Coupled high-throughput functional screening and next generation sequencing for identification of plant polymer decomposing enzymes in metagenomic libraries

Frontiers in Microbiology

Volumn 4, Issue SEP, 2013, Pages

  Nyyssönen, Mari ^a   Tran, Huu M ^b,c   Karaoz, Ulas ^a   Weihe, Claudia ^d   Hadi, Masood Z ^b,f   Martiny, Jennifer B H ^d   Martiny, Adam C ^d   Brodie, Eoin L ^a,e  

^a LAWRENCE BERKELEY NATIONAL LABORATORY   (United States)

^b JOINT BIOENERGY INSTITUTE   (United States)

^c SANDIA NATIONAL LABORATORIES   (United States)

^d UNIVERSITY OF CALIFORNIA   (United States)

^e UNIVERSITY OF CALIFORNIA   (United States)

^f NASA AMES RESEARCH CENTER   (United States)

Author keywords

Carbon cycling; Decomposers; Enzyme activity; Functional metagenomics; Gene annotation; Metagenomics; Microbial communities; Trait based modeling

Indexed keywords

CELLOBIOSE; CELLULOSE; CHITIN; ENZYME; GLYCOSIDASE; HEMICELLULOSE; N ACETYLGLUCOSAMINE; PHOSPHATE; PLANT POLYMER DECOMPOSING ENZYME; STARCH; UNCLASSIFIED DRUG; XYLAN ENDO 1, 3 BETA XYLOSIDASE;

ACTINOBACTERIA; ARTICLE; BACTEROIDETES; BIOLOGICAL TRAIT; CONTROLLED STUDY; ESCHERICHIA COLI; FOSMID; FUNGUS; GENE DISRUPTION; HIGH THROUGHPUT SCREENING; HIGH THROUGHPUT SEQUENCING; LEAF LITTER; METAGENOME; METAGENOMICS; MICROBIAL DIVERSITY; MOLECULAR LIBRARY; NEXT GENERATION SEQUENCING; NONHUMAN; NUCLEOTIDE SEQUENCE; PHYLOGENY; POLYMERASE CHAIN REACTION; PROCESS OPTIMIZATION; PROTEOBACTERIA; SEQUENCE ANALYSIS; UNINDEXED SEQUENCE; VALIDATION PROCESS;

ACTINOBACTERIA; BACTERIA (MICROORGANISMS); BACTEROIDETES; FUNGI; PROTEOBACTERIA;

EID: 84885408574     PISSN: None     EISSN: 1664302X     Source Type: Journal    
DOI: 10.3389/fmicb.2013.00282     Document Type: Article

References (79)

