Advancing species identification: A non-invasive molecular approach through spider silk proteome analysis

 

Advancing species identification: A non-invasive molecular approach through spider silk proteome analysis

   Abstract

Species identification is crucial in various scientific disciplines such as biology, ecology, medicine, and agriculture. While traditional methods rely on morphological characteristics, DNA barcoding has gained popularity due to its molecular biology approach. Nonetheless, DNA barcoding can be problematic for small animals such as insects, as it requires damaging their bodies for DNA extraction, impacting subsequent breeding and experiments. In this paper, we propose a non-invasive molecular method for species identification that examines the protein composition of animal produced biomaterials. We chose spider silk, with species-specific protein sequences, as our subject of analysis. First, we established a universal silk-dissolving method that applies to silks from various species. We constructed a bioinformatics pipeline employing metrics of significant difference through proteomic analysis to identify spider species by analyzing peptide sequences present in silk proteins. As a result, we achieved a species identification accuracy of 86% across 15 species. An appropriate reference dataset was successfully created, in addition, we also discovered some species are difficult to distinguish due to sequence similarities. This technology has been confirmed to be applicable to spider webs taken from the field. This non-invasive approach can complement DNA barcoding, especially in situations where it is infeasible, such as in studies involving spider-parasitoid wasps that eat spiders. Furthermore, it can be applied to other organisms that release biological substances, such as silkworm pupae, termite digestive enzymes, and tick saliva, aiding in species identification and pest control efforts.


Advancing species identification: A non-invasive molecular approach through spider silk proteome analysis, Phillip K Yamamoto, Keizo Takasuka, Masaru Mori, Takeshi Masuda, Nobuaki Kono, bioRxiv 2024.05.09.593458; doi: https://doi.org/10.1101/2024.05.09.593458