Protein interaction networks in neurodegenerative diseases: from physiological function to aggregation

Causal associations and shared genetic etiology of neurodegenerative diseases with epigenetic aging and human longevity

The causative mechanisms underlying the genetic relationships of neurodegenerative diseases with epigenetic aging and human longevity remain obscure. We aimed to detect causal associations and shared genetic etiology of neurodegenerative diseases with epigenetic aging and human longevity. We obtained large-scale genome-wide association study summary statistics data for four measures of epigenetic age (GrimAge, PhenoAge, IEAA, and HannumAge) (N = 34,710), multivariate longevity (healthspan, lifespan, and exceptional longevity) (N = 1,349,462), and for multiple neurodegenerative diseases (N = 6618-482,730), including Lewy body dementia, Alzheimer's disease (AD), Parkinson's disease, amyotrophic lateral sclerosis, and multiple sclerosis. Main analyses were conducted using multiplicative random effects inverse-variance weighted Mendelian randomization (MR), and conditional/conjunctional false discovery rate (cond/conjFDR) approach. Shared genomic loci were functionally characterized to gain biological understanding. Evidence showed that AD patients had 0.309 year less in exceptional longevity (IVW beta = -0.309, 95% CI: -0.38 to -0.24, p = 1.51E-19). We also observed suggestively significant causal evidence between AD and GrimAge age acceleration (IVW beta = -0.10, 95% CI: -0.188 to -0.013, p = 0.02). Following the discovery of polygenic overlap, we identified rs78143120 as shared genomic locus between AD and GrimAge age acceleration, and rs12691088 between AD and exceptional longevity. Among these loci, rs78143120 was novel for AD. In conclusion, we observed that only AD had causal effects on epigenetic aging and human longevity, while other neurodegenerative diseases did not. The genetic overlap between them, with mixed effect directions, suggested complex shared genetic etiology and molecular mechanisms.

Proteomic analysis of cerebrospinal fluid of amyotrophic lateral sclerosis patients in the presence of autologous bone marrow derived mesenchymal stem cells

BACKGROUND

Amyotrophic lateral sclerosis (ALS) is a fatal and rapidly progressive motoneuron degenerative disorder. There are still no drugs capable of slowing disease evolution or improving life quality of ALS patients. Thus, autologous stem cell therapy has emerged as an alternative treatment regime to be investigated in clinical ALS.

METHOD

Using Proteomics and Protein-Protein Interaction Network analyses combined with bioinformatics, the possible cellular mechanisms and molecular targets related to mesenchymal stem cells (MSCs, 1 × 106 cells/kg, intrathecally in the lumbar region of the spine) were investigated in cerebrospinal fluid (CSF) of ALS patients who received intrathecal infusions of autologous bone marrow-derived MSCs thirty days after cell therapy. Data are available via ProteomeXchange with identifier PXD053129.

RESULTS

Proteomics revealed 220 deregulated proteins in CSF of ALS subjects treated with MSCs compared to CSF collected from the same patients prior to MSCs infusion. Bioinformatics enriched analyses highlighted events of Extracellular matrix and Cell adhesion molecules as well as related key targets APOA1, APOE, APP, C4A, C5, FGA, FGB, FGG and PLG in the CSF of cell treated ALS subjects.

CONCLUSIONS

Extracellular matrix and cell adhesion molecules as well as their related highlighted components have emerged as key targets of autologous MSCs in CSF of ALS patients.

TRIAL REGISTRATION

Clinicaltrial.gov identifier NCT0291768. Registered 28 September 2016.

Nanotechnology-driven Microemulsion Based Intranasal Delivery to Neurotechnology-driven Neuralink: Strategies to Improve Management of Neurodegenerative Disorders

Neurodegenerative disorder refers to malfunctioning of neurons their degradation leading to death of neurons. Among various neurodegenerative disorders APHD (Alzheimer's, Parkinson's, and Huntington's Disease) are particularly concerning due to their progressive and debilitating nature. The therapeutic agent used for treatment and management of APHD often show unsatisfactory clinical outcome owing to poor solubility and limited permeability across blood brain barrier (BBB). The nose-to brain delivery can overcome this BBB challenge as it can transport drug directly to brain though olfactory pathways bypassing BBB. Additionally, the nanotechnology has emerged as a cutting-edge methodology to address this issue and specifically mucoadhesive micro/nanoemulsion can improve the overall performance of the drug when administered intranasally. Beyond the therapy neurotechnology has emerged as are revolutionary AI-driven BCI (Brain computer interface) aimed to restore independence in patients with function loss due to neuron degeneration/death. A promising BCI Neuralink has been recently explored for clinical trials and results revealed that a quadriplegia bearing person with implanted Neuralink chip was able to perform few normal functions of daily routine such as playing online games, text messaging, reading, and learning foreign languages online through accessing the particular websites. This review will discuss the fundamental concepts of neurodegeneration, application of micro/nanoemulsion through intranasal route and integration of neurotechnology for the management and treatment of APHD.

