Genomic determinants of antigen expression hierarchy in African trypanosomes

• 成果类型: Article
• 署名作者: Keneskhanova, Zhibek; Mcwilliam, Kirsty R.; Cosentino, Raul O.; Barcons-Simon, Anna; Dobrynin, Atai; Smith, Jaclyn E.; Subota, Ines; Mugnier, Monica R.; Colome-Tatche, Maria; Siegel, T. Nicolai
• 署名单位: University of Munich; University of Munich; Helmholtz Association; Helmholtz-Center Munich - German Research Center for Environmental Health; Johns Hopkins University; Johns Hopkins Bloomberg School of Public Health; University of Edinburgh
• 刊物名称: Nature
• ISSN/ISSBN: 0028-1621
• DOI: 10.1038/s41586-025-08720-w
• 发表日期: 2025-06-05
• 关键词: blood-stream forms; gene-expression

摘要

Antigenic variation is an immune evasion strategy used by many different pathogens. It involves the periodic, non-random switch in the expression of different antigens throughout an infection. How the observed hierarchy in antigen expression is achieved has remained a mystery1,2. A key challenge in uncovering this process has been the inability to track transcriptome changes and potential genomic rearrangements in individual cells during a switch event. Here we report the establishment of a highly sensitive single-cell RNA sequencing approach for the model protozoan parasite Trypanosoma brucei. This approach has revealed genomic rearrangements that occur in individual cells during a switch event. Our data show that following a double-strand break in the transcribed antigen-coding gene-an important trigger for antigen switching-the type of repair mechanism and the resultant antigen expression depend on the availability of a homologous repair template in the genome. When such a template was available, repair proceeded through segmental gene conversion, creating new, mosaic antigen-coding genes. Conversely, in the absence of a suitable template, a telomere-adjacent antigen-coding gene from a different part of the genome was activated by break-induced replication. Our results show the critical role of repair sequence availability in the antigen selection mechanism. Furthermore, our study demonstrates the power of highly sensitive single-cell RNA sequencing methods in detecting genomic rearrangements that drive transcriptional changes at the single-cell level.