1. Aakvik, T., Degnes, K. F., Dahlsrud, R., Schmidt, F., Dam, R., Yu, L., et al. (2009). A plasmid RK2-based broad-host-range cloning vector useful for transfer of metagenomic libraries to a variety of bacterial species. FEMS Microbiol. Lett. 296, 149-158. doi:10.1111/j.1574-6968.2009.01639.x.
2. Allen, H. K., Moe, L. A., Rodbumrer, J., Gaarder, A., and Handelsman, J. (2009). Functional metagenomics reveals diverse β-lactamases in a remote Alaskan soil. ISME J. 3, 243-251. doi:10.1038/ismej.2008.86.
3. Allison, S. D. (2012). A trait-based approach for modeling microbial litter decomposition. Ecol. Lett. 15, 1058-1070. doi:10.1111/j.1461-0248.2012.01807.x.
4. Allison, S. D., Lu, Y., Weihe, C., Goulden, M. L., Martiny, A. C., Treseder, K. K., et al. (2013). Microbial abundance and composition influence litter decomposition response to environmental change. Ecology 94, 714-725. doi:10.1890/12-1243.1.
5. Allison, S. D., and Martiny, J. B. H. (2008). Resistance, resilience, and redundancy in microbial communies. Proc. Natl. Acad. Sci. U.S.A. 108, 11512-11519. doi:10.1073/pnas.0801925105.
6. Altschul, S. F., Gish, W., Miller, W., Myers, E. W., and Lipman, D. J. (1990). Basic local alignment search tool. J. Mol. Biol. 215, 403-410. doi:10.1006/jmbi.1990.9999.
7. Baba, T., Ara, T., Hasegawa, M., Takai, Y., Okumura, Y., Baba, M., et al. (2006). Construction of Escherichia coli K-12 in-frame, single-gene knockout mutants:the Keio collection. Mol. Syst. Biol. 2, 8. doi:10.1038/msb4100050.
8. Berlemont, R., and Martiny, A. C. (2013). Phylogenetic distribution of potential cellulases in bacteria. Appl. Environ. Microbiol. 79, 1545-1554. doi:10.1128/AEM.03305-12.
9. Biely, P., Vrsanska, M., Tenkanen, M., and Kluepfel, D. (1997). Endo-β-1,4-xylanase families:differences in catalytic properties. J. Biotechnol. 57, 151-166. doi:10.1016/S0168-1656(97)00096-5.
10. Blankenberg, D., Von Kuster, G., Coraor, N., Ananda, G., Lazarus, R., Mangan, M., et al. (2010). Galaxy:a web-based genome analysis tool for experimentalists. Curr. Protoc. Mol. Biol. 19, 19.10.1-19.10.21. doi:10.1002/0471142727.mb1910s89.
11. Brennerova, M. V., Josefiova, J., Brenner, V., Pieper, D. H., and Junca, H. (2009). Metagenomics reveals diversity and abundance of meta-cleavage pathways in microbial communities from soil highly contaminated with jet fuel under air-sparging bioremediation. Environ. Microbiol. 11, 2216-2227. doi:10.1111/j.1462-2920.2009.01943.x.
12. Cantarel, B. L., Coutinho, P. M., Rancurel, C., Bernard, T., Lombard, V., and Henrissat, B. (2009). The carbohydrate-active enzymes database (CAZy):an expert resource for glycogenomics. Nucleic Acids. Res. 37, D233-D238. doi:10.1093/nar/gkn663.
13. Chow, J., Kovacic, F., Antonia, Y. D., Krauss, U., Fersini, F., Schmeisser, C., et al. (2012). The metagenome-derived enzymes LipS and LipT increase the diversity of known lipases. PLoS ONE 7:e47665. doi:10.1371/journal.pone.0047665.
14. Chung, E. J., Lim, H. K., Kim, J. C., Choi, G. J., Park, E. J., Lee, M. H., et al. (2008). Forest soil metagenome gene cluster involved in antifungal activity expression in E. coli. Appl. Environ. Microbiol. 74, 723-730. doi:10.1128/AEM.01911-07.
15. Cournoyer, B., and Faure, D. (2003). Radiation and functional specialization of the family-3 glycoside hydrolases. J. Mol. Microbiol. Biotechnol. 5, 190-198. doi:10.1159/000070269.
