Characterization of the strain-rate–dependent mechanical response of single cell–cell junctions

Cell–cell adhesions are often subjected to mechanical strains of different rates and magnitudes in normal tissue function. However, the rate-dependent mechanical behavior of individual cell–cell adhesions has not been fully characterized due to the lack of proper experimental techniques and therefore remains elusive. This is particularly true under large strain conditions, which may potentially lead to cell–cell adhesion dissociation and ultimately tissue fracture. In this study, we designed and fabricated a single-cell adhesion micro tensile tester (SCAµTT) using two-photon polymerization and performed displacement-controlled tensile tests of individual pairs of adherent epithelial cells with a mature cell–cell adhesion. Straining the cytoskeleton–cell adhesion complex system reveals a passive shear-thinning viscoelastic behavior and a rate-dependent active stress-relaxation mechanism mediated by cytoskeleton growth. Under low strain rates, stress relaxation mediated by the cytoskeleton can effectively relax junctional stress buildup and prevent adhesion bond rupture. Cadherin bond dissociation also exhibits rate-dependent strengthening, in which increased strain rate results in elevated stress levels at which cadherin bonds fail. This bond dissociation becomes a synchronized catastrophic event that leads to junction fracture at high strain rates. Even at high strain rates, a single cell–cell junction displays a remarkable tensile strength to sustain a strain as much as 200% before complete junction rupture. Collectively, the platform and the biophysical understandings in this study are expected to build a foundation for the mechanistic investigation of the adaptive viscoelasticity of the cell–cell junction.

Adhesive organelles between neighboring epithelial cells form an integrated network as the foundation of complex tissues (1). As part of normal physiology, this integrated network is constantly exposed to mechanical stress and strain, which is essential to normal cellular activities, such as proliferation (2–4), migration (5, 6), differentiation (7), and gene regulation (7, 8) associated with a diverse set of functions in tissue morphogenesis (9–11) and wound healing (9). A host of developmental defects or clinical pathologies in the form of compromised cell–cell associations will arise when cells fail to withstand external mechanical stress due to genetic mutations or pathological perturbations (12, 13). Indeed, since the mechanical stresses are mainly sustained by the intercellular junctions, which may represent the weakest link and limit the stress tolerance within the cytoskeleton network of a cell sheet, mutations or disease-induced changes in junction molecules and components in adherens junctions and desmosomes lead to cell layer fracture and tissue fragility, which exacerbate the pathological conditions (14–17). This clinical relevance gives rise to the importance of understanding biophysical transformations of the cell–cell adhesion interface when cells are subjected to mechanical loads.As part of their normal functions, cells often experience strains of tens to a few hundred percent at strain rates of 10⁻⁴ to 1 s⁻¹ (18–21). For instance, embryonic epithelia are subjected to strain rates in the range of 10⁻⁴ to 10⁻³ s⁻¹ during normal embryogenesis (22). Strain rates higher than 0.1 s⁻¹ are often experienced by adult epithelia during various normal physiological functions (21, 23, 24), such as breathing motions in the lung (1 to 10 s⁻¹) (25), cardiac pulses in the heart (1 to 6.5 s⁻¹) (20), peristaltic movements in the gut (0.4 to 1.5 s⁻¹), and normal stretching of the skin (0.1 to 5 s⁻¹). Cells have different mechanisms to dissipate the internal stress produced by external strain to avoid fracture, often via cytoskeleton remodeling and cell–cell adhesion enhancement (26, 27). These coping mechanisms may have different characteristic timescales. Cytoskeleton remodeling can dissipate mechanical stress promptly due to its viscoelastic nature and the actomyosin-mediated cell contractility (17, 28–32). Adhesion enhancement at the cell–cell contact is more complex in terms of timescale. Load-induced cell–cell adhesion strengthening has been shown via the increase in the number of adhesion complexes (33–35) or by the clustering of adhesion complexes (36–39), which occurs on a timescale ranging from a few minutes up to a few hours after cells experience an initial load (28). External load on the cell–cell contact also results in a prolonged cell–cell adhesion dissociation time (40, 41), suggesting cadherin bonds may transition to catch bonds under certain loading conditions (42, 43), which can occur within seconds (44). With the increase in cellular tension, failure to dissipate the stress within the cell layer at a rate faster than the accumulation rate will inevitably lead to the fracture of the cell layer (45). Indeed, epithelial fracture often aggravates the pathological outcomes in several diseases, such as acute lung injuries (46), skin disorders (47), and development defects (48). It is generally accepted that stress accumulation in the cytoskeleton network (49, 50) and potentially in the cytoplasm is strain-rate–dependent (51). However, to date, there is a lack of understanding about the rate-dependent behavior of cell–cell adhesions, particularly about which of the stress-relaxation mechanisms are at play across the spectrum of strain rates. In addition, it remains unclear how the stress relaxation interplays with adhesion enhancement under large strains, especially at high strain rates which may lead to fracture, that is, a complete separation of mature cell–cell adhesions under a tensile load (45, 52, 53). Yet, currently, there is a lack of quantitative technology that enables the investigation of these mechanobiological processes in a precisely controlled manner. This is especially true at high strain rates.To delineate this mechanical behavior, the cleanest characterization method is to directly measure stress dynamics at a single mature cell–cell adhesion interface. Specifically, just as a monolayer cell sheet is a reduction from three-dimensional (3D) tissue, a single cell–cell adhesion interface, as a reduction from a monolayer system, represents the smallest unit to study the rheological behavior of cellular junctions. The mechanistic understanding uncovered with this single unit will inform cellular adaptations to a more complex stress microenvironment in vivo and in vitro, in healthy and diseased conditions. To this end, we developed a single-cell adhesion micro tensile tester (SCAµTT) platform based on nanofabricated polymeric structures using two-photon polymerization (TPP). This platform allows in situ investigation of stress–strain characteristics of a mature cell–cell junction through defined strains and strain rates. With SCAµTT, we reveal some interesting biophysical phenomena at the single cell–cell junction that were previously not possible to observe using existing techniques. We show that cytoskeleton growth can effectively relax intercellular stress between an adherent cell pair in a strain-rate–dependent manner. Along with cadherin-clustering–induced bond strengthening, it prevents failure to occur at low strain rates. At high strain rates, insufficient relaxation leads to stress accumulation, which results in cell–cell junction rupture. We show that a remarkably large strain can be sustained before junction rupture (>200%), even at a strain rate as high as 0.5 s⁻¹. Collectively, the rate-dependent mechanical characterization of the cell–cell junction builds the foundation for an improved mechanistic understanding of junction adaptation to an external load and potentially the spatiotemporal coordination of participating molecules at the cell–cell junction.     

