Author response: Structure-based inhibitors of amyloid beta core suggest a common interface with tau (2019)

Article Figures and data Abstract Introduction Results Discussion Materials and methods Data availability References Decision letter Author response Article and author information Metrics Abstract Alzheimer’s disease (AD) pathology is characterized by plaques of amyloid beta (Aβ) and neurofibrillary tangles of tau. Aβ aggregation is thought to occur at early stages of the disease, and ultimately gives way to the formation of tau tangles which track with cognitive decline in humans. Here, we report the crystal structure of an Aβ core segment determined by MicroED and in it, note characteristics of both fibrillar and oligomeric structure. Using this structure, we designed peptide-based inhibitors that reduce Aβ aggregation and toxicity of already-aggregated species. Unexpectedly, we also found that these inhibitors reduce the efficiency of Aβ-mediated tau aggregation, and moreover reduce aggregation and self-seeding of tau fibrils. The ability of these inhibitors to interfere with both Aβ and tau seeds suggests these fibrils share a common epitope, and supports the hypothesis that cross-seeding is one mechanism by which amyloid is linked to tau aggregation and could promote cognitive decline. https://doi.org/10.7554/eLife.46924.001 Introduction Although Alzheimer’s disease (AD) is the most prevalent form of dementia, there are limited treatments to alleviate symptoms and none that halt its progression. Histological features of AD are extracellular senile plaques of amyloid beta (Aβ) and intracellular neurofibrillary tangles of tau (Glenner et al., 1984; Goedert et al., 2017). While Aβ aggregation is thought to occur at the early stages of AD, tau aggregation correlates better to disease progression, with characteristic spreading along linked brain areas, and severity of symptoms correlating to the number of observed inclusions (Tanzi, 2012; Hardy and Selkoe, 2002; Manczak and Reddy, 2014; Seward et al., 2013; Brier et al., 2016; Schwarz et al., 2016). Structural information about the aggregated forms of Aβ and tau is accumulating, but to date this knowledge has not led to successful chemical interventions (Chen et al., 2017). A link between the appearance of Aβ and tau pathologies has been noted in transgenic mouse models generated by crossing or co-expressing mutant Aβ and mutant tau, but the mechanism is not yet understood at the molecular level (Oddo et al., 2003). By injecting Aβ seeds derived from synthetic peptide, transgenic mouse or AD patient tissue, tau pathology can be found both at the site of injection, and also in functionally connected brain areas (Bolmont et al., 2007; Götz et al., 2001; Morales et al., 2015). Tau aggregation has also been reported to follow Aβ seeding in 3D neuronal stem cell cultures that express early onset hereditary mutations to drive overproduction and aggregation of Aβ (Choi et al., 2014). In spite of these observations, the molecular linkage of Aβ to tau remains unresolved. Proposed hypotheses include Aβ causing downstream cellular changes that trigger tau phosphorylation and eventual aggregation, and/or a direct interaction and seeding of tau by aggregated Aβ (Ittner and Götz, 2011; Stancu et al., 2014; Morales et al., 2013). Several lines of evidence support the direct interaction model, although questions still remain; for example, how such an interaction could occur since Aβ plaques deposit extracellularly, while tau neurofibrillary tangles are intracellular. One possible model for intracellular aggregation could be that Aβ is cleaved from APP inside endosomes, and then exported (Rajendran et al., 2006). Another model proposes that smaller diffusible Aβ oligomers are the toxic species (Lesné et al., 2006; Lambert et al., 1998; Benilova et al., 2012); indeed oligomers of Aβ isolated from AD serum are sufficient to induce tau aggregation (Jin et al., 2011). Aβ has also been found co-localize intra-neuronally with tau as well as at synaptic terminals, with increased interactions correlating with disease progression (Manczak and Reddy, 2014). Furthermore, soluble and insoluble complexes of Aβ bound to