Esophageal squamous cell carcinoma (ESCC) is a common gastrointestinal malignancy with poor patient prognosis. Current treatment for ESCC, including immunotherapy, is only beneficial for a small subset of patients. Better characterization of the tumor microenvironment (TME) and the development of novel therapeutic targets are urgently needed.In the present study, we hypothesized that integration of single-cell transcriptomic sequencing and large microarray sequencing of ESCC biopsies would reveal the key cell subtypes and therapeutic targets that determine the prognostic and tumorigenesis of ESCC. We characterized the gene expression profiles, gene sets enrichment, and the TME landscape of a microarray cohort including 84 ESCC tumors and their paired peritumor samples. We integrated single-cell transcriptomic sequencing and bulk microarray sequencing of ESCC to reveal key cell subtypes and druggable targets that determine the prognostic and tumorigenesis of ESCC. We then designed and screened a blocking peptide targeting Chemokine C–C motif ligand 18 (CCL18) derived from tumor associated macrophages and validated its potency by MTT assay. The antitumor activity of CCL18 blocking peptide was validated in vivo by using 4-nitroquinoline-1-oxide (4-NQO) induced spontaneous ESCC mouse model.Comparative gene expression and cell–cell interaction analyses revealed dysregulated chemokine and cytokine pathways during ESCC carcinogenesis. TME deconvolution and cell interaction analyses allow us to identify the chemokine CCL18 secreted by tumor associated macrophages could promote tumor cell proliferation via JAK2/STAT3 signaling pathway and lead to poor prognosis of ESCC. The peptide Pep3 could inhibit the proliferation of EC-109 cells promoted by CCL18 and significantly restrain the tumor progression in 4-NQO-induced spontaneous ESCC mouse model.For the first time, we discovered and validated that CCL18 blockade could significantly prevent ESCC progression. Our study revealed the comprehensive cell–cell interaction network in the TME of ESCC and provided novel therapeutic targets and strategies to ESCC treatment.The online version contains supplementary material available at 10.1186/s13046-023-02612-5. Esophageal cancer ranked the sixth among malignant tumors worldwide. Over 90% of the tumor cases are esophageal squamous cell carcinoma (ESCC) , 2. DespSo far, large-scale whole-exome sequencing of ESCC have unveiled several high frequency of mutations  and mutational processes  , 7. HoweTumor microenvironment consists various immune cells and stromal cells, which play crucial roles in cancer progression and therapeutic responses , 13. It The conventional methods to characterize the cell content of TME are fluorescence-activated cell sorting (FACS) and immunohistochemistry (IHC) staining. However, FACS requires a large amount of tumor biopsies and IHC can only reflect limited markers of a single tissue slice. To address these drawbacks, recent studies have utilized single-cell RNA sequencing (scRNA-seq) to dissect heterogeneous tumors and decipher the interaction of ESCC TME components , 25. DesIn the present study, we hypothesized that the integration of single-cell transcriptomic sequencing and large microarray sequencing of ESCC biopsies would reveal the key cell subtypes and therapeutic targets that determine the prognosis and tumorigenesis of ESCC. We characterized the gene expression profiles, gene sets enrichment, and the TME landscape of a microarray cohort including 84 ESCC tumors and their paired peritumor samples. We then utilized CIBERSORTx method with publicly available ESCC scRNA-seq dataset to deconvolute the TME of the ESCC microarray cohort and examine the prognostic value of TME components. We identified dysregulated chemokine and cytokine pathways during ESCC tumorigenesis with comparative analysis of molecular signaling combing differential expressed gene analysis and cell–cell interaction analysis. The comprehensive TME and immune landscape analyses allow us to identify the chemokine CCL18 (Chemokine C–C motif ligand 18) derived from TAMs, which could promote tumor cell proliferation and lead to poor prognosis of ESCC. We then designed and screened a CCL18 blocking peptide and validated its potency by MTT assay. The antitumor activity of CCL18 blocking peptide was validated in vivo by using 4-nitroquinoline-1-oxide (4-NQO)-induced spontaneous ESCC mouse model . For data processing, raw data were normalized using the Robust Multi-array Average procedure in the R package oligo. We implemented Bayes statistics using empirical Bayes (eBayes) in the limma package to identify expressed genes between paired tumor and peritumor samples with significant differences.Single cell RNA-seq data of ESCC with 41,237 cells from PRJNA777911  were selP value was less than 0.01 using R package limma.In brief, mRNA expression data in 84 paired tumor and peritumor samples were extracted by quantile normalization and were log2 scaled transformed. For genes with more than one probe, mean expression was calculated. Differentially expressed genes (DEGs) were characterized by log2 fold change of greater than 2, and an eBayes test P value of less than 0.05 was considered as statistical significance unless stated otherwise. A Cox proportional hazard regression model adjusting or not adjusting for available prognostic clinical covariates was performed to calculate hazard ratios (HRs) and 95% confidence intervals. The P values were adjusted to false discovery rate (FDR) using the Benjamini–Hochberg method in multiple comparisons. The survival curves were compared using Kaplan–Meier method and log rank test. All data analyses and visualization were performed using R (version 4.0.1).Student’s t-test, analysis of variance, and the Kruskal–Wallis test were utilized to compare continuous variables and ordered categorical variables. All tests were two sided, and a Gene set enrichment analysis (GSEA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) Gene Ontology (GO) annotation were performed using the R package clusterProfiler with the DEGs identified previously. Hallmark gene sets and canonical KEGG pathways gene sets were retrieved from the Molecular Signatures Database (v7.4). The enrichment scores of molecular pathways and gene expression signatures were evaluated using the single-sample gene set enrichment analysis (R package GSVA). KEGG Pathway enrichment analysis result was visualized using ClueGO (Version 2.5.6) within Cytoscape (Version 3.7.2).https://cibersortx.stanford.edu/runcibersortx.php) with the log-normalized expression matrix of 10 major cell populations as a reference matrix with default parameters. Using the resulting signature matrix, CIBERSORTx deconvolution was performed on the ESCC microarray cohort with 1000 permutations and S-mode batch correction.We used CIBERTSORTx  to inferWe used CellChat  to inferThe function computeCommunProbPathway inferred the cell–cell communication at a signaling pathway level. We used the netVisual_circle function to show the strength or weakness of cell–cell communication networks from the target cell cluster to different cell clusters in ESCC TME. The netVisual_bubble function shows the bubble plots of significant ligand-receptor interactions between the target cell cluster and other TME clusters.vs. cells in peritumor. Signaling molecules are considered as upregulated in the second condition if (i) the p values are less than 0.05, (ii) the log fold-changes are higher than 0.1, and (iii) the percentage of cells with expression in the second condition is higher than 25%. Signaling molecules are considered as downregulated in the tumor samples if they are upregulated in the peritumor samples. The ligand-receptor pairs are upregulated or downregulated if both ligands and receptors are upregulated or downregulated.To identify statistically significant upregulated and downregulated ligand-receptor pairs between tumor and peritumor sites, we combined cell–cell communication analysis with differential gene expression analysis. Specifically, for each cell group, we performed Wilcoxon rank-sum test for gene expression of cells in tumor samples 2 under fully humidified conditions.ESCC cell lines  and HET-1A, a normal human squamous esophageal epithelial cell line, were cultured in Roswell Park Memorial Institute (RPMI)-1640  with 10% fetal bovine serum (FBS)  and commercial antibiotic cocktail of penicillin and streptomycin  at 37 °C with 5% COPeripheral blood mononuclear cells (PBMCs) were obtained from healthy donors and isolated with Ficoll density gradient centrifugation. Cells were differentiated into monocyte derived macrophage (MDM) in vitro in the presence of 50 ng/mL M-CSF  for 6 days. The MDMs were then cultured in medium containing 10 ng/mL M-CSF and polarized for 24 h by adding 20 ng/mL IFN-γ and 20 ng/mL LPS (M1) or 20 ng/mL IL-4 and 20 ng/mL IL-13 (M2). Cells were stained with the following antibodies, anti-human CD14 eVolve-605 , anti-human CD163 PE , anti-human CD80 eFlour710 , and anti-human CD206 (MMR) FITC . The expression of cell surface molecules was analyzed by a BD FACS Celesta flow cytometer.For the induction of murine macrophages BMDM, the bone marrow cells were isolated from the C57BL/6 J mice and cultured in the medium with 20 ng/mL of GM-CSF  for 6 days, and the medium was refreshed every three days. The BMDMs were then cultured in medium containing 20 ng/mL GM-CSF for 24 h and further polarized by adding 20 ng/mL IFN-γ and 100 ng/mL LPS for M1 macrophages or 20 ng/mL IL-4 and 20 ng/mL IL-13 for M2 macrophages. The expression of mouse CCL3 in mRNA and protein levels were detected by qRT-PCR and ELISA, respectively. The primers 5’-TGACCTGGAACTGAATGCCT-3’ and 5’- TCAAGCCCCTGCTCTACACG-3’ were used for mouse CCL3. The primers for mouse PITPNM3 were 5’-TGATTCGGTGGAGAGTTCAGA-3’ and 5’-CTGGCTCATTCCAATAAGGATGG-3’, and primers 5’-GCATCCACTGGTGCTGCC-3’ and 5’-TCATCATACTTGGCAGGTTTC-3’ were used for the reference gene mouse GAPDH.For the knockdown of human PITPNM3, the shRNA sequence was designed and synthesized by Sangon Biotech, and then cloned into the lentiviral vector pSicoR-GFP. The inserting sequence was formed with the forward primer: 5’- TGCTGAGGAATGTCACGGCTAATCTCGAGATTAGCCGTGACATTCCTCAGTTTTTTC -3’ and reverse primer: 5’-TCGAGAAAAAACTGAGGAATGTCACGGCTAATCTCGAGATTAGCCGTGACATTCCTCAGCA -3’. To produce the lentivirus with shRNA, HEK-293 T cells were transfected with the packing vector pMD2.G , psPAX2  and pSicoR-GFP or pSicoR-GFP-shPITPNM3. The lentivirus was collected and used to infect the EC-109 cells.5 cells/well with or without the presence of 40 ng/mL rCCL18. With a 72 h treatment, the cells were harvest and stained with PI , or stained with the cell apoptosis kit  with Annexin V-APC and 7-AAD, according to the manufacturer’s instructions. The cells were acquired and analyzed by a BD FACSCelesta flow cytometer.EC-109, EC-109 Vector and EC-109 shPITPNM3 cells were seeded into 6-well plates at a density of 3×10The proliferation of EC-109 cells effected by the knockdown of PITPNM3, recombinant human rhCCL18 , or the peptides were determined by MTT assay. Briefly, cells were seeded into a 96-well plate at a density of 3,000 cells/well. After 24, 48, and 72 h, cell viability was detected using MTT reagent  dissolved in 5 mg/mL of PBS 7.2 and incubated at 37 °C for 4 h. Then 150 μL of DMSO replaced the incubation medium. MTT reduction was quantified by measuring the absorbance at 490 nm.EC-109, EC-109 Vector and EC-109 shPITPNM3 cells were seeded into 6-well plates at a density of 500 cells/well, the cell culture media RPMI-1640 were refreshed every 4 days. Over 12 days, colonies were fixed with 4% polyformaldehyde solution and stained with 0.2% crystal violet . The visible colonies of each well were recorded and counted.5 cells/well into the upper chamber within 200 μL medium without FBS, and the lower chamber was filled with 600 μL of medium containing 10% FBS. After 48 h incubation, cells were fixed with 4% paraformaldehyde, stained with crystal violet, and photographed.The Transwell assay was performed using a 24-well plate. EC-109, EC-109 Vector or EC-109 shPITPNM3 cells were seeded at a density of 5 × 105 cells/well into a 24-well plate. The monolayer cell was wounded by sterile tips to allow the formation of a cell-free path, and the suspended cells were washed. The cells were photographed at 0 h and 48 h, and the scratch areas were calculated.EC-109, EC-109 Vector or EC-109 shPITPNM3 cells were seeded at a density of 5 × 10EC-109, EC-109 Vector and EC-109 shPITPNM3 cells were treated with or without 40 ng/mL rCCL18 in the presence or absence of STAT3 inhibitor S3I-201 . The total cell lysates were prepared using protein lysis buffer. Then protein