Biological conversion assay using Clostridium phytofermentans to estimate plant feedstock quality
© Lee et al; licensee BioMed Central Ltd. 2012
Received: 27 September 2011
Accepted: 8 February 2012
Published: 8 February 2012
There is currently considerable interest in developing renewable sources of energy. One strategy is the biological conversion of plant biomass to liquid transportation fuel. Several technical hurdles impinge upon the economic feasibility of this strategy, including the development of energy crops amenable to facile deconstruction. Reliable assays to characterize feedstock quality are needed to measure the effects of pre-treatment and processing and of the plant and microbial genetic diversity that influence bioconversion efficiency.
We used the anaerobic bacterium Clostridium phytofermentans to develop a robust assay for biomass digestibility and conversion to biofuels. The assay utilizes the ability of the microbe to convert biomass directly into ethanol with little or no pre-treatment. Plant samples were added to an anaerobic minimal medium and inoculated with C. phytofermentans, incubated for 3 days, after which the culture supernatant was analyzed for ethanol concentration. The assay detected significant differences in the supernatant ethanol from wild-type sorghum compared with brown midrib sorghum mutants previously shown to be highly digestible. Compositional analysis of the biomass before and after inoculation suggested that differences in xylan metabolism were partly responsible for the differences in ethanol yields. Additionally, we characterized the natural genetic variation for conversion efficiency in Brachypodium distachyon and shrub willow (Salix spp.).
Our results agree with those from previous studies of lignin mutants using enzymatic saccharification-based approaches. However, the use of C. phytofermentans takes into consideration specific organismal interactions, which will be crucial for simultaneous saccharification fermentation or consolidated bioprocessing. The ability to detect such phenotypic variation facilitates the genetic analysis of mechanisms underlying plant feedstock quality.
Lignocellulosic plant biomass is comprised mostly of cell walls, which are a complex composite of proteins, lignin, and polysaccharides; the latter holds promise as raw material for biofuel production. The most abundant polysaccharide in the majority of tissues is cellulose, which exists as unbranched chains containing up to 15,000 β-(1,4)-linked glucose molecules . By contrast, the shorter hemicelluloses are chemically and physically more complex . The most abundant forms exist as glucan chains much shorter than cellulose or β-(1,4)-linked xylose, both with diverse side-chain substitutions of arabinose, galactose, fucose, xylose, or glucuronic acid. Biological conversion relies on an organism, such as a unicellular fungus or bacterium, which will convert these simple sugars to high-energy chemicals such as ethanol or butanol. Unlike seed starch or the soluble sugars found in phloem sap, the fermentable sugars found in cell walls are recalcitrant to extraction. The composition and interaction between the polysaccharides and lignin strongly influence their amenability for conversion to renewable fuels. Whereas lignification has extensive merits for the plant, it has adverse effects on the digestibility by ruminant and biofuel-generating microbes. For example, up to 50% of the variation in in vitro digestibility of commercial maize hybrids can be attributed to differences in their lignin content . Lignin is composed ofthree monolignols: p-coumaryl, coniferyl, and sinapyl alcohols, which polymerize to form p-hydroxyphenyl, guaiacyl, and syringyl phenylpropanoid units, respectively . The biosynthesis of alcohol monomers occurs in a specialized branch of phenylpropanoid metabolism, through which successive reductions, hydroxylations and methylations can occur. Crosslinking lignin with polysaccharides in the secondary cell walls of vascular tissue increases hydrophobicity, and thus gives these functional tissues the capacity to efficiently conduct water . Concurrently, the polysaccharides are less accessible to enzymatic digestion or mechanical penetration by potential pathogens . The pathway for lignin biosynthesis is well conserved among vascular plants, and involves at least 10 gene families, including CAD (cinnamyl alcohol dehydrogenase) and COMT. Each step in the lignin pathway has been perturbed in various species, resulting in changes in lignin content, composition, and, in many cases, digestibility [7, 8].
Genetic diversity of plant cell-wall properties within species is evident in the decades of plant breeding for improved feed and forage quality in crops such as maize, sorghum, and alfalfa [9, 10]. The merits of animal feed have been tested frequently in vivo, either by evaluating animal performance in response to a particular feeding regimen, or by estimating digestibility in vivo using livestock with fistulae . With the latter approach, the gastrointestinal tract of a surgically prepared animal is sampled to measure the remaining biomass. An equivalent in vitro method was developed using rumen fluid inoculum from fistulated cows . Digestibility is estimated through analysis of the organic matter lost from the simulated ruminant gut conditions after 4 days of incubation. The throughput of this approach is considerably higher than in vivo, and begins to meet the needs of traditional plant-breeding efforts and genetics research. High-throughput assays to estimate feed and forage quality parameters also include compositional measurements of cellulose , total lignin and monomer content [14, 15], and hemicellulose content and composition [16, 17], which also serve as valid measurements of biofuel feedstock quality. Although the parallels between digestibility and amenability to conversion to biofuels might be apparent, industry standards for biofuel feedstock quality are still needed.
