Skip to main content

Advertisement

SpringerLink
Log in

Shift of Maternal Gut Microbiota of Tibetan Antelope (Pantholops hodgsonii) During the Periparturition Period

  • Published:
Current Microbiology Aims and scope Submit manuscript

Abstract

The maternal gut microbiota can influence and be affected by the substantial physiological changes taking place during the periparturition period. However, little information is known about the changes in the maternal gut microbiota and hormonal variations during this period in nonmodel organisms. Tibetan antelope (Pantholops hodgsonii) provide a unique system to address this issue because their summer migration cycle is synchronized with the periparturition period. Here, we used fecal microbiota as a proxy of gut microbiota. We characterized fecal microbial community of female migratory Tibetan antelope in the late pregnancy and postpartum periods using 16S rRNA gene sequencing and quantified fecal glucocorticoids (GCs) and triiodothyronine (T3) metabolite concentrations through enzyme immunoassays to identify the associations between maternal gut microbiota and physiological changes related with reproduction. We found that the fecal microbiota of Tibetan antelope was dominated by Firmicutes and Bacteroidetes. The microbial composition was significantly altered during the transition from late pregnancy to the postpartum period. Fecal T3 concentration was significantly higher in the postpartum period compared to late pregnancy, whereas GC metabolite concentration did not significantly differ between two reproductive states. We identified six genera (Anaerofustis, Bacteroides, Coprococcus_2, Ruminiclostridium_5, Ruminococcaceae_UCG-007, and Tyzzerella) that were significantly associated with reproductive states. We also found two genera (Christensenellaceae_R-7_group and Rikenellaceae_RC9_gut_group) significantly associated with GC metabolite concentration and two genera (Agathobacter and Papillibacter) significantly associated with T3 metabolite concentration, though these correlations were weak with coefficient values ranging from − 0.007 to 0.03. Our results indicate that many members of the gut microbiota are associated with the physiological changes in the transition from late pregnancy to the postpartum period, likely reflecting the metabolic and immune system dynamics during the periparturition period. This study highlights the importance of integrating microbiota, hormones and migration pattern to study the reproductive health of wildlife. By establishing a baseline of the physiological changes during the migration/periparturition period, we can have a better understanding of the impacts of increasing human activities on the Tibetan Plateau on the reproductive health of Tibetan antelope.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Data Availability

Raw sequence reads (fastq.gz) used in this research along with corresponding metadata were archived in the NCBI Sequence Read Archive (BioProject ID: PRJNA673151) using the publicly accessible Genomic Observatories Metadatabase (GUID: https://n2t.net/ark:/21547/Dfw2). Scripts used in this study were deposited on Github (https://github.com/melodysyue/TibetanAntelope_Microbiome_Hormone). ASV sequences (fasta), ASV abundance table and taxonomic classification (tsv), and sample metadata information (csv) along with intermediate data files generated from various analyses were deposited in the same Github repository as well.

References

  1. Blaser MJ, Domínguez-Bello MG (2016) The human microbiome before birth. Cell Host Microbe 20:558–560. https://doi.org/10.1016/j.chom.2016.10.014

    Article  CAS  PubMed  Google Scholar 

  2. Prince AL, Chu DM, Seferovic MD et al (2015) The perinatal microbiome and pregnancy: moving beyond the vaginal microbiome. Cold Spring Harbor Perspect Med 5:a023051–a023051. https://doi.org/10.1101/cshperspect.a023051

    Article  CAS  Google Scholar 

  3. Dunlop AL, Mulle JG, Ferranti EP et al (2015) Maternal microbiome and pregnancy outcomes that impact infant health. Adv Neonatal Care 15:377–385. https://doi.org/10.1097/ANC.0000000000000218

    Article  PubMed  PubMed Central  Google Scholar 

  4. Zeng Z, Liu F, Li S (2017) Metabolic adaptations in pregnancy: a review. Ann Nutr Metab 70:59–65. https://doi.org/10.1159/000459633

    Article  CAS  PubMed  Google Scholar 

  5. Lain KY, Catalano PM (2007) Metabolic changes in pregnancy. Clin Obstet Gynecol 50:938–948. https://doi.org/10.1097/GRF.0b013e31815a5494