Early nuclear phenotypes and reactive transformation in human iPSC-derived astrocytes from ALS patients with SOD1 mutations

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterized by the progressive death of motor neurons (MNs). Glial cells play roles in MN degeneration in ALS. More specifically, astrocytes with mutations in the ALS-associated gene Cu/Zn superoxide dismutase 1 (SOD1) promote MN death. The mechanisms by which SOD1-mutated astrocytes reduce MN survival are incompletely understood. To characterize the impact of SOD1 mutations on astrocyte physiology, we generated astrocytes from human induced pluripotent stem cell (iPSC) derived from ALS patients carrying SOD1 mutations, together with control isogenic iPSCs. We report that astrocytes harboring SOD1(A4V) and SOD1(D90A) mutations exhibit molecular and morphological changes indicative of reactive astrogliosis when compared to isogenic astrocytes. We show further that a number of nuclear phenotypes precede, or coincide with, reactive transformation. These include increased nuclear oxidative stress and DNA damage, and accumulation of the SOD1 protein in the nucleus. These findings reveal early cell-autonomous phenotypes in SOD1-mutated astrocytes that may contribute to the acquisition of a reactive phenotype involved in alterations of astrocyte-MN communication in ALS.

Unraveling the role of physicochemical differences in predicting protein-protein interactions

The ability to accurately predict protein-protein interactions is critically important for understanding major cellular processes. However, current experimental and computational approaches for identifying them are technically very challenging and still have limited success. We propose a new computational method for predicting protein-protein interactions using only primary sequence information. It utilizes the concept of physicochemical similarity to determine which interactions will most likely occur. In our approach, the physicochemical features of proteins are extracted using bioinformatics tools for different organisms. Then they are utilized in a machine-learning method to identify successful protein-protein interactions via correlation analysis. It was found that the most important property that correlates most with the protein-protein interactions for all studied organisms is dipeptide amino acid composition (the frequency of specific amino acid pairs in a protein sequence). While current approaches often overlook the specificity of protein-protein interactions with different organisms, our method yields context-specific features that determine protein-protein interactions. The analysis is specifically applied to the bacterial two-component system that includes histidine kinase and transcriptional response regulators, as well as to the barnase-barstar complex, demonstrating the method's versatility across different biological systems. Our approach can be applied to predict protein-protein interactions in any biological system, providing an important tool for investigating complex biological processes' mechanisms.

Rational design of small-sized peptidomimetic inhibitors disrupting protein-protein interaction

Protein-protein interactions are fundamental to nearly all biological processes. Due to their structural flexibility, peptides have emerged as promising candidates for developing inhibitors targeting large and planar PPI interfaces. However, their limited drug-like properties pose challenges. Hence, rational modifications based on peptide structures are anticipated to expedite the innovation of peptide-based therapeutics. This review comprehensively examines the design strategies for developing small-sized peptidomimetic inhibitors targeting PPI interfaces, which predominantly encompass two primary categories: peptidomimetics with abbreviated sequences and low molecular weights and peptidomimetics mimicking secondary structural conformations. We have also meticulously detailed several instances of designing and optimizing small-sized peptidomimetics targeting PPIs, including MLL1-WDR5, PD-1/PD-L1, and Bak/Bcl-xL, among others, to elucidate the potential application prospects of these design strategies. Hopefully, this review will provide valuable insights and inspiration for the future development of PPI small-sized peptidomimetic inhibitors in pharmaceutical research endeavors.

14-3-3 Protein-Protein Interactions: From Mechanistic Understanding to Their Small-Molecule Stabilization

Protein-protein interactions (PPIs) are of utmost importance for maintenance of cellular homeostasis. Herein, a central role can be found for 14-3-3 proteins. These hub-proteins are known to bind hundreds of interaction partners, thereby regulating their activity, localization, and/or stabilization. Due to their ability to bind a large variety of client proteins, studies of 14-3-3 protein complexes flourished over the last decades, aiming to gain greater molecular understanding of these complexes and their role in health and disease. Because of their crucial role within the cell, 14-3-3 protein complexes are recognized as highly interesting therapeutic targets, encouraging the discovery of small molecule modulators of these PPIs. We discuss various examples of 14-3-3-mediated regulation of its binding partners on a mechanistic level, highlighting the versatile and multi-functional role of 14-3-3 within the cell. Furthermore, an overview is given on the development of stabilizers of 14-3-3 protein complexes, from initially used natural products to fragment-based approaches. These studies show the potential of 14-3-3 PPI stabilizers as novel agents in drug discovery and as tool compounds to gain greater molecular understanding of the role of 14-3-3-based protein regulation.

