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Zhang H, Qiao M, Gao D, Wang J, Sun C, Sun Y, Zhang Y, Liu H, Zhang Z, Gao M. Shuyu capsule alleviates premenstrual depression via allopregnanolone metabolic pathway targeting GABA (A) receptors δ subunit in the hippocampus. Asian J Psychiatr 2023; 90:103800. [PMID: 37898099 DOI: 10.1016/j.ajp.2023.103800] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Accepted: 10/16/2023] [Indexed: 10/30/2023]
Abstract
To reveal the exact changes of allopregnanolone-mediated γ-aminobutyric acid A receptor pathways and its specific therapeutic targets by Shuyu Capsule treating premenstrual depression, female Wistar rat models of premenstrual depression was established by Forced swimming test (FST). Behavioral tests, enzyme-linked immunosorbent assay (ELISA), interference knockdown adenovirus, and overexpressed vector adenovirus of GABAARδ, RT-qPCR, Western-Blot, and immunohistochemical detecting expressions were applied to identify the therapeutic targets. FST-based rat model indicated that Shuyu capsules alleviated typical premenstrual depression and may regulate alternations of 5α-reductase and 3α-steroid dehydrogenase, enhancing the metabolic pathway of progesterone to allopregnanolone, as well as targeting the GABAARδ subunit, thereby alleviating premenstrual depression of PMDD rat models.
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Affiliation(s)
- Hao Zhang
- Experimental Center, Shandong University of Traditional Chinese Medicine, Jinan, Shandong Province, China
| | - Mingqi Qiao
- College of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, Shandong Province, China
| | - Dongmei Gao
- College of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, Shandong Province, China
| | - Jieqiong Wang
- School of Pharmacy, Shandong University of Traditional Chinese Medicine, Jinan, Shandong Province, China
| | - Chunyan Sun
- College of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, Shandong Province, China
| | - Ya Sun
- Innovative Institute of Chinese Medicine and Pharmacy , Shandong University of Traditional Chinese Medicine, Jinan, Shandong Province, China
| | - Yang Zhang
- Innovative Institute of Chinese Medicine and Pharmacy , Shandong University of Traditional Chinese Medicine, Jinan, Shandong Province, China
| | - Huayuan Liu
- College of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, Shandong Province, China
| | - Zhen Zhang
- Guizhou University of Traditional Chinese Medicine, Guiyang, Guizhou Province, China
| | - Mingzhou Gao
- Innovative Institute of Chinese Medicine and Pharmacy , Shandong University of Traditional Chinese Medicine, Jinan, Shandong Province, China.
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2
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Turner ZB, Lima FS, Conley AJ, McNabb BR, Rowe JD, Garzon A, Urbano TM, Morris CM, Pereira RV. Cystic ovarian disease in dairy cattle: Diagnostic accuracy when using B-mode and color Doppler ultrasound. J Dairy Sci 2023; 106:3411-3420. [PMID: 36894418 DOI: 10.3168/jds.2022-22498] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Accepted: 10/24/2022] [Indexed: 03/09/2023]
Abstract
The most frequently reported definition of cystic ovarian disease in cattle is an abnormally persistent follicle (>7 to 10 d) with a diameter >25 mm. Discrimination between luteal and follicular ovarian cystic structures has traditionally been conducted by measuring the rim width of luteal tissue. The most common practice used in the field for diagnosis of cystic ovarian disease is examination by rectal palpation with or without the use of a B-mode ultrasound. Color Doppler ultrasound technology allows assessment of blood flow area measurements in the ovary, which has been proposed as a potential indirect measure for plasma progesterone (P4) concentrations. The objective of this