Effect of the Synaptic Plasma Membrane on the Stability of the Amyloid Precursor Protein Homodimer

Cholesterol and Lipid Rafts in the Biogenesis of Amyloid-β Protein and Alzheimer's Disease

Cholesterol has been conjectured to be a modulator of the amyloid cascade, the mechanism that produces the amyloid-β (Aβ) peptides implicated in the onset of Alzheimer's disease. We propose that cholesterol impacts the genesis of Aβ not through direct interaction with proteins in the bilayer, but indirectly by inducing the liquid-ordered phase and accompanying liquid-liquid phase separations, which partition proteins in the amyloid cascade to different lipid domains and ultimately to different endocytotic pathways. We explore the full process of Aβ genesis in the context of liquid-ordered phases induced by cholesterol, including protein partitioning into lipid domains, mechanisms of endocytosis experienced by lipid domains and secretases, and pH-controlled activation of amyloid precursor protein secretases in specific endocytotic environments. Outstanding questions on the essential role of cholesterol in the amyloid cascade are identified for future studies.

Impact of A2T and D23N mutations on C99 homodimer conformations

The proteolytic cleavage of C99 by γ-secretase is the last step in the production of amyloid-β (Aβ) peptides. Previous studies have shown that membrane lipid composition, cholesterol concentration, and mutation in the transmembrane helix modified the structures and fluctuations of C99. In this study, we performed atomistic molecular dynamics simulations of the homodimer of the 55-residue congener of the C-terminal domain of the amyloid protein precursor, C99(1-55), in a POPC-cholesterol lipid bilayer, and we compared the conformational ensemble of WT sequence to those of the A2T and D23N variants. These mutations are particularly interesting as the protective Alzheimer's disease (AD) A2T mutation is known to decrease Aβ production, whereas the early onset AD D23N mutation does not affect Aβ production. We found noticeable differences in the structural ensembles of the three sequences. In particular, A2T varies from both WT and D23N by having long-range effects on the population of the extracellular justamembrane helix, the interface between the G29xxx-G33xxx-G37 motifs and the fluctuations of the transmembrane helical topologies.

CLoNe: automated clustering based on local density neighborhoods for application to biomolecular structural ensembles

Motivation

Proteins are intrinsically dynamic entities. Flexibility sampling methods, such as molecular dynamics or those arising from integrative modeling strategies, are now commonplace and enable the study of molecular conformational landscapes in many contexts. Resulting structural ensembles increase in size as technological and algorithmic advancements take place, making their analysis increasingly demanding. In this regard, cluster analysis remains a go-to approach for their classification. However, many state-of-the-art algorithms are restricted to specific cluster properties. Combined with tedious parameter fine-tuning, cluster analysis of protein structural ensembles suffers from the lack of a generally applicable and easy to use clustering scheme.

Results

We present CLoNe, an original Python-based clustering scheme that builds on the Density Peaks algorithm of Rodriguez and Laio. CLoNe relies on a probabilistic analysis of local density distributions derived from nearest neighbors to find relevant clusters regardless of cluster shape, size, distribution and amount. We show its capabilities on many toy datasets with properties otherwise dividing state-of-the-art approaches and improves on the original algorithm in key aspects. Applied to structural ensembles, CLoNe was able to extract meaningful conformations from membrane binding events and ligand-binding pocket opening as well as identify dominant dimerization motifs or inter-domain organization. CLoNe additionally saves clusters as individual trajectories for further analysis and provides scripts for automated use with molecular visualization software.

Availability and implementation

www.epfl.ch/labs/lbm/resources, github.com/LBM-EPFL/CLoNe.

Supplementary information

Supplementary data are available at Bioinformatics online.

