Article Cite This: ACS Biomater. Sci. Eng. XXXX, XXX, XXX−XXX
Mechanical Properties of Tandem-Repeat Proteins Are Governed by Network Defects Abdon Pena-Francesch,†,‡ Huihun Jung,†,‡ Mo Segad,†,# Ralph H. Colby,†,§ Benjamin D. Allen,∥,⊥ and Melik C. Demirel*,†,‡,⊥ †
Materials Research Institute, ‡Department of Engineering Science and Mechanics, Pennsylvania State University, University Park, Pennsylvania 16802, United States § Department of Materials Science and Engineering, ∥Department of Biochemistry and Molecular Biology, ⊥Huck Institutes of Life Sciences, Pennsylvania State University, University Park, Pennsylvania 16802, United States # Advanced Light Source, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States S Supporting Information *
ABSTRACT: Topological defects in highly repetitive structural proteins strongly affect their mechanical properties. However, there are no universal rules for structure−property prediction in structural proteins due to high diversity in their repetitive modules. Here, we studied the mechanical properties of tandem-repeat proteins inspired by squid ring teeth proteins using rheology and tensile experiments as well as spectroscopic and X-ray techniques. We also developed a network model based on entropic elasticity to predict structure−property relationships for these proteins. We demonstrated that shear modulus, elastic modulus, and toughness scale inversely with the number of repeats in these proteins. Through optimization of structural repeats, we obtained highly efficient protein network topologies with 42 MJ/m3 ultimate toughness that are capable of withstanding deformations up to 350% when hydrated. Investigation of topological network defects in structural proteins will improve the prediction of mechanical properties for designing novel protein-based materials. KEYWORDS: protein network, protein hydrogel, protein elasticity, squid ring teeth, bioelastomers, biomimetics, protein mechanics, topological network defects
■
INTRODUCTION Gene duplication has resulted in repetitive modular structures in natural occurring structural proteins.1−6 Such proteins share common motifs in their amino acid sequences. For example, the building blocks of elastin contain repetitive [VPGVG],7 resilin contains glycine-rich disordered domains cross-linked via tyrosines,8,9 and spider silk contains repetitive [AAAAAAAA] hydrophobic domains that assemble into cross-linked fibers through a natural drawing process.10,11 The tandem repetition (TR) of amino acid segments in structural proteins are favorable because periodic recurrent interactions promote structural stability and enhance the ultimate performance of biomaterials for survival of the organism. For example, in elastin, repetition provides elasticity to vertebrate animal tissues such as blood vessels, lungs, and skin.7,12 For resilin, repetitions provide efficient energy conservation and resilience in insect wings and jumping appendages.8 For silk proteins, repetitive domains provide tough and strong support for spider webs (predatory) and silkworm cocoons (protective).10,13 For squid, repetitions in squid ring teeth (SRT) proteins provide highstrength predatory appendages located in the suction cups along their arms and tentacles (Figure 1a).14,15 Although repetitive proteins have served as rich inspiration for biomimetic materials design,16−20 there are no universal rules © XXXX American Chemical Society
for structure−property prediction in these properties due to high diversity in their repeating-unit sequences and selfassembly mechanisms.10,21−24 Here, we studied the mechanical properties of structural proteins inspired by squid ring teeth15,23,25 as a function of tandem repetition in biosynthetic polypeptides. First, using a rolling-circle amplification method, we synthesized polypeptides with repetitive crystal-forming and amorphous blocks by varying the number of repeat units.21 Then, we measured mechanical properties using rheology and tensile experiments. Finally, we developed a network model based on entropic elasticity26,27 to predict structure−property relationship for SRT-inspired TR proteins. Topological defects in protein networks have a strong impact on mechanical properties.28−30 This study provides a descriptive and predictive model of mechanical properties in repetitive protein-based materials based on network defect theory. Received: October 31, 2017 Accepted: January 31, 2018 Published: January 31, 2018 A
DOI: 10.1021/acsbiomaterials.7b00830 ACS Biomater. Sci. Eng. XXXX, XXX, XXX−XXX
Article
ACS Biomaterials Science & Engineering
the same semicrystalline β-sheet domains21 but have not investigated how these crystalline domains are networked (Figure 1d and Supporting Information, Figure S1), which is the focus of this study. Considering both intra- and intermolecular β-sheet hydrogen-bonding, the network structure can adopt tie chain or loop conformations (i.e., connecting two neighboring β-sheet crystals or starting and ending at the same β-sheet crystal, respectively). Loops as well as dangling ends are considered defective structures in elastic networks because they do not bear any stress and have a weakening effect on the bulk mechanical properties. Estimation of defects in a protein network is a challenging task29,30,35 because defective chains are chemically and spectroscopically identical to effective chains (e.g., advanced mass labeling methods36,37 are required in particular cases). Fortunately, the density of network defects can be estimated from mechanical characterization and structural analysis for linear chains. The mechanical properties of TR proteins were analyzed by oscillatory rheology to estimate the molecular network morphology (Figure 2a). TR proteins were plasticized with water (20 ± 1% weight fraction, Supporting