CYK-1/Formin activation in cortical RhoA signaling centers promotes organismal left–right symmetry breaking

Proper left–right symmetry breaking is essential for animal development, and in many cases, this process is actomyosin-dependent. In Caenorhabditis elegans embryos active torque generation in the actomyosin layer promotes left–right symmetry breaking by driving chiral counterrotating cortical flows. While both Formins and Myosins have been implicated in left–right symmetry breaking and both can rotate actin filaments in vitro, it remains unclear whether active torques in the actomyosin cortex are generated by Formins, Myosins, or both. We combined the strength of C. elegans genetics with quantitative imaging and thin film, chiral active fluid theory to show that, while Non-Muscle Myosin II activity drives cortical actomyosin flows, it is permissive for chiral counterrotation and dispensable for chiral symmetry breaking of cortical flows. Instead, we find that CYK-1/Formin activation in RhoA foci is instructive for chiral counterrotation and promotes in-plane, active torque generation in the actomyosin cortex. Notably, we observe that artificially generated large active RhoA patches undergo rotations with consistent handedness in a CYK-1/Formin–dependent manner. Altogether, we conclude that CYK-1/Formin–dependent active torque generation facilitates chiral symmetry breaking of actomyosin flows and drives organismal left–right symmetry breaking in the nematode worm.

The emergence of left–right asymmetry is essential for normal animal development and, in the majority of animal species, one type of handedness is dominant (1). The actin cytoskeleton plays an instrumental role in establishing the left–right asymmetric body plan of invertebrates like fruit flies (2–6), nematodes (7–11), and pond snails (12–15). Moreover, an increasing number of studies showed that vertebrate left–right patterning also depends on a functional actomyosin cytoskeleton (13, 16–22). Actomyosin-dependent chiral behavior has even been reported in isolated cells (23–28) and such cell-intrinsic chirality has been shown to promote left–right asymmetric morphogenesis of tissues (29, 30), organs (21, 31), and entire embryonic body plans (12, 13, 32, 33). Active force generation in the actin cytoskeleton is responsible for shaping cells and tissues during embryo morphogenesis. Torques are rotational forces with a given handedness and it has been proposed that in plane, active torque generation in the actin cytoskeleton drives chiral morphogenesis (7, 8, 34, 35).What could be the molecular origin of these active torques? The actomyosin cytoskeleton consists of actin filaments, actin-binding proteins, and Myosin motors. Actin filaments are polar polymers with a right-handed helical pitch and are therefore chiral themselves (36, 37). Due to the right-handed pitch of filamentous actin, Myosin motors can rotate actin filaments along their long axis while pulling on them (33, 38–42). Similarly, when physically constrained, members of the Formin family rotate actin filaments along their long axis while elongating them (43). In both cases the handedness of this rotation is determined by the helical nature of the actin polymer. From this it follows that both Formins and Myosins are a potential source of molecular torque generation that could drive cellular and organismal chirality. Indeed, chiral processes across different length scales, and across species, are dependent on Myosins (19), Formins (13–15, 26), or both (7, 8, 21, 44). It is, however, unclear how Formins and Myosins contribute to active torque generation and the emergence chiral processes in developing embryos.In our previous work we showed that the actomyosin cortex of some Caenorhabditis elegans embryonic blastomeres undergoes chiral counterrotations with consistent handedness (7, 35). These chiral actomyosin flows can be recapitulated using active chiral fluid theory that describes the actomyosin layer as a thin-film, active gel that generates active torques (7, 45, 46). Chiral counterrotating cortical flows reorient the cell division axis, which is essential for normal left–right symmetry breaking (7, 47). Moreover, cortical counterrotations with the same handedness have been observed in Xenopus one-cell embryos (32), suggesting that chiral counterrotations are conserved among distant species. Chiral counterrotating actomyosin flow in C. elegans blastomeres is driven by RhoA signaling and is dependent on Non-Muscle Myosin II motor proteins (7). Moreover, the Formin CYK-1 has been implicated in actomyosin flow chirality during early polarization of the zygote as well as during the first cytokinesis (48, 49). Despite having identified a role for Myosins and Formins, the underlying mechanism by which active torques are generated remains elusive.Here we show that the Diaphanous-like Formin, CYK-1/Formin, is a critical determinant for the emergence of actomyosin flow chirality, while Non-Muscle Myosin II (NMY-2) plays a permissive role. Our results show that cortical CYK-1/Formin is recruited by active RhoA signaling foci and promotes active torque generation, which in turn tends to locally rotate the actomyosin cortex clockwise. In the highly connected actomyosin meshwork, a gradient of these active torques drives the emergence of chiral counterrotating cortical flows with uniform handedness, which is essential for proper left–right symmetry breaking. Together, these results provide mechanistic insight into how Formin-dependent torque generation drives cellular and organismal left–right symmetry breaking.     

Replisome bypass of a protein-based R-loop block by Pif1

Efficient and faithful replication of the genome is essential to maintain genome stability. Replication is carried out by a multiprotein complex called the replisome, which encounters numerous obstacles to its progression. Failure to bypass these obstacles results in genome instability and may facilitate errors leading to disease. Cells use accessory helicases that help the replisome bypass difficult barriers. All eukaryotes contain the accessory helicase Pif1, which tracks in a 5′–3′ direction on single-stranded DNA and plays a role in genome maintenance processes. Here, we reveal a previously unknown role for Pif1 in replication barrier bypass. We use an in vitro reconstituted Saccharomyces cerevisiae replisome to demonstrate that Pif1 enables the replisome to bypass an inactive (i.e., dead) Cas9 (dCas9) R-loop barrier. Interestingly, dCas9 R-loops targeted to either strand are bypassed with similar efficiency. Furthermore, we employed a single-molecule fluorescence visualization technique to show that Pif1 facilitates this bypass by enabling the simultaneous removal of the dCas9 protein and the R-loop. We propose that Pif1 is a general displacement helicase for replication bypass of both R-loops and protein blocks.

