Analysis of post-translational modifications in Alzheimer's disease by mass spectrometry

Progress in Core-Shell Magnetic Mesoporous Materials for Enriching Post-Translationally Modified Peptides

Endogenous peptides, particularly those with post-translational modifications, are increasingly being studied as biomarkers for diagnosing various diseases. However, they are weakly ionizable, have a low abundance in biological samples, and may be interfered with by high levels of proteins, peptides, and other macromolecular impurities, resulting in a high limit of detection and insufficient amounts of post-translationally modified peptides in real biological samples to be examined. Therefore, separation and enrichment are necessary before analyzing these biomarkers using mass spectrometry. Mesoporous materials have regular adjustable pores that can eliminate large proteins and impurities, and their large specific surface area can bind more target peptides, but this may result in the partial loss or destruction of target peptides during centrifugal separation. On the other hand, magnetic mesoporous materials can be used to separate the target using an external magnetic field, which improves the separation efficiency and yield. Core-shell magnetic mesoporous materials are widely utilized for peptide separation and enrichment due to their biocompatibility, efficient enrichment capability, and excellent recoverability. This paper provides a review of the latest progress in core-shell magnetic mesoporous materials for enriching glycopeptides and phosphopeptides and compares their enrichment performance with different types of functionalization methods.

The Role of RIN3 Gene in Alzheimer's Disease Pathogenesis: a Comprehensive Review

Alzheimer's disease (AD) is a globally prevalent form of dementia that impacts diverse populations and is characterized by progressive neurodegeneration and impairments in executive memory. Although the exact mechanisms underlying AD pathogenesis remain unclear, it is commonly accepted that the aggregation of misfolded proteins, such as amyloid plaques and neurofibrillary tau tangles, plays a critical role. Additionally, AD is a multifactorial condition influenced by various genetic factors and can manifest as either early-onset AD (EOAD) or late-onset AD (LOAD), each associated with specific gene variants. One gene of particular interest in both EOAD and LOAD is RIN3, a guanine nucleotide exchange factor. This gene plays a multifaceted role in AD pathogenesis. Firstly, upregulation of RIN3 can result in endosomal enlargement and dysfunction, thereby facilitating the accumulation of beta-amyloid (Aβ) peptides in the brain. Secondly, RIN3 has been shown to impact the PICLAM pathway, affecting transcytosis across the blood-brain barrier. Lastly, RIN3 has implications for immune-mediated responses, notably through its influence on the PTK2B gene. This review aims to provide a concise overview of AD and delve into the role of the RIN3 gene in its pathogenesis.

N6-methyladenosine-modified circRIMS2 mediates synaptic and memory impairments by activating GluN2B ubiquitination in Alzheimer's disease

BACKGROUND

Synaptic degeneration occurs in the early stage of Alzheimer's disease (AD) before devastating symptoms, strongly correlated with cognitive decline. Circular RNAs (circRNAs) are abundantly enriched in neural tissues, and aberrant expression of circRNAs precedes AD symptoms, significantly correlated with clinical dementia severity. However, the direct relationship between circRNA dysregulation and synaptic impairment in the early stage of AD remains poorly understood.

METHODS

Hippocampal whole-transcriptome sequencing was performed to identify dysregulated circRNAs and miRNAs in 4-month-old wild-type and APP/PS1 mice. RNA antisense purification and mass spectrometry were utilized to unveil interactions between circRIMS2 and methyltransferase 3, N6-adenosine-methyltransferase complex catalytic subunit (METTL3). The roles of circRIMS2/miR-3968 in synaptic targeting of UBE2K-mediated ubiquitination of GluN2B subunit of NMDA receptor were evaluated via numerous lentiviruses followed by morphological staining, co-immunoprecipitation and behavioral testing. Further, a membrane-permeable peptide was used to block the ubiquitination of K1082 on GluN2B in AD mice.