Information, Figure S2) and taken to a rubbery state to probe the disordered amorphous chains. The storage modulus (G′ > G″) of TR proteins exhibits a frequency-independent curve in the lowfrequency limit (Figure 2a), which is characteristic of crosslinked networks. Such behavior is explained by the formation of a hydrogen-bond-stabilized network in which the crystalline βsheet domains act as physical cross-links and the amorphous chains are stretchable network strands. A weak frequency dependence is observed at ω > 0.1 rad/s, which originates from the gradual relaxations of network defects (e.g., dangling ends and loop structures, common in imperfect polymer networks).29 Compared to other physically cross-linked protein gels (e.g., coiled-coil interactions, phase transition aggregation), TR proteins exhibit a stable MPa modulus over a wide range of frequencies due to the high stability of β-sheet interactions.17,22,38−40 We measured the viscoelastic response in a concentrated urea solution to estimate the possible contribution to the modulus from chain entanglements. Urea is a wellknown disruptor of protein structure that is extensively used in protein-unfolding experiments. Urea disrupts the β-sheet structures and eliminates physical cross-linking from the protein network (Supporting Information, Figure S3).41−44 Modulus of the TR proteins in urea decreases due to the unfolding of β-sheet domains and the consequent removal of cross-linking points (Supporting Information, Figure S3). However, the viscoelastic response still exhibits an overall frequency-independent modulus. Without hydrogen-bonded structures present to stabilize the network, these results suggest that chain entanglements are responsible for the modulus of the gels in urea.29 Therefore, we concluded that both entanglement and physically cross-linked network strands contribute to the modulus of the assembled TR proteins. To better estimate the chain morphology and separate the contribution from tiechains and entanglements, the total modulus for TR proteins is divided into two parts: G′t ≈ G′x + G′e, where G′x and G′e are the modulus of the cross-linked network and entangled network, respectively (taken as the equilibrium modulus at the low frequency limit) (Figure 2b). G′e is constant for all TR proteins and shows no dependence on repetition; the molecular-weight-independence of G′e is also observed in entanglement-dominated systems of high molecular weight.28 On the other hand, G′x has a linear dependence with reciprocal
Figure 1. SRT-inspired TR proteins. (a) SRT are located in the suction cups in arms and tentacles of squid species and are composed of a group of proteins with molecular weight ranging between 15 and 60 kDa. (b) Inspired by these proteins, we constructed tandem repeat proteins with a glycine-rich amorphous domain and a crystal-forming segment with the amino acid sequence AAASVSTVHH. Four TR proteins were constructed with repeats of n = 4, 7, 11, and 25. (c) SDS-PAGE shows the molecular weights four TR proteins expressed in E. coli. (d) Cross-linked gel model proposed for TR proteins studied in this manuscript.
■
RESULTS AND DISCUSSION Natural squid ring teeth are composed of a protein complex with several proteins ranging between 15 and 65 kDa in molecular weight. Analyses of SRT proteins revealed a common motif in the amino acid sequence across squid species, which consists of alternating AVSTH-rich and glycine-rich segments.21,31,32 This repetitive sequence motif with crystalforming and amorphous segments (AVSTH-rich and glycinerich, respectively) results in an architecture reminiscent of hydrogen bonded (β-sheet-rich) cross-linked networks.21,23,32 Although this motif is commonly observed across squid species, amino acid composition and length of the building block segments are diverse even within the same species,23,25,31,33,34 which impedes a comprehensive understanding of SRT mechanical properties. To facilitate the study of model, perfect-repeat polypeptides, we developed a rolling-circle amplification method to produce tandem-repeat coding sequences in a single cloning step.21 The designed building block for the TR proteins in this study is based on the crosslinked crystal-forming sequence PAAASVSTVHHP and amorphous sequence YGYGGLYGGLYGGLGY observed in native SRT (Figure 1b). Four sequences with repeat numbers 4, 7, 11, and 25 (with molecular weights 15, 25, 42, and 86 kDa, and named TR-n15, TR-n25, TR-n42, and TR-n86, respectively) were expressed in Escherichia coli, and their molecular weights were analyzed by SDS-PAGE, as shown in Figure 1c.21 We demonstrated earlier that the resulting polypeptides have B
DOI: 10.1021/acsbiomaterials.7b00830 ACS Biomater. Sci. Eng. XXXX, XXX, XXX−XXX
Article
ACS Biomaterials Science & Engineering
Figure 2. (a) Oscillatory rheology of TR proteins as a function of frequency sweep. (b) Equilibrium shear modulus of TR proteins as a function of reciprocal repeat unit 1/n. The contribution to the modulus from entanglements and from the β-sheet physically cross-linked network is divided as G′t ≈ G′x + G′e, where t is total, x is the urea, and e is the tie-chain modulus. (c) Rubbery tensile response of TR proteins under large deformation. Stress−strain curves show strain hardening at high elongation. Experimental data and fit to a freely jointed chain model are solid and dashed lines, respectively. (d) The tensile modulus shows a linear dependence with reciprocal repeat units 1/n. (e) Cyclic tensile testing of TR proteins. Toughness or energy absorbed per cycle shows three regions with increasing strain: (i) homogeneous deformation of random coils, (ii) unraveling of random coils, and (iii) backbone stretching. (f) Ultimate toughness upon failure shows a linear dependence with reciprocal repeat units 1/n.