Efficient and faithful replication of the genome is essential to maintain genome stability and is carried out by a multiprotein complex called the replisome (1–4). There are numerous obstacles to progression of the replisome during the process of chromosome duplication. These obstacles include RNA-DNA hybrids (R-loops), DNA secondary structures, transcribing RNA polymerases, and other tightly bound proteins (5–9). Failure to bypass these barriers may result in genome instability, which can lead to cellular abnormalities and genetic disease. Cells contain various accessory helicases that help the replisome bypass these difficult barriers (10–20). A subset of these helicases act on the opposite strand of the replicative helicase (1, 2, 14, 19).All eukaryotes contain an accessory helicase, Pif1, which tracks in a 5′–3′ direction on single-stranded DNA (ssDNA) (11–16). Pif1 is important in pathways such as Okazaki-fragment processing and break-induced repair that require the removal of DNA-binding proteins as well as potential displacement of R-loops (11–13, 21, 15–18, 22–25). Genetic studies and immunoprecipitation pull-down assays indicate that Pif1 interacts with PCNA (the DNA sliding clamp), Pol ε (the leading-strand polymerase), the MCMs (the motor subunits of the replicative helicase CMG), and RPA (the single-stranded DNA-binding protein) (15, 26, 27). Pif1 activity in break-induced repair strongly depends on its interaction with PCNA (26). These interactions with replisomal components suggest that Pif1 could interact with the replisome during replication. In Escherichia coli, the replicative helicase is the DnaB homohexamer that encircles the lagging strand and moves in a 5′–3′ direction (20). E. coli accessory helicases include the monomeric UvrD (helicase II) and Rep, which move in the 3′–5′ direction and operate on the opposite strand from the DnaB hexamer. It is known that these monomeric helicases promote the bypass of barriers during replication such as stalled RNA polymerases (5). The eukaryotic replicative helicase is the 11-subunit CMG (Cdc45, Mcm2–7, GINS) and tracks in the 3′–5′ direction, opposite to the direction of Pif1 (25, 28). Once activated by Mcm10, the MCM motor domains of CMG encircle the leading strand (29–32). We hypothesized that, similar to UvrD and Rep in E. coli, Pif1 interacts with the replisome tracking in the opposite direction to enable bypass of replication obstacles.In this report, we use an in vitro reconstituted Saccharomyces cerevisiae replisome to study the role of Pif1 in bypass of a “dead” Cas9 (dCas9), which is a Cas9 protein that is deactivated in DNA cleavage but otherwise fully functional in DNA binding. As with Cas9, dCas9 is a single-turnover enzyme that can be programmed with a guide RNA (gRNA) to target either strand. The dCas9–gRNA complex forms a roadblock consisting of an R-loop and a tightly bound protein (dCas9), a construct that is similar to a stalled RNA polymerase. This roadblock (hereafter dCas9 R-loop) arrests replisomes independent of whether the dCas9 R-loop is targeted to the leading or lagging strand (30). Besides its utility due to its programmable nature (33), the use of the dCas9 R-loop allows us to answer several mechanistic questions. For example, the ability to program the dCas9 R-loop block to any specific sequence enables us to observe whether block removal is different depending on whether the block is on the leading or lagging strand. Furthermore, the inner diameter of CMG can accommodate double-stranded DNA (dsDNA) and possibly an R-loop, but not a dCas9 protein. Using the dCas9 R-loop block allows us to determine the fate of each of its components.Here, we report that Pif1 enables the bypass of the dCas9 R-loop by the replisome. Interestingly, dCas9 R-loops targeted to either the leading or lagging strand are bypassed with similar efficiency. In addition, the PCNA clamp is not required for bypass of the block, indicating that Pif1 does not need to interact with PCNA during bypass of the block. We used a single-molecule fluorescence imaging to show that both the dCas9 and the R-loop are displaced as an intact nucleoprotein complex. We propose that Pif1 is a general displacement helicase for replication bypass of both R-loops and protein blocks.     

Cell type-specific lipid storage changes in Parkinson’s disease patient brains are recapitulated by experimental glycolipid disturbance

Neurons are dependent on proper trafficking of lipids to neighboring glia for lipid exchange and disposal of potentially lipotoxic metabolites, producing distinct lipid distribution profiles among various cell types of the central nervous system. Little is known of the cellular distribution of neutral lipids in the substantia nigra (SN) of Parkinson’s disease (PD) patients and its relationship to inflammatory signaling. This study aimed to determine human PD SN neutral lipid content and distribution in dopaminergic neurons, astrocytes, and microglia relative to age-matched healthy subject controls. The results show that while total neutral lipid content was unchanged relative to age-matched controls, the levels of whole SN triglycerides were correlated with inflammation-attenuating glycoprotein non-metastatic melanoma protein B (GPNMB) signaling in human PD SN. Histological localization of neutral lipids using a fluorescent probe (BODIPY) revealed that dopaminergic neurons and midbrain microglia significantly accumulated intracellular lipids in PD SN, while adjacent astrocytes had a reduced lipid load overall. This pattern was recapitulated by experimental in vivo inhibition of glucocerebrosidase activity in mice. Agents or therapies that restore lipid homeostasis among neurons, astrocytes, and microglia could potentially correct PD pathogenesis and disease progression.

