Biochemical Conversion

Biochemical conversion of switchgrass straw, and other lignocellulosic biomass, to biofuel typically has the following three major steps: pretreatment, saccharification, and fuel synthesis. Biochemical conversion is also known as direct microbial conversion and biological conversion. First, the harvested and chopped biomass is pretreated to breakdown its microstructure and improve accessibility of the polysaccharides. Conventional pretreatments include a combination of heat, pressure, acid, and/or base treatment (Agbor et al. 2011). Use and recycling of ionic liquids is an example of a new and highly effective pretreatment (Li et al. 2010). In the second step, enzymes are added to the neutralized slurry to breakdown the cellulose and other polysaccharides into monosaccharides, a process known as saccharification. Finally, in the fuel synthesis step, microbial metabolism, typically fermentation, is enlisted to convert the sugars into fuel. The prototype fuel is ethanol, though recent research has demonstrated synthesis from sugars of higher energy-content fuels, including butanol, alkanes, and fatty acid esters, also known as biodiesel (Peralta-Yahya et al. 2010). In this chapter, we will provide essential information about each of these steps with a focus on how they relate in particular to the use of switchgrass as a bioenergy crop.

While higher and more consistent biomass yields for switchgrass and other bioenergy crops are essential, currently the cost and inefficiency of saccharification represent the greatest barriers to wide-spread commercial realization of lignocellulosic biofuel production (Lynd et al. 2008). This chapter will review the major research efforts dedicated toward optimizing lignocellulose composition and the enzymes that degrade it toward improving sugar yields from grasses. Research on plants has focused on understanding the synthesis and regulation of plant lignocellulose toward developing plant biomass that results in the highest yields of monosaccharides per unit mass (Carpita 2012; Youngs et al. 2012). Of course, stature and plant health must be maintained in the quality-optimized genotypes. Research on enzymes that hydrolyze lignocellulose has delved into understanding their basic mechanisms and the biophysics of their interactions with biomass. Moreover, researchers continue to use advanced methodologies to identify and generate additional hydrolase diversity. These two fields intersect with the overexpression of lignocellulolytic enzymes by plants themselves. This and other approaches to consolidate the steps of biofuel production are thought of as being important ways to improve biochemical biofuel production efficiency (Lynd et al. 2008). We note that the production of co-products, i. e., valuable uses for biomass components that do not become fuel, is extremely important in the life cycle analysis of the economic and environmental feasibility of biofuel production (Farrell et al. 2006; Lynd et al. 2008), especially via biological conversion, but will not be covered here.

DNA molecular markers started with restriction fragment length polymorphism (RFLP), which refers to the differences of restriction sites between two or more DNA samples. After a DNA sample is digested into pieces by restriction enzymes, the resulting restriction fragments are separated according to their lengths and detected by hybridization with labeled nucleotide probes. Although now largely outdated, RFLP was the first-generation DNA profiling technique used for genetic diversity analysis and linkage map construction in switchgrass (Hultquist et al. 1996; Missaoui et al. 2005b, 2006).

Next widely used first-generation marker system is random amplified polymorphic DNA (RAPD). RAPD does not require any information of the DNA sequence of a target organism, thus it is cheaper to develop than RFLP. It has been used for switchgrass genetic diversity and evolution studies (Gunter et al. 1996; Casler et al. 2007). One major disadvantage of RAPD is its low reproducibility and instability due to slippage and low specificity of random primer binding.

Simple sequence repeat (SSR) markers, also known as microsatellites, are repeats of short nucleotide sequences, usually equal to or less than six bases in length per core repeat. SSRs are highly variable in the number of repeats at a specific locus and distributed throughout the eukaryotic genomes. In addition, SSR markers are amplified using the polymerase chain reaction (PCR) with fewer experimental steps and a lower cost and smaller amount of DNA templates compared with RFLP, thus allowing for the rapid generation of data from a relatively small amount of plant tissues. They have been popularly used as the second-generation DNA markers in construction of linkage maps, QTL (quantitative trait loci) mapping, gene cloning, germplasm diversity study, cultivar identification, and marker — assisted selection.

