Evaluating rectal swab collection method for gut microbiome analysis in the common marmoset (Callithrix jacchus)
Autoři:
Stephen C. Artim aff001; Alexander Sheh aff001; Monika A. Burns aff001; James G. Fox aff001
Působiště autorů:
Division of Comparative Medicine, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
aff001
Vyšlo v časopise:
PLoS ONE 14(11)
Kategorie:
Research Article
prolekare.web.journal.doi_sk:
https://doi.org/10.1371/journal.pone.0224950
Souhrn
The common marmoset (Callithrix jacchus) is increasingly used as an animal model for biomedical research; however, gastrointestinal diseases causing significant morbidity are endemic in many captive marmoset colonies. Establishing gut microbiome patterns in a marmoset colony may aid in clinical decision-making and model reproducibility. A standardized method of sample collection and storage is essential for proper interpretation of microbiome data. While microbiome studies commonly utilize fecal samples, the goal of this study was to determine whether the microbiome profile from a rectal swab performed on a sedated animal was comparable to the microbiome profile from a fecal sample. During routine physical exams, paired fecal and rectal swab samples were collected from each of 23 marmosets. DNA was extracted from all fecal and rectal swab samples and 16S ribosomal RNA gene sequences were amplified and analyzed. Initial comparison of the relative abundance of bacterial phyla between paired samples had a r2 value of 0.70 with S of 0.08 with no significant differences in α and β diversity metrics between fecal and rectal samples. Initial analysis however, revealed 5 discordant fecal-rectal pairs which corresponded only with the 5 rectal swabs that were classified as free of visible fecal matter during collection. Exclusion of these 5 pairs resulted in an optimized fit of the data as evidenced by a r2 value of 0.91 with S of 0.05. These results demonstrate that rectal swabs are a reliable method for profiling the fecal microbiome in the marmoset since the bacterial composition from a rectal swab with visible fecal contents correlated well with the bacterial composition from a fecal sample from the same marmoset. This study highlights the importance of standardized sample collection methods and exclusion of inappropriate samples.
Klíčová slova:
RNA sequence analysis – DNA sequence analysis – Microbiome – Rectum – Colon – Sedation – Marmosets
Zdroje
1. Marini RP, Wachtman LM, Tardif SD, Mansfield K, Fox JG. The Common Marmoset in Captivity and Biomedical Research. Academic Press; 2018.
2. t Hart BA, Abbott DH, Nakamura K, Fuchs E. The marmoset monkey: a multi-purpose preclinical and translational model of human biology and disease. Drug Discovery Today. 2012;17: 1160–1165. doi: 10.1016/j.drudis.2012.06.009 22728226
3. Tardif SD, Mansfield KG, Ratnam R, Ross CN, Ziegler TE. The marmoset as a model of aging and age-related diseases. ILAR J. 2011;52: 54–65. doi: 10.1093/ilar.52.1.54 21411858
4. Nishijima K, Saitoh R, Tanaka S, Ohsato-Suzuki M, Ohno T, Kitajima S. Life span of common marmoset (Callithrix jacchus) at CLEA Japan breeding colony. Biogerontology. 6 ed. 2012;13: 439–443. doi: 10.1007/s10522-012-9388-1 22752736
5. Ridley RM, Baker HF, Windle CP, Cummings RM. Very long term studies of the seeding of β-amyloidosis in primates. J Neural Transm. 2005;113: 1243–1251. doi: 10.1007/s00702-005-0385-2 16362635
6. Ross CN, Davis K, Dobek G, Tardif SD. Aging Phenotypes of Common Marmosets (Callithrix jacchus). 2012;2012: 1–6. doi: 10.1155/2012/567143 22506113