was fractionated by 10% SDS-PAGE, transferred to polyvinylidene fluoride (PVDF) membrane , and then blocked with 5% defatted milk dissolved in PBS (pH7.2) containing 0.1% Tween 20 for 2 h at room temperature. The PVDF membranes were incubated with the following primary human antibodies at 4 °C overnight: JAK2 , P-JAK2 , STAT3 , P-STAT3 . The reference antibody was β-actin . Thereafter, the PVDF membranes were incubated with secondary antibody , the blots were visualized using ECL system .The tumor tissues from the human esophageal and the whole mouse esophageal tissues were fixed with 4% paraformaldehyde phosphate solution and were embedded in paraffin. The sections were then incubated with monoclonal antibodies against CD68 , CD206 , and CCL18 . For trial staining, the primary antibodies were incubated one by one with HRP conjugated secondary antibody  and fluorescein, whereafter the sections were heated by a microwave using an EDTA antigen retrieval buffer (pH 8.0) to remove the combined antibodies. Nucleus shows blue by staining with DAPI . Signals were detected by an Ortho-Fluorescent Microscopy  and Imaging system .The protein sequences of human CCL18, human and mouse CCL3 were obtained and aligned by ClustalW. The structures of the above proteins were taken from the PDB database. The human CCL18  , human CPeptides were selected from the N and C terminal of the human CCL18 and CCL3 according to the sequence alignment and the superposed structure. The two Cysteine residues in the N terminal were replaced by Serine to avoid the formation of disulfide bond. The peptides were synthesized by Fmoc-based solid-phase peptide synthesis (SPPS) according to the standard protocol and purified by high performance liquid chromatography (HPLC).Female C57BL/6 J mice of 6–7 weeks aged were purchased from the Vital River Laboratory Animal Technology Co. Ltd . Mice were housed in SPF animal facility at room temperature with humidity of 40–60% and light and dark cycle for 12 h. Ethical consent and experimental procedures were approved by the Ethics Committee Zhengzhou University .For the induction of spontaneous ESCC, the mice were fed with drinking water containing 100 μg/mL 4-nitroquinoline-1-oxide (4-NQO) for 16 weeks. Thereafter, the mice were fed with sterilized pure water to allow the formation of ESCC. During the whole experiment, the activity status, food and water intake behaviors, body weight, and survival status of mice were observed and recorded every 2 days. The whole esophageal tissues of mice fed for 16, 28 and 32 weeks were performed the H&E staining for the detection of the ESCC induction process. Besides, the total RNA of the esophageal tissues of mice fed for 28 weeks were extracted and used to determine the expression of CCL3, CCR1 and CCR5. Also, the esophageal tissues were subjected to immunofluorescence staining for DAPI, CCL3 and the macrophages (F4/80). At week 31, the 4-NQO induced ESCC mice were randomly divided into two groups, and were intraperitoneally injected with 200 μL of normal saline or 10 mg/kg Pep3 daily for 8 days. At the end of treatment, the esophageal tissues of mice were harvested and photographed by an anatomical microscope, and the number and length diameter of tumor lesions were recorded.+ T cells, CD4+ T cells and macrophages, the splenocyte was stained with the following antibodies purchased from eBioscience, anti-CD45 (30-F11), anti-CD3 (17A2), anti-CD8 (53–6.7), anti-CD11b (M1/70), anti-CD11c (N418), anti-F4/80 (BM8) and anti-CD206 (MR6F3). The mouse esophageal tissues were subjected to H&E staining and immunofluorescence staining for DAPI, Ki67, F4/80, and immunohistochemistry staining for PITPNM3  by Servicebio .The spleen of the ESCC tumor bearing mice treated with NS or Pep3 were grinded and filtered into a single cell suspension. For the detection of the CD8The mRNA expression profiles of 84 paired treatment naïve ESCC samples were determined by microarray analysis. There were 351 differentially expressed genes (DEGs) with log2 fold change greater than 2 as shown in heatmap  played pivotal roles in ESCC TME. To gain further insight into local intercellular signaling in ESCC, we systematically searched for differentially expressed genes that coded for ligand and receptor/co-receptor pairs using the algorithm CellChat. CellChat infers cell–cell communications from scRNA-seq data by computing the expression of signaling ligands and receptor/co-receptors. We focused the study on cytokine- and chemokine-mediated interactions between epithelial/tumor and immune cells. To avoid missing any possible interactions, we at first updated ligand-receptor interaction database CellChatDB with Omnipathdb, leading to a comprehensive ligand–receptor database including 6260 unique connections. To investigate global differences in cell–cell communications between peritumor and ESCC tumors, we employed comparative CellChat (see Methods session) to study signaling interactions among all major cell types.We first examined the total number of possible cell–cell communications and the prominently affected cell types Fig. A and B. After gaining an understanding of the general cell–cell communications in ESCC tumors, we next investigated the molecular signaling mechanisms in deapth to identify potential pathways underlying the altered cellular compositions and communications in the ESCC ecosystem. We identified dysregulated ligand-receptor pairs in ESCC by combining differential expression analysis with cell–cell communication analysis. CellChat predicted significant upregulation of 24 ligand-receptor pairs from 11 signaling pathways in ESCC tumor tissues compared with peritumor tissues.P < 0.05)  Fig. SB and C. + macrophages (mainly M1-like macrophages) than CD206+ macrophages (mainly M2-like macrophages) . Therefore, these results suggested that CCL18 secreted by TAM might promote the tumor proliferation and lead to poor prognosis in ESCC patients.Among the top upregulated chemokines, CCL18 was highly expressed in tumor and correlated with poor prognosis Fig. C. As a res) Fig. F. SubseqAs the key functional receptor for CCL18, PITPNM3 is expressed primarily on the cell surface of tumor cells and it has been reported that TAM secreted CCL18 interacted with its receptor PITPNM3 to promote breast cancer metastasis and angiogenesis , 17. To The effects of PITPNM3 knockdown on the proliferation and colony formation of EC-109 cells were also tested. There were no significant differences in the cell proliferation detected by cell number counting, MTT assay, and colony formation Fig. A and B. As reported, CCL18 could promote the migration, invasion, EMT and metastasis of the breast cancer and hepatocellular carcinoma cells through the phosphorylation of PyK2 or NF-κB signaling pathway , 18. BesThere is no corresponding gene to CCL18 in mice. After examining all chemokines with sequences and structures similar to CCL18, we discovered the sequence similarity between CCL18 and human CCL3 was 62.3%, and that was 56.52% with mouse CCL3  to test our hypothesis. A total of 19,829 cells from 3 normal mice and 6 ESCC mice (including 3 CIS mice and 3 ICA mice)   Fig. C. The tr36) Fig. D. Comparlls Fig. E. In thells Fig. F. Additills Fig. G, which lls Fig. . Above aSo far, the development of early diagnostic biomarkers and therapeutic targets for ESCC has been relatively slow, which has hampered clinical outcome. The TME, which reflects the immune response in a number of malignancies and plays a significant role in the genesis and progression of cancer , 38, 39.To characterize the whole TME landscape of ESCC, we first identified that the differentially expressed genes in ESCC revealed the crucial function of ECM-related genes  and immune checkpoints during tumor invasion and EMT Fig. B-D. PrevOur integrated analysis of single cell RNA-seq and microarray data not only defined the ESCC TME, but also provided novel insights into the cell–cell interactions between tumor and immune cells in ESCC . CompareCombing clinical information in the ESCC microarray cohort, we were able to uncover prognostically relevant cell subtypes and cell communication ligands by dissecting the ESCC TME. In multiple solid tumors, TAMs are actively recruited to the TME through paracrine communication and chemotaxis with the tumor cells , 19, 36.Comparative analysis of cell communication further screened prognostic ligand receptor pairs regulating ESCC TME including CCL3/CCR1, CCL3/CCR5 and CCL18/PITPNM3 Fig. SE. Chemok+ T cell response  Bubble heatmap showing expression levels of CCL3,CCL18 and their receptors in different cell types and locations based on ESCC scRNA-seqdataset. Dot size indicates percentage of expressing cells, colored based onnormalized expression levels. (B) Kaplan-Meier curves of overall survival ofESCC microarray cohort stratified by the expression of CCL3 and its receptorsCCR1 and CCR5. (C) Kaplan-Meier curves of overall survival of ESCC microarraycohort stratified by the expression of CCL18 receptors ACKR1, ERG28 and CCR8. FigureS2. Cell-cell communication network of ESCC. Differential number of possible interactions and interaction strength(edge weight) between the five major cell types between peri- and tumor sites(A and B). Number of possible interactions between the 11 cell types in peri-and tumor sites (C and D). Figure S3. Cell-cellcommunication in 4-nitroquinoline 1-oxide (4NQO) inducedmouse ESCC model. (A) UMAP visualization of 19,829 cells from 3 normal mice, 3 carcinoma in situ(CIS) mice and 3 invasive carcinoma (ICA) mice (CRA002118). (B) Differential numberof possible interactions between any two cell populations. Red  and blue  in the color bar indicate higher number ofpredicted interactions in normal and tumor mice samples, respectively. (C)A circle plotshowing the number of possible interactions in normal mice estimated byCellChat. (D) A circle plot showing the number of possible interactions in CIS and ICAmice estimated by CellChat. (E)A circle plot showing the cell-cell communicationnetwork of CCL pathway estimated by CellChat. (F)The significantly related ligand–receptor interactions of CCL pathway in theESCC mouse model inferred by CellChat analysis. Figure S4. The expression of CCL3 or its receptor inthe ESCC tissues or macrophages. (A)The mRNA expression level of CCL3, CCR1 and CCR5 in the ESCC tissues of 4-NQOinduced mice with ESCC by qPCR. (B) The expression of CCL3 and co-localizationwith macrophages (F4/80) in the mouse ESCC tissues. Representative views were shown. (C) The expression of CCL3 in BMDM polarized M1 or M2 macrophages inmRNA and protein levels. . Figure S5.The cell cycle and apoptosis of EC-109, EC-109 Vector and EC-109 shPITPNM3cells. (A) Cell cycles of EC-109, EC-109 Vectorand EC-109 shPITPNM3 cells treated with or without 40ng/mL CCL18 for 72 h. *P< 0.05. (B) Flow cytometry analysis of the apoptosis of EC-109, EC-109Vector and EC-109 shPITPNM3 cells treated with or without 40ng/mL CCL18 for 72h. n.s., no significance. Figure S6. The proliferation, colony formation and migration analysis ofEC-109, EC-109 Vector and EC-109 shPITPNM3 cells. (A) The cell growth curve and cell viability of EC-109, EC-109 Vector andEC-109 shPITPNM3 cells determined by the cell number counting and MTT assay. (B)The colony formation of EC-109, EC-109 Vector and EC-109 shPITPNM3 cells toform clones. (C) Representative results of the Transwell assay of EC-109,EC-109 Vector and EC-109 shPITPNM3 cells at 48 h. Bar = 200 μm. (D) Representativeimages of the wound-healing assay of EC-109, EC-109 Vector and EC-109 shPITPNM3cells after 48 h. n.s., no significance. Figure S7. (A)Representative results of the Transwell assay of EC-109 cells in the presenceor absence of rhCCL18 at increasing concentrations (10–40 ng/mL) for 48 h. (B)Representative images of the wound-healing assay of EC-109 cells in thepresence or absence of rhCCL18 at increasing concentrations (10–40 ng/mL) at 0h and 48 h. n.s., no significance. Figure S8. The expression of PITPNM3 inthe ESCC tissues with or without Pep3 treatment. (A) The mRNA expression level of PITPNM3 in the ESCC tissues of 4-NQOinduced mouse model by qPCR. (B) Representative images of PITPNM3 staining inthe ESCC tissues, bar = 50 μm. ***P < 0.001. Figure S9. Correlationof CCL18 with immune scores, CD8 T cells and 40 known immune checkpoints in ESCC. The correlationmap between 40 common immune checkpoint genes andthe expression of CCL18 is as follows: *** P < 0.001, ** P< 0.01, * P < 0.05. Most correlated immune checkpoint genes arehighlighted in red. Figure S10. Correlation of CCL18 with known immunecheckpoints. Calculated from RNA-seqexpression data from The Cancer Genome Atlas (TCGA)datasets across 33 different cancer types. *** P < 0.001, ** P< 0.01, * P < 0.05.