    Article  PubMed  Google Scholar 

  6. Butte NF, King JC (2005) Energy requirements during pregnancy and lactation. Publ Health Nutr 8:1010–1027. https://doi.org/10.1079/PHN2005793

    Article  Google Scholar 

  7. Picciano MF (2003) Pregnancy and lactation: physiological adjustments, nutritional requirements and the role of dietary supplements. J Nutr 133:1997S-2002S

    Article  Google Scholar 

  8. Palme R, Rettenbacher S, Touma C et al (2006) Stress hormones in mammals and birds: comparative aspects regarding metabolism, excretion, and noninvasive measurement in fecal samples. Ann N Y Acad Sci 1040:162–171. https://doi.org/10.1196/annals.1327.021

    Article  CAS  Google Scholar 

  9. Douyon L, Schteingart DE (2002) Effect of obesity and starvation on thyroid hormone, growth hormone, and cortisol secretion. Endocrinol Metab Clin North Am 31:173–189

    Article  CAS  Google Scholar 

  10. Capuco AV, Connor EE, Wood DL (2008) Regulation of mammary gland sensitivity to thyroid hormones during the transition from pregnancy to lactation. Exp Biol Med (Maywood) 233:1309–1314. https://doi.org/10.3181/0803-RM-85

    Article  CAS  Google Scholar 

  11. Koren O, Goodrich JK, Cullender TC et al (2012) Host remodeling of the gut microbiome and metabolic changes during pregnancy. Cell 150:470–480. https://doi.org/10.1016/j.cell.2012.07.008

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Jost T, Lacroix C, Braegger C, Chassard C (2013) Stability of the maternal gut microbiota during late pregnancy and early lactation. Curr Microbiol 68:419–427. https://doi.org/10.1007/s00284-013-0491-6

    Article  CAS  PubMed  Google Scholar 

  13. Crusell MKW, Hansen TH, Nielsen T et al (2018) Gestational diabetes is associated with change in the gut microbiota composition in third trimester of pregnancy and postpartum. Microbiome. https://doi.org/10.1186/s40168-018-0472-x

    Article  PubMed  PubMed Central  Google Scholar 

  14. Lima FS, Oikonomou G, Lima SF et al (2015) Prepartum and postpartum rumen fluid microbiomes: characterization and correlation with production traits in dairy cows. Appl Environ Microbiol 81:1327–1337. https://doi.org/10.1128/AEM.03138-14

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. West AG, Waite DW, Deines P et al (2019) The microbiome in threatened species conservation. Biol Conserv 229:85–98. https://doi.org/10.1016/j.biocon.2018.11.016

    Article  Google Scholar 

  16. Alipour MJ, Jalanka J, Pessa-Morikawa T et al (2018) The composition of the perinatal intestinal microbiota in cattle. Sci Rep 8:1–14. https://doi.org/10.1038/s41598-018-28733-y

    Article  CAS  Google Scholar 

  17. Husso A, Jalanka J, Alipour MJ et al (2020) The composition of the perinatal intestinal microbiota in horse. Sci Rep. https://doi.org/10.1038/s41598-019-57003-8

    Article  PubMed  PubMed Central  Google Scholar 

  18. O’Donnell MM, Harris HMB, Ross RP, O’Toole PW (2017) Core fecal microbiota of domesticated herbivorous ruminant, hindgut fermenters, and monogastric animals. MicrobiologyOpen. https://doi.org/10.1002/mbo3.509

    Article  Google Scholar 

  19. Redford KH, Segre JA, Salafsky N et al (2012) Conservation and the microbiome. Conserv Biol 26:195–197. https://doi.org/10.1111/j.1523-1739.2012.01829.x

    Article  PubMed  PubMed Central  Google Scholar 

  20. Trevelline BK, Fontaine SS, Hartup BK, Kohl KD (2019) Conservation biology needs a microbial renaissance: a call for the consideration of host-associated microbiota in wildlife management practices. Proc Biol Sci 286:20182448–20182449. https://doi.org/10.1098/rspb.2018.2448

