Qilin Xie’s research while affiliated with Japan Science and Technology Agency (JST) and other places

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Publications (6)


Figure 1. (a) Contact ratio C ID (i) (eq 1) as a function of residue ordinal number i in ID SK for both the u-state and p-state systems. (b) Contact ratio C VP (j) (eq 3) as a function of residue ordinal number j of VP16ad. Inter-residue contact map between ID SK and VP16ad for (c) the u-state system and (d) the p-state system. Amino acids pS15, pS17, and pS19 are phosphorylated serine residues. White regions were not sampled in the simulation because the free energy assigned to those regions is extremely high.
Figure 2. FEL for the (a) u-state and (b) p-state systems, which are presented in 2D PC space constructed by PC1 and PC2. The insets present typical conformations picked from the lowest free-energy basins, where "N" and "C" respectively denote the N-and C-termini of ID SK . SEAC and K-rich segments are presented by green and red models, respectively. Gray and black models are respectively the (PC4ctd) 2 dimer and VP16ad. The magenta-colored frames are mentioned in the text.
Figure 3. Intra-ID SK contact map C ID−ID (i, j) for conformations in the lowest free-energy basin (Figure 2) for (a) the u-state and (b) the p-state systems. The contents of the yellow and white rectangles in panels (a) and (b), respectively, are described in the text. Amino acids pS15, pS17, and pS19 are phosphorylated serine residues. White regions were not sampled in simulation because the free energy assigned to those regions is extremely high.
Figure 4. FELs for the (a) u-state and (b) p-state systems in 2D PC space constructed by PC1 and PC2. PCA was performed using C α atoms in Atom ID . Two clusters "Clst 1" and "Clst 2" are mentioned in the text.
Figure 5. (a) Two conformations of the u-state system picked from the low free-energy basin of Figure 4a. (b) Three conformations from the major basin (Clst 1 of Figure 4b) of the p-state system. Side chains of three phosphoserine residues pS15, pS17, and pS19 are explicit; side chains of contact partners to the phosphoserine residues are also shown. Magenta rectangles represent the SEAC−K-rich contact region corresponding to the specific contact pattern shown by the white rectangle in Figure 3b. (c) Two conformations from the minor basin (Clst 2 of Figure 4b) of the p-state system. Magenta circles indicate the twisted conformation mentioned in the text. Green and red segments respectively represent the SEAC and K-rich segments. Gray and black models are respectively the (PC4ctd) 2 dimer and VP16ad.
Molecular Mechanisms of Functional Modulation of Transcriptional Coactivator PC4 via Phosphorylation on Its Intrinsically Disordered Region
  • Article
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April 2023

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32 Reads

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3 Citations

ACS Omega

Qilin Xie

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Junichi Higo

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Takuya Takahashi

To investigate the effects of phosphorylation on the function of the human positive cofactor 4 (PC4), an enhanced molecular dynamics (MD) simulation was performed. The simulation system consists of the N-terminal intrinsic disordered region (IDR) of PC4 and a complex that comprises the C-terminal acidic activation domain of a herpes simplex virion protein 16 (VP16ad) and a homodimer of the C-terminal structured core domain of PC4 (PC4ctd). An earlier report of an experimental study reported that the PC4-VP16ad interaction is modulated by incremental phosphorylation of the IDR. That report also proposed a dynamic model where phosphorylated serine residues of a segment (SEAC) in the IDR contact positively charged residues (lysin and arginine) of another segment (K-rich) in the IDR. This contact formation induced by the phosphorylation results in variation of PC4-VP16ad interaction. However, this contact formation has not yet been measured directly because it is transiently formed and because the SEAC and K-rich segments are unstructured with high flexibility. We performed two simulations to mimic the incremental phosphorylation: the IDR was not phosphorylated in one simulation and only partially phosphorylated in the other. Our simulation results indicate that the phosphorylation weakens the IDR-VP16ad contact considerably with the induction of a compact structure in the IDR. This structure was stabilized by electrostatic interactions between the phosphorylated serine residues of a segment and lysine or arginine residues of another segment in the IDR, but the conformational fluctuation of this compact structure was considerably large. Consequently, the present study supports the experimentally proposed dynamic model. Results of this study can be important for computational elucidation of the functional modulation of PC4.

