Aggregate Interactome Based on Protein Cross-linking Interfaces Predicts Drug Targets to Limit Aggregation in Neurodegenerative Diseases

Leave-one-out-analysis (LOOA): web-based tool to predict influential proteins and interactions in aggregate-crosslinking proteomic data

Many age-progressive diseases are accompanied by (and likely caused by) the presence of protein aggregation in affected tissues. Protein aggregates are conjoined by complex protein-protein interactions, which remain poorly understood. Knowledge of the proteins that comprise aggregates, and their adherent interfaces, can be useful to identify therapeutic targets to treat or prevent pathology, and to discover small molecules for disease interventions. We present web-based software to evaluate and rank influential proteins and protein-protein interactions based on graph modelling of the cross linked aggregate interactome. We have used two network-graph-based techniques: Leave-One-Vertex-Out (LOVO) and Leave-One-Edge-Out (LOEO), each followed by dimension reduction and calculation of influential vertices and edges using Principal Components Analysis (PCA) implemented as an R program. This method enables researchers to quickly and accurately determine influential proteins and protein-protein interactions present in their aggregate interactome data.

Alzheimer's-specific brain amyloid interactome: Neural-network analysis of intra-aggregate crosslinking identifies novel drug targets

Alzheimer's disease (AD) is characterized by peri-neuronal amyloid plaque and intra-neuronal neurofibrillary tangles. These aggregates are identified by the immunodetection of "seed" proteins (Aβ1-42 and hyperphosphorylated tau, respectively), but include many other proteins incorporated nonrandomly. Using click-chemistry intra-aggregate crosslinking, we previously modeled amyloid "contactomes" in SY5Y-APPSw neuroblastoma cells, revealing that aspirin impedes aggregate growth and complexity. By an analogous strategy, we now construct amyloid-specific aggregate interactomes of AD and age-matched-control hippocampi. Comparing these interactomes reveals AD-specific interactions, from which neural-network (NN) analyses predict proteins with the highest impact on pathogenic aggregate formation and/or stability. RNAi knockdowns of implicated proteins, in C. elegans and human-cell-culture models of AD, validated those predictions. Gene-Ontology meta-analysis of AD-enriched influential proteins highlighted the involvement of mitochondrial and cytoplasmic compartments in AD-specific aggregation. This approach derives dynamic consensus models of aggregate growth and architecture, implicating highly influential proteins as new targets to disrupt amyloid accrual in the AD brain.

O-GlcNAcylation regulates OTX2's proteostasis

O-GlcNAcylation is a key post-translational modification, playing a vital role in cell signaling during development, especially in the brain. In this study, we investigated the role of O-GlcNAcylation in regulating the homeobox protein OTX2, which contributes to various brain disorders, such as combined pituitary hormone deficiency, retinopathy, and medulloblastoma. Our research demonstrated that, under normal physiological conditions, the proteasome plays a pivotal role in breaking down endogenous OTX2. However, when the levels of OTX2 rise, it forms oligomers and/or aggregates that require macroautophagy for clearance. Intriguingly, we demonstrated that O-GlcNAcylation enhances the solubility of OTX2, thereby limiting the formation of these aggregates. Additionally, we unveiled an interaction between OTX2 and the chaperone protein CCT5 at the O-GlcNAc sites, suggesting a potential collaborative role in preventing OTX2 aggregation. Finally, our study demonstrated that while OTX2 physiologically promotes cell proliferation, an O-GlcNAc-depleted OTX2 is detrimental to cancer cells.

