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GLBRC's Publications

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Publications

When it comes to interdisciplinary collaboration, the titles of GLBRC publications speak for themselves. Each new year of operation has seen more publications from multiple labs that span the four Research Areas, accelerating the Center's production of the basic research that generates technology to convert cellulosic biomass to advanced biofuels.

Publications

Winter memory throughout the plant kingdom: different paths to flowering

Frédéric Bouché; Daniel P. Woods; Richard M. Amasino

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2017

14-3-3 protein mediates plant seed oil biosynthesis through interaction with AtWRI1

Wei Ma; Que Kong; Jenny J. Mantyla; Yang Yang; John B. Ohlrogge; C. Benning

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2016

Plant 14-3-3 proteins are phosphopeptide-binding proteins, belonging to a large family of proteins involved in numerous physiological processes including primary metabolism, although knowledge about the function of 14-3-3s in plant lipid metabolism is sparse. WRINKLED1 (WRI1) is a key transcription factor that governs plant oil biosynthesis. At present, AtWRI1-interacting partners remain largely unknown. Here, we show that 14-3-3 proteins are able to interact with AtWRI1, both in yeast and plant cells. Transient co-expression of 14-3-3- and AtWRI1-encoding cDNAs led to increased oil biosynthesis in Nicotiana benthamiana leaves. Stable transgenic plants overproducing a 14-3-3 protein also displayed increased seed oil content. Co-production of a 14-3-3 protein with AtWRI1 enhanced the transcriptional activity of AtWRI1. The 14-3-3 protein was found to increase the stability of AtWRI1. A possible 14-3-3 binding motif was identified in one of the two AP2 domains of AtWRI1, which was also found to be critical for the interaction of AtWRI1 with an E3 ligase linker protein. Thus, we hypothesize a regulatory mechanism by which the binding of 14-3-3 to AtWRI1 interferes with the interaction of AtWRI1 and the E3 ligase, thereby protecting AtWRI1 from degradation. Taken together, our studies identified AtWRI1 as a client of 14-3-3 proteins and provide insights into a role of 14-3-3 in mediating plant oil biosynthesis. This article is protected by copyright. All rights reserved.

3D sorghum reconstructions from depth images identify QTL regulating shoot architecture

Ryan F. McCormick; Sandra K. Truong; John E. Mullet

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2016

Dissecting the genetic basis of complex traits is aided by frequent and non-destructive measurements. Advances in range imaging technologies enable the rapid acquisition of three-dimensional (3D) data from an imaged scene. A depth camera was used to acquire images of Sorghum bicolor, an important grain, forage, and bioenergy crop, at multiple developmental timepoints from a greenhouse-grown recombinant inbred line population. A semi-automated software pipeline was developed and used to generate segmented, 3D plant reconstructions from the images. Automated measurements made from 3D plant reconstructions identified quantitative trait loci (QTL) for standard measures of shoot architecture such as shoot height, leaf angle, and leaf length and for novel composite traits such as shoot compactness. The phenotypic variability associated with some of the QTL displayed differences in temporal prevalence; for example, alleles closely linked with the sorghum Dwarf3 gene, an auxin transporter and pleiotropic regulator of both leaf inclination angle and shoot height, influence leaf angle prior to an effect on shoot height. Furthermore, variability in composite phenotypes that measure overall shoot architecture, such as shoot compactness, is regulated by loci underlying component phenotypes like leaf angle. As such, depth imaging is an economical and rapid method to acquire shoot architecture phenotypes in agriculturally important plants like sorghum to study the genetic basis of complex traits.