16. Craig, J. W., Chang, F. Y., Kim, J. H., Obiajulu, S. C., and Brady, S. F. (2010). Expanding small-molecule functional metagenomics through parallel screening of broad-host-range cosmid environmental DNA libraries in diverse proteobacteria. Appl. Environ. Microbiol. 76, 1633-1641. doi:10.1128/AEM.02169-09.
17. Darriba, D., Taboada, G. L., Doallo, R., and Posada, D. (2011). ProtTest 3:fast selection of best-fit models of protein evolution. Bioinformatics 27, 1164-1165. doi:10.1093/bioinformatics/btr088.
18. Datsenko, K. A., and Wanner, B. L. (2000). One-step inactivation of chromosomal genes in Escherichia coli K-12 using PCR products. Proc. Natl. Acad. Sci. U.S.A. 97, 6640-6645. doi:10.1073/pnas.120163297.
19. Denef, V. J., and Banfield, J. F. (2012). In situ evolutionary rate measurements show ecological success of recently emerged bacterial hybrids. Science 336, 462-466. doi:10.1126/science.1218389.
20. Dick, G. J., Andersson, A. F., Baker, B. J., Simmons, S. L., Thomas, B. C., Yelton, A. P., et al. (2009). Community-wide analysis of microbial genome sequence signatures. Genome Biol. 10:R85. doi:10.1186/gb-2009-10-8-r85.
21. Earth Microbiome Project:http://www.earthmicrobiome.org.
22. Ewing, B., and Green, P. (1998). Basecalling of automated sequencer traces using phred. II. Error probabilities. Genome Res. 8, 186-194. doi:10.1101/gr.8.3.175.
23. Ewing, B., Hillier, L., Wendl, M., and Green, P. (1998). Basecalling of automated sequencer traces using phred. I. Accuracy assessment. Genome Res. 8, 175-185. doi:10.1101/gr.8.3.175.
24. Fawal, N., Li, Q., Savelli, B., Brette, M., Passaia, G., Fabre, M., et al. (2013). PeroxiBase:a database for large-scale evolutionary analysis of peroxidases. Nucleic Acids Res. 41, D441-D444. doi:10.1093/nar/gks1083.
25. Fierer, N., Leff, J. W., Adams, B. J., Nielsen, U. N., Bates, S. T., Lauber, C. L., et al. (2012). Cross-biome metagenomic analyses of soil microbial communities and their functional attributes. Proc. Natl. Acad. Sci. U.S.A. 109, 21390-21395. doi:10.1073/pnas.1215210110.
26. Gabor, E. M., Alkema, W. B. L., and Janssen, D. B. (2004). Quantifying the accessibility of the metagenome by random expression cloning techniques. Environ. Microbiol. 6, 879-886. doi:10.1111/j.1462-2920.2004.00640.x.
27. Giardine, B., Riemer, C., Hardison, R. C., Burhans, R., Elnitski, L., Shah, P., et al. (2005). Galaxy:a platform for interactive large-scale genome analysis. Genome Res. 15, 1451-1455. doi:10.1101/gr.4086505.
28. Goecks, J., Nekrutenko, A., Taylor, J., and The Galaxy Team. (2010). Galaxy:a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences. Genome Biol. 11:R86. doi:10.1186/gb-2010-11-8-r86.
29. Gouy, M., Guindon, S., and Gascuel, O. (2010). SeaView version 4:a multiplatform graphical user interface for sequence alignment and phylogenetic tree building. Mol. Biol. Evol. 27, 221-224. doi:10.1093/molbev/msp259.
30. Great Prairie Grand Challenge:http://genome.jgi.doe.gov/GrePraGChallenge/GrePraGChallenge.info.html.
31. Guindon, S., Dufayard, J. F., Lefort, V., Anisimova, M., Hordijk, W., and Gascuel, O. (2010). New algorithms and methods to estimate maximum-likelihood phylogenies:assessing the performance of PhyML 3.0. Syst. Biol. 59, 307-321. doi:10.1093/sysbio/syq010.
32. Hill, A. D., and Reilly, P. J. (2008). Computational analysis of glycoside hydrolase family 1 specificities. Biopolymers 89, 1021-1031. doi:10.1002/bip.21052.
33. Hu, Y., Zhang, G., Li, A., Chen, J., and Ma, L. (2008). Cloning and enzymatic characterization of a xylanase gene from a soil-derived metagenomic library with an efficient approach. Appl. Microbiol. Biotechnol. 80, 823-830. doi:10.1007/s00253-008-1636-6.
