Goats as Valuable Animal Model to Test the Targeted Glutamate Supplementation upon Antral Follicle Number, Ovulation Rate, and LH-Pulsatility

Biology (Basel). 2022 Jul 6;11(7):1015. doi: 10.3390/biology11071015.

Abstract

The potential effect of intravenous administration of glutamate on the ovarian activity and the LH secretion pattern, considering the anestrous yearling goat as an animal model, were assessed. In late April, yearling goats (n = 20) were randomly assigned to either (1) Glutamate supplemented (GLUT; n = 10, Live Weight (LW) = 29.6 ± 1.02 kg, Body Condition (BCS) = 3.4 ± 0.2 units; i.v. supplemented with 7 mg GLUT kg−1 LW) or (2) Non-supplemented (CONT; n = 10; LW = 29.2 ± 1.07 kg, BCS = 3.5 ± 0.2 units; i.v. saline). The oats were estrus-synchronized; blood sampling (6 h × 15 min) was carried out for LH quantification. Response variables included pulsatility (PULSE), time to first pulse (TTFP), amplitude (AMPL), nadir (NAD), and area under the curve (AUC) of LH. Ovaries were ultra-sonographically scanned to assess ovulation rate (OR), number of antral follicles (AF), and total ovarian activity (TOA = OR + AF). LH-PULSE was quantified with the Munro algorithm; significant treatment x time interactions were evaluated across time. The variables LW and BCS did not differ (p > 0.05) between the experimental groups. Nevertheless, OR (1.77 vs. 0.87 ± 0.20 units), TOA (4.11 vs. 1.87 ± 0.47 units) and LH-PULSE (5.0 vs. 2.2 pulses 6 h-1) favored (p < 0.05) to the GLUT group. Our results reveal that targeted glutamate supplementation, the main central nervous system neurotransmitter, arose as an interesting strategy to enhance the hypothalamic−hypophyseal−ovarian response considering the anestrous-yearling goat as an animal model, with thought-provoking while promising translational applications.

Keywords: LH; animal models; glutamate; goats; ovarian function; translational models.

Grants and funding

This study was supported by diverse International Collaborative Projects from the National Council of Science and Technology (CONACYT, Mexico): CONACYT-FOMIX-DURANGO: DGO-2008-C01-87559 and DGO-2009-C02-116746, and CONACYT-SIVILLA-1998-0401010, as well as the ALFA-III-ALAS/ALFA-III-82, supported by the European Union. We also acknowledge the Research Sectorial Fund SAGARPA-CONACYT: 2017-4-291691, which also contributed to the generation of most of the information presented in this study.