RESULTS

circRIMS2 was significantly upregulated in 4-month-old APP/PS1 mice, which was mediated by METTL3-dependent N6-methyladenosine (m6A) modification. Overexpression of circRIMS2 led to synaptic and memory impairments in 4-month-old C57BL/6 mice. MiR-3968/UBE2K was validated as the downstream of circRIMS2. Elevated UBE2K induced synaptic dysfunction of AD through ubiquitinating K1082 on GluN2B. Silencing METTL3 or blocking the ubiquitination of K1082 on GluN2B with a short membrane-permeable peptide remarkably rescued synaptic dysfunction in AD mice.

CONCLUSIONS

In conclusion, our study demonstrated that m6A-modified circRIMS2 mediates the synaptic and memory impairments in AD by activating the UBE2K-dependent ubiquitination and degradation of GluN2B via sponging miR-3968, providing novel therapeutic strategies for AD.

The Involvement of Post-Translational Modifications in Regulating the Development and Progression of Alzheimer's Disease

Post-translational modifications (PTMs) have been recently reported to be involved in the development and progression of Alzheimer's disease (AD). In detail, PTMs include phosphorylation, glycation, acetylation, sumoylation, ubiquitination, methylation, nitration, and truncation, which are associated with pathological functions of AD-related proteins, such as β-amyloid (Aβ), β-site APP-cleavage enzyme 1 (BACE1), and tau protein. In particular, the roles of aberrant PTMs in the trafficking, cleavage, and degradation of AD-associated proteins, leading to the cognitive decline of the disease, are summarized under AD conditions. By summarizing these research progress, the gaps will be filled between PMTs and AD, which will facilitate the discovery of potential biomarkers, leading to the establishment of novel clinical intervention methods against AD.

S-Palmitoylation of Synaptic Proteins in Neuronal Plasticity in Normal and Pathological Brains

Protein lipidation is a common post-translational modification of proteins that plays an important role in human physiology and pathology. One form of protein lipidation, S-palmitoylation, involves the addition of a 16-carbon fatty acid (palmitate) onto proteins. This reversible modification may affect the regulation of protein trafficking and stability in membranes. From multiple recent experimental studies, a picture emerges whereby protein S-palmitoylation is a ubiquitous yet discrete molecular switch enabling the expansion of protein functions and subcellular localization in minutes to hours. Neural tissue is particularly rich in proteins that are regulated by S-palmitoylation. A surge of novel methods of detection of protein lipidation at high resolution allowed us to get better insights into the roles of protein palmitoylation in brain physiology and pathophysiology. In this review, we specifically discuss experimental work devoted to understanding the impact of protein palmitoylation on functional changes in the excitatory and inhibitory synapses associated with neuronal activity and neuronal plasticity. The accumulated evidence also implies a crucial role of S-palmitoylation in learning and memory, and brain disorders associated with impaired cognitive functions.

Mass Spectrometry-Based Analysis of Lipid Involvement in Alzheimer’s Disease Pathology—A Review

Irregularities in lipid metabolism have been linked to numerous neurodegenerative diseases. The roles of abnormal brain, plasma, and cerebrospinal fluid (CSF) lipid levels in Alzheimer’s disease (AD) onset and progression specifically have been described to a great extent in the literature. Apparent hallmarks of AD include, but are not limited to, genetic predisposition involving the APOE Ɛ4 allele, oxidative stress, and inflammation. A common culprit tied to many of these hallmarks is disruption in brain lipid homeostasis. Therefore, it is important to understand the roles of lipids, under normal and abnormal conditions, in each process. Lipid influences in processes such as inflammation and blood–brain barrier (BBB) disturbance have been primarily studied via biochemical-based methods. There is a need, however, for studies focused on uncovering the relationship between lipid irregularities and AD by molecular-based quantitative analysis in transgenic animal models and human samples alike. In this review, mass spectrometry as it has been used as an analytical tool to address the convoluted relationships mentioned above is discussed. Additionally, molecular-based mass spectrometry strategies that should be used going forward to further relate structure and function relationships of lipid irregularities and hallmark AD pathology are outlined.

