Competing gene regulatory networks drive naive and memory B cell differentiation.

IF 6.7 1区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY
Molecular Systems Biology Pub Date : 2026-07-01 Epub Date: 2026-04-16 DOI:10.1038/s44320-026-00207-8
Pietro Demela, Laura Esposito, Pietro Marchesan, Leonardo Nossa, Davide Bolognini, Edoardo Giacopuzzi, Eugenia Ricciardelli, Paolo Ferrari, Silvia Bombelli, Clelia Peano, Daniele Prati, Luca Valenti, Blagoje Soskic
{"title":"Competing gene regulatory networks drive naive and memory B cell differentiation.","authors":"Pietro Demela, Laura Esposito, Pietro Marchesan, Leonardo Nossa, Davide Bolognini, Edoardo Giacopuzzi, Eugenia Ricciardelli, Paolo Ferrari, Silvia Bombelli, Clelia Peano, Daniele Prati, Luca Valenti, Blagoje Soskic","doi":"10.1038/s44320-026-00207-8","DOIUrl":null,"url":null,"abstract":"<p><p>Elucidating the gene regulatory networks (GRNs) that control human B cell differentiation is crucial for understanding immune responses to infection, vaccination, and autoimmunity. Here, we map the GRNs guiding naive and memory B cell differentiation. Early in activation, both cell types engage highly similar GRNs. However, at later stages, naive B cells diverge into two opposing GRNs that promote differentiation into either plasma cells or germinal center (GC) cells. In contrast, memory B cells predominantly activate the GRNs associated with plasma cell differentiation, such as IRF4. CRISPR perturbations of IRF4 and its downstream effector PRDM1 rewired the GRNs, blocking plasma cell programs and promoting GC fate. Finally, we trained machine learning algorithms to predict sister cells, solely based on the transcriptome. This showed that plasma cell gene expression is tightly correlated among sister cells, revealing heritable transcriptional programs. Collectively, our findings reveal distinct regulatory trajectories in naive and memory B cells and uncover heritable transcriptional states that shape human B cell fate decisions.</p>","PeriodicalId":18906,"journal":{"name":"Molecular Systems Biology","volume":" ","pages":"1097-1117"},"PeriodicalIF":6.7000,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13328623/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Molecular Systems Biology","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1038/s44320-026-00207-8","RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2026/4/16 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

Elucidating the gene regulatory networks (GRNs) that control human B cell differentiation is crucial for understanding immune responses to infection, vaccination, and autoimmunity. Here, we map the GRNs guiding naive and memory B cell differentiation. Early in activation, both cell types engage highly similar GRNs. However, at later stages, naive B cells diverge into two opposing GRNs that promote differentiation into either plasma cells or germinal center (GC) cells. In contrast, memory B cells predominantly activate the GRNs associated with plasma cell differentiation, such as IRF4. CRISPR perturbations of IRF4 and its downstream effector PRDM1 rewired the GRNs, blocking plasma cell programs and promoting GC fate. Finally, we trained machine learning algorithms to predict sister cells, solely based on the transcriptome. This showed that plasma cell gene expression is tightly correlated among sister cells, revealing heritable transcriptional programs. Collectively, our findings reveal distinct regulatory trajectories in naive and memory B cells and uncover heritable transcriptional states that shape human B cell fate decisions.

竞争基因调控网络驱动幼稚和记忆B细胞分化。
阐明控制人类B细胞分化的基因调控网络(grn)对于理解对感染、疫苗接种和自身免疫的免疫反应至关重要。在这里,我们绘制了引导幼稚和记忆B细胞分化的grn。在激活的早期,两种细胞类型参与高度相似的grn。然而,在后期,幼稚B细胞分化为两个相反的grn,促进分化为浆细胞或生发中心(GC)细胞。相反,记忆B细胞主要激活与浆细胞分化相关的grn,如IRF4。CRISPR对IRF4及其下游效应物PRDM1的扰动使GRNs重新连接,阻断浆细胞程序并促进GC命运。最后,我们训练机器学习算法来预测姊妹细胞,完全基于转录组。这表明浆细胞基因表达在姐妹细胞之间密切相关,揭示了可遗传的转录程序。总的来说,我们的研究结果揭示了幼稚B细胞和记忆B细胞中不同的调节轨迹,并揭示了塑造人类B细胞命运决定的可遗传转录状态。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Molecular Systems Biology
Molecular Systems Biology 生物-生化与分子生物学
CiteScore
18.50
自引率
1.00%
发文量
62
审稿时长
6-12 weeks
期刊介绍: Systems biology is a field that aims to understand complex biological systems by studying their components and how they interact. It is an integrative discipline that seeks to explain the properties and behavior of these systems. Molecular Systems Biology is a scholarly journal that publishes top-notch research in the areas of systems biology, synthetic biology, and systems medicine. It is an open access journal, meaning that its content is freely available to readers, and it is peer-reviewed to ensure the quality of the published work.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信
小红书