1. Immunology and Inflammation
  2. Microbiology and Infectious Disease

Glycosylated IgG antibodies contribute to the recovery of haemorrhagic fever with renal syndrome patients

  1. Chuansong Quan
  2. Lu Wang
  3. Jiming Gao
  4. Yaoni Li
  5. Xiaoyu Xu
  6. Houqiang Li
  7. Zixuan Gao
  8. Wenxu Ruan
  9. Hongzhi Liu
  10. Qian Li
  11. Weijia Xing
  12. Liqiong Zhao
  13. Michael J Carr
  14. Weifeng Shi  Is a corresponding author
  15. Haifeng Hou  Is a corresponding author
  1. Key Laboratory of Emerging Infectious Diseases in Universities of Shandong, Shandong First Medical University and Shandong Academy of Medical Sciences, China
  2. The Second Affiliated Hospital of Shandong First Medical University, China
  3. School of Public Health, Shandong First Medical University and Shandong Academy of Medical Sciences, China
  4. Medical Records and Statistics Management Office, Tengzhou Central People’s Hospital, China
  5. Department of Neurobiology and Physiology, School of Clinical and Basic Medicine, Shandong First Medical University and Shandong Academy of Medical Sciences, China
  6. Baoji Central Hospital, China
  7. School of Life Sciences, Shandong First Medical University and Shandong Academy of Medical Sciences, China
  8. National Virus Reference Laboratory, School of Medicine, University College Dublin, Ireland
  9. International Collaboration Unit, International Institute for Zoonosis Control, Hokkaido University, Japan
  10. Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, China
  11. Shanghai Institute of Virology, Shanghai Jiao Tong University School of Medicine, China
https://doi.org/10.7554/eLife.106989.4
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Cite this article
  1. Chuansong Quan
  2. Lu Wang
  3. Jiming Gao
  4. Yaoni Li
  5. Xiaoyu Xu
  6. Houqiang Li
  7. Zixuan Gao
  8. Wenxu Ruan
  9. Hongzhi Liu
  10. Qian Li
  11. Weijia Xing
  12. Liqiong Zhao
  13. Michael J Carr
  14. Weifeng Shi
  15. Haifeng Hou
(2025)
Glycosylated IgG antibodies contribute to the recovery of haemorrhagic fever with renal syndrome patients
eLife 14:RP106989.
https://doi.org/10.7554/eLife.106989.4
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4 figures, 1 table and 12 additional files

Figures

Figure 1
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Flowchart of Haemorrhagic fever with renal syndrome (HFRS) patient recruitment in Baoji Central Hospital in Shaanxi province from November 2019 to January 2022.
Figure 2 with 2 supplements
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Immunophenotypic remodeling in the B cell subsets during acute Haemorrhagic fever with renal syndrome (HFRS).

(A) t-distributed stochastic neighbor embedding (t-SNE) plot showing antibody-secreting memory B cells (ASM), double-negative (DN) B cells, intermediate memory cells (IM), marginal zone-like cells (MZB), naive B cells, plasmablasts (PB), quiescent resting memory cells (RM), and exhausted tissue-like memory B cells (TLM) of peripheral blood mononuclear cells (PBMCs) identified using an integrated and classification analysis. (B) t-SNE projection of canonical markers, including CD19, CD27, CD38, IgD, and IgM. (C) Proportions of the eight B cell subsets, colored by the healthy group (green,n=8) and Hantaan virus (HTNV) groups (red, n=15). Boxplot features: minimum box, 25th percentile; center, median; maximum box, 75th percentile.The Wilcoxon signed rank test was used. (D) Frequency of the eight B cell subsets in between the healthy group and the HTNV groups. (E) FACS gating strategy for the measurement of the B cell subsets: activated memory B cells (CD21- CD27+, AM), RM B cells (CD21+ CD27+), IM B cells (CD21+ CD27-), TLM B cells (CD21- CD27-), naive B cells (CD27- IgD+), MZB B cells (CD27+ IgD+), ASM B cells (CD27+ IgD-), DN B cells (CD27- IgD-), PB (CD38+ CD27+), and class-switched memory B cells (CD38- CD27+, CSM), respectively. (F) The proportion of ASM, CSM, naive B, and PB cells in CD19+ B cells in the acute (n=27) and convalescent HFRS patients (n=25). The Wilcoxon signed rank test was used. Data are presented as mean ± SEM in panels C and F. *p<0.05,**p<0.01, ***p<0.001, ns, no significane.

