Nikolaos Louros

ATTR amyloidosis is caused by transthyretin (TTR) amyloid deposition, yet the sequence-encoded events linking TTR misfolding to fibril nucleation and structural polymorphism remain incompletely defined. Here, we exploit the modular organization of patient-derived TTR fibrils to investigate two components of the pathological core: an N-terminal β-hairpin spanning residues 11–35 (N-TTR) and a larger C-terminal fragment spanning residues 57–123 (C-TTR). Both fragments independently form β-rich amyloid fibrils, as demonstrated by electron microscopy, circular dichroism, and fluorescence spectroscopy. Yet, their activities differ markedly. N-TTR fibrils promote full-length TTR aggregation and seed in an engineered cellular biosensor platform established to detect templated TTR assembly, whereas C-TTR aggregates show no detectable templating activity. Cryo-electron microscopy reveals two N-TTR polymorphs that preserve structural features of disease-derived folds, while energetic profiling identifies N-TTR as a stabilizing hotspot within ex vivo structures, providing a basis for this templating functionality. These findings reveal a functional hierarchy among amyloidogenic segments of TTR, since distinct regions form fibrils independently, but only those with structural compatibility efficiently template the parent protein. N-TTR therefore represents an autonomous amyloidogenic segment that links local sequence propensity to TTR nucleation, templating, and fibril polymorphism.

TATA-box binding protein-associated factor 15 (TAF15) is an RNA-binding protein and the primary fibrillar constituent in a subset of frontotemporal lobar degeneration (FTLD) cases. However, the molecular determinants underlying TAF15 aggregation remain unclear. Here, we show that TAF15 forms amyloid fibrils under physiological conditions and develop a cellular biosensor to monitor its propagation. Both recombinant TAF15 fibrils and pathological aggregates extracted from FTLD patient brains selectively seed TAF15 biosensor cells, demonstrating prion-like properties. The closely related protein FUS does not seed TAF15 aggregation, revealing a cross-seeding barrier, but partially incorporates into inclusions during TAF15-induced seeding, potentially explaining their pathological overlap in FTLD. Computational and peptide-based mapping identifies aggregation-prone motifs within the low-complexity domain that stabilize ex vivo fibril cores and drive TAF15 propagation. These findings establish TAF15 as an amyloid-forming, prion-like protein and define sequence determinants underlying its self-assembly, providing a mechanistic framework for FTLD-TAF15 and potential therapeutic targets.

Functional amyloids serve as structural scaffolds across biology, yet the molecular architecture and assembly principles of many remain unresolved. The lepidopteran egg coat, or chorion, presents a striking example: hundreds of paralogous proteins sharing a conserved central domain form a mechanically resilient amyloid matrix essential for embryo protection. Here, combining evolutionary analysis of more than 500 sequences with cryo-electron microscopy and biophysical assays, we determine the atomic structure of chorion amyloid filaments and uncover the principles governing their assembly. Contrary to previous structural predictions, chorion filaments adopt a β-serpentine fold stabilized by a short hexapeptide motif that forms homotypic steric-zipper interfaces, self-assembles autonomously, and seeds full-length filament growth. Amyloid formation proceeds through secondary nucleation, while thermodynamic and structural analyses support a hierarchical assembly mechanism in which motif-driven interactions nucleate filament formation prior to consolidation of the mature yet lalbile protofilament core. These findings establish the molecular basis of insect egg-coat assembly and demonstrate that mechanisms commonly associated with pathological aggregation can also operate within a biologically regulated functional amyloid framework.

Amyloid fibrils are intrinsically polymorphic protein assemblies that form distinct structural strains linked to diverse biological and pathological outcomes. Yet, the principles governing how sequence encodes diverse fibril architectures, and the extent to which a given fold constrains underlying amino-acid sequence compatibility, remain poorly understood. Here, we apply generative protein design to directly interrogate the sequence–structure relationship of defined fibril architectures, using α-synuclein (αS), a protein known to form highly polymorphic amyloid fibrils, as a model system. Sampling sequence space under structural constraints reveals a continuous compatibility manifold in which diverse sequences encode a common amyloid architecture. De novo designed sequences assemble into fibrils, often with enhanced aggregation efficiency relative to αS. A subset exhibits strain-like behaviour, including similar morphologies, efficient cross-templating, and induction of αS cellular propagation, thereby functionally validating structural compatibility with the native fibril fold. Energetic analysis shows that stability is achieved through distinct but compensatory interactions, supporting a non-unique mapping between sequence and structure. Together, our results define a continuous and constrained compatibility landscape underlying amyloid strains, providing a framework for understanding the determinants of polymorphism and establishing generative protein design as a strategy to access this space, interrogate amyloid sequence–structure relationships, and engineer fibrillar protein assemblies and functional biomaterials.

