparticles without affecting their target recognition. This is advantageous for high consistency and ease in scaling up due to the simple add-and-mix coating procedure used and the ability to tune cellular autophagy to desired levels. Since the functionalized nanomaterials were known to affect the cell cycle and the growth micro-environment of tumor cells, we expect that our materials can induce tumor cell autophagy, therefore suppress tumor growth in vivo. Thus, these general and facile methods for functionalizing nanoparticles with peptides through phosphorylation

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tethering might be ideally suited for cancer diagnostic and therapy applications. Materials and Methods Synthesis of the linear peptides with the RGD targeting motifs. After a mixture of 2-Cl-trityl-Cl resin (500.0 mg, 0.75mmol/g), Fmoc-Ser(HPO3Bzl)-OH (0.2 mmol) and DIEA (300.0 µL) in DMF (5 mL) was shaken 1.5 h on a vortex mixer at room temperature, the resin was filtered off and washed several times with MeOH, DCM and DMF. The Ser(HPO3Bzl)-linked resin was then used for the construction of full length peptides. The protocols employed were: deprotection of Fmoc with 20% piperidine in DMF (15 min) and peptide coupling using 5 eq. of amino acid, 4.5 eq. of HCTU and 10 eq. of DIEA. All coupling reactions were set to perform 1 h at room temperature. In the synthesis of RGDS(p), amino acids Fmoc-Asp(But)-OH, Fmoc-Gly-OH and Fmoc-Arg(pbf)-OH were sequentially installed to construct peptide on the resin. The peptide-loaded resin was treated with a mixture of TIPS/TFA (5:95, 10 mL) for 2 h at room temperature. The resin was filtered off and was washed with TFA. The crude product was dissolved in water and purified by HPLC (conditions: Supelco Discovery C18, 250×10 mm, suitable ratio of acetonitrile-0.1%TFA in water-0.1%TFA, 4 mL/min) to give the final product. In the synthesis of RGDS, amino acids Fmoc-Ser-OH, Fmoc-Asp(But)-OH, Fmoc-Gly-OH and Fmoc-Arg(pbf)-OH were sequentially installed. In the synthesis of RGD, amino acids Fmoc-Asp(But)-OH, Fmoc-Gly-OH and Fmoc-Arg(pbf)-OH were sequentially installed.

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Synthesis of the cyclic peptides with the RGD targeting motifs. After a mixture of 2-Cl-trityl-Cl resin (500.0 mg, 0.75mmol/g), Fmoc-Asp-(OAllyl) (0.2 mmol) and DIEA (300.0 µL) in DMF (5 mL) was shaken for 1.5 h on a vortex mixer at room temperature, the resin was filtered off and washed several times with MeOH, DCM and DMF. The Fmoc-Asp-(OAllyl)-linked resin was then used for the construction of full length peptides. The protocols employed were: deprotection of Fmoc with 20% piperidine in DMF (15 min) and peptide coupling using 5 eq. of amino acid, 4.5 eq. of HCTU and 10 eq. of DIEA. All coupling reactions were set to perform 1 h at room temperature. In the synthesis of c(RGDfK)S(p), amino acids Fmoc-Gly-OH, Fmoc-Arg(pbf)-OH, Fmoc-Lys(Dde)-OH and Fmoc-D-Phe-OH were sequentially installed to construct peptide on the resin. Then, the resin was treated with Pd(PPh3)4, morpholine and HATU/HOBt/DIEA to afford cyclic products. Finally, the resin was reacted with 2% NH2NH2 in DMF and coupled with Fmoc-Ser(HPO3Bzl)-OH. After removal of Fmoc group, the peptide-loaded resin was treated with a mixture of TIPS/TFA (5:95, 10 mL) for 2 h at room temperature. The resin was filtered off and was washed with TFA. The crude product was dissolved in water and purified by HPLC to give the final product. In the synthesis of c(RGDfK)D, amino acids Fmoc-Asp-OH were installed instead of Fmoc-Ser(HPO3Bzl)-OH. Synthesis of UCNPs. Synthetic processes of UCNPs with different sizes and compositions are available in the supplementary material. In a typical method for the synthesis of 18-nm NaGdF4: 20 % Yb, 2 % Er@NaGdF4 UCNPs, 0.78 mmol of anhydrous GdCl3, 0.20 mmol of YbCl3 and 0.02 mmol of ErCl3 were added to a

