The phenotype of an individual can be affected not only by the individual’s own genotypes, known as direct genetic effects (DGE), but also by genotypes of interacting partners, indirect genetic effects (IGE). IGE have been detected using polygenic models in multiple species, including laboratory mice and humans. However, the underlying mechanisms remain largely unknown. Genome-wide association studies of IGE (igeGWAS) can point to IGE genes, but have not yet been applied to non-familial IGE arising from “peers” and affecting biomedical phenotypes. In addition, the extent to which igeGWAS will identify loci not identified by dgeGWAS remains an open question. Finally, findings from igeGWAS have not been confirmed by experimental manipulation.Epha4 gives rise to IGE on stress-coping strategy and wound healing.We leverage a dataset of 170 behavioral, physiological, and morphological phenotypes measured in 1812 genetically heterogeneous laboratory mice to study IGE arising between same-sex, adult, unrelated mice housed in the same cage. We develop and apply methods for igeGWAS in this context and identify 24 significant IGE loci for 17 phenotypes (FDR < 10%). We observe no overlap between IGE loci and DGE loci for the same phenotype, which is consistent with the moderate genetic correlations between DGE and IGE for the same phenotype estimated using polygenic models. Finally, we fine-map seven significant IGE loci to individual genes and find supportive evidence in an experiment with a knockout model that Our results demonstrate the potential for igeGWAS to identify IGE genes and shed light into the mechanisms of peer influence.The online version contains supplementary material available at 10.1186/s13059-021-02415-x. The phenotype of an individual can be affected not only by the individual’s own genotypes  but also by environmental factors, including the genotypes of other, interacting individuals  –3 Fig. a. IGE arspecific traits of partners using trait-based models [unknown heritable traits of partners using variance component models [Most prior studies of IGE have used polygenic modeling approaches to study aggregate genetic effects , either focusing on IGE mediated by d models , 28 or pd models , 25, or t models , 29, 30.t models , 31–35.However, igeGWAS has only been applied in limited settings: in particular, it has not been used to study non-familial IGE from peers affecting biomedical phenotypes, despite growing evidence from polygenic models in laboratory mice  and in hTo address these issues, we leveraged a published dataset of 170 behavioral, physiological, and morphological phenotypes measured in 1812 male and female, genetically heterogeneous mice  Illumina sequencing, see the “5x Illumiρ between DGE and IGE. As this correlation is equivalent to the correlation between DGE on the phenotype of interest and DGE on the traits mediating IGE , indicating that, often, the traits mediating IGE on a phenotype of interest are genetically correlated  with the phenotype of interest. Evidence that ρ is different from zero was strongest for mean weight of the adrenal glands, which correlates with stress [ρ is different from ±1 for 10 phenotypes (P < 0.05), with the strongest evidence for a measure of stress-coping strategy (immobility in the forced swim test) and rate of healing from an ear punch. These results indicate that IGE on a phenotype of interest are often mediated by traits of partners different from the phenotype of interest. To uncover those traits, we turned to igeGWAS.Initially, we used polygenic models to assess the extent to which loci are shared between DGE and IGE affecting the same phenotype. Briefly, for each trait, we estimated the genetic correlation IGE Fig. b, a corrIGE Fig. : Fig. S1h stress , mean plNext, to compare DGE and IGE at the level of individual loci, we considered the LD-pruned set of variants and performed igeGWAS and dgeGWAS in an analogous manner for each of the 170 phenotypes. For igeGWAS, we estimated the “social genotype” of a mouse at a variant as the sum of the reference allele dosages across its two cage mates at the variant , 39 and igeGWAS identified a total of 24 significant loci across 17 of the 170 tested phenotypes (FDR < 10%), including measures relevant to behavior, adult neurogenesis, blood biochemistry, red and white blood cells, apparent bone mineral content, electrocardiography, and ventilatory responses to acute hypoxia  are important, in addition to the parameters also determining the power of dgeGWAS, namely minor allele frequency (MAF) and allelic effect ; Pkn2, Slit3, and Pgk1-rs7 (at three different loci for sleep); H60c (home cage activity); and Adcy1 (osteopetrosis).Linkage disequilibrium decays faster in the CFW population than in many other mouse populations used for mapping, which facilitates identification of putative causal genes at associated loci , 44, 45.Epha4, which was identified at an IGE locus on chromosome 1 for immobility during the first 2 min of the forced swim test (FST), a measure of stress-coping strategy [Epha4 initially because it was the only putative causal gene at a significant locus, the locus was in the top half of the list in terms of significance, and a knockout mouse model was readily available from a neighboring institute. In addition, Epha4 is in a gene desert and the only protein-coding gene in a chromatin topological domain [Epha4 locus likely affect the expression of Epha4 and not that of a neighboring gene.One example of a putative causal IGE gene identified via this strategy is strategy  , thereby giving rise to IGE on stress-coping strategy. To investigate this hypothesis, we tested whether Epha4 has direct effects on FST immobility in CFW mice, using the full set of variants in the same 1.5-Mb window including Epha4 as for IGE analysis. We found little evidence that Epha4 directly affects FST immobility in CFW mice  and because IGE on wound healing seem to be ubiquitous in laboratory mice: indeed, we have found a significant aggregate contribution of IGE to rate of healing from an ear punch in all three mouse populations we have looked at to date .We found two additional significant IGE loci for FST immobility, more precisely for immobility during the last 4 min of the test  was co-housed with one focal FVB/NJ (FVB) mouse of the same sex . The FVB strain was chosen because it is the inbred strain whose genetic background is most similar to that of the outbred CFW mice used in igeGWAS, contributing 38% of all alleles in CFW mice [We tested the hypotheses that CFW mice . Focal FAlthough FVB mice are genetically similar to CFW mice, we observed that focal FVB mice showed much less immobility during the first 2 min of the FST than CFW mice . Therefore, in our analysis of FVB focal mice, we focused on immobility during the last 4 min of the test, even though this measure showed a less significant association in igeGWAS than immobility during the first 2 min of the test .Epha4 on wound healing is consistent with the observation of stronger IGE at the Epha4 locus in male CFW mice compared to female CFW mice  or wound healing . However, model comparison using the Akaike Information Criterion (AIC) indicated there is an interaction between sex and genotype of the cage mate  for both FST immobility and wound healing, as the model including an interaction term between sex and genotype of the cage mate was favored. Therefore, we considered the two sexes separately and observed, in males but not in females, suggestive evidence of IGE on FST immobility  and wound healing  , indicating behavioral contagion is unlikely to explain these IGE.As was the case in CFW mice, we did not observe a direct effect of Dlgap1 on FST immobility.Finally, we found no evidence of IGE from Epha4, on stress-coping strategy and wound healing using a knockout model.In this study, we leveraged a published dataset of 170 behavioral, physiological, and morphological phenotypes measured in 1812 genetically heterogeneous mice housed in same-sex groups of three to characterize the relationship between DGE and IGE for the same phenotype and identify individual IGE loci. Using polygenic models, we showed that the genetic correlation ρ between DGE and IGE for the same phenotype is often significantly different from ±1, indicating IGE loci are different from DGE loci for the same phenotype. Consistently, we found that none of the 24 significant IGE loci identified for 17 phenotypes using igeGWAS overlapped with significant DGE loci identified for the same phenotypes using dgeGWAS. We fine-mapped seven significant IGE loci to a single putative causal gene and experimentally validated IGE from one of them, The analysis of the genetic correlation ρ between DGE and IGE for the same phenotype provides insights into the overlap between DGE and IGE loci for a given phenotype and whether the traits mediating IGE on a phenotype of interest are genetically correlated  with that phenotype. The correlation ρ was expected to be different from 0 for many phenotypes, based on reports that emotions –57, behaConsistent with the estimates of ρ from polygenic models, we found no overlap between the 24 loci identified by igeGWAS for 17 phenotypes and the loci identified by dgeGWAS for the same phenotypes. Our survey of a large number of phenotypes suggests that the loci identified by igeGWAS will, generally, be different from those identified by dgeGWAS, meaning igeGWAS holds great potential to uncover new loci underlying phenotypic variation and that these loci will point to traits of cage mates different from the phenotype studied.Abca12 at a locus for adult neurogenesis; Epha4 at a locus for stress-coping strategy; Pkn2, Slit3, and Pgk1-rs7 at three different loci for sleep; H60c at a locus for home cage activity; and Adcy1 at a locus for osteopetrosis. Among the loci with a single putative causal gene, the Epha4 locus stood out because of its relatively high significance and because Epha4 is the only gene in a well-characterized topological domain [Epha4 locus likely affect the expression of Epha4 and not that of a neighboring gene. Hence, we tested Epha4 in an experiment with a knockout model. Model selection analysis using the AIC indicated an interaction between the Epha4 allele and the sex of cage mates for both stress-coping strategy and wound healing and, indeed, we found suggestive evidence of IGE from Epha4 on both phenotypes in male mice , but not in females. A limitation of our experiment is that FVB focal mice showed little to no immobility during the first 2 min of the FST, in contrast with the CFW mice used in igeGWAS. Hence, even though the significant igeGWAS locus was for immobility during the first 2 min of the test, we had to focus on immobility during the last 4 min when analyzing the behavior of FVB mice. Similarly, immobility during the last 4 min was lower in FVB female mice than FVB male mice, which may explain why we only observed IGE from Epha4 in males. Effects of the genetic background of knockout models have been reported in studies of DGE [Identifying IGE genes using igeGWAS has been previously attempted , 31–35, l domain , 49, meas of DGE ; our resEpha4 plays an important role in the development of the central nervous system and in synaptic plasticity [Epha4 were mediated by behaviours of cage mates, more specifically by focal mice copying the stress-coping strategy of their cage mates . We found no evidence of DGE from Epha4 in either CFW or FVB mice however, suggesting other behaviours of cage mates—or other traits altogether—are involved. As far as wound healing is concerned, the reported expression of Epha4 in platelets in humans [Epha4 on wound healing.The seven genes listed above as single putative causal genes at IGE loci are valuable starting points to gain insights into the mechanisms of IGE. In some cases, it is possible to make testable hypotheses as to the mechanisms mediating IGE from knowledge of the expression profile and function of the gene. For example, asticity , 51, andasticity , 53. Henn humans , the pren humans , and then humans  suggest Finally, we identified