Polymeric curcumin nanospheres for lysozyme aggregation inhibition, antibacterial, and wound healing applications

The present study reports highly stable polymeric nanoparticles comprising curcumin and polyvinylpyrrolidone, and then conjugated with gold nanoparticles, resulting in C-PVP and C-PVP-Au, respectively. The synthesized conjugates C-PVP and C-PVP-Au were investigated for amyloid aggregation inhibition activity, antimicrobial activity, and wound healing applications. The anti-amyloidogenic capacity of nanoconjugates were studied for model protein, hen egg-white lysozyme (HEWL). The ThT binding assay, fibril size measurement, and electron microscopy results revealed that conjugates suppress fibrillogenesis in HEWL. The highest amyloid inhibition activity obtained against C-PVP and C-PVP-Au was 31 μg.mL-1 and 30 μg.mL-1, respectively. The dissociation activity for amyloid aggregation was observed against Q-PVP and Q-PVP-Au at 29 μg.mL-1 and 27 μg.mL-1, respectively. The antibacterial studies show significant efficacy against Escherichia coli (E. coli) in the presence of C-PVP and C-PVP-Au. The substantial antibacterial potential of C-PVP@PVA and C-PVP-Au@PVA membranes shows promising wound healing applications. The PVA membranes with nanoparticles promote the antibacterial activity and wound healing activity in the Drosophila model. C-PVP-Au@PVA membrane healed the wound faster than the C-PVP@PVA, and it can be used for better results in wound healing. Thus, C-PVP-Au and C-PVP have higher bioavailability and stability and can act as multifunctional therapeutic agents for amyloid-related diseases and as wound healing agents. Graphical abstract C-PVP, and C-PVP-Au conjugates for inhibition of HEWL aggregation, antibacterial and wound healing activity.

Spatially resolved multiomics on the neuronal effects induced by spaceflight in mice

Impairment of the central nervous system (CNS) poses a significant health risk for astronauts during long-duration space missions. In this study, we employed an innovative approach by integrating single-cell multiomics (transcriptomics and chromatin accessibility) with spatial transcriptomics to elucidate the impact of spaceflight on the mouse brain in female mice. Our comparative analysis between ground control and spaceflight-exposed animals revealed significant alterations in essential brain processes including neurogenesis, synaptogenesis and synaptic transmission, particularly affecting the cortex, hippocampus, striatum and neuroendocrine structures. Additionally, we observed astrocyte activation and signs of immune dysfunction. At the pathway level, some spaceflight-induced changes in the brain exhibit similarities with neurodegenerative disorders, marked by oxidative stress and protein misfolding. Our integrated spatial multiomics approach serves as a stepping stone towards understanding spaceflight-induced CNS impairments at the level of individual brain regions and cell types, and provides a basis for comparison in future spaceflight studies. For broader scientific impact, all datasets from this study are available through an interactive data portal, as well as the National Aeronautics and Space Administration (NASA) Open Science Data Repository (OSDR).

Systematic identification of structure-specific protein-protein interactions

The physical interactome of a protein can be altered upon perturbation, modulating cell physiology and contributing to disease. Identifying interactome differences of normal and disease states of proteins could help understand disease mechanisms, but current methods do not pinpoint structure-specific PPIs and interaction interfaces proteome-wide. We used limited proteolysis-mass spectrometry (LiP-MS) to screen for structure-specific PPIs by probing for protease susceptibility changes of proteins in cellular extracts upon treatment with specific structural states of a protein. We first demonstrated that LiP-MS detects well-characterized PPIs, including antibody-target protein interactions and interactions with membrane proteins, and that it pinpoints interfaces, including epitopes. We then applied the approach to study conformation-specific interactors of the Parkinson's disease hallmark protein alpha-synuclein (aSyn). We identified known interactors of aSyn monomer and amyloid fibrils and provide a resource of novel putative conformation-specific aSyn interactors for validation in further studies. We also used our approach on GDP- and GTP-bound forms of two Rab GTPases, showing detection of differential candidate interactors of conformationally similar proteins. This approach is applicable to screen for structure-specific interactomes of any protein, including posttranslationally modified and unmodified, or metabolite-bound and unbound protein states.

Neurotropic virus infection and neurodegenerative diseases: Potential roles of autophagy pathway

Neurodegenerative diseases (NDs) constitute a group of disorders characterized by the progressive deterioration of nervous system functionality. Currently, the precise etiological factors responsible for NDs remain incompletely elucidated, although it is probable that a combination of aging, genetic predisposition, and environmental stressors participate in this process. Accumulating evidence indicates that viral infections, especially neurotropic viruses, can contribute to the onset and progression of NDs. In this review, emerging evidence supporting the association between viral infection and NDs is summarized, and how the autophagy pathway mediated by viral infection can cause pathological aggregation of cellular proteins associated with various NDs is discussed. Furthermore, autophagy-related genes (ARGs) involved in Herpes simplex virus (HSV-1) infection and NDs are analyzed, and whether these genes could link HSV-1 infection to NDs is discussed. Elucidating the mechanisms underlying NDs is critical for developing targeted therapeutic approaches that prevent the onset and slow the progression of NDs.

Heavy Metal Mediated Progressive Degeneration and Its Noxious Effects on Brain Microenvironment

Heavy metals, including lead (Pb), cadmium (Cd), arsenic (As), cobalt (Co), copper (Cu), manganese (Mn), zinc (Zn), and others, have a significant impact on the development and progression of neurodegenerative diseases in the human brain. This comprehensive review aims to consolidate the recent research on the harmful effects of different metals on specific brain cells such as neurons, microglia, astrocytes, and oligodendrocytes. Understanding the potential influence of these metals in neurodegeneration is crucial for effectively combating the ongoing advancement of these diseases. Metal-induced neurodegeneration involves molecular mechanisms such as apoptosis induction, dysregulation of metabolic and signaling pathways, metal imbalance, oxidative stress, loss of synaptic transmission, pathogenic peptide aggregation, and neuroinflammation. This review provides valuable insights by compiling the supportive evidence from recent research findings. Additionally, we briefly discuss the modes of action of natural neuroprotective compounds. While this comprehensive review aims to consolidate the recent research on the harmful effects of various metals on specific brain cells, it may not cover all studies and findings related to metal-induced neurodegeneration. Studies that are done using bioinformatics tools, microRNAs, long non-coding RNAs, emerging disease models, and studies based on the modes of exposure to toxic metals are a future prospect to be explored.

