DOI QR코드

DOI QR Code

Comparison of mice gut microbiota before and after fasting for a day

절식이 마우스 장내미생물에 미치는 영향

  • Hong, Jiwan (Faculty of Biotechnology, College of Applied Life Sciences, SARI, Jeju National University) ;
  • Jo, Hyejun (Faculty of Biotechnology, College of Applied Life Sciences, SARI, Jeju National University) ;
  • Unno, Tatsuya (Faculty of Biotechnology, College of Applied Life Sciences, SARI, Jeju National University)
  • Received : 2019.08.08
  • Accepted : 2019.10.02
  • Published : 2019.12.31

Abstract

In this study, we investigated the effects of fasting on gut microbiota of mice fed normal (CTL) or high-fat diets (HF). Mice were raised for 16 weeks and fasted for a day at the end of the experiment. Fecal samples were collected one day before and after fasting, which were analyzed using MiSeq. Our results showed that the species richness and evenness were decreased in fasted HF group, whereas no difference was observed for CTL groups. Moreover, HF fed mice gut microbiota showed different microbial communities after fasting, while CTL groups did not show microbiota shifts. Differential abundance analysis showed that fasting CTL group mice increased and decreased one operational taxonomic unit (OTU) in S24_7 and one OTU in Ruminococcaceae, respectively. On the other hand, fasting HF group mice decreased 10 OTUs and increased 3 OTUs most of which were classified to Ruminococcaceae. Our results suggest that fasting mice may affect the abundance of Ruminococcaceae species and effects of fasting seem to be more obvious for HF-fed mice compared to those of mice fed CTL-diet.

본 연구에서는 절식이 일반사료 및 고지방사료를 섭취한 마우스의 장내미생물생태에 미치는 영향에 관하여 조사하였다. 일반 사료 및 고지방사료를 마우스에 16주 동안 무한급이 형태로 섭취하게 하여 실험종료 직전에 1일(24시간) 간 절식시켰으며, 절식 전 후의 분변 샘플을 채집하고 MiSeq을 이용하여 장내미생물생태 분석을 진행하였다. 본 연구의 결과는 고지방사료를 섭취한 마우스에서는 절식 전후 장내미생물생태 내의 종 풍부성과 균등성이 감소한 반면, 일반사료를 섭취한 마우스에서는 차이를 나타내지 않았다. 또한, 고지방사료를 섭취한 마우스의 장내미생물생태에서는 절식 후 변화하는 것을 확인하였으며, 일반 사료를 섭취한 마우스의 절식 전후 변화가 없었다. Difference abundance analysis는 일반사료를 섭취한 마우스에서 절식 이후 S24-7로 분류되는 OTU는 증가하고, Ruminococcaceae로 분류되는 OTU가 감소하는 것으로 확인되었다. 반면, 고지방사료를 섭취한 마우스에서는 절식 이후 10OTUs가 감소하고, 3OTUs가 증가하였는데, 대부분 Ruminococcaceae로 분류되는 것으로 확인되었다. 본 연구 결과는 마우스에서의 절식이 장내미생물생태 중 Ruminococcaceae의 abundance에 영향을 미치며, 일반사료를 섭취한 마우스에 비해 고지방사료를 섭취한 마우스에서 절식에 대한 효과가 더 명확하게 나타난다는 것을 시사한다.