7. Baxter VK, Shaw GC, Sotuyo NP, Carlson CS, Olson EJ, Zink MC, et al. Serum Albumin and Body Weight as Biomarkers for the Antemortem Identification of Bone and Gastrointestinal Disease in the Common Marmoset. Glogauer M, editor. PLoS ONE. 2013;8: e82747–10. doi: 10.1371/journal.pone.0082747 24324827
8. DeGruttola AK, Low D, Mizoguchi A, Mizoguchi E. Current Understanding of Dysbiosis in Disease in Human and Animal Models. Inflamm Bowel Dis. 2016;22: 1137–1150. doi: 10.1097/MIB.0000000000000750 27070911
9. Bäckhed F, Fraser CM, Ringel Y, Sanders ME, Sartor RB, Sherman PM, et al. Defining a Healthy Human Gut Microbiome: Current Concepts, Future Directions, and Clinical Applications. Cell host & microbe. Cell Press; 2012;12: 611–622. doi: 10.1016/j.chom.2012.10.012 23159051
10. Ross CN, Austad S, Brasky K, Brown CJ, Forney LJ, Gelfond JA, et al. The development of a specific pathogen free (SPF) barrier colony of marmosets (Callithrix jacchus) for aging research. Aging (Albany NY). 2017;9: 2544–2558. doi: 10.18632/aging.101340 29227963
11. Bassis CM, Moore NM, Lolans K, Seekatz AM, Weinstein RA, Young VB, et al. Comparison of stool versus rectal swab samples and storage conditions on bacterial community profiles. BMC Microbiology 2012 12:1. BMC Microbiology; 2017;17: 1–7. doi: 10.1186/s12866-016-0921-2
12. Fouhy F, Deane J, Rea MC, O’Sullivan Ó, Ross RP, O’Callaghan G, et al. The Effects of Freezing on Faecal Microbiota as Determined Using MiSeq Sequencing and Culture-Based Investigations. Neu J, editor. PLoS ONE. Public Library of Science; 2015;10: e0119355. doi: 10.1371/journal.pone.0119355 25748176
13. Carroll IM, Ringel-Kulka T, Siddle JP, Klaenhammer TR, Ringel Y. Characterization of the Fecal Microbiota Using High-Throughput Sequencing Reveals a Stable Microbial Community during Storage. Neufeld J, editor. PLoS ONE. Public Library of Science; 2012;7: e46953. doi: 10.1371/journal.pone.0046953 23071673
14. Kim D, Hofstaedter CE, Zhao C, Mattei L, Tanes C, Clarke E, et al. Optimizing methods and dodging pitfalls in microbiome research. Microbiome. BioMed Central; 2017;5: 52. doi: 10.1186/s40168-017-0267-5 28476139
15. McKenna P, Hoffmann C, Minkah N, Aye PP, Lackner A, Liu Z, et al. The macaque gut microbiome in health, lentiviral infection, and chronic enterocolitis. PLOS Pathog. 2008;4: e20. doi: 10.1371/journal.ppat.0040020 18248093
16. Yasuda K, Oh K, Ren B, Tickle TL, Franzosa EA, Wachtman LM, et al. Biogeography of the intestinal mucosal and lumenal microbiome in the rhesus macaque. Cell host & microbe. 2015;17: 385–391. doi: 10.1016/j.chom.2015.01.015 25732063
17. Consortium THMP, Huttenhower C, Gevers D, Knight R, Abubucker S, Badger JH, et al. Structure, function and diversity of the healthy human microbiome. Nature. Nature Publishing Group; 2012;486: 207–214. doi: 10.1038/nature11234 22699609
18. Ericsson AC, Gagliardi J, Bouhan D, Spollen WG, Givan SA, Franklin CL. The influence of caging, bedding, and diet on the composition of the microbiota in different regions of the mouse gut. Scientific Reports. Nature Publishing Group; 2018;8: 4065. doi: 10.1038/s41598-018-21986-7 29511208
19. Shen Z, Feng Y, Sheh A, Everitt J, Bertram F, Paster BJ, et al. Isolation and characterization of a novel Helicobacter species, Helicobacter jaachi sp. nov., from common marmosets (Callithrix jaachus). J Med Microbiol. 2015;64: 1063–1073. doi: 10.1099/jmm.0.000113 26297446
