Packing Density of the Amyloid Precursor Protein in the Cell Membrane

Celebrating the Birthday of AMPA Receptor Nanodomains: Illuminating the Nanoscale Organization of Excitatory Synapses with 10 Nanocandles

A decade ago, in 2013, and over the course of 4 summer months, three separate observations were reported that each shed light independently on a new molecular organization that fundamentally reshaped our perception of excitatory synaptic transmission (Fukata et al., 2013; MacGillavry et al., 2013; Nair et al., 2013). This discovery unveiled an intricate arrangement of AMPA-type glutamate receptors and their principal scaffolding protein PSD-95, at synapses. This breakthrough was made possible, thanks to advanced super-resolution imaging techniques. It fundamentally changed our understanding of excitatory synaptic architecture and paved the way for a brand-new area of research. In this Progressions article, the primary investigators of the nanoscale organization of synapses have come together to chronicle the tale of their discovery. We recount the initial inquiry that prompted our research, the preceding studies that inspired our work, the technical obstacles that were encountered, and the breakthroughs that were made in the subsequent decade in the realm of nanoscale synaptic transmission. We review the new discoveries made possible by the democratization of super-resolution imaging techniques in the field of excitatory synaptic physiology and architecture, first by the extension to other glutamate receptors and to presynaptic proteins and then by the notion of trans-synaptic organization. After describing the organizational modifications occurring in various pathologies, we discuss briefly the latest technical developments made possible by super-resolution imaging and emerging concepts in synaptic physiology.

Advancements and Practical Considerations for Biophysical Research: Navigating the Challenges and Future of Super-resolution Microscopy

The introduction of super-resolution microscopy (SRM) has significantly advanced our understanding of cellular and molecular dynamics, offering a detailed view previously beyond our reach. Implementing SRM in biophysical research, however, presents numerous challenges. This review addresses the crucial aspects of utilizing SRM effectively, from selecting appropriate fluorophores and preparing samples to analyzing complex data sets. We explore recent technological advancements and methodological improvements that enhance the capabilities of SRM. Emphasizing the integration of SRM with other analytical methods, we aim to overcome inherent limitations and expand the scope of biological insights achievable. By providing a comprehensive guide for choosing the most suitable SRM methods based on specific research objectives, we aim to empower researchers to explore complex biological processes with enhanced precision and clarity, thereby advancing the frontiers of biophysical research.

The transmembrane domain of the amyloid precursor protein is required for anti-amyloidogenic processing by α-secretase ADAM10

Neurotoxic amyloid β-peptides (Aβ) are thought to be a causative agent of Alzheimer's disease in humans. The production of Aβ from amyloid precursor protein (APP) could be diminished by enhancing α-processing; however, the physical interactions between APP and α-secretases are not well understood. In this study, we employed super-resolution light microscopy to examine in cell-free plasma membranes the abundance and association of APP and α-secretases ADAM10 and ADAM17. We found that both secretase molecules localize similarly closely to APP (within ≤ 50 nm). However, when cross-linking APP with antibodies directed against the GFP-tag of APP, in confocal microscopy we observed that only ADAM10 co-aggregated with APP. Furthermore, we mapped the involved protein domain by using APP variants with an exchanged transmembrane segment or lacking cytoplasmic/extracellular domains. We identified that APP's transmembrane domain is required for association with α-secretases and, as analysed by Western Blot, for α-processing. We propose that the APP transmembrane domain interacts either directly or indirectly with ADAM10, but not with ADAM17, explaining the dominant role of ADAM10 in α-processing of APP. Further understanding of this interaction may facilitate the development of a therapeutic strategy based on promoting APP cleavage by α-secretases.