study was to compare the diagnostic accuracy of differentiating luteal structures from follicular ovarian cysts using measures collected with B-mode and color Doppler transrectal ultrasonography. The definition of an ovarian cyst was a follicle greater than 20 mm in diameter in the absence of a corpus luteum that persisted for at least 10 d. A 3-mm luteal rim width was used to differentiate follicular and luteal cysts. A total of 36 cows were enrolled in the study during routine herd reproductive examination visits, with 26 and 10 having follicular and luteal cysts, respectively. Cows enrolled in the study were examined using a Mini-ExaPad mini ultrasound with color Doppler capabilities (IMV Imaging Ltd.). Blood samples were collected from each cow to measure P4 serum concentrations. History and signalment of each cow, including days in milk, lactation, times bred, days since last heat, milk composition, and somatic cell counts, were retrieved from an online database (DairyComp 305, Valley Agricultural Software). The accuracy of diagnosing follicular from luteal cysts based on luteal rim thickness was analyzed by receiver operating characteristic (ROC) curve using P4 as the gold standard, where P4 concentrations exceeding 1 ng/mL was defined as luteal, and all other structures with less P4 were considered follicular. Luteal rim and blood flow area were selected for further analysis because they presented the best ROC curves for differentiating cystic ovarian structures, with areas under the curve of 0.80 and 0.76, respectively. Luteal rim width of 3 mm was used as the cutoff standard in the study, resulting in sensitivity and specificity of 50% and 86%, respectively. Blood flow area of 0.19 cm2 was used as the cutoff standard in the study, resulting in sensitivity and specificity of 79% and 86%, respectively. When combining the use of luteal rim width and blood flow area to differentiate cystic ovarian structures, a parallel approach resulted in sensitivity and specificity of 73% and 93%, respectively, whereas an in-series approach resulted in sensitivity and specificity of 35% and 100%, respectively. In conclusion, the use of color Doppler ultrasonography when discriminating between luteal and follicular ovarian cysts in dairy cattle resulted in higher diagnostic accuracy compared with using B-mode ultrasonography alone.
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Affiliation(s)
- Z B Turner
- Veterinary Medicine Teaching Hospital, Livestock Herd Health and Reproduction Service, University of California, Davis 95616
| | - F S Lima
- Department of Population Health and Reproduction, University of California, Davis 95616
| | - A J Conley
- Department of Population Health and Reproduction, University of California, Davis 95616
| | - B R McNabb
- Veterinary Medicine Teaching Hospital, Livestock Herd Health and Reproduction Service, University of California, Davis 95616; Department of Population Health and Reproduction, University of California, Davis 95616
| | - J D Rowe
- Veterinary Medicine Teaching Hospital, Livestock Herd Health and Reproduction Service, University of California, Davis 95616; Department of Population Health and Reproduction, University of California, Davis 95616
| | - A Garzon
- Department of Population Health and Reproduction, University of California, Davis 95616
| | - T M Urbano
- Veterinary Medicine Teaching Hospital, Livestock Herd Health and Reproduction Service, University of California, Davis 95616
| | - C M Morris
- Veterinary Medicine Teaching Hospital, Livestock Herd Health and Reproduction Service, University of California, Davis 95616
| | - R V Pereira
- Veterinary Medicine Teaching Hospital, Livestock Herd Health and Reproduction Service, University of California, Davis 95616; Department of Population Health and Reproduction, University of California, Davis 95616.