Both neurons and glia depend on tight regulation and exchange of lipids for proper function. Typically through lipid transport mechanisms (1, 2), the continuous exchange of lipids is essential for maintaining physiological function as brain lipid content, transport, and distribution are complex and critical aspects of neuropathology. Recently, both clinical findings and experimental studies have implicated lipid storage and trafficking in the pathogenesis of Parkinson’s disease (PD) and related disorders (3, 4). Reduced function of lysosomal hydrolases that are associated with lysosomal storage disorders increases the risk for PD and results in brain pathology similar to that seen in most sporadic and genetic forms of the disease (5–11).One of the strongest genetic risk factors for PD is heterozygous loss-of-function mutations in GBA1, encoding the lysosomal hydrolase glucocerebrosidase (GCase) (12–14), a deficiency that causes systemic accumulation of its glycolipid substrate glucosylceramide (GlcCer). GCase activity is reduced with aging of both the human and murine brain (6, 15), and age is the overall greatest risk factor for developing PD (16). In contrast, the more severe loss of GCase activity in homozygous GBA1 mutant carriers causes the lysosomal storage disease Gaucher disease (GD) (17). Conduritol beta epoxide (CBE), an irreversible inhibitor of GCase, causes widespread accumulation of GlcCer and related glycosphingolipids in mice. In this model, there is marked increase of high molecular weight alpha-synuclein (aSYN) and deposition of proteinase K-resistant aSYN resembling that seen in PD (18–20). aSYN is a constituent of the classical Lewy bodies and Lewy neurites (21) found in surviving dopaminergic neurons in postmortem PD materials as a standard pathological criterion for PD (22). aSYN has a lipid-binding domain, and aSYN protein–lipid interactions are potentially perturbed in PD (reviewed in refs. 17, 23, 24). We recently demonstrated that excessive aSYN can deposit into lipid compartments, and that this process is reversible under increased lysosomal β-hexosaminidase expression (25).Several in vitro physiological studies have demonstrated that a reduction in neuronal neutral lipid storage or knockdown of fatty acid desaturases protects cultured neurons from degeneration (26–28). However, as neurons exhibit limited capacity to synthesize, metabolize, and transport lipid species under physiological conditions (29), other resident cells of the substantia nigra (SN), such as glial cells, are required to maintain lipid homeostasis in the brain. Astrocyte health and lipid exchange function—and microglial activation—are potentially central to PD pathogenesis and other age-dependent neurodegenerative diseases (30–33). Brain resident microglia can accumulate and generate lipids, which may propagate inflammatory processes through, for example, TREM2 binding of apolipoproteins (34–38). Proinflammatory cytokines present in chronic conditions are attenuated by the binding of glycoprotein nonmetastatic melanoma protein B (GPNMB) to the CD44 receptor on astrocytes (39). In GD patient serum, GPNMB level is significantly correlated with disease severity (40), and GPNMB is increased in human PD SN and following CBE-induced glycolipid accumulation in mice (41).There are surprisingly little data on lipid distribution patterns in PD-affected cell types given the relevance of lipid homeostasis, aSYN–lipid interactions, and lipidopathy-associated inflammatory signatures as they relate to PD (17, 41). In this study, we measured the differences in total lipid content and cellular distribution between PD and healthy subject (HS) SN and compared them with a lipid-associated neuroinflammatory signal, GPNMB. To quantify cell type-specific intracellular lipid content, colocalization analysis was performed on human postmortem SN sections that were costained for neutral lipids and markers of dopaminergic neurons, astrocytes, and microglia. Compared with HS SN, the lipid content of PD dopaminergic neurons and microglia was significantly higher, and that of astrocytes was significantly lower. To understand a possible mechanistic reason for this lipid distribution pattern, we used an in vivo mouse model of glycolipid dysregulation and attendant aSYN accumulation through GCase inhibition by CBE. This in vivo model recapitulated the lipid distribution pattern that we observed in human PD SN. Based on these data, we propose that PD is characterized by a unique neutral lipid distribution signature in neurons, astrocytes, and microglia that can be recapitulated experimentally by glycolipid dysregulation.     

LGI1–ADAM22–MAGUK configures transsynaptic nanoalignment for synaptic transmission and epilepsy prevention

Physiological functioning and homeostasis of the brain rely on finely tuned synaptic transmission, which involves nanoscale alignment between presynaptic neurotransmitter-release machinery and postsynaptic receptors. However, the molecular identity and physiological significance of transsynaptic nanoalignment remain incompletely understood. Here, we report that epilepsy gene products, a secreted protein LGI1 and its receptor ADAM22, govern transsynaptic nanoalignment to prevent epilepsy. We found that LGI1–ADAM22 instructs PSD-95 family membrane-associated guanylate kinases (MAGUKs) to organize transsynaptic protein networks, including NMDA/AMPA receptors, Kv₁ channels, and LRRTM4–Neurexin adhesion molecules. Adam22^ΔC5/ΔC5 knock-in mice devoid of the ADAM22–MAGUK interaction display lethal epilepsy of hippocampal origin, representing the mouse model for ADAM22-related epileptic encephalopathy. This model shows less-condensed PSD-95 nanodomains, disordered transsynaptic nanoalignment, and decreased excitatory synaptic transmission in the hippocampus. Strikingly, without ADAM22 binding, PSD-95 cannot potentiate AMPA receptor-mediated synaptic transmission. Furthermore, forced coexpression of ADAM22 and PSD-95 reconstitutes nano-condensates in nonneuronal cells. Collectively, this study reveals LGI1–ADAM22–MAGUK as an essential component of transsynaptic nanoarchitecture for precise synaptic transmission and epilepsy prevention.

Epilepsy, characterized by unprovoked, recurrent seizures, affects 1 to 2% of the population worldwide. Many genes that cause inherited epilepsy when mutated encode ion channels, and dysregulated synaptic transmission often causes epilepsy (1, 2). Although antiepileptic drugs have mainly targeted ion channels, they are not always effective and have adverse effects. It is therefore important to clarify the detailed processes for synaptic transmission and how they are affected in epilepsy.Recent superresolution imaging of the synapse reveals previously overlooked subsynaptic nano-organizations and pre- and postsynaptic nanodomains (3–6), and mathematical simulation suggests their nanometer-scale coordination in individual synapses for efficient synaptic transmission: presynaptic neurotransmitter release machinery and postsynaptic receptors precisely align across the synaptic cleft to make “transsynaptic nanocolumns” (7, 8).So far, numerous transsynaptic cell-adhesion molecules have been identified (9–12), including presynaptic Neurexins and type IIa receptor protein tyrosine phosphatases (PTPδ, PTPσ, and LAR) and postsynaptic Neuroligins, LRRTMs, NGL-3, IL1RAPL1, Slitrks, and SALMs. Neurexins–Neuroligins have attracted particular attention because of their synaptogenic activities when overexpressed and their genetic association with neuropsychiatric disorders (e.g., autism). Another type of transsynaptic adhesion complex mediated by synaptically secreted Cblns (e.g., Neurexin–Cbln1–GluD2) promotes synapse formation and maintenance (13–15). Genetic studies in Caenorhabditis elegans show that secreted Ce-Punctin, the ortholog of the mammalian ADAMTS-like family, specifies cholinergic versus GABAergic identity of postsynaptic domains and functions as an extracellular synaptic organizer (16). However, the molecular identity and in vivo physiological significance of transsynaptic nanocolumns remain incompletely understood.LGI1, a neuronal secreted protein, and its receptor ADAM22 have recently emerged as major determinants of brain excitability (17) as 1) mutations in the LGI1 gene cause autosomal dominant lateral temporal lobe epilepsy (18); 2) mutations in the ADAM22 gene cause infantile epileptic encephalopathy with intractable seizures and intellectual disability (19, 20); 3) Lgi1 or Adam22 knockout mice display lethal epilepsy (21–24); and 4) autoantibodies against LGI1 cause limbic encephalitis characterized by seizures and amnesia (25–28). Functionally, LGI1–ADAM22 regulates AMPA receptor (AMPAR) and NMDA receptor (NMDAR)-mediated synaptic transmission (17, 22, 29) and Kv₁ channel-mediated neuronal excitability (30, 31). Recent structural analysis shows that LGI1 and ADAM22 form a 2:2 heterotetrameric assembly (ADAM22–LGI1–LGI1–ADAM22) (32), suggesting the transsynaptic configuration.In this study, we identify ADAM22-mediated synaptic protein networks in the brain, including pre- and postsynaptic MAGUKs and their functional bindings to transmembrane proteins (NMDA/AMPA glutamate receptors, voltage-dependent ion channels, cell-adhesion molecules, and vesicle-fusion machinery). ADAM22 knock-in mice lacking the MAGUK-binding motif show lethal epilepsy of hippocampal origin. In this mouse, postsynaptic PSD-95 nano-assembly as well as nano-scale alignment between pre- and postsynaptic proteins are significantly impaired. Importantly, PSD-95 is no longer able to modulate AMPAR-mediated synaptic transmission without binding to ADAM22. These findings establish that LGI1–ADAM22 instructs MAGUKs to organize transsynaptic nanocolumns and guarantee the stable brain activity.     

