RESUMO
Loss of function of the RNA-binding protein TDP-43 (TDP-LOF) is a hallmark of amyotrophic lateral sclerosis (ALS) and other neurodegenerative disorders. Here we describe TDP-REG, which exploits the specificity of cryptic splicing induced by TDP-LOF to drive protein expression when and where the disease process occurs. The SpliceNouveau algorithm combines deep learning with rational design to generate customizable cryptic splicing events within protein-coding sequences. We demonstrate that expression of TDP-REG reporters is tightly coupled to TDP-LOF in vitro and in vivo. TDP-REG enables genomic prime editing to ablate the UNC13A cryptic donor splice site specifically upon TDP-LOF. Finally, we design TDP-REG vectors encoding a TDP-43/Raver1 fusion protein that rescues key pathological cryptic splicing events, paving the way for the development of precision therapies for TDP43-related disorders.
Assuntos
Esclerose Lateral Amiotrófica , Proteínas de Ligação a DNA , Demência Frontotemporal , Medicina de Precisão , Splicing de RNA , Animais , Humanos , Camundongos , Esclerose Lateral Amiotrófica/genética , Esclerose Lateral Amiotrófica/terapia , Aprendizado Profundo , Proteínas de Ligação a DNA/genética , Proteínas de Ligação a DNA/metabolismo , Demência Frontotemporal/genética , Demência Frontotemporal/terapia , Edição de Genes , Células HEK293 , Sítios de Splice de RNA , Proteínas de Ligação a RNA/metabolismo , Proteínas de Ligação a RNA/genéticaRESUMO
A system enabling the expression of therapeutic proteins specifically in diseased cells would be transformative, providing greatly increased safety and the possibility of pre-emptive treatment. Here we describe "TDP-REG", a precision medicine approach primarily for amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD), which exploits the cryptic splicing events that occur in cells with TDP-43 loss-of-function (TDP-LOF) in order to drive expression specifically in diseased cells. In addition to modifying existing cryptic exons for this purpose, we develop a deep-learning-powered algorithm for generating customisable cryptic splicing events, which can be embedded within virtually any coding sequence. By placing part of a coding sequence within a novel cryptic exon, we tightly couple protein expression to TDP-LOF. Protein expression is activated by TDP-LOF in vitro and in vivo, including TDP-LOF induced by cytoplasmic TDP-43 aggregation. In addition to generating a variety of fluorescent and luminescent reporters, we use this system to perform TDP-LOF-dependent genomic prime editing to ablate the UNC13A cryptic donor splice site. Furthermore, we design a panel of tightly gated, autoregulating vectors encoding a TDP-43/Raver1 fusion protein, which rescue key pathological cryptic splicing events. In summary, we combine deep-learning and rational design to create sophisticated splicing sensors, resulting in a platform that provides far safer therapeutics for neurodegeneration, potentially even enabling preemptive treatment of at-risk individuals.