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Chen X, Huang K, Hu S, Lan G, Gan X, Gao S, Deng Y, Hu J, Li L, Hu B, He H, Liu H, Xia L, Wang J. Integrated Transcriptome and Metabolome Analysis Reveals the Regulatory Mechanisms of FASN in Geese Granulosa Cells. Int J Mol Sci 2022; 23:ijms232314717. [PMID: 36499045 PMCID: PMC9736573 DOI: 10.3390/ijms232314717] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2022] [Revised: 11/23/2022] [Accepted: 11/23/2022] [Indexed: 11/27/2022] Open
Abstract
FASN plays a critical role in lipid metabolism, which is involved in regulating ovarian follicular development. However, the molecular mechanisms of how FASN regulate the function of ovarian follicular cells still remain elusive. In this study, by overexpression or interference of FASN in pre-hierarchical follicle granulosa cells (phGCs) and hierarchical follicle granulosa cells (hGCs), we analyzed their effects on the granulosa cell transcriptome and metabolome profiles using RNA-Seq and LC-MS/MS, respectively. The results showed that overexpression of FASN promoted proinflammatory factors expression by activating TLR3/IRF7 and TLR3/NF-κB pathways in phGCs, but only by activating TLR3/IRF7 pathways in hGCs. Then, necroptosis and apoptosis were triggered through the JAK/STAT1 pathway (induced by inflammatory factors) and BAK/caspase-7 pathway, respectively. The combined analysis of the metabolome and transcriptome revealed that FASN affected the demand of GCs for 5-hydroxytryptamine (5-HT) by activating the neuroactive ligand-receptor interaction pathway in two categorized GCs and only altering the metabolic pathway of tryptophan in phGCs, and ultimately participated in regulating the physiological function of geese GCs. Taken together, this study showed that the mechanisms of FASN regulating the physiological function of geese phGCs and hGCs were similar, but they also had some different characteristics.
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Affiliation(s)
- Xi Chen
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Kailiang Huang
- Key Laboratory of Agricultural Information Engineering of Sichuan Province, College of Information Engineering, Sichuan Agricultural University, Yaan 625014, China
| | - Shenqiang Hu
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Gang Lan
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Xiang Gan
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Shanyan Gao
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Yan Deng
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Jiwei Hu
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Liang Li
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Bo Hu
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Hua He
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Hehe Liu
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Lu Xia
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Jiwen Wang
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
- Correspondence:
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Legacki E, Sattler R, Conley A. Longitudinal patterns in progesterone metabolites in pregnant and non-pregnant Steller sea lions (Eumetopias jubatus). Gen Comp Endocrinol 2022; 326:114069. [PMID: 35679975 DOI: 10.1016/j.ygcen.2022.114069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Revised: 05/17/2022] [Accepted: 06/02/2022] [Indexed: 11/04/2022]
Abstract
Similar to the several pinniped and a few terrestrial carnivore species, the Steller sea lion has a seasonal synchronized mating scheme enabled by a female reproductive cycle that includes embryonic diapause, delayed implantation, and pseudopregnancy (a state in which the corpus luteum produces progesterone for approximately as long as in pregnant females). Due to this, circulating systemic progesterone concentrations cannot be used to differentiate pregnant and nonpregnant females during early gestation. With the use of advanced measurement technologies such as liquid chromatography tandem mass spectrometry (LC-MS/MS) additional steroid hormones are measurable which can provide additional information on the endocrine pathways throughout gestation. Our objectives were to further characterize endocrine patterns in female Steller sea lion pregnancy by 1) quantifying longitudinal profiles of hormone metabolites in pregnant and non-pregnant female sera, and 2) evaluating hormone profiles to identify pregnant animals within the early stage of gestation. Three gestation stages were delineated based on what is believed to be the period of implantation (September-October): EARLY (August- November), MID (December-February), and LATE (March to May). Five steroids, Progesterone (P4), 5α-dihydroprogesterone (DHP), 17αOH-progesterone (17OHP), 20αOH-progesterone (20OHP), and androstenedione (A4), were detected in both pregnant and non-pregnant animals. A significant difference in P4 concentrations was measured between EARLY and MID gestation (p ≤ 0.01) in both pregnant and non-pregnant animals. During MID gestation there was a significant difference (p ≤ 0.05) between pregnant and non-pregnant animals in all pregnanes measured. Significant patterns of correlation between P4 and 17OHP and between P4 and DHP were detected during EARLY and MID gestation in non-pregnant animals. While those significant correlations also exist in EARLY pregnant animals, this pattern was lost by MID gestation. This loss of correlation suggests a potential shift in progesterone metabolism from ovarian to alternative tissue (e.g. fetal gonads or adrenal glands) by MID gestation in Steller sea lions. We were unable to identifying a steroid hormone biomarker capable of differentiating pseudopregnancy from pregnant animals and conclude that such a biomarker likely falls outside of the traditional progesterone metabolic pathway.
