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# High-throughput screening and rational design of biofunctionalized surfaces with optimized biocompatibility and antimicrobial activity

## Abstract

Peptides are widely used for surface modification to develop improved implants, such as cell adhesion RGD peptide and antimicrobial peptide (AMP). However, it is a daunting challenge to identify an optimized condition with the two peptides showing their intended activities and the parameters for reaching such a condition. Herein, we develop a high-throughput strategy, preparing titanium (Ti) surfaces with a gradient in peptide density by click reaction as a platform, to screen the positions with desired functions. Such positions are corresponding to optimized molecular parameters (peptide densities/ratios) and associated preparation parameters (reaction times/reactant concentrations). These parameters are then extracted to prepare nongradient mono- and dual-peptide functionalized Ti surfaces with desired biocompatibility or/and antimicrobial activity in vitro and in vivo. We also demonstrate this strategy could be extended to other materials. Here, we show that the high-throughput versatile strategy holds great promise for rational design and preparation of functional biomaterial surfaces.

## Introduction

In the clinic, a generation of biomaterials with improved biofunctions is urgently required1,2,3,4. As the interface between biomaterials and tissues is crucial5, biofunctionalization of the surfaces, i.e., improvement of the composition6, topography7,8, or hydrophobicity9 of the surfaces, is considered as a suitable strategy for the design of biomaterials. One approach to surface biofunctionalization is the display of peptides on biomaterials10,11. The peptides can be integrated onto biomaterial surfaces via physical adsorption12,13,14 or covalent immobilization15,16,17 to stimulate specific bioactivities, including biocompatibility18, hemocompatibility19, antimicrobial activity20, osteogenic activity21, or angiogenic activity22. Furthermore, more than one peptide can be used to functionalize the same surface of a biomaterial11,23.

Regardless of mono- or dual-peptide functionalization, the density of peptides on the surface often plays a critical role in the biofunction24,25,26. We27,28, along with others29,30,31, have revealed that low peptide densities can cause insufficient activities, while high peptide densities can generate undesired side effects. For example, antimicrobial peptide (AMP) has been utilized on biomaterial surface to inhibit bacterial infection32,33, but excessive AMP on the surface leads to cytotoxicity and inhibits tissue healing27,34. In addition, nonoptimized peptide densities on a dual-peptide functionalized surface could also sacrifice the biofunctions from one of the two peptides35,36,37. Therefore, it is of great importance to develop a method for the rational design of the optimized peptide densities, in particular, for dual-peptide functionalization.

However, to the best of our knowledge, there is still a lack of an efficient strategy for rational design and preparation of the biofunctionalized surfaces. As a traditional technique, orthogonal testing is time consuming, requiring the preparation of many surfaces for optimizing the parameters11,38. In some cases, microfluidic techniques were powerful to simplify the optimization process and obtain best conditions39,40,41. However, the systems were complicated to build. Still, it was not practical to apply them on some widely used biomaterials, e.g., titanium (Ti), directly to obtain the optimized preparation parameters for preparing biofunctionalized surfaces42,43,44.

A gradient surface can be used to collect a large amount of data by continuously varying the parameters in a single surface. Such surface can be employed to reveal the interactions between the cells and the surface properties45,46,47,48,49,50,51,52,53,54,55, e.g., surface topography45,46,47, the densities of biomolecules48,49,50,51, and surface compositions52,53,54,55. Unfortunately, until now, using a gradient surface to rationally design the optimized implants was still unrevealed, and almost no studies have been dedicated to the use of it as a platform for high-throughput screening of the optimized parameters for rational design and preparation of biofunctionalized surfaces.

To tackle this challenge, we develop a high-throughput strategy based on the gradient surface for rational design and preparation of a mono- or dual-peptide functionalized biomaterial surface, in particular, obtaining the optimized peptide densities/ratios and preparation parameters (Fig. 1). We choose Ti as a substrate because it is an important biomaterial widely used in the clinic for orthopedic and cardiovascular treatments56,57,58. We employ RGD peptide (abbreviated as RGD, Arg-Gly-Asp, improving biocompatibility59,60) and HHC36 peptide (abbreviated as AMP, Lys-Arg-Trp-Trp-Lys-Trp-Trp-Arg-Arg, improving antimicrobial activity61) as two model peptides. The two peptides bear a sequence of Cys-Pro-Ala-Pro-Ala-Pro at the N-terminus as a rigid spacer to improve their orientation and bioactivity62,63. Then, we introduce an alkene group onto the Ti surface via a silane coupling agent, and form mono- or dual-peptide functionalized surface by the thiol–ene click chemistry64,65,66,67 with a gradient in the peptide density via the “titration” or “evaporation” technique.

Here, we show the gradient surface with mono or dual peptides can be generated on the Ti surfaces. We further confirm that the resultant gradient surface can be used as a high-throughput platform to discover the optimized parameters for forming a specific peptide density that can achieve best biocompatibility and excellent antimicrobial activity both in vitro and in vivo. Finally, we demonstrate that our strategy can be extended to generate gradient surfaces on other materials such as gold.

