Detection of Cancer Exosomes By a Localized Surface Plasmon Resonance Method Using Gold Nano-Islands
Notice bibliographique
Résumé
Introduction Noble metals have a most important property, the Localized Surface Plasmon Resonance (LSPR) that can be tuned by changing the size and shape of the nanoparticles. This property is useful to perform any real-time label-free monitoring of biomolecular interactions, by measuring the shift of the Plasmon band towards longer wavelengths due to the change in the local refractive index upon molecule binding [1, 2]. Exosomes are nano-sized particles (30-100 nm) released to the extracellular space by all cells in large numbers, prospective biomarkers for early-stage cancer diagnosis [3-5]. The aim of the present study is the detection and capture of exosomes, by using (1) a synthetic peptide and (2) antibodies specific to the surface proteins of exosomes. In both approaches, the biomolecules are immobilized on gold (Au) nano-islands. The first approach makes use of a synthetic polypeptide Vn96 (Venceremin) that has a high affinity towards the heat shock proteins present on the surface of exosomes. The second approach is based on the antibodies (CD63, CD81 and CD9) that are specific to the proteins present on the surface of exosomes. Method The gold nano-islands are fabricated by the thermal convection of ex-situ synthesized gold nanoparticles, followed by the heat treatment of substrates at 560oC to tune the size and shape of the particles. Au nano-islands are initially functionalized by 11-mercaptoundecanoic acid (Nanothink) to form a self-assembled monolayer. This layer is activated, using a cross-linker, which is a mixture of N-(3-dimethylaminopropyl)-N′-ethylcarbodiimide hydrochloride (EDC) and N-Hydroxysuccinimide (NHS) in the ratio of 1:1. The activated layer is coated with streptavidin to bind, biotinylated Vn96 peptide to capture exosomes whereas, in the antibody-based approach, streptavidin-biotin step is replaced with the antibodies. To the immobilized molecules of polypeptide/antibody (anti-CD63/81), MCF7 (breast cancer cell line) cell culture conditioned media, containing EVs/exosomes is added. At each successive functionalization and immobilization step, the position of the Au plasmon band in the UV-Visible spectrum is measured and the corresponding shift is calculated. Results The preliminary results obtained by using the two protocols indicate that both approaches have the capability to detect and capture the exosomes for cancer diagnosis. The wavelength shift observed in the antibody-based approach, is relatively higher, compared to the one observed when Vn96 was used to capture the exosomes. By using specifically, the anti-CD63 antibody, there is at least an appreciable increase in the wavelength shift, compared to Vn96 polypeptide. In addition, the sensing protocol can be simplified and the detection can be carried out in a shorter time. Conclusions The quantification of exosomes has been performed by using two different LSPR methods. One approach uses the Vn96 peptide for the capture of exosomes, while the other, makes use of the antibodies corresponding to surface proteins. Both methods provided reliable results. However, the method using antibodies results in a larger shift of the Plasmon band showing a stronger interaction and the method can be carried out in a shorter time. References Nath and A. Chilkoti, “Label-free biosensing by surface plasmon resonance of nanoparticles on glass: optimization of nanoparticle size," Anal. Chem., vol. 76, pp. 5370-5378, 2004 Nath and A. Chilkoti, “Label free colorimetric biosensing using nanoparticles,” J. Fluoresc., vol. 14, pp. 377-389, 2004. María Yáñez-Mó, Pia R.-M. Siljander, Zoraida Andreu, Apolonija Bedina Zavec, Francesc E. Borràs, et al., “Biological properties of extracellular vesicles and their physiological functions,” Journal of Extracellular Vesicles, vol.4: 27066, 2015. Gregor Fuhrmann, Inge K. Herrmann, and Molly M. Stevensa, “Cell-derived vesicles for drug therapy and diagnostics: Opportunities and challenges,” Nano Today, vol.10, pp.397—409, 2015. Bathini, D. Raju, S. Badilescu, et al., “Nano–Bio Interactions of Extracellular Vesicles with Gold Nanoislands for Early Cancer Diagnosis,” Research, vol. 2018, Article ID 3917986, 10 pages, 2018.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».