Regardless of species, all new crop varieties must meet certain standards for industrial-processing efficiency and consumer-market quality. Beyond the expectation of high biomass yield with few inputs on marginal land, conversion quality standards for energy crops have yet to be defined by the biofuels industry. Recently, several methods, including some high-throughout platforms, have been established that treat plant samples with hydrolytic enzyme cocktails, such as fungal cellulase and xylanase/xylosidase, then assay for total sugars as a measurement of digestibility [18–22]. This approach can be taken one step further, using translational assays that mimic industrial simultaneous saccharification and fermentation (SSF) paradigms, in which the liberated sugars from the polymers can then be fermented by Saccharomyces cerevisiae to measure total ethanol yield [23, 24].
A distinct and promising approach to cellulosic biofuel production is consolidated bioprocessing (CBP) technology for conversion of biomass to fuel. CBP could lead to a significant reduction in processing costs, greater than the reductions gained from any other potential improvement, such as reducing enzyme loading, eliminating pre-treatment, or improving the processes associated with converting sugars to ethanol . The recently discovered anaerobic forest soil bacterium Clostridium phytofermentans may further enhance the efficiency of CBP. This organism produces ethanol as its major fermentation byproduct during growth on all substrates tested, including cellulose, hemicellulose, pectin, and starch , as well as switchgrass, corn stover, and pulp wastes ([Warnick and Leschine, unpublished data). Unlike S. cerevisiae, of which only engineered strains are capable of limited pentose utilization ,C. phytofermentans directly converts a wide array of fermentable components of biomass to ethanol, including cellulose, pectin, polygalacturonic acid, starch, xylan, arabinose, cellobiose, fructose, galactose, gentiobiose, glucose, lactose, maltose, mannose, ribose, and xylose . Without the addition of exogenous cellulases and xylanases, CPB using C. phytofermentans can yield approximately 70% of the yield of SSF using engineered S. cerevisiae.
In this paper, we report on an assay that provides the ability to measure the influence of variation in biomass composition, pre-treatment methods, and conversion processes on digestibility, and thereby determine the potential effects of numerous variables in biofuel production. In addition to sorghum, feedstock quality was evaluated for cultivars of shrub willow (Salix spp.) and Brachypodium distachyon accessions to demonstrate the applicability of this assay for a wide range of feedstocks, from woody crops to herbaceous grasses. The C. phytofermentans bioassay provides a direct and quantitative means of assessing feedstock quality, both in terms of digestibility and conversion.
Effect of feedstock concentration and time on ethanol concentration
Effect of lignin mutants on Clostridium phytofermentans polysaccharide metabolism and ethanol concentration
Effect of feedstock particle size on ethanol concentration
Among the many pleiotropic effects of bmr mutations in sorghum is an effect on the rigidity of cell walls, reflected as increased lodging of field-grown plants . That being the case, it might be possible that differences in digestibility, measured by ethanol concentration, are a product of differences between genotypes in the particle-size distribution after grinding.
The effect of genetic variation on the biological conversion efficiency of sorghum landraces, Brachypodium distachyon accessions, and shrub-willow germplasm
Mean values for supernatant ethanol concentration of S1 families derived from Sorghum bicolor ssp. Accessions 3d after inoculation with Clostridium phytofermentans.
Ethanol, mg ethanol/g* feedstock†
Genetic effects account for most of the variation measured by the feedstock quality assay.
Source of variation
Accessions tested, %a
Genotype × experiment
Mean values for supernatant ethanol concentration of shrub willow (Salix spp.) cultivars 5d after inoculation with Clostridium phytofermentans.
Ethanol, mg ethanol/g feedstock*
S. sacchalinensis/S. miyabeana
S. viminalis/S. miyabeana
S. viminalis/S. sacchalinensis/S. miyabeana
S. sacchalinensis/S. miyabeana
S. purpurea/S. miyabeana
S. viminalis hybrid
S. koriyangi /S. viminalis
S. purpurea/S. miyabeana
S. viminalis/S. miyabeana
S. viminalis/S. miyabeana
Some key crop species, such as maize, wheat, and rice, have been domesticated from about 10,000 years ago, and have been under continuous selection for important agronomic and quality traits. Whereas progenitor species of many crops are unrecognizable from their domesticated counterparts, many of our potential energy crops are at best just a few crosses away from the wild accessions. Miscanthus, switchgrass, energy cane, and willow are just beginning the process of domestication. Thus, there is equivalent potential for improvement of fuel yield per unit of land through breeding of energy crops, but this must be accomplished in an abbreviated timeframe to have an effect on global climate change [32, 33]. One trait to improve upon is the ease of biomass deconstruction to simple sugars that are suitable for conversion to a liquid fuel . Many species have demonstrated genetic variation in digestibility for both forage quality and enzymatic digestion, thus traditional plant breeding facilitated by suitable phenotypic assays, such as the bioconversion approach described here, will lead to a more efficient biofuels industry [3, 35]. The overall content and composition of cell-wall lignin has proven to be a significant determining factor for lignocellulosic biomass digestibility [7, 8]. In the 1920s, agronomists identified the first lignin mutants in maize as genotypes with characteristic browning of the leaf midrib, hence the mutant name 'brown midrib' . Negative perturbation of multiple points in the lignin biosynthetic pathway results in increased digestibility in numerous species including maize, sorghum, switchgrass, tall fescue, alfalfa, tobacco, and poplar [4, 7]. In both sorghum and maize, mutations in the CAD or COMT genes have been identified as causes for the brown midrib phenotype [37–39].