## Results

### The RGD-functionalized Ti surface

All peptides with given sequences (Supplementary Table 1) were synthesized with or without a fluorescent tag (FITC or Mca). Before the preparation of the gradient surface, Ti was modified with silane-PEG2000-MAL (Ti–S). The results of XPS, AFM, and FTIR (Supplementary Figs. 13) demonstrated that the silanization was homogeneous on Ti–S. The CCK-8 and antimicrobial results showed that Ti–S had similar biocompatibility and antimicrobial activity as the pristine Ti (Supplementary Fig. 4). Subsequently, we developed a “titration” method to prepare a gradient surface on Ti–S (Fig. 2a). Ti–S was first vertically oriented in an empty well. Then, a thiolated RGD–FITC solution with a concentration of m (m = 0.1, 0.5, or 1 μM) was added to the well at a rate of 0.5 mL/h, elevating the liquid level in the well. RGD was conjugated to the freshly immersed section of the Ti–S by a thiol–ene click reaction between double bonds in maleimide (MAL) and thiol groups in RGD. It takes at least 2 h to complete a thiol–ene click reaction on a materials surface67. Thus, we set the “titration” time as 4 h to ensure the click reaction is completed for the area immersed in the solution for the longest time. After 4 h, the Ti substrate was pulled out of the well and washed with ethanol. For convenience, the Ti surface was artificially divided into ten bands, numbered 1–10 from top to bottom, with a band width of 1 mm. Thus, the higher number a given band belonged to, the longer the immersion time (and the click reaction time) that band experienced, and the higher the RGD density that band would have. Namely, the RGD density was expected to be increasing from band 1 to 10. The resultant gradient surface was denoted as Ti-Grad-mRGD, in which m represents the concentration of the RGD solution.

The fluorescent peptides were often employed to quantify the grafting density of the peptides on the surface11. Herein, we also used the FITC-labeled peptides, i.e., RGD–FITC and AMP–FITC, to calculate the grafting density of the specific peptide. The all-atom molecular dynamic (MD) simulation results showed that the peptides with and without FITC had similar radius of gyration (Supplementary Fig. 5), demonstrating that the introduction of FITC had a negligible effect on the steric hindrance. FITC fluorescence imaging of different bands (Fig. 2b and Supplementary Fig. 6) showed that the mean fluorescence intensities (MFI) of Ti-Grad-0.5RGD increased from 688.6 ± 14.4 to 991.4 ± 7.0 a.u. from band 1 to band 10 (Fig. 2c). By establishing a standard curve following the reported fluorescence method11 (Supplementary Fig. 7), we found that there was an inverse linear relation between MFI and the reciprocal of the RGD–FITC density. Thus, we determined that the RGD density increased from 31.1 ± 0.4 ng/cm2 (one molecule in 4.8 nm2) in band 1 to 43.6 ± 0.4 ng/cm2 (one molecule in 3.4 nm2) in band 10 on Ti-Grad-0.5RGD (Fig. 2d). The surface XPS N1s intensity from each band also exhibited that a higher band number was corresponding to a higher N content (and thus a higher RGD density) (Fig. 2e and Supplementary Fig. 8). Meanwhile, the FTIR results showed that the intensities of carbonyl groups in amide I increased from band 1 to band 10, further demonstrating the gradient distribution of RGD (Supplementary Fig. 9).

Based on the parameters extracted from bands 9 and 10 on Ti-Grad-0.5RGD, we prepared uniform Ti surfaces of Ti-RGD-P1 and Ti-RGD-P2 by immersing Ti–S in 0.5 μM of RGD or RGD–FITC solution for 216 and 240 min, respectively. Both Ti-RGD-P1 and Ti-RGD-P2 presented high fluorescence due to the high RGD–FITC density (Fig. 3c). According to the standard curve (Supplementary Fig. 7) and the MFI of both surfaces (954.5 ± 21.2 and 1000.9 ± 71.4 a.u. for Ti-RGD-P1 and Ti-RGD-P2, respectively), we found that these two surfaces had similar densities of RGD (41.4 ± 1.1 and 44.3 ± 4.4 ng/cm2, respectively) as bands 9 and 10 on Ti-Grad-0.5RGD, demonstrating that the conditions used for producing a particular band extracted from the gradient surface study could be effectively used to produce nongradient surface with the same properties as that band. Further, CCK-8 results revealed that compared to that of Ti–S, the biocompatibilities of Ti-RGD-P1 and Ti-RGD-P2 were improved 1.2- and 1.2-folds after 3 days (Fig. 3d). We also prepared Ti-RGD-P3 surface with 1 μM of RGD–FITC solution and 240 min of incubation. This surface had an increased MFI of 3045.5 ± 30.2 a.u. (Fig. 3c), demonstrating the larger density of RGD. However, Ti-RGD-P3 exhibited a little lower biocompatibility than Ti-RGD-P1 and Ti-RGD-P2, which was 1.1-fold that of Ti–S (Fig. 3d). This finding was consistent with our results (Supplementary Fig. 14) and other reports50 that an excessive RGD density had a negligible or even negative effect on improving the cell viability. The above results suggested that the biocompatibility of the surface could be optimized when the densities of RGD were ~41.4–44.3 ng/cm2 on Ti. Moreover, we could obtain the optimized preparation parameters (0.5 μM of RGD solution and 216–240 min of reaction time) for preparing such surfaces from the gradient RGD-functionalized Ti surface.

