Development of a fluorescent-based single liposome assay for studying calcium transporter LMCA1

The morphological and functional unit of all the living organisms is the cell. The transmembrane proteins, localized in the plasma membrane of cells, play a key role in the survival of the cells themselves. These proteins perform a variety of different tasks, for example the control of the homeostasis. In order to control the homeostasis, these proteins have to regulate the concentration of chemical elements, like ions, inside and outside the cell. These regulations are fundamental for the survival of the cell and to understand them we need to understand how transmembrane proteins work. Two of the most important categories of transmembrane proteins are ion channels and transporter proteins. The ion channels have been depth studied at the single molecule level since late 1970s with the development of patch-clamp technique. It is not possible to apply this technique to study the transporter proteins so a new technique is under development in order to investigate the behavior of transporter proteins at the single molecule level. This thesis describes the development of a nanoscale single liposome assay for functional studies of transporter proteins based on quantitative fluorescence microscopy in a highly-parallel manner and in real time. The transporter of interest is the prokaryotic transporter Listeria Monocytogenes Ca2+-ATPase1 (LMCA1), a structural analogue of the eukaryotic calcium pumps SERCA and PMCA. This technique will allow the characterization of LMCA1 functionality at the single molecule level. Three systematically characterized fluorescent sensors were tested at the single liposome scale in order to investigate if their properties are suitable to study the function of the transporter of interest. Further studies will be needed in order to characterize the selected calcium sensor and pH sensor both implemented together in single liposomes and in presence of the reconstituted protein LMCA1.

Image Analysis Methods for Sugar Beet Phenotyping

In un mondo che richiede sempre maggiormente un'automazione delle attività della catena produttiva industriale, la computer vision rappresenta uno strumento fondamentale perciò che viene già riconosciuta internazionalmente come la Quarta Rivoluzione Industriale o Industry 4.0. Avvalendomi di questo strumento ho intrapreso presso l'azienda Syngenta lo studio della problematica della conta automatica del numero di foglie di una pianta. Il problema è stato affrontato utilizzando due differenti approcci, ispirandosi alla letteratura. All'interno dell'elaborato è presente anche la descrizione progettuale di un ulteriore metodo, ad oggi non presente in letteratura. Le metodologie saranno spiegate in dettaglio ed i risultati ottenuti saranno confrontati utilizzando i primi due approcci. Nel capitolo finale si trarranno le conclusioni sulle basi dei risultati ottenuti e dall'analisi degli stessi.