The SSR markers in switchgrass are available. Tobias and colleagues reported the primer sequences of 32 effective SSR markers developed from a switchgrass expressed sequence tag (EST) project (Tobias et al. 2005,

2006) . Later, Tobias et al. (2008) developed additional 830 EST-derived SSR markers. Not long after, 185 and 1,030 genomic SSRs were developed from sequencing SSR-enriched genomic libraries by two research groups, respectively (Okada et al. 2010; Wang et al. 2011). Recently 538 effective EST-SSRs were reported by our group (Liu et al. 2013b). Our experiments clearly showed higher polymorphisms of genomic SSRs than EST-SSRs in switchgrass (Wang et al. 2011; Liu et al. 2012).

Single nucleotide polymorphisms (SNPs) are a single nucleotide variation in sequence, and represent the most abundant type of genetic polymorphisms in plant genomes (Kwok 2001). While the majority of the SNPs are of no biological consequences, a fraction of the substitutions have functional significance and are the basis for plant diversity. Compared to SSRs, SNPs are, to some extents, more amenable to high-throughput automated genotyping assays that allow samples to be genotyped faster and more economically (Rafalski 2002; Ha and Boerma 2008; Han et al.

2011) . Scanning for new SNPs can be divided into two methods: i. e., global and regional approaches. Global SNP discovery is generally time — and labor-consuming. It is limited by the amount of funding available and whole genome sequence to provide the reference against which all other sequencing data can be compared. In contrast, local SNP discovery are relatively inexpensive to develop and rely mostly on direct DNA sequencing. SNP detection technologies have evolved from expensive, time-consuming, and labor-intensive processes to some of the most highly automated, efficient, and relatively inexpensive methods of DNA marker detection (Kwok and Chen 2003; Han et al. 2011). Two complete switchgrass chloroplast (cp) genomes were sequenced from upland (‘Summer’) and lowland (‘Kanlow’) ecotypes, and totally 116 SNPs were identified (Young et al. 2011). As a marker system developed from cp genome, their application in breeding is limited due to maternal inheritance of cp genome. Recently, Ersoz et al. (2012) established EST libraries of leaf tissues from thirteen diverse switchgrass cultivars, which represented upland and lowland ecotypes, as well as tetraploid and octoploid genomes. These libraries were sequenced by ABI 3730 instruments, and 100,000 EST sequences were produced. Subsequently, they generated reduced-representation genomic libraries from the same samples, which were massively sequenced as short — reads (35 bp) on a first-generation Illumina Genome Analyzer. Using EST as reference framework, these short sequence reads were assembled, and over 149,000 SNPs were identified. In addition, through combining with previously published 500,000 ESTs by Tobias et al. (2005, 2008), 25,000 additional SNPs were identified from the entire EST collection (Ersoz et al. 2012).

Next-generation sequencing (NGS) technologies are making a substantial impact on crop breeding. Genotyping by sequencing (GBS) is an emerging technology based on the platform of NGS. It utilizes ample SNPs generated by sequencing for genetic research. Comparing to other marker systems, GBS reduces sample handling time, uses fewer PCR samples, lowers costs if in a high-resolution scale. In addition, restriction enzymes can be used to reduce genome complexity and avoid the repetitive sequences of the genome, which is essential to expand in switchgrass genome. In wheat and barley, NGS was proven effective and over 200,000 sequence tags were mapped (Elshire et al. 2011). Its use in switchgrass is ongoing (http:// www. maizegenetics. net/snp-discovery-in-switchgrass) and expected to have a substantial role for genotyping but, to a large degree, depending on funding availability.

Transgenic approach manipulating gene expression for trait modification is one of the effective strategies for switchgrass breeding and genetic improvement (Sticklen 2006; Gressel 2008; Li and Qu 2011; Mann et al.

