Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Experimental validation of small mammal gut microbiota sampling from faeces and from the caecum after death

Abstract

Data on the gut microbiota (GM) of wild animals are key to studies on evolutionary biology (host–GM interactions under natural selection), ecology and conservation biology (GM as a fitness component closely connected to the environment). Wildlife GM sampling often requires non-invasive techniques or sampling from dead animals. In a controlled experiment profiling microbial 16S rRNA in 52 house mice (Mus musculus) from eight families and four genetic backgrounds, we studied the effects of live- and snap-trapping on small mammal GM and evaluated the suitability of microbiota from non-fresh faeces as a proxy for caecal GM. We compared CM from individuals sampled 16–18 h after death with those in live traps and caged controls, and caecal and faecal GM collected from mice in live-traps. Sampling delay did not affect GM composition, validating data from fresh cadavers or snap-trapped animals. Animals trapped overnight displayed a slight but significant difference in GM composition to the caged controls, though the change only had negligible effect on GM diversity, composition and inter-individual divergence. Hence, the trapping process appears not to bias GM profiling. Despite their significant difference, caecal and faecal microbiota were correlated in composition and, to a lesser extent, diversity. Both showed congruent patterns of inter-individual divergence following the natural structure of the dataset. Thus, the faecal microbiome represents a good non-invasive proxy of the caecal microbiome, making it suitable for detecting biologically relevant patterns. However, care should be taken when analysing mixed datasets containing both faecal and caecal samples.

This is a preview of subscription content

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1: Alpha diversity variation of caecal microbiota between control-in-cage (control), alive-in-trap (alive) and dead-on-trap (dead) mice.
Fig. 2: Compositional variation of caecal microbiota between control-in-cage (control), alive-in-trap (alive) and dead-on-trap (dead) mice.
Fig. 3: Microbiota diversity and composition in caeca vs. faeces.
Fig. 4: Dissimilarity in microbiota composition between and within mouse families.

Data availability

Sequencing data associated with this study were archived in the European Nucleotide Archive, under the study accession number PRJEB41530. Accession numbers of each sample are available in Table S1.

References

  1. Aivelo T, Norberg A (2018) Parasite-microbiota interactions potentially affect intestinal communities in wild mammals. J Anim Ecol 87:438–447

    PubMed  Article  Google Scholar 

  2. Alberdi A, Aizpurua O, Bohmann K, Zepeda-Mendoza ML, Gilbert MTP (2016) Do vertebrate gut metagenomes confer rapid ecological adaptation? Trends Ecol Evol 31:689–699

    PubMed  Article  Google Scholar 

  3. Amaral WZ, Lubach GR, Proctor A, Lyte M, Phillips GJ, Coe CL (2017) Social influences on Prevotella and the gut microbiome of young monkeys. Psychosom Med 79:888–897

    PubMed  PubMed Central  Article  Google Scholar 

  4. Amato KR, Sanders GJ, Song SJ, Nute M, Metcalf JL, Thompson LR et al. (2019) Evolutionary trends in host physiology outweigh dietary niche in structuring primate gut microbiomes. ISME J 13:576–587

    CAS  PubMed  Article  Google Scholar 

  5. Benjamini Y, Hochberg Y (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Ser B Methodol 57:289–300

    Google Scholar 

  6. Björk JR, Dasari M, Grieneisen L, Archie EA (2019) Primate microbiomes over time: longitudinal answers to standing questions in microbiome research. Am J Primatol 81:e22970

    PubMed  PubMed Central  Article  Google Scholar 

  7. Brooks JW (2016) Postmortem changes in animal carcasses and estimation of the postmortem interval. Vet Pathol 53:929–940

    CAS  PubMed  Article  Google Scholar 

  8. Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJA, Holmes SP (2016) DADA2: High-resolution sample inference from Illumina amplicon data. Nat Methods 13:581–583

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  9. Callahan BJ, Wong J, Heiner C, Oh S, Theriot CM, Gulati AS et al. (2019) High-throughput amplicon sequencing of the full-length 16S rRNA gene with single-nucleotide resolution. Nucleic Acids Res 47:e103

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  10. Clayton JB, Vangay P, Huang H, Ward T, Hillmann BM, Al-Ghalith GA et al. (2016) Captivity humanizes the primate microbiome. Proc Natl Acad Sci U S A 113:10376–10381

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  11. Cryan JF, Dinan TG (2012) Mind-altering microorganisms: the impact of the gut microbiota on brain and behaviour. Nat Rev Neurosci 13:701–712