Physiological Consequences of Targeting 14-3-3 and Its Interacting Partners in Neurodegenerative Diseases

The mammalian 14-3-3 family comprises seven intrinsically unstructured, evolutionarily conserved proteins that bind >200 protein targets, thereby modulating cell-signaling pathways. The presence of 14-3-3 proteins in cerebrospinal fluid provides a sensitive and specific biomarker of neuronal damage associated with Alzheimer’s disease (AD), Creutzfeldt−Jakob disease (CJD), spongiform encephalitis, brain cancers, and stroke. We observed significant enrichment of 14-3-3 paralogs G, S, and Z in human brain aggregates diagnostic of AD. We used intra-aggregate crosslinking to identify 14-3-3 interaction partners, all of which were significantly enriched in AD brain aggregates relative to controls. We screened FDA-approved drugs in silico for structures that could target the 14-3-3G/hexokinase interface, an interaction specific to aggregates and AD. C. elegans possesses only two 14-3-3 orthologs, which bind diverse proteins including DAF-16 (a FOXO transcription factor) and SIR-2.1 (a sensor of nutrients and stress), influencing lifespan. Top drug candidates were tested in C. elegans models of neurodegeneration-associated aggregation and in a human neuroblastoma cell-culture model of AD-like amyloidosis. Several drugs opposed aggregation in all models assessed and rescued behavioral deficits in C. elegans AD-like neuropathy models, suggesting that 14-3-3 proteins are instrumental in aggregate accrual and supporting the advancement of drugs targeting 14-3-3 protein complexes with their partners.

Machine-learning analysis of intrinsically disordered proteins identifies key factors that contribute to neurodegeneration-related aggregation

Protein structure is determined by the amino acid sequence and a variety of post-translational modifications, and provides the basis for physiological properties. Not all proteins in the proteome attain a stable conformation; roughly one third of human proteins are unstructured or contain intrinsically disordered regions exceeding 40% of their length. Proteins comprising or containing extensive unstructured regions are termed intrinsically disordered proteins (IDPs). IDPs are known to be overrepresented in protein aggregates of diverse neurodegenerative diseases. We evaluated the importance of disordered proteins in the nematode Caenorhabditis elegans, by RNAi-mediated knockdown of IDPs in disease-model strains that mimic aggregation associated with neurodegenerative pathologies. Not all disordered proteins are sequestered into aggregates, and most of the tested aggregate-protein IDPs contribute to important physiological functions such as stress resistance or reproduction. Despite decades of research, we still do not understand what properties of a disordered protein determine its entry into aggregates. We have employed machine-learning models to identify factors that predict whether a disordered protein is found in sarkosyl-insoluble aggregates isolated from neurodegenerative-disease brains (both AD and PD). Machine-learning predictions, coupled with principal component analysis (PCA), enabled us to identify the physiochemical properties that determine whether a disordered protein will be enriched in neuropathic aggregates.

Glial Fibrillary Acidic Protein: A Biomarker and Drug Target for Alzheimer’s Disease

Glial fibrillary acidic protein (GFAP) is an intermediate filament structural protein involved in cytoskeleton assembly and integrity, expressed in high abundance in activated glial cells. GFAP is neuroprotective, as knockout mice are hypersensitive to traumatic brain injury. GFAP in cerebrospinal fluid is a biomarker of Alzheimer’s disease (AD), dementia with Lewy bodies, and frontotemporal dementia (FTD). Here, we present novel evidence that GFAP is markedly overexpressed and differentially phosphorylated in AD hippocampus, especially in AD with the apolipoprotein E [ε4, ε4] genotype, relative to age-matched controls (AMCs). Kinases that phosphorylate GFAP are upregulated in AD relative to AMC. A knockdown of these kinases in SH-SY5Y-APP_Sw human neuroblastoma cells reduced amyloid accrual and lowered protein aggregation and associated behavioral traits in C. elegans models of polyglutamine aggregation (as observed in Huntington’s disease) and of Alzheimer’s-like amyloid formation. In silico screening of the ChemBridge structural library identified a small molecule, MSR1, with stable and specific binding to GFAP. Both MSR1 exposure and GF AP-specific RNAi knockdown reduce aggregation with remarkably high concordance of aggregate proteins depleted. These data imply that GFAP and its phosphorylation play key roles in neuropathic aggregate accrual and provide valuable new biomarkers, as well as novel therapeutic targets to alleviate, delay, or prevent AD.

