Uncovering carbohydrate metabolism through a genotype-phenotype association study of 56 lactic acid bacteria genomes
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
Owing to their unique potential to ferment carbohydrates, both homo- and heterofermentative lactic acid bacteria (LAB) are widely used in the food industry. Deciphering the genetic basis that determine the LAB fermentation type, and hence carbohydrate utilization, is paramount to optimize LAB industrial processes. Deep sequencing of 24 LAB species and comparison with 32 publicly available genome sequences provided a comparative data set including five major LAB genera for further analysis. Phylogenomic reconstruction confirmed Leuconostoc and Pediococcus species as independently emerging from the Lactobacillus genus, within one of the three phylogenetic clades identified. These clades partially grouped LABs according to their fermentation types, suggesting that some metabolic capabilities were independently acquired during LAB evolution. In order to apply a genome-wide association study (GWAS) at the multigene family level, utilization of 49 carbohydrates was also profiled for these 56 LAB species. GWAS results indicated that obligately heterofermentative species lack 1-phosphofructokinase, required for D-mannose degradation in the homofermentative pathway. Heterofermentative species were found to often contain the araBAD operon, involved in L-arabinose degradation, which is important for heterofermentation. Taken together, our results provide helpful insights into the genetic determinants of LAB carbohydrate metabolism, and opens for further experimental research, aiming at validating the role of these candidate genes for industrial applications.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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