Bioinformatic analysis of the human brain extracellular matrix proteome in neurodegenerative disorders

A collaborative network analysis for the interpretation of transcriptomics data in Huntington's disease

Rare diseases may affect the quality of life of patients and be life-threatening. Therapeutic opportunities are often limited, in part because of the lack of understanding of the molecular mechanisms underlying these diseases. This can be ascribed to the low prevalence of rare diseases and therefore the lower sample sizes available for research. A way to overcome this is to integrate experimental rare disease data with prior knowledge using network-based methods. Taking this one step further, we hypothesized that combining and analyzing the results from multiple network-based methods could provide data-driven hypotheses of pathogenic mechanisms from multiple perspectives.We analyzed a Huntington's disease transcriptomics dataset using six network-based methods in a collaborative way. These methods either inherently reported enriched annotation terms or their results were fed into enrichment analyses. The resulting significantly enriched Reactome pathways were then summarized using the ontological hierarchy which allowed the integration and interpretation of outputs from multiple methods. Among the resulting enriched pathways, there are pathways that have been shown previously to be involved in Huntington's disease and pathways whose direct contribution to disease pathogenesis remains unclear and requires further investigation.In summary, our study shows that collaborative network analysis approaches are well-suited to study rare diseases, as they provide hypotheses for pathogenic mechanisms from multiple perspectives. Applying different methods to the same case study can uncover different disease mechanisms that would not be apparent with the application of a single method.

A Systematic Review of Extracellular Matrix-Related Alterations in Parkinson's Disease

The role of the extracellular matrix (ECM) in Parkinson's disease (PD) is not well understood, even though it is critical for neuronal structure and signaling. This systematic review identified the top deregulated ECM-related pathways in studies that used gene set enrichment analyses (GSEA) to document transcriptomic, proteomic, or genomic alterations in PD. PubMed and Google scholar were searched for transcriptomics, proteomics, or genomics studies that employed GSEA on data from PD tissues or cells and reported ECM-related pathways among the top-10 most enriched versus controls. Twenty-seven studies were included, two of which used multiple omics analyses. Transcriptomics and proteomics studies were conducted on a variety of tissue and cell types. Of the 17 transcriptomics studies (16 data sets), 13 identified one or more adhesion pathways in the top-10 deregulated gene sets or pathways, primarily related to cell adhesion and focal adhesion. Among the 8 proteomics studies, 5 identified altered overarching ECM gene sets or pathways among the top 10. Among the 4 genomics studies, 3 identified focal adhesion pathways among the top 10. The findings summarized here suggest that ECM organization/structure and cell adhesion (particularly focal adhesion) are altered in PD and should be the focus of future studies.

Matrisome Transcriptome Dynamics during Tissue Aging

The extracellular matrix (ECM) is a complex three-dimensional network of macromolecules that provides structural support for the cells and plays a significant role in tissue homeostasis and repair. Growing evidence indicates that dysregulation of ECM remodeling contributes to various pathological conditions in the body, including age-associated diseases. In this work, gene expression data of normal human tissues obtained from the Genotype-Tissue Expression project, as well as data from MatrisomeDB 2.0, the ECM-protein knowledge database, are used to estimate the age-dependent matrisome transcriptome dynamics in the blood, heart, brain, liver, kidneys, lungs, and muscle. Differential gene expression (DE) analysis revealed dozens of matrisome genes encoding both structural elements of the ECM and ECM-associated proteins, which had a tissue-specific expression profile with age. Among common DE genes that changed expression with age in at least three tissues, COL18A1, MFAP1, IGFBP7, AEBP1, LTBP2, LTBP4, LG14, EFEMP1, PRELP, BGN, FAM20B, CTSC, CTSS, and CLEC2B were observed. The findings of the study also reveal that there are sex-specific alterations during aging in the matrisome gene expression. Taken together, the results obtained in this work may help in understanding the role of the ECM in tissue aging and might prove valuable for the future development of the field of ECM research in general.

