Conformation Transitions of Recombinant Spidroins via Integration of

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Conformation Transitions of Recombinant Spidroins via Integration of Time-Resolved FTIR Spectroscopy and Molecular Dynamic Simulation Shengjie Ling, Nina Dinjaski, Davoud Ebrahimi, Joyce Y Wong, David L Kaplan, and Markus J. Buehler ACS Biomater. Sci. Eng., Just Accepted Manuscript • DOI: 10.1021/acsbiomaterials.6b00234 • Publication Date (Web): 20 Jun 2016 Downloaded from http://pubs.acs.org on June 23, 2016

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ACS Biomaterials Science & Engineering

Conformation Transitions of Recombinant Spidroins via Integration of Time-Resolved FTIR Spectroscopy and Molecular Dynamic Simulation Shengjie Ling,†,‡,§ Nina Dinjaski,†,§ Davoud Ebrahimi,†,‡ Joyce Wong,ǁ David L. Kaplan,*,§ and Markus J. Buehler*,‡,#, ‡

△

Department of Civil and Environmental Engineering, Massachusetts Institute of Technology,

Cambridge, MA, 02139, USA §

ǁ

Department of Biomedical Engineering, Tufts University, Medford, MA, 02155, USA

Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA

#

Center for Materials Science and Engineering, Massachusetts Institute of Technology, 77

Massachusetts Ave., Cambridge, Massachusetts 02139, USA △

Center for Computational Engineering, Massachusetts Institute of Technology, 77

Massachusetts Ave., Cambridge, Massachusetts 02139, USA KEYWORDS: spider silk, self-assembly, structure-function relationship, conformation transition, modeling

1

ACS Paragon Plus Environment


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ABSTRACT. Current trends in biomaterial designs require a detailed understanding of structurefunction relationships in order to efficiently address specific utilities. As a prototype, spider silk has been widely studied with diversified characterization or simulation methods, exploiting the integration of experimental and modeling approaches to gain insight into structure-function relationships. Yet the assembly mechanisms of spider silk in natural and non-natural environments remain incompletely understood. In the present study experiment and simulation approaches were utilized to study assembly mechanisms of recombinant spider silks. Two spider silk constructs, H(AB)12 and H(AB)12NtSp, were produced and studied. Deconvoluted Fourier Transform Infrared Spectroscopy (FTIR) spectra and molecular dynamics simulations, before and after ethanol treatment, were analyzed to quantify secondary structures, and a higher helix content was observed in H(AB)12NtSp compared with H(AB)12. Time-resolved FTIR analysis was used to monitor conformation transitions. A higher rate of β-sheet formation was found in H(AB)12NtSp compared with in H(AB)12. These results suggest that the N-terminal domain accelerates self-assembly of recombinant spidroins under ethanol treatment. The approaches used in this study provide insights into the function of the N-terminal domain in conformational transitions of spider silks under non-natural conditions, as well as fiber formation. This approach should enable the more efficient design, synthesis and preparation of new recombinant spidroin materials with tunable mechanical properties.

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INTRODUCTION Research into biomaterials has entered a new era through the integration of synthetic polymer design, characterization and simulation tools. Genetic engineering (a bio-tool) provides a pathway to analyze structures of selected protein domains and interactions between these domains.1 Characterization (an analysis tool) and simulation (a modeling tool) provide the ability to decipher the intricate interplay of mechanisms involved at different length scales, from the atomic to the macroscopic level. The integration of these tools provides a foundation for moving the field forward in a more rational approach to biomaterial designs and implementation.2,3 With the combination of these tools a variety of hierarchical biomaterial systems such as silk, elastin and collagen have been investigated for their mechanical properties and self-assembling mechanisms.1,2,4-10 In particular, spider silks, a unique protein model biomaterial, is of interest because of the excellent portfolio of mechanical properties as well as the remarkable spinning process that converts water-soluble protein (spidroin) into water-insoluble solid silk fibers. This process is conducted under physiological conditions including ambient temperature, low hydrostatic pressure, low extrusion rate, low draw down ratio, and without toxic solvents.8,9 Recent advances in understanding the natural silk spinning process, combined with detailed molecular studies of partial length spidroins, have revealed that spider silk formation is regulated in part by the non-repetitive (N-terminal and C-terminal) domains. N-terminal domain regulates spidroin assembly by inhibiting aggregation during storage and accelerates and directs selfassembly when the pH is lowered along the extrusion duct in the silk producing gland.11-13 The C-terminal domain controls the switch between storage and assembly forms of spidroins.14 The synergy between the N-terminal and C-terminal domains allows spidroin conformational 3