BdCESA7, BdCESA8, and BdPMT utility promoter constructs for targeted expression to secondary cell-wall-forming cells of grasses

Deborah L. Petrik; Cynthia L. Cass; Dharshana Padmakshan; Cliff E. Foster; John P. Vogel; Steven D. Karlen; John Ralph; John C. Sedbrook

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2016

Utility vectors with promoters that confer desired spatial and temporal expression patterns are useful tools for studying gene and cellular function and for industrial applications. To target the expression of DNA sequences of interest to cells forming plant secondary cell walls, which generate most of the vegetative biomass, upstream regulatory sequences of the Brachypodium distachyon lignin biosynthetic gene BdPMT and the cellulose synthase genes BdCESA7 and BdCESA8 were isolated and cloned into binary vectors designed for Agrobacterium-mediated transformation of monocots. Expression patterns were assessed using the beta-glucuronidase gene GUSPlus and X-glucuronide staining. All three promoters showed strong expression levels in stem tissue at the base of internodes where cell wall deposition is most active, in both vascular bundle xylem vessels and tracheids, and in interfascicular tissues, with expression less pronounced in developmentally older tissues. In leaves, BdCESA7 and BdCESA8 promoter-driven expression was strongest in leaf veins, leaf margins, and trichomes; relatively weaker and patchy expression was observed in the epidermis. BdPMT promoter-driven expression was similar to the BdCESA promoters expression patterns, including strong expression in trichomes. The intensity and extent of GUS staining varied considerably between transgenic lines, suggesting that positional effects influenced promoter activity. Introducing the BdPMT and BdCESA8 Open Reading Frames into BdPMT and BdCESA8 utility promoter binary vectors, respectively, and transforming those constructs into Brachypodium pmt and cesa8 loss-of-function mutants resulted in rescue of the corresponding mutant phenotypes. This work therefore validates the functionality of these utility promoter binary vectors for use in Brachypodium and likely other grass species. The identification, in Bdcesa8-1 T-DNA mutant stems, of an 80% reduction in crystalline cellulose levels confirms that the BdCESA8 gene is a secondary-cell-wall-forming cellulose synthase.

FUSCA3 activates triacylglycerol accumulation in Arabidopsis seedlings and tobacco BY2 cells

Meng Zhang; Xia Cao; Qingli Jia; John Ohlrogge

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2016

Triacylglycerol (TAG) is the main storage lipid in plant seeds and the major form of plant oil used for food and, increasingly, for industrial and biofuel applications. Several transcription factors, including FUSCA3 (At3g26790, FUS3), are associated with embryo maturation and oil biosynthesis in seeds. However, the ability of FUS3 to increase TAG biosynthesis in other tissues has not been quantitatively examined. Here, we evaluated the ability of FUS3 to activate TAG accumulation in non-seed tissues. Overexpression of FUS3 driven by an estradiol-inducible promoter increased oil contents in Arabidopsis seedlings up to 6% of dry weight; more than 50 fold over controls. Eicosenoic acid, a characteristic fatty acid of Arabidopsis seed oil, accumulated to over 20% of fatty acids in cotyledons and leaves. These large increases depended on added sucrose, although without sucrose TAG increased 3-4 fold. Inducing the expression of FUS3 in tobacco BY2 cells also increased TAG accumulation, and co-expression of FUS3 and diacylglycerol acyltransferase 1 (DGAT1) further increased TAG levels to 4% of dry weight. BY2 cell growth was not altered by FUS3 expression, although Arabidopsis seedling development was impaired, consistent with the ability of FUS3 to induce embryo characteristics in non-seed tissues. Microarrays of Arabidopsis seedlings revealed that FUS3 overexpression increased expression of a higher proportion of genes involved in TAG biosynthesis than genes involved in fatty acid biosynthesis or other lipid pathways. Together these results provide additional insights into FUS3 functions in TAG metabolism and suggest complementary strategies for engineering vegetative oil accumulation. This article is protected by copyright. All rights reserved.

