Structural polymorphism of ex-vivo ALECT2 amyloid fibrils revealed by cryo-EM

Domain: neuroscience
Published: 2026-04-11
Editorial outcome: major_revision

Abstract
ALECT2 amyloidosis is a rare systemic disease characterized by the pathological deposition of leukocyte cell-derived chemotaxin-2 (LECT2) as amyloid fibrils, primarily affecting the kidneys and liver. The molecular mechanisms underlying LECT2 aggregation remain poorly defined, hindering diagnostic and therapeutic development. Here, we present cryo-electron microscopy structures of ex-vivo ALECT2 fibrils extracted from a patient’s kidney. We identified three fibril polymorphs: a predominant single-protofilament morphology and two minor double-protofilament morphologies. The dominant single-protofilament morphology comprises the full-length 133-residue LECT2 protein and retains all three native disulfide bonds. Low-resolution reconstructions of double-protofilament morphologies suggest they adopt a similar fold to the single protofilament morphology, but form paired assemblies with different inter-filament interfaces. Mass spectrometry also reveals acetylation within the fibrils. These findings offer critical insights into the structural basis of ALECT2 amyloid formation and identify molecular features that could inform future diagnostic and therapeutic approaches.

Introduction
ALECT2 amyloidosis is a protein disorder caused by the pathological deposition of Leucocyte Cell-Derived Chemotaxin-2 (LECT2) as amyloid fibrils in various tissues and organs1. The kidneys and liver are predominantly affected, while the spleen, lungs, adrenal glands, and colon are also involved to a lesser extent with varying degrees of penetrance and clinical overlap. ALECT2 amyloidosis has emerged as the third most common form of renal amyloidosis in the United States2. Worldwide, the disease exhibits a distinct ethnic predisposition, with higher prevalence observed in specific populations, including Hispanics of Mexican descent, Punjabis, Egyptians, Sudanese, Chinese, and Native Americans3. Currently, no targeted therapies are available for ALECT2 amyloidosis, and treatment remains largely supportive, with kidney transplantation considered as an option in patients experiencing advanced renal disease2.

The native structure of LECT2 provides insight into the factors that may contribute to its misfolding and aggregation in amyloidosis. LECT2 is produced by the liver as a 151-residue protein and released into the systemic circulation as a 133-residue protein following signal peptide cleavage. Functionally, mature LECT2 is a chemotactic factor involved in various biological processes including the immune response, where it attracts neutrophils to sites of inflammation and metabolism4. Structurally, the globular form of human LECT2 contains three disulfide bonds and adopts an M23 metalloendopeptidase fold. In native state, this fold includes a conserved Zn(II) coordination geometry formed by His35, Asp39, and His120, with the fourth site occupied by water instead of a coordinating residue, rendering LECT2 enzymatically inactive4. In disease state, the loss of zinc coordination has been suggested to destabilize the native structure of LECT2, promoting its aggregation and conversion into amyloid fibrils5,6. Interestingly, all patients diagnosed with ALECT2 amyloidosis are homozygous for the G-allele single-nucleotide polymorphism (at cDNA position 172; allele frequency of 0.477 overall), resulting in the presence of a valine at position 407-9. In vitro studies using microfluidics sSystem have shown that the LECT2-I40V variant exhibits an increased propensity for fibril formation compared to wild-type LECT26.

Structural studies of amyloid LECT2 lag, with limited models largely derived from recombinant systems and computational tools. A study combining experimental and computational approaches identified two "aggregation prone regions", residues from Val38 to Gly58 and from Val73 to Lys88, considered critical interfaces for the aggregation of recombinant LECT210. A cryo-electron microscopy (cryo-EM) study of recombinant LECT2-I40V fibrils identified residues Met55 to Ile75, which forms the key intermolecular interface stabilizing the amyloid structure11. These observations highlight the critical need to study the structures of ex-vivo ALECT2 amyloid fibrils.

In the present work, we use cryo-EM to determine the structure of ex-vivo ALECT2 amyloid fibrils extracted from the kidney of an ALECT2 amyloidosis patient1. Benson and colleagues reported that this patient was homozygous for the G allele leading to I40V substitution1, which we confirmed by mass spectrometry. We found that ALECT2-I40V fibrils can assemble into three distinct morphologies: a single protofilament morphology (the major population) and two double protofilament morphologies (the minor populations). The single protofilament morphology incorporated all 133 residues of the LECT2 protein with the original three disulfide bonds preserved. While the density maps of the two double protofilament morphologies were of lower resolution, they appear to adopt a similar fold to the single protofilament morphology but forming paired assemblies with distinct inter-filament interfaces. Using mass spectrometry, we also detected lysine acetylation in ALECT2 amyloid fibrils. Leveraging the structural and biochemical information, we speculate on the possible mechanism of ALECT2 amyloid formation. Our study may provide critical structural information of ALECT2 amyloid fibrils, laying a foundation for developing targeted diagnostic and therapeutic approaches against ALECT2 amyloidosis.

Results
Histological and biochemical characterization of ALECT2 fibrils.
We obtained fresh frozen ALECT2 tissue samples from the kidney of a patient homozygous for the I40V variant and performed histological staining. The patient (>60 years in age) presented with nephrotic syndrome caused by renal amyloid deposits, which slowly progressed to renal failure over several years1. They underwent nephrectomy for renal carcinoma, after which they progressed to end-stage renal disease requiring dialysis. The sample reported here was collected post-nephrectomy and obtained from the laboratory of Dr. Merrill D. Benson at the University of Indiana. We performed a histological analysis to confirm the presence of amyloids in kidney sections. Hematoxylin and eosin (H&E) staining highlighted tissue architecture while Congo red staining and Thioflavin-S staining of the kidney tissue sections revealed abundant amyloid deposits within the glomeruli and the interstitium of the kidney (Fig. 1a).

We extracted ALECT2 fibrils from the tissue using a water-EDTA based protocol adapted from a previously described method12. Transmission electron microscopy with negative staining confirmed the presence of well dispersed fibrillar structures in the extractions (Fig. 1b). We verified the protein identity using mass spectrometry (Fig. 1c) and western blot analysis with a polyclonal antibody against full-length human LECT2 (Supplementary Fig. 1a). Western blot analysis showed a ~16 KDa band that coincides with the mass of intact LECT2 protein along with additional bands at higher molecular weight, indicating the presence of multimeric species (Supplementary Fig. 1a-b). Intact mass spectrometry confirmed the presence of full-length LECT2 protein, carrying a valine at position 40 (Supplementary Fig. 1b). The intact mass spectra also revealed the presence of three disulfide bonds, with no detectable proteolytic cleavage products, consistent with the western blot analysis (Supplementary Fig. 1a-b). Interestingly, intact mass spectrometry of the fibrils revealed a secondary minor peak with an additional mass of 42 Da (Supplementary Fig. 1b and Supplementary table 1), suggestive of lysine acetylation13. Indeed, chymotrypsin-based mass spectrometry analysis suggests the presence of multiple lysine acetylation sites (Supplementary Table 2). A low-abundance N-terminally acetylated peptide was detected, but its signal intensity was >200-fold lower than that of the corresponding non-acetylated peptide based on extracted ion chromatograms (XIC). This indicates that N-terminal acetylation, if present, occurs only in a very small fraction of molecules (Supplementary Table 2).

