A Semi-Automated Antibody-Discovery Platform to Target Challenging Biomolecules

A major bottleneck in biomedical research is the scarcity of tools to study disease mechanisms directly in their 'true' biological environments, such as in living being, in an accurate manner. A remarkable example of the implications of this technology gap is given by our current understanding of dementia. Dementia is an umbrella term referring to a set of incurable diseases, including Alzheimer's, Parkinson's, and frontotemporal dementia. Altogether, these pathologies currently affect more than 50 million people worldwide. Despite this prevalence of dementia, we still lack effective diagnostic and therapeutic molecules for it because of the sparse information on the pathological mechanisms. A major mechanism of dementia is the formation of protein clusters in the nervous system, which are associated with cellular death. Over the last two decades, researchers have focused on understanding protein clustering under highly controlled experimental conditions using proteins in isolation (in vitro approaches). These accurate studies have contributed to the understanding of the physical laws that regulate protein clustering; nevertheless, they have also provided an overly simplistic picture of the clustering mechanism. They did not account for the many events in the nervous system, as proven by the fact that protein clusters isolated from patients are heavily chemically modified and tightly associated with other biomolecules, including nucleic acids.

Because of their specific binding to targets, antibodies represent a fast-growing class of protein drugs and find a wide application as probes in biomedical research. Antibodies allow scientists to bridge highly precise in vitro measurements with the use of highly complex biological samples. Nevertheless, despite their potential, the use of antibodies is still hindered by challenges associated with their production. Antibody discovery can be a lengthy and costly procedure. Furthermore, several biomolecules, such as chemically modified proteins, protein clusters, and nucleic acids, are challenging to target with standard antibody-discovery approaches, despite these biomolecules being highly prevalent in diseases, e.g., dementia. The goal of this project is to deliver an innovative, generally applicable antibody-discovery technology able to target protein clusters which are chemically modified or in complex with other biomolecules, such as nucleic acids. To achieve our goal, we will work on two systems, the protein FUS and the transactive response DNA-binding protein 43 (TDP-43), involved in amyotrophic lateral sclerosis, frontotemporal dementia and Alzheimer's disease. Both proteins have been reported to undergo several types of chemical modifications and to bind to different RNA molecules. We will develop antibodies using our integrative discovery platform with the addition of a semi-automated screening component to target clusters of the proteins of interest carrying chemical modifications and/or in complex with RNAs associated with the disease. Thus, we will use the antibodies to monitor the distribution of the protein-RNA aggregates in human tissue. Our results will provide novel information on these diseases and lead to a generally applicable time- and cost-effective antibody-discovery technology to produce antibodies against biomolecules beyond proteins.