Microbial Ecology

, Volume 78, Issue 3, pp 631–650 | Cite as

Microbiomes of China’s Space Station During Assembly, Integration, and Test Operations

  • Ying ZhangEmail author
  • Lan-tao Zhang
  • Zhi-dong Li
  • Cong-xin Xin
  • Xiao-qiong Li
  • Xiang WangEmail author
  • Yu-lin DengEmail author
Environmental Microbiology


Sufficient evidence indicates that orbiting space stations contain diverse microbial populations, which may threaten astronaut health and equipment reliability. Understanding the composition of microbial communities in space stations will facilitate further development of targeted biological safety prevention and maintenance practices. Therefore, this study systematically investigated the microbial community of China’s Space Station (CSS). Air and surface samples from 46 sites on the CSS and Assembly Integration and Test (AIT) center were collected, from which 40 bacteria strains were isolated and identified. Most isolates were cold- and desiccation-resistant and adapted to oligotrophic conditions. Bacillus was the dominant bacterial genus detected by both cultivation-based and Illumina MiSeq amplicon sequencing methods. Microbial contamination on the CSS was correlated with encapsulation staff activities. Analysis by spread plate and qPCR revealed that the CSS surface contained 2.24 × 103–5.47 × 103 CFU/100 cm2 culturable bacteria and 9.32 × 105–5.64 × 106 16S rRNA gene copies/100cm2; BacLight™ analysis revealed that the viable/total bacterial cell ratio was 1.98–13.28%. This is the first study to provide important systematic insights into the microbiome of the CSS during assembly that describes the pre-launch microbial diversity of the space station. Our findings revealed the following. (1) Bacillus strains and staff activities should be considered major concerns for future biological safety. (2) Autotrophic and multi-resistant microbial communities were widespread in the AIT environment. Although harsh cleaning methods reduced the number of microorganisms, stress-resistant strains were not completely removed. (3) Sampling, storage and analytical methods for the space station were thoroughly optimized, and are expected to be applicable to low-biomass environments in general. Microbiology-related future works will follow up to comprehensively understand the changing characteristics of microbial communities in CSS.


China’s Space Station Microbiome Illumina MiSeq Cleanroom microbiota Confined habitat 



LIVE/DEAD® Bacterial Viability Kit


Propidium monoazide quantitative PCR


Operational taxonomic unit


International Space Station


Assembly, Integration, and Test


Phosphate-buffered saline


Principal component analysis


Nutrient agar medium


Sabouraud’s agar medium


Luria-Bertani medium

PCA Medium/ Plate

Plate count agar medium


Baird-Parker plates medium


Potato Dextrose agar


Hutchinson fluid medium


Cellulose Cong red medium


Trypticase soy agar medium


Reasoner’s 2A agar medium


Autotrophic all-rounder liquid medium


Hino and Wilson N2-free liquid medium modified


Homoacetogen liquid medium


Autotrophic sulfate reducer medium


The ratio of viable/total bacteria



We are very grateful to the China Aeronautics and Space Administration for the logistic support and overall management of samplings. This work was financed by the National Natural Science Foundation of China (Project No.31600404).

Availability of Data and Materials

Sequencing reads were deposited as entire raw data in the National Center for Biotechnology Information Sequence Read Archive (NCBI SRA; accession number SRP105019).

Compliance with Ethical Standards

Competing Interests

The authors declare that they have no competing interests.

Supplementary material

248_2019_1344_MOESM1_ESM.docx (87 kb)
ESM 1 (DOCX 86 kb)


