Prospecting for Energy-Rich Renewable Raw Materials: \u3cem\u3eAgave\u3c/em\u3e Leaf Case Study

Plant biomass from different species is heterogeneous, and this diversity in composition can be mined to identify materials of value to fuel and chemical industries. Agave produces high yields of energy-rich biomass, and the sugar-rich stem tissue has traditionally been used to make alcoholic beverages. Here, the compositions of Agave americana and Agave tequilana leaves are determined, particularly in the context of bioethanol production. Agave leaf cell wall polysaccharide content was characterized by linkage analysis, non-cellulosic polysaccharides such as pectins were observed by immuno-microscopy, and leaf juice composition was determined by liquid chromatography. Agave leaves are fruit-like--rich in moisture, soluble sugars and pectin. The dry leaf fiber was composed of crystalline cellulose (47-50% w/w) and non-cellulosic polysaccharides (16-22% w/w), and whole leaves were low in lignin (9-13% w/w). Of the dry mass of whole Agave leaves, 85-95% consisted of soluble sugars, cellulose, non-cellulosic polysaccharides, lignin, acetate, protein and minerals. Juice pressed from the Agave leaves accounted for 69% of the fresh weight and was rich in glucose and fructose. Hydrolysis of the fructan oligosaccharides doubled the amount of fermentable fructose in A. tequilana leaf juice samples and the concentration of fermentable hexose sugars was 41-48 g/L. In agricultural production systems such as the tequila making, Agave leaves are discarded as waste. Theoretically, up to 4000 L/ha/yr of bioethanol could be produced from juice extracted from waste Agave leaves. Using standard Saccharomyces cerevisiae strains to ferment Agave juice, we observed ethanol yields that were 66% of the theoretical yields. These data indicate that Agave could rival currently used bioethanol feedstocks, particularly if the fermentation organisms and conditions were adapted to suit Agave leaf composition

Identification of barley mutants and characterisation of their mixed-linkage (1,3;1,4)-~-glucan (MLG)

