BAG6 prevents the aggregation of neurodegeneration-associated fragments of TDP43

Proteostasis in neurodegenerative diseases

Proteostasis is essential for normal function of proteins and vital for cellular health and survival. Proteostasis encompasses all stages in the "life" of a protein, that is, from translation to functional performance and, ultimately, to degradation. Proteins need native conformations for function and in the presence of multiple types of stress, their misfolding and aggregation can occur. A coordinated network of proteins is at the core of proteostasis in cells. Among these, chaperones are required for maintaining the integrity of protein conformations by preventing misfolding and aggregation and guide those with abnormal conformation to degradation. The ubiquitin-proteasome system (UPS) and autophagy are major cellular pathways for degrading proteins. Although failure or decreased functioning of components of this network can lead to proteotoxicity and disease, like neuron degenerative diseases, underlying factors are not completely understood. Accumulating misfolded and aggregated proteins are considered major pathomechanisms of neurodegeneration. In this chapter, we have described the components of three major branches required for proteostasis-chaperones, UPS and autophagy, the mechanistic basis of their function, and their potential for protection against various neurodegenerative conditions, like Alzheimer's, Parkinson's, and Huntington's disease. The modulation of various proteostasis network proteins, like chaperones, E3 ubiquitin ligases, proteasome, and autophagy-associated proteins as therapeutic targets by small molecules as well as new and unconventional approaches, shows promise.

Network medicine informed multi-omics integration identifies drug targets and repurposable medicines for Amyotrophic Lateral Sclerosis

Amyotrophic Lateral Sclerosis (ALS) is a devastating, immensely complex neurodegenerative disease by lack of effective treatments. To date, the challenge to establishing effective treatment for ALS remains formidable, partly due to inadequate translation of existing human genetic findings into actionable ALS-specific pathobiology for subsequent therapeutic development. This study evaluates the feasibility of network medicine methodology via integrating human brain-specific multi-omics data to prioritize drug targets and repurposable treatments for ALS. Using human brain-specific genome-wide quantitative trait loci (x-QTLs) under a network-based deep learning framework, we identified 105 putative ALS-associated genes enriched in various known ALS pathobiological pathways, including regulation of T cell activation, monocyte differentiation, and lymphocyte proliferation. Specifically, we leveraged non-coding ALS loci effects from genome-wide associated studies (GWAS) on brain-specific expression quantitative trait loci (QTL) (eQTL), protein QTLs (pQTL), splicing QTL (sQTL), methylation QTL (meQTL), and histone acetylation QTL (haQTL). Applying network proximity analysis of predicted ALS-associated gene-coding targets and existing drug-target networks under the human protein-protein interactome (PPI) model, we identified a set of potential repurposable drugs (including Diazoxide, Gefitinib, Paliperidone, and Dimethyltryptamine) for ALS. Subsequent validation established preclinical and clinical evidence for top-prioritized repurposable drugs. In summary, we presented a network-based multi-omics framework to identify potential drug targets and repurposable treatments for ALS and other neurodegenerative disease if broadly applied.

Genome-wide CRISPR/Cas9 screen shows that loss of GET4 increases mitochondria-endoplasmic reticulum contact sites and is neuroprotective

Organelles form membrane contact sites between each other, allowing for the transfer of molecules and signals. Mitochondria-endoplasmic reticulum (ER) contact sites (MERCS) are cellular subdomains characterized by close apposition of mitochondria and ER membranes. They have been implicated in many diseases, including neurodegenerative, metabolic, and cardiac diseases. Although MERCS have been extensively studied, much remains to be explored. To uncover novel regulators of MERCS, we conducted a genome-wide, flow cytometry-based screen using an engineered MERCS reporter cell line. We found 410 genes whose downregulation promotes MERCS and 230 genes whose downregulation decreases MERCS. From these, 29 genes were selected from each population for arrayed screening and 25 were validated from the high population and 13 from the low population. GET4 and BAG6 were highlighted as the top 2 genes that upon suppression increased MERCS from both the pooled and arrayed screens, and these were subjected to further investigation. Multiple microscopy analyses confirmed that loss of GET4 or BAG6 increased MERCS. GET4 and BAG6 were also observed to interact with the known MERCS proteins, inositol 1,4,5-trisphosphate receptors (IP3R) and glucose-regulated protein 75 (GRP75). In addition, we found that loss of GET4 increased mitochondrial calcium uptake upon ER-Ca2+ release and mitochondrial respiration. Finally, we show that loss of GET4 rescues motor ability, improves lifespan and prevents neurodegeneration in a Drosophila model of Alzheimer's disease (Aβ42Arc). Together, these results suggest that GET4 is involved in decreasing MERCS and that its loss is neuroprotective.

Sequential CRISPR screening reveals partial NatB inhibition as a strategy to mitigate alpha-synuclein levels in human neurons

Alpha-synuclein (αSyn) protein levels correlate with the risk and severity of Parkinson's disease and related neurodegenerative diseases. Lowering αSyn is being actively investigated as a therapeutic modality. Here, we systematically map the regulatory network that controls endogenous αSyn using sequential CRISPR-knockout and -interference screens in an αSyn gene (SNCA)-tagged cell line and induced pluripotent stem cell-derived neurons (iNeurons). We uncover αSyn modifiers at multiple regulatory layers, with amino-terminal acetyltransferase B (NatB) enzymes being the most potent endogenous αSyn modifiers in both cell lines. Amino-terminal acetylation protects the cytosolic αSyn from rapid degradation by the proteasome in a Ube2w-dependent manner. Moreover, we show that pharmacological inhibition of methionyl-aminopeptidase 2, a regulator of NatB complex formation, attenuates endogenous αSyn in iNeurons carrying SNCA triplication. Together, our study reveals several gene networks that control endogenous αSyn, identifies mechanisms mediating the degradation of nonacetylated αSyn, and illustrates potential therapeutic pathways for decreasing αSyn levels in synucleinopathies.

