Eta-secretase-like processing of the amyloid precursor protein (APP) by the rhomboid protease RHBDL4.

The amyloid precursor protein (APP) is a key protein in Alzheimer's disease synthesized in the endoplasmic reticulum (ER) and translocated to the plasma membrane where it undergoes proteolytic cleavages by several proteases. Conversely, to other known proteases, we previously elucidated rhomboid protease RHBDL4 as a novel APP processing enzyme where several cleavages likely occur already in the ER. Interestingly, the pattern of RHBDL4-derived large APP C-terminal fragments resembles those generated by the η-secretase or MT5-MMP, which was described to generate so-called Aη fragments. The similarity in large APP C-terminal fragments between both proteases raised the question of whether RHBDL4 may contribute to η-secretase activity and Aη-like fragments. Here, we identified two cleavage sites of RHBDL4 in APP by mass spectrometry, which, intriguingly, lie in close proximity to the MT5-MMP cleavage sites. Indeed, we observed that RHBDL4 generates Aη-like fragments in vitro without contributions of α-, ß-, or γ-secretases. Such Aη-like fragments are likely generated in the ER since RHBDL4-derived APP-C-terminal fragments do not reach the cell surface. Inherited, familial APP mutations appear to not affect this processing pathway. In RHBDL4 knockout mice, we observed increased cerebral full-length APP in comparison to wild type (WT) in support of RHBDL4 being a physiologically relevant protease for APP. Furthermore, we found secreted Aη fragments in dissociated mixed cortical cultures from WT mice, however significantly fewer Aη fragments in RHBDL4 knockout cultures. Our data underscores that RHBDL4 contributes to the η-secretease-like processing of APP and that RHBDL4 is a physiologically relevant protease for APP.

An approach to measuring protein turnover in human induced pluripotent stem cell organoids by mass spectrometry.

Patient-derived organoids from induced pluripotent stem cells have emerged as a model for studying human diseases beyond conventional two-dimensional (2D) cell culture. Briefly, these three-dimensional organoids are highly complex, capable of self-organizing, recapitulate cellular architecture, and have the potential to model diseases in complex organs, such as the brain. For example, the hallmark of Parkinson's disease (PD) - proteostatic dysfunction leading to the selective death of neurons in the substantia nigra - present a subtle distinction in cell type specificity that is lost in 2D cell culture models. As such, the development of robust methods to study global proteostasis and protein turnover in organoids will remain essential as organoid models evolve. To solve this problem, we have designed a workflow to reproducibly extract proteins from brain organoids, measure global turnover using mass spectrometry, and statistically investigate turnover differences between genotypes. We also provide robust methodology for data filtering and statistical treatment of turnover data. Using human midbrain organoids (hMO) as a model system, our method accurately characterized the half-lives of 773 midbrain proteins. We compared these half-lives both to Parkin knockout hMOs and to previously reported data from primary cell cultures and in vivo models. Overall, this method will facilitate the study of proteostasis in organoid models of human disease and will provide an analytical and statistical framework to measure protein turnover in organoids of all cell types.