Hua, A. | Search bioRxiv

bioRxiv2024

An updated AL-Base reveals ranked enrichment of immunoglobulin light chain variable genes in AL amyloidosis

BackgroundEach monoclonal antibody light chain associated with AL amyloidosis has a unique sequence. Defining how these sequences lead to amyloid deposition could facilitate faster diagnosis and lead to new treatments. MethodsLight chain sequences are collected in the Boston University AL-Base repository. Monoclonal sequences from AL amyloidosis, multiple myeloma and the healthy polyclonal immune repertoire were compared to identify differences in precursor gene use, mutation frequency and physicochemical properties. ResultsAL-Base now contains 2,193 monoclonal light chain sequences from plasma cell dyscrasias. Sixteen germline precursor genes were enriched in AL amyloidosis, relative to multiple myeloma and the polyclonal repertoire. Two genes, IGKV1-16 and IGLV1-36, were infrequently observed but highly enriched in AL amyloidosis. The number of mutations varied widely between light chains. AL-associated {kappa} light chains harbored significantly more mutations compared to multiple myeloma and polyclonal sequences, whereas AL-associated {lambda} light chains had fewer mutations. Machine learning tools designed to predict amyloid propensity were less accurate for new sequences than their original training data. ConclusionsRarely-observed light chain variable genes may carry a high risk of AL amyloidosis. New approaches are needed to define sequence-associated risk factors for AL amyloidosis. AL-Base is a foundational resource for such studies.

bioinformatics↗

bioRxiv2022

Characterizing adjuvants' effects at the murine immunoglobulin repertoire level

High-throughput immunoglobulin sequencing (IgSeq) has been developed and applied to study the adaptive immune response extensively for more than a decade. However, generating large-scale, high-fidelity sequencing data is still challenging, and furthermore, not much has been done to characterize adjuvants effects at the repertoire level. Thus, we developed an improved library prep protocol and standardized the data analysis pipeline for accurate repertoire profiling. In addition, two metrics were implemented to assess repertoire clone properties. We then studied systemically the effects of two adjuvants, CpG and Alum, on the Ig heavy chain repertoire using the ovalbumin (OVA) challenged mouse model. Ig repertoires of different tissues (spleen and bone marrow) and isotypes (IgG and IgM) were examined and compared in terms of sequence mutation frequency, IGHV gene usage, CDR3 length, rescaled Hill numbers for clonal diversity, and clone selection strength. As a result, Ig repertoires of different tissues or isotypes exhibited distinguishable profiles at the non-immunized steady state. Adjuvanted immunizations further resulted in statistically significant alterations in Ig repertoire compared with PBS or OVA alone immunized groups. Lastly, we applied unsupervised machine learning techniques - multiple factor analysis and clustering - to identify Ig repertoire signatures in different compartments and under varying immunizations. We found that the IGH repertoires of distinct tissue-isotype compartments or under varying immunizations differed in unique sets of properties. Notably, Alum and CpG effects on the Ig repertoire exhibited different tissue and isotype preferences. The former led to increased diversity of abundant clones of both isotypes in BM only, and the latter promoted the selection of IgG clones only but in both tissues. The patterns of Ig repertoire changes likely reflected possible action mechanisms of these two adjuvants.

immunology↗