In silico whole genome sequencer and analyzer (iWGS): a computational pipeline to guide the design and analysis of de novo genome sequencing studies

Xioafan Zhou; David Peris; Jacek Kominek; Cletus P. Kurtzman; Chris T. Hittinger; Antonis Rokas

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2016

The availability of genomes across the tree of life is highly biased toward vertebrates, pathogens, human disease models, and organisms with relatively small and simple genomes. Recent progress in genomics has enabled the de novo decoding of the genome of virtually any organism, greatly expanding its potential for understanding the biology and evolution of the full spectrum of biodiversity. The increasing diversity of sequencing technologies, assays, and de novo assembly algorithms have augmented the complexity of de novo genome sequencing projects in non-model organisms. To reduce the costs and challenges in de novo genome sequencing projects and streamline their experimental design and analysis, we developed iWGS (in silico Whole Genome Sequencer and Analyzer), an automated pipeline for guiding the choice of appropriate sequencing strategy and assembly protocols. iWGS seamlessly integrates the four key steps of a de novo genome sequencing project: data generation (through simulation), data quality control, de novo assembly, and assembly evaluation and validation. The last three steps can also be applied to the analysis of real data. iWGS is designed to enable the user to have great flexibility in testing the range of experimental designs available for genome sequencing projects, and supports all major sequencing technologies and popular assembly tools. Three case studies illustrate how iWGS can guide the design of de novo genome sequencing projects and evaluate the performance of a wide variety of user-specified sequencing strategies and assembly protocols on genomes of differing architectures. iWGS, along with a detailed documentation, is freely available at https://github.com/zhouxiaofan1983/iWGS.

Lactobacillus casei as a biocatalyst for biofuel production

Elena Vinay-Lara; Song Wang; Lina Bai; Ekkarat Phrommao; Jeff R. Broadbent; James L. Steele

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2016

Microbial fermentation of sugars from plant biomass to alcohols represents an alternative to petroleum-based fuels. The optimal biocatalyst for such fermentations needs to overcome hurdles such as high concentrations of alcohols and toxic compounds. Lactic acid bacteria, especially lactobacilli, have high innate alcohol tolerance and are remarkably adaptive to harsh environments. This study assessed the potential of five Lactobacillus casei strains as biocatalysts for alcohol production. L. casei 12A was selected based upon its innate alcohol tolerance, high transformation efficiency and ability to utilize plant-derived carbohydrates. A 12A derivative engineered to produce ethanol (L. casei E1) was compared to two other bacterial biocatalysts. Maximal growth rate, maximal optical density and ethanol production were determined under conditions similar to those present during alcohol production from lignocellulosic feedstocks. L. casei E1 exhibited higher innate alcohol tolerance, better growth in the presence of corn stover hydrolysate stressors, and resulted in higher ethanol yields.

Zymomonas mobilis as a model system for production of biofuels and biochemicals

Shihui Yang; Qiang Fei; Yaoping Zhang; Lydia M. Contreras; Sagar M. Utturkar; Steven D. Brown; Michael E. Himmel; Min Zhang

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2016

Zymomonas mobilis is a natural ethanologen with many desirable industrial biocatalyst characteristics. In this review, we will discuss work to develop Z. mobilis as a model system for biofuel production from the perspectives of substrate utilization, development for industrial robustness, potential product spectrum, strain evaluation and fermentation strategies. This review also encompasses perspectives related to classical genetic tools and emerging technologies in this context.

A novel pathway for triacylglycerol biosynthesis is responsible for the accumulation of massive quantities of glycerolipids in the surface wax of Bayberry (Myrica pensylvanica) fruit