Keywords

References

  1. Longo VD, Mattson MP (2014) Fasting: molecular mechanisms and clinical applications Cell Metab 19: 181-192 doi:10.1016/j.cmet.2013.12.008
  2. Patterson RE, Sears DD (2017) Metabolic Effects of Intermittent Fasting Annu Rev Nutr 37: 371-393 doi:10.1146/annurev-nutr-071816-064634
  3. Descamps O, Riondel J, Ducros V, Roussel AM (2005) Mitochondrial production of reactive oxygen species and incidence of age-associated lymphoma in OF1 mice: effect of alternate-day fasting Mech Ageing Dev 126: 1185-1191 doi:10.1016/j.mad.2005.06.007
  4. Harvie MN, Pegington M, Mattson MP, Frystyk J, Dillon B, Evans G, Cuzick J, Jebb SA, Martin B, Cutler RG, Son TG, Maudsley S, Carlson OD, Egan JM, Flyvbjerg A, Howell A (2011) The effects of intermittent or continuous energy restriction on weight loss and metabolic disease risk markers: a randomized trial in young overweight women Int J Obes (Lond) 35: 714-727 doi:10.1038/ijo.2010.171
  5. Ley RE, Backhed F, Turnbaugh P, Lozupone CA, Knight RD, Gordon JI (2005) Obesity alters gut microbial ecology Proc Natl Acad Sci USA 102: 11070-11075 doi:10.1073/pnas.0504978102
  6. Ley RE, Turnbaugh PJ, Klein S, Gordon JI (2006) Microbial ecology: human gut microbes associated with obesity Nature 444: 1022-1023 doi:10.1038/4441022a
  7. 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 doi:10.1038/nature05414
  8. Kohl KD, Amaya J, Passement CA, Dearing MD, McCue MD (2014) Unique and shared responses of the gut microbiota to prolonged fasting: a comparative study across five classes of vertebrate hosts FEMS Microbiol Ecol 90: 883-894 doi:10.1111/1574-6941.12442
  9. Zhang C, Li S, Yang L, Huang P, Li W, Wang S, Zhao G, Zhang M, Pang X, Yan Z, Liu Y, Zhao L (2013) Structural modulation of gut microbiota in life-long calorie-restricted mice Nat Commun 4: 2163 doi:10.1038/ncomms3163
  10. Lien EL, Boyle FG, Wrenn JM, Perry RW, Thompson CA, Borzelleca JF (2001) Comparison of AIN-76A and AIN-93G diets: a 13-week study in rats Food Chem Toxicol 39: 385-392 https://doi.org/10.1016/S0278-6915(00)00142-3
  11. Kozich JJ, Westcott SL, Baxter NT, Highlander SK, Schloss PD (2013) Development of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on the MiSeq Illumina sequencing platform Appl Environ Microbiol 79: 5112-5120 doi:10.1128/AEM.01043-13
  12. Schloss PD, Westcott SL, Ryabin T, Hall JR, Hartmann M, Hollister EB, Lesniewski RA, Oakley BB, Parks DH, Robinson CJ, Sahl JW, Stres B, Thallinger GG, Van Horn DJ, Weber CF (2009) Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities Appl Environ Microbiol 75: 7537-7541 doi:10.1128/AEM.01541-09
  13. Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P, Peplies J, Glockner FO (2013) The SILVA ribosomal RNA gene database project: improved data processing and web-based tools Nucleic Acids Res 41: D590-596 doi:10.1093/nar/gks1219
  14. DeSantis TZ, Hugenholtz P, Larsen N, Rojas M, Brodie EL, Keller K, Huber T, Dalevi D, Hu P, Andersen GL (2006) Greengenes, a chimerachecked 16S rRNA gene database and workbench compatible with ARB Appl Environ Microbiol 72: 5069-5072 doi:10.1128/AEM.03006-05
  15. Rognes T, Flouri T, Nichols B, Quince C, Mahe F (2016) VSEARCH: a versatile open source tool for metagenomics PeerJ 4: e2584 doi:10.7717/peerj.2584
  16. Segata N, Izard J, Waldron L, Gevers D, Miropolsky L, Garrett WS, Huttenhower C (2011) Metagenomic biomarker discovery and explanation Genome Biol 12: R60 doi:10.1186/gb-2011-12-6-r60
  17. Parks DH, Tyson GW, Hugenholtz P, Beiko RG (2014) STAMP: statistical analysis of taxonomic and functional profiles Bioinformatics 30: 3123-3124 doi:10.1093/bioinformatics/btu494
  18. Beaumont M, Goodrich JK, Jackson MA, Yet I, Davenport ER, Vieira-Silva S, Debelius J, Pallister T, Mangino M, Raes J, Knight R, Clark AG, Ley RE, Spector TD, Bell JT (2016) Heritable components of the human fecal microbiome are associated with visceral fat Genome Biol 17: 189 doi:10.1186/s13059-016-1052-7
  19. Konikoff T, Gophna U (2016) Oscillospira: a Central, Enigmatic Component of the Human Gut Microbiota Trends Microbiol 24: 523-524 doi:10.1016/j.tim.2016.02.015
  20. Peters BA, Shapiro JA, Church TR, Miller G, Trinh-Shevrin C, Yuen E, Friedlander C, Hayes RB, Ahn J (2018) A taxonomic signature of obesity in a large study of American adults Sci Rep 8: 9749 doi:10.1038/s41598-018-28126-1
  21. Reichardt N, Duncan SH, Young P, Belenguer A, McWilliam Leitch C, Scott KP, Flint HJ, Louis P (2014) Phylogenetic distribution of three pathways for propionate production within the human gut microbiota ISME J 8: 1323-1335 doi:10.1038/ismej.2014.14
  22. Schwiertz A, Lehmann U, Jacobasch G, Blaut M (2002) Influence of resistant starch on the SCFA production and cell counts of butyrateproducing Eubacterium spp. in the human intestine J Appl Microbiol 93: 157-162 https://doi.org/10.1046/j.1365-2672.2002.01679.x