repeat units 1/n, indicating that the tie-chain density and the network morphology are dependent on tandem repetition.28,29,45 The mechanical properties of TR proteins under large deformations were further investigated by tensile analysis. Figure 2c shows linear stress−strain dependence at low deformation whereas nonlinear strain−stress dependence is recorded at higher tensile strain. This strain-hardening response is explained by the finite extensibility of the protein chains. Freely jointed chain models have a Langevin dependence of the normalized end-to-end distance that accounts for the finite length of the chains:46−48
σ=
⎛1 + ε ⎞ 1 ⎟ − σ0 E N L−1⎜ ⎝ N ⎠ 3
(1)
where σ is the stress, σ0 is the stress at zero strain, ε is the strain, E is the tensile modulus, N is the length of the tie-chain, and L−1 is the inverse Langevin function. This freely jointed chain model, which has been used in polymers and biomolecules,47−49 describes accurately the elastomeric behavior of the TR polypeptides. The fitting of the stress curves gives N = 16−18 amino acids per tie-chain, which agrees with the glycine-rich strands 17 amino acid sequence. Furthermore, the tensile modulus E (Figure 2d) increases with tandem repetition, C
DOI: 10.1021/acsbiomaterials.7b00830 ACS Biomater. Sci. Eng. XXXX, XXX, XXX−XXX
Article
ACS Biomaterials Science & Engineering
Figure 3. (a) The elastic effectiveness parameter or εeff (fraction of elastically effective chains) is plotted against reciprocal repeat units 1/n for different crystallite sizes. Experimental data from shear modulus measurements (filled circles) fall within εeff predictions. (b) The elastic effectiveness parameter or εeff model (εeff ≈ 0 in defective networks and εeff ≈ 1 in nearly perfect networks) is validated with shear modulus, tensile modulus, and toughness data for TR proteins, showing good agreement.
and represents the fraction of elastically effective strands in a physically cross-linked network:
indicating a higher tie chain density increasing number of tandem repeats. The energy dissipation of TR proteins during stretching was measured in cyclic loading experiments (Supporting Information, Figure S4). The absorbed energy or toughness for every cycle is shown in Figure 2e, where 3 regions with different toughness slope can be differentiated: (i) fully reversible region (below 0.5 MJ/m3) at cycle strains up to 50−60%, (ii) moderate increase in absorbed energy at cycle strains between 50 and 150%, (iii) high hysteresis of absorbed energy at cycle strains higher than 150%. The toughness compared to strain cycle slopes are very similar in region i, where the disordered chains are homogeneously stretched, but the slopes are steeper for higher-molecular-weight proteins in regions ii and iii. TR proteins with higher tandem repetition exhibit higher toughness, indicating a higher number of stretched chains, as shown in Figure 2f. The tie chain density of polymer networks can be estimated by entropic elasticity theory models.28,29,50 Considering that the contribution to the modulus is kT per tie-chain, the modulus of any network is estimated according to the affine network model: G = νkT = ρRT/Ms, where ν is the number density of strands (number of network strands per unit volume), k is Boltzmann constant, T is temperature, ρ is density, R is the molar constant, and Ms is the average molar mass of a network strand. However, the affine network model considers a perfect cross-linked network and ignores network defects (i.e., ν is not known in real networks, causing discrepancies between predictive and experimental quantification of the modulus). Further modifications to the model include correction factors for nonperfect networks such as the phantom network model (e.g, a correction factor of 1 − 2/f, where f is the functionality of the network junctions and accounts for fluctuations of the cross-linking junctions) or Flory’s correction for terminal dangling ends (e.g., a correction factor of 1 − 2Ms/M, where M is the total molecular weight).28,50 However, none of these models accurately describe the TR protein networks due to the highly defective structures at low tandem repetition. If the loop defects are known a priori, which is only possible in limited polymer chemistries via mass labeling, the model could be improved.36,37 We define a structure factor, εeff or elastic effectiveness, to the network model, which introduces average network topology
G′total
1/3⎤ ⎡ ⎛ ⎞1/3 εeff ⎛ φx ⎞ ⎥ 1 φe ⎢ ⎜ ⎟ ⎜ ⎟ ≅ G′e + G′x = ρRT + ⎜ ⎟ ⎢ Me ⎜⎝ φ ⎟⎠ M x ⎝ φx0 ⎠ ⎥⎦ e0 ⎣