Physical-Chemical Features Selection Reveals That Differences in Dipeptide Compositions Correlate Most with Protein-Protein Interactions

The ability to accurately predict protein-protein interactions is critically important for our understanding of major cellular processes. However, current experimental and computational approaches for identifying them are technically very challenging and still have limited success. We propose a new computational method for predicting protein-protein interactions using only primary sequence information. It utilizes a concept of physical-chemical similarity to determine which interactions will most probably occur. In our approach, the physical-chemical features of protein are extracted using bioinformatics tools for different organisms, and then they are utilized in a machine-learning method to identify successful protein-protein interactions via correlation analysis. It is found that the most important property that correlates most with the protein-protein interactions for all studied organisms is dipeptide amino acid compositions. The analysis is specifically applied to the bacterial two-component system that includes histidine kinase and transcriptional response regulators. Our theoretical approach provides a simple and robust method for quantifying the important details of complex mechanisms of biological processes.

Aggregation of rhodopsin mutants in mouse models of autosomal dominant retinitis pigmentosa

Mutations in rhodopsin can cause it to misfold and lead to retinal degeneration. A distinguishing feature of these mutants in vitro is that they mislocalize and aggregate. It is unclear whether or not these features contribute to retinal degeneration observed in vivo. The effect of P23H and G188R misfolding mutations were examined in a heterologous expression system and knockin mouse models, including a mouse model generated here expressing the G188R rhodopsin mutant. In vitro characterizations demonstrate that both mutants aggregate, with the G188R mutant exhibiting a more severe aggregation profile compared to the P23H mutant. The potential for rhodopsin mutants to aggregate in vivo was assessed by PROTEOSTAT, a dye that labels aggregated proteins. Both mutants mislocalize in photoreceptor cells and PROTEOSTAT staining was detected surrounding the nuclei of photoreceptor cells. The G188R mutant promotes a more severe retinal degeneration phenotype and greater PROTEOSTAT staining compared to that promoted by the P23H mutant. Here, we show that the level of PROTEOSTAT positive cells mirrors the progression and level of photoreceptor cell death, which suggests a potential role for rhodopsin aggregation in retinal degeneration.

The Diverse Roles of Reactive Astrocytes in the Pathogenesis of Amyotrophic Lateral Sclerosis

Astrocytes displaying reactive phenotypes are characterized by their ability to remodel morphologically, molecularly, and functionally in response to pathological stimuli. This process results in the loss of their typical astrocyte functions and the acquisition of neurotoxic or neuroprotective roles. A growing body of research indicates that these reactive astrocytes play a pivotal role in the pathogenesis of amyotrophic lateral sclerosis (ALS), involving calcium homeostasis imbalance, mitochondrial dysfunction, abnormal lipid and lactate metabolism, glutamate excitotoxicity, etc. This review summarizes the characteristics of reactive astrocytes, their role in the pathogenesis of ALS, and recent advancements in astrocyte-targeting strategies.

Predictive Models and Impact of Interfacial Contacts and Amino Acids on Protein-Protein Binding Affinity

Protein-protein interactions (PPIs) play a central role in nearly all cellular processes. The strength of the binding in a PPI is characterized by the binding affinity (BA) and is a key factor in controlling protein-protein complex formation and defining the structure-function relationship. Despite advancements in understanding protein-protein binding, much remains unknown about the interfacial region and its association with BA. New models are needed to predict BA with improved accuracy for therapeutic design. Here, we use machine learning approaches to examine how well different types of interfacial contacts can be used to predict experimentally determined BA and to reveal the impact of the specific amino acids at the binding interface on BA. We create a series of multivariate linear regression models incorporating different contact features at both residue and atomic levels and examine how different methods of identifying and characterizing these properties impact the performance of these models. Particularly, we introduce a new and simple approach to predict BA based on the quantities of specific amino acids at the protein-protein interface. We found that the numbers of specific amino acids at the protein-protein interface were correlated with BA. We show that the interfacial numbers of amino acids can be used to produce models with consistently good performance across different data sets, indicating the importance of the identities of interfacial amino acids in underlying BA. When trained on a diverse set of complexes from two benchmark data sets, the best performing BA model was generated with an explicit linear equation involving six amino acids. Tyrosine, in particular, was identified as the key amino acid in controlling BA, as it had the strongest correlation with BA and was consistently identified as the most important amino acid in feature importance studies. Glycine and serine were identified as the next two most important amino acids in predicting BA. The results from this study further our understanding of PPIs and can be used to make improved predictions of BA, giving them implications for drug design and screening in the pharmaceutical industry.