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transitions to form fibers in an extremely short time under a mild stimulation environment.15,16 Based on this mechanism, a variety of recombinant spidroins with N-terminal and/or C-terminal domains have been synthesized to generate recombinant silk fibers. However, none of these fibers, even when they are formed from native-sized recombinant spidiroins, could emulate the extraordinary mechanical properties of native spider silk.15-19 The main reason is the sophisticated process of spider spinning, which is regulated by different environmental inputs such as pH, ion content and shear, that are difficult to reproduce in artificial spinning. Industrial wet spinning techniques (ejection of the dope into a coagulation bath, most often containing methanol, ethanol or isopropanol), as substitution for the native process, have been used to mimic fiber formation and to produce useful recombinant spidroin fibers.20,21 Usually organic solvents and/or coagulation baths are used to induce conformational transitions of recombinant spidroins from soluble random coil/helix structures to insoluble β-sheets.20 The differences between the natural and artificial spinning conditions remain significant. Thus, additional insight and inputs are required to better understand and mimic those processes with the aim to improve the mechanical properties of recombinant spidroin fibers. The main goal of the present work is to synergistically apply recombinant DNA technology (a bio-tool), time-resolved Fourier Transform Infrared Spectroscopy (FTIR, an analysis tool) and molecular simulation (a modeling tool) to better understand the impact of the N-terminal domain on spidroin assembly under artificial spinning conditions. Spidroin genes are large and repetitive with a high percentage of guanine (G)-cytosine (C) units, limiting spidroin gene replication and transcription approaches via genetic engineering methods.1,22 An alternative is to select specific segments in spidroin and rebuild spidroin analogs. In previous work, we built two sequence motifs according to the sequence of spidroin: a hydrophobic poly-alanine rich block (A) and a 4


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hydrophilic glycine-rich block (B).23-26 The A block which consists of poly(A) and poly(GA) repeats (GAGAAAAAGGAG) is responsible for β-sheet formation or crystallization. The B block composed of four GGX repeats that are separated by the GSQGSGR sequence, is hydrophilic and forms random coil. Through arrangements of these two motifs, a series of (AB)n sequences were recombinantly produced.23-26 Here, two constructs, H(AB)12 and H(AB)12NtSp, have been produced to analyze the effect of the N-terminal domain on conformation transitions. In terms of H(AB)12 and H(AB)12NtSp, H is a histidine tag; A is the hydrophobic block; B is the hydrophilic block; and NtSp is the N-terminal spidroin domain. For artificial spinning,20 an ethanol aqueous solution was selected to induce conformation transitions of recombinant spider silks. The secondary structures of the two proteins under natural and non-natural conditions were assessed along with conformational transition dynamics. A mechanism of conformation transitions of recombinant spidroins is proposed based on the data collected. EXPERIMENTAL SECTION Synthesis of Recombinant Proteins. To express and purify H(AB)12 and H(AB)12NtSp, previously designed expression plasmids were used.26 Briefly, DNA sequences were designed to encode the hydrophobic A domain (RGGGYAGAGAAAAAGGAGAA), hydrophilic B domain (QGGYGGLGSQGSGRGGLGGQ) and N-terminal domain derived from the major ampullate dragline silk I (MaSp I) of the golden orb weaver spider, Nephila clavipes. The whole sequences of the two proteins can be found in Figure S1. The genetic sequences encoding the protein polymers were cloned into a commercially available expression vector pET30a(+) following procedures which were described elsewhere.26 Sequences were expressed under the T7 promoter in Escherichia coli strain BL21Star (DE3) (Invitrogen, Carlsbad, CA). The recombinant strains 5



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were grown overnight at 37 °C in Luria-Bertani medium at 250 rpm. Next, minimal medium supplemented with 1% yeast extract was inoculated at an optical density (OD600) of 0.1. Ammonia was used to maintain the pH at 6.8. When the pH exceeded 6.88 a feed solution (50% glucose, 10% yeast extract, 2% MgSO4 × 7H2O) was added. All culture media contained kanamycin (50 µg/mL). Once the OD600 reached approximately 10, expression was induced by the addition of 1 mM isopropyl-β-D-thiogalactopyranoside (IPTG) (Sigma-Aldrich, St. Louis, MO). At 6 h after induction cells were harvested by centrifugation at 8000 rpm for 15 min at 4 °C. Protein purification was performed under denaturing conditions on Ni–NTA resins (Qiagen, Valencia, CA) using previously described procedures.25 Dialyzed proteins were lyophilized and the purity of the proteins was determined via sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS–PAGE) followed by Colloidal Blue staining. Preparation of Recombinant Protein Films. To prepare films, lyophilized recombinant proteins were dissolved in deionized water at a concentration of 2% (mg/mL), then 30 µL of the protein solution was deposited onto polydimethylsiloxane (PDMS) substrates and air-dried at room temperature. Time-Resolved Fourier Transform Infrared Spectroscopy Measurement. All infrared spectra were recorded by a Jasco FTIR-6200 (Jasco Instruments, Easton, MD) spectrometer in transmission mode. For each measurement, 64 interferograms were co-added and Fouriertransformed employed a Genzel-Happ apodization function to yield spectra with a nominal resolution of 4 cm-1. For FTIR measurements of the recombinant protein films, two BaF2 windows were used as a holder to sandwich the films. The thickness of the films was similar (about 5 µm), thus the absolute absorbance presented in figures was reproducible. For the time6


