Mateo-Otero Yentel, Fernández-López Pol, Delgado-Bermúdez Ariadna, Nolis Pau, Roca Jordi, Miró Jordi, Barranco Isabel, Yeste Marc
Biotechnology of Animal and Human Reproduction (TechnoSperm), Institute of Food and Agricultural Technology, University of Girona, ES-17003, Girona, Spain.
Department of Biology, Unit of Cell Biology, Faculty of Sciences, University of Girona, ES-17003, Girona, Spain.
J Anim Sci Biotechnol. 2021 Nov 12;12(1):113. doi: 10.1186/s40104-021-00636-5.
Metabolomic approaches, which include the study of low molecular weight molecules, are an emerging -omics technology useful for identification of biomarkers. In this field, nuclear magnetic resonance (NMR) spectroscopy has already been used to uncover (in) fertility biomarkers in the seminal plasma (SP) of several mammalian species. However, NMR studies profiling the porcine SP metabolome to uncover in vivo fertility biomarkers are yet to be carried out. Thus, this study aimed to evaluate the putative relationship between SP-metabolites and in vivo fertility outcomes. To this end, 24 entire ejaculates (three ejaculates per boar) were collected from artificial insemination (AI)-boars throughout a year (one ejaculate every 4 months). Immediately after collection, ejaculates were centrifuged to obtain SP-samples, which were stored for subsequent metabolomic analysis by NMR spectroscopy. Fertility outcomes from 1525 inseminations were recorded over a year, including farrowing rate, litter size, stillbirths per litter and the duration of pregnancy.
A total of 24 metabolites were identified and quantified in all SP-samples. Receiver operating characteristic (ROC) curve analysis showed that lactate levels in SP had discriminative capacity for farrowing rate (area under the curve [AUC] = 0.764) while carnitine (AUC = 0.847), hypotaurine (AUC = 0.819), sn-glycero-3-phosphocholine (AUC = 0.833), glutamate (AUC = 0.799) and glucose (AUC = 0.750) showed it for litter size. Similarly, citrate (AUC = 0.743), creatine (AUC = 0.812), phenylalanine (AUC = 0.750), tyrosine (AUC = 0.753) and malonate (AUC = 0.868) levels had discriminative capacity for stillbirths per litter; and malonate (AUC = 0.767) and fumarate (AUC = 0.868) levels for gestation length.
The assessment of selected SP-metabolites in ejaculates through NMR spectroscopy could be considered as a promising non-invasive tool to predict in vivo fertility outcomes in pigs. Moreover, supplementing AI-doses with specific metabolites should also be envisaged as a way to improve their fertility potential.
代谢组学方法包括对低分子量分子的研究，是一种新兴的“组学”技术，有助于生物标志物的识别。在该领域，核磁共振（NMR）光谱已被用于揭示几种哺乳动物物种精浆（SP）中的（不）育生物标志物。然而，尚未开展对猪精浆代谢组进行分析以揭示体内育性生物标志物的NMR研究。因此，本研究旨在评估精浆代谢物与体内育性结果之间的假定关系。为此，在一年时间里从人工授精（AI）公猪收集了24份完整射精样本（每头公猪3份射精样本）（每4个月采集1份射精样本）。采集后立即对射精样本进行离心以获得精浆样本，将其储存用于后续通过NMR光谱进行代谢组学分析。记录了一年中1525次授精的育性结果，包括产仔率、窝产仔数、每窝死胎数和妊娠期时长。
在所有精浆样本中总共鉴定并定量了24种代谢物。受试者工作特征（ROC）曲线分析表明，精浆中乳酸水平对产仔率具有判别能力（曲线下面积[AUC]=0.764），而肉碱（AUC=0.847）、亚牛磺酸（AUC=0.819）、sn-甘油-3-磷酸胆碱（AUC=0.833）、谷氨酸（AUC=0.799）和葡萄糖（AUC=0.750）对窝产仔数具有判别能力。同样，柠檬酸盐（AUC=0.743）、肌酸（AUC=0.812）、苯丙氨酸（AUC=0.750）、酪氨酸（AUC=0.753）和丙二酸盐（AUC=0.868）水平对每窝死胎数具有判别能力；丙二酸盐（AUC=0.767）和富马酸盐（AUC=0.868）水平对妊娠期时长具有判别能力。
通过NMR光谱对射精样本中选定的精浆代谢物进行评估可被视为一种有前景的非侵入性工具，用于预测猪的体内育性结果。此外，还应考虑用特定代谢物补充人工授精剂量，作为提高其育性潜力的一种方法。