34. Huson, D. H., Mitra, S., Weber, N., Ruscheweyh, H., and Schuster, S. C. (2011). Integrative analysis of environmental sequences using MEGAN4. Genome Res. 21, 1552-1560. doi:10.1101/gr.120618.111.
35. Hyatt, D., Chen, G. L., Locascio, P. F., Land, M. L., Larimer, F. W., and Hauser, L. J. (2010). Prodigal:prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics. 11:119. doi:10.1186/1471-2105-11-119.
36. Iverson, V., Morris, R. M., Frazar, C. D., Berthiaume, C. T., Morales, R. L., and Armbrust, E. V. (2012). Untangling genomes from metagenomes:revealing an uncultured class of marine Euryarchaeota. Sci. 335, 587-590. doi:10.1126/science.1212665.
37. Jiang, C., Li, S. X., Luo, F. F., Jin, K., Wang, Q., Hao, Z. Y., et al. (2011). Biochemical characterization of two novel β-glucosidase genes by metagenome expression cloning. Bioresour. Technol. 102, 3272-3278. doi:10.1016/j.biortech.2010.09.114.
38. Kellner, H., Luis, P., Portetelle, D., and Vandenbol, M. (2011). Screening of a soil metatranscriptomic library by functional complementation of Saccharomyces cerevisiae mutants. Microbiol. Res. 166, 360-368. doi:10.1016/j.micres.2010.07.006.
39. Langmead, B., Trapnell, C., Pop, M., and Salzberg, S. L. (2009). Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol. 10:R25. doi:10.1186/gb-2009-10-3-r25.
40. Larkin, M. A., Blackshields, G., Brown, N. P., Chenna, R., McGettigan, P. A., McWilliam, H., et al. (2007). Clustal W and Clustal X version 2.0. Bioinformatics 23, 2947-2948. doi:10.1093/bioinformatics/btm404.
41. Letunic, I., and Bork, P. (2006). Interactive Tree Of Life (iTOL):an online tool for phylogenetic tree display and annotation. Bioinformatics 23, 127-128. doi:10.1093/bioinformatics/btl529.
42. Letunic, I., and Bork, P. (2011). Interactive Tree Of Life v2:online annotation and display of phylogenetic trees made easy. Nucleic Acids Res. 39, W475-W478. doi:10.1093/nar/gkr201.
43. Lohse, M., Bolger, A. M., Nagel, A., Fernie, A. R., Lunn, J. E., Stitt, M., et al. (2012). RobiNA:a user-friendly, integrated software solution for RNA-Seq-based transcriptomics. Nucleic Acids Res. 40, W622-W627. doi:10.1093/nar/gks540.
44. Loreau, M., Naeem, S., Inchausti, P., Bengtsson, J., Grime, J. P., Hector, A., et al. (2001). Biodiversity and ecosystem functioning:current knowledge and future challenges. Science 294, 804-808. doi:10.1126/science.1064088.
45. MacGregor, E. A., Janecek, S., and Svensson, B. (2001). Relationship of sequence and structure to specificity in the alpha-amylase family of enzymes. Biochim. Biophys. Acta. 1546, 1-20. doi:10.1016/S0167-4838(00)00302-2.
46. Mackelprang, R., Waldrop, M. P., DeAngelis, K. M., David, M. M., Chavarria, K. L., Blazewicz, S. J., et al. (2011). Metagenomic analysis of a permafrost microbial community reveals a rapid response to thaw. Nature 480, 368-371. doi:10.1038/nature10576.
47. Martinez, A., Bradley, A. S., Waldbauer, J. R., Summons, R. E., and DeLong, E. F. (2007). Proteorhodopsin photosystem gene expression enables photophosphorylation in a heterologous host. Proc. Natl. Acad. Sci. U.S.A. 104, 5590-5595. doi:10.1073/pnas.0611470104.
48. Martiny, A. C., Treseder, K., and Pusch, G. (2012). Phylogenetic conservatism of functional traits in microorganisms. ISME J. 7, 830-838. doi:10.1038/ismej.2012.160.