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resolved measurements, 100 µL of protein solution (2 mg/mL) was dropped onto a BaF2 window and air-dried. Then the sample window and a clean BaF2 window were mounted to a liquid cell with 100 µm spacer. The ethanol D2O solutions (shortened to ‘‘ethanol solution’’ in this paper) with concentrations ranging from 20% (v/v) to 60% were quickly injected into the liquid cell and the spectra were collected immediately. The total data collection time was 60 min for each measurement. Data Processing of Fourier Transform Infrared Spectroscopy Spectra. Deconvolution of amide I bands was carried out using PeakFit 4.12. The numbers and positions of peaks were defined from the results of second derivative spectra. The peak positions were only allowed to shift in a range of 4 cm-1 to reach the best fit results with the coefficient of determination (R2) closest to 1. A Gaussian model was selected for the band shape and the band width was fixed since it has a strong effect on the deconvolution results.27 IR molar extinction coefficients of the different secondary structures were not the same, thus the area of deconvolution peaks in each conformation was rescaled by their respective molar absorptivities.28 It should be noted that each spectrum shown in this paper was from a single experiment, but the data obtained from the spectra (e.g., β-sheet content) were the average of five separate deconvolutions from different samples. The difference spectra were calculated by the subtraction of an absorbance spectrum collected at 60 min from each absorbance spectrum at time t after the addition of ethanol. The data shown in the figures are from single experiments, but closely similar results were obtained in replicates. Kinetics of the ethanol-induced conformation transitions were studied by fitting curves using Origin 7.0 (OriginLab Corporation). The significance of differences in deconvolution results of FTIR spectra was determined by one way ANOVA on the statistics package in OriginPro 8 using a fixed-effects model and Fischer’s test (F-test) to separate means. 7



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Protein Secondary Structure and Aggregation Propensity Prediction. SOPMA29,30 (http://nhjy.hzau.edu.cn/kech/swxxx/jakj/dianzi/Bioinf7/Expasy/Expasy8.htm) and GARNIER3133

(http://www.biochem.ucl.ac.uk/bsm/dbbrowser/jj/gorfrm.html) were used to predict the

secondary structure of H(AB)12 and H(AB)12NtSp. Computational Methods. The in silico set up to study effect of solvent on the secondary structure of protein is summarized in Figure S2. In the force field benchmarks of both folded34 and unfolded proteins35,36 the most recent CHARMM force field performed well compared to other force fields in reproducing the experimental data. All molecular dynamics (MD) simulations were performed using the GROMACS 5.0.1 suite37 and the latest version of the CHARMM36 force field38 including CHARMM General FF39 version 3.0.1 (updated June 2015). In all cases, the three dimensional periodic boundary conditions were applied. The atomistic structures were visualized using VMD molecular graphic software.40 The procedure starts with initial guess of protein 3D structures (H(AB)12 and H(AB)12NtSp) using the I-TASSER method of homology modelling.41-43 Then replica exchange molecular dynamics (REMD) was performed to create an ensemble of energy minimized models in implicit water (with dielectric coefficient ξ=80) and 70% ethanol (ξ=41.15). Implicit solvation calculations were carried out using the generalized Born-formalism and the HCT model44 for calculating the Born radii. The long range electrostatic Coulombic interactions were calculated using the reaction field method45 with a cutoff radius of 10 Å. The same cutoff radius was used for short range interactions. The equations of motions were integrated using the leap-frog algorithm46 with the integration time step of 2 fs (femto second). Each replica was simulated for 10 ns. During REMD simulations, all bond lengths and angles were constrained using the LINCS algorithm.47 For H(AB)12 and H(AB)12NtsSp, 25 and 28 replicas were used covering temperatures from 300 K to 500 K. The 8


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distribution of temperatures was determined by using temperature generator for REMD simulation proposed Patriksson and van der Spoel.48 The exchange attempts were made every 5 ps. All the REMD simulations were done in the canonical (NVT) ensemble using the NoseHoover49,50 thermostat for the system. The simulation trajectories were saved every 5 ps for subsequent analyses. For each case the last 2.5 ns ensemble (from 7.5 ns to 10 ns) was analyzed from the lowest temperature replica (i.e., 300 K) to select the most probable representative structure. The single linkage clustering algorithm based on root mean square deviations (RMSDs) with 1 Å cutoff was used to cluster conformations. In this algorithm two samples belong to the same cluster if their minimum distance is less than the cutoff value. For each case, the structure with the smallest average distance from the other structures in the most populated cluster was chosen as the representative structure for the next step. The representative structures were solvated in the center of cubic boxes with a side length of 125 Å. The solvation process was performed by stacking equilibrated boxes of SPC water or 70% ethanol molecules. Solvent molecules are removed from the boxes if the distance between an atom in the solvent and an atom in the protein is less than their van der Waals radii. Each system was energy minimized using steepest descent algorithm and a 50 ps NVT simulation followed by another 50 ps NPT simulation to prepare the system for a longer NPT simulations (60 ns for H(AB)12 and 100 ns for H(AB)12NtSp). All the simulations were performed at pressure of 1 atm and temperature of 300 K. In all explicit solvent simulations, the equations of motions were integrated with an integration time step of 1 fs. The long range electrostatic coulombic interactions were calculated using particle mesh ewald summation.51 The Berendsen52 thermostat and Parrinello-Rahman53 barostat were used to control temperature and pressure in the system. The properties of the systems were reported by averaging over the last 20 ns trajectories of the simulations. In all 9



