Co-utilization of L-arabinose and D-xylose by laboratory and industrial Saccharomyces cerevisiae strains

Background  

Fermentation of lignocellulosic biomass is an attractive alternative for the production of bioethanol. Traditionally, the yeast Saccharomyces cerevisiae is used in industrial ethanol fermentations. However, S. cerevisiae is naturally not able to ferment the pentose sugars D-xylose and L-arabinose, which are present in high amounts in lignocellulosic raw materials.     

Enzymatic hydrolyzing performance of Acremonium cellulolyticus and Trichoderma reesei against three lignocellulosic materials

Background  

Bioethanol isolated from lignocellulosic biomass represents one of the most promising renewable and carbon neutral alternative liquid fuel sources. Enzymatic saccharification using cellulase has proven to be a useful method in the production of bioethanol. The filamentous fungi Acremonium cellulolyticus and Trichoderma reesei are known to be potential cellulase producers. In this study, we aimed to reveal the advantages and disadvantages of the cellulase enzymes derived from these fungi.     

A family of E. coli expression vectors for laboratory scale and high throughput soluble protein production

Background  

In the past few years, both automated and manual high-throughput protein expression and purification has become an accessible means to rapidly screen and produce soluble proteins for structural and functional studies. However, many of the commercial vectors encoding different solubility tags require different cloning and purification steps for each vector, considerably slowing down expression screening. We have developed a set of E. coli expression vectors with different solubility tags that allow for parallel cloning from a single PCR product and can be purified using the same protocol.     

An NIRS-based assay of chemical composition and biomass digestibility for rapid selection of Jerusalem artichoke clones

Background

High-throughput evaluation of lignocellulosic biomass feedstock quality is the key to the successful commercialization of bioethanol production. Currently, wet chemical methods for the determination of chemical composition and biomass digestibility are expensive and time-consuming, thus hindering comprehensive feedstock quality assessments based on these biomass specifications. To find the ideal bioethanol feedstock, we perform a near-infrared spectroscopic (NIRS) assay to rapidly and comprehensively analyze the chemical composition and biomass digestibility of 59 Jerusalem artichoke (Helianthus tuberosus L., abbreviated JA) clones collected from 24 provinces in six regions of China.

Results

The distinct geographical distribution of JA accessions generated varied chemical composition as well as related biomass digestibility (after soluble sugars extraction and mild alkali pretreatment). Notably, the soluble sugars, cellulose, hemicellulose, lignin, ash, and released hexoses, pentoses, and total carbohydrates were rapidly and perfectly predicted by partial least squares regression coupled with model population analyses (MPA), which exhibited significantly higher predictive performance than controls. Subsequently, grey relational grade analysis was employed to correlate chemical composition and biomass digestibility with feedstock quality score (FQS), resulting in the assignment of tested JA clones to five feedstock quality grades (FQGs). Ultimately, the FQGs of JA clones were successfully classified using partial least squares-discriminant analysis model coupled with MPA, attaining a significantly higher correct rate of 97.8% in the calibration subset and 91.1% in the validation subset.

Conclusions

Based on the diversity of JA clones, the present study has not only rapidly and precisely examined the biomass composition and digestibility with MPA-optimized NIRS models but has also selected the ideal JA clones according to FQS. This method provides a new insight into the selection of ideal bioethanol feedstock for high-efficiency bioethanol production.

     

A simple method to determine bioethanol content in gasoline using two-step extraction and liquid scintillation counting

A simple method for determining bioethanol content in gasoline containing bioethanol (denoted as E-gasoline in this study) is urgently required. Liquid scintillation counting (LSC) was employed based on the principle that ¹⁴C exists in bioethanol but not in synthetic ethanol. Bioethanol was extracted in two steps by water from E-gasoline containing 3% (E3) or 10% (E10) bioethanol. The ¹⁴C radioactivity was measured by LSC and converted to the amount of bioethanol. The bioethanol content in E-gasoline was determined precisely from the partition coefficient in the extraction and the amount of bioethanol in the water phases: 2.98 ± 0.10% for E3 and 10.0 ± 0.1% for E10 (means ± SD; n = 3). It appears that this method can be used to determine bioethanol content in E-gasoline quickly and easily.     