(2)
where Me is the average molar mass of an entanglement strand, Mx is the average molar mass of a network strand (extrapolated to n = ∞), and ϕ0 and ϕ are the initial and equilibrium swelling protein volume fraction, respectively (ϕe and ϕx denote swelling of entanglement and network strands, measured in aqueous urea and in H2O, respectively). Similar derivations of the effective branch functionality have been used to estimate defect content in large clusters of metal−organic frameworks.51 The elastic effectiveness or εeff structure factor accounts for the defects generated by β-sheet nanoconfinement (i.e., β-sheets can accommodate only a limited number of crystalline strands). Once a β-sheet crystallite is at maximum capacity due to internal energy constraints, the protein chain will move on to the next neighboring cross-link. The elastic effectiveness parameter can be estimated as εeff = (1 − βc/n), where βc is the β-sheet crystallite size in number of strands. For TR proteins, βc is equal to 4 strands, and n is the number of repeats in the polypeptide chain (e.g., 4, 7, 11, or 25). The elastic effectiveness parameter εeff is plotted against the reciprocal repeat unit 1/n for different crystallite strand capacities βc (Figure 3a). The experimental εeff values are in good agreement with the prediction obtained for a β-sheet crystallite capacity of 4 strands (Supporting Information, Table S1). The cross-linking and entanglement moduli of a perfect TR protein network (εeff = 1) can be calculated by extrapolation to an infinite number of repeat units. The average entanglement modulus is Ge = 1.42 ± 0.09 MPa, which corresponds to an average entanglement strand of Me = 2268 ± 146 g mol−1. On the other hand, the cross-linking modulus of a perfect TR network is extrapolated to Gx = 2.75 ± 0.15 MPa, which corresponds to an average entanglement strand of Mx = 1277 ± 174 g mol−1. If the average molecular weight per amino acid residue in the chain is approximated as 96.8 g mol−1, then the average entanglement and cross-linking strands have an estimated length of Me = 23.4 ± 1.8 and Mx = 13.2 ± 1.8 amino acids, which falls within the length of the repetitive disordered segment sequence (17 amino acids long). D
DOI: 10.1021/acsbiomaterials.7b00830 ACS Biomater. Sci. Eng. XXXX, XXX, XXX−XXX
Article
ACS Biomaterials Science & Engineering
Figure 4. Strain-induced β-sheet alignment. (a) Amide I band (FTIR) shifts toward the β-sheet region with increasing strain. (inset) β-sheet content increase at strains higher than 50%. (b) WAXS. (c) SAXS reveals the anisotropy and alignment of the β-sheet nanostructure with increasing strain.
Wide angle X-ray scattering (WAXS, Figure 4b) shows very similar diffraction patterns for unstretched and highly deformed (200% strain) Tr-n11 films. The two overlapping diffraction profiles (i.e., peaks characteristic of β-sheet structures at 2θ ≈ 9.5°, 19.5°, 25°)21 suggest that the size of β-sheet crystallites is conserved upon stretching (possibly due to the presence of proline in the amino acid sequence). The small increase in βsheet content might arise from localized β-sheet formation in the stretched amorphous chains. More importantly, small-angle X-ray scattering (SAXS, Figure 4c and Supporting Information, Figure S7) provided reorientation and anisotropy changes in TR-n11 films under tensile deformation. While nondeformed films have an isotropic 2D diffractogram, all stretched films have preferential directionality and exhibit increasing anisotropy with increasing strain. Films stretched to 50, 100, and 150% strain show increasingly stretched ellipsoidal diffraction patterns. When stretched to 200%, high anisotropy is observed due to the splitting in the diffractogram, suggesting that the βsheet semicrystalline structure of the protein is reorienting and aligning into a nematic phase. Whether the β-sheets are disrupted and reformed during stretching remains unclear at this point, although computational and experimental work on similar protein systems (e.g., silk fibroin) suggest that slippage of β-sheet strands might be possible.52,53 These results suggest that TR protein networks are isotropic and do not suffer significant structural changes at small deformations. However, high deformation induces chain alignment, β-sheet-crystal reorientation, and possible formation of β-sheet fibrils within the protein matrix. We also note that the orientation of the βsheet crystals seems to be less affected by the stretching in comparison with the large-scale morphology (Figure S8).
