Wang C, Dong D, Wang H, Müller K, Qin Y, Wu W. Metagenomic analysis of microbial consortia enriched from compost: new insights into the role of Actinobacteria in lignocellulose decomposition. Biotechnol Biofuels. 2016;9:22.
Article
Google Scholar
Simmons CW, Reddy AP, D’haeseleer P, Khudyakov J, Billis K, Pati K, et al. Metatranscriptomic analysis of lignocellulolytic microbial communities involved in high-solids decomposition of rice straw. Biotechnol Biofuels. 2014;7:495.
Article
Google Scholar
Mhuantong W, Charoensawan V, Kanokratana P, Tangphatsornruang S, Champreda V. Comparative analysis of sugarcane bagasse metagenome reveals unique and conserved biomass-degrading enzymes among lignocellulolytic microbial communities. Biotechnol Biofuels. 2015;8:16.
Article
Google Scholar
Jiang Y, Xiong X, Danska J, Parkinson J. Metatranscriptomic analysis of diverse microbial communities reveals core metabolic pathways and microbiome-specific functionality. Microbiome. 2016;4:2.
Article
Google Scholar
Berlemont R, Martiny AC. Phylogenetic distribution of potential cellulases in bacteria. Appl Environ Microbiol. 2013;79:1545–54.
Article
CAS
Google Scholar
Hess M, Sczyrba A, Egan R, Kim TW, Chokhawala H, Schroth G, et al. Metagenomic discovery of biomass-degrading genes and genomes from cow rumen. Science. 2011;331:463–7.
Article
CAS
Google Scholar
Martins LF, Antunes LP, Pascon RC, de Oliveira JC, Digiampietri LA, Barbosa D, et al. Metagenomic analysis of a tropical composting operation at the são paulo zoo park reveals diversity of biomass degradation functions and organisms. PLoS ONE. 2013;8:e61928.
Article
CAS
Google Scholar
Allgaier M, Reddy A, Park JI, Ivanova N, D’haeseleer P, Lowry S, et al. Targeted discovery of glycoside hydrolases from a switchgrass-adapted compost community. PLoS ONE. 2010;5:e8812.
Article
Google Scholar
Evans R, Alessi AM, Bird S, McQueen-Mason SJ, Bruce NC, Brockhurst MA. Defining the functional traits that drive bacterial decomposer community productivity. ISME J. 2017. https://doi.org/10.1038/ismej.2017.22.
Google Scholar
Brulc JM, Antonopoulos DA, Miller ME, Wilson MK, Yannarell AC, Dinsdale EA, et al. Gene-centric metagenomics of the fiber-adherent bovine rumen microbiome reveals forage specific glycoside hydrolases. Proc Natl Acad Sci USA. 2009;106:1948–53.
Article
CAS
Google Scholar
Warnecke F, Luginbühl P, Ivanova N, Ghassemian M, Richardson TH, Stege JT, et al. Metagenomic and functional analysis of hindgut microbiota of a wood-feeding higher termite. Nature. 2007;450:560–5.
Article
CAS
Google Scholar
Zhu L, Wu Q, Dai J, Zhang S, Wei F. Evidence of cellulose metabolism by the giant panda gut microbiome. Proc Natl Acad Sci USA. 2011;108:17714–9.
Article
CAS
Google Scholar
Engel P, Martinson VG, Moran NA. Functional diversity within the simple gut microbiota of the honey bee. Proc Natl Acad Sci USA. 2012;109:11002–7.
Article
CAS
Google Scholar
Pope PB, Denman SE, Jones M, Tringe SG, Barry K, Malfatti SA, et al. Adaptation to herbivory by the Tammar wallaby includes bacterial and glycoside hydrolase profiles different from other herbivores. Proc Natl Acad Sci USA. 2010;107:14793–8.
Article
CAS
Google Scholar
Lamendella R, Domingo JW, Ghosh S, Martinson J, Oerther DB. Comparative fecal metagenomics unveils unique functional capacity of the swine gut. BMC Microbiol. 2011;11:103.
Article
CAS
Google Scholar
Tartar A, Wheeler MM, Zhou X, Coy MR, Boucias DG, Scharf ME. Parallel metatranscriptome analyses of host and symbiont gene expression in the gut of the termite Reticulitermes flavipes. Biotechnol Biofuels. 2009;2:25.
Article
Google Scholar
Urich T, Lanzén A, Qi J, Huson DH, Schleper C, Schuster SC. Simultaneous assessment of soil microbial community structure and function through analysis of the meta-transcriptome. PLoS ONE. 2008;3:e2527.