Super-resolution microscopy: a closer look at synaptic dysfunction in Alzheimer disease

The synapse has emerged as a critical neuronal structure in the degenerative process of Alzheimer disease (AD), in which the pathogenic signals of two key players - amyloid-β (Aβ) and tau - converge, thereby causing synaptic dysfunction and cognitive deficits. The synapse presents a dynamic, confined microenvironment in which to explore how key molecules travel, localize, interact and assume different levels of organizational complexity, thereby affecting neuronal function. However, owing to their small size and the diffraction-limited resolution of conventional light microscopic approaches, investigating synaptic structure and dynamics has been challenging. Super-resolution microscopy (SRM) techniques have overcome the resolution barrier and are revolutionizing our quantitative understanding of biological systems in unprecedented spatio-temporal detail. Here we review critical new insights provided by SRM into the molecular architecture and dynamic organization of the synapse and, in particular, the interactions between Aβ and tau in this compartment. We further highlight how SRM can transform our understanding of the molecular pathological mechanisms that underlie AD. The application of SRM for understanding the roles of synapses in AD pathology will provide a stepping stone towards a broader understanding of dysfunction in other subcellular compartments and at cellular and circuit levels in this disease.

Noradrenaline in the aging brain: Promoting cognitive reserve or accelerating Alzheimer's disease?

Many believe that engaging in novel and mentally challenging activities promotes brain health and prevents Alzheimer's disease in later life. However, mental stimulation may also have risks as well as benefits. As neurons release neurotransmitters, they often also release amyloid peptides and tau proteins into the extracellular space. These by-products of neural activity can aggregate into the tau tangle and amyloid plaque signatures of Alzheimer's disease. Over time, more active brain regions accumulate more pathology. Thus, increasing brain activity can have a cost. But the neuromodulator noradrenaline, released during novel and mentally stimulating events, may have some protective effects-as well as some negative effects. Via its inhibitory and excitatory effects on neurons and microglia, noradrenaline sometimes prevents and sometimes accelerates the production and accumulation of amyloid-β and tau in various brain regions. Both α2A- and β-adrenergic receptors influence amyloid-β production and tau hyperphosphorylation. Adrenergic activity also influences clearance of amyloid-β and tau. Furthermore, some findings suggest that Alzheimer's disease increases noradrenergic activity, at least in its early phases. Because older brains clear the by-products of synaptic activity less effectively, increased synaptic activity in the older brain risks accelerating the accumulation of Alzheimer's pathology more than it does in the younger brain.

Alteration in synaptic nanoscale organization dictates amyloidogenic processing in Alzheimer's disease

Despite intuitive insights into differential proteolysis of amyloid precursor protein (APP), the stochasticity behind local product formation through amyloidogenic pathway at individual synapses remain unclear. Here, we show that the major components of amyloidogenic machinery namely, APP and secretases are discretely organized into nanodomains of high local concentration compared to their immediate environment in functional zones of the synapse. Additionally, with the aid of multiple models of Alzheimer's disease (AD), we confirm that this discrete nanoscale chemical map of amyloidogenic machinery is altered at excitatory synapses. Furthermore, we provide realistic models of amyloidogenic processing in unitary vesicles originating from the endocytic zone of excitatory synapses. Thus, we show how an alteration in the stochasticity of synaptic nanoscale organization contributes to the dynamic range of C-terminal fragments β (CTFβ) production, defining the heterogeneity of amyloidogenic processing at individual synapses, leading to long-term synaptic deficits as seen in AD.

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Components of amyloidogenic machinery are organized into nanodomains

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Assembly of nanodomains differs between functional zones of the synapse

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Stochasticity of nanoscale organization dictates dynamic range of APP proteolysis

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Variability in composition of amyloidogenic machinery is associated with AD

Nanoscale rearrangement of APP organization as a therapeutic target for Alzheimer's disease

