CoChat
Sign Up
Cited by 31Spaceflight effects on biologyGenomics and Phylogenetic StudiesSpace Science and Extraterrestrial Life

The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.

Adaptation to space conditions of novel bacterial species isolated from the International Space Station revealed by functional gene annotations and comparative genome analysis

Open access
Szydlowski, Lukasz M., Bulbul, Alper A., Simpson, Anna C., Kaya, Deniz E., Singh, Nitin K., Sezerman, Ugur O., Łabaj, Paweł P., Kosciolek, Tomasz, Venkateswaran, Kasthuri·2024·Microbiome
DOI 10.1186/s40168-024-01916-8PMC PMC11451251

Published version of a preprint

Open this paper in CoChat — free accountOpen PDF

Abstract

BACKGROUND: The extreme environment of the International Space Station (ISS) puts selective pressure on microorganisms unintentionally introduced during its 20+ years of service as a low-orbit science platform and human habitat. Such pressure leads to the development of new features not found in the Earth-bound relatives, which enable them to adapt to unfavorable conditions. RESULTS: In this study, we generated the functional annotation of the genomes of five newly identified species of Gram-positive bacteria, four of which are non-spore-forming and one spore-forming, all isolated from the ISS. Using a deep-learning based tool-deepFRI-we were able to functionally annotate close to 100% of protein-coding genes in all studied species, overcoming other annotation tools. Our comparative genomic analysis highlights common characteristics across all five species and specific genetic traits that appear unique to these ISS microorganisms. Proteome analysis mirrored these genomic patterns, revealing similar traits. The collective annotations suggest adaptations to life in space, including the management of hypoosmotic stress related to microgravity via mechanosensitive channel proteins, increased DNA repair activity to counteract heightened radiation exposure, and the presence of mobile genetic elements enhancing metabolism. In addition, our findings suggest the evolution of certain genetic traits indicative of potential pathogenic capabilities, such as small molecule and peptide synthesis and ATP-dependent transporters. These traits, exclusive to the ISS microorganisms, further substantiate previous reports explaining why microbes exposed to space conditions demonstrate enhanced antibiotic resistance and pathogenicity. CONCLUSION: Our findings indicate that the microorganisms isolated from ISS we studied have adapted to life in space. Evidence such as mechanosensitive channel proteins, increased DNA repair activity, as well as metallopeptidases and novel S-layer oxidoreductases suggest a convergent adaptation among these diverse microorganisms, potentially complementing one another within the context of the microbiome. The common genes that facilitate adaptation to the ISS environment may enable bioproduction of essential biomolecules need during future space missions, or serve as potential drug targets, if these microorganisms pose health risks. Video Abstract.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1186/s40168-024-01916-8

Cites

4 of 4 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Flagged first, then by citations