Exploring the properties and potential of the neural extracellular matrix for next-generation regenerative therapies

The extracellular matrix (ECM) is a dynamic and complex network of proteins and molecules that surrounds cells and tissues in the nervous system and orchestrates a myriad of biological functions. This review carefully examines the diverse interactions between cells and the ECM, as well as the transformative chemical and physical changes that the ECM undergoes during neural development, aging, and disease. These transformations play a pivotal role in shaping tissue morphogenesis and neural activity, thereby influencing the functionality of the central nervous system (CNS). In our comprehensive review, we describe the diverse behaviors of the CNS ECM in different physiological and pathological scenarios and explore the unique properties that make ECM-based strategies attractive for CNS repair and regeneration. Addressing the challenges of scalability, variability, and integration with host tissues, we review how advanced natural, synthetic, and combinatorial matrix approaches enhance biocompatibility, mechanical properties, and functional recovery. Overall, this review highlights the potential of decellularized ECM as a powerful tool for CNS modeling and regenerative purposes and sets the stage for future research in this exciting field. This article is categorized under: Implantable Materials and Surgical Technologies > Nanotechnology in Tissue Repair and Replacement Therapeutic Approaches and Drug Discovery > Nanomedicine for Neurological Disease Implantable Materials and Surgical Technologies > Nanomaterials and Implants.

Exposure to environmental airborne particulate matter caused wide-ranged transcriptional changes and accelerated Alzheimer's-related pathology: A mouse study

Air pollution poses a significant threat to human health, though a clear understanding of its mechanism remains elusive. In this study, we sought to better understand the effects of various sized particulate matter from polluted air on Alzheimer's disease (AD) development using an AD mouse model. We exposed transgenic Alzheimer's mice in their prodromic stage to different sized particulate matter (PM), with filtered clean air as control. After 3 or 6 months of exposure, mouse brains were harvested and analyzed. RNA-seq analysis showed that various PM have differential effects on the brain transcriptome, and these effects seemed to correlate with PM size. Many genes and pathways were affected after PM exposure. Among them, we found a strong activation in mRNA Nonsense Mediated Decay pathway, an inhibition in pathways related to transcription, neurogenesis and survival signaling as well as angiogenesis, and a dramatic downregulation of collagens. Although we did not detect any extracellular Aβ plaques, immunostaining revealed that both intracellular Aβ1-42 and phospho-Tau levels were increased in various PM exposure conditions compared to the clean air control. NanoString GeoMx analysis demonstrated a remarkable activation of immune responses in the PM exposed mouse brain. Surprisingly, our data also indicated a strong activation of various tumor suppressors including RB1, CDKN1A/p21 and CDKN2A/p16. Collectively, our data demonstrated that exposure to airborne PM caused a profound transcriptional dysregulation and accelerated Alzheimer's-related pathology.

Mass spectrometry methods for analysis of extracellular matrix components in neurological diseases

The brain extracellular matrix (ECM) is a highly glycosylated environment and plays important roles in many processes including cell communication, growth factor binding, and scaffolding. The formation of structures such as perineuronal nets (PNNs) is critical in neuroprotection and neural plasticity, and the formation of molecular networks is dependent in part on glycans. The ECM is also implicated in the neuropathophysiology of disorders such as Alzheimer's disease (AD), Parkinson's disease (PD), and Schizophrenia (SZ). As such, it is of interest to understand both the proteomic and glycomic makeup of healthy and diseased brain ECM. Further, there is a growing need for site-specific glycoproteomic information. Over the past decade, sample preparation, mass spectrometry, and bioinformatic methods have been developed and refined to provide comprehensive information about the glycoproteome. Core ECM molecules including versican, hyaluronan and proteoglycan link proteins, and tenascin are dysregulated in AD, PD, and SZ. Glycomic changes such as differential sialylation, sulfation, and branching are also associated with neurodegeneration. A more thorough understanding of the ECM and its proteomic, glycomic, and glycoproteomic changes in brain diseases may provide pathways to new therapeutic options.

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.

Proteomics of the astrocyte secretome reveals changes in their response to soluble oligomeric Aβ

Astrocytes associate with amyloid plaques in Alzheimer's disease (AD). Astrocytes react to changes in the brain environment, including increasing concentrations of amyloid-β (Aβ). However, the precise response of astrocytes to soluble small Aβ oligomers at concentrations similar to those present in the human brain has not been addressed. In this study, we exposed astrocytes to media from neurons that express the human amyloid precursor protein (APP) transgene with the double Swedish mutation (APPSwe), and which contains APP-derived fragments, including soluble human Aβ oligomers. We then used proteomics to investigate changes in the astrocyte secretome. Our data show dysregulated secretion of astrocytic proteins involved in the extracellular matrix and cytoskeletal organization and increase secretion of proteins involved in oxidative stress responses and those with chaperone activity. Several of these proteins have been identified in previous transcriptomic and proteomic studies using brain tissue from human AD and cerebrospinal fluid (CSF). Our work highlights the relevance of studying astrocyte secretion to understand the brain response to AD pathology and the potential use of these proteins as biomarkers for the disease.