The combined measurements of tensile modulus and toughness (together with previous measurements of shear modulus) exhibit a linear dependence on the reciprocal repeat unit 1/n and have been used to validate the elastic effectiveness model (Figure 3b). Due to β-sheet confinement, the number of tie chains increases with n (i.e., high εeff is achieved with high tandem repetition and small β-sheet crystallites). On the other hand, low tandem repetition TR proteins (βc ≈ n) self-assemble into loop-rich structures with εeff ≈ 0 (i.e., high density of network defects result in weak and brittle materials). The model not only accurately describes the mechanical properties of TR proteins but also provides a predictive framework for quantifying the network morphology (effective vs defective strands) in repetitive proteins. Finally, we return back to the validity of point cross-link topology. In the entropic elastic network model, we assumed that β-sheet crystallites are isotropic in orientation (1/3 constant in eq 1) and do not deform under tensile or shear loads. Obviously, this assumption is not justified and should be investigated in detail. Hence, we studied the evolution of the network structure under deformation using infrared spectroscopy and X-ray diffraction. Fourier transform infrared (FTIR) spectroscopy data of TR-n11 films provides insight during stretching (Figure 4a). TR-n11 was chosen for this study compared to other TR proteins due to its molecular weight (42 kDa), which is most representative of the average molecular weight of native SRT protein complex.25 The amide I band (i.e., 1600−1700 cm−1 corresponding to the carbonyl stretching vibration) shows a progressive shift toward lower wavenumbers with increasing strain. Analysis of the secondary structure content of the stretched TR-n11 film by Fourier selfdeconvolution (FSD) and profile fitting (Supporting Information, Figures S5 and S6) revealed an increase in β-sheet content from 54 to 60% at 200% strain (Figure 4a, inset), most likely due to chain alignment and backbone stretching. However, the β-sheet content does not change at low deformations (0−67% strain) because of the reversible deformation of the random coil chains, as also confirmed by cyclic loading region (i) in Figure 2e.
■
CONCLUSIONS In summary, we studied mechanical properties of SRT inspired TR proteins, which assemble into physically cross-linked elastic networks. We demonstrated that varying the total number of building blocks in the polypeptide chain results in major morphological differences that define the mechanical properties of the protein material. An entropic elasticity model with βE
DOI: 10.1021/acsbiomaterials.7b00830 ACS Biomater. Sci. Eng. XXXX, XXX, XXX−XXX
Article
ACS Biomaterials Science & Engineering
at a rate 5 mm/min to a strain of 0.5, 1, 1.5, 2.5, 5, 7.5, 10, 15, 20, 30, and 40 mm and back to 0 mm in each cycle. SAXS. The small-angle X-ray scattering experiments were performed using SAXS/WAXS laboratory beamline (Xeuss 2.0) at the Materials Characterization Lab user facility in Penn State. The Xray source is GeniX3D, which is a compact system of microfocus sealed tube and X-ray optics with wavelength of 1.54 Å. This laboratory beamline is equipped with Pilatus 200 K-A detector, and the sample-to-detector distance was 2.5 m with 20 min of exposure time. The samples were placed into an aluminum holder with no mica or Kapton windows.
sheet crystallite nanoconfinement is proposed to evaluate and quantify the network defects (e.g., loop strands and dangling ends) and morphology. The model was validated with extensive mechanical characterization and accurately describes the viscoelastic response of synthetic TR polypeptides with molecular weights varying from 15 to 86 kDa. High tandem repetition and a small β-sheet crystallite size produce an increased density of tie chains, which results in more effective protein networks with higher moduli and toughness. Furthermore, the optimization of the tie-chain density and network morphology led to SRT-inspired high strength elastomeric protein materials (up to 350% strain) that have not been reported previously. These elastomeric SRT-inspired materials exhibit strain-induced crystallization and alignment, resulting in highly anisotropic protein networks. The work presented here introduces new design rules in engineering biomimetic protein materials, taking advantage of tandem repetition of modular β-sheet and disordered domains in structural proteins.
■
■