    Article  PubMed  PubMed Central  Google Scholar 

  21. Schaller GB (1998) Wildlife of the Tibetan Steppe. University of Chicago Press, Chicago

    Google Scholar 

  22. Buho H, Jiang Z, Liu C et al (2011) Preliminary study on migration pattern of the Tibetan antelope (Pantholops hodgsonii) based on satellite tracking. Adv Space Res 48:43–48. https://doi.org/10.1016/j.asr.2011.02.015

    Article  CAS  Google Scholar 

  23. Leclerc C, Bellard C, Luque GM, Courchamp F (2015) Overcoming extinction: understanding processes of recovery of the Tibetan antelope. Ecosphere. https://doi.org/10.1890/ES15-00049.1.sm

    Article  Google Scholar 

  24. Yasuda K, Oh K, Ren B et al (2015) Biogeography of the intestinal mucosal and lumenal microbiome in the Rhesus Macaque. Cell Host Microbe 17:385–391. https://doi.org/10.1016/j.chom.2015.01.015

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Ingala MR, Simmons NB, Wultsch C et al (2018) Comparing microbiome sampling methods in a wild mammal: fecal and intestinal samples record different signals of host ecology. Evolution 9:141–113. https://doi.org/10.3389/fmicb.2018.00803

    Article  Google Scholar 

  26. Ley RE, Hamady M, Lozupone C et al (2008) Evolution of mammals and their gut microbes. Science 320:1647–1651. https://doi.org/10.1126/science.1155390

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Xia L, Yang Q, Li Z et al (2007) The effect of the Qinghai-Tibet railway on the migration of Tibetan antelope Pantholops hodgsonii in Hoh-xil National Nature Reserve, China. ORX. https://doi.org/10.1017/S0030605307000116

    Article  Google Scholar 

  28. Lian X, Zhang T, Cao Y et al (2007) Group size effects on foraging and vigilance in migratory Tibetan antelope. Behav Proc 76:192–197. https://doi.org/10.1016/j.beproc.2007.05.001

    Article  Google Scholar 

  29. Menke S, Meier M, Sommer S (2015) Shifts in the gut microbiome observed in wildlife faecal samples exposed to natural weather conditions: lessons from time-series analyses using next-generation sequencing for application in field studies. Methods Ecol Evol 6:1080–1087. https://doi.org/10.1007/978-0-387-87458-6

    Article  Google Scholar 

  30. Mori H, Maruyama F, Kato H et al (2014) Design and experimental application of a novel non-degenerate universal primer set that amplifies prokaryotic 16S rRNA genes with a low possibility to amplify eukaryotic rRNA genes. DNA Res 21:217–227. https://doi.org/10.1093/dnares/dst052

    Article  CAS  PubMed  Google Scholar 

  31. Callahan BJ, McMurdie PJ, Rosen MJ et al (2016) DADA2: High-resolution sample inference from Illumina amplicon data. Nat Methods 13:581–583. https://doi.org/10.1038/nmeth.3869

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Quast C, Pruesse E, Yilmaz P et al (2012) The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res 41:D590–D596. https://doi.org/10.1093/nar/gks1219

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Plummer E, Twin J (2015) A comparison of three bioinformatics pipelines for the analysis of preterm gut microbiota using 16S rRNA gene sequencing data. J Proteomics Bioinform. https://doi.org/10.4172/jpb.1000381

    Article  Google Scholar 

  34. Zhang Y, Parmigiani G, Johnson WE (2020) ComBat-Seq: batch effect adjustment for RNA-Seq count data. bioRxiv 19:881–21. https://doi.org/10.1101/2020.01.13.904730

    Article  Google Scholar 

  35. Wasser SK, Azkarate JC, Booth RK et al (2010) Non-invasive measurement of thyroid hormone in feces of a diverse array of avian and mammalian species. Gen Comput Endocrinol 168:1–7. https://doi.org/10.1016/j.ygcen.2010.04.004

    Article  CAS  Google Scholar 

  36. Wasser SK, Hunt KE, Brown JL et al (2000) A generalized fecal glucocorticoid assay for use in a diverse array of nondomestic mammalian and avian species. Gen Comput Endocrinol 120:260–275. https://doi.org/10.1006/gcen.2000.7557

