PhD Scientific Days 2024

Poster Session F - Molecular Medicine 3.

The Use of Compartmentalization Databases in the Logical Modelling of the Epithelial-Mesenchymal Transition

Előadó neve

Mr. Kerestély, Márk

Neptun code

FP0TED

Előadó munkahelye

Department of Molecular Biology, Institute of Biochemistry and Molecular Biology, Semmelweis University, Budapest, Hungary

Előadó telefonszáma

+36305362937

Előadó e-mail címe

kerestely.mark@stud.semmelweis.hu

Az előadás címe

The Use of Compartmentalization Databases in the Logical Modelling of the Epithelial-Mesenchymal Transition

Szerző(k) neve és munkahelye

Márk Kerestély¹, Péter Mendik¹, Sebestyén Kamp², Dávid Deritei^1,3, Nina Kunšič^1,4, István Narozsny¹, Gábor Máthé¹, Péter Csermely¹, Dániel V. Veres^1,2

1: Department of Molecular Biology, Institute of Biochemistry and Molecular Biology, Semmelweis University, Budapest, Hungary
2: Turbine Ltd, Budapest, Hungary.
3: Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, United States of America
4: NIJZ: National Institute of Public Health, Ljubljana, Slovenia

Bemutatás módja

Poszter

Szekció

Poster Session F - Molecular Medicine 3.

Language of the presentation

English

Preferred session

Molecular Medicine

Összefoglaló szövege

Introduction: Intracellular signalling can be computationally modelled on a compartment-level by using compartmentalization databases such as the ComPPI (COMpartmentalized Protein-Protein Interaction) and Translocatome databases. Translocatome contains manually curated and machine learning predicted data on protein-translocation. One relevant use for these databases is the modelling of the epithelial-mesenchymal transition (EMT), which has a central role in the cancer metastasis process and is substantially regulated by protein-translocations.
Aims: Our aim was to utilize ComPPI and Translocatome in the logical modelling of EMT. We also aimed to identify areas of improvement for their use in logical modelling.
Method: We used a Gene Ontology based enrichment analysis to ascertain the relevance of protein-translocation in the signalling of EMT. We conducted a literature review of translocating EMT proteins based on the predictions of Translocatome. Using information on compartmentalized interactions from ComPPI and the literature, we incorporated these protein-translocations into a previously established Boolean model of TGFB mediated EMT. We built our model in the BooleanNet simulation framework.
Results: We found that, in Translocatome, predicted translocating proteins were enriched among EMT proteins (p < 0.0001), while predicted non-translocating proteins were de-enriched among EMT proteins (p < 0.0001). We manually curated 21 translocating proteins relevant to the previously established EMT model, which had 19 nodes and 70 edges. After incorporating the protein-translocations, the updated model reached 31 nodes and 101 edges. 3 out of 5 instances of differing behaviour in the dynamic simulations between the original and the updated model involved an incorporated protein-translocation.
Conclusion: Our work serves as a proof-of-concept for compartmentalized logical modelling of complex intracellular signalling processes utilizing compartmentalization databases. In the future, the adoption of a data format suitable for logical modelling in the databases could enable the algorithmic inference of compartmentalized logical models.
Funding: Supported by the ÚNKP-23-2-I-SE-59 New National Excellence Program of the Ministry for Culture and Innovation from the source of the National Research, Development and Innovation Fund.

University

Semmelweis University

Other university, not listed above

-

Supervisor

Prof. Péter Csermely, Dr. Dániel V. Veres PhD

Publication of my abstract

I give consent to the publication of my abstract on the website of the congress.

Kind

Szabad

Status

elfogadva

Accepted presentation method

poszter

Előadás fájl jóváhagyás

nem rendelkezett róla

Előadó

8257

Start

15:40

End

15:43