Aggregate Interactome Based on Protein Cross-linking Interfaces Predicts Drug Targets to Limit Aggregation in Neurodegenerative Diseases

Abstract

Diagnosis of neurodegenerative diseases hinges on "seed" proteins detected in disease-specific aggregates. These inclusions contain diverse constituents, adhering through aberrant interactions that our prior data indicate are nonrandom. To define preferential protein-protein contacts mediating aggregate coalescence, we created click-chemistry reagents that cross-link neighboring proteins within human, APP_Sw-driven, neuroblastoma-cell aggregates. These reagents incorporate a biotinyl group to efficiently recover linked tryptic-peptide pairs. Mass-spectroscopy outputs were screened for all possible peptide pairs in the aggregate proteome. These empirical linkages, ranked by abundance, implicate a protein-adherence network termed the "aggregate contactome." Critical hubs and hub-hub interactions were assessed by RNAi-mediated rescue of chemotaxis in aging nematodes, and aggregation-driving properties were inferred by multivariate regression and neural-network approaches. Aspirin, while disrupting aggregation, greatly simplified the aggregate contactome. This approach, and the dynamic model of aggregate accrual it implies, reveals the architecture of insoluble-aggregate networks and may reveal targets susceptible to interventions to ameliorate protein-aggregation diseases.

Keywords: Molecular Neuroscience; Neural Networks; Neuroscience; Proteomics.

Graphical abstract

Figure 1

Analysis of Aggregate-Specific Interactomes (A) Amyloid-like aggregates were stained with thioflavin T, in SY5Y neuroblastoma cells (top panel) and SY5Y-APP_Sw cells (bottom panels). Scale bar indicates 10 μm. (B) Fluorescence intensity was quantified for cells stained with thioflavin-T; significance was determined by one-tailed t tests. Data are shown as mean ± S.E.M. (C) Graphical view of the insoluble-aggregate interactome of SY5Y-APP_Sw cells. Node (protein) color is based on degree, the number of interacting partners (see key); the edge (interaction) color indicates whether the observed protein-protein contact is peculiar to SY5Y-APP_Sw cells (green) or is also present in untransformed (“WT”) SY5Y cells (black). (D) Venn diagram indicating number of interactions that are specific to SY5Y-APP_Sw cells, specific to SY5Y, or present in both. (E) Average spectral hits for observed peptide pairs (total per protein) quantified from SY5Y(WT) and SY5Y-APP_Sw cross-linking proteomics. “WT + APP” indicates hits for proteins shared by SY5Y(WT) and SY5Y-APP_Sw (see D). (F) Proteins (nodes) from the aggregate interactome were categorized based on the number of interacting partners (degree), ranging from hub connectors that connect two to nine hub proteins, to mega-hubs (≥100 partners).

Figure 2

The Aggregate Interactome Identifies Indirect Interactions of APP_Sw and Tau (A) Identified interacting partners of APP (E2 domain) in insoluble SY5Y-APP_Sw aggregates. (B) Domain architecture of APP protein, as inferred from the Protein DataBank (PDB). ECM, extracellular matrix; 1mwp, 3nyl, 1iyt: APP domain IDs in PDB. (C) Protein-protein docking of SRRM2 and the APP-E2 domain corroborates observed cross-linking data (yellow highlighted area). (D) Protein-protein docking of TOP1 with APP-E2 corroborates observed cross-linking data (yellow highlighted oval indicates concordant evidence of interaction). (E) Tau-interacting proteins identified from SY5Y-APP_Sw insoluble aggregates. Proteins in dashed boxes also interact with the APP-E2 domain. (F) Interactions of phosphorylated tau peptides, characteristic of hP-TAU, identified in insoluble aggregates from SY5Y-APP_Sw. SRSF6_P (dashed box) also interacts with APP-E2.

Figure 3

Protein Phosphorylation in the Aggregate Interactome (A) Aggregate protein-phosphorylation details inferred from SY5Y-APP_Sw proteomics. Three categories of aggregate proteins were observed: those identified via peptides that are always phosphorylated (red), those with peptides having both phosphorylated and unmodified forms (purple), and those whose peptides are always unmodified (blue). Hub connectors are shown in green. (B) Venn diagram depicting the composition of aggregate proteins, based on peptide phosphorylation as in (A). (C) Cross-linked contacts of phosphorylated CAND1 (arrow, cullin-associated and neddylation-dissociated protein 1), showing contactome linkages to other hub proteins, including DYHC1 and mega-hub SRRM2. Of 19 connected hubs, 12 are phosphorylation-state-specific (red or blue). (D) Cross-linked contacts of phosphorylated DYHC1 (arrow, dynein heavy chain 1), showing that its contactome linkages with other hub proteins are mostly phosphorylation-specific (12 red/always, 17 blue/never, 11 purple/mixed). (E) Cross-linked contacts of phosphorylated DYN2 (arrow, dynamin 2), showing its contactome linkages with 7 always-phosphorylated/red hub proteins, 4 never-phosphorylated/blue hubs and 2 mixed/purple hubs. (F) Cross-linked contacts of phosphorylated SYNE2 (arrow, spectrin repeat containing nuclear envelope protein 2) showing complex, mega-hub interactions with other hubs and mega-hubs.