Article
Google Scholar
Hollister EB, Forrest AK, Wilkinson HH, Ebbole DJ, Tringe SG, Malfatti SA, et al. Mesophilic and thermophilic conditions select for unique but highly parallel microbial communities to perform carboxylate platform biomass conversion. PLoS ONE. 2012;7:e39689.
Article
CAS
Google Scholar
Ghai R, Rodriguez-Valera F, McMahon KD, Toyama D, Rinke R, Oliveira CST, et al. Metagenomics of the water column in the pristine upper course of the Amazon river. PLoS ONE. 2011;6:e23785.
Article
CAS
Google Scholar
Kumar R, Wyman CE. Effect of xylanase supplementation of cellulase on digestion of corn stover solids prepared by leading pretreatment technologies. Bioresour Technol. 2009;100:4203–13.
Article
CAS
Google Scholar
Johnson RL, Schmidt-Rohr K. Quantitative solid-state C-13 NMR with signal enhancement by multiple cross polarization. J Magn Reson. 2014;239:44–9.
Article
CAS
Google Scholar
Bernardinelli OD, Lima MA, Rezende CA, Polikarpov I, deAzevedo ER. Quantitative C-13 MultiCP solid-state NMR as a tool for evaluation of cellulose crystallinity index measured directly inside sugarcane biomass. Biotechnol Biofuels. 2015;8:110.
Article
Google Scholar
Wickholm K, Larsson PT, Iversen T. Assignment of non-crystalline forms in cellulose I by CP/MAS 13C NMR spectroscopy. Carbohydr Res. 1998;312:123–9.
Article
CAS
Google Scholar
Templeton DW, Scarlata CJ, Sluiter JB, Wolfrum EJ. Compositional analysis of lignocellulosic feedstocks. 2. Method uncertainties. J Agric Food Chem. 2010;58:9054–62.
Article
CAS
Google Scholar
Rezende CA, de Lima MA, Maziero P, Deazevedo ER, Garcia W, Polikarpov I. Chemical and morphological characterization of sugarcane bagasse submitted to a delignification process for enhanced enzymatic digestibility. Biotechnol Biofuels. 2011;4:54.
Article
CAS
Google Scholar
Focher B, Marzetti A, Cattaneo M, Beltrame PL, Carniti P. Effects of structural features of cotton cellulose on enzymatic hydrolysis. J Appl Polym Sci. 1981;26:1989–99.
Article
CAS
Google Scholar
Hallac BB, Sannigrahi P, Pu Y, Ray M, Murphy RJ, Ragauskas AJ. Biomass characterization of Buddleja davidii: a potential feedstock for biofuel production. J Agric Food Chem. 2009;57:1275–81.
Article
CAS
Google Scholar
El Hage R, Brosse N, Sannigrahi P, Ragauskas A. Effects of process severity on the chemical structure of Miscanthus ethanol organosolv lignin. Polym Degrad Stab. 2010;95:997–1003.
Article
Google Scholar
Sannigrahi P, Miller SJ, Ragauskas AJ. Effects of organosolv pretreatment and enzymatic hydrolysis on cellulose structure and crystallinity in Loblolly pine. Carbohydr Res. 2010;345:965–70.
Article
CAS
Google Scholar
Foston MB, Hubbell CA, Ragauskas AJ. Cellulose isolation methodology for NMR analysis of cellulose ultrastructure. Materials. 2011;4:1985–2002.
Article
CAS
Google Scholar
Martínez AT, González AE, Valmaseda M, Dale BE, Lambregts MJ, Haw JF. Solid-state NMR studies of lignin and plant polysaccharide degradation by fungi. Holzforschung Int J Biol Chem Phys Technol Wood. 1991;45:49–54.
Google Scholar
Lima MA, Gomez LD, Steele-King CG, Simister R, Bernardinelli OD, Carvalho MA, et al. Evaluating the composition and processing potential of novel sources of Brazilian biomass for sustainable biorenewables production. Biotechnol Biofuels. 2014;7:10.
Article
Google Scholar
Coletta VC, Rezende CA, Conceição FR, Polikarpov I, Guimarães FE. Mapping the lignin distribution in pretreated sugarcane bagasse by confocal and fluorescence lifetime imaging microscopy. Biotechnol Biofuels. 2013;6:43.
Article
CAS
Google Scholar
Finn RD, Clements J, Eddy SR. HMMER web server: interactive sequence similarity searching. Nucleic Acids Res. 2011;39:W29–37.
Article
CAS
Google Scholar
Yin Y, Mao X, Yang J, Chen X, Mao F, Xu Y. dbCAN: a web resource for automated carbohydrate-active enzyme annotation. Nucleic Acids Res. 2012;40:W445–51.