Jeffrey P. Simpson; John B. Ohlrogge

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2016

Bayberry fruits synthesize an extremely thick and unusual layer of crystalline surface wax that accumulates to 30% of fruit dry weight, the highest reported surface lipid accumulation in plants. The composition is also striking, consisting of completely saturated triacylglycerol, diacylglycerol and monoacylglycerol with palmitate and myristate acyl chains. To gain insight into the unique properties of Bayberry wax synthesis we examined the chemical and morphological development of the wax layer, monitored wax biosynthesis through [14C]-radiolabeling, and sequenced the transcriptome. Radiolabeling identified sn-2 MAG as the first glycerolipid intermediate. The kinetics of [14C]-DAG and [14C]-TAG accumulation and the regiospecificity of their [14C]-acyl chains indicated distinct pools of acyl donors and that final TAG assembly occurs outside of cells. The most highly expressed genes were associated with production of cutin, whereas transcripts for conventional TAG synthesis were >50-fold less abundant. The biochemical and expression data together indicate that Bayberry surface glycerolipids are synthesized by a previously unknown pathway for TAG synthesis that is related to cutin biosynthesis. The combination of a unique surface wax and massive accumulation may aid understanding of how plants produce and secrete non-membrane glycerolipids, and also how to engineer alternative pathways for lipid production in non-seeds.

A superstructure representation, generation, and modeling framework for chemical process synthesis

WenZhao Wu; Carlos A. Henao; Christos T. Maravelias

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2016

We present a framework for the efficient representation, generation, and modeling of superstructures for process synthesis. First, we develop a new representation based on three basic elements: units, ports, and conditioning streams. Second, we present four rules based on “minimal” and “feasible” component sets for the generation of simple superstructures containing all feasible embedded processes. Third, in terms of modeling, we develop a modular approach, and formulate models for each basic element. We also present a canonical form of element models using input/output variables and constrained/free variables. The proposed methods provide a coherent framework for superstructure-based process synthesis, allowing efficient model generation and modification. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3199–3214, 2016

A superstructure-based framework for simultaneous process synthesis, heat integration, and utility plant design

Lingxun Kong; Murat Sen; Carlos A. Henao; James A. Dumesic; Christos T. Maravelias

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2016

We propose a superstructure optimization framework for process synthesis with simultaneous heat integration and utility plant design. Processing units in the chemical plant can be modeled using rigorous unit models or surrogate models generated from experimental results or off-line calculations. The utility plant subsystem includes multiple steam types with variable temperature and pressure. For the heat integration subsystem, we consider variable heat loads of process streams as well as variable intervals for the utilities. To enhance the solution of the resulting mixed-integer nonlinear programming models, we develop (1) new methods for the calculation of steam properties, (2) algorithms for variable bound calculation, and (3) systematic methods for the generation of redundant constraints. The applicability of our framework is illustrated through a biofuel case study which includes a novel non-enzymatic hydrolysis technology and new separation technologies, both of which are modeled based on experimental results.

Accuracy of genomic prediction in switchgrass (Panicum virgatum L.) improved by accounting for linkage disequilibrium

Guillaume P. Ramstein; Joseph Evans; Shawn M. Kaeppler; Robert B. Mitchell; Kenneth P. Vogel; Robin Buell; Michael D. Casler

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2016

Switchgrass is a relatively high-yielding and environmentally sustainable biomass crop, but further genetic gains in biomass yield must be achieved to make it an economically viable bioenergy feedstock. Genomic selection is an attractive technology to generate rapid genetic gains in switchgrass and meet the goals of a substantial displacement of petroleum use with biofuels in the near future. In this study, we empirically assessed prediction procedures for genomic selection in two different populations consisting of 137 and 110 half-sib families of switchgrass, tested in two locations in the United States for three agronomic traits: dry matter yield, plant height and heading date. Marker data was produced for the families' parents by exome capture sequencing, generating up to 141,030 polymorphic markers with available genomic-location and annotation information. We evaluated prediction procedures that varied not only by learning schemes and prediction models, but also by the way the data was preprocessed to account for redundancy in marker information. More complex genomic prediction procedures were generally not significantly more accurate than the simplest procedure, likely due to limited population sizes. Nevertheless, a highly significant gain in prediction accuracy was achieved by transforming the marker data through a marker correlation matrix. Our results suggest that marker-data transformations and, more generally, the account of linkage disequilibrium among markers, offer valuable opportunities for improving prediction procedures in genomic selection. Some of the achieved prediction accuracies should motivate implementation of genomic selection in switchgrass breeding programs./p>.