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Identification of Siglec-5 as a CNT-recognizing receptor
a, Strategy for in silico screening of macrophage receptors harbouring clusters of aromatic residues. b, Three-dimensional structures of Siglec-5, Siglec-3 and Tim4. Arrowheads indicate aromatic residues: WY50/51 (Siglec-5), YY49/50 (Siglec-3) and WF119/120 (Tim4). c, Parental NIH-3T3 cells and NIH-3T3 cells stably expressing Siglec-5, Siglec-3 or Tim4 were cultured with 10 or 30 μg ml⁻¹ of MWCNTs for 30 min and binding was analysed by flow cytometry. The delta median side scatter intensity (∆MSI) was calculated by subtracting the MSI of MWCNT-treated cells from the MSI of untreated cells. See also Extended Data Fig. 1. Data are shown as mean ± s.d. (n = 3). ***P < 0.001, two-way ANOVA with Tukey–Kramer test.
Source data
MD simulations and in vitro validation to clarify the binding modes of Siglec-5 to MWCNTs
a, Snapshots from the simulation trajectories in modes 1, 2 and 4 are shown. See also Supplementary Fig. 4 for modes 3 (unbound form) and 5. b, The architecture of the CNT interaction interface of Siglec-5 is schematically presented. The simulation model for Siglec-5 consists of extracellular domains that are indicated by open and filled cylinders. The four interaction interfaces at the bottom of the V-set Ig-like domain are marked with pink triangles. c, Relative populations of each binding mode in simulation ensembles of WT (left), WY50/51AA (centre) and WYYY50/51/68/69AAAA (right) are shown as pie charts. d, Diverse tilt angle of Siglec-5 over the CNT surface was observed in simulation trajectories of WT (black), WY50/51AA (red) and WYYY50/51/68/69AAAA (cyan) models. The tilt angle is defined as the C–B–A angle, as shown on the left. See also Methods. The standard deviations of the angles of WT, WY50/51AA and WYYY50/51/68/69AAAA were 8.95°, 15.8° and 16.3°, respectively. e, The recognition of MWCNTs by the indicated NIH-3T3 cells was analysed as in Fig. 1c. See also Supplementary Fig. 6. Data are shown as mean ± s.d. (n = 3). **P = 0.0023, ***P < 0.001, two-way ANOVA with Tukey–Kramer test.
Source data
Siglec-14, but not Siglec-5, engulfs MWCNTs to induce IL-1β secretion and pulmonary inflammation
a, Siglec expression in cells treated with MWCNTs for 24 h was analysed by immunoblot. See also Methods. b,c, Siglec expression on MWCNT-treated cells was analysed by flow cytometry at 5 h (b) and at the indicated time points (c). Red and black lines indicate SY2 and control mouse IgG1 (cIg) staining, respectively (b). The percentage reduction of Siglec expression on cells was calculated as the MSI of Siglec staining on MWCNT-treated cells at the indicated time point × 100/MSI of Siglec staining on untreated cells (c). d, Cell recognition of MWCNTs was analysed as in Fig. 1c. Data are shown as mean ± s.d. (n = 3). ***P < 0.001, two-way ANOVA with Tukey–Kramer test. e, MWCNT-treated cells were stained with AF488-phalloidin and 4,6-diamidino-2-phenylindole and were then analysed by fluorescence microcopy. f, Caspase-1 activation was analysed by immunoblot. See also Methods. g, IL-1β secretion was analysed by ELISA. Data are shown as mean ± s.d. (n = 3). ***P < 0.001, two-way ANOVA with Tukey–Kramer test. h, B6 mice (n = 4) were intratracheally infected with mock or Siglec-14 lentivirus (lenti). Siglec-14 expression on Siglec-F⁺ alveolar macrophages was analysed in BALF cells by flow cytometry. Representative data are shown. See also Supplementary Fig. 11a. i, Siglec-14-transduced mice (n = 4) were intratracheally injected with a single dose of MWCNTs (50 μg per head). After 1 day, BALF cells were harvested. MWCNT recognition by Siglec-F⁺ Siglec-14⁻ or Siglec-F⁺ Siglec-14⁺ alveolar macrophages was analysed as in Fig. 1c. See also Supplementary Fig. 11b. ***P < 0.001, unpaired two-tailed t-test. j, Mock- or Siglec-14-transduced mice (n = 4 each) were treated as in i. IL-1β was quantified in BALF by ELISA. Data are shown as mean ± s.d. (n = 3). *P = 0.0228, ***P < 0.001, two-way ANOVA with Tukey–Kramer test. k, Mock- or Siglec-14-transduced mice (n = 3 each) were treated as in i. Lungs were analysed by haematoxylin and eosin staining. Representative data are shown. Boxed areas in Supplementary Fig. 11c show higher magnification.
