Journal: bioRxiv

Article Title: Population-scale immunoglobulin genetics resolves the human B-cell system

doi: 10.64898/2026.03.30.715216

Figure Lengend Snippet: (A) Effect-size heatmaps for allelic series at TNFRSF13B (TACI) and TNFSF13 (APRIL). Left : effects across Ig traits. Right : plasma pQTLs related to TACI–APRIL signaling and B-cell subpopulation markers. FCRL2 marks unswitched memory B cells, with elevated levels concordant with accumulation of unswitched memory B cells observed by flow cytometry ( Figure S5D,E ). TNFRSF17, IL5RA, MZB1, and FCRL5 reflect mature B-cell and plasma-cell pool size . (B) TNFRSF13B (TACI) locus showing the location of rs577044977 overlaid with ATAC-sequencing data for memory B cells and ChIP-seq data for BACH1 in GM12878 cells . rs577044977-C is predicted to increase binding of the BACH1 transcriptional repressor, consistent with reduced TNFRSF13B expression ( Figure S10A ). (C) TNFSF13 (APRIL) locus showing the location of rs187256434 overlaid with ATAC-sequencing and EGR1 CUT&RUN data for macrophages. The rare variant rs187256434-T overlaps an EGR1 binding site and is predicted to disrupt the EGR1 motif, consistent with reduced TNFSF13 protein levels in plasma pQTL data ( Table S5A ). (D) ELISA quantification of plasma APRIL in 793 blood donors stratified by rs3803800 genotype. The A allele is associated with increased APRIL, consistent with cis -pQTL effects in proteomics data ( Table S5A ). (E) ELISA quantification of plasma APRIL stratified by rs9907657 genotype showing no significant association (regression P = 0.99). (F) Luciferase reporter assays for rs187256434 alleles in the monocytic MOLM-13 cell line. The T allele shows reduced activity relative to the C allele. siRNA-mediated knockdown of EGR1 abolishes the allelic difference by selectively reducing C allele activity, supporting disruption of an EGR1 binding site by rs187256434-T.

Article Snippet: Optimal siRNA concentration was determined by serial dilution, and knockdown efficiency was evaluated using qPCR quantification of EGR1 mRNA (Thermo Scientific #4331182, assay id: Hs00152928_m1).

Techniques: Clinical Proteomics, Flow Cytometry, Sequencing, ChIP-sequencing, Binding Assay, Expressing, Variant Assay, Enzyme-linked Immunosorbent Assay, Luciferase, Activity Assay, Knockdown, Disruption

Journal: Frontiers in Immunology

Article Title: Myeloid EGR1 contributes to Th17/Treg imbalance during acute liver allograft rejection in a rat model

doi: 10.3389/fimmu.2026.1901189

Figure Lengend Snippet: Single-cell transcriptomic analysis of GSE285476 reveals immune-cell remodeling and preferential Egr1 expression in myeloid cells during acute liver allograft rejection. (A, B) Violin plots showing the distributions of the number of detected genes (nFeature_RNA) and total transcript counts (nCount_RNA) across the six individual samples following and prior to quality-control filtering, respectively. (C) Identification of highly variable genes used for downstream dimensionality reduction; red dots indicate the 3,000 selected variable features. (D) Principal component analysis (PCA) showing the distribution of cells from the six individual liver graft samples. (E) Genes with the largest contributions to the first four principal components (PC1–PC4). (F) Elbow plot showing the standard deviations of the principal components used to guide dimensionality selection. (G) UMAP visualization of unsupervised clustering, identifying 23 transcriptionally distinct cell clusters. (H) Heatmap showing representative marker-gene expression used for annotation of the major cell populations. (I) Relative cellular composition of the syngeneic and rejection groups, showing marked remodeling of the graft cellular landscape during rejection. (J) UMAP visualization showing the distribution of the seven major annotated cell populations in the syngeneic and rejection groups. (K) UMAP visualization of the seven major annotated cell populations, including hepatocytes, cholangiocytes, endothelial cells, fibroblasts, hepatic stellate cells, myeloid cells, and lymphoid cells (left), together with the distribution of Egr1 expression across the graft cellular landscape (right). (L) Dot plot showing the expression of representative stress-responsive and immediate-early genes (Fos, Fosb, Jun, Junb, Jund, Atf3, Egr1, Dusp1, and Ier3) across the major cell populations. Dot size represents the percentage of cells expressing each gene, and color intensity represents average scaled expression. Stress-responsive genes were broadly distributed across multiple cell types, whereas Egr1 showed more prominent expression in myeloid than in lymphoid cells. (M) Comparison of dissociation stress scores between the syngeneic and rejection groups. No significant difference was observed between the two groups (P = 0.10).