2012) . As one of the important regulatory factors in plants, miRNA genes and their targets are potential candidates for this purpose. Although little is known about the functions of miRNAs in switchgrass, several miRNA families are evolutionarily conserved in plant species, so is the miRNA — mediated regulatory mechanism (Jones-Rhoades et al. 2006; Chen 2009; Voinnet 2009; Cuperus et al. 2011). Therefore, it is possible to make use of the miRNAs whose functions have been identified in other species to modify this bioenergy crop.

Seeding rate is one of the most important variables determining the success of a new seeding. Seeding rate can be measured as either the weight of seed per unit area, or the number of seeds per unit area. The conversion between these two measures is the specific seed weight (i. e., g seed1), and this conversion varies among species, cultivars, and even seed lots. Seeding rates should be based on the delivery of pure live seed (PLS) per unit area, and thus also needs to account for hard seed, the percent germination of the seed being planted, and the presence of inert materials such as impurities and seed coatings. Switchgrass seed can also have high levels of dormancy, which can further complicate seeding recommendations or practices, and we discuss this in the next section.

Among all crops, recommended seeding rates vary by species, location and intended use of the stand. The recommended rates are usually not a specific value, but a defined range of seed per unit area. Recommended seeding rates have been determined over the years from research and experience in the field and tend to be higher for broadcast than drilled stands to offset poorer seed-soil contact. Rates generally are lower in drier climates due to seedling mortality and because higher seeding rates can decrease stand productivity due to excessive intra-species competition for water. Lower rates are also usually recommended for conservation plantings where forage production is not the primary objective.

Switchgrass seed is relatively expensive; thus, minimizing seed costs will be an important factor for optimizing returns from switchgrass as a commercial bioenergy crop. Proper seeding rate should ensure enough seedling survival so that the optimal 40% stand frequency is achieved for successful switchgrass establishment (Schmer et al. 2006). Current seeding rate recommendations range from 2.2 to 11.2 kg PLS ha-1 (Parrish et al. 2008). Refining seeding rates above which no additional biomass increases are achieved is important for the economic feasibility of switchgrass production. In Tennessee, ‘Alamo’ planted at seeding rates ranging from 2.8 to 14.0 kg PLS ha-1 produced similar DM yield when harvested after frost (Mooney et al. 2009). Foster et al. (2012) reported seeding rates of 2.24 to 4.48 kg PLS ha-1 were optimal for switchgrass emergence and DM yields. The lower the seeding rate for successful stand establishment, the more economical the production of switchgrass for biomass energy purposes (Perrin et al.

2008) .

Fungal endophytes are most commonly found living in aboveground plant tissues and occasionally in roots (Saikkonen et al. 1998). Plants infected with fungal endophytes gain growth promotion, stress tolerance, water use efficiency, and protection against vertebrate herbivores and root nematodes (Schardl et al. 2004; Rodriguez and Redman 2008; Rodriguez et al. 2009). During the interactions, endophytes obtain shelter, nutrition and dissemination through propagules of the host plants (Schardl et al. 2004). Like bacterial endophytes, fungal endophytes also promote host plant growth, such as increased root growth and longer root hairs (Malinowski et al. 1999), which may contribute to enhanced nutrient uptake. For instance, the root and shoot biomass of poplar, maize, tobacco, bacopa, Artemisia, and parsley was doubled compared with their respective controls after four weeks of Piriformospora indica inoculation (Varma et al. 1999).

Fungal endophytes of the genus Neotyphodium (an asexual form of Epichloe spp.) have been well studied for their symbiotic associations with different grass species, especially the family Pooideae, which includes many important species of forage and turf grasses (Clay 1990; Schardl et al. 2004; Sugawara 2011). Through this symbiosis, grasses have exhibited increased growth, tolerance to stress and resistance to herbivores (Schardl et al. 2004; Faeth et al. 2010). For instance, plant growth, biomass yield and tiller number increased when ryegrass (Lolium perenne) was inoculated with N. lolii (Spiering et al. 2006), and Dahurian wild rye (Elymus dahuricus) with Neotyphodium spp. (Zhang and Nan 2007). Endophyte-infected plants showed a higher survival rate, regrowth rate, and more biomass seed production compared to non-infected plants after a year in the field (Iannone et al. 2012).