Research works printed but not linked: 78

  1. Vaishampayan PA, Rabbow E, Horneck G, Venkateswaran KJ. Survival of Bacillus pumilus spores for a prolonged period of time in real space conditions. Astrobiology. 2012;12(5):487–97. https://doi.org/10.1089/ast.2011.0738. · DOI
  2. Cox MM, Battista JR. Deinococcus radiodurans - the consummate survivor. Nat Rev Microbiol. 2005;3(11):882–92. https://doi.org/10.1038/nrmicro1264. · DOI
  3. Onofri S, De Vera JP, Zucconi L, Selbmann L, Scalzi G, Venkateswaran KJ, et al. Survival of Antarctic Cryptoendolithic Fungi in Simulated Martian Conditions on Board the International Space Station. Astrobiology. 2015;15(12):1052–9. https://doi.org/10.1089/ast.2015.1324. · DOI
  4. Rebecchi L, Altiero T, Cesari M, Bertolani R, Rizzo AM, Corsetto Pa, et al. Resistance of the anhydrobiotic eutardigrade Paramacrobiotus richtersi to space flight (LIFE-TARSE mission on FOTON-M3). J Zool Syst Evol Res. 2011;49:98–103. https://doi.org/10.1111/j.1439-0469.2010.00606.x. · DOI
  5. Ricci C, Caprioli M, Boschetti C, Santo N. Macrotrachela quadricornifera featured in a space experiment. Hydrobiologia. 2005;534(1–3):239–44. https://doi.org/10.1007/s10750-004-1509-7. · DOI
  6. Rummel JD. Planetary exploration in the time of astrobiology: protecting against biological contamination. Proc Natl Acad Sci U S A. 2001;98(5):2128–31. https://doi.org/10.1073/pnas.061021398. · DOI
  7. Koehle AP, Brumwell SL, Seto EP, Lynch AM, Urbaniak C. Microbial applications for sustainable space exploration beyond low Earth orbit. NPJ Microgravity. 2023;9(1). https://doi.org/10.1038/s41526-023-00285-0. · DOI
  8. Prasad B, Richter P, Vadakedath N, Haag FWM, Strauch SM, Mancinelli R, et al. How the space environment influences organisms: An astrobiological perspective and review. Int J Astrobiol. 2021;20(2):159–77. https://doi.org/10.1017/S1473550421000057. · DOI
  9. Blaustein RA, Mcfarland AG, Maamar B, Lopez A, Castro-wallace S, Hartmann EM. Pangenomic Approach To Understanding Microbial Adaptations within a Model Built Environment , the International Space Station , Relative to Human Hosts and Soil. mSystems. 2019;4(1). https://doi.org/10.1128/mSystems.00281-18. · DOI
  10. Milojevic T, Weckwerth W. Molecular Mechanisms of Microbial Survivability in Outer Space: A Systems Biology Approach. Front Microbiol. 2020;11(May). https://doi.org/10.3389/fmicb.2020.00923. · DOI
  11. Blachowicz A, Romsdahl J, Chiang AJ, Masonjones S, Kalkum M, Stajich JE, et al. The International Space Station Environment Triggers Molecular Responses in Aspergillus niger. Front Microbiol. 2022;13(June). https://doi.org/10.3389/fmicb.2022.893071. · DOI
  12. Senatore G, Mastroleo F, Leys N, Mauriello G. Effect of microgravity and space radiation on microbes. Future Microbiol. 2018;13(7):831–47. https://doi.org/10.2217/fmb-2017-0251. · DOI
  13. Kumar RK, Singh NK, Balakrishnan S, Parker CW, Raman K, Venkateswaran K. Metabolic modeling of the International Space Station microbiome reveals key microbial interactions. Microbiome. 2022;10(1):1–16. https://doi.org/10.1186/s40168-022-01279-y. · DOI
  14. Simões MF, Antunes A. Microbial pathogenicity in space. Pathogens. 2021;10(4):1–23. https://doi.org/10.3390/pathogens10040450. · DOI
  15. Ott E, Kawaguchi Y, Kölbl D, Rabbow E, Rettberg P, Mora M, et al. Molecular repertoire of Deinococcus radiodurans after 1 year of exposure outside the International Space Station within the Tanpopo mission. Microbiome. 2020;8. https://doi.org/10.1186/s40168-020-00927-5. · DOI
  16. Chen Y, Zhang Q, Wang D, Shu YG, Shi H. Memory Effect on the Survival of Deinococcus radiodurans after Exposure in Near Space. Microbiol Spectr. 2023;11(2). https://doi.org/10.1128/spectrum.03474-22. · DOI
  17. Tierney BT, Singh NK, Simpson AC, Hujer AM, Bonomo RA, Mason CE, et al. Multidrug-resistant Acinetobacter pittii is adapting to and exhibiting potential succession aboard the International Space Station. Microbiome. 2022;10(1):1–14. https://doi.org/10.1186/s40168-022-01358-0. · DOI
  18. Ott E, Fuchs FM, Moeller R, Hemmersbach R, Kawaguchi Y. Molecular response of Deinococcus radiodurans to simulated microgravity explored by proteometabolomic approach. 2019:1–13. https://doi.org/10.1038/s41598-019-54742-6. · DOI
  19. Voorhies AA, Ott CM, Mehta S, Pierson DL, Crucian BE, Feiveson A, et al. Study of the impact of long- duration space missions at the International Space Station on the astronaut microbiome. Sci Rep. 2019;9(9911):1–17. https://doi.org/10.1038/s41598-019-46303-8. · DOI