Barley is one of Australia’s main cereal crops, used for human consumption, animal feed, malting and brewing. Mixed-linkage (1,3;1,4)-β-glucan (MLG) is the major fibre constituent of barley grain that has positive impacts on human health and negative impacts on animal diet and the brewing industry. Thus, the modification of MLG content in barley grain in both high and low directions could have a potential market value. However, there are still few available details with regards to the molecular control of MLG content in barley grain and the regulatory genes controlling its biosynthesis other than the CslF6 gene. A better understanding of MLG biosynthesis would be valuable to researchers and industry alike and historically the use of mutants has been a powerful tool in dissecting complex processes. Three barley mutants with altered MLG profiles are thus used here to try and further our understanding of biosynthesis of this important cell wall polysaccharide. The work carried out in this project was designed to characterise and analyse three barley mutants showing reduced MLG content in mature grain known as 45(7), M-737 and Chalky Glen with their parents Flagship, Minerva and Glen, respectively. For the three MLG barley mutants, the reduction of grain MLG content was associated with perturbations in grain phenotypic traits, grain biochemical composition and/or internal grain morphology compared to their parents. MLG contents % (w/w) were significantly less in the three mutants compared to their parents during grain development. At a molecular level and throughout grain development, CslF6 transcript levels were outstandingly lower in the three mutants compared to abundant transcript levels in their parents. In addition, high transcript abundance of the Glb1 gene, especially in 45(7) and M-737 mutants, in mid and late grain development was also detected. Genetic variation within the CslF6 gene is rare since no differences were found in the putative promoter region, coding region and GT-motif region of the CslF6 gene that could explain the differences in grain MLG content, suggesting other regulatory sequences or proteins, acting independently or in combination are likely to be involved in the observed differences in the grain MLG content between the three mutants and their parents. Accordingly, a transcriptome analysis was performed for the two mutants 45(7) and M-737 and their parents Flagship and Minerva respectively, at 10, 14 and 18 days after pollination (DAP) of grain development to identify compromised molecular pathways, differentially expressed genes (DEGs), and sequence polymorphisms that might contribute to the low MLG phenotype in grain. In 45(7), the expression of the CslF6 gene was not significantly reduced, suggesting other factors could cause the phenotype. Sequence polymorphism analysis of 45(7) identified a point mutation in the soluble starch synthase III (SSIII) gene and the nuclear factor YB1 (NF-YB1) transcriptional regulator, both of which have previously been implicated in grain composition. Altered NF-YB1 activity might explain the reduced transcript levels of several starch biosynthesis genes including FLOURY ENDOSPERM6 (FLO6), consistent with a reduction in grain starch content such that the effect on grain MLG content is pleiotropic. A third mutation was detected in the myosin heavy chain gene that could affect MLG shuttling to the plasma membrane, accordingly reducing grain MLG content. In M-737, CslF6 expression was significantly reduced and was accompanied by a mutation in the aldose-1-epimerase gene. This enzyme is implicated in D-galactose uptake and reduced activity could potentially reduce the biosynthesis of the sugar donors (substrate availability) required for grain MLG biosynthesis. These findings could be used for designing crosses and planning marker selection strategies in mapping populations, and subsequently providing greater opportunity for quantitative trait locus (QTL) detection. The M-737 mutant was chosen for a micro-malting study as it displays good malting characteristics as judged by the low MLG content compared to the parent cultivar Minerva. This study quantified MLG content and the activity of the (1,3;1,4)-β-glucanase enzyme during the micro-malting experiment and a number of micro-malting quality traits of the final malt, including hot water extract, wort viscosity, wort MLG, free amino nitrogen and soluble protein were measured. During micro-malting stages, MLG content % (w/w) was significantly less in M-737 than Minerva, however the relative rate of hydrolysis was similar. M-737 and Minerva showed no significant differences in their (1,3;1,4)-β-glucanase enzyme activity during micro-malting stages, suggesting that a lower abundance of MLG does not translate into faster hydrolysis of MLG during germination. In terms of malt quality traits, M-737 exhibited better traits than Minerva, including significantly low wort viscosity and wort MLG, and significantly higher hot water extract, soluble protein and free amino nitrogen. The three low MLG mutants and their parents were used as a training set to develop a new screening method based on Fourier transform mid infrared (FTMIR) spectroscopy. Scans of non-embryo half grain were significantly (p-value <0.05) correlated with the Megazyme assay (r = 0.903). FTMIR spectroscopy was subsequently used to screen 300 M2 Compass mutant lines, resulting in the identification of 41 M3 mutants of interest via univariate and multivariate analysis. Megazyme assays confirmed that MLG levels were altered in these mutants. MLG quantification of M4 grain confirmed two mutants (182-5 and 1669-1) that showed significantly low MLG content in grain. This method also showed a strong correlation between absorbance and MLG content for six oat (Avena sativa) breeding lines that were tested. Thus, the FTMIR method appears to be a promising method for detecting variation in MLG content and with additional optimisation, this method could be used for research and breeding programs.Thesis (Ph.D.) -- University of Adelaide, School of Agriculture, Food and Wine, 202

Flowchart outlining the steps taken to process and analyze <i>Agave</i> leaves.

<p>Flowchart outlining the steps taken to process and analyze <i>Agave</i> leaves.</p

Quantification of juice sugars from <i>A</i>. <i>americana</i> leaves and <i>A</i>. <i>tequilana</i> leaves and stem.

<p>The amount of glucose, fructose and sucrose present in both raw and TFA-treated juice samples (a). Data are presented as g/L. Additional peaks for which there are no known standards were detected in the chromatograms of raw juice (b). <i>A</i>. <i>tequilana</i> stem juice is used as a representative of all three, very similar, chromatograms for the raw and treated samples. Chromatogram of TFA-treated <i>A</i>. <i>tequilana</i> stem juice (c). Chromatogram of fructanase-treated <i>A</i>. <i>tequilana</i> stem juice (d).</p

Fermentation of <i>Agave tequilana</i> leaf juice using <i>Saccharomyces cerevisiae</i>.