challenges and solutions to different sources of confounding in igeGWAS. In particular, we demonstrated that correlations between direct and social genotypes arise when study individuals play both roles of focal individuals and social partners and that, counter-intuitively, these correlations arise even when all individuals are strictly unrelated. We showed that accounting for direct effects of the locus tested in the null model for igeGWAS permits avoiding spurious IGE associations. These insights, combined with the light we shed on two key parameters determining the power of igeGWAS, namely the number of cage mates and the mode of aggregation of IGE across cage mates, will inform the design and analysis of future igeGWAS.Our results demonstrate the potential for igeGWAS to uncover genetic effects expressed only in the context of social interactions and to serve as a starting point for follow-up analyses and experiments that will improve our understanding of peer effects on health and disease.http://wp.cs.ucl.ac.uk/outbredmice/. Phenotypes were normalized using the boxcox function  for 1934 male and female Crl:CFW(SW)-US_P08 (CFW) mice were retrieved from  package ) in R; pMice were 4 to 7 weeks old when they arrived at the phenotyping facility and were housed in same-sex groups of three mice. They were left undisturbed for 9 to 12 weeks during their time in quarantine and spent another 4 weeks together during phenotyping.Cage assignments were not included in the publicly available dataset but were provided by the authors upon request and are now provided in Additional file Finally, all mice were singly housed during the sleep test and until sacrifice a few days later. Hence, we investigated “persistent” IGE on sleep and tissue phenotypes.http://wp.cs.ucl.ac.uk/outbredmice/, we retrieved both allele dosages for 7 million variants and allele dosages for a subset of 353,697 high quality, LD-pruned variants . We used LD-pruned variants for all analyses but the identification of putative causal genes at IGE loci (see below), for which we used the full set of variants.From The genetic relatedness matrix (GRM) was calculated as the cross-product of the LD-pruned dosage matrix after standardizing the dosages for each variant to mean 0 and variance 1. A few pairs of mice were outliers in the distribution of GRM values, which made us suspect that siblings had been included in the sample even though they were not supposed to be (siblings were excluded by design). To mitigate confounding of DGE and IGE analyses by parental and litter effects, we excluded 19 cages (57 mice) from all analyses.The same model as described in detail in Baud et al.  was usedyf is the phenotypic value of the focal mouse f, Xf is a row of the matrix X of covariate values, and b a column vector of corresponding coefficients. f. Zf is a row of the matrix Z that indicates cage mates  and Wf is a row of the matrix W that indicates cage assignment and c the column vector of cage effects.The joint distribution of all random effects is defined as:where A is the GRM matrix and I the identity matrix.The phenotypic covariance is:When all cages have the same number of mice, as is the case in this study, the non-genetic random effects are not identifiable , 66. An We checked that both model  and thisThe aggregate contributions of DGE and IGE were calculated, respectively, assampleVar(C) and sampleVar is the sample variance of the corresponding covariance matrix: suppose that we have a vector M, the sample variance of M is calculated aswhere Tr denotes the trace, n is the sample size, and The significance of the IGE variance component was assessed using a two-degree of freedom log likelihood ratio (LLR) test (for the variance component and the covariance with DGE). Note that this testing procedure is conservative. The Q value for the aggregate contribution of IGE was calculated for each phenotype using the R package qvalue . Signifiρ between The correlation We tested whether ρ was significantly different from 0 and whether |ρ| was significantly different from 1 using a one-degree of freedom LLR test, which is conservative for the latter test.Phenotypes were simulated based on the genotypes and cage relationships of the full set of 1812 mice. Phenotypes were drawn from model  and ZfG is the sum of the genotypes of the two cage mates of f, the “social genotype” of f [bD the coefficient for local DGE and bS the coefficient for local IGE. Note that Zf could be defined as the average of the genotypes of the two cage mates of f, in which case GfbD in models .The significance of local IGE was calculated by comparing models  and 3)  3) with dgeGWAS was carried out by comparing model  above toZfGbS in model   ZfGbS infor each phenotype independently of the results for the other phenotypes in the dataset. More precisely, for each phenotype and for each type of genetic effect (direct and indirect), we performed 100 “permuted GWAS” by permuting the rows of the matrix of social (respectively direct) genotypes and testing each variant at a time using the permuted genotypes together with the un-permuted phenotypes, un-permuted covariates, un-permuted GRM, and un-permuted matrix of direct  genotypes (for conditioning) [We used a genome-wide permutation strategy to control the FDR for each phenotype, as done by Nicod et al. . This sttioning) , 41. ForWe reported those loci with FDR < 10%.At each significantly associated locus, we defined a 1.5-Mb window centered on the lead variant corresponding, in this sample, to the 95% confidence interval for the association . We idenhttps://genome.sph.umich.edu/wiki/LocusZoom_Standalone). The plots for all 24 significant IGE loci reported in Additional file figshare [We identified putative causal genes using locusZoom plots . To creafigshare .http://genenetwork.org/) ([https://pubmed.ncbi.nlm.nih.gov/33472826/)). The data are accessible by selecting Mouse as Species, CFW Outbred GWAS as Group, Hippocampus mRNA as Type, and UCSD CFW Hippocampus (Jan17) RNA-Seq Log2 Z-score as Dataset. To retrieve the genes whose expression is most highly correlated with that of Epha4, we entered “Epha4” in the Get Any field. Following the selection of the Epha4 record (click on ENSMUSG00000026235), we used Calculate Correlations with Sample r as Method, UCSD CFW Hippocampus (Jan17) RNA-Seq Log2 Z-score as Database, and Spearman rank as correlation Type. Additional file Sample rho).Gene expression in the hippocampus of an independent sample of 79 male CFW mice, initially published in Parker et al. , was avak.org/)  with additional fixed effects for both DGE and IGE of lead SNPs at all significant IGE loci . After fitting the model, the variance was calculated as:sampleVar(C) is the sample variance of the covariance matrix in this model.where The variance explained by a significant DGE association was estimated in a similar model but considering all significant DGE associations and calculated as:Phenotypes were simulated based on the genotypes and cage relationships of the 1812 mice. Null phenotypes  were simulated from model , we simulated an allelic effect of 0.2, which is similar to the average allelic effect estimated in the igeGWAS. Power was calculated at a genome-wide significance threshold of negative log P 5, which is similar to the significance of associations detected at FDR < 10%.Local DGE and IGE were simulated at variants with low MAF (MAF < 0.05), medium MAF (0.225 < MAF < 0.275), or high MAF (MAF > 0.45). Local IGE were simulated using two alternative generative models: an “additive” model by using in model   on a mixed C57BL/6, C57BL/10 and 129 genetic background, originally created by Dottori et al. [Dlgap1, wild-type (WT), heterozygote (Het), and homozygote knockout (KO) offspring. For Epha4, homozygote knockout offspring usually died before weaning, leaving Het and WT offspring only. Within 3 days of weaning, we paired one focal FVB mouse with either a Dlgap1  or an Epha4 (WT or Het) cage mate of the same sex . Immediately prior to pairing, the FVB mice were ear punched on each ear using 2-mm ear punch scissors. Pairs of mice were then left to interact for 2 months before all mice were phenotyped in the forced swim test (FST) and sacrificed and the ears of FVB mice were collected. The sample size was 52 Epha4 Het mice and 33 Epha4 WT mice for wound healing; for FST, there were only 48 Epha4 Het mice as one mouse died during the FST, two mice had to be separated from their cage mate due to fighting in the days before the FST , and during the FST of the fourth mouse, the battery of the camera ran out. A small subset of mice were video recorded in a new enclosure for 24 h a few days before the FST but the data from this pilot project are not reported here. Throughout the experiment, all mice were housed on a 12-h:12-h light-dark cycle, with lights on at 06:00, and all behavioral testing occurred during the light phase of the light-dark cycle.All animal procedures were approved by the Institutional Animal Care and Use Committee of the University of California San Diego (UCSD) and were conducted in accordance with the NIH Guide for the Care and Use of Laboratory Animals. FVB/NJ (hereafter FVB) breeder mice were originally purchased from the Jackson Laboratory , then bred on site. i et al. , were geEpha4 and Dlgap1) mice. The analysis of IGE focused on immobility of FVB mice in the last 4 min of the test as FVB mice are rarely immobile during the first 2 min of the test.Following the same protocol as in the CFW study , mice weEpha4 or a Dlgap1 cage mate at weaning. Following the same protocol as in the CFW study [Both ears of FVB mice were punched with a 2-mm-diameter ear punch scissor just before the mice were paired with an FW study , the earFW study  and the Epha4 mice, tail or ear biopsies were sent to Transnetyx Inc. for genotyping . Transnetyx Inc. utilize real-time PCR and duplicate sample processing to ensure the accuracy of each mutation. Additionally, Sanger sequencing and gene expression analysis were performed to further validate the results of the Transnetyx assays.For genotyping Dlgap1 mice, we used a multiplex PCR with primers: CCGTAAGTGAAGTCTCCATCAACAG (Fw1), CGGCTAGGATTTCAGAGTTTGTTC (Fw2) and CTTCCTCTCCTACACCATCAACAC (Rev1), yielding a 308-bp band in the presence of a WT allele and a 392-bp band in the presence of a knockout allele.For genotyping For both FST immobility and wound healing, five fixed effect models were first compared using the Akaike Information Criterion (AIC): a model with intercept only, a model with the sex of the pair , a model with the genotype of the cage mate, a model with both sex and genotype of cage mate, and finally a model with main effects of sex and genotype of cage mate and their interaction.IGE were then tested in males using an analysis of variance (ANOVA) with one degree of freedom.Additional file 1: Table S1. Cages for all mice across their time at the phenotyping facility.Additional file 2: Supplementary note. Correlation ρ between direct and social genotypes arising from using each individual as both focal individual and social partner. Fig. S1. Estimation of the correlation ρ between IGE and DGE in simulations. Fig. S2. Correlations between direct and social genotypes of CFW mice, and implications for GWAS. Fig. S3. Proportion of phenotypic variance explained by significant DGE and IGE loci. Fig. S4. Power to detect DGE and IGE associations in simulations. Fig. S5. Quantile-quantile (QQ) plot for the igeGWAS P values for Immobility during the first two minutes of the forced swim test. Fig. S6. Information relevant to the role of Dlgap1 in giving rise to IGE on immobility during the last four minutes of the FST. Fig. S7. Phenotypes of the outbred CFW mice used in igeGWAS.Additional file 3: Table S2. Information about each phenotype, aggregate contributions of IGE and DGE, and correlation ⍴ between IGE and DGE.Additional file 4: Table S3. Genome-wide significant IGE associations (per-phenotype FDR < 10%).Additional file 5: Table S4. Genome-wide significant DGE associations (per-phenotype FDR < 10%).Additional file 6:. Review history.