Overall, breast cancer risk was highest (OR = 1.5) between 70 nmol/L and 80 nmol/L of serum 25(OH)D concentration. Then after serum 25(OH)D 80 nmol/L concentration, the breast cancer risk declined. In multivariate-adjusted logistic regression, the risk of having breast cancer was significantly higher in serum 25(OH)D 75–˂100 nmol/L category compared to the 25(OH)D < 30 nmol/L category [OR and 95% CI: 2.4 (1.4–4.0)]. In conclusion, serum vitamin D concentrations ≥ 100 nmol/L are associated with reduced risk of breast cancer in postmenopausal women. Controlled trials are required to verify if serum 25(OH)D ≥ 100 nmol/L offers protection against breast cancer in postmenopausal women.The association between serum 25-hydroxyvitamin D [25(OH)D] concentration and breast cancer risk in postmenopausal women is not well understood. The aim of this study was to investigate the association between serum 25(OH)D concentration and breast cancer in postmenopausal women in the United States using nationally representative sample surveys. We used the data from seven cycles of National Health and Nutrition Examination Surveys from 2001 to 2014. Participants were non-institutionalized postmenopausal women (n = 8108). In restricted cubic spline analysis, a significant, nonlinear, invert ‘U’ relationship was observed between serum 25(OH)D concentrations and breast cancer in postmenopausal women ( All functions of vitamin D are attributed to the action of 1,25(OH)2D via vitamin D receptors (VDR). The well-established role of vitamin D is to maintain calcium and phosphorous homeostasis. Recently, the role of vitamin D in non-calcemic functions has received much attention. Many studies have linked serum 25(OH)D concentrations to several chronic diseases such as diabetes . 25(OH)D is hydroxylated to 1,25-dihydroxyvitamin D , self-reported race-ethnicity, education level, alcohol consumption, physical activity, smoking status, use of supplements, season of the survey, BMI, and hormone replacement therapy (HRT). BMI and age were used as continuous variables. Remaining variables were used as categorical variables.The data were analyzed using Stata statistical software package  taking sample weights for cumulative 7 cycles of NHANES, 2001–2014 into consideration according to the NCHS analytical guidelines. Serum 25(OH)D concentrations were stratified into 5 categories based on the recommendations by the Institute of Medicine (IOM)  and the p-value of <0.05.Unadjusted, age-adjusted, race-ethnicity-adjusted, and multivariate-adjusted logistic regression analyses were performed to determine the association between serum 25(OH)D concentrations and breast cancer prevalence. Confounding variables such as age, education level, HRT, physical activity, the season of survey, smoking status, alcohol consumption, PIR, and BMI were used in the multivariate logistic regression. Additionally, we also evaluated the interaction effects of supplement use (yes and no), season of survey (winter and summer), and race-ethnicity  in the association of serum 25(OH)D concentrations with breast cancer in postmenopausal women. Further, we tested the nonlinear relationship between serum 25(OH)D concentrations (used as a continuous variable) and breast cancer using a restrict cubic spline method with three knots at 5th, 50th, and 95th percentiles. Statistical significance was set at a p < 0.001). In this study, ≈8.6% had serum 25(OH)D < 30 nmol/L, ≈32% had <50 nmol/L, ≈67% had <75 nmol/L, ≈89% had 75–˂100 nmol/L, and 11% had ≥100 nmol/L. In the ≥100 nmol/L serum 25(OH)D concentration category, there were more NHW than NHB or MA/H. Prevalence of <30 nmol/L serum 25(OH)D was the highest in NHB (47%) compared to NHW (≈27%) or MA/H (≈16%). The highest percentage of subjects who participated in the survey in summer was in the serum 25(OH)D ≥ 100 nmol/L category (≈64%), whereas the highest percentage of subjects who were surveyed in winter was in the serum 25(OH)D < 30 nmol/L category (≈58%). About ≈90% of subjects who reported taking supplements a month before the survey was in the 25(OH)D ≥ 100 nmol/L concentration category, while the highest proportion of subjects who did not take supplements was in the lowest 25(OH)D category.The final analytic sample was 8108 after excluding missing data for 25(OH)D and confounding variables . The chap for nonlinear trend 0.014) (p for nonlinear trend 0.031) D concentrations is presented in d 0.014) A. Furthed 0.031) B. Overalp for trend ˂ 0.031). In age-adjusted, race-ethnicity-adjusted, and multivariate-adjusted models, the risk of having breast cancer was highest in the 25(OH)D 75–˂100 nmol/L category. In general, in all three models, the ORs increased from the serum 25(OH)D < 30 nmol/L category to the 25(OH)D 75–˂100 nmol/L category and then decreased in the serum 25(OH)D ≥ 100 nmol/L category. This observed relationship was similar to the invert U relationship that was observed in the cubic spline logistic regression (The relationship between serum 25(OH)D concentration (categorized) and breast cancer prevalence in postmenopausal women is shown in gression . In the gression .p = 0.95), season of survey (p = 0.59), and race-ethnicity (p = 0.12) in the relationship between serum 25(OH)D and breast cancer. Association between serum 25(OH)D concentration and breast cancer prevalence in postmenopausal women who participated in NHANES 2001–2014 by race-ethnicity is presented in This study is the first to demonstrate a significant nonlinear association between serum 25(OH)D concentrations and breast cancer in postmenopausal women in a nationally representative sample of the US population. The odds of having cancer in postmenopausal women is more than 2 times higher in serum 25(OH)D concentrations of 75–˂100nmol/L compared to the group with ˂30 nmol/L. Moreover, in cubic spline regression analysis, the risk of breast cancer was highest (OR ≈ 1.5) at ≈75 nmol/L of serum 25(OH)D concentrations, with reducing risk after serum 25(OH)D 80 nmol/L. By and large, both analyses are in agreement with the overall invert ‘U’ trend relation between serum 25(OH)D and breast cancer in postmenopausal women.A limited number of studies have shown a higher risk of breast cancer with increasing serum 25(OH)D concentrations ,34, althIn the race-ethnicity subgroup analysis, we found a significant nonlinear relation between breast cancer and serum 25(OH)D only in NHW but not in other race-ethnicities. Lack of relation between breast cancer and serum 25(OH)D in NHB and in MA/H was more likely due to lower sample sizes and lower serum 25(OH) concentrations in these race-ethnicities compared to the NHW race . Further2D, an active hormone, in the kidney, which suggests that a high serum concentration of 25(OH)D does not necessarily correspond to higher concentrations of 1,25(OH)2D [2D has been shown to contribute to controlling cell growth and proliferation. Vitamin D can be a regulatory factor in the whole process of tumor development starting from early initiation to metastasis. Vitamin D’s anti-inflammatory role and antioxidant defense protects against tumor initiation [The liver conversion of vitamin D to 25(OH)D is less regulated than the conversion of 25(OH)D to 1,25(OH)25(OH)2D . 1,25(OHitiation . It has itiation .2D) activity is optimum [2D 24-hydroxylase (CYP24A1) expression and a decrease in CYP27B1 expression [2D to inactive 24,25(OH)2D. The CYP24A1 gene has been observed to amplify in breast cancer [2D. Nonetheless, it is not known at what concentrations 25(OH)D is protective against breast cancer.High serum 25(OH)D has been found to be protective against cancer, only when 25(OH)D 1-α hydroxylase (CYP27B1) (converts serum 25(OH)D to 1,25(OH) optimum . However optimum ,50. In bt cancer . Additiot cancer . The cont cancer . AccordiOverall, results from studies reporting the association of serum 25(OH)D with the prevalence/incidence of breast cancer are equivocal. Recent evidence from meta-analysis studies suggested an inverse association of serum 25(OH)D (not dietary vitamin D intake) with breast cancer ,54. In aThe findings from this study should be viewed in terms of a few limitations. Due to the cross-sectional nature of this study, the cause-and-effect relation between serum vitamin D and breast cancer should not be assumed. In this study, the majority of the breast cancer diagnosis must have happened before the serum 25(OH)D measurement. There were no data on for how long the women had been diagnosed with breast cancer before the serum 25(OH)D measurement was taken. One cross-sectional measurement of serum 25(OH)D concentration may not reflect the concentrations many years prior especially in those who had a major change in their health status (such as cancer diagnosis). Therefore, it may be that some cancer patients after cancer diagnosis started taking vitamin D supplements or modified their diets to include more vitamin D-rich foods. To what extent this affected the results is not known. Additionally, it is possible that breast cancer therapy may have affected the circulating 25(OH)D concentration. It has been reported that the treatment of early stages of breast cancer using anti-hormone therapy with tamoxifen has been shown to increase serum 25(OH)D . It is nA strength of this study includes a combined seven cycles of NHANES based on a nationally representative sample. This makes the results of this study generalizable to the population described in this study. Current data analysis was based on standardized 25(OH)D concentrations which allowed us to concatenate various cycles of NHNAES into one large database. This increased the precision of the estimate. Additionally, we used clinically meaningful cut-off values based on the ES and the IOM recommendations in assessing the association between serum 25(OH)D and breast cancer rather than artificial cut-off quartiles or tertiles.In conclusion, an invert ‘U’ association was observed between serum 25(OH)D concentrations and breast cancer in postmenopausal women. It appears that serum 25(OH)D concentrations ≥ 100 nmol/L may be protective against breast cancer in postmenopausal women. Controlled trials are needed to study the association between serum 25(OH)D and breast cancer risk and to further elucidate the mechanism of vitamin D in cancer pathogenesis in postmenopausal women.


