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Record W2945574747 · doi:10.3168/jds.2018-15875

Expression of genes related to energy metabolism and the unfolded protein response in dairy cow mammary cells is affected differently during dietary supplementation with energy from protein and fat

2019· article· en· W2945574747 on OpenAlexaff
K. Nichols, J. Dijkstra, H. van Laar, J.J.M. Kim, J.P. Cant, A. Bannink

Bibliographic record

VenueJournal of Dairy Science · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMeat and Animal Product Quality
Canadian institutionsUniversity of Guelph
FundersWageningen University and ResearchVereniging Diervoederonderzoek NederlandMinisterie van Landbouw, Natuur en Voedselkwaliteit
KeywordsSilageDry matterBiologyUnfolded protein responseTotal mixed rationDairy cattleRapeseedInternal medicineEndoplasmic reticulumCatabolismLactationEndocrinologyFood scienceChemistryMetabolismBiochemistryAnimal scienceIce calving

Abstract

fetched live from OpenAlex

Secretory capacity of bovine mammary glands is enabled by a high number of secretory cells and their ability to use a range of metabolites to produce milk components. We isolated RNA from milk fat to measure expression of genes involved in energy-yielding pathways and the unfolded protein response in mammary glands of lactating cows given supplemental energy from protein (PT) and fat (FT) tested in a 2 × 2 factorial arrangement. We hypothesized that PT and FT would affect expression of genes in the branched-chain AA catabolic pathway and tricarboxylic acid (TCA) cycle based on the different energy types (aminogenic versus lipogenic) used to synthesize milk components. We also hypothesized that the response of genes related to endoplasmic reticulum (ER) homeostasis via the unfolded protein response would reflect the increase in milk production stimulated by PT and FT. Fifty-six multiparous Holstein-Friesian dairy cows were fed a basal total mixed ration (34% grass silage, 33% corn silage, 5% grass hay, and 28% concentrate on a dry matter basis) for a 28-d control period. Experimental rations were then fed for 28 d, consisting of (1) low protein, low fat (LP/LF); (2) high protein, low fat (HP/LF); (3) low protein, high fat (LP/HF); or (4) high protein and high fat (HP/HF). To obtain the high-protein (HP) and high-fat (HF) diets, intake of the basal ration was restricted and supplemented isoenergetically (net energy basis) with 2.0 kg/d rumen-protected protein (soybean + rapeseed, 50:50 mixture on dry matter basis) and 0.68 kg/d hydrogenated palm fatty acids on a dry matter basis. RNA from milk fat samples collected on d 27 of each period underwent real-time quantitative PCR. Energy from protein increased expression of BCAT1 (branched-chain amino acid transferase 1) mRNA, but only at the LF level, and tended to decrease expression of mRNA encoding the main subunit of the branched-chain keto-acid dehydrogenase complex. mRNA expression of malic enzyme, a proposed channeling route for AA though the TCA cycle, was decreased by PT, but only at the LF level. Expression of genes associated with de novo fatty acid synthesis was not affected by PT or FT. Energy from fat had no independent effect on genes related to ER homeostasis. At the LF level, PT activated XBP1 (X-box binding protein 1) mRNA. At the HF level, PT increased mRNA expression of the gene encoding GADD34 (growth arrest and DNA damage-inducible 34). These findings support our hypothesis that mammary cells use aminogenic and lipogenic precursors differently for milk component production when dietary intervention alters AA and fatty acid supply. They also suggest that mammary cells respond to increased AA supply through mechanisms of ER homeostasis, dependent on the presence of FT.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.013
GPT teacher head0.222
Teacher spread0.209 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations14
Published2019
Admission routes1
Has abstractyes

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