The C99 domain of the amyloid precursor protein resides in the disordered membrane phase

Processing of the amyloid precursor protein (APP) via the amyloidogenic pathway is associated with the etiology of Alzheimer's disease. The cleavage of APP by β-secretase to generate the transmembrane 99-residue C-terminal fragment (C99) and subsequent processing of C99 by γ-secretase to yield amyloid-β (Aβ) peptides are essential steps in this pathway. Biochemical evidence suggests that amyloidogenic processing of C99 occurs in cholesterol- and sphingolipid-enriched liquid-ordered phase membrane rafts. However, direct evidence that C99 preferentially associates with these rafts has remained elusive. Here, we tested this by quantifying the affinity of C99-GFP for raft domains in cell-derived giant plasma membrane vesicles (GPMVs). We found that C99 was essentially excluded from ordered domains in vesicles from HeLa cells, undifferentiated SH-SY5Y cells, or SH-SY5Y-derived neurons; instead, ∼90% of C99 partitioned into disordered domains. The strong association of C99 with disordered domains occurred independently of its cholesterol-binding activity or homodimerization, or of the presence of the familial Alzheimer disease Arctic mutation (APP E693G). Finally, through biochemical studies we confirmed previous results, which showed that C99 is processed in the plasma membrane by α-secretase, in addition to the well-known γ-secretase. These findings suggest that C99 itself lacks an intrinsic affinity for raft domains, implying that either i) amyloidogenic processing of the protein occurs in disordered regions of the membrane, ii) processing involves a marginal subpopulation of C99 found in rafts, or iii) as-yet-unidentified protein-protein interactions with C99 in living cells drive this protein into membrane rafts to promote its cleavage therein.

Bicelles Rich in both Sphingolipids and Cholesterol and Their Use in Studies of Membrane Proteins

How the distinctive lipid composition of mammalian plasma membranes impacts membrane protein structure is largely unexplored, partly because of the dearth of isotropic model membrane systems that contain abundant sphingolipids and cholesterol. This gap is addressed by showing that sphingomyelin and cholesterol-rich (SCOR) lipid mixtures with phosphatidylcholine can be cosolubilized by n-dodecyl-β-melibioside to form bicelles. Small-angle X-ray and neutron scattering, as well as cryo-electron microscopy, demonstrate that these assemblies are stable over a wide range of conditions and exhibit the bilayered-disc morphology of ideal bicelles even at low lipid-to-detergent mole ratios. SCOR bicelles are shown to be compatible with a wide array of experimental techniques, as applied to the transmembrane human amyloid precursor C99 protein in this medium. These studies reveal an equilibrium between low-order oligomer structures that differ significantly from previous experimental structures of C99, providing an example of how ordered membranes alter membrane protein structure.

Targeting γ-secretase triggers the selective enrichment of oligomeric APP-CTFs in brain extracellular vesicles from Alzheimer cell and mouse models

BACKGROUND

We recently demonstrated an endolysosomal accumulation of the β-secretase-derived APP C-terminal fragment (CTF) C99 in brains of Alzheimer disease (AD) mouse models. Moreover, we showed that the treatment with the γ-secretase inhibitor (D6) led to further increased endolysosomal APP-CTF levels, but also revealed extracellular APP-CTF-associated immunostaining. We here hypothesized that this latter staining could reflect extracellular vesicle (EV)-associated APP-CTFs and aimed to characterize these γ-secretase inhibitor-induced APP-CTFs.

METHODS

EVs were purified from cell media or mouse brains from vehicle- or D6-treated C99 or APPswedish expressing cells/mice and analyzed for APP-CTFs by immunoblot. Combined pharmacological, immunological and genetic approaches (presenilin invalidation and C99 dimerization mutants (GXXXG)) were used to characterize vesicle-containing APP-CTFs. Subcellular APP-CTF localization was determined by immunocytochemistry.

