Česká společnost pro hmotnostní spektrometrii

(Česká konference hmotnostní spektrometrie 2024 - Pl-01)
Metabolomics, the Panome and AI-Based Metabolic Modelling – applications in Immunometabolism, Cancer and Natural Product Treatment

Wolfram Weckwerth ^1 *

1. University of Vienna, Austria

Abstrakt

The integration of metabolomics with AI-based metabolic modeling offers a powerful approach to understanding complex biological systems. This study builds on the application of metabolomics, proteomics and RNAseq in conjunction of AI-based metabolic modelling on macrophage metabolism, highlighting the role of mTOR signaling in various biological contexts. Recently, the Weckwerth lab demonstrated that PHGDH acts as a metabolic checkpoint regulated by mTORC1, influencing macrophage function and proliferation [1]. Based on this study PHGDH was proposed to be a metabolic checkpoint in tumor-associated macrophages (TAM). This could be confirmed in a follow-up study by deleting the PHGDH in a mouse model thereby reversing the immunosuppressive phenotype of TAMs through α-ketoglutarate and mTORC1 signaling and leading to reduced solid tumor growth [2]. Additionally, studies on natural products, such as hesperetin and norbergenin, reveal their potential to modulate mTORC1 signaling, mitophagy and apoptosis, thereby offering protective effects against inflammatory responses and lipotoxicity in NAFLD [3,4]. By leveraging high-throughput metabolomic and proteomic data and sophisticated AI algorithms, we aim to elucidate the metabolic pathways involved in immune responses, cancer progression, and the effects of natural product treatments. Our findings underscore the power of combining metabolomics and AI to uncover critical metabolic alterations and identify potential biomarkers for disease diagnosis and treatment efficacy. This interdisciplinary approach holds significant promise for advancing precision and natural medicine.

* Korespondující autor: wolfram.weckwerth@univie.ac.at

Literatura

1. Wilson, J. L., Nägele, T., Linke, M., Demel, F., Fritsch, S. D., Mayr, H. K., Cai, Z., Katholnig, K., Sun, X. & Fragner, L. Inverse data-driven modeling and multiomics analysis reveals phgdh as a metabolic checkpoint of macrophage polarization and pro
2. Cai, Z., Li, W., Hager, S., Wilson, J. L., Afjehi-Sadat, L., Heiss, E. H., Weichhart, T., Heffeter, P. & Weckwerth, W. Targeting PHGDH reverses the immunosuppressive phenotype of tumor-associated macrophages through alpha-ketoglutarate and mTORC1 sign
3. Li, W., Cai, Z., Schindler, F., Bahiraii, S., Brenner, M., Heiss, E. H. & Weckwerth, W. Norbergenin prevents LPS-induced inflammatory responses in macrophages through inhibiting NFkappaB, MAPK and STAT3 activation and blocking metabolic reprogramming.