bioRxiv Science⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/2024.03.04.583202

The structure of an Amyloid Precursor Protein/talin complex indicates a mechanical basis of Alzheimer's Disease.

Ellis, C.·Ward, N. L.·Rice, M.·Ball, N. J.·Lambert, J.-C.·Chapuis, J.·Goult, B. T.
View original source ↗Export metadata ↓

Abstract

Misprocessing of Amyloid Precursor Protein (APP) is one of the major causes of Alzheimers disease. APP is a transmembrane protein comprising a large extracellular region, a single transmembrane helix and a short cytoplasmic tail containing an NPxY motif (normally referred to as the YENPTY motif). Talins are synaptic scaffold proteins that connect the cytoskeletal machinery to the plasma membrane via binding to one of two highly conserved NPxY motifs in the cytoplasmic tail of integrin transmembrane receptors. Here we report the crystal structure of an APP/talin1 complex identifying a new way to couple the cytoskeletal machinery to synaptic sites via APP. Proximity Ligation Assay (PLA) confirmed the close proximity of talin1 and APP in primary neurons, and we show that talin1 depletion has a dramatic effect on APP processing in cells. Structural modelling indicates that APP has the capacity to form an extracellular meshwork that mechanically couples the cytoskeletal meshworks of both the pre-, and post-synaptic compartments. In this context, we propose APP processing as a mechanical signalling pathway with similarities to Notch signalling, whereby the cleavage sites in APP represent mechanical sensors, with varying accessibility to cleavage by secretases. During synaptogenesis in healthy neurons, the APP/talin linkage would provide an exquisite mechanical coupling between synapses, with tightly controlled APP processing providing instructions to maintain this synchrony. Furthermore, APP directly coupling to the binary switches in talin indicates a role for APP in mechanical memory storage as postulated by the MeshCODE theory. The implication that APP is a regulator of mechanical signalling leads to a new hypothesis for Alzheimers disease, where mis-regulation of APP dynamics results in loss of mechanical integrity of the synapse, corruption and loss of mechanical binary data, and excessive generation of the toxic plaque-forming A{beta}42 peptide. Much needs to be done to experimentally validate this idea, but we present here a novel theory of Alzheimers Disease with a role for APP in the mechanically coded binary information storage in the synapse, which identifies a potential novel therapeutic strategy for treating Alzheimers Disease. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=131 SRC="FIGDIR/small/583202v4_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@ba0768org.highwire.dtl.DTLVardef@13c4672org.highwire.dtl.DTLVardef@352178org.highwire.dtl.DTLVardef@288bf6_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical AbstractC_FLOATNO Graphical Abstract Legend: Amyloid Precursor Protein (APP) forms an extracellular meshwork that provides a coupling between the mechanical signalling machinery of the pre- and post-synaptic neurons.A) APP binds to talin indicating that APP will experience mechanical forces which leads us to propose that APP processing is a Notch-like signalling pathway that maintains mechanical homeostasis at the synapse. B) The crystal structure of APP bound to talin F2F3. C) APP is part of the adhesion complex that attaches talin to the membrane. D) The loss of adhesion integrity in the synapse, or other factors that lead to misprocessing of APP will perturb this coupling and contribute to Alzheimers Disease. See also Movie 1. C_FIG

Source connections

Explore related subjects

neurosciencePreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Ellis, C., Ward, N. L., Rice, M., Ball, N. J., Lambert, J.-C., Chapuis, J., Goult, B. T.. 2024-03-06. The structure of an Amyloid Precursor Protein/talin complex indicates a mechanical basis of Alzheimer's Disease.. https://doi.org/10.1101/2024.03.04.583202

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

Same Movements, Different Skills: How Context Shapes Learning in Humans and Neural Networks

What determines whether experiences are integrated into shared representations or split? Motor skill learning offers a revealing test: when two tasks require an identical sequence of movements, both intuition and theory suggest that practice in one should generalize to the other. Yet we find that changing context can make identical movements different skills. In simple recurrent networks trained on the same sequence across contexts, splitting was greatest when strong contextual inputs coincided with a high initial weight scale; neither alone sufficed. Greater representational separation coincided with separate context-specific learning curves. Humans practicing the same finger sequence while alternating between two performance-irrelevant contexts likewise exhibited context-specific curves, rather than the single continuous trajectory observed when practicing in a single context. State-space modeling favored split learning states in humans and very weakly coupled states in the most context-dependent networks. These findings have broader implications for understanding how learning generalizes across contexts.

neuroscience↗
bioRxiv2026

Postpartum resource scarcity reshapes maternal care, offspring prioritization, and the steroid-sensitive medial preoptic area

Parental care requires balancing offspring needs with environmental constraints, yet how resource scarcity alters the organization of maternal responses remains poorly understood. Here, we examined maternal behavior, offspring prioritization, and steroid receptor-associated extracellular matrix organization in postpartum rats exposed to limited bedding and nesting (LBN) or control conditions with ample nesting materials. LBN increased pup-directed and reduced self-directed behaviors but also increased behavioral entropy, a measure of behavioral fragmentation, indicating less predictable caregiving sequences. LBN dams preferentially retrieved male pups first, whereas control dams preferentially retrieved females first. LBN also increased the proportion of pup-investigation time directed toward males compared with controls. In offspring on postnatal day 10, corticosterone was elevated in female but not male LBN pups, a pattern that paralleled the maternal male bias. To identify associated neurobiological changes, we assessed steroid receptors and extracellular matrix organization in the medial preoptic area (mPOA), a key region for maternal behavior. LBN increased numbers of estrogen receptor (ER)- and androgen receptor (AR)-immunoreactive cells, reduced perineuronal net (PNN) abundance, and decreased receptor-positive cell enwrapment. Because PNNs constrain structural plasticity, these findings suggest that the postpartum environment alters the organization of steroid receptor-associated extracellular matrix, potentially modulating experience-dependent plasticity in neurosteroid-sensitive circuits. In sum, LBN increases the levels of maternal engagement while reshaping its temporal organization and allocation, accompanied by selective remodeling of steroid-sensitive preoptic architecture. Therefore, maternal adaptation to adversity may be better understood as changes in caregiving allocation strategies rather than a simple gain or loss of maternal care.

neuroscience↗
bioRxiv2026

The Computational Grammar of Human Behaviour in a Biological Environment

Human behaviour unfolds as an extended stream of spontaneous actions shaped by environmental demands and the agent's goals. The organisation of these actions, situated between setting abstract goals and concrete movement execution, remains poorly characterised. Here, we introduce DynaClade, an unsupervised temporal action segmentation algorithm for human full-body motion capture data, and apply it to freely moving participants navigating ecologically realistic risky foraging environments in virtual reality. DynaClade identifies discrete actions whose kinematic characteristics and spatial distributions correspond to environmental affordances, supporting the validity of the approach. Among these actions, we discovered a hitherto undescribed movement pattern defined by increased body sway without locomotion. Action sequences were highly non-random and showed clear history dependence beyond first-order Markov structure, most of which was explained by a second-order prediction. This higher-order structure was well captured in a hidden Markov model, in which some of the observed actions were associated with more than one latent state. Each of these latent states corresponded to the same action in a distinct action context. These findings suggest that spontaneous human actions are predominantly selected based on the current action and context, rather than following pre-planned or habitually assembled sequences.

neuroscience↗