### The AMP-functionalized Ti surface

We also prepared the AMP-functionalized gradient surface on Ti–S based on the “evaporation” technique (Fig. 4a). By this method, the reaction time and the reactant concentration were also changed in different bands during the evaporation of the AMP–FITC solution (with Ti–S vertically oriented in the well) for 210 min. During the evaporation, the solution level was reduced to increase the concentration of the solution phase. As a result, a lower section of the Ti substrate with a larger band number would have been exposed to the AMP solution with a higher concentration and for a longer time and thus be modified with more AMP, making the AMP density increasing vertically from band 1 to 10. The resultant gradient surface was denoted as Ti-Grad-mAMP, in which m represents the concentration of the AMP solution.

The antimicrobial activity of Ti-Grad-20AMP was characterized by the Petrifilm method. The surface started to exhibit antimicrobial activity from the point denoted with the black line in band 6, which was set as P1 (antimicrobial starting point; 48.3 μM of AMP for 123.1 min) (Fig. 5a). Moreover, we found that the gradient surface exhibited excellent antimicrobial activity (without live bacteria being detected) from band 7 to 10 but poor antimicrobial activity (with live bacteria being detected) from band 1 to 6 (Fig. 5a). Consequently, we denoted the position with the purple line as P2 (the boundary between bands 6 and 7; 50.0 μM of AMP for 126.0 min) and that with the cyan line as P3 (midpoint of band 7; 57.1 μM of AMP for 136.5 min). According to the distribution of AMP (Fig. 4d), the AMP density at P1 was ~171.2 ± 13.1 ng/cm2 (same as that of band 6), and the densities of AMP at P2 and P3 were ~181.0 ± 12.2 ng/cm2 (same as that of band 7). In addition, we found that there was no gradient distribution of AMP on Ti-Grad-1AMP (Supplementary Fig. 21), which should be caused by the insufficient initial density of AMP. Consequently, the surfaces of Ti–S and Ti-Grad-1AMP did not exhibited gradient antimicrobial activity due to the lack of AMP, and the bacteria distributed uniformly on the surfaces (Supplementary Fig. 22).

Based on the preparation parameters obtained from the three positions (P1, P2, and P3) on Ti-Grad-20AMP, we prepared the nongradient surfaces and denoted these surfaces as Ti-AMP-P1, Ti-AMP-P2, and Ti-AMP-P3. The MFI of these three surfaces were 403.1 ± 9.1, 412.5 ± 21.4, and 426.6 ± 24.3 a.u. (Fig. 5b). According to the standard curve (Supplementary Fig. 16), the AMP densities on these three surfaces were determined to be 164.7 ± 5.1, 170.8 ± 12.8, and 180.2 ± 17.5 ng/cm2, respectively, which were similar to the densities of the specific sites (P1, P2, and P3) on Ti-Grad-20AMP. Furthermore, the antimicrobial assays illustrated that Ti-AMP-P1, Ti-AMP-P2, and Ti-AMP-P3 exhibited an efficiency of 98.0, 99.0, and 99.7% in the inhibition of S. aureus, respectively, compared to Ti–S (Fig. 5c).

Excellent antimicrobial activity for P1, P2, and P3 positions on gradient surfaces as well as the nongradient surfaces of their counterparts suggested that the optimized AMP densities were ~164.7–180.2 ng/cm2 on Ti implant. The parameters for producing such nongradient surfaces, which were derived from the gradient surface study, are to immerse Ti–S into an AMP solution (48.3–57.1 μM) for a given time (123.1–136.5 min, respectively). Unfortunately, besides the antimicrobial activity, these nongradient surfaces exhibited evident cytotoxicity to mBMSCs (Fig. 5d). Compared to Ti–S, the biocompatibilities of Ti-AMP-P3 were only 81.3 and 80.5% on day 1 and 3, respectively, due to the high density of AMP on the surface. In addition, the cytotoxicity of the uniform surface would further increase with its antimicrobial activity (Supplementary Figs. 23 and 24). It could also demonstrate the limitation of the mono-functionalized surfaces for biomaterials, suggesting the need to develop a AMP/RGD dual-peptide functionalized gradient surface.

### The dual-functionalized gradient Ti surface

The RGD-functionalized surfaces exhibited negligible antimicrobial activity and improved biocompatibility, whereas the AMP-functionalized surface had evident cytotoxicity but excellent antimicrobial activity at an improper peptide density. In addition, there exists an optimized density of RGD or AMP for best biocompatibility or antimicrobial capability. Therefore, we proceeded to construct RGD/AMP dual-peptide functionalized gradient surface and used such surface as a high-throughput platform for determining the best combination of RGD and AMP density that can achieve excellent combination of biocompatibility and antimicrobial activity.