  20. Singh NK, Lavire C, Nesme J, Vial L, Nesme X, Mason CE, et al. Comparative Genomics of Novel Agrobacterium G3 Strains Isolated From the International Space Station and Description of Agrobacterium tomkonis sp. nov. Front Microbiol. 2021;12(December):1–15. https://doi.org/10.3389/fmicb.2021.765943. · DOI
  21. Bijlani S, Singh NK, Eedara VVR, Podile AR, Mason CE, Wang CCC, et al. Methylobacterium ajmalii sp. nov., Isolated From the International Space Station. Front Microbiol. 2021;12(March):1–14. https://doi.org/10.3389/fmicb.2021.639396. · DOI
  22. Fajardo-Cavazos P, Nicholson WL. Cultivation of Staphylococcus epidermidis in the human spaceflight environment leads to alterations in the frequency and spectrum of spontaneous rifampicin-resistance mutations in the rpoB gene. Front Microbiol. 2016;7(JUN):1–10. https://doi.org/10.3389/fmicb.2016.00999. · DOI
  23. Urbaniak C, Morrison MD, Thissen JB, Karouia F, Smith DJ, Mehta S, et al. Microbial Tracking-2, a metagenomics analysis of bacteria and fungi onboard the International Space Station. Microbiome. 2022;10(1):1–19. https://doi.org/10.1186/s40168-022-01293-0. · DOI
  24. Coil DA, Neches RY, Lang JM, Brown WE, Severance M, Cavalier D, et al. Growth of 48 built environment bacterial isolates on board the International Space Station (ISS). PeerJ. 2016;2016(3):1–11. https://doi.org/10.7717/peerj.1842. · DOI
  25. Enav H, Paz I, Ley RE. Strain tracking in complex microbiomes using synteny analysis reveals per-species modes of evolution. Nat Biotechnol. 2024. https://doi.org/10.1038/s41587-024-02276-2. · DOI
  26. Zhang Y, Skolnick J. TM-align: A protein structure alignment algorithm based on the TM-score. Nucleic Acids Res. 2005;33(7):2302–9. https://doi.org/10.1093/nar/gki524. · DOI · Paper page
  27. Simpson AC, Sengupta P, Zhang F, Hameed A, Parker CW, Singh NK, et al. Phylogenomics, phenotypic, and functional traits of five novel (Earth-derived) bacterial species isolated from the International Space Station and their prevalence in metagenomes. Sci Rep. 2023;13. https://doi.org/10.1038/s41598-023-44172-w. · DOI
  28. Högel P, Götz A, Kuhne F, Ebert M, Stelzer W, Rand KD, et al. Glycine Perturbs Local and Global Conformational Flexibility of a Transmembrane Helix. 2018;57. https://doi.org/10.1021/acs.biochem.7b01197. · DOI
  29. Chavez A, Topolski C, Hicks J, Villafania M, Baez N, Burke M, et al. Phenotypical changes in Escherichia coli K12 after prolonged exposure to simulated microgravity. Front Space Technol. 2024;4. https://doi.org/10.3389/frspt.2023.1282850. · DOI
  30. Manyi-Loh C, Mamphweli S, Meyer E, Okoh A. Antibiotic use in agriculture and its consequential resistance in environmental sources: Potential public health implications. Molecules. 2018;23. https://doi.org/10.3390/molecules23040795. · DOI · Paper page
  31. Fajardo-Cavazos P, Nicholson WL. Mechanotransduction in prokaryotes: A possible mechanism of spaceflight adaptation. Life. 2021;11(1):1–11. https://doi.org/10.3390/life11010033. · DOI
  32. Daly MJ, Gaidamakova EK, Matrosova VY, Vasilenko A, Zhai M, Leapman RD, et al. Protein oxidation implicated as the primary determinant of bacterial radioresistance. PLoS Biol. 2007;5(4):769–79. https://doi.org/10.1371/journal.pbio.0050092. · DOI
  33. Bengtsson-Palme J, Kristiansson E, Larsson DGJ. Environmental factors influencing the development and spread of antibiotic resistance. FEMS Microbiol Rev. 2018;42(1):68-80. · DOI · Paper page
  34. Sharma G, Curtis PD. The Impacts of Microgravity on Bacterial Metabolism. Life. 2022;12:774. · DOI · Paper page
  35. Mora M, Wink L, Kögler I, Mahnert A, Rettberg P, Schwendner P, et al. Space Station conditions are selective but do not alter microbial characteristics relevant to human health. Nat Commun. 2019;10. https://doi.org/10.1038/s41467-019-11682-z. · DOI
  36. Singh NK, Wood JM, Patane J, Maria L, Moura S, Lombardino J. Characterization of Metagenome Assembled Genomes from the International Space Station. BMC Microbiome. 2022:1–20. https://doi.org/10.21203/rs.3.rs-1934191/v1. · DOI
  37. Bradbury P, Wu H, Choi JU, Rowan AE, Zhang H, Poole K, et al. Modeling the Impact of Microgravity at the Cellular Level: Implications for Human Disease. Front Cell Dev Biol. 2020;8(February):1–8. https://doi.org/10.3389/fcell.2020.00096. · DOI
