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Spec-seq unveils transcriptional subpopulations of antibody-secreting cells following influenza vaccination
Karlynn E. Neu, … , Aly A. Khan, Patrick C. Wilson
Karlynn E. Neu, … , Aly A. Khan, Patrick C. Wilson
Published November 19, 2018
Citation Information: J Clin Invest. 2019;129(1):93-105. https://doi.org/10.1172/JCI121341.
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Research Article Immunology Article has an altmetric score of 8

Spec-seq unveils transcriptional subpopulations of antibody-secreting cells following influenza vaccination

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Abstract

Vaccines are among the most effective public health tools for combating certain infectious diseases such as influenza. The role of the humoral immune system in vaccine-induced protection is widely appreciated; however, our understanding of how antibody specificities relate to B cell function remains limited due to the complexity of polyclonal antibody responses. To address this, we developed the Spec-seq framework, which allows for simultaneous monoclonal antibody (mAb) characterization and transcriptional profiling from the same single cell. Here, we present the first application of the Spec-seq framework, which we applied to human plasmablasts after influenza vaccination in order to characterize transcriptional differences governed by B cell receptor (BCR) isotype and vaccine reactivity. Our analysis did not find evidence of long-term transcriptional specialization between plasmablasts of different isotypes. However, we did find enhanced transcriptional similarity between clonally related B cells, as well as distinct transcriptional signatures ascribed by BCR vaccine recognition. These data suggest IgG and IgA vaccine–positive plasmablasts are largely similar, whereas IgA vaccine–negative cells appear to be transcriptionally distinct from conventional, terminally differentiated, antigen-induced peripheral blood plasmablasts.

Authors

Karlynn E. Neu, Jenna J. Guthmiller, Min Huang, Jennifer La, Marcos C. Vieira, Kangchon Kim, Nai-Ying Zheng, Mario Cortese, Micah E. Tepora, Natalie J. Hamel, Karla Thatcher Rojas, Carole Henry, Dustin Shaw, Charles L. Dulberger, Bali Pulendran, Sarah Cobey, Aly A. Khan, Patrick C. Wilson

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Figure 4

IgA plasmablasts cluster by their ability to bind the vaccine.

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IgA plasmablasts cluster by their ability to bind the vaccine.
(A) tSNE ...
(A) tSNE projection of the IgA plasmablasts (n = 176), population indicated by color and relative binding affinity (area under the curve) indicated by dot size. (B) Volcano plot showing the differential expression of all genes between IgA vaccine-negative (IgAVN) and IgA vaccine-positive (IgAVP) plasmablasts. Genes with log fold greater than or equal to 1.5 with a Benjamini-Hochberg adjusted P ≤ 0.05 (2-sided t test) are colored red. Some of the most significant genes are labeled. (C) Pie charts showing repertoire usage frequency between IgAVN and IgAVP plasmablasts. Increased usage of the lambda light chain was found within IgAVP cells (P = 0.0192, χ2) and increased IGHA2 usage was found within IgAVN cells (P = 7.45 × 10–5, χ2). (D) tSNE projection of the IgA plasmablasts repeated after the exclusion of Ig genes. (E) Violin plots of FUT8 and B4GALT1 between IgAVN and IgAVP plasmablasts, where the location on the y axis shows each cell’s gene expression level and the x axis distribution is randomly assigned to improve spot visualization.

Copyright © 2025 American Society for Clinical Investigation
ISSN: 0021-9738 (print), 1558-8238 (online)

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