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Record W4402542038 · doi:10.1093/jas/skae234.437

478 Impact of crude protein and phosphorus deficiencies on liver mitochondrial content and transcriptome in growing Merino wethers

2024· article· en· W4402542038 on OpenAlexaff
Elmer A. Fernández, Nicholas J. Hudson, David Innes, S. P. Quigley, Dennis Poppi

Bibliographic record

VenueJournal of Animal Science · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicConstructed Wetlands for Wastewater Treatment
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsTranscriptomePhosphorusBiologyAnimal scienceChemistryBiochemistryGeneGene expression

Abstract

fetched live from OpenAlex

Abstract In grazing systems in Northern Australia, crude protein (CP) and phosphorus (P) availability varies, affecting ruminant production due to voluntary reduced intake and therefore body weight (BW) gain. We were interested in understanding metabolic regulation in this model system, both in terms of a) identifying key tissues, and b) detecting any modifications in mitochondrial physiology, given the central role of this organelle in bioenergetic homeostasis. Merino wethers (n = 24) were subjected to three dietary regimens: High CP, High P, (Control), Low CP, Low P (Deficient), and High CP, High P, with restricted feed intake (Restricted). Mitochondrial DNA (mtDNA) copy numbers, indicative of mitochondrial content, were measured via qPCR. Transcriptomic analyses through RNA sequencing targeted mitochondria-associated gene expression changes and pathways, using the MitoCarta 3.0 database. There was a significant decrease of mtDNA copy numbers in the liver of sheep under either Deficient and Restricted diets (P < 0.01), with as much as a 2-fold difference between the Control and Deficient diets. This may suggest reduced mitochondrial biogenesis as an adaptation to decreased energy intake. When compared with the Control group, both the Deficient and Restricted groups upregulated pathways related to vitamin metabolism (Log2FC: 0.231 and 0.449) and folate and 1-C metabolism (Log2FC: 0.409 and 0.706). However, impacted pathways shared between these two comparisons (Control v Deficient, Control v Restricted) also include choline and betaine metabolism, amino acid metabolism, and glycine metabolism, which suggests similar mechanisms being impacted by decreased energy intake, regardless of whether it is due to satiety from nutrient deficiency or restricted feed intake. Notably, the creatine metabolism pathway was uniquely upregulated in the Restricted group compared with the Deficient group (Log2FC: 0.114), although the CKMT2 gene was upregulated in the Restricted group compared with both the Control and Deficient group (Log2FC: 1.30 and 0.879). Additionally, the SLC25A family pathway, responsible for mitochondrial metabolite transport, was found to be upregulated in the Restricted group when compared with both Control and Deficient groups (Log2FC: 0.33 and 0.865). Overall, this study demonstrated a pronounced decrease in mitochondrial content in the liver of growing Merino wethers subjected to nutritional deficiencies and feed restriction. Multiple metabolic pathways were shared between the comparisons of the Control diet group to both Deficient and Restricted nutritional treatments. However, the SLC25A transporter family pathway was uniquely upregulated in the Restricted group compared with either an optimal or deficient diet. The regulation of these metabolic pathways is a subject of further study that may represent a systemic response to maintain homeostasis while undergoing significantly lower energy intake, with implications for animal growth, tissue deposition, and energetic maintenance. Understanding distinctions in the response to feed restriction and nutrient deficiency induced reduction in intake may help improve production strategies for ruminants grazing in these conditions.

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 score0.002
Threshold uncertainty score0.005

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 head0.018
GPT teacher head0.246
Teacher spread0.228 · 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".

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Citations1
Published2024
Admission routes1
Has abstractyes

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