Whole Genome Sequence Analysis of a Novel Apilactobacillus Species from Giant Honeybee (Apis dorsata) Gut Reveals Occurrence of Genetic Elements Coding Prebiotic and Probiotic Traits
Bibliographic record
Abstract
Apilactobacillus spp. are classified as obligate fructophilic lactic acid bacteria (FLAB) that inhabit fructose-rich niches such as honeybee gut. Lactic acid bacteria are an important component of the gut microbiome and play a crucial role in maintaining gut health. In this study, a new FLAB strain HBW1, capable of producing glucan-type exopolysaccharide, was isolated from giant honeybee (Apis dorsata) gut and subjected to whole genome sequencing (WHS) to determine its health-beneficial traits. The genome size of the isolate was 1.49 Mb with a GC content of 37.2%. For species level identity, 16S rDNA sequence similarity, genome to genome distance calculator (dDDH), and average nucleotide identity (ANI) values were calculated. Phylogenetic analysis showed that the isolate HBW1 belongs to the Apilactobacillus genus. The dDDH and ANI values in comparison with closely clustered Apilactobacillus kunkeei species were 52% and 93.10%, respectively. Based on these values, we concluded that HBW1 is a novel species of Apilactobacillus, and we propose the name Apilactobacillus waqarii HBW1 for it. Further, WHS data mining of HBW1 revealed that it harbors two glucosyltransferase genes for prebiotic glucan-type exopolysaccharide synthesis. Moreover, chaperon (clp) and methionine sulfoxide reductase (msrA, msrB, and msrC) genes as well as nutritional marker genes for folic acid (folD) and riboflavin biosynthesis (rib operon), important for conferring probiotic properties, were also detected. Occurrence of these genetic traits make HBW1 an excellent candidate for application to improve gut function.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 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".