Source data
Siglec-14-mediated recognition of MWCNTs by human monocytes
a, Human pulmonary fibrosis tissue was stained with anti-CD68 and SY2, followed by AF568-anti-rabbit IgGs and AF488-anti-mouse IgGs, respectively. b, Siglec-5/14 expression on PBMCs from healthy human donors was analysed as in Fig. 3b. c, Schematic illustration of Siglec14 gene structure and primers for the genotyping PCR. d, Genomic DNA was prepared from PBMCs and the Siglec14 (S14) genotype was determined by standard PCR using a primer pair shown in c. e, PBMCs pretreated with cIg or SY2 (10 μg ml⁻¹ each) were treated with MWCNTs (30 μg ml⁻¹) for 30 min. Then cells were stained with anti-CD14 mAb. Numbers indicate MSI. f, PBMCs were treated as in e. MWCNT recognition by CD14⁺ PB monocytes or CD14⁻ PB lymphocytes was calculated as in Fig. 1c. Data are shown as mean ± s.d. (n = 3). ***P < 0.001, two-way ANOVA with Tukey–Kramer test. g, LPS (1 ng ml⁻¹)-primed PBMCs were pretreated with mAb (10 μg ml⁻¹) and were then treated with MWCNTs or ATP for 3 h. IL-1β secretion was analysed by ELISA. Data are shown as mean ± s.d. (n = 3). *P = 0.0306, **P = 0.0043, ***P < 0.001, two-way ANOVA with Tukey–Kramer test.
Source data
Siglec-14-Syk-mediated inflammatory responses to MWCNTs are blocked by fostamatinib
a, Syk null cells were generated by CRISPR/Cas9-mediated targeting and were cloned by limiting dilution. Syk expression was analysed by immunoblot. b, Sequence of Syk in WT cells and mutant clone #3 alleles around the target locus. The gRNA target sequence is in bold. Deleted bases are indicated by hyphens. c, Cell surface expression of Siglec-14 on the indicated THP-1 cells was analysed as in Fig. 3b. d, Phagocytosis of MWCNTs by the indicated THP-1 cells was analysed as in Fig. 3e. e, IL-1β secretion from the indicated THP-1 cells was analysed as in Fig. 3g. Data are shown as mean ± s.d. (n = 3). ***P < 0.001, one-way ANOVA with Tukey–Kramer test. f, PMA-primed Siglec-14/THP-1 cells were pretreated with the indicated dose of R406 for 1 h and then were treated with MWCNTs (30 μg ml⁻¹) or nigericin (3 μM) for 5 h. The percentage reduction of IL-1β secretion was calculated as the amount of IL-1β produced by the indicated dose of R406-treated cells × 100/the amount of IL-1β produced by R406-untreated cells. Data are shown as mean ± s.d. (n = 3). **P = 0.0042, ***P < 0.001, one-way ANOVA with Tukey–Kramer test. g, LPS-primed S14+/− donor PBMCs (n = 4) were pretreated the indicated dose of R406 for 1 h and then were treated with MWCNTs (10 μg ml⁻¹) or ATP (1 mM) for 3 h. The percentage reduction of IL-1β secretion in individuals was calculated as in f. Data are shown as mean ± s.d. (n = 4). ***P < 0.01, one-way ANOVA with Tukey–Kramer test. h, Mock- or Siglec-14-transduced mice (n = 6 each) generated as in Fig. 3h were orally administered with R788 (0.6 mg per head) or vehicle (0.5% w/v methyl cellulose 400 solution) at 12 h and 0.5 h before intratracheal injection of MWCNTs (50 μg per head). One day later, the concentration of IL-1β and TNF-α in BALF was measured by ELISA. *P = 0.0267, ***P < 0.001, two-way ANOVA with Tukey–Kramer test.
Source data
Carbon nanotube recognition by human Siglec-14 provokes inflammation

