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Cited by 5Monoclonal and Polyclonal Antibodies ResearchT-cell and B-cell ImmunologySingle-cell and spatial transcriptomics

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Single-cell 5′ RNA sequencing of camelid peripheral B cells provides insights into cellular basis of heavy-chain antibody production

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Yi, Li, Guo, Xin, Liu, Yuexing, Jirimutu, Wang, Zhen·2024·Computational and Structural Biotechnology Journal
DOI 10.1016/j.csbj.2024.04.041PMC PMC11059136

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Abstract

Camelids produce both conventional tetrameric antibodies (Abs) and dimeric heavy-chain antibodies (HCAbs). Although B cells that generate these two types of Abs exhibit distinct B cell receptors (BCRs), whether these two B cell populations differ in their phenotypes and developmental processes remains unclear. Here, we performed single-cell 5′ RNA profiling of peripheral blood mononuclear cell samples from Bactrian camels before and after immunization. We characterized the functional subtypes and differentiation trajectories of circulating B cells in camels, and reconstructed single-cell BCR sequences. We found that in contrast to humans, the proportion of T-bet+ B cells was high among camelid peripheral B cells. Several marker genes of human B cell subtypes, including CD27 and IGHD , were expressed at low levels in the corresponding camel B cell subtypes. Camelid B cells expressing variable genes of HACbs ( VHH ) were widely present in various functional subtypes and showed highly overlapping differentiation trajectories with B cells expressing variable genes of conventional Abs ( VH ). After immunization, the transcriptional changes in VHH + and VH + B cells were largely consistent. Through structure modeling, we identified a variety of scaffold types among the reconstructed VHH sequences. Our study provides insights into the cellular context of HCAb production in camels and lays the foundation for developing single-B cell-based camelid single-domain Ab screening.