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explicit solvent simulations dispersion corrections were applied for energy and pressure as this has been shown to affect simulated structural properties of proteins.35 The secondary structures were determined with the DSSP algorithm.54 The algorithm uses the atomic coordinates and hydrogen bonding patterns to assign each residue to the following structural elements: β-bridge, extended β-strands, 3-10 helix, α-helix, π helix, β-turns and bends. All other residues are labeled unassigned. For our analyses, we combined the β-bridge and extended β-strands into a single structural element of β-sheet, combined all helix structures, and combined bends and unassigned into random structures. As a result we report four kinds of secondary structures (including β-turns) comparable with the experimental data. RESULTS AND DISCUSSION Secondary Structure Assessment of H(AB)12 and H(AB)12NtSp via FTIR Spectra. Figure 1 shows FITR spectra of as-cast films of H(AB)12 and H(AB)12NtSp. The 1800-1000 cm-1 region was examined as it includes amide I, amide II and amide III bands, whose vibrations provide information on the secondary structures of the protein backbone.55-60 The amide I band mainly comes from C=O stretching (80%) with minor contributions from N-H in-plane bending. The amide II band is mainly caused by C–N stretching and N–H in-plane bending of the chain backbone of silk fibroin molecule, while amide III is more complex in that it stems from Hα bending, C-N stretching and N-H in-plane bending.55,56 Moreover, in this region, there are several fingerprint peaks that are sensitive to secondary structure. Since our designed sequences come from spider silk, and the spectra of those are remarkably similar,57 we can assign peaks of H(AB)12 and H(AB)12NtSp, based on the assignments of natural silks. In Figure 1a and b, the 10


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H(AB)12 and H(AB)12NtSp have similar specific peaks, which illustrate absorptions at 1660, 1540, 1453, 1413, 1381, 1335 and 1235 cm-1. Among them, 1650 and 1540 cm-1 were assigned to random coil and/or helix; 1335 cm-1 was attributed to α-helix.56-60 The detailed assignments are summarized in Table 1. Amide I prevailed in protein conformation analysis. In order to precisely locate the specific peaks, second derivative spectra were calculated to define criteria for peak assignment. The second derivative spectra discriminate against broad background absorptions and are narrower than the original bands with their negative peaks corresponding to the maximum of the original spectra. Therefore, this approach permits the identification of individual features in complex contours and is often employed in the visualization of overlapping absorptions.61-63 The second derivative spectrum of H(AB)12 presents 5 negative peaks:1694, 1670, 1660, 1645 and 1620 cm-1; H(AB)12NtSp only has 3 negative peaks: 1670, 1660 and 1645 cm-1. On the basis of classic protein structure assignments,63 1670, 1660 and 1645 cm-1 present in the two proteins are assigned to 310-helix, α-helix and random coil, respectively. However, it is difficult to distinguish different helix structures (e.g., 310-helix and α-helix) of peptides and proteins in infrared spectra due to the similar vibrational modes.64,65 310-helix peptides, containing Cα-tetra-substituted αamino acids, have amide I bands at higher frequencies (1658-1666 cm-1) than α-helices (16501658 cm-1) in non-aqueous solutions. This small frequency shift of the amide I band cannot uniquely determine the conformation, as both distortions and irregularities in the helix, different types of residues, helix length, solvent effects, and strain in the amide band can result in higher (or lower) frequencies for either structure.66-68 To achieve clarity, peaks at 1670 and 1660 cm-1 were attributed to helix structure, which is consistent with the infrared spectra of silks.69 The peaks at 1620 and 1694 cm-1 in H(AB)12 were attributed to β-sheet, and β-turn conformations, 11



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respectively, are associated with the anti-parallel β-sheet structure.56-60 As a result, in as cast films, H(AB)12 contained a certain amount of β-sheet, while H(AB)12NtSp had no β-sheet structure. After assigning conformations to the characteristic absorption peaks in the amide band, a semi-quantitative analysis (deconvolution method) was performed to assess secondary structure content from the amide I bands57,58 (Figure 2a and b). The ratios of the different conformations were calculated in the amide I region (Table 2). H(AB)12NtSp contained a significantly higher content of helical domains, 45±2% compared with 34±2% for H(AB)12. H(AB)12 had 12±2% βsheet, whereas H(AB)12NtSp had no detectable β-sheet. Accordingly, the random coil content in H(AB)12NtSp (55±2%) was higher than in H(AB)12 (43±2%). This trend is in agreement with the results obtained by using secondary structure predication tools, SOPMA and GARNIER. Both methods predict the relative content of secondary structures based on the amino acid sequence. The SOPMA predicts α-helix contents of 29.4% in H(AB)12 and 36.1% in H(AB)12NtSp; the GARNIER supports α-helix contents of 23.0% in H(AB)12 and of 29.0% in H(AB)12NtSp. These predications reveal that both H(AB)12 and H(AB)12NtSp have helical structures, supported by the fact that the GGX rich block B has a high propensity to form α-helical structures. In addition, H(AB)12NtSp presents a higher helix structure content when compared with H(AB)12, probably due to the presence of the N-terminal domain. The structure of Euprosthenops australis N-terminal domain has been confirmed as a homodimer, in which each subunit adopts a five-helix bundle fold and helices 2, 3 and 5 form the dimer interface.11 This supports the hypothesis that the N-terminal domain might affect the increase of helical structures when added to the core spider silk domain. 12


