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Microbial Ecology

, Volume 74, Issue 1, pp 89–105 | Cite as

Diversity of Microbial Carbohydrate-Active enZYmes (CAZYmes) Associated with Freshwater and Soil Samples from Caatinga Biome

  • Ana Camila Andrade
  • Adriana Fróes
  • Fabyano Álvares Cardoso Lopes
  • Fabiano L. Thompson
  • Ricardo Henrique Krüger
  • Elizabeth Dinsdale
  • Thiago BruceEmail author
Environmental Microbiology

Abstract

Semi-arid and arid areas occupy about 33% of terrestrial ecosystems. However, little information is available about microbial diversity in the semi-arid Caatinga, which represents a unique biome that extends to about 11% of the Brazilian territory and is home to extraordinary diversity and high endemism level of species. In this study, we characterized the diversity of microbial genes associated with biomass conversion (carbohydrate-active enzymes, or so-called CAZYmes) in soil and freshwater of the Caatinga. Our results showed distinct CAZYme profiles in the soil and freshwater samples. Glycoside hydrolases and glycosyltransferases were the most abundant CAZYme families, with glycoside hydrolases more dominant in soil (∼44%) and glycosyltransferases more abundant in freshwater (∼50%). The abundances of individual glycoside hydrolase, glycosyltransferase, and carbohydrate-binding module subfamilies varied widely between soil and water samples. A predominance of glycoside hydrolases was observed in soil, and a higher contribution of enzymes involved in carbohydrate biosynthesis was observed in freshwater. The main taxa associated with the CAZYme sequences were Planctomycetia (relative abundance in soil, 29%) and Alphaproteobacteria (relative abundance in freshwater, 27%). Approximately 5–7% of CAZYme sequences showed low similarity with sequences deposited in non-redundant databases, suggesting putative homologues. Our findings represent a first attempt to describe specific microbial CAZYme profiles for environmental samples. Characterizing these enzyme groups associated with the conversion of carbohydrates in nature will improve our understanding of the significant roles of enzymes in the carbon cycle. We identified a CAZYme signature that can be used to discriminate between soil and freshwater samples, and this signature may be related to the microbial species adapted to the habitat. The data show the potential ecological roles of the CAZYme repertoire and associated biotechnological applications.

Keywords

Metagenomics Caatinga CAZYome Carbohydrate-active enzymes (CAZYmes) Biomass conversion Environmental microbial diversity 

Notes

Acknowledgements

This work was supported by the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq, 475088/2012-3-APQ) and the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES, 23038.009420/2012-71). Thanks to Dr. Carlos Rezende and his team from the Universidade Estadual do Norte Fluminense for help with sampling and mapping.

Supplementary material

248_2016_911_MOESM1_ESM.xlsx (46 kb)
ESM 1 (XLSX 46 kb)
248_2016_911_MOESM2_ESM.pdf (5 kb)
ESM 2 (PDF 4 kb)