Regulatory mechanisms of tau protein fibrillation under the conditions of liquid–liquid phase separation

One of the hallmarks of Alzheimer’s disease and several other neurodegenerative disorders is the aggregation of tau protein into fibrillar structures. Building on recent reports that tau readily undergoes liquid–liquid phase separation (LLPS), here we explored the relationship between disease-related mutations, LLPS, and tau fibrillation. Our data demonstrate that, in contrast to previous suggestions, pathogenic mutations within the pseudorepeat region do not affect tau441’s propensity to form liquid droplets. LLPS does, however, greatly accelerate formation of fibrillar aggregates, and this effect is especially dramatic for tau441 variants with disease-related mutations. Most important, this study also reveals a previously unrecognized mechanism by which LLPS can regulate the rate of fibrillation in mixtures containing tau isoforms with different aggregation propensities. This regulation results from unique properties of proteins under LLPS conditions, where total concentration of all tau variants in the condensed phase is constant. Therefore, the presence of increasing proportions of the slowly aggregating tau isoform gradually lowers the concentration of the isoform with high aggregation propensity, reducing the rate of its fibrillation. This regulatory mechanism may be of direct relevance to phenotypic variability of tauopathies, as the ratios of fast and slowly aggregating tau isoforms in brain varies substantially in different diseases.

Tau is a major neuronal protein that plays a key role in Alzheimer’s disease (AD) and a number of other neurodegenerative disorders that are collectively classified as tauopathies. The latter include frontotemporal dementia with parkinsonism linked to chromosome 17 (FTDP-17), progressive supranuclear palsy, Pick’s disease, corticobasal degeneration, and chronic traumatic encephalopathy (1–5). Under normal physiological conditions, tau is localized to axons where it is involved in the assembly of microtubules (1–6). In tauopathies, the protein self-associates into different forms of filaments that contain largely hyperphosphorylated tau and have properties of amyloid fibrils (1–5).Alternative splicing of the MAPT gene that encodes tau results in six major isoforms in the human central nervous system. These isoforms differ with respect to the number of N-terminal inserts as well as the number of 31 to 32 residue pseudorepeat sequences in the C-terminal part of the protein (1–5). Structurally, tau is largely an intrinsically disordered protein, with local secondary structures existing only within the pseudorepeat region (1, 7). A large number of mutations have been identified in the latter region that correlate with inherited cases of FTDP-17 (8, 9). These mutations not only diminish the ability of tau to promote microtubule assembly, but many also promote self-association of tau into amyloid fibrils (10–12). This strongly suggests that tau misfolding and aggregation is one of the key events in disease pathogenesis.A number of recent reports indicate that purified full-length tau (tau441) has a high propensity to undergo liquid–liquid phase separation (LLPS) in vitro in the presence of crowding agents that emulate the high concentration of macromolecules in the cell. This was observed both for the phosphorylated (13) and nonphosphorylated protein (14–16), and it was determined that tau LLPS is driven largely by attractive electrostatic intermolecular interactions between the negatively charged N-terminal and positively charged middle/C-terminal regions of the protein (15). Tau condensation into droplets (complex coacervation) was also observed in the presence of polyanions such as RNA or heparin (17, 18). These observations in vitro are partially supported by studies in cells (13, 19–24), especially within the context of tau interaction with microtubules (21). However, it remains unclear whether tau could undergo LLPS in cells on its own or, rather, its recruitment to membraneless organelles such as stress granules is largely driven by interactions with other proteins and/or RNA. These limitations notwithstanding, the observations that tau has a propensity for LLPS have potentially important implications for the pathogenic process in tauopathies, as studies with other proteins involved in neurodegenerative diseases (e.g., TDP-43, FUS) indicate that the environment of liquid droplets is conducive to the pathological aggregation of these proteins (25–32). In line with these findings, it was recently suggested that LLPS can initiate tau aggregation. However, the evidence for this was very limited and largely based on optical microscopy observations (13).In the present study, we explored the relationship between pathogenic mutations of tau, protein LLPS, and aggregation into amyloid fibrils. Our data show that, in contrast to previous suggestions (13), pathogenic mutations within the pseudorepeat region do not affect the propensity of tau to undergo LLPS. These mutations, however, do dramatically accelerate the liquid-to-solid phase transition within the droplets, leading to rapid formation of fibrillar aggregates. Most important, this study also reveals a previously unrecognized mechanism by which LLPS can regulate the rate of amyloid formation in mixtures containing tau isoforms with different aggregation propensities. These findings strongly suggest that LLPS may play a major regulatory role in the formation of pathological tau aggregates in neurodegenerative diseases.     

Segregation,integration, and balance of large-scale resting brain networks configure different cognitive abilities

Diverse cognitive processes set different demands on locally segregated and globally integrated brain activity. However, it remains an open question how resting brains configure their functional organization to balance the demands on network segregation and integration to best serve cognition. Here we use an eigenmode-based approach to identify hierarchical modules in functional brain networks and quantify the functional balance between network segregation and integration. In a large sample of healthy young adults (n = 991), we combine the whole-brain resting state functional magnetic resonance imaging (fMRI) data with a mean-filed model on the structural network derived from diffusion tensor imaging and demonstrate that resting brain networks are on average close to a balanced state. This state allows for a balanced time dwelling at segregated and integrated configurations and highly flexible switching between them. Furthermore, we employ structural equation modeling to estimate general and domain-specific cognitive phenotypes from nine tasks and demonstrate that network segregation, integration, and their balance in resting brains predict individual differences in diverse cognitive phenotypes. More specifically, stronger integration is associated with better general cognitive ability, stronger segregation fosters crystallized intelligence and processing speed, and an individual’s tendency toward balance supports better memory. Our findings provide a comprehensive and deep understanding of the brain’s functioning principles in supporting diverse functional demands and cognitive abilities and advance modern network neuroscience theories of human cognition.