Peripheral Pathways to Neurovascular Unit Dysfunction, Cognitive Impairment, and Alzheimer’s Disease

Alzheimer’s disease (AD) is the most common form of dementia. It was first described more than a century ago, and scientists are acquiring new data and learning novel information about the disease every day. Although there are nuances and details continuously being unraveled, many key players were identified in the early 1900’s by Dr. Oskar Fischer and Dr. Alois Alzheimer, including amyloid-beta (Aβ), tau, vascular abnormalities, gliosis, and a possible role of infections. More recently, there has been growing interest in and appreciation for neurovascular unit dysfunction that occurs early in mild cognitive impairment (MCI) before and independent of Aβ and tau brain accumulation. In the last decade, evidence that Aβ and tau oligomers are antimicrobial peptides generated in response to infection has expanded our knowledge and challenged preconceived notions. The concept that pathogenic germs cause infections generating an innate immune response (e.g., Aβ and tau produced by peripheral organs) that is associated with incident dementia is worthwhile considering in the context of sporadic AD with an unknown root cause. Therefore, the peripheral amyloid hypothesis to cognitive impairment and AD is proposed and remains to be vetted by future research. Meanwhile, humans remain complex variable organisms with individual risk factors that define their immune status, neurovascular function, and neuronal plasticity. In this focused review, the idea that infections and organ dysfunction contribute to Alzheimer’s disease, through the generation of peripheral amyloids and/or neurovascular unit dysfunction will be explored and discussed. Ultimately, many questions remain to be answered and critical areas of future exploration are highlighted.

Mass spectrometric studies of the variety of beta-amyloid proteoforms in Alzheimer's disease

This review covers the results of the application of mass spectrometric (MS) techniques to study the diversity of beta-amyloid (Aβ) peptides in human samples. Since Aβ is an important hallmark of Alzheimer's disease (AD), which is a socially significant neurodegenerative disorder of the elderly worldwide, analysis of its endogenous variations is of particular importance for elucidating the pathogenesis of AD, predicting increased risks of the disease onset, and developing effective therapy. MS approaches have no alternative for the study of complex samples, including a wide variety of Aβ proteoforms, differing in length and modifications. Approaches based on matrix-assisted laser desorption/ionization time-of-flight and liquid chromatography with electrospray ionization tandem MS are most common in Aβ studies. However, Aβ forms with isomerized and/or racemized Asp and Ser residues require the use of special methods for separation and extra sensitive and selective methods for detection. Overall, this review summarizes current knowledge of Aβ species found in human brain, cerebrospinal fluid, and blood plasma; focuses on application of different MS approaches for Aβ studies; and considers the potential of MS techniques for further studies of Aβ-peptides.

Enhanced identification of Tau acetylation and phosphorylation with an engineered aerolysin nanopore

Posttranslational modifications (PTMs) affect protein function/dysfunction, playing important roles in the occurrence and development of tauopathies including Alzheimer's disease. PTM detection is significant and still challenging due to the requirements of high sensitivity to identify the subtle structural differences between modifications. Herein, in terms of the unique geometry of the aerolysin (AeL) nanopore, we elaborately engineered a T232K AeL nanopore to detect the acetylation and phosphorylation of Tau segment (Pep). By replacing neutral threonine (T) with positively charged lysine (K) at the 232 sites, the T232K and K238 rings of this engineered T232K AeL nanopore corporately work together to enhance electrostatic trapping of the acetylated and phosphorylated Tau peptides. Translocation speed of the monophosphorylated Pep-P was decelerated by up to 46 folds compared to the wild-type (WT) AeL nanopore. The prolonged residences within the T232K AeL nanopore enabled to simultaneously identify the monoacetylated Pep-Ac, monophosphorylated Pep-P, di-modified Pep-P-Ac and non-modified Pep. The tremendous potential is demonstrated for PTM sensing by manipulating non-covalent interactions between nanopores and single analytes.

DeepSSPred: A Deep Learning Based Sulfenylation Site Predictor Via a Novel nSegmented Optimize Federated Feature Encoder

BACKGROUND

S-sulfenylation (S-sulphenylation, or sulfenic acid) proteins, are special kinds of post-translation modification, which plays an important role in various physiological and pathological processes such as cytokine signaling, transcriptional regulation, and apoptosis. Despite these aforementioned significances, and by complementing existing wet methods, several computational models have been developed for sulfenylation cysteine sites prediction. However, the performance of these models was not satisfactory due to inefficient feature schemes, severe imbalance issues, and lack of an intelligent learning engine.

