Background: Local protein synthesis and mRNA metabolism mediated by mRNP granules in the dendrites and the postsynaptic compartment is essential for synaptic remodeling and plasticity in neuronal cells. Dysregulation of these processes caused by TDP-43 proteinopathy leads to neurodegenerative diseases, such as frontotemporal lobar degeneration and amyotrophic lateral sclerosis. Methods: Using biochemical analysis and imaging techniques, including super-resolution microscopy, we provide evidence, for the first time, for the postsynaptic localization of TDP-43 in mammalian synapses and we show that TDP-43 is a component of neuronal mRNP granules. Results: With activity stimulation and various molecular approaches, we further demonstrate activity-dependent mRNP granule dynamics involving disassembly of mRNP granules, release of mRNAs, activation of local protein translation, and the impairment of granule disassembly in cellular, animal and human models of TDP-43 proteinopathy. Conclusion: Our study elucidates the interplay between TDP-43 and neuronal mRNP granules in normal physiology and TDP-43 proteinopathy in the regulation of local protein translation and mRNA metabolism in the postsynaptic compartment.

TAR DNA binding protein-43 (TDP-43) proteinopathies are accompanied by the pathological hallmark of cytoplasmic inclusions in the neurodegenerative diseases, including frontal temporal lobar degeneration (FTLD-TDP) and amyotrophic lateral sclerosis (ALS). We found that TTR accumulates with TDP-43 cytoplasmic inclusions in FTLD-TDP human patients and transgenic mice, in which TTR exhibits dramatic expression decline in elderly mice. The upregulation of TTR expression was demonstrated to facilitate the clearance of cytoplasmic TDP-43 inclusions through autophagy, whereof TTR induces autophagy upregulation via ATF4. Of interest, TTR upregulated ATF4 expression and promoted ATF4 nuclear import, presenting physical interaction. Neuronal expression of TTR in FTLD-TDP mice restored autophagy function and facilitated early soluble TDP-43 aggregates for autophagosome targeting, ameliorating neuropathology and behavioral deficits. Thus, TTR conducted two-way regulations by either inducing autophagy activation or escorting TDP-43 aggregates targeted autophagosomes, suggesting that TTR is a potential modulator therapy for neurological disorders caused by TDP-43 proteinopathy.

To overcome the diffraction limit and resolve target structures in greater detail, far-field super-resolution techniques such as stochastic optical reconstruction microscopy (STORM) have been developed, and different STORM algorithms have been developed to deal with the various problems that arise. In particular, the effect of the local structure is an important issue. For objects with closely correlated distributions, simple Gaussian-based localization algorithms often used in STORM imaging misinterpret overlapping point spread functions (PSFs) as one, which limits the ability of super-resolution imaging to resolve nanoscale local structures and leads to inaccurate length measurements. The STORM super-resolution images of biological specimens from the cluster-forming proteins in the nervous system were reconstructed for localization-based analysis. Generally, the localization of each fluorophore was determined by two-dimensional Gaussian function fitting. Further, the physical shape of the cluster structure information was incorporated into the size parameter of the localization structure analysis in order to generate structure-based fitting algorithms. In the present study, we proposed a novel, structure-based, super-resolution image analysis method: structure-based analysis (SBA), which combines a structural function and a super-resolution localization algorithm. Using SBA, we estimated the size of fluorescent beads, inclusion proteins, and subtle synaptic structures in both wide-field and STORM images. The results show that SBA has a comparable and often superior performance to the commonly used full width at half maximum (FWHM) parameter. We demonstrated that SBA is able to estimate molecular cluster sizes in far-field super-resolution STORM images, and that SBA was comparable and often superior to FWHM. We also certified that SBA provides size estimations that corroborate previously published electron microscopy data.

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