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As mentioned, conformation transitions are crucial steps for natural and artificial spinning to convert the protein from soluble random coil/helix structures to insoluble β-sheets. Here, ethanol aqueous solution was used to induce the structural transitions of H(AB)12 and H(AB)12NtSp. Figure 1c and d depict the FTIR spectra of H(AB)12 and H(AB)12NtSp treated with 60% ethanol aqueous solution at room temperature for 24 h. The FTIR spectra exhibit a strong β-sheet peak at 1620 cm-1 with a β-turn shoulder peak at 1694 cm-1. The maxim peak in amide II also shifted from 1540 (random coil/helix) to 1523 cm-1 (β-sheet). The deconvolution (Figure 2c and d, and Table 2) revealed slightly higher β-sheet content in H(AB)12 (31±1%) than that of H(AB)12NtSp (28±2%) , while the helix content in H(AB)12 was only 28±2%, lower than that of H(AB)12NtSp, which was 33±2%. Moreover, the results demonstrated a sharp increase of β-sheet and β-turn structures for both H(AB)12 and H(AB)12NtSp after conformational transitions (Table 2). For H(AB)12, the β-sheet and β-turn contents were 31±1% and 21±1%, respectively. For H(AB)12NtSp, the β-sheet and β-turns were 28±2% and 19±3%, respectively. Secondary Structures of H(AB)12 and H(AB)12NtSp via Molecular Dynamics Simulations. Molecular dynamic (MD) simulations offer a tool to explain the mechanisms of change in protein folding by changing the solvent from water to ethanol, as an analog to the experimental approach described above. Replica exchange molecular dynamics (REMD) simulations (10 ns each replica) of H(AB)12 and H(AB)12NtSp in implicit solvent (water and 70% ethanol) followed by 60 and 100 ns regular explicit solvent MD simulations (for H(AB)12 and H(AB)12NtSp, respectively) on representative structures, were used to study the mechanism of change in the folding of proteins at the molecular level (Figure S2). Convergence of the lowest temperature replicas (300 K) of the REMD simulations are shown in Figure S3. For each 13



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simulation, the last 2.5 ns was clustered (see methods section) and representative structures were solvated in explicit solvent (water and 70% ethanol). Changes in the secondary structures and their averages over the last 2.5 ns for the lowest temperature replica (T=300 K) are reported in Figure S4. Figure 3 describes the decreasing rate of the change in two metrics during equilibration of the proteins in explicit solvent: the root-mean-square deviation (RMSD) and solvent accessible surface area (SASA) which indicated sufficient convergence of the simulations (convergence up to more than 85% of the final RMSD value in each case based on the fitted function (Supporting Information part A). The structural properties of the proteins are reported by averaging the results over the last 20 ns of simulations. To find ensembles of structures close to the native state before sampling, the observed changes from the REMD implicit solvent predictions indicate the importance of performing explicit solvent simulations. Figure 4 illustrates final sample structures of the proteins in water and 70% ethanol solvents. The increase in β-sheet content can be seen by comparing Figures 4c vs. 4a and 4d vs. 4b. Moreover, H(AB)12NtSp (right column images) shows more helix content compared with H(AB)12 (left column images), which is the same trend observed in the FTIR experiments and secondary structure predication assays described earlier in section 3.1. Figure 4 shows that the increase of helix content in H(AB)12NtSp compared to H(AB)12 occurs in the N-terminal domain. Changes in the secondary structures of proteins are shown in Figure 5. Comparing averages of the secondary structures after explicit solvation (Figure 5) with the results of implicit REMD (Figure S4(e) and (f)) shows that explicit solvation changed the secondary structures, supported by the change of RMSD and SASA (Figure 3). Changing the solvent from water to ethanol resulted in β-sheet content in H(AB)12 increasing from ~ 6.1% to 9.5% and in H(AB)12NtSp from

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~5.6% to 7.4%. In Figure 5 similar increases in β-turns were seen by ethanol treatment. The increase in ordered structure comes with a decrease in random structure in ethanol. The average values are reported in Table 2. The simulation results are consistent with the FTIR results which indicate the formation of β-sheet in an ethanol environment and the corresponding decrease in random structures. While computational simulation can capture the trend of increased β-sheets and β-turns and decreased random structures when the solvent is changed from water to ethanol, the amount of predicted secondary structures are lower than the experimental values. The observed differences between the amount of ordered (β-sheet, helix, β turn) and disordered (random) structures may be due to the model size. Simulations on short peptides (AGAAAAGA) impact the stability of β sheets, as the number of chains increase to 6-8.70 In this study we performed folding simulations of single chains of H(AB)12 (with 533 amino acids) and H(AB)12NtSp (with 666 amino acids). Analysis of the contribution of distinctive amino acids in β-sheet structures (Tables S1 and S2) shows that the main growth of β-sheets in ethanol derives from the alanine (A) and glycine (G) residues. In other words, rearrangement of these residues acts like a switch to drive the new protein conformation. We expect to obtain larger and more stable β-sheet structures by having more chains in the simulations because of the numbers of alanine and glycine residues that can contribute to the β-sheet content. To build larger models exceeds current computational capacity and it is beyond the scope of the current study. From simulation we could gain insight into the effect of the N-terminal domain on the conformation of H(AB)12 protein. Table S3 summarizes the secondary structure of H(AB)12 before and after adding the N-terminal domain. The results indicate no significant change in βsheet content in water or ethanol. But in both solvents there was a decrease in random content 15