tau have been detected in AD tissue extracts (Manczak and Reddy, 2014; Guo et al., 2006). In vitro, soluble complexes of Aβ and tau have been found to promote aggregation of tau (Guo et al., 2006), while another study found that Aβ fibrils can seed tau (Vasconcelos et al., 2016). Taking the evidence together, we hypothesize that cross-seeding of tau by Aβ promotes tangle formation in AD, which could be prevented not only by inhibiting Aβ aggregation, but also by disrupting the binding site of Aβ with tau. A number of interaction sites have been proposed on both proteins. In Aβ, both the amyloid core KLVFFA, along with region spanning the carboxy terminal residues were found to bind tau (Guo et al., 2006). Conversely peptides from regions of tau in exons 7 and 9, well as aggregation prone sequences VQIINK and VQIVYK located at the beginning of repeat 2 (R2) and repeat 3 (R3) of the microtubule domain (K18), respectively, were found to bind Aβ (Guo et al., 2006). A computational seeding model predicts that the amyloid core of Aβ can form intermolecular β-sheet interactions with VQIINK or VQIVYK (Miller et al., 2011). On this basis, we hypothesized that an inhibitor capable of targeting the amyloid core, which itself is an important sequence for Aβ aggregation (Tjernberg et al., 1999; Bernstein et al., 2005; Marshall et al., 2016), might block both Aβ aggregation and tau seeding by Aβ. However, this segment has been observed in multiple conformations in steric zipper structures (Colletier et al., 2011) and fiber models (Lührs et al., 2005; Colvin et al., 2016; Qiang et al., 2012; Huber et al., 2015; Wälti et al., 2016), impeding structure-based inhibitor design. In an effort to characterize a toxic conformation of this sequence, we focused our efforts on determining the structure of the segment 16–26, containing the Iowa early onset hereditary mutation, D23N (Van Nostrand et al., 2001). Based on this structure, we designed several inhibitors and found that they indeed blocked aggregation of Aβ, prevented cross-seeding of tau by Aβ, and surprisingly, also blocked tau homotypic seeding. We suggest that the efficacy of these structure-based inhibitors against both proteins, but not other amyloid fibrils, implies there is a similar binding interface displayed on both Aβ and tau aggregates, supporting the cross-amyloid cascade hypothesis in AD. Results Atomic structure of Aβ16-26 D23N determined using MicroED With crystals only a few hundred nanometers thick, we used micro-electron diffraction (MicroED) to determine the structure of Aβ residues 16–26 containing the hereditary mutation D23N, (Figure 1A), KLVFFAENVGS. The structure revealed pairs of anti-parallel β-sheets each composed of ~4000 strands, stacked into a fibril that spans the entire length of the crystal. Neighboring sheets are oriented face to back (Figure 1B, Table 1) defining a Class seven steric zipper motif. Figure 1 with 2 supplements see all Download asset Open asset MicroED structure of segment Aβ 16–26 D23N from microcrystals. (A) Electron micrograph of 3D crystals used for data collection, scale bar is 1 µm. (B) The crystal structure reveals tightly mated pairs of anti-parallel β-sheets with opposing sheets in gray and cyan. The side-chains interdigitate to form a dry interface. Two neighboring sheets are viewed perpendicular to the β-sheets. (C) View of 6 layers perpendicular to the fibril axis (black line). The β-sheets stack out of register along the fibril axis. https://doi.org/10.7554/eLife.46924.002 Table 1 Statistics of MicroED data collection and atomic refinement. https://doi.org/10.7554/eLife.46924.005 KLVFFAENVGSExcitation Voltage (kV)200Electron Sourcefield emission gunWavelength (Å)0.0251Total dose per crystal (e-/ Å2)2.7Frame rate (frame/s)0.3–0.5Rotation rate (°/s)0.3#crystals used13Total angular rotation collected (°)941Merging StatisticsSpace groupP21Cell dimensionsa, b, c (Å)11.67, 51.91, 12.76α, β, γ (°)90, 114.18, 90Resolution (Å)11.64–1.4 (1.44–1.40)*Rmerge24.0% (65.2%)No. Reflections47,598 (1966)Unique Reflections2355 (163)Completeness (%)86.2% (78.0%)Multiplicity21 (12)I/σ9.06 (2.88)CC1/299.5% (69.7%)Refinement StatisticsNo. reflections2354Reflections in test