  1. 1.
    Wilhite AW, Chai P (2014) Plan B for US Human Space Exploration Program. In: AIAA SPACE 2014 Conference and Exposition. San Diego, CA, p 4237.
  2. 2.
    Mishra S, Ajello L, Ahearn D, Burge H, Kurup V, Pierson D et al (1992) Environmental mycology and its importance to public health. J Med Vet Mycol 30:287–305CrossRefGoogle Scholar
  3. 3.
    Novikova N (2004) Review of the knowledge of microbial contamination of the Russian manned spacecraft. Microb Ecol 47:127–132. CrossRefGoogle Scholar
  4. 4.
    Novikova N, De Boever P, Poddubko S, Deshevaya E, Polikarpov N, Rakova N et al (2006) Survey of environmental biocontamination on board the International Space Station. Res Microbiol 157:5–12. CrossRefGoogle Scholar
  5. 5.
    Pierson DL, Botkin DJ, Bruce RJ, Castro VA, Smith MJ, Oubre CM et al (2013) Microbial monitoring of the International Space Station. 8th International Workshop on Space Microbiology, 20-21 May 2013; Osaka; Japan.(Document ID: 20130013534)
  6. 6.
    Maule J, Wainwright N, Steele A, Gunter D, Flores G, Effinger M, et al (2009) Rapid monitoring of bacteria and fungi aboard the International Space Station (ISS). In 47th AIAA Aerospace Sciences Meeting including The New Horizons Forum and Aerospace Exposition. 959Google Scholar
  7. 7.
    Checinska A, Probst A, Vaishampayan P, White J, Kumar D, Stepanov V et al (2015) Microbiomes of the dust particles collected from the International Space Station and spacecraft assembly facilities. Microbiome 3:50. CrossRefGoogle Scholar
  8. 8.
    Kminek G, Rummel JD (2015) COSPAR planetary protection policy. Space Res Today.
  9. 9.
    Koskinen K, Rettberg P, Pukall R, Auerbach A, Wink L, Barczyk S, Perras A, Mahnert A, Margheritis D, Kminek G, Moissl-Eichinger C (2017) Microbial biodiversity assessment of the European Space Agency’s ExoMars 2016 mission. Microbiome 5:143. CrossRefGoogle Scholar
  10. 10.
    La Duc MT, Venkateswaran K, Conley CA (2014) A genetic inventory of spacecraft and associated surfaces. Astrobiology 14:15–23. CrossRefGoogle Scholar
  11. 11.
    La Duc MT, Nicholson W, Kern R, Venkateswaran K (2003) Microbial characterization of the Mars odyssey spacecraft and its encapsulation facility. Environ Microbiol 5:977–985. CrossRefGoogle Scholar
  12. 12.
    Probst A, Facius R, Wirth R, Wolf M, Moissl-Eichinger C (2011) Recovery of Bacillus spore contaminants from rough surfaces: a challenge to space mission cleanliness control. Appl Environ Microbiol 77:1628–1637. CrossRefGoogle Scholar
  13. 13.
    Venkatswaran K, La Duc MT, Vaishampayan P (2012) Genetic inventory task: final report. JPL Publ 1:12–12Google Scholar
  14. 14.
    Bashir M, Ahmed M, Weinmaier T, Ciobanu D, Ivanova N, Pieber TR, Vaishampayan PA (2016) Functional metagenomics of spacecraft assembly cleanrooms: presence of virulence factors associated with human pathogens. Front Microbiol 7.
  15. 15.
    Rettberg P, Fritze D, Verbarg S, Nellen J, Horneck G, Stackebrandt E et al (2006) Determination of the microbial diversity of spacecraft assembly, testing and launch facilities: first results of the ESA project MiDiv. Adv Space Res 38:1260–1265. CrossRefGoogle Scholar
  16. 16.
    Stieglmeier M, Wirth R, Kminek G, Moissl-Eichinger C (2009) Cultivation of anaerobic and facultatively anaerobic bacteria from spacecraft-associated clean rooms. Appl Environ Microbiol 75:3484–3491. CrossRefGoogle Scholar
  17. 17.
    Moissl-Eichinger C, Rettberg P, Pukall R (2012) The first collection of spacecraft-associated microorganisms: a public source for extremotolerant microorganisms from spacecraft assembly clean rooms. Astrobiology 12:1024–1034. CrossRefGoogle Scholar
  18. 18.
    Stieglmeier M, Rettberg P, Barczyk S, Bohmeier M, Pukall R, Wirth R, Moissl-Eichinger C (2012) Abundance and diversity of microbial inhabitants in European spacecraft-associated clean rooms. Astrobiology 12:572–585. CrossRefGoogle Scholar
