Initiation of intervertebral disc degeneration is thought to be biologically driven. This reflects
a process, where biochemical and mechanical stimuli affect cell activity (CA) that
compromise the tissue strength over time. Experimental research enhanced our
understanding about the effect of such stimuli on different CA, such as protein
synthesis or mRNA expression. However, it is still unclear how cells respond to their
native environment that consists of a “cocktail” of different stimuli that ...
Initiation of intervertebral disc degeneration is thought to be biologically driven. This reflects
a process, where biochemical and mechanical stimuli affect cell activity (CA) that
compromise the tissue strength over time. Experimental research enhanced our
understanding about the effect of such stimuli on different CA, such as protein
synthesis or mRNA expression. However, it is still unclear how cells respond to their
native environment that consists of a “cocktail” of different stimuli that might locally vary.
This work presents an interdisciplinary approach of experimental and in silico research to
approximate Nucleus Pulposus CA within multifactorial biochemical environments.
Thereby, the biochemical key stimuli glucose, pH, and the proinflammatory cytokines
TNF-α and IL1β were considered that were experimentally shown to critically affect CA. To
this end, a Nucleus Pulposus multicellular system was modelled. It integrated experimental
findings from in vitro studies of human or bovine Nucleus Pulposus cells, to relate the
individual effects of targeted stimuli to alterations in CA. Unknown stimulus-CA
relationships were obtained through own experimental 3D cultures of bovine Nucleus
Pulposus cells in alginate beads. Translation of experimental findings into suitable
parameters for network modelling approaches was achieved thanks to a new
numerical approach to estimate the individual sensitivity of a CA to each stimulus type.
Hence, the effect of each stimulus type on a specific CA was assessed and integrated to
approximate a multifactorial stimulus environment. Tackled CA were the mRNA
expressions of Aggrecan, Collagen types I & II, MMP3, and ADAMTS4. CA was
assessed for four different proinflammatory cell states; non-inflamed and inflamed for
IL1β, TNF-α or both IL1β&TNF-α. Inflamed cell clusters were eventually predicted in a multicellular 3D agent-based model. Experimental results showed that glucose had no
significant impact on proinflammatory cytokine or ADAMTS4 mRNA expression, whereas
TNF-α caused a significant catabolic shift in most explored CA. In silico results showed that
the presented methodology to estimate the sensitivity of a CA to a stimulus type
importantly improved qualitative model predictions. However, more stimuli and/or
further experimental knowledge need to be integrated, especially regarding predictions
about the possible progression of inflammatory environments under adverse nutritional
conditions. Tackling the multicellular level is a new and promising approach to estimate
manifold responses of intervertebral disc cells. Such a top-down high-level network
modelling approach allows to obtain information about relevant stimulus environments
for a specific CA and could be shown to be suitable to tackle complex biological systems,
including different proinflammatory cell states. The development of this methodology
required a close interaction with experimental research. Thereby, specific experimental
needs were derived from systematic in silico approaches and obtained results were
directly used to enhance model predictions, which reflects a novelty in this research field.
Eventually, the presented methodology provides modelling solutions suitable for multiscale
approaches to contribute to a better understanding about dynamics over multiple spatial
scales. Future work should focus on an amplification of the stimulus environment by
integrating more key relevant stimuli, such as mechanical loading parameters, in order to
better approximate native physiological environments.
+