  38. Nothaft H, Szymanski CM. Protein glycosylation in bacteria: Sweeter than ever. Nat Rev Microbiol. 2010;8(11):765–78. https://doi.org/10.1038/nrmicro2383. · DOI
  39. Lee J, Park JS. Tolerance at the genetic level of the brine shrimp Artemia salina to a wide range of salinity. 2020. Preprint at https://doi.org/10.21203/rs.3.rs-91049/v1. · DOI
  40. Su X, Guo Y, Fang T, Jiang X, Wang D, Li D, et al. Effects of Simulated Microgravity on the Physiology of Stenotrophomonas maltophilia and Multiomic Analysis. Front Microbiol. 2021;12. https://doi.org/10.3389/fmicb.2021.701265. · DOI
  41. Su X, Fang T, Fang L, Wang D, Jiang X, Liu C, et al. Effects of short-term exposure to simulated microgravity on the physiology of Bacillus subtilis and multiomic analysis. Can J Microbiol. 2023;69:464–78. https://doi.org/10.1139/cjm-2023-0061. · DOI
  42. Jönsson KI, Harms-Ringdahl M, Torudd J. Radiation tolerance in the eutardigrade Richtersius coronifer. Int J Radiat Biol. 2005;81(9):649–56. https://doi.org/10.1080/09553000500368453. · DOI
  43. Gladyshev E, Meselson M. Extreme resistance of bdelloid rotifers to ionizing radiation. Proc Natl Acad Sci U S A. 2008;105(13):5139–44. https://doi.org/10.1073/pnas.0800966105. · DOI
  44. Butala M, Žgur-Bertok D, Busby SJW. The bacterial LexA transcriptional repressor. Cell Mol Life Sci. 2009;66(1):82–93. https://doi.org/10.1007/s00018-008-8378-6. · DOI
  45. Boschetti C, Pouchkina-stantcheva N, Hoffmann P, Tunnacliffe A. Foreign genes and novel hydrophilic protein genes participate in the desiccation response of the bdelloid rotifer Adineta ricciae. J Exp Biol. 2011;214:59–68. https://doi.org/10.1242/jeb.050328. · DOI
  46. Eyres I, Boschetti C, Crisp A, Smith TP, Fontaneto D, Tunnacliffe A, et al. Horizontal gene transfer in bdelloid rotifers is ancient, ongoing and more frequent in species from desiccating habitats. BMC Biol. 2015;13(1). https://doi.org/10.1186/s12915-015-0202-9. · DOI
  47. Gladyshev E, Meselson M, Arkhipova I. A deep-branching clade of retrovirus-like retrotransposons in bdelloid rotifers. Gene. 2007;390:136–45. · DOI
  48. Pasternak C, Dulermo R, Ton-Hoang B, Debuchy R, Siguier P, Coste G, et al. ISDra2 transposition in Deinococcus radiodurans is downregulated by TnpB. Mol Microbiol. 2013;88:443–55. https://doi.org/10.1111/mmi.12194. · DOI
  49. Seuylemezian A, Vaishampayan P, Cooper K, Venkateswaran K. Draft genome sequences of Acinetobacter and Bacillus strains isolated from spacecraft-associated surfaces. Genome Announc. 2018;6(6):1–2. https://doi.org/10.1128/genomeA.01554-17. · DOI
  50. Borders CL, Broadwater JA, Bekeny PA, Salmon JE, Lee AS, Eldridge AM, et al. A structural role for arginine in proteins: Multiple hydrogen bonds to backbone carbonyl oxygens. Protein Sci. 1994;3(4):541–8. https://doi.org/10.1002/pro.5560030402. · DOI
  51. Donald JE, Kulp DW, Degrado WF. Salt Bridges: Geometrically Specific, Designable Interactions. Biochemistry. 2012;79(3):898–915. https://doi.org/10.1002/prot.22927.Salt. · DOI
  52. Sokalingam S, Raghunathan G, Soundrarajan N, Lee SG. A study on the effect of surface lysine to arginine mutagenesis on protein stability and structure using green fluorescent protein. PLoS ONE. 2012;7(7). https://doi.org/10.1371/journal.pone.0040410. · DOI
  53. Aledo JC. Methionine in proteins: The Cinderella of the proteinogenic amino acids. Protein Sci. 2019;28(10):1785–96. https://doi.org/10.1002/pro.3698. · DOI
  54. Kim W, Tengra FK, Young Z, Shong J, Marchand N, Chan HK, et al. Spaceflight Promotes Biofilm Formation by Pseudomonas aeruginosa. PLoS ONE. 2013;8(4):1–8. https://doi.org/10.1371/journal.pone.0062437. · DOI
  55. Gillor O, Vriezen JAC, Riley MA. The role of SOS boxes in enteric bacteriocin regulation. Microbiology. 2008;154(6):1783–92. https://doi.org/10.1099/mic.0.2007/016139-0. · DOI
  56. Gligorijević V, Renfrew PD, Kosciolek T, Leman JK, Berenberg D, Vatanen T, et al. Structure-based protein function prediction using graph convolutional networks. Nat Commun. 2021;12(1). https://doi.org/10.1038/s41467-021-23303-9. · DOI
  57. Huerta-Cepas J, Szklarczyk D, Heller D, Hernández-Plaza A, Forslund SK, Cook H, et al. EggNOG 5.0: A hierarchical, functionally and phylogenetically annotated orthology resource based on 5090 organisms and 2502 viruses. Nucleic Acids Res. 2019;47(D1):D309–D314. https://doi.org/10.1093/nar/gky1085. · DOI