Mycobacterium tuberculosis (MtCM) has only low activityon its own. Remarkably, its catalytic efficiency kcat/Km can be boosted morethan 100-fold by complex formation with a partner enzyme. Recently,an autonomously fully active MtCM variant was generated using directedevolution, and its structure was solved by X-ray crystallography.However, key residues were involved in crystal contacts, challengingthe functional interpretation of the structural changes. Here, weaddress these challenges by microsecond molecular dynamics simulations,followed up by additional kinetic and structural analyses of selectedsets of specifically engineered enzyme variants. A comparison of wild-typeMtCM with naturally and artificially activated MtCMs revealed theoverall dynamic profiles of these enzymes as well as key interactionsbetween the C-terminus and the active site loop. In the artificiallyevolved variant of this model enzyme, this loop is preorganized andstabilized by Pro52 and Asp55, two highly conserved residues in typical,highly active chorismate mutases. Asp55 stretches across the activesite and helps to appropriately position active site residues Arg18and Arg46 for catalysis. The role of Asp55 can be taken over by anotheracidic residue, if introduced at position 88 close to the C-terminusof MtCM, as suggested by molecular dynamics simulations and confirmedby kinetic investigations of engineered variants.Unlike typical chorismatemutases, the enzyme from  In fact, the first discovered AroQδ enzyme, the intracellular CM from Mycobacteriumtuberculosis (MtCM),21 is on itsown only a poor catalyst (kcat/Km = 1.8 × 103 M–1 s–1),21 despite itscrucial role for producing the aromatic amino acids Tyr and Phe. However,this low activity can be boosted more than 100-fold to a kcat/Km of 2.4 × 105 M–1 s–1 through formationof a noncovalent complex with the first enzyme of the shikimate pathway,3-deoxy-d-arabino-heptulosonate 7-phosphate(DAHP) synthase (MtDS)  1A.2121 or its corresponding cationic residues in other CMs (of both AroHand AroQ families).22 However, high catalyticprowess is only achieved when this cationic residue is optimally positionedsuch that it can stabilize the developing negative charge at the etheroxygen in the transition state  twiceexceeding that of wild-type MtCM in the MtCM–MtDS complex,and can no longer be activated further through the addition of MtDS.12 The biggest gains in catalytic activity weredue to replacements T52P and V55D in the H1–H2 loop and R87P,L88D, G89A, and H90M at the C-terminus , followed by T52P (6-foldgain).12 Combined, these two changes, discussedin detail in a previous publication, gave a kcat/Km that was 22 times highercompared to wild-type MtCM.12 The fourC-terminal amino acid replacements together increased the activitymore modestly (by a factor of 4), and the five exchanges introducedin the two final evolutionary rounds yielded an additional factorof 5. The resulting combination of large-impact and more subtle residuesubstitutions in MtCMV  and differs considerably from that observed in free MtCM simulations to investigatethe behavior of MtCM in the absence or presence of ligands and toanalyze whether the protein is able to interconvert between activatedand nonactivated conformations in the absence of the MtDS partnerenzyme. We also compared the wild-type MtCM with the evolved MtCME. coli DH5αor XL1-Blue . All cloning techniquesand bacterial culturing were performed according to standard procedures.29 Oligonucleotide synthesis and DNA sequencingwere performed by Microsynth AG .General cloningwas carried out in 6 tag, first 5 residues missing). Partsof the MtCM gene (Gene Rv0948c) were amplified using oligonucleotides412-MtCM-N-V55D (5′-GTTCGCTAGCGGAGGTACACGTTTGGATCATAGTCGGGAGATGAAGGTCATCGAAC)or 413-MtCM-N-T52P (5′-GTTCGCTAGCGGAGGTCCGCGTTTGGTCCATAGTCGGGAGATGAAGGTCATCGAAC)together with oligonucleotides 386-LpLib-N2 (5′-GGTTAAAGCTTCCGCAGCCACTAGTTATTAGTGACCGAGGCGGCCACGGCCCAAT)on template pMG24812 to create a 163 bpPCR product. The PCR products were restriction digested with NheI and HindIII and the resulting 148bp fragments were individually ligated to the accordingly cut 2873bp fragment from acceptor vector pKTNTET-0.12 The ligation was performed with T4 DNA ligase  overnight at 16 °C. The ligation productswere transformed into chemically competent E. coli XL1-Blue cells. The cloned PCR’ed DNA fragments were confirmedby Sanger sequencing. Subsequently, the genes for MtCM-T52Pand MtCM-V55D were isolated by restriction digestion using enzymes XhoI and SpeI followed by a preparativeagarose gel, yielding corresponding 260 bp fragments. pKTCMM-H21 was used as acceptor vector and was accordinglyrestriction digested with XhoI and SpeI, yielding a 4547 bp acceptor fragment. The fragments were ligatedovernight at 16 °C, using T4 DNA ligase. The ligation productswere transformed into chemically competent E. coli KA12 cells23 and the inserts were analyzedby Sanger sequencing. The gene for variant PHS10-3p3,12 carrying an N-terminal His6-tag and missingthe first five residues, was recloned into the native format providedby plasmid pKTCMM-H. Acceptor vector pKTCMM-Hand pKTNTET-PHS10-3p3 were restriction digested with XhoI and SpeI, and the fragments were isolated frompreparative agarose gels. The 4547 bp and 260 bp fragments were ligatedovernight at 16 °C with T4 DNA ligase and transformed into chemicallycompetent XL1-Blue cells. The relevant gene sequence was confirmedby Sanger sequencing.Forthe construction of expression plasmids pKTCMM-H-V55D and pKTCMM-H-T52Pfor the native MtCM single variants, the individual site-directedmutants were first constructed in the pKTNTET background  anddifferent reverse primers  on different DNA templates. The gene encoding MtCM L88Dwas produced by PCR with primers LB5 (5′-TCCGCACATATGAACCTGGAAATG) and LB4 (5′-TAAGCAACTAGTTATTAGTGACCGTCGCG) on the template plasmid pKTCMM-H carrying thewild-type gene.21 The gene for the triplevariant MtCM (T52P V55D L88D) was assembled with primers LB5 and LB4on a pKTCMM-H derivative containing MtCM variant 3p3 (T52P V55D).12 The gene for MtCM variant PNAM (D88N) was generatedwith primers LB5 and LB6 (5′-TAAGCAACTAGTTATTACATAGCATTCGGA), and for the MtCM variant PLAM (D88L) with primersLB5 and LB7 (5′-TAAGCAACTAGTTATTAGTGACCAAGCGGA),in both cases using a version of the template plasmid pKTCMM-H, intowhich the gene for the top-evolved s4.15 variant had been inserted.12 The resulting 296 bp PCR fragments containing NdeI and SpeI restriction sites at the5′ and 3′ ends of the MtCM gene, respectively, weredigested with the corresponding enzymes to yield 278 bp fragments.These fragments were ligated to the 4529 bp NdeI–SpeI fragment of pKTCMM-H yielding the final 4807 bp plasmids.Different C-terminal variants of the MtCMgene were generated byPCR mutagenesis. DNA fragments were amplified with the same forwardprimer (containing an E. coli strain KA1330 carrying anendogenous UV5 Plac-expressed T7 RNA polymerase gene wasused to overproduce the (untagged) MtCM variants. KA13 cells weretransformed by electroporation with the appropriate pKTCMM-H plasmidderivative that carries the desired MtCM gene variant.T52P) and V55D(MtCMT52P), the transformed cells were grown in baffledflasks at 30 °C in LB medium containing 100 μg/mL sodiumampicillin until the OD600 reached 0.5. Gene expressionwas induced through the addition of isopropyl-β-d-thiogalactopyranoside(IPTG) to a final concentration of 0.5 mM, and incubation was continuedovernight. The cells were harvested by centrifugation (6500g for 20 min at 4 °C) and frozen at −80 °Cbefore being resuspended in a buffer suitable for ion exchange chromatography,supplemented with DNase I (Sigma), 150 μM phenylmethanesulfonylfluoride (PMSF) and cOmplete protease inhibitor cocktail(Roche). The cells were lysed using BeadBeater , with four times 30 s pulses with a 60 s wait betweeneach pulse. Insoluble debris was removed by centrifugation .For thetwo crystallized MtCM variants T52P (MtCMN-morpholino)ethanesulfonicacid (MES), pH 6.5. MtCM V55D has a pI of 6.74; therefore, the pelletwas resuspended in 50 mM acetic acid, pH 5.25. After lysis and centrifugation,the soluble lysate was loaded onto a HiTrap XL SP column for cation exchange chromatography and eluted with a 0–0.5M NaCl gradient. The purity of the eluted fractions was gauged bysodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE)analysis and sufficiently pure fractions were pooled and concentratedusing concentrator tubes with a 5 kDa molecular mass cutoff (VivaspinMWCO 5K). The proteins were then further purified by size-exclusionchromatography using a Superdex 75 300/10 column  withrunning buffer 20 mM 1,3-bis[tris(hydroxymethyl)methylamino]propane(BTP), pH 7.5, 150 mM NaCl. Finally, the proteins were concentrated(Vivaspin MWCO 5K), frozen, and stored at −80 °C.The resuspension bufferwas selected based on the theoretical isoelectricpoint (pI) of the protein. MtCM T52P has a pI of 8.14, so the pelletwas resuspended in 50 mM 2- and washed once with 100mM tris(hydroxymethyl)aminomethane(Tris)–HCl, pH 7.5. The cells were pelleted again, and thecell pellet was either frozen for storage at −20 °C ordirectly resuspended in 80 mL of sonication buffer . The cells were disrupted by sonication on ice. The crude lysate was clearedby centrifugation .The supernatant was supplemented with sonication buffer to 100 mL,42 g of ammonium sulfate was added, and the solution was stirred at4 °C for 1.5 h. The precipitate was pelleted by centrifugation, dissolved in 8mL of low-salt buffer , and dialyzed against1 L of low-salt buffer overnight. Dialysis was repeated against another1 L of low-salt buffer for 3 h before application to a MonoQ  FPLC column .The sample was eluted over 80 mL in 20 mM piperazine by applying agradient from 0 to 30% of a high-salt buffer .The cells were harvested by centrifugation was determined using the Bradford assay.31The MonoQ fractions containing the proteinof interest were pooledand concentrated to less than 1 mL. The concentrated sample was directlyapplied to a gel-filtration column  and eluted in 20 mM BTP, 150 mM NaCl, pH 7.5. Proteinidentity was confirmed by liquid chromatography–mass spectrometry(LC-MS) ,with the observed mass being within 1 Da of the calculated mass. Proteinpurity was assessed by SDS-PAGE  and the enzyme concentration () ranging from 10 to 1500 μM were usedat 274 nm (ε274 = 2630 M–1 cm–1) or 310 nm (ε310 = 370 M–1 cm–1). Chorismate disappearance upon enzyme additionwas monitored to determine the initial reaction velocity (v0). The obtained data were fitted to the Michaelis–Mentenequation with the program KaleidaGraph  to obtain the catalytic parameters kcat and Km.Michaelis–Menten kinetics of the untaggedpurified MtCM variants were determined by a continuous spectroscopicchorismate depletion assay .The purified enzymes were diluted into 20 mM potassium phosphate,pH 7.5, containing 0.01 mg mL2VKL)21 or from the structure of the CM polypeptide in the apoMtCM–MtDS complex .The malate complex was chosen over ligand-free MtCM (PDB ID: 2QBV)41 due to its higher resolution and better refinement statistics.Both simulations gave essentially the same result; therefore, we willnot refer to the second data set any further. For the highly activeevolved MtCM variant (MtCMV), we used the recent crystalstructure (PDB ID: 5MPV).12 The MtCM–ligand complex (MtCMLC) was taken from PDB ID: 2W1A,21 excludingthe MtDS partner protein, where MtCM was co-crystallized with a transitionstate analog (TSA) in its active site (Table S1). Residues that were not