ABM CDT Spatial proteomic profiling of native human meniscus and bioprinted meniscal tissue analogues

Meniscus injuries represent a significant long-term health problem, but current treatments offer relatively poor outcomes and novel interventions are required. We are currently working to engineer biomimetic human meniscal tissue analogues using 3D bioprinting and aim to use these to study the mechanisms driving healthy tissue formation and, ultimately, as clinical implants.

The meniscus displays regional differences in cell and tissue composition, but there is currently a lack of detailed understanding of this native composition which impacts on strategies to engineer biomimetic meniscal tissue. Hence the aims of this internationally-leading project are to: (1) employ multiomic (lipidome, metabolome and proteome) spatial profiling to investigate regional differences in human meniscal cells/tissue and understand how this is impacted by injury; (2) develop methodologies to analyse the spatial multiomic profile of engineering meniscus analogues and the profiles to that of native tissue; and (3) investigate how variation in cell and bioink composition influences expression and regional deposition of extracellular matrix within bioprinted constructs. During this inter-disciplinary project, the student will work closely with relevant academic, clinical and commercial experts who will offer training in a range of state-of-the-art techniques, including spatial multiomic profiling, bioinformatic data analysis, bioprinting and stem cell culture. 

Background:

Over 1.5 million people across the USA and Europe suffer from injuries to the knee meniscus which can significantly reduce their mobility and quality of life. The most common treatment for this type of lesion encompasses the partial or total surgical removal of the affected tissue (meniscectomy). Whilst this procedure is able to provide short term pain relief and restore temporary knee function, the biomechanical instability caused by the loss of tissue becomes irreversible and frequently results in osteoarthritis. We are currently developing protocols to engineer biomimetic human meniscal tissue analogues using 3D bioprinting of human cells. These engineered meniscus analogues have potential both to enable investigation into mechanisms driving healthy tissue formation and, ultimately, as clinical implants to restore knee function.

The meniscus is a biphasic tissue, comprising an inner, avascular cartilaginous zone and an outer, vascularised fibrocartilaginous zone. However, there is currently a lack of detailed understanding of the matrix composition and cell phenotype within each of these zones which impacts on strategies to engineer biomimetic meniscal tissue. This project will employ multiomic spatial imaging (lipidomics, metabolomics and proteomics) to map regional differences in native healthy and injured human meniscal cells/tissue. Novel methodology will also be developed to perform equivalent multiomic spatial imaging on bioprinted meniscus tissue analogues in order to compare native and engineered tissues. This knowledge will help establish how closely engineered meniscus tissues mimic native tissues to aid translation of meniscus repair/regeneration therapies.

Questions to be answered:

This project will utilise existing expertise in meniscus bioprinting and -omics technologies to develop a new platform to spatially map the multiomic profile of native and bioengineered meniscus tissue. The student will the assess how variations in bioprinting parameters influence the multiomic profile of engineered meniscus analogues. As such, the project will focus on the following primary questions:

1. How does the multiomic profile (lipidome, metabolome and proteome) of native human meniscus tissue vary spatially and during health and injury/disease?
2. How does the spatial multiomic profile of bioengineered meniscus tissue compare to that of native meniscus?
3. How does variation in cell and bioink composition influence expression and regional deposition of extracellular matrix within bioprinted constructs?