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Carbon nanotube recognition by human Siglec-14 provokes inflammation

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Shin-Ichiro Yamaguchi
Shin-Ichiro Yamaguchi
Shin-Ichiro Yamaguchi
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Qilin Xie
Qilin Xie
Qilin Xie
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Fumiya Ito at Johns Hopkins University
Fumiya Ito
Kazuki Terao
Kazuki Terao
Kazuki Terao
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Abstract and Figures

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.
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
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
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, 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-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
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
… 
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Nature Nanotechnology | Volume 18 | June 2023 | 628–636 628
nature nanotechnology
Article
https://doi.org/10.1038/s41565-023-01363-w
Carbon nanotube recognition by human
Siglec-14 provokes inflammation
Shin-Ichiro Yamaguchi1,2,12, Qilin Xie2,3,12, Fumiya Ito   2,4, Kazuki Terao1,
Yoshinobu Kato1, Miki Kuroiwa1, Satoshi Omori   5, Hideo Taniura6,
Kengo Kinoshita   5,7,8,9, Takuya Takahashi   3, Shinya Toyokuni   2,4,10,
Kota Kasahara   2,3,11 & Masafumi Nakayama   1,2
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 identied 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 inammation. Furthermore, fostamatinib, a Syk
inhibitor, blocked S ig le c- 14 -m ediated p ro in  am matory 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 inammation.
Carbon nanotubes (CNTs) have attracted great interest for use in
multiple fields including electronics, material science, biology and
medicine
1,2
. However, due to their possible toxicity and persistence in
nature, the International Chemical Secretariat (ChemSec) has recently
added CNTs to the SIN (‘Substitute It Now’) list of chemicals, propos-
ing that CNTs should not be used without human health risk assess-
ment3. Therefore, additional efforts are needed to understand the
interactions between CNTs and human molecules
4,5
that may induce
inflammation and control toxicity
6
. This knowledge is critical for the
design and development of safer CNTs.
We and others have reported that long and rigid multiwalled CNTs
(MWCNTs) have asbestos-like pathogenicity in rodents7–9. As with
asbestos, after being intraperitoneally injected, MWCNTs are pre-
ferentially engulfed by macrophages, and subsequent macrophage
inflammatory responses are considered to cause chronic inflammation
leading to mesothelioma
7–9
. Indeed, in vitro studies have shown that
Received: 5 October 2021
Accepted: 28 February 2023
Published online: 6 April 2023
Check for updates
1Laboratory of Immunology and Microbiology, College of Pharmaceutical Sciences, Ritsumeikan University, Kusatsu, Japan. 2CREST, Japan Science
and Technology Agency (JST), Kawaguchi, Japan. 3Computational Structural Biology Laboratory, College of Life Sciences, Ritsumeikan University,
Kusatsu, Japan. 4Department of Pathology and Biological Responses, Nagoya University Graduate School of Medicine, Nagoya, Japan. 5Graduate
School of Information Sciences, Tohoku University, Sendai, Japan. 6Laboratory of Neurochemistry, College of Pharmaceutical Sciences, Ritsumeikan
University, Kusatsu, Japan. 7Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan. 8Advanced Research Center for Innovations in
Next-Generation Medicine, Tohoku University, Sendai, Japan. 9Department of In Silico Analyses, Institute of Development, Aging and Cancer (IDAC),
Tohoku University, Sendai, Miyagi, Japan. 10Center for Low Temperature Plasma Science, Nagoya University, Nagoya, Japan. 11Present address: Central
Pharmaceutical Research Institute, Japan Tobacco Inc., Takatsuki, Japan. 12These authors contributed equally: Shin-Ichiro Yamaguchi, Qilin Xie.
e-mail: kota.kasahara@jt.com; mnakayam@fc.ritsumei.ac.jp
Content courtesy of Springer Nature, terms of use apply. Rights reserved
... 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]. ...
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  • Nov 2020
Among the diverse development of stimuli-responsive assemblies, plasmonic nanoparticle (NP) assemblies functionalized with responsive molecules are of a major interest. In this review, we outline a comprehensive and up-to-date overview of recently reported studies on in vitro and in vivo assembly/disassembly and biomedical applications of plasmonic NPs, wherein stimuli such as enzymes, light, pH, redox potential, temperature, metal ions, magnetic or electric field, and/or multi-stimuli were involved. Stimuli-responsive assemblies have been applied in various biomedical fields including biosensors, surfaced-enhanced Raman scattering (SERS), photoacoustic (PA) imaging, multimodal imaging, photo-activated therapy, enhanced X-ray therapy, drug release, stimuli-responsive aggregation-induced cancer therapy, and so on. The rerspectives on the use of stimuli-responsive plasmonic assemblies are discussed by addressing future scientific challenges involving assembly/disassembly strategies and applications.