  19. 19.
    Moissl-Eichinger C, Pukall R, Probst AJ, Stieglmeier M, Schwendner P, Mora M, Barczyk S, Bohmeier M, Rettberg P (2013) Lessons learned from the microbial analysis of the Herschel spacecraft during assembly, integration, and test operations. Astrobiology 13:1125–1139. CrossRefGoogle Scholar
  20. 20.
    Schwendner P, Moissl-Eichinger C, Barczyk S, Bohmeier M, Pukall R, Rettberg P (2013) Insights into the microbial diversity and bioburden in a south American spacecraft assembly clean room. Astrobiology 13:1140–1154. CrossRefGoogle Scholar
  21. 21.
    ECSS-Q-ST-70-55 Working Group (2008) Microbial examination of flight hardware and clean rooms. ECSS-Q-ST-70-55C, European Cooperation for Space Standardization, ESA Requirements and Standards DivisionGoogle Scholar
  22. 22.
    Kwan K, Cooper M, La Duc M, Vaishampayan P, Stam C, Benardini J et al (2011) Evaluation of procedures for the collection, processing, and analysis of biomolecules from low-biomass surfaces. Appl Environ Microbiol 77:2943–2953. CrossRefGoogle Scholar
  23. 23.
    Gilbert Y, Veillette M, Duchaine C (2010) Airborne bacteria and antibiotic resistance genes in hospital rooms. Aerobiologia 26:185–194. CrossRefGoogle Scholar
  24. 24.
    Nocker A, Sossa KE, Camper AK (2007) Molecular monitoring of disinfection efficacy using propidium monoazide in combination with quantitative PCR. J Microbiol Methods 70:252–260CrossRefGoogle Scholar
  25. 25.
    Vaishampayan P, Probst AJ, La Duc MT, Bargoma E, Benardini JN, Andersen GL et al (2013) New perspectives on viable microbial communities in low-biomass cleanroom environments. ISME J 7:312–324. CrossRefGoogle Scholar
  26. 26.
    NASA (2010) Handbook for the Microbiological Examination of Space Hardware, NASA-HDBK-6022.
  27. 27.
    Blachowicz A, Mayer T, Bashir M, Pieber TR, De León P, Venkateswaran K (2017) Human presence impacts fungal diversity of inflated lunar/Mars analog habitat. Microbiome 5:62. CrossRefGoogle Scholar
  28. 28.
    Wahman DG, Wulfeck-Kleier KA, Pressman JG (2009) Monochloramine disinfection kinetics of Nitrosomonas europaea by propidium monoazide quantitative PCR and live/dead BacLight methods. Appl Environ Microbiol 75:5555–5562. CrossRefGoogle Scholar
  29. 29.
    Rahman ME, Hossain DM, Suzuki K, Shiiya A, Suzuki K, Dey TK et al (2016) Suppressive effects of Bacillus spp. on mycelia, apothecia and sclerotia formation of Sclerotinia sclerotiorum and potential as biological control of white mold on mustard. Australas Plant Pathol 45:103–117. CrossRefGoogle Scholar
  30. 30.
    Kostov O, Rankov V, Atanacova G, Lynch J (1991) Decomposition of sawdust and bark treated with cellulose-decomposing microorganisms. Biol Fertil Soils 11:105–110CrossRefGoogle Scholar
  31. 31.
    Teather RM, Wood PJ (1982) Use of Congo red-polysaccharide interactions in enumeration and characterization of cellulolytic bacteria from the bovine rumen. Appl Environ Microbiol 43:777–780Google Scholar
  32. 32.
    Hendricks CW, Doyle JD, Hugley B (1995) A new solid medium for enumerating cellulose-utilizing bacteria in soil. Appl Environ Microbiol 61:2016–2019Google Scholar
  33. 33.
    Pospiech A, Neumann B (1995) A versatile quick-prep of genomic DNA from gram-positive bacteria. Trends Genet 11:217–218CrossRefGoogle Scholar
  34. 34.
    Weisburg WG, Barns SM, Pelletier DA, Lane DJ (1991) 16S ribosomal DNA amplification for phylogenetic study. J Bacteriol 173:697–703CrossRefGoogle Scholar
  35. 35.
    Kumar S, Tamura K, Nei M (2004) MEGA3: integrated software for molecular evolutionary genetics analysis and sequence alignment. Brief Bioinform 5:150–163. CrossRefGoogle Scholar
  36. 36.