  58. Blin K, Shaw S, Augustijn HE, Reitz ZL, Biermann F, Alanjary M, et al. antiSMASH 7.0: new and improved predictions for detection, regulation, chemical structures and visualisation. Nucleic Acids Res. 2023;51(May):46–50. https://doi.org/10.1093/nar/gkad344. · DOI
  59. Sielaff AC, Urbaniak C, Babu G, Mohan M, Stepanov VG, Tran Q, et al. Characterization of the total and viable bacterial and fungal communities associated with the International Space Station surfaces. Microbiome. 2019;7:50. · DOI
  60. Bankevich A, Nurk S, Antipov D, Gurevich AA, Dvorkin M, Kulikov AS, et al. SPAdes: A new genome assembly algorithm and its applications to single-cell sequencing. J Comput Biol. 2012;19:455–77. https://doi.org/10.1089/cmb.2012.0021. · DOI
  61. Chen S, Zhou Y, Chen Y, Gu J. Fastp: An ultra-fast all-in-one FASTQ preprocessor. 2018;34:i884–i890. https://doi.org/10.1093/bioinformatics/bty560. · DOI · Paper page
  62. Gurevich A, Saveliev V, Vyahhi N, Tesler G. QUAST: Quality assessment tool for genome assemblies. Bioinformatics. 2013;29:1072–5. https://doi.org/10.1093/bioinformatics/btt086. · DOI · Paper page
  63. Parks DH, Imelfort M, Skennerton CT, Hugenholtz P, Tyson GW. CheckM: Assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Res. 2015;25:1043–55. https://doi.org/10.1101/gr.186072.114. · DOI · Paper page
  64. Yoon SH, min Ha S, Lim J, Kwon S, Chun J. A large-scale evaluation of algorithms to calculate average nucleotide identity. Anton Leeuw Int J Gen Mol Microbiol. 2017;110:1281–1286. https://doi.org/10.1007/s10482-017-0844-4. · DOI
  65. Meier-Kolthoff JP, Carbasse JS, Peinado-Olarte RL, Göker M. TYGS and LPSN: A database tandem for fast and reliable genome-based classification and nomenclature of prokaryotes. Nucleic Acids Res. 2022;50:D801–7. https://doi.org/10.1093/nar/gkab902. · DOI
  66. Tatusova T, Dicuccio M, Badretdin A, Chetvernin V, Nawrocki EP, Zaslavsky L, et al. NCBI prokaryotic genome annotation pipeline. Nucleic Acids Res. 2016;44(14):6614–24. https://doi.org/10.1093/nar/gkw569. · DOI
  67. Steinegger M, Söding J. MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets. Nat Biotechnol. 2017;35(11):1026–8. https://doi.org/10.1038/nbt.3988. · DOI · Paper page
  68. Koehler Leman J, Szczerbiak P, Renfrew PD, Gligorijevic V, Berenberg D, Vatanen T, et al. Sequence-structure-function relationships in the microbial protein universe. Nat Commun. 2023;14(1). https://doi.org/10.1038/s41467-023-37896-w. · DOI
  69. Fu L, Niu B, Zhu Z, Wu S, Li W. CD-HIT: Accelerated for clustering the next-generation sequencing data. Bioinformatics. 2012;28(23):3150–2. https://doi.org/10.1093/bioinformatics/bts565. · DOI · Paper page
  70. Galperin MY, Wolf YI, Makarova KS, Alvarez RV, Landsman D, Koonin EV. COG database update: Focus on microbial diversity, model organisms, and widespread pathogens. Nucleic Acids Res. 2021;49(D1):D274–81. https://doi.org/10.1093/nar/gkaa1018. · DOI
  71. Edgar RC. Muscle5: High-accuracy alignment ensembles enable unbiased assessments of sequence homology and phylogeny. Nat Commun. 2022;13(1):1–9. https://doi.org/10.1038/s41467-022-34630-w. · DOI
  72. Guindon S, Dufayard JF, Lefort V, Anisimova M, Hordijk W, Gascuel O. New algorithms and methods to estimate maximum-likelihood phylogenies: Assessing the performance of PhyML 3.0. Syst Biol. 2010;59(3):307–321. https://doi.org/10.1093/sysbio/syq010. · DOI · Paper page
  73. Zhou Y, Liang Y, Lynch KH, Dennis JJ, Wishart DS. PHAST: a fast phage search tool. Nucleic Acids Res. 2011;39(SUPPL. 2):347–52. https://doi.org/10.1093/nar/gkr485. · DOI
  74. Arndt D, Grant JR, Marcu A, Sajed T, Pon A, Liang Y, et al. PHASTER: a better, faster version of the PHAST phage search tool. Nucleic Acids Res. 2016;44(W1):W16–21. https://doi.org/10.1093/nar/gkw387. · DOI
  75. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. J Mol Biol. 1990;215(3):403–10. https://doi.org/10.1016/S0022-2836(05)80360-2. · DOI · Paper page
  76. Reimand J, Kull M, Peterson H, Hansen J, Vilo J. G:Profiler-a web-based toolset for functional profiling of gene lists from large-scale experiments. Nucleic Acids Res. 2007;35(SUPPL.2):193–200. https://doi.org/10.1093/nar/gkm226. · DOI
  77. Consortium U. UniProt: A worldwide hub of protein knowledge. Nucleic Acids Res. 2019;47(D1):D506–15. https://doi.org/10.1093/nar/gky1049. · DOI · Paper page
  78. Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, et al. Gene Ontology: tool for the unification of biology. Nature Genet. 2000;25(1):25–9. https://doi.org/10.1038/75556. · DOI · Paper page