References

  1. 1.
    Leal I, Tabareli M, Cardos da Silva JM (2003) Ecologia e conservação da caatinga, 2nd ed. Editora Universitária UFPEGoogle Scholar
  2. 2.
    Queiroz LP de, Rapini A, Giulietti AM (2006) Towards greater knowledge of the Brazilian semi-arid biodiversity, 1st edn. Ministério do Meio AmbienteGoogle Scholar
  3. 3.
    Ministério do Meio Ambiente Áreas Prioritárias para Conservação, Uso Sustentável e Repartição de Benefícios da Biodiversidade BrasileiraGoogle Scholar
  4. 4.
    Lozupone CA, Knight R (2007) Global patterns in bacterial diversity. Proc Natl Acad Sci 104:11436–11440. doi: 10.1073/pnas.0611525104 CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    Dunbar J, Takala S, Barns SM et al (1999) Levels of bacterial community diversity in four arid soils compared by cultivation and 16S rRNA gene cloning. Appl Environ Microbiol 65:1662–1669PubMedPubMedCentralGoogle Scholar
  6. 6.
    Garcia-Pichel F, Johnson SL, Youngkin D, Belnap J (2003) Small-scale vertical distribution of bacterial biomass and diversity in biological soil crusts from arid lands in the Colorado plateau. Microb Ecol 46:312–321. doi: 10.1007/s00248-003-1004-0 CrossRefPubMedGoogle Scholar
  7. 7.
    Campbell JH, Clark JS, Zak JC (2009) PCR-DGGE comparison of bacterial community structure in fresh and archived soils sampled along a Chihuahuan Desert elevational gradient. Microb Ecol 57:261–266. doi: 10.1007/s00248-008-9479-3 CrossRefPubMedGoogle Scholar
  8. 8.
    Köberl M, Müller H, Ramadan EM, Berg G (2011) Desert farming benefits from microbial potential in arid soils and promotes diversity and plant health. PLoS One 6:e24452. doi: 10.1371/journal.pone.0024452 CrossRefPubMedPubMedCentralGoogle Scholar
  9. 9.
    Ben-David EA, Zaady E, Sher Y, Nejidat A (2011) Assessment of the spatial distribution of soil microbial communities in patchy arid and semi-arid landscapes of the Negev Desert using combined PLFA and DGGE analyses. FEMS Microbiol Ecol 76:492–503. doi: 10.1111/j.1574-6941.2011.01075.x CrossRefPubMedGoogle Scholar
  10. 10.
    Clark JS, Campbell JH, Grizzle H et al (2009) Soil microbial community response to drought and precipitation variability in the Chihuahuan Desert. Microb Ecol 57:248–260. doi: 10.1007/s00248-008-9475-7 CrossRefPubMedGoogle Scholar
  11. 11.
    Pasternak Z, Al-Ashhab A, Gatica J et al (2013) Spatial and temporal biogeography of soil microbial communities in arid and semiarid regions. PLoS One 8:e69705. doi: 10.1371/journal.pone.0069705 CrossRefPubMedPubMedCentralGoogle Scholar
  12. 12.
    Bruce T, de Castro A, Kruger R et al (2012) Microbial diversity of Brazilian biomes. In: Nelson KE, Jones-Nelson B (eds) Genomics applications for the developing world. Springer, New York, pp 217–247CrossRefGoogle Scholar
  13. 13.
    Lopes FAC, Catão ECP, Santana RH et al (2016) Microbial community profile and water quality in a protected area of the Caatinga biome. PLoS One 11:e0148296. doi: 10.1371/journal.pone.0148296 CrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    Pacchioni RG, Carvalho FM, Thompson CE et al (2014) Taxonomic and functional profiles of soil samples from Atlantic forest and Caatinga biomes in northeastern Brazil. Microbiology Open 3:299–315. doi: 10.1002/mbo3.169 CrossRefPubMedPubMedCentralGoogle Scholar
  15. 15.
    Lombard V, Golaconda Ramulu H, Drula E et al (2014) The carbohydrate-active enzymes database (CAZy) in 2013. Nucleic Acids Res 42:D490–495. doi: 10.1093/nar/gkt1178 CrossRefPubMedGoogle Scholar
  16. 16.
    André I, Potocki-Véronèse G, Barbe S et al (2014) CAZyme discovery and design for sweet dreams. Curr Opin Chem Biol 19:17–24. doi: 10.1016/j.cbpa.2013.11.014 CrossRefPubMedGoogle Scholar
  17. 17.
    Cantarel BL, Coutinho PM, Rancurel C et al (2009) The Carbohydrate-Active EnZymes database (CAZy): an expert resource for glycogenomics. Nucleic Acids Res 37:D233–238. doi: 10.1093/nar/gkn663 CrossRefPubMedGoogle Scholar