Cryo-EM data processing, refinement, and modeling of ALECT2 amyloid fibrils
We collected cryo-EM images of ALECT2 fibrils to investigate their structural organization in the kidney (Fig. 2a). Two-dimensional (2D) classification revealed two distinct fibril morphologies: the most prevalent species consisting of one single protofilament and a minor population of fibrils consisting of double protofilaments which could further be classified into two subpopulations based on their stitching (Supplementary Fig. 2a-c). Three-dimensional (3D) classification confirmed the presence of the three morphologies (Fig. 2b and Supplementary Fig. 3). The reconstructed single protofilament morphology displayed a rise of 4.75 Å per layer and a helical crossover of 940 Å, organized with a C1 symmetry (Supplementary Fig. 4). A density map at a resolution 2.4 Å was obtained, providing detailed structural insights (Fig. 2c and Supplementary Fig. 5).

Leveraging the high resolution of the reconstructed map, we modeled the structure of the single protofilament morphology. The accurate positioning of peptide bonds revealed that the fibrils have a left-handed twist (Supplementary Fig. 4). Additionally, the well resolved electron-density for sidechains allowed us to unambiguously validate protein identity and sequence with a valine in position 40, consistent with the mass spectrometry data (Fig. 2c-d and Fig. 1c). We modeled all 133 residues of the full-length LECT2 sequence into the amyloid structure of the single protofilament morphology, supporting the intact mass spectrometry data and western blotting (Fig. 2c and Supplementary Fig. 1). The filament fold contains eleven β-strands (Fig. 2d). The amyloid structure of the fibril retained the three original disulfide bonds bridging Cys18 with Cys23, Cys7 with Cys42, and Cys81 with Cys124 (Fig. 2c and Supplementary Fig. 6a).

Molecular interactions stabilizing the single protofilament morphology.
We observe a non-planar arrangement of layers in the single-protofilament morphology that enables inter-layer interactions within the fibril. The top view of the filament appears highly folded upon itself with Gly45 serving as an inflection point contributing to this non-planar arrangement (Fig. 3a). This bend divides the polypeptide chain into two distinct planar regions: an N-terminal segment (Gly1–Gly45) and a C-terminal segment (Ser46–Leu133) (Fig. 3a-b). The two planes are related by a 7° rotation, approximately, which enables the interaction of three consecutive layers (Fig. 3c).

Additionally, we identified other molecular interactions that stabilize the fold and support fibril cohesion. These include intra-layer hydrogen bonds (Fig. 3d) and intra-layer salt bridges (Fig. 3e and Supplementary Fig. 7 a). Across the layers, the fibrils are stabilized by salt bridges such as or Glu14 of layer n with Arg16 of layer n+1 or Asp19 of layer n with Arg20 of layer n+1, (Fig. 3f-g). Additionally, sidechain stacking hydrogen bonding of Asn and Gln residues form a network of polar ladders that stabilize the fibril (Supplementary Fig. 7 c-d). π-π stacking interactions by aromatic residues add further stability (Supplementary Fig. 7e)14. Aromatic residues Tyr92 of layer n also interacts with Tyr132 of layer n+2 (Fig. 3c). The fold is further stabilized by multiple compact steric zippers formed by interdigitating residues for example residues Ile69 and Asn71 of 6 strand with residues Val119 and Ile121, of 10 strand (Supplementary Fig. 7f). Ordered water molecules also stabilize the layers such as those interacting with the Leu106, Phe52-Thr53 and Arg16-Thr17 (Supplementary Fig. 8). In addition to the water molecules, we also observed some non-proteinaceous densities, separated from the main fibril density (Fig. 2c). These densities do not match the typical density or coordination profiles of zinc or other metal ions, and their identity remains unconfirmed. Together these interactions contribute to the overall stability of the fold and across the fibril layers. We estimated the free energy of solvation of the ALECET2 fibrils and found that their solvation energy was -67.9 kcal/mol per chain and -0.51 kcal/mol per layer (Supplementary Fig. 9).

Structural characterization of double protofilament morphologies.
Although the number of particles was limited, we identified two distinct double-protofilament morphologies. Since the individual protofilaments in both double-protofilament morphologies adopt a fold closely resembling that of the single-protofilament morphology (Fig. 2c), we performed molecular docking to rigidly fit the single-protofilament model into the double-protofilament map (Fig. 4a, see paragraph below for more details). In both morphologies, the two protofilaments are rotated relative to each other. In the first morphology (crossover 1068Å, 4.75Å, C1 symmetry), the rotation angle is 180°, creating an interface between residues Ser11 and His21 on both protofilaments (Fig. 4a-b). In the second morphology (crossover 1056Å, rise 4.75Å, C1 symmetry), the rotation angle is ~35°, resulting in a smaller interface, where residues Ser11–Arg16 on one filament interact with His21–Arg16 on the other (Fig. 4a-b).

The final resolutions of the double protofilament 1 and 2 maps are 5.0 Å and 5.6 Å, respectively. At such resolutions, the backbone density appears hollow with undefined regions and the side chain features are not well resolved, preventing reliable model building and accurate calculation of the model-to-map correlation. Thus, we did not perform de novo modeling, but instead rigid body docked the high-resolution single protofilament structure into these lower resolution densities (Fig. 4a). We obtained a Q-score of 0.42 from the map of the double protofilament 1, reflecting interpretable correlation of model-to-map. In contrast, the map of the double protofilament 2 produced only a Q-score of 0.16, consistent with its lower resolution at 5.6 Å. Visual inspection of the fit indicates that the backbone of the single protofilament model docks reasonably well within the protofilament density of the double protofilament maps although local variations very likely exist (Fig. 4a).

By tracing the fibril segments corresponding to these two density maps back to their micrographs, we found that both double-protofilament morphologies and the single-protofilament morphology can coexist within a single fibril (Fig. 4c). Tracing was performed using well-resolved particles that persist through the refinement process. Consequently, protofilament coverage remains incomplete and the remaining protofilaments may contain one or all three polymorphs.

Computational prediction of Aggregation-Prone Regions (APRs).
We computationally predicted Aggregation-Prone Regions (APRs) using four prediction models (WALTZ, TANGO, Aggrescan, and AmylPred)15-18. We then calculated an overall APR prediction score for each residue ranging from zero to four, based on the number of prediction models that predicted the presence of an APR at that particular residue19. We obtained four APR predictions (Fig. 5). APR2 and APR3 were predicted by two models, and span residues Phe80 to Lys88, and Phe52 to Val57. APR1 and APR4 were predicted by only one of the four models, and span residues Val38 to Ala50, and Leu108 to Tyr112. APR1 and APR3 contain cysteine residues (Cys42 and Cys81, respectively) involved in disulfide bond formation (Fig. 5). We performed a separate analysis using the next-generation Aggrescan tool (ASggresScan3D 2.0), which predicts aggregation propensity based on structural context, solvent accessibility, and amino acid composition20. The model identifies only two residues in the native structure as aggregation-prone, in contrast to the fibril structure, where the predicted aggregation pattern correlates with our scoring system (Fig. 5 and Supplementary Fig. 10). To further evaluate the contribution of these regions to fibril stability, we analyzed solvent-accessible surface area and solvation energy across the fibril (Supplementary Fig. 9d), which revealed that APR1, APR2, and APR4 form a hydrophobic and energetically stable core consistent with our aggregation-propensity predictions.

