Abstract
The transmembrane pattern recognition receptor, Toll-like receptor (TLR), are best known for their roles in innate immunity via recognition of pathogen and initiation of signaling response. Mammalian TLRs recognize molecular patterns associated with pathogens and initiate innate immune response. We have studied the evolutionary diversity of mammalian TLR genes for differences in immunological response. Reconstruction of ancestral sequences is a key aspect of the molecular evolution of TLR to track changes across the TLR genes. The comprehensive analysis of mammalian TLRs revealed a distinct pattern of evolution of TLR9. Various sequence-based features such as amino acid usage, hydrophobicity, GC content, and evolutionary constraints are found to influence the divergence of TLR9 from other TLRs. Ancestral sequence reconstruction analysis also revealed that the gradual evolution of TLR genes in several ancestral lineages leads to the distinct pattern of TLR9. It demonstrates evolutionary divergence with the progressive accumulation of mutations results in the distinct pattern of TLR9.
Similar content being viewed by others
Data Availability
All sequence information is available in public databases and the accession numbers of the sequences used in the present study are provided in Supplementary Table 1.
References
Areal H, Abrantes J, Esteves PJ (2011) Signatures of positive selection in Toll-like receptor (TLR) genes in mammals. BMC Evol Biol 11:368. https://doi.org/10.1186/1471-2148-11-368
Botos I, Segal DM, Davies DR (2011) The structural biology of Toll-like receptors. Structure 19:447–459. https://doi.org/10.1016/j.str.2011.02.004
Cook DN, Pisetsky DS, Schwartz DA (2004) Toll-like receptors in the pathogenesis of human disease. Nat Immunol 5:975–979. https://doi.org/10.1038/ni1116
de Castro E, Sigrist CJ, Gattiker A et al (2006) ScanProsite: detection of PROSITE signature matches and ProRule-associated functional and structural residues in proteins. Nucleic Acids Res 34(W362):W365. https://doi.org/10.1093/nar/gkl124
Ghosh M, Basak S, Dutta S (2022) Natural selection shaped the evolution of amino acid usage in mammalian toll like receptor genes. Comput Biol Chem 97:107637. https://doi.org/10.1016/j.compbiolchem.2022.107637
Gumulya Y, Gillam EM (2017) Exploring the past and the future of protein evolution with ancestral sequence reconstruction: the ‘retro’ approach to protein engineering. Biochem J 474:1–19. https://doi.org/10.1042/BCJ20160507
Karapetyan L, Luke JJ, Davar D (2020) Toll-like receptor 9 agonists in cancer. Onco Targets Ther 13:10039–10060. https://doi.org/10.2147/OTT.S247050
Khan RT, Musil M, Stourac J (2021) Fully automated ancestral sequence reconstruction using FireProtASR. Curr Protoc 1:e30. https://doi.org/10.1002/cpz1.30
Kumar S, Stecher G, Li M et al (2018) MEGA X: molecular evolutionary genetics analysis across computing platforms. Mol Biol Evol 35(6):1547–1549. https://doi.org/10.1093/molbev/msy096
Madeira F, Pearce M, Tivey ARN et al (2022) Search and sequence analysis tools services from EMBL-EBI in 2022. Nucleic Acids Res 50:W276–W279. https://doi.org/10.1093/nar/gkac240
Merkl R, Sterner R (2016) Ancestral protein reconstruction: techniques and applications. Biol Chem 397:1–21. https://doi.org/10.1515/hsz-2015-0158
Mirdita M, Schütze K, Moriwaki Y et al (2022) ColabFold: making protein folding accessible to all. Nat Methods 19:679–682. https://doi.org/10.1038/s41592-022-01488-1
Muffato M, Louis A, Nguyen NTT (2023) Reconstruction of hundreds of reference ancestral genomes across the eukaryotic kingdom. Nat Ecol Evol 7:355–366. https://doi.org/10.1038/s41559-022-01956-z
Musil M, Khan RT, Beier A et al (2021) FireProtASR a web server for fully automated ancestral sequence reconstruction. Brief Bioinform 22:bbaa337. https://doi.org/10.1093/bib/bbaa337
Nei M, Gojobori T (1986) Simple methods for estimating the numbers of synonymous and nonsynonymous nucleotide substitutions. Mol Biol Evol 3:418–426. https://doi.org/10.1093/oxfordjournals.molbev.a040410
Nie L, Cai SY, Shao JZ et al (2018) Toll-like receptors, associated biological roles, and signaling networks in non-mammals. Front Immunol 9:1523. https://doi.org/10.3389/fimmu.2018.01523
Peden JF (2000) Analysis of codon usage (Doctoral dissertation). University of Nottingham, United Kingdom
Roach JC, Glusman G, Rowen L et al (2005) The evolution of vertebrate Toll-like receptors. Proc Natl Acad Sci USA 102:9577–9582. https://doi.org/10.1073/pnas.0502272102
Roy A, Banerjee R, Basak S (2017) HIV progression depends on codon and amino acid usage profile of envelope protein and associated host-genetic influence. Front Microbiol 8:1083. https://doi.org/10.3389/fmicb.2017.01083
Takeda K, Akira S (2005) Toll-like receptors in innate immunity. Int Immunol 17:1–14. https://doi.org/10.1093/intimm/dxh186
Vidya MK, Kumar VG, Sejian V et al (2018) Toll-like receptors: significance, ligands, signaling pathways, and functions in mammals. Int Rev Immunol 37:20–36. https://doi.org/10.1080/08830185.2017.1380200
Yan Y, Zhang D, Zhou P et al (2017) HDOCK: a web server for protein-protein and protein-DNA/RNA docking based on a hybrid strategy. Nucleic Acids Res 45:W365–W373. https://doi.org/10.1093/nar/gkx407
Yang Z (2007) PAML 4: phylogenetic analysis by maximum likelihood. Mol Biol Evol 24:1586–1591. https://doi.org/10.1093/molbev/msm088
Yang Z, Zeng X, Zhao Y et al (2023) AlphaFold2 and its applications in the fields of biology and medicine. Signal Transduct Target Ther 8:115. https://doi.org/10.1038/s41392-023-01381-z
Zhang Y, Skolnick J (2005) TM-align: a protein structure alignment algorithm based on the TM-score. Nucleic Acids Res 33:2302–2309. https://doi.org/10.1093/nar/gki524
Zhou W, Li Y, Pan X, Gao Y et al (2013) Toll-like receptor 9 interaction with CpG ODN–an in silico analysis approach. Theor Biol Med Model 10:18. https://doi.org/10.1186/1742-4682-10-18
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Below is the link to the electronic supplementary material.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Ghosh, M., Basak, S. & Dutta, S. Evolutionary divergence of TLR9 through ancestral sequence reconstruction. Immunogenetics 76, 203–211 (2024). https://doi.org/10.1007/s00251-024-01338-8
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00251-024-01338-8