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The characteristics of proteome and metabolome associated with contrasting sperm motility in goat seminal plasma

Sperm motility is an index tightly associated with male fertility. A close relationship between seminal plasma and sperm motility has been confirmed. This study was to assess the protein and metabolite profiles of seminal plasma obtained from adult goats with high or low sperm motility using the pro...

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Detalles Bibliográficos
Autores principales: Jia, Baoyu, Liang, Jiachong, Lv, Chunrong, Memon, Sameeullah, Fang, Yi, Wu, Guoquan, Quan, Guobo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8324791/
https://www.ncbi.nlm.nih.gov/pubmed/34330982
http://dx.doi.org/10.1038/s41598-021-95138-9
Descripción
Sumario:Sperm motility is an index tightly associated with male fertility. A close relationship between seminal plasma and sperm motility has been confirmed. This study was to assess the protein and metabolite profiles of seminal plasma obtained from adult goats with high or low sperm motility using the proteomic and metabolomic strategies. In total, 2098 proteins were found. 449 differentially abundant proteins (DAPs) were identified, and 175 DAPs were enriched in the high motility group. The obtained DAPs primarily exist in cytoplasma and extra-cellular portion. The Gene Ontology enrichment analysis demonstrated the main functional roles of these DAPs in regulating biological process, metabolic process of organic substances, cellular-metabolic process, primary-metabolic process, metabolic process of nitrogen compounds, etc. Additionally, the Kyoto-Encyclopedia of Genes and Genomes (KEGG) analysis revealed that these DAPs were primarily involved in phosphatidylinositol signaling system, salivary secretion, proteasome, apoptosis, mitophagy-animal, etc. Aided by the parallel reaction monitoring technology, the abundance changing pattern of 19 selected DAPs was consistent with that of the corresponding proteins obtained by TMT. A total of 4603 metabolites were identified in seminal plasma. 1857 differential metabolites were found between the high motility group and the low motility group, and 999 metabolites were up-regulated in the high motility group. The KEGG analysis demonstrated the primary involvement of the differential metabolites in metabolic and synthetic activities. In conclusion, we first established the proteome and metabolome databank of goat seminal plasma, detecting some proteins and metabolites which may affect sperm motility. This study will be valuable for understanding mechanisms leading to poor sperm motility.