| Literature DB >> 30366463 |
Aldo Nicosia1, Alexander Mikov2, Matteo Cammarata3, Paolo Colombo4, Yaroslav Andreev5,6, Sergey Kozlov7, Angela Cuttitta8.
Abstract
Blue biotechnologies implement marine bio-resources for addressing practical concerns. The isolation of biologically active molecules from marine animals is one of the main ways this field develops. Strikingly, cnidaria are considered as sustainable resources for this purpose, as they possess unique cells for attack and protection, producing an articulated cocktail of bioactive substances. The Mediterranean sea anemone Anemonia viridis has been studied extensively for years. In this short review, we summarize advances in bioprospecting of the A. viridis toxin arsenal. A. viridis RNA datasets and toxin data mining approaches are briefly described. Analysis reveals the major pool of neurotoxins of A. viridis, which are particularly active on sodium and potassium channels. This review therefore integrates progress in both RNA-Seq based and biochemical-based bioprospecting of A. viridis toxins for biotechnological exploitation.Entities:
Keywords: bio-prospecting; computational biology; neurotoxins; transcriptomics
Mesh:
Substances:
Year: 2018 PMID: 30366463 PMCID: PMC6266578 DOI: 10.3390/md16110407
Source DB: PubMed Journal: Mar Drugs ISSN: 1660-3397 Impact factor: 5.118
Transcriptome datasets of A. viridis available at NCBI.
| Accession | Experiment Title | Platform | Submitter | Amount |
|---|---|---|---|---|
| ERX1926108 | Study of mitogenome and corresponding transcriptome of sea anemones | Ion Torrent PGM and Sanger technology | The Arctic University of Norway (UiT) | unspecified |
| Small RNA sequencing of | AB 5500Xl Genetic Analyzer | Urbarova et al., 2018 | 2.9 × 103 Mb | |
| SRX699624 | Illumina HiSeq 2000 | University of Haifa | 5.4 × 103 Mb | |
| Under different accession | Symbiotic sea anemone | ABI-3730 Genetic Analyze (Sanger Technology) | Sabourault et al., 2010 | 39,939 ESTs |
| SRX971460 | Tissue specific transcriptomes of the emerging model organism | Illumina HiSeq 1500 | The Ohio State University | 8.8 × 103 Mb |
| SRX971488 | Tissue specific transcriptomes | Illumina HiSeq 2000 | The Ohio State University | 33.9 × 103 Mb |
Figure 1Pipeline for in silico bio-prospecting and candidate toxins identification. This includes library preparation, RNA deep sequencing, data analyses by motif and/or homology screening, and recovery of matching sequences, expression and subsequent functional testing.
Figure 2Multiple sequence alignment of the NaVs toxins in A. viridis. Based on S-S bonds arrangement, Nav toxins are reported as Type I on the top, Type II on the middle and Type III on the bottom. Alignment was performed with T-coffee tool [43]. Similar residues are written in bold characters and boxed in yellow, whereas conserved residues are in white bold characters and boxed in red. The sequence numbering on the top refers to the alignment. For each alignment, the pattern of Cys residues forming disulfide bridges is shown. Pro-peptide processing sites are pointed out by an inverted black triangle. The four motifs of the active toxins for Avi 9a-1 and Avi 9a-2 are indicated by the blue arrows.
Figure 3Multiple sequence alignment of the KVs toxins in A. viridis. Alignment was performed with the T-coffee tool [43]. Similar residues are written in bold characters and boxed in yellow, whereas conserved residues are in white bold characters and boxed in red. The sequence numbering on the top refers to the alignment. For each alignment, the pattern of Cys residues forming disulfide bridges is shown. Type 1, 2, 3 and 5 KV blockers are reported; while no member of Type 4 has been identified to date. No S-S bonds and Cys pattern are defined for type V KTx because of the absence of any 3D structure experimentally determined to date.