OBJECTIVE

In this study, our motivation is to establish a strong and novel computational predictor for discrimination of sulfenylation and non-sulfenylation sites.

METHODS

In this study, we report an innovative bioinformatics feature encoding tool, named DeepSSPred, in which, resulting encoded features is obtained via nSegmented hybrid feature, and then the resampling technique called synthetic minority oversampling was employed to cope with the severe imbalance issue between SC-sites (minority class) and non-SC sites (majority class). State of the art 2D-Convolutional Neural Network was employed over rigorous 10-fold jackknife cross-validation technique for model validation and authentication.

RESULTS

Following the proposed framework, with a strong discrete presentation of feature space, machine learning engine, and unbiased presentation of the underline training data yielded into an excellent model that outperforms with all existing established studies. The proposed approach is 6% higher in terms of MCC from the first best. On an independent dataset, the existing first best study failed to provide sufficient details. The model obtained an increase of 7.5% in accuracy, 1.22% in Sn, 12.91% in Sp and 13.12% in MCC on the training data and12.13% of ACC, 27.25% in Sn, 2.25% in Sp, and 30.37% in MCC on an independent dataset in comparison with 2nd best method. These empirical analyses show the superlative performance of the proposed model over both training and Independent dataset in comparison with existing literature studies.

CONCLUSION

In this research, we have developed a novel sequence-based automated predictor for SC-sites, called DeepSSPred. The empirical simulations outcomes with a training dataset and independent validation dataset have revealed the efficacy of the proposed theoretical model. The good performance of DeepSSPred is due to several reasons, such as novel discriminative feature encoding schemes, SMOTE technique, and careful construction of the prediction model through the tuned 2D-CNN classifier. We believe that our research work will provide a potential insight into a further prediction of S-sulfenylation characteristics and functionalities. Thus, we hope that our developed predictor will significantly helpful for large scale discrimination of unknown SC-sites in particular and designing new pharmaceutical drugs in general.

Predicting phosphorylation sites using machine learning by integrating the sequence, structure, and functional information of proteins

BACKGROUND

Post-translational modification (PTM) is a biological process that alters proteins and is therefore involved in the regulation of various cellular activities and pathogenesis. Protein phosphorylation is an essential process and one of the most-studied PTMs: it occurs when a phosphate group is added to serine (Ser, S), threonine (Thr, T), or tyrosine (Tyr, Y) residue. Dysregulation of protein phosphorylation can lead to various diseases-most commonly neurological disorders, Alzheimer's disease, and Parkinson's disease-thus necessitating the prediction of S/T/Y residues that can be phosphorylated in an uncharacterized amino acid sequence. Despite a surplus of sequencing data, current experimental methods of PTM prediction are time-consuming, costly, and error-prone, so a number of computational methods have been proposed to replace them. However, phosphorylation prediction remains limited, owing to substrate specificity, performance, and the diversity of its features.

METHODS

In the present study we propose machine-learning-based predictors that use the physicochemical, sequence, structural, and functional information of proteins to classify S/T/Y phosphorylation sites. Rigorous feature selection, the minimum redundancy/maximum relevance approach, and the symmetrical uncertainty method were employed to extract the most informative features to train the models.

RESULTS

The RF and SVM models generated using diverse feature types in the present study were highly accurate as is evident from good values for different statistical measures. Moreover, independent test sets and benchmark validations indicated that the proposed method clearly outperformed the existing methods, demonstrating its ability to accurately predict protein phosphorylation.

CONCLUSIONS

The results obtained in the present work indicate that the proposed computational methodology can be effectively used for predicting putative phosphorylation sites further facilitating discovery of various biological processes mechanisms.

