ETD

Archivio digitale delle tesi discusse presso l'Università di Pisa

Tesi etd-09212014-181203


Tipo di tesi
Tesi di laurea magistrale
Autore
SCIPIONI, LORENZO
URN
etd-09212014-181203
Titolo
Detection and characterization of exosomal biomarkers via noble metal nanoparticles conjugation
Dipartimento
FISICA
Corso di studi
FISICA
Relatori
relatore Prof. Luin, Stefano
Parole chiave
  • metal
  • nanoparticles
  • Exosomes
Data inizio appello
20/10/2014
Consultabilità
Completa
Riassunto
Earlier diagnosis of cancerous conditions allows the use of simpler and more efficient treatment for dealing with the disease. In order to do so, a screening assay should be performed on the biggest possible number of potential patients, therefore it should be easily applicable and predictive.

Abstract In recent years, exosomes have emerged as a potential tool for diagnosing tumoral conditions: exosomes are biological nanoparticles exocytated from their mother cells as intercellular communication vehicles, carrying material from a cell to another. It has been demonstrated that their membrane composition can be used for detecting the presence and type of a tumoral state; furthermore their presence in easily accessible fluids such as blood, plasma and urine makes them a good choice for reaching the goal introduced above.

Abstract The work I carried out during this thesis is part of an ongoing research project at NEST laboratories of Scuola Normale Superiore. The project focuses on the detection and characterization of exosomial biomarkers, and aims at developing a tool for a new tumoral screening assay relying on the specific conjugation of noble metal nanoparticles to exosomes, also exploiting the peculiar optical properties of these nanoparticles.

Abstract The main goal of this thesis work is to implement and optimize protocols for conjugating metal nanoparticles to exosomes via antibodies recognising exosomial membrane proteins, and for investigating the success of the conjugations. As a possible way to determine the biochemical composition of the exosome sample by optical methods, a nanoparticle tracking analysis computer program has been developed, which is also able to specifically discriminate the size distribution of bound and unbound species. The thesis will be structured as follows.

After a brief introduction of the project in which this work is inserted, a theoretical section is presented, which provides the necessary background to understand the techniques and methods used in the following chapters. I will introduce here the main properties of nanoparticles and antibodies, as well as a description of the chemical reactions used in this work.

Then, the instruments and techniques used for characterising and detecting the exosomes, as well as the parameters used for their analyses, will be described: these include the Zetasizer for dynamic light scattering and zeta potential measurements, the UV-vis spectrophotometer, electronic microscopes and confocal microscopes. Moreover, a description of the materials used in this project, from nanoparticles to coating polymers, to antibodies and fluorescent probes, to exosomes, with details on their specifications, will be presented, together with the experimental protocols. The description of the NTA (Nanoparticle Tracking Analysis) algorithm and its implementation for the analyses of the samples will be given.

The discussion proceeds presenting the results of the experiments, from the characterization of the single particles (e.g. exosomes and nanoparticles) to the coating procedure, from the exosome-antibody conjugation to the final nanoparticle-antibody-exosome system, with the presentation of the results compared to control samples. We will show that the successful nanoparticle-exosome conjugation has been achieved and that it can provide a >90% pure nanoparticle-exosome sample. Furthermore, the NTA algorithm has been successful in determining the size of specific nanoparticles (both fluorescent beads used as a test and labeled exosomes) imaged with a confocal microscope. In the end, some conclusions from these results and further optimizations and perspectives that can be implemented in the future will be discussed.
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