ASSOCIATED CONTENT
S Supporting Information *
The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acsbiomaterials.7b00830. Table with experimental and calculated elastic effectiveness parameter, structural information (infrared spectroscopy and X-ray diffraction data) of TR polypeptides, water content analysis, unfolding of β-sheets, cycling tensile testing, and analysis of stretched protein films (PDF)
MATERIALS AND METHODS
Sample Preparation. TR proteins are constructed and expressed based on the protocols that are described earlier.21 All protein (15, 25, 42, and 86 kDa) was dissolved in 1,1,1,3,3,3-hexafluoro-2-propanol (HFIP) to a concentration of 50 mg/mL in a sonication bath for 1 h. Protein solution was cast on polydimethylsiloxane (PDMS) molds, and solvent was evaporated overnight at room temperature in the chemical fume hood. Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy). Spectral data were collected (Thermo Scientific Nicolet 6700 FT-IR) under attenuated total reflection (diamond crystal) mode using Happ-Genzel apodization with 4 cm−1 resolution from wavenumber 400 to 4000 cm−1 (256 scans per measurement). Fourier self-deconvolution (FSD) and second derivative of the amide I band (1580−1706 cm−1) were performed by OMNIC software (Thermo Scientific, v7.3). Signal processing and curve fitting were performed as described elsewhere.54,55 Rheology. TR proteins were compression molded in PDMS molds (hydrated, 70 °C) into disk shaped samples 2 mm in diameter and 1 mm in height. Measurements were performed in a Rheometric Scientific ARES rheometer with a 3 mm diameter parallel plate geometry with a 10 mL liquid reservoir in the bottom plate. Samples were adhered to the plates using Click Bond CB200 adhesive (2 h curing time at room temperature, with modulus in the GPa range). Liquid was fed into the reservoir with a peristaltic pump (Ultra Low Flow Mini-pump model 3384, Control Company) with a flow rate of 0.4 mL/min to compensate for evaporation, and the system was equilibrated at 70 °C for 90 min. Ultrapure water and 8 M urea were used for measuring the total modulus and the entanglements, respectively. Dynamic frequency scans with 2% strain were performed from 0.001 to 100 rad/s. Swelling of TR Films. Water uptake was estimated by recording volumetric swelling in a microscope and by thermogravimetric analysis (TGA). TGA was performed on a TA Instruments Q50 instrument coupled to a Pfeiffer vacuum mass spectrometer. Samples were heated from 25 to 500 °C at a heating rate of 10 °C/min in a helium gas flow (90.0 mL/min). Hydrated samples were immersed in DI water for 2 h at room temperature before the experiment, and excess surface water was removed before transferring the samples to the furnace. The initial sample weight was in the range between 6.5 and 9.0 mg. Mechanical Testing. TR films are casted in dog-bone shape with 30 μm in thickness, 2 mm in width, and 15 mm in gauge length from HFIP solution. Specimens were tested in an Instron model 5866 load frame with a 10 N cell and a 7.5 L custom-built liquid chamber. All measurements were performed with the specimens immersed in DI water. Tensile stretching measurements were performed at a rate of 5 mm/min until failure. Cyclic stretching measurements were performed
■
AUTHOR INFORMATION
Corresponding Author
*E-mail:
[email protected]. ORCID
Melik C. Demirel: 0000-0003-0466-7649 Author Contributions
M.C.D. conceived the idea and supervised the research. B.D.A introduced the tandem-repeat strategy in consultation with M.C.D. and supervised molecular biology and protein production efforts. A.P.F. performed the characterization measurements and developed the model. B.B. and A.P.F. performed the proton conductivity measurements in collaboration with M.H. and M.C.D. H.J. worked on the cloning, recombinant expression, and purification of proteins with B.D.A. M.S. performed WAXS and SAXS measurements and data analysis. All authors contributed to writing and revising the manuscript and agreed on the final content of the manuscript. Notes
The authors declare no competing financial interest.
■
ACKNOWLEDGMENTS M.C.D., B.D.A., A.P.F., and H.J. were supported partially by the Army Research Office under Grant W911NF-16-1-0019 and the Materials Research Institute of the Pennsylvania State University.
■
REFERENCES