Methods
Patients and tissue material.
Frozen kidney tissue specimen from an ALECT2 amyloidosis patient1 were obtained from the laboratory of the late Dr. Merrill D. Benson at the University of Indiana. Samples have been saved for further analysis. These specimens are under a material transfer agreement with Indiana University and cannot be distributed freely. The patient samples was fully anonymized prior to transfer and were therefore exempt from Institutional Review Board oversight at our institution. Informed consent for tissue collection and research use was obtained under the protocols governing the original studies conducted at Indiana University School of Medicine. No participants were recruited for the present study and no compensation was provided.

Ethical statement
UT Southwestern Medical Center’s Office of the Human Research Protection Program granted exemption from the Internal Review Board review because the specimens were anonymized.

Histology
Fresh-frozen tissue was thawed at 4°C overnight and then fixed in 20X volume excess of 10% neutral buffered formalin for 48-hours at room temperature with agitation. Then, samples were transferred to 70% ethanol and paraffin processed according to established protocols34. Sections from prepared paraffin blocks were prepared for routine hematoxylin and eosin staining (H&E), Congo Red and Thioflavin-S staining. Regressive H&E was performed on a Sakura DRS-601 x,y,z robot utilizing Leica-Surgipath Selectech reagents following the Sheehan’s textbook methodology. Congo Red slides counterstained with hematoxylin were evaluated for pathologic amyloid aggregation under bright-field. Color was imparted to amyloid by utilizing 0.1% Congo Red in alcoholic-saline following sensitization of the slides with alkaline-alcoholic-saline (10% NaCl/0.5% NaOH/80% EtOH). Slides stained with Thioflavin-S were examined for amyloid deposits indicative of plaque-like and vascular amyloid. These deposits emit bright fluorescence upon excitation with ultraviolet light (400–440 nm excitation, emission captured using a 470 nm+ long-pass filter). The staining procedure followed an adapted protocol originally detailed by Guntern et al35. Briefly, paraffin-embedded tissue sections were first hydrated and subjected to a series of chemical pretreatments: initial oxidation with potassium permanganate (0.25% w/v), followed by bleaching steps with potassium metabisulfite (1%) and oxalic acid (1%), peroxidation using hydrogen peroxide (1%) in sodium hydroxide solution (2%), and finally acidification with acetic acid solution (0.25%). Each chemical step was interspersed with thorough water rinses. Subsequently, slides were equilibrated in 50% ethanol and stained for seven minutes in a solution of Thioflavin-S (0.004%) in ethanol. After staining, excess dye was removed by washing in ethanol solutions, followed by dehydration and clearing. Finally, slides were cover-slipped using Cytoseal 60, a non-fluorescent permanent mounting medium (Epredia, Kalamazoo, MI).

Extraction of ALECT2 amyloid fibrils
ALECT2 amyloid fibrils were isolated from fresh-frozen human tissue following a previously established protocol with modifications12. Approximately 300 mg of frozen tissue was first thawed at room temperature and finely minced using a scalpel. The tissue fragments were then suspended in 0.5 mL of Tris-calcium buffer (20 mM Tris, 138 mM NaCl, 2 mM CaCl₂, 0.1% NaN₃, pH 8.0) and centrifuged at 7000 × g for 5 minutes at 4 °C. The resulting pellet underwent four additional washes with the same Tris-calcium buffer. Following these washes, the pellet was incubated overnight at 37 °C with agitation at 700 rpm in 0.5 mL collagenase solution (5 mg mL⁻¹ collagenase dissolved in Tris-calcium buffer) containing cOmplete EDTA-free protease inhibitor cocktail (Roche). After incubation, the mixture was centrifuged at 7000 × g for 30 minutes at 4 °C. The pellet obtained was then resuspended in 0.5 mL of Tris-EDTA buffer (20 mM Tris, 140 mM NaCl, 10 mM EDTA, 0.1% NaN₃, pH 8.0), followed by centrifugation at 7000 × g for 5 minutes at 4°C. This washing step with Tris-EDTA buffer was repeated nine more times. After completing these washes, fibrils were extracted by resuspending the pellet in 150 μL ice-cold water supplemented with 5 mM EDTA and centrifuging at 3100 × g for 5 minutes at 4°C. The fibril extraction procedure was repeated twice more.

Negative-stained transmission electron microscopy.
The presence of ALECT2 amyloid fibril was confirmed by transmission electron microscopy as described12. Briefly, a 4 μL fibril sample was spotted onto a freshly glow-discharged carbon film 300 mesh copper grid (Electron Microscopy Sciences), incubated for 1 min, and gently blotted onto a filter paper to remove the solution. 4 μL uranyl acetate was applied onto the grid and immediately removed. The grid was negatively stained with 4 µL of 2% uranyl acetate for 1 min and gently blotted to remove the solution. A FEI Tecnai G2 Spirit Biotwin electron microscope (Thermo Fisher Scientific) at an accelerating voltage of 120 kV was used to examine the specimens.

Western blot of extracted ALECT2 fibrils.
Western blot was performed on the extracted fibrils. Briefly, 0.5 µg of fibrils were dissolved in tricine SDS sample buffer and boiled for 2 minutes at 85 °C. The samples were then loaded and run onto a Novex™ 16% tris-tricine gel system using a tricine SDS running buffer. After electrophoresis, the proteins were transferred to a 0.2 µm nitrocellulose membrane. The membrane was probed with a polyclonal goat anti-human antibody targeting full length human LECT2 protein (Cat No. AF722; Lot: CZB0421051; R&D Systems™, 1:1000). A horseradish peroxidase-conjugated rabbit anti-goat IgG (Cat No. SA00001-4; Proteintech Group Inc, 1:1000) was used as the secondary antibody. The LECT2 protein was visualized using Promega Chemiluminescent Substrate, following the manufacturer's instructions.

Mass Spectrometry (MS) sample preparation, data acquisition and analysis.
For LC- MS/MS analysis, 0.5 µg of extracted fibrils (n=1, patient sample) were dissolved in a tricine SDS sample buffer, boiled for 2 minutes at 85°C, and run on a Novex™ 16% tris-tricine gel system using a Tricine SDS running buffer. Gel was stained with Coomassie dye, destained and ALECT2 smear was cut from the gel. Sample was sent for MS analysis. Samples were digested overnight with trypsin (Pierce) or chymotrypsin (Worthington) following reduction and alkylation with DTT and iodoacetamide (Sigma-Aldrich). The samples then underwent solid-phase extraction cleanup with an Oasis HLB plate (Waters) and the resulting samples were injected onto a Q Exactive HF mass spectrometer coupled to an Ultimate 3000 RSLC-Nano liquid chromatography system. Samples were injected onto a 75 um i.d., 15-cm long EasySpray column (Thermo) and eluted with a gradient from 0-28% buffer B over 90 min. Buffer A contained 2% (v/v) ACN and 0.1% formic acid in water, and buffer B contained 80% (v/v) ACN, 10% (v/v) trifluoroethanol, and 0.1% formic acid in water. The mass spectrometer operated in positive ion mode with a source voltage of 2.5 kV and an ion transfer tube temperature of 300°C. MS scans were acquired at 120,000 resolution in the Orbitrap and up to 20 MS/MS spectra were obtained in the ion trap for each full spectrum acquired using higher-energy collisional dissociation (HCD) for ions with charges 2-8. Dynamic exclusion was set for 20 s after an ion was selected for fragmentation.