The pro-oncogenic protein IF1 does not contribute to the Warburg effect and is not regulated by PKA in cancer cells

The endogenous inhibitor of mitochondrial F1Fo-ATPase (ATP synthase), IF1, has been shown to exert pro-oncogenic actions, including reprogramming of cellular energy metabolism (Warburg effect). The latter action of IF1 has been reported to be hampered by its PKA-dependent phosphorylation, but both reprogramming of metabolism and PKA-dependent phosphorylation are intensely debated. To clarify these critical issues, we prepared stably IF1-silenced clones and compared their bioenergetics with that of the three parental IF1-expressing cancer cell lines. All functional parameters: respiration rate, ATP synthesis rate (OXPHOS), and mitochondrial membrane potential were similar in IF1-silenced and control cells, clearly indicating that IF1 cannot inhibit the ATP synthase in cancer cells when the enzyme works physiologically. Furthermore, all cell types exposed to PKA modulators and energized with NAD+-dependent substrates or succinate showed similar OXPHOS rate regardless of the presence or absence of IF1. Therefore, our results rule out that IF1 action is modulated by its PKA-dependent phosphorylated/dephosphorylated state. Notably, cells exposed to a negative PKA modulator and energized with NAD+-dependent substrates showed a significant decrease of the OXPHOS rate matching previously reported inactivation of complex I. Overall, this study definitively demonstrates that IF1 inhibits neither mitochondrial ATP synthase nor OXPHOS in normoxic cancer cells and does not contribute to the Warburg effect. Thus, currently the protection of cancer cells from severe hypoxia/anoxia and apoptosis remain the only unquestionable actions of IF1 as pro-oncogenic factor that may be exploited to develop therapeutic approaches.

Trehalose-Bearing Carriers to Target Impaired Autophagy and Protein Aggregation Diseases

In recent years, trehalose, a natural disaccharide, has attracted growing attention because of the discovery of its potential to induce autophagy. Trehalose has also been demonstrated to preserve the protein's structural integrity and to limit the aggregation of pathologically misfolded proteins. Both of these properties have made trehalose a promising therapeutic candidate to target autophagy-related disorders and protein aggregation diseases. Unfortunately, trehalose has poor bioavailability due to its hydrophilic nature and susceptibility to enzymatic degradation. Recently, trehalose-bearing carriers, in which trehalose is incorporated either by chemical conjugation or physical entrapment, have emerged as an alternative option to free trehalose to improve its efficacy, particularly for the treatment of neurodegenerative diseases, atherosclerosis, nonalcoholic fatty liver disease (NAFLD), and cancers. In the current Perspective, we discuss all existing literature in this emerging field and try to identify key challenges for researchers intending to develop trehalose-bearing carriers to stimulate autophagy or inhibit protein aggregation.

A multi-layered network model identifies Akt1 as a common modulator of neurodegeneration

The accumulation of misfolded and aggregated proteins is a hallmark of neurodegenerative proteinopathies. Although multiple genetic loci have been associated with specific neurodegenerative diseases (NDs), molecular mechanisms that may have a broader relevance for most or all proteinopathies remain poorly resolved. In this study, we developed a multi-layered network expansion (MLnet) model to predict protein modifiers that are common to a group of diseases and, therefore, may have broader pathophysiological relevance for that group. When applied to the four NDs Alzheimer's disease (AD), Huntington's disease, and spinocerebellar ataxia types 1 and 3, we predicted multiple members of the insulin pathway, including PDK1, Akt1, InR, and sgg (GSK-3β), as common modifiers. We validated these modifiers with the help of four Drosophila ND models. Further evaluation of Akt1 in human cell-based ND models revealed that activation of Akt1 signaling by the small molecule SC79 increased cell viability in all models. Moreover, treatment of AD model mice with SC79 enhanced their long-term memory and ameliorated dysregulated anxiety levels, which are commonly affected in AD patients. These findings validate MLnet as a valuable tool to uncover molecular pathways and proteins involved in the pathophysiology of entire disease groups and identify potential therapeutic targets that have relevance across disease boundaries. MLnet can be used for any group of diseases and is available as a web tool at http://ssbio.cau.ac.kr/software/mlnet.

Stalling the Course of Neurodegenerative Diseases: Could Cyanobacteria Constitute a New Approach toward Therapy?

Neurodegenerative diseases (NDs) are characterized by progressive and irreversible neuronal loss, accompanied by a range of pathological pathways, including aberrant protein aggregation, altered energy metabolism, excitotoxicity, inflammation, and oxidative stress. Some of the most common NDs include Alzheimer's Disease (AD), Parkinson's Disease (PD), Multiple Sclerosis (MS), Amyotrophic Lateral Sclerosis (ALS), and Huntington's Disease (HD). There are currently no available cures; there are only therapeutic approaches that ameliorate the progression of symptoms, which makes the search for new drugs and therapeutic targets a constant battle. Cyanobacteria are ancient prokaryotic oxygenic phototrophs whose long evolutionary history has resulted in the production of a plethora of biomedically relevant compounds with anti-inflammatory, antioxidant, immunomodulatory, and neuroprotective properties, that can be valuable in this field. This review summarizes the major NDs and their pathophysiology, with a focus on the anti-neurodegenerative properties of cyanobacterial compounds and their main effects.

