Next-generation biomass feedstocks for biofuel production

The development of second-generation biofuels - those that do not rely on grain crops as inputs - will require a diverse set of feedstocks that can be grown sustainably and processed cost-effectively. Here we review the outlook and challenges for meeting hoped-for production targets for such biofuels in the United States.     

Strategies to enhance production of microalgal biomass and lipids for biofuel feedstock

ABSTRACT

Microalgae have enormous potential as feedstock for biofuel production compared with other sources, due to their high areal productivity, relatively low environmental impact, and low impact on food security. However, high production costs are the major limitation for commercialization of algal biofuels. Strategies to maximize biomass and lipid production are crucial for improving the economics of using microalgae for biofuels. Selection of suitable algal strains, preferably from indigenous habitats, and further improvement of those ‘platform strains’ using mutagenesis and genetic engineering approaches are desirable. Conventional approaches to improve biomass and lipid productivity of microalgae mainly involve manipulation of nutritional (e.g. nitrogen and phosphorus) and environmental (e.g. temperature, light and salinity) factors. Approaches such as the addition of phytohormones, genetic and metabolic engineering, and co-cultivation of microalgae with yeasts and bacteria are more recent strategies to enhance biomass and lipid productivity of microalgae. Improvement in culture systems and the use of a hybrid system (i.e. a combination of open ponds and photobioreactors) is another strategy to optimize algal biomass and lipid production. In addition, the use of low-cost substrates such as agri-industrial wastewater for the cultivation of microalgae will be a smart strategy to reduce production costs. Such systems not only generate high algal biomass and lipid productivity, but are also useful for bioremediation of wastewater and bioremoval of waste CO₂. The aim of this review is to highlight the advances in the use of various strategies to enhance production of algal biomass and lipids for biofuel feedstock.     

Optimization of Chlorella biomass harvesting by flocculation and its potential for biofuel production

Optimization of microalgal biomass harvesting is essential to produce effective and optimum outcomes that can contribute towards a feasible and economical harvesting technique. Two Chlorella species were used, namely, C. vulgaris and C. sorokiniana UKM3. Two essential factors affecting microalgal biomass harvesting via flocculation, namely, the initial pH of the microalgal broth and flocculant (chitosan) concentration were studied. The optimization process was conducted by using a response surface methodology (RSM) based on the model of face-centered-central composite design (FC-CCD). The potential for biofuel application of the harvested biomass was evaluated based on the production of fatty acid methyl esters (FAMEs) by transesterification. The quadratic models obtained from the RSM significantly fitted the experiment data as the p-values were less than 0.05. The initial pH of the microalgal suspension was found to have a more significant effect on the flocculation process than flocculant concentration. For C. vulgaris, the highest flocculant efficiency of 98.7% was obtained at a chitosan concentration of 0.2 g L^?1 and an initial pH of 12.0, whereas for C. sorokiniana UKM3, at 0.15 g L^?1 of chitosan and initial pH of 12.0 produced the highest efficiency of 97.1%. The harvested biomass of both species exhibited a high content of palmitic acid (C16:0) with 29.74 wt% and 11.81 wt% of dry biomass for C. vulgaris and C. sorokiniana UKM3, respectively. This study showed that Chlorella species can be harvested efficiently using the flocculation process and manifested an excellent potential for biodiesel production where palmitic acid (C16:0) is one of the main compounds for high-acid oil-biodiesel.

     

Sequencing intractable DNA to close microbial genomes

Advancement in high throughput DNA sequencing technologies has supported a rapid proliferation of microbial genome sequencing projects, providing the genetic blueprint for in-depth studies. Oftentimes, difficult to sequence regions in microbial genomes are ruled "intractable" resulting in a growing number of genomes with sequence gaps deposited in databases. A procedure was developed to sequence such problematic regions in the "non-contiguous finished" Desulfovibrio desulfuricans ND132 genome (6 intractable gaps) and the Desulfovibrio africanus genome (1 intractable gap). The polynucleotides surrounding each gap formed GC rich secondary structures making the regions refractory to amplification and sequencing. Strand-displacing DNA polymerases used in concert with a novel ramped PCR extension cycle supported amplification and closure of all gap regions in both genomes. The developed procedures support accurate gene annotation, and provide a step-wise method that reduces the effort required for genome finishing.     

A novel polyculture growth model of native microalgal communities to estimate biomass productivity for biofuel production

Native polyculture microalgae is a promising scheme to produce microalgal biomass as biofuel feedstock in an open raceway pond. However, predicting biomass productivity of native polycultures microalgae is incredibly complicated. Therefore, developing polyculture growth model to forecast biomass yield is indispensable for commercial-scale production. This research aims to develop a polyculture growth model for native microalgal communities in the Minamisoma algae plant and to estimate biomass and biocrude oil productivity in a semicontinuous open raceway pond. The model was built based on monoculture growth of polyculture species and it is later formulated using species growth, polyculture factor (k_value), initial concentration, light intensity, and temperature. In order to calculate species growth, a simplified Monod model was applied. In the simulation, 115 samples of the 2014–2015 field dataset were used for model training, and 70 samples of the 2017 field dataset were used for model validation. The model simulation on biomass concentration showed that the polyculture growth model with k_value had a root-mean-square error of 0.12, whereas model validation provided a better result with a root-mean-square error of 0.08. Biomass productivity forecast showed maximum productivity of 18.87 g/m²/d in June with an annual average of 13.59 g/m²/d. Biocrude oil yield forecast indicated that hydrothermal liquefaction process was more suitable with a maximum productivity of 0.59 g/m²/d compared with solvent extraction which was only 0.19 g/m²/d. With satisfactory root-mean-square errors less than 0.3, this polyculture growth model can be applied to forecast the productivity of native microalgae.     