    Thompson JD, Higgins DG, Gibson TJ (1994) CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res 22:4673–4680CrossRefGoogle Scholar
  37. 37.
    Qu Y, Zhang X, Shen W, Ma Q, You S, Pei X, Li S, Ma F, Zhou J (2016) Illumina MiSeq sequencing reveals long-term impacts of single-walled carbon nanotubes on microbial communities of wastewater treatment systems. Bioresour Technol 211:209–215CrossRefGoogle Scholar
  38. 38.
    Bokulich NA, Subramanian S, Faith JJ, Gevers D, Gordon JI, Knight R, Mills DA, Caporaso JG (2013) Quality-filtering vastly improves diversity estimates from Illumina amplicon sequencing. Nat Methods 10:57–59. CrossRefGoogle Scholar
  39. 39.
    Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello EK, Fierer N, Peña AG, Goodrich JK, Gordon JI, Huttley GA, Kelley ST, Knights D, Koenig JE, Ley RE, Lozupone CA, McDonald D, Muegge BD, Pirrung M, Reeder J, Sevinsky JR, Turnbaugh PJ, Walters WA, Widmann J, Yatsunenko T, Zaneveld J, Knight R (2010) QIIME allows analysis of high-throughput community sequencing data. Nat Methods 7:335–336. CrossRefGoogle Scholar
  40. 40.
    Edgar RC (2013) UPARSE: highly accurate OTU sequences from microbial amplicon reads. Nat Methods 10:996–998. CrossRefGoogle Scholar
  41. 41.
    Haas BJ, Gevers D, Earl AM, Feldgarden M, Ward DV, Giannoukos G, Ciulla D, Tabbaa D, Highlander SK, Sodergren E, Methe B, DeSantis TZ, The Human Microbiome Consortium, Petrosino JF, Knight R, Birren BW (2011) Chimeric 16S rRNA sequence formation and detection in sanger and 454-pyrosequenced PCR amplicons. Genome Res 21:494–504. CrossRefGoogle Scholar
  42. 42.
    Edgar RC, Haas BJ, Clemente JC, Quince C, Knight R (2011) UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 27:2194–2200. CrossRefGoogle Scholar
  43. 43.
    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. CrossRefGoogle Scholar
  44. 44.
    Martiny JBH, Bohannan BJ, Brown JH, Colwell RK, Fuhrman JA, Green JL et al (2006) Microbial biogeography: putting microorganisms on the map. Nat Rev Microbiol 4:102–112. CrossRefGoogle Scholar
  45. 45.
    Heberle H, Meirelles GV, da Silva FR, Telles GP, Minghim R (2015) InteractiVenn: a web-based tool for the analysis of sets through Venn diagrams. BMC Bioinformatics 16(169):169. CrossRefGoogle Scholar
  46. 46.
    Taguchi Y-H, Oono Y (2005) Relational patterns of gene expression via non-metric multidimensional scaling analysis. Bioinformatics 21:730–740. CrossRefGoogle Scholar
  47. 47.
    Clopper C, Pearson S (1934) The use of confidence or fiducial limits illustrated in the case of the binomial. Biometrika 26:404–413CrossRefGoogle Scholar
  48. 48.
    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. CrossRefGoogle Scholar
  49. 49.
    Hugenholtz P, Goebel BM, Pace NR (1998) Impact of culture-independent studies on the emerging phylogenetic view of bacterial diversity. J Bacteriol 180:4765–4774Google Scholar
  50. 50.
    Legendre P, Oksanen J, ter Braak CJ (2011) Testing the significance of canonical axes in redundancy analysis. Methods Ecol Evol 2:269–277CrossRefGoogle Scholar
  51. 51.
    Liang Y, Wu L, Clark IM, Xue K, Yang Y, Van Nostrand JD et al (2015) Over 150 years of long-term fertilization alters spatial scaling of microbial biodiversity. Mbio 6:e00240–e00215. CrossRefGoogle Scholar
  52. 52.
    Venkateswaran K, Satomi M, Chung S, Kern R, Koukol R, Basic C, White D (2001) Molecular microbial diversity of a spacecraft assembly facility. Syst Appl Microbiol 24:311–320CrossRefGoogle Scholar
  53. 53.
    Pierson DL, Ott CM, Bruce R, Castro VA, Mehta SK (2011) Microbiological lessons learned from the space shuttle. Space 5:6. Google Scholar
  54. 54.
    Mora M, Perras A, Alekhova TA, Wink L, Krause R, Aleksandrova A, Novozhilova T, Moissl-Eichinger C (2016) Resilient microorganisms in dust samples of the international Space Station—survival of the adaptation specialists. Microbiome 4:65. CrossRefGoogle Scholar
