Network approach identifies Pacer as an autophagy protein involved in ALS pathogenesis

A RAB7A phosphoswitch coordinates Rubicon Homology protein regulation of Parkin-dependent mitophagy

Activation of PINK1 and Parkin in response to mitochondrial damage initiates a response that includes phosphorylation of RAB7A at Ser72. Rubicon is a RAB7A binding negative regulator of autophagy. The structure of the Rubicon:RAB7A complex suggests that phosphorylation of RAB7A at Ser72 would block Rubicon binding. Indeed, in vitro phosphorylation of RAB7A by TBK1 abrogates Rubicon:RAB7A binding. Pacer, a positive regulator of autophagy, has an RH domain with a basic triad predicted to bind an introduced phosphate. Consistent with this, Pacer-RH binds to phosho-RAB7A but not to unphosphorylated RAB7A. In cells, mitochondrial depolarization reduces Rubicon:RAB7A colocalization whilst recruiting Pacer to phospho-RAB7A-positive puncta. Pacer knockout reduces Parkin mitophagy with little effect on bulk autophagy or Parkin-independent mitophagy. Rescue of Parkin-dependent mitophagy requires the intact pRAB7A phosphate-binding basic triad of Pacer. Together these structural and functional data support a model in which the TBK1-dependent phosphorylation of RAB7A serves as a switch, promoting mitophagy by relieving Rubicon inhibition and favoring Pacer activation.

The autophagy protein Def8 is altered in Alzheimer's disease and Aβ42-expressing Drosophila brains

Alzheimer's disease (AD) is the most common neurodegenerative disorder, characterized by protein accumulation in the brain as a main neuropathological hallmark. Among them, Aβ42 peptides tend to aggregate and create oligomers and plaques. Macroautophagy, a form of autophagy characterized by a double-membrane vesicle, plays a crucial role in maintaining neuronal homeostasis by degrading protein aggregates and dysfunctional organelles as a quality control process. Recently, DEF8, a relatively uncharacterized protein, has been proposed as a participant in vesicular traffic and autophagy pathways. We have reported increased DEF8 levels in lymphocytes from mild cognitive impairment (MCI) and early-stage AD patients and a neuronal profile in a murine transgenic AD model. Here, we analyzed DEF8 localization and levels in the postmortem frontal cortex of AD patients, finding increased levels compared to healthy controls. To evaluate the potential function of DEF8 in the nervous system, we performed an in silico assessment of its expression and network profiles, followed by an in vivo evaluation of a neuronal Def8 deficient model using a Drosophila melanogaster model of AD based on Aβ42 expression. Our findings show that DEF8 is an essential protein for maintaining cellular homeostasis in the nervous system, and it is upregulated under stress conditions generated by Aβ42 aggregation. This study suggests DEF8 as a novel actor in the physiopathology of AD, and its exploration may lead to new treatment avenues.

Intersection of network medicine and machine learning towards investigating the key biomarkers and pathways underlying amyotrophic lateral sclerosis: a systematic review

BACKGROUND

Network medicine is an emerging area of research that focuses on delving into the molecular complexity of the disease, leading to the discovery of network biomarkers and therapeutic target discovery. Amyotrophic lateral sclerosis (ALS) is a complicated rare disease with unknown pathogenesis and no available treatment. In ALS, network properties appear to be potential biomarkers that can be beneficial in disease-related applications when explored independently or in tandem with machine learning (ML) techniques.

OBJECTIVE

This systematic literature review explores recent trends in network medicine and implementations of network-based ML algorithms in ALS. We aim to provide an overview of the identified primary studies and gather details on identifying the potential biomarkers and delineated pathways.

METHODS

The current study consists of searching for and investigating primary studies from PubMed and Dimensions.ai, published between 2018 and 2022 that reported network medicine perspectives and the coupling of ML techniques. Each abstract and full-text study was individually evaluated, and the relevant studies were finally included in the review for discussion once they met the inclusion and exclusion criteria.

