Putative Antimicrobial Peptides of the Posterior Salivary Glands from the Cephalopod Octopus vulgaris Revealed by Exploring a Composite Protein Database

Identifying Natural Bioactive Peptides from the Common Octopus (Octopus vulgaris Cuvier, 1797) Skin Mucus By-Products Using Proteogenomic Analysis

The common octopus is a cephalopod species subject to active fisheries, with great potential in the aquaculture and food industry, and which serves as a model species for biomedical and behavioral studies. The analysis of the skin mucus allows us to study their health in a non-invasive way, by using a hardly exploited discard of octopus in the fishing sector. A shotgun proteomics approach combined with liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) using an Orbitrap-Elite instrument was used to create a reference dataset from octopus skin mucus. The final proteome compilation was investigated by integrated in-silico studies, including Gene Ontology (GO), the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, network studies, and prediction and characterization analysis of potential bioactive peptides. This work presents the first proteomic analysis of the common octopus skin mucus proteome. This library was created by merging 5937 identified spectra of 2038 different peptides. A total of 510 non-redundant proteins were identified. Obtained results show proteins closely related to the defense, which highlight the role of skin mucus as the first barrier of defense and the interaction with the environment. Finally, the potential of the bioactive peptides with antimicrobial properties, and their possible application in biomedicine, pharmaceutical, and nutraceutical industry was addressed.

Emerging Computational Approaches for Antimicrobial Peptide Discovery

In the last two decades many reports have addressed the application of artificial intelligence (AI) in the search and design of antimicrobial peptides (AMPs). AI has been represented by machine learning (ML) algorithms that use sequence-based features for the discovery of new peptidic scaffolds with promising biological activity. From AI perspective, evolutionary algorithms have been also applied to the rational generation of peptide libraries aimed at the optimization/design of AMPs. However, the literature has scarcely dedicated to other emerging non-conventional in silico approaches for the search/design of such bioactive peptides. Thus, the first motivation here is to bring up some non-standard peptide features that have been used to build classical ML predictive models. Secondly, it is valuable to highlight emerging ML algorithms and alternative computational tools to predict/design AMPs as well as to explore their chemical space. Another point worthy of mention is the recent application of evolutionary algorithms that actually simulate sequence evolution to both the generation of diversity-oriented peptide libraries and the optimization of hit peptides. Last but not least, included here some new considerations in proteogenomic analyses currently incorporated into the computational workflow for unravelling AMPs in natural sources.

Quantitative proteomic analysis of marine biofilms formed by filamentous cyanobacterium

Cyanobacterial molecular biology can identify pathways that affect the adhesion and settlement of biofouling organisms and, consequently, obtain novel antifouling strategies for marine applications. Proteomic analyses can provide an essential understanding of how cyanobacteria adapt to different environmental settings. However, only a few qualitative studies have been performed in some cyanobacterial strains. Considering the limited knowledge about protein expression in cyanobacteria in different growing conditions, a quantitative proteomic analysis by LC-MS/MS of biofilm cells from a filamentous strain was performed. Biofilms were also analysed through standard methodologies for following cyanobacterial biofilm development. Biofilms were formed on glass and perspex at two relevant hydrodynamic conditions for marine environments (average shear rates of 4 s^-1 and 40 s^-1). Biofilm development was higher at 4 s^-1 and no significant differences were found between surfaces. Proteomic analysis identified 546 proteins and 41 were differentially expressed. Differences in protein expression were more noticeable between biofilms formed on glass and perspex at 4 s^-1. When comparing biofilms formed on different surfaces, results suggest that biofilm development may be related to the expression of several proteins like a beta-propeller domain-containing protein, chaperone DnaK, SLH domain-containing proteins, an OMF family outer membrane protein, and/or additional uncharacterized proteins. Regarding the hydrodynamic effect, biofilm development can be related to SOD enzyme expression, to proteins related to photosynthetic processes and to a set of uncharacterized proteins with calcium binding domains, disordered proteins, and others involved in electron transfer activity. Studies that combine distinct approaches are essential for finding new targets for antibiofilm agents. The characterisation performed in this work provides new insights into how shear rate and surface affect cyanobacterial biofilm development and how cyanobacteria adapt to these different environmental settings from a macroscopic standpoint to a proteomics context.

Bioactive compounds from Octopus vulgaris ink extracts exerted anti-proliferative and anti-inflammatory effects in vitro

Underutilized marine food products such as cephalopods' ink could be sources of bioactive compounds providing health benefits. This study aimed to assess the anti-proliferative and anti-inflammatory effects from Octopus vulgaris ink extracts (hexane-, ethyl acetate-, dichloromethane- (DM), and water extracts) using human colorectal (HT-29/HCT116) and breast (MDA-MB-231) cancer cells, and LPS-challenged murine RAW 264.7 cells. Except by ethyl-acetate, all of the extracts exhibited anti-proliferative effects without being cytotoxic to ARPE-19 and RAW 264.7 cells. Among DM fractions (F1/F2/F3), DM-F2 showed the highest anti-proliferative effect (LC₅₀ = 52.64 μg/mL), inducing pro-apoptotic morphological disruptions in HCT116 cells. On RAW 264.7 cells, DM-F2 displayed the lowest nitrites reduction and up-regulation of key-cytokines from the JAK-STAT, PI3K-Akt, and IL-17 pathways. Compared to control, DM-F2 increased IL-4 and decreased NF-κB fluorometric expression in peripheral blood mononuclear cells (PBMCs). Metabolomic analysis of DM-F2 highlighted hexadecanoic acid and 1-(15-methyl-1-oxohexadecyl)-pyrrolidine as the most important metabolites. These compounds also exhibited high in silico binding affinity (-4.6 to -5.8 kcal/mol) to IL-1α, IL-1β, and IL-2. Results suggested the joint immuno-modulatory and anti-proliferative effect derived from selected compounds of underutilized marine food products such as ink. This is the first report of such biological activities in extracts from O. vulgaris ink.

Data Employed in the Construction of a Composite Protein Database for Proteogenomic Analyses of Cephalopods Salivary Apparatus

Here we provide all datasets and details applied in the construction of a composite protein database required for the proteogenomic analyses of the article “Putative Antimicrobial Peptides of the Posterior Salivary Glands from the Cephalopod Octopus vulgaris Revealed by Exploring a Composite Protein Database”. All data, subdivided into six datasets, are deposited at the Mendeley Data repository as follows. Dataset_1 provides our composite database “All_Databases_5950827_sequences.fasta” derived from six smaller databases composed of (i) protein sequences retrieved from public databases related to cephalopods’ salivary glands, (ii) proteins identified with Proteome Discoverer software using our original data obtained by shotgun proteomic analyses of posterior salivary glands (PSGs) from three Octopus vulgaris specimens (provided as Dataset_2) and (iii) a non-redundant antimicrobial peptide (AMP) database. Dataset_3 includes the transcripts obtained by de novo assembly of 16 transcriptomes from cephalopods’ PSGs using CLC Genomics Workbench. Dataset_4 provides the proteins predicted by the TransDecoder tool from the de novo assembly of 16 transcriptomes of cephalopods’ PSGs. Further details about database construction, as well as the scripts and command lines used to construct them, are deposited within Dataset_5 and Dataset_6. The data provided in this article will assist in unravelling the role of cephalopods’ PSGs in feeding strategies, toxins and AMP production.