Raw MS data files were analyzed using Proteome Discoverer v3.0 SP1 (Thermo), with peptide identification performed using a semitryptic or semi-chymotryptic search with Sequest HT against the human reviewed protein database from UniProt. Fragment and precursor tolerances of 10 ppm and 0.02 Da were specified, and three missed cleavages were allowed. Carbamidomethylation of Cys was set as a fixed modification, with oxidation of Met set as a variable modification. The false-discovery rate (FDR) cutoff was 1% for all peptides.

For intact protein mass analysis, 20 µL (5 µg) of extracted ALECT2 fibrils was spun at 21000 x g for 1h at 4 °C. The 10 µL of supernatant was removed and 5 µL of 8M GuHCl was added to dissociate the fibrils. Mixture was incubated at 37 C for 1 at with continuous shaking at 1000 rpm (Thermomizer). Then, an additional 5 µL 8M GuHCl was added and again incubated at 37°C for 1 at with continuous shaking at 1000 rpm. Samples with or without reducing agent (DTT) were desalted and analyzed by LC/MS, using a Sciex X500B QTOF mass spectrometer coupled to an Agilent 1290 Infinity II HPLC. Samples were injected onto a POROS R1 reverse-phase column (2.1 x 30 mm, 20 µm particle size, 4000 Å pore size) and desalted. The mobile phase flow rate was 300 µL/min and the gradient was as follows: 0-3 min: 0% B, 3-4 min: 0-15% B, 4-16 min: 15-55% B, 16-16.1 min: 55-80% B, 16.1-18 min: 80% B. The column was then re-equilibrated at initial conditions prior to the subsequent injection. Buffer A contained 0.1% formic acid in water and buffer B contained 0.1% formic acid in acetonitrile.

The mass spectrometer was controlled by Sciex OS v.3.0 using the following settings: Ion source gas 1 30 psi, ion source gas 2 30 psi, curtain gas 35, CAD gas 7, temperature 300 °C, spray voltage 5500 V, declustering potential 135 V, collision energy 10 V. Data was acquired from 400-2000 Da with a 0.5 s accumulation time and 4 time bins summed. The acquired mass spectra for the proteins of interest were deconvoluted using Bio Tool Kit within Sciex OS in order to obtain the molecular weights. Peaks were deconvoluted over the entire mass range of the mass spectra, with an output mass range of 7000-9000 Da, using low input spectrum isotope resolution.

For post-translational modification LC-MS/MS analysis, 0.5 µg of extracted fibrils were dissolved in a tricine SDS sample buffer, boiled for 2 minutes at 85 °C, and run on a Novex™ 16% tris-tricine gel system using a Tricine SDS running buffer. Gel was stained with Coomassie dye, destained and ALECT2 smear was cut from the gel. Sample was sent for MS analysis. Samples were digested overnight at room temperature with chymotrypsin (Worthington) following reduction and alkylation with DTT and iodoacetamide (Sigma–Aldrich). Following solid-phase extraction cleanup with an Oasis HLB µelution plate (Waters), the resulting peptides were reconstituted in 10 uL of 2% (v/v) acetonitrile (ACN) and 0.1% trifluoroacetic acid in water. 5 uL of each sample were injected onto an Orbitrap Fusion Lumos mass spectrometer (Thermo Electron) coupled to an Ultimate 3000 RSLC-Nano liquid chromatography system (Dionex). Samples were injected onto a 75 μm i.d., 75-cm long EasySpray column (Thermo), and eluted with a gradient from 0-28% buffer B over 90 min. Buffer A contained 2% (v/v) ACN and 0.1% formic acid in water, and buffer B contained 80% (v/v) ACN, 10% (v/v) trifluoroethanol, and 0.1% formic acid in water. The mass spectrometer operated in positive ion mode with a source voltage of 2.5 kV and an ion transfer tube temperature of 300 °C. MS scans were acquired at 120,000 resolution in the Orbitrap and up to 10 MS/MS spectra were obtained in the Orbitrap for each full spectrum acquired using higher-energy collisional dissociation (HCD) for ions with charges 2-7. Dynamic exclusion was set for 25 s after an ion was selected for fragmentation. Our purification protocol is biased towards amyloid fibrils; therefore, we do not expect significant monomers or oligomers to be present in the fibril preparation. Although we cannot completely rule out the presence of a small amount of monomer or oligomer, the influence of these would likely be considered spectra noise. The chymotrypsin digestion performed on the sample showed chymotryptic peptides mapped to the entire LECT2 protein, confirming the success of the digestion.

Raw MS data files were analyzed using Proteome Discoverer v3.0 SP1 (Thermo), with peptide identification performed using Sequest HT searching against the human reviewed protein database from UniProt. Fragment and precursor tolerances of 10 ppm and 0.02 Da were specified, and up to six missed cleavages were allowed with cleavage allowed at Phe, Leu, Met, Trp, and Tyr. Carbamidomethylation of Cys was set as a fixed modification, with phosphorylation of Ser, Thr, Tyr, acetylation of Lys, methylation of Lys and Arg, dimethylation of Lys and Arg, trimethylation of Lys, N terminal acetylation, methionine oxidation and Asn/Gln deamidation were set as variable modifications. The false-discovery rate (FDR) cutoff was 1% for all peptides.

The mass spectrometry proteomics data has been deposited to MassIVE (a member of ProteomeXchange)36 and can be accessed at MSV000098220.

Cryo-EM sample preparation, data collection, and processing.
Freshly extracted fibril samples (3 µL) were applied to glow-discharged R 1.2/1.3, 300 mesh, Cu grids (Quantifoil), blotted with filter paper to remove excess sample, and plunge-frozen in liquid ethane using a Vitrobot Mark IV (FEI/Thermo Fisher Scientific). Cryo-EM samples were screened on Talos Arctica at the Cryo-Electron Microscopy Facility (CEMF) at The University of Texas Southwestern Medical Center (UTSW), and the final datasets were collected on a 300 keV Titan Krios microscope (FEI/Thermo Fisher Scientific) with ColdFEG/Falcon4i/Selectris operated at slit width of 10 eV at the Stanford-SLAC Cryo-EM Center (S2C2). Pixel size, frame rate, dose rate, final dose, and number of micrographs per sample are detailed in (Supplementary Table 3).