Arabinose and xylose fermentation by recombinant Saccharomyces cerevisiae expressing a fungal pentose utilization pathway

Background  

Sustainable and economically viable manufacturing of bioethanol from lignocellulose raw material is dependent on the availability of a robust ethanol producing microorganism, able to ferment all sugars present in the feedstock, including the pentose sugars L-arabinose and D-xylose. Saccharomyces cerevisiae is a robust ethanol producer, but needs to be engineered to achieve pentose sugar fermentation.     

Towards an automatic classification of protein structural domains based on structural similarity

Background  

Formal classification of a large collection of protein structures aids the understanding of evolutionary relationships among them. Classifications involving manual steps, such as SCOP and CATH, face the challenge of increasing volume of available structures. Automatic methods such as FSSP or Dali Domain Dictionary, yield divergent classifications, for reasons not yet fully investigated. One possible reason is that the pairwise similarity scores used in automatic classification do not adequately reflect the judgments made in manual classification. Another possibility is the difference between manual and automatic classification procedures. We explore the degree to which these two factors might affect the final classification.     

A spatially explicit whole-system model of the lignocellulosic bioethanol supply chain: an assessment of decentralised processing potential

Background  

Lignocellulosic bioethanol technologies exhibit significant capacity for performance improvement across the supply chain through the development of high-yielding energy crops, integrated pretreatment, hydrolysis and fermentation technologies and the application of dedicated ethanol pipelines. The impact of such developments on cost-optimal plant location, scale and process composition within multiple plant infrastructures is poorly understood. A combined production and logistics model has been developed to investigate cost-optimal system configurations for a range of technological, system scale, biomass supply and ethanol demand distribution scenarios specific to European agricultural land and population densities.     

Airtight storage of moist wheat grain improves bioethanol yields

Background  

Drying is currently the most frequently used conservation method for cereal grain, which in temperate climates consumes a major part of process energy. Airtight storage of moist feed grain using the biocontrol yeast Pichia anomala as biopreservation agent can substantially reduce the process energy for grain storage. In this study we tested the potential of moist stored grain for bioethanol production.     

Diversity of lactic acid bacteria of the bioethanol process

Background  

Bacteria may compete with yeast for nutrients during bioethanol production process, potentially causing economic losses. This is the first study aiming at the quantification and identification of Lactic Acid Bacteria (LAB) present in the bioethanol industrial processes in different distilleries of Brazil.     

Lignocellulose conversion for biofuel: a new pretreatment greatly improves downstream biocatalytic hydrolysis of various lignocellulosic materials

Background

Lignocellulosic biomass is an attractive renewable resource for future liquid transport fuel. Efficient and cost-effective production of bioethanol from lignocellulosic biomass depends on the development of a suitable pretreatment system. The aim of this study is to investigate a new pretreatment method that is highly efficient and effective for downstream biocatalytic hydrolysis of various lignocellulosic biomass materials, which can accelerate bioethanol commercialization.

Results

The optimal conditions for the hydrogen peroxide–acetic acid (HPAC) pretreatment were 80 °C, 2 h, and an equal volume mixture of H₂O₂ and CH₃COOH. Compared to organo-solvent pretreatment under the same conditions, the HPAC pretreatment was more effective at increasing enzymatic digestibility. After HPAC treatment, the composition of the recovered solid was 74.0 % cellulose, 20.0 % hemicelluloses, and 0.9 % lignin. Notably, 97.2 % of the lignin was removed with HPAC pretreatment. Fermentation of the hydrolyzates by S. cerevisiae resulted in 412 mL ethanol kg^?1 of biomass after 24 h, which was equivalent to 85.0 % of the maximum theoretical yield (based on the amount of glucose in the raw material).

Conclusion

The newly developed HPAC pretreatment was highly effective for removing lignin from lignocellulosic cell walls, resulting in enhanced enzymatic accessibility of the substrate and more efficient cellulose hydrolysis. This pretreatment produced less amounts of fermentative inhibitory compounds. In addition, HPAC pretreatment enables year-round operations, maximizing utilization of lignocellulosic biomass from various plant sources.