Article
CAS
Google Scholar
McCleary BV. Measurement of polysaccharide degrading enzymes using chromogenic and colorimetric substrates. Chemistry in Australia. 1991;58:398–401.
CAS
Google Scholar
Watanabe M, Inoue H, Inoue B, Yoshimi M, Fujii T, Ishikawa K. Xylanase (GH11) from Acremonium cellulolyticus: homologous expression and characterization. AMB Express. 2014;4:27.
Article
Google Scholar
Qi M, Wang P, O’Toole N, Barboza PS, Ungerfeld E, Leigh MB, Selinger LB, Butler G, Tsang A, McAllister TA, Forster RJ. Snapshot of the eukaryotic gene expression in muskoxen rumen—a metatranscriptomic approach. PLoS ONE. 2011;6:e20521.
Article
CAS
Google Scholar
Dai X, Tian Y, Li J, Luo Y, Liu D, Zheng H, et al. Metatranscriptomic analyses of plant cell wall polysaccharide degradation by microorganisms in the cow rumen. Appl Environ Microbiol. 2015;81:1375–86.
Article
Google Scholar
Jiménez DJ, Chaves-Moreno D, van Elsas JD. Unveiling the metabolic potential of two soil-derived microbial consortia selected on wheat straw. Sci Rep. 2015;5:13845.
Article
Google Scholar
Alessi AM, Bird SM, Bennett JP, Oates NC, Li Y, Dowle AA, et al. Revealing the insoluble metasecretome of lignocellulose-degrading microbial communities. Sci Rep. 2017;7:2356.
Article
Google Scholar
Heiss-Blanquet S, Fayolle-Guichard F, Lombard V, Hébert A, Coutinho PM, Groppi A, et al. Composting-like conditions are more efficient for enrichment and diversity of organisms containing cellulase-encoding genes than submerged cultures. PLoS ONE. 2016;11:e0167216.
Article
Google Scholar
Mello BL, Alessi AM, McQueen-Mason S, Bruce NC, Polikarpov I. Nutrient availability shapes the microbial community structure in sugarcane bagasse compost-derived consortia. Sci Rep. 2016;6:38781.
Article
CAS
Google Scholar
Yu K, Zhang T. Metagenomic and metatranscriptomic analysis of microbial community structure and gene expression of activated sludge. PLoS ONE. 2012;7:e38183.
Article
CAS
Google Scholar
Pauchet Y, Wilkinson P, Chauhan R, Ffrench-Constant RH. Diversity of beetle genes encoding novel plant cell wall degrading enzymes. PLoS ONE. 2010;5:e15635.
Article
Google Scholar
Colbourne JK, Pfrender ME, Gilbert D, Thomas WK, Tucker A, Oakley TH, et al. The ecoresponsive genome of Daphnia pulex. Science. 2011;331:555–61.
Article
CAS
Google Scholar
Danchin EG, Rosso MN, Vieira P, Almeida-Engler J, Coutinho PM, Henrissat B, et al. Multiple lateral gene transfers and duplications have promoted plant parasitism ability in nematodes. Proc Natl Acad Sci USA. 2010;107:17651–6.
Article
CAS
Google Scholar
Kern M, McGeehan JE, Streeter SD, Martin RN, Besser K, Elias L, et al. Structural characterization of a unique marine animal family 7 cellobiohydrolase suggests a mechanism of cellulase salt tolerance. Proc Natl Acad Sci USA. 2013;110:10189–94.
Article
CAS
Google Scholar
Camilo CM, Polikarpov I. High-throughput cloning, expression and purification of glycoside hydrolases using ligation-independent cloning (LIC). Protein Expr Purif. 2014;99:35–42.
Article
CAS
Google Scholar
Bacic A, Fincher GB, Stone BA. Chemistry, biochemistry, and biology of (1–3)-beta-glucans and related polysaccharides. 1st ed. New York: Elsevier; 2009.
Google Scholar
Wood PJ, Weisz J, Blackwell BA. Structural studies of (1–3), (1–4)-beta-d-glucans by c(13)-nuclear magnetic-resonance spectroscopy and by rapid analysis of cellulose-like regions using high-performance anion-exchange chromatography of oligosaccharides released by lichenase. Cereal Chem. 1994;71:301–7.
CAS
Google Scholar
Sarethy IP, Saxena Y, Kapoor A, Sharma M, Sharma SK, Gupta V, et al. Alkaliphilic bacteria: applications in industrial biotechnology. J Ind Microbiol Biotechnol. 2011;38:769–90.