We prepared the nongradient dual-functionalized surfaces of Ti-Dual-P1, Ti-Dual-P2, Ti-Dual-P3, and Ti-Dual-P4 using parameters corresponding to P1–P4 on Ti-Grad-Dual. We calculated the densities of AMP and RGD on these surfaces based on the standard curve (Supplementary Figs. 7 and 16) and fluorescence images (Supplementary Fig. 30). The densities of AMP on Ti-Dual-P1, Ti-Dual-P2, Ti-Dual-P3, and Ti-Dual-P4 were 238.1 ± 16.0, 274.7 ± 21.9, 305.4 ± 31.2, and 338.2 ± 26.2 ng/cm2, respectively (Supplementary Table 2), which were consistent with the densities between bands 7 and 8 on Ti-Grad-Dual (266.7 ± 12.3–329.7 ± 23.4 ng/cm2) (Fig. 6d). The densities of RGD on Ti-Dual-P1, Ti-Dual-P2, Ti-Dual-P3, and Ti-Dual-P4 were 31.2 ± 1.2, 29.9 ± 0.6, 28.4 ± 0.8, and 27.8 ± 0.4 ng/cm2, respectively (Supplementary Table 2), which were also similar to the densities between bands 7 and 8 on Ti-Grad-Dual (28.4 ± 0.3–28.0 ± 0.3 ng/cm2) (Fig. 6f). Moreover, compared to Ti–S, these surfaces exhibited antimicrobial activities and exhibited 50.2, 81.7, 93.3, and 98.2% inhibition of S. aureus, respectively (Fig. 6h). Besides excellent antimicrobial activity, Ti-Dual-P4 also exhibited good biocompatibility, being similar to Ti–S (Fig. 6i). These results indicate that RGD improved the biocompatibility of the AMP-functionalized antimicrobial surfaces. And the best molar ratio of AMP to RGD was 5.3:1 for a combination of excellent antimicrobial activity and biocompatibility.

### In vivo antimicrobial and osteogenesis assay in the infection model

Furthermore, we employed the extracted parameters of P3 on Ti-Grad-RGD, P3 on Ti-Grad-20AMP, and P4 on Ti-Grad-Dual to prepare the functionalized Ti rods (also denoted as Ti-RGD-P3, Ti-AMP-P3, and Ti-Dual-P4) and characterized the antimicrobial activity of the implants in vivo in the New Zealand rabbit bone defect model (Fig. 7a). After 7 days of acute infection, the antimicrobial assay and hematoxylin and eosin (H&E) staining were used to evaluate the antimicrobial activity in vivo (Fig. 7b). Both Ti-AMP-P3 and Ti-Dual-P4 rods exhibited an excellent antimicrobial activity compared to Ti rods, killing 99.2 and 99.6% of S. aureus on the implant, respectively, while Ti-RGD-P3 rods had no obvious antimicrobial activity (Fig. 7c, e). In addition, the immunohistochemistry staining results showed that bacteria (the spots pointed by red arrows) were present in the tissues around Ti, Ti–S, and Ti-RGD-P3 rods, while almost no bacteria were observed in the tissues around Ti-AMP-P3 and Ti-Dual-P4 rods (Supplementary Fig. 31). H&E staining results showed that the tissues around Ti–S and Ti-RGD-P3 rods had clear infiltration of inflammatory cells (blue spots pointed by black arrows), while the tissues around Ti-AMP-P3 and Ti-Dual-P4 rods had little destruction and infection (Fig. 7d). The inflammatory cell contents in Ti-AMP-P3 and Ti-Dual-P4 groups were 90.2 and 93.9% lower than those in the Ti group (Fig. 7f). It was reported that the serious infiltration of inflammatory cells was mainly caused by bacterial infection rather than by the antimicrobial implants72,73,74. Overall, Ti-AMP-P3 and Ti-Dual-P4 rods have the best antimicrobial activity.

We further characterized the osseointegration of the implants by the in vivo infection model adopted in other reports75,76 (Fig. 8a). After 7, 30, and 60 days of implantation, the results of methylene blue and basic fuchsin and toluidine blue staining of the hard tissue sections (Fig. 8b, c) showed that compared to other groups, there were negligible fibrous connective tissues around Ti-Dual-P4. Especially after 30 and 60 days of implantation, tight osteointegration was formed between Ti-Dual-P4 and tissues. Meanwhile, the amount of fibrous connective tissues around Ti-AMP-P3 was lower than that around Ti, Ti–S, and Ti-RGD-P3, as Ti-AMP-P3 could inhibit infection to protect the osteointegration. We quantitatively analyzed the methylene blue and basic fuchsin staining results as in other reports77,78,79. The results (Fig. 8d, e) showed that after 60 days of implantation and compared to Ti, Ti–S, and Ti-RGD-P3, the area of fibrous connective tissue at the interface of Ti-Dual-P4 was significantly reduced by 87.8%, 89.2% and 89.1%, respectively. The BIC of Ti-Dual-P4 was 4.5-, 5.7-, and 3.8-folds that of Ti, Ti–S, and Ti-RGD-P3, respectively. Although compared to Ti, Ti–S, and Ti-RGD-P3, the area of fibrous connective tissue at the interface of Ti-AMP-P3 was lower and its BIC was higher, Ti-AMP-P3 was not as good as Ti-Dual-P4, demonstrating that the single functionalization of AMPs with antimicrobial activities was not enough for the formation of the connective tissue.