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along with an increase in helix and β-turn values by adding the N-terminal domain. The amount of change in ethanol (~7% decrease of random content) was more pronounced compared to water (~3% decrease of random content). One of the factors that dominate the stability of the protein secondary structure is the hydrogen bonding network between solvent-protein (external hydrogen bonds) and proteinprotein (internal hydrogen bonds). Figure 6 compares changes in the number of solvent-protein and protein-protein hydrogen bonds for different cases. As the solvent changes from water to ethanol, the external hydrogen bond network that stabilizes the protein becomes weaker (decrease in the number of solvent-protein hydrogen bonds in Figure 6a) and the protein stabilizes by forming more internal hydrogen bonds (i.e., increase in the number of proteinprotein hydrogen bonds in Figure 6b). This feature results in the formation of more ordered structures in ethanol. Conformational Transition Kinetics of H(AB)12 and H(AB)12NtSp. To gain an in-depth view of conformation transitions and to identify key domains that drive the transitions from less to more organized structures, ultimately resulting in protein folding, the conformational transition kinetics of H(AB)12 and H(AB)12NtSp were monitored via time-resolved FTIR analysis. Figure 7a and b present the time-resolved FTIR spectra and the related difference spectra of H(AB)12 from 1 to 60 min after the addition of 60% ethanol. As time increased, the shape of the amide I band gradually changed, while the maximum was shifted from 1650 to 1620 cm-1. The changes could be examined more clearly in the three-dimensional plots (Figure 7c and d). The increased negative bands at 1620 and 1694 cm-1 reflected elevated β-sheet structures

16


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whereas the reduction in the single positive band around 1650 cm-1 indicated the loss of random coil and/or helical structures. Figure 8 provides the normalized ∆absorbance vs time curves at 1620 cm-1 of H(AB)12 and H(AB)12NtSp with different ethanol concentrations in order to compare the conformation transition kinetics. Single exponential decay functions (equation 1) were fitted to the normalized ∆absorbance-time plots71: ௧

‫ܣ = ܣ‬1 exp ቀ− ቁ + ‫ݍ‬ ఛ

(1)

Where A denotes the normalized ∆absorbance in difference spectra; A1 is the amplitude; t denotes the experiment time, and ߬ is the time constant. The fitting results are listed in Table 3. The curve for H(AB)12 in 60% ethanol specifies an immediate sharp rise, and ߬ is 4.9±0.1 min, indicating the rapid formation of β-sheet under this condition. With a reduction in ethanol concentration from 60% to 20%, progressive lower rate of β-sheet formation was observed, and ߬ raises to 8.4±0.3 min in 40% ethanol and to 16.2±1.0 min in 20% ethanol. The H(AB)12NtSp presents the same trend, but the ߬ value was lower than that of H(AB)12 at each ethanol concentration; 2.9±0.1 min in 60% ethanol, 5.3±0.4 min in 40% ethanol and 13.2±1.5 min in 20% ethanol, implying faster β-sheet formation for H(AB)12NtSp compared with H(AB)12. Interestingly, unlike “S” type curves in conformation transition kinetics of natural silks,72,73 in our study, curves with only a growth phase and final plateau can be observed, but no lag phase is detected in both H(AB)12NtSp and H(AB)12 at an ethanol level even of 20%. This distinction may be due to the lack of the C-terminal domain, which is critical in stabilization and regulation of spidroins.14 Another possible reason is that H(AB)12NtSp (57.5 kDa) and H(AB)12 (43.7 kDa) 17



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have smaller molecular sizes than native spidroins (about 350 kDa5), thus the shorter proteins undergo dynamic changes in structures much more readily. Influence of N-terminal Domain and Ethanol Concentration on Conformation Transition Kinetics of Recombinant Spidroins. The N-terminal domain is the most conserved part of spidroin, playing a pivotal role in the initial phase of natural spinning and is used as a trigger to manipulate spidroin assembly in nature spinning. There are two ways that the Nterminal domain controls the self-assembly of spidroin: solubilization/stabilization and accelerating self-assembly. During storage of the spidroin at neutral pH and high salt concentrations in the spinning gland, the N-terminal domain is mainly present as a salt-stabilized monomer, while the bipolar subunits can interact by long-range electrostatic interactions.22 This structure promotes the stabilization of spidroin in the proximal sac and keeps spider silks in aqueous solution at high concentrations. While spidroin passes through the spinning duct, the pH (pH ~6.5) and NaCl concentration are reduced. The N-terminal domain pre-aligns by forming weakly associated dimers, which permits structural rearrangements of the spidroin and thereby prevents premature or incorrect assembly. When the pH drops to 5.5 or below (pH at exit of spinning duct), the N-terminal domain forms stable dimers, interconnecting the spidroins, and hence, accelerates and directs self-assembly of spidroins.11,12,22 Recent studies have shown that the addition of the N-terminal domain to H(AB)12 significantly increased the solubility of the protein, from water insoluble H(AB)12 to 20 wt% solubility without precipitate formation upon the addition of N-terminal domains.74 Another study demonstrated the key role of the N-terminal domain in stabilization and locking of spidroins into multimers though ultrafast self-association (only 60 µs) via urea denaturation and 18