Article
CAS
Google Scholar
Knob A, Carmona EC. Purification and characterization of two extracellular xylanases from Penicillium sclerotiorum: a novel acidophilic xylanase. Appl Biochem Biotechnol. 2010;162:429–43.
Article
CAS
Google Scholar
Chang L, Ding M, Bao L, Chen Y, Zhou J, Lu H. Characterization of a bifunctional xylanase/endoglucanase from yak rumen microorganisms. Appl Microbiol Biotechnol. 2011;90:1933–42.
Article
CAS
Google Scholar
Amel BD, Nawel B, Khelifa B, Mohammed G, Manon J, Salima KG, et al. Characterization of a purified thermostable xylanase from Caldicoprobacter algeriensis sp. nov. strain TH7C1(T). Carbohydr Res. 2016;419:60–8.
Article
CAS
Google Scholar
Kataoka M, Akita F, Maeno Y, Inoue B, Inoue H, Ishikawa K. Crystal structure of Talaromyces cellulolyticus (formerly known as Acremonium cellulolyticus) GH family 11 xylanase. Appl Biochem Biotechnol. 2014;174:1599–612.
Article
CAS
Google Scholar
Jänis J, Hakanpää J, Hakulinen N, Ibatullin FM, Hoxha A, Derrick PJ, et al. Determination of thioxylo-oligosaccharide binding to family 11 xylanases using electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry and X-ray crystallography. FEBS J. 2005;272:2317–33.
Article
Google Scholar
Vardakou M, Dumon C, Murray JW, Christakopoulos P, Weiner DP, Juge N, et al. Understanding the structural basis for substrate and inhibitor recognition in eukaryotic GH11 xylanases. J Mol Biol. 2008;375:1293–305.
Article
CAS
Google Scholar
Wakarchuk WW, Campbell RL, Sung WL, Davoodi J, Yaguchi M. Mutational and crystallographic analyses of the active site residues of the Bacillus circulans xylanase. Protein Sci. 1994;3:467–75.
Article
CAS
Google Scholar
Paës G, Berrin JG, Beaugrand J. GH11 xylanases: structure/function/properties relationships and applications. Biotechnol Adv. 2012;30:564–92.
Article
Google Scholar
Valenzuela SV, Lopez S, Biely P, Sanz-Aparicio J, Pastor FI. The Glycoside hydrolase family 8 reducing-end xylose-releasing exo-oligoxylanase Rex8A from Paenibacillus barcinonensis BP-23 is active on branched xylooligosaccharides. Appl Environ Microbiol. 2016;82:5116–24.
Article
CAS
Google Scholar
Juturu V, Wu JC. Microbial xylanases: engineering, production and industrial applications. Biotechnol Adv. 2012;30:1219–27.
Article
CAS
Google Scholar
Qing Q, Yang B, Wyman CE. Xylooligomers are strong inhibitors of cellulose hydrolysis by enzymes. Bioresour Technol. 2010;101:9624–30.
Article
CAS
Google Scholar
Bennet JW, Lasure LL. Growth Media. In: Bennett JW, Lasure LL, editors. More gene manipulation in fungi. New York: Elsevier; 1991. p. 441–57.
Chapter
Google Scholar
Griffiths RI, Whiteley AS, O’Donnell AG, Bailey MJ. Rapid method for coextraction of DNA and RNA from natural environments for analysis of ribosomal DNA- and rRNA-based microbial community composition. Appl Environ Microbiol. 2000;66:5488–91.
Article
CAS
Google Scholar
Caporaso JG, Lauber CL, Walters WA, Berg-Lyons D, Lozupone CA, Turnbaugh PJ, et al. Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. Proc Natl Acad Sci USA. 2011;108:4516–22.
Article
CAS
Google Scholar
Fierer N, Jackson JA, Vilgalys R, Jackson RB. Assessment of soil microbial community structure by use of taxon-specific quantitative PCR assays. Appl Environ Microbiol. 2005;71:4117–20.
Article
CAS
Google Scholar
Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114–20.
Article
CAS
Google Scholar
Kopylova E, Noe L, Touzet H. SortMeRNA: fast and accurate filtering of ribosomal RNAs in metatranscriptomic data. Bioinformatics. 2012;28:3211–7.
Article
CAS
Google Scholar
Pruesse E, Quast C, Knittel K, Fuchs BM, Ludwig W, Peplies J, et al. SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB. Nucleic Acids Res. 2007;35:7188–96.
Article
CAS
Google Scholar
Gardner PP, Daub J, Tate J, Moore BL, Osuch IH, Griffiths-Jones S, et al. Rfam: wikipedia, clans and the “decimal” release. Nucleic Acids Res. 2011;39:D141–5.