Effects of pasture conversion to sugarcane for biofuel production on stream fish assemblages in tropical agroecosystems

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Sequencing complete mitochondrial and plastid genomes

Organelle genomics has become an increasingly important research field, with applications in molecular modeling, phylogeny, taxonomy, population genetics and biodiversity. Typically, research projects involve the determination and comparative analysis of complete mitochondrial and plastid genome sequences, either from closely related species or from a taxonomically broad range of organisms. Here, we describe two alternative organelle genome sequencing protocols. The "random genome sequencing" protocol is suited for the large majority of organelle genomes irrespective of their size. It involves DNA fragmentation by shearing (nebulization) and blunt-end cloning of the resulting fragments into pUC or BlueScript-type vectors. This protocol excels in randomness of clone libraries as well as in time and cost-effectiveness. The "long-PCR-based genome sequencing" protocol is specifically adapted for DNAs of low purity and quantity, and is particularly effective for small organelle genomes. Library construction by either protocol can be completed within 1 week.     

Pretreatment of woody biomass for biofuel production: energy efficiency, technologies, and recalcitrance

This mini review discusses several key technical issues associated with cellulosic ethanol production from woody biomass: energy consumption for woody biomass pretreatment, pretreatment energy efficiency, woody biomass pretreatment technologies, and quantification of woody biomass recalcitrance. Both total sugar yield and pretreatment energy efficiency, defined as the total sugar recovery divided by total energy consumption for pretreatment, should be used to evaluate the performance of a pretreatment process. A post-chemical pretreatment wood size-reduction approach was proposed to significantly reduce energy consumption. The review also emphasizes using a low liquid-to-wood ratio (L/W) to reduce thermal energy consumption for any thermochemical/physical pretreatment in addition to reducing pretreatment temperature.     

Alternatives to Trichoderma reesei in biofuel production

Mutant strains of Trichoderma reesei are considered indisputable champions in cellulase production among biomass-degrading fungi. So, it is not surprising that most R&D projects on bioethanol production from lignocellulosics have been based on using T. reesei cellulases. The present review focuses on whether any serious alternatives to T. reesei enzymes in cellulose hydrolysis exist. Although not widely accepted, more and more data have been accumulated that demonstrate that fungi belonging to the genera Penicillium, Acremonium and Chrysosporium might represent such alternatives because they are competitive to T. reesei on some important parameters, such as protein production level, cellulase hydrolytic performance per unit of activity or milligram of protein.     

Impact of agronomic uncertainty in biomass production and endogenous commodity prices on cellulosic biofuel feedstock composition

This study evaluates the effect of agronomic uncertainty on bioenergy crop production as well as endogenous commodity and biomass prices on the feedstock composition of cellulosic biofuels under a binding mandate in the United States. The county‐level simulation model focuses on both field crops (corn, soybean, and wheat) and biomass feedstocks (corn stover, wheat straw, switchgrass, and Miscanthus). In addition, pasture serves as a potential area for bioenergy crop production. The economic model is calibrated to 2022 in terms of yield, crop demand, and baseline prices and allocates land optimally among the alternative crops given the binding cellulosic biofuel mandate. The simulation scenarios differ in terms of bioenergy crop type (switchgrass and Miscanthus) and yield, biomass production inputs, and pasture availability. The cellulosic biofuel mandates range from 15 to 60 billion L. The results indicate that the 15 and 30 billion L mandates in the high production input scenarios for switchgrass and Miscanthus are covered entirely by agricultural residues. With the exception of the low production input for Miscanthus scenario, the share of agricultural residues is always over 50% for all other scenarios including the 60 billion L mandate. The largest proportion of agricultural land dedicated to either switchgrass or Miscanthus is found in the southern Plains and the southeast. Almost no bioenergy crops are grown in the Midwest across all scenarios. Changes in the prices for the three commodities are negligible for cellulosic ethanol mandates because most of the mandate is met with agricultural residues. The lessons learned are that (1) the share of agricultural residue in the feedstock mix is higher than previously estimated and (2) for a given mandate, the feedstock composition is relatively stable with the exception of one scenario.     

Sequencing crop genomes: approaches and applications

Many challenges face plant scientists, in particular those working on crop production, such as a projected increase in population, decrease in water and arable land, changes in weather patterns and predictability. Advances in genome sequencing and resequencing can and should play a role in our response to meeting these challenges. However, several barriers prevent rapid and effective deployment of these tools to a wide variety of crops. Because of the complexity of crop genomes, de novo sequencing with next-generation sequencing technologies is a process fraught with difficulties that then create roadblocks to the utilization of these genome sequences for crop improvement. Collecting rapid and accurate phenotypes in crop plants is a hindrance to integrating genomics with crop improvement, and advances in informatics are needed to put these tools in the hands of the scientists on the ground.     