The assembly of synaptic protein-DNA complexes by specialized proteins is critical for bringing together two distant sites within a DNA molecule or bridging two DNA molecules. The assembly of such synaptosomes is needed in numerous genetic processes requiring the interactions of two or more sites. The molecular mechanisms by which the protein brings the sites together, enabling the assembly of synaptosomes, remain unknown. Such proteins can utilize sliding, jumping, and segmental transfer pathways proposed for the single-site search process, but none of these pathways explains how the synaptosome assembles. Here we used restriction enzyme SfiI, that requires the assembly of synaptosome for DNA cleavage, as our experimental system and applied time-lapse, high-speed AFM to directly visualize the site search process accomplished by the SfiI enzyme. For the single-site SfiI-DNA complexes, we were able to directly visualize such pathways as sliding, jumping, and segmental site transfer. However, within the synaptic looped complexes, we visualized the threading and site-bound segment transfer as the synaptosome-specific search pathways for SfiI. In addition, we visualized sliding and jumping pathways for the loop dissociated complexes. Based on our data, we propose the site-search model for synaptic protein-DNA systems. The formation of such loops for various synaptosomes has been visualized with Atomic Force Microscopy (AFM) in our previous papers , 2 μL of DNA substrate (86 ng/μL), 1 μL 1 mM DTT, 1 μL SfiI enzyme, and 5 μL di-water was incubated for 15 min at room temperature, diluted through serial dilutions, and deposited on APS-functionalized mica [Complex assembly was performed as described in our previous study . Brieflyzed mica  for AFM HS-AFM experiments followed our earlier protocol for protein-DNA complexes ,27. BrieFor characterization of the SfiI-DNA complex assembly, 2 μL of the diluted reaction mixture was deposited on the APS-mica. The mica sample was then placed in the HS-AFM cell containing reaction buffer. Imaging was carried by continuously scanning an area on the mica surface, with a typical scan size of 300 nm × 300 nm and scan rate of 600 ms/frame.To observe the protein dynamics of the SfiI-DNA complexes very gentle, i.e., low tip-sample force, was used during imaging of the sample. This was possible due to low amplitude setpoint as well as use of dynamic PID , resultiAnalysis was performed using FemtoScan software  for the individual frames as described earlier ,26. The The SfiI site-search process was directly visualized using time-lapse HS-AFM. A model for the formation of synaptic protein-DNA complexes is presented based on the data obtained in this study. According to the model, SfiI utilizes threading and site-bound segment transfer pathways to assemble the synaptosome. During the site-search, transient loops are formed, facilitating the search of another specific site. In addition, we have observed the sliding and jumping of SfiI, which the protein utilizes to initiate the site-search process. The contribution of the threading pathway in the site-search process is slightly greater than the site-bound segment transfer pathway in our observation; however, a combination of both site-bound segment transfer and threading facilitates the assembly of the protein-DNA synaptic complex.


V1.5) is a protein with four domains (DI-DIV), each with six transmembrane segments. Its opening and subsequent inactivation results in the brief rapid influx of Na+ ions resulting in the depolarization of cardiomyocytes. The neurotoxin veratridine (VTD) inhibits NaV1.5 inactivation resulting in longer channel opening times, and potentially fatal action potential prolongation. VTD is predicted to bind at the channel pore, but alternative binding sites have not been ruled out. To determine the binding site of VTD on NaV1.5, we perform docking calculations and high-throughput electrophysiology experiments in the present study. The docking calculations identified two distinct binding regions. The first site was in the pore, close to the binding site of NaV1.4 and NaV1.5 blocking drugs in experimental structures. The second site was at the “mouth” of the pore at the cytosolic side, partly solvent-exposed. Mutations at this site  had large effects on VTD binding, while residues deeper in the pore had no effect, consistent with VTD binding at the mouth site. Overall, our results suggest a VTD binding site close to the cytoplasmic mouth of the channel pore. Binding at this alternative site might indicate an allosteric inactivation mechanism for VTD at NaV1.5.The cardiac sodium ion channel (Na V) are ion channels consisting of four transmembrane domains (DI-DIV) containing six segments each (S1–S6) and found in multiple cell types. The S5 and S6 segments assemble to form an ion pore that is responsible for sodium ion conduction through the protein, depending on the voltage changes in the environment as sensed by the S4 segments spirost-5-en, ID: 9Z9) bound to the opening of the pore , which V1.5. The pore site scores were lower than the mouth site scores on average, but this difference was less than 1.0 Rosetta Energy Units (REUs)  . The varPose 1 has Ring 1 facing the direction of the solvent with the DMP ring buried in the pore . At the Pose 2 is “flipped” compared to Pose 1, whereby the charged nitrogen is facing the pore and the DMP ring is situated closer to the mouth of the pore . All thePose 3 lies on the mouth of the pore without significant interactions with the residues lining the bottom of the previous two poses, such as L409 or I1466 . A413, LPoses 4 and 5 bound deeper in the pore contrary to the first three poses and had no contacts with the residues lining the mouth of the pore, such as E417 and D1471 . Pose 4,Overall, the five clusters were inconsistent with each other and suggested different binding sites and different binding orientations with the charged nitrogen placed in different positions. Two of the five poses bound deeper in the pore, two poses bound along the pore, and one pose bound to the mouth of the pore with a tilted angle. Next, we investigated VTD binding to the pore site.Pose 1 runs parallel to the channel pore with the ring group of DMP facing the extracellular side of the membrane . This grPose 3 has only Ring 1 inside the channel pore, and the rest of the molecule extended towards the sides of the protein between multiple α-helices that run in the direction between the cytoplasmic and the extracellular sides of the membrane . The DMPBased on the poses obtained from different clusters, we chose eleven variants at eight sites. Some of these were designed to remove charged or hydrophobic interactions to probe interactions between these side chains and the VTD poses to eliminate irrelevant docking poses, whereas others were designed to introduce minor changes to the side chain structures to pinpoint the location of specific residue—ligand interactions. It is important to note that considering the large number of residues that interact with VTD in all the different pose clusters, it was feasible to investigate only a fraction of these putative interactions. The residues selected for the experiments were chosen to exploit the similarities and the differences observed between the mouth site and the pore site poses in addition to the configurational differences at each site.The two E417 mutations (E417A and E417R) were selected to test the effect of mouth site mutations on VTD binding. This residue sits at a solvent-exposed region at the mouth of the ion channel and its mutation would have no effect if the ligand binds to the pore site. E417A was designed to sever hydrogen bonding or electrostatic interactions between VTD and this residue. E417R was designed to block the pore opening due to the larger size of arginine and to cause a clash between the charged nitrogen of VTD if E417 and this nitrogen are in close proximity.F942 sits close to the opening of the mouth where it forms hydrophobic interactions with a small number of poses. The F942A mutation was selected to rule out these poses, and the F942Y mutation was selected to test whether the additional -OH group could form hydrogen bonds with the -OH groups of VTD in the vicinity, thus improving the binding of VTD.The L409S and L1462S mutations were selected to check whether these two residues form hydrophobic interactions with the VTD rings that would suffer from the removal of the leucine methyl groups. The I1466T and I1771T mutations also had a similar logic, but this time the focus was on removing the ethyl group only to test the extent of hydrophobic interactions between these residues and VTD. It is important to note that L409 and I1466 are situated in a position that forms the bottom border of the proposed mouth site and the top border of the pore site, therefore these mutations would be expected to be relevant for VTD binding at both sites.F1760 is situated at the pore site below the residues L409 and I1466. This residue interacted with the pore site poses through hydrophobic and π-cation interactions but had no significant interactions with the mouth site poses. The F1760A mutation was chosen to abolish the hydrophobic and π-cation interactions formed between VTD and the pore poses. The F1760Y mutation was chosen to increase the size of the side chain that could interact with the DMP ring of the mouth site poses, and to test whether another aromatic residue is tolerated if VTD binds to the pore site. Likewise, the F1465Y mutation was selected to introduce an additional -OH group that increases the size of the phenylalanine side chain, which was predicted to extend further towards the ion channel and improve VTD binding at the mouth site.SCN5A mutations expressed in HEK293 cells, we measured the effect of