Imaging-Based Study on Control Factors over Self-Sorting of

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Imaging-based study on control factors over self-sorting of supramolecular nanofibers formed from peptide- and lipid-type hydrogelators Ryou Kubota, Shuang Liu, Hajime Shigemitsu, Keisuke Nakamura, Wataru Tanaka, Masato Ikeda, and Itaru Hamachi Bioconjugate Chem., Just Accepted Manuscript • DOI: 10.1021/acs.bioconjchem.8b00260 • Publication Date (Web): 09 May 2018 Downloaded from http://pubs.acs.org on May 10, 2018

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Bioconjugate Chemistry

Imaging-based Study on Control Factors over Self-sorting of Supramolecular Nanofibers formed from Peptide- and Lipid-type Hydrogelators Ryou Kubota1, Shuang Liu1,2, Hajime Shigemitsu1,†,#, Keisuke Nakamura1, Wataru Tanaka1, Masato Ikeda3,4,5, Itaru Hamachi1,6* 1

Department of Synthetic Chemistry and Biological Chemistry, Graduate School of

Engineering, Kyoto University, Katsura, Nishikyo-ku, Kyoto 615-8510, Japan 2

School of Materials Science and Engineering, Wuhan University of Technology,

Wuhan 430070, China 3

Department of Chemistry and Biomolecular Science, Faculty of Engineering, Gifu

University, Gifu 501-1193, Japan 4

Department of Life Science and Chemistry, Graduate School of Natural Science and

Technology, Gifu University, Gifu 501-1193, Japan 5

United Graduate School of Drug Discovery and Medical Information Sciences, Gifu

University, Gifu 501-1193, Japan 6

Core Research for Evolutional Science and Technology (CREST), Japan Science and

Technology Agency, 5 Sanbancho, Chiyoda-ku, Tokyo 102-0075, Japan †

Present address: Department of Applied Chemistry, Graduate School of Engineering,

Osaka University, 2-1 Yamadaoka, Suita, Osaka 565-0871, Japan #

Present address: Frontier Research Base for Global Young Researchers, Graduate

School of Engineering, Osaka University, 2-1 Yamadaoka, Suita, Osaka 565-0871, Japan Correspondence: [email protected]

1 ACS Paragon Plus Environment

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Abstract Multicomponent self-assembly is a fascinating strategy for the construction of smart soft materials. Among them, supramolecular hydrogels comprising self-sorting nanofibers have recently attracted significant attention owing to their rationally incorporated stimulus responsiveness. However, there have been limited investigations of the crucial factors that control the self-sorting phenomena. Here, we describe an imaging-based approach to evaluate the factors that control the formation of self-sorting nanofibers from peptide- and lipid-type hydrogelators. We screened a small library of hydrogelators with distinct chemical properties by direct visualization of their self-assembly behavior by using confocal laser scanning microscopy. Our systematic research identified two important factors that influence the self-sorting behavior of nanofibers: (i) the surface charge of the hydrogelators; and (ii) the hydrophobicity of the side chain on the peptide-type hydrogelators. We determined that the same net/surface charge on the hydrogelators and a side chains with a lower hydrophobicity on the peptide-type hydrogelators were preferred. These findings, in combination with the previously reported kinetic factors, were used to design and successfully prepare a three-component orthogonal self-assembly composed of supramolecular nanofibers from peptide- and lipid-type hydrogelators and a cationic organorhodium complex. Our findings would be beneficial for the design of intelligent soft materials based on self-sorting phenomena. Keywords Self-sorting; Supramolecular nanofiber; Hydrogel; Confocal laser scanning microscopy; Orthogonal self-assembly


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Introduction Supramolecular self-assembly is an intriguing method for the construction of functional soft materials for biosensors, luminescence materials, and biomedical applications.1–4 One of the next grand challenges of supramolecular chemistry is the creation of multicomponent supramolecular systems that exhibit dynamic and multiple functions integrated in one system, such as living cells.5–15 To achieve this, orthogonal self-assembly that relies on self-sorting phenomena represents a promising strategy for rationally incorporating functional supramolecular assemblies without interference of a feature of each component.16 Inspired by excellent biological examples, many researchers have recently devoted their efforts to creating self-sorted, orthogonal architectures

comprising

supramolecular

nanofibers17–29,

vesicles30–33,

and

organic/inorganic host materials.34–36 Among them, multicomponent supramolecular hydrogels based on self-sorting phenomena have recently attracted significant attention as platforms for drug-delivery systems and regenerative medicine owing to the ability to rationally install sophisticated stimulus responsiveness.17–21,30–32,34,35 For instance, we reported unique polyamine and polyanion sensors based on hybrids of supramolecular hydrogels and inorganic host materials.34,35 van Esch et al. constructed an intelligent delivery platform with a tunable release rate of functional small molecules by a supramolecular fiber network encapsulating an enzyme-embedded liposome.30–32 Although promising, the control of self-sorting phenomena in an aqueous solution remains challenging for synthetic chemists because hydrophobic interactions, a dominant driving force for self-assembly in water, are currently less controllable. Therefore, understanding the factors that control the self-sorting phenomena in water is strongly desirable. Recently, van Esch et al. thoroughly investigated the self-assembly behavior of different kinds of hydrogelators and phospholipids (liposomes).37 They clarified that distinct sets of self-assembled interactions and a strong driving force were the key factors for orthogonal self-assembly. Adams et al. examined the structural relationship of the pH-controlled self-sorting of peptide-type hydrogelators.20,21 They found that structurally similar hydrogelators tend to coassemble with each other even if the hydrogelators have different pKa values.38 These pioneering works strongly indicated that structurally distinct building blocks and driving forces are crucial for self-sorting; however, the effects of other chemical parameters (e.g., charge, hydrophobicity) on self-sorting have not been well investigated. 3 ACS Paragon Plus Environment


