In silico identification of defensins in the black soldier fly

Abstract

Antimicrobial peptides (AMPs) are small bioactive protein inside eukaryotes and function as first-line immunology defensing against microbial invasion. They have been investigating as a potential solution to address traditional antibiotics problems, which is the exploding antibiotics resistance all over the world. Insects have been demonstrated as a large-valuable source of novel, powerful AMPs with wide structural diversity. Hermetia illucens, which is popularly known as Black Soldier Fly (BSF), was recorded as possessing the largest number of AMPs, in which defensin emerged as the most abundant type and widely functioned against bacteria, fungi, and virus. However, research into the identification, functional evaluation, and therapeutic development of BSF’s AMPs as an alternative for traditional antibiotics still remained in a preliminary stage. This study aimed to discover defensins in BSF genome also their crucial properties. With inhouse bioinformatics pipeline and manual validation, a total of 31 defensins including 22 putative novel defensins were found in chromosome 1, 5, and 6 of BSF genome. All discovered defensins were then tested with various machine learning-algorithms, such as the Support Vector Machine (SVM), the Artificial Neural Network (ANN), the Discriminant Analysis (DA), and the Random Forest (RF) which is available on the Collection of Anti-Microbial Peptides (CAMP) database to predict their microbicidal potency. Besides, MetaiAVP and Antifp tool were used to predict antiviral and antifungal capacity of these peptides, respectively. These analyses generated prediction that all discovered defensins are resistant to bacteria, 17 defensins are effective against virus, and 2 defensins are effective against fungi. When building phylogeny tree, other defensins from closely related species were also included to the list resulting in 54 defensins in total. While almost all annotated defensins specifically clustered in BSF species, there were 4 defensins located closer to other species’defensins. In evolutionary aspect, the result indicated the dynamic evolution of BSF defensins in the context of survival competition. The in silico approaches in this study may contribute to extend the diversity of AMP not only in BSF and insect but also in vertebrate species.