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New Mechanistic Insights on Carbon Nanotubes Nanotoxicity Using Isolated Submitochondrial Particles, Molecular Docking, and Nano-QSTR Approaches
Article
Full-text available
  • Sep 2020
Herein, we present a combination of experimental and computational study on the mitochondrial F0F1-ATPase nanotoxicity inhibition induced by single-walled carbon nanotubes (SWCNT-pristine, SWCNT-COOH). To this end, the in vitro inhibition responses in submitochondrial particles (SMP) as F0F1-ATPase enzyme were strongly dependent on the concentration assay (from 3 to 5 µ g/ml) for both types of carbon nanotubes. Besides, both SWCNTs show an interaction inhibition pattern like the oligomycin A (the specific mitochondria F0F1-ATPase inhibitor). Furthermore, the best crystallography binding pose obtained for the docking complexes based on the free energy of binding (FEB), fit well with the previous in vitro evidences from the thermodynamics point of view. Following an affinity order as: FEB (oligomycin A/F0-ATPase complex) =-9.8 kcal/mol > FEB (SWCNT-COOH/F0-ATPase complex) =-6.8 kcal/mol ~ FEB (SWCNT-pristine complex) =-5.9 kcal/mol. With predominance of van der Waals hydrophobic nanointeractions with key F0-ATPase binding site residues (Phe 55 and Phe 64). By the other hand, results on elastic network models, and fractal-surface analysis suggest that SWCNTs induce significant perturbations by triggering abnormal allosteric responses and signals propagation in the inter-residue network which could affect the substrate recognition ligand geometrical specificity of the F0F1-ATPase enzyme in order (SWCNT-pristine > SWCNT-COOH). Besides, the performed Nano-QSTR models for both SWCNTs show that this method may be used for the prediction of the nanotoxicity induced by SWCNT. Overall, the obtained results may open new avenues toward to the better understanding and prediction of new nanotoxicity mechanisms, rational drug-design based nanotechnology, and potential biomedical application in precision nanomedicine.
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Asbestos conceives Fe(II)-dependent mutagenic stromal milieu through ceaseless macrophage ferroptosis and β-catenin induction in mesothelium
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  • Jun 2020
Asbestos is still a social burden worldwide as a carcinogen causing malignant mesothelioma. Whereas recent studies suggest that local iron reduction is a preventive strategy against carcinogenesis, little is known regarding the cellular and molecular mechanisms surrounding excess iron. Here by differentially using high-risk and low-risk asbestos fibers (crocidolite and anthophyllite, respectively), we identified asbestos-induced mutagenic milieu for mesothelial cells. Rat and cell experiments revealed that phagocytosis of asbestos by macrophages results in their distinctive necrotic death; initially lysosome-depenent cell death and later ferroptosis, which increase intra- and extra-cellular catalytic Fe(II). DNA damage in mesothelial cells, as assessed by 8-hydroxy-2’-deoxyguanosine and γ-H2AX, increased after crocidolite exposure during regeneration accompanied by β-catenin activation. Conversely, β-catenin overexpression in mesothelial cells induced higher intracellular catalytic Fe(II) with increased G2/M cell-cycle fraction, when p16INK4A genomic loci localized more peripherally in the nucleus. Mesothelial cells after challenge of H2O2 under β-catenin overexpression presented low p16INK4A expression with a high incidence of deletion in p16INK4A locus. Thus, crocidolite generated catalytic Fe(II)-rich mutagenic environment for mesothelial cells by necrotizing macrophages with lysosomal cell death and ferroptosis. These results suggest novel molecular strategies to prevent mesothelial carcinogenesis after asbestos exposure.