Here, we evaluate the chemical properties crucial for self-sorting phenomena of two supramolecular nanofibers comprising structurally distinct peptide- and lipid-type hydrogelators (Fig. 1).17,18 These hydrogelators form into supramolecular nanofibers through different driving forces such as hydrogen bonding/π-π interactions and hydrophobic interactions/hydrogen bonding. We prepared a small library of hydrogelators containing different chemical structures, charge, and hydrophobicity (Fig. 2) and directly visualized the self-assembly behaviors (self-sorting or coassembly) of these pairs by using confocal laser scanning microscopy (CLSM) with appropriate fluorescent probes. From direct imaging, we found not only new self-sorting pairs but also coassembly pairs. The systematic study suggested that an identical net/surface charge of the hydrogelators and the degree of hydrophobicity had a crucial impact on the self-sorting phenomena. Based on our findings, we succeeded in the orthogonal self-assembly of three different supramolecular nanofibers. Our results provide invaluable information for the design of multicomponent hybrid materials whose functions could be rationally installed.

Fig. 1. Schematic illustration of an imaging-based screening assay of self-sorting and coassembly behavior of two distinct hydrogelators. We here investigated the crucial control factors on self-sorting phenomena of supramolecular nanofibers.


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Fig. 2 (A, B) Chemical structures of (A) peptide- and (B) lipid-type hydrogelators. The hydrophilic head and hydrophobic tail groups of the lipid-type hydrogelators were highlighted by blue and red, respectively. (C, D) Chemical structures of the fluorescent probes for (C) peptide- and (D) lipid-type nanofibers.



Results and discussion Design of a library of peptide- and lipid-type hydrogelators We recently reported the formation of self-sorted supramolecular nanofibers comprising peptide- and lipid-type hydrogelators.17,18 It was conceivable that one of the main controlling factors of the self-sorting phenomena was their distinct driving force of self-assembly, namely π-π stacking and hydrogen bonding of the peptide-type hydrogelators (BPmoc-F3 and NPmoc-F(F)F) and hydrophobic interaction and hydrogen bonding (different motif from peptide-type) of the lipid-type hydrogelators (Phos-cycC6). However, other factors, such as the chemical structures, net charge, and hydrophobicity, have not been examined in detail. Therefore, we investigated the self-assembly behaviors of a mixture of two different hydrogelators. As a structure-focused library, we prepared 6 peptide-type hydrogelators39,40 and 7 lipid-type hydrogelators17,41–43 (Fig. 2, see Supporting Information for the organic syntheses). The peptide-type hydrogelators were categorized into two classes depending on the

N-terminal moiety: boronophenyl (BPmoc) or nitrophenyl (NPmoc) groups (Fig. 2A). Furthermore, we synthesized 5 derivatives of the NPmoc hydrogelators with a slightly different side chain. The hydrophobicity of the peptide-type hydrogelators could be systematically controlled by the introduction of a fluorine atom and CF3 group at the

para-position of the phenyl group (Table S1). We prepared lipid-type hydrogelators bearing a different charge (negative: phosphate (Phos) and sulfonate (Sulf), neutral: GalNAc, zwitterionic: Lys, cationic: guanidium (Gua)) and different hydrophobic moieties (cyclic and normal hexyl (cycC6 and norC6, respectively) and methyl cyclopentyl (MecycC5)) to examine the effect of the surface charge and the inner hydrophobic structures of the lipid-type hydrogelators (Fig. 2B). CLSM analyses of self-assembly behaviors of BPmoc-F3 and lipid-type hydrogelators We examined the self-assembly behavior of BPmoc-F3 and lipid-type hydrogelators by in situ imaging using CLSM (Table 1; first row). The selective staining of the supramolecular nanofibers with appropriate fluorescent probes allowed us to directly assess the degree of self-sorting without applying any drying processes, which is quite difficult with conventional indirect spectroscopic methods and other microscopic techniques.17,44 We initially investigated the effect of the inner hydrophobic 6 ACS Paragon Plus Environment