Article Snippet: After blocking, the membranes were incubated with primary antibodies against EGR1 (1:10,000, Novus Biologicals) and GAPDH (1:10,000, Sigma, USA), followed by peroxidase-conjugated secondary antibodies.

Techniques: Single Cell, Analysis, Immune Cell, Expressing, QC/EQA/Proficiency, Selection, Marker, Gene Expression, Comparison

Journal: Frontiers in Immunology

Article Title: Myeloid EGR1 contributes to Th17/Treg imbalance during acute liver allograft rejection in a rat model

doi: 10.3389/fimmu.2026.1901189

Figure Lengend Snippet: Temporal expression profile of EGR1 in liver grafts post-transplantation. (A) Representative immunohistochemistry (IHC) images and quantification of EGR1-positive cells per field in liver tissues from the Sham, Syngraft, and Allograft groups at 6 h, 12 h, 24 h, 5 d, and 10 d post-operation. Quantification was performed by counting EGR1-positive cells per field. Scale bars = 50 μm. (B) Relative mRNA expression levels of Egr1 in liver grafts determined by RT-qPCR. (C) EGR1 protein concentrations in the respective groups. (D) Representative Western blot images (left) and densitometric quantification (right) of EGR1 protein expression in liver grafts at indicated time points. Data are presented as mean ± SD (n = 3 per group). *p < 0.05, **p < 0.01, ***p < 0.001; ns, no significance. Allo, allograft; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; IHC, immunohistochemistry; RT-qPCR, reverse transcription quantitative polymerase chain reaction; Syn, syngraft.

Article Snippet: After blocking, the membranes were incubated with primary antibodies against EGR1 (1:10,000, Novus Biologicals) and GAPDH (1:10,000, Sigma, USA), followed by peroxidase-conjugated secondary antibodies.

Techniques: Expressing, Transplantation Assay, Immunohistochemistry, Counting, Quantitative RT-PCR, Western Blot, Reverse Transcription, Real-time Polymerase Chain Reaction

Journal: Frontiers in Immunology

Article Title: Myeloid EGR1 contributes to Th17/Treg imbalance during acute liver allograft rejection in a rat model

doi: 10.3389/fimmu.2026.1901189

Figure Lengend Snippet: Virtual knockout analysis of Egr1 reveals immune-related regulatory perturbations in graft myeloid cells. (A) Proportion of significant and non-significant differentially regulated genes following virtual Egr1 knockout. Approximately 0.2% of the analyzed genes met the significance criterion. (B) Top five virtual-KO perturbed genes ranked according to the differential-regulation fold change (FC) relative to the expected network-perturbation level. S100a6, S100a4, MGC105649, Anxa2, and Lsp1 showed the strongest perturbation signals. (C) Differential-regulation plot showing the Z-score and −log10-adjusted P value for individual genes following virtual Egr1 knockout. Genes with prominent perturbation signals are labeled. (D, E) Correlation between S100a6 and Egr1 expression in myeloid cells from the day-7 syngeneic (D) and rejection (E) groups. S100a6 was weakly negatively correlated with Egr1 in both groups (syngeneic: R = −0.22, P < 2.2 × 10 - ¹ 6 ; rejection: R = −0.11, P < 2.2 × 10 - ¹ 6 ). Each point represents an individual myeloid cell, and the red line indicates the fitted trend. (F) Gene Ontology enrichment analysis of significant virtual-KO perturbed genes, showing representative Biological Process (BP), Cellular Component (CC), and Molecular Function (MF) terms. (G) Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of significant virtual-KO perturbed genes, highlighting pathways related to complement and coagulation cascades, cell adhesion, phagocytosis, hematopoietic cell lineage, NF-κB signaling, and efferocytosis. DR, differential regulation; FC, fold change relative to the expected differential-regulation distance; GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes.

