Advertisement

Metagenomic analyses uncover the differential effect of azide treatment on bacterial community structure by enriching a specific Cyanobacteria present in a saline-alkaline environmental sample

  • José Félix Aguirre-Garrido
  • Francisco Martínez-Abarca
  • Daniel Montiel-Lugo
  • Luis Mario Hernández-Soto
  • Hugo Ramírez-SaadEmail author
Original Article

Abstract

Treatment of environmental samples under field conditions may require the application of chemical preservatives, although their use sometimes produces changes in the microbial communities. Sodium azide, a commonly used preservative, is known to differentially affect the growth of bacteria. Application of azide and darkness incubation to Isabel soda lake water samples induced changes in the structure of the bacterial community, as assessed by partial 16S rRNA gene pyrosequencing. Untreated water samples (WU) were dominated by gammaproteobacterial sequences accounting for 86%, while in the azide-treated (WA) samples, this group was reduced to 33% abundance, and cyanobacteria-related sequences became dominant with 53%. Shotgun sequencing and genome recruitment analyses pointed to Halomonas campanensis strain LS21 (genome size 4.07 Mbp) and Synechococcus sp. RS9917 (2.58 Mbp) as the higher recruiting genomes from the sequence reads of WA and WU environmental libraries, respectively, covering nearly the complete genomes. Combined treatment of water samples with sodium azide and darkness has proven effective on the selective enrichment of a cyanobacterial group. This approach may allow the complete (or almost-complete) genome sequencing of Cyanobacteria from metagenomic DNA of different origins, and thus increasing the number of the underrepresented cyanobacterial genomes in the databases.

Keywords

16S rRNA analysis Amplitag-pyrosequencing Genome recruitment Halo-alkalophile bacteria Halomonas Synechococcus 

Notes

Acknowledgments

DML and HRS acknowledge to the Mexican Consejo Nacional de Ciencia y Tecnología (CONACyT) for fellowships numbers 291062 Becas Mixtas de Movilidad en el Extranjero Programme and 710228 Estancias Sabática al Extranjero Programme, respectively. We specially thank Dr. Antonio J. Fernández-González and Mario R. Mestre for their valuable help with drawings of the recruitment plots.

Funding information

This work was supported by the Spanish Ministerio de Ciencia, Innovación y Universidades (research grant BIO2017-82244-P).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

10123_2020_119_MOESM1_ESM.pdf (150 kb)
ESM 1 (PDF 150 kb)
10123_2020_119_MOESM2_ESM.pdf (84 kb)
ESM 2 (PDF 84 kb)