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structures of the lipid-type hydrogelators on the self-sorting phenomena (Phos-cycC6, -MecycC5, and -norC6). According to our previous report on the visualization of the self-sorting nanofibers (e.g., BPmoc-F3 and Phos-cycC6), we conducted CLSM imaging of the BPmoc-F3 and Phos-MecycC5 pair with two different fluorescent probes, whose core structures were identical with or similar to the corresponding peptide- and lipid-type hydrogelators (BP-OG and Alexa546-cycC6, respectively) (Fig. 2 C,D, see Table S3 and Fig. S1 for their excitation and emission spectra). We prepared the hydrogel samples by using a heating-cooling protocol, that is, a powder of BPmoc-F3 was dissolved in an aqueous buffer (100 mM MES, pH 7.0) by heating at 120 ºC for 5 min with a hot plate to form a homogenous solution (3.2 mM). The solution of Phos-MecycC5 was also prepared by dissolving a powder by using a heat gun (4.8 mM). Then, equal amounts of BPmoc-F3 and Phos-MecycC5 solutions were mixed, and to this mixture, the fluorescent probes were added (BP-OG and Alexa546-cycC6 in DMSO solution). The resulting mixture (BPmoc-F3: 1.6 mM, Phos-MecycC5: 2.4 mM, BP-OG: 4.0 µM, Alexa546-cycC6: 4.0 µM, DMSO concentration: 2.0 vol%) was heated at 120 ºC for 1 min to form a homogenous solution followed by cooling to room temperature, and then subjected to CLSM observation (see the experimental section for details). First, we confirmed the staining selectivity of the fluorescent probes. The CLSM images clearly showed that BP-OG successfully stained the thin fibrous morphology of BPmoc-F3, whereas no clear images were obtained for Phos-MecycC5 (Fig. 3A; left). In contrast, Alexa546-cycC6 could be used to visualize the well-elongated helical nanofibers of Phos-MecycC5 but not BPmoc-F3 (Fig. 3A; right). These data indicated the two fluorescent probes were sufficiently orthogonal for staining these two fibers. We then conducted CLSM imaging of the hydrogel prepared by

the

heating-cooling

process

of

the

mixture

of

four

components

(BPmoc-F3/Phos-MecycC5/BP-OG/Alexa546-cycC6). The overlay images acquired by BP-OG (green) and Alexa546-cycC6 (magenta) channels demonstrated that the greenand magenta-colored nanofibers were well entangled but did not overlap with each other (Fig. 3B). Interestingly, the helical fibrous morphology of the magenta-colored nanofibers was retained even in the mixture of two types of hydrogelators. To estimate the degree of self-sorting, we calculated Pearson’s correlation coefficient45, which is a good indicator of the degree of self-sorting. In image analyses, it is generally accepted that the correlation between two variables (the pixel-by-pixel intensity values of two 7 ACS Paragon Plus Environment


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channels) has a weak linear relationship if the absolute value of Pearson’s correlation coefficient is lower than 0.4. Considering both Pearson’s correlation coefficients and the CLSM images, we evaluated whether the hydrogelator pair is self-sorted or not. In most cases, the hydrogelators are self-sorted with each other if the absolute value of Pearson’s

correlation coefficient is

lower than

0.3.

In

the

case

of the

BPmoc-F3/Phos-MecycC5 pair, the Pearson’s correlation coefficient was estimated to be 0.17, suggesting that the two types of nanofibers did not overlap.

Table 1. Self-assembly behaviors of peptide- and lipid-type hydrogelators judged by CLSM

Phos-cycC6

Phos-MecycC5

Phos-norC6

Sulf-cycC6

Gua-cycC6

Lys-cycC6

GalNAc-cycC6

BPmoc-F3

S*

S

S

S

C*

C*

N.D.

NPmoc-F(F)F

S*

S

S

S

–

–

–

NPmoc-FF(F)

S

S

S

S

–

–

–

NPmocF(F)F(F)

S

S

S

S

–

–

–

NPmoc-F(CF3)F

C

C

C

C

–

–

–

NPmoc-FF(CF3)

C

C

C

C

–

–

–

S: self-sorting, C: coassembly, N.D.: not determined, –: not measured, *: already reported17,18


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Fig. 3. (A) CLSM images of BPmoc-F3 or Phos-MecycC5 in the presence of (green) BP-OG or (magenta) Alexa546-cycC6. These images clearly showed that BP-OG and Alexa546-cycC6 selectively stain BPmoc-F3 and Phos-MecycC5, respectively. (B) CLSM

images

of

the

mixture

of

four

components

(BPmoc-F3/Phos-MecycC5/BP-OG/Alexa546-cycC6). The left and middle images were acquired by BP-OG and Alexa546-cycC6 channels, respectively. The right was the overlay image of both channels. (C) CLSM images of the four-component mixture (BPmoc-F3/Sulf-cycC6/BP-OG/Alexa546-cycC6). The left and middle images were acquired by BP-OG and Alexa546-cycC6 channels, respectively. The right was the overlay image of both channels. The orthogonality of the fluorescent probes was shown in Fig. S6. [BPmoc-F3] = 1.6 mM, [Phos-MecycC5] = 2.4 mM, [Sulf-cycC6] = 2.4 mM, 9 ACS Paragon Plus Environment


[BP-OG] = 4.0 µM, [Alexa546-cycC6] = 4.0 µM in 100 mM MES, pH 7.0. Scale bar: 20 µm.