     

ParaHaplo: A program package for haplotype-based whole-genome association study using parallel computing

Background  

Fungi from environmental samples are typically identified to species level through DNA sequencing of the nuclear ribosomal internal transcribed spacer (ITS) region for use in BLAST-based similarity searches in the International Nucleotide Sequence Databases. These searches are time-consuming and regularly require a significant amount of manual intervention and complementary analyses. We here present software – in the form of an identification pipeline for large sets of fungal ITS sequences – developed to automate the BLAST process and several additional analysis steps. The performance of the pipeline was evaluated on a dataset of 350 ITS sequences from fungi growing as epiphytes on building material.     

Life cycle assessment of energy and GHG emissions during ethanol production from grass straws using various pretreatment processes

Purpose  

The aim of this study was to perform a well-to-pump life cycle assessment (LCA) to investigate the overall net energy balance and environmental impact of bioethanol production using Tall Fescue grass straw as feedstock. The energy requirements and greenhouse gas (GHG) emissions were compared to those of gasoline to explore the potential of bioethanol as sustainable fuel.     

Comparative secretome analyses of two <Emphasis Type="Italic">Trichoderma reesei</Emphasis> RUT-C30 and CL847 hypersecretory strains

Background  

Due to its capacity to produce large amounts of cellulases, Trichoderma reesei is increasingly been researched in various fields of white biotechnology, especially in biofuel production from lignocellulosic biomass. The commercial enzyme mixtures produced at industrial scales are not well characterized, and their proteinaceous components are poorly identified and quantified. The development of proteomic methods has made it possible to comprehensively overview the enzymes involved in lignocellulosic biomass degradation which are secreted under various environmental conditions.     

Identification of glycolaldehyde as the key inhibitor of bioethanol fermentation by yeast and genome-wide analysis of its toxicity

Degradation of lignocellulose with pressurised hot water is an efficient method of bioethanol production. However, the resultant solution inhibits ethanol fermentation by Saccharomyces cerevisiae. Here, we first report that glycolaldehyde, which is formed when lignocellulose is treated with pressurised hot water, inhibits ethanol fermentation. The final concentration of glycolaldehyde formed by the treatment of lignocellulose with pressurised hot water ranges from 1 to 24 mM, and 1–10 mM glycolaldehyde was sufficient to inhibit fermentation. This result indicates that glycolaldehyde is one of the main substances responsible for inhibiting fermentation after pressurised hot water degradation of lignocellulose. Genome-wide screening of S. cerevisiae revealed that genes encoding alcohol dehydrogenase, methylglyoxal reductase, polysomes, and the ubiquitin ligase complex are required for glycolaldehyde tolerance. These novel findings will provide new perspectives on breeding yeast for bioethanol production from biomass treated with pressurised hot water.     

Large‐scale screening and characterisation of Lemna aequinoctialis and Spirodela polyrhiza strains for starch production

• Duckweed is considered a promising feedstock for bioethanol production due to its high biomass and starch production. Selection of duckweed strains with high starch accumulation is essential for application of duckweeds to bioethanol production. Geographic differentiation had a large influence on genetic diversity of duckweeds.
• Biomass production, starch content and starch amount in geographically isolated strains of 20 Lemna aequinoctialis and Spirodela polyrhiza were calculated to evaluate their potential for bioethanol production. The influence of different collection time, culture medium and NaCl concentration on starch accumulation of the best strains were analysed.
• The results showed that biomass production, starch content and starch production of duckweeds demonstrated clonal dependency. The best strain was L. aequinoctialis 6000, with biomass production of 15.38 ± 1.47 g m^?2, starch content of 28.68 ± 1.10% and starch production of 4.39 ± 0.25 g m^?2. Furthermore, starch content of L. aequinoctialis 6000 was highest after 8 h of light, tap water was the best medium for starch induction, and NaCl did not induce starch accumulation.
• This study suggests duckweed biomass production and starch production demonstrate clonal dependency, indicating that extensive clonal comparisons will be required to identify the most suitable isolates for duckweed selective breeding for bioethanol.

