Yamamoto Phillip K, Takasuka Keizo, Mori Masaru, Masuda Takeshi, Kono Nobuaki
Systems Biology Program, Graduate School of Media and Governance, Keio University, Fujisawa, Kanagawa, 252-0882, Japan.
Institute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata, 997-0017, Japan.
Sci Rep. 2025 Apr 22;15(1):13844. doi: 10.1038/s41598-025-97105-0.
Accurate species identification is essential in biology, ecology, medicine, and agriculture, yet traditional methods relying on morphological characteristics often fail due to phenotypic plasticity and cryptic species. These limitations are particularly pronounced in small organisms with minimal distinguishing features. DNA barcoding has become a popular alternative; however, it requires invasive tissue sampling, making it unsuitable for delicate or rare organisms like insects and spiders. To address this challenge, we propose a non-invasive molecular method using proteomic analysis focused on species-specific protein sequences in spider silk, offering a viable solution for species identification without harming specimens. We developed a universal silk-dissolving method, followed by sequence similarity analysis to classify species into those identifiable at the species level and those distinguishable only to a group of closely related species. A bioinformatics pipeline was established to analyze peptide sequences, achieving 96% accuracy across 15 spider species, even in the presence of contaminants. This technique complements DNA barcoding and can be extended to other organisms producing biological materials. It holds promise in pest management, medical diagnostics, and improving public health by enabling accurate species identification without invasive procedures.
准确的物种鉴定在生物学、生态学、医学和农业领域至关重要,但依赖形态特征的传统方法往往因表型可塑性和隐存种而失败。这些局限性在具有极少显著特征的小型生物中尤为明显。DNA条形码已成为一种流行的替代方法;然而,它需要进行侵入性组织采样,这使得它不适用于昆虫和蜘蛛等脆弱或珍稀生物。为应对这一挑战,我们提出了一种非侵入性分子方法,利用蛋白质组分析聚焦于蜘蛛丝中的物种特异性蛋白质序列,为物种鉴定提供了一种可行的解决方案,同时不会伤害标本。我们开发了一种通用的丝溶解方法,随后进行序列相似性分析,将物种分为可在物种水平鉴定的和只能区分到一组近缘物种的。建立了一个生物信息学流程来分析肽序列,在存在污染物的情况下,对15种蜘蛛物种的准确率达到了96%。这项技术补充了DNA条形码,并且可以扩展到其他产生生物材料的生物。它有望通过无需侵入性程序就能实现准确的物种鉴定,在害虫管理、医学诊断和改善公共卫生方面发挥作用。