The raw movie frames were gain-corrected, aligned, motion-corrected and dose-weighted using RELION’s own implemented motion correction program37. Contrast transfer function (CTF) estimation was performed using CTFFIND 4.138. All steps of helical reconstruction, three-dimensional (3D) refinement, and post-process were carried out using RELION 4.039,40. The filaments were picked automatically using Topaz in RELION 4.041,42. Particles were extracted using a box size of 1024 and 300 pixels with an inter-box distance of 3 asymmetrical units at helical rise of 4.8 Å. 2D classification of 1024-pixel particles was only used to estimate the fibril crossover distance. 2D classifications of 300-pixel particles were used to remove suboptimal segments. An initial 3D reference model was generated from a subset of 2D class averages using relion_helix_inimodel2d program, as previously described43. Fibril helix was assumed left-handed for 3D reconstruction and 3D auto refinements were performed. Subsequent 3D auto refinements with optimization of helical twist and rise were carried out once the estimated resolution of the map reached beyond 4.75 Å. 3D classifications without particle alignment were used to further remove suboptimal segments, and to separate different conformation as in the case of the double filaments. Particles potentially leading to the best reconstructed map were further chosen and run through additional 3D auto-refinements. CTF refinements, 3D auto refinements, and post-processing were repeated to obtain higher resolution. The final overall resolution was estimated from Fourier shell correlations at 0.143 threshold between two independently refined half-maps (Supplementary Fig. 5).

Atomic model building and refinement.
We used the automated machine-learning ModelAngelo approach with minor modifications to obtain an initial atomic model44. First, COOT v0.9.8.1 was used to build the peptide backbone of a single fibril layer featuring all alanine residues45. We then created a new density map of one fibril layer in ChimeraX v1.8 using the command ‘vol zone #1 near #2 range 3 new true’, where #1 refers to the post-processed fibril density map and #2 is the peptide backbone model46. This new map was then entered into ModelAngelo, both with and without the primary LECT2 sequence, to obtain the initial atomic models of ALECT2 fibrils. Using COOT, we made residue modifications and real-space refinements to finalize the model. Further refinement was carried out using ‘phenix.real_space_refine’ from PHENIX 1.2047. ChimeraX v1.8 was used for molecular graphics and structural analysis48. Model statistics are summarized in Supplementary Table 3.

Particle tracing.
Particles used in helical reconstruction were selected from the output of the 2DClass jobs as class averages. Class averages from RELION corresponding to the desired morphology were selected using subset selection, which resulted in a particles.star file for each particular subset or morphology. We used class averages with a resolution better than 5 Å. This cutoff balances a suitable number of particles per micrograph while maintaining a high confidence that the class averages match the intended morphology. Using the CoordinateX and CoordinateY columns within the particles.star file, each individual particle was graphed as a scatterplot and then overlaid onto the corresponding micrograph listed in the MicrographName column. Please note that only clearly resolved segments of fibrils were utilized in the reconstruction process, while segments of insufficient quality were excluded. Consequently, the selected segments, even when derived from a single fibril, might appear discontinuous or scattered, as depicted in Fig. 4c.

Stabilization energy calculation
The stabilization energy per residue was calculated by the sum of the products of the area buried for each atom and the corresponding atomic solvation parameters (Supplementary Fig. 9). The overall energy was calculated by the sum of energies of all residues, and different colors were assigned to each residue, instead of each atom, in the solvation energy map14.

APR analysis
Four prediction models; TANGO16, WALTZ17, Aggrescan15, and AmylPred18,49 were used to predict APRs. The LECT2 sequence was input to a file. Residues identified as APRs by a model (“hits”) received a score of 1, while non-APR residues received a score of 0. This process was repeated across all four models, and the per-residue score was calculated as the sum of hits from the models. Criteria for calling hits were based on the requirements set by the creators of each model. Briefly, they are as follows: For TANGO, hits were counted for any stretch of 5 residues or more with a 5.0 or higher aggregation score, according to the TANGO usage guidelines. For WALTZ, hits were counted for any residue with a score greater than 0. For Aggrescan, hits were counted as any stretch of 5 or more residues with an aggregation score of 0.02 or higher. For AmylPred, hits were counted as any residues with a consensus score of 3 or more. The cumulative hits for each residue were tabulated and recorded in a PDB file as B-factors, enabling visualization in a heatmap model. The heatmap was generated using ChimeraX46 (v1.7.1.4). For Aggrescan 3D 2.0, PDBs for native (PDB ID:5B0H) and ALECT2 fibril (PDB ID: 9NON) were provided as input.

Figure Panels
All figure panels were created with Adobe Illustrator.