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Graphical abstract CC BY-NC-ND · PubMed Central
Fig. 1 Major cell types of camel PBMCs revealed by scRNA-seq. (A) UMAP visualization of cell clustering. Cell types are annotated based on the expression of marker genes and their proportion in PBMCs is shown. (B) Dot plot depicting average expression and expression percentage of marker genes in each cell cluster.
Fig. 1 Major cell types of camel PBMCs revealed by scRNA-seq. (A) UMAP visualization of cell clustering. Cell types are annotated based on the expression of marker genes and their proportion in PBMCs is shown. (B) Dot plot depicting average expression and expression percentage of marker genes in each cell cluster.CC BY-NC-ND · PubMed Central
Fig. 2 Characterization of camel B cell subtypes. (A) UMAP plot of B cells colored by their subtypes. The proportion of each subtype in B cells is calculated. (B) Expression of marker genes among the B cell subtypes identified by Seurat FindMarkers. T-bet+ B cells show lower expression of CR2 but higher expression of ITGAX and TBX21. Naive B cells show higher expression of CXCR4, CD69 and SELL. Memory B cells show higher expression of ITGB1, ITGB7, S100A6, S100A13 and IGHA. Intermediate B cells show higher expression of IGHM. (C) Comparison of marker genes for peripheral B cells and their subtypes between humans and camels based on CellMarker 2.0. Only genes significantly over-expressed in humans are showed. Markers for total B cells should be significantly over-expressed compared to other PBMC types, while markers for B cell subtypes should be significantly over-expressed compared to other B cells. Genes with Bonferroni-adjusted P < 0.05 are marked with stars. The log-average expression and log-fold change (logFC) are indicated by colors and sizes of the dots, respectively. Genes without expression detected are colored in grey. (D) B cell state and differentiation trajectories inferred using Monocle2. Cells are colored according to their subtypes, and the proportion of subtypes in each state is displayed by pie plots. The pseudotime is assigned by assuming naive B cells as the root. Plasma cells are excluded from the analysis. (E) Heatmap depicting the relative expression of marker genes along the trajectories. The color bar at the top represents gene clusters with similar expression tendencies, while the color bar at the right represents cell types.
Fig. 2 Characterization of camel B cell subtypes. (A) UMAP plot of B cells colored by their subtypes. The proportion of each subtype in B cells is calculated. (B) Expression of marker genes among the B cell subtypes identified by Seurat FindMarkers. T-bet+ B cells show lower expression of CR2 but higher expression of ITGAX and TBX21. Naive B cells show higher expression of CXCR4, CD69 and SELL. Memory B cells show higher expression of ITGB1, ITGB7, S100A6, S100A13 and IGHA. Intermediate B cells show higher expression of IGHM. (C) Comparison of marker genes for peripheral B cells and their subtypes between humans and camels based on CellMarker 2.0. Only genes significantly over-expressed in humans are showed. Markers for total B cells should be significantly over-expressed compared to other PBMC types, while markers for B cell subtypes should be significantly over-expressed compared to other B cells. Genes with Bonferroni-adjusted P < 0.05 are marked with stars. The log-average expression and log-fold change (logFC) are indicated by colors and sizes of the dots, respectively. Genes without expression detected are colored in grey. (D) B cell state and differentiation trajectories inferred using Monocle2. Cells are colored according to their subtypes, and the proportion of subtypes in each state is displayed by pie plots. The pseudotime is assigned by assuming naive B cells as the root. Plasma cells are excluded from the analysis. (E) Heatmap depicting the relative expression of marker genes along the trajectories. The color bar at the top represents gene clusters with similar expression tendencies, while the color bar at the right represents cell types.CC BY-NC-ND · PubMed Central
Fig. 3 Characterization of camel single-cell BCRs. (A) Number of cells with different IGHC types in each B cell subtype. The IGHC types are assigned based on gene expression. NA represents cells without IGHC expression detected. (B) Number of cells with different IGHV types (VH/VHH) in each B cell subtype. The IGHV types are assigned based on the hallmark substitutions in FR2. NA represents cells without FR2 recovered. (C) Sankey diagram depicting the relationships between B cell subtypes, IGHC and IGHV types. Although most IGHG2/3+ cells are associated with VHH, and most conventional IGHC are associated with VH, non-typical associations are widely present. (D) Mapping IGHV types to differentiation trajectories of B cells inferred using Monocle2. Cells are colored according to their IGHV types, and the proportion in each state is displayed by pie plots. (E) Number of cells with different clonal size in each B cell subtype. The clonotypes are determined by IGHV CDR3 sequences. NA represents cells without CDR3 recovered.
Fig. 3 Characterization of camel single-cell BCRs. (A) Number of cells with different IGHC types in each B cell subtype. The IGHC types are assigned based on gene expression. NA represents cells without IGHC expression detected. (B) Number of cells with different IGHV types (VH/VHH) in each B cell subtype. The IGHV types are assigned based on the hallmark substitutions in FR2. NA represents cells without FR2 recovered. (C) Sankey diagram depicting the relationships between B cell subtypes, IGHC and IGHV types. Although most IGHG2/3+ cells are associated with VHH, and most conventional IGHC are associated with VH, non-typical associations are widely present. (D) Mapping IGHV types to differentiation trajectories of B cells inferred using Monocle2. Cells are colored according to their IGHV types, and the proportion in each state is displayed by pie plots. (E) Number of cells with different clonal size in each B cell subtype. The clonotypes are determined by IGHV CDR3 sequences. NA represents cells without CDR3 recovered.CC BY-NC-ND · PubMed Central
Fig. 4 Structure predictions for VHH sequences. (A) Number of complete VHH sequences with different shapes based on the length of CDR3 sequences: concave (<10 aa), loop (10–14 aa), and convex (>14 aa). Within each shape, VHH sequences with ≤ 3 and > 3 cysteines are separated. (B-D) Structure prediction of VHH sequences with long convex shape (>20 aa) using AlphaFold2 (purple) and ImmuneBuilder (blue). The AlphaFold2 structure is presented as the top-ranked model. pLDDT scores above 90 indicate very high accuracy, while scores between 70 to 90 indicate reliable prediction. pTM scores greater than 0.5 indicate the same globular fold as the template. Non-canonical disulfide bonds are shown in the inserted panels. (B) No non-canonical disulfide bonds. (C) One non-canonical disulfide bond in FR2-CDR3. (D) Two non-canonical disulfide bonds in CDR1-CDR3 and CDR3-CDR3.
Fig. 4 Structure predictions for VHH sequences. (A) Number of complete VHH sequences with different shapes based on the length of CDR3 sequences: concave (<10 aa), loop (10–14 aa), and convex (>14 aa). Within each shape, VHH sequences with ≤ 3 and > 3 cysteines are separated. (B-D) Structure prediction of VHH sequences with long convex shape (>20 aa) using AlphaFold2 (purple) and ImmuneBuilder (blue). The AlphaFold2 structure is presented as the top-ranked model. pLDDT scores above 90 indicate very high accuracy, while scores between 70 to 90 indicate reliable prediction. pTM scores greater than 0.5 indicate the same globular fold as the template. Non-canonical disulfide bonds are shown in the inserted panels. (B) No non-canonical disulfide bonds. (C) One non-canonical disulfide bond in FR2-CDR3. (D) Two non-canonical disulfide bonds in CDR1-CDR3 and CDR3-CDR3.CC BY-NC-ND · PubMed Central
Fig. 5 scRNA-seq of post-immunization PBMCs and comparative analysis. (A) Immunization schedule and serum Ab titer. Two camels received four doses of BSA on the days indicated by black arrows, and PBMCs were collected for scRNA-seq before and after immunization on the days indicated by red arrows. The Ab titer was measured as the highest serum dilution using ELISA. (B) Number of DEGs identified in major cell types (PC, plasma cell). Up-regulated genes in post-immunization samples compared to pre-immunization samples are colored in orange, while down-regulated genes are colored in blue. (C) Dot plot of selected DEGs with functional enrichment in B cells and PCs. The color of dots indicates log-fold change (logFC) while the size of dots indicates the normalized mean expression on the pseudobulk level. DEGs with BH-adjusted P < 0.05 in a population are marked with stars. (D, E) Comparison of subtype composition in VH+ and VHH+ B cells. The average proportion before immunization (D) and changes in the proportion after immunization (E) are estimated using a linear model for each subtype. The error bars represent standard errors of estimation. P-values are calculated using the two-sided t-test and adjusted using the BH method. (F) Comparison of the logFC of DEGs between VH+ and VHH+ B cells during immunization. DEGs are identified separately in non-PCs and PCs, with IGHC genes excluded from the analysis. The Pearson’s correlation coefficient R and its P-value are shown.
Fig. 5 scRNA-seq of post-immunization PBMCs and comparative analysis. (A) Immunization schedule and serum Ab titer. Two camels received four doses of BSA on the days indicated by black arrows, and PBMCs were collected for scRNA-seq before and after immunization on the days indicated by red arrows. The Ab titer was measured as the highest serum dilution using ELISA. (B) Number of DEGs identified in major cell types (PC, plasma cell). Up-regulated genes in post-immunization samples compared to pre-immunization samples are colored in orange, while down-regulated genes are colored in blue. (C) Dot plot of selected DEGs with functional enrichment in B cells and PCs. The color of dots indicates log-fold change (logFC) while the size of dots indicates the normalized mean expression on the pseudobulk level. DEGs with BH-adjusted P < 0.05 in a population are marked with stars. (D, E) Comparison of subtype composition in VH+ and VHH+ B cells. The average proportion before immunization (D) and changes in the proportion after immunization (E) are estimated using a linear model for each subtype. The error bars represent standard errors of estimation. P-values are calculated using the two-sided t-test and adjusted using the BH method. (F) Comparison of the logFC of DEGs between VH+ and VHH+ B cells during immunization. DEGs are identified separately in non-PCs and PCs, with IGHC genes excluded from the analysis. The Pearson’s correlation coefficient R and its P-value are shown.CC BY-NC-ND · PubMed Central

