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Time series analysis of microbiome and metabolome at multiple body sites in steady long-term isolation confinement
  1. Qiang Feng1,2,
  2. Xiang Lan1,
  3. Xiaoli Ji1,
  4. Meihui Li1,
  5. Shili Liu1,3,
  6. Jianghui Xiong4,5,
  7. Yanbo Yu6,
  8. Zhipeng Liu5,
  9. Zi Xu4,5,
  10. Li He4,
  11. Ying Chen4,5,
  12. Haisheng Dong6,7,
  13. Pu Chen6,7,
  14. Bin Chen4,7,
  15. Kunlun He8,
  16. Yinghui Li4,5,6
  1. 1 Department of Human Microbiome, School and Hospital of Stomatology, Cheeloo College of Medicine, Shandong University & Shandong Key Laboratory of Oral Tissue Regeneration & Shandong Engineering Laboratory for Dental Materials and Oral Tissue Regeneration, Jinan, Shandong, China
  2. 2 State Key Laboratory of Microbial Technology, Shandong University, Qingdao, China
  3. 3 School of Basic Medical Science, Cheeloo College of Medicine, Shandong University, Jinan, China
  4. 4 State Key Laboratory of Space Medicine Fundamentals and Application, China Astronaut Research and Training Center, Beijing, China
  5. 5 Lab of Epigenetics and Advanced Health Technology, Space Institute of Southern China, Shenzhen, China
  6. 6 Lab of Functional Food Technology, Space Institute of Southern China, Shenzhen, China
  7. 7 Key Laboratory of Space Nutrition and Food Engineering, China Astronaut Research and Training Center, Beijing, China
  8. 8 Beijing Key Laboratory for Precision Medicine of Chronic Heart Failure, Chinese PLA General Hospital, Beijing, China
  1. Correspondence to Professor Qiang Feng, Department of Human Microbiome, JinanSchool and Hospital of Stomatology, Cheeloo College of Medicine, Shandong University & Shandong Key Laboratory of Oral Tissue Regeneration & Shandong Engineering Laboratory for Dental Materials and Oral Tissue Regeneration, Jinan, Shandong, China; fengqiang{at}sdu.edu.cn; Professor Yinghui Li, State Key Laboratory of Space Medicine Fundamentals and Application, China Astronaut Research and Training Center, Beijing, China; yinghuidd{at}vip.sina.com

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We read the article by Flemer et al,1 which suggests that the combined analysis of the oral and faecal microbiota may have significant value in the detection of colorectal cancer, with great interest. The oral and intestinal microbiomes are distant anatomic populations that highly abundant, with distinct microbiota and metabolomes, but microbes from the two sites interact with each other.2 External factors, such as residence changes, bacterial infections, irregular diet and circadian rhythm alterations, can lead to a shift in the microbial ecosystem.3 Therefore, understanding the dynamic changes of the microbiome and metabolic profile of faeces and saliva in steady long-term isolation confinement can establish the change rule of human microbiome and the possible disease risk in a long time space travel.

In this study, we examined the human microbiome and metabolome with a time series from multiple body sites to evaluate the stability of the microbial ecosystem and its connection with the human metabolome. The salivary and faecal microbiome and the plasmatic, urinary and faecal metabolome of four simulated astronauts were investigated at a total of 18 time points and were compared with before, during and after 180 days of a test of living in the well-controlled ecological life support system (CELSS) (figure 1 and online supplementary file).

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Figure 1

Overview of the study design and sample collection (saliva (S), faeces (F) and plasma (P)) in the controlled ecological life support system. The experiment was divided into five stages: before going into the space capsule (Before), pre-Mars landing (M1), Mars landing (M2), leaving Mars and returning to Earth (M3) and landing on Earth and exiting the space capsule (After). ‘-’ means that a sample was not obtained from this person at this time point. See online supplementary file for more details.