fully defined were addedto the models using (often weak) electron density maps as referencein Coot.37 When no interpretabledensity was visible, geometric restraints  were applied during model building, to ensurestable starting geometries. The N-termini of all of the models wereset at Glu13, corresponding to the first defined residue in almostall of the resolved structures available. Glu13 was capped with anacetyl group to imply the continuation of the H1 helix. CM dimerswere generated by 2-fold crystallographic symmetry.Molecular dynamics (MD)simulations were carried out on a number of representative structuresfor CM. They included two independent sets of simulations for apoMtCM, starting either from the X-ray crystal structure of MtCM incomplex with malate   and 55 (V55D), we set outto determine the crystal structures of these two enzyme variants.Together, these two substitutions led to an increase in kcat/Km by 22-fold comparedto the parent enzyme.12The fact that MtCM exhibitsonly low natural catalytic activityprovided us with a perfect opportunity to probe features that optimizeCM catalysis by directed evolution.T52P crystals had the same spacegroup (P43212) and similarcell parameters as the wild-type enzyme , where the asymmetric unit contained the biologicaldimer. The MtCMT52P structure was refined to 1.6 Åand Rwork/Rfree values of 24.0/26.5% , whereas MtCMV55D diffraction data yielded lower-qualityelectron density, particularly for the H1–H2 loop . Consistent with this, the Wilson B-factor of MtCMV55D is high (57.8 Å2), indicating structural disorder. Refinement of the 2.1 ÅMtCMV55D model stalled at Rwork/Rfree values of 27.6/34.9%, with veryhigh B-factors for H1–H2 loop residues, especiallyfor protomer B. For both structures, residues preceding residue Glu13and C-terminal to Leu88 showed poorly defined electron density. Therefore,the terminal residues were not included in the final model.Whereas MtCMgroup P432 and sim2VKL(2QBV), with oT52P (PDBID: 6YGT) andMtCMV55D are very similar to the structure of substrate-freewild-type MtCM (PDB ID: 2QBV),41 with RMSD = 0.3 and0.4 Å, respectively. However, the H1–H2 loops (47MASGGPRLDHS57) of both protomers of MtCMV55D adopt a different conformation (RMSD = 2.3 Å compared to PDBID: 2QBV), whichmost closely resembles the kinked conformation in the MtCM–MtDScomplex  . This interaction preorganizesthe active sites of both MtCM variants for catalytic activity, mimickingMtCM in the complex with MtDS , differs significantly between the structures  2A. In th compare S1E,G,H. LC ). In particular, helix H2 showed a tendencyto unravel  from the original crystal structure geometry forthe CM core regions (RMSD = 2.8 ± 1.2 Å (MtCM) or 3.4 ±1.5 Å . The fact that the fluctuationsof the MtCMV H1–H2 loop are contained within theconformational basin of the catalytically competent geometry . Interestingly,ligand presence in one of the two binding pockets was sufficient tostabilize the structure of the whole dimer. Nonetheless, the H1–H2active site loop of the apo protomer retained its intrinsic flexibility. This result reflects the expected rigidification occurring uponsubstrate binding due to additional protein–ligand interactionsin MtCMLC. MtCMV accomplishes rigidificationas a direct consequence of its evolved sequence. Interestingly, alsoMtCMV55D shows generally dampened fluctuations, possiblydue to the extended helical motif observed in that structure.Overall, MtCMThe MtCM activesite contains four arginine residues 1F, amongWT, the two variants MtCMV and MtCMV55D exhibited lower RMSF values for all active site Arg residues.A crucial factor for the enhanced activityof MtCM in the MtCM–MtDScomplex is an MtDS-induced interaction between MtCM’s H1–H2loop and its C-terminus.Figure S4B,C).Our 1 μs-long simulations detected persistent, multiple interactionsinvolving the C-terminal carboxylate. In contrast, the hydrophobiccontacts between Leu54 and Leu88 were disrupted in the first nanoseconds,and almost never observed again during the rest of the simulationtime are substituted with Pro–Asp–Ala–Met (PDAM) atpositions 87–90, which include another carboxylate, introducedthrough Asp88. Our MD simulations show that the Asp88 carboxylatein the evolved variant MtCMV offers an alternative modeof interaction with Arg53 of the H1–H2 loop (S5), which is not possible for wild-type MtCM. This allowsfor a persistent interaction of C-terminal residues with the H1–H2loop throughout the simulation, while maintaining a highly flexibleC-terminus. Moreover, in MtCMV, Arg46 is topologicallydisplaced from its original position with respect to the loop andno longer able to engage in a catalytically unproductive salt bridgewith the C-terminus.In MtCM–H2 loop 6B and S5V, is a proline residue (RLGHto PDAM).12 However, in contrast to Pro52,Pro87 did not appear to have a major influence on the simulations.While Pro52 is likely contributing to H1–H2 loop rigidity,with an average RMSF of 1.6 Å in MtCMV compared to2.5 Å (MtCM) for this region, the C-termini showed similarlyhigh RMSF values in the two models (>3 Å). Although Pro87induceda kink at the C-terminus, this did not appear to affect the flexibilityof the three terminal residues Asp88–Ala89–Met90.Another interesting substitution, whichemerged within the four C-terminal residues during the laboratoryevolution toward variant MtCMV, the L88D replacement was only acquired after theH1–H2 loop-stabilizing substitutions T52P and V55D were alreadyintroduced. Guided by the outcome of the MD simulations, we thereforeprobed the kinetic impact of the innocuous single L88D exchange inthe context of three different sets of MtCM variants to experimentallyassess the benefit of the introduced negative charge for fine-tuningand optimizing catalytic efficiency. We looked at (i) changing Asp88in the MtCMV sequence 87PDAM90 intoAsn88 or Leu88, (ii) directly introducing Asp88 into the MtCM wild-typesequence, and (iii) the triple variant T52P V55D L88D (MtCM Triple).All variants were obtained in their native format, i.e., with their native N-terminus and without a His-tag, to allow foroptimal comparison with the structural and computational results.The variants were purified by ion-exchange and size-exclusion chromatographyfrom the E. coli host strain KA13,which is devoid of CM genes to rule out contamination by endogenousCMs.30 Subsequently, the enzymes’ kineticparameters were characterized by a spectrophotometric chorismate depletionassay.In the course of the directed evolution ofMtCMV leads toa 2.5-fold drop in the catalytic efficiency kcat/Km to 1.7 × 105 M–1 s–1. This decrease is dueboth to a slightly lower catalytic rate constant (kcat) as well as a reduced substrate affinity (doubled Km). When residue 88 is further changed to thesimilarly sized but nonpolar wild-type residue Leu88 in variant MtCMPLAM, the catalytic parameters essentially remain the same as forthe Asn88 variant , a trend for anincrease in catalytic activity upon replacing Leu88 by Asp88 was observed51 in thecomplex with MtDS (PDB ID: 2W1A)21 . This kink is much less prominent in wild-typeMtCM, or even MtCMT52P (S1B), andcompletely lost during the simulations of MtCMWT (we didnot carry out simulations on the single variant MtCMT52P). Thus, this conformation may well be a crystallization artifactrather than a prerequisite for an active MtCM.Both MtCMV.12 This residue is located onthe C-terminal side of the H1–H2 loop . During the MD simulations of MtCMV and the single variant MtCMV55D, the presence of Asp55reduced the mobility of active site residues. By interacting withArg18′ and Arg46, this residue helps to preorganize the activesite for catalysis and reduce unfavorable conformational fluctuationscaused by electrostatic repulsion in the absence of a substrate. Thisis supported by the lower RMSF values of MtCMV comparedto uncomplexed wild-type MtCM  measurements; preliminary data). By decreasingthermal fluctuations in the active site, Asp55 likely also reducesthe entropic penalty associated with substrate binding. Pro52 appearsto exert a similar stabilizing effect on the protein, despite therather small structural changes, as suggested by a 2 °C increasein melting temperature of MtCMT52P in DSF experiments comparedto MtCM (preliminary data). This single substitution alone raisesthe kcat/Km value of the enzyme by a factor of six.12 It is worth noting that the simultaneous substitution of T52P andV55D increased the melting temperature by 6 °C (monitored bycircular dichroism spectroscopy) and boosted kcat/Km by 22-fold.12 The top-evolved MtCMV even showed a meltingtemperature of 83 °C compared to 74 °C for the parent MtCM.12Nevertheless,preorganization and prestabilization appear to beof crucial importance for the catalytic prowess of MtCM. The largestboost in catalytic efficiency (12-fold enhancement) by a single substitutionwas observed for the V55D replacement found in the evolved MtCM–H2 loop 1D,E and –H2 loop 5A, an inype MtCM 1 and by 21 Specifically,a salt bridge is formed between the C-terminal carboxylate of MtCM(which is repositioned upon MtDS binding) and loop residue Arg53,possibly bolstered by a newly formed hydrophobic interaction betweenLeu88 and Leu54 . The 1 μssimulations suggest that salt bridge formation with Arg53 occurs insolution in all tested cases, whereas the hydrophobic contact is lessimportant.MtCMactivation by MtDSinvolves a change in conformation of the C-terminus of MtCM and itsactive site H1–H2 loop.26 Conserved positions emerged only when probingfor an intact activation mechanism by MtDS.26 Still, when residues 87–90 of MtCMV were evolvedfrom Arg–Leu–Gly–His to Pro–Asp–Ala–Met.Our simulations indicate that in free wild-typeMtCM, an interactionof the C-terminal carboxylate with the key active site residue Arg46is possible but infrequent due to fluctuations 1. In conc pocket 5 and 2B,ket V in 7. In theδ subclass CM of M. tuberculosis to the evolutionary distinct AroHclass CMs, or even to the structurally and functionally divergentAroQα, AroQβ, and AroQγ subclasses.53 Neither of those groupsof CMs have evolved to be deliberately poor catalysts that becomeproficient upon regulatory interaction with a partner protein suchas MtDS.21 To be amenable to ‘inter-enzymeallosteric’ regulation,28 the H1–H2loop in MtCM must be malleable and allow for conformational switchingbetween a poorly and a highly active form. In contrast, this regionis rigidified in a catalytically competent conformation in the overwhelmingmajority of CMs from other subclasses. This is exemplified by theprototypic EcCM (AroQα subclass) and the secreted*MtCM (AroQγ), which possess the sequence 45PVRD48 and 66PIED69, respectively, at the positioncorresponding to the malleable H1–H2 loop sequence 52TRLV55 of wild-type MtCM.12 Remarkably, the two most impactful substitutionsT52P and V55D occurring during the evolution of MtCMV haveled to the tetrapeptide sequence 52PRLD55, with both Pro and Asp being conserved in naturallyhighly active CMs.12It is obviouslyimpossible to directly transfer our findings of critical detailedmolecular contacts from the AroQδ subclass CM from Corynebacterium glutamicum is another structurally well-characterized poorly active CM (kcat/Km = 110 M–1 s–1) that requires complex formationwith its cognate DAHP synthase for an impressive 180-fold boost incatalytic efficiency.54 In that case, inter-enzymeallosteric regulation involves a conformational change of a differentmalleable segment between helices H1 and H2. Thus, while the moleculardetails important for the activation of a particular AroQδ CM cannot