RESULTS

We identified 109 eligible publications from primary studies representing this systematic review. The data coalesced into two themes: application of network science to identify disease modules and promising biomarkers in ALS, along with network-based ML approaches. Conclusion This systematic review gives an overview of the network medicine approaches and implementations of network-based ML algorithms in ALS to determine new disease genes, and identify critical pathways and therapeutic target discovery for personalized treatment.

Neuronal Rubicon Represses Extracellular APP/Amyloid β Deposition in Alzheimer's Disease

Alzheimer’s disease (AD) is the most prevalent age-associated neurodegenerative disease. A decrease in autophagy during aging contributes to brain disorders by accumulating potentially toxic substrates in neurons. Rubicon is a well-established inhibitor of autophagy in all cells. However, Rubicon participates in different pathways depending on cell type, and little information is currently available on neuronal Rubicon’s role in the AD context. Here, we investigated the cell-specific expression of Rubicon in postmortem brain samples from AD patients and 5xFAD mice and its impact on amyloid β burden in vivo and neuroblastoma cells. Further, we assessed Rubicon levels in human-induced pluripotent stem cells (hiPSCs), derived from early-to-moderate AD and in postmortem samples from severe AD patients. We found increased Rubicon levels in AD-hiPSCs and postmortem samples and a notable Rubicon localization in neurons. In AD transgenic mice lacking Rubicon, we observed intensified amyloid β burden in the hippocampus and decreased Pacer and p62 levels. In APP-expressing neuroblastoma cells, increased APP/amyloid β secretion in the medium was found when Rubicon was absent, which was not observed in cells depleted of Atg5, essential for autophagy, or Rab27a, required for exosome secretion. Our results propose an uncharacterized role of Rubicon on APP/amyloid β homeostasis, in which neuronal Rubicon is a repressor of APP/amyloid β secretion, defining a new way to target AD and other similar diseases therapeutically.

The Autophagy Protein Pacer Positively Regulates the Therapeutic Potential of Mesenchymal Stem Cells in a Mouse Model of DSS-Induced Colitis

Mesenchymal stem cells (MSC) have emerged as a promising tool to treat inflammatory diseases, such as inflammatory bowel disease (IBD), due to their immunoregulatory properties. Frequently, IBD is modeled in mice by using dextran sulfate sodium (DSS)-induced colitis. Recently, the modulation of autophagy in MSC has been suggested as a novel strategy to improve MSC-based immunotherapy. Hence, we investigated a possible role of Pacer, a novel autophagy enhancer, in regulating the immunosuppressive function of MSC in the context of DSS-induced colitis. We found that Pacer is upregulated upon stimulation with the pro-inflammatory cytokine TNFα, the main cytokine released in the inflammatory environment of IBD. By modulating Pacer expression in MSC, we found that Pacer plays an important role in regulating the autophagy pathway in this cell type in response to TNFα stimulation, as well as in regulating the immunosuppressive ability of MSC toward T-cell proliferation. Furthermore, increased expression of Pacer in MSC enhanced their ability to ameliorate the symptoms of DSS-induced colitis in mice. Our results support previous findings that autophagy regulates the therapeutic potential of MSC and suggest that the augmentation of autophagic capacity in MSC by increasing Pacer levels may have therapeutic implications for IBD.

ATGPred-FL: sequence-based prediction of autophagy proteins with feature representation learning

Autophagy plays an important role in biological evolution and is regulated by many autophagy proteins. Accurate identification of autophagy proteins is crucially important to reveal their biological functions. Due to the expense and labor cost of experimental methods, it is urgent to develop automated, accurate and reliable sequence-based computational tools to enable the identification of novel autophagy proteins among numerous proteins and peptides. For this purpose, a new predictor named ATGPred-FL was proposed for the efficient identification of autophagy proteins. We investigated various sequence-based feature descriptors and adopted the feature learning method to generate corresponding, more informative probability features. Then, a two-step feature selection strategy based on accuracy was utilized to remove irrelevant and redundant features, leading to the most discriminative 14-dimensional feature set. The final predictor was built using a support vector machine classifier, which performed favorably on both the training and testing sets with accuracy values of 94.40% and 90.50%, respectively. ATGPred-FL is the first ATG machine learning predictor based on protein primary sequences. We envision that ATGPred-FL will be an effective and useful tool for autophagy protein identification, and it is available for free at http://lab.malab.cn/~acy/ATGPred-FL , the source code and datasets are accessible at https://github.com/jiaoshihu/ATGPred .

