Third party funded individual grant
Start date : 01.01.2019
End date : 31.12.2020
Modern Life Sciences in research and education have become crucially dependent on advanced biomedical technologies to increase throughput, content or to facilitate previously strenuous work steps. Good examples are genomics facilities, lab-on-a-chip systems or semi-automated gel electrophoresis systems. In higher university education, there are still many lab techniques that are passed on from technicians to generations of students, a fact that becomes more and more critical in times of budget threats to technical staff. One way to implement solutions for graduate and PhD student training, but also new staff and interested students during their education, is through virtual skills and training laboratories (vLabs), where bioprocesses from the lab are deposited in learning goal modules that provide circumscribed tasks, on-site analysis and personalized feedback. In particular, for education systems with staff shortage or shortage of high-end and expensive technologies available on site, virtual learning provides a valuable solution also in terms of lab resources and repeatability.
Biomechanics of living cells and tissue samples is one of the most difficult experimental parameters to assess, and has long required manual manipulation of single cells, e.g. muscle fibres or small fibre bundles, with force transducers and manual actuator systems. The German applicant and his team have engineered the MyoRobot, a fully automated biomechatronics system suitable for the high-content assessment of skeletal muscle tissue and linear biopolymer biomechanics. It introduces objective automated experimental execution, thus minimizing human error and data file confusion (Haug et al. 2018 Biosens Bioelectron). Still, that unique system is not generally available and requires intensive hand-to-hand training. Also, biomechanics in life science study course education still relies on old manual and inaccurate systems. Thus, a virtual skills lab environment including the MyoRobot technology (German team) in conjunction with a firm research question on skeletal muscle biomechanics in a pre-diabetic disease model (Australian team) would represent a unique learning tool in biomedical research and education that could be implemented worldwide on a web-based platform.
To bring together these two innovative concepts, the goals of this project are:
1) To apply MyoRobot biomechatronics technology to skeletal muscle single fibres of pre-diabetic ABCA1/ABCG1 (cholesterol efflux regulatory protein, aka CERP) mice that present with a phenotype of elevated pancreatic ß-cell cholesterol levels (ß-DKO), impaired insulin secretion, reduced plasma insulin, increased body fat and reduced skeletal muscle mass, to clarify biomechanical mechanisms explaining a pre-diabetic myopathy on the cellular level.
2) To assess active (Ca2+-activated force, pCa-force relationships) and passive (resting length-tension curves, viscoelastic behavior) biomechanics parameters in ß-DKO animals, wt littermates, animals receiving subcutaneous insulin pump treatment and animals following treadmill exercise for 28 d with/without insulin pump treatment. Gender-specific differences will be accounted for.
To video-tape all sequences from animal handling, dissection of muscles, single muscle fibre preparations and MyoRobot control for different protocols (solution pipetting, setting software environments, data recording selection, execution and analysis) to build a sequential vLab environment using video footage coupled with simulations and personalized adaptive feedback tailored for student and research staff training in advanced biomechanics skills.