<p>Two strains of <i>S</i>. <i>cerevisiae</i> were used to ferment untreated <i>A</i>. <i>tequilana</i> leaf juice with a starting sugar concentration of 41.4 g/ L and WSC concentration of 30.0 g/L. Conversion efficiencies are based on a maximum conversion rate of sugar to ethanol of 51.1% w/w.</p><p>Fermentation of <i>Agave tequilana</i> leaf juice using <i>Saccharomyces cerevisiae</i>.</p

<i>Agave</i> processing and moisture content.

<p>Whole leaves were crushed, producing juice and wet bagasse fractions (a). These fractions were dried separately to calculate moisture content. Data is presented as percentage of fresh (wet) starting mass (% w/w). The values shown in gray are used to calculate total moisture content. The distribution of leaf fresh mass (% w/w) in <i>A</i>. <i>americana</i> and <i>A</i>. <i>tequilana</i> (b).</p

Theoretical ethanol yields for lignocellulosic feedstocks.

<p>*Calculations were based on the compositional values listed in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0135382#pone.0135382.t001" target="_blank">Table 1</a> [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0135382#pone.0135382.ref005" target="_blank">5</a>].</p><p>^{^}Calculations based on data obtained in this study.</p><p>^#Assumes that 56.7% dry w/w of the whole 3 year old plants is leaf material [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0135382#pone.0135382.ref008" target="_blank">8</a>].</p><p>^†Assumes that juice accounted for 69% of plant wet weight; <i>A</i>. <i>americana</i> leaf was 88.5% w/w water; and <i>A</i>. <i>tequilana</i> leaf was 83.3% w/w water.</p><p>^‡ Tonnes of wet weight rather than dry weight. Units for data are given in table headings. Constants for ethanol calculations are consistent with the National Renewable Energy Laboratory Theoretical Ethanol Yield Calculator [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0135382#pone.0135382.ref073" target="_blank">73</a>]: 1.111 kg monomeric C6 sugar per 1 kg polymeric C6 polymer (glucan, fructan); 1.1363 kg monomeric C5 sugar per 1 kg polymeric C5 polymer (xylan, arabinan); 0.51 kg of ethanol produced from 1 kg of sugar. Productivity per hectare is based on previous studies [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0135382#pone.0135382.ref018" target="_blank">18</a>,<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0135382#pone.0135382.ref074" target="_blank">74</a>–<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0135382#pone.0135382.ref078" target="_blank">78</a>].</p><p>Theoretical ethanol yields for lignocellulosic feedstocks.</p

Different fractions of <i>Agave</i> material.

<p>Two year old <i>A</i>. <i>tequilana</i> plants in Australia (a). Partially dried leaves reduced to smaller particle sizes using a ball mill (b). Juice extracted from leaves using an experimental shredder (c). Dried fibers after extraction from wet bagasse (d).</p

Carbohydrates in fiber-enriched fractions from <i>Agave</i> leaves.

<p>Data are presented as a percentage of dry weight (% w/w).</p><p>*Includes mannose, rhamnose, glucuronic acid, galacturonic acid and galactose</p><p>Carbohydrates in fiber-enriched fractions from <i>Agave</i> leaves.</p

Comparison of potential biofuel feedstocks.

<p>Cellulose is the major source of glucose in feedstocks. Non-cellulosic polysaccharides contribute some fermentable hexose (glucose and galactose) and pentose (xylose and arabinose) sugars. Lignin is a non-sugar polymer that inhibits cell wall degradation and subsequent fermentation. Data are presented as percentage of dry weight (% w/w). Data may be accessed through the United States Department of Energy, Energy Efficiency & Renewable Energy, Biomass Feedstock Composition and Property Database, 2013 [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0135382#pone.0135382.ref005" target="_blank">5</a>].</p><p>Comparison of potential biofuel feedstocks.</p