The whole-organism heavy chain B cell repertoire from Zebrafish self-organizes into distinct network features

BACKGROUND: The adaptive immune system is based on selected populations of molecularly distinct individual B and T cell clones. However, it has not been possible to characterize these clones in a comprehensive and informatics manner to date; attempts have been limited by the number of cells in the adaptive immune system and an inability to quantify them. Recently, using the Zebrafish (ZF) Danio rerio as a model organism and parallel sequencing as the quantifying technology, Weinstein et al. overcame this major hurdle and quantified the entire heavy chain B-cell repertoire in ZF. Here, we present a novel network analysis of the data from the Weinstein group, providing new insights into the network structure of the B-cell repertoire. RESULTS: Using a collection of computational methods, the IgM sequences from 14 fish were analyzed. This analysis demonstrated that the B-cell repertoire of the ZF is structured along similar lines to those previously detected in limited parts of the human B-cell immune system. The analysis confirms the validity of the global data and the evolutionary placement of the ZF based on known sequence motifs. Recombination events in the repertoire were quantified, and demonstrated a lack of shared recombined V, J groups across fish. Nevertheless, it was demonstrated that a similar network architecture is shared among fish. However, the network analysis identified two distinct populations within the group; these findings are compatible with the occurrence of an immune response in a subset of the fish. The emerging connectivity network was demonstrated and quantified, and mutation drifts within the groups were characterized. Dissection of sequence data revealed common network features of the B-cell repertoire as well as individual differences. CONCLUSION: The ZF B-cell repertoire reveals an underlying order that is compatible with self-organization representing every portion of the sequence-based network. This pattern varies in individual specimens, perhaps as a response to an immune challenge. However, a sequence-non-specific network that maintains a common architecture of sequence diversity was detected. The common feature among different individuals can be captured by the network architecture and characteristics, rather than specific clones. We believe that further study of the dynamics of this network could provide insight into modes of operation of the immune system.