Associating Biological Activity and Predicted Structure of Antimicrobial Peptides from Amphibians and Insects

Assessing Wolbachia circulation in wild populations of phlebotomine sand flies from Spain and Morocco: implications for control of leishmaniasis

BACKGROUND

Vector-borne diseases such as leishmaniasis exert a huge burden of morbidity and mortality that are mainly controlled through vector control. The increasing threat of insecticide-resistant vectors entails incorporating more vector control interventions to eliminate these diseases. Introduction of Wolbachia into wild vector populations has been suggested as a potential vector control measure that would require extensive regional knowledge. The aim of this work is to estimate the prevalence of Wolbachia infection and monitor circulating strains in wild sand fly populations from Spain and Morocco, two countries where leishmaniasis is endemic.

METHODS

Wolbachia was detected using polymerase chain reaction (PCR). Haplotype diversity was performed by sequencing, and phylogenetic relationships were then established. In silico prediction of the Wolbachia surface protein (WSP) structures was performed. To investigate the relationship between epidemiological variables and the presence of Wolbachia, regression analyses were employed.

RESULTS

Wolbachia was detected in 45.8% of the specimens tested (319/697), and similar infection rates were found (P = 0.92) in males (46.1%; 94/204) and females (45.6%; 225/493). Differences in infection were detected among Spanish sand fly species (P < 0.001), being higher for Phlebotomus papatasi (35/52) and Phlebotomus perniciosus (239/384). No infected Phlebotomus sergenti specimens were found in Spain, whereas two different Wolbachia haplotypes were detected in P. sergenti sand flies from Morocco. No significant differences were found between sex, species, or capture sites in specimens captured in Morocco (P > 0.05). Five Wolbachia haplotypes distributed in the known A and B supergroups were identified. Structural analysis showed a nine-amino acid insertion in the fourth loop of a Wolbachia haplotype found in P. sergenti specimens from El Borouj (Morocco).

CONCLUSIONS

We confirmed the circulation of different Wolbachia strains in all sand fly species investigated. All L. infantum proven or suspected vectors shared the same, or a closely related, Wolbachia haplotype. The haplotype bearing the loop insertion was found in the locality undergoing an anthroponotic cutaneous leishmaniasis outbreak. These extracellular loops might have some role in enhancing or inhibiting the development of Leishmania and other pathogens in sand flies. These findings are very promising and highlight the need to further investigate the tripartite interactions between Wolbachia strain, Leishmania species, and sand fly species/lineage.

Mining the UniProtKB/Swiss-Prot database for antimicrobial peptides

The ever-growing global health threat of antibiotic resistance is compelling researchers to explore alternatives to conventional antibiotics. Antimicrobial peptides (AMPs) are emerging as a promising solution to fill this need. Naturally occurring AMPs are produced by all forms of life as part of the innate immune system. High-throughput bioinformatics tools have enabled fast and large-scale discovery of AMPs from genomic, transcriptomic, and proteomic resources of selected organisms. Public protein sequence databases, comprising over 200 million records and growing, serve as comprehensive compendia of sequences from a broad range of source organisms. Yet, large-scale in silico probing of those databases for novel AMP discovery using modern deep learning techniques has rarely been reported. In the present study, we propose an AMP mining workflow to predict novel AMPs from the UniProtKB/Swiss-Prot database using the AMP prediction tool, AMPlify, as its discovery engine. Using this workflow, we identified 8008 novel putative AMPs from all eukaryotic sequences in the database. Focusing on the practical use of AMPs as suitable antimicrobial agents with applications in the poultry industry, we prioritized 40 of those AMPs based on their similarities to known chicken AMPs in predicted structures. In our tests, 13 out of the 38 successfully synthesized peptides showed antimicrobial activity against Escherichia coli and/or Staphylococcus aureus. AMPlify and the companion scripts supporting the AMP mining workflow presented herein are publicly available at https://github.com/bcgsc/AMPlify.

De novo synthetic antimicrobial peptide design with a recurrent neural network

Antibiotic resistance is recognized as an imminent and growing global health threat. New antimicrobial drugs are urgently needed due to the decreasing effectiveness of conventional small-molecule antibiotics. Antimicrobial peptides (AMPs), a class of host defense peptides, are emerging as promising candidates to address this need. The potential sequence space of amino acids is combinatorially vast, making it possible to extend the current arsenal of antimicrobial agents with a practically infinite number of new peptide-based candidates. However, mining naturally occurring AMPs, whether directly by wet lab screening methods or aided by bioinformatics prediction tools, has its theoretical limit regarding the number of samples or genomic/transcriptomic resources researchers have access to. Further, manually designing novel synthetic AMPs requires prior field knowledge, restricting its throughput. In silico sequence generation methods are gaining interest as a high-throughput solution to the problem. Here, we introduce AMPd-Up, a recurrent neural network based tool for de novo AMP design, and demonstrate its utility over existing methods. Validation of candidates designed by AMPd-Up through antimicrobial susceptibility testing revealed that 40 of the 58 generated sequences possessed antimicrobial activity against Escherichia coli and/or Staphylococcus aureus. These results illustrate that AMPd-Up can be used to design novel synthetic AMPs with potent activities.

