Temperature adaptation in structure and function in lactate dehydrogenase-A reflects convergent evolution in a few key protein regions

TL;DR

This study shows how a few key amino acid changes in an enzyme help fish adapt to different temperatures, and uses this to build a model predicting their thermal limits.

Contribution

The study identifies convergent evolution in specific protein regions across fish species, enabling a deep learning model to predict thermal adaptation.

Findings

A few amino acid substitutions in LDH-A influence thermal adaptation through changes in hydrophobicity.

Convergent evolution occurs at specific sites (TRSS) across diverse fish species.

A deep learning model was developed to predict thermal limits of fish based on these findings.

Abstract

Substitutions in a few amino acids can significantly alter the structural and functional responses of enzymes to temperature, traits that are closely related to establishing the thermal optima and limits of organisms. A cross-taxa analysis of 277 fish lactate dehydrogenase-A (LDH-A) orthologs, which incorporated bioinformatic, in silico and in vitro methodologies, reveals striking convergence in the sites of temperature-adaptive evolution of LDH-As. Based on these findings, a deep learning model was developed to predict thermal limits of fish. These results further the understanding of how fish adapt to divergent thermal environments and provide a valuable model for assessing the potential thermal ranges of fish.

Adaptive differences in the thermal stabilities of enzyme structure and function play critical roles in establishing the thermal optima and limits of all organisms. Thus, understanding the mechanisms underlying these adaptations can yield insights into protein structure–function relationships, protein evolution, and the consequences of temperature shifts on species distributions. Past studies have suggested that only a small number of amino acid substitutions are needed for adaptive change, but whether similar sites in the sequence, which we term thermal adaptation–related sequence sites (TRSS), and similar changes in amino acid content at these TRSS occur across widely different taxa remains to be elucidated. For detecting TRSS among orthologs of species adapted to a wide range of temperatures, we investigated 277 lactate dehydrogenase-A (LDH-A) orthologs in marine fish from diverse habitats. We validated the importance of several TRSS variants using site-directed mutagenesis on zebrafish LDH-A, effectively recreating the variants in the zebrafish ortholog. Our results indicate that enzyme thermal adaptation arises primarily from a few substitutions that influence hydrophobicity in functionally important regions of secondary structures. These findings reveal striking convergence in the sites (the TRSS) of temperature-adaptive evolution of LDH-As and provide insights into the types of amino acid substitutions that foster adaptation to temperature. Furthermore, the patterns of convergent evolution identified in this study supported development of a deep learning model for predicting thermal limits. This model can provide an important tool for predicting thermal ranges of species and the potential effects of temperature change on distribution patterns.

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