April 2023

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157 Reads

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19 Citations

Nature Nanotechnology

Shin-Ichiro Yamaguchi

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Qilin Xie

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[...]

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Masafumi Nakayama

For the design and development of innovative carbon nanotube (CNT)-based tools and applications, an understanding of the molecular interactions between CNTs and biological systems is essential. In this study, a three-dimensional protein-structure-based in silico screen identified the paired immune receptors, sialic acid immunoglobulin-like binding lectin-5 (Siglec-5) and Siglec-14, as CNT-recognizing receptors. Molecular dynamics simulations showed the spatiotemporally stable association of aromatic residues on the extracellular loop of Siglec-5 with CNTs. Siglec-14 mediated spleen tyrosine kinase (Syk)-dependent phagocytosis of multiwalled CNTs and the subsequent secretion of interleukin-1β from human monocytes. Ectopic in vivo expression of human Siglec-14 on mouse alveolar macrophages resulted in enhanced recognition of multiwalled CNTs and exacerbated pulmonary inflammation. Furthermore, fostamatinib, a Syk inhibitor, blocked Siglec-14-mediated proinflammatory responses. These results indicate that Siglec-14 is a human activating receptor recognizing CNTs and that blockade of Siglec-14 and the Syk pathway may overcome CNT-induced inflammation.


Extended ensemble simulations of a SARS-CoV-2 nsp1–5’-UTR complex

January 2022

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82 Reads

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7 Citations

Nonstructural protein 1 (nsp1) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a 180-residue protein that blocks translation of host mRNAs in SARS-CoV-2-infected cells. Although it is known that SARS-CoV-2’s own RNA evades nsp1’s host translation shutoff, the molecular mechanism underlying the evasion was poorly understood. We performed an extended ensemble molecular dynamics simulation to investigate the mechanism of the viral RNA evasion. Simulation results suggested that the stem loop structure of the SARS-CoV-2 RNA 5’-untranslated region (SL1) binds to both nsp1’s N-terminal globular region and intrinsically disordered region. The consistency of the results was assessed by modeling nsp1-40S ribosome structure based on reported nsp1 experiments, including the X-ray crystallographic structure analysis, the cryo-EM electron density map, and cross-linking experiments. The SL1 binding region predicted from the simulation was open to the solvent, yet the ribosome could interact with SL1. Cluster analysis of the binding mode and detailed analysis of the binding poses suggest residues Arg124, Lys47, Arg43, and Asn126 may be involved in the SL1 recognition mechanism, consistent with the existing mutational analysis.


All-Atom Molecular Dynamics Elucidating Molecular Mechanisms of Single-Transmembrane Model Peptide Dimerization in a Lipid Bilayer

May 2021

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57 Reads

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3 Citations

ACS Omega

Protein–protein interactions between transmembrane helices are essential elements for membrane protein structures and functions. To understand the effects of peptide sequences and lipid compositions on these interactions, single-molecule experiments using model systems comprising artificial peptides and membranes have been extensively performed. However, their dynamic behavior at the atomic level remains largely unclear. In this study, we applied the all-atom molecular dynamics (MD) method to simulate the interactions of single-transmembrane helical peptide dimers in membrane environments, which has previously been analyzed by single-molecule experiments. The simulations were performed with two peptides (Ala- and Leu-based artificially designed peptides, termed “host peptide”, and the host peptide added with the GXXXG motif, termed “GXXXG peptide”), two membranes (pure-POPC and POPC mixed with 30% cholesterols), and two dimer directions (parallel and antiparallel), consistent with those in the previous experiment. As a result, the MD simulations with parallel dimers reproduced the experimentally observed tendency that introducing cholesterols weakened the interactions in the GXXXG dimer and facilitated those in the host dimer. Our simulation suggested that the host dimer formed hydrogen bonds but the GXXXG dimer did not. However, some discrepancies were also observed between the experiments and simulations. Limitations in the space and time scales of simulations restrict the large-scale undulation and peristaltic motions of the membranes, resulting in differences in lateral pressure profiles. This effect could cause a discrepancy in the rotation angles of helices against the membrane normal.


Figure 3. Molecular dynamics simulations of the interaction between Tim4 mutants and CNT (A) Snapshots of the interaction between Tim4 mutant IgV domains and CNT are shown at the indicated simulation time points. Tim4 mutants are shown in the same way as in Figure 2B. See also Videos S2, S3, S4, and S5. (B) Root-mean-square fluctuation (RMSF) of the Ca atom of WT Tim4, and the indicated mutant was calculated over the MD trajectories. L1-L8 are the large loops in Tim4 shown in Figure 2B. See also Figure S2. (C) Schematic diagram of the tilt angle, which is defined as the angle between the x-y plane and the vector connecting Ca atoms of W119 and G105. (D) Distribution of the tilt angle defined as in (C) is shown over 100 ns MD trajectories. (E) Schematic diagram of the area of interface between Tim4 and CNT. (F) Distribution of the interface area defined as in (E) is shown over 95 ns MD trajectories. See also Figure S4.
Tim4 recognizes carbon nanotubes and mediates phagocytosis leading to granuloma formation