Protein-protein interaction and site prediction using transfer learning

The advanced language models have enabled us to recognize protein-protein interactions (PPIs) and interaction sites using protein sequences or structures. Here, we trained the MindSpore ProteinBERT (MP-BERT) model, a Bidirectional Encoder Representation from Transformers, using protein pairs as inputs, making it suitable for identifying PPIs and their respective interaction sites. The pretrained model (MP-BERT) was fine-tuned as MPB-PPI (MP-BERT on PPI) and demonstrated its superiority over the state-of-the-art models on diverse benchmark datasets for predicting PPIs. Moreover, the model's capability to recognize PPIs among various organisms was evaluated on multiple organisms. An amalgamated organism model was designed, exhibiting a high level of generalization across the majority of organisms and attaining an accuracy of 92.65%. The model was also customized to predict interaction site propensity by fine-tuning it with PPI site data as MPB-PPISP. Our method facilitates the prediction of both PPIs and their interaction sites, thereby illustrating the potency of transfer learning in dealing with the protein pair task.

The Properties and Domain Requirements for Phase Separation of the Sup35 Prion Protein In Vivo

The Sup35 prion protein of budding yeast has been reported to undergo phase separation to form liquid droplets both at low pH in vitro and when energy depletion decreases the intracellular pH in vivo. It also has been shown using purified proteins that this phase separation is driven by the prion domain of Sup35 and does not re-quire its C-terminal domain. In contrast, we now find that a Sup35 fragment consisting of only the N-terminal prion domain and the M-domain does not phase separate in vivo; this phase separation of Sup35 requires the C-terminal domain, which binds Sup45 to form the translation termination complex. The phase-separated Sup35 not only colocalizes with Sup45 but also with Pub1, a stress granule marker protein. In addition, like stress granules, phase separation of Sup35 appears to require mRNA since cycloheximide treatment, which inhibits mRNA release from ribosomes, prevents phase separation of Sup35. Finally, unlike Sup35 in vitro, Sup35 condensates do not disassemble in vivo when the intracellular pH is increased. These results suggest that, in energy-depleted cells, Sup35 forms supramolecular assemblies that differ from the Sup35 liquid droplets that form in vitro.

Valosin containing protein (VCP): initiator, modifier, and potential drug target for neurodegenerative diseases

The AAA+ ATPase valosin containing protein (VCP) is essential for cell and organ homeostasis, especially in cells of the nervous system. As part of a large network, VCP collaborates with many cofactors to ensure proteostasis under normal, stress, and disease conditions. A large number of mutations have revealed the importance of VCP for human health. In particular, VCP facilitates the dismantling of protein aggregates and the removal of dysfunctional organelles. These are critical events to prevent malfunction of the brain and other parts of the nervous system. In line with this idea, VCP mutants are linked to the onset and progression of neurodegeneration and other diseases. The intricate molecular mechanisms that connect VCP mutations to distinct brain pathologies continue to be uncovered. Emerging evidence supports the model that VCP controls cellular functions on multiple levels and in a cell type specific fashion. Accordingly, VCP mutants derail cellular homeostasis through several mechanisms that can instigate disease. Our review focuses on the association between VCP malfunction and neurodegeneration. We discuss the latest insights in the field, emphasize open questions, and speculate on the potential of VCP as a drug target for some of the most devastating forms of neurodegeneration.

Integrative multi-omics and systems bioinformatics in translational neuroscience: A data mining perspective

Bioinformatic analysis of large and complex omics datasets has become increasingly useful in modern day biology by providing a great depth of information, with its application to neuroscience termed neuroinformatics. Data mining of omics datasets has enabled the generation of new hypotheses based on differentially regulated biological molecules associated with disease mechanisms, which can be tested experimentally for improved diagnostic and therapeutic targeting of neurodegenerative diseases. Importantly, integrating multi-omics data using a systems bioinformatics approach will advance the understanding of the layered and interactive network of biological regulation that exchanges systemic knowledge to facilitate the development of a comprehensive human brain profile. In this review, we first summarize data mining studies utilizing datasets from the individual type of omics analysis, including epigenetics/epigenomics, transcriptomics, proteomics, metabolomics, lipidomics, and spatial omics, pertaining to Alzheimer's disease, Parkinson's disease, and multiple sclerosis. We then discuss multi-omics integration approaches, including independent biological integration and unsupervised integration methods, for more intuitive and informative interpretation of the biological data obtained across different omics layers. We further assess studies that integrate multi-omics in data mining which provide convoluted biological insights and offer proof-of-concept proposition towards systems bioinformatics in the reconstruction of brain networks. Finally, we recommend a combination of high dimensional bioinformatics analysis with experimental validation to achieve translational neuroscience applications including biomarker discovery, therapeutic development, and elucidation of disease mechanisms. We conclude by providing future perspectives and opportunities in applying integrative multi-omics and systems bioinformatics to achieve precision phenotyping of neurodegenerative diseases and towards personalized medicine.

