Dissecting the Biology of the Fungal Wheat Pathogen <i>Zymoseptoria tritici</i>: A Laboratory Workflow
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The fungus Zymoseptoria tritici is one of the most devastating pathogens of wheat. Aside from its importance as a disease-causing agent, this species has emerged as a powerful model system for evolutionary genetic studies of crop-infecting fungal pathogens. Z. tritici exhibits exceptionally high levels of genetic and phenotypic diversity as well as morphological plasticity, which can make experimental studies and comparability of results obtained in different laboratories, e.g., from infection assays, challenging. Therefore, standardized experimental methods are crucial for research on Z. tritici biology and the interaction of this fungus with its wheat host. Here, we describe a suite of well-tested and optimized protocols ranging from isolation of Z. tritici field specimens to analyses of virulence assays under controlled conditions. Several biological and technical aspects of working with Z. tritici under laboratory conditions are considered and carefully described in each protocol. © 2020 The Authors. Basic Protocol 1: Purification of Z. tritici field isolates from leaf material Basic Protocol 2: Molecular identification of Z. tritici isolates Support Protocol 1: Rapid extraction of Z. tritici genomic DNA Support Protocol 2: Extraction of high-quality Z. tritici genomic DNA Basic Protocol 3: In vitro culture and long-term storage of Z. tritici isolates Basic Protocol 4: Analysis of Z. tritici virulence in wheat Support Protocol 3: Preparation of Z. tritici inoculum.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it