Dynamic proximity interaction profiling suggests that YPEL2 is involved in cellular stress surveillance

YPEL2 is a member of the evolutionarily conserved YPEL family involved in cellular proliferation, mobility, differentiation, senescence, and death. However, the mechanism by which YPEL2, or YPEL proteins, mediates its effects is largely unknown. Proteins perform their functions in a network of proteins whose identities, amounts, and compositions change spatiotemporally in a lineage-specific manner in response to internal and external stimuli. Here, we explored interaction partners of YPEL2 by using dynamic TurboID-coupled mass spectrometry analyses to infer a function for the protein. Our results using inducible transgene expressions in COS7 cells indicate that proximity interaction partners of YPEL2 are mainly involved in RNA and mRNA metabolic processes, ribonucleoprotein complex biogenesis, regulation of gene silencing by miRNA, and cellular responses to stress. We showed that YPEL2 interacts with the RNA-binding protein ELAVL1 and the selective autophagy receptor SQSTM1. We also found that YPEL2 localizes stress granules in response to sodium arsenite, an oxidative stress inducer, which suggests that YPEL2 participates in stress granule-related processes. Establishing a point of departure in the delineation of structural/functional features of YPEL2, our results suggest that YPEL2 may be involved in stress surveillance mechanisms.

Proteotoxic stresses stimulate dissociation of UBL4A from the tail-anchored protein recognition complex

Inclusion body formation is associated with cytotoxicity in a number of neurodegenerative diseases. However, the molecular basis of the toxicity caused by the accumulation of aggregation-prone proteins remains controversial. In this study, we found that disease-associated inclusions induced by elongated polyglutamine chains disrupt the complex formation of BAG6 with UBL4A, a mammalian homologue of yeast Get5. UBL4A also dissociated from BAG6 in response to proteotoxic stresses such as proteasomal inhibition and mitochondrial depolarization. These findings imply that the cytotoxicity of pathological protein aggregates might be attributed in part to disruption of the BAG6-UBL4A complex that is required for the biogenesis of tail-anchored proteins.

Bayesian genome-wide TWAS with reference transcriptomic data of brain and blood tissues identified 93 risk genes for Alzheimer's disease dementia

Background

Transcriptome-wide association study (TWAS) is an influential tool for identifying novel genes associated with complex diseases, where their genetic effects may be mediated through transcriptome. TWAS utilizes reference genetic and transcriptomic data to estimate genetic effect sizes on expression quantitative traits of target genes (i.e., effect sizes of a broad sense of expression quantitative trait loci, eQTL). These estimated effect sizes are then employed as variant weights in burden gene-based association test statistics, facilitating the mapping of risk genes for complex diseases with genome-wide association study (GWAS) data. However, most existing TWAS of Alzheimer's disease (AD) dementia have primarily focused on cis -eQTL, disregarding potential trans -eQTL. To overcome this limitation, we applied the Bayesian Genome-wide TWAS (BGW-TWAS) method which incorporated both cis - and trans -eQTL of brain and blood tissues to enhance mapping risk genes for AD dementia.

Methods

We first applied BGW-TWAS to the Genotype-Tissue Expression (GTEx) V8 dataset to estimate cis - and trans -eQTL effect sizes of the prefrontal cortex, cortex, and whole blood tissues. Subsequently, estimated eQTL effect sizes were integrated with the summary data of the most recent GWAS of AD dementia to obtain BGW-TWAS (i.e., gene-based association test) p-values of AD dementia per tissue type. Finally, we used the aggregated Cauchy association test to combine TWAS p-values across three tissues to obtain omnibus TWAS p-values per gene.

Results

We identified 37 genes in prefrontal cortex, 55 in cortex, and 51 in whole blood that were significantly associated with AD dementia. By combining BGW-TWAS p-values across these three tissues, we obtained 93 significant risk genes including 29 genes primarily due to trans -eQTL and 50 novel genes. Utilizing protein-protein interaction network and phenotype enrichment analyses with these 93 significant risk genes, we detected 5 functional clusters comprised of both known and novel AD risk genes and 7 enriched phenotypes.

Conclusion

We applied BGW-TWAS and aggregated Cauchy test methods to integrate both cis - and trans -eQTL data of brain and blood tissues with GWAS summary data to identify risk genes of AD dementia. The risk genes we identified provide novel insights into the underlying biological pathways implicated in AD dementia.

Detection and modulation of neurodegenerative processes using graphene-based nanomaterials: Nanoarchitectonics and applications

Neurodegenerative disorders (NDDs) are caused by progressive loss of functional neurons following the aggregation and fibrillation of proteins in the central nervous system. The incidence rate continues to rise alarmingly worldwide, particularly in aged population, and the success of treatment remains limited to symptomatic relief. Graphene nanomaterials (GNs) have attracted immense interest on the account of their unique physicochemical and optoelectronic properties. The research over the past two decades has recognized their ability to interact with aggregation-prone neuronal proteins, regulate autophagy and modulate the electrophysiology of neuronal cells. Graphene can prevent the formation of higher order protein aggregates and facilitate the clearance of such deposits. In this review, after highlighting the role of protein fibrillation in neurodegeneration, we have discussed how GN-protein interactions can be exploited for preventing neurodegeneration. A comprehensive understanding of such interactions would contribute to the exploration of novel modalities for controlling neurodegenerative processes.