Data Availability
Unless otherwise stated, all data supporting the results of this study can be found in the article, supplementary, and source data files. Mass spectrometry data have been deposited to MassIVE database (a member of ProteomeXchange) under accession code MSV000098220 [ https://massive.ucsd.edu/ProteoSAFe/dataset.jsp?task=f539b207aeb047b2ac7a99f031120125 ]. Graphed data is provided in the source data file. Cryo-EM maps have been deposited in the Electron Microscopy Data Bank under accession codes as following; single protofilament morphology (EMD-49601[https://www.ebi.ac.uk/emdb/EMD-49601]), double protofilament 1 morphology (EMD-49624 [https://www.ebi.ac.uk/emdb/EMDS-49624]), double protofilament 2 morphology (EMD-49623 [https://www.ebi.ac.uk/emdb/EEMD-49623]). The atomic model of ALECT2 single protofilament morphology is available at the Protein Data Bank under accession code 9NON [https://www.rcsb.org/structure/9NON]. This data can also be accessed using Figshare [https://doi.org/10.6084/m9.figshare.29803442]. All data generated or analyzed during this study that support the findings are available within this published article and its supplementary data files. Source data are provided with this paper.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "The article by Afrin et al. reports the first structure of fibrils derived from ALECT2, a systemic amyloidosis affecting the\nkidney. The three dimensional structure of the ALECT2 fibril core is revealed with sufficient clarity to indicate backbone\ngeometry and the presence of buried disulfide bridges. It also confirms a homozygous sequence polymorphism at position\n40. While the density does not directly reveal the positions of acetylated lysine residues, these are mapped by mass\nspectrometry. Stabilizing molecular interactions are described within the fibril core, and appear to match those observed in\nother amyloid fibrils including polar ladders across staggered fibril layers.\nGiven the novelty of this structure and its implications for the field of systemic amyloidosis, and ALECT2 in particular, I am\nenthusiastic about its publication, but urge the authors to consider the questions and points raised below.\nMajor questions:\nSince ALECT2 is a relatively recently characterized amyloidosis, but has a known disease-correlated sequence\npolymorphism, I40V, and since the structure determined was from a patient homozygous for Valine at position 40, do the\nauthors expect the structure determined to be the same for heterozygous patients or those homozygous for Isoleucine at that\nposition?\nIt is intriguing that the patient harboring the fibrils whose structure was determined also had a co-occurring carcinoma. Are\nthe authors able to discriminate the effects of the carcinoma on the structure of the fibrils? In other words, are these fibrils\nexpected of ALECT2 patients that did not suffer renal carcinoma, or are they a unique presentation of this condition?\nHow does MS indicate the acetylation is integrated into fibrils, not just in free monomers or oligomers (e.g. the\nmultimeric species identified by western blot)? On this point, it would be helpful to verify that the chymotrypsin\ndigestion used to detect the acetylation was indeed successful on the fibrils.\nAlthough the double protofilament type 1 appears to be 2 fold symmetric, the type 2 protofilament structure seems\nasymmetric. In each case, the correlation of the model to the map for each protofilament would be a useful metric to know. It\nmight also help indicate whether all protofilament structures described by the lower resolution maps match the single\nprotofilament fold equally well.\nMinor questions:\nAlthough the putative fibril cofactors could not be identified on the basis of their densities, it would help if those\ndensities were labeled or in some way catalogued and if their respective volumes were also estimated.\nRather than labeling certain waters as stabilizing, it would be more clear to label them as 'ordered waters'.\nIt would help if the fibril core structure shown in Fig 2C had more residues numbered, including the location of the I40V\npolymorphism.\nThe double protofilaments in Figure 4 are described as being related to each other by inversion, but the operation appears to\nbe a simple rotation (of approximately 180 degrees) about the fibril growth axis.\nIt would be helpful to include in Sup. Table 3 the refined helical parameters of the structures and for the text to note how\ndifferent these were across the different protofilament types.\nThe energetics maps displayed (Figure S8) do not clearly indicate what regions of the fibril core are more stabilizing than\nothers. Would it be possible for the authors to combine the information from their aggregation propensity predictions and the\nenergetics estimates to better indicate how these two correlate?\nIn Figure 5b, it would be helpful to have the beta strands in the schematic numbered or labeled for both the native and fibril\nfolds.", "reviewer_2": "This manuscript reports the high-resolution Cryo-EM structure of ex vivo kidney ALECT2 fibrils from an affected patient.\nBesides defining the structure of the most prevalent single protofilament, the results show the presence of less abundant\ndouble protofilament morphologies. This is the first resolved natural ALECT fibril structure and provides important novel\nmolecular knowledge, fundamental to cast light on the unfolding process and dynamics in tissues. Even more so,\nconsidering that the structure of in vitro ALECT2 fibrils does not fully match the natural one.\nIn addition to providing the fibril structure, the authors perform an MS-based characterization of the amyloid extract, to\nconfirm LECT2 sequence and to explore the presence of PTMs. In the undigested extract, they observe a major\ndeconvoluted peak in line with full-length I40V ALECT2 with intact disulphide bridges, and several additional peaks of\nhigher molecular mass, consistent with PTMs-containing LECT2 proteoforms. The most intense such peak is consistent with\nmonoacetylated LECT2. Presence of acetylation on several K residues, surface-exposed on the fibril structure, has then\nbeen confirmed by high-resolution MS/MS analysis. It is not clear to me, instead, if acetylation of the N terminus, frequent in\neukaryotic proteins and potentially accounting for a significant fraction of LECT2 proteoforms forming the +42 Da peak, has\nbeen explored (it is not indicated in the methods). Is the presence of K acetylation compatible with the densities observed by\nCryo-EM?\nGiven the emphasis on PTMs in the manuscript, it must be noted that other potentially relevant PTMs have not been\nconsidered. The authors should comment on the additional peaks in the deconvoluted spectrum. Amyloid fibrils from various\nproteins have been reported to contain multiple potentially destabilizing PTMs, e.g. extensive oxidation and deamidation.\nHave they been searched for?\nOverall, although opening an interesting scenario, the considerations on the potential role of acetylation in LECT2\namyloidogenesis are currently speculative. The timing of acetylation is in fact unclear, no information is available on this\nPTM in soluble ALECT2 in diseased and healthy individuals, the actual distribution of the acetyl groups on the various K\nresidues or on the N-terminus is undefined (addition of a single acetyl group per LECT2 molecule seems the most frequent\ncase), and no clear experimental mapping of this PTMs on the structure is presented."}, "author_response": "Response: We thank the reviewer for raising this important point. We are not aware of any confirmed cases of\npatients homozygous for isoleucine at position 40 (I40/I40) in ALECT2. Furthermore, existing clinical data\nindicate that the V40 allele is strongly associated with disease risk and is required for pathogenesis1. We note,\nhowever, that there is at least one documented heterozygous I40/V40 case. In that context, we speculate that\nthe fibril fold would be similar because the Ile40 to Val40 mutation is conservative with respect to size and\nhydrophobicity, as well as compatible with the fibril fold.\nStructurally, the I40V substitution slightly weakens local hydrophobic packing (Reviewer Figure 1a), leading to a\nmarginally lower estimated solvation energy for the Val40 form (–67.9 kcal/mol per layer) compared to the Ile40\nform (–68.2 kcal/mol per layer), assuming similar backbone conformation (Reviewer figure 1b-c). This difference\nis minimal and unlikely to affect the overall fibril structure or stability.\nReviewer\nfigure 1. (a)\ndepiction of\nhydrophobic\ninteractions\nbetween Ile40\n(layer n) and\nVal48 of layer\nn and n+1.\nFree energy\nof solvation\ncalculated for\n(b) Ile40 form\nand (c) Val40\nform. Strongly\nstabilizing\nside chains\nare colored red, and destabilizing side chains are colored blue.\nSimilarly, APR prediction using Aggrescan3D showed nearly identical profiles with only a minimal increase in the\nscore for Ile40 form (Reviewer Figure 2). Overall, these findings suggest that the I40V mutation has little impact\non the final fibril structure and its stability. It is possible that the mutation has more influence on the native form\nof LECT2. The I40V mutation is believed to increase the conformational heterogeneity of the zinc free form of\nLECT21.