Molecules (Sep 2022)

Conservation of Three-Dimensional Structure of Lepidoptera and Trichoptera L-Fibroins for 290 Million Years

  • Russell J. Stewart,
  • Paul B. Frandsen,
  • Steffen U. Pauls,
  • Jacqueline Heckenhauer

DOI
https://doi.org/10.3390/molecules27185945
Journal volume & issue
Vol. 27, no. 18
p. 5945

Abstract

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The divergence of sister orders Trichoptera (caddisflies) and Lepidoptera (moths and butterflies) from a silk-spinning ancestor occurred around 290 million years ago. Trichoptera larvae are mainly aquatic, and Lepidoptera larvae are almost entirely terrestrial—distinct habitats that required molecular adaptation of their silk for deployment in water and air, respectively. The major protein components of their silks are heavy chain and light chain fibroins. In an effort to identify molecular changes in L-fibroins that may have contributed to the divergent use of silk in water and air, we used the ColabFold implementation of AlphaFold2 to predict three-dimensional structures of L-fibroins from both orders. A comparison of the structures revealed that despite the ancient divergence, profoundly different habitats, and low sequence conservation, a novel 10-helix core structure was strongly conserved in L-fibroins from both orders. Previously known intra- and intermolecular disulfide linkages were accurately predicted. Structural variations outside of the core may represent molecular changes that contributed to the evolution of insect silks adapted to water or air. The distributions of electrostatic potential, for example, were not conserved and present distinct order-specific surfaces for potential interactions with or modulation by external factors. Additionally, the interactions of L-fibroins with the H-fibroin C-termini are different for these orders; lepidopteran L-fibroins have N-terminal insertions that are not present in trichopteran L-fibroins, which form an unstructured ribbon in isolation but become part of an intermolecular β-sheet when folded with their corresponding H-fibroin C-termini. The results are an example of protein structure prediction from deep sequence data of understudied proteins made possible by AlphaFold2.

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