(1) Andrade, M. A.; Perez-Iratxeta, C.; Ponting, C. P. Protein Repeats: Structures, Functions, and Evolution. J. Struct. Biol. 2001, 134, 117−131. (2) Dobson, C. M. Protein Misfolding, Evolution and Disease. Trends Biochem. Sci. 1999, 24, 329−332. (3) Söding, J.; Lupas, A. N. More than the Sum of Their Parts: On the Evolution of Proteins from Peptides. BioEssays 2003, 25, 837−846. (4) Lupas, A. N.; Ponting, C. P.; Russell, R. B. On the Evolution of Protein Folds: Are Similar Motifs in Different Protein Folds the Result of Convergence, Insertion, or Relics of an Ancient Peptide World? J. Struct. Biol. 2001, 134, 191−203.
F
DOI: 10.1021/acsbiomaterials.7b00830 ACS Biomater. Sci. Eng. XXXX, XXX, XXX−XXX
Article
ACS Biomaterials Science & Engineering (5) Balaji, S. Internal Symmetry in Protein Structures: Prevalence, Functional Relevance and Evolution. Curr. Opin. Struct. Biol. 2015, 32, 156−166. (6) Longo, L. M.; Kumru, O. S.; Middaugh, C. R.; Blaber, M. Evolution and Design of Protein Structure by Folding Nucleus Symmetric Expansion. Structure 2014, 22, 1377−1384. (7) Wise, S. G.; Mithieux, S. M.; Weiss, A. S. Engineered Tropoelastin and Elastin-Based Biomaterials. Adv. Protein Chem. Struct. Biol. 2009, 78, 1−24. (8) Qin, G.; Hu, X.; Cebe, P.; Kaplan, D. L. Mechanism of Resilin Elasticity. Nat. Commun. 2012, 3, 1003. (9) Elvin, C. M.; Carr, A. G.; Huson, M. G.; Maxwell, J. M.; Pearson, R. D.; Vuocolo, T.; Liyou, N. E.; Wong, D. C. C.; Merritt, D. J.; Dixon, N. E. Synthesis and Properties of Crosslinked Recombinant proResilin. Nature 2005, 437, 999−1002. (10) Gosline, J. M.; DeMont, M. E.; Denny, M. W. The Structure and Properties of Spider Silk. Endeavour 1986, 10, 37−43. (11) Jin, H.-J.; Kaplan, D. L. Mechanism of Silk Processing in Insects and Spiders. Nature 2003, 424, 1057−1061. (12) Dorrington, K. L.; McCrum, N. G. Elastin as a Rubber. Biopolymers 1977, 16, 1201−1222. (13) Gosline, J. M.; Denny, M. W.; DeMont, M. E. Spider Silk as Rubber. Nature 1984, 309, 551−552. (14) Williams, L. W. The Anatomy of the Common Squid; E. J. Brill, 1909. (15) Nixon, M.; Dilly, P. N. Sucker Surfaces and Prey Capture. Symp. Zool. Soc. London 1977, 1. (16) Yang, Y. J.; Holmberg, A. L.; Olsen, B. D. Artificially Engineered Protein Polymers. Annu. Rev. Chem. Biomol. Eng. 2017, 8, 549−575. (17) Li, H.; Kong, N.; Laver, B.; Liu, J. Hydrogels Constructed from Engineered Proteins. Small 2016, 12, 973−987. (18) DiMarco, R. L.; Heilshorn, S. C. Multifunctional Materials through Modular Protein Engineering. Adv. Mater. 2012, 24, 3923− 3940. (19) Langer, R.; Tirrell, D. A. Designing Materials for Biology and Medicine. Nature 2004, 428, 487−492. (20) Webber, M. J.; Appel, E. A.; Meijer, E. W.; Langer, R. Supramolecular Biomaterials. Nat. Mater. 2016, 15, 13−26. (21) Jung, H.; Pena-Francesch, A.; Saadat, A.; Sebastian, A.; Kim, D. H.; Hamilton, R. F.; Albert, I.; Allen, B. D.; Demirel, M. C. Molecular Tandem Repeat Strategy for Elucidating Mechanical Properties of High-Strength Proteins. Proc. Natl. Acad. Sci. U. S. A. 2016, 113, 6478−6483. (22) Muiznieks, L. D.; Keeley, F. W. Biomechanical Design of Elastic Protein Biomaterials: A Balance of Protein Structure and Conformational Disorder. ACS Biomater. Sci. Eng. 2017, 3, 661−679. (23) Guerette, P. a; Hoon, S.; Seow, Y.; Raida, M.; Masic, A.; Wong, F. T.; Ho, V. H. B.; Kong, K. W.; Demirel, M. C.; Pena-Francesch, A. Accelerating the Design of Biomimetic Materials by Integrating RNASeq with Proteomics and Materials Science. Nat. Biotechnol. 2013, 31, 908−915. (24) Fratzl, P. Collagen: Structure and Mechanics, an Introduction. In Collagen; Springer US: Boston, MA, 2008; pp 1−13. (25) Pena-Francesch, A.; Akgun, B.; Miserez, A.; Zhu, W.; Gao, H.; Demirel, M. C. Pressure Sensitive Adhesion of an Elastomeric Protein Complex Extracted from Squid Ring Teeth. Adv. Funct. Mater. 2014, 24, 6227−6233. (26) Bahar, I.; Atilgan, A. R.; Demirel, M. C.; Erman, B. Vibrational Dynamics of Folded Proteins: Significance of Slow and Fast Motions in Relation to Function and Stability. Phys. Rev. Lett. 1998, 80, 2733− 2736. (27) Demirel, M. C.; Lesk, A. M. Molecular Forces in Antibody Maturation. Phys. Rev. Lett. 2005, 95, 1 DOI: 10.1103/PhysRevLett.95.208106. (28) Flory, P. J. Principles of Polymer Chemistry; Cornell University Press: Cornell, 1953. (29) Rubinstein, M.; Colby, R. H. Polymer Physics; OUP: Oxford, 2003.