Figure 4

Hub-Protein Knockdown Results Are Consistent with Network-Based Predictions of Hub Centrality and Efficacy (A) Chemotaxis levels of uninduced C. elegans adults (strain CL2355, with pan-neuronal leaky expression of human Aβ₄₂), declined to an average chemotaxis index (C.I.) of 0.27 at 5 days of adult age (FV bars). C.I. levels (shown as mean ± S.E.M. for triplicate experiments) are higher for RNAi-treated worms, indicating up to 54% rescue relative to day 1 adult worms (C.I. ≈ 0.9). Knockdown targets were nematode orthologs or homologs of randomly selected human proteins identified in each indicated hub category, from the cross-link-defined contactome of SY5Y-APP_Sw neuroblastoma cells. Numbers over bars indicate the unadjusted significance (p values) of hub RNAi knockdowns differing from FV controls, based on heteroscedastic two-tailed paired t tests, considering the C.I. from each of three independent experiments as a single data point. **Unadjusted chi-squared (χ²) significance of p ≤ 0.001, combined from three independent experiments, i.e., the product of three χ² p values comparing treated worms to their simultaneous controls. (B) Network diagram of the SY5Y-APP_Sw contactome, displaying for each hub its degree (number of interactions; see key for node sizes) and the neural network prediction of knockdown efficacy (rescue of chemotaxis as determined in [A]; see key for node colors). (C) Network diagram of control data, a scale-free network generated with the same node sizes as in (B). In a scale-free network, the degree distribution follows a power law; real-world networks, including protein-protein interaction networks, are widely considered to be scale-free. The distributions of node sizes, edges, and knockdown efficacies are here far more uniform than in the interactome based on empirically observed interactions (B).

Figure 5

Hub-Connector Knockdowns Rescue Age-Dependent Chemotaxis Decline (A) SY5Y-APP_Sw interactome showing the distribution of hub connectors (green dots) across the network. Insets show the local contactomes of six hub proteins: SERF2 (small EDRK-rich factor 2 [Balasubramaniam et al., 2018]); PP1A (α catalytic subunit of protein phosphatase 1, PP1, a serine/threonine protein phosphatase involved in cardiac function, learning, and memory); DRG1 (developmentally regulated GTP-binding protein 1, expressed in neural precursor cells); ACTN1 (actinin α1, a cytoskeletal protein related to spectrins and dystrophins); RPS5 (ribosomal protein S5); and COPG1 (coatomer complex subunit γ1, required for budding from Golgi membranes and for retrograde Golgi-to-ER transport of dilysine-tagged proteins). (B) Rescue of age-dependent chemotaxis loss, by knockdown of hub connectors in C. elegans strain CL2355 (uninduced, pan-neuronal Aβ₄₂ expression). Results are shown for three independent experiments (different-colored bars). *p < 0.04 by one-tailed paired t test, comparing each knockdown to its corresponding, simultaneous FV control. (C) Computational model of ATRX interacting weakly but directly with PPIG (ΔE_interaction = −73.2 kcal/mol). (D) Computational model of ATRX interacting strongly with PPIG via the hub connector RPS5 (ΔE_interaction = −120.9 kcal/mol).

Figure 6

Aspirin Treatment Reduces Aggregate Complexity (A) Thioflavin-T staining of amyloid in SY5Y-APP_Sw cells (images on left), ± simultaneous exposure to 0.5 mM aspirin. DAPI staining of nuclei (images on right) demonstrates similar cell density. Scale bar indicates 10 μm. (B) Normalized quantitations of amyloid-like aggregation per cell in SY5Y-APP_Sw cells, with or without aspirin treatment. Data are shown as mean ± S.E.M. *p < 0.02 by one-tailed t test. (C) The insoluble-aggregate interactome of SY5Y-APP_Sw cells exposed to 0.5 mM aspirin for 48 h shows substantially reduced hub degree and complexity relative to untreated cells (compare with Figure 1C). See also Figure S2. (D) Number of aggregate-network interactions is reduced by half in SY5Y-APP_Sw cells exposed to 0.5 mM aspirin, relative to untreated control cells. (E) Aspirin (1 mM) protects SY5Y-APP_Sw cells against chemotaxis decline in C. elegans strain CL2355 (pan-neuronal Aβ₄₂ expression) relative to vehicle-only controls. ***p < 2.5 × 10⁻⁵, significance by chi-squared (χ²) test. (F) Interaction energies (ΔG_binding) predicted by computational docking of aspirin with candidate proteins (blue bars, network-implicated hub proteins) versus previously reported ASA-binding targets (tan bars, five positive controls to confirm correct docking parameters). (G–J) Aspirin docking poses of proteins predicted to be direct ASA-binding targets (Ayyadevara et al., 2017): (G) HSP90A (heat shock protein 90α); (H) PP1A (see Figure 5A legend); (I) TUBB4A (tubulin beta chain 4A, a major constituent of microtubules); and (J) LMNA (lamin 4 A/C, a constituent of nuclear lamina; mutations are implicated in several muscular and cardiac dystrophies and in Hutchinson-Gilford progeria).