Figure 2—figure supplement 1
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Single-cell transcriptomes of peripheral blood mononuclear cells (PBMCs) from patients with Haemorrhagic fever with renal syndrome (HFRS).

(A) Uniform manifold approximation and projection (UMAP) presentation of the major peripheral immune cell types in the PBMCs from 15 HFRS patients and eight healthy controls. (B) The Dot plot shows the expression levels of canonical marker-related genes in the different subpopulations. (C) UMAP presentation of the major peripheral immune cell types among HFRS and healthy control groups. (D) Proportions of the eight cell subsets, colored by the healthy group (green, n=8) and Hantaan virus (HTNV, n=15) groups (red). Boxplot features: minimum box, 25th percentile; center, median; maximum box, 75th percentile. (E) Frequency of the eight cell subsets in between the healthy group and the HTNV group. (F) The UMAP plot shows the differentiation trajectories of different cell types calculated by pseudotime analysis.*p<0.05, **p<0.01, ***p<0.001, ns, no significance. The Wilcoxon signed rank test was used to assess the difference.

Figure 2—figure supplement 2
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Dynamic analysis of the B cell subsets in Haemorrhagic fever with renal syndrome (HFRS) patients.

(A) Expression of marginal zone-like B cells (MZB) in CD19+ B cells. (B) Expression of double-negative B cells (DN) in CD19+ B cells. (C) Expression of tissue-like memory B cells (TLM) in CD19+ B cells. (D) Expression of AM in CD19+ B cells. (E) Expression of resting memory B cells (RM) in CD19+ B cells. (F) Expression of intermediate memory B cells (IM) in CD19+ B cells.Data are presented as median (IQR). 27 acute and 25 recovery samples were included for analysis.ns, no significance (Wilcoxon signed rank test).

Figure 3
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Glycosylation modification of antibodies associated with Hantaan virus (HTNV) infection.

(A) Changes of different glycosylation types in both HTNV NP-specific IgG-negative and positive plasma from 24 Haemorrhagic fever with renal syndrome (HFRS) patients. (B) Differential IgG glycosylation patterns across antibody titer levels quantified by enzyme-linked immunosorbent assay (ELISA). (C) Comparison of different glycosylation levels before and after the fourfold increase in the IgG antibody titers. *p<0.05, **p<0.01, ***p<0.001,ns, no significance . For paired samples, the Wilcoxon signed rank test was used to assess the difference.

Figure 4 with 1 supplement
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Glycosylation modifications of antibodies primarily derived from antibody-secreting and plasmablast subpopulations.

(A) The correlation between the proportion of plasmablasts (PB) cells and the sialylation level. (B) The correlation between the proportion of antibody-secreting memory (ASM) cells and the sialylation level. (C) The correlation between the proportion of ASM cells and the galactosylation level. (D) Dot plot shows the expression levels of glycosylation-related genes in the eight B cell groups. The pink color represents mannose-related genes, the green color represents N-glycosylation-related genes, the orange color represents galactosylation-related genes, the purple represents sialylation-related genes, and the red color represents fucosylation-related genes. (E) Enriched pathways in the plasmablast and ASM subsets by GO enrichment analysis of the differentially expressed genes (DEGs). (F) The GSEA map presents the enrichment score of glycosylation-related genes (GRGs) in N-glycan biosynthesis.

Figure 4—figure supplement 1
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The differentially expressed genes and their functional changes in the B cell subsets post-Hantaan virus (HTNV) infection.

(A) The volcano plot shows the differentially expressed genes of different B cell subsets in acute Haemorrhagic fever with renal syndrome (HFRS) patients. The red font represents the upregulation of the B cell subpopulations, and the blue font represents the downregulation of the B cell subpopulations. (B and C) The volcano plot displays the differentially expressed genes in upregulation B cell subpopulations, including antibody-secreting memory B cells, plasmablasts, and quiescent resting memory B cells (B), and downregulation B cell subpopulations, including naive B cells, double-negative B cells, and intermediate memory B cells (C).

