Isolation and Identification of Nematode‐Infecting Microsporidia
Bibliographic record
Abstract
Nematodes are naturally infected by the fungal-related pathogen microsporidia. These ubiquitous eukaryotic parasites are poorly understood, despite infecting most types of animals. Identifying novel species of microsporidia and studying them in an animal model can expedite our understanding of their infection biology and evolution. Nematodes present an excellent avenue for pursuing such work, as they are abundant in the environment and many species are easily culturable in the laboratory. The protocols presented here describe how to isolate bacterivorous nematodes from rotting substrates, screen them for microsporidia infection, and molecularly identify the nematode and microsporidia species. Additionally, we detail how to remove environmental contaminants and generate a spore preparation of microsporidia from infected samples. We also discuss potential pitfalls and provide suggestions on how to mitigate them. These protocols allow for the identification of novel microsporidia species, which can serve as an excellent starting point for genomic analysis, determination of host specificity, and infection characterization. © 2024 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Gathering samples Support Protocol 1: Generating 10× and 40× Escherichia coli OP50 and seeding NGM plates Basic Protocol 2: Microsporidia screening, testing for Caenorhabditis elegans susceptibility, and sample freezing Basic Protocol 3: DNA extraction, PCR amplification, and sequencing to identify nematode and microsporidia species Basic Protocol 4: Removal of contaminating microbes and preparation of microsporidia spores Support Protocol 2: Bleach-synchronizing nematodes.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.012 |
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".