Nucleus pulposus cell network modelling in the intervertebral disc.

IF 3.5 2区生物学 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY NPJ Systems Biology and Applications Pub Date : 2025-01-31 DOI:10.1038/s41540-024-00479-6

Sofia Tseranidou, Maria Segarra-Queralt, Francis Kiptengwer Chemorion, Christine Lyn Le Maitre, Janet Piñero, Jérôme Noailly

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Abstract

Intervertebral disc degeneration (IDD) results from an imbalance between anabolic and catabolic processes in the extracellular matrix (ECM). Due to complex biochemical interactions, a comprehensive understanding is needed. This study presents a regulatory network model (RNM) for nucleus pulposus cells (NPC), representing normal intervertebral disc (IVD) conditions. The RNM includes 33 proteins, and 153 interactions based on literature, incorporating key NPC regulatory mechanisms. A semi-quantitative approach calculates the basal steady state, accurately reflecting normal NPC activity. Model validation through published studies replicated pro-catabolic and pro-anabolic shifts, emphasizing the roles of transforming growth factor beta (TGF-β) and interleukin-1 receptor antagonist (IL-1Ra) in ECM regulation. This IVD RNM is a valuable tool for predicting IDD progression, offering insights into ECM degradation mechanisms and guiding experimental research on IVD health and degeneration.

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来源期刊

NPJ Systems Biology and Applications Mathematics-Applied Mathematics

CiteScore

5.80

自引率

0.00%

发文量

审稿时长

8 weeks

期刊介绍： npj Systems Biology and Applications is an online Open Access journal dedicated to publishing the premier research that takes a systems-oriented approach. The journal aims to provide a forum for the presentation of articles that help define this nascent field, as well as those that apply the advances to wider fields. We encourage studies that integrate, or aid the integration of, data, analyses and insight from molecules to organisms and broader systems. Important areas of interest include not only fundamental biological systems and drug discovery, but also applications to health, medical practice and implementation, big data, biotechnology, food science, human behaviour, broader biological systems and industrial applications of systems biology. We encourage all approaches, including network biology, application of control theory to biological systems, computational modelling and analysis, comprehensive and/or high-content measurements, theoretical, analytical and computational studies of system-level properties of biological systems and computational/software/data platforms enabling such studies.