Article Snippet: After blocking, the membranes were incubated with primary antibodies against EGR1 (1:10,000, Novus Biologicals) and GAPDH (1:10,000, Sigma, USA), followed by peroxidase-conjugated secondary antibodies.

Techniques: Knock-Out, Analysis, Labeling, Expressing, Coagulation

Journal: Frontiers in Immunology

Article Title: Myeloid EGR1 contributes to Th17/Treg imbalance during acute liver allograft rejection in a rat model

doi: 10.3389/fimmu.2026.1901189

Figure Lengend Snippet: EGR1-expressing myeloid cells and T cell-associated immune responses in liver allografts during acute rejection. (A) Representative immunohistochemistry (IHC) images and quantitative analysis of CD86-positive area in liver grafts from the Sham and Allograft groups at indicated time points after transplantation. (B) Representative multiplex immunofluorescence (mIF) staining showing CD86 (green) and EGR1 (red) expression in liver grafts. DAPI (blue) was used for nuclear counterstaining. (C) Representative mIF staining of CD4 (green) and IL-17A (red) in syngraft and allograft liver tissues. (D) Representative mIF staining of CD4 (green) and FOXP3 (red) in syngraft and allograft liver tissues. Scale bars = 50μm. EGR1, early growth response 1; IHC, immunohistochemistry; mIF, multiplex immunofluorescence; DAPI, 4’,6-diamidino-2-phenylindole; FOXP3, forkhead box P3.

Article Snippet: After blocking, the membranes were incubated with primary antibodies against EGR1 (1:10,000, Novus Biologicals) and GAPDH (1:10,000, Sigma, USA), followed by peroxidase-conjugated secondary antibodies.

Techniques: Expressing, Immunohistochemistry, Analysis, Transplantation Assay, Multiplex Assay, Immunofluorescence, Staining

Journal: Frontiers in Immunology

Article Title: Myeloid EGR1 contributes to Th17/Treg imbalance during acute liver allograft rejection in a rat model

doi: 10.3389/fimmu.2026.1901189

Figure Lengend Snippet: EGR1-overexpressing BMDCs promote CD4 + T-cell proliferation and alter Th17/Treg differentiation in vitro . (A) Flow cytometry analysis and quantification of the surface maturation markers CD80, CD86, and MHC-II on bone marrow-derived dendritic cells (BMDCs) treated with PBS or LPS. (B) Western blot analysis (left) and quantification (right) verifying EGR1 overexpression (EGR1-OE) in BMDCs and its suppression by an EGR1 inhibitor (OE + Inh). (C) ELISA quantification of pro-inflammatory cytokines (TNF-α, IL-6, IL-12) and the anti-inflammatory cytokine (IL-10) in the BMDC culture supernatants. (D) CD4 + T cell proliferation assessed by EdU incorporation assay following co-culture with negative control (NC) or EGR1-overexpressing BMDCs. (E) Flow cytometry analysis of intracellular cytokines and transcription factors in co-cultured CD4 + T cells. Representative dot plots (left) and statistical quantification (right) showing the proportions of pro-inflammatory Th17 cells (CD4 + IL-17A + FOXP3 - ) and immunosuppressive Tregs (CD4 + FOXP3 + IL-17A - ) in the NC and EGR1 groups. The gating strategy is shown in . Data are presented as mean ± SEM of three independent experiments. * p < 0.05, *** p < 0.001. EGR1, early growth response 1; BMDC, bone marrow-derived dendritic cell; LPS, lipopolysaccharide; OE, overexpression; Inh, inhibitor; ELISA, enzyme-linked immunosorbent assay; EdU, 5-ethynyl-2’-deoxyuridine; MFI, mean fluorescence intensity; Treg, regulatory T cell; Th17, T helper 17 cell; FOXP3, forkhead box P3; IL-17, interleukin-17.

Article Snippet: After blocking, the membranes were incubated with primary antibodies against EGR1 (1:10,000, Novus Biologicals) and GAPDH (1:10,000, Sigma, USA), followed by peroxidase-conjugated secondary antibodies.