The bioconversion assay described here was developed using a well-characterized set of sorghum bmr NILs, the same samples previously described by Dien. . In this study, the Klason lignin content was 15% lower in the bmr-6 and bmr-12 single mutants than in wild-type sorghum, and nearly twice as low (27%) in the bmr-6/bmr-12 double mutant. Interestingly, no other differences were between the NILs were seen for carbohydrate content or non-lignin-associated measures of in vitro digestibility, such as neutral or acid detergent fiber . Therefore, the differential effects of C. phytofermentans inoculation on NILs is not due to the total amount of digestible sugars in the NILs, but rather the accessibility of those polysaccharides to enzymatic digestion, which is therefore strongly influenced by lignin content. Fermentation of the same material by S. cerevisiae after dilute acid pre-treatment and cellulase and β-glucosidase enzymatic digestion produced improvements in ethanol-conversion efficiency of 11% and 17% for the single and double mutants, respectively . The differences in ethanol production by NILs digested by S. cerevisiae were far less pronounced than those digested with C. phytofermentans. Considering that xylose yield was roughly constant across the NILs, and that S. cerevisiae is capable of fermenting hexoses only, it is likely that the differences in ethanol yield were due to differential enzymatic release of glucose. C. phytofermentans digests plant biomass with secreted cellulolytic enzymes, and subsequently imports and metabolizes pentoses and hexoses. Thus, ethanol yield is a combined measure of the digestibility of hemicelluloses and cellulose.
To gain a greater understanding into why ethanol yields might be greater with the bmr mutants, we assayed the polysaccharide content both before and after inoculation, using a comprehensive collection of 147 glycan-directed monoclonal antibodies to quantify changes in most major classes of cell-wall polysaccharides . Considering the minute quantities of pectins in sorghum stems , we focused on changes in the abundance of xylan, which accounted for a substantial proportion of the overall biomass content . The relative amount of extractable xylan differed between the NILs, as did the difference in extractable xylan metabolized by C. phytofermentans. Therefore, the increased quantities of ethanol produced from the bmr mutants is in part due to the increased accessibility of xylan to hydrolysis.
Although it was apparent that there are genetic differences in plant properties that influence feedstock digestibility, several analyses of sorghum, maize, and alfalfa lignin mutants revealed genotype × chemical pre-treatment interaction effects. In other words, the magnitude of the differences between genotypes or even their rank order will change depending on the method of pre-treatment. Enzymatic release of glucose from the maize lignin mutant bm1 was equivalent to that of wild type after alkali pre-treatment, but significantly greater after acid pre-treatment . Relative to untreated sorghum, the difference between wild-type sorghum and the sorghum lignin mutants bmr-3 and bmr-12 diminished after dilute acid pre-treatment . In the same study, mutations in other loci resulting in a bmr phenotype produced little or no change in response to pre-treatment. Similarly, the magnitude of the difference in enzymatic saccharification between wild-type alfalfa and plants downregulated for several different lignin genes varied in response to acid pre-treatment . In the case of plants downregulated for CCoAMT, a significant difference from wild type was seen only in the absence of pre-treatment. By contrast, the difference in hydrolysis efficiency between C4H and HCT downregulated plants and wild type was twice as large in the absence of pre-treatment. After treatment with 15% ammonium hydroxide the hydrolysis yield potential of a large panel of sorghum accessions ranged from the same level as that of the untreated sorghum up to an approximately threefold increase over the untreated plants . The goal of pre-treatment is to improve the accessibility of the polysaccharides to hydrolysis . Clearly, there is a complex relationship between efficiency of feedstock utilization and pre-treatment. In this study, we attempted to maximize the ease of conducting the bioconversion quality assay and to maximize the sensitivity of the assay to detect genetic differences. Although small differences in genetic potential may not be relevant in certain industrial scenarios, detection remains important for development of energy crops. Consistent and incremental progress in modern plant breeding is the product of changing the frequencies of alleles with small additive effects. Thus, a sensitive assay is required to detect such variation, and certain pretreatments may diminish sensitivity.