set236Rwork23.7%Rfree28.3%R.m.s. deviationsBond lengths (Å)0.014Bond angles (°)1.5Avg. B factor (Å2)9.46Wilson B factor (Å2)7.2Ramachandran (%)Favored100%Allowed0%Outliers0 *Highest resolution shell shown in parenthesis. In addition, the three C-terminal residues adopt an extended, non-β conformation which stabilizes the packing between steric zippers (Figure 1—figure supplement 1). The sheet–sheet interface is strengthened by interdigitating side chains, Lys 16, Val18, Phe20, Glu22 from the face of one strand, and Leu17, Phe19, and the N-terminus from the back of the other. The zipper has an extensive interface with a high shape complementarity of 0.76 and a total buried solvent accessible surface area of 258 Å2. This structure is partly identical to that of a shorter peptide segment, Aβ16–21, KLVFFA (crystal form-I) (Colletier et al., 2011), which we used successfully as a search model for molecular replacement. Both the longer and shorter segments have class seven symmetry. However, the two segments differ in registry. The shorter segment maintains an in-register hydrogen bonding pattern while the longer segment is out-of-register. That is, the strands of Aβ16–26 are tilted away from perpendicular to the fibril axis—a departure from canonical cross-β architecture. This elongated beta strand from residues 16–22 has also been observed in the full length in vitro fibrillar structure determined by cryoEM (Figure 1—figure supplement 2) (Gremer et al., 2017). The antiparallel architecture and lack of registration of Aβ16–26 suggest this crystalline ‘fibrillar’-like assembly has some characteristics of an amyloid oligomer. Structural studies of amyloid oligomers most frequently reveal anti-parallel β sheet architecture (Tay et al., 2013; Laganowsky et al., 2012; Sarkar et al., 2014), whereas fibril structures have revealed parallel β sheets (Lührs et al., 2005; Colvin et al., 2016; Wälti et al., 2016; Krotee et al., 2018), with the exception of some short segments of Aβ (Colletier et al., 2011) and in Aβ1-40 containing the early onset hereditary mutation D23N which leads to in-register anti-parallel fiber deposition in plaques (Qiang et al., 2012; Tycko et al., 2009). The out-of-register stacking of anti-parallel β strands has been proposed to be the defining trait of toxic oligomers (Laganowsky et al., 2012; Liu et al., 2012). The segment Aβ16–22 has been proposed to be able to form such oligomers in silica (Sun et al., 2018). The structures of Aβ16–21, Aβ16–26, and the full length fibrils may offer clues to designing inhibitors that impede both fibrillar and oligomeric assemblies. Efficacy of inhibitors of Aβ aggregation designed against Aβ 16–26 D23N As the zipper motif observed in the atomic structure of Aβ16-26 D23N may be relevant to a variety of amyloid beta assemblies, we sought to use it to develop structure-based peptide inhibitors of Aβ1-42. Our laboratory has developed a Rosetta-based design strategy using steric zipper structures to design capping peptide inhibitors for a number of amyloid proteins implicated in disease (Sievers et al., 2011; Seidler et al., 2018; Saelices et al., 2015; Soragni et al., 2016; Krotee et al., 2018). We chose to truncate our structure to residues 16–22 for the search model, omitting the residues not in the β strand. We threaded amino acids onto a capping β strand and minimized energies of sidechains. From our first round of design, we chose six distinct inhibitor candidates; those that were identified as good candidates but containing strong amino acid similarities to other top inhibitors were discarded. Our initial pool of inhibitors contained four L-form peptides, 2 each of 6 and 8 amino acids length, termed L1-L4, and two D-peptides six amino acids long, termed D1 and D2. We assessed the efficacy of the inhibitors at a 10 molar excess by testing if they prevented Aβ1-42 toxicity on Neuro-2a (N2a) cells, a mouse neuroblastoma cell line, (Olmsted et al., 1970). We measured cytotoxicity using 3-(4,5-dimethylthiazol-2-yl)−2,5-diphenyltetrazolium bromide (MTT) dye reduction (Mosmann, 1983; Liu et al., 1997). Our toxicity assay revealed one inhibitor, D1 with the sequence (D)-LYIWVQ, that was able to eliminate the