Functionally distinct regions of the locus Leishmania major response 15 control IgE or IFNγ level in addition to skin lesions - Krayem, Imtissal; Sohrabi, Yahya; Havelková, Helena; Gusareva, Elena S.; Strnad, Hynek; Čepičková, Marie; Volkova, Valeryia; Kurey, Iryna; Vojtíšková, Jarmila; Svobodová, Milena; Demant, Peter; Lipoldová, Marie (Frontiers in Immunology, 2023)
Leishmaniasis, a disease caused by parasites of Leishmania spp. endangers more than 1 billion people living in endemic countries and has three clinical forms: cutaneous, mucocutaneous, and visceral. Understanding of individual differences in susceptibility to infection and heterogeneity of its pathology is largely lacking. Different mouse strains show a broad and heterogeneous range of disease manifestations such as skin lesions, splenomegaly, hepatomegaly, and increased serum levels of immunoglobulin E and several cytokines. Genome-wide mapping of these strain differences detected more than 30 QTLs (Quantitative trait loci) that control response to Leishmania major. Some control different combinations of disease manifestations, but the nature of this heterogeneity is not yet clear. In this study we analyzed the L. major response locus Lmr15 originally mapped in the strain CcS-9 that carries 12.5 % of genome of the resistant strain STS on the genetic background of the susceptible strain BALB/c. For this analysis we used advanced intercross line K3FV between the strains BALB/c and STS. We confirmed the previously detected loci Lmr15, Lmr18, Lmr24 and Lmr27 and performed genetic dissection of effects of Lmr15 on chromosome 11. We prepared interval-specific recombinant strains 6232HS1 and 6229FUD, carrying two STS derived segments comprising the peak linkage of Lmr15 whose length were 6.32 and 17.4 Mbp, respectively, and analyzed their response to L. major infection. These experiments revealed at least two linked but functionally distinct chromosomal regions controlling IFNγ response and IgE response, respectively, in addition to control of skin lesions. Bioinformatics and expression analysis identified potential candidate gene Top3a. This finding further clarifies the genetic organization of factors relevant for understanding differences of individual risk of disease.