Culture-Dependent and Amplicon Sequencing Approaches Reveal Diversity and Distribution of Black Fungi in Antarctic Cryptoendolithic Communities
Bibliographic record
Abstract
In the harshest environmental conditions of the Antarctic desert, normally incompatible with active life, microbes are adapted to exploit the cryptoendolithic habitat (i.e., pore spaces of rocks) and represent the predominant life-forms. In the rocky niche, microbes take advantage of the thermal buffering, physical stability, protection against UV radiation, excessive solar radiation, and water retention—of paramount importance in one of the driest environments on Earth. In this work, high-throughput sequencing and culture-dependent approaches have been combined, for the first time, to untangle the diversity and distribution of black fungi in the Antarctic cryptoendolithic microbial communities, hosting some of the most extreme-tolerant microorganisms. Rock samples were collected in a vast area, along an altitudinal gradient and opposite sun exposure—known to influence microbial diversity—with the aim to compare and integrate results gained with the two approaches. Among black fungi, Friedmanniomyces endolithicus was confirmed as the most abundant taxon. Despite the much stronger power of the high-throughput sequencing, several species were not retrieved with DNA sequencing and were detectable by cultivation only. We conclude that both culture-dependent and -independent analyses are needed for a complete overview of black fungi diversity. The reason why some species remain undetectable with molecular methods are speculated upon. The effect of environmental parameters such as sun exposure on relative abundance was clearer if based on the wider biodiversity detected with the molecular approach.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".