  18. 18.
    Uroz S, Ioannidis P, Lengelle J et al (2013) Functional assays and metagenomic analyses reveals differences between the microbial communities inhabiting the soil horizons of a Norway spruce plantation. PLoS One 8:e55929. doi: 10.1371/journal.pone.0055929 CrossRefPubMedPubMedCentralGoogle Scholar
  19. 19.
    Brulc JM, Antonopoulos DA, Berg Miller ME et al (2009) Gene-centric metagenomics of the fiber-adherent bovine rumen microbiome reveals forage specific glycoside hydrolases. Proc Natl Acad Sci U S A 106:1948–1953. doi: 10.1073/pnas.0806191105 CrossRefPubMedPubMedCentralGoogle Scholar
  20. 20.
    Warnecke F, Luginbühl P, Ivanova N et al (2007) Metagenomic and functional analysis of hindgut microbiota of a wood-feeding higher termite. Nature 450:560–565. doi: 10.1038/nature06269 CrossRefPubMedGoogle Scholar
  21. 21.
    Wang L, Hatem A, Catalyurek UV et al (2013) Metagenomic insights into the carbohydrate-active enzymes carried by the microorganisms adhering to solid digesta in the rumen of cows. PLoS One 8:e78507. doi: 10.1371/journal.pone.0078507 CrossRefPubMedPubMedCentralGoogle Scholar
  22. 22.
    Kaoutari AE, Armougom F, Gordon JI et al (2013) The abundance and variety of carbohydrate-active enzymes in the human gut microbiota. Nat Rev Microbiol 11:497–504. doi: 10.1038/nrmicro3050 CrossRefPubMedGoogle Scholar
  23. 23.
    Tringe SG (2005) Comparative metagenomics of microbial communities. Science 308:554–557. doi: 10.1126/science.1107851 CrossRefPubMedGoogle Scholar
  24. 24.
    Dinsdale EA, Edwards RA, Hall D et al (2008) Functional metagenomic profiling of nine biomes. Nature 452:629–632. doi: 10.1038/nature06810 CrossRefPubMedGoogle Scholar
  25. 25.
    Fairley P (2011) Introduction: next generation biofuels. Nature 474:S2–S5. doi: 10.1038/474S02a CrossRefPubMedGoogle Scholar
  26. 26.
    Sanderson K (2011) Lignocellulose: a chewy problem. Nature 474:S12–S14. doi: 10.1038/474S012a CrossRefPubMedGoogle Scholar
  27. 27.
    Lynd LR, Weimer PJ, van Zyl WH, Pretorius IS (2002) Microbial cellulose utilization: fundamentals and biotechnology. Microbiol Mol Biol Rev MMBR 66:506–577 (table of contents)CrossRefPubMedGoogle Scholar
  28. 28.
    Meyer F, Paarmann D, D’Souza M et al (2008) The metagenomics RAST server—a public resource for the automatic phylogenetic and functional analysis of metagenomes. BMC Bioinformatics 9:386. doi: 10.1186/1471-2105-9-386 CrossRefPubMedPubMedCentralGoogle Scholar
  29. 29.
    Parks DH, Tyson GW, Hugenholtz P, Beiko RG (2014) STAMP: statistical analysis of taxonomic and functional profiles. Bioinforma Oxf Engl 30:3123–3124. doi: 10.1093/bioinformatics/btu494 CrossRefGoogle Scholar
  30. 30.
    Rice P, Longden I, Bleasby A (2000) EMBOSS: the European Molecular Biology Open Software Suite. Trends Genet TIG 16:276–277CrossRefPubMedGoogle Scholar
  31. 31.
    Finn RD, Clements J, Eddy SR (2011) HMMER web server: interactive sequence similarity searching. Nucleic Acids Res 39:W29–W37. doi: 10.1093/nar/gkr367 CrossRefPubMedPubMedCentralGoogle Scholar
  32. 32.
    Nayfach S, Pollard KS (2015) Average genome size estimation improves comparative metagenomics and sheds light on the functional ecology of the human microbiome. Genome Biol 16:51. doi: 10.1186/s13059-015-0611-7
  33. 33.
    Altschul SF, Madden TL, Schäffer AA et al (1997) Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res 25:3389–3402CrossRefPubMedPubMedCentralGoogle Scholar
  34. 34.
    Huson DH, Auch AF, Qi J, Schuster SC (2007) MEGAN analysis of metagenomic data. Genome Res 17:377–386. doi: 10.1101/gr.5969107 CrossRefPubMedPubMedCentralGoogle Scholar
  35. 35.
