bioRxivEvolutionary BiologyPreprint
Dynamic evolution of bacterial ligand recognition by formyl peptide receptors
N. M. Paterson, H. Al-Zubieri, J. Ragona, J. Tirado, B. V. Geisbrecht, M. F. Barber
Abstract
The detection of invasive pathogens is critical for host immune defense. Cell surface receptors play a key role in the recognition of diverse microbe-associated molecules, triggering leukocyte recruitment, phagocytosis, release of antimicrobial factors, and cytokine production. The intense selective forces acting on innate immune receptor genes has led to their rapid diversification across plant and animal species. However, the impacts of this genetic variation on immune functions are often unclear. Formyl peptide receptors (FPRs) are a family of animal G-protein coupled receptors which are activated in response to a variety of ligands including formylated bacterial peptides, microbial virulence factors, and host-derived peptides. Here we investigate patterns of gene loss, sequence diversity, and ligand recognition among primate and carnivore FPRs. We observe that FPR1, which plays a critical role in innate immune defense in humans, has been lost in New World primates. Patterns of amino acid variation in FPR1 and FPR2 suggest a history of repeated positive selection acting on extracellular domains involved in ligand binding. To assess the consequences of FPR variation on bacterial ligand recognition, we measured interactions between primate FPRs and the FPR agonist Staphylococcus aureus enterotoxin B, as well as S. aureus FLIPr-like which functions as an FPR inhibitor. We find that comparatively few sequence differences between great ape FPRs are sufficient to modulate recognition of S. aureus ligands, further demonstrating how genetic variation can act to tune FPR activation in response to diverse microbial binding partners. Together this study reveals how rapid evolution of host immune receptors shapes the detection of diverse microbial molecules.
- organism: human
- organism: mouse
- organism: non-human primate
- assay: proteomics
- research focus: host-pathogen & immune response
- approach: statistical model
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