We measured significant genetic variation among collections of two plant taxa considered to have excellent potential as energy crops, sorghum and shrub willow, and a model for grasses, B. distachyon[44–46]. The variation was notable considering that the samples tested by no means represent the overall genetic variation within each taxon. Thus, we would expect a wider range of phenotypic variation with an increase in sample number and diversity. The ethanol yields from sorghum were similar to those from willow, ranging from 26.5 to 39.4 mg ethanol/g feedstock. For willow, no significant correlations were seen between ethanol yield and biomass compositional data (Serapiglia and Smart, unpublished data). Most of the variation could be attributed to genetics rather than to experimental differences; consequently, routine gain from selection could be expected in the range of variation detected. At the same time, the assay could clearly identify differences between major genetic perturbations in biomass composition (typical of the bmr mutations) and continuous variation among natural and segregating populations. The most digestible genotypes from all three biofuel crop taxa yielded approximately 25% more ethanol that the most recalcitrant. This is only slightly less than the differences between wild-type sorghum and the single-gene bmr mutants. The quantity of material tested is well within the amount of stem biomass typically produced by a single plant of rapid-cycling model plants such as Arabidopsis thaliana and B. distachyon. We are currently using this system in a 96-well format, which, combined with a commercial robotics preparation [19, 22], is capable of throughput levels required by a core feedstock testing facility for plant breeding and mutant screens.
In this paper we have described a laboratory assay that quantifies the amount of ethanol produced by C. phytofermentans cultured on plant biomass. This approach may be useful to estimate the potential effects of pre-treatment, conversion methods, and microbial and plant genetic diversity on biofuel manufacturing. The assay is capable of measuring subtle genetic differences within energy crops and the research model species B. distachyon, making it particularly useful for genetic analysis of the mechanisms underlying plant feedstock amenability to biological conversion. The C. phytofermentans bioassay provides a means of assessing feedstock quality in terms of both digestibility and conversion.
Genetic material consisted of Sorghum bicolor 'Atlas' (designated as the wild type for this analysis), and three near-isogenic brown midrib (bmr) mutant lines: bmr-6, bmr-12, and the double mutant bmr-6/bmr-12. Degrained plant samples were collected as previously described  from a single field at the University of Nebraska Agricultural Research and Development Station (Lincoln, NE, USA) in the summer of 2005. Briefly, when all plants reached the hard-dough stage of maturity, samples of all four genotypes were taken from each of two replicate plots arranged in randomized complete blocks. After harvesting by flail chopper, samples were oven-dried at 50°C. In a separate experiment, 17 accessions of S. bicolor subspecies bicolor, Sorghum verticilliflorum, and Sorghum drummondii were collected in the summer of 2010 (Table 1). All but one accession, cultivar RTx430 , are S1 families derived from Plant Introduction accessions obtained from the Plant Genetic Resources Conservation Unit, and represent an array of S. bicolor subspecies diversity. The replicates were composited to create a single sample for each genotype. All plant biomass samples were then washed using a hot ethanol solution to remove free sugars. First, the samples were placed in 50 ml plastic screw cap tubes, filled with 70% v/v ethanol solution, and then incubated at 70° C for 1 hour. After 30 minutes, the supernatant was discarded, replaced with fresh ethanol solution, and returned to the water bath for an additional 30 minutes. Samples were then given a final rinse with a 70% (v/v) methanol solution and subsequently air-dried for 24 hours in a fume hood. Using a 25.0 ml stainless-steel grinding jar (catalog number #02.462.0213; Retsch Inc, Newtown, PA) with one stainless-steel grinding ball of 15 mm in size (catalog number 05.368.0109; Retsch) per jar, samples were homogenized (Mixer Mill MM400; Retsch) for 3 minutes at 30 Hz. Particle-size determinations were made using the USP General Test 786 Method I by analytical sieving. First, 5 g of dry plant tissue was placed on the top of the sieves and the apparatus was covered. The ground plant tissue was then passed through increasingly fine wire-mesh sieves (US standard sieves #80 (177 μm), #120 (125 μm), #160 (88 μm), #230 (62 μm), #270 (53 μm)). The sieves were shaken vigorously for 1 minute, then each sieve was carefully weighed, covered again, and the process resumed until the weight of each fraction was within 5% of the previous measurement. At that time, the fractions in each sieve were carefully collected, and final measurements taken. The weight of each sieve fraction was recorded, and divided by the total weight to determine the percentage each fraction represented.
Dry seeds from five inbred B. distachyon accessions were sown directly into 100 mm pots containing potting mix (#2; Conrad Fafard Inc., Agawa, MA, USA) Growth chamber temperature was maintained at 20°C with a 20 hour light/4 hour dark cycle at a fluence rate of 200 μmol of photons/m2/s, and relative humidity of 68.0 to 68.5. Fully senesced stems were washed and milled as described above. Seed of Bd30-1, Bd3-1, Bd21, and Bd2-3 were kindly provided by David F. Garvin (USDA-ARS) and seed of ABR8 by John Draper (Aberystwyth University, UK).
Shrub willow (Salix spp.) biomass samples from 14 genetically diverse genotypes were selected for conversion-efficiency analysis. These included commercial cultivars selected from controlled intraspecies and interspecies crosses, and unimproved accessions obtained from naturally established stands in northeastern USA and Canada. Biomass was harvested in December 2009 after the third post-coppice season from plants growing in four replicate plots in the 2006 Yield Trial in Constableville, NY, USA. Stems were chipped. and the four replicates pooled. The chips were dried to a constant weight at 65°C and rough-milled using a mill (Wiley mill; Thomas Scientific, Swedesboro, NJ, USA) with a 20-mesh screen. Further fine milling down to a particle size of 0.5 μm was performed using an analytical mill (MF 10; IKA, Willmington, NC, USA). Samples were then milled and washed as described above for sorghum.