mutations on VTD’s modulation of NaV1.5 late current. When added to NaV1.5, VTD partially inhibits channel inactivation and increases the NaV1.5 late current from minimal (~0.3% of peak current) to large (10–30% of peak current) (V1.5 by 10% (Using automated patch clamping of current) . To quan5 by 10% . Six out5 by 10% .The three mutations that have the largest effects on VTD activity are L409S, I1466T, and E417R . The ineThe moderate binding diminution caused by F1465Y and F1760Y suggests increasing the residue size close to the ion pore is not well-tolerated. The ineffectiveness of the F1760A mutation rules out a large number of pore site poses that formed hydrophobic and π-cation interactions with this residue. Likewise, the large effect of L409S and I1466T mutations rules out the pore site poses that extend orthogonal to the ion pore with no interactions with these residues. Overall, these results favor VTD binding to the mouth site due to the decrease caused by the E417R mutation and the lack of a binding change due to the F1760A mutation. In addition, the results rule out the mouth site poses that do not contact the residues L409 and I1466. Next, we ran in silico ΔΔG calculations to identify the VTD poses at both binding sites consistent with the measured binding data.ddGScan protocol [2 values were calculated with Python and these values were used to select the best pose at each site. With this approach, the best pore site poses had an R2 value of 0.75, but the calculated scores were close to 0 for most cases and they could not distinguish between the significant and insignificant residues. On the other hand, the mouth site poses have R2 values up to 0.85, which also reflect the distribution of the measured binding changes upon mutations , F1283 (NaV1.5 F1465), I1284 (NaV1.5 I1466), F1579 (NaV1.5 F1760), N1584 (NaV1.5 N1765), and F1236 (NaV1.5 F1418).VTD activity at Na protein . The intV1.5, only the first two were tested, where the L1462S and F1760A mutations had little effect on delayed activation, and F1760Y had a minor effect. The difference in the L1462 results can be explained by the formation of additional hydrogen bonds in the case of L1462S to compensate for the lost hydrophobic interactions of leucine, while the L1462A mutation is incapable of forming hydrogen bonds and the long sidechain of L1462K can easily block VTD binding in the vicinity. As for F1579, the diminution observed in NaV1.4 experiments contradicts our findings whereby no significant effect on the VTD concentration required for 10% delayed activation was observed for the F1760A mutation, although F1760Y caused a slight increase. For the peak currents, the diminished values caused by the L1462S, F1465Y, and F1760A mutations are consistent with the corresponding A/K mutations in NaV1.4 experiments  of 35 was used for the refinement calculations, followed by B-factor fitting with 50 iterations. A total of 100 relaxed structures were generated. The quality of the lowest-scoring structure selected by total score was inspected through the MolProbity server [V1.5 protein model for the docking calculations.The human cardiac sodium channel structure with a bound quinidine molecule (PDB ID: 6LQA) was used for the calculations . The ligstraints ,21 usingfunction . A dens_y server , wherebymolfile_to_params.py script embedded in Rosetta was used to generate the .params files necessary for the docking calculations with a total charge of +1 on the molecule. The center of the grid box was defined as the approximate middle point of E417 atom OE1 and N406 atom OD1 for the mouth site and the approximate middle point of F1760 and F1418 CZ atoms for the pore site. The ligand.wts score function weights were used for the docking calculations [BCL was used to create a conformer library of VTD that resulted in a total of 100 conformers . These culations ,26. The matplotlib.pyplot module of Python. The five selected clusters for each site were inspected visually to identify the key interactions between the VTD poses and the NaV1.5 residues.The ligand RMSD values were calculated as the 3D distance between the lowest-scoring pose and all the other poses using aligned protein structures. The interface scores were used to plot the score versus RMSD plots. Ligand clustering was performed with the k-means method using an in-house script, and a total of five clusters were chosen for each calculation. All plots were generated with the ddGScan application was used to screen for the mutants that showed the best correlation with the experimental binding data. Repacking and relax for both the bound and unbound states were switched off to reduce the time necessary for the calculations, and to prevent perturbations at the binding site that may affect the results. Specifically, the Rosetta scores were calculated in the absence and presence of the VTD molecule (ΔG) prior to and after the introduction of a particular mutation. The ΔGmutant − ΔGWT difference was used as the ΔΔG value for each mutation.The Rosetta 2 values were calculated using the ΔΔG values and the measured VTD 10% delayed activation concentration values. The ten structures that presented the best correlation scores were inspected visually to identify the similarities among the poses. The highest-correlation pose was used for all the visual analyses.Correlation analysis was performed with in-house Python scripts using the numpy module of Python. The RSCN5A mutagenesis and Human Embryonic Kidney (HEK) 293 stable cell line generation were performed, as previously described [SCN5A:IRES:mCherry. This plasmid was integrated into HEK293 “landing pad” negative selection cells [escribed . Brieflyon cells , the lanThe cells were assayed on the SyncroPatch 384 PE, as previously described , with th


The whole exome sequencing (WES) with targeted gene analysis is an effective diagnostic tool for cardiomyopathy. The early‐onset sudden cardiac death (SCD) was commonly associated with dilated cardiomyopathy (DCM) induced by pathogenic genetic mutations.In a Chinese Han family, the patient of 24 years old occurred with early‐onset and DCM and died of SCD associated with ICD storms induced by repetitive ventricular tachycardia/fibrillation (VT/F). Genomic DNA samples of peripheral blood were conducted for WES and Sanger sequence. Then, we performed bioinformatics analysis for 200 genes susceptible to cardiomyopathies and arrhythmias. Further, we analyzed how the potential pathogenic mutations affecting the secondary structure, hydrophobicity, and phosphorylation of amino acids, protein properties, and their joint pathogenicity by ProtParam, SOPMA, and ORVAL algorisms. The protein–protein interaction was analyzed by STRING algorism.The mutations of LDB3 p.M456R, MYH6 p.S180Y, and SYNE1 p.S4607F were identified as “Damaging/Deleterious.” The SYNE1 (p.S4607F) increased one of alpha helix and decreased one of beta sheet. The LDB3 (p.M456R) reduced one of beta sheet and increased one of beta turn. The MYH6 (p.S180Y) decreased two of beta sheets and four of beta turns, but significantly increased twelve coils. The hydrophobicity of amino acid residues and their adjacent sequences were decreased by LDB3 (p.M456R) and MYH6 (p.S180Y), and significantly increased by SYNE1 (p.S4607F). The mutations of LDB3 (p.M456R), SYNE1 (p.S4607F), and MYH6 (p.S180Y) resulted in the phosphorylation changes of the corresponding amino acid sites or the nearby amino acid sites. The pairwise combinations of LDB3, MYH6, and SYNE1 mutations have the high probability of causing disease, especially the highest probability for SYNE1 and LDB3 mutations. There was obviously indirect interaction of the proteins encoded by SYNE1, LDB3, and MYH6.The multiple heterozygous mutations of SYNE1, LDB3, and MYH6 may be associated with young and early‐onset of DCM and SCD. We firstly reported that the multiple heterozygous mutations of SYNE1 (p.S4607F), LDB3 (p.M456R), and MYH6 (p.S180Y) may be associated with young and early‐onset dilated cardiomyopathy, malignant ventricular arrhythmia, and sudden cardiac death.The mutations of LDB3, MYH6, and SYNE1 were identified as “Damaging/Deleterious,” and abnormally changed the secondary structure, hydrophobicity, and phosphorylation of amino acids, which therefore increased the joint pathogenicity.There was obviously indirect interaction of the proteins encoded by SYNE1, LDB3, and MYH6.1Cardiomyopathies are classified as dilated cardiomyopathy (DCM), hypertrophic cardiomyopathy (HCM), restrictive cardiomyopathy (RCM), and arrhythmogenic right ventricular cardiomyopathy/dysplasia (ARVC/D). DCM is a rare cardiac disease characterized by left ventricular enlargement, reduced left ventricular contractility, and impaired systolic function, which can lead to sudden cardiac death (SCD), with a reported frequency of 46%  with targeted gene analysis is an effective diagnostic tool for patients with DCM in a clinical setting. The pathogenic or likely pathogenic mutations were identified in 12% of DCM by WES ]. Detailed clinical information was collected. The clinical information included family history, age of presentation, initial symptoms of ventricular tachycardia, physical examination, electrocardiograms (ECGs), and echocardiograms based on their informed consents.2.2Genomic DNA samples of patients were isolated from peripheral blood using a standard DNA extraction protocol. The isolated genomic DNA was then fragmented into 150–200 bp and subjected to DNA library preparation using established Illumina paired‐end protocols. Adaptor‐ligated libraries were amplified via PCR. A portion of each library was used to create an equimolar pool. Each pool was amplified to enrich targets sequenced by the Agilent SureSelectXT Target Enrichment System . Whole exome capture was performed with the Agilent SureSelectXT Human