     

Bayesian optimal discovery procedure for simultaneous significance testing

Background  

In high throughput screening, such as differential gene expression screening, drug sensitivity screening, and genome-wide RNAi screening, tens of thousands of tests need to be conducted simultaneously. However, the number of replicate measurements per test is extremely small, rarely exceeding 3. Several current approaches demonstrate that test statistics with shrinking variance estimates have more power over the traditional t statistic.     

High throughput screening of hydrolytic enzymes from termites using a natural substrate derived from sugarcane bagasse

Background

Short rotation coppice willow is a potential lignocellulosic feedstock in the United Kingdom and elsewhere; however, research on optimising willow specifically for bioethanol production has started developing only recently. We have used the feedstock Salix viminalis × Salix schwerinii cultivar 'Olof' in a three-month pot experiment with the aim of modifying cell wall composition and structure within the stem to the benefit of bioethanol production. Trees were treated for 26 or 43 days with tension wood induction and/or with an application of the cellulose synthesis inhibitor 2,6-dichlorobenzonitrile that is specific to secondary cell walls. Reaction wood (tension and opposite wood) was isolated from material that had received the 43-day tension wood induction treatment.

Results

Glucan content, lignin content and enzymatically released glucose were assayed. All measured parameters were altered without loss of total stem biomass yield, indicating that enzymatic saccharification yield can be enhanced by both alterations to cell wall structure and alterations to absolute contents of either glucan or lignin.

Conclusions

Final glucose yields can be improved by the induction of tension wood without a detrimental impact on biomass yield. The increase in glucan accessibility to cell wall degrading enzymes could help contribute to reducing the energy and environmental impacts of the lignocellulosic bioethanol production process.     

Non‐destructive allometric estimates of above‐ground and below‐ground biomass of high‐mountain vegetation in the Andes

Aim

Studies that monitor high‐mountain vegetation, such as paramo grasslands in the Andes, lack non‐destructive biomass estimation methods. We aimed to develop and apply allometric models for above‐ground, below‐ground and total biomass of paramo plants.

Location

The paramo of southern Colombia between 1°09′N and 077°50′W, at 3,400 and 3,700 m a.s.l.

Methods

We established 61 1‐m² plots at random locations, excluding disturbed, inaccessible and peat bog areas. We measured heights and basal diameters of all vascular plants in these plots and classified them into seven growth forms. Near each plot, we sampled the biomass from plants of abundant genera, after having measured their height and basal diameter. Hence, we measured the biomass of 476 plants (allometric set). For each growth form we applied power‐law functions to develop allometric models of biomass against basal diameter, height, height x basal diameter and height × basal area. The best models were selected using AIC_c weights. Using the observed and predicted plant biomass of the allometric set we calculated absolute percentage errors using cross‐validation. The biomass of a plot was estimated by summing the predicted biomass of all plants in a plot. Confidence limits around these sums were calculated by bootstrapping.

Results

For groups of <20 plants the biomass predictions yielded large (>15%) errors. Applying groups that resembled the 1‐m² plots in density and composition, the errors for above‐ground and total biomass estimates were <15%. Across all plots, we obtained an above‐ground, below‐ground and total plot biomass of 329 ± 190, 743 ± 486 and 1011 ± 627 g/m² (mean ± SD), respectively. These values were within the range of biomass estimates obtained destructively in the tropical Andes.

Conclusions

In new applications, if target vegetation samples are similar regarding growth forms and genera to our allometric set, their biomass might be predicted applying our equations, provided they contain at least 50–100 plants. In other situations, we would recommend gathering additional biomass measurements from local plants to evaluate new regression equations.     

Cell-wall structural changes in wheat straw pretreated for bioethanol production

Background  

Pretreatment is an essential step in the enzymatic hydrolysis of biomass and subsequent production of bioethanol. Recent results indicate that only a mild pretreatment is necessary in an industrial, economically feasible system. The Integrated Biomass Utilisation System hydrothermal pretreatment process has previously been shown to be effective in preparing wheat straw for these processes without the application of additional chemicals. In the current work, the effect of the pretreatment on the straw cell-wall matrix and its components are characterised microscopically (atomic force microscopy and scanning electron microscopy) and spectroscopically (attenuated total reflectance Fourier transform infrared spectroscopy) in order to understand this increase in digestibility.