C. phytofermentans ISDg (ATCC 700394) was cultured in a defined medium, MQM5.1 (2.0 g/l Na H2PO4, 10.0 g/l K2HPO4, 1.0 g/l (NH4)2SO4, 1.0 g/l L-cysteine hydrochloride monohydrate, 20 ml/l XT solution (5.0 g/l xanthine and 5.0 g/l thymine in 0.06 N NaOH) 10 ml/l AA1 solution (.0 g/l of each of the following amino acids: alanine, arginine, histidine, isoleucine, leucine, methinonine, proline and valine), and 10 ml/l Bach's trace element (BTE) solution ), Resazurin (1 mg/l) was added as an oxidation/reduction indicator. After autoclaving, 10 ml/l CPV3 solution (20 mg/l p-aminobenzoic acid, 1 mg/l biotin, 30 mg/l folinic acid, 80 mg/l nicotinamide, 5 mg/l pantethine, 2 mg/l pyridoxal hydrochloride, 30 mg/l riboflavin, and 10 mg/l thiamine) was added.
The C. phytofermentans inoculum was initially grown in MQM5.1 with 3 g/l cellobiose using the anaerobic techniques described by Hungate  in 10 ml volumes in 18 × 180 mm tubes sealed with neoprene stoppers.
For the biological conversion- quality assay, Hungate tubes, containing 50 mg of plant tissue and 10 ml of MQM5.1 media were inoculated with 0.1 ml of the initial culture. Sorghum and B. distachyon samples were incubated without shaking for 72 hours at 37°C, unless specified otherwise. Willow samples were incubated for 120 hours. At that time, 1.0 ml of each sample supernatant was collected and filtered using a 0.22 μm syringe-driven filter unit (Millipore Corp., Billerica, MA, USA). Samples were separated using an HPLC (Shimadzu Corp., Kyoto, Japan) equipped with a carbohydrate analysis column (300 mm × 7.8 mm; Aminex HPX-87H; Bio-Rad Laboratories, Inc., Hercules, CA, USA) and a refractive-index detector. The column was operated at 30°C with 0.005 N sulfuric acid as the running buffer at a rate of 0.7 ml/min, and 5.0 μL sample injections. Retention time for ethanol (17.84 ± 0.02 minutes), was determined using a commercial mix (Fuel Ethanol Residual Saccharides Mix; catalog number 48468-U; Sigma-Aldrich, St Louis, MO, USA) containing glycerol, glucose, maltotriose, maltose monohydrate, lactic acid, acetic acid, dextrin, and ethanol. Standards were run at the beginning, middle, and end of every distinct HPLC analysis to ensure accuracy and precision of measurements.
Cell-wall extraction and glycome profiling
Approximately 100 mg of wild type and bmr mutant sorghum biomass, either inoculated with C. phytofermentans or uninoculated, were washed sequentially with absolute ethanol and acetone. The biomass materials were dried overnight in a fume hood at room temperature. The dry residues were sequentially extracted with increasingly harsh reagents at suspensions of 10 mg/ml (based on starting biomass weight used) to obtain fractions enriched with cell-wall components. The biomass was first incubated as a suspension in 50 mmol/l ammonium oxalate (pH 5.0) and mixed overnight at room temperature on a shaker. The suspension was then separated by centrifugation at 3400 g for 15 minutes at room temperature. The clear supernatant obtained was decanted, and saved as the ammonium oxalate fraction. The pellet was washed by suspending in the same volume of deionized water, followed by centrifugation as above. The resulting supernatant in the washing step was discarded. The pellet was then subjected to additional sequential extractions using in turn 50 mmol/l sodium carbonate (pH 10) with 0.5% sodium borohydride w/v, 1 mol/l containing 1% sodium borohydride w/v, and 4 mol/l KOH containing 1% sodium borohydride w/v following the same steps as described above to obtain the sodium carbonate, 1 mol/l KOH and 4 mol/l KOH fractions respectively. Both KOH fractions were neutralized using glacial acetic acid. All fractions were dialyzed using molecular-porous membrane tubing (Spectra/Por; Spectrum Laboratories Inc., Rancho Dominguez, CA, USA) with a nominal molecular-weight cut-off (MWCO) of 3,500 against four changes of deionized water (sample:water approximately 1:60) at room temperature for a total of 48 hours, and then lyophilized.
All extracts were first dissolved in deionized water to a concentration of 0.2 mg/ml. Total sugar content of the cell-wall extracts were then determined using the phenol-sulfuric acid method [51, 52]. The extracts were subsequently diluted to the same sugar concentration of 60 μg sugar/ml for loading onto ELISA plates (Costar 3598; Corning Costar Corp., Corning, NY, USA). A sample (50 μL) of each diluted extract was added to each well and allowed to evaporate overnight at 37°C until dry. ELISA was conducted using an array of 147 monoclonal antibodies (see Additional file 1) specific to epitopes from most major groups of plant cell-wall polysaccharides as described previously . ELISA data are presented as heat maps in which antibodies are grouped based on a hierarchical clustering analysis of their binding specificities against a diverse set of plant glycans .