49. McGarvey, K. M., Queitsch, K., and Fields, S. (2012). Wide variation in antibiotic resistance proteins identified by functional metagenomic screening of a soil DNA library. Appl. Environ. Microbiol. 78, 1708-1714. doi:10.1128/AEM.06759-11.
50. MetaSoil Project:http://www.genomenviron.org/Projects/METASOIL.html.
51. Mewis, K., Taupp, M., and Hallam, S. J. (2011). A high throughput screen for biomining cellulase activity from metagenomic libraries. J. Vis. Exp. 1, pii:2461. doi:10.3791/2461.
52. Mirete, S., de Figueras, C. G., and González-Pastor, J. E. (2007). Novel nickel resistance genes from the Rhizosphere Metagenome of plants adapted to acid mine drainage. Appl. Environ. Microbiol. 73, 6001-6011. doi:10.1128/AEM.00048-07.
53. Nacke, H., Will, C., Herzog, S., Nowka, B., Engelhaupt, M., and Daniel, R. (2011). Identification of novel lipolytic genes and gene families by screening of metagenomic libraries derived from soil samples of the German Biodiversity Exploratories. FEMS Microbiol. Ecol. 78, 188-201. doi:10.1111/j.1574-6941.2011.01088.x.
54. Ono, A., Miyazaki, R., Sota, M., Ohtsubo, Y., Nagata, Y., and Tsuda, M. (2007). Isolation and characterization of naphthalene-catabolic genes and plasmids from oil-contaminated soil by using two cultivation-independent approaches. Appl. Microbiol. Biotechnol. 74, 501-510. doi:10.1007/s00253-006-0671-4.
55. Pang, H., Zhang, P., Duan, C. J., Mo, X. C., Tang, J. L., and Feng, J. X. (2009). Identification of cellulase genes from the metagenomes of compost soils and functional characterization of one novel endoglucanase. Curr. Microbiol. 58, 404-408. doi:10.1007/s00284-008-9346-y.
56. Park, S. H., Cheong, D. E., Lee, J. Y., Han, S. S., Lee, J. H., and Kim, G. J. (2007). Analyses of the structural organization of unidentified open reading frames from metagenome. Biochem. Biophys. Res. Commun. 356, 961-967. doi:10.1016/j.bbrc.2007.03.090.
57. Potts, D. L., Suding, K. N., Winston, G. C., Rocha, A. V., and Goulden, M. L. (2012). Ecological effects of experimental drought and prescribed fire in a southern California coastal grassland. J. Arid. Environ. 81, 59-66. doi:10.1016/j.jaridenv.2012.01.007.
58. Prakash, T., and Taylor, T. D. (2012). Functional assignment of metagenomic data:challenges and applications. Brief Bioinform. 13, 711-727. doi:10.1093/bib/bbs033.
59. Punta, M., Coggill, P. C., Eberhardt, R. Y., Mistry, J., Tate, J., Boursnell, C., et al. (2011). The Pfam protein families database. Nucleic Acids Res. 40, D290-D301. doi:10.1093/nar/gkr1065.
60. R Core Team (2012). R:A Language and Environment for Statistical Computing. Vienna:R Foundation for Statistical Computing. ISBN 3-900051-07-0. Available online at:http://www.R-project.org/.
61. Riaz, K., Elmerich, C., Moreira, D., Raffoux, A., Dessaux, Y., and Faure, D. (2008). A metagenomic analysis of soil bacteria extends the diversity of quorum-quenching lactonases. Environ. Microbiol. 10, 560-570. doi:10.1111/j.1462-2920.2007.01475.x.
62. Schnoes, A. M., Brown, S. D., Dodevski, I., and Babbitt, P. C. (2009). Annotation error in public databases:misannotation of molecular function in enzyme superfamilies. PLoS Comput. Biol. 5:e1000605. doi:10.1371/journal.pcbi.1000605.
63. Sharrock, K. R. (1988). Cellulase assay methods:a review. J. Biochem. Biophys. Methods 17, 81-106. doi:10.1016/0165-022X(88)90040-1.
64. Sirim, D., Wagner, F., Wang, L., Schmid, R. D., and Pleiss, J. (2011). The laccase engineering database:a classification and analysis system for laccases and related multicopper oxidases. Database 2011:bar006. doi:10.1093/database/bar006.