be transferred directly from one system to another, ourfindings suggest as a general regulatory principle the deliberateand reversible destabilization of a catalytically critical loop conformation.The AroQM. tuberculosis with the top-performing MtCM variant MtCMV (kcat/Km = 4.3 × 105 M–1 s–1), which emerged from directed evolution experiments. Both in MtDS-activatedwild-type MtCM and in MtCMV, high activity correlated witha kinked H1–H2 loop conformation and an interaction of thisregion with the C-terminus of MtCM. The autonomously fully activevariant MtCMV had amino acid changes in both of these regionsthat augment these structural features. In this report, we focussedon substitutions T52P, V55D, and L88D.MDgreatly aided the analysis of crystal structures that were compromisedor biased by extensive crystal contacts at the most interesting structuralsites. Our aim was to obtain insight into the crucial factors underlyingCM activity by comparing the structure and dynamics of the poorlyactive wild-type MtCM  are responsible for binding and rearranging the doubly negativelycharged substrate chorismate. Only one of these residues (Arg35) isfirmly in position before the substrate enters the active site. Ofcritical importance for catalysis is Arg46. During the MD simulations,Arg46 competes with another arginine residue (Arg53) for binding tothe C-terminal carboxylate 6A and adof Arg46 7,explaiV, namely, T52P, V55D, and L88D by investigating singlevariants as well as combinations with other residue replacements thatwere found to augment catalysis. The variants were characterized bycrystallography, MD simulations, and enzyme kinetics. The two residuesPro52 and Asp55 exert a major impact by prestabilization and preorganizationof catalytically competent conformations of active site residues,while Asp88 contributes to fine-tuning and optimizing the catalyticprocess. By expanding on the previous directed evolution studies,we have shown here how the accumulated set of amino acid substitutionsfound in MtCMV has resulted in an activity level matchingthat of the most active CMs known to date.12In summary, we tested our hypotheses on the specificimportanceof critical substitutions acquired during the directed evolution ofMtCM


Delta) of its spike glycoprotein, which bindsto the peptidase domain (PD) of angiotensin-converting enzyme 2 (ACE2)receptors in host cells. The RBD–PD interaction has been targetedby antibodies and nanobodies to prevent viral infection, but theireffectiveness against the Delta variant remains unclear. Here, weinvestigated RBDDelta–PD interactions in the presenceand absence of nanobodies H11-H4, H11-D4, and Ty1 by performing 21.8μs of all-atom molecular dynamics simulations. Unbiased simulationsrevealed that Delta variant mutations strengthen RBD binding to ACE2by increasing the hydrophobic interactions and salt bridge formation,but weaken interactions with H11-H4, H11-D4, and Ty1. Among thesenanobodies H11-H4 and H11-D4 bind RBD without overlapping ACE2. Theywere unable to dislocate ACE2 from RBDDelta when boundside by side with ACE2 on RBD. Steered molecular dynamics simulationsat comparable loading rates to high-speed atomic force microscopy(AFM) experiments estimated lower rupture forces of the nanobodiesfrom RBDDelta compared to ACE2. Our results suggest thatexisting nanobodies are less effective to inhibit RBDDelta–PD interactions and a new generation of nanobodies is neededto neutralize the Delta variant.The Delta variantspreads more rapidly than previous variants ofSARS-CoV-2. This variant comprises several mutations on the receptor-bindingdomain (RBD Thus, it remains to be explored how this mutationaffects the binding strength. A recent in vitro and in silico study32 estimated thatthe S protein of the Delta variant of SARS-CoV-2 binds to ACE2 withsimilar strength compared to WT and weaker than the Alpha variant.Considering that Delta became more dominant than the Alpha variant,it is also critical to investigate how these novel mutations affectthe effectiveness of antibodies and nanobodies to prevent S–ACE2interactions.In our recent study, we performed extensive molecular dynamics(MD) simulations of the nanobodies H11-H4, H11-D4, and Ty1 in complexwith WT, Alpha, and Beta variants of the RBD of SARS-CoV-2 S protein.Delta) in complex with eitherthe peptidase domain (PD) of human ACE2 or nanobodies H11-H4, H11-D4,and Ty1. ACE2-bound H11-H4 and H11-D4 do not sterically overlap withthe RBD–ACE2 binding site, while Ty1 sterically overlaps withACE2. Thus, we also simulated RBDDelta in complex withboth ACE2 and either H11-H4 or H11-D4. These nanobodies were not ableto dislocate ACE2 from RBDDelta upon binding, indicatinglower neutralizing activity against this variant. In addition, wesimulated the detachment of the nanobodies from RBD at loading ratesdirectly comparable to high-speed atomic force microscopy (AFM) studies.34 Our simulations totaling 21.8 μs in lengthshow that the Delta variant mutations increase the binding strengthof RBDDelta to ACE2 while reducing the binding strengthof the nanobodies to RBDDelta.To explore the effect of Delta variant mutationson neutralizingnanobodies, we performed all-atom MD simulations of the RBD of S proteinof the Delta variant  simulations,each system was solvated in a water box (using the TIP3P water model)with a 25 Å cushion in each direction (50 Å water cushionbetween the protein complexes and their periodic images). For steeredMD39 (SMD) simulations, systems were solvatedhaving a 50 Å cushion along the pulling direction to create enoughspace for unbinding simulations and a 15 Å cushion in all otherdirections. Ions were added to neutralize the system and NaCl concentrationwas set to 150 mM. The size of solvated systems was ∼150,000,∼120,000, and ∼280,000 atoms for cMD, SMD, and RBDDelta–PD–nanobody simulations, respectively.All system preparation steps were performed in VMD.The structureof SARS-CoV-2 S protein RBD bound with ACE2 at 2.45 Å resolution(PDB ID: 6M0J) was use40 using the CHARMM3641 force field witha time step of 2 fs. Using the Langevin Nosé–Hoovermethod with an oscillation period of 100 fs and a damping time scaleof 50 fs, the pressure was maintained at 1 atm. Using Langevin dynamicswith a damping coefficient of 1 ps–1, the temperaturewas kept at 310 K. For van der Waals interactions, a 12 Å cutoffdistance was used. To calculate long-range electrostatic interactions,the particle-mesh Ewald method was used. In all simulations, periodicboundary conditions were applied. First, each system was minimizedfor 10,000 steps and subsequently equilibrated for 2 ns by keepingthe protein fixed. A second minimization–equilibration cyclewas performed: the complete system was minimized for additional 10,000steps without fixing the protein, followed by 4 ns of equilibrationby applying harmonic constraints on Cα atoms. Asa final step before production runs, the constraints were releasedand the system was equilibrated for additional 4 ns, during whichthe root-mean-square deviation (RMSD) values converged. These simulationsare expected to account for the structural differences due to theradically different thermodynamic conditions of crystallization solutionsand MD simulations.42 After the final equilibrationstep, each simulation (Table S1) was runfor 400 ns length to determine interactions between proteins. MD simulationswere performed in Longhorn, Expanse, and Stampede2 using a total of∼9 million core-hours.All MD simulations were performedunder N, P, and T conditions in NAMD 2.14Delta and PDof human ACE2. For salt bridge formation, a cutoff distance of 6 Åbetween the basic nitrogen and acidic oxygen was used.44 For hydrogen bond formation, a cutoff distance of 3.5 Å betweenhydrogen bond donor and acceptor and a 30° angle between thehydrogen atom, the donor heavy atom, and the acceptor heavy atom wereused.45 Interaction pairs that did not satisfy theangle criterion but satisfied the distance criterion was classifiedas electrostatic interactions. For hydrophobic interactions, a cutoffdistance of 8 Å between the side-chain carbon atoms was used.48 Observation frequencies were classified as high and moderate forinteractions that occur in 49% and above and between 15 and 48% ofthe total trajectory, respectively.49 All reportedchanges in interactions frequency classifications due to the Deltamutations were statistically different from that of the RBD of WTSARS-CoV-2 S protein (RBDWT ) .49 Pairwise interactions with observation frequencies below 15% wereexcluded from further analysis.Using MD simulationtrajectories, we determined salt bridges, hydrogen bonds, and electrostaticand hydrophobic interactions between the RBDα atoms at the nanobody–RBD and RBD–ACE2interface (Table S2). The vector pointingfrom the center of mass of fixed atoms to the center of mass of steeredatoms was selected as a pulling direction . Each SMD simulation was performed until the rupture eventis observed for the nanobody. Four different starting conformations were taken from each cMD simulationto perform SMD.Steered and fixed atoms were selectedas the CWT in complex withthe PD of human ACE2.49 To determine howRBDDelta interacts with PD, we performed MD simulationsof the RBDDelta–PD complex. L452R and T478K mutationswere manually introduced to the RBDWT structure (PDB ID: 6M0J)33 to obtain the RBDDelta structure. Two sets ofcMD simulations, each of 400 ns in length (Table S1), were performed to determine the salt bridges, hydrogenbonds, and electrostatic and hydrophobic interactions . Two setsof cMD simulations were combined and observation frequencies werereported based on this 800 ns long trajectory. We detected one newsalt bridge (R403-E37), four new hydrophobic , and two new electrostatic interactionsat high frequencies in the RBDDelta–PD complex comparedto RBDWT (WT–PD were observedin moderate frequencies in the RBDDelta–PD complex(Delta–PD complex (Table S3). Three hydrogen bond interactions observed withmoderate frequencies for RBDWT  were either observed at low frequencies or completely disappearedin RBDDelta. For each system, observation frequencies ofhydrogen bonds and electrostatic interactions differed moderatelybetween two sets of simulations, but similar frequencies were detectedfor most hydrophobic interaction and salt bridge formations (Table S4).In ourprevious study, we determined the interaction network between RBD–PDby performing MD simulations of the RBDions see , and then length S1, were n length S1, were WT, we divided the RBD–ACE2 interactionsurface into three contact regions (CR1–3) and proposed thatthe RBD–ACE2 interaction is primarily stabilized by hydrophobicinteractions in CR1.50 Due to the Delta variant mutations,CR1 gains two additional hydrophobic interactions (A475-Y83 and Y489-T27),while CR2 remains unaffected. Remarkably, CR3 gains one salt bridge(R403-E37) and two hydrophobic interactions (V503-T324 and Y505-F356)while losing three hydrogen bonds with PD. In our previous study,49 we highlightedthe role of CR1 in anchoring ACE2 and the importance of blocking itssurface for S protein inhibition. Because CR3 also forms an extensiveinteraction network in the Delta variant, it may also be criticalto target CR3 to prevent S–ACE2 interactions in the Delta variant.For RBDDelta with nanobodies, we introduced Delta variant mutationsto the co-structures of RBD in complex with H11-H4,9 H11-D4,9 and Ty1.2 For each RBDDelta–nanobodycomplex, two sets of cMD simulations, each of 400 ns length (Table S1), were performed to determine pairwiseinteractions. Although H11-H4 and H11-D4 