Techniques: In Vitro, Flow Cytometry, Analysis, Derivative Assay, Western Blot, Over Expression, Enzyme-linked Immunosorbent Assay, EdU Assay, Co-culture Assay, Negative Control, Cell Culture, Fluorescence

Journal: Neurotherapeutics

Article Title: The EGR1/ZFP36 axis governs glycosphingolipid metabolic reprogramming in monocyte-derived macrophages in guillain-barré syndrome

doi: 10.1016/j.neurot.2026.e00895

Figure Lengend Snippet: Analysis of differentially expressed genes in the peripheral blood immune cell profile and disease-characteristic monocyte subsets of GBS patients. (a–b) Types and proportions of immune cells in the peripheral blood of GBS patients compared to healthy controls. The proportion of CD14 + monocytes was significantly increased in GBS patients. ( c –d) Types and proportions of monocyte subsets in the peripheral blood of GBS patients compared to healthy controls. CD163 + and IL1R2 + monocyte subsets were enriched in GBS patients. (e) Volcano plot of the top 5 (IL1R2, FKBP5, CD163, SAP30, and CXCR4) upregulated and top 5 (EGR1, FOSB, KLF4, CXCL8, and CCL3) downregulated differentially expressed genes in IL1R2 + monocytes from GBS patients' peripheral blood. (f) Top 20 B P enriched by GO analysis of differentially expressed genes in IL1R2 + monocytes. (g) PPI network of differentially expressed genes in IL1R2 + monocytes ranked by node score.

Article Snippet: Lentiviral vectors for EGR1 overexpression, EGR1 knockdown (sh-EGR1), and corresponding controls were constructed by GeneChem (Shanghai, China).

Techniques:

Journal: Neurotherapeutics

Article Title: The EGR1/ZFP36 axis governs glycosphingolipid metabolic reprogramming in monocyte-derived macrophages in guillain-barré syndrome

doi: 10.1016/j.neurot.2026.e00895

Figure Lengend Snippet: Analysis of DEGs in sciatic nerve transcriptome data of EAN rats. (a) Volcano plot of DEGs during the peak period of sciatic nerve in EAN rats and the top 5 DEGs with the lowest P -value. Egr1 was a significantly downregulated gene. (b) Heatmap of the expression levels of the top 5 upregulated and downregulated genes during the peak period of sciatic nerve in EAN rats in various samples, showing consistent downregulation of Cyp2c11 and Egr1 across all EAN samples. (c) Immunoinfiltration analysis of sciatic nerve ssGSEA in EAN rats, revealing significantly elevated infiltration of monocyte lineage cells. (d) Intersection Venn diagram of DEGs in GBS peripheral blood monocytes and EAN sciatic nerve, identifying 14 common genes. (e) The correlation between 14 DEGs in the sciatic nerve of EAN rats and infiltrating immune cells demonstrates that EGR1, FOS, ZFP36, and FOSB were negatively correlated with monocyte-macrophage infiltration.

Article Snippet: Lentiviral vectors for EGR1 overexpression, EGR1 knockdown (sh-EGR1), and corresponding controls were constructed by GeneChem (Shanghai, China).

Techniques: Expressing

Journal: Neurotherapeutics

Article Title: The EGR1/ZFP36 axis governs glycosphingolipid metabolic reprogramming in monocyte-derived macrophages in guillain-barré syndrome

doi: 10.1016/j.neurot.2026.e00895

Figure Lengend Snippet: The expression levels of EGR1 and ZFP36 in GBS patients, monocyte-derived macrophages, and EAN. (a) The level of EGR1 in the cerebrospinal fluid of normal (n = 25) and GBS patients (n = 48). EGR1 was significantly downregulated in GBS patients. (b) ROC curve of diagnostic efficacy of EGR1 level in cerebrospinal fluid for GBS (AUC = 0.921). ( c –d) qRT-PCR was employed to quantify the mRNA expression levels of iNOS, CD86, Arg1, CD163, EGR1, and ZFP36 in M0, M1, and M2 monocyte-derived macrophages (n = 3). EGR1 and ZFP36 were downregulated in M1 macrophages but upregulated in M2 macrophages. (e) WB was performed to analyze the protein expression of EGR1 and ZFP36 in M0 and M1 macrophages, confirming reduced expression in M1 macrophages (n = 3). (f) Immunofluorescence was employed to assess the expression and localization of EGR1 and ZFP36 in M1 macrophages, showing cytoplasmic localization and reduced fluorescence intensity (n = 3). (g–h) The expression levels of EGR1 and ZFP36 in M1 macrophages from the peripheral blood of EAN rats were confirmed by qRT-qPCR and WB analyses, further confirming their downregulation (n = 3). Data are presented as mean ± SD. ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001 vs HC/M0/Con group.