65. Slámová, K., Bojarová, P., Petrásková, L., and Kren, V. (2010a). β-N-acetylhexosaminidase:what's in a name...? Biotechnol. Adv. 28, 682-693. doi:10.1016/j.biotechadv.2010.04.004.
66. Slámová, K., Gazák, R., Bojarová, P., Kulik, N., Ettrich, R., Pelantová, H., et al. (2010b). 4-Deoxy-substrates for beta-N-acetylhexosaminidases:how to make use of their loose specificity. Glycobiology 20, 1002-1009. doi:10.1093/glycob/cwq058.
67. Suenaga, H., Koyama, Y., Miyakoshi, M., Miyazaki, R., Yano, H., Sota, M., et al. (2009). Novel organization of aromatic degradation pathway genes in a microbial community as revealed by metagenomic analysis. ISME J. 3, 1335-1348. doi:10.1038/ismej.2009.76.
68. Tasse, L., Bercovici, J., Pizzut-Serin, S., Robe, P., Tap, J., Klopp, C., et al. (2010). Functional metagenomics to mine the human gut microbiome for dietary fiber catabolic enzymes. Genome Res. 20, 1605-1612. doi:10.1101/gr.108332.110.
69. Teeling, H., Meyerdierks, A., Bauer, M., Amann, R., and Glöckner, F. O. (2004). Application of tetranucleotide frequencies for the assignment of genomic fragments. Environ. Microbiol. 6, 938-947. doi:10.1111/j.1462-2920.2004.00624.x.
70. Tringe, S. G., von Mering, C., Kobayashi, A., Salamov, A. A., Chen, K., Chang, H. W., et al. (2005). Comparative metagenomics of microbial communities. Science 308, 554-557. doi:10.1126/science.1107851.
71. Tyson, G. W., Chapman, J., Hugenholtz, P., Allen, E. E., Ram, R. J., Richardson, P. M., et al. (2004). Community structure and metabolism through reconstruction of microbial genomes from the environment. Nature 428, 37-43. doi:10.1038/nature02340.
72. Ultsch, A., and Moerchen, F. (2005). ESOM-Maps:Tools for Clustering, Visualization, and Classification with Emergent SOM. Technical Report, No. 46, Department of Mathematics and Computer Science, University of Marburg.
73. van Elsas, J. D., Costa, R., Jansson, J., Sjoling, S., Bailey, M., Nalin, R., et al. (2008). The metagenomics of disease-suppressive soils-experiences from the METACONTROL project. Trends Biotechnol. 26, 591-601. doi:10.1016/j.tibtech.2008.07.004.
74. Venter, J. C., Remington, K., Heidelberg, J. F., Halpern, A. L., Rusch, D., Eisen, J. A., et al. (2004). Environmental genome shotgun sequencing of the Sargasso Sea. Science 304, 66-74. doi:10.1126/science.1093857.
75. Wrighton, K. C., Thomas, B. C., Sharon, I., Miller, C. S., Castelle, C. J., VerBerkmoes, N. C., et al. (2012). Fermentation, hydrogen, and sulfur metabolism in multiple uncultivated bacterial phyla. Science 337, 1661-1665. doi:10.1126/science.1224041.
76. Yin, Y., Mao, X., Ynag, J. C., Chen, X., Mao, F., and Xu, Y. (2012). dbCAN:a web source for automated carbohydrate-active enzyme annotation. Nucleic Acids Res. 40, W445-W451. doi:10.1093/nar/gks479.
77. Yoon, M. Y., Lee, K. M., Yoon, Y., Go, J., Park, Y., Cho, Y. J., et al. (2013). Functional screen of a metagenomic library reveals operons responsible for enhanced intestinal colonization by gut commensals. Appl. Environ. Microbiol. 79, 3829-3838. doi:10.1128/AEM.00581-13.
78. Zerbino, D. R., and Birney, E. (2008). Velvet:algorithms for de novo short read assembly using de Bruijn graphs. Genome Res. 18, 821-829. doi:10.1101/gr.074492.107.
79. Zimmerman, A. E., Martiny, A. C., and Allison, S. D. (2013). Microdiversity of extracellular enzyme genes among sequenced prokaryotic genomes. ISME J. 7, 1187-1199. doi:10.1038/ismej.2012.176.