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100-mL flask containing 10 mL of oleic acid and 15 mL of 1-octadecene. The mixture was heated at 150 °C for 30 min before cooling down to 50 °C to remove the water content from the solution. Shortly thereafter, 10 mL of methanol solution containing NH4F (2.75 mmol) and NaOH (2.5 mmol) was added and the resultant solution was stirred for 30 min to remove the methanol. After methanol was evaporated, the solution was heated to 300 °C under argon for 1 h and then cooled down to room temperature. The resulting 15-nm NaGdF4:Yb,Er nanoparticles were precipitated by addition of ethanol, collected by centrifugation at 6000 rpm for 5 min, washed with ethanol several times, and re-dispersed in 10 mL of cyclohexane. To obtain the 18-nm NaGdF4:Yb,Er@NaGdF4 UCNPs, 2.5 mL of the purified 15-nm NaGdF4:Yb,Er initial core solution was mixed with 4.0 mL of OA and 6.0 mL of ODE. The flask was pumped at 70 °C for 30 min to remove cyclohexane and residual air. Subsequently, the system was switched to Ar flow and the reaction mixture was further heated to 280 °C at a rate of ~20 °C/min. Then Gd-OA (0.05 M) and Na-TFA-OA (0.20 M) host shell precursors were alternately introduced by dropwise addition at 280 °C and the time interval between each injection was 15 min. The amounts of the shell precursors for each addition were calculated and summarized in Table S1. Finally, the obtained NaGdF4:Yb,Er@NaGdF4 UCNPs with a diameter of 18 nm were centrifuged and washed as above and dispersed in cyclohexane. Modification of phosphopeptide RGDS(p)-nanoparticles. OA-capped UCNPs (100 mg) were dispersed in a 10 mL aqueous solution of HCl (pH~4.0) and stirred overnight, during which reaction the carboxylate groups of the oleate ligands were

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protonated and the oleate ligands were away off the surface of nanoparticles. After the reaction was completed, the aqueous solution was mixed with ethanol, and centrifugated at 18000 rpm for 30 min to collect ligand-free nanoparticles. The product was washed with ethanol for at least 3 times, 18000 rpm for 30 min each. The ligand-free UCNPs (10 mg) were re-dispersed in 1 mL deionized H2O, and the pH of the solution adjusted to ~7.0. After adding 1 mg of RGDS(p) peptide, the aqueous solution was stirred at 0 °C for 2 hours. Then the product of RGDS(p)-UCNPs were collected by dialysis with MWCO 3000 Da dialysis bag to remove unbounded peptides. In vitro bioimaging for cancer cells with the phosphopeptide modified UCNPs. U87MG cells (~106/dish) were seeded in confocal dishes in 1 mL of Eagle’s minimum essential medium (EMEM) medium supplemented with 10% FBS and 1% antibiotics and incubated in CO2 for 24 h at 37 °C. Then, 100 µg/mL of RGDS(p)-UCNPs in HEPES was added and incubated in CO2 incubator for 30 min at 37 °C. Then the treated U87MG cells were washed with HEPES (3 × 1 mL). The cell samples were subsequently imaged by confocal laser scanning microscopy with wide-field or scan excitations with 980-nm continuous-wavelength (CW) laser. HeLa cell autophagic response. Cells were seeded at approximately 10,000 cells/well in 6-well clear bottom imaging tissue culture plates (NEST Biotechnology Co., Ltd., Jiangsu, China) and pre-treated as described. For confocal laser scanning microscopy, samples were stained by specific stain with Cyto-ID® autophagy detection kit (immunofluorescence confocal assay). For transmission electron