In switchgrass, NF/GA-993 (a synthetic lowland switchgrass cultivar) inoculated with six strains of Sebacina vermifera fungal endophytes showed increased plant growth, root length, and biomass production (Ghimire et al. 2009). Recently, Sasan and Bidochka (2012) found that the fungal endophyte Metarhizium robertsii was able to endophytically colonize the roots of switchgrass and promoted growth and increased the density of root hairs (Sasan and Bidochka 2012). However, fungal endophytes recently isolated from switchgrass plants had both beneficial and detrimental effects on switchgrass biomass yields in greenhouse conditions. Phaeosphaeria pontiformis, Epicoccum nigrum, Alternaria spp. and Colletotrichum spp. increased total biomass by 25-33%, Stagonospora spp. increased shoot biomass by 22%, and Colletotrichum sp. increased root biomass by 45%, but over 60% of isolates tested reduced switchgrass growth (Kleczewski et al. 2012).

After biomass production, harvesting, and transport, biochemical conversion of biomass to biofuels typically includes a pretreatment to improve accessibility of the biomass, followed by enzymatic digestion to depolymerize the cell wall polysaccharides, and finally fuel synthesis. Here, we briefly discuss pretreatment approaches and then review biochemical conversion platforms, including the goal of consolidating the different steps of biochemical conversion into a single reaction vessel. We then provide an overview of the enzymes and enzyme complexes that digest biomass. In the last section we especially highlight progress in one means of bioconversion consolidation, expressing cell wall digesting enzymes in plants.

Germplasm Characterization by Molecular Markers

Diverse germplasms are fundamental for crop improvement in all plants including switchgrass. Fortunately, switchgrass is genetically highly diverse as revealed by recent molecular marker investigations. The existing germplasm will provide abundant genetic variability to improve bioenergy traits for new cultivars development. As an allogamous species, switchgrass has tremendous genetic diversity among germplasm sources, such as morphological traits, biomass and quality traits, biotic resistance and abiotic stress tolerances. Molecular studies on genetic diversity analysis in switchgrass include RFLP, RAPD, SSRs and high-throughput sequencing (Morris et al. 2011). Gunter et al. (1996) used RAPDs to assess the genetic diversity among and within 14 populations of switchgrass and found markers were useful for population identification. Hultquist et al. (1996) utilized chloroplast DNA RFLP to investigate 18 switchgrass strains, and found polymorphism existed between lowland and upland ecotypes, but not among upland cultivars. Casler et al. (2007) reported that 46 remnant populations and 11 cultivars could be highly unrelated to each other. They further indicated that RAPD markers could not distinguish between cultivars and remnant wild populations. Casler et al. (2007) also used RAPDs to test the plants with the same region and found little differentiation correlated with geography, but part of them was related with hardiness zones and ecotypes. Missaoui et al. (2006) used RFLPs to assess genetic variation between 21 switchgrass genotypes and they found higher diversity between upland and lowland accessions than within each of cultivars. They also used a trnL (UAA) chloroplastic marker and found a polymorphism between upland and lowland ecotypes. The trnL UAA intron region is located on chloroplast genome and is inherited through the maternal parent (Martinez-Reyna et al. 2001). Narasimha-moorthy et al. (2008) used the materials from USDA Germplasm Resources Information Network (GRIN), and found higher variation within populations than among populations. Cortese et al. (2010) used marker and morphological data among 12 populations of switchgrass and indicated that morphological and adaptive traits could be identified by molecular markers. Zalapa et al. (2011) used 55 SSR markers and six chloroplast markers to study diversity within and between 18 switchgrass cultivars. The SSR markers could discriminate ecotypes correctly, but chloroplast markers could not. Zhang et al. (2011a) sampled a total of 384 genotypes from 49 accessions. They identified primary centers of diversity were in the eastern and western Gulf Coast regions. Todd et al. (2011b) utilized amplified fragment length polymorphism (AFLP) procedure to quantify genetic diversity of seven upland and 49 lowland genotypes from throughout the USA. They found upland and lowland accessions clustered according to ecotypes, with one exception (TN104). Morris et al. (2011) sequenced 40.9 billion base pairs of chloroplast genomes from 24 individuals from across the species’ range and 20 individuals from the Indiana Dunes. Analysis of plastome sequence revealed three deeply divergent haplogroups, which correspond to the previously described lowland-upland ecotypic split and a novel upland haplogroup split that dates to the mid-Pleistocene.