    CAS  PubMed  Article  Google Scholar 

  12. De Filippo C, Cavalieri D, Di Paola M, Ramazzotti M, Poullet JB, Massart S et al. (2010) Impact of diet in shaping gut microbiota revealed by a comparative study in children from Europe and rural Africa. Proc Natl Acad Sci U S A 107:14691–14696

    PubMed  PubMed Central  Article  Google Scholar 

  13. Dill-McFarland KA, Neil KL, Zeng A, Sprenger RJ, Kurtz CC, Suen G et al. (2014) Hibernation alters the diversity and composition of mucosa-associated bacteria while enhancing antimicrobial defence in the gut of 13-lined ground squirrels. Mol Ecol 23:4658–4669

    CAS  PubMed  Article  Google Scholar 

  14. Donaldson GP, Lee SM, Mazmanian SK (2016) Gut biogeography of the bacterial microbiota. Nat Rev Microbiol 14:20–32

    CAS  PubMed  Article  Google Scholar 

  15. Dubois S, Fenwick N, Ryan EA, Baker L, Baker SE, Beausoleil NJ et al. (2017) International consensus principles for ethical wildlife control. Conserv Biol J Soc Conserv Biol 31:753–760

    Article  Google Scholar 

  16. Earl JP, Adappa ND, Krol J, Bhat AS, Balashov S, Ehrlich RL et al. (2018) Species-level bacterial community profiling of the healthy sinonasal microbiome using Pacific Biosciences sequencing of full-length 16S rRNA genes. Microbiome 6:190

    PubMed  PubMed Central  Article  Google Scholar 

  17. Edgar RC, Haas BJ, Clemente JC, Quince C, Knight R (2011) UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 27:2194–2200

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  18. Ericsson AC, Johnson PJ, Lopes MA, Perry SC, Lanter HR (2016) A microbiological map of the healthy equine gastrointestinal tract. PLoS ONE 11:e0166523

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  19. García-Amado MA, Michelangeli F, Gueneau P, Perez ME, Domínguez-Bello MG (2007) Bacterial detoxification of saponins in the crop of the avian foregut fermenter Opisthocomus hoazin. J Anim Feed Sci 16:82–85

    Article  Google Scholar 

  20. Gomez A, Petrzelkova KJ, Burns MB, Yeoman CJ, Amato KR, Vlckova K et al. (2016) Gut microbiome of coexisting BaAka pygmies and Bantu reflects gradients of traditional subsistence patterns. Cell Rep 14:2142–2153

    CAS  PubMed  Article  Google Scholar 

  21. Gomez A, Petrzelkova K, Yeoman CJ, Vlckova K, Mrázek J, Koppova I et al. (2015) Gut microbiome composition and metabolomic profiles of wild western lowland gorillas (Gorilla gorilla gorilla) reflect host ecology. Mol Ecol 24:2551–2565

    CAS  PubMed  Article  Google Scholar 

  22. Gorvitovskaia A, Holmes SP, Huse SM (2016) Interpreting Prevotella and bacteroides as biomarkers of diet and lifestyle. Microbiome 4:15

    PubMed  PubMed Central  Article  Google Scholar 

  23. Gregorová S, Forejt J (2000) PWD/Ph and PWK/Ph inbred mouse strains of Mus m. musculus subspecies–a valuable resource of phenotypic variations and genomic polymorphisms. Folia Biol 46:31–41

    Google Scholar 

  24. Gu S, Chen D, Zhang J-N, Lv X, Wang K, Duan L-P et al. (2013) Bacterial community mapping of the mouse gastrointestinal tract. PLoS ONE 8:e74957

  25. Heimesaat MM, Boelke S, Fischer A, Haag L-M, Loddenkemper C, Kühl AA et al. (2012) Comprehensive postmortem analyses of intestinal microbiota changes and bacterial translocation in human flora associated mice. PloS ONE 7:e40758

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  26. Hird SM (2017) Evolutionary biology needs wild microbiomes. Front Microbiol 8:725

  27. Iljazovic A, Roy U, Gálvez EJC, Lesker TR, Zhao B, Gronow A et al. (2020) Perturbation of the gut microbiome by Prevotella spp. enhances host susceptibility to mucosal inflammation. Mucosal Immunol 14:113–124

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  28. Ingala MR, Simmons NB, Wultsch C, Krampis K, Speer KA, Perkins SL (2018) Comparing microbiome sampling methods in a wild mammal: fecal and intestinal samples record different signals of host ecology, evolution. Front Microbiol 9:803