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References 66 · Cited by 5

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Metadata

Authors
Yi, L., Guo, X., Liu, Y., Jirimutu, & Wang, Z.
Affiliations
  • Key Laboratory of Dairy Biotechnology and Engineering, Ministry of Education, College of Food Science and Engineering, Inner Mongolia Agricultural University, Huhhot 010018, China
  • Shanghai Institute of Nutrition and Health (CN)
  • Guangzhou Laboratory (CN)
  • Inner Mongolia Agricultural University (CN)
Corresponding author
  • Jirimutu
  • Wang, Zhen
ORCID
Venue
Computational and Structural Biotechnology Journal
Publisher
American Association for the Advancement of Science (AAAS)
Published
2024-04-16
Volume
23
Pages
1705-1714
ISSN
2001-0370 (ISSN-L)
DOI
10.1016/j.csbj.2024.04.041
PMC
PMC11059136
OpenAlex
W4394893321
Cited by
5
References
66
Citations by year
2026: 2 · 2025: 3
FWCI
1.27
Type
journal article
Language
en
Open access
Licence
Locations
  • Computational and Structural Biotechnology Journal (publishedVersion, cc-by-nc-nd)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Funders
National Natural Science Foundation of China
Topics
  • Life Sciences › Immunology and Microbiology › Immunology › Monoclonal and Polyclonal Antibodies Research
  • Life Sciences › Immunology and Microbiology › Immunology › T-cell and B-cell Immunology
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
Keywords
heavy-chain antibodies, B cell receptor repertoire, VHH, Bactrian camel, immunization, B cell subsets

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Yi, L., Guo, X., Liu, Y., Jirimutu, & Wang, Z. (2024). Single-cell 5′ RNA sequencing of camelid peripheral B cells provides insights into cellular basis of heavy-chain antibody production. Computational and Structural Biotechnology Journal. https://doi.org/10.1016/j.csbj.2024.04.041