stayed bound to RBDDelta in a binding mode throughout the simulations, Ty1 was observed toleave its original binding mode in one of the simulations (∼100ns into the simulation) and sampled various binding modes within 400ns . Thus, the interaction network for Ty1 is reported basedon a single trajectory where it kept its original binding mode, whileboth trajectories are used for H11-H4 and H11-D4 (S2 and Table S3).To investigate the interactions of the RBDWT and RBDDelta shows that two hydrogen bonds(Y449-H100 and F490-Y104) and one hydrophobic interaction (L452-V102)disappeared upon Delta mutations (Table S3). In addition,we detected one new hydrogen bond (Q493-Y101), two new hydrophobic(A475-Y104 and V483-A58) and two new electrostatic interactions atmoderate frequencies (Table S3).A comparison of H11-H4’s high-frequency interactionswithRBDutations 1. While Delta . One high-frequency hydrogen bond (Q493-S104) was observed in moderatefrequency. However, we detected six new electrostatic interactionsat moderate frequencies  and two of its hydrophobic interactions (L452-V102and L455-L105) either completely disappeared  or were observed at a lower frequency (E484-S57 andS494-V102) with RBDquencies 1, while Delta was observed, two of its hydrogen bonds (V483-V34and S494-S107) and 11 of its hydrophobic interactions  either completely disappeared orwere observed at low frequency (Table S3). Onehydrogen bond (E484-N56) and six electrostatic interactions observedwith moderate frequencies completely disappeared. For the second setof Ty1-RBDDelta MD simulation, a stable binding was notobserved, and all interactions observed between Ty1 and RBDWT completely disappeared.For Ty1 nanobody, based on the single trajectorywhere bindingto RBDrequency 1. We detrequency 1. Thus, requency 1. In addDelta–PD interactions, we performed threesets of 400 ns cMD simulations of each RBDDelta–PD–nanobodycomplex (Table S1). Nanobodies were manuallydocked onto the complex . In addition, H11-H4 was dislocatedfrom its RBD binding pose in all three simulations (Movie S2) due to the repulsion of identically charged residuesof ACE2 and H11-H4  using t ID: 6M0J and 6YZ5 ID: 6M0J). Althouulations 4 and S4.Delta nor considerably affect its interaction with RBDDelta. However, H11-D4 remained bound to RBDDelta in the presence of PD, probably because it forms salt bridges R103-E35,R103-D38, and D108-K31 with ACE2 , while H11-H4 has a serine at position 103 and is unable to formthese salt bridges. Collectively, these results suggest substantiallyreduced nanobody effectiveness against the Delta variant.Similar to H11-H4, H11-D4 wasneither able to dislocate ACE2 fromRBDDelta, we performedSMD simulations at loading rates (a springconstant of 10 pN/Å and a pulling velocity of 0.1 Å/ns)comparable to those used in high-speed AFM experiments.34 SMD simulations were performed by pulling thenanobodies at constant velocity along a vector pointing away fromthe binding interface . To bein accord with SMD studies on WT, Alpha, and Beta variants,29 RBDDelta was pulled away from ACE2to estimate ACE2’s binding strength to RBDDelta.Eight SMD simulations were performed for each system and their ruptureforces were recorded (S6). The average rupture forceswere reduced by 5, 19, and 32% for H11-H4, H11-D4, and Ty1, respectively,when compared to ACE2. In comparison, we previously reported thatH11-H4 has a higher binding strength for RBDWT, while H11-D4and Ty1 have a slightly lower binding strength than that of ACE2.Collectively, our in silico pulling experiments indicatethat nanobodies are not able to bind stronger to the RBDDelta compared to ACE2, and they also suggest that especially for H11-H4there is a strong tendency for the binding strengths to decrease relativeto ACE2.To estimate the bindingstrength of ACE2 and nanobodies to RBDrecorded 5 and S6.Delta–PD interactions. Toestimate rupture forces of the nanobodies and ACE2 from RBDDelta, we also performed SMD simulations at loading rates (1 pN/ns) comparableto high-speed AFM studies, which are ∼4–5 orders ofmagnitude lower than generally applied loading rates in SMD simulation.Thus, our SMD simulations provide a unique set of rupture forces thatare directly comparable to experiments. Our simulations revealed thatthe Delta variant mutations lead to an increase in S–ACE2 interactionswhile decreasing the number of nanobody–S protein interactions.As a result, nanobodies H11-H4, H11-D4, and Ty1 have lower ruptureforces from RBDDelta. H11-H4 and H11-D4 remained stablybound to RBDDelta, but they were unable to abrogate ACE2binding when bound side by side on RBDDelta. In comparison,Ty1 exhibited floppy binding in one of the two simulations. Collectively,our results show the importance of identifying nanobodies for neutralizingspecific variants of SARS-CoV-249 and highlight the requirementof designing novel nanobodies to effectively neutralize the Deltavariant.In this study, we performed an extensive setof cMD simulationsto investigate whether Delta variant mutations on the RBD of S proteinaffect its interactions with ACE2 and determined whether nanobodiesare able to disrupt RBD49 we had shownthat CR1 acts as the main anchor for SARS-CoV-2 S protein bindingto ACE2, which is mainly facilitated through 10 hydrophobic interactions.Close inspection of the rupture events under load also shows thatRBDWT performs a zipper-like detachment, with CR1 detachingat the last in 80% of the simulations. In the Delta variant, CR1 formstwo extra hydrophobic interactions, whereas CR3 gains one salt bridgeand two hydrophobic interactions. CR1 detaches the last in five outof eight in silico pulling simulations, whereas CR3detaches either the last or at the same time with CR1 in other simulations.This difference may be attributed to an increase in the number ofpairwise interactions in CR3. Therefore, it may be critical to targetboth CR1 and CR3 to effectively inhibit S–ACE2 interactionsof the Delta variant.In our previous study,in silico strategyto predict the effectiveness of nanobodies to inhibit variant SARS-CoV-2S protein’s RBDs, which may guide the design of novel nanobodiesthat can target specific SARS-CoV-2 variants. Well-established andproven in silico techniques, cMD and SMD simulations,are used to explore the binding strength of the nanobodies to RBD,and whether nanobody binding to RBD displaces ACE2 from RBD. The ruptureforce of RBDWT from ACE2 was measured by AFM51 at loading rates of 5–6 orders smallerthan those applied in our SMD simulations. This study reported ruptureforces ranging from 70 to 105 pN. Although we applied loading rates5–6 orders of magnitude larger than these experiments, we reportedrupture forces with the same order of magnitude. Future experimentalstudies are needed to investigate how Delta mutations affect the RBDbinding strength of H11-H4, H11-D4, and Ty1 nanobodies.This manuscript presents a robust


HSPB1 are known to cause Charcot-Marie-Tooth disease type 2F (CMT2F) and distal hereditary motor neuropathy (dHMN). In this study, we presented three patients with mutation in HSPB1 who were diagnosed with dHMN. Proband 1 was a 14-year-old male with progressive bilateral lower limb weakness and walking difficulty for four years. Proband 2 was a 65-year-old male with chronic lower limb weakness and restless legs syndrome from the age of 51. Proband 3 was a 50-year-old female with progressive weakness, lower limbs atrophy from the age of 44. The nerve conduction studies (NCS) suggested axonal degeneration of the peripheral motor nerves and needle electromyography (EMG) revealed chronic neurogenic changes in probands. Open sural nerve biopsy for proband 2 and the mother of proband 1 showed mild to moderate loss of myelinated nerve fibers with some nerve fiber regeneration. A novel p.V97L in HSPB1 was identified in proband 3, the other two variants (p.P182A and p.R127W) in HSPB1 have been reported previously. The functional studies showed that expressing mutant p.V97L HSPB1 in SH-SY5Y cells displayed a decreased cell activity and increased apoptosis under stress condition. Our study expands the clinical phenotypic spectrum and etiological spectrum of HSPB1 mutation.Mutations in  HSPB1 on chromosome 7 were first associated with CMT2F and dHMN [HSPB1 have been found in patients with CMT2F and dHMN. Most of them are missense mutations, while a few are nonsense mutations or frameshift mutations [HSPB1 mutation are mostly autosomal dominant (AD). In 2008, Houlden, H., et al. first reported CMT2F inherited in the way of autosomal recessive (AR) (p.L99M) [HSPB1 gene mutation have certain heterogeneity in symptoms and onset age [HSPB1 mutations have been found in seven unrelated patients with sporadic amyotrophic lateral sclerosis (ALS); among them, bulbar symptoms were relatively common (5/7), and cognitive impairment was found in two patients [HSPB1 constituted the most common cause of dHMN in various population with a frequency about 8~14.3% of clinical diagnostic dHMN [HSPB1 mutation account for about 4% clinical identified CMT2 patients [Mutant HSPB1 (heat shock protein family B member 1) can cause a group of length-dependent peripheral axonal neuropathy, including Charcot-Marie-Tooth disease type 2F (CMT2F) and distal hereditary motor neuropathy (dHMN). These two peripheral neuropathies are classified according to the presence or absence of sensory involvement. CMT2F has sensory symptom and (or) mild distal axonal sensory nerve degeneration in electrophysiology. In 2001, the pathogenic gene of CMT2F was identified on chromosome 7q11-q21 in a Russian family by linkage analysis [utations . The inhp.L99M) . In the (p.L99M) . The clinset age . Even innset age ,8. So fapatients ,9,10,11.9M . In ttic dHMN ,13,14. Apatients ,18,19,20HSPB1, also known as HSP27 (the protein molecular weight is 27KD), located on 7q11.2, is a member of the sHSP family. It is constituted by a highly conserved α-crystallin domain (ACD) and the N-terminus and C-terminus in flank of ACD. The ACD, which has 90 amino acids, is characteristic of sHSP family, while N-terminus and C-terminus evolved independently and thereby is distinct from other sHSP . HSPB1 iHSPB1 variations. c.C544G (p.P182A) and c.379C > T (p.R127W) have been reported in previous studies. c.G289C (p.V97L) is a novel variant and located in the α-crystallin domain. Through our study, we will provide new insights into the pathogenicity of the novel mutation and expand the clinical phenotypic spectrum and etiological spectrum of HSPB1 gene mutation.In this study, we present three dHMN patients with There are 3 hereditary peripheral neuropathy families from Shanghai Jiao Tong University Affiliated Sixth People’s Hospital in this study. Detailed clinical history collection and electrophysiological examination were carried in 3 probands. This study was approved by the hospital ethics committee and all participating members signed written informed consent.Sural nerve biopsy was performed on proband 2 (at the age of 59) and the mother (at the age of 45) of proband 1. Nerve tissue was fixed in 2.5% glutaraldehyde solution with pH 7.2 and 4 °C overnight, fixed with 1% osmium tetroxide buffer for 2 h and embedded in Epoxy 618 resin. Toluidine blue staining was performed on semithin sections (0.7–1.0 μm) and observed with transmission microscopy .The peripheral blood of probands and available family members in 3 families were collected for genetic analysis. A Qiagen kit  was used to extract DNA from peripheral blood. Whole exome sequencing (WES) was used for found pathogenic mutation and carried in the