The microbial diversity measured by PD whole tree and Principal coordinate analysis 1(PCoA1) curves during ‘space travel’ and ‘Mars solar day’ decreased in faeces but increased in saliva, although we did not observe a significant difference (p≥0.05) (figure 2A, B). At the phylum level, results showed that the relative abundance of Bacteroidetes concomitantly varied with Firmicutes both in faeces and saliva from the ‘Mars solar day’ period to the exit of the space capsule (figure 2C, D and online supplementary tables S1 and S2). The ratio of Firmicutes to Bacteroidetes, which was reported in an obesity study,4 varied in the network with time series (figure 2E-I). At the genus and species level, results showed the different distribution at the different time periods (p<0.05), which were clustered into specific groups in faeces and saliva according to their patterns of change (online supplementary tables 3–6, online supplementary figures S1 and S2) respectively. In faeces, anti-inflammatory microbes showed increasing trends from entering the space capsule to exiting the space capsule, while proinflammatory microbes showed decreasing trends (figure 2H and online supplementary figures S1, S2 and tables S7, S8). Correlation analysis between faecal microbes and the metabolome of plasma showed the regulation of the ratio of phosphatidylcholine:phosphatidylethanolamine played a key role in inflammation (figure 2J, K, online supplementary figure S3 and online supplementary table S9).5 In saliva, entering the space capsule tended to promote an increase in periodontitis-related microbes (figure 2I, online supplementary figures S1 and S2), and metabolites enriched in this stage are reported to be associated with biofilms, alveolar bone loss and systemic diseases (figure 2L, online supplementary figure S4 and online supplementary table S10).6 Additionally, Streptococcus salivarius subsp. salivarius and Streptococcus dentisani, which are coexisting, differentially abundant species in faeces and saliva (online supplementary figure S2).

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Figure 2

Longitudinal dynamics of the microbiome and metabolome. Alpha diversity detected by the PD whole tree index (A), Principal coordinate analysis 1(PCoA1) (B). (C, D) Relative abundances of the faecal and salivary microbiota at the phylum level. (E, F) Network of co-occurring species in faeces and saliva. Nodes (species) were partly coloured by the phylum in C and D. The area of each node is proportional to the number of connections with other nodes. The red edges of the node represent differentially abundant species compared with the same sample in the previous phase. (G) Network of co-occurring species in faeces and saliva, coloured the same as in E and F. Ratio of the sum of the differential species divided into different phyla or diseases that were present in faeces (H) (online supplementary figure S2, online supplementary table S2) and saliva (I) (online supplementary table S2, online supplementary figure S2). (J, L) Network analysis of the interactions between the differential species and plasmatic (P), urinary (U) and faecal (F) metabolites (correlation>0.6; p<0.05) (online supplementary figures S2–S4, online supplementary table S9, S10). (K) Diagram of the ratio of phosphatidylethanolamine (PE):phosphatidylcholine (PC) (online supplementary figure S3). The red and blue edges of the connection in the network represent negative and positive significant correlations, respectively (correlation>0.6; p<0.05).

Overall, this study showed the changes in the human microbiome and metabolome that occur during the process of entering, living in a ground space capsule for 180 days and leaving the capsule, and the linkage between the microbiome and metabolome at multiple body sites. Some of the changes may be associated with disease risk, while the human microbiota of the two sites was generally stable throughout the whole process, which was mostly consistent with the findings of Turroni et al.7 The present study enhanced our understanding of the relative stability of the human microbial ecosystem living in a closed environment for a long period and be considered during future mission of modified CELSS or the real space flights.

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Footnotes

  • QF, XL, XJ, ML and SL are joint first authors.

  • QF, XL, XJ, ML and SL contributed equally.

  • Contributors FQ, LX, JXL, LMH, LSL contributed equally to this paper.FQ and LYH designed and conducted the experiments. XJH, YYB, LZP, XZ, HL, CY, DHS, CP, CB conducted the experiment. LX, LMH analysed the data. JXL, LSL, HKL, FQ and LYH edited the manuscript.

  • Funding This study was supported by the National Natural Science Foundation of China (No. 81630072), The Fundamental Research Funds of Shandong University (2015JC010), Programme of Qilu young scholars of Shandong University (sdxz201699000032), the constructional engineering Special Found of Taishan Scholar programme (tsqn20190918). We would like to express special thankfulness to the Development and Reform Commission of Shenzhen Municipality for sponsoring the 4-person-180-day CELSS integrated experiment, and funds from Shenzhen Science & Technology Programme (JCYJ20151029154245758, CKFW2016082915204709). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

  • Competing interests None declared.

  • Provenance and peer review Not commissioned; externally peer reviewed.