    Article  CAS  Google Scholar 

  37. Palme R, Fischer P, Schildorfer H, Ismail MN (1996) Excretion of infused 14C-steroidhormones via faeces and urine in domestic livestock. Anim Reprod Sci 43:43–63

    Article  CAS  Google Scholar 

  38. Touma C, Palme R (2006) Measuring fecal glucocorticoid metabolites in mammals and birds: the importance of validation. Ann N Y Acad Sci 1046:54–74. https://doi.org/10.1196/annals.1343.006

    Article  CAS  Google Scholar 

  39. McMurdie PJ, Holmes S (2013) phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data. PLoS ONE 8:e61217–e61311. https://doi.org/10.1371/journal.pone.0061217

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. McMurdie PJ, Holmes S (2014) Waste not, want not: why rarefying microbiome data is inadmissible. PLoS Comput Biol 10:e1003531. https://doi.org/10.1371/journal.pcbi.1003531.s002

    Article  PubMed  PubMed Central  Google Scholar 

  41. Bai X, Lu S, Yang J et al (2018) Precise fecal microbiome of the herbivorous tibetan antelope inhabiting high-altitude Alpine plateau. Front Microbiol 9:1480–1513. https://doi.org/10.3389/fmicb.2018.02321

    Article  Google Scholar 

  42. Lau SKP, Teng JLL, Chiu TH et al (2018) Differential microbial communities of omnivorous and herbivorous cattle in southern China. Comput Struct Biotechnol J 16:54–60. https://doi.org/10.1016/j.csbj.2018.02.004

    Article  PubMed  PubMed Central  Google Scholar 

  43. Friedman ES, Bittinger K, Esipova TV et al (2018) Microbes vs. chemistry in the origin of the anaerobic gut lumen. Proc Natl Acad Sci USA 115:4170–4175. https://doi.org/10.1073/pnas.1718635115

    Article  CAS  PubMed  Google Scholar 

  44. Nagpal R, Tsuji H, Takahashi T et al (2017) Ontogenesis of the gut microbiota composition in healthy, full-term, vaginally born and breast-fed infants over the first 3 years of life: a quantitative bird’s-eye view. Front Microbiol 8:583–589. https://doi.org/10.3389/fmicb.2017.01388

    Article  Google Scholar 

  45. Krajmalnik-Brown R, Ilhan Z-E, Kang D-W, DiBaise JK (2012) Effects of gut microbes on nutrient absorption and energy regulation. Nutr Clin Pract 27:201–214. https://doi.org/10.1177/0884533611436116

    Article  PubMed  PubMed Central  Google Scholar 

  46. Dearing MD, Kohl KD (2017) Beyond fermentation: other important services provided to endothermic herbivores by their gut microbiota. Integr Comp Biol 57:723–731. https://doi.org/10.1093/icb/icx020

    Article  CAS  PubMed  Google Scholar 

  47. David LA, Maurice CF, Carmody RN et al (2013) Diet rapidly and reproducibly alters the human gut microbiome. Nature 505:559–563. https://doi.org/10.1038/nature12820

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Cardman Z, Arnosti C, Durbin A et al (2014) Verrucomicrobia are candidates for polysaccharide-degrading bacterioplankton in an arctic fjord of Svalbard. Appl Environ Microbiol 80:3749–3756. https://doi.org/10.1128/AEM.00899-14

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Belzer C, de Vos WM (2012) Microbes inside - from diversity to function: the case of Akkermansia. ISME J 6:1449–1458. https://doi.org/10.1038/ismej.2012.6

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Di Rienzi SC, Sharon I, Wrighton KC et al (2013) The human gut and groundwater harbor non-photosynthetic bacteria belonging to a new candidate phylum sibling to Cyanobacteria. eLife Sci 2:611–25. https://doi.org/10.7554/eLife.01102

    Article  CAS  Google Scholar 

  51. Stuebe A, Rich-Edwards J (2008) The reset hypothesis: lactation and maternal metabolism. Am J Perinatol 26:081–088. https://doi.org/10.1055/s-0028-1103034