  55. 55.
    Pierson DL (2007) Microbial contamination of spacecraft. Gravit Space Biol Bull 14:2Google Scholar
  56. 56.
    Maule J, Wainwright N, Steele A, Monaco L, Morris H, Gunter D, Damon M, Wells M (2009) Rapid culture-independent microbial analysis aboard the International Space Station (ISS). Astrobiology 9:759–775. CrossRefGoogle Scholar
  57. 57.
    MBd R, Rampelotto PH, Schuch NJ, Schuch AP, Munakata N (2009) Spore dosimetry: Bacillus subtilis TKJ6312 as biosensor of biologically effective solar radiation. Quim Nova 32:282–285. CrossRefGoogle Scholar
  58. 58.
    Rampelotto PH (2010) Resistance of microorganisms to extreme environmental conditions and its contribution to astrobiology. Sustainability 2:1602–1623. CrossRefGoogle Scholar
  59. 59.
    Rampelotto PH, da Rosa MB, Schuch NJ, Munakata N (2009) Exobiological application of spore dosimeter in studies involving solar UV radiation. In: Origins of life and evolution of biospheres. Springer, Dordrecht, p 373–374Google Scholar
  60. 60.
    Horneck G, Klaus DM, Mancinelli RL (2010) Space microbiology. Microbiol Mol Biol Rev 74:121–156. CrossRefGoogle Scholar
  61. 61.
    Pande S, Kost C (2017) Bacterial unculturability and the formation of intercellular metabolic networks. Trends Microbiol timi1438:13. Google Scholar
  62. 62.
    Zhang Y, Deng CP, Shen B, Yang JS, Wang ET, Yuan HL (2016) Syntrophic interactions within a butane-oxidizing bacterial consortium isolated from Puguang gas field in China. Microb Ecol 72:538–548. CrossRefGoogle Scholar
  63. 63.
    Griffin DW, Kellogg CA, Garrison VH, Lisle JT, Borden TC, Shinn EA (2003) Atmospheric microbiology in the northern Caribbean during African dust events. Aerobiologia 19:143e157. CrossRefGoogle Scholar
  64. 64.
    Hara K, Zhang D (2012) Bacterial abundance and viability in long-range transported dust. Atmos Environ 47:20–25. CrossRefGoogle Scholar
  65. 65.
    Bruckner J, Yalamanchili R, Fields R, Sumner R, Venkateswaran K (2005) Systematic sampling and processing of nucleic acids for low biomass samples. In 105th General Meeting of the American Society of Microbiology, AtlantaGoogle Scholar
  66. 66.
    Hodges L, Rose L, Peterson A, Noble-Wang J, Arduino M (2006) Evaluation of a macrofoam swab protocol for the recovery of Bacillus anthracis spores from a steel surface. Appl Environ Microbiol 72:4429–4430. CrossRefGoogle Scholar
  67. 67.
    Moore G, Griffith C (2002) A comparison of traditional and recently developed methods for monitoring surface hygiene within the food industry: an industry trial. Int J Environ Health Res 12:317–329CrossRefGoogle Scholar
  68. 68.
    Rose L, Jensen B, Peterson A, Banerjee S, Arduino M (2004) Swab materials and Bacillus anthracis spore recovery from nonporous surfaces. Emerg Infect Dis 10:1023–1029. CrossRefGoogle Scholar
  69. 69.
    Sanderson WT, Hein MJ, Taylor L, Curwin BD, Kinnes GM, Seitz TA, Popovic T, Holmes HT, Kellum ME, McAllister SK, Whaley DN, Tupin EA, Walker T, Freed JA, Small DS, Klusaritz B, Bridges JH (2002) Surface sampling methods for Bacillus anthracis spore contamination. Emerg Infect Dis 8:1145–1151. CrossRefGoogle Scholar
  70. 70.
    Nocker A, Camper AK (2009) Novel approaches toward preferential detection of viable cells using nucleic acid amplification techniques. FEMS Microbiol Lett 291:137–142. CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.School of Life ScienceBeijing Institute of TechnologyBeijingChina
  2. 2.Institute of Manned Space System EngineeringChina Academy of Space TechnologyBeijingChina
  3. 3.Beijing Institute of Spacecraft System EngineeringBeijingChina

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