\nReviewer Figure 2. (a) Aggrescan3D visual representation of the aggregation score for Val40 (top) and Ile40 (bottom). The\nresidues are colored according to their score, ranging from blue, which implies a soluble residue, to various red shades\nindicating aggregation prone residues. (b) zoomed in view of the original Val40 form (upper panel) and Ile40 form (created\nby mutating the structure of the Val40 form (lower panel). (c) Aggrescan3D analysis plot and score of the original Val40\n(upper) form and mutated Ile40 (lower) form. The plots display per-residue aggregation scores, where positive values\nindicate regions prone to aggregation, and negative values suggest aggregation-resistant regions.\nIn light of this comment, we have now updated the manuscript discussion, which now reads “Indeed, the analysis\nof the solvation energy of the ex-vivo ALECT2 amyloid structure when incorporating an isoleucine in position 40\nshows little to no change in the estimated structure stability (Supplementary Fig. 8c). Thus, the ex-vivo ALECT2\namyloid fold could be compatible with both residues.” We have included a panel in the Supplementary Fig. 8c\nwith the free energy of solvation of the ex-vivo ALECT2 amyloid structure with an isoleucine in the residue\nposition 40.\n2. It is intriguing that the patient harboring the fibrils whose structure was determined also had a co-occurring\ncarcinoma. Are the authors able to discriminate the effects of the carcinoma on the structure of the fibrils? In\nother words, are these fibrils expected of ALECT2 patients that did not suffer renal carcinoma, or are they a\nunique presentation of this condition?\nResponse: We thank the reviewer for this thoughtful question. In this patient, amyloid deposition was clinically\nevident at age 54, whereas the renal carcinoma was not identified until age 61, at the time of nephrectomy2. This\ntimeline strongly suggests that amyloidogenesis preceded the carcinoma, making it unlikely that the tumor\ninfluenced the fibril fold we report.\nStudies have reported that about 12.5% of ALECT2 patients are also diagnosed with carcinoma, most often\ndiscovered incidentally at the time of nephrectomy. In these cases (including in our patient), the amyloid deposits\nare consistently located in the non-neoplastic portion of the kidney, rather than within the tumor itself2,3. This\nseparation further supports that the fibril structure is unlikely to be influenced by the carcinoma. We therefore\nexpect that the conformation observed here is representative of ALECT2 patients without carcinoma, although\nadditional analyses of fibrils from patients with and without comorbidities will be important to confirm this\nconclusion. We have noted this in the revised Discussion, which now reads “For instance, in the patient analyzed\nhere, the co-occurrence of carcinoma might have influenced fibril formation; however, because the cancer\ndeveloped after amyloid deposition, this seems unlikely.”\n3. How does MS indicate the acetylation is integrated into fibrils, not just in free monomers or oligomers (e.g. the\nmultimeric species identified by western blot)? On this point, it would be helpful to verify that the chymotrypsin\ndigestion used to detect the acetylation was indeed successful on the fibrils.\nResponse: We thank the reviewer for this observation. We have now included the following to the Materials and\nMethods section: “Our purification protocol is biased towards amyloid fibrils; therefore, we do not expect\nsignificant monomers or oligomers to be present in the fibril preparation. Although we cannot completely rule out\nthe presence of a small amount of monomer or oligomer, the influence of these would likely be considered\nspectra noise. The chymotrypsin digestion performed on the sample showed chymotryptic peptides mapped to\nthe entire LECT2 protein, confirming the success of the digestion.”\n4. Although the double protofilament type 1 appears to be 2-fold symmetric, the type 2 protofilament structure\nseems asymmetric. In each case, the correlation of the model to the map for each protofilament would be a\nuseful metric to know. It might also help indicate whether all protofilament structures described by the lower\nresolution maps match the single protofilament fold equally well.\nResponse: We thank the reviewer for this helpful suggestion and have included the following information into\nthe Results section. “The final resolutions of the double protofilament type 1 and type 2 maps are 5.0 Å and 5.6\nÅ, respectively. At such resolutions, fibril backbone and side chain features are not well resolved, preventing\nreliable model building and accurate calculation of the model to the map correlation. For this reason, we did not\nperform de novo modeling, but instead rigid body docked the high resolution protofilament structure into these\nlower resolution densities (Fig. 4a). Given the limited resolution and the presence of unresolved densities in both\nthe type 1 and type 2 double protofilament maps, any quantitative metrics would be unreliable and potentially\nmisleading. Visual inspection of the fit indicates that the backbone of single protofilament model docks\nreasonably well within the protofilament density of the double protofilament maps although local variations very\nlikely exist (Fig. 4a).”\nMinor questions:\n1. Although the putative fibril cofactors could not be identified on the basis of their densities, it would help if those\ndensities were labeled or in some way catalogued and if their respective volumes were also estimated.\nResponse: We do observe extra densities in the reconstructed maps at lower contour levels, suggesting the\npresence of non-proteinaceous cofactors. However, at the higher contour levels used for reliable model building,\nthese densities become poorly defined due to low signal-to-noise and appear hollow. In the post-processed\nmaps, the signal quality was further reduced, which prevents us from confidently interpreting these features.\nAdditionally, while we attempted to estimate the volumes of the extra densities, this proved challenging because\nsome of these features appear continuous across multiple fibril layers, whereas others are localized to individual\nlayers. Without precise information on the number of repeating layers in the fibril, it is not possible to accurately\ndefine the volume of these densities. For this reason, we believe adding this information to the paper would be\ntoo speculative. However, to address our curiosity and that of this reviewer, we calculated the projected area of\neach density at the cross-sectional level, which provides a two-dimensional measure within the available data,\nwhich are included here for the reviewer’s consideration.\nReviewer Figure 3. Quantification of extra densities observed in the ALECT2 single-protofilament structure.\nCryo-EM density map of the ALECT2 single protofilament overlaid with the atomic model, showing non-proteinaceous extra\ndensities (black). Each density was assigned a Roman numeral label (i–xvi), and its projected cross-sectional area was\nestimated in Å2.\n2. Rather than labeling certain waters as stabilizing, it would be more clear to label them as 'ordered waters'.\nResponse: Thank you for this suggestion. These waters are now referred to as ordered waters in the results\nand figure legend for Supplementary Fig 7.\n3. It would help if the fibril core structure shown in Fig 2C had more residues numbered, including the location of\nthe I40V polymorphism.\nResponse: Thank you for suggesting this. We have now numbered every tenth residues and also labeled the\nmutated residue.\n4. The double protofilaments in Figure 4 are described as being related to each other by inversion, but the\noperation appears to be a simple rotation (of approximately 180 degrees) about the fibril growth axis.\nResponse: We thank the reviewer for this correction. We have now changed the description from inversion to\nrotation where applicable.\n5. It would be helpful to include in Sup. Table 3 the refined helical parameters of the structures and for the text\nto note how different these were across the different protofilament types.\nResponse: We missed this information in the stats table, thank you for your observation. It is now included in\nthe stats table as well as the results.\n6. The energetics maps displayed (Figure S8) do not clearly indicate what regions of the fibril core are more\nstabilizing than others. Would it be possible for the authors to combine the information from their aggregation\npropensity predictions and the energetics estimates to better indicate how these two correlate?\nResponse: We thank the reviewer for this insightful comment. We have added an updated panel to\nSupplementary Figure 8 (d) highlighting the overlap between APRs and regions of low solvation energy, and we\ndescribe this correlation in both the results and discussions as follows.\nThe Results section now reads “To further evaluate the contribution of these regions to fibril stability, we analyzed\nsolvent-accessible surface area and solvation energy across the fibril (Supplementary Fig. 8d), which revealed\nthat APR1, APR2, and APR4 form a hydrophobic and energetically stable core consistent with our aggregation-\npropensity predictions.”\nThe Discussion section now reads “Our solvent-accessible surface area and solvation energy analyses\n(Supplementary Fig. 8d) showed that regions corresponding to APR1, APR2, and APR4 formed a hydrophobic\nand energetically stable core, exhibiting lower solvation energy and reduced surface exposure relative to other\nfibril regions. These observations were consistent with our aggregation-propensity predictions (Fig. 5a).\nTogether, these findings suggested that the APRs corresponded to regions contributing most significantly to fibril\nstabilization.”