    Article  Google Scholar 

  52. Nelson SM, Matthews P, Poston L (2010) Maternal metabolism and obesity: modifiable determinants of pregnancy outcome. Hum Reprod Update 16:255–275. https://doi.org/10.1093/humupd/dmp050

    Article  PubMed  Google Scholar 

  53. Gohir W, Whelan FJ, Surette MG et al (2015) Pregnancy-related changes in the maternal gut microbiota are dependent upon the mother’s periconceptional diet. Gut Microbes 6:310–320. https://doi.org/10.1080/19490976.2015.1086056

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Collado MC, Isolauri E, Laitinen K, Salminen S (2008) Distinct composition of gut microbiota during pregnancy in overweight and normal-weight women. Am J Clin Nutr 88:894–899. https://doi.org/10.1093/ajcn/88.4.894

    Article  CAS  PubMed  Google Scholar 

  55. Wu Y, Bible PW, Long S et al (2019) Metagenomic analysis reveals gestational diabetes mellitus-related microbial regulators of glucose tolerance. Acta Diabetol 57:569–581. https://doi.org/10.1007/s00592-019-01434-2

    Article  CAS  PubMed  Google Scholar 

  56. Wexler HM (2007) Bacteroides: the good, the bad, and the nitty-gritty. Clin Microbiol Rev 20:593–621. https://doi.org/10.1128/CMR.00008-07

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Wingfield B, Coleman S, McGinnity TM, Bjourson A (2018) Robust microbial markers for non-invasive inflammatory bowel disease identification. IEEE/ACM Trans Comput Biol Bioinform. https://doi.org/10.1109/TCBB.2018.2831212

    Article  PubMed  Google Scholar 

  58. Sacks GP, Studena K, Sargent IL, Redman CWG (1998) Normal pregnancy and preeclampsia both produce inflammatory changes in peripheral blood leukocytes akin to those of sepsis. Am J Obstet Gynecol 179:80–86

    Article  CAS  Google Scholar 

  59. Mor G, Cardenas I, Abrahams V, Guller S (2011) Inflammation and pregnancy: the role of the immune system at the implantation site. Ann N Y Acad Sci 1221:80–87. https://doi.org/10.1111/j.1749-6632.2010.05938.x

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Rudolph MD, Graham AM, Feczko E et al (2018) Maternal IL-6 during pregnancy can be estimated from newborn brain connectivity and predicts future working memory in offspring. Nat Neurosci 21:765–772. https://doi.org/10.1038/s41593-018-0128-y

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Zhang K, Fujita Y, Chang L et al (2019) Abnormal composition of gut microbiota is associated with resilience versus susceptibility to inescapable electric stress. Transl Psychiatry. https://doi.org/10.1038/s41398-019-0571-x

    Article  PubMed  PubMed Central  Google Scholar 

  62. Kelly TN, Bazzano LA, Ajami NJ et al (2016) Gut microbiome associates with lifetime cardiovascular disease risk profile among bogalusa heart study participants. Circ Res 119:956–964. https://doi.org/10.1161/CIRCRESAHA.116.309219

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Hendrick V, Altshuler LL, Suri R (2011) Hormonal changes in the postpartum and implications for postpartum depression. Psychosomatics 39:93–101. https://doi.org/10.1016/S0033-3182(98)71355-6

    Article  Google Scholar 

  64. Robeck TR, Amaral RS, da Silva VMF et al (2019) Thyroid hormone concentrations associated with age, sex, reproductive status and apparent reproductive failure in the Amazon river dolphin (Inia geoffrensis). Conserv Physiol 7:354–413. https://doi.org/10.1093/conphys/coz041

    Article  CAS  Google Scholar 

  65. Che L, Hu Q, Wang R et al (2019) Inter-correlated gut microbiota and SCFAs changes upon antibiotics exposure links with rapid body-mass gain in weaned piglet model. J Nutr Biochem 74:108246. https://doi.org/10.1016/j.jnutbio.2019.108246

    Article  CAS  PubMed  Google Scholar 

  66. Kulecka M, Fraczek B, Mikula M et al (2020) The composition and richness of the gut microbiota differentiate the top Polish endurance athletes from sedentary controls. Gut Microbes 11:1374–1384. https://doi.org/10.1080/19490976.2020.1758009