toxic effect of Aβ1-42 (Figure 2A, Supplementary file 1); none of the inhibitors were toxic to N2a cells alone (Figure 2—figure supplement 1A). In our molecular model of the inhibitor, smaller hydrophobic residues of D1 mimic interactions with the fibril interface on one side of the peptide, which promotes recognition, (Figure 2B), while the other side of the peptide positions large aromatic residues between Aβ residues, blocking possible further interactions (Figure 2C). Figure 2 with 1 supplement see all Download asset Open asset Development of inhibitors of Aβ fibril formation using structure-based design against Aβ 16–26 D23N. (A) Identification of Aβ1–42 inhibitor. 10 μM Aβ1–42 was incubated alone or with 100 μM of each candidate peptide inhibitor for 12 hr at 37°C and then diluted 1:10 with pre-plated N2a cells. Cytotoxicity was quantified using MTT dye reduction Bars represent mean with individual technical replicates, error bars display one standard deviation (n = 3; ns = not significant; ****, p<0.0001 using an ordinary one-way ANOVA- Dunnett’s relative to leftmost column) (B, C) Segment KLVFFAEN, derived from the Aβ 16–26 D23N crystal structure, was used as the design target. Model of peptide inhibitor D1(magenta) bound to the design target, KLVFFAEN (gray). Smaller hydrophobic residues of D1 mimic interactions with the fibril interface on one side of the peptide (B), whereas the other side of the peptide positions large aromatic residues between Aβ residues, breaking possible further interactions (C). (D) Overview of peptide inhibitors in D and L amino acid conformations, as indicated, used in this study and their sequences. Peptide LC is the L-form cognate peptide of D-form peptide D1 and is the negative control for peptide inhibitor D1 and its derivatives D1b and D1d. IC50 values were determined using four parameter nonlinear fit for half maximal inhibition. N.D., not determined. (E) Peptide inhibitors D1, D1b, and D1d reduce the cytotoxicity of Aβ1–42 in a dose dependent manner, whereas control peptide LC does not. 10 μM Aβ1–42 was incubated alone or with various concentrations of each peptide inhibitor for 12 hr at 37°C and then diluted 1:10 with pre-plated N2a cells. Cytotoxicity was quantified using MTT dye reduction. Bars represent mean with individual technical replicates, error bars display one standard deviation (n = 3–6; ns = not significant; **, p<0.002; ****, p<0.0001 using an ordinary one-way ANOVA Dunnett’s relative to leftmost column). https://doi.org/10.7554/eLife.46924.006 Figure 2—source data 1 Toxicity data points—Aβ incubated with inhibitors and inhibitor controls. https://doi.org/10.7554/eLife.46924.008 Download elife-46924-fig2-data1-v2.xlsx We focused on these key features of the inhibitor sequence for our second round of design and aimed to improve efficacy. We lengthened our peptides to extend over more of our available structure towards the carboxy-terminus and made conservative residue changes to the face containing smaller hydrophobic residues. We selected and tested six new designs. Of the six, four were eight amino acids long such that the inhibitor would extend over more of our crystal structure, which we called D1a-D1d. The additional two, termed D1e and D1f, were six amino acids long featuring slight sequence perturbations from D1 (Supplementary file 1). We identified two of the eight amino acid long inhibitors, D1b and D1d, that were also effective at reducing AB1-42 toxicity at both a tenfold excess and at an equimolar ratio (Figure 2—figure supplement 1B,C). We then tested these two inhibitors, as well as D1, across a range of concentrations with final concentrations ranging from 100 nM to 10 μM (Figure 2D,E). We found that all inhibitors elicited a dose dependent response, with all having an estimated IC50 of less than 1 μM. The six residue long inhibitors, D1e and D1g, also had a similar effect on toxicity reduction as D1, however they did not perform as well as D1 in additional characterization and were not explored further (Figure 3—figure supplement 1B). The cognate negative peptide control, LC, the L-form peptide of inhibitor D1, did not reduce toxicity (Figure 2E). Reduction of toxicity by