We also confirmed the self-sorting behavior of BPmoc-F3 and Phos-MecycC5 by CD spectroscopy because Cotton signals induced by the self-assembly of hydrogelators are sensitive to self-sorting phenomena. If the hydrogelators were self-sorted with each other, the CD spectrum of the mixture would be the sum of the CD spectra of each component.26 The CD spectrum of BPmoc-F3 showed positive and negative Cotton peaks at 208 and 223 nm, respectively, whereas that of Phos-MecycC5 showed negative and positive peaks at 220 and 257 nm, respectively (Fig. S2A, B). The spectrum of the mixture showed positive and negative peaks at 221 and 258 nm, which corresponded well with the theoretical sum of the CD spectra of each component (Fig. S2C). To evaluate the effects of the fluorescent probes on the self-assembly behaviors, we also measured CD spectra of BPmoc-F3, Phos-MecycC5, and their mixture in the presence of the fluorescent probes (Fig. S3). The resultant CD spectra agreed well with those without the fluorescent probes, indicating that the fluorescent probes did not affect the self-assembly behaviors of hydrogelators. These data strongly supported that BPmoc-F3 and Phos-MecycC5 orthogonally self-assembled into two distinct nanofibers and were a potent self-sorting pair. We also investigated the self-assembly of the BPmoc-F3 and Phos-norC6 pair in the same manner. Alexa546-norC6 was employed as the fluorescent probe for Phos-norC6 (Fig. 2D). Similar to the BPmoc-F3 and Phos-MecycC5 pair, the overlay image clearly showed the orthogonal self-assembled nanofibers of BPmoc-F3 and Phos-norC6 (Fig. S5). These results indicated that the inner hydrophobic moieties of the lipid-type hydrogelators did not have a substantial impact on the self-sorting phenomena. Next, we examined the effect of the surface charge of the lipid-type hydrogelators on self-sorting. Thanks to the structural flexibility at the hydrophilic head group of the lipid-type hydrogelators, we investigated the self-sorting behavior of BPmoc-F3 and lipid-type hydrogelators possessing a variety of surface charges. As previously demonstrated, anionic BPmoc-F3 and anionic Phos-cycC6 self-sorted with each other, whereas cationic and zwitterionic lipid-type hydrogelators (Gua-cycC6 and Lys-cycC6, 10 ACS Paragon Plus Environment

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respectively) coassembled with BPmoc-F3 to form spherical assemblies.17 These data suggested that the net or surface charge of the lipid-type nanofibers were crucial for self-sorting. To test our hypothesis, we evaluated the self-assembly properties of new lipid-type hydrogelators, Sulf-cycC6 and GalNAc-cycC6, which had an anionic alkylsulfate and a neutral N-acetylgalactosamine group, respectively, instead of the alkylphosphate group of Phos-cycC6. The CLSM images of the four-component mixture (BPmoc-F3/Sulf-cycC6/BP-OG/Alexa546-cycC6) showed the orthogonal entanglement of two types of nanofibers with distinct localization patterns (Pearson’s correlation coefficient: 0.11), strongly supporting that BPmoc-F3 and Sulf-cycC6 were the self-sorting pair (Fig. 3C, S6). Conversely, in the case of GalNAc-cycC6 and BPmoc-F3, we were not able to distinguish whether self-sorting or coassembly occurred because we could not find fluorescent probes that were appropriately orthogonal for staining this pair (Fig. S7). We also performed CD spectroscopy to examine the self-assembly behavior of the BPmoc-F3/Sulf-cycC6 and BPmoc-F3/GalNAc-cycC6 pairs. The CD spectrum of Sulf-cycC6 showed a positive Cotton peak at 258 nm (Fig. S8B). The spectrum of the mixture showed two positive peaks at 209 and 258 and a negative peak at 223 nm, which corresponded well with the theoretical spectra (Fig. S8C). Therefore, the BPmoc-F3 and Sulf-cycC6 pair was the self-sorting pair, as indicated by the CLSM imaging. However, GalNAc-cycC6 did not show any assembly-induced Cotton peaks (Fig. S9). Disappointingly, we could not conclude whether the BPmoc-F3 and GalNAc-cycC6 pair was self-sorted by CLSM and CD spectroscopy. These results suggested that the same net or surface charge of the hydrogelators may be preferred for self-sorting. CLSM analyses of self-assembly behavior of NPmoc-type hydrogelators and anionic lipid-type hydrogelators Next, we investigated the effect of the hydrophobicity of the peptide-type hydrogelators using pairs of NPmoc-type hydrogelators and anionic lipid-type hydrogelators (Table 1).46 In these combinations, we used NP-Alexa647 and NBD-cycC6 as fluorescent probes for staining the NPmoc-type hydrogelators and lipid-type hydrogelators, respectively (Fig. 2C, D, Table S3 and Fig. S1 for their excitation and emission spectra).18 Because it was previously reported that the NPmoc-F(F)F/Phos-cycC6 pair formed self-sorting networks, we first tested the pairs 11 ACS Paragon Plus Environment


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of NPmoc-type hydrogelators bearing various F-substituents and Phos-cycC6. As shown in the CLSM images in Fig. 4A, S10, and S11, the NPmoc-FF(F)/Phos-cycC6 and NPmoc-F(F)F(F)/Phos-cycC6

pairs

formed

orthogonal

self-sorting

nanofibers

(Pearson’s correlation coefficient: 0.23 and 0.28, respectively).