RESULTS

Purified EVs from both AD cell or mouse models were enriched in APP-CTFs as compared to EVs from control cells/brains. Surprisingly, EVs from D6-treated cells not only displayed increased C99 and C99-derived C83 levels but also higher molecular weight (HMW) APP-CTF-immunoreactivities that were hardly detectable in whole cell extracts. Accordingly, the intracellular levels of HMW APP-CTFs were amplified by the exosomal inhibitor GW4869. By combined pharmacological, immunological and genetic approaches, we established that these HMW APP-CTFs correspond to oligomeric APP-CTFs composed of C99 and/or C83. Immunocytochemical analysis showed that monomers were localized mainly to the trans-Golgi network, whereas oligomers were confined to endosomes and lysosomes, thus providing an anatomical support for the selective recovery of HMW APP-CTFs in EVs. The D6-induced APP-CTF oligomerization and subcellular mislocalization was indeed due to γ-secretase blockade, since it similarly occurred in presenilin-deficient fibroblasts. Further, our data proposed that besides favoring APP-CTF oligomerization by preventing C99 proteolysis, γ-secretase inhibiton also led to a defective SorLA-mediated retrograde transport of HMW APP-CTFs from endosomal compartments to the TGN.

CONCLUSIONS

This is the first study to demonstrate the presence of oligomeric APP-CTFs in AD mouse models, the levels of which are selectively enriched in endolysosomal compartments including exosomes and amplified by γ-secretase inhibition. Future studies should evaluate the putative contribution of these exosome-associated APP-CTFs in AD onset, progression and spreading.

Structural Investigation of Human Prolactin Receptor Transmembrane Domain Homodimerization in a Membrane Environment through Multiscale Simulations

It is well established that prolactin (PRL) and its receptor (PRLR) are associated with hundreds of biological functions. They have been postulated to be linked to breast and prostate cancers, and PRLR signaling has attracted considerable medical and pharmaceutical interest in the development of compounds targeting PRLR. Dimerization of the receptor through its transmembrane (TM) domain is a key step for understanding its signaling and related issues. Our multiscale simulation results revealed that its TM domain can form dimers in a membrane environment with distinct states stabilized by different residue motifs. On the basis of the simulated data, an activation mechanism of PRL with the importance of two symmetrical tryptophan residues was proposed in detail to determine the conformational change of its receptor, which is essential for signal transduction. The better knowledge of PRLR structure and its protein-protein interaction can considerably contribute to a further understanding of PRLR signaling action and thereby help to develop some new PRLR signaling-based strategies for PRL-related diseases.

Exploring the impact of proteins on the line tension of a phase-separating ternary lipid mixture

The separation of lipid mixtures into thermodynamically stable phase-separated domains is dependent on lipid composition, temperature, and system size. Using molecular dynamics simulations, the line tension between thermodynamically stable lipid domains formed from ternary mixtures of di-C16:0 PC:di-C18:2 PC:cholesterol at 40:40:20 mol. % ratio was investigated via two theoretical approaches. The line tension was found to be 3.1 ± 0.2 pN by capillary wave theory and 4.7 ± 3.7 pN by pressure tensor anisotropy approaches for coarse-grained models based on the Martini force field. Using an all-atom model of the lipid membrane based on the CHARMM36 force field, the line tension was found to be 3.6 ± 0.9 pN using capillary wave theory and 1.8 ± 2.2 pN using pressure anisotropy approaches. The discrepancy between estimates of the line tension based on capillary wave theory and pressure tensor anisotropy methods is discussed. Inclusion of protein in Martini membrane lipid mixtures was found to reduce the line tension by 25%-35% as calculated by the capillary wave theory approach. To further understand and predict the behavior of proteins in phase-separated membranes, we have formulated an analytical Flory-Huggins model and parameterized it against the simulation results. Taken together these results suggest a general role for proteins in reducing the thermodynamic cost associated with domain formation in lipid mixtures and quantifies the thermodynamic driving force promoting the association of proteins to domain interfaces.