designed inhibitors is explained by a reduction of Aβ1-42 aggregation We next sought to understand the mechanism by which our peptide inhibitors reduce the toxic effect of Aβ1-42. We therefore assayed fibril formation to discern if this reduction of toxicity could be explained by reduced aggregation. We incubated Aβ1-42 with our inhibitors at 10:1, 1:1, and 1:10 molar ratios and monitored fibril formation by thioflavin-T (ThT) fluorescence at 37°C under quiescent conditions. We observe that all of our inhibitors reduce fibril formation in a dose dependent manner, while the negative control peptide, LC, does not (Figure 3A, Figure 3—figure supplement 1A). The longer inhibitors, D1b and D1d, appear effective at an equimolar ratio. However, when assayed at higher concentrations, the inhibitors appear to self-assemble, but remain effective at reducing Aβ1-42 toxicity (Figure 3—figure supplement 1C, Figure 2E). After 72 hr, samples were taken for negative-stain TEM analysis, which confirmed the reduced abundance of Aβ1–42 fibrils. D1b and D1d were more effective at reducing fibril formation than D1, although all three inhibitors showed near equal efficiency in reducing toxicity. Fibrils were observed in the equimolar ratio sample of Aβ1-42 with D1, whereas the comparable samples with D1b and D1d did not contain fibrils. Inhibitors that were not efficient at such as and were also less effective at blocking fiber formation (Figure 2—figure supplement 1C, Figure 3—figure supplement 1A). Figure 3 with 2 supplements see all Download asset Open asset inhibitors reduce aggregation of (A) Peptide inhibitors D1, D1b, and D1d reduce fibril formation of while negative control peptide LC does not. 10 μM of Aβ1–42 was incubated alone or at a 1:1, or molar ratio to each inhibitor under quiescent at formation was monitored using the of three technical with one standard deviation (B) TEM the of the in Figure were as and incubated for 72 hr TEM of Aβ1–42 to D1 D1b and D1d were at scale bars are 2 µm. other were at scale bars are (C) Peptide inhibitors reduce the formation of Aβ1–42 by while negative control peptides not. 10 μM Aβ1–42 was incubated alone column) or with molar excess of each peptide-based inhibitor. of the were tested for at 6 hr, hr, and 72 were as for Figure data 1 data Download and not fibrils, are to be the more toxic species of Aβ (Lesné et al., 2006; Lambert et al., 1998; Benilova et al., 2012; et al., 2011), we then if our inhibitors the formation of oligomers or other Aβ1-42 species. We used to samples of Aβ1-42 incubated with a excess of inhibitor at by and a of was reduced by all of our inhibitors (Figure Figure 3—figure supplement 1C, Figure 3—figure supplement While we have not determined the oligomeric the inhibitors are our binding data with the of our toxicity suggest that the formation of a toxic oligomeric assembly is the inhibitors reduced the abundance of Aβ conformations by and bind fibrillar plaques from patient derived AD tissue and/or mouse tissue et al., 2014). these that our inhibitors may reduce as well as disease relevant fibrillar Inhibitors bind and reduce toxicity of Aβ As AD is only long Aβ aggregation has we if these inhibitors would not only amyloid from but also if they can reduce the toxic effect of we incubated 10 μM Aβ at 37°C for 12 hr to form oligomers (Figure supplement 1A), and then inhibitors at various concentrations to to N2a cells and assayed toxicity by MTT dye reduction. We found that the inhibitor to Aβ1-42 to had a from inhibitor to Aβ1-42 with Aβ, the shorter D1 inhibitor was as effective as D1b and D1d at reducing when to Aβ assemblies, only the longer inhibitors D1b and D1d were effective at reducing toxicity (Figure Both of the longer inhibitors could toxicity of at 10 but D1d is more with effective reduction of toxicity to 1 μM. D1b from D1d only at amino acid positions 6 and We the in efficacy is from residue both inhibitors contain residues at but at 6 D1b a while D1d has a Our that while peptide inhibitors can both aggregation and block toxicity of aggregated assemblies, the to be more to slight perturbations in inhibitor Figure with 2 supplements see all Download asset Open asset Inhibitors bind and