Aligning Cross-Species Interactomes for Studying Complex and Chronic Diseases

Neurodegenerative diseases (NDs) are a group of complex disorders characterized by the progressive degeneration and dysfunction of neurons in the central nervous system. NDs encompass many conditions, including Alzheimer's disease and Parkinson's disease. Alzheimer's disease (AD) is a complex disease affecting almost forty million people worldwide. AD is characterized by a progressive decline of cognitive functions related to the loss of connections between nerve cells caused by the prevalence of extracellular Aβ plaques and intracellular neurofibrillary tangles plaques. Parkinson's disease (PD) is a neurodegenerative disorder that primarily affects the movement of an individual. The exact cause of Parkinson's disease is not fully understood, but it is believed to involve a combination of genetic and environmental factors. Some cases of PD are linked to mutations in the LRRK2, PARKIN and other genes, which are associated with familial forms of the disease. Different research studies have applied the Protein Protein Interaction (PPI) networks to understand different aspects of disease progression. For instance, Caenorhabditis elegans is widely used as a model organism for the study of AD due to roughly 38% of its genes having a human ortholog. This study's goal consists of comparing PPI network of C. elegans and human by applying computational techniques, widely used for the analysis of PPI networks between species, such as Local Network Alignment (LNA). For this aim, we used L-HetNetAligner algorithm to build a local alignment among two PPI networks, i.e., C. elegans and human PPI networks associated with AD and PD built-in silicon. The results show that L-HetNetAligner can find local alignments representing functionally related subregions. In conclusion, since local alignment enables the extraction of functionally related modules, the method can be used to study complex disease progression.

Lost in traffic: consequences of altered palmitoylation in neurodegeneration

One of the first molecular events in neurodegenerative diseases, regardless of etiology, is protein mislocalization. Protein mislocalization in neurons is often linked to proteostasis deficiencies leading to the build-up of misfolded proteins and/or organelles that contributes to cellular toxicity and cell death. By understanding how proteins mislocalize in neurons, we can develop novel therapeutics that target the earliest stages of neurodegeneration. A critical mechanism regulating protein localization and proteostasis in neurons is the protein-lipid modification S-acylation, the reversible addition of fatty acids to cysteine residues. S-acylation is more commonly referred to as S-palmitoylation or simply palmitoylation, which is the addition of the 16-carbon fatty acid palmitate to proteins. Like phosphorylation, palmitoylation is highly dynamic and tightly regulated by writers (i.e., palmitoyl acyltransferases) and erasers (i.e., depalmitoylating enzymes). The hydrophobic fatty acid anchors proteins to membranes; thus, the reversibility allows proteins to be re-directed to and from membranes based on local signaling factors. This is particularly important in the nervous system, where axons (output projections) can be meters long. Any disturbance in protein trafficking can have dire consequences. Indeed, many proteins involved in neurodegenerative diseases are palmitoylated, and many more have been identified in palmitoyl-proteomic studies. It follows that palmitoyl acyl transferase enzymes have also been implicated in numerous diseases. In addition, palmitoylation can work in concert with cellular mechanisms, like autophagy, to affect cell health and protein modifications, such as acetylation, nitrosylation, and ubiquitination, to affect protein function and turnover. Limited studies have further revealed a sexually dimorphic pattern of protein palmitoylation. Therefore, palmitoylation can have wide-reaching consequences in neurodegenerative diseases.

Synucleinopathies Take Their Toll: Are TLRs a Way to Go?

The misfolding and subsequent abnormal accumulation and aggregation of α-Synuclein (αSyn) as insoluble fibrils in Lewy bodies and Lewy neurites is the pathological hallmark of Parkinson's disease (PD) and several neurodegenerative disorders. A combination of environmental and genetic factors is linked to αSyn misfolding, among which neuroinflammation is recognized to play an important role. Indeed, a number of studies indicate that a Toll-like receptor (TLR)-mediated neuroinflammation might lead to a dopaminergic neural loss, suggesting that TLRs could participate in the pathogenesis of PD as promoters of immune/neuroinflammatory responses. Here we will summarize our current understanding on the mechanisms of αSyn aggregation and misfolding, focusing on the contribution of TLRs to the progression of α-synucleinopathies and speculating on their link with the non-motor disturbances associated with aging and neurodegenerative disorders.

Characterization of Cystatin B Interactome in Saliva from Healthy Elderly and Alzheimer’s Disease Patients

Cystatin B is a small, multifunctional protein involved in the regulation of inflammation, innate immune response, and neuronal protection and found highly abundant in the brains of patients with Alzheimer’s disease (AD). Recently, our study demonstrated a significant association between the level of salivary cystatin B and AD. Since the protein is able to establish protein-protein interaction (PPI) in different contexts and aggregation-prone proteins and the PPI networks are relevant for AD pathogenesis, and due to the relevance of finding new AD markers in peripheral biofluids, we thought it was interesting to study the possible involvement of cystatin B in PPIs in saliva and to evaluate differences and similarities between AD and age-matched elderly healthy controls (HC). For this purpose, we applied a co-immunoprecipitation procedure and a bottom-up proteomics analysis to purify, identify, and quantify cystatin B interactors. Results demonstrated for the first time the existence of a salivary cystatin B-linked multi-protein complex composed by 82 interactors and largely expressed in the body. Interactors are involved in neutrophil activation, antimicrobial activity, modulation of the cytoskeleton and extra-cellular matrix (ECM), and glucose metabolism. Preliminary quantitative data showed significantly lower levels of triosophosphate isomerase 1 and higher levels of mucin 7, BPI, and matrix Gla protein in AD with respect to HC, suggesting implications associated with AD of altered glucose metabolism, antibacterial activities, and calcification-associated processes. Data are available via ProteomeXchange with identifiers PXD039286 and PXD030679.