\n7. In Figure 5b, it would be helpful to have the beta strands in the schematic numbered or labeled for both the\nnative and fibril folds.\nResponse: We have now included the β strand numbering for both the native and fibril fold as suggested.\nResponse: Based on the reviewer’s suggestion we included protein N-terminal acetylation as part of the search\nprotocol. In the tryptic dataset, an N-terminally acetylated peptide was identified but at more than 200-fold lower\nabundance than the non-acetylated version, suggesting that if present, N-terminal acetylation represents only a\nvery minor fraction of the molecules.\nWe added the following clarification to the Results: “A low-abundance N-terminally acetylated peptide was\ndetected though its intensity was more than 200-fold lower than that of the corresponding non-acetylated peptide,\nindicating that N-terminal acetylation, if present, occurred only in a very small fraction of molecules\n(Supplementary Table 2).” We also added this PTM to Supplementary Table 2.\n2. Is the presence of K acetylation compatible with the densities observed by Cryo-EM?\nResponse: Densities are not compatible with lysine acetylation.\n3. Given the emphasis on PTMs in the manuscript, it must be noted that other potentially relevant PTMs have\nnot been considered. The authors should comment on the additional peaks in the deconvoluted spectrum.\nAmyloid fibrils from various proteins have been reported to contain multiple potentially destabilizing PTMs, e.g.\nextensive oxidation and deamidation. Have they been searched for?\nResponse: We originally searched for phosphorylation, acetylation, methylation, dimethylation, trimethylation,\nand ubiquitination, and consistently identified acetylation. Based on reviewer feedback, we extended our\nsearches to include methionine oxidation and Asn/Gln deamidation. Now the results section includes the\nfollowing “We also detected low-abundance hits for Asn/Gln deamidation, but we could not confidently confirm\nthese by the intact mass analysis due to the small mass shifts (1 Da) and overlap with naturally occurring isotope\npeaks. A single methionine oxidation (Met 55) was observed as well, though both methionine oxidation and\ndeamidation can occur during sample preparation, for example, prolonged incubations at neutral pH or oxidative\nhandling conditions are known to cause these changes14,15. Thus, while we cannot exclude their presence in\nvivo, we interpret these modifications cautiously and regard them as potential preparation artifacts rather than\nas defining features of the fibrils.” We also added these PTMs to Supplementary Table 2.\n4. Overall, although opening an interesting scenario, the considerations on the potential role of acetylation in\nLECT2 amyloidogenesis are currently speculative. The timing of acetylation is in fact unclear, no information is\navailable on this PTM in soluble ALECT2 in diseased and healthy individuals, the actual distribution of the acetyl\ngroups on the various K residues or on the N-terminus is undefined (addition of a single acetyl group per LECT2\nmolecule seems the most frequent case), and no clear experimental mapping of this PTMs on the structure is\npresented.\nResponse: We thank the reviewer for their input. We agree that the current evidence is preliminary. We\nacknowledge that our observations on lysine acetylation in ALECT2 fibrils are exploratory and do not yet define\nthe timing, frequency, or distribution of this PTM.\nHowever, what we do know from our data is the following:\n Intact mass spectrometry revealed that the predominant modified species carried a single lysine\nacetylation, while chymotrypsin-based MS/MS analysis identified multiple potential acetylation sites,\nindicating that different lysines can be acetylated across the fibril population, though typically only one\nper monomer (Supplementary Table 2).\n Importantly, because these data were obtained from fibril extracts, where soluble monomeric LECT2 does\nnot copurify, our analyses reflect modifications present in fibril-associated LECT2 rather than soluble\nLECT2 species.\nBased on this comment we clarified our language in the Discussion, which now reads “Given the limited\nexperimental evidence and the preliminary nature of our findings, it remains challenging to determine the timing,\nfrequency and distribution of acetylation or its specific role in ALECT2 amyloidosis. Further exploration is\nnecessary to understand how this modification influences protein-protein interactions and whether it plays a\nfunctional role in the pathogenesis of ALECT2 amyloidosis.”"}, {"round": 2, "reviewer_comments": {"reviewer_1": "The authors have significantly improved their manuscript by systematically addressing each of the reviewer comments.\nOverall, the author responses satisfactorily addressed most of my questions and suggestions. However, I would like to note\nthat despite the middling resolutions observed for their double protofilament structures, cited at 5 and 5.6Å, the authors could\nstill more robustly characterize the map to model fit. Rather than appearing misleading, the metrics used, e.g. fit scores from\nmolecular dynamics or Rosetta modeling to cryoem maps (https://pubs.acs.org/doi/10.1021/ct500995d) and Q-score\nanalyses (https://www.nature.com/articles/s41592-020-0731-1) would be informative of overall map and model quality.\nSome of these tools also permit fitting to variably resolved areas of a map.", "reviewer_2": "The authors have addressed the concerns raised during the first revision.\nMinor observations:\n- given that they mention a 200-fold lower intensity of the acetylated compared to the non-acetylated N-terminal peptide,\nI suggest specifying what this calculation is based on (PSM, XIC etc).\n- In my opinion, the following considerations could be moved to the supplementary material: “We also detected low-\nabundance hits for Asn/Gln deamidation, but we could not confidently confirm these by the intact mass analysis due to the\nsmall mass shifts (1 Da) and overlap with naturally occurring isotope peaks. A single methionine oxidation (Met 55) was\nobserved as well, though both methionine oxidation and deamidation can occur during sample preparation, for example,\nprolonged incubations at neutral pH or oxidative handling conditions are known to cause these changes. Thus, while we\ncannot exclude their presence in vivo, we interpret these modifications cautiously and regard them as potential preparation\nartifacts rather than as defining features of the fibrils”"}, "author_response": "Response: We appreciate the reviewer’s suggestion. The double protofilament maps are of low resolution and\ndisplay limited structural detail including low signal-to-noise, hollow interior features, lack of side-chain\ninformation, and non-separated β-strand layers (see Extra Fig. 1). To explore whether any meaningful model\nfitting, we first clipped the maps into thin Z-sections using ChimeraX, and then using COOT to perform manual\ndocking of the Cα backbone into the densities followed local Rigid Body Fit Zone. We also attempted automated\nmodel optimization using Phenix. For the double protofilament 2 map (5.6 Å), all refinement attempts failed to\nimprove the fit and consistently produced models worse than the original manually fitted version (Extra Fig. 2a).\nThe estimated model-to-map Q-score for double protofilament 2 was 0.16, consistent with the map’s severe\nlimitations. In contrast, refinement of the double protofilament 1 map (5 Å) yielded a Q-score of 0.42, reflecting\ninterpretable correlation of model to map (Extra Fig. 2b).\nBased on these observations, the Results section now reads as follows:\n“The final resolutions of the double protofilament 1 and 2 maps are 5.0 Å and 5.6 Å, respectively.\nAt such resolutions, the backbone density appears hollow with undefined regions and the side chain\nfeatures are not well resolved, preventing reliable model building and accurate calculation of the model-\nto-map correlation. Thus, we did not perform de novo modeling, but instead rigid body docked the high-\nresolution single protofilament structure into these lower resolution densities (Fig. 4a). We obtained a\nQ-score of 0.42 from the map of the double protofilament 1, reflecting interpretable correlation of model-\nto-map. In contrast, the map of the double protofilament 2 produced only a Q-score of 0.16, consistent\nwith its lower resolution at 5.6 Å. Visual inspection of the fit indicates that the backbone of the single\nprotofilament model docks reasonably well within the protofilament density of the double protofilament\nmaps although local variations very likely exist (Fig. 4a).”\nExtra figure 1: Side view (a) and top view (b) of the double protofilament 2.\nExtra figure 2: Rigid body fitting of a single-layer model of the single protofilament into the density map of double\nprotofilament 1 (a) and 2 (b).\nResponse: We thank the reviewer for this suggestion. We have now specified the what the calculation is based\non and it now reads “A low-abundance N-terminally acetylated peptide was detected, but its signal intensity was\n>200-fold lower than that of the corresponding non-acetylated peptide based on extracted ion chromatograms\n(XIC). This indicates that N-terminal acetylation, if present, occurs only in a very small fraction of molecules\n(Supplementary Table 2).”\nResponse: We thank the reviewer for their suggestion. We have now moved this information to the\nsupplementary table 2."}, {"round": 3, "reviewer_comments": {"reviewer_1": "All my concerns have been addressed."}, "author_response": ""}]

Decision letter