Excretory-secretory products from the brown stomach worm, Teladorsagia circumcincta, exert antimicrobial activity in in vitro growth assays

Structural and functional analyses of nematode-derived antimicrobial peptides support the occurrence of direct mechanisms of worm-microbiota interactions

The complex relationships between gastrointestinal (GI) nematodes and the host gut microbiota have been implicated in key aspects of helminth disease and infection outcomes. Nevertheless, the direct and indirect mechanisms governing these interactions are, thus far, largely unknown. In this proof-of-concept study, we demonstrate that the excretory-secretory products (ESPs) and extracellular vesicles (EVs) of key GI nematodes contain peptides that, when recombinantly expressed, exert antimicrobial activity in vitro against Bacillus subtilis. In particular, using time-lapse microfluidics microscopy, we demonstrate that exposure of B. subtilis to a recombinant saposin-domain containing peptide from the 'brown stomach worm', Teladorsagia circumcincta, and a metridin-like ShK toxin from the 'barber's pole worm', Haemonchus contortus, results in cell lysis and significantly reduced growth rates. Data from this study support the hypothesis that GI nematodes may modulate the composition of the vertebrate gut microbiota directly via the secretion of antimicrobial peptides, and pave the way for future investigations aimed at deciphering the impact of such changes on the pathophysiology of GI helminth infection and disease.

A dominance of Mu class glutathione transferases within the equine tapeworm Anoplocephala perfoliata

The most common equine tapeworm, Anoplocephala perfoliata, has often been neglected amongst molecular investigations and has been faced with limited treatment options. However, the recent release of a transcriptome dataset has now provided opportunities for in-depth analysis of A. perfoliata protein expression. Here, global, and sub-proteomic approaches were utilized to provide a comprehensive characterization of the A. perfoliata soluble glutathione transferases (GST) (ApGST). Utilizing both bioinformatics and gel-based proteomics, GeLC and 2D-SDS PAGE, the A. perfoliata ‘GST-ome’ was observed to be dominated with Mu class GST representatives. In addition, both Sigma and Omega class GSTs were identified, albeit to a lesser extent and absent from affinity chromatography approaches. Moreover, 51 ApGSTs were localized across somatic (47 GSTs), extracellular vesicles (EVs) (Whole: 1 GST, Surface: 2 GSTs) and EV depleted excretory secretory product (ESP) (9 GSTs) proteomes. In related helminths, GSTs have shown promise as novel anthelmintic or vaccine targets for improved helminth control. Thus, provides potential targets for understanding A. perfoliata novel infection mechanisms, host–parasite relationships and anthelmintic treatments.

Integrating a Multi-label Deep Learning Approach with Protein Information to Compare Bioactive Peptides in Brain and Plasma

Peptide therapeutics is gaining momentum. Advances in the field of peptidomics have enabled researchers to harvest vital information from various organisms and tissue types concerning peptide existence, expression and function. The development of mass spectrometry techniques for high-throughput peptide quantitation has paved the way for the identification and discovery of numerous known and novel peptides. Though much has been achieved, scientists are still facing difficulties when it comes to reducing the search space of the large mass spectrometry-generated peptidomics datasets and focusing on the subset of functionally relevant peptides. Moreover, there is currently no straightforward way to analytically compare the distributions of bioactive peptides in distinct biological samples, which may reveal much useful information when seeking to characterize tissue- or fluid-specific peptidomes. In this chapter, we demonstrate how to identify, rank, and compare predicted bioactive peptides and bioactivity distributions from extensive peptidomics datasets. To aid this task, we utilize MultiPep, a multi-label deep learning approach designed for classifying peptide bioactivities, to identify bioactive peptides. The predicted bioactivities are synergistically combined with protein information from the UniProt database, which assist in navigating through the jungle of putative therapeutic peptides and relevant peptide leads.

Helminthic host defense peptides: using the parasite to defend the host

Parasitic helminths are destined to share niches with a variety of microbiota that inevitably influence their interaction with the host. To modulate the microbiome for their benefit and defend against pathogenic isolates, helminths have developed host defense peptides (HDPs) and proteins as integral elements of their immunity. These often exert a relatively nonspecific membranolytic activity toward bacteria, sometimes with limited or no toxicity toward host cells. With a few exceptions, such as nematode cecropin-like peptides and antibacterial factors (ABFs), helminthic HDPs are largely underexplored. This review scrutinizes current knowledge on the repertoire of such peptides in helminths and promotes their research as potential leads for an anti-infective solution to the burgeoning problem of antibiotic resistance.