The lipid composition of the exo-metabolome from Haemonchus contortus
Bibliographic record
Abstract
Abstract Background Several livestock parasitic nematode species have developed anthelmintic resistance, limiting their control in grazing animals. Metabolomic studies of different parasite-derived biomolecules, such as lipids, are currently under investigation to expand novel strategies for controlling these pathogens and characterizing their metabolism. However, the extremely low concentrations and complexity of exocellular fluids produced by these organisms remain a challenge for untargeted approaches. Lipids are essential pleiotropic biomolecules in invertebrates, including helminths. Still, there is a gap in the knowledge about their functions in parasitic nematode biology and their impact on the interaction with the host. We aimed to describe the detailed lipid composition of the exo-metabolome secreted by Haemonchus contortus, the major parasitic nematode of small ruminants worldwide, using untargeted lipidomics. Methods H. contortus adult worms were recovered from infected sheep and cultured ex-vivo. Parasite medium was collected at three time points (2, 4 and 8h), and samples were subjected to an untargeted global lipidomic analysis. Firstly, lipids were isolated using a modified version of the classic Folch liquid-liquid extraction. The extracts were subjected to Liquid Chromatography-Mass Spectrometry (LC/MS) analysis. Chromatograms from samples and quality control injections were analyzed in positive and negative ionization. Lipid identification was run through a three-tier approach. For tiers 1 and 2, the experimental data was matched to databases through tandem-MS (MS/MS) spectral similarity scores. Lipids with MS/MS scores ≥ 500 were deemed Tier 1, while lower scores were considered Tier 2. Features not matched by MS/MS were subjected to mass-matching using the LIPID MAPS database (Tier 3). Lipids were subjected to a 9-tier filtering and scoring approach to select the best identification. The peak intensities were normalized by a set of internal standards to reduce experimental variability. The normalized peak intensities for identified lipids were subjected to statistical analysis comparing global lipid clusters' fold change (FC) and individual lipid features. Lipids were also analyzed by fatty acyl composition, segregating each lipid category by structural length and saturation bonding. Results Initially, 2562 lipid features were detected in all samples from our global untargeted lipidomic analysis, including background hits on the RPMI medium. A total of 1057 lipids were identified, including 171 lipids in Tiers 1 and 2 (high-confidence MS/MS identifications), whereas 886 putative lipids were identified in Tier 3 based on mass matches. The main lipid categories correspond to glycerophospholipids, followed by fatty acyls, sphingolipids, glycerolipids, and sterol lipids, structurally corresponding mainly to unsaturated lipids. We found variations in the parasite media lipid profile in a time-dependent manner. Many lipids have been described in multicellular organisms, but little is known about their role in parasitic nematodes. We predict their activity as signalling molecules in physiological functions such as adaptation to nutrient changes, life span and mating. Also, many lipids in the found profile have been documented as modulators on the host immune responses. Conclusions Our findings regarding the composition of the lipids secreted by H. contortus provide new information about how these biomolecules derived from this economically important veterinary nematode impact the host and how lipids play essential functions for the parasite’s homeostasis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".