Fig. 4. (A, B, C) CLSM images of the mixture of (A) NPmoc-FF(F)/Phos-cycC6, (B) NPmoc-F(CF3)F/Phos-cycC6 and (C) NPmoc-FF(CF3)/Phos-cycC6 in the presence of (magenta) NP-Alexa647 and (green) NBD-cycC6. The left and middle images were acquired by NP-Alexa647 and NBD-cycC6 channels, respectively. The right was the 12 ACS Paragon Plus Environment

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overlay image of both channels. The orthogonality of the fluorescent probes was shown in Fig. S10, S12, and S13, respectively. [NPmoc-FF(F)] = 5.9 mM, [NPmoc-F(CF3)F] = [NPmoc-FF(CF3)] = 1.8 mM, [Phos-cycC6] = 2.4 mM, [NP-Alexa647] = 4.4 µM, [NBD-cycC6] = 10 µM in 100 mM MES, pH 7.0. Scale bar: 20 µm.

Conversely, the more hydrophobic peptide-type hydrogelators NPmoc-F(CF3)F and NPmoc-FF(CF3) formed partially coassembled structures with Phos-cycC6. First, we examined the self-assembly behavior of NPmoc-F(CF3)F. The CLSM imaging showed that there were many spherical aggregates of NPmoc-F(CF3)F together with very thin nanofibers (Fig. S12; left). After confirming the staining selectivity of the fluorescent probes (Fig. S12), we conducted CLSM imaging of the four-component mixtures

(NPmoc-F(CF3)F/Phos-cycC6/NP-Alexa647/NBD-cycC6).

The

image

acquired by the Alexa647-cycC6 channel showed small and bright spherical puncta as the main objects and very thin nanofibers, similar to the image of the single component NPmoc-F(CF3)F (by NP-Alexa647) (Fig. 4B; left). The image acquired by the NBD-cycC6 channel was slightly different from that of the single component Phos-cycC6, that is, not only the nanofibers but also many small puncta (diameter: ca. 2 µm) were observed (Fig. 4B; middle). The overlay image clearly revealed that the spherical puncta were stained by both fluorescent probes, whereas most of the nanofibers showed distinct fluorescence (Fig. 4B; right). These imaging data suggested that the spherical puncta may be the coassembled structure of NPmoc-F(CF3)F and Phos-cycC6, whereas the fibers seemed to be self-sorted. In contrast to NPmoc-F(CF3)F, NPmoc-FF(CF3) formed well-elongated nanofibers without the coexistence of spherical aggregates (Fig. S13; left). In the NPmoc-FF(CF3) and Phos-cycC6 pair, the fluorescent probes (NP-Alexa647 and NBD-cycC6) showed good selectivity (Fig. S13). From the resultant CLSM images of the

four-component

mixture

of

NPmoc-FF(CF3)/Phos-cycC6/NP-Alexa647/NBD-cycC6, it was clear that both coassembled and self-sorted nanofibers formed (Fig. 4C). In detail, the thick nanofibers were stained by both NP-Alexa647 and NBD-cycC6, whereas the relatively thin nanofibers did not seem to overlap. The Pearson’s correlation coefficient was determined to be 0.48, an intermediate value indicating a partial merge. Therefore, these 13 ACS Paragon Plus Environment


observations

suggested

that

NPmoc-FF(CF3)

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and

Phos-cycC6

partially

self-sorted/coassembled with each other. As demonstrated in the cases of the NPmoc-F(CF3)F/Phoc-cycC6 and NPmoc-FF(CF3)/Phos-cycC6 pairs, examples of coexistence of self-sorted and coassembled nanostructures in one solution have been still rare. Very recently, Adams et

al. reported the formation of coassembled and self-sorting nanofibers comprising two distinct peptide-type hydrogelators.47 However, it is still quite difficult to well characterize such the complicated mixtures by spectroscopic techniques. Our present data demonstrated that the in situ real-time CLSM imaging is powerful to visualize and analyze the multicomponent, complex self-assembly behaviors. We conducted a systematic examination using pairs of other anionic lipid-type hydrogelators (Phos-MecycC5, Phos-norC6, and Sulf-cycC6) with various NPmoc-type hydrogelators. For all these pairs, NP-Alexa647 and NBD-cycC6 were used as appropriate fluorescent probes. As summarized in Table 1, these pairs showed almost the same tendency as Phos-cycC6, that is, NPmoc-F(F)F, -FF(F), -F(F)F(F) and all of the anionic lipid-type hydrogelators were self-sorted, whereas NPmoc-F(CF3)F formed a mixture of coassembled spherical aggregates and self-sorted nanofibers and NPmoc-FF(CF3) showed both self-sorted and coassembled nanofibrous structures with the lipid-type hydrogelators such as Sulf-cycC6, Phos-norC6, and Phos-MecycC5 (Figs. S14–28). The overall CLSM results suggested that there were two important factors that influence the self-sorting of supramolecular nanofibers: (i) the same net or surface charge of the hydrogelators is important for self-sorting owing to electrostatic repulsion; (ii) the hydrophobicity of the side chain of the peptide-type hydrogelators had a strong impact on the self-sorting event, whereas the hydrophobicity of the structures of the lipid-type hydrogelators did not have a significant effect on self-sorting. The self-sorting behaviors of the NPmoc-type hydrogelators and lipid-type hydrogelators seem to correlate well with the ClogP values (the partition coefficient between n-octanol and water, calculated by ChemDraw) of NPmoc-type hydrogelators, an estimated measure of their hydrophobicity (Table S1). The hydrogelators with lower ClogP values (NPmoc-F(F)F and -FF(F): 4.20, -F(F)F(F): 4.33) formed self-sorted nanofibers with the anionic lipid-type hydrogelators, whereas the hydrogelators with higher ClogP values (NPmoc-F(CF3)F and -FF(CF3): 4.94) formed a mixture of self-sorted and 14 ACS Paragon Plus Environment