20. Won YS, Vandamme P, Yoon JH, Park YH, Hyun BH, Kim HC, et al. Helicobacter callitrichissp. nov., a novel Helicobacterspecies isolated from the feces of the common marmoset (Callithrix jacchus). FEMS Microbiology Letters. 2007;271: 239–244. doi: 10.1111/j.1574-6968.2007.00721.x 17439542
21. Ladinsky MS, Araujo LP, Zhang X, Veltri J, Galan-Diez M, Soualhi S, et al. Endocytosis of commensal antigens by intestinal epithelial cells regulates mucosal T cell homeostasis. Science. 2019;363: eaat4042–12. doi: 10.1126/science.aat4042 30846568
22. Lynch SV, Pedersen O. The Human Intestinal Microbiome in Health and Disease. Phimister EG, editor. The New England journal of medicine. 2016;375: 2369–2379. doi: 10.1056/NEJMra1600266 27974040
23. Franklin CL, Ericsson AC. Microbiota and reproducibility of rodent models. Lab Anim. NIH Public Access; 2017;46: 114–122. doi: 10.1038/laban.1222 28328896
24. Debelius J, Song SJ, Vazquez-Baeza Y, Xu ZZ, González A, Knight R. Tiny microbes, enormous impacts: what matters in gut microbiome studies? Genome Biol. Genome Biology; 2016;17: 1–12. doi: 10.1186/s13059-015-0866-z
25. Bleich A, Hansen AK. Time to include the gut microbiota in the hygienic standardisation of laboratory rodents. Comparative Immunology, Microbiology and Infectious Diseases. 2012;35: 81–92. doi: 10.1016/j.cimid.2011.12.006 22257867
26. Comeau AM, Douglas GM, Langille MGI, Eisen J. Microbiome Helper: a Custom and Streamlined Workflow for Microbiome Research. Eisen J, editor. mSystems. American Society for Microbiology Journals; 2017;2: e00127–16. doi: 10.1128/mSystems.00127-16 28066818
27. Zhang J, Kobert K, Flouri T, Stamatakis A. PEAR: a fast and accurate Illumina Paired-End reAd mergeR. Bioinformatics. Oxford University Press; 2014;30: 614–620. doi: 10.1093/bioinformatics/btt593 24142950
28. Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello EK, et al. QIIME allows analysis of high-throughput community sequencing data. Nat Methods. Nature Publishing Group; 2010;7: 335–336. doi: 10.1038/nmeth.f.303 20383131
29. Hamady M, Knight R. Microbial community profiling for human microbiome projects: Tools, techniques, and challenges. Genome Res. Cold Spring Harbor Lab; 2009;19: 1141–1152. doi: 10.1101/gr.085464.108 19383763
30. Kuczynski J, Costello EK, Nemergut DR, Zaneveld J, Lauber CL, Knights D, et al. Direct sequencing of the human microbiome readily reveals community differences. Genome Biol. BioMed Central; 2010;11: 210. doi: 10.1186/gb-2010-11-5-210 20441597
31. Lozupone C, Hamady M, Knight R. UniFrac–An online tool for comparing microbial community diversity in a phylogenetic context. BMC Bioinformatics 2015 16:1. BioMed Central; 2006;7: 371. doi: 10.1186/1471-2105-7-371 16893466
32. Wickham H. ggplot2: elegant graphics for data analysis. 2016. doi: 10.18637/jss.v077.b02
Článok vyšiel v časopise
PLOS One
2019 Číslo 11
- Metamizol jako analgetikum první volby: kdy, pro koho, jak a proč?
- Nejasný stín na plicích – kazuistika
- Masturbační chování žen v ČR − dotazníková studie
- Je Fuchsova endotelová dystrofie rohovky neurodegenerativní onemocnění?
- Fixní kombinace paracetamol/kodein nabízí synergické analgetické účinky
Najčítanejšie v tomto čísle
- A daily diary study on maladaptive daydreaming, mind wandering, and sleep disturbances: Examining within-person and between-persons relations
- A 3’ UTR SNP rs885863, a cis-eQTL for the circadian gene VIPR2 and lincRNA 689, is associated with opioid addiction
- A substitution mutation in a conserved domain of mammalian acetate-dependent acetyl CoA synthetase 2 results in destabilized protein and impaired HIF-2 signaling
- Molecular validation of clinical Pantoea isolates identified by MALDI-TOF