  29. Karasov WH, Douglas AE (2013) Comparative digestive physiology. Compr Physiol 3:741–783

    PubMed  PubMed Central  Article  Google Scholar 

  30. Kartzinel TR, Hsing JC, Musili PM, Brown BRP, Pringle RM (2019) Covariation of diet and gut microbiome in African megafauna. Proc Natl Acad Sci U S A 116:23588–23593

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  31. Kohl KD, Dearing MD (2016) The woodrat gut microbiota as an experimental system for understanding microbial metabolism of dietary toxins. Front Microbiol 7:1165

  32. Kohl KD, Luong K, Dearing MD (2015) Validating the use of trap-collected feces for studying the gut microbiota of a small mammal (Neotoma lepida). J Mammal 96:90–93

    Article  Google Scholar 

  33. Kohl KD, Varner J, Wilkening JL, Dearing MD (2018) Gut microbial communities of American pikas (Ochotona princeps): Evidence for phylosymbiosis and adaptations to novel diets. J Anim Ecol 87:323–330

    PubMed  Article  PubMed Central  Google Scholar 

  34. Kreisinger J, Bastien G, Hauffe HC, Marchesi J, Perkins SE (2015) Interactions between multiple helminths and the gut microbiota in wild rodents. Philos Trans R Soc B Biol Sci 370:20140295

  35. Kreisinger J, Čížková D, Vohánka J, Piálek J (2014) Gastrointestinal microbiota of wild and inbred individuals of two house mouse subspecies assessed using high-throughput parallel pyrosequencing. Mol Ecol 23:5048–5060

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  36. Kreisinger J, Kropáčková L, Petrželková A, Adámková M, Tomášek O, Martin J-F et al. (2017) Temporal stability and the effect of transgenerational transfer on fecal microbiota structure in a long distance migratory bird. Front Microbiol 8:50

  37. Laukaitis CM, Critser ES, Karn RC (1997) Salivary androgen-binding protein (ABP) mediates sexual isolation in Mus musculus. Evol Int J Org Evol 51:2000–2005

    CAS  Article  Google Scholar 

  38. Lawrence K, Lam K, Morgun A, Shulzhenko NLöhr C (2019) Effect of temperature and time on the thanatomicrobiome of the cecum, ileum, kidney, and lung of domestic rabbits. J Vet Diagn Invest 31. https://doi.org/10.1177/1040638719828412

  39. Legendre P, Anderson MJ (1999) Distance-based redundancy analysis: testing multispecies responses in multifactorial ecological experiments. Ecol Monogr 69:1–24

    Article  Google Scholar 

  40. Li D, Chen H, Mao B, Yang Q, Zhao J, Gu Z et al. (2017) Microbial biogeography and core microbiota of the rat digestive tract. Sci Rep 7:45840

    PubMed Central  Article  CAS  PubMed  Google Scholar 

  41. Maslanik T, Tannura K, Mahaffey L, Loughridge AB, Benninson L, Ursell L et al. (2012) Commensal bacteria and MAMPs are necessary for stress-induced increases in IL-1β and IL-18 but not IL-6, IL-10 or MCP-1. PLoS ONE 7:e50636

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  42. Matsuo Y, Komiya S, Yasumizu Y, Yasuoka Y, Mizushima K, Takagi T et al. (2020) Full-length 16S rRNA gene amplicon analysis of human gut microbiota using MinIONTM nanopore sequencing confers species-level resolution. bioRxiv. https://doi.org/10.1101/2020.05.06.078147

  43. McKenzie VJ, Song SJ, Delsuc F, Prest TL, Oliverio AM, Korpita TM et al. (2017) The effects of captivity on the mammalian gut microbiome. Integr Comp Biol 57:690–704

    PubMed  PubMed Central  Article  Google Scholar 

  44. McMurdie PJ, Holmes S (2014) Waste not, want not: why rarefying microbiome data is inadmissible. PLOS Comput Biol 10:e1003531

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  45. 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

    Article  Google Scholar 

  46. Miller AW, Oakeson KF, Dale C, Dearing MD (2016) Microbial community transplant results in increased and long-term oxalate degradation. Micro Ecol 72:470–478

    CAS  Article  Google Scholar 

  47. Pafčo B, Čížková D, Kreisinger J, Hasegawa H, Vallo P, Shutt K et al. (2018) Metabarcoding analysis of strongylid nematode diversity in two sympatric primate species. Sci Rep 8:5933

  48. Palm NW, de Zoete MR, Cullen TW, Barry NA, Stefanowski J, Hao L et al. (2014) Immunoglobulin A coating identifies colitogenic bacteria in inflammatory bowel disease. Cell 158:1000–1010