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Affiliation(s)
- Erin Legacki
- School of Veterinary Medicine, University of California Davis, Davis, CA 95616, United States; National Cold Water Marine Aquaculture Center, USDA, Franklin, ME 04469, United States.
| | - Renae Sattler
- Alaska Department of Fish and Game, Palmer, AK 99645, United States; Alaska SeaLife Center, 301 Railway Avenue, Seward, AK 99664, United States
| | - Alan Conley
- School of Veterinary Medicine, University of California Davis, Davis, CA 95616, United States
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Conley AJ, Loux SC, Legacki EL, Stoops MA, Pukazhenthi B, Brown JL, Sattler R, French HM, Tibary A, Robeck TR. The steroid metabolome of pregnancy, insights into the maintenance of pregnancy and evolution of reproductive traits. Mol Cell Endocrinol 2021; 528:111241. [PMID: 33711335 DOI: 10.1016/j.mce.2021.111241] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/03/2020] [Revised: 03/01/2021] [Accepted: 03/03/2021] [Indexed: 11/28/2022]
Abstract
Modes of mammalian reproduction are diverse and not always conserved among related species. Progesterone is universally required to supports pregnancy but sites of synthesis and metabolic pathways vary widely. The steroid metabolome of mid-to late gestation was characterized, focusing on 5α-reduced pregnanes in species representing the Perissodactyla, Cetartiodactyla and Carnivora using mass spectrometry. Metabolomes and steroidogenic enzyme ortholog sequences were used in heirarchial analyses. Steroid metabolite profiles were similar within orders, whales within cetartiodactyls for instance, but with notable exceptions such as rhinoceros clustering with goats, and tapirs with pigs. Steroidogenic enzyme sequence clustering reflected expected evolutionary relationships but once again with exceptions. Human sequences (expected outgroups) clustered with perissodactyl CYP11A1, CYP17A1 and SRD5A1 gene orthologues, forming outgroups only for HSD17B1 and SRD5A2. Spotted hyena CYP19A1 clustered within the Perissodactyla, between rhinoceros and equid orthologues, whereas CYP17A1 clustered within the Carnivora. This variability highlights the random adoption of divergent physiological strategies as pregnancy evolved among genetically similar species.
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Affiliation(s)
- A J Conley
- Department of Population Health & Reproduction, School of Veterinary Medicine, University of California, Davis, CA, USA.
| | - S C Loux
- Maxwell H. Gluck Equine Research Center, Department of Veterinary Science, University of Kentucky, Lexington, KY, USA
| | - E L Legacki
- Department of Population Health & Reproduction, School of Veterinary Medicine, University of California, Davis, CA, USA; Hollings Marine Laboratory, National Institute of Standards & Technology, Charleston, SC, USA
| | - M A Stoops
- Omaha's Henry Doorly Zoo and Aquarium, Omaha, NE, USA
| | - B Pukazhenthi
- Center for Species Survival, Smithsonian Conservation Biology Institute, Front Royal, VA, USA
| | - J L Brown
- Center for Species Survival, Smithsonian Conservation Biology Institute, Front Royal, VA, USA
| | - R Sattler
- Alaska Department of Fish and Game, Palmer, AK, USA
| | - H M French
- Department of Clinical Sciences, Ross University School of Veterinary Medicine, St. Kitts, West Indies
| | - A Tibary
- Comparative Theriogenology, Department of Veterinary Clinical Sciences, College of Veterinary Medicine, Washington State University, Pullman, WA, USA
| | - T R Robeck
- Zoological Operations, SeaWorld Parks and Entertainment, Orlando, FL, USA
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Hiew MWH, Megahed AA, Horstman LA, Constable PD. Clinical utility of plasma progesterone and blood and plasma glucose concentrations in predicting parturition in Holstein cows. J Dairy Sci 2020; 103:5575-5590. [PMID: 32307156 DOI: 10.3168/jds.2019-17800] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2019] [Accepted: 02/13/2020] [Indexed: 12/27/2022]