The brain dynamically reconfigures its functional organization to support diverse cognitive task performances (1, 2). Successful reconfiguration underlying better task performance relies not only on sufficiently independent processing in specialized subsystems (i.e., segregation) but also on effective global cooperation between different subsystems (i.e., integration) (1–6). It has been observed that diverse cognitive tasks set different demands on segregation and integration (3, 5, 7–12). Higher segregation has been linked to simple motor tasks, and higher integration seems to underlie performance on tasks with a heavy cognitive load (8–12). However, it remains a great challenge to understand how the brain’s functional organization is configured to support heterogeneous demands on segregation and integration for diverse cognitive processes.Independently from specific task demands, the brain’s functional organization at rest can mirror relevant task-induced activity patterns and thus predict task performance (13, 14). Emerging evidence suggests that smaller differences between functional patterns at rest versus task states can facilitate better cognitive performance (13–16). Since diverse cognitive tasks differently demand on segregation and integration (3, 5, 7–12), the brain’s functional organization at rest is expected to possess the intrinsic capability of supporting diverse cognitive processes. Furthermore, previous studies suggest that healthy resting brains operate near a critical state to render the capability of rapidly exploring and switching in the brain’s state space with large operating repertoires (3, 13, 17–19). Resting brains are thus supposed to balance the segregation and integration (17, 20), so as to satisfy competing cognitive demands. However, this theory still lacks empirical evidence regarding whether large-scale brain networks at rest entail a balance between segregation and integration and whether the functional balance is associated with individual differences in cognitive abilities.To date, most of the relationships between brain functional configurations at rest and cognitive abilities are based on single tasks (7–12) that assess only specific aspects of cognition. General and domain-specific cognitive abilities are modeled at the latent level based on multiple tasks in differential psychology (21–24). These latent cognitive abilities are generalizations across tasks of the same domain and account for measurement error (25), and thus, they are much more suitable to reveal the neural basis of individual differences in human cognition. Recently, a cross-disciplinary network neuroscience theory (NNT) proposed a general framework to investigate the neural basis of cognitive abilities relying on system-wide topology characteristics and the dynamics of brain networks (26). According to NNT, brain networks functioning in an easy-to-reach state serve crystallized intelligence, whereas a difficult-to-reach state is needed for fluid intelligence (26). General cognitive ability, which is a statistical summary of fluid and crystallized intelligence, is considered to be facilitated by the capacity to flexibly switch between the above mentioned network states, i.e., an optimal balance between local and global processing (26). These predictions are still built upon a fragile empirical basis (27). Elucidating the relationship between functional balance and different cognitive abilities is crucial for validating and reframing NNT, particularly regarding the question of whether a functional balance in the brain at the resting state is beneficial for general cognitive ability of individuals.Before these questions can be robustly answered, the balance between segregation and integration in the large-scale brain must be explicitly defined and quantified. The modular structure of brain’s functional connectivity (FC) networks is known to provide the basis for specialized information processing within modules and the integration between them (8, 10, 15, 26, 28, 29). Although many studies have applied measures based on modules at a single level to study functional segregation and integration (7, 8, 10, 15, 28, 30), empirical evidence for a balance in the brain’s functional organization is still lacking. In fact, brain FC networks are hierarchically organized (31–33). Such an organization potentially supports nested segregation and integration across multiple levels. However, the classically applied modular partition at a single level does not allow the detection of hierarchical modules across multiple levels (34, 35). This insufficiency seems to be the main reason for the lack of a robust quantitative definition of the balance between segregation and integration.Here we explicitly identified the functional balance based on hierarchical modules of resting brain FC networks and explored associations with diverse cognitive abilities in a sample of 991 heathy young adults from the Washington University–University of Minnesota Consortium (WU-Minn) Human Connectome Project (HCP) (36). Using our previously published method called nested-spectral partition (NSP) based on eigenmodes (19), we first detected hierarchical modules in FC networks to propose an explicit balance measure. Second, we combined real data and a Gaussian linear model to demonstrate the functional balance in the group-averaged brain at the resting state. Then, we investigated individual differences in the balance and relationships to the temporal switching between segregated and integrated states. Finally, we applied structural equation modeling (SEM) to estimate latent factors of general and domain-specific cognitive abilities and investigated how segregation, integration, and their balance configure them.     

Identifying hydrophobic protein patches to inform protein interaction interfaces

Interactions between proteins lie at the heart of numerous biological processes and are essential for the proper functioning of the cell. Although the importance of hydrophobic residues in driving protein interactions is universally accepted, a characterization of protein hydrophobicity, which informs its interactions, has remained elusive. The challenge lies in capturing the collective response of the protein hydration waters to the nanoscale chemical and topographical protein patterns, which determine protein hydrophobicity. To address this challenge, here, we employ specialized molecular simulations wherein water molecules are systematically displaced from the protein hydration shell; by identifying protein regions that relinquish their waters more readily than others, we are then able to uncover the most hydrophobic protein patches. Surprisingly, such patches contain a large fraction of polar/charged atoms and have chemical compositions that are similar to the more hydrophilic protein patches. Importantly, we also find a striking correspondence between the most hydrophobic protein patches and regions that mediate protein interactions. Our work thus establishes a computational framework for characterizing the emergent hydrophobicity of amphiphilic solutes, such as proteins, which display nanoscale heterogeneity, and for uncovering their interaction interfaces.