Article Snippet: Lentiviral vectors for EGR1 overexpression, EGR1 knockdown (sh-EGR1), and corresponding controls were constructed by GeneChem (Shanghai, China).

Techniques: Expressing, Derivative Assay, Diagnostic Assay, Quantitative RT-PCR, Immunofluorescence, Fluorescence

Journal: Neurotherapeutics

Article Title: The EGR1/ZFP36 axis governs glycosphingolipid metabolic reprogramming in monocyte-derived macrophages in guillain-barré syndrome

doi: 10.1016/j.neurot.2026.e00895

Figure Lengend Snippet: EGR1 specifically binds to ZFP36 and activates its transcription. (a) Venn diagram of the intersection between EGR1 downstream binding targets predicted based on four datasets from the TFBS database and DEGs of IL1R2 + monocytes in GBS, identifying ZFP36 and THBS1 as common targets. (b) WB detection of ZFP36 expression in M0 macrophages after overexpression and knockdown of EGR1, showing that EGR1 positively regulates ZFP36 expression (n = 3). (c) Schematic diagram showing the binding between EGR1 and ZFP36 promoter. (d). Enrichment of EGR1 binding to ZFP36 promoter was detected in M0 macrophages by ChIP-qPCR analysis, confirming specific binding of EGR1 to the ZFP36 promoter (n = 3). (e) M0 macrophages were co-transfected with ZFP36-WT or ZFP36-MUT reporter plasmids and OE-EGR1 or OE-NC plasmids; subsequently, luciferase reporter assays were performed to evaluate EGR1-mediated regulation of the ZFP36 promoter, demonstrating that EGR1 activates ZFP36 transcription through direct promoter binding (n = 3). Data are presented as mean ± SD. ∗∗∗ p < 0.001 vs ctrl/sh-NC/PMA/PMA + OE-EGR1/OE-NC + ZFP36-WT/OE-EGR1+ZFP36-WT.

Article Snippet: Lentiviral vectors for EGR1 overexpression, EGR1 knockdown (sh-EGR1), and corresponding controls were constructed by GeneChem (Shanghai, China).

Techniques: Binding Assay, Expressing, Over Expression, Knockdown, ChIP-qPCR, Transfection, Luciferase

Journal: Neurotherapeutics

Article Title: The EGR1/ZFP36 axis governs glycosphingolipid metabolic reprogramming in monocyte-derived macrophages in guillain-barré syndrome

doi: 10.1016/j.neurot.2026.e00895

Figure Lengend Snippet: Transcriptomic and metabolomic pathway enrichment analysis in EGR1-overexpressing and macrophages. (a–b) Top 20 KEGG pathways from GSEA of the ZFP36 gene set in transcriptomic data of EGR1-overexpression/knockdown macrophages. Glycosphingolipid metabolism pathways were commonly enriched in both datasets. ( c –d) Top 20 KEGG pathways from metabolomic data of EGR1-overexpression/knockdown macrophages. Sphingolipid metabolism showed positive enrichment upon EGR1 overexpression and negative enrichment upon EGR1 knockdown.

Article Snippet: Lentiviral vectors for EGR1 overexpression, EGR1 knockdown (sh-EGR1), and corresponding controls were constructed by GeneChem (Shanghai, China).

