Use of solid-state NMR and MD simulations for the study of tissue engineering scaffolds

Abstract

The behaviour and fate of stem cells is governed by the material properties of their surrounding microenvironment. Hence emulating the extracellular matrix poses as an attractive target for tissue engineering endeavours to create a stem cell substrate. Currently, the knowledge of the material properties is mostly limited to the macroscopic level which considerably limits the understanding of tissue engineering scaffolds. Here, we present solid-state NMR as a method capable of inspection of the innate properties of tissue engineering scaffolds at atomic level, physiological-like conditions and at natural isotope abundance. By using a high-resolution method, we uncover how material properties such as the assembly mechanics and scaffold dispersity modulate the viability of human neural stem cells. By combining solid-state NMR with restrained molecular dynamics simulations we derive the supramolecular organisation of the most promising material. This study shows that our method presents a compelling approach to advance the research of nanomaterials useful in regenerative medicine.

Popular Abstract

From self-assembly to regeneration

The ability of stem cells to develop into many different cell types offers unique potential to regenerate damaged tissues. In order to unlock this potential, it is necessary to provide stem cells with an ideal environment resembling the natural extracellular matrix. This matrix forms an intricate 3D construction that provides mechanical support to cells like scaffold does to a building that is being repaired.

In our study, we have explored mechanisms of peptides (short proteins) that have the ability to self-assemble into fibers and form a supportive matrix. First, we looked into the mechanics using solid-state nuclear magnetic resonance (NMR) spectroscopy, which enables the study of stem cell matrices at the atomic-scale and close-to-physiological conditions. In this method, usually the substances have to be enriched with isotopes in order to detect NMR signals. In our study, we were able to detect a signal without any labelling which substantially decreases the costs and promises wide applicability of our method.

We have measured a series of hydrogels, composed of peptides which were derived from a functional motif called ‘Bone Marrow Homing Peptide 1’, which had previously shown a stimulant effect on human neural stem cells, increasing their health and differentiation. We compared the obtained NMR spectra with functional studies to understand why some peptides work better than the others. We saw that peptide B24 performed best in stem cell viability assays and when studied with rheology it behaved like an elastic solid. The NMR results were in line with these observations, demonstrating that hydrogel B24 is rigidly assembled and exhibits only one conformation.

Study with molecular dynamics simulations
From the obtained chemical shifts, we could derive restraints for molecular dynamics (MD) simulation to combine experimental data in computer simulations. In this way, we can get additional information about scaffold formation and features important for this mechanism. Molecular dynamics have their defined mechanics that describe interactions between atoms to simulate the reality of such interactions. We have placed 100 B24 peptide molecules into a virtual box (blue cube in the figure) and simulated the motions and interactions of this system.

We have observed a formation of a strand-like object in 1 µ second that resembles a scaffold capable of providing an environment for stem cell growth. Analyses of the acquired data showed that N-terminal biotin tag and phenylalanine 5 are important for the forming of such strand and residues on the C-terminus work as a functional group, stimulating the cells.

Master’s Degree Project in Bioinformatics 60 credits 2018
Department of Biology, Lund University

Advisor: Markus Weingarth
Bijvoet centre, Utrecht University, Department of Chemistry

• author: Prachař, Marek
• supervisor: Markus Weingarth
• organization: Degree Projects in Bioinformatics
• course: BINP52 20172
• year: 2018
• type: H2 - Master's Degree (Two Years)
• subject: Biology and Life Sciences
• language: English
• id: 8965395
• date added to LUP: 2019-01-08 14:26:30
• date last changed: 2019-01-08 14:26:30