Phase separation behavior of TDP-43 governs its protein interactome and regulation of alternative splicing
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Abstract
TDP-43 is a nuclear RNA-binding protein regulating numerous steps in RNA metabolism, including alternative splicing. It is a major pathological hallmark of several neurodegenerative diseases, where it forms cytoplasmic aggregates in affected brain regions. TDP-43 can undergo phase separation (PS) and this condensation behavior may be linked to aggregate formation. Whether and how PS governs TDP-43’s RNA regulatory functions remains poorly understood.
Here we utilized rationally designed mutations in the TDP-43 low complexity domain to tune TDP-43 PS, yielding a panel of TDP-43 variants with reduced propensity to form condensates (“PS-deficient”), and a panel of TDP-43 variants that form more irreversible, undynamic condensates (“solid-like”) in vitro and in cells. Affinity proteomics coupled to mass spectrometry identified a set of interactors whose association with TDP-43 is PS-dependent. This includes multiple splicing regulators and the RNA helicase UPF1, which show increased interactions with solid-like TDP-43 variants. Consistently, we identified PS-dependent alternative splicing events that translate into measurable changes in RNA and protein abundance. Our results highlight that TDP-43 PS regulates RNA and protein homeostasis both directly, by altering a subset of TDP-43-dependent alternative splicing events, and indirectly, by changing interactions with other RNA regulatory factors.
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In contrast, for exon inclusion events, the link between RNA and protein levels is less evident.
This is so interesting and really highlights the importance of assessing both RNA and protein levels, especially in murky contexts like this involving multiple RNA-binding proteins that in turn are regulating the expression of proteins involved in processes like splicing.
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in at least two variants per group
I'm curious how many RNAs were excluded with this step. How many RNAs showed variant-specific shifts, and are there any trends in these clusters that can inform our understanding of the consequences of specific mutations in TDP-43?
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we designed a panel of TDP-43 variants which we predicted to be either condensation-deficient or more condensation-prone.
It's neat that you designed multiple variants predicted to be better or worse at phase separation rather than relying on one in each direction, it makes the datasets so much richer for informing future variant design!
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