The link between neuroinflammation and the neurovascular unit in synucleinopathies

The neurovascular unit (NVU) is composed of vascular cells, glial cells, and neurons. As a fundamental functional module in the central nervous system, the NVU maintains homeostasis in the microenvironment and the integrity of the blood-brain barrier. Disruption of the NVU and interactions among its components are involved in the pathophysiology of synucleinopathies, which are characterized by the pathological accumulation of α-synuclein. Neuroinflammation contributes to the pathophysiology of synucleinopathies, including Parkinson's disease, multiple system atrophy, and dementia with Lewy bodies. This review aims to summarize the neuroinflammatory response of glial cells and vascular cells in the NVU. We also review neuroinflammation in the context of the cross-talk between glial cells and vascular cells, between glial cells and pericytes, and between microglia and astroglia. Last, we discuss how α-synuclein affects neuroinflammation and how neuroinflammation influences the aggregation and spread of α-synuclein and analyze different properties of α-synuclein in synucleinopathies.

Message in a Scaffold: Natural Biomaterials for Three-Dimensional (3D) Bioprinting of Human Brain Organoids

Brain organoids are invaluable tools for pathophysiological studies or drug screening, but there are still challenges to overcome in making them more reproducible and relevant. Recent advances in three-dimensional (3D) bioprinting of human neural organoids is an emerging approach that may overcome the limitations of self-organized organoids. It requires the development of optimal hydrogels, and a wealth of research has improved our knowledge about biomaterials both in terms of their intrinsic properties and their relevance on 3D culture of brain cells and tissue. Although biomaterials are rarely biologically neutral, few articles have reviewed their roles on neural cells. We here review the current knowledge on unmodified biomaterials amenable to support 3D bioprinting of neural organoids with a particular interest in their impact on cell homeostasis. Alginate is a particularly suitable bioink base for cell encapsulation. Gelatine is a valuable helper agent for 3D bioprinting due to its viscosity. Collagen, fibrin, hyaluronic acid and laminin provide biological support to adhesion, motility, differentiation or synaptogenesis and optimize the 3D culture of neural cells. Optimization of specialized hydrogels to direct differentiation of stem cells together with an increased resolution in phenotype analysis will further extend the spectrum of possible bioprinted brain disease models.

Age-Related Changes in Extracellular Matrix

Extracellular matrix (ECM) is an extracellular tissue structure that, in addition to mechanical support to the cell, is involved in regulation of many cellular processes, including chemical transport, growth, migration, differentiation, and cell senescence. Age-related changes in the structure and composition of the matrix and increase of ECM stiffness with age affect functioning of many tissues and contribute to the development of various pathological conditions. This review considers age-related changes of ECM in various tissues and organs, in particular, effect of ECM changes on aging is discussed.

3D biocomposite culture enhances differentiation of dopamine-like neurons from SH-SY5Y cells: A model for studying Parkinson's disease phenotypes

Studies of underlying neurodegenerative processes in Parkinson's Disease (PD) have traditionally utilized cell cultures grown on two-dimensional (2D) surfaces. Biomimetic three-dimensional (3D) cell culture platforms have been developed to better emulate features of the brain's natural microenvironment. We here use our bioengineered brain-like tissue model, composed of a silk-hydrogel composite, to study the 3D microenvironment's contributions on the development and performance of dopaminergic-like neurons (DLNs). Compared with 2D culture, SH-SY5Y cells differentiated in 3D microenvironments were enriched for DLNs concomitant with a reduction in proliferative capacity during the neurodevelopmental process. Additionally, the 3D DLN cultures were more sensitive to oxidative stresses elicited by the PD-related neurotoxin 1-methyl-4-phenylpyridinium (MPP). MPP induced transcriptomic profile changes specific to 3D-differentiated DLN cultures, replicating the dysfunction of neuronal signaling pathways and mitochondrial dynamics implicated in PD. Overall, this physiologically-relevant 3D platform resembles a useful tool for studying dopamine neuron biology and interrogating molecular mechanisms underlying neurodegeneration in PD.