Protein–protein interactions play a crucial role in numerous biological processes, ranging from signal transduction and immune response to protein aggregation and phase behavior (1–3). Consequently, being able to understand, predict, and modulate protein interactions has important implications for understanding cellular processes and mitigating the progression of disease (4, 5). A necessary first step toward this ambitious goal is uncovering the interfaces through which proteins interact (6–8). In principle, identifying hydrophobic protein regions, which interact weakly with water, should be a promising strategy for uncovering protein interaction interfaces (9, 10). Indeed, the release of weakly interacting hydration waters from hydrophobic regions can drive protein interactions, as well as other aqueous assemblies (11–13). However, even when the structure of a protein is available at atomistic resolution, it is challenging to identify its hydrophobic patches because they are not uniformly nonpolar, but display variations in polarity and charge at the nanoscale. Moreover, the emergent hydrophobicity of a protein patch stems from the collective response of protein hydration waters to the nanoscale chemical and topographical patterns displayed by the patch (14–20) and cannot be captured by simply counting the number of nonpolar groups in the patch, or even through more involved additive approaches, such as hydropathy scales or surface-area models (21–28).To address this challenge, we build upon seminal theoretical advances and molecular simulation studies, which have shown that near a hydrophobic surface, it is easier to disrupt surface–water interactions and form interfacial cavities (29–34). To uncover protein regions that have the weakest interactions with water, here, we employ specialized molecular simulations, wherein protein–water interactions are disrupted by systematically displacing water molecules from the protein hydration shell (35–37). By identifying the protein patches that nucleate cavities most readily in our simulations, we are then able to uncover the most hydrophobic protein regions. Interestingly, we find that both hydrophobic and hydrophilic protein patches are highly heterogeneous and contain comparable numbers of nonpolar and polar atoms. Our results thus highlight the nontrivial relationship between the chemical composition of protein patches and their emergent hydrophobicity (24–26), and further emphasize the importance of accounting for the collective solvent response in characterizing protein hydrophobicity (16). We then interrogate whether the most hydrophobic protein patches, which nucleate cavities readily, are also likely to mediate protein interactions. Across five proteins that participate in either homodimer or heterodimer formation, we find that roughly 60 to 70% of interfacial contacts and only about 10 to 20% of noncontacts nucleate cavities. Our work thus provides a versatile computational framework for characterizing hydrophobicity and uncovering interaction interfaces of not just proteins, but also of other complex amphiphilic solutes, such as cavitands, dendrimers, and patchy nanoparticles (38–41).     

Cholinergic suppression of hippocampal sharp-wave ripples impairs working memory

Learning and memory are assumed to be supported by mechanisms that involve cholinergic transmission and hippocampal theta. Using G protein–coupled receptor-activation–based acetylcholine sensor (GRAB_ACh3.0) with a fiber-photometric fluorescence readout in mice, we found that cholinergic signaling in the hippocampus increased in parallel with theta/gamma power during walking and REM sleep, while ACh3.0 signal reached a minimum during hippocampal sharp-wave ripples (SPW-R). Unexpectedly, memory performance was impaired in a hippocampus-dependent spontaneous alternation task by selective optogenetic stimulation of medial septal cholinergic neurons when the stimulation was applied in the delay area but not in the central (choice) arm of the maze. Parallel with the decreased performance, optogenetic stimulation decreased the incidence of SPW-Rs. These findings suggest that septo–hippocampal interactions play a task-phase–dependent dual role in the maintenance of memory performance, including not only theta mechanisms but also SPW-Rs.

The neurotransmitter acetylcholine is thought to be critical for hippocampus-dependent declarative memories (1, 2). Reduction in cholinergic neurotransmission, either in Alzheimer’s disease or in experiments with cholinergic antagonists, such as scopolamine, impairs memory function (3–8). Acetylcholine may bring about its beneficial effects on memory encoding by enhancing theta rhythm oscillations, decreasing recurrent excitation, and increasing synaptic plasticity (9–11). Conversely, drugs which activate cholinergic receptors enhance learning and, therefore, are a neuropharmacological target for the treatment of memory deficits in Alzheimer’s disease (5, 12, 13).The contribution of cholinergic mechanisms in the acquisition of long-term memories and the role of the hippocampal–entorhinal–cortical interactions are well supported by experimental data (5, 12, 13). In addition, working memory or “short-term” memory is also supported by the hippocampal–entorhinal–prefrontal cortex (14–16). Working memory in humans is postulated to be a conscious process to “keep things in mind” transiently (16). In rodents, matching to sample task, spontaneous alternation between reward locations, and the radial maze task have been suggested to function as a homolog of working memory [“working memory like” (17)].Cholinergic activity is a critical requirement for working memory (18, 19) and for sustaining theta oscillations (10, 20–22). In support of this contention, theta–gamma coupling and gamma power are significantly higher in the choice arm of the maze, compared with those in the side arms where working memory is no longer needed for correct performance (23–26). It has long been hypothesized that working memory is maintained by persistent firing of neurons, which keep the presented items in a transient store in the prefrontal cortex and hippocampal–entorhinal system (27–31), although the exact mechanisms are debated (32–37). An alternative hypothesis holds that items of working memory are stored in theta-nested gamma cycles (38). Common in these models of working memory is the need for an active, cholinergic system–dependent mechanism (39–41). However, in spontaneous alternation tasks, the animals are not moving continuously during the delay, and theta oscillations are not sustained either. During the immobility epochs, theta is replaced by intermittent sharp-wave ripples (SPW-R), yet memory performance does not deteriorate. On the contrary, artificial blockade of SPW-Rs can impair memory performance (42, 43), and prolongation of SPW-Rs improves performance (44). Under the cholinergic hypothesis of working memory, such a result is unexpected.To address the relationship between cholinergic/theta versus SPW-R mechanism in spontaneous alternation, we used a G protein–coupled receptor-activation–based acetylcholine sensor (GRAB_ACh3.0) (45) to monitor acetylcholine (ACh) activity during memory performance in mice. In addition, we optogenetically enhanced cholinergic tone, which suppresses SPW-Rs by a different mechanism than electrically or optogenetically induced silencing of neurons in the hippocampus (43, 44). We show that cholinergic signaling in the hippocampus increases in parallel with theta power/score during walking and rapid eye movement (REM) sleep and reaches a transient minimum during SPW-Rs. Selective optogenetic stimulation of medial septal cholinergic neurons decreased the incidence of SPW-Rs during non-REM sleep (46–48), as well as during the delay epoch of a working memory task and impaired memory performance. These findings demonstrate that memory performance is supported by complementary theta and SPW-R mechanisms.     