Three or four independent fermentation reactions were sampled at each time for each feedstock sample. Analysis of variance and Scheffé's test were performed using the agricolae package, and Student's t-test using a Bonferroni's correction for multiple comparisons in R v2.11.0. Significance was set a P < 0.05 or rP < 0.01.
List of abbreviations
amino acid solution
Bach's trace element
saccharification and fermentation
This research was supported by Office of Science (BER) Department of Energy Grant DE-FG02-08ER64700DE to SPH and by the BioEnergy Science Center (SP, HM, VB, MGH), which is a US Department of Energy Bioenergy Research Center supported by the Office of Biological and Environmental Research in the DOE Office of Science. We thank Brian Whitcomb (School of Public Health, University of Massachusetts Amherst) for assistance with statistical analysis. We thank Dominick Matos and Jessica Sysopha (Biology Department, University of Massachusetts Amherst) for expert assistance with micrograph image preparation and sample preparation, respectively. The CCRC series of plant glycan-directed antibodies was generated with support from the National Science Foundation Plant Genome Program (DBI-0421683) to MGH. We thank the Plant Genetic Resources Conservation Unit for providing sorghum accessions. We thank George Huber (Department of Chemical Engineering, University of Massachusetts Amherst) and the UMass Biofuels Research Laboratory for generous access to the HPLC equipment.
- Brett CT: Cellulose microfibrils in plants: biosynthesis, deposition, and integration into the cell wall. Int Rev Cytol 2000, 199: 161.View ArticleGoogle Scholar
- Scheller HV, Ulvskov P: Hemicelluloses. Annu Rev Plant Biol 2010,61(1):263-289. 10.1146/annurev-arplant-042809-112315View ArticleGoogle Scholar
- Barriere Y, Guillet C, Goffner D, Pichon M: Genetic variation and breeding strategies for improved cell wall digestibility in annual forage crops. A review. Anim Res 2003,52(3):193-228. 10.1051/animres:2003018View ArticleGoogle Scholar
- Bonawitz ND, Chapple C: The genetics of lignin biosynthesis: connecting genotype to phenotype. Ann Rev Genet 2010, 337-363.Google Scholar
- Grabber JH: How do lignin composition, structure, and cross-linking affect degradability? A review of cell wall model studies. Crop Sci 2005, 45: 820. 10.2135/cropsci2004.0191View ArticleGoogle Scholar
- Xu Z, Zhang D, Hu J, Zhou X, Ye X, Reichel K, Stewart N, Syrenne R, Yang X, Gao P, et al.: Comparative genome analysis of lignin biosynthesis gene families across the plant kingdom. BMC Bioinformatics 2009,10(Suppl 11):S3. 10.1186/1471-2105-10-S11-S3View ArticleGoogle Scholar
- Li X, Weng J-K, Chapple C: Improvement of biomass through lignin modification. Plant J 2008,54(4):569-581. 10.1111/j.1365-313X.2008.03457.xView ArticleGoogle Scholar
- Chen F, Dixon RA: Lignin modification improves fermentable sugar yields for biofuel production. Nat Biotech 2007,25(7):759-761. 10.1038/nbt1316View ArticleGoogle Scholar
- Vogel KP, Jung HG: Genetic modification of herbacious plants for feed and fuel. Crit Rev Plant Sc 2001,20(1):15-49.View ArticleGoogle Scholar
- Hill RR Jr, Shenk JS, Barnes RF: Breeding for yield and quality. In Alfalfa and alfalfa improvement. Edited by: Hanson AA, Barnes DK, Hill RR Jr. Madison: Amer Society of Agronomy; 1988:809-825.Google Scholar
- Scales GH, Streeter CL, Denham AH, Ward GM: A comparison of indirect methods of predicting in vivo digestibility of grazed forage. J Anim Sci 1974,38(1):192-199.Google Scholar
- Tilly J, Terry R: A two stage technique for the in vitro digestion of forage crops. J Br Grassland Soc 1963, 18: 104-111. 10.1111/j.1365-2494.1963.tb00335.xView ArticleGoogle Scholar
- Updegraff D: Semimicro determination of cellulose in biological materials. Anal Biochem 1969,32(3):420-424. 10.1016/S0003-2697(69)80009-6View ArticleGoogle Scholar
- Kirk T, Obst J: Lignin determination. In Methods in Enzymology. Edited by: Wood W, Kellogg S. New York: Academic Press, Inc.; 1988:87-101.Google Scholar
- Hedges JI, Mann DC: The characterization of plant tissues by their lignin oxidation products. Geochim Cosmochim Ac 1979,43(11):1803-1807. 10.1016/0016-7037(79)90028-0View ArticleGoogle Scholar