In addition, following a reported method76,80,81, we employed the in vivo noninfection model to characterize the osteointegration of the implants (Fig. 7a). The results also showed that Ti-Dual-P4 had excellent osteointegration without bacterial infection, similar to that of Ti-RGD-P3 (Supplementary Fig. 32).

Collectively, the in vivo results demonstrated that only the dual-functionalized Ti implant (Ti-Dual-P4) exhibited the best combination of both excellent antimicrobial activity and osteogenic activity for bone defect repair at the same time.

### Extension of the high-throughput strategy to Au substrates

We further demonstrated that our strategy displayed broad-spectrum applications for other biomaterials, i.e., Au, which had wide application in biosensing82,83. We integrated the above peptides on Au directly via the thiol group. Similar to Ti, we prepared the RGD-functionalized, AMP-functionalized, and dual-peptide-functionalized gradient surfaces, and prepared the uniform surfaces with the optimized parameters extracted from these gradient surfaces (Supplementary Figs. 3359). The results demonstrated that our strategy can be extended to the controlled dual-peptide modification on a variety of biomaterials.

## Discussion

Biofunctionalization of surfaces with peptides is considered a suitable strategy for the design of biomaterials10,84. And for this strategy, previous studies showed that the density of peptides on the surfaces often played a critical role in achieving desired biofunctions48. Nonetheless, until now, there is still a lack of an efficient strategy for rational design and preparation of the biofunctionalized surfaces. For the functionalized surface, particularly the dual-functionalized surface on which a peptide may affect the function of another one, complex orthogonal tests were always employed to optimize a large number of variables, i.e., the densities and ratios of peptides, reaction time, and reactant concentrations11,85.

The gradient surface had been used to reveal the relationships between the cells and the surface properties45,46,47,48,49,50,55,85,86. In contrast to these reports, we demonstrated that the gradient surface could serve as a high-throughput platform to screen the optimized preparation parameters for rational design and preparation of the biofunctionalized Ti surface. In our strategy, due to the controllable preparation of gradient surface, the above-mentioned rational reaction parameters, i.e., reaction time and reactant concentration, could be extracted accurately. When a substrate was treated with these parameters, a nongradient surface was prepared with the densities and ratios of peptides highly similar to those of the specific site on the gradient surface. Subsequently, the uniform surfaces exhibited desired biofunctions, for both the mono- and dual-functionalized implant. These results demonstrated the high accuracy of our high-throughput strategy. Meanwhile, the extension of this high-throughput strategy to Au substrates illustrated that it had a broad-spectrum application.

We employed the orthopedic Ti implants as the substrates to verify the feasibility of our high-throughput strategy. Biomaterial-associated infection (BAI) and the delay of osseointegration are two main clinical reasons for the failure of surgery87,88,89. Previous reports and clinical experience showed that overcoming one of these two problems was not enough90. Our study also confirmed this phenomenon. For example, a mono-functionalized surface, Ti-RGD-P3, had high risk of bacterial infection due to the lack of AMP, but another one, Ti-AMP-P3, had fibrous connective tissues around it and showed delayed osseointegration due to the lack of RGD. Unfortunately, in the previous study, it is very difficult to explore Ti implants with both excellent antimicrobial activity and the promotion of osseointegration simultaneously by simply mixing two peptides because these two peptides had contradictory biological effects91. And finding their best density/ratio turned out to be difficult. However, with our high-throughput strategy to maximize the functions of the two peptides in one biomaterial, we could rationally design the dual-functionalized implant, i.e., Ti-Dual-P4, to show these two contradictory biological activities can be achieved at the same time. Compared with the implants functionalized with a single peptide, the multifunctional implant Ti-Dual-P4 could inhibit BAI and promote osseointegration in both infection and noninfection models in vivo (Figs. 7 and 8 and Supplementary Fig. 32). Also, the reported dual-functionalized implants often required the use of external stimuli, including electricity91, light75, and temperature92, but our rationally designed dual-functionalized implant did not rely on the external stimuli, making our approach more practical in the clinic.

Herein, a high-throughput strategy was developed based on gradient surfaces for rational design and preparation of peptide functionalized surfaces. This strategy provided a series of optimized parameters in a convenient and rapid manner, including the densities and ratios of the peptides, and the related preparation parameters of reaction time and reactant concentrations. With the extracted parameters from the gradient surface, we prepared both mono- and dual-peptide functionalized Ti surfaces with highly similar biofunctions to those of the specific site on the gradient surface, displaying biocompatibility or/and antimicrobial activity both in vitro and in vivo. In addition, our strategy could be extended to functionalize other biomaterials. We believe that this high-throughput method holds great potential for rational design and preparation of biomaterial surface.

