Cellulosic Biomass Pretreatment and Sugar Yields

as a Function of Biomass Particle Size

Outcomes • Ionic liquid (IL) pretreatment results in

greater cell wall disruption

reduced crystallinity

increase accessible surface area

Higher saccharification efficiencies

Background • Lignocellulosic biomass has enormous

potential as feedstock for fuels and

chemical products.

• Efficient pretreatment processes are

needed for optimal enzymatic

saccharification.

Approach • Compared four feedstock pretreatments

as a function of particle size and sugar

yields

• Determined and compared:

Composition

Crystallinity

Structural Differences

Accessible Surface Area

Enzymatic Saccharification

Significance • Ionic liquid (IL) pretreatment gives higher saccharification efficiencies than other methods,

greatest at larger particle sizes above 75m; thus, less energy input to size reduction of starting

materials.

Compositions of untreated vs. pretreated switchgrass

Crystallinity Index

Surface area of the biomass samples (m2 / g)

SEM images of untreated vs. pretreated swichgrass Yield of reducing sugars

Dougherty, M. J., et al. PLOS ONE, 9(6), e100836 (2014). DOI: 0.1371/journal.pone.0100836

Synthetic Biology Open Language (SBOL)

design communication standard

Outcomes • Implemented SBOL as an XML/RDF data serialization and developed software libraries and specification documentation.

• Demonstrated utility of SBOL for design exchange between different software tools and between academia and industry.

SBOL-enabled design collaboration across research and commercial institutions

Galdzicki, et al., Nature Biotechnology 32:545–550 (2014).

Background • Re-using previously validated

designs is critical to the progression

of synthetic biology from a research

discipline to an engineering practice.

• SBOL represents designs in a

community-driven, formalized format

for exchange between software tools,

research groups, and commercial

service providers.

Approach • Standardize SBOL as a design

exchange data format, and provide

software libraries and specification

documentation to help scientists

benefit from SBOL in their own

research.

Significance • SBOL contributes to the principled engineering of biological organisms through the

standardization of design information exchange.

The plant glycosyltransferase clone

collection for functional genomics

Outcomes • The clone collection contains 403 Arabidopsis GTs and 96 rice GTs all sequence verified

• The creation of particle bombardment plasmids (pBullet) that are optimized for transient co-

localization studies1

Robotics used for high-

throughput cloning

Lao, et al., Plant Journal. DOI: 10.1111/tpj.12577 (2014).

Background • Glycosyltransferases (GTs) are

involved in plant cell wall

biosynthesis

• Plant biomass, composed of cell

walls, can be used for production

of advanced biofuels

• The specific functions of these

GTs remain largely unknown

Approach • Use of robotics system for high-

throughput cloning

• Manual cloning of difficult and

complicated genes that cannot

be done with robotics

• Creation of tools to allow for

easy localization studies

Significance • This collection can help accelerate our understanding of lignocellulosic material in plants

and development of improved bioenergy crops

• This allows the scientific community to study the GTs without going through the mundane

task of manually cloning interesting candidates

Plasmid map of the pBullet plasmids Plasmid map of the pBullet plasmids

Demonstrating the utilization of the pBullet collection. Confirmation of pBullet co-localization marker with ECFP in onion epidermal cells. Scale bar = 10 µm.

Bombardment tool for co-localization studies in plants

Economic impact of advances in ionic

liquid pretreatment on cellulosic biorefinery

Background • A novel One-Pot (OP) ionic liquid (IL)

pretreatment process developed at JBEI was

shown to reduce water consumption compared

to standard Water-Wash (WW) IL pretreatment

process1.

• Economic viability of both WW and OP routes

was investigated in this study2.

Approach • A technoeconomic analysis (TEA) of the entire

biorefinery (Fig. 1) with WW- and OP-based

pretreatments was carried out to benchmark

the Minimum Ethanol Selling Price (MESP)

and to identify important cost drivers.

Outcomes • From an economic perspective, both the WW

and the OP processes require high biomass

loading (50%) (Fig 2a).

• While at 50% biomass loading both WW and

OP processes exhibited comparable

economics (MESP of $6.3/gal), the OP route

was found to be more sustainable as it

requires significantly less water (Fig 2b).

Significance • TEA has successfully identified cost drivers - i.e., water usage in WW route and acid/base

consumption in OP route (Fig 2a and 2c)

• Lignin valorization was found to be essential for economic feasibility (Fig 2d)

1Shi, Jian, et al. Green Chem. 15.9:2579-2589 (2014). 2Konda, NVSN Murthy, et al. Biotechnology for Biofuels 7.1:86 (2014).

Figure 1. Simplified representation of biorefinery with WW (blue) and OP (red) IL pretreatment processes

Figure 2. Comparison of economic and water usage impacts of WW and OP routes.

High-throughput prediction of eucalypt lignin syringyl/guaiacyl content

using multivariate analysis: a comparison between mid-infrared, near-

infrared, and Raman spectroscopies for model development

Outcomes

• MIR and Raman spectroscopy led to the most

accurate predictive models.2

• High-throughput Raman modelling of lignin

S/G ratios in Acacias and eucalypts resulted in

the ability to predict the S/G ratio in 269

unknown samples with an accuracy equivalent

to the standard data used to construct the model.

Background

• The standard methods for evaluating the important

traits of biomass are laborious, may require toxic

chemicals, and can destroy the sample.1

• The use of spectroscopy coupled with a standard

method can alleviate these shortcomings, and allow

the rapid screening of thousands of different plant

species to assess which may be best suited for

further biofuel research.1,2

Approach • Develop robust models capable of predicting the trait of

interest (i.e. lignin syringyl/guaiacyl (S/G) ratio) from the

standard method and spectral data using of mid-infrared,

near-infrared, and Raman spectroscopy.2

Significance

• Enables researchers to rapidly evaluate more

plant samples much faster than the standard

methods, thereby reducing experimental time

and expense.

1Lupoi et al., Bioenergy Research, Vol.7: 1-23 (2014). 2Lupoi et al., Biotechnology for Biofuels, Vol.7: 93 (2014).

Reference vs. predicted lignin S/G ratios

using Raman spectra and pyrolysis data

Step 1. Collect Spectral Data Step 2. Collect Reference Data

Step 3. Construct & Evaluate

Predictive Models

Step 4. Validate Models

& Calculate Predictions

Raman Spectrometer Pyrolysis Molecular Beam

Mass Spectrum (pyMBMS) @ NREL

Specific mass fragments

correspond to S and G molecules,

enabling calculation of ratio

Spectral Transformation

Combine calibration and validation

data sets; assess accuracy of

pyMBMS reference means to those

predicted using model