In-depth transcriptome reveals the potential biotechnological application of Bothrops jararaca venom gland

• Autor(a) principal: Pereira,Leandro de Mattos
• Data de Publicação: 2020
• Outros Autores: Messias,Elisa Alves, Sorroche,Bruna Pereira, Oliveira,Angela das Neves, Arantes,Lidia Maria Rebolho Batista, Carvalho,Ana Carolina de, Tanaka-Azevedo,Anita Mitico, Grego,Kathleen Fernandes, Carvalho,André Lopes, Melendez,Matias Eliseo
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: The Journal of venomous animals and toxins including tropical diseases (Online)
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1678-91992020000100336
• topic: Bothrops jararaca; Venom gland; Transcriptome; Biotechnological application; Stonustoxin; Verrucotoxin

Abstract Background: Lack of complete genomic data of Bothrops jararaca impedes molecular biology research focusing on biotechnological applications of venom gland components. Identification of full-length coding regions of genes is crucial for the correct molecular cloning design. Methods: RNA was extracted from the venom gland of one adult female specimen of Bothrops jararaca. Deep sequencing of the mRNA library was performed using Illumina NextSeq 500 platform. De novo assembly of B. jararaca transcriptome was done using Trinity. Annotation was performed using Blast2GO. All predicted proteins after clustering step were blasted against non-redundant protein database of NCBI using BLASTP. Metabolic pathways present in the transcriptome were annotated using the KAAS-KEGG Automatic Annotation Server. Toxins were identified in the B. jararaca predicted proteome using BLASTP against all protein sequences obtained from Animal Toxin Annotation Project from Uniprot KB/Swiss-Pro database. Figures and data visualization were performed using ggplot2 package in R language environment. Results: We described the in-depth transcriptome analysis of B. jararaca venom gland, in which 76,765 de novo assembled isoforms, 96,044 transcribed genes and 41,196 unique proteins were identified. The most abundant transcript was the zinc metalloproteinase-disintegrin-like jararhagin. Moreover, we identified 78 distinct functional classes of proteins, including toxins, inhibitors and tumor suppressors. Other venom proteins identified were the hemolytic lethal factors stonustoxin and verrucotoxin. Conclusion: It is believed that the application of deep sequencing to the analysis of snake venom transcriptomes may represent invaluable insight on their biotechnological potential focusing on candidate molecules.