## Methods

### Materials

Ti substrates (square with side length of 4 or 10 mm, Chemhui Metal Materials Ltd., Baoji, China), Gold (Au) substrates (square with side length of 4 or 10 mm, Tsinghua-Foxconn Nanotechnology Research Center, Beijing, China), silane-PEG2000-MAL (Ponsure Biotech, Inc., Shanghai, China), peptides (GL Biochemical Ltd., Shanghai, China), cells and bacteria (mBMSCs, ATCC CRL-12424; S. aureus, ATCC 6538P. VWR International, LLC, Pennsylvania, USA), cell counting kit-8 (CCK-8, Dojindo, Shanghai, China), and Petrifilm (Minnesota Mining and Manufacturing Company, Saint Paul, USA) were purchased. The reagents for the cell assay were got from Gibco (USA). The reagents for bacterial cultivation were purchased from Guangdong Huankai Microbial Technology Co., Ltd. (Guangzhou, China). The other reagents for preparation of the surfaces were got from Tianjin Damao Factory (Tianjin, China).

### Pretreatment of the Ti substrates

Ti substrates were cleaned ultrasonically with ethanol/deionized water, dried by nitrogen stream, and treated by 5 M NaOH (60 °C for 24 h). After being cleaned with deionized water for three times and dried by nitrogen stream, Ti substrates were reacted with 1 mL of silane-PEG2000-MAL solution (0.5 mg/mL, 95% ethanol and 5% deionized water) at 50 °C in an oil bath for 12 h. Then, Ti substrates were washed with ethanol, dried by nitrogen stream, and denoted as Ti–S.

### Preparation of the RGD-functionalized gradient Ti surface

The RGD-functionalized gradient Ti surface was prepared based on the “perfusion” technique. Ti–S (10 mm × 10 mm) was placed vertically into a 24-well plate. RGD or RGD–FITC was dissolved in ethanol at the specified concentrations (0.1, 0.5, or 1 μM). Then, the solution was injected into a well (0.5 mL/h) with a single-syringe pump (LSP01-1A, LONGER, Baoding). After 4 h, the whole substrate would be immersed in the solution. The sample was then cleaned with ethanol for three times immediately from top to bottom and denoted as Ti-Grad-mRGD, in which m represents the concentration of RGD solution (m = 0.1, 0.5, or 1 μM).

### Preparation of the AMP-functionalized gradient Ti surface

The AMP-functionalized gradient Ti surface was prepared based on the “evaporation” technique. Briefly, Ti–S (10 mm × 10 mm) was placed vertically in a 24-well plate, and AMP or AMP–FITC was dissolved in ethanol at the concentrations of 1, 20, or 50 μM. Then, 2 mL of the solution was injected to immerse the sample completely. The system was placed under air ejector fans. The air speed was controlled to evaporate the solution completely in 210 min. After that, the surface was washed with ethanol for three times immediately from top to bottom and denoted as Ti-Grad-mAMP, in which m represents the initial concentration of AMP solution (m = 1, 20, or 50 μM).

### Preparation of the dual-functionalized gradient Ti surface

The dual-functionalized gradient Ti surface was prepared based on the AMP-functionalized gradient Ti surface. Briefly, Ti-Grad-50AMP or Ti-Grad-20AMP was immersed into 0.5 μM of RGD, RGD–Mca, or RGD–FITC solution for 4 h. Then, the surfaces were cleaned with ethanol immediately from top to bottom, denoted as Ti-Grad-Dual (from Ti-Grad-50AMP) or Ti-Grad-20Dual (from Ti-Grad-20AMP).

### Calculation of the peptide density

The peptide density was calculated by the reported fluorescence method11. Briefly, a standard calibration curve of MFI-density was obtained as follows. 0.6 μL of AMP–FITC or RGD–FITC with different concentrations in deionized water was added directly onto Ti–S or Au surfaces (4 mm × 4 mm). The peptide solution concentration ranged from 4.43 μM (calculated with a peptide density of 0.1 molecule per nm2, which corresponded to the grafting densities of AMP–FITC and RGD–FITC of 42.2 and 23.2 ng/cm2, respectively) to 132.90 μM (determined from a peptide density of three molecules per nm2, which corresponded to the grafting densities of AMP–FITC and RGD–FITC of 1266.0 and 696.0 ng/cm2, respectively). After that, MFI of the surface was obtained via the fluorescence microscope (Eclipse Ti-U, Nikon) by choosing ten points randomly.