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microscopy (TEM), cells incubated with 1 mg/mL of 80-nm RGDS(p)-UCNPs for 24h, were treated as described. The samples were then stained with uranylacetate and lead citrate in a Leica Ultracut microtome and examined with a JEM-1400plus trans mission electron microscopy at an accelerating voltage of 80 kV. Characterization. TEM of nanoparticles was performed on a JEOL 2011 transmission electron microscope with an accelerating voltage of 200 kV. The cooling stage used was Gatan 636 Model with double-tilting function. The upconversion spectra were characterized on a Hitachi Fluorescence Spectrometer F4500 instrument and Ocean Optics UV-VIS-NIR CCD (QE65000) equipped with a 0~2 W adjustable continuous-wavelength laser (980-nm, Beijing Hi-Tech Optoelectronic Co., China) as the excitation source Dynamic light scattering (DLS) experiments were carried out on a Malvern Zetasizer 3600 (Malvern Instruments). Confocal luminescence images were made using an Olympus FV1000 confocal laser scanning microscope, with a continuous-wave (CW) NIR laser at 980 and 405 nm as the excitation source.

COMPUTATIONAL METHOD Force fields parameters of NaGdF4. The interatomic potentials of NaGdF4 crystal was described by a broadly applied semiempirical force field with the form of

 σ  12  σ  6  Etot = ∑ kr (rij − r0 ) + ∑ kθ (θ ijk − θ 0 ) + ∑ + ∑ 4ε  0  −  0   4 πε ε r  rij   rij   bond angle ij ij 0 r ij  . 2

2

qi q j

The unit cell of NaGdF4 was first built based on its crystal structure and treated with periodic boundary conditions30. The corresponding energy of bulk crystal was

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obtained by ab initio density functional theory (DFT) calculation based on the generalized-gradient

approximation

(GGA)

function

with

the

Perdew-Burke-Ernzerhof (PBE) correction31. The partial charges of atoms in unit cell were then assigned by Hirshfeld population analysis32. All the DFT calculations were perfromed by SIESTA 3.2 program33,34. The Lennard-Jones (LJ) paprameter were obtained in OPLS library and listed in Table S1. Parameters kr , kθ were obtained by fitting to the potential energy profiles obtained from DFT calculations. Since the experimental analysis suggests that adsorption is dominated by noncovalent bonding contribution, interaction between the crystal surface and peptide was described by electrostatic interaction and Lennad-Jones potential following the rule of geometric averages. DFT calculations were performed again for NaGdF4 (100) and (001) surface to derive their partial charges. The LJ parameters for surface atoms were set as the same with the value in Table S2. Molecular dynamics simulation. Each peptide was created by Molefacture in VMD software35. The charges of peptides RGDS(p), c(RGDfK)S(p) and c(RGDfK)D were derived by charge fitting to electrostatic potential from the quantum mechanical calculation of peptides in gas phase evironment. For each system, peptides were first solvated in water box and subject to a 100 ps NPT simulation, from which the initial peptide conformation for later calculations was randomly selected. The model of crystal was built as a 15×15×3 supercell and solvated in TIP3P water box of 7.19× 6.22×7.38 Å3 and 7.38×6.39×6.81 Å3 for NaGdF4 (100) and (001) surface respectively. All systems were treated with periodic boundary condition in three

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dimensions. The peptides were then randomly inserted into water box. Sodium and chlorine were added to neutral the whole system. The systems were first minimized with steepest descent method. After being heated up and equilibrated for 500 ps at 300 K in NPT ensemble, the systems were simulated for 30 ns production run in NVT ensemble. All the systems achieved equilibrium quickly within 10 ns. All the simulations were carried out by using GROMACS 4.6 program36 and uesd the particle mesh Ewald (PME) to calculate long-range electrostatic interaction37. SHAKE algorithm was used to constrain hydrogen bonds of peptides38. Langevin thermostat was used to maintain the temperature at 300K39.