All Exon 50 Mb Kit (Agilent Technologies Inc.) following the manufacturer's protocol. The exome‐enriched libraries were sequenced with the Illumina Hiseq 2000 platform  according to the manufacturer's instructions, and 100 bp paired‐end sequencing reads were generated. Each sample was sequenced per lane to obtain an average theoretical depth of 100×.2.3Raw reads were collected for quality control, in which low‐quality reads were filtered, and 3′/5′ adapters were trimmed using the Trim Galore program. Clean reads were aligned to the human reference genome  using the Burrows‐Wheeler Aligner (BWA) program. The quality scores were recalibrated, and reads were realigned to the reference genome using the Genome Analysis Toolkit (GATK) software package. Following the exclusion of duplicate reads, insertion‐deletions (InDels) and single‐nucleotide polymorphisms (SNPs) were called using the GATK or Sequence Alignment/Map tools (SAM tools).http://sift.jcvi.org/www/)  .MYH6: AGGGTGTAGTTGGGAGGAGAG, GAGGGGAGGGTTAGGGGTA, 406 bp, 57.0°C.LDB3: CTTCCTGATTTTCTTTATTGT, GAGTTGCTTTCTCTGTTACC, 497 bp, 48.5℃.SYNE1: AAGAGTGAAGTGCTGGGGAAG, AGGGGTCAAGGTGTGGGG, 961 bp, 58.5°C.COL3A1: GCATTCCTTCGACTTCTC, TATTTCAACTGGTTTTCATCT, 404 bp, 49.5°C.PSEN2: AGGTCCTTGTGCTCCTTTTTC, TCATCATTACTTCCCTTCTCCC, 301 bp, 57.5°C.OBSCN: CATCCTCCAGTCTCCTTTCCC, CCCCACCTTACCTGCCCTT, 608 bp, 61.5°C.PKP2: CAAGTCTCCAGGTGTCCGC, TTTCCACAAGCAAGTCGGTC, 671 bp, 58.4°C.TTN, CAACAGGTCTTCGTCGGATT, CCTCTTGCTTGGGTATTTTCAT, 877 bp, 57.5°C.TTN: TAAAATGGGAGAAAGATGGTCA,TTGGGATGTGATAGGTTGAATA, 1,023 bp, 56.5°C.COL1A2: AGCCCCTCCCACTAAAGAC,AAAATACACCACACGATACAACT, 909 bp, 55.0°C.A 50 μl polymerase chain reaction (PCR) mix was made up of 10× PCR buffer , 125 μM dNTPs, 10 pmol of each primer, 2 U of Taq DNA polymerase, and 100 ng genomic DNA templates. The following steps were used for the PCR: 94°C for 3 min and 35 cycles , followed by 72°C for 10 min. The PCR products were purified using a Wizard Miniprep Kit. The purified PCR products were sequenced with an ABI PRISM BigDye Terminator Cycle Sequencing Ready Reaction Kit using standard conditions. The sequencing products were purified using ethanol/EDTA/sodium acetate precipitation and analyzed on an ABI 3730xl Automated DNA Sequencer.2.5The right internal jugular vein was punctured, and a 7‐Fr vascular sheath was inserted. A long, flexible catheter with forceps in the head end was inserted into a vein and threaded up into the heart while monitored by X‐ray. Five small snips of muscle at the apical septum of the right ventricle were grabbed. Some cardiac tissues, which were fixed with formalin solutions, then dehydrated, paraffin‐embedded and sliced, were used for HE and Masson staining. Some cardiac tissues were fixed with glutaraldehyde and osmic acid, dehydrated, resin embedded and sliced, and then prepared for uranyl acetate and lead nitrate staining and analyzed using a transmission electron microscope.2.6ProtParam is a tool which allows the computation of various physical and chemical parameters for a given protein for a user entered protein sequence. The computed parameters include the molecular weight, theoretical pI, amino acid composition, atomic composition, extinction coefficient, estimated half‐life, instability index, aliphatic index, and grand average of hydropathicity (GRAVY)  is the first web bioinformatics platform for the exploration of predicted candidate disease‐causing variant combinations, aiming to aid in uncovering the causes of oligogenic diseases . This tool integrates innovative machine learning methods for combinatorial variant pathogenicity prediction, further external annotations and interactive and exploratory visualization techniques  was used to extract the target protein information from PPI database to explore any direct and indirect protein–protein interactions (PPIs) in the target genes  presented with palpitations, dizziness, fatigue, sweating, and then syncope after exertion for 1 year. She woke up on her own for about 1 min Figure . During , probanda Figure ; multi‐sa Figure ; ventrica Figure . Echocar3.2The pathological examination showed that some muscle fibers of myocardial tissue were atrophied and reduced in volume, some muscle fibers were hypertrophic; the nucleus of myocardium was large and deeply stained, and obvious interstitial fiber hyperplasia was found Figure . The int3.3In this family Figure , a set o3.4Compared with wild type (WT) of MYH6, the total number of positively charged residues (Arg + Lys) was obviously reduced by MYH6 p.S180Y 362 vs. 316). The total number of positively charged residues (Arg + Lys) increased from 54 of LDB3 (WT) to 55 of LDB3 p.M456R  , two light chain subunits and two regulatory subunits. MYH6 encodes the alpha myosin heavy chain subunit (α‐MHC) that encompasses ~26,000 bp and consists of 39 exons, 37 of which contain coding information. The α‐MHC consisting of head, neck, and tail domains plays a vital role in myofibril assembly and proper heart development. The tail domains of α‐MHC form a coiled coil that stabilizes the molecule so that the head domain is able to generate force through its interaction with actin  ]. With the consent of the ethics committee, we followed up the patients and their family members under the condition of informed consents and obtained blood samples for genetic analysis.


LRRK2 (leucine-rich repeat kinase 2) cause 1–2% of all cases of Parkinson’s disease (PD) albeit with incomplete and age-dependent penetrance. All pathogenic LRRK2 mutations reside within the two catalytic domains of LRRK2—either in its kinase domain (e.g. G2019S) with modest effect or its ROC-COR GTPase domain (e.g. R1441G/H) with large effect on LRRK2 kinase activity. We have previously reported assays to interrogate LRRK2 kinase pathway activity in human bio-samples measuring phosphorylation of its endogenous substrate Rab10, that mirrors LRRK2 kinase activation status. Here, we isolated neutrophils from fresh peripheral blood from 101 participants including 42 LRRK2 mutation carriers (21 with the G2019S and 21 with the R1441G mutations), 27 patients with idiopathic PD, and 32 controls. Using a dual approach, LRRK2 dependent Rab10 phosphorylation at Threonine 73 (pRab10Thr73) was measured by quantitative multiplexed immunoblotting for pRab10Thr73/total Rab10 as well as targeted mass-spectrometry for absolute pRab10Thr73 occupancy. We found a significant over fourfold increase in pRab10Thr73 phosphorylation in carriers of the LRRK2 R1441G mutation irrespective of clinical disease status. The effect of the LRRK2 G2019S mutation did not reach statistical significance. Furthermore, we show that LRRK2 phosphorylation at Serine 935 is not a marker for LRRK2 kinase activity in human neutrophils. When analysing pRab10Thr73 phosphorylation in post-mortem brain samples, we observed overall high variability irrespective of clinical and LRRK2 mutation status and attributed this mainly to the adverse effect of the peri- and post-mortem period on the stability of posttranslational modifications such as protein phosphorylation. Overall, in vivo LRRK2 dependent pRab10Thr73 phosphorylation in human peripheral blood neutrophils is a specific, robust and promising biomarker for significant LRRK2 kinase hyperactivation, as with the LRRK2 R1441G mutation. Additional readouts and/or assays may be needed to increase sensitivity to detect modest LRRK2 kinase activation, as with the LRRK2 G2019S mutation. Our assays could be useful for patient stratification and target engagement studies for LRRK2 kinase inhibitors.Heterozygous gain-of-kinase function variants in The online version contains supplementary material available at 10.1007/s00401-021-02325-z. Parkinson’s disease (PD) is a common neurodegenerative condition that affects 1% of people over the age of 60 and over 6 million people worldwide . People The Leucine-rich repeat kinase 2 (LRRK2) is such a highly pursued therapeutic target. It is a large multidomain protein made up of 51 exons and 2537 amino acids with a predicted molecular weight of 286 kDaltons. Its catalytic core is made up of a kinase and ROC-COR GTPase domain as well as other protein–protein interaction motifs: the N-terminal armadillo, ankyrin and leucine-rich repeat motifs and a C-terminal WD40 motif , 43. PatAll pathogenic LRRK2 mutations have in common that they augment kinase activity suggesting that inhibition of the LRRK2 kinase with small molecules is a promising strategy for disease modification. The LRRK2 kinase domain mutations—G2019S and I2020T—increase LRRK2 kinase activity only modestly, under twofold in in vitro and in vivo cell and animal studies (reviewed in ) by domaThr73) is quantified by either immunoblot analysis deploying highly sensitive monoclonal phosphospecific antibodies raised against the pRab10Thr73 epitope . Cell lysates were kept on ice for 10 min and then clarified by centrifugation at 20,800g for 15 min at 4 °C. Supernatants were used for Bradford assay (Thermo Scientific) and stored at − 80 °C after snap freezing.Peripheral blood neutrophils were isolated directly from fresh blood using EasySep Direct Human Neutrophil Isolation Kit  based on an immunonegative magnetic selection process as described before , 12. PurBrain samples were obtained from institutionally approved autopsy collections held by the Columbia University Medical Center in New York, USA and the IDIBAPS Biobank at the Hospital Clinic in Barcelona, Spain.g for 10 min at 4 °C. Supernatants were collected, quantified by the Bradford assay (Thermo Scientific) and subjected to immunoblot analysis.Frozen human matched frontal (Brodmann area 9) and occipital (Brodmann area 17) cortex samples from nine individuals including three controls, three G2019S mutation carriers with PD and three with iPD were obtained from the brain bank at the