Article
CAS
Google Scholar
Grabherr MG, Haas BJ, Yassour M, Levin JZ, Thompson DA, Amit I, et al. Full-length transcriptome assembly from RNA-Seq data without a reference genome. Nat Biotechnol. 2011;29:644–52.
Article
CAS
Google Scholar
Ismail WM, Ye Y, Tang H. Gene finding in metatranscriptomic sequences. BMC Bioinform. 2014;15(Suppl 9):S8.
Article
Google Scholar
Roberts A, Pachter L. Streaming fragment assignment for real-time analysis of sequencing experiments. Nat Methods. 2013;10:71–3.
Article
CAS
Google Scholar
Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods. 2012;9:357–9.
Article
CAS
Google Scholar
Huson DH, Auch AF, Qi J, Schuster SC. MEGAN analysis of metagenomic data. Genome Res. 2007;17:377–86.
Article
CAS
Google Scholar
Anders S, Pyl PT, Huber W. HTSeq—a Python framework to work with high-throughput sequencing data. Bioinformatics. 2015;31:166–9.
Article
CAS
Google Scholar
Kanehisa M, Goto S. KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 2000;28:27–30.
Article
CAS
Google Scholar
Kanehisa M, Sato Y, Morishima K. BlastKOALA and GhostKOALA: KEGG tools for functional characterization of genome and metagenome sequences. J Mol Biol. 2016;428:726–31.
Article
CAS
Google Scholar
Aslanidis C, Dejong PJ. Ligation-independent cloning of PCR products (LIC-PCR). Nucleic Acids Res. 1990;18:6069–74.
Article
CAS
Google Scholar
Michael RG, Joseph S. Molecular cloning: a laboratory manual. 4th ed. New York: Cold Spring Harbor; 2012.
Laemmli UK. Cleavage of structural proteins during the assembly of the head of bacteriophage T4. Nature. 1970;227:680–5.
Article
CAS
Google Scholar
Sievers F, Wilm A, Dineen D, Gibson TJ, Karplus K, Li W, et al. Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal Omega. Mol Syst Biol. 2011;7:539.
Article
Google Scholar
Miller GL. Use of dinitrosalicylic acid reagent for determination of reducing sugar. Anal Chem. 1959;31:426–8.
Article
CAS
Google Scholar
Sluiter A, Hames B, Ruiz R, Scarlata C, Sluiter J, Templeton D. In: Determination of sugars, byproducts, and degradation products in liquid fraction process samples. NREL/TP-510-42623. 2008. http://www.nrel.gov/docs/gen/fy08/42623.pdf. Accessed 28 Apr 2016.
Selig M, Weiss N, Ji Y. In: Enzymatic Saccharification of lignocellulosic biomass. NREL/TP-510-42629. 2008. http://www.nrel.gov/docs/gen/fy08/42629.pdf. Accessed 28 Apr 2016.
Guimarães BG, Sanfelici L, Neuenschwander RT, Rodrigues F, Grizolli WC, Raulik MA, et al. The MX2 macromolecular crystallography beamline: a wiggler X-ray source at the LNLS. J Synchrotron Radiat. 2009;16:69–75.
Article
Google Scholar
Kabsch W. XDS. Acta Crystallogr D Biol Crystallogr. 2010;66:125–32.
Article
CAS
Google Scholar
McCoy AJ, Grosse-Kunstleve RW, Adams PD, Winn MD, Storoni LC, Read RJ. Phaser crystallographic software. J Appl Crystallogr. 2007;40:658–74.
Article
CAS
Google Scholar
Adams PD, Afonine PV, Bunkóczi G, Chen VB, Davis IW, Echols N, et al. PHENIX: a comprehensive Python-based system for macromolecular structure solution. Acta Crystallogr D Biol Crystallogr. 2010;66:213–21.
Article
CAS
Google Scholar
Emsley P, Cowtan K. Coot: model-building tools for molecular graphics. Acta Crystallogr D Biol Crystallogr. 2004;60:2126–32.
Article
Google Scholar
Chen VB, Arendall WB, Headd JJ, Keedy DA, Immormino RM, Kapral GJ, et al. MolProbity: all-atom structure validation for macromolecular crystallography. Acta Crystallogr D Biol Crystallogr. 2010;66:12–21.
Article
CAS
Google Scholar
Berlemont R, Allison SD, Weihe C, Lu Y, Brodie EL, Martiny JBH, et al. Cellulolytic potential under environmental changes in microbial communities from grassland litter. Front Microbiol. 2014;5:639.
Article
Google Scholar