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temperature stability assays.13,75 These studies highlighted the importance of the N-terminal domains in solubilization/stabilization and acceleration of self-assembly of recombinant spidroins under non-environmental conditions. This suggests that the solubilization/stabilization and acceleration of self-assembly due to the N-terminal domains in the natural spinning process can also be applied to some extent during artificial spinning. It is worth noting that the Nterminal domains are primarily involved in the initial phase (less than 100 µs) of fiber formation. The rates of fiber formation in both natural and artificial spinning, however, are controlled by the rate of conformational transition of (recombinant) spidroins. In terms of the conformational transition of silk protein, the mechanism is mainly nucleation-dependent aggregation.72,76 The rate of conformational transition depends on a competition between breaking the original hydrogen bonds and the formation of new ones among the spidroin chains. Based on the above discussion, the effects of the N-terminal domains on conformational transitions for H(AB)12 and H(AB)12NtSp are proposed here. In the initial phase of conformational transition (before nucleation), H(AB)12NtSp has a more rapid swelling rate than H(AB)12 because of the N-terminal domain, which has solubilization/stabilization effects. Accordingly, the molecular chain segments of H(AB)12NtSp undergo earlier motion under the plasticizing effect of water molecules. When the chain segment can move freely, the N-terminal domains accelerate multimer formation by rapid self-association, leading the molecules to form pre-aligned aggregate structures. Compared with random molecular chain of H(AB)12, the prealigned aggregates of H(AB)12NtSp have a more regular/organized molecular arrangement. Thus, by the presence of the N-terminal domain, the probability of forming protein-protein hydrogen bonds increases (as discussed before, formation of hydrogen bonds is the prerequisite factor for conformation transition). These effects accelerate the formation of aggregates and shorten the 19



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nucleation time of H(AB)12NtSp. Consequently, H(AB)12NtSp undergoes a more rapid conformational transition than H(AB)12 during exposure to ethanol. Nevertheless, the blocks consisting of poly(A) and poly(GA) repeats (GAGAAAAAGGAG), motifs that form β-sheets, are the same in H(AB)12NtSp and H(AB)12. Hence, the β-sheet content in the two proteins is the same after conformational transitions. The concentration of ethanol, which is another primary factor in regulation of hydrogen bonds formation, governs the conformation transitions of H(AB)12 and H(AB)12NtSp. As discussed, the rate of the conformation transition relies on competition between the loss of the original hydrogen bonds and the formation of new hydrogen bonds among the protein and protein chains. Subsequently, at relatively high ethanol concentrations (for instance, 60% in the present experiments), the polypeptide chains can move but not very freely, thus both nucleation and growth of β-sheets readily occurs rapidly by adjusting the segments of individual chains. With a decline in ethanol concentration, the original hydrogen bonds are easier to break, and the polypeptide chains move more smoothly, hindering the formation of new hydrogen bonds. As a result, for H(AB)12 and H(AB)12NtSp, increased ethanol concentration leads to increased rates of conformation transitions. CONCLUSIONS Integrated experimental and molecular modeling approaches were used to gain insight into chain folding and assembly of recombinant spidroins. The experimental data supported by modeling predictions, suggested conformational differences between two recombinant spidroins, H(AB)12 and H(AB)12NtSp. Higher content of helical structure in H(AB)12NtSp compared to H(AB)12, was due to the presence of α-helix rich N-terminal domain. Importantly, the two 20


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proteins shared almost the same β-sheet content generated from random coil and/or helical structures after conformational transitions. Time-resolved FTIR assays disclosed that both the Nterminal domain and ethanol content act in the conformational transitions. The N-terminal domain triggered self-assembly of the recombinant spidroins. Ethanol was a coagulator and a denaturant to control the relative rates of destruction and formation of hydrogen bond networks. These findings provide insight into the mechanism of conformation transitions of silk proteins in artificial non-natural environments, and enable efficient design, synthesis and preparation of new recombinant spidroin materials with predictable robust mechanical properties. ASSOCIATED CONTENT Supporting Information The Supporting Information is available free of charge on the ACS Publications website at DOI:xxx. Amino acid sequence of H(AB)12 and H(AB)12NtSp; flowchart of simulation procedure; convergence of the lowest temperature replica of the replica exchange molecular dynamics simulations; change of the secondary structures during equilibration in REMD implicit solvent; amino acid composition and total number of residues in β-sheet structures of H(AB)12 and H(AB)12NtSp solvated in water and ethanol from simulations; comparison of conformation content (%) of H(AB)12 due to adding NtSp in H(AB)12NtSp from simulations; and fitting of the RMSD values in simulations (PDF) AUTHOR INFORMATION Corresponding Author 21



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*David L. Kaplan. E-mail [email protected]. *Markus J. Buehler. E-mail: [email protected]. Author Contributions †S. L., N. D. and D. E. contributed equally to this work. Notes The authors declare no competing financial interest. ACKNOWLEDGMENTS We thank the NIH (U01 EB014976) for support of this work. The computational resources used for this project have been provided by the National Science Foundation through the Extreme Science and Engineering Discovery Environment (XSEDE) and the Texas Advanced Computing Center under Grant Numbers TG-DMR140101 and TG-MSS090007. REFERENCES (1)

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Kamphuis, J.; Toniolo, C.; Keiderling, T. A. Conformational Characterization of Terminally Blocked l-(αMe)Val Homopeptides Using Vibrational and Electronic Circular Dichroism. 310Helical Stabilization by Peptide−Peptide Interaction. J. Am. Chem. Soc. 1997, 119, 10278-10285. (69)

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Table 1. The FTIR band assignments of H(AB)12 and H(AB)12NtSp. band assignment wavenumbers (cm-1)

reference vibration mode

conformation

1700

amide I, C=O s, C-N s

β-turn

55-60

1670


helix

55-60

1660


helix

55-60

1645


random coil

55-60

1620


β-sheet

55-60

1540

amide II, N-H ib, C-N s

random coil and/or helix

55-60

1523

amide II, N-H ib, C-N s

β-sheet

55-60

1453

CH3 ab, CH2 b

55,56

1413

Hα b, CH2 w

55,56

1335

CH3 sb, Hα b

1235

amide III, Hα b, C-N s, N-H ib

helix

55-60 55,56

* Abbreviations: s= stretching, ib= in-plane bending, ab= anti-symmetric bending, b= bending, w= wagging.