Columbia University Medical Center in New York. Additionally, we received 20 frontal cortex samples including seven controls, seven iPD, fife G2019S and one R1441H mutation carriers with PD from the IDIBAPS Biobank at the Hospital Clinic in Barcelona, Spain. Brain samples were weighed and added to a tenfold volume excess of ice-cold lysis buffer , and homogenised using POLYTRON homogenizer (KINEMATICA) on ice . Lysates were cleared by centrifugation at 20 800Cell lysates were mixed with 4 × SDS–PAGE loading buffer  to a final total protein concentration of 1 µg/µl and heated at 70 °C for 10 min. 10 µg of each sample was loaded onto a NuPAGE 4–12% Bis–Tris Midi Gel  and electrophoresed at 130 V for 2 h with the NuPAGE MOPS SDS running buffer . At the end of electrophoresis, proteins were electrophoretically transferred onto a nitrocellulose membrane  at 100 V for 90 min on ice in transfer buffer (48 mM Tris–HCl and 39 mM glycine). Transferred membrane was blocked with 5% (w/v) skim milk powder dissolved in TBS-T  at room temperature for 1 h. The membrane was then cropped into three pieces, namely the ‘top piece’ (from the top of the membrane to 75 kDa), the ‘middle piece’ (between 75 and 30 kDa) and the ‘bottom piece’ (from 30 kDa to the bottom of the membrane). The top piece was incubated with rabbit anti-LRRK2 pS935 UDD2 antibody multiplexed with mouse anti-LRRK2 C-terminus total antibody diluted in 5% (w/v) skim milk powder in TBS-T to a final concentration of 1 µg/ml for each of the antibody. The middle piece was incubated with mouse anti-GAPDH antibody diluted in 5% (w/v) skim milk powder in TBS-T to a final concentration of 50 ng/ml. The bottom piece was incubated with rabbit MJFF-pRAB10 monoclonal antibody multiplexed with mouse MJFF-total Rab10 monoclonal antibody diluted in 2% (w/v) bovine serum albumin in TBS-T to a final concentration of 0.5 µg/ml for each of the antibody. All blots were incubated in primary antibody overnight at 4 °C. Prior to secondary antibody incubation, membranes were washed three times with TBS-T for 10 min each. The top and bottom pieces were incubated with goat anti-mouse IRDye 680LT (#926-68020) secondary antibody multiplexed with goat anti-rabbit IRDye 800CW (#926-32211) secondary antibody diluted in TBS-T  for 1 h at room temperature. The middle piece was incubated with goat anti-mouse IRDye 800CW (#926-32210) secondary antibody diluted in TBS-T  at room temperature for 1 h. Membranes were washed with TBS-T for three times with a 10 min incubation for each wash. Membranes were scanned using the LICOR Odyssey CLx imaging system.Quantification of the protein bands was performed on the scanned images using the Odyssey Scan band tool in a blinded manner with regards to genotype and clinical status of the participants by an independent analyst using the Image Studio software. Each sample set including DMSO and MLi-2 treated neutrophil lysates for each participant or each autopsy brain lysate was run in duplicates and two independent replicate immunoblotting experiments were performed and used for quantification. The intensities of the total LRRK2 and total Rab10 protein bands were normalized to that of the housekeeping protein GAPDH  while the specific posttranslational phosphorylation modifications were quantified against the multiplexed total target protein irrespective of modification . Inter-gel variability was controlled for by normalization against the same control sample on each gel per set of experiments. In total, three sets of Western blot experiments run with samples 1–66 (Barcelona set), samples 67–82 (San Sebastian set 1) and 83–101 (San Sebastian set 2) were performed at different time points. To combine Western blot results for all three sets of neutrophil lysates, results for each set were normalized to the average of its controls and then combined.The method utilized here was adopted according to the recently published paper by Karayel et al. . Brieflyg for 10 min at room temperature to allow binding of peptides onto the disks. Flowthrough was collected and reloaded onto stage tips for another round of binding. Subsequently, stage tips were washed twice with 100 µl of 1% (v/v) trifluoroacetic acid in isopropanol, and then with 100 µl of 0.2% (v/v) trifluroacetic acid in 3% (v/v) acetonitrile. Wash steps were undertaken by centrifugation at 2000g for 6 min at room temperature and the flowthrough was discarded. Peptides were eluted sequentially with freshly prepared 1.25% (v/v) ammonium hydroxide in 50% (v/v) acetonitrile and 1.25% (v/v) ammonium hydroxide in 80% (v/v) acetonitrile. Purified peptides were snap frozen with dry ice and dried in a Speedvac evaporator.SDB-RP tips were prepared in-house by punching two layers of SDB-RP disks using a 16 gauge syringe needle, which were then pushed into a 250 µl pipette tip. Vacuum dried peptides from the previous step were reconstituted with 100 µl of 1% (v/v) trifluoroacetic acid in isopropanol and directly loaded on SDB-RP tips. Samples were centrifuged at 1500Thr73 occupancy, an equimolar mixture of 25 fmol of heavy stable isotope-labelled (SIL) phosphorylated and non-phosphorylated Rab10 counterpart peptides and 25 fmol of PRTC retention time calibration mix were spiked in. The peptide sample mix was then subjected to sonication in a water bath sonicator (Branson) for 10 min and centrifuged at 17,000g at room temperature for 10 min. Evotips  were activated by adding 20 µl of buffer B [100% (v/v) acetonitrile in 0.1% (v/v) formic acid] and centrifuged at 800g for 1 min. Tips were immersed into 200 µl of isopropanol and then equilibrated by adding 20 µl of buffer A [0.1% (v/v) formic acid in water] and centrifuging at 800g for 1 min. This step was repeated one more time. Peptides were loaded on Evotips using gel loading tips and centrifuged at 700g for 5 min. The flowthrough was collected, reapplied and centrifuged. Next, the tips were washed twice with buffer A. 100 µl of buffer A was applied to the Evotips which were then placed on the autosampler tray of EvoSep LC system.Sample loading on Evotips was performed as described previously  with minm/z values are provided in supplementary table 1). Dynamic on-the-fly retention time correction was enabled to correct the scheduled retention time. Full MS scan was acquired within 300–800 m/z and acquired at 120,000 resolution at 200 m/z using Orbitrap mass analyser. Each of the targeted analytes was isolated using Quadrupole mass filter with a 0.7 Da isolation window and fragmented using normalized 27% higher energy collisional dissociation (HCD) and measured at 30,000 resolution at 200 m/z using Orbitrap mass analyser. The loop cycle was maintained at ten scan per duty cycle. The automatic gain control (AGC) targets for full MS and PRM were at 3E6 and 1E5 ions, respectively, and a maximum of 50 ms for MS1 and 300 ms for PRM scan. For the limit of detection (LOD) experiments  data were acquired on QE HF-X Mass spectrometer interfaced in line with an EvoSep liquid chromatography (LC) system. EvoTips were loaded on EvoSep LC system autosampler tray and analysed using a 21 min (60 samples per day) script. The EvoSep LC system elutes peptides by applying a partial gradient using low pressure pump-A and B into the long storage capillary sample loop where peptides were partially stored and focused by pre-formed gradient using low pressure pump-C and pump-D. Peptides were subsequently directed to an analytical column  by high pressure pump which is housed into the Easy nano source. Peptides were then directly electrosprayed into the mass spectrometer by maintaining 2000 voltage. Mass spectrometer was operated in a targeted PRM mode by employing one full MS scan followed by a PRM scan which is instructed to operate by following the imported inclusion list with a scheduled retention time  for Arg and (13C615N2) for Lys residues, phosphorylation of Ser/Thr were set as dynamic modification. Percolator node was used to filter that data at 1% FDR. The output.msf files were directly imported into Skyline software suite to serve as a spectral library which was then used for all of the subsequent human neutrophils PRM data.The retention times of heavy stable peptides were determined using an equimolar mixture of 50 fmol and 25 fmol of PRTC peptide mixture was acquired using data dependent acquisition (DDA) mode on QE HF-X mass spectrometer in line with the EvoSep LC system. The DDA data were acquired using one full MS and 10 top N MS2 scans by disabling dynamic exclusion option. MS1 and MS2 scans were acquired at 120,000 and 30,000 resolution at 200 z = 2) and triple (z = 3) charge states were used. Extracted ion chromatograms of both MS1 and MS2 fragment transitions were manually examined and adjusted for any interfering ions. The light/heavy internal standard ratio values were exported to calculate the pRab10Thr73 occupancy as described before . All of the neutrophil samples phosphorylation occupancy calculations are provided in Tables All of the PRM raw data were imported into Skyline software suite. An In-house generated spectral library was used to pick the precursor and top six fragment ions. Both double  via the PRIDE repository. The data can be accessed with the following identifier (PXD024898) [All of the proteomics mass spectrometry raw data and database search result output files have been submitted to ProteomeXchange consortium (D024898) .https://skyline.ms/project/home/software/Skyline/begin.view), Microsoft Excel and Graphpad Prism (GraphPad Software). Data visualization was done using GraphPad Prism (GraphPad Software). In general, grouped data analysis was performed using one-way ANOVA for multiple comparisons or unpaired t-test and displayed graphically using GraphPad Prism software (version 9).Bioinformatic analyses in this study were performed with Skyline  