Special Poster Session 50th International Society for the Study of the Lumbar Spine Annual Meeting 2024

INTRODUCTION

Intervertebral disc (IVD) degeneration (IDD) involves the imbalance between the anabolic and the catabolic processes that regulate the extracellular matrix of the disc. These processes are complex; and involve many interlinked connections, in-depth characterization of control cells in experimental studies is mainly important, to properly interpret the cell culture designs and the measured responses upon perturbations. Accordingly, we present a novel assessment of control and perturbed cultures of human pulposus cell (NPC) through proteomics analyses and a validated regulatory network model (RNM).

METHODS

A previously developed and validated RNM for NPC activity represented proteins as nodes that interact among each other through activation and inhibition links (Fig.1). Semi-quantitative steady states (SS) of the RNM (node activations) were calculated through fuzzy interpolation of Boolean rules [1]. The model represented the expected activity of both normal and degenerate NPC (Fig.2). It was further evaluated against metabolic events measured in non-healthy human NP explant cultures, after 2 days of perturbation by either 1ng/ml IL-1β or 10ng/ml of IL-4 or IL-10. Proteomics analyses were conducted for 72 proteins, including 6 different panels. Proteomics data were normalized after post-processing and the experimental SS were calculated by using the responses to IL-1β, IL-4 and IL-10. To characterize the basal activity in the control samples, we prescribed the values of the RNM nodes that corresponded to the proteins shared with the proteomics panels (22 proteins), to the normalized values measured for the samples. Then, we simulated the IL-1β perturbation experiment (Fig.3B, yellow bars) and compared it with the theoretical stimulated baseline of the RNM (Fig.2, yellow bars).

RESULTS

The proteins mostly secreted in the control samples, according to proteomics, were MMP2, MMP1, VEGF, CCL2, and TIMP1 (Fig.3A), which was further captured by the control-specific RNM baseline (Fig.3B, blue bars). Simulated perturbation with IL-1β increased the levels of the chemokines CCL and CCL22, the proinflammatory cytokines IL-12A, IL-17A, IL-18, IL-1α, IL-1β, IL-4, IL-6, IL-8, TNF, the degrading enzymes MMP1 and its inhibitor TIMP1, and the growth factor TGF-β (Fig.3B, yellow bars). Furthermore, node activity decreased for the catabolic markers MMP13, MMP2, MMP9, VEGF and the cytokine IL-1RA (Fig.3B, yellow bars). RNM simulations reached 82% of agreement with the proteomics results for the stimulated samples but downregulated IL-1RA, MMP13 and MMP2, that were experimentally upregulated (IL-1RA) or almost unchanged (MMP13, MMP2).

DISCUSSION

The RNM was able to characterize the proteomics analysis of the control samples, which revealed pro-catabolic NPC baseline activity. In the experimental studies, we often assume that the control cells are giving a normal baseline, which was not the case. The corresponding rewiring of cell activity indicated by the control sample baseline (Fig. 3B), compared to the normal one (Fig. 2) might explain unexpected results for the IL-1β stimulated samples, such as decreased VEGF, MMP9, or increased TGF-β (Fig.3C). To sum up, RNM might stand for a useful tool to characterize the expression level of the control values and an interpret perturbed states, in cell culture studies.