Comparison of the mesophilic cellulosome‐producing Clostridium cellulovorans genome with other cellulosome‐related clostridial genomes

Clostridium cellulovorans, an anaerobic and mesophilic bacterium, degrades native substrates in soft biomass such as corn fibre and rice straw efficiently by producing an extracellular enzyme complex called the cellulosome. Recently, we have reported the whole‐genome sequence of C. cellulovorans comprising 4220 predicted genes in 5.10 Mbp [Y. Tamaru et al., (2010) J. Bacteriol., 192: 901–902]. As a result, the genome size of C. cellulovorans was about 1 Mbp larger than that of other cellulosome‐producing clostridia, mesophilic C. cellulolyticum and thermophilic C. thermocellum. A total of 57 cellulosomal genes were found in the C. cellulovorans genome, and they coded for not only carbohydrate‐degrading enzymes but also a lipase, peptidases and proteinase inhibitors. Interestingly, two novel genes encoding scaffolding proteins were found in the genome. According to KEGG metabolic pathways and their comparison with 11 Clostridial genomes, gene expansion in the C. cellulovorans genome indicated mainly non‐cellulosomal genes encoding hemicellulases and pectin‐degrading enzymes. Thus, by examining genome sequences from multiple Clostridium species, comparative genomics offers new insight into genome evolution and the way natural selection moulds functional DNA sequence evolution. Our analysis, coupled with the genome sequence data, provides a roadmap for constructing enhanced cellulosome‐producing Clostridium strains for industrial applications such as biofuel production.     

RNAi suppression of lignin biosynthesis in sugarcane reduces recalcitrance for biofuel production from lignocellulosic biomass

Sugarcane is a prime bioethanol feedstock. Currently, sugarcane ethanol is produced through fermentation of the sucrose, which can easily be extracted from stem internodes. Processes for production of biofuels from the abundant lignocellulosic sugarcane residues will boost the ethanol output from sugarcane per land area. However, unlocking the vast amount of chemical energy stored in plant cell walls remains expensive primarily because of the intrinsic recalcitrance of lignocellulosic biomass. We report here the successful reduction in lignification in sugarcane by RNA interference, despite the complex and highly polyploid genome of this interspecific hybrid. Down‐regulation of the sugarcane caffeic acid O‐methyltransferase (COMT) gene by 67% to 97% reduced the lignin content by 3.9% to 13.7%, respectively. The syringyl/guaiacyl ratio in the lignin was reduced from 1.47 in the wild type to values ranging between 1.27 and 0.79. The yields of directly fermentable glucose from lignocellulosic biomass increased up to 29% without pretreatment. After dilute acid pretreatment, the fermentable glucose yield increased up to 34%. These observations demonstrate that a moderate reduction in lignin (3.9% to 8.4%) can reduce the recalcitrance of sugarcane biomass without compromising plant performance under controlled environmental conditions.     

Strategies for the production of cell wall‐deconstructing enzymes in lignocellulosic biomass and their utilization for biofuel production

Microbial cell wall‐deconstructing enzymes are widely used in the food, wine, pulp and paper, textile, and detergent industries and will be heavily utilized by cellulosic biorefineries in the production of fuels and chemicals. Due to their ability to use freely available solar energy, genetically engineered bioenergy crops provide an attractive alternative to microbial bioreactors for the production of cell wall‐deconstructing enzymes. This review article summarizes the efforts made within the last decade on the production of cell wall‐deconstructing enzymes in planta for use in the deconstruction of lignocellulosic biomass. A number of strategies have been employed to increase enzyme yields and limit negative impacts on plant growth and development including targeting heterologous enzymes into specific subcellular compartments using signal peptides, using tissue‐specific or inducible promoters to limit the expression of enzymes to certain portions of the plant or certain times, and fusion of amplification sequences upstream of the coding region to enhance expression. We also summarize methods that have been used to access and maintain activity of plant‐generated enzymes when used in conjunction with thermochemical pretreatments for the production of lignocellulosic biofuels.     

A multiple species approach to biomass production from native herbaceous perennial feedstocks

Due to the rapid rate of worldwide consumption of nonrenewable fossil fuels, production of biofuels from cellulosic sources is receiving increased research emphasis. Here, we review the feasibility to produce lignocellulosic biomass on marginal lands that are not well-suited for conventional crop production. Large areas of these marginal lands are located in the central prairies of North America once dominated by tallgrass species. In this article, we review the existing literature, current work, and potential of two native species of the tallgrass prairie, prairie cordgrass (Spartina pectinata), and little bluestem (Schizachyrium scoparium) as candidates for commercial production of biofuel. Based on the existing literature, we discuss the need to accelerate research in the areas of agronomy, breeding, genetics, and potential pathogens. Cropping systems based on maintaining biodiversity across landscapes are essential for a sustainable production and to mitigate impact of pathogens and pests.