- Lerouxel O, Choo TS, Seveno M, Usadel B, Faye L, Lerouge P, Pauly M: Rapid structural phenotyping of plant cell wall mutants by enzymatic oligosaccharide fingerprinting. Plant Physiol 2002,130(4):1754-1763. 10.1104/pp.011965View ArticleGoogle Scholar
- Hazen SP, Hawley RM, Davis GL, Henrissat B, Walton JD: Quantitative trait loci and comparative genomics of cereal cell wall composition. Plant Physiol 2003,132(1):263-271. 10.1104/pp.103.020016View ArticleGoogle Scholar
- Studer MH, DeMartini JD, Brethauer S, McKenzie HL, Wyman CE: Engineering of a high-throughput screening system to identify cellulosic biomass, pretreatments, and enzyme formulations that enhance sugar release. Biotechnol Bioeng 2009,105(2):231-238.View ArticleGoogle Scholar
- Santoro N, Cantu S, Tornqvist C-E, Falbel T, Bolivar J, Patterson S, Pauly M, Walton J: A high-throughput platform for screening milligram quantities of plant biomass for lignocellulose digestibility. BioEnerg Res 2010, 3: 93-102. 10.1007/s12155-009-9074-6View ArticleGoogle Scholar
- Chundawat S, Balan V, Dale B: High-throughput microplate technique for enzymatic hydrolysis of lignocellulosic biomass. Biotechnol Bioeng 2008, 99: 1281-1294. 10.1002/bit.21805View ArticleGoogle Scholar
- Navarro D, Couturier M, da Silva G, Berrin J-G, Rouau X, Asther M, Bignon C: Automated assay for screening the enzymatic release of reducing sugars from micronized biomass. Microb Cell Fact 2010,9(1):58. 10.1186/1475-2859-9-58View ArticleGoogle Scholar
- Gomez L, Whitehead C, Barakate A, Halpin C, McQueen-Mason S: Automated saccharification assay for determination of digestibility in plant materials. Biotechnol Biofuels 2010,3(1):23. 10.1186/1754-6834-3-23View ArticleGoogle Scholar
- Dien B, Sarath G, Pedersen J, Sattler S, Chen H, Funnell-Harris D, Nichols N, Cotta M: Improved sugar conversion and ethanol yield for forage sorghum ( Sorghum bicolor L. Moench) lines with reduced lignin contents. BioEnerg Res 2009,2(3):153-164. 10.1007/s12155-009-9041-2View ArticleGoogle Scholar
- Fu C, Mielenz JR, Xiao X, Ge Y, Hamilton CY, Rodriguez M, Chen F, Foston M, Ragauskas A, Bouton J, et al.: Genetic manipulation of lignin reduces recalcitrance and improves ethanol production from switchgrass. Proc Natl Acad Sci USA 2011.Google Scholar
- Lynd LR, Laser MS, Bransby D, Dale BE, Davison B, Hamilton R, Himmel M, Keller M, McMillan JD, Sheehan J, et al.: How biotech can transform biofuels. Nat Biotech 2008,26(2):169-172. 10.1038/nbt0208-169View ArticleGoogle Scholar
- Warnick TA, Methe BA, Leschine SB: Clostridium phytofermentans sp. nov., a cellulolytic mesophile from forest soil. Int J Syst Evol Microbiol 2002,52(4):1155-1160. 10.1099/ijs.0.02125-0View ArticleGoogle Scholar
- van Zyl W, Lynd L, den Haan R, McBride J: Consolidated bioprocessing for bioethanol production using Saccharomyces cerevisiae . Biofuels 2007, 205-235.View ArticleGoogle Scholar
- Jin M, Balan V, Gunawan C, Dale BE: Consolidated bioprocessing (CBP) performance of Clostridium phytofermentans on AFEX-treated corn stover for ethanol production. Biotechnol Bioeng 2011. n/a-n/aGoogle Scholar
- Pattathil S, Avci U, Baldwin D, Swennes AG, McGill JA, Popper Z, Bootten T, Albert A, Davis RH, Chennareddy C, et al.: A comprehensive toolkit of plant cell wall glycan-directed monoclonal antibodies. Plant Physiol 2010,153(2):514-525. 10.1104/pp.109.151985View ArticleGoogle Scholar
- Smith BG, Harris PJ: The polysaccharide composition of Poales cell walls: Poaceae cell walls are not unique. Biochem Syst Ecol 1999, 27: 33. 10.1016/S0305-1978(98)00068-4View ArticleGoogle Scholar
- Pedersen JF, Vogel KP, Funnell DL: Impact of reduced lignin on plant fitness. Crop Sci 2005,45(3):812-819. 10.2135/cropsci2004.0155View ArticleGoogle Scholar
- Jessup R: Development and status of dedicated energy crops in the United States. In Vitro Cell Dev-Pl 2009,45(3):282-290. 10.1007/s11627-009-9221-yView ArticleGoogle Scholar
- Heaton EA, Flavell RB, Mascia PN, Thomas SR, Dohleman FG, Long SP: Herbaceous energy crop development: recent progress and future prospects. Curr Opin Biotechnol 2008, 19: 202. 10.1016/j.copbio.2008.05.001View ArticleGoogle Scholar