Switchgrass breeding programs have aimed to double its biomass yield in the near future (Schubert 2006). Improving the biomass yield of switchgrass under various field or geographic conditions can be achieved by promoting vegetative growth, increasing the photosynthetic sink-source ratio, increasing resistance to biotic/abiotic stress, and improving water and nutrient use efficiency (WUE and NUE). Improving certain biological traits of switchgrass, such as NUE, can also decrease production input. Producing high value additives, such as plastics, enzymes, and secondary metabolic chemicals, can further increase the economics of growing switchgrass (Somleva et al. 2008). Selection and use of plant-growth promoting microbes may also improve grass growth and resistance to stress (Compant et al. 2005). Candidate genetic components, as well as pathways potentially useful for switchgrass improvement, are discussed in the following section with an emphasis on lignin reduction, biomass enhancement, value-added engineering, and stress resistance.

Once switchgrass stands reach canopy closure, weed pressure will be minimal with appropriate management. Herbicides such as 2,4-D amine can be used to control broadleaf weeds anytime after switchgrass reaches the 4-leaf stage—which is when most grasses are considered established (Ries and Svejcar 1991). Once established, pendimethalin (Prowl H2O®; Anonymous 2011b) can be applied to winter dormant warm-season grasses

like switchgrass early in the season prior to weed germination to reduce warm-season annual grass weeds like crabgrass in southern USA and foxtails in northern USA.

As new and improved cultivars are developed and marketed, there may be a need or desire to renovate or remove an existing switchgrass stand. Since switchgrass is a bunchgrass, it is susceptible to deep tillage. However, for best results glyphosate should be applied in the autumn, when switchgrass is translocating carbohydrates from the shoots to its roots, prior to tillage. Any survivors can be retreated with glyphosate the following spring.

Mitchell et al. (2005) provided guidelines for converting perennial grasses using minimum tillage and glyphosate-tolerant soybeans. The soybeans can be no-till seeded into the grass stand and managed using standard recommendations for two consecutive growing seasons. This process maintains residue on site, reduces soil erosion and desiccation, and produces income during renovation. Soybeans are preferable to corn because soybeans provide residual nitrogen, produce an excellent seedbed for no-till planting, and leave sufficient residue to protect the soil without interfering with seeding. Additionally, it prepares an excellent weed-free seedbed for grass establishment, and no-till seeding perennial grasses into soybean stubble reduces tillage and weed control costs during establishment.

In order to classify and study functions of endophytes and mycorrhizal fungi, endophytes first need to be isolated from host plants and mycorrhizal fungi from soil samples containing host plant roots. Next, the organisms need to be purified before they are identified and finally characterized using molecular tools.

Endophyte Isolation

In general, for bacterial and fungal endophyte isolation, the samples, including any host plant tissue, are collected and brought to laboratories where they can be stored in plastic bags at 4°C for a few days prior to surface sterilization.

Surface Sterilization

Root samples should first be washed with tap water to remove any soil from the root surface before sterilization. Aboveground plant tissue can be directly washed with 70% ethanol for one minute, sterilized with 20-50% bleach solution for 10-20 min depending on the type of tissue; for tender tissues, a lower concentration of bleach and shorter duration of time should be used. The tissue is finally rinsed with sterile water 3-5 times under aseptic conditions. After sterilization, the tissue surface should be clean and free of microorganisms. To ensure the efficacy of surface-sterilization, 50 gl of the final wash should be plated, and surface-sterilized tissues can be rolled onto culture media and incubated at 27°C for a few days to see if any remaining microorganisms were present (Coombs and Franco 2003).