Actionable knowledge for ecological intensification of agriculture

Willemien Geertsema; Walter A.H. Rossing; Douglas A. Landis; Felix J.J.A. Bianchi; Paul C.J. van Rijn; Joop H.J. Schaminée; Teja Tscharntke; Wopke van der Werf

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2016

Ecological intensification of agriculture (EI) aims to conserve and promote biodiversity and the sustainable use of associated ecosystem services to support resource-efficient production. In many cases EI requires fundamental changes in farm and landscape management as well as the organizations and institutions that support agriculture. Ecologists can facilitate EI by engaging with stakeholders and, in the process, by generating “actionable knowledge” (that is, knowledge that specifically supports stakeholder decision making and consequent actions). Using three case studies as examples, we propose four principles whereby science can improve the delivery of actionable knowledge for EI: (1) biodiversity conservation helps to ensure the delivery of ecosystem services, (2) management of ecosystem services benefits from a landscape-scale approach, (3) ecosystem service trade-offs and synergies need to be articulated, and (4) EI is associated with complex social dynamics involving farmers, governments, researchers, and related institutions. These principles have the potential to enhance adoption of EI, but institutional and policy challenges remain.

An engineered solvent system for sugar production from lignocellulosic biomass using biomass derived γ-valerolactone

Ali Hussain Motagamwala; Wangyun Won; Christos T. Maravelias; James A. Dumesic

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2016

γ-Valerolactone (GVL) is a biomass-derived solvent which completely solubilizes all fractions of lignocellulosic biomass, leading to the recovery of polysaccharides (cellulose and hemicellulose) as soluble carbohydrates at high yields (>70%) without the use of expensive reagents, like enzymes and ionic liquids. Biological upgrading of carbohydrates to biofuels or bio-based chemicals requires that the carbohydrates are separated from GVL. We demonstrate that an engineered solvent system consisting of GVL, water and an organic co-solvent is mono-phasic at the temperatures used for biomass fractionation (e.g., 160 °C) and is bi-phasic at lower temperatures (e.g., room temperature). The advantage of using this engineered solvent system is that the carbohydrates are spontaneously separated from organic solvent components into an aqueous hydrolysate stream, thereby avoiding the need for expensive and potentially hazardous separation processes, such as operation at elevated pressures required for separation using liquid CO2. We also show that the organic co-solvent can be selected from an array of organic components, leading to a trade-off between the efficacy of carbohydrate separation and the ‘greenness’ of the solvent. We show further that toluene is a promising co-solvent component, and techno-economic analyses of the process, wherein toluene is used as a co-solvent, lead to a minimum selling price of ethanol of $3.10 per gallon of gasoline equivalent.

An essential role of caffeoyl shikimate esterase in monolignol biosynthesis in Medicago truncatula

Chan Ma Ha; Luis Escamilla-Trevino; Juan Carlos Ser Yarce; Hoon Kim; John Ralph; Fang Chen; Richard A. Dixon

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2016

Biochemical and genetic analyses have identified caffeoyl shikimate esterase (CSE) as an enzyme in the monolignol biosynthesis pathway in Arabidopsis thaliana (Vanholme et al., 2013b), although the generality of this finding has been questioned. Here we show the presence of CSE genes and associated enzyme activity in barrel medic (Medicago truncatula, dicot, Leguminosae), poplar (Populus deltoides, dicot, Salicaceae), and switchgrass (Panicum virgatum, monocot, Poaceae). Loss of function of CSE in transposon insertion lines of M. truncatula results in severe dwarfing, altered development, reduction in lignin content, and preferential accumulation of hydroxyphenyl units in lignin, indicating that the CSE enzyme is critical for normal lignification in this species. However, the model grass Brachypodium distachyon and corn (Zea mays) do not possess orthologs of the currently characterized CSE genes, and crude protein extracts from stems of these species exhibit only week esterase activity with caffeoyl shikimate. Our results suggest that the reaction catalyzed by CSE may not be essential for lignification in all plant species. This article is protected by copyright. All rights reserved.