- Ragauskas AJ, Williams CK, Davison BH, Britovsek G, Cairney J, Eckert CA, Frederick WJ Jr, Hallett JP, Leak DJ, Liotta CL, et al.: The path forward for biofuels and biomaterials. Science 2006,311(5760):484-489. 10.1126/science.1114736View ArticleGoogle Scholar
- Sarath G, Akin D, Mitchell R, Vogel K: Cell-wall composition and accessibility to hydrolytic enzymes is differentially altered in divergently bred switchgrass ( Panicum virgatum L.) genotypes. Appl Biochem Biotechnol 2008,150(1):1-14. 10.1007/s12010-008-8168-5View ArticleGoogle Scholar
- Jorgensen JR: Brown midrib in maize and its linkage relationships. J Am Soc Agron 1931, 23: 549-557. 10.2134/agronj1931.00021962002300070005xView ArticleGoogle Scholar
- Xin Z, Wang ML, Barkley NA, Burow G, Franks C, Pederson G, Burke J: Applying genotyping (TILLING) and phenotyping analyses to elucidate gene function in a chemically induced sorghum mutant population. BMC Plant Biol 2008, 8: 103. 10.1186/1471-2229-8-103View ArticleGoogle Scholar
- Sattler SE, Saathoff AJ, Haas EJ, Palmer NA, Funnell-Harris DL, Sarath G, Pedersen JF: A nonsense mutation in a cinnamyl alcohol dehydrogenase gene Is responsible for the sorghum brown midrib6 phenotype. Plant Physiol 2009,150(2):584-595. 10.1104/pp.109.136408View ArticleGoogle Scholar
- Vignols F, Rigau J, Torres M, Capellades M, Puigdomenech P: The brown midrib3 ( bm3 ) mutation in maize occurs in the gene encoding caffeic acid O-methyltransferase. Plant Cell 1995,7(4):407-416.View ArticleGoogle Scholar
- Hatfield RD, Wilson JR, Mertens DR: Composition of cell walls isolated from cell types of grain sorghum stems. J Sci Food Agric 1999,79(6):891-899. 10.1002/(SICI)1097-0010(19990501)79:6<891::AID-JSFA304>3.0.CO;2-#View ArticleGoogle Scholar
- Saballos A, Vermerris W, Rivera L, Ejeta G: Allelic association, chemical characterization and saccharification properties of brown midrib mutants of sorghum ( Sorghum bicolor (L.) Moench). BioEnerg Res 2008,1(3):193-204. 10.1007/s12155-008-9025-7View ArticleGoogle Scholar
- Vandenbrink JP, Delgado MP, Frederick JR, Feltus FA: A sorghum diversity panel biofuel feedstock screen for genotypes with high hydrolysis yield potential. Ind Crop Products 2010,31(3):444-448. 10.1016/j.indcrop.2010.01.001View ArticleGoogle Scholar
- Kumar P, Barrett DM, Delwiche MJ, Stroeve P: Methods for pretreatment of lignocellulosic biomass for efficient hydrolysis and biofuel production. Ind Eng Chem Res 2009,48(8):3713-3729. 10.1021/ie801542gView ArticleGoogle Scholar
- Initiative TIB: Genome sequencing and analysis of the model grass Brachypodium distachyon . Nature 2010,463(7282):763-768. 10.1038/nature08747View ArticleGoogle Scholar
- Smart LB, Cameron KD: Genetic improvement of willow ( Salix spp.) as a dedicated bioenergy crop. In Genetic Improvement of Bioenergy Crops. Edited by: Vermerris W. NY: Springer Science; 2008:347-376.Google Scholar
- Rooney WL, Blumenthal Jr, Bean B, Mullet JE: Designing sorghum as a dedicated bioenergy feedstock. Biofpr 2007,1(2):147-157.Google Scholar
- Pedersen JF, Toy JJ, Funnell DL, Sattler SE, Oliver AL, Grant RA: Registration of BN611, AN612, BN612, and RN613 sorghum genetic stocks with stacked -6 and -12 genes. J Plant Reg 2008,2(3):258-262. 10.3198/jpr2008.01.0065crsView ArticleGoogle Scholar
- Miller R: Registration of RTx430 sorghum parental line. Crop Sci 1984, 24: 1224.View ArticleGoogle Scholar
- Cote RJ, Gherna RL: Nutrition and media. In Methods for General and Molecular Microbiology. Edited by: Gerhardt P, Murray RGE, Wood WA, Krieg NR. Washington, DC: American Society for Microbiology; 1994:155-178.Google Scholar
- Hungate RE: A roll tube method for cultivation of strict anaerobes. Methods Microbiol 1969, 3B: 117-132.View ArticleGoogle Scholar
- DuBois M, Gilles KA, Hamilton JK, Rebers PA, Smith F: Colorimetric method for determination of sugars and related substances. Anal Chem 1956,28(3):350-356. 10.1021/ac60111a017View ArticleGoogle Scholar
- Masuko T, Minami A, Iwasaki N, Majima T, Nishimura S-I, Lee YC: Carbohydrate analysis by a phenol-sulfuric acid method in microplate format. Anal Biochem 2005,339(1):69-72. 10.1016/j.ab.2004.12.001View ArticleGoogle Scholar
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