Untargeted and targeted metabolomics profiling reveals the underlying pathogenesis and abnormal arachidonic acid metabolism in laying hens with fatty liver hemorrhagic syndrome.

arachidonic acid fatty liver hemorrhagic syndrome liver mass spectrometry metabolomic

Journal

Poultry science
ISSN: 1525-3171
Titre abrégé: Poult Sci
Pays: England
ID NLM: 0401150

Informations de publication

Date de publication:
Sep 2021
Historique:
received: 27 04 2021
revised: 01 06 2021
accepted: 04 06 2021
pubmed: 19 7 2021
medline: 1 9 2021
entrez: 18 7 2021
Statut: ppublish

Résumé

As a metabolic disease, fatty liver hemorrhagic syndrome (FLHS) has become the major factor responsible for the noninfectious cause of mortality in laying hens, which lead to huge economic losses to poultry industry. However, the pathogenesis of FLHS remains unclear. The aim of present study was to identify novel liver metabolites associated with FLHS. Twenty healthy Chinese commercial Jing Fen laying hens aged 90 d were used in present study. After acclimatization for 2 wk, the hens were divided into 2 treatments (n = 10): control group (normal diet) and FLHS group (high-energy low-protein diet). The experiment lasted for 48 d, and the laying hens were killed for blood and liver sampling at the end of the experiment. Blood biochemical indicators and liver pathological changes were examined. Meanwhile, the changes in liver metabolic profile were investigated with the application of metabolomics approach. Significant increased levels of alanine aminotransferase, aspartate aminotransferase, low density lipoprotein, total cholesterol and triglycerides, decreased high density lipoprotein (P < 0.01), and hepatic steatosis were observed in hens of FLHS group, which suggested FLHS was successfully established in this study. Distinct changes in metabolite patterns in liver between control and FLHS group were observed by partial least-squares discriminant analysis. In total, 42 liver metabolites including tyrosine, glutathione, carnitine, linoleic acid, uric acid, arachidonic acid (ARA), lactate and lysophosphatidylcholine (14: 0) were identified and considered to be related with pathogenesis of FLHS. Pathway analysis revealed that these metabolites were mainly involved in amino acid metabolism, fatty acid metabolism, ARA metabolism, glucose metabolism and glycerophospholipid metabolism. Furthermore, targeted metabolomics found that ARA metabolites such as prostaglandins and hydroxyeicosatetraenoic acids were significantly increased in FLHS group (P < 0.05). In conclusion, our data showed that liver metabolites and ARA metabolism were linked to the pathophysiology of FLHS, which provided a basis for understanding the pathogenesis of FLHS in laying hens.

Identifiants

pubmed: 34274572
pii: S0032-5791(21)00354-0
doi: 10.1016/j.psj.2021.101320
pmc: PMC8319003
pii:
doi:

Substances chimiques

Arachidonic Acids 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

101320

Informations de copyright

Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.

Auteurs

Jiacheng Meng (J)

College of Veterinary Medicine, Hebei Agricultural University, Baoding 071001, Hebei, China.

Ning Ma (N)

College of Veterinary Medicine, Hebei Agricultural University, Baoding 071001, Hebei, China; Hebei Veterinary Biotechnology Innovation Center, Baoding 071001, Hebei, China.

Hailong Liu (H)

Hainan Academy of Agricultural Sciences, Haikou 571100, Hainan, China.

Jing Liu (J)

College of Veterinary Medicine, Hebei Agricultural University, Baoding 071001, Hebei, China.

Juxiang Liu (J)

College of Veterinary Medicine, Hebei Agricultural University, Baoding 071001, Hebei, China.

Jianping Wang (J)

College of Veterinary Medicine, Hebei Agricultural University, Baoding 071001, Hebei, China.

Xin He (X)

College of Veterinary Medicine, Hebei Agricultural University, Baoding 071001, Hebei, China.

Xinghua Zhao (X)

College of Veterinary Medicine, Hebei Agricultural University, Baoding 071001, Hebei, China. Electronic address: xianzhaoxinghua@163.com.

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Classifications MeSH