Phosphoinositide-3-kinase regulatory subunit 4 participates in the occurrence and development of amyotrophic lateral sclerosis by regulating autophagy

The development of amyotrophic lateral sclerosis (ALS) may be related to the abnormal alterations of multiple proteins. Our previous study revealed that the expression of phosphoinositide-3-kinase regulatory subunit 4 (PIK3R4) was decreased in ALS. However, the role of PIK3R4 in ALS pathogenesis remains unknown. This study was the first to find that transfection of PC12 cells with small interfering RNA against the PIK3R4 gene significantly decreased the expression levels of PIK3R4 and the autophagy-related proteins p62 and LC3. Additionally, in vivo experiments revealed that the PIK3R4 protein was extensively expressed in the anterior horn, posterior horn, central canal, and areas surrounding the central canal in cervical, thoracic, and lumbar segments of the spinal cord in adult mice. PIK3R4 protein was mainly expressed in the neurons within the spinal lumbar segments. PIK3R4 and p62 expression levels were significantly decreased at both the pre-onset and onset stages of ALS disease in Tg(SOD1*G93A)1Gur mice compared with control mice, but these proteins were markedly increased at the progression stage. LC3 protein expression did not change during progression of ALS. These findings suggest that PIK3R4 likely participates in the prevention of ALS progression. This study was approved by the Ethics Committee for Animal Care and Use of Jiangxi Provincial People's Hospital, Affiliated People's Hospital of Nanchang University (approval No. 2020025) on March 26, 2020.

DEF8 and Autophagy-Associated Genes Are Altered in Mild Cognitive Impairment, Probable Alzheimer’s Disease Patients, and a Transgenic Model of the Disease

Background: Disturbances in the autophagy/endolysosomal systems are proposed as early signatures of Alzheimer’s disease (AD). However, few studies are available concerning autophagy gene expression in AD patients. Objective: To explore the differential expression of classical genes involved in the autophagy pathway, among them a less characterized one, DEF8 (Differentially expressed in FDCP 8), initially considered a Rubicon family member, in peripheral blood mononuclear cells (PBMCs) from individuals with mild cognitive impairment (MCI) and probable AD (pAD) and correlate the results with the expression of DEF8 in the brain of 5xFAD mice. Method: By real-time PCR and flow cytometry, we evaluated autophagy genes levels in PBMCs from MCI and pAD patients. We evaluated DEF8 levels and its localization in brain samples of the 5xFAD mice by real-time PCR, western blot, and immunofluorescence. Results: Transcriptional levels of DEF8 were significantly reduced in PBMCs of MCI and pAD patients compared with healthy donors, correlating with the MoCA and MoCA-MIS cognitive tests scores. DEF8 protein levels were increased in lymphocytes from MCI but not pAD, compared to controls. In the case of brain samples from 5xFAD mice, we observed a reduced mRNA expression and augmented protein levels in 5xFAD compared to age-matched wild-type mice. DEF8 presented a neuronal localization. Conclusion: DEF8, a protein proposed to act at the final step of the autophagy/endolysosomal pathway, is differentially expressed in PBMCs of MCI and pAD and neurons of 5xFAD mice. These results suggest a potential role for DEF8 in the pathophysiology of AD.

Advances in protein-protein interaction network analysis for Parkinson's disease

Protein-protein interactions (PPIs) are a key component of the subcellular molecular networks which enable cells to function. Due to their importance in homeostasis, alterations to the networks can be detrimental, leading to cellular dysfunction and ultimately disease states. Parkinson's disease (PD) is a progressive neurodegenerative condition with multifactorial aetiology, spanning genetic variation and environmental modifiers. At a molecular and systems level, the characterisation of PD is the focus of extensive research, largely due to an unmet need for disease modifying therapies. PPI network analysis approaches are a valuable strategy to accelerate our understanding of the molecular crosstalk and biological processes underlying PD pathogenesis, especially due to the complex nature of this disease. In this review, we describe the utility of PPI network approaches in modelling complex systems, focusing on previous work in PD research. We discuss four principal strategies for using PPI network approaches: to infer PD related cellular functions, pathways and novel genes; to support genomics studies; to study the interactome of single PD related genes; and to compare the molecular basis of PD to other neurodegenerative disorders. This is an evolving area of research which is likely to further expand as omics data generation and availability increase. These approaches complement and bridge-the-gap between genetics and functional research to inform future investigations. In this review we outline several limitations that require consideration, acknowledging that ongoing challenges in this field continue to be addressed and the refinement of these approaches will facilitate further advances using PPI network analysis for understanding complex diseases.