Bisphenol-A (BPA) Impairs Hippocampal Neurogenesis via Inhibiting Regulation of the Ubiquitin Proteasomal System

The ubiquitin-proteasome system (UPS) controls protein homeostasis to maintain cell functionality and survival. Neurogenesis relies on proteasome function, and a defective proteasome system during brain development leads to neurological disorders. An endocrine-disrupting xenoestrogen bisphenol-A (BPA) used in plastic products adversely affects human health and causes neurotoxicity. Previously, we reported that BPA reduces neural stem cells (NSCs) proliferation and differentiation, impairs myelination and mitochondrial protein import, and causes excessive mitochondrial fragmentation leading to cognitive impairments in rats. Herein, we examined the effect(s) of prenatal BPA exposure on UPS functions during NSCs proliferation and differentiation in the hippocampus. Rats were orally treated with 40 µg/kg body weight BPA during day 6 gestation to day 21 postnatal. BPA significantly reduced proteasome activity in a cellular extract of NSCs. Immunocytochemistry exhibited a significant reduction of 20S proteasome/Nestin⁺ and PSMB5/Nestin⁺ cells in NSCs culture. BPA decreased 20S/Tuj1⁺ and PSMB5/Tuj1⁺ cells, indicating disrupted UPS during neuronal differentiation. BPA reduced the expression of UPS genes, 20S, and PSMB5 protein levels and proteasome activity in the hippocampus. It significantly reduced overall protein synthesis by the loss of Nissl substances in the hippocampus. Pharmacological activation of UPS by a bioactive triterpenoid 18α-glycyrrhetinic acid (18α GA) caused increased proteasome activities, significantly increased neurosphere size and number, and enhanced NSCs proliferation in BPA exposed culture, while proteasome inhibition by MG132 further aggravates BPA-mediated effects. In silico studies demonstrated that BPA strongly binds to catalytic sites of UPS genes (PSMB5, TRIM11, Parkin, and PSMD4) which may result in UPS inactivation. These results suggest that BPA significantly reduces NSCs proliferation by impairing UPS, and UPS activation by 18α GA could suppress BPA-mediated neurotoxicity and exerts neuroprotection.

Mechanisms Underlying Neurodegenerative Disorders and Potential Neuroprotective Activity of Agrifood By-Products

Neurodegenerative diseases, characterized by progressive loss in selected areas of the nervous system, are becoming increasingly prevalent worldwide due to an aging population. Despite their diverse clinical manifestations, neurodegenerative diseases are multifactorial disorders with standard features and mechanisms such as abnormal protein aggregation, mitochondrial dysfunction, oxidative stress and inflammation. As there are no effective treatments to counteract neurodegenerative diseases, increasing interest has been directed to the potential neuroprotective activities of plant-derived compounds found abundantly in food and in agrifood by-products. Food waste has an extremely negative impact on the environment, and recycling is needed to promote their disposal and overcome this problem. Many studies have been carried out to develop green and effective strategies to extract bioactive compounds from food by-products, such as peel, leaves, seeds, bran, kernel, pomace, and oil cake, and to investigate their biological activity. In this review, we focused on the potential neuroprotective activity of agrifood wastes obtained by common products widely produced and consumed in Italy, such as grapes, coffee, tomatoes, olives, chestnuts, onions, apples, and pomegranates.

Lysophospholipids: A Potential Drug Candidates for Neurodegenerative Disorders

Neurodegenerative diseases (NDs) commonly present misfolded and aggregated proteins. Considerable research has been performed to unearth the molecular processes underpinning this pathological aggregation and develop therapeutic strategies targeting NDs. Fibrillary deposits of α-synuclein (α-Syn), a highly conserved and thermostable protein, are a critical feature in the development of NDs such as Alzheimer's disease (AD), Lewy body disease (LBD), Parkinson's disease (PD), and multiple system atrophy (MSA). Inhibition of α-Syn aggregation can thus serve as a potential approach for therapeutic intervention. Recently, the degradation of target proteins by small molecules has emerged as a new therapeutic modality, gaining the hotspot in pharmaceutical research. Additionally, interest is growing in the use of food-derived bioactive compounds as intervention agents against NDs via functional foods and dietary supplements. According to reports, dietary bioactive phospholipids may have cognition-enhancing and neuroprotective effects, owing to their abilities to influence cognition and mental health in vivo and in vitro. However, the mechanisms by which lipids may prevent the pathological aggregation of α-Syn warrant further clarification. Here, we review evidence for the potential mechanisms underlying this effect, with a particular focus on how porcine liver decomposition product (PLDP)-derived lysophospholipids (LPLs) may inhibit α-Syn aggregation.