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Bridging DE gap to autoimmunity: A comparative study of the autoreactive features of H-CDR1 and H-CDR2 in SLC-/- mice
University of Skövde, School of Bioscience.
2024 (English)Independent thesis Advanced level (degree of Master (Two Years)), 30 credits / 45 HE creditsStudent thesis
Abstract [en]

The immune system is a fundamental part to the survival of all species. Failure to distinguish between self and non-self tissues, dysregulation of B cell functions and failure to filter out unfavourable genetic recombinations are some of the causes that lead to autoimmune disease. Surrogate light chain deficient (SLC-/-) mice are a model of autoimmunity that results in defective antibody heavy chain selection. The aim of this project was to investigate whether an integral component of the heavy chain, H-CDR2, encoded in the germline configuration, has excessive autoreactive features in SLC-/- mice. The NGS analysis of the heavy chain repertoires of sorted IgMpos and IgGpos memory B cells from SLC-/- mice was analysed using a pipeline built by custom code developed in R based on the dedicated packages developed by the Immcantation Team. In H-CDR1 and H-CDR2, germline-encoded polar amino acid residues such as aspartic acid (D), glutamic acid (E), arginine (R) and lysine (K) are most likely to be conserved or replaced by equivalent charged residues, suggesting a correlation between charged residues and autoreactive features. Linear regression analysis further highlighted the lack of correlation between the mutational load and clonal expansion characteristics such as group size. Throughout the study, substitutions that appear random look increasingly patterned when analysed through the lens of molecular mimicry. The deeper layers of analysis came together to show a new perspective on the germline encoded H-CDR1 and H-CDR2 and how their encoded features are part of what causes autoimmunity to affect organisms. Although the study would have benefited from larger datasets to sample and refine, the real conclusion at this stage is a call to move forward.

Place, publisher, year, edition, pages
2024. , p. 63
National Category
Bioinformatics and Computational Biology
Identifiers
URN: urn:nbn:se:his:diva-24359OAI: oai:DiVA.org:his-24359DiVA, id: diva2:1883717
External cooperation
Salghrenska Hospital & Göteborg Universitet
Subject / course
Systems Biology
Educational program
Infection Biology - Master’s Programme 120 ECTS
Supervisors
Examiners
Available from: 2024-07-11 Created: 2024-07-11 Last updated: 2025-09-29Bibliographically approved

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