prikaz prve stranice dokumenta Usporedba preciznosti robotizirane i manualne metode za analizu glikozilacije proteina
  Download
PDF 4.94 MB
master's thesis
Usporedba preciznosti robotizirane i manualne metode za analizu glikozilacije proteina
Zagreb: University of Zagreb, Faculty of Chemical Engineering and Technology, 2023. urn:nbn:hr:149:409102
Fančović, Matko
University of Zagreb
Faculty of Chemical Engineering and Technology

Institutional repository: Repository of Faculty of Chemical Engineering and Technology University of Zagreb

Cite this document

Fančović, M. (2023). Usporedba preciznosti robotizirane i manualne metode za analizu glikozilacije proteina (Master's thesis). Zagreb: University of Zagreb, Faculty of Chemical Engineering and Technology. Retrieved from https://urn.nsk.hr/urn:nbn:hr:149:409102

Fančović, Matko. "Usporedba preciznosti robotizirane i manualne metode za analizu glikozilacije proteina." Master's thesis, University of Zagreb, Faculty of Chemical Engineering and Technology, 2023. https://urn.nsk.hr/urn:nbn:hr:149:409102

Fančović, Matko. "Usporedba preciznosti robotizirane i manualne metode za analizu glikozilacije proteina." Master's thesis, University of Zagreb, Faculty of Chemical Engineering and Technology, 2023. https://urn.nsk.hr/urn:nbn:hr:149:409102

Fančović, M. (2023). 'Usporedba preciznosti robotizirane i manualne metode za analizu glikozilacije proteina', Master's thesis, University of Zagreb, Faculty of Chemical Engineering and Technology, accessed 04 November 2024, https://urn.nsk.hr/urn:nbn:hr:149:409102

Fančović M. Usporedba preciznosti robotizirane i manualne metode za analizu glikozilacije proteina [Master's thesis]. Zagreb: University of Zagreb, Faculty of Chemical Engineering and Technology; 2023 [cited 2024 November 04] Available at: https://urn.nsk.hr/urn:nbn:hr:149:409102

M. Fančović, "Usporedba preciznosti robotizirane i manualne metode za analizu glikozilacije proteina", Master's thesis, University of Zagreb, Faculty of Chemical Engineering and Technology, Zagreb, 2023. Available at: https://urn.nsk.hr/urn:nbn:hr:149:409102

Metadata
TitleUsporedba preciznosti robotizirane i manualne metode za analizu glikozilacije proteina
Title (english)Comparison of the accuracy of robotic and manual methods for the analysis of protein glycosylation
AuthorMatko Fančović
MentorTomislav Bolanča (mentor)
Committee memberTomislav Bolanča (predsjednik povjerenstva)
Committee memberMatija Cvetnić (član povjerenstva)
Committee memberGordan Lauc (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Chemical Engineering and Technology
Zagreb
Defense date and country2023-07-13, Croatia
Scientific / art field,
discipline and subdiscipline		NATURAL SCIENCES
Chemistry
Abstract
Glikani su lančane strukture sastavljene od velikog broja glikozidno povezanih molekula šećera. Glikozilacija je enzimski kontrolirani proces kovalentnog vezanja glikana na mjesto neglikanskog entiteta (aglikona). Ona igra ključnu ulogu u funkcioniranju organskog sustava u njegovim fiziološkim i patofiziološkim stanjima. Imunoglobulin G (IgG) je glavni serumski glikoprotein koji obnaša ulogu protutijela u imunosnom sustavu. Razvojem univerzalne automatizirane metode pripreme za analizu glikozilacije proteina, uspjeli bi se izbjeći problemi koji nastaju djelovanjem ljudske ruke. U okviru ovog rada razvila se robotizirana metoda pripreme glikana za analizu glikozilacije proteina iz krvi s Guthrijevih kartica, nakon čega se preciznost iste usporedila s već korištenom manualnom metodom. Robotska radna stanica na kojoj je vršen ovaj rad je TECAN EVO 200 unutar kojeg je implementirana samostalna jedinica za pozitivni tlak Reslovex A200. Karakterizacija uzoraka je provedena multipleksnom kapilarnom gel elektroforezom potpomognutom laserski induciranom fluorescencijom. Metoda je uspješno razvijena, a kvantitativnom i kvalitativnom analizom statističkih izračunatih podataka potvrđuje se pouzdanost robotizirane metode pripreme za analizu glikozilacije proteina. Robotizirana i manualna metoda su međusobno usporedne budući da su vrijednosti prosječnih relativnih postotnih površina glikanskih vrhova vrlo slične. Standardne devijacije su nešto veće za robotiziranu metodu, što je bilo i očekivano s obzirom da je u ovom radu ova metoda prvi puta pokrenuta. Daljnjim razvojem metode te implementacijom dodatnih uređaja preciznost će se povećati te će se ova metoda približiti potpunoj automatizaciji.
Abstract (english)
Glycans are chain-like structures composed of a large number of glycosidically linked sugar molecules. Glycosylation is an enzymatically controlled process of covalently attaching glycans to a non-glycan entity (aglycone). It plays a key role in the functioning of the organic system in both physiological and pathophysiological states. Immunoglobulin G (IgG) is the main serum glycoprotein that functions as an antibody in the immune system. By developing a universal automated preparation method for protein glycosylation analysis, the problems caused by human intervention could be avoided. In this study, a robotic method for glycan preparation from blood samples collected on Guthrie cards was developed and its accuracy was compared with the previously used manual method. The robotic workstation used for this study was the TECAN EVO 200, equipped with a self-contained positive pressure Reslovex A200 unit. Sample characterization was performed using mltiplex capillary gel electrophoresis with laserinduced fluorescence detection. The method was successfully developed, and the reliability of the robotic method for protein glycosylation analysis was confirmed through quantitative and qualitative analysis of statistically calculated data. The robotic and manual methods were comparable, as the values of the average relative percentage areas of glycan peaks were very similar. The standard deviations were slightly higher for the robotic method, which was expected since this method was first implemented in this study. Further method development and implementation of additional devices will increase precision and bring this method closer to complete automation.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:149:409102
Study programmeTitle: Chemical Engineering - Graduate study
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka kemijskog inženjerstva (magistar/magistra inženjer/inženjerka kemijskog inženjerstva)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2023-07-27 11:59:01