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coassembled nanofibers. However, the ClogP value was not a universal parameter because

the

self-sorting

behaviors

of

BPmoc-F3,

NPmoc-F(CF3)F,

and

NPmoc-FF(CF3), which have a similar ClogP values (4.92, 4.94, 4.94, respectively), were completely different. This implied that the N-terminal structures of the peptide-type hydrogelators may also be crucial for self-sorting. Similarly, the ClogP values of lipid-type hydrogelators seemed to show poor correlation with self-sorting behaviors (Table S2). The anionic lipid-type hydrogelators, which showed a range of ClogP values (Phos-cycC6: 3.93, Phos-MecycC5: 4.05, Phos-norC6: 5.16, Sulf-cycC6: 3.93), were self-sorted with BPmoc-F3, whereas Gua-cycC6 with a similar ClogP value (3.72) was coassembled with BPmoc-F3. Crystallographic analyses of structurally relevant peptide- and lipid-type hydrogelators39,48 may give possible reasons for distinct effects of the hydrophobic moiety over their self-sorting event. The crystal structure of the peptide-type hydrogelators showed that the hydrogelators self-assembled into one-dimensional nanofibers with a β-sheet like packing structure. In this structure, the hydrophobic phenyl side chains exposed outside, thus these groups may be able to interact with other hydrophobic molecules (e.g. lipid-type nanofibers). Therefore, more hydrophobic peptide-type hydrogelators (NPmoc-F(CF3)F and NPmoc-FF(CF3)) may tend to form the coassembled aggregates with the lipid-type hydrogelators. In contrast, lipid-type hydrogelators self-assembled in the bilayer-like packing mode, in which the hydrophobic tail groups are buried in the inner core to prevent the tail groups from interacting with other hydrophobic molecules. Combined with the kinetic factors for self-sorting17, it was reasonably concluded that the hydrophobic tail groups of the lipid-type hydrogelators may have almost negligible impacts on the self-sorting behaviors. In addition, an appropriate pair of fluorescent probes is essential to evaluate the degree of self-sorting. As described in the case of the BPmoc-F3/GalNAc-cycC6 pair, some of the fluorescent probes stain both peptide- and lipid-type hydrogelators. Indeed, it is hard to predict the chemical properties of the fluorescent probes, which highly depend on the properties of the dye skeleton and charge in addition to the core structure. Careful selection of the fluorescent probes selective to each nanofiber is required for an imaging-based study of the self-sorting phenomena.



Formation of three-component orthogonal supramolecular nanofibers Finally, we attempted to construct an orthogonal self-assembly composed of three different nanofibers. We selected the BPmoc-F3 and Phos-cycC6 pair as the first and second types of supramolecular nanofibers. As a candidate for the third type of nanofiber, we chose a RhI complex, which self-assembles through metal-metal interactions as the driving force distinct from the other peptide- and lipid-type hydrogelators (Fig. 5A).49 The RhI complex had a cationic net charge at the metal center, but this cationic charge was largely masked by the aromatic groups, which may prevent the intermolecular interactions with the other anionic hydrogelators. Moreover, the RhI complex showed aggregation-induced emission at approximately 700–850 nm (excitation wavelength: 645 nm), which did not overlap with the excitation and emission wavelengths of BP-OG and Alexa546-cycC6. Indeed, CLSM imaging of the single component RhI complex clearly visualized well-developed nanofibers of the RhI complex with a diameter of ca. 1.0 µm a length >100 µm (Fig. 5B; right).


