Peptidomics of Haemonchus contortus

Abstract

The nematode Haemonchus contortus (the barber’s pole worm) is an endoparasite infecting wild and domesticated ruminants worldwide. Widespread anthelmintic resistance of H. contortus requires alternative strategies to control this parasite. Neuropeptide signaling represents a promising target for anthelmintic drugs. Identification and relative quantification of nematode neuropeptides are, therefore, required for the development of such therapeutic targets. In this work, we undertook the profiling of the whole H. contortus larvae at different stages for the direct sequencing of the neuropeptides expressed at low levels in these tissues. We set out a peptide extraction protocol and a peptidomic workflow to biochemically characterize bioactive peptides from both first-stage (L1) and third-stage larvae (L3) of H. contortus . This work led to the identification and quantification at the peptidomic level of more than 180 mature neuropeptides, including amidated and nonamidated peptides, arising from 55 precursors of H. contortus . The differential peptidomic approach provided evidence that both life stages express most FMRFamide-like peptides (FLPs) and neuropeptide-like proteins (NLPs). The H. contortus peptidome resource, established in this work, could add the discovery of neuropeptide system-targeting drugs for ruminants.

Advancing Strongyloides omics data: bridging the gap with Caenorhabditis elegans

“…The Schoofs laboratory has developed a high-throughput LC–MS/MS peptidomics approach adapted from Drosophila melanogaster for application in C. elegans . This has resulted in the identification of a raft of C. elegans neuropeptides [147–149] that have also been detected in parasitic nematodes [150,151]. Advances in C. elegans peptidomics highlights the need for expanded LC–MS/MS studies in parasitic nematodes that exploit in silico analyses [152,153] and interrogate somatic, ESP and EV extracts.…”

“…The Schoofs laboratory has developed a high-throughput LC-MS/MS peptidomics approach adapted from Drosophila melanogaster for application in C. elegans. This has resulted in the identification of a raft of C. elegans neuropeptides [147][148][149] that have also been detected in parasitic nematodes [150,151]. Advances in C. elegans peptidomics highlights the need for expanded LC-MS/MS studies in parasitic nematodes that exploit in silico analyses [152,153] peptidomics data parallel advances in LC-MS/MS technology, it will become possible to map specific cell/neuron peptide expression and dynamics to provide novel insights into nematode peptide biology that will also aid our understanding of parasite systems.…”

“…Much of the initial parasitic nematode peptidomics research was focused on the pig parasite A. suum [154][155][156][157]. Since the advent of high-throughput peptidomics only H. contortus has been studied in addition to A. suum, and the focus has primarily been the identification of neuropeptide and antimicrobial peptide profiles in somatic extracts [150,151,158].…”

“…peptidomics studies will rely on the continued expansion, improvement and integration of in silico datasets, peptidomics tools, LC-MS/MS technologies and optimized analysis pipelines. Specifically, future research in this area should prioritize the translation of the peptidomics pipelines used for H. contortus [150,151] and C. elegans [148] to probe Strongyloides spp., life cycle stage, somatic, ESP and EV peptidomes. These analyses will facilitate downstream functional analyses to inform aspects of Strongyloides peptide biology, including host-parasite-microbiome interactions.…”

Improving helminth genome resources in the post-genomic era

“…Genome-led analyses now include, for example, characterising transcription at single-cell [26][27][28], temporal [29], and spatially defined resolutions [30], large-scale RNAi screens to understand gene function and reveal novel drug targets [31], extensive gene family characterisation, for example, chemoreceptors [32] or small noncoding RNAs [33], and targeted genome modification and transgenesis are becoming more efficient in a range of species [34][35][36][37]. These genomic analyses are also increasingly being complemented by other 'omic approaches such as proteomics [38], peptidomics [39], metabolomics [40], and lipidomics [41]. However, generating 'omics data that heavily rely on existing genomics resources is potentially problematic.…”