Gene-Silencing-Induced Changes in Carbohydrate Conformation in Relation to Bioenergy Value and Carbohydrate Subfractions in Modeled Plant (Medicago sativa) with Down-Regulation of HB12 and TT8 Transcription Factors
Bibliographic record
Abstract
Gene silencing with RNA interference (RNAi) technology may be capable of modifying internal structure at a molecular level. This structural modification could affect biofunctions in terms of biodegradation, biochemical metabolism, and bioactive compound availability. The objectives of this study were to (1) Detect gene silencing-induced changes in carbohydrate molecular structure in an alfalfa forage (Medicago sativa spp. sativa: alfalfa) with down-regulation of genes that encode transcription factors TT8 and HB12; (2) Determine gene silencing-induced changes in nutrient bioutilization and bioavailability in the alfalfa forage (Medicago sativa); and (3) Quantify the correlation between gene silencing-induced molecular structure changes and the nutrient bioutilization and bioavailability in animals of ruminants. The experimental treatments included: T1 = Non-transgenic and no-gene silenced alfalfa forage (code "NT"); T2 = HB12-RNAi forage with HB12 gene down regulation (code "HB12"); T3 = TT8-RNAi forage with TT8 gene down regulation (code "TT8"). The HB12 and TT8 gene silencing-induced molecular structure changes were determined by non-invasive and non-destructive advanced molecular spectroscopy in a middle infrared radiation region that focused on structural, non-structural and total carbohydrate compounds. The nutrient bioutilization and bioavailability of the modified forage were determined using NRC-2001 system in terms of total digestive nutrient (TDN), truly digestible fiber (tdNDF), non-fiber carbohydrate (tdNDF), fatty acid (tdFA), crude protein (tdCP) and bioenergy profiles (digestible energy, metabolizable energy, net energy) for ruminants. The carbohydrate subfractions were evaluated using the updated CNCPS 6.0 system. The results showed that gene silencing significantly affected tdNFC (42.3 (NT) vs. 38.7 (HB12) vs. 37.4% Dry Matter (TT8); p = 0.016) and tdCP (20.8 (NT) vs. 19.4 (HB12) vs. 22.3% DM (TT8); p = 0.009). The gene-silencing also affected carbohydrate CA4 (7.4 (NT) vs. 4.2 (HB12) and 4.4% carbohydrate (CHO) (TT8), p = 0.063) and CB1 fractions (5.3 (NT) vs. 2.0 (HB12) and 2.6% CHO (TT8), p = 0.006). The correlation study showed that the structural CHO functional group peak area intensity at ca. 1315 cm(-1) was significantly correlated to the TDN1x (r = -0.83, p = 0.042) and the tdNFC (r = -0.83, p = 0.042), the structural CHO functional group height intensity at ca. 1370 cm(-1) was significantly correlated to the tdNDF (r = -0.87, p = 0.025). The A_Non-stCHO to A_StCHO ratio and A_Non-stCHO to A_CHO ratio were significantly correlated to the tdFA (r = 0.83-0.91, p < 0.05). As to carbohydrate fractions, both CA4 and CB1 correlated with carbohydrate spectral intensity of the H_1415 and the H_1315 (p = 0.039; p = 0.059, respectively), CB3 tended to correlate with the H_1150, H_1100 and H_1025 (p < 0.10). In conclusion, RNAi-mediated silencing of HB12 and TT8 modified not only inherent CHO molecular structure but also the biofunctions. The CHO molecular structure changes induced by RNAi gene silencing were associated with biofunctions in terms of the carbohydrate subfractions and nutrient digestion.
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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) | 0.001 | 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".