By the obtained standard curves, the densities of the peptides on the surfaces were calculated according to the MFI of the band/surface (10 mm × 10 mm) with RGD–FITC or AMP–FITC by adding 3.75 μL of deionized water. Three points in one band or five points on one uniform surface were chosen randomly for the calculation. Particularly, for the dual-functionalized gradient/uniform surface, we hypothesized that the integration of RGD would not impact the immobilized AMP. Therefore, the MFI values of the surfaces with AMP–FITC were collected as described above before the integration of RGD. In addition, we employed the combination of AMP and RGD–FITC to calculate the density of RGD on the dual-functionalized surface, and the MFI values of the surfaces were collected as described above.

### Extraction of the parameters from the specific sites on the gradient surface for producing uniform surfaces

The preparation parameters of the specific site on the gradient surface were extracted, including the peptide densities, reaction times, and reactant concentrations. For the RGD-functionalized gradient surface, the reaction time of the specific site (tx) was the same as that of the band having this site, and could be calculated as follows:

$${{t}}_{{x}}={{t}}_{{p}}\times \frac{{{N}}_{{x}}}{{N}}$$
(1)

where tp was the total time of the titering, Nx was the band no. for a specific site, and N was the number of the total bands (n = 10).

For the AMP-functionalized gradient surface and dual-functionalized gradient surface, the reaction time of the specific site with AMP (tx) and the reactant concentration of AMP (Cx) at time tx were calculated as follows:

$${{t}}_{{x}}={{t}}_{{e}}\times \frac{{{l}}_{{x}}}{{l}}$$
(2)
$$\,{{C}}_{{x}}=C\times \frac{{l}}{{{l-l}}_{{x}}}$$
(3)

where te was the total time of the evaporation, lx was the vertical distance between the specific site and the bottom of the substrate, l was the length of the substrate sides, and C was the initial concentration of the AMP.

Based on these parameters, we prepared the uniform surfaces by immersing the samples (Ti–S or Au) into the solution with the given concentration of peptide for the specific reaction time. Then, the surfaces were washed with ethanol for three times immediately.

### Antimicrobial assay

The antimicrobial activity of the samples against S. aureus was characterized by the Petrifilm or the agar plate. For Petrifilm assay, the samples (10 mm × 10 mm) were incubated with the bacterial suspension (20 μL, 1 × 105 CFU/mL in PBS) in 24-well plate. Meanwhile, the Petrifilm was pretreated with 1 mL of sterilized water. After 2 h of culturing (37 °C), the samples were dried naturally in a biological safety cabinet, and transferred to the Petrifilm immediately. After another 24 h of culturing (37 °C), the bacterial distribution was observed on the Petrifilm directly. In agar plate assay, the samples were incubated with the bacterial suspension (20 μL, 1 × 105 CFU/mL in PBS) in 24-well plate. After 2 h of culturing (37 °C), the samples were moved into a tube with the bacterial suspension. Then, 1.98 mL of PBS was injected into the tube. The tube was ultrasonicated for 2 min, and vortexed for another 1 min. After that, the detached bacteria were transferred to a new tube, and 60 μL of the suspension was added on the agar plate to characterize the bacterial viability.

### Cell assay

Mice mBMSCs were cultured with medium (High-Dulbecco’s modified Eagle Medium containing 10% fetal bovine serum). Cells in passages 3–5 were used for the following assays. The Ti samples (10 mm × 10 mm) were placed in 24-well plate, to which mBMSCs (3 × 104 cells per well) were added. In the fluorescence-based assay, after 24 h, the Ti samples were cleaned with PBS, and treated with 4 vol% neutral paraformaldehyde solution at 4 °C overnight. Then, the Ti samples were treated with 0.1% Triton for 12 min, F-actin solution (10 mg/L) for 60 min, and DAPI solution (5 mg/L) for 6 min. After that, the samples were cleaned with PBS and characterized with the Eclipse Ti-U instrument (Nikon, Japan) under the FITC and DAPI channels. To characterize the distribution of the cells on the gradient surface, we obtained 9 images along the gradient direction of the sample, then combined them into one image, and divided the combined image into 10 bands.

The biocompatibilities of the Ti samples were characterized by the CCK-8 assay. After being cultured with the cells for 24 and 72 h, the Ti samples were transferred to new 24-well plates. Then, the complete medium (350 μL) and the CCK-8 solution (35 μL) were added for each Ti sample. After 3 h of culturing, the OD value of the solution (100 μL) was characterized at the wavelength of 450 nm.

### In vivo assay

All in vivo experiments were approved by the Institutional Animal Care and Use Committee of Guangdong Medical Laboratory Animal Center (Foshan, China). Overall, 40 rabbits (12-week old and ~1.8 kg) were divided into five groups for in vivo assay (n = 8). First, all the rabbits were anesthetized with pentobarbital sodium, and two holes perpendicular to the centerline of the femur were drilled with an electric drill (Φ 2 mm) in each rabbit femur (the distance between the two holes was 1 cm). Then, for the infection model, 15 μL of bacterial solution (containing 7.5 × 106 CFU of S. aureus) was injected into the implant site as described in the literature93, and Ti rods (Φ 2 mm × 6 mm) were implanted. For the noninfection model, the Ti rods were implanted without bacteria. After being sealed with bone candle, the skin was stitched with sutures. Then, the rabbits were raised with the food without antibiotics.