Metadata

Authors
Szydlowski, L. M., Bulbul, A. A., Simpson, A. C., Kaya, D. E., Singh, N. K., Sezerman, U. O., Łabaj, P. P., Kosciolek, T., & Venkateswaran, K.
Affiliations
  • Jagiellonian University (PL)
  • California Institute of Technology (US)
Corresponding author
Venkateswaran, Kasthuri
ORCID
Venue
Microbiome
Publisher
Springer Science and Business Media LLC
Published
2024-10-04
Volume
12
Issue
1
Pages
190-190
ISSN
2049-2618 (ISSN-L)
DOI
10.1186/s40168-024-01916-8
PMC
PMC11451251
OpenAlex
W4403092733
Cited by
31
References
4
Citations by year
2026: 13 · 2025: 16 · 2024: 2
FWCI
8.82
Type
journal article
Language
en
Open access
Licence
Locations
  • Microbiome (publishedVersion, cc-by-nc-nd)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • Jagiellonian University Repository (Jagiellonian University) (submittedVersion, cc-by-nc-nd)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Funders
  • Narodowe Centrum Nauki (2020/38/E/NZ2/00598, 2019/35/D/NZ2/04353)
  • Jet Propulsion Laboratory
Topics
  • Health Sciences › Medicine › Physiology (medical) › Spaceflight effects on biology
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
  • Physical Sciences › Physics and Astronomy › Astronomy and Astrophysics › Space Science and Extraterrestrial Life
Keywords
International Space Station, Gram-positive bacteria, functional gene annotation, comparative genomics, microgravity, hypoosmotic stress, DNA repair, radiation exposure, mobile genetic elements, pathogenicity, antibiotic resistance, metalloproteinases, adaptive convergence
MeSH terms
Adaptation, Physiological, Bacteria, Humans, Phylogeny, Space Flight, Weightlessness, Genome, Bacterial, Spacecraft, Proteome, Genomics, Molecular Sequence Annotation

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review