Plaques of the amyloid beta (Aβ) peptide are a pathological hallmark of Alzheimer's Disease (AD), the most common form of dementia. Mutations in Aβ also cause familial forms of AD (fAD). Here we use deep mutational scanning to quantify the effects of >14,000 mutations on the aggregation of Aβ. The resulting genetic landscape reveals mechanistic insights into fibril nucleation, including the importance of charge and gatekeeper residues in the disordered region outside of the amyloid core in preventing nucleation. Strikingly, unlike computational predictors and previous measurements, the empirical nucleation scores accurately identify all known dominant fAD mutations in AB42, genetically validating that the mechanism of nucleation in a cell-based assay is likely to be very similar to the mechanism that causes the human disease. These results provide the first comprehensive atlas of how mutations alter the formation of any amyloid fibril and a resource for the interpretation of genetic variation in Aβ.
Raw sequencing data and the processed data table (Supplementary file 3) have been deposited in NCBI's Gene Expression Omnibus (GEO) as record GSE151147. All code used for data analysis is available at https://github.com/BEBlab
The genetic landscape for amyloid beta fibril nucleation accurately discriminates familial Alzheimer's disease mutationsNCBI Gene Expression Omnibus, GSE151147.
- Benedetta Bolognesi
- Ben Lehner
- Ben Lehner
- Ben Lehner
- Mireia Seuma
- Ben Lehner
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
- Patrik Verstreken, KU Leuven, Belgium
© 2021, Seuma et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Brain signal decoding promises significant advances in the development of clinical brain computer interfaces (BCI). In Parkinson’s disease (PD), first bidirectional BCI implants for adaptive deep brain stimulation (DBS) are now available. Brain signal decoding can extend the clinical utility of adaptive DBS but the impact of neural source, computational methods and PD pathophysiology on decoding performance are unknown. This represents an unmet need for the development of future neurotechnology. To address this, we developed an invasive brain-signal decoding approach based on intraoperative sensorimotor electrocorticography (ECoG) and subthalamic LFP to predict grip-force, a representative movement decoding application, in 11 PD patients undergoing DBS. We demonstrate that ECoG is superior to subthalamic LFP for accurate grip-force decoding. Gradient boosted decision trees (XGBOOST) outperformed other model architectures. ECoG based decoding performance negatively correlated with motor impairment, which could be attributed to subthalamic beta bursts in the motor preparation and movement period. This highlights the impact of PD pathophysiology on the neural capacity to encode movement vigor. Finally, we developed a connectomic analysis that could predict grip-force decoding performance of individual ECoG channels across patients by using their connectomic fingerprints. Our study provides a neurophysiological and computational framework for invasive brain signal decoding to aid the development of an individualized precision-medicine approach to intelligent adaptive DBS.
Aneuploidy, a state of chromosome imbalance, is a hallmark of human tumors, but its role in cancer still remains to be fully elucidated. To understand the consequences of whole-chromosome-level aneuploidies on the proteome, we integrated aneuploidy, transcriptomic, and proteomic data from hundreds of The Cancer Genome Atlas/Clinical Proteomic Tumor Analysis Consortium tumor samples. We found a surprisingly large number of expression changes happened on other, non-aneuploid chromosomes. Moreover, we identified an association between those changes and co-complex members of proteins from aneuploid chromosomes. This co-abundance association is tightly regulated for aggregation-prone aneuploid proteins and those involved in a smaller number of complexes. On the other hand, we observed that complexes of the cellular core machinery are under functional selection to maintain their stoichiometric balance in aneuploid tumors. Ultimately, we provide evidence that those compensatory and functional maintenance mechanisms are established through post-translational control, and that the degree of success of a tumor to deal with aneuploidy-induced stoichiometric imbalance impacts the activation of cellular protein degradation programs and patient survival.