Fig. . AnalysiThe aim for using the LRRK2 kinase inhibitor MLi-2 at a concentration of 200 nM was to achieve near complete dephosphorylation of Rab10 at the LRRK2 dependent phosphoepitope Threonine 73. Dose–response studies of MLi-2 in human peripheral blood neutrophils derived from two healthy donors demonstrated as before  that 50%Thr73 in peripheral blood neutrophils from 42 LRRK2 mutation carriers in comparison to 32 controls as well as 27 iPD patients. Peripheral blood neutrophils were isolated from fresh blood by immunomagnetic negative selection as previously described [Thr73 phosphorylation is mediated by the LRRK2 kinase. When analysed by quantitative multiplex immunoblotting, we observed a striking 4.5-fold increase in LRRK2 dependent pRab10Thr73 phosphorylation in R1441G mutation carriers compared to controls, iPD and G2019S mutation carriers  based assay for analysing pRab10Thr73 phosphorylation occupancy with spike in of synthetic stable isotope-labelled (SIL) tryptic Rab 10 peptides around the Threonine 73 epitope in its phosphorylated as well as unphosphorylated form as internal standards [Thr73 phosphorylation levels for the G2019S mutation carrier group or iPD patients when compared to controls.In parallel to quantitative immunoblotting for pRab10tandards  Thr73 phosphorylation occupancies in all MLi-2 treated and untreated (DMSO) neutrophil samples from all 101 participants . Here again, the MS assay confirmed that there was no significant difference between control group occupancies in comparison to the iPD (1.61%) and G2019S mutation carrier groups (1.90%) (Tables p = 0.23) or between G2019S-PD manifesting and non-manifesting individuals (p = 0.33)  which was significantly reduced when compared to the untreated (DMSO) samples for each group   and also no significant difference when each group including controls, iPD, G2019S and R1441G mutation carriers was segregated by sex .As male and female sex is an important determinant for PD susceptibility, we assessed the effect of sex on LRRK2 dependent pRab10p = 0.045), but no difference when compared to G2019S mutation carriers or controls . We also did not find a statistically significant reduction of Serine 935 phosphorylation of LRRK2 in G2019S mutation carriers irrespective of disease status when compared to iPD or in fact any of the other groups. LRRK2 total protein levels did not significantly differ between the R1441G mutation carriers, G2019S mutation carriers, iPD and controls  to assess pRab10Thr73 phosphorylation against total Rab10 levels and LRRK2 Serine 935 phosphorylation against total LRRK2. Total protein levels for Rab10 and LRRK2 were measured by normalization against a housekeeping protein. With regards to pRab10Thr73 phosphorylation, we observed high variability amongst samples from low to almost undetectable levels in the majority of samples and very high levels in some irrespective of group or LRRK2 mutation status; in fact, some of the highest pRab10Thr73 phosphorylation levels were observed amongst the control samples. Also, the LRRK2 R1441H genotype, which is as R1441G another hotspot mutation at the R1441 site and known to significantly augment LRRK2 dependent pRab10Thr73 phosphorylation in the heterologous overexpression system (unpublished results), did not result in significantly elevated pRab10Thr73 phosphorylation levels. While the variances were higher for the control samples (standard deviation = 8.233 vs. 2.495 (LRRK2 mutation carriers) and 2.640 (iPD)), there were no significant differences between the control, LRRK2 mutation carrier and iPD groups . Total Rab10 levels displayed less variability amongst frontal cortex samples and did not significantly differ between the groups  where the levels in the occipital lobe were higher)  , while total LRRK2 levels were significantly reduced in the occipital lobe when compared to matched frontal lobe samples (p = 0.001)  We show for the first time that LRRK2 dependent pRab10Thr73 phosphorylation as a surrogate marker for LRRK2 kinase activation status is significantly elevated in carriers of a specific pathogenic variant in the LRRK2 gene, namely the R1441G mutation in the ROC-COR GTPase domain. (2) This significant increase in pRab10Thr73 phosphorylation in LRRK2 R1441G mutation carriers is irrespective of clinical disease status and observed in non-manifesting carriers as well as those diagnosed with PD. (3) We have not observed a statistically significant increase in LRRK2 dependent pRab10Thr73 phosphorylation in carriers of the common G2019S mutation deploying two independent assays. (4) Furthermore, our explorative analysis of markers of the LRRK2 kinase pathway in human autopsy brain samples highlights important aspects and indeed problems with regards to feasibility, suitability and differences across different biomatrices. Additionally, we show that both Serine 935 phosphorylation of LRRK2 as well as pRab10Thr73 phosphorylation serve as biomarkers for LRRK2 kinase inhibition when using kinase inhibitors such as MLi-2. In this regard, it is important to note that pharmacokinetic properties vary depending on cellular context and assay readouts and that a relatively high concentration of MLi-2 was required to suppress Rab10 phosphorylation at Threonine 73 in peripheral blood neutrophils compared to previously reported IC50 of between 0.76 nM and 3.4 nM [This is to date the largest study of LRRK2 dependent phosphorylation of its endogenous substrate pRab10d 3.4 nM , 13.Thr73 phosphorylation levels was seen in LRRK2 R1441G mutation carriers when compared to iPD, G2019S mutation carriers or controls. This increase was irrespective of disease status, and there was no significant difference between R1441G mutation carriers with and without PD manifestation. We also did not see an effect of female or male sex on LRRK2 dependent pRab10Thr73 phosphorylation. This suggests that the effect on pRab10Thr73 phosphorylation levels in circulating blood neutrophils is mainly driven by the underlying mutation itself rather than by the accompanying PD disease process. In future experiments it would be interesting to monitor larger numbers of participants and over time to better assess the utility of LRRK2 dependent pRab10Thr73 phosphorylation as a marker of LRRK2 driven disease conversion or disease state.Utilizing our facile and robust multiplex immunoblotting assay using sensitive phosphospecific antibodies against the Threonine 73 phospho-site of Rab10 that is phosphorylated by the LRRK2 kinase, a statistically significant increase of more than fourfold in pRab10Thr73 phosphorylation levels in 21 LRRK2 G2019S mutation carriers despite promising results from a previous much smaller study of pRab10Thr73 phosphorylation stoichiometry in neutrophils from 4 G2019S mutation carriers in comparison to 4 non-mutation carriers [Thr73 phosphorylation levels. Given that the LRRK2 G2019S mutation induces an under twofold enhancement of pRab10Thr73 phosphorylation in homozygosity, one would expect a relative reduction to < 1.5-fold in heterozygosity. We, therefore, conclude that the effect of the LRRK2 G2019S mutation in heterozygosity as with the participants in our study coupled with the biological variation in between human samples is too small to accurately yield a significant difference by quantitative multiplexed immunoblotting or even more sensitive mass-spectrometry methodologies. On the other hand, measuring pRab10Thr73 phosphorylation levels using our relatively straightforward immunoblotting assay [Heterologous systems such as HEK293 overexpression of LRRK2 variants and genetic animal models with knock-in of LRRK2 mutations in the homozygous state have shown that the LRRK2 ROC and COR GTPases domain mutations—including R1441G/H that suppress GTPases activity and promote GTP binding—mediate a 3 to 4-fold increase in LRRK2 kinase activity , 39 whilng assay  may be aA recent study found a statistically significant decrease in Serine 935 phosphorylation of LRRK2 in human peripheral blood mononuclear cells (PBMCs) derived from LRRK2 G2019S mutation carriers with PD but not G2019S non-manifesting mutation carriers when compared to iPD . This paThr73 phosphorylation has previously been shown to be elevated in substantia nigra of patients with iPD when compared to controls [Thr73 phosphorylation signal was not or hardly detectable in the majority of cases and otherwise variable irrespective of genotype and clinical disease status. In particular, we did not observe significant pRab10Thr73 hyperphosphorylation in the one LRRK2 R1441H mutation carrier sample which biochemically should have the same augmenting effect on LRRK2 dependent pRab10Thr73 phosphorylation as the R1441G mutation [pRab10controls . While wmutation . While tmutation .Thr73 phosphorylation in autopsy brain material to a larger number of cases, in particular of carriers of R1441 hotspot or the VPS35 D620 mutations, there are important factors to consider such as circumstances and cause of death and post-mortem interval that may affect tissue quality and in particular stability of posttranslational phosphorylation modifications [Thr73 phosphorylation in post-mortem brain lysates is uninformative mainly due to the instability of posttranslational modifications.While it would be worthwhile to expand the analysis of pRab10ications . AnotherThr73 phosphorylation in human peripheral blood neutrophils is a specific, robust and promising biomarker for significant LRRK2 kinase hyperactivation, as with the LRRK2 R1441G mutation or as previously demonstrated with the VPS35 D620N mutation [In conclusion our findings add compelling evidence that interrogating in vivo LRRK2 dependent pRab10mutation . Furthermutation , assays Supplementary file1 (PDF 8801 kb)Below is the link to the electronic supplementary material.