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  49. Pechal JL, Schmidt CJ, Jordan HR, Benbow ME (2018) A large-scale survey of the postmortem human microbiome, and its potential to provide insight into the living health condition. Sci Rep 8:5724

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  50. Pollock J, Glendinning L, Wisedchanwet T, Watson M (2018) The madness of microbiome: attempting to find consensus “best practice” for 16S microbiome studies. Appl Environ Microbiol 84:e02627–17

    PubMed  PubMed Central  Article  Google Scholar 

  51. Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P et al. (2013) The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res 41:D590–D596

    CAS  Article  Google Scholar 

  52. R Core Team (2018) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/

    Google Scholar 

  53. Rosshart SP, Vassallo BG, Angeletti D, Hutchinson DS, Morgan AP, Takeda K et al. (2017) Wild mouse gut microbiota promotes host fitness and improves disease resistance. Cell 171:1015–1028.e13

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  54. Round JL, Mazmanian SK (2009) The gut microbiome shapes intestinal immune responses during health and disease. Nat Rev Immunol 9:313–323

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  55. Scher JU, Sczesnak A, Longman RS, Segata N, Ubeda C, Bielski C et al. (2013) Expansion of intestinal Prevotella copri correlates with enhanced susceptibility to arthritis. eLife 2:e01202

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  56. Sommer F, Ståhlman M, Ilkayeva O, Arnemo JM, Kindberg J, Josefsson J et al. (2016) The gut microbiota modulates energy metabolism in the hibernating brown bear Ursus arctos. Cell Rep 14:1655–1661

    CAS  PubMed  Article  Google Scholar 

  57. Stalder GL, Pinior B, Zwirzitz B, Loncaric I, Jakupović D, Vetter SG et al. (2019) Gut microbiota of the European Brown Hare (Lepus europaeus). Sci Rep 9:2738

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  58. Stanley D, Geier MS, Chen H, Hughes RJ, Moore RJ (2015) Comparison of fecal and cecal microbiotas reveals qualitative similarities but quantitative differences. BMC Microbiol 15:51

    PubMed  PubMed Central  Article  Google Scholar 

  59. Stearns JC, Lynch MDJ, Senadheera DB, Tenenbaum HC, Goldberg MB, Cvitkovitch DG et al. (2011) Bacterial biogeography of the human digestive tract. Sci Rep 1:170

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  60. Stothart MR, Palme R, Newman AEM (2019) It’s what’s on the inside that counts: stress physiology and the bacterial microbiome of a wild urban mammal. Proc R Soc B Biol Sci 286:20192111

    Article  Google Scholar 

  61. Suzuki TA, Martins FM, Nachman MW (2019) Altitudinal variation of the gut microbiota in wild house mice. Mol Ecol 28:2378–2390

    CAS  PubMed  Article  Google Scholar 

  62. Suzuki TA, Nachman MW (2016) Spatial heterogeneity of gut microbial composition along the gastrointestinal tract in natural populations of house mice (EG Zoetendal, Ed.). PLoS ONE 11:e0163720

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  63. Tanca A, Manghina V, Fraumene C, Palomba A, Abbondio M, Deligios M et al. (2017) Metaproteogenomics reveals taxonomic and functional changes between cecal and fecal microbiota in mouse. Front Microbiol 8:391

  64. Tang Q, Jin G, Wang G, Liu T, Liu X, Wang B et al. (2020) Current sampling methods for gut microbiota: a call for more precise devices. Front Cell Infect Microbiol 10:151

  65. Tang W, Zhu G, Shi Q, Yang S, Ma T, Mishra SK et al. (2019) Characterizing the microbiota in gastrointestinal tract segments of Rhabdophis subminiatus: dynamic changes and functional predictions. MicrobiologyOpen 8:e789

  66. 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 R Soc B Biol Sci 286:20182448

    Article  Google Scholar 

  67. Tuomisto S, Karhunen PJ, Pessi T (2013) Time-dependent post mortem changes in the composition of intestinal bacteria using real-time quantitative PCR. Gut Pathog 5:35

  68. Turnbaugh PJ, Ley RE, Mahowald MA, Magrini V, Mardis ER, Gordon JI (2006) An obesity-associated gut microbiome with increased capacity for energy harvest. Nature 444:1027–1031

    Article  Google Scholar 

  69. Vasemägi A, Visse M, Kisand V (2017) Effect of Environmental Factors and an Emerging Parasitic Disease on Gut Microbiome of Wild Salmonid Fish. mSphere 2:e00418–17