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Aromatic clusters in protein–protein and protein–drug complexes
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  • May 2020
Abstract Aromatic rings are important residues for biological interactions and appear to a large extent as part of protein–drug and protein–protein interactions. They are relevant for both protein stability and molecular recognition processes due to their natural occurrence in aromatic aminoacids (Trp, Phe, Tyr and His) as well as in designed drugs since they are believed to contribute to optimizing both affinity and specificity of drug-like molecules. Despite the mentioned relevance, the impact of aromatic clusters on protein–protein and protein–drug complexes is still poorly characterized, especially in those that go beyond a dimer. In this work, we studied protein–drug and protein–protein complexes and systematically analyzed the presence and structure of their aromatic clusters. Our results show that aromatic clusters are highly prevalent in both protein–protein and protein–drug complexes, and suggest that protein–protein aromatic clusters have idealized interactions, probably because they were optimized by evolution, as compared to protein–drug clusters that were manually designed. Interestingly, the configuration, solvent accessibility and secondary structure of aromatic residues in protein–drug complexes shed light on the relation between these properties and compound affinity, allowing researchers to better design new molecules.
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Key principles and methods for studying the endocytosis of biological and nanoparticle therapeutics
Article
  • Mar 2021
Endocytosis is a critical step in the process by which many therapeutic nanomedicines reach their intracellular targets. Our understanding of cellular uptake mechanisms has developed substantially in the past five years. However, these advances in cell biology have not fully translated to the nanoscience and therapeutics literature. Misconceptions surrounding the role of different endocytic pathways and how to study these pathways are hindering progress in developing improved nanoparticle therapies. Here, we summarize the latest insights into cellular uptake mechanisms and pathways. We highlight limitations of current systems to study endocytosis, particularly problems with non-specific inhibitors. We also summarize alternative genetic approaches to robustly probe these pathways and discuss the need to understand how cells endocytose particles in vivo. We hope that this critical assessment of the current methods used in studying nanoparticle uptake will guide future studies at the interface of cell biology and nanomedicine. Successful nanomedicine approaches rely on the efficient cellular uptake of nanoparticles, yet endocytic mechanisms remain challenging to probe. In this Review the authors describe the different cellular endocytic pathways and provide a critical discussion of the available tools and systems for their study.
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Inorganic nanoparticles in clinical trials and translations
Article
  • Dec 2020
  • NANO TODAY
The development and application of nanotechnology-related knowledge and tools in modern medicine has been showing great potentials in elevating human’s living standards and improving mankind’s healthcare conditions via the prevention, early detection, diagnosis, treatment and follow-up of various diseases. The significant progress of nanomedicine has been achieved by the exploration of nanoparticulate formulations for theranostic purposes in a living organism. Among abundant nanoparticles, inorganic nanoparticles feature distinctive physiochemical properties and biological effects, with which conventional organic counterparts are typically not endowed. In the past thirty years, to be true, very few inorganic nanomaterials have been made from bench to bedside translation. It is thus more vital than ever for the scientific community to make ever-greater efforts to realize their clinical translations. Therefore, this review highlights and discusses such a compelling topic on the clinical trials and translation of inorganic nanoparticles. We will provide an update of the current progresses in clinic-relevant applications in terms of inorganic nanoparticles being used as detecting tools, contrast agents as well as therapeutic vehicles. Especially, the crucial challenges and future prospects in translating inorganic nanoparticles into clinical practices are highlighted and outlooked. This review aims to bring the issues of clinical relevance and translatability of inorganic nanoparticles to the forefront, which is the primary impetus, and also critically important, for the development of inorganic nanoparticles-based nanobiotechnology and nanomedicine.
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Nanoparticle Toxicology
Article
  • Jan 2021
Nanoparticles from natural and anthropogenic sources are abundant in the environment, thus human exposure to nanoparticles is inevitable. Due to this constant exposure, it is critically important to understand the potential acute and chronic adverse effects and toxicity that nanoparticles may cause to humans. In this review, we explore and highlight the current state of nanotoxicology research with a focus on mechanistic understanding of nanoparticle toxicity at organ, tissue, cell, and biomolecular levels. We discuss nanotoxicity mechanisms, including generation of reactive oxygen species, nanoparticle disintegration, modulation of cell signaling pathways, protein corona formation, and poly(ethylene glycol)-mediated immunogenicity. We conclude with a perspective on potential approaches to advance current understanding of nanoparticle toxicity. Such improved understanding may lead to mitigation strategies that could enable safe application of nanoparticles in humans. Advances in nanotoxicity research will ultimately inform efforts to establish standardized regulatory frameworks with the goal of fully exploiting the potential of nanotechnology while minimizing harm to humans. Expected final online publication date for the Annual Review of Pharmacology and Toxicology, Volume 61 is January 8, 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
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