    Article  PubMed  PubMed Central  Google Scholar 

  67. Concannon PW, Butler WR, Hansel W et al (1978) Parturition and lactation in the bitch: serum progesterone, cortisol and prolactin. Biol Reprod 19:1113–1118

    Article  CAS  Google Scholar 

  68. Glynn LM, Davis EP, Sandman CA (2013) New insights into the role of perinatal HPA-axis dysregulation in postpartum depression. Neuropeptides 47:363–370. https://doi.org/10.1016/j.npep.2013.10.007

    Article  CAS  PubMed  Google Scholar 

  69. Abou-Saleh MT, Ghubash R, Karim L et al (1998) Hormonal aspects of postpartum depression. Psychoneuroendocrinology 23:465–475

    Article  CAS  Google Scholar 

  70. Jung C, Ho JT, Torpy DJ et al (2011) A longitudinal study of plasma and urinary cortisol in pregnancy and postpartum. J Clin Endocrinol Metab 96:1533–1540. https://doi.org/10.1210/jc.2010-2395

    Article  CAS  PubMed  Google Scholar 

  71. Kong F, Hua Y, Zeng B et al (2016) Gut microbiota signatures of longevity. Curr Biol 26:R832–R833. https://doi.org/10.1016/j.cub.2016.08.015

    Article  CAS  PubMed  Google Scholar 

  72. Goodrich JK, Waters JL, Poole AC et al (2014) Human genetics shape the gut microbiome. Cell 159:789–799. https://doi.org/10.1016/j.cell.2014.09.053

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Lundberg R, Bahl MI, Licht TR et al (2017) Microbiota composition of simultaneously colonized mice housed under either a gnotobiotic isolator or individually ventilated cage regime. Sci Rep. https://doi.org/10.1038/srep42245

    Article  PubMed  PubMed Central  Google Scholar 

  74. Gomez-Arango LF, Barrett HL, McIntyre HD et al (2016) Connections between the gut microbiome and metabolic hormones in early pregnancy in overweight and obese women. Diabetes 65:2214–2223. https://doi.org/10.2337/db16-0278

    Article  CAS  PubMed  Google Scholar 

  75. Song J, Ma W, Gu X et al (2019) Metabolomic signatures and microbial community profiling of depressive rat model induced by adrenocorticotrophic hormone. J Transl Med. https://doi.org/10.1186/s12967-019-1970-8

    Article  PubMed  PubMed Central  Google Scholar 

  76. Joly K, Wasser SK, Booth R (2015) Non-invasive assessment of the interrelationships of diet, pregnancy rate, group composition, and physiological and nutritional stress of barren-ground caribou in late winter. PLoS ONE 10:e0127586-e127613. https://doi.org/10.1371/journal.pone.0127586

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. Cuyler C, Østergaard JB (2006) Fertility in two West Greenland caribou Rangifer tarandus groenlandicus populations during 1996/97: potential for rapid growth. Wildl Biol 11:221–227. https://doi.org/10.2981/0909

    Article  Google Scholar 

  78. Jiang Z, Seiki T, Gao Z, Jin K (1998) The preset status, ecology and conservation of the Mongolian gazelle, Procapra gutturosa: a review. Mammal Study 23:63–78

    Article  Google Scholar 

  79. Olson KA, Fuller TK, Schaller GB et al (2005) Reproduction, neonatal weights, and first-year survival of Mongolian gazelles (Procapra gutturosa). J Zool 265:227–233. https://doi.org/10.1017/S0952836904006284

    Article  Google Scholar 

  80. Schaller GB, Aili K, Xinbin C, Yanlin L (2006) Migratory and calving behavior of Tibetan antelope population. Acta Theriologica Sinica 26:105–113

    Google Scholar 

  81. Hodges K, Heistermann M (2011) Field and laboratory methods in primatology. A practical guide. Cambridge University Press, Cambridge

    Google Scholar 

  82. Cao Y, Su J, Lian X et al (2008) Food habits of Tibetan antelope (Pantholops hodgsoni) in the Kekexili Nature Reserve. Acta Theriologica Sinica 28:14–19