    PubMed  PubMed Central  Article  Google Scholar 

  70. Videvall E, Strandh M, Engelbrecht A, Cloete S, Cornwallis C (2017) Measuring the gut microbiome in birds: Comparison of faecal and cloacal sampling. Mol Ecol Resour 18:424–434

    PubMed  Article  CAS  Google Scholar 

  71. Vlčková K, Shutt-Phillips K, Heistermann M, Pafčo B, Petrželková KJ, Todd A et al. (2018) Impact of stress on the gut microbiome of free-ranging western lowland gorillas. Microbiol Read Engl 164:40–44

    Article  CAS  Google Scholar 

  72. Wang Q, Garrity GM, Tiedje JM, Cole JR (2007) Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl Environ Microbiol 73:5261–5267

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  73. Wang J, Linnenbrink M, Künzel S, Fernandes R, Nadeau M-J, Rosenstiel P et al. (2014) Dietary history contributes to enterotype-like clustering and functional metagenomic content in the intestinal microbiome of wild mice. Proc Natl Acad Sci U S A 111:E2703–2710

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  74. Warne RW, Kirschman L, Zeglin L (2017) Manipulation of gut microbiota reveals shifting community structure shaped by host developmental windows in amphibian larvae. Integr Comp Biol 57:786–794

    PubMed  Article  Google Scholar 

  75. Weldon L, Abolins S, Lenzi L, Bourne C, Riley EM, Viney M (2015) The gut microbiota of wild mice. PLoS ONE 10:e0134643

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  76. Wu GD, Chen J, Hoffmann C, Bittinger K, Chen Y-Y, Keilbaugh SA et al. (2011) Linking long-term dietary patterns with gut microbial enterotypes. Science 334:105–108

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  77. Yan W, Sun C, Zheng J, Wen C, Ji C, Zhang D et al. (2019) Efficacy of fecal sampling as a gut proxy in the study of chicken gut microbiota. Front Microbiol 10:2126

  78. Yasuda K, Oh K, Ren B, Tickle TL, Franzosa EA, Wachtman LM et al. (2015) Biogeography of the intestinal mucosal and lumenal microbiome in the rhesus macaque. Cell Host Microbe 17:385–391

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  79. Zemanova MA (2019) Poor implementation of non-invasive sampling in wildlife genetics studies. Rethink Ecol 4:119–132

    Article  Google Scholar 

  80. Zemanova MA (2020) Towards more compassionate wildlife research through the 3Rs principles: moving from invasive to non-invasive methods. Wildl Biol 2020. https://doi.org/10.2981/wlb.00607

  81. Zhao W, Wang Y, Liu S, Huang J, Zhai Z, He C et al. (2015) The dynamic distribution of porcine microbiota across different ages and gastrointestinal tract segments. PLoS ONE 10:e0117441

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  82. Zilber-Rosenberg I, Rosenberg E (2008) Role of microorganisms in the evolution of animals and plants: the hologenome theory of evolution. FEMS Microbiol Rev 32:723–735

    CAS  PubMed  Article  Google Scholar 

Download references

Acknowledgements

This study was supported through the Czech Science Foundation, Project no. 19-19307S. Access to computing and storage facilities owned by parties and projects contributing to the National Grid Infrastructure MetaCentrum, provided under the programme ‘Projects of Large Infrastructure for Research, Development, and Innovations’ (LM2010005), is greatly appreciated. We also acknowledge the Genomics Core Facility, Central European Institute of Technology, Masaryk University, supported by the National Centre for Medical Genomics research infrastructure (LM2015091 funded by the Ministry of Education, Youth and Sports, Czech Republic). Especial thanks go to Filip Pardy and Boris Tichý for their support while obtaining the scientific data presented in this paper. The upkeep and management of the mouse colony were supported by the Czech Academy of Sciences under the Strategy AV 21 program.

Author information

Affiliations

Authors

Contributions

JK and DČ conceived the idea and designed the methodology; JP provided the experimental animals; DČ and LĎ collected the data; JK analysed the data; JK and DČ wrote the manuscript. All authors contributed to the drafts and gave final approval for publication.

Corresponding author

Correspondence to Dagmar Čížková.

Ethics declarations

Conflict of interest

The authors declare no competing interests.

Additional information

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

Associate editor Xiangjiang Zhan.

Supplementary information

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Čížková, D., Ďureje, Ľ., Piálek, J. et al. Experimental validation of small mammal gut microbiota sampling from faeces and from the caecum after death. Heredity 127, 141–150 (2021). https://doi.org/10.1038/s41437-021-00445-6

Download citation

Search

Quick links