Emerging Diversity in Lipid-Protein Interactions

Membrane lipids interact with proteins in a variety of ways, ranging from providing a stable membrane environment for proteins to being embedded in to detailed roles in complicated and well-regulated protein functions. Experimental and computational advances are converging in a rapidly expanding research area of lipid-protein interactions. Experimentally, the database of high-resolution membrane protein structures is growing, as are capabilities to identify the complex lipid composition of different membranes, to probe the challenging time and length scales of lipid-protein interactions, and to link lipid-protein interactions to protein function in a variety of proteins. Computationally, more accurate membrane models and more powerful computers now enable a detailed look at lipid-protein interactions and increasing overlap with experimental observations for validation and joint interpretation of simulation and experiment. Here we review papers that use computational approaches to study detailed lipid-protein interactions, together with brief experimental and physiological contexts, aiming at comprehensive coverage of simulation papers in the last five years. Overall, a complex picture of lipid-protein interactions emerges, through a range of mechanisms including modulation of the physical properties of the lipid environment, detailed chemical interactions between lipids and proteins, and key functional roles of very specific lipids binding to well-defined binding sites on proteins. Computationally, despite important limitations, molecular dynamics simulations with current computer power and theoretical models are now in an excellent position to answer detailed questions about lipid-protein interactions.

Structure of APP-C991-99 and implications for role of extra-membrane domains in function and oligomerization

The 99 amino acid C-terminal fragment of Amyloid Precursor Protein APP-C99 (C99) is cleaved by γ-secretase to form Aβ peptide, which plays a critical role in the etiology of Alzheimer's Disease (AD). The structure of C99 consists of a single transmembrane domain flanked by intra and intercellular domains. While the structure of the transmembrane domain has been well characterized, little is known about the structure of the flanking domains and their role in C99 processing by γ-secretase. To gain insight into the structure of full-length C99, REMD simulations were performed for monomeric C99 in model membranes of varying thickness. We find equilibrium ensembles of C99 from simulation agree with experimentally-inferred residue insertion depths and protein backbone chemical shifts. In thin membranes, the transmembrane domain structure is correlated with extra-membrane structural states and the extra-membrane domain structural states become less correlated to each other. Mean and variance of the transmembrane and G₃₇G₃₈ hinge angles are found to increase with thinning membrane. The N-terminus of C99 forms β-strands that may seed aggregation of Aβ on the membrane surface, promoting amyloid formation. In thicker membranes the N-terminus forms α-helices that interact with the nicastrin domain of γ-secretase. The C-terminus of C99 becomes more α-helical as the membrane thickens, forming structures that may be suitable for binding by cytoplasmic proteins, while C-terminal residues essential to cytotoxic function become α-helical as the membrane thins. The heterogeneous but discrete extra-membrane domain states analyzed here open the path to new investigations of the role of C99 structure and membrane in amyloidogenesis. This article is part of a Special Issue entitled: Protein Aggregation and Misfolding at the Cell Membrane Interface edited by Ayyalusamy Ramamoorthy.

Recruitment of the amyloid precursor protein by γ-secretase at the synaptic plasma membrane

Γ-secretase is a membrane-embedded protease that cleaves single transmembrane helical domains of various integral membrane proteins. The amyloid precursor protein (APP) is an important substrate due to its pathological relevance to Alzheimer's disease. The mechanism of the cleavage of APP by γ-secretase that leads to accumulation of Alzheimer's disease causing amyloid-β (Aβ) is still unknown. Coarse-grained molecular dynamics simulations in this study reveal initial lipids raft formation near the catalytic site of γ-secretase as well as changes in dynamic behavior of γ-secretase once interacting with APP. The results suggest a precursor of the APP binding mode and hint at conformational changes of γ-secretase in the nicastrin (NCT) domain upon APP binding.

Signal Sensing and Transduction by Histidine Kinases as Unveiled through Studies on a Temperature Sensor