The challenge of detecting modifications on proteins

Post-translational modifications (PTMs) are integral to the regulation of protein function, characterising their role in this process is vital to understanding how cells work in both healthy and diseased states. Mass spectrometry (MS) facilitates the mass determination and sequencing of peptides, and thereby also the detection of site-specific PTMs. However, numerous challenges in this field continue to persist. The diverse chemical properties, low abundance, labile nature and instability of many PTMs, in combination with the more practical issues of compatibility with MS and bioinformatics challenges, contribute to the arduous nature of their analysis. In this review, we present an overview of the established MS-based approaches for analysing PTMs and the common complications associated with their investigation, including examples of specific challenges focusing on phosphorylation, lysine acetylation and redox modifications.

Diverse proteins aggregate in mild cognitive impairment and Alzheimer's disease brain

BACKGROUND

All cells accumulate insoluble protein aggregates throughout their lifespan. While many studies have characterized the canonical disease-associated protein aggregates, such as those associated with amyloid plaques, additional, undefined proteins aggregate in the brain and may be directly associated with disease and lifespan.

METHODS

A proteomics approach was used to identify a large subset of insoluble proteins in the mild cognitively impaired (MCI) and Alzheimer's disease (AD) human brain. Cortical samples from control, MCI, and AD patients were separated into detergent-soluble and detergent-insoluble fractions, and high-resolution LC/MS/MS technology was used to determine which proteins became more insoluble in the disease state. Bioinformatics analyses were used to determine if the alteration of protein aggregation between AD and control patients was associated with any specific biological process. Western blots were used to validate the proteomics data and to assess the levels of secondary protein modifications in MCI and AD.

RESULTS

There was a stage-dependent increase in detergent-insoluble proteins, with more extreme changes occurring in the AD cohort. Glycolysis was the most significantly overrepresented gene ontology biological process associated with the alteration of protein aggregation between AD and control patients. It was further shown that many low molecular weight proteins that were enriched in the AD brain were also highly aggregated, migrating on SDS-PAGE far above their predicted molecular masses. Glucose-6-phosphate isomerase, ubiquitin carboxyl-terminal hydrolase isoenzyme L1 (UCHL1/PARK5), and the DNA damage repair enzyme KU70 were among the top insoluble proteins identified by proteomics and validated by Western blot to be increased in the insoluble fractions of both MCI and AD brain samples.

CONCLUSIONS

Diverse proteins became more detergent-insoluble in the brains of both MCI and AD patients compared to age-matched controls, suggesting that multiple proteins aggregate in these diseases, likely posing a direct toxic insult to neurons. Furthermore, detergent-insoluble proteins included those with important biological activities for critical cellular processes such as energetics, proteolysis, and DNA damage repair. Thus, reduced protein solubility likely promotes aggregation and limits functionality, reducing the efficiency of multiple aspects of cell physiology. Pharmaceutical interventions that increase autophagy may provide a useful therapeutic treatment to combat protein aggregation.

Emerging proteomic approaches to identify the underlying pathophysiology of neurodevelopmental and neurodegenerative disorders

Proteomics is the large-scale study of the total protein content and their overall function within a cell through multiple facets of research. Advancements in proteomic methods have moved past the simple quantification of proteins to the identification of post-translational modifications (PTMs) and the ability to probe interactions between these proteins, spatially and temporally. Increased sensitivity and resolution of mass spectrometers and sample preparation protocols have drastically reduced the large amount of cells required and the experimental variability that had previously hindered its use in studying human neurological disorders. Proteomics offers a new perspective to study the altered molecular pathways and networks that are associated with autism spectrum disorders (ASD). The differences between the transcriptome and proteome, combined with the various types of post-translation modifications that regulate protein function and localization, highlight a novel level of research that has not been appropriately investigated. In this review, we will discuss strategies using proteomics to study ASD and other neurological disorders, with a focus on how these approaches can be combined with induced pluripotent stem cell (iPSC) studies. Proteomic analysis of iPSC-derived neurons have already been used to measure changes in the proteome caused by patient mutations, analyze changes in PTMs that resulted in altered biological pathways, and identify potential biomarkers. Further advancements in both proteomic techniques and human iPSC differentiation protocols will continue to push the field towards better understanding ASD disease pathophysiology. Proteomics using iPSC-derived neurons from individuals with ASD offers a window for observing the altered proteome, which is necessary in the future development of therapeutics against specific targets.