February 2021

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71 Reads

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29 Citations

Cell Reports

Macrophage recognition and phagocytosis of crystals is critical for the associated fibrosis and cancer. Of note, multi-walled carbon nanotubes (MWCNTs), the highly representative products of nanotechnology, induce macrophage NLRP3 inflammasome activation and cause asbestosis-like pathogenesis. However, it remains largely unknown how macrophages efficiently recognize MWCNTs on their cell surfaces. Here, we identify by a targeted screening of phagocyte receptors the phosphatidylserine receptors T cell immunoglobulin mucin 4 (Tim4) and Tim1 as the pattern-recognition receptors for carbon crystals. Docking simulation studies reveal spatiotemporally stable interfaces between aromatic residues in the extracellular IgV domain of Tim4 and one-dimensional carbon crystals. Further, CRISPR-Cas9-mediated deletion of Tim4 and Tim1 reveals that Tim4, but not Tim1, critically contributes to the recognition of MWCNTs by peritoneal macrophages and to granuloma development in a mouse model of direct mesothelium exposure to MWCNTs. These results suggest that Tim4 recognizes MWCNTs through aromatic interactions and mediates phagocytosis leading to granulomas.


Citations (5)


... PCA has been used to visualize the distribution by projecting the points to a low-dimensional space. 54−57 We applied PCA to the ensembles of the snapshots according to our earlier study, 57 the methodological details of which are explained in Supplementary Section 5. Below we briefly present an outline of the PCA done for this study. The variance-covariance matrix is calculated from atom-pair distances between the whole Cα atoms of PLpro (316 Cα atoms) and the heavy atoms (eight atoms) in a core region of the compound ( Figure S5 of SI). ...

Reference:

Affinity of Drug Candidates Binding to SARS CoV-2 PLpro Assessed Using a Generalized-ensemble Method
Molecular Mechanisms of Functional Modulation of Transcriptional Coactivator PC4 via Phosphorylation on Its Intrinsically Disordered Region

ACS Omega

... cNt exposure can cause oxidative stress via overproduction of ROS in cells, leading to cytotoxicity [81,[91][92][93]. they can activate inflammatory pathways, triggering the release of pro-inflammatory cytokines and chemokines [94][95][96][97]. they can directly damage DNA or indirectly induce DNA damage (genotoxicity) through ROS production, potentially leading to mutations and cancer development [98,99]. ...

Carbon nanotube recognition by human Siglec-14 provokes inflammation

Nature Nanotechnology

... Several models have been proposed to explain the escape of viral mRNA from degradation. The most reliable one suggests that viral mRNAs containing the SL1 interact with Nsp1 and, in association with cellular factor(s), induce a conformational change in Nsp1 that unplugs its C-terminal domain from the 40S entry channel, thereby allowing mRNA translation [36,[47][48][49]. Specific mutations within NTD of Nsp1 (R 99 A and R 124 A/K 125 A) have negative effects on the translation of SARS-CoV-2 leader mRNA, instead. ...

Extended ensemble simulations of a SARS-CoV-2 nsp1–5’-UTR complex

... 23,[30][31][32][33][34][35] Transmembrane helices are also useful in computer simulation studies to examine the effects of membrane physicochemical properties on the associations of transmembrane helices at the molecular level. [36][37][38][39] My collaborators and I used three types of model transmembrane helices (1TM, GXXXG, and 2TM) to examine the effects of cholesterol (Fig. 5). The helices were prepared by Fmoc solid-phase peptide synthesis, and the N-termini were labeled with cyanine dyes Cy3B (FRET donor) and Cy5 (FRET acceptor). ...

All-Atom Molecular Dynamics Elucidating Molecular Mechanisms of Single-Transmembrane Model Peptide Dimerization in a Lipid Bilayer

ACS Omega

... [122][123][124] Furthermore, MWCNTs enhance macrophage activation by upregulating CD40 and CD80, stimulating phagocytosis through NLRP3 inflammasome activation via Tim4 receptor recognition. 125,126 Collectively, these NPs contribute to sepsis treatment by modulating inflammatory pathways, enhancing pathogen clearance and maintaining inflammatory balance. Table 2 provides a detailed classification and mechanism overview of macrophage-targeted nanoparticles in sepsis research, highlighting various NP types and their specific roles in modulating macrophage functions. ...

Tim4 recognizes carbon nanotubes and mediates phagocytosis leading to granuloma formation

Cell Reports