Histidine kinases (HK) are the sensory proteins of two-component systems, responsible for a large fraction of bacterial responses to stimuli and environmental changes. Prototypical HKs are membrane-bound proteins that phosphorylate cognate response regulator proteins in the cytoplasm upon signal detection in the membrane or periplasm. HKs stand as potential drug targets but also constitute fascinating systems for studying proteins at work, specifically regarding the chemistry and mechanics of signal detection, transduction through the membrane, and regulation of catalytic outputs. In this Account, we focus on Bacillus subtilis DesK, a membrane-bound HK part of a two-component system that maintains appropriate membrane fluidity at low growth temperatures. Unlike most HKs, DesK has no extracytoplasmic signal-sensing domains; instead, sensing is carried out by 10 transmembrane helices (coming from two protomers) arranged in an unknown structure. The fifth transmembrane helix from each protomer connects, without any of the intermediate domains found in other HKs, into the dimerization and histidine phosphotransfer (DHp) domain located in the cytoplasm, which is followed by the ATP-binding domains (ABD). Throughout the years, genetic, biochemical, structural, and computational studies on wild-type, mutant, and truncated versions of DesK allowed us to dissect several aspects of DesK's functioning, pushing forward a more general understanding of its own structure/function relationships as well as those of other HKs. We have shown that the sensing mechanism is rooted in temperature-dependent membrane properties, most likely a combination of thickness, fluidity, and water permeability, and we have proposed possible mechanisms by which DesK senses these properties and transduces the signals. X-ray structures and computational models have revealed structural features of TM and cytoplasmic regions in DesK's kinase- and phosphatase-competent states. Biochemical and genetic experiments and molecular simulations further showed that reversible formation of a two-helix coiled coil in the fifth TM segment and the N-terminus of the cytoplasmic domain is essential for the sensing and signal transduction mechanisms. Together with other structural and functional works, the emerging picture suggests that diverse HKs possess distinct sensing and transduction mechanisms but share as rather general features (i) a symmetric phosphatase state and an asymmetric kinase state and (ii) similar functional outputs on the conserved DHp and ABD domains, achieved through different mechanisms that depend on the nature of the initial signal. We here advance (iii) an important role for TM prolines in transducing the initial signals to the cytoplasmic coiled coils, based on simulations of DesK's TM helices and our previous work on a related HK, PhoQ. Lastly, evidence for DesK, PhoQ, BvgS, and DctB HKs shows that (iv) overall catalytic output is tuned by a delicate balance between hydration potentials, coiled coil stability, and exposure of hydrophobic surface patches at their cytoplasmic coiled coils and at the N-terminal and C-terminal sides of their TM helices. This balance is so delicate that small perturbations, either physiological signals or induced by mutations, lead to large remodeling of the underlying conformational landscape achieving clear-cut changes in catalytic output, mirroring the required response speed of these systems for proper biological function.

Protein post-translational modifications: In silico prediction tools and molecular modeling

Post-translational modifications (PTMs) occur in almost all proteins and play an important role in numerous biological processes by significantly affecting proteins' structure and dynamics. Several computational approaches have been developed to study PTMs (e.g., phosphorylation, sumoylation or palmitoylation) showing the importance of these techniques in predicting modified sites that can be further investigated with experimental approaches. In this review, we summarize some of the available online platforms and their contribution in the study of PTMs. Moreover, we discuss the emerging capabilities of molecular modeling and simulation that are able to complement these bioinformatics methods, providing deeper molecular insights into the biological function of post-translational modified proteins.

Specific Binding of Cholesterol to C99 Domain of Amyloid Precursor Protein Depends Critically on Charge State of Protein

Recent NMR chemical shift measurements of the 99 residue C-terminal fragment of amyloid precursor protein (APP-C99) in the presence of cholesterol provide evidence of binary complex formation between C99 and cholesterol in membrane mimetic environments. It has also been observed that the production of Aβ protein is enhanced under conditions of high cholesterol concentration. In this study, we investigated the impact of the charge state of C99 on the structure and stability of the C99-cholesterol complex. We observed that the binding of C99 to cholesterol depends critically on the charge state of Glu 693 (E22) and Asp 694 (D23). Evaluation of the pKa values of the Asp and Glu side chains suggests that these residues may be predominantly neutral in existing experimental observations of a stable C99-cholesterol complex at lower pH (characteristic of the endosomal environment), while binding is destabilized near neutral pH (characteristic of the cytoplasm). These observations suggest that specific binding of cholesterol to C99 is a sensitive function of the pH encountered in vivo, with key E22 and D23 residues serving as a "pH switch" controlling C99-cholesterol binding.