Applications of constraint-based models for biochemical production

Cameron Cotten; Jennifer L. Reed

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2016

Biofuels are metabolic products, and knowledge of how metabolism operates is critical to understanding and improving biofuel production by microorganisms. Constraint-based metabolic modeling has been an important technique to broaden and deepen our knowledge of microbial metabolism and regulation. Genome-scale metabolic models enable global analysis of microbial metabolism by considering all metabolic reactions simultaneously. Genome-scale metabolic reconstructions are comprehensive listings of all the reactions, compounds, and genes that are involved in cellular metabolism for a particular organism. Constraint-based modeling methods use the information in metabolic reconstructions to predict intracellular fluxes and design strains for chemical and biofuel production. Recently, constraint-based modeling has been successful in designing a number of chemical production strains.

Balancing biofuel production and biodiversity: Harvesting frequency effects on production and community composition in planted tallgrass prairie

Karen A. Stahlheber; Bradley Watson; Timothy L. Dickson; Ryan Disney; Katherine L. Gross

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2016

Native perennial grasslands have been proposed as a source of feedstocks for the production of second-generation lignocellulosic biofuels in the Midwestern USA. Although the consequences of some management decisions for biomass production and plant community composition are well understood (e.g. fertilization), less is known about the effects of harvesting frequency. We compared a once- and twice-annual harvesting regime at two restored prairies in southwestern Michigan established with identical seed mixtures as part of a large-scale bioenergy experiment. We determined biomass production and species composition in experimental plots and also measured the availability of light, inorganic nitrogen and soil moisture. The plant communities that established at the two sites differed markedly in composition and there was little evidence of convergence after five years. At the site dominated by warm-season C4 grasses, single harvests generally produced more biomass than double harvests. By contrast, biomass production was unaffected by harvesting at the more diverse site. Contrary to our prediction that a summer harvest would increase diversity, we found small and subtle effects on plant community composition. This may be due in part to the timing of our harvest treatment. Our results suggest that a single, end-of-season harvest is the best practice for maximizing biomass production in prairies, especially at sites where warm-season grasses dominate. However, at more diverse sites, two harvests can produce the same total biomass and may support other beneficial ecosystem services. This study indicates that in the short term, double harvests are unlikely to affect plant species diversity or community composition in prairie plantings.

Bioenergy cropping systems that incorporate native grasses stimulate growth of plant-associated soil microbes in the absence of nitrogen fertilization

Lawrence G. Oates; David S. Duncan; Gregg R. Sanford; Chao Liang; Randall D. Jackson

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2016

The choice of crops and their management can strongly influence soil microbial communities and their processes. We used lipid biomarker profiling to characterize how soil microbial composition of five potential bioenergy cropping systems diverged from a common baseline five years after they were established. The cropping systems we studied included an annual system (continuous no-till corn) and four perennial crops (switchgrass, miscanthus, hybrid poplar, and restored prairie). Partial- and no-stover removal were compared for the corn system, while N-additions were compared to unfertilized plots for the perennial cropping systems. Arbuscular mycorrhizal fungi (AMF) and Gram-negative biomass was higher in unfertilized perennial grass systems, especially in switchgrass and prairie. Gram-positive bacterial biomass decreased in all systems relative to baseline values in surface soils (0–10 cm), but not subsurface soils (10–25 cm). Overall microbial composition was similar between the two soil depths. Our findings demonstrate the capacity of unfertilized perennial cropping systems to recreate microbial composition found in undisturbed soil environments and indicate how strongly agroecosystem management decisions such as N addition and plant community composition can influence soil microbial assemblages.

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