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Fig. 5. (A) Chemical structure of RhI complex. (B) CLSM images of the nanofibers of (yellow) the RhI complex in the presence of (green) BP-OG and (magenta) Alexa546-cycC6. The left, middle, and right images were acquired by BP-OG, Alexa546-cycC6, and RhI complex channels, respectively. Scale bar: 10 µm. (C) 17 ACS Paragon Plus Environment


CLSM

images

of

the

five-component

mixture

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(BPmoc-F3/Phos-cycC6/RhI

complex/BP-OG/Alexa546-cycC6) prepared by the one-step protocol (see the experimental section for detail). The green, magenta, and yellow images were acquired by BP-OG, Alexa546-cycC6, and RhI complex channels, respectively. The right figure was the overlay image of three channels. Scale bar: 10 µm. In the one-step protocol, not nanofibers but spherical aggregates could be observed by RhI complex channel, which were overlapped with Phos-cycC6 nanofibers. (D) Schematic illustration of the two-step protocol. (E) The high resolution CLSM images (with an Airyscan unit) of the five-component

(BPmoc-F3/Phos-cycC6/RhI

mixture

complex/BP-OG/Alexa546-cycC6) prepared by the two-step protocol. The overlay image clearly showed the three orthogonal nanofibers. A white line was used for a line plot shown in Fig. 5G. Scale bar: 20 µm. (F) Pearson’s correlation coefficients of distinct combinations of two hydrogelators. (G) Line plot along a white line shown in the overlay image of Fig. 5E. [BPmoc-F3] = 1.6 mM, [Phos-cycC6] = 2.4 mM, [RhI complex] = 0.38 mM, [BP-OG] = 4.0 µM, [Alexa546-cycC6] = 4.0 µM in 100 mM MES, pH 7.0. Scale bar: 20 µm.

Then, we attempted the self-assembly of the RhI complex with BPmoc-F3 and Phos-cycC6. First, we confirmed the orthogonality of the fluorescent probes. The CLSM imaging of the RhI complex mixed with BP-OG and Alexa546-cycC6 showed that no fibrous structures could be detected with the BP-OG and Alexa546-cycC6 channels, indicating that BP-OG and Alexa546-cycC6 never stained the nanofibers of the RhI complex (Fig. 5B). Then, we conducted CLSM imaging of the mixture of five components (BPmoc-F3/Phos-cycC6/BP-OG/Alexa546-cycC6/RhI complex) prepared by the one-step heating-cooling protocol. The CLSM images showed that orthogonal nanofibers were not formed (Fig. 5C). The images acquired from the BP-OG and Alexa546-cycC6 channels showed two distinct nanofiber networks that were self-sorted with each other (Pearson’s correlation coefficient: 0.29). However, the image of the RhI complex channel visualized spherical aggregates (diameter: ca. 1.0 µm) but no nanofibers. These data suggested that the cationic RhI complex interacted with the anionic BPmoc-F3 and Phos-cycC6 to form spherical coassembled structures, unlike the case of the single component RhI complex. 18 ACS Paragon Plus Environment

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Therefore, we changed the mixing protocol according to Adam’s method, which emphasizes that kinetic factors are critical for self-sorting20. In this protocol, the RhI nanofibers were preorganized before the addition of the mixture of BPmoc-F3 and Phos-cycC6 (Fig. 5D). We prepared a solution of RhI nanofibers by heating of a suspension of RhI complex at 120 ºC for 5 min and cooling to room temperature. Then, a mixture of BPmoc-F3/BP-OG/Phos-cycC6/Alexa546-cycC6 was heated at 120 ºC for 10 min, cooled at room temperature for 3 min, and added to the RhI nanofiber solution 30 min after it was prepared, and we conducted the CLSM imaging after 30 min incubation (see the experimental section for the detailed protocol). In this two-step protocol, we successfully obtained the orthogonal assembly of three distinct nanofibers. The high-resolution CLSM imaging (with an Airyscan detector) clearly showed three types of orthogonally assembled supramolecular nanofibers (Fig. 5E, Fig. S29). The Pearson’s correlation coefficients were determined to be 0.30, –0.14, and –0.02 for the BP-OG/Alexa546-cycC6 pair, BP-OG/RhI complex pair, and Alexa546-cycC6/RhI complex pair, respectively, suggesting almost no correlation between the three types of nanofibers (Fig. 5F). The line plot also indicated that the three different networks had different spatial profiles (Fig. 5G), which revealed that the nanofibers of BPmoc-F3, Phos-cycC6, and the RhI complex formed three orthogonal supramolecular nanofibers. This example highlighted the importance of the influence of the structural factors and the kinetic parameter in self-sorting of nanofibers, the combination of which allowed for the orthogonal self-assembly of multicomponent supramolecular systems. To the best of our knowledge, this is the first example of direct visualization of three distinct sets of self-assembled nanofibers. Conclusion We investigated the critical factors that influence the self-sorting behavior of the structurally distinct peptide- and lipid-type hydrogelators. By direct imaging of two different supramolecular nanofibers by CLSM, we found two important factors for self-sorting: (i) the net or surface charge of hydrogelators; (ii) the hydrophobicity of the peptide-type hydrogelators but not the lipid-type hydrogelators. Based on our results, we achieved an orthogonal self-assembly of three different types of supramolecular nanofibers. Our results would be beneficial for the rational design of multicomponent soft materials comprising not only supramolecular nanofibers but also other functional 19 ACS Paragon Plus Environment


materials including liposomes, organic/inorganic materials, and protein assemblies. Such multicomponent smart materials with programmed functions would be promising for a variety of applications, such as diagnosis, controlled drug release, and regenerative medicine.