Techniques: Metabolomic, Over Expression, Knockdown

Journal: Neurotherapeutics

Article Title: The EGR1/ZFP36 axis governs glycosphingolipid metabolic reprogramming in monocyte-derived macrophages in guillain-barré syndrome

doi: 10.1016/j.neurot.2026.e00895

Figure Lengend Snippet: Enrichment patterns of sphingolipid metabolism pathway genes and metabolites in EGR1-overexpressing/knockdown macrophages. (a) Heatmap of gene expression in the sphingolipid metabolism pathway in EGR1-overexpressing and EGR1-knockdown macrophages, showing upregulation of 17 genes including HEXA and HEXB in the flag-EGR1 group. (b) KEGG network diagram integrating changes in genes and metabolites within the sphingolipid metabolism pathway in EGR1-overexpressing macrophages, demonstrating coordinated upregulation of HEXA, HEXB, and their metabolites globotriaosylceramide and lactosylceramide.

Article Snippet: Lentiviral vectors for EGR1 overexpression, EGR1 knockdown (sh-EGR1), and corresponding controls were constructed by GeneChem (Shanghai, China).

Techniques: Knockdown, Gene Expression

Journal: Neurotherapeutics

Article Title: The EGR1/ZFP36 axis governs glycosphingolipid metabolic reprogramming in monocyte-derived macrophages in guillain-barré syndrome

doi: 10.1016/j.neurot.2026.e00895

Figure Lengend Snippet: EGR1 targets ZFP36 to regulate glycosphingolipid metabolism and macrophage phenotype. (a) qRT-PCR was conducted to detect the efficiency of OE-ZFP36 and si-ZFP36 in macrophages, confirming successful overexpression and knockdown of ZFP36 for subsequent rescue experiments (n = 3). In vitro experimental groups: OE-EGR1+si-NC, OE-EGR1+si-ZFP36, OE-EGR1+si-ZFP36+OE-ZFP36. (b–c) Expression levels of glycosphingolipid metabolism markers (HEXA, HEXB, GLA) in macrophages were determined by qRT-PCR and WB (n = 3). Overexpression of EGR1 combined with ZFP36 knockdown downregulates the expression of these markers, while subsequent overexpression of ZFP36 reverses this trend. ( d –e) The proportion of M1 macrophages (CD86 + ) and M2 macrophages (CD163 + ) was determined by flow cytometry, with representative gating plots and quantitative bar charts shown, demonstrating that ZFP36 mediates EGR1 regulation of M1/M2 balance (n = 3). Data are presented as mean ± SD. ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001 vs OE-NC/si-NC/OE + EGR1+si-NC/OE + EGR1+si-ZFP36.

Article Snippet: Lentiviral vectors for EGR1 overexpression, EGR1 knockdown (sh-EGR1), and corresponding controls were constructed by GeneChem (Shanghai, China).

Techniques: Quantitative RT-PCR, Over Expression, Knockdown, In Vitro, Expressing, Flow Cytometry

Journal: Neurotherapeutics

Article Title: The EGR1/ZFP36 axis governs glycosphingolipid metabolic reprogramming in monocyte-derived macrophages in guillain-barré syndrome

doi: 10.1016/j.neurot.2026.e00895

Figure Lengend Snippet: Validation of EGR1 targeting ZFP36 to regulate myelination in EAN rat models. (a–b) Knockdown efficiency of ZFP36 as verified by qRT-PCR and WB, confirming successful ZFP36 knockdown in rat sciatic nerve following intrathecal siRNA injection (n = 3). (c) Assessment of hindlimb motor function using a grip strength test, showing that ZFP36 knockdown abrogated EGR1 overexpression-induced improvement in motor function (n = 6). (d) TEM was used to examine the pathological changes in myelin, revealing that ZFP36 knockdown reversed the protective effect of EGR1 on myelin structure. (e–f) qRT-PCR and WB were employed to assess the expression levels of myelin-related markers (MBP, S100B, and MPZ), demonstrating that ZFP36 mediates EGR1 regulation of myelin integrity markers (n = 3). Data are presented as mean ± SD. ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001 vs si-NC/EAN + OE-NC/EAN + OE-EGR1.

Article Snippet: Lentiviral vectors for EGR1 overexpression, EGR1 knockdown (sh-EGR1), and corresponding controls were constructed by GeneChem (Shanghai, China).

Techniques: Biomarker Discovery, Knockdown, Quantitative RT-PCR, Injection, Over Expression, Expressing