For the antimicrobial assay, on the 7th day, the implants were extracted from the infection model of euthanized rabbits, treated with 3 mL of nutrient broth for 3 h at 37 °C, and vortexed for 1 min. Subsequently, the suspension was collected and diluted 103-fold and 104-fold in PBS. The diluted suspension (10 μL) was employed to characterize the bacterial viability on blood agar plates. The residual femur was successively treated with 4% formaldehyde for 3 days and EDTA solution for 60 days. The decalcified tissue was successively dehydrated with 75, 85, 90, 95, and 100% ethanol for 4, 2, 2, 1, and 0.5 h, respectively. After being treated with dimethylbenzene (three times, each for 10 min), the samples were fixed with paraffin wax (60 °C, 1 h), and cooled for solidification. After that, the tissue sections (4 μm) were obtained and baked (40 °C, 36 h). For the immunohistochemistry staining, the tissues were boiled in sodium citrate buffer for antigen retrieval and then incubated with primary antibody (anti-protein A, Abcam, Cambridge, UK) and secondary antibody (IgG H&L (HRP), Cambridge, UK) successively. Each antibody was diluted for 1000 times. For the pathological examinations, the tissue slices were treated with dimethylbenzene (two times, each for 15 min) and ethanol (three times, each for 5 min). The samples were washed with deionized water (5 min) and treated with hematoxylin (2 min). Then, the slices were treated by eosin solution (5 min), dehydrated with alcohol (10 min) as well as dimethylbenzene (30 min). Finally, the samples were characterized with the Eclipse Ti-U instrument (Nikon, Japan) under the bright field, and the inflammatory cell numbers were calculated from four areas.

For the osseointegration assay, after implantation for indicated times in infection or noninfection model, the Ti rods were collected and fixed in 10% formalin, dehydrated with acetone in −20 °C for eight times, and subsequently embedded in poly(methylmethacrylate). Then, the sections (10–20 μm) were made with a diamond histological saw, stained with methylene blue and basic fuchsin or toluidine blue for histological observation by the Eclipse Ti-U instrument (Nikon, Japan) under the bright field channels. The methylene blue and basic fuchsin staining images with ×10 magnification were employed for quantitative analysis, in which nearly a whole side of the interface between the implant and the cortical bone could be shown (~2 mm). Specifically, the area of fibrous connective tissue at the interface between bone tissue and implant was measured by Image J software, while the area in the bone tissue (not in contact with implant) was not calculated. The bone–implant contact length and implant total length were measured by the software in Eclipse Ti-U instrument (Nikon, Japan) to calculate the bone–implant contact (BIC, defined as bone–implant contact length/implant total length). Five sections in each group were chosen for the quantitative analysis.

### Statistics and reproducibility

The data shown as the mean ± standard deviation (SD) were obtained by at least three independent experiments and analyzed by the GraphPad Prism 8.0.0 software. The statistical significance of observed differences was analyzed by ANOVA test.

### Reporting summary

Further information on research design is available in the Nature Research Reporting Summary linked to this article.

## Data availability

All data are reported in this manuscript and supporting information also available from the authors upon request.

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## Acknowledgements

This work was financially supported by the National Key R&D Program of China (2018YFC1105402, 2017YFC1104402, 2020YFB0204803, 2016YFA0100900), National Natural Science Foundation of China (U1801252, 31771027, 32022041), Science and Technology Program of Guangzhou (201804020060), the Guangdong Natural Science Funds for Distinguished Young Scholars (2019B151502029), and the Pearl River Nova Program of Guangzhou (201806010156). L.W. thanks the Funds for Young Pearl River Scholars. C.M. would like to thank the support from the Institute of Biomedical Engineering, Science and Technology of the University of Oklahoma.

## Author information

Authors

### Contributions

C.M., L.W., and Y.W. conceived the study idea. L.W., X.S., and Y.Z. designed the experiments. Z.F., J.C., Y.Z., and L.W. performed the cell experiments. Z.F., J.C., L.W., G.H., H.X., and K.G. performed the bacterial experiments. Z.F., J.C., G.H., Q.L., and H.X. performed the animals experiments. L.X. performed the MD simulation experiments. All authors contributed to writing the manuscript, discussing the results, and implications and editing the manuscript at all stages.

### Corresponding authors

Correspondence to Lin Wang, Xuetao Shi, Yingjun Wang or Chuanbin Mao.

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### Competing interests

L.W., Z.F., J.C., G.H., and H.X. have applied for patents related to this study. The remaining authors declare no competing interests.

Peer review information Nature Communications thanks Fabiola Costa Moutinho, Jinjun Shi and the other anonymous reviewers for their contribution to the peer review of this work.

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Fang, Z., Chen, J., Zhu, Y. et al. High-throughput screening and rational design of biofunctionalized surfaces with optimized biocompatibility and antimicrobial activity. Nat Commun 12, 3757 (2021). https://doi.org/10.1038/s41467-021-23954-8

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