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)1

In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.

The neuroprotective effects of activated α7 nicotinic acetylcholine receptor against mutant copper-zinc superoxide dismutase 1-mediated toxicity

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease characterized by the selective and progressive loss of motor neurons. Although many drugs have entered clinical trials, few have shown effectiveness in the treatment of ALS. Other studies have shown that the stimulation of α7 nicotinic acetylcholine receptor (nAChR) can have neuroprotective effects in some models of neurodegenerative disease, as well as prevent glutamate-induced motor neuronal death. However, the effect of α7 nAChR agonists on ALS-associated mutant copper-zinc superoxide dismutase 1 (SOD1) aggregates in motor neurons remains unclear. In the present study, we examined whether α7 nAChR activation had a neuroprotective effect against SOD1^G85R-induced toxicity in a cellular model for ALS. We found that α7 nAChR activation by PNU282987, a selective agonist of α7 nAChR, exhibited significant neuroprotective effects against SOD1^G85R-induced toxicity via the reduction of intracellular protein aggregates. This reduction also correlated with the activation of autophagy through the AMP-activated protein kinase (AMPK)-mammalian target of rapamycin (mTOR) signaling pathway. Furthermore, the activation of α7 nAChRs was found to increase the biogenesis of lysosomes by inducing translocation of the transcription factor EB (TFEB) into the nucleus. These results support the therapeutic potential of α7 nAChR activation in diseases that are characterized by SOD1^G85R aggregates, such as ALS.

RAB39B Deficiency Impairs Learning and Memory Partially Through Compromising Autophagy

RAB39B is located on the X chromosome and encodes the RAB39B protein that belongs to the RAB family. Mutations in RAB39B are known to be associated with X-linked intellectual disability (XLID), Parkinson’s disease, and autism. However, the patho/physiological functions of RAB39B remain largely unknown. In the present study, we established Rab39b knockout (KO) mice, which exhibited overall normal birth rate and morphologies as wild type mice. However, Rab39b deficiency led to reduced anxiety and impaired learning and memory in 2 months old mice. Deletion of Rab39b resulted in impairments of synaptic structures and functions, with reductions in NMDA receptors in the postsynaptic density (PSD). RAB39B deficiency also compromised autophagic flux at basal level, which could be overridden by rapamycin-induced autophagy activation. Further, treatment with rapamycin partially rescued impaired memory and synaptic plasticity in Rab39b KO mice, without affecting the PSD distribution of NMDA receptors. Together, these results suggest that RAB39B plays an important role in regulating both autophagy and synapse formation, and that targeting autophagy may have potential for treating XLID caused by RAB39B loss-of-function mutations.