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Experimental procedures CLSM imaging of the mixture of two types of hydrogelators and their fluorescent probes. A powder of peptide-type hydrogelators was dissolved in an aqueous buffer (100 mM MES, pH 7.0) by heating at 120 ºC for 5 min with a hot plate (As One) to form a homogenous solution. The solution of lipid-type hydrogelators was also prepared by dissolving a powder by using a hot plate (120 ºC, 5 min) or a heat gun (Ishizaki Electric MFG). Then, equal amounts of solutions of peptide- and lipid-type hydrogelators were mixed, and to this mixture, the fluorescent probes (DMSO solutions) were added (final DMSO concentration: 1~2 vol%). Suspensions of the appropriate component mixtures (the concentrations were described in figure captions) were heated at 120 ºC for 1 min to form homogeneous solutions and cooled at room temperature (rt) for 1 min. Before gelation, the solution (30 µL) was spotted on a glass-bottom dish (Matsunami, non-coat, 0.15–0.18 mm glass bottom) and incubated with water drops (50 µL) to avoid dryness at rt for 30 min. The obtained solutions or hydrogels were subjected to CLSM observation. CLSM observation was conducted with a FV1000 equipped with a 100×, numerical aperture (NA) 1.40 oil objective. The excitation wavelengths were 488 nm for BP-OG and NBD-cycC6, 543 nm for Alexa546-cycC6, and 633 nm for NP-Alexa647. CLSM imaging of orthogonal self-assembly of peptide-, lipid-type hydrogelators and RhI complex One-step

protocol.

A

suspension

of

the

five-component

mixture

I

(BPmoc-F3/BP-OG/Phos-cycC6/Alexa546-cycC6/Rh complex) was heated at 120 ºC to form a homogenous solution. After incubation at rt for 3 min, the resulting mixture was spotted on a glass-bottom dish (Matsunami, non-coat, 0.15–0.18 mm glass bottom) and incubated at rt for 1 h in the presence of water drops (50 µL) to avoid dryness. The obtained hydrogel was subjected to CLSM observation. The excitation wavelengths were 488 nm for BP-OG, 543 nm for Alexa546-cycC6, and 633 nm for the RhI complex. Two-step protocol. A suspension of the RhI complex (0.76 mM) was heated at 120 ºC to form a homogenous solution. After incubation at rt for 3 min, the resulting solution was spotted on a glass-bottom dish (Matsunami, non-coat, 0.15–0.18 mm glass bottom) 21 ACS Paragon Plus Environment


and incubated at rt for 30 min in the presence of water drops (50 µL) to avoid dryness. A mixture of BPmoc-F3 (3.2 mM), Phos-cycC6 (4.8 mM), BP-OG (8.0 µM), and Alexa546-cycC6 (8.0 µM) was heated at 120 ºC for 10 min, cooled at room temperature for 3 min, and added to the suspension of the RhI complex, followed by incubated at rt for 30 min. Then, the resultant mixture was subjected to CLSM observation. To probe the orthogonality of fluorescent probes. A suspension of the RhI complex was heated at 120 ºC to form a homogenous solution. After incubation at rt for 3 min, the resulting solution was spotted on a glass-bottom dish (Matsunami, non-coat, 0.15– 0.18 mm glass bottom) and incubated with water drops (50 µL) to avoid dryness at rt for 30 min. A buffer solution of BP-OG and Alexa546-cycC6 was added to the suspension of the RhI complex, followed by incubated at rt for 30 min. Then, the resultant mixture was subjected to CLSM observation. CD measurements. The samples were prepared by mixing the hot homogeneous solutions of gelators in a 1:1 volume ratio. The obtained gels or solutions were poured into a quartz cell (path length of 0.05 mm). After incubation for 30 min at rt, the CD spectra were measured by using a JASCO J-720WI spectrometer. The theoretical CD spectra of the mixture were obtained from a sum of CD spectra of each component by using Microsoft Excel for Mac 2011 (Microsoft).

Supporting information The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.bioconjchem. Organic syntheses, characterization data, supporting tables, and supporting figures.

Author information Corresponding author *E-mail: [email protected] ORCID Ryou Kubota: 0000-0001-8112-8169 22 ACS Paragon Plus Environment

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Hajime Shigemitsu: 0000-0002-3104-049X Masato Ikeda: 0000-0003-4097-8292 Itaru Hamachi: 0000-0002-3327-3916 Notes The authors declare no competing financial interest.

Acknowledgements The authors thank Dr. F. Ishidate and Center for Meso-Bio Single-Molecule Imaging (CeMI, WPI-iCeMS) for high-resolution CLSM imaging (LSM880 equipped with an Airyscan detector). This work was also supported by a Grant-in-Aid for Scientific Research on Innovative Areas “Chemistry for Multimolecular Crowding Biosystems” (JSPS KAKENHI Grant No. 17H06348 for I.H.) and for Young Scientists (JSPS KAKENHI Grant No. 18K14333 for R.K.). S.L. and H.S. acknowledge JSPS Research Fellowships for Young Scientists (17F17045 and 16J10716, respectively). The authors acknowledge financial support from The Mitsubishi Foundation.



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Imaging-Based Study on Control Factors over Self-Sorting of

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