References

  1. Aguirre-Garrido JF, Ramírez-Saad HC, Toro N, Martínez-Abarca F (2016) Bacterial diversity in the soda saline crater lake from Isabel Island, Mexico. Microb Ecol 71(1):68–77.  https://doi.org/10.1007/s00248-015-0676-6 CrossRefPubMedGoogle Scholar
  2. Alcocer J, Lugo A, Sánchez MR, Escobar E (1998) Isabela crater-lake: a Mexican insular saline lake. Hydrobiologia 381:1–7CrossRefGoogle Scholar
  3. Alvarenga DO, Fiore MF, Varani AM (2017) A metagenomic approach to Cyanobacterial genomics. Front Microbiol 8:809.  https://doi.org/10.3389/fmicb.2017.00809 CrossRefPubMedPubMedCentralGoogle Scholar
  4. Aronesty E (2011) Ea-utils: command-line tools for processing biological sequencing data; http://code.google.com/p/ea-utils
  5. Audicana A, Perales I, Borrego JJ (1995) Modification of kanamycin-esculin-azide agar to improve selectivity in the enumeration of fecal streptococci from water samples. Appl Environ Microbiol 61:4168–4183CrossRefGoogle Scholar
  6. Bowyer JW, Skerman WBD (1968) Production of axenic cultures of soil-borne and endophytic blue-green algae. J Gen Microbiol 54:299–306CrossRefGoogle Scholar
  7. Bundy DA, , Golden MH. (1985). Sodium azide preservation of faecal specimens for Kato analysis. Parasitology 90 3:463–469CrossRefGoogle Scholar
  8. Burgsdorf I, Slaby BM, Handley KM, Haber M, Blom J, Marshall CW, Gilbert JA, Hentschel U, Steindler L (2015) Lifestyle evolution in cyanobacterial symbionts of sponges. MBio. 6(3):e00391–e00315.  https://doi.org/10.1128/mBio.00391-15 CrossRefPubMedPubMedCentralGoogle Scholar
  9. Case RJ, Boucher Y, Dahllöf I, Holmström C, Doolittle WF, Kjelleberg S (2007) Use of 16S rRNA and rpoB genes as molecular markers for microbial ecology studies. Appl Environ Microbiol 73(1):278–288.  https://doi.org/10.1128/AEM.01177-06 CrossRefPubMedGoogle Scholar
  10. Dufresne A, Ostrowski M, Scanlan DJ, Garczarek L, Mazard S, Palenik BP, Paulsen IT, de Marsac NT, Wincker P, Dossat C, Ferriera S, Johnson J, Post AF, Hess WR, Partensky F (2008) Unraveling the genomic mosaic of a ubiquitous genus of marine cyanobacteria. Gen Biol 9:R90.  https://doi.org/10.1186/gb-2008-9-5-r90 CrossRefGoogle Scholar
  11. Edgar RC, Haas BJ, Clemente JC, Quince C, Knight R (2011) UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 27:2194–2200.  https://doi.org/10.1093/bioinformatics/btr381 CrossRefPubMedPubMedCentralGoogle Scholar
  12. Ferris M, Hirsch CF (1991) Method for isolation and purification of cyanobacteria. Appl Environ Microbiol 57:1448–1452CrossRefGoogle Scholar
  13. Flynn JM, Brown EA, Chain FJJ, MacIsaac HJ, Cristescu ME (2015) Toward accurate molecular identification of species in complex environmental samples: testing the performance of sequence filtering and clustering methods. Ecol Evol 5:2252–2266.  https://doi.org/10.1002/ece3.1497 CrossRefPubMedPubMedCentralGoogle Scholar
  14. Gao ZM, Wang Y, Tian RM, Wong YH, Batang ZB, Al-Suwailem AM, Bajic VB, Qian PY (2014) Symbiotic adaptation drives genome streamlining of the cyanobacterial sponge symbiont “Candidatus Synechococcus spongiarum”. MBio 5(2):e00079-14.  https://doi.org/10.1128/mBio.00079-14 CrossRefPubMedPubMedCentralGoogle Scholar
  15. Garza DL, Dutilh BE (2015) From cultured to uncultured genome sequences: metagenomics and modeling microbial ecosystems. Cell Mol Life Sci 72:4287–4308.  https://doi.org/10.1007/s00018-015-2004-1 CrossRefPubMedPubMedCentralGoogle Scholar
  16. Gerencser VF, Weaver RH (1958) A new technique for the use of sodium azide (hydrazoic acid) as inhibitive agent. Appl Microbiol 7:113–115CrossRefGoogle Scholar
  17. Ghai R, Martín-Cuadrado AB, Gonzaga-Molto A, García-Heredia I, Cabrera R, Martin J, Verdú M, Deschamps P, Moreira D, López-García P, Mira A, Rodríguez Valera F (2010) Metagenome of the Mediterranean deep chlorophyll maximum studied by direct and fosmid library 454 pyrosequencing. ISME J 4:1154–1166.  https://doi.org/10.1038/ismej.2010.44 CrossRefPubMedGoogle Scholar
  18. Heaney SI, Jaworski GHM (1977) A simple separation technique for purifying micro-algae. Br Phycol J 12:171–174CrossRefGoogle Scholar