Amyloid assembly in vivo occurs in complex environments where multiple aggregation-prone species coexist. Aβ and medin are prevalent amyloids in ageing humans that co-localize in cerebral amyloid angiopathy (CAA), yet their structural interactions remain poorly understood. Here, using cryo-electron microscopy, we determine high-resolution fibril structures from in vitro mixtures of Aβ40 and medin. From the same reaction, we resolve three distinct fibril populations: (i) a previously characterized Aβ40 polymorph that also forms in isolation, (ii) a Aβ40 polymorph with Aβ42-like features, including ordered N- and C-terminal regions, and (iii) the atomic structure of full-length medin fibrils. Biochemical and immunogold analyses demonstrate Aβ–medin association within mixed assemblies, though medin is not resolved within the ordered Aβ core. These findings support two non-exclusive mechanisms: transient heterotypic interactions redirecting Aβ folding, or partial medin incorporation into fibril architecture. Our data reveal how coexisting amyloids remodel each other’s polymorphic landscapes.

TATA-box binding protein–associated factor 15 (TAF15) is an RNA-binding member of the FET family recently identified as the primary fibrillar constituent in a subset of frontotemporal lobar degeneration (FTLD-FET) cases. Although TAF15 is also linked to amyotrophic lateral sclerosis (ALS), the molecular basis and propagation behavior of its aggregates remain unknown. In this work, we show that recombinant TAF15 forms amyloid fibrils under physiological conditions and developed a single-fluorophore TAF15 biosensor to quantitatively monitor their cellular propagation. Using this system, we demonstrate that both recombinant TAF15 fibrils and pathological aggregates extracted from atypical FTLD with ubiquitin inclusions (aFTLD-U) patient brains seed aggregation efficiently and transmit serially between cells, demonstrating hallmark features of prion-like propagation. Seeding was specific to TAF15 and absent for other amyloidogenic proteins, including the homologous protein fused-in-sarcoma (FUS), revealing an unexpected cross-seeding barrier. Occasional colocalization of FUS within TAF15 inclusions was observed upon transient co-expression, suggesting that FUS can be passively recruited rather than acting as an inducer of pathology in FTLD-FET brains. Computational and peptide-based experimental mapping identified multiple aggregation-prone regions within the TAF15 low-complexity domain that coincide with hotspots stabilizing the core of ex vivo TAF15 amyloid fibrils. These short motifs encode the propagation propensity of TAF15 aggregation in vitro and in cells. Together, these findings establish TAF15 as a bona fide amyloid-forming, prion-like protein and define the sequence grammar underlying its self-assembly, providing a mechanistic framework for its role in FTLD-FET and ALS and offering tractable molecular targets for therapeutic intervention.

Amyloid fibrils adopt diverse structural polymorphs linked to disease-specific phenotypes, but the thermodynamic principles guiding their formation and maturation remain unclear. Here, we apply energetic profiling to structural time series from cryo-EM datasets of IAPP, tau, and α-synuclein to decode the principles governing fibril maturation and polymorphic divergence. By mapping residue-level free energy contributions across experimentally resolved assembly pathways, we reconstruct their maturation trajectories and find that amyloid assembly is anchored by aggregation-prone regions that serve as sequence-encoded stabilizing motifs. As assembly progresses, these motifs are reorganized and expanded, while additional regions introduce structural frustration that enables conformational flexibility. Environmental cofactors such as metal ions or polyanions are observed in association with regions of structural remodeling, where they may act to compensate for otherwise energetically strained conformations. This framework offers mechanistic insight into how distinct polymorphs arise from a common sequence and mature through both intrinsic and extrinsic thermodynamic influences.

Amyloid fibrils underpin both functional and pathological protein assemblies and exhibit extensive structural polymorphism. More than 600 high-resolution fibril structures are now available across over 50 protein sequences, yet comparative analysis has been hindered by fragmented resources and inconsistent annotation. Here we present Amyloid Explorer, an open-access platform that integrates the complete fibril archive into a standardized, quality-controlled, and thermodynamically annotated framework. Each entry includes residue- and segment-level stability maps, structural quality metrics, and interactive visualization tools. Global analysis across the dataset reveals conserved rules of amyloid assembly, including cooperative cores, framework polymorphism through reuse of conserved segments in distinct folds, polymorph-specific energetic anchors, and short frustration zones. By combining scale with accessibility, Amyloid Explorer transforms a static archive into a discovery platform for mechanistic insight, classification, and the design of aggregation modulators.

Motivation: Atomic Force Microscopy-based Infrared spectroscopy (AFM-IR) is a novel and innovative method for label-free high-resolution structural biology. However, the nature of the data files generated by AFM-IR instruments precludes investigation by conventional open-source scientific image analysis software suites. As a result, reporting of AFM-IR datasets is not standardized and the data itself is difficult to audit. Results: We have developed a web application that allows anyone to open, review, and audit raw AFM-IR data files easily and without deep knowledge of the method. It also exposes all metadata recorded by the microscope at the time of measurement. The web application is based on a Python package that supports custom data analyses within the scientific Python ecosystem. This tool provides an accessible, transparent solution for AFM-IR data review, with the potential to support reproducibility and standardization in AFM-IR research and encourage wider adoption of this innovative spectroscopy method. Availability and implementation: The web app is hosted at https://anasys-python-tools-gui.streamlit.app. Its source code is listed at https://github.com/wduverger/anasys-python-tools-gui. The underlying Python package is available at https://github.com/GeorgRamer/anasys-python-tools and can be installed using pip.