Intrinsically disordered proteins identified in the aggregate proteome serve as biomarkers of neurodegeneration

A protein's structure is determined by its amino acid sequence and post-translational modifications, and provides the basis for its physiological functions. Across all organisms, roughly a third of the proteome comprises proteins that contain highly unstructured or intrinsically disordered regions. Proteins comprising or containing extensive unstructured regions are referred to as intrinsically disordered proteins (IDPs). IDPs are believed to participate in complex physiological processes through refolding of IDP regions, dependent on their binding to a diverse array of potential protein partners. They thus play critical roles in the assembly and function of protein complexes. Recent advances in experimental and computational analyses predicted multiple interacting partners for the disordered regions of proteins, implying critical roles in signal transduction and regulation of biological processes. Numerous disordered proteins are sequestered into aggregates in neurodegenerative diseases such as Alzheimer's disease (AD) where they are enriched even in serum, making them good candidates for serum biomarkers to enable early detection of AD.

RNA Dynamics in Alzheimer's Disease

Alzheimer's disease (AD) is the most common age-related neurodegenerative disorder that heavily burdens healthcare systems worldwide. There is a significant requirement to understand the still unknown molecular mechanisms underlying AD. Current evidence shows that two of the major features of AD are transcriptome dysregulation and altered function of RNA binding proteins (RBPs), both of which lead to changes in the expression of different RNA species, including microRNAs (miRNAs), circular RNAs (circRNAs), long non-coding RNAs (lncRNAs), and messenger RNAs (mRNAs). In this review, we will conduct a comprehensive overview of how RNA dynamics are altered in AD and how this leads to the differential expression of both short and long RNA species. We will describe how RBP expression and function are altered in AD and how this impacts the expression of different RNA species. Furthermore, we will also show how changes in the abundance of specific RNA species are linked to the pathology of AD.

"Protein aggregates" contain RNA and DNA, entrapped by misfolded proteins but largely rescued by slowing translational elongation

All neurodegenerative diseases feature aggregates, which usually contain disease-specific diagnostic proteins; non-protein constituents, however, have rarely been explored. Aggregates from SY5Y-APP_Sw neuroblastoma, a cell model of familial Alzheimer's disease, were crosslinked and sequences of linked peptides identified. We constructed a normalized "contactome" comprising 11 subnetworks, centered on 24 high-connectivity hubs. Remarkably, all 24 are nucleic acid-binding proteins. This led us to isolate and sequence RNA and DNA from Alzheimer's and control aggregates. RNA fragments were mapped to the human genome by RNA-seq and DNA by ChIP-seq. Nearly all aggregate RNA sequences mapped to specific genes, whereas DNA fragments were predominantly intergenic. These nucleic acid mappings are all significantly nonrandom, making an artifactual origin extremely unlikely. RNA (mostly cytoplasmic) exceeded DNA (chiefly nuclear) by twofold to fivefold. RNA fragments recovered from AD tissue were ~1.5-to 2.5-fold more abundant than those recovered from control tissue, similar to the increase in protein. Aggregate abundances of specific RNA sequences were strikingly differential between cultured SY5Y-APP_Sw glioblastoma cells expressing APOE3 vs. APOE4, consistent with APOE4 competition for E-box/CLEAR motifs. We identified many G-quadruplex and viral sequences within RNA and DNA of aggregates, suggesting that sequestration of viral genomes may have driven the evolution of disordered nucleic acid-binding proteins. After RNA-interference knockdown of the translational-procession factor EEF2 to suppress translation in SY5Y-APP_Sw cells, the RNA content of aggregates declined by >90%, while reducing protein content by only 30% and altering DNA content by ≤10%. This implies that cotranslational misfolding of nascent proteins may ensnare polysomes into aggregates, accounting for most of their RNA content.

