Variation in Leishmania chemokine suppression driven by diversification of the GP63 virulence factor

Abstract

Leishmaniasis is a neglected tropical disease with diverse outcomes ranging from self-healing lesions, to progressive non-healing lesions, to metastatic spread and destruction of mucous membranes. Although resolution of cutaneous leishmaniasis is a classic example of type-1 immunity leading to self-healing lesions, an excess of type-1 related inflammation can contribute to immunopathology and metastatic spread. Leishmania genetic diversity can contribute to variation in polarization and robustness of the immune response through differences in both pathogen sensing by the host and immune evasion by the parasite. In this study, we observed a difference in parasite chemokine suppression between the Leishmania (L.) subgenus and the Viannia (V.) subgenus, which is associated with severe immune-mediated pathology such as mucocutaneous leishmaniasis. While Leishmania (L.) subgenus parasites utilize the virulence factor and metalloprotease glycoprotein-63 (gp63) to suppress the type-1 associated host chemokine CXCL10, L. (V.) panamensis did not suppress CXCL10. To understand the molecular basis for the inter-species variation in chemokine suppression, we used in silico modeling to identify a putative CXCL10-binding site on GP63. The putative CXCL10 binding site is in a region of gp63 under significant positive selection, and it varies from the L. major wild-type sequence in all gp63 alleles identified in the L. (V.) panamensis reference genome. Mutating wild-type L. (L.) major gp63 to the L. (V.) panamensis sequence at the putative binding site impaired cleavage of CXCL10 but not a non-specific protease substrate. Notably, Viannia clinical isolates confirmed that L. (V.) panamensis primarily encodes non-CXCL10-cleaving gp63 alleles. In contrast, L. (V.) braziliensis has an intermediate level of activity, consistent with this species having more equal proportions of both alleles. Our results demonstrate how parasite genetic diversity can contribute to variation in immune responses to Leishmania spp. infection that may play critical roles in the outcome of infection.

Revisiting Leishmania GP63 host cell targets reveals a limited spectrum of substrates

“…The abundant Leishmania zinc-metalloprotease GP63 is one of the pathogenicity factors that contribute to the colonization of mammalian hosts through the modulation of antimicrobial mechanisms and immune evasion [ 13 , 15 , 21 , 30 , 36 , 38 , 41 ]. The main mode of action of GP63 resides in the cleavage/degradation of key host proteins that regulate processes involved in host defense against infection.…”

“…mechanisms and immune evasion [13,15,21,30,36,38,41]. The main mode of action of GP63 resides in the cleavage/degradation of key host proteins that regulate processes involved in host defense against infection.…”

TriTrypDB: An integrated functional genomics resource for kinetoplastida

“…Some of the TriTrypDB tools that are popularly used by researchers include the genome browser [ 83 , 90 ], GO enrichment [ 19 , 86 ] and BLAST [ 71 , 79 ]. In addition, researchers have utilized integrated datasets including MS-based proteomics [ 91 , 92 ], RNAi [ 87 ] and SNPs [ 93 ], implemented searches ranging from gene IDs [ 94 ], text/ keywords [ 76 , 94 ], EC numbers [ 95 ], protein features and properties such as InterPro domains, signal peptides and transmembrane domains [ 86 , 96 , 97 ], and the search strategy system [ 86 ] to ask their research questions or test their hypotheses.…”

“…Below are a few recent examples of how TriTrypDB data and tools have been utilized by the research community to conduct their own research. TriTrypDB genomes and annotations have been used to characterize individual genes [69][70][71][72][73] or gene families [74,75], identify orthologs across species [55,70,76], conduct genome-wide analyses to study genetic variations such as SNPs, CNVs and hybridization events [77][78][79], perform comparative genomic [80][81][82] and phylogenetic/ phylogenomic [82,83] analyses, and as reference genomes for the assembly and/or annotation of newly generated genomes [16,84]. Similarly, the genome assemblies and annotations have also been utilized for the analysis of differential gene expression [19,72,85], protein expression [85][86][87], the identification of post-translational modifications [72] and potential new genes missing in the official gene sets [88].…”

“…Some of the TriTrypDB tools that are popularly used by researchers include the genome browser [83,90], GO enrichment [19,86] and BLAST [71,79]. In addition, researchers have utilized integrated datasets including MS-based proteomics [91,92], RNAi [87] and SNPs [93], implemented searches ranging from gene IDs [94], text/ keywords [76,94], EC numbers [95],…”