    Google Scholar 

  83. Yin B, Huai H, Zhang Y et al (2008) Trophic niches of Pantholops hodgsoni, Procapra picticaudata and Equus kiang in Kekexili region. Chin J Appl Ecol 18:766–770

    Google Scholar 

  84. Clemmons BA, Martino C, Schneider LG et al (2019) Temporal stability of the ruminal bacterial communities in beef steers. Sci Rep. https://doi.org/10.1038/s41598-019-45995-2

    Article  PubMed  PubMed Central  Google Scholar 

  85. Snelling TJ, Auffret MD, Duthie C-A et al (2019) Temporal stability of the rumen microbiota in beef cattle, and response to diet and supplements. Anim Microbiome. https://doi.org/10.1186/s42523-019-0018-y

    Article  PubMed  PubMed Central  Google Scholar 

  86. Leeming ER, Johnson AJ, Spector TD, Le Roy CI (2019) Effect of diet on the gut microbiota: rethinking intervention duration. Nutrients 11:2862–2928. https://doi.org/10.3390/nu11122862

    Article  PubMed Central  Google Scholar 

  87. Leslie DM, Schaller GB (2008) Pantholops Hodgsonii (Artiodactyla: Bovidae). Mamm Spec 817:1–14. https://doi.org/10.1644/817.1

    Article  Google Scholar 

Download references

Acknowledgements

We thank Rebecca Booth for advice on hormonal assays. We thank Kekexili Natural Nature Reserve Administration for assistance in the fieldwork. We thank Richard G. Olmstead, Noah Synder-Mackler, Hyeon Jeong Kim, and three anonymous reviewers for feedback that greatly improved the manuscript.

Funding

The study was funded by the China Scholarship Council (CSC) Graduate Research Fellowship, Fritz/Boeing International Research Fellowship, and WRF Hall Fellowship.

Author information

Author notes

  1. Yue Shi

    Present address: College of Fisheries and Ocean Sciences, University of Alaska Fairbanks, 17101 Point Lena Loop Road, Juneau, AK, 99801, USA

  2. Jian-Ping Su and Samuel K. Wasser are Co-last authors.

Authors and Affiliations

  1. Department of Biology, University of Washington, Box 351800, Seattle, WA, 98195, USA

    Yue Shi & Samuel K. Wasser

  2. Qinghai Key Laboratory of Animal Ecological Genomics, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, No. 23 Xinning Road, Xining, 810008, Qinghai, China

    Zi-Yan Miao & Jian-Ping Su

  3. Museum of Natural Resources of Qinghai Province, Xining, 810008, Qinghai, China

    Zi-Yan Miao

Authors
  1. Yue Shi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Zi-Yan Miao
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jian-Ping Su
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Samuel K. Wasser
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

YS involved in conceptualization, project administration, methodology, investigation, formal analysis, data curation, visualization, and writing-original draft; ZYM contributed to investigation and resources; JPS performed conceptualization, project administration, investigation, and supervision; SKW participated in conceptualization and writing-reviewing & editing.

Corresponding author

Correspondence to Yue Shi.

Ethics declarations

Conflict of interest

The Authors and the legal representative of Jian-Ping Su declare that they have no conflicts of interest.

Ethical Approval

Tibetan antelope is listed in the Category I of the National Key Protected Wild Animal Species under China’s Wild Animal Protection Law. In September 2016, Tibetan antelope were reclassified from Endangered to Near Threatened by the International Union for Conservation of Nature (IUCN) Red List due to the recovery of their population size. Sample collection and field studies adhered to the Wild Animals Protection Law of the People’s Republic of China. Fresh scat samples were collected under University of Washington IACUC protocol #2850–12 and local regulations to minimize disturbance.

Additional information

Deceased Jian-Ping Su on 27 June 2018.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Shi, Y., Miao, ZY., Su, JP. et al. Shift of Maternal Gut Microbiota of Tibetan Antelope (Pantholops hodgsonii) During the Periparturition Period. Curr Microbiol 78, 727–738 (2021). https://doi.org/10.1007/s00284-020-02339-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00284-020-02339-y

Search

Navigation