Homeostatic Roles of the Proteostasis Network in Dendrites

Cellular protein homeostasis, or proteostasis, is indispensable to the survival and function of all cells. Distinct from other cell types, neurons are long-lived, exhibiting architecturally complex and diverse multipolar projection morphologies that can span great distances. These properties present unique demands on proteostatic machinery to dynamically regulate the neuronal proteome in both space and time. Proteostasis is regulated by a distributed network of cellular processes, the proteostasis network (PN), which ensures precise control of protein synthesis, native conformational folding and maintenance, and protein turnover and degradation, collectively safeguarding proteome integrity both under homeostatic conditions and in the contexts of cellular stress, aging, and disease. Dendrites are equipped with distributed cellular machinery for protein synthesis and turnover, including dendritically trafficked ribosomes, chaperones, and autophagosomes. The PN can be subdivided into an adaptive network of three major functional pathways that synergistically govern protein quality control through the action of (1) protein synthesis machinery; (2) maintenance mechanisms including molecular chaperones involved in protein folding; and (3) degradative pathways (e.g., Ubiquitin-Proteasome System (UPS), endolysosomal pathway, and autophagy. Perturbations in any of the three arms of proteostasis can have dramatic effects on neurons, especially on their dendrites, which require tightly controlled homeostasis for proper development and maintenance. Moreover, the critical importance of the PN as a cell surveillance system against protein dyshomeostasis has been highlighted by extensive work demonstrating that the aggregation and/or failure to clear aggregated proteins figures centrally in many neurological disorders. While these studies demonstrate the relevance of derangements in proteostasis to human neurological disease, here we mainly review recent literature on homeostatic developmental roles the PN machinery plays in the establishment, maintenance, and plasticity of stable and dynamic dendritic arbors. Beyond basic housekeeping functions, we consider roles of PN machinery in protein quality control mechanisms linked to dendritic plasticity (e.g., dendritic spine remodeling during LTP); cell-type specificity; dendritic morphogenesis; and dendritic pruning.

Pharmacological Tools to Modulate Autophagy in Neurodegenerative Diseases

Considerable evidences suggest a link between autophagy dysfunction, protein aggregation, and neurodegenerative diseases. Given that autophagy is a conserved intracellular housekeeping process, modulation of autophagy flux in various model organisms have highlighted its importance for maintaining proteostasis. In postmitotic cells such as neurons, compromised autophagy is sufficient to cause accumulation of ubiquitinated aggregates, neuronal dysfunction, degeneration, and loss of motor coordination-all hallmarks of neurodegenerative diseases. Reciprocally, enhanced autophagy flux augments cellular and organismal health, in addition to extending life span. These genetic studies not-withstanding a plethora of small molecule modulators of autophagy flux have been reported that alleviate disease symptoms in models of neurodegenerative diseases. This review summarizes the potential of such molecules to be, perhaps, one of the first autophagy drugs for treating these currently incurable diseases.

Implications of Selective Autophagy Dysfunction for ALS Pathology

Amyotrophic lateral sclerosis (ALS) is a lethal neurodegenerative disorder that progressively affects motor neurons in the brain and spinal cord. Due to the biological complexity of the disease, its etiology remains unknown. Several cellular mechanisms involved in the neurodegenerative process in ALS have been found, including the loss of RNA and protein homeostasis, as well as mitochondrial dysfunction. Insoluble protein aggregates, damaged mitochondria, and stress granules, which contain RNA and protein components, are recognized and degraded by the autophagy machinery in a process known as selective autophagy. Autophagy is a highly dynamic process whose dysregulation has now been associated with neurodegenerative diseases, including ALS, by numerous studies. In ALS, the autophagy process has been found deregulated in both familial and sporadic cases of the disease. Likewise, mutations in genes coding for proteins involved in the autophagy machinery have been reported in ALS patients, including selective autophagy receptors. In this review, we focus on the role of selective autophagy in ALS pathology.

Network Analysis for Complex Neurodegenerative Diseases

Purpose of Review

Biomedicine is witnessing a paradigm shift in the way complex disorders are investigated. In particular, the need for big data interpretation has led to the development of pipelines that require the cooperation of different fields of expertise, including medicine, functional biology, informatics, mathematics and systems biology. This review sits at the crossroad of different disciplines and surveys the recent developments in the use of graph theory (in the form of network analysis) to interpret large and different datasets in the context of complex neurodegenerative diseases. It aims at a professional audience with different backgrounds.

Recent Findings

Biomedicine has entered the era of big data, and this is actively changing the way we approach and perform research. The increase in size and power of biomedical studies has led to the establishment of multi-centre, international working groups coordinating open access platforms for data generation, storage and analysis. Particularly, pipelines for data interpretation are under development, and network analysis is gaining momentum since it represents a versatile approach to study complex systems made of interconnected multiple players.

Summary

We will describe the era of big data in biomedicine and survey the major freely accessible multi-omics datasets. We will then introduce the principles of graph theory and provide examples of network analysis applied to the interpretation of complex neurodegenerative disorders.