  19. Kearse M, Moir R, Wilson A, Stones-Havas S, Cheung M, Sturrock S, Buxton S, Cooper A, Markowitz S, Duran C, Thierer T, Ashton B, Meintjes P, Drummond A (2012) Geneious basic: an integrated and extendable desktop software platform for the organization and analysis of sequence data. Bioinformatics. 28:1647–1649.  https://doi.org/10.1093/bioinformatics/bts199 CrossRefPubMedPubMedCentralGoogle Scholar
  20. Kurtz S, Phillippy A, Delcher AL, Smoot M, Shumway M, Antonescu C, Salzberg SL (2004) Versatile and open software for comparing large genomes. Genome Biol 5(2):R12.  https://doi.org/10.1186/gb-2004-5-2-r12 CrossRefPubMedPubMedCentralGoogle Scholar
  21. Lichstein HC, Soule MH (1943a) The action of sodium azide on microbic growth and respiration: I. The action of sodium azide on microbic growth. J Bacteriol 47(3):221–230CrossRefGoogle Scholar
  22. Lichstein HC, Soule MH (1943b) The action of sodium azide on microbic growth and respiration: II. The action of sodium azide on bacterial catalase. J Bacteriol 47(3):231–238CrossRefGoogle Scholar
  23. Llopis MB, Marugán MR, Althaus RL, Pons MP (2013) Effect of storage and preservation of milk samples on the response of microbial inhibitor tests. J Dairy Res 80(4):475–484.  https://doi.org/10.1017/S0022029913000423 CrossRefPubMedGoogle Scholar
  24. Parks DH, Tyson GW, Hugenholtz P, Beiko RG (2014) STAMP: statistical analysis of taxonomic and functional profiles. Bioinformatics 30:3123–3124.  https://doi.org/10.1093/bioinformatics/btu494 CrossRefPubMedPubMedCentralGoogle Scholar
  25. Ramírez-Saad H, Akkermans WL, Akkermans ADL (2004) DNA extraction from actinorhizal nodules. In: Kowalchuk G, de Bruijn F, Head IA, Akkermans ADL, van Elsas JD (eds) Molecular microbial ecology manual II. Kluwer Academic Publishers, DordrechtGoogle Scholar
  26. Rippka R (1988) Isolation and purification of Cyanobacteria. Methods Enzymol 167:3–27CrossRefGoogle Scholar
  27. 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.  https://doi.org/10.1128/AEM.01541-09 CrossRefPubMedPubMedCentralGoogle Scholar
  28. Schmieder R, Edwards R (2011) Quality control and preprocessing of metagenomic datasets. Bioinformatics 27:863–864.  https://doi.org/10.1093/bioinformatics/btr026 CrossRefPubMedPubMedCentralGoogle Scholar
  29. Sena L, Rojas D, Montiel E, González H, Morett J, Naranjo L (2011) A strategy to obtain axenic cultures of Arthrospira spp. Cyanobacteria. W J Microbiol Biotechnol 27:1045–1053.  https://doi.org/10.1007/s11274-010-0549-6 CrossRefGoogle Scholar
  30. Sitz TO, Schmidt RR (1973) Purification of Synechococcus lividus by equilibrium centrifugation and its synchronization by differential centrifugation. J Bacteriol 115:43–46CrossRefGoogle Scholar
  31. Vaara T, Vaara M, Niemela S (1979) Two improved methods for obtaining axenic cultures of cyanobacteria. Appl Environ Microbiol 38:1011–1014CrossRefGoogle Scholar
  32. Vandeputte D, Tito RY, Vanleeuwen R, Falony G, Raes J. (2017). Practical considerations for large-scale gut microbiome studies. FEMS Microbiol. Rev. 41 (Suppl. 1):S154–S167. doi:  https://doi.org/10.1093/femsre/fux027
  33. Winter C, Kerros ME, Weinbauer M (2012) Effects of sodium azide on the abundance of prokaryotes and viruses in marine samples. PLoS One 7:e37597.  https://doi.org/10.1371/journal.pone.0037597 CrossRefPubMedPubMedCentralGoogle Scholar
  34. Yilmaz P, Parfrey LW, Yarza P, Gerken J, Pruesse E, Quast C, Schweer T, Peplies J, Ludwig W, Glöckner FO (2014) The SILVA and ball-species Living Tree Project (LTP): taxonomic frameworks. Nucleic Acids Res 42:D643–D648.  https://doi.org/10.1093/nar/gkt1209 CrossRefPubMedGoogle Scholar
  35. Yue H, Ling C, Yang T, Chen X, Chen Y, Deng H, Wu Q, Chen J, Chen G-Q (2014) A seawater-based open and continuous process for polyhydroxyalkanoates production by recombinant Halomonas campaniensis LS21 grown in mixed substrates. Biotechnol Biofuels 7:108–119.  https://doi.org/10.1186/1754-6834-7-108 CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Departamento de Ciencias AmbientalesUniversidad Autónoma Metropolitana-LermaLerma de VilladaMexico
  2. 2.Grupo de Ecología Genética Estación Experimental del Zaidín, Consejo Superior de Investigaciones CientíficasGranadaSpain
  3. 3.Maestría en Ciencias AgropecuariasUniversidad Autónoma Metropolitana-XochimilcoMexico CityMexico
  4. 4.Departamento Sistemas BiológicosUniversidad Autónoma Metropolitana-XochimilcoMexico CityMexico

Personalised recommendations