Differential Gene Expression in Auristatin PHE-Treated <i>Cryptococcus neoformans</i>
Bibliographic record
Abstract
The antifungal pentapeptide auristatin PHE was recently shown to interfere with microtubule dynamics and nuclear and cellular division in the opportunistic pathogen Cryptococcus neoformans. To gain a broader understanding of the cellular response of C. neoformans to auristatin PHE, mRNA differential display (DD) and reverse transcriptase PCR (RT-PCR) were applied. Examination of approximately 60% of the cell transcriptome from cells treated with 1.5 times the MIC (7.89 micro M) of auristatin PHE for 90 min revealed 29 transcript expression differences between control and drug-treated populations. Differential expression of seven of the transcripts was confirmed by RT-PCR, as was drug-dependent modulation of an additional seven transcripts by RT-PCR only. Among genes found to be differentially expressed were those encoding proteins involved in transport, cell cycle regulation, signal transduction, cell stress, DNA repair, nucleotide metabolism, and capsule production. For example, RHO1 and an open reading frame (ORF) encoding a protein with 91% similarity to the Schizophyllum commune 14-3-3 protein, both involved in cell cycle regulation, were down-regulated, as was the gene encoding the multidrug efflux pump Afr1p. An ORF encoding a protein with 57% identity to the heat shock protein HSP104 in Pleurotus sajor-caju was up-regulated. Also, three transcripts of unknown function were responsive to auristatin PHE, which may eventually contribute to the elucidation of the function of their gene products. Further study of these differentially expressed genes and expression of their corresponding proteins are warranted to evaluate how they may be involved in the mechanism of action of auristatin PHE. This information may also contribute to an explanation of the selectivity of auristatin PHE for C. neoformans. This is the first report of drug action using DD in C. neoformans.
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.
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 | 0.000 | 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".