Peanut allergy can result in life-threatening reactions and is a major public health concern. Oral immunotherapy (OIT) induces desensitization to food allergens through administration of increasing amounts of allergen. To dissect peanut-specific immunoglobulin E (IgE) and IgG responses in subjects undergoing OIT, we have developed AllerScan, a method that leverages phage-display and next-generation sequencing to identify the epitope targets of peanut-specific antibodies. We observe a striking diversification and boosting of the peanut-specific IgG repertoire after OIT and a reduction in pre-existing IgE levels against individual epitopes. High-resolution epitope mapping reveals shared recognition of public epitopes in Ara h 1, 2, 3, and 7. In individual subjects, OIT-induced IgG specificities overlap extensively with IgE and exhibit strikingly similar antibody footprints, suggesting related clonal lineages or convergent evolution of peanut-specific IgE and IgG B cells. Individual differences in epitope recognition identified via AllerScan could inform safer and more effective personalized immunotherapy.  •Phage immunoprecipitation sequencing simultaneously maps IgE and IgG peanut epitopes•Ara h 1, 2, 3, and 7 epitopes are highly shared among allergic individuals•High-resolution epitope mapping is achieved by saturation mutagenesis•Oral immunotherapy induces IgG specificities overlapping with pre-existing IgE Chen et al. use a phage-display-based method to simultaneously map IgE and IgG epitopes in peanut-allergic patients undergoing oral immunotherapy (OIT). They identify shared epitopes and potentially therapeutically relevant individual differences in epitope recognition. OIT boosts and diversifies IgG responses that overlap with IgE, often with similar critical residues. However, the mechanisms underlying successful induction of the peanut unresponsive state are incompletely understood. Investigations of immune responses during OIT have revealed decreases in peanut-specific IgE concentration and increases in peanut-specific IgG concentration in the serum, suggesting two possible mechanisms that might contribute to desensitization.Our group has previously developed phage-display-based platforms for autoantigen discoveryTo map epitopes targeted by the antibody response to peanut in allergic subjects, we constructed a phage-display library of 397 20-mer peptides tiling every 10 amino acids across the sequences of all 12 peanut allergens listed in the World Health Organization and International Union of Immunological Societies (WHO/IUIS) Allergen Nomenclature Sub-committee database at the time of library design . GeneticZ score cutoff of 3.5, 20 peptides were recognized by >30% of patients; 10 peptides were recognized by >50% of patients; and 5 peptides were recognized by >70% of patients. The most public epitopes, Ara h 2.02 amino acid (aa)21–40, Ara h 3.01 aa301–320 and Ara h 2.01 aa61–80, were recognized by IgE in 13/15 patients. We also detected IgE responses to 59 additional “private” epitopes, recognized by <30% of allergic patients  individuals at week 0 of PRROTECT (before OIT) and 54 serum samples from non-allergic (NA) control donors C. We propatients .We observed IgG responses to peanut peptides in allergic patients as well as in some NA donors, but the diversity of peptides recognized by NA individuals was much lower A. On aveTo map the epitopes more precisely within the peanut peptides, we analyzed binding to saturation mutagenesis peptides to calculate a substitution score, or the average depletion of all mutants at each given amino acid position compared to the wild-type peptide. This analysis enabled us to identify the critical residues in the epitopes, as substitutions of these residues generally disrupt antibody binding. Consistent with our previous analysis of the wild-type peptides, the substitution scores indicated the presence of public epitopes in Ara h 1, 2, 3, and 7. For most public epitopes, various allergic patients exhibited similar patterns of critical residues . IgG exhWe next examined the antibody binding to the saturation mutant peptides in greater detail to determine whether the epitopes recognized by different patients on the same peptide were related. For each of the saturation mutant versions of a given peanut peptide, we calculated the relative depletion of the mutant compared to the wild-type peptide. We then generated a heatmap to illustrate the effect of each amino acid substitution on antibody binding. These heatmaps represented the “high-resolution antibody footprints” of an epitope.We selected three representative IgE public epitope peptides for further analysis: Ara h 2.02 aa21–40; Ara h 3.01 aa301–320; and Ara h 7.01 aa71–90, which were recognized by 13, 13, and 9 patients before OIT, respectively A–3C. ForDespite the fact that, frequently, a large proportion of patients who recognized a public epitope peptide shared the same critical residues, some individual footprints deviated from the dominant pattern. For example, patient S09 recognized the N-terminal RQQWELQG-RR stretch in Ara h 2.02 aa21–40, while the dominant footprint recognized by all other 12 patients resided in the C-terminal RR-QS–ER stretch. For peptide Ara h 3.01 aa301–320, the differences between dominant and subdominant footprints were more subtle: the Y4 (tyrosine at position 4) was critical in the dominant footprint shared by 9 patients, while all substitutions except proline at this position were tolerated by patient B23. In contrast, Y6 was critical for B23 but dispensable for the dominant footprint. Uniquely for patient B04, both Y4 and Y6 were critical for antibody binding. As a final example, R11 mutations in Ara h 7.01 aa71–90 had little effect on IgE binding by patient B16 and 6 others that shared the dominant footprint, but this position was critical for patient C04. Sequence logo plots generated for the same epitopes also revealed these differences in antibody footprints among individuals A.21To summarize, we found that, for 16/20 peptides that were recognized by IgE in >30% of the allergic subjects at week 0, a single dominant footprint was shared by ≥50% of individuals G. The prAlthough peanut OIT has shown some promise in the clinic in recent years, the specific changes to the antibody repertoire induced by OIT remain incompletely understood. A 3 to 4 log induction of allergen-specific IgG levels occurs during OIT, but important questions remain about whether this reflects a more diversified IgG repertoire or simply an expansion of pre-existing IgG specificities. Therefore, we applied AllerScan to a cohort of allergic subjects sampled pre- and post-OIT to dissect IgE and IgG repertoire changes with high resolution A.Figure ,9We first evaluated the overall breadth of peanut-specific IgE and IgG repertoires pre- and post-OIT. To this end, we counted the number of wild-type peptides recognized by IgG and, separately, IgE in each patient sample at week 0 (pre-OIT) and at week 52 (post-OIT). To avoid counting homologous peptides encoded by different protein variants multiple times, we limited this analysis to peptides from only 1 variant of each Ara h protein. We found that IgE epitope diversity did not change significantly after OIT: patients exhibited IgE recognition of 14 peanut peptides on average both before and after OIT B. In conZ score increases of up to 25-fold .,Surprisingly, Ara h 6, a major allergen homologous to Ara h 2, was only bound by IgE from 3/15 patients. Although Ara h 6 is generally recognized at a lower frequency than Ara h 2,,,,,Z score. It remains of interest to validate and further elucidate the association between Ara-h-7-specific IgG antibodies and successful desensitization to peanut.We and others,Additionally, IgG epitopes that emerged during OIT were found to substantially overlap with pre-existing IgE specificities and share highly similar antibody footprints. This observation suggests that OIT-induced IgG could result from preferential stimulation of IgG B cells clonally related to peanut-specific IgE B cells. Affinity-matured IgG memory B cells have been suggested to replenish the pool of the IgE-producing plasma cells responsible for allergy in mice.Using our peanut AllerScan platform, we identified extensively shared public epitopes in the major peanut allergens Ara h 1, 2, 3, and 7, with recognition frequency of up to 87% in our cohort of 15 allergic patients. Interestingly, the antibody footprints derived from saturation mutagenesis of these epitopes also showed a tremendous degree of similarity across individuals, suggesting structural and sequence similarity of public epitope-specific antibodies. In agreement with our finding, recent studies that performed B cell receptor (BCR) sequencing of peanut-specific B cells reported shared immunoglobulin heavy and light chain gene (IGH and IGL) segment usage and homologous CDR sequences among different PA individuals.Interestingly, Hoh et al.,Although examples of sequence similarity between peanut-specific antibodies from different individuals and between IgE and IgG peanut-specific B cells from the same individual have previously been described,33The power of AllerScan to rapidly evaluate hundreds of sera samples in parallel at low cost could enable novel strategies for personalized immunotherapy. Our findings show that, despite shared recognition of public epitopes by allergic patients, the exact constellation of public epitopes recognized by any individual varied. For instance, out of 20 peptides recognized by IgE of at least 5/15 allergic patients pre-OIT, each patient lacked IgE responses to 4–15 (average = 9) peptides. We envision that the personalized identification of sets of “missing” public epitopes could inform a novel and much safer type of allergen immunotherapy. In this approach, the set of peptides containing missing public epitopes would be formulated into a peptide vaccine designed to elicit protective IgG responses. In the absence of pre-existing IgE responses to these peptides, the risk for allergic reactions would be greatly minimized compared to whole-peanut OIT.In summary, our findings reveal that the phage immunoprecipitation platform, AllerScan, provides an innovative, precise, and efficient approach for investigating antibody responses in allergic subjects. Peptide phage display has also been applied to wheat allergies in a recent study.Although we were able to identify many peanut epitopes using AllerScan, we acknowledge the limitation that discontinuous epitopes might not be detected using peptides. The existence of conformational epitopes in peanut allergy is suggested by a number of studies, but the relative contributions of conformational versus linear epitopes to IgE-mediated food reactions remain unclear. We look forward to the development of new technologies capable of characterizing and quantifying conformational epitope binding to aid in the investigation of this question. Although our study identified a strong induction of Ara-h-7-specific IgG by OIT, the clinical relevance of this IgG response will require further investigation. We have suggested that the high degree of similarity between the IgE and IgG footprints within individuals indicates that OIT-induced IgG and IgE B cells originate from the same lineages, but the alternative possibility that the overlapping IgE and IgG responses arise from convergent immunodominant responses is not excluded by our analysis and will be the subject of future studies.selledge@genetics.med.harvard.edu).Further information and requests for resources and reagents should be directed to the Lead Contact, Stephen J. Elledge . The study was approved by the Institutional Review Boards of all participating institutionsAllergic sera used in this study were originally collected in PRROTECT, a multicenter randomized placebo-controlled study of oral peanut desensitization under cover of anti-IgE  in highly allergic subjects  and T7-PRA (caagcagaagACTCGAGCTCTTCCCTG) primers, digested with EcoRI and XhoI, and ligated into the EcoRI/SalI site of the T7FNS2 vector397 20-mer wild-type peanut peptides were designed by tiling every 10 amino acids across 12 peanut allergens . Saturathttps://doi.org/10.17632/zp97585dkp.1).Phage immunoprecipitation and sequencing was performed as described previouslyStatistical analysis was performed using either GraphPad Prism version 9.1.2 or R version 3.6.1. Corresponding statistical details are indicated in figure legends. Detailed bioinformatic analyses of AllerScan data were performed as follows.For every wild-type peanut epitope, we calculated Z-scores representing the relative enrichment value compared to mock IP reactions as previously describedTo quantify the breadth of antibody repertoires B, we firTo assess the effects of amino acid substitutions on antibody binding to a given peptide, we first estimated the wild-type peptide enrichment by calculating the mean enrichment of the wild-type peptide and the top 50% of the alanine mutants of that peptide. We found that this value was a more robust estimate of the true enrichment of the wild-type peptide than the enrichment value of the single wild-type peptide alone. Then, the enrichment of each mutant peptide was divided by the estimated enrichment of wild-type peptide as calculated above. This became the relative-to-wild-type enrichment. This process was repeated for all saturating mutants of a given wild-type peptide. To generate a high-resolution antibody footprint on an epitope A–4C, we To visualize the substitution effect at each amino acid position , and S3,https://clinicaltrials.gov/ct2/show/NCT01781637Information on PRROTECT clinical trial (registry number NCT01781637):