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Table 2. Comparison of conformation content (%) of H(AB)12 and H(AB)12NtSp obtained by different methodsα. H(AB)12

Analysis

H(AB)12-NtSp

Method

β-sheet

helix

random coil

β-turn

SOPMA

0.4

29.4

54.9

15.4

GARNIER

0

23.0

41.4

12.0

FTIR

12±2

34±2

43±2

Simulation of one chain in water

6.1±0.8

2.1±0.4

FTIR ethanol treatment

31±1

Simulation of one chain in ethanol

9.5±1.0

others

β-sheet

helix

random coil

β-turn

0.9

36.1

49.3

13.7

0

29.0

38.6

11.0

11±3

0

45±2**

55±2

0

82.2±1.0

9.4±0.7

5.6±0.6

10.0±0.5

71.3±0.8

12.9±0.9

28±2

20±2

21±1

28±2

33±2**

20±4

19±3

1.3±0.3

77.1±1.1

11.9±0.7

7.4±0.5

10.3±0.7

66.2±0.8

16.0±1.0

23.6

α

others

21.3

Statistical analysis of FTIR deconvolution results was performed by one-way analysis of variance (ANOVA). **indicates significant difference between H(AB)12 and H(AB)12NtSp (p < 0.05). The least-significant digits of SOPMA, GARNIER and simulation results are 0.1, so the summation of each sample is not 100%.

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Page 34 of 43

Table 3. Conformational transition kinetics of recombinant spider silk films probed by absorbance changes of the β-sheet band at 1620 cm-1. ethanol (%)

t of H(AB)12

t of H(AB)12NtSp

20

16.2±1.0

13.2±1.5

40

8.4±0.3

5.3±0.4

60

4.9±0.1

2.9±0.1

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Figure 1. FTIR (solid line) and second derivative (dash-dot line) spectra of recombinant spidroin membranes: (a) H(AB)12 membrane as cast, (b) H(AB)12NtSp membrane as cast, (c) H(AB)12 membrane treated with 70% ethanol aqueous solution at room temperature for 24 h, (d) H(AB)12NtSp membrane treated with 70% ethanol aqueous solution at room temperature for 24 h.

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Page 36 of 43

Figure 2. Deconvolution results of amide I band of recombinant spidroin: (a) H(AB)12 membrane as cast, (b) H(AB)12NtSp membrane as cast, (c) H(AB)12 membrane treated with 70% ethanol aqueous solution at room temperature for 24 h, (d) H(AB)12NtSp membrane treated with 70% ethanol aqueous solution at room temperature for 24 h (circles, original spectrum; dashed curve, deconvoluted peaks; solid curve, simulated spectrum from summed peaks).

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Figure 3. Convergence during equilibration of structures with explicit solvent. The decreasing rate of change in (a) and (b): root-mean-square deviation (RMSD), and (c) and (d): solvent accessible surface area (SASA) indicated sufficient convergence of the structures for each case. Further equilibration was not considered useful. The arrows in (a) and (b) represent the time of converging to 85% of the final RMSD values based on the fitted function (Supplementary part A). The properties are reported by averaging over the last 20 ns of simulation in each case where RMSD has converged to more than 85% of its asymptote.


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Page 38 of 43

Figure 4. Comparing protein structures in explicit water and 70% ethanol solvents (a) H(AB)12 (b) H(AB)12NtSp in water; (c) H(AB)12 and (d) H(AB)12NtSp in 70% ethanol. The NtSp domain in (b) and (d) is highlighted. Helices and β-structures are colored in red and blue, respectively. The rest of the protein is random coil.


38

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Figure 5. Average of the secondary structures in explicit solvent (a) H(AB)12 (b) H(AB)12NtSp. In both cases ethanol treatment results in increase of β-sheet and β-turn and decrease of random content.


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Page 40 of 43

Figure 6. Change of the number of hydrogen bonds in water and 70% ethanol solvents for H(AB)12 and H(AB)12NtSp proteins (a) number of solvent-protein hydrogen bonds in ethanol solvent decreases and (b) number of protein-protein hydrogen bonds in ethanol solvent increases.


40

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Figure 7. Original and difference FTIR spectra of H(AB)12 during the conformational transition process by 60% ethanol from the beginning to 60 min. (a) normal spectra; (b) difference spectra; (c, d) three-dimensional spectra of (a) and (b). The original and difference FTIR spectra of H(AB)12-NtSp have same style, for the sake of simplicity, here just show typical time-resolved FTIR spectra of H(AB)12 during the conformational transition process by 40% ethanol from the beginning to 60 min.


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Page 42 of 43

Figure 8. Comparison of conformational transition kinetics of recombinant spidroin induced by different concentrations of ethanol: (a) H(AB)12; (b) H(AB)12NtSp. The dash lines are fitted curves using single exponential decay functions.


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For Table of Contents Use Only

Conformation Transitions of Recombinant Spidroins via Integration of Time-Resolved FTIR Spectroscopy and Molecular Dynamic Simulation Shengjie Ling,†,‡,§ Nina Dinjaski,†,§ Davoud Ebrahimi,†,‡ Joyce Wong,ǁ David L. Kaplan,*,§ and Markus J. Buehler*,‡,#,

△


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Conformation Transitions of Recombinant Spidroins via Integration of

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