Homocysteine fibrillar assemblies display cross-talk with Alzheimer’s disease β-amyloid polypeptide

High levels of homocysteine are reported as a risk factor for Alzheimer’s disease (AD). Correspondingly, inborn hyperhomocysteinemia is associated with an increased predisposition to the development of dementia in later stages of life. Yet, the mechanistic link between homocysteine accumulation and the pathological neurodegenerative processes is still elusive. Furthermore, despite the clear association between protein aggregation and AD, attempts to develop therapy that specifically targets this process have not been successful. It is envisioned that the failure in the development of efficacious therapeutic intervention may lie in the metabolomic state of affected individuals. We recently demonstrated the ability of metabolites to self-assemble and cross-seed the aggregation of pathological proteins, suggesting a role for metabolite structures in the initiation of neurodegenerative diseases. Here, we provide a report of homocysteine crystal structure and self-assembly into amyloid-like toxic fibrils, their inhibition by polyphenols, and their ability to seed the aggregation of the AD-associated β-amyloid polypeptide. A yeast model of hyperhomocysteinemia indicates a toxic effect, correlated with increased intracellular amyloid staining that could be rescued by polyphenol treatment. Analysis of AD mouse model brain sections indicates the presence of homocysteine assemblies and the interplay between β-amyloid and homocysteine. This work implies a molecular basis for the association between homocysteine accumulation and AD pathology, potentially leading to a paradigm shift in the understanding of AD initial pathological processes.

Alzheimer’s disease (AD) is the most common neurodegenerative disorder, currently affecting tens of millions of individuals globally and leading to immense social and financial impacts (1, 2). Despite the vast efforts to develop a pharmacological treatment for the disease, recent clinical trials had failed (3, 4). While it is very clear that amyloid formation is associated with AD (5, 6) and genetic variations in the gene coding for the β-amyloid polypeptide are associated with early onset of the disease (7), direct targeting of the aggregation of AD-associated pathological proteins and polypeptides has so far not resulted in clinical development of any disease-modifying treatment (8–10). Therefore, there is an essential need to understand the early biological changes that may induce the diverse pathologies observed in AD and other forms of dementia in order to identify new therapeutic targets (10).In the last decades, an enormous body of research had provided important information on the amyloid cascade, oxidative stress, and inflammatory response that are involved in AD (3, 11). Specifically, the notion of β-amyloid toxicity and extracellular plaque formation as the main cause of neuronal and synaptic loss has been extensively studied (12–14). Yet, the key to AD treatment and prevention remains elusive, and the initial steps leading to the formation and accumulation of these protein aggregates and the role of nonproteinaceous agents in this process are still not understood (10). Since only 1% of AD cases result from a familial mutation and the majority of patients are sporadic (2, 4), it is important to explore new directions to understand the biological mechanisms underlying these cases. Studies of metabolite profiling in brain regions and body fluids of AD and Parkinson’s disease (PD) patients show interference with specific metabolic pathways (15–19). Homocysteine (Hcy), a noncoded amino acid, was identified as a major risk factor for AD as high plasma concentrations were associated with the progression of the disease (20–22). Higher Hcy serum concentration was also correlated with behavioral and psychological symptoms of AD (23) and was associated with changes in motor function and cognitive decline in PD as well as with a more severe cognitive impairment in elderly adults (24–26). Furthermore, it was shown that significantly decreased hippocampal and cortical volume is associated with increased Hcy plasma concentration (27).Cystathionine β-synthase (CBS) deficiency, leading to excess of Hcy, results in the hyperhomocysteinemia inborn error of metabolism (IEM) disorder characterized by severe cognitive consequences (28–30). While elevated plasma Hcy is frequently reported as a strong and independent risk factor for the development of cognitive decline and dementia, the mechanism of its involvement is elusive (20, 31–34). Interestingly, the association between Hcy and AD-related pathological proteins was also demonstrated. Hcy-rich medium was shown to be cytotoxic to hippocampal and cortical neurons, resulting in increased β-amyloid–induced cell death (35–37). In addition, Hcy was found to bind β-amyloid_1-40, thereby stimulating β-sheet structure formation to facilitate its deposition. Indeed, induced Hcy accumulation in the brains of rats caused an elevation of β-amyloid deposition (38, 39). Furthermore, Hcy increased total tau and phosphorylated tau protein levels as well as the level of tau oligomers (40). Although the involvement of Hcy accumulation in AD pathology is evidential, no mechanistic insight has so far been suggested.We have previously demonstrated that small metabolites can self-assemble into amyloid-like structures with amyloidogenic characteristics (41–44). The presence of metabolite assemblies in IEM disorders (e.g., phenylalanine in Phenylketonuria) exemplifies their physiological importance in pathologically diversified diseases. Interestingly, recent studies demonstrated that metabolite assemblies could cross-seed the aggregation of proteins under physiological conditions, thereby suggesting a possible mechanism in which accumulated metabolites interfere with protein function and folding (45, 46). Assemblies of quinolinic acid, an endogenous neurometabolite that is involved in the pathology of PD, induce the aggregation of α-synuclein both in vitro and in cell culture (45). In addition, phenylalanine preformed fibrils were shown to initiate the aggregation of several proteins under physiological conditions (46). Metabolite accumulation, structure formation, and seeding of proteins may thus underlie the unknown role of metabolites in neurodegenerative pathologies (47). Specifically, seeding of amyloidogenic proteins by preformed fibrils may be part of the mechanisms underlying the stereotypical spreading of toxic aggregates in the brains of AD patients.We recently established an in vivo yeast model for IEM disorders by genetically modifying the yeast to reflect the mutations found in patients showing accumulation of the adenine nucleobase and its derivatives (48). Yeast model systems provide a powerful platform to elucidate the pathophysiology of diseases, as well as for the screening and development of disease-modifying therapeutics (49). This model was found to be a valid system, as supported by its robust sensitivity to adenine feeding and by the fact that adenine supramolecular structures could be detected. Furthermore, the addition of a generic fibrillation-modifying polyphenolic compound rescued the toxic effect without lowering the concentration of adenine, indicating the therapeutic potential of our model for the modulation of structure formation (48, 50).Here, aiming to explore the role of Hcy in AD, we demonstrate the formation of amyloid-like fibrils by Hcy in vitro and in vivo in a yeast model. Structural characterization of the Hcy fibrils and their cytotoxic effect were both studied. In addition, we revealed that polyphenolic inhibitors could rescue the toxic effect of Hcy assemblies and inhibit its structure formation. Remarkably, immunohistochemistry allowed the detection of Hcy fibrils in the brain of AD model mice as well as the apparent interplay between Hcy and β-amyloid. Finally, we demonstrated the cross-seeding of AD-related pathological protein by Hcy assemblies. Our work suggests a research direction for the association between metabolite accumulation and the initiation of neurodegenerative processes, thus offering a path for the development of therapeutic treatments that will target the key early stages of the disease.