From fuzziness to precision medicine: on the rapidly evolving proteomics with implications in mitochondrial connectivity to rare human disease

Mitochondrial (mt) dysfunction is linked to rare diseases (RDs) such as respiratory chain complex (RCC) deficiency, MELAS, and ARSACS. Yet, how altered mt protein networks contribute to these ailments remains understudied. In this perspective article, we identified 21 mt proteins from public repositories that associate with RCC deficiency, MELAS, or ARSACS, engaging in a relatively small number of protein-protein interactions (PPIs), underscoring the need for advanced proteomic and interactomic platforms to uncover the complete scope of mt connectivity to RDs. Accordingly, we discuss innovative untargeted label-free proteomics in identifying RD-specific mt or other macromolecular assemblies and mapping of protein networks in complex tissue, organoid, and stem cell-differentiated neurons. Furthermore, tag- and label-based proteomics, genealogical proteomics, and combinatorial affinity purification-mass spectrometry, along with advancements in detecting and integrating transient PPIs with single-cell proteomics and transcriptomics, collectively offer seminal follow-ups to enrich for RD-relevant networks, with implications in RD precision medicine.

Structural modeling of GSK3β implicates the inactive (DFG-out) conformation as the target bound by TDZD analogs

Glycogen synthase kinase-3β (GSK3β) controls many physiological pathways, and is implicated in many diseases including Alzheimer’s and several cancers. GSK3β-mediated phosphorylation of target residues in microtubule-associated protein tau (MAPTAU) contributes to MAPTAU hyperphosphorylation and subsequent formation of neurofibrillary tangles. Inhibitors of GSK3β protect against Alzheimer’s disease and are therapeutic for several cancers. A thiadiazolidinone drug, TDZD-8, is a non-ATP-competitive inhibitor targeting GSK3β with demonstrated efficacy against multiple diseases. However, no experimental data or models define the binding mode of TDZD-8 with GSK3β, which chiefly reflects our lack of an established inactive conformation for this protein. Here, we used metadynamic simulation to predict the three-dimensional structure of the inactive conformation of GSK3β. Our model predicts that phosphorylation of GSK3β Serine9 would hasten the DFG-flip to an inactive state. Molecular docking and simulation predict the TDZD-8 binding conformation of GSK3β to be inactive, and are consistent with biochemical evidence for the TDZD-8–interacting residues of GSK3β. We also identified the pharmacophore and assessed binding efficacy of second-generation TDZD analogs (TDZD-10 and Tideglusib) that bind GSK3β as non-ATP-competitive inhibitors. Based on these results, the predicted inactive conformation of GSK3β can facilitate the identification of novel GSK3β inhibitors of high potency and specificity.

Misconnecting the dots: altered mitochondrial protein-protein interactions and their role in neurodegenerative disorders

Introduction: Mitochondria (mt) are protein-protein interaction (PPI) hubs in the cell where mt-localized and associated proteins interact in a fashion critical for cell fitness. Altered mtPPIs are linked to neurodegenerative disorders (NDs) and drivers of pathological associations to mediate ND progression. Mapping altered mtPPIs will reveal how mt dysfunction is linked to NDs.Areas covered: This review discusses how database sources reflect on the number of mt protein or interaction predictions, and serves as an update on mtPPIs in mt dynamics and homeostasis. Emphasis is given to mRNA expression profiles for mt proteins in human tissues, cellular models relevant to NDs, and altered mtPPIs in NDs such as Parkinson's disease (PD), Amyotrophic lateral sclerosis (ALS) and Alzheimer's disease (AD).Expert opinion: We highlight the scarcity of biomarkers to improve diagnostic accuracy and tracking of ND progression, obstacles in recapitulating NDs using human cellular models to underpin the pathophysiological mechanisms of disease, and the shortage of mt protein interactome reference database(s) of neuronal cells. These bottlenecks are addressed by improvements in induced pluripotent stem cell creation and culturing, patient-derived 3D brain organoids to recapitulate structural arrangements of the brain, and cell sorting to elucidate mt proteome disparities between cell types.