Tables

Author response table 1
Comparative analysis of serum biomarker concentrations in acute and convalescent phase cohorts.
BiomarkerNumberMeanStandard deviationCoefficient of variationPhase
Fuc16594.031.511.61Acute
Convalescent
Bis16515.912.0012.57
Gal16574.164.576.17
Sial6522.923.1513.73
Fuc26594.591.601.69
Bis26514.821.8312.38
Gal26571.785.587.78
Sia26521.533.3915.74

Additional files

Supplementary file 1

The proportion of different B cell subpopulations between healthy and acute Haemorrhagic fever with renal syndrome (HFRS) groups.

https://cdn.elifesciences.org/articles/106989/elife-106989-supp1-v1.xlsx
Supplementary file 2

Difference in main IgG glycome features of Haemorrhagic fever with renal syndrome (HFRS) patients between age groups.

https://cdn.elifesciences.org/articles/106989/elife-106989-supp2-v1.xlsx
Supplementary file 3

Difference in main IgG glycome features of Haemorrhagic fever with renal syndrome (HFRS) patients between sex groups.

https://cdn.elifesciences.org/articles/106989/elife-106989-supp3-v1.xlsx
Supplementary file 4

Relative abundance (%) of the main IgG-Fc glycome features in Haemorrhagic fever with renal syndrome (HFRS) patients.

https://cdn.elifesciences.org/articles/106989/elife-106989-supp4-v1.xlsx
Supplementary file 5

Results of multiple linear regression analysis for fucosylation.

APTT, activated partial thromboplastin time; MCHC, mean corpuscular hemoglobin concentration; NEUT, neutrophil; PLT, platelet; WBC, white blood cell; CRE, creatinine; Cys-C, cystatin C.

https://cdn.elifesciences.org/articles/106989/elife-106989-supp5-v1.xlsx
Supplementary file 6

Results of multiple linear regression analysis for bisecting GlcNAc.

APTT, activated partial thromboplastin time; MCHC, mean corpuscular hemoglobin concentration; NEUT, neutrophil; PLT, platelet; WBC, white blood cell; CRE, creatinine; Cys-C, cystatin C.

https://cdn.elifesciences.org/articles/106989/elife-106989-supp6-v1.xlsx
Supplementary file 7

Results of multiple linear regression analysis for galactosylation.

APTT, activated partial thromboplastin time; MCHC, mean corpuscular hemoglobin concentration; NEUT, neutrophil; PLT, platelet; WBC, white blood cell; CRE, creatinine; Cys-C, cystatin C.

https://cdn.elifesciences.org/articles/106989/elife-106989-supp7-v1.xlsx
Supplementary file 8

Results of multiple linear regression analysis for sialylation.

APTT, activated partial thromboplastin time; MCHC, mean corpuscular hemoglobin concentration; NEUT, neutrophil; PLT, platelet; WBC, white blood cell; CRE, creatinine; Cys-C, cystatin C.

https://cdn.elifesciences.org/articles/106989/elife-106989-supp8-v1.xlsx
Supplementary file 9

Differentially expressed genes among different B cell subgroups in healthy and acute Haemorrhagic fever with renal syndrome (HFRS) groups.

https://cdn.elifesciences.org/articles/106989/elife-106989-supp9-v1.xlsx
Supplementary file 10

Differential expression genes in the antibody-secreting memory B cells (ASM), plasmablasts (PB), and resting memory (RM) B cell subpopulations.

https://cdn.elifesciences.org/articles/106989/elife-106989-supp10-v1.xlsx
Supplementary file 11

Differential expression genes in the DN, IM, and naive B cell subpopulations.

https://cdn.elifesciences.org/articles/106989/elife-106989-supp11-v1.xlsx
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https://cdn.elifesciences.org/articles/106989/elife-106989-mdarchecklist1-v1.docx

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  1. Chuansong Quan
  2. Lu Wang
  3. Jiming Gao
  4. Yaoni Li
  5. Xiaoyu Xu
  6. Houqiang Li
  7. Zixuan Gao
  8. Wenxu Ruan
  9. Hongzhi Liu
  10. Qian Li
  11. Weijia Xing
  12. Liqiong Zhao
  13. Michael J Carr
  14. Weifeng Shi
  15. Haifeng Hou
(2025)
Glycosylated IgG antibodies contribute to the recovery of haemorrhagic fever with renal syndrome patients
eLife 14:RP106989.
https://doi.org/10.7554/eLife.106989.4