Despite the importance of canonical processing of Amyloid Precursor Protein at synapses as a major risk factor for the development of Alzheimer's Disease, there have been very little progress on designing effective therapeutic paradigms targeting it. Majority of the drugs developed or under clinical evaluation focus on the clearance of the detrimental proteoforms or secretases involved in the proteolysis of APP. The lack of interventions targeting APP is in part due to the lack of information in understanding the fine organization of APP and the chemical map of its association with subsynaptic functional zones of the synapse. The recent advances to evaluate the molecular organization of synapses allows us to readdress the need for designing tools to target the full-length APP. Here, we describe the potential role of nanoscale segregation of synaptic APP and how this organization influences the local processing of APP in different subsynaptic compartments opening avenues for early intervention strategies. We envision the need to design smart molecules which would interfere with the real-time chemical composition and physical properties of APP at nanoscale. These tools could alter the balance of proteoforms generated and/or enhance the proteolysis by selective secretases to reduce the toxic products formed through amyloidogenic pathway. We believe that such an approach would be rational to treat or delay the onset of neurodegenerative diseases like AD.

Assistance for Folding of Disease-Causing Plasma Membrane Proteins

An extensive catalog of plasma membrane (PM) protein mutations related to phenotypic diseases is associated with incorrect protein folding and/or localization. These impairments, in addition to dysfunction, frequently promote protein aggregation, which can be detrimental to cells. Here, we review PM protein processing, from protein synthesis in the endoplasmic reticulum to delivery to the PM, stressing the main repercussions of processing failures and their physiological consequences in pathologies, and we summarize the recent proposed therapeutic strategies to rescue misassembled proteins through different types of chaperones and/or small molecule drugs that safeguard protein quality control and regulate proteostasis.

Real-time nanoscale organization of amyloid precursor protein

Despite an intuitive understanding of the role of APP in health and disease, there exist few attempts to dissect its molecular localization at excitatory synapses. Though the biochemistry involved in the enzymatic processing of APP is well understood, there is a void in understanding the nonuniformity of the product formation in vivo. Here, we employed multiple paradigms of single molecules and ensemble based nanoscopic imaging to reveal that APP molecules are organized into regulatory nanodomains that are differentially compartmentalized in the functional zones of an excitatory synapse. Furthermore, with the aid of high density single particle tracking, we show that the lateral diffusion of APP in live cells dictates an equilibrium between these nanodomains and their nano-environment, which is affected in a detrimental variant of APP. Additionally, we incorporate this spatio-temporal detail 'in silico' to generate a realistic nanoscale topography of APP in dendrites and synapses. This approach uncovers a nanoscale heterogeneity in the molecular organization of APP, depicting a locus for differential APP processing. This holistic paradigm, to decipher the real-time heterogeneity of the substrate molecules on the nanoscale, could enable us to better evaluate the molecular constraints overcoming the ensemble approaches used traditionally to understand the kinetics of product formation.

The Accuracy of Determining Cluster Size by Analyzing Ripley’s K Function in Single Molecule Localization Microscopy

Ripley’s K function was developed to analyze the spatial distribution characteristics in point pattern analysis, including geography, economics and biomedical research. In biomedical applications, it is popularly used to analyze the clusters of proteins on the cell plasma membrane in single molecule localization microscopy (SMLM), such as photo activated localization microscopy (PALM), stochastic optical reconstruction microscopy (STORM), universal point accumulation imaging in nanoscale topography (uPAINT), etc. Here, by varying the parameters of the simulated clusters on a modeled SMLM image, the effects of cluster size, cluster separation and protein ratio inside/outside the cluster on the accuracy of cluster analysis by analyzing Ripley’s K function were studied. Although the predicted radius of clusters by analyzing Ripley’s K function did not exactly correspond to the actual radius, we suggest the cluster radius could be estimated within a factor of 1.3. Employing peak analysis methods to analyze the experimental epidermal growth factor receptor (EGFR) clusters at fibroblast-like cell lines derived from monkey kidney tissue - COS7 cell surface observed by uPAINT method, the cluster properties were characterized with errors. Our results present quantification of clusters and can be used to enhance the understanding of clusters in SMLM.