    Delmont TO, Prestat E, Keegan KP et al (2012) Structure, fluctuation and magnitude of a natural grassland soil metagenome. ISME J 6:1677–1687. doi: 10.1038/ismej.2011.197 CrossRefPubMedPubMedCentralGoogle Scholar
  36. 36.
    Breitbart M, Hoare A, Nitti A et al (2009) Metagenomic and stable isotopic analyses of modern freshwater microbialites in Cuatro Ciénegas, Mexico. Environ Microbiol 11:16–34. doi: 10.1111/j.1462-2920.2008.01725.x CrossRefPubMedGoogle Scholar
  37. 37.
    Garbeva P, van Veen JA, van Elsas JD (2004) Microbial diversity in soil: selection microbial populations by plant and soil type and implications for disease suppressiveness. Annu Rev Phytopathol 42:243–270. doi: 10.1146/annurev.phyto.42.012604.135455 CrossRefPubMedGoogle Scholar
  38. 38.
    Park BH, Karpinets TV, Syed MH et al (2010) CAZymes Analysis Toolkit (CAT): web service for searching and analyzing carbohydrate-active enzymes in a newly sequenced organism using CAZy database. Glycobiology 20:1574–1584. doi: 10.1093/glycob/cwq106 CrossRefPubMedGoogle Scholar
  39. 39.
    Berlemont R, Martiny AC (2015) Genomic potential for polysaccharide deconstruction in bacteria. Appl Environ Microbiol 81:1513–1519. doi: 10.1128/AEM.03718-14 CrossRefPubMedPubMedCentralGoogle Scholar
  40. 40.
    Wilson DB (2009) Cellulases and biofuels. Curr Opin Biotechnol 20:295–299. doi: 10.1016/j.copbio.2009.05.007 CrossRefPubMedGoogle Scholar
  41. 41.
    Himmel ME, Xu Q, Luo Y et al (2010) Microbial enzyme systems for biomass conversion: emerging paradigms. Biofuels 1:323–341. doi: 10.4155/bfs.09.25 CrossRefGoogle Scholar
  42. 42.
    Phitsuwan P, Laohakunjit N, Kerdchoechuen O et al (2013) Present and potential applications of cellulases in agriculture, biotechnology, and bioenergy. Folia Microbiol (Praha) 58:163–176. doi: 10.1007/s12223-012-0184-8 CrossRefGoogle Scholar
  43. 43.
    Paës G, Berrin J-G, Beaugrand J (2012) GH11 xylanases: structure/function/properties relationships and applications. Biotechnol Adv 30:564–592. doi: 10.1016/j.biotechadv.2011.10.003 CrossRefPubMedGoogle Scholar
  44. 44.
    Stroobants A, Portetelle D, Vandenbol M (2014) New carbohydrate-active enzymes identified by screening two metagenomic libraries derived from the soil of a winter wheat field. J Appl Microbiol 117:1045–1055. doi: 10.1111/jam.12597 CrossRefPubMedGoogle Scholar
  45. 45.
    Sathya TA, Khan M (2014) Diversity of glycosyl hydrolase enzymes from metagenome and their application in food industry. J Food Sci 79:R2149–2156. doi: 10.1111/1750-3841.12677 CrossRefPubMedGoogle Scholar
  46. 46.
    Oh I-N, Jane J-L, Wang K et al (2015) Novel characteristics of a carbohydrate-binding module 20 from hyperthermophilic bacterium. Extrem Life Extreme Cond 19:363–371. doi: 10.1007/s00792-014-0722-1 CrossRefGoogle Scholar
  47. 47.
    Boraston AB, Bolam DN, Gilbert HJ, Davies GJ (2004) Carbohydrate-binding modules: fine-tuning polysaccharide recognition. Biochem J 382:769–781. doi: 10.1042/BJ20040892 CrossRefPubMedPubMedCentralGoogle Scholar
  48. 48.
    Guillén D, Sánchez S, Rodríguez-Sanoja R (2010) Carbohydrate-binding domains: multiplicity of biological roles. Appl Microbiol Biotechnol 85:1241–1249. doi: 10.1007/s00253-009-2331-y CrossRefPubMedGoogle Scholar
  49. 49.
    Kumar V (2010) Analysis of the key active subsites of glycoside hydrolase 13 family members. Carbohydr Res 345:893–898. doi: 10.1016/j.carres.2010.02.007 CrossRefPubMedGoogle Scholar
  50. 50.
    Stam MR, Danchin EGJ, Rancurel C et al (2006) Dividing the large glycoside hydrolase family 13 into subfamilies: towards improved functional annotations of alpha-amylase-related proteins. Protein Eng Des Sel PEDS 19:555–562. doi: 10.1093/protein/gzl044 CrossRefPubMedGoogle Scholar
  51. 51.
    Elleuche S, Schröder C, Sahm K, Antranikian G (2014) Extremozymes—biocatalysts with unique properties from extremophilic microorganisms. Curr Opin Biotechnol 29:116–123. doi: 10.1016/j.copbio.2014.04.003 CrossRefPubMedGoogle Scholar