(30) Zhong, M.; Wang, R.; Kawamoto, K.; Olsen, B. D.; Johnson, J. A. Quantifying the Impact of Molecular Defects on Polymer Network Elasticity. Science (Washington, DC, U. S.) 2016, 353, 1264−1268. (31) Pena-Francesch, A.; Florez, S.; Jung, H.; Sebastian, A.; Albert, I.; Curtis, W.; Demirel, M. C. Materials Fabrication from Native and Recombinant Thermoplastic Squid Proteins. Adv. Funct. Mater. 2014, 24, 7401−7409. (32) Sariola, V.; Pena-Francesch, A.; Jung, H.; Ç etinkaya, M.; Pacheco, C.; Sitti, M.; Demirel, M. C. Segmented Molecular Design of Self-Healing Proteinaceous Materials. Sci. Rep. 2015, 5, 13482. (33) Demirel, M. C.; Cetinkaya, M.; Pena-Francesch, A.; Jung, H. Recent Advances in Nanoscale Bioinspired Materials. Macromol. Biosci. 2015, 15, 300−311. (34) Keten, S.; Xu, Z.; Ihle, B.; Buehler, M. J. Nanoconfinement Controls Stiffness, Strength and Mechanical Toughness of β-Sheet Crystals in Silk. Nat. Mater. 2010, 9, 359−367. (35) Zhou, H.; Woo, J.; Cok, A. M.; Wang, M.; Olsen, B. D.; Johnson, J. A. Counting Primary Loops in Polymer Gels. Proc. Natl. Acad. Sci. U. S. A. 2012, 109, 19119−19124. (36) Kawamoto, K.; Zhong, M.; Wang, R.; Olsen, B. D.; Johnson, J. A. Loops versus Branch Functionality in Model Click Hydrogels. Macromolecules 2015, 48, 8980−8988. (37) Zhou, H.; Schön, E.-M.; Wang, M.; Glassman, M. J.; Liu, J.; Zhong, M.; Díaz Díaz, D.; Olsen, B. D.; Johnson, J. A. Crossover Experiments Applied to Network Formation Reactions: Improved Strategies for Counting Elastically Inactive Molecular Defects in PEG Gels and Hyperbranched Polymers. J. Am. Chem. Soc. 2014, 136, 9464−9470. (38) Dooling, L. J.; Buck, M. E.; Zhang, W.; Tirrell, D. A. Programming Molecular Association and Viscoelastic Behavior in Protein Networks. Adv. Mater. 2016, 28, 4651−4657. (39) Dooling, L. J.; Tirrell, D. A. Engineering the Dynamic Properties of Protein Networks through Sequence Variation. ACS Cent. Sci. 2016, 2, 812−819. (40) Petka, W. A. Reversible Hydrogels from Self-Assembling Artificial Proteins. Science (80-.). 1998, 281, 389−392. (41) Bennion, B. J.; Daggett, V. The Molecular Basis for the Chemical Denaturation of Proteins by Urea. Proc. Natl. Acad. Sci. U. S. A. 2003, 100, 5142−5147. (42) Pace, C. N.; Scholtz, J. M. Measuring the Conformational Stability of a Protein. In Protein Structure: A Practical Approach; Oxford University Press: New York, 1997; Vol. 2, pp 299−321. (43) Shirley, B. A. Urea and Guanidine Hydrochloride Denaturation Curves. In Protein Stability and Folding; Humana Press: NJ, 1995; pp 177−190. (44) Guerette, P. a.; Hoon, S.; Ding, D.; Amini, S.; Masic, A.; Ravi, V.; Venkatesh, B.; Weaver, J. C.; Miserez, A. Nanoconfined β-Sheets Mechanically Reinforce the Supra-Biomolecular Network of Robust Squid Sucker Ring Teeth. ACS Nano 2014, 8, 7170−7179. (45) Izuka, A.; Winter, H. H.; Hashimoto, T. Molecular Weight Dependence of Viscoelasticity of Polycaprolactone Critical Gels. Macromolecules 1992, 25, 2422−2428. (46) Boyce, M. C.; Arruda, E. M. Constitutive Models of Rubber Elasticity: A Review. Rubber Chem. Technol. 2000, 73, 504−523. (47) Termonia, Y. Molecular Modeling of Spider Silk Elasticity. Macromolecules 1994, 27, 7378−7381. (48) Jerry, Q. H.; Ortiz, C.; Boyce, M. C. Mechanics of Biomacromolecular Networks Containing Folded Domains. J. Eng. Mater. Technol. 2006, 128, 509. (49) Termonia, Y.; Smith, P. Kinetic Model for Tensile Deformation of Polymers. Macromolecules 1987, 20, 835−838. (50) Treloar, L. R. G. The Physics of Rubber Elasticity; Oxford University Press: New York, 1975. (51) Zhukhovitskiy, A. V.; Zhong, M.; Keeler, E. G.; Michaelis, V. K.; Sun, J. E. P.; Hore, M. J. A.; Pochan, D. J.; Griffin, R. G.; Willard, A. P.; Johnson, J. A. Highly Branched and Loop-Rich Gels via Formation of Metal−organic Cages Linked by Polymers. Nat. Chem. 2016, 8, 33− 41. G
DOI: 10.1021/acsbiomaterials.7b00830 ACS Biomater. Sci. Eng. XXXX, XXX, XXX−XXX
Article
ACS Biomaterials Science & Engineering (52) Nova, A.; Keten, S.; Pugno, N. M.; Redaelli, A.; Buehler, M. J. Molecular and Nanostructural Mechanisms of Deformation, Strength and Toughness of Spider Silk Fibrils. Nano Lett. 2010, 10, 2626−2634. (53) Liu, R.; Deng, Q.; Yang, Z.; Yang, D.; Han, M.; Liu, X. Y. NanoFishnet” Structure Making Silk Fibers Tougher. Adv. Funct. Mater. 2016, 26, 5534−5541. (54) Goormaghtigh, E.; Cabiaux, V.; Ruysschaert, J.-M. Determination of Soluble and Membrane Protein Structure by Fourier Transform Infrared Spectroscopy. In Subcellular Biochemistry Vol. 23. Physicochemical Methods in the Study of Biomembranes; Springer: 1994; pp 405−450. (55) Hu, X.; Kaplan, D.; Cebe, P. Determining Beta-Sheet Crystallinity in Fibrous Proteins by Thermal Analysis and Infrared Spectroscopy. Macromolecules 2006, 39, 6161−6170.
H
DOI: 10.1021/acsbiomaterials.7b00830 ACS Biomater. Sci. Eng. XXXX, XXX, XXX−XXX