Structure-aware deep learning model for peptide toxicity prediction

Antimicrobial resistance is a critical public health concern, necessitating the exploration of alternative treatments. While antimicrobial peptides (AMPs) show promise, assessing their toxicity using traditional wet lab methods is both time-consuming and costly. We introduce tAMPer, a novel multi-modal deep learning model designed to predict peptide toxicity by integrating the underlying amino acid sequence composition and the three-dimensional structure of peptides. tAMPer adopts a graph-based representation for peptides, encoding ColabFold-predicted structures, where nodes represent amino acids and edges represent spatial interactions. Structural features are extracted using graph neural networks, and recurrent neural networks capture sequential dependencies. tAMPer's performance was assessed on a publicly available protein toxicity benchmark and an AMP hemolysis data we generated. On the latter, tAMPer achieves an F1-score of 68.7%, outperforming the second-best method by 23.4%. On the protein benchmark, tAMPer exhibited an improvement of over 3.0% in the F1-score compared to current state-of-the-art methods. We anticipate tAMPer to accelerate AMP discovery and development by reducing the reliance on laborious toxicity screening experiments.

Transcriptomic profiling of Rana [Lithobates] catesbeiana back skin during natural and thyroid hormone-induced metamorphosis under different temperature regimes with particular emphasis on innate immune system components

As amphibians undergo thyroid hormone (TH)-dependent metamorphosis from an aquatic tadpole to the terrestrial frog, their innate immune system must adapt to the new environment. Skin is a primary line of defense, yet this organ undergoes extensive remodelling during metamorphosis and how it responds to TH is poorly understood. Temperature modulation, which regulates metamorphic timing, is a unique way to uncover early TH-induced transcriptomic events. Metamorphosis of premetamorphic tadpoles is induced by exogenous TH administration at 24 °C but is paused at 5 °C. However, at 5 °C a "molecular memory" of TH exposure is retained that results in an accelerated metamorphosis upon shifting to 24 °C. We used RNA-sequencing to identify changes in Rana (Lithobates) catesbeiana back skin gene expression during natural and TH-induced metamorphosis. During natural metamorphosis, significant differential expression (DE) was observed in >6500 transcripts including classic TH-responsive transcripts (thrb and thibz), heat shock proteins, and innate immune system components: keratins, mucins, and antimicrobial peptides (AMPs). Premetamorphic tadpoles maintained at 5 °C showed 83 DE transcripts within 48 h after TH administration, including thibz which has previously been identified as a molecular memory component in other tissues. Over 3600 DE transcripts were detected in TH-treated tadpoles at 24 °C or when tadpoles held at 5 °C were shifted to 24 °C. Gene ontology (GO) terms related to transcription, RNA metabolic processes, and translation were enriched in both datasets and immune related GO terms were observed in the temperature-modulated experiment. Our findings have implications on survival as climate change affects amphibia worldwide.

Diversity and Molecular Evolution of Antimicrobial Peptides in Caecilian Amphibians

Antimicrobial peptides (AMPs) are key molecules in the innate immune defence of vertebrates with rapid action, broad antimicrobial spectrum, and ability to evade pathogen resistance mechanisms. To date, amphibians are the major group of vertebrates from which most AMPs have been characterised, but most studies have focused on the bioactive skin secretions of anurans (frogs and toads). In this study, we have analysed the complete genomes and/or transcriptomes of eight species of caecilian amphibians (order Gymnophiona) and characterised the diversity, molecular evolution, and antimicrobial potential of the AMP repertoire of this order of amphibians. We have identified 477 candidate AMPs within the studied caecilian genome and transcriptome datasets. These candidates are grouped into 29 AMP families, with four corresponding to peptides primarily exhibiting antimicrobial activity and 25 potentially serving as AMPs in a secondary function, either in their entirety or after cleavage. In silico prediction methods were used to identify 62 of those AMPs as peptides with promising antimicrobial activity potential. Signatures of directional selection were detected for five candidate AMPs, which may indicate adaptation to the different selective pressures imposed by evolutionary arms races with specific pathogens. These findings provide encouraging support for the expectation that caecilians, being one of the least-studied groups of vertebrates, and with ~300 million years of separate evolution, are an underexplored resource of great pharmaceutical potential that could help to contest antibiotic resistance and contribute to biomedical advance.

The Potential Use of Peptides in the Fight against Chagas Disease and Leishmaniasis

Chagas disease and leishmaniasis are both neglected tropical diseases that affect millions of people around the world. Leishmaniasis is currently the second most widespread vector-borne parasitic disease after malaria. The World Health Organization records approximately 0.7-1 million newly diagnosed leishmaniasis cases each year, resulting in approximately 20,000-30,000 deaths. Also, 25 million people worldwide are at risk of Chagas disease and an estimated 6 million people are infected with Trypanosoma cruzi. Pentavalent antimonials, amphotericin B, miltefosine, paromomycin, and pentamidine are currently used to treat leishmaniasis. Also, nifurtimox and benznidazole are two drugs currently used to treat Chagas disease. These drugs are associated with toxicity problems such as nephrotoxicity and cardiotoxicity, in addition to resistance problems. As a result, the discovery of novel therapeutic agents has emerged as a top priority and a promising alternative. Overall, there is a need for new and effective treatments for Chagas disease and leishmaniasis, as the current drugs have significant limitations. Peptide-based drugs are attractive due to their high selectiveness, effectiveness, low toxicity, and ease of production. This paper reviews the potential use of peptides in the treatment of Chagas disease and leishmaniasis. Several studies have demonstrated that peptides are effective against Chagas disease and leishmaniasis, suggesting their use in drug therapy for these diseases. Overall, peptides have the potential to be effective therapeutic agents against Chagas disease and leishmaniasis, but more research is needed to fully investigate their potential.