  52. 52.
    Li L-L, McCorkle SR, Monchy S et al (2009) Bioprospecting metagenomes: glycosyl hydrolases for converting biomass. Biotechnol Biofuels 2:10. doi: 10.1186/1754-6834-2-10 CrossRefPubMedPubMedCentralGoogle Scholar
  53. 53.
    Faure D (2002) The family-3 glycoside hydrolases: from housekeeping functions to host-microbe interactions. Appl Environ Microbiol 68:1485–1490CrossRefPubMedPubMedCentralGoogle Scholar
  54. 54.
    Lairson LL, Henrissat B, Davies GJ, Withers SG (2008) Glycosyltransferases: structures, functions, and mechanisms. Annu Rev Biochem 77:521–555. doi: 10.1146/annurev.biochem.76.061005.092322 CrossRefPubMedGoogle Scholar
  55. 55.
    Hart GW, Akimoto Y (2009) The O-GlcNAc modification. In: Varki A, Cummings RD, Esko JD et al. (eds) Essentials of glycobiology, 2nd edn. Cold Spring Harbor Laboratory Press, New York, p 784Google Scholar
  56. 56.
    Gomez-Casati DF, Martín M, Busi MV (2013) Polysaccharide-synthesizing glycosyltransferases and carbohydrate binding modules: the case of starch synthase III. Protein Pept Lett 20:856–863CrossRefPubMedGoogle Scholar
  57. 57.
    Ruane KM, Davies GJ, Martinez-Fleites C (2008) Crystal structure of a family GT4 glycosyltransferase from Bacillus anthracis ORF BA1558. Proteins 73:784–787. doi: 10.1002/prot.22171 CrossRefPubMedGoogle Scholar
  58. 58.
    Borneman J, Triplett EW (1997) Molecular microbial diversity in soils from eastern Amazonia: evidence for unusual microorganisms and microbial population shifts associated with deforestation. Appl Environ Microbiol 63:2647–2653PubMedPubMedCentralGoogle Scholar
  59. 59.
    Zhou J, Xia B, Huang H et al. (2003) Bacterial phylogenetic diversity and a novel candidate division of two humid region, sandy surface soils. http://www.sciencedirect.com/science/article/pii/S003807170300124X. Accessed 26 April 2016
  60. 60.
    Kuske CR, Barns SM, Busch JD (1997) Diverse uncultivated bacterial groups from soils of the arid southwestern United States that are present in many geographic regions. Appl Environ Microbiol 63:3614–3621PubMedPubMedCentralGoogle Scholar
  61. 61.
    Buckley DH, Huangyutitham V, Nelson TA et al (2006) Diversity of Planctomycetes in soil in relation to soil history and environmental heterogeneity. Appl Environ Microbiol 72:4522–4531. doi: 10.1128/AEM.00149-06 CrossRefPubMedPubMedCentralGoogle Scholar
  62. 62.
    Elshahed MS, Youssef NH, Luo Q et al (2007) Phylogenetic and metabolic diversity of Planctomycetes from anaerobic, sulfide- and sulfur-rich Zodletone Spring, Oklahoma. Appl Environ Microbiol 73:4707–4716. doi: 10.1128/AEM.00591-07 CrossRefPubMedPubMedCentralGoogle Scholar
  63. 63.
    Bondoso J, Balagué V, Gasol JM, Lage OM (2014) Community composition of the Planctomycetes associated with different macroalgae. FEMS Microbiol Ecol 88:445–456. doi: 10.1111/1574-6941.12258 CrossRefPubMedGoogle Scholar
  64. 64.
    Pollet T, Tadonleke RD, Humbert JF (2011) Spatiotemporal changes in the structure and composition of a less-abundant bacterial phylum (Planctomycetes) in two perialpine lakes. Appl Environ Microbiol 77:4811–4821. doi: 10.1128/AEM.02697-10 CrossRefPubMedPubMedCentralGoogle Scholar
  65. 65.
    Fierer N, Jackson RB (2006) The diversity and biogeography of soil bacterial communities. Proc Natl Acad Sci 103:626–631. doi: 10.1073/pnas.0507535103 CrossRefPubMedPubMedCentralGoogle Scholar
  66. 66.
    Percent SF, Frischer ME, Vescio PA et al (2008) Bacterial community structure of acid-impacted lakes: what controls diversity? Appl Environ Microbiol 74:1856–1868. doi: 10.1128/AEM.01719-07 CrossRefPubMedPubMedCentralGoogle Scholar
  67. 67.
    Newton RJ, Jones SE, Eiler A et al (2011) A guide to the natural history of freshwater lake bacteria. Microbiol Mol Biol Rev MMBR 75:14–49. doi: 10.1128/MMBR.00028-10 CrossRefPubMedGoogle Scholar
