Microbial Communities and Their Predicted Metabolic Functions in Growth Laminae of a Unique Large Conical Mat from Lake Untersee, East Antarctica
Bibliographic record
Abstract
In this study, we report the distribution of microbial taxa and their predicted metabolic functions observed in the top (U1), middle (U2) and inner (U3) decadal growth laminae of a unique large conical microbial mat from a perennially ice-covered freshwater Lake Untersee of East Antarctica, using NextGen sequencing of the 16S rRNA gene and bioinformatics tools. The results showed that the U1 lamina was dominated by cyanobacteria, specifically Phormidium sp., Leptolyngbya sp. and Pseudanabaena sp. The U2 and U3 laminae had high abundances of Actinobacteria, Verrucomicrobia, Proteobacteria, and Bacteroidetes. Closely related taxa within each abundant bacterial taxon found in each lamina were further differentiated at the highest taxonomic resolution using the oligotyping method. PICRUSt analysis, which determines predicted KEGG functional categories from the gene contents and abundances among microbial communities, revealed a high number of sequences belonging to carbon fixation, energy metabolism, cyanophycin, chlorophyll and photosynthesis proteins in the U1 lamina. The functional predictions of the microbial communities in U2 and U3 represented signal transduction, membrane transport, zinc transport and amino acid-, carbohydrate-, and arsenic- metabolisms. The Nearest Sequenced Taxon Index (NSTI) values processed through PICRUSt were 0.10, 0.13 and 0.11 for U1, U2 and U3 laminae, respectively. These values indicated a close correspondence with the reference microbial genome database, implying high confidence in the predicted metabolic functions of the microbial communities in each lamina. Distribution of microbial taxa observed in each lamina and their predicted metabolic functions reveled in this study contributes to an insight into the Lake Untersee mat microbial ecosystem and lays the foundation for future studies for our understanding of detailed mechanisms that led to the formation of these unique mat structures and their evolutionary significance.
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 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 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".