Physicochemical and microstructural characteristics of canola meal fermented by autonomously screened Bacillus licheniformis DY145 and its immunomodulatory effects on gut microbiota
Bibliographic record
Abstract
Canola meal (CM), a variety of double-low rapeseed meal (RSM), is a valuable protein source due to its reduced glucosinolate (<20 μmol/L) and erucic acid (<2 %) content. In this study, bioactive small peptides were derived from CM through fermentation with an autonomously screened Bacillus licheniformis DY145 strain. Strain mutagenesis and fermentation condition optimization further enhanced peptide activity. The physicochemical and microstructural changes in fermented canola meal (FCM) were analyzed, and the immunomodulatory effects of active peptides on lipopolysaccharide (LPS)-induced inflammatory mice were investigated. Fermentation significantly increased the soluble peptide concentration and DPPH radical scavenging capacity of CM (P < 0.05), while reducing protein molecular weight and glucosinolate content (P < 0.05). Scanning electron microscopy revealed a loose structure in CM after fermentation, and canola peptides (CPs) from fermented CM exhibited higher zeta potential, a reduced α-helix ratio, and lower fluorescence intensity compared to those from unfermented CM. Structural characterization of CPs was performed using LC-MS/MS, followed by bioactivity analysis. CPs significantly downregulated serum levels of TNF-α, IL-6, and IL-1β in LPS-induced mice (P < 0.05), while upregulating IgA and IgG levels (P < 0.05). Moreover, CP supplementation restored the gut microbial composition, normalizing dominant flora and increasing Lactobacillus abundance (P < 0.05). This study demonstrates the potential of CPs as functional food ingredients to mitigate gut inflammation and enhance the high-value utilization of CM. Additionally, it introduces a novel strain and fermentation method for bioactive peptide production, providing a theoretical foundation for the development of gut health-promoting functional foods. Furthermore, the preliminary structure-activity relationship analysis of CPs lays the groundwork for designing peptides with gut microbiota-modulating properties.
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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 | 0.000 |
| 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) | 0.000 | 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".