  68. 68.
    Kirchman DL (2002) The ecology of Cytophaga-Flavobacteria in aquatic environments. FEMS Microbiol Ecol 39:91–100. doi: 10.1111/j.1574-6941.2002.tb00910.x PubMedGoogle Scholar
  69. 69.
    Fernández-Gómez B, Richter M, Schüler M et al (2013) Ecology of marine Bacteroidetes: a comparative genomics approach. ISME J 7:1026–1037. doi: 10.1038/ismej.2012.169 CrossRefPubMedPubMedCentralGoogle Scholar
  70. 70.
    Breznak JA (2002) Phylogenetic diversity and physiology of termite gut spirochetes. Integr Comp Biol 42:313–318. doi: 10.1093/icb/42.2.313 CrossRefPubMedGoogle Scholar
  71. 71.
    Henrissat B, Coutinho PM (2001) Classification of glycoside hydrolases and glycosyltransferases from hyperthermophiles. Methods Enzymol 330:183–201CrossRefPubMedGoogle Scholar
  72. 72.
    Alvarez TM, Paiva JH, Ruiz DM et al (2013) Structure and function of a novel cellulase 5 from sugarcane soil metagenome. PLoS One 8:e83635. doi: 10.1371/journal.pone.0083635 CrossRefPubMedPubMedCentralGoogle Scholar
  73. 73.
    Liu J, Liu W-D, Zhao X-L et al (2011) Cloning and functional characterization of a novel endo-β-1,4-glucanase gene from a soil-derived metagenomic library. Appl Microbiol Biotechnol 89:1083–1092. doi: 10.1007/s00253-010-2828-4 CrossRefPubMedGoogle Scholar
  74. 74.
    Xiang L, Li A, Tian C et al (2014) Identification and characterization of a new acid-stable endoglucanase from a metagenomic library. Protein Expr Purif 102:20–26. doi: 10.1016/j.pep.2014.07.009 CrossRefPubMedGoogle Scholar
  75. 75.
    Patel DD, Patel AK, Parmar NR et al (2014) Microbial and carbohydrate active enzyme profile of buffalo rumen metagenome and their alteration in response to variation in the diet. Gene 545:88–94. doi: 10.1016/j.gene.2014.05.003 CrossRefPubMedGoogle Scholar
  76. 76.
    Patel AB, Patel AK, Shah MP et al (2016) Isolation and characterization of novel multifunctional recombinant family 26 glycoside hydrolase from Mehsani buffalo rumen metagenome. Biotechnol Appl Biochem 63:257–265. doi: 10.1002/bab.1358 CrossRefPubMedGoogle Scholar
  77. 77.
    Kanokratana P, Eurwilaichitr L, Pootanakit K, Champreda V (2015) Identification of glycosyl hydrolases from a metagenomic library of microflora in sugarcane bagasse collection site and their cooperative action on cellulose degradation. J Biosci Bioeng 119:384–391. doi: 10.1016/j.jbiosc.2014.09.010 CrossRefPubMedGoogle Scholar
  78. 78.
    Klippel B, Sahm K, Basner A et al (2014) Carbohydrate-active enzymes identified by metagenomic analysis of deep-sea sediment bacteria. Extrem Life Extreme Cond 18:853–863. doi: 10.1007/s00792-014-0676-3 CrossRefGoogle Scholar
  79. 79.
    Stöveken J, Singh R, Kolkenbrock S et al (2015) Successful heterologous expression of a novel chitinase identified by sequence analyses of the metagenome from a chitin-enriched soil sample. J Biotechnol 201:60–68. doi: 10.1016/j.jbiotec.2014.09.010 CrossRefPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  • Ana Camila Andrade
    • 1
  • Adriana Fróes
    • 2
  • Fabyano Álvares Cardoso Lopes
    • 3
  • Fabiano L. Thompson
    • 2
  • Ricardo Henrique Krüger
    • 3
  • Elizabeth Dinsdale
    • 4
  • Thiago Bruce
    • 1
    • 4
    • 5
    Email author
  1. 1.Faculdade de Tecnologia e CiênciasGrupo de Biotecnologia Ambiental, Department of BioenergySalvadorBrazil
  2. 2.Laboratory of Microbiology, Institute of Biology, and SAGE-COPPEFederal University of Rio de Janeiro (UFRJ)Rio de JaneiroBrazil
  3. 3.Cellular Biology DepartmentUniversity of Brasília (UnB)BrasíliaBrazil
  4. 4.Department of BiologySan Diego State UniversitySan DiegoUSA
  5. 5.Institute of Biology, Microbiology department, Universidade Federal da Bahia (UFBA)Rio de JaneiroBrazil

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