Illumina HiSeq 2000 platform . All results were confirmed with Sanger sequencing. The pathogenic of candidate variants was classified according to the American College of Medical Genetics and Genomics (ACMG) guidelines.2, and the medium was changed every two days. After reaching 80% confluence, the cells were split with 0.25% trypsin and sub-cultured for further passages.SH-SY5Y cells, human neuroblastoma cell line, were obtained from American type culture collection  and cultivated in DMEM  with 10% fetal bovine serum (FBS) and 1% penicillin–streptomycin in a humidified incubator at 37 °C with 5% CO® I Medium , mixed with an equal volume of Lipofectamine 3000 Reagent (5 μL) and incubated for 10–15 min at room temperature. The DNA–Lipofectamine complex was then added to SH-SY5Y cells and incubated for 24 or 48 h.Plasmid vector (PAcGFP-N1) carrying a full length of wild-type HSPB1 cDNA, was designed in our laboratory and constructed by manufacturer . V97L mutation was induced by using site-directed mutagenesis kit  to obtain a mutant HSPB1 vector with the same framework. SH-SY5Y cells were cultured in 96-well plates overnight and transfected with plasmid vector carrying p.V97L HSPB1 mutation or wild-type HSPB1 cDNA by Lipofectamine 3000 reagent , according to the manufacturer’s instructions. Briefly, mutant p.V97L HSPB1 vector (0.1 µg) was diluted in 5 μL of reduced-serum medium Opti-MEM2O2 (300 µM) for 24 h, the cells were incubated with CCK-8 solution (10 µL) for 2 h at 37 °C and the absorbance at 450 nm was read using a microplate reader . The assays were performed three times in triplicate for each group. For morphological analysis, SH-SY5Y were imaged with the Olympus microscope system  at 20× magnification.Cell viability was measured with the CCK-8 assay  using 96-well culture plates. Briefly, after transfection for 24 or 48 h and after being treated with H2O2 (300 µM) for 24 h. After treatment, the cells were fixed with 4% PFA for 30 min and washed with PBS 3 times followed by incubation in 0.3% Triton-X-100 PBS. After washing with PBS 3 times, SH-SY5Y were cultured with TUNEL solution  at 37 °C for 1 h in the dark, following the manufacturer’s instruction. All images were captured with a fluorescence microscope .SH-SY5Y cells were transfected with DNA–Lipofectamine complex for 48 h and treated with HAfter transfection and treatment, cultured cells were harvested and lysed in RIPA buffer supplemented with protease and phosphatase inhibitors on ice for 10 min and centrifuged at 12,000 rpm for 30 min at 4 °C. Supernatants were collected and the total protein concentration was evaluated using a BCA kit. Thereafter, an equal amount of protein (30 µg/well) was separated by sodium dodecyl sulphate-polyacrylamide gel electrophoresis (SDS-PAGE) and transferred to polyvinylidene fluoride (PVDF) membranes for 60 min at 250 mA. After membrane blocking with 5% non-fat milk, the membrane was incubated with primary antibodies  in TBS-T at 4 °C overnight followed by incubating with horseradish peroxidase (HRP)-conjugated immunoglobulin G (IgG) secondary antibodies . β-tubulin primary antibody  was used for normalization. The protein bands were detected using the ECL western blot detection system according to the manufacturer’s instruction. Digital images were analyzed using ImageJ gel analysis software to obtain the grey-scale value of signals.Proband 1: F1-III-3 A was a 1Nerve conduction studies (NCS) performed at age 13 showed reduced compound muscle action potential (CMAP) amplitude with normal motor nerve conductive velocity (MCV) in examined median, ulnar, tibial, and common peroneal nerve, the reductions of CMAP amplitude were more remarkable in the lower limb. The sensory nerve action potential (SNAP) amplitude and sensory nerve conduction velocity (SCV) were normal in all examined limbs. EMG showed spontaneous potential activities such as fibrillation wave and normal phase wave were observed in the distal of the limb. The MUP time limit was widened with unchanged amplitude, the polyphase wave was significantly increased. Some distal muscles showed simple phase in heavy contraction. Sural nerve biopsy of F1-II-2 A displayHSPB1 gene had been found in F1-III-3 (WES was used for pathogenic gene screening. A heterozygous c.C544G (NM_001540) on exon 3 of F1-III-3 B, resultProband 2: F2-II-7 C, a 65-yOn examination, no obvious muscle wasting was found in limb. Foot drop was observed in the bilateral without significant foot deformity. He had normal strength in the upper limbs and proximal lower limb, but reduced strength in the distal lower limb (MRC 4/5). Reflexes were absent at the ankles and knees, and diminished at the upper limb. The sensory examination was normal. No obvious abnormality was found in the cranial nerve. Pathological plantar reflex and ataxia were not found on examination. Mental psychological and cognitive tests were normal.NCS performed at the age of 59 showed significantly reduced CMAP amplitude in the bilateral common peroneal nerve and slightly reduced MCV in the right common peroneal nerve, and absent motor response in bilateral tibial nerve. The SNAP amplitude and SCV were normal in all limbs. EMG displayed fibrillation wave and positive sharp wave in the bilateral anterior tibial muscle and medial peroneal muscle, MUP showed prolonged duration with increased amplitude, polyphase wave increased, and recruitment potential reduced. According to the findings of the clinical history, examination and electrophysiology, the diagnosis of dHMN and restless legs syndrome (RLS) was established.HSPB1 gene were found in proband 2 (WES was used for pathogenic gene screening. A heterozygous missense mutation c.379C>T p.R127W) in roband 2 D. The va7W in robProband 3: F3-IV-1 E. This 5On examination, she had severe wasting of the distal lower limb I. There NCS showed significantly reduced CMAP amplitude with slow MCV in the common peroneal nerve, and an absence of motor response in the bilateral tibial nerve. The SNAP amplitude and SCV were normal in all limbs. EMG revealed chronic neurogenic impairments with some fibrillation potentials and positive sharp wave in upper and lower limb muscles, T8 paraspinal muscle, sternocleidomastoid muscles, rectus abdominis. Based on the findings of the clinical history, examination and electrophysiology, the diagnosis of dHMN was established.HSPB1 gene, a heterozygous change of c.G289C (p.V97L) on exon 1 of HSPB1 gene  for 24 h. We found that transfected with mutated HSPB1 or wild-type HSPB1 alone had little toxic effect on SH-SY5Y cells. However, the expression of mutant HSBP1 lowered the cell viability remarkably, especially at 48 h, compared to wild-type HSPB1 in H2O2-treated cells (2O2 (300 µM) incubation for 24 h were used in subsequent experiments.To study the pathogenicity of HSPB1-p. V97L mutation, we investigated the effect of this novel mutation on cell survival using CCK-8 cell viability assay. SH-SY5Y cells were transiently transfected with plasmid vector expressing green fluorescent protein (GFP)-tagged p. V97L mutant HSPB1 or wild-type for 24 h or 48 h and then incubated with Hed cells A. Thus, 2O2-induced morphological changes. As shown in 2O2, cell connections disappeared and cell shrinkage appeared in mutant HSBP1 and wild-type HSPB1 group. Moreover, the number of cells in mutant HSBP1 group were significantly lower than that in the wild-type HSPB1 group. The above observations indicated that p.V97L mutant HSPB1 could exert neurotoxicity on H2O2-treated SH-SY5Y cells.The inverted phase-contrast microscope was used to further evaluate the effects of mutated HSPB1 and wild-type HSPB1 on H2O2, TUNEL stained cells were observed much more in the mutant HSBP1 group than in the wild-type HSPB1 group. The expression levels of apoptotic markers were further investigated to see if mutant HSPB1 reduced cell viability through apoptosis. After treating with H2O2 for 24 h, the expression levels of apoptosis-related protein including bcl2, bax, and caspase-3 in SH-SY5Y cells 48 h after transfection with HSPB1-p. V97L and wild-type HSPB1 were quantified using Western blot. Results showed that the expression of pro-apoptotic proteins bax and caspase-3 were dramatically upregulated, while the expression of anti-apoptotic protein bcl2 was significantly downregulated in SH-SY5Y cells transfected with mutant HSPB1, compared with those cells transfected with wild-type HSPB1, suggesting that HSPB1-p.V97L mutation induced the cell death via apoptosis  involvement presenting with spastic paraplegia, hyperreflexia, pyramidal signs, even ALS-like phenotype, were continuously reported. It is worth noting that patients with the same mutation can have different types of affected neurons. For example, patients carried the p.R127W of HSPB1 can manifest as axonal peripheral neuropathy, but also ALS in some. Pathogenic mutations of three probands reported here are located on three exons of HSPB1. The clinical manifestations are not only dominated by lower limb weakness as a common feature, but also presented exclusive characteristics: case 1 had an early onset age, case 2 was accompanied with RLS, case 3 had multiple muscle groups involved in EMG.In this study we present three distal axonal peripheral neuropathy families who carried heterozygous mutation in malities .Althoughmalities . Some paThe first proband had an early onset age and harbored the p.P182A mutation, which was located in the variable C-terminal domain and which has already been well descried in patients with dHMN or CMT2 ,33. The HSPB1 [The second proband with dHMN carried the p.R127W mutation, which located in the conserved ACD and has already been well described in patients with dHMN or CMT2 ,36. AnotHSPB1 . FurtherHSPB1 ,39. We sHSPB1 .HSPB1 missense mutation (p.V97L), which has not been reported previously, and was located in the highly conserved ACD. The variant was not present in gnomAD, 1000 Genome Project database and ExAC database. It was predicted to be pathogenic using in silico tools including PolyPhen2 and Mutationtaster whilst neutral in SIFT. The proband 2 had an asymptomatic younger female cousin carrying the p.V97L mutation. One possible reason is that the cousin was under the age of onset; the other is incomplete penetrance of the mutation. Therefore, the follow-up study in this pedigree will be important. An adjacent variant (p.L99M) of p.V97L was reported in a consanguineous Pakistani family who was diagnosed with dHMN and presented AR inheritance [HSPB1 mutation. The cascade reaction induced by oxidative stress has been well-described in other variants; Kalmar et al. observed decreased mitochondrial complex I activity, increased superoxide, impaired mitochondrial glutathione levels, and increased nitrotyrosine expression in S135F mutant mouse motor neurons in response to antimycin A treatment [2O2 stimulation, these findings were in accord with the results of cell viability assay and indicated that the mutation induced cell death via apoptosis. Elevated apoptosis has also been seen in other HSPB1 mutations (p.T139M) [The third proband was diagnosed with dHMN; she carried eritance . Mechanieritance . The funreatment . In addireatment . To furttion p.V9L, which p.T139M) . Similarp.T139M) . The posp.T139M) . Of noteHSPB1 mutation in three patients and describes a novel p.V97L mutation of HSPB1. Functional studies showed that reduced viability and increased apoptosis in cells carrying p.V97L mutation may contribute to pathogenesis.In sum, this study reported heterogeneous clinical phenotypes of dHMN caused by