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ASSOCIATED CONTENT Supporting Information Supporting Information is available from http://pubs.acs.org or from the author. Synthesis of the upconversion nanoparticles; calculation of the shell precursor amount for the growth of each monolayer; live cell treatment of UCNPs in vitro; the structures of designed RGD motifs-contained non-phosphorylated and phosphorylated peptides; the viability of HeLa cells interacting with various sizes and concentrations of RGDS(p)-UCNPs; HPLC and MS of designed RGD motifs-contained non-phosphorylated and phosphorylated peptides.

AUTHOR INFORMATION Corresponding Author *Fan Zhang, E-mail: [email protected], Tel: (+86)21-51630322; Fax: (+86)21-5163-0307; *Wenning Wang, [email protected]. Author Contributions †

Chi Yao and Caiyi Wei contribute equally for this work.

Funding Sources The work was supported by the NSFC (Grant Nos. 21322508, 21210004), the China National Key Basic Research Program (973 Project) (Nos. 2013CB934100,

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2012CB224805), and the Program for New Century Excellent Talents in University (NCET).

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FIGURE CAPTIONS

Figure

1.

a)

Schematic

peptide-functionalized

illustration

UCNPs

using

for

the

synthetic

designed

procedure

of

RGDS(p)/c(RGDfK)S(p)

phosphopeptides through non-covalent interaction. b) TEM and images of i) OA-capped, ii) ligand-free, iii) RGDS(p)-modified and iv) c(RGDfK)S(p)-modified NaGdF4:20 %Yb3+, 2 %Er3+@NaGdF4. Scale bar represents 50 nm.

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Figure 2. a) Peptide (20 µg/100 µL)-binding capacities of UCNPs (20 µg) with various particle sizes. b) Time course of the dissociation of bound peptides from the UCNPs, expressed as the percentage of the peptide released to the supernatant relative to the amount that was bound to the UCNPs at the start of the assay. c) TEM images of i) as-prepared 4-nm NaGdF4:Yb,Er@NaGdF4, ii) 40-nm NaGdF4:Yb,Er@NaGdF4, iii) 80-nm NaYF4:Yb,Er@NaYF4, and iv) 200-nm NaYF4:Yb,Er@NaYF4 UCNPs, respectively. d) Binding capacities of RGDS(p) and RGDS (20 µg) to various metal compounds (20 µg). e) The effect of pH on the binding of peptides to UCNPs. f) The effect of NaCl concentration on the binding of peptides to UCNPs.

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Figure 3. a) Percentage of peptides bound with (100) and (001) surface. b-f ) Left: Representative structures of peptide on (100) surface in five systems. Right: the density profile of the functional groups or residues distributing along the normal of the solid surface. From b to f, the peptides are RGDS(p), c(RGDfK)S(p), RGDS, c(RGDfK)D and RGD, respectively.

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Figure 4. a) The map of density distribution was calculated from simulation of RGDS(p)/NaGdF4 (100) system and projected onto a XY plane perpendicular to the solid surface. The cloudy shaped area is the density distribution of RGDS(p) peptide. The line shaped area is the density distribution of (100) surface. The other part represents the distribution of water. It is clearly seen that a layer of water locates at the interface between the solid surface and the bulk solvent. b) The distribution profile of charge density of water along the normal of (100) surface.

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Figure 5. CLSM images of U87MG cells treated with RGDS(p)-UCNPs, c(RGDfK)S(p)-UCNPs, RGDS-UCNPs, RGD-UCNPs, c(RGDfK)D-UCNPs and ligand-free UCNPs. The scale bar represents 20 µm. The statistical results on the right side shows the corresponding green and red UCL signal intensity.

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Figure 6. Enhancement of cell interaction and autophagy induction by peptide-modified UCNPs. a) Dose response of various peptide- modified UCNPs. The scale bar represents 20 µm. b) TEM images of HeLa cells that were treated for 24 h with 1000 µg/mL of RGDS(p)-UCNPs (i), and not treated as control (iii). The typical autophagosomes are indicated using arrowheads in the magnified area from the RGDS(p)-UCNPs treated cells (ii). The scale bars represent 2.0 µm. c) The size response of HeLa cells to RGDS(p)-UCNPs. The scale bar represents 20 µm.

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Table of Contents Graphic

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