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Tesi etd-09242023-171621


Tipo di tesi
Tesi di laurea magistrale
Autore
GRAVILI, IRENE
URN
etd-09242023-171621
Titolo
A proteomic analysis of metformin effects: dependence on sex, age and tissue
Dipartimento
BIOLOGIA
Corso di studi
BIOTECNOLOGIE MOLECOLARI
Relatori
relatore Prof. Cellerino, Alessandro
relatore Prof. Pè, Mario Enrico
Parole chiave
  • proteomic
  • metformin
  • aging
  • Nothobranchius furzeri
Data inizio appello
24/10/2023
Consultabilità
Non consultabile
Data di rilascio
24/10/2093
Riassunto
Metformin is a synthetic biguanide and the first-line oral anti-hyperglycemic treatment in patients affected by type 2 diabetes mellitus (T2DM). Metformin has recently been found to extend lifespan in nematode worms but its effect on mouse lifespan is debated. In humans, metformin treatment in diabetic patients causes an increase in overall survival compared to healthy controls. These pieces of evidence have drawn attention to metformin as a potential anti-aging drug. However, little is known about the molecular responses to metformin and the effects of age, sex, dose, and duration of treatment.
This analysis investigates metformin mechanisms of action in the vertebrate model organism Nothobranchius furzeri in the brain and liver tissues. N. furzeri is the shortest-lived fish that can be cultured in captivity and is the model of choice for pharmacological interventions in the context of aging. To probe metformin's beneficial role during aging systematic proteomics analysis was conducted. Proteomic data were obtained from young and old individuals treated with different concentrations of metformin administered via water in static tanks. Short-term and long-term exposures were given to cohorts of both young and old individuals from both sexes.
The first step in proteomics data analysis was Exploratory Data Analysis to understand the relationship between the different samples. Secondly, Spearman´s rank correlation test was used to correlate protein expression with metformin doses. The third step was to perform Fisher's meta-analysis to unveil patterns of differential expression in proteins and the most regulated pathways in cells triggered by metformin exposure. Finally, Weighted Gene Co-expression Network analysis was conducted to identify clusters of highly co-regulated proteins and their correlation with the external conditions.
This analysis revealed that the global response to metformin strongly depends on external factors. On a cellular level, this analysis implies that metformin may play a role in alleviating cotranslational and proteostasis dysfunction during the aging process.
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