A Multiomics Approach Unravels New Toxins With Possible In Silico Antimicrobial, Antiviral, and Antitumoral Activities in the Venom of Acanthoscurria rondoniae

Abstract

The Araneae order is considered one of the most successful groups among venomous animals in the world. An important factor for this success is the production of venoms, a refined biological fluid rich in proteins, short peptides and cysteine-rich peptides (CRPs). These toxins may present pharmacologically relevant biological actions, as antimicrobial, antiviral and anticancer activities, for instance. Therefore, there is an increasing interest in the exploration of venom toxins for therapeutic reasons, such as drug development. However, the process of peptide sequencing and mainly the evaluation of potential biological activities of these peptides are laborious, considering the low yield of venom extraction and the high variability of toxins present in spider venoms. Here we show a robust methodology for identification, sequencing, and initial screening of potential bioactive peptides found in the venom of Acanthoscurria rondoniae. This methodology consists in a multiomics approach involving proteomics, peptidomics and transcriptomics analyses allied to in silico predictions of antibacterial, antifungal, antiviral, and anticancer activities. Through the application of this strategy, a total of 92,889 venom gland transcripts were assembled and 84 novel toxins were identified at the protein level, including seven short peptides and 10 fully sequenced CRPs (belonging to seven toxin families). In silico analysis suggests that seven CRPs families may have potential antimicrobial or antiviral activities, while two CRPs and four short peptides are potentially anticancer. Taken together, our results demonstrate an effective multiomics strategy for the discovery of new toxins and in silico screening of potential bioactivities. This strategy may be useful in toxin discovery, as well as in the screening of possible activities for the vast diversity of molecules produced by venomous animals.

Combined Transcriptome and Proteome Leukocyte’s Profiling Reveals Up-Regulated Module of Genes/Proteins Related to Low Density Neutrophils and Impaired Transcription and Translation Processes in Clinical Sepsis

“…Label-free quantification was performed in Progenesis QI for proteomics (NonLinear Dynamics, Newcastle, UK) as previously reported ( 23 , 24 ). Briefly, the raw files were loaded in the software, and the samples were aligned based on the precursor ion retention time of the reference run, which was automatically selected.…”

Diversity and prevalence of ANTAR RNAs across actinobacteria

“…An HMM model for the ANTAR domain was taken from Pfam v33.0 (PF03861) and HMMsearch (hmmer v3.2.1) was performed against all actinobacterial proteomes with e-value threshold 1e-4. E-value threshold was determined from previous studies [ 71 – 75 ]. This identified proteins having ANTAR domains.…”

Antimicrobial Peptides Derived From Insects Offer a Novel Therapeutic Option to Combat Biofilm: A Review

“…Currently, in silico drug discovery approach or computational intelligence platform-based drug discovery plays a crucial role both in academia as well as in industry by locating possible active molecules from a bunch of desired molecules, predicts the structure and function of the active molecule with homologous/similar candidates information, able to predict toxicity-pharmacokinetic profiles based on chemical composition, mechanism of inhibition targeting any particular disease associated targets/enzyme, etc., (Malathi and Ramaiah, 2018;Duarte et al, 2019;Swain et al, 2020). Similarly, various tools, databases and software's of bioinformatics can also help speed up the peptide-based research through analysis within a limited time and resources (Gupta et al, 2016;Agrawal et al, 2018;Câmara et al, 2020). The universal National Center for Biotechnology Information (NCBI) 1 , and Universal Protein Resource or UniPort 2 , protein data bank or PDB 3 , with some specific sources such as data repository of antimicrobial peptides or DRAMP 4 , update linking antimicrobial peptides or LAMP2 5 .…”