block toxicity of aggregated (A) The toxicity of Aβ1–42 is by peptide 10 μM Aβ1–42 was incubated alone for 12 hr at molar ratio of inhibitor was to the incubated Aβ1–42 and then diluted 1:10 with pre-plated N2a cells. Cytotoxicity was quantified using MTT dye reduction. Bars represent mean with individual technical (n = 3–6; ns = not significant; ****, p<0.0001 using an ordinary one-way ANOVA- Dunnett’s relative to leftmost column). (B, C) Inhibitors bind to Aβ1–42 fibrils. (B) Peptide inhibitors not Aβ. 10 μM Aβ1–42 was incubated alone for 72 hr at Peptide inhibitors were at molar excess and incubated at for hr TEM were at scale bars are (C) of inhibitor D1d to fibrillar The maximal response was derived by over a range of D1d concentrations to the binding model with a of 6 displayed as a values are = as a of and to a binding model, displayed as a Figure data 1 Toxicity data points—Aβ with Download We next TEM to determine if our inhibitors could or if the are as our inhibitor design would We aggregated 10 μM Aβ1-42 for 72 hr at 37°C under then inhibitors at 100 μM and incubated As the are still we that our inhibitors are indeed capping or the at toxicity further seeding or toxic (Figure the capping ability of our inhibitors, we the inhibitors to Aβ1-42 the of fibril (Figure supplement 1B). We found that at the of inhibitor, 10 μM 1 μM inhibitor, we see of for inhibitors D1b and D1d. we observed a slight of samples with a inhibitor addition, to inhibitors bound to the fibrils. As the inhibitors aggregation as well (Figure we are to the of this as the inhibitor could be or from to the fibrils. We to that our inhibitors bind to We that the most inhibitor of aggregated assemblies, D1d, to Aβ1-42 fibrils with an of μM (Figure Figure supplement We used a model to fit the the may be to the of D1d and Aβ fibrils. we have shown that inhibitors D1b and D1d not only aggregation of Aβ, but also bind aggregated Inhibitors reduce seeding of tau by aggregated Aβ1-42 that our inhibitors block a toxic interface on Aβ, we next if this interface could also be in seeding tau. we sought to the direct seeding mechanism that has been reported by (Guo et al., 2006; et al., 2011; et al., 2016). We tested seeding of the microtubule binding domain of tau, in a assay at 37°C under and found that fibrils of Aβ1-42 and Aβ16-26 D23N aggregation, not as as fibrils of (Figure Figure supplement 1A). This seeding effect was also observed on full length tau in the of (Figure supplement 1B). was to seed Aβ (Figure supplement Figure with 2 supplements see all Download asset Open asset Tau aggregation is by Aβ and reduced by structure-based (A) μM was with of fibrils of Aβ16-26 D23N or under at at 37°C in formation was monitored using bars the standard deviation of the of three technical (B) The number of intracellular in cells to cell by the of nM or nM Aβ1–42 fibrils. bars the standard deviation of the mean of technical (n = 3; ****, using an ordinary one-way ANOVA- Dunnett’s relative to leftmost and **, in test of Aβ (C) of cells from B at scale bar 100 and dependent of Aβ1–42 seeding of tau aggregation in cells. (D) seeding by Aβ as a of inhibitor bars the standard deviation of the mean of technical (n = 3; ns = not significant; **, ****, p<0.0001 using an ordinary one-way ANOVA- Dunnett’s relative to leftmost and the the mean number of from Aβ1–42 fibrils. (E) of cells the effect of D1b on seeding. are shown at scale bar 100 Figure data 1 Tau seeding data points—Aβ and other amyloid fibrils with and Download we tested seeding in a cell line, which the microtubule binding domain of tau This cell line, to as cells, has been used to seeding from tau fibrils to cells and has been used as a model to test tau inhibitors et al., 2018; et al., 2012). We cells with or Aβ fibrils (Figure supplement to a final of We found that Aβ was able to intracellular than the but only at efficiency of is not that Aβ has such a efficiency of this a in a similar (Vasconcelos et al., 2016). is possible that tau fibrils contain multiple and capable of homotypic whereas Aβ may have a more limited number of tau in vitro Aβ aggregation may ratios of to those in AD. it remains that some Aβ species is The that Aβ