Abstract
An accurate, practical, and low-cost method for predicting parturition is urgently needed in the dairy industry. The objective of this study was to evaluate changes in plasma progesterone concentration ([prog]) and glucose concentration in whole blood ([gluc]b) and plasma ([gluc]p) as predictors of parturition within 6, 12, and 24 h in primiparous and multiparous Holstein cows. Blood samples were obtained daily at approximately 0900 h from 34 primiparous and 72 multiparous Holstein cows in late gestation and the time of calving recorded to the nearest hour. Plasma [prog] was measured using an ELISA, and [gluc]b and [gluc]p using a low-cost point-of-care glucose meter. The optimal cut-point for predicting parturition was determined using binomial logistic regression with general estimating equations, because the data set consisted of repeated measures for each cow. Diagnostic test performance was evaluated by comparing the area under the receiver operating characteristic curve (AUC) and calculating the sensitivity, specificity, and κ at the optimal cut-point for predicting parturition. Plasma [prog] was the most accurate predictor of parturition within 24 h (AUC = 0.96) and 12 h (AUC = 0.93), whereas [gluc]b was the most accurate predictor of parturition within 6 h (primiparous, AUC = 0.96; multiparous, AUC = 0.86). We conclude that a decrease in plasma [prog] is currently the most accurate test for predicting calving within 24 h. Measurement of [gluc]b is a promising new test for the cow-side prediction of parturition in dairy cows due to its accuracy, practicality, and low cost.
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Affiliation(s)
- M W H Hiew
- Department of Veterinary Clinical Science, College of Veterinary Medicine, Purdue University, West Lafayette, IN 47907; Department of Veterinary Clinical Studies, Faculty of Veterinary Medicine, Universiti Putra, Selangor 43400, Malaysia
| | - A A Megahed
- Department of Veterinary Clinical Science, College of Veterinary Medicine, Purdue University, West Lafayette, IN 47907; Department of Animal Medicine, Internal Medicine, Faculty of Veterinary Medicine, Benha University, Moshtohor-Toukh, Kalyobiya 13736, Egypt
| | - L A Horstman
- Department of Veterinary Clinical Science, College of Veterinary Medicine, Purdue University, West Lafayette, IN 47907
| | - P D Constable
- Department of Veterinary Clinical Science, College of Veterinary Medicine, Purdue University, West Lafayette, IN 47907; Department of Veterinary Clinical Medicine, College of Veterinary Medicine, University of Illinois at Urbana-Champaign 61802.
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Legacki EL, Robeck TR, Steinman KJ, Conley AJ. Comparative analysis of steroids in cyclic and pregnant killer whales, beluga whales and bottlenose dolphins by liquid chromatography tandem mass spectrometry. Gen Comp Endocrinol 2020; 285:113273. [PMID: 31525377 DOI: 10.1016/j.ygcen.2019.113273] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/21/2019] [Revised: 09/10/2019] [Accepted: 09/12/2019] [Indexed: 11/21/2022]
Abstract
There exists a surprising diversity in the physiology and endocrinology of pregnancy among mammals in both the source (luteal/placental) and metabolism of progesterone. To evaluate the possible diversity of steroid metabolism within toothed cetaceans, we investigated 5α-reduced progesterone metabolites and androgens in cyclic (luteal phase) and pregnant captive killer whales, belugas and bottlenose dolphins (n = 5/species) bled longitudinally in early, mid- and late pregnancy (0.16, 0.50 and 0.85 fractions of 535, 464 and 380 gestation days, respectively). Mid-luteal samples were also collected. Serum was analyzed by liquid chromatography tandem-mass spectrometry as previously validated for (among others) progesterone, 20αOH-progesterone (20αOHP), 5α-dihydroprogesterone (DHP), several additional 5α-reduced metabolites and androgens (dehydroepiandrosterone, androstenedione and testosterone). The predominant mid-luteal pregnanes were: progesterone, belugas; progesterone and 20αOHP, dolphins; allopregnanolone (3α-DHP) and progesterone, killer whales. Progesterone was 2-4-fold higher in early pregnancy than mid-luteal samples but decreased thereafter. The predominant metabolite, 3β,20α-dihydroprogesterone (3β,20α-DHP; 40-80 ng/ml) was higher in mid- and late-than early gestation in all 3 species. Concentrations of 20αOHP and 3β,20α-DHP were similar at mid-gestation but 20αOHP declined in late-gestation in killer whales, and 20αOHP was lower than 3β,20α-DHP in belugas and dolphins throughout gestation. Other 5α-reduced metabolites, DHP, 3α-DHP and 20α-DHP, were far lower throughout pregnancy (<10 ng/ml). DHP and 3α-DHP decreased from early to mid-gestation in belugas, but changed little in killer whales and dolphins. These data suggest that progesterone metabolism is relatively conserved among these cetacean species. As in equine pregnancies, 3β,20α-DHP is the major metabolite, increasing at the expense of progesterone as pregnancy progresses. Androstenedione and testosterone also increased detectably in mid- to late-gestation in these species. The tissue source remains unknown, but progesterone metabolism during gestation in these cetaceans is similar to horses and, together with androgens, may be reliable biomarkers of pregnancy.
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Affiliation(s)
- Erin L Legacki
- Department of Population Health & Reproduction, School of Veterinary Medicine, University of California, Davis, CA 95616, USA
| | - Todd R Robeck
- SeaWorld Parks and Entertainment, Inc., SeaWorld and Busch Gardens Species Preservation Laboratory, San Diego, CA 92109, USA
| | - Karen J Steinman
- SeaWorld Parks and Entertainment, Inc., SeaWorld and Busch Gardens Species Preservation Laboratory, San Diego, CA 92109, USA
| | - Alan J Conley
- Department of Population Health & Reproduction, School of Veterinary Medicine, University of California, Davis, CA 95616, USA.
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Progestogen profiling in plasma during the estrous cycle in cattle using an LC-MS based approach. Theriogenology 2019; 142:376-383. [PMID: 31708192 DOI: 10.1016/j.theriogenology.2019.10.005] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2019] [Revised: 10/02/2019] [Accepted: 10/08/2019] [Indexed: 11/23/2022]
Abstract
In many mammalian species, corpus luteum derived progesterone (P4) is the main functional gestagen during the estrous cycle and pregnancy. P4 can be metabolized into various metabolites, of which some are biologically active. While some metabolites target the classical nuclear progesterone receptor (PR), neurosteroids bind the receptors of type A γ-aminobutyric acid (GABAA-r) in the brain. According to the position of reduction within the molecule, metabolites of P4 can be characterized into C20-reduced progestogens (20α-dihydroprogesterone (20α-DHP) and 20β-dihydroprogesterone (20β-DHP)), C3-reduced progestogens (3α-dihydroprogesterone (3α-DHP) and 3β-dihydroprogesterone (3β-DHP)), 5α-reduced progestogens (5α-dihydroprogesterone (5α-DHP), allopregnanolone and isopregnanolone) and 5β-reduced progestogens (5β-dihydroprogesterone (5β-DHP), pregnanolone and epipregnanolone). We questioned whether the reduced progestogens are present in bovine plasma during the estrous cycle and whether their profiles differed from the profile of the common precursor P4 around the time of luteolysis. The analytes were monitored in plasma samples using liquid chromatography mass spectrometry (LC-MS). While progestogens lagged behind the drop of P4 at luteolysis, they followed the profile of P4 during the estrous cycle. The abundance of P4 was predominant followed by allopregnanolone, pregnanolone, epipregnanolone and 20β-DHP. Further studies will need to focus particularly on the period around luteolysis.
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