High-throughput Screening of Recalcitrance Variations in Lignocellulosic Biomass: Total Lignin, Lignin Monomers, and Enzymatic Sugar Release

Summary

Plant cell wall structure and chemistry traits are evaluated to identify ideal feedstocks for biofuels and bio-materials. Standard methods have limitations when applied to large data sets. These high-throughput pretreatment, enzyme saccharification, and pyrolysis-molecular beam mass spectrometry methods compare large numbers of biomass samples with decreased experimental time and cost.

Abstract

The conversion of lignocellulosic biomass to fuels, chemicals, and other commodities has been explored as one possible pathway toward reductions in the use of non-renewable energy sources. In order to identify which plants, out of a diverse pool, have the desired chemical traits for downstream applications, attributes, such as cellulose and lignin content, or monomeric sugar release following an enzymatic saccharification, must be compared. The experimental and data analysis protocols of the standard methods of analysis can be time-consuming, thereby limiting the number of samples that can be measured. High-throughput (HTP) methods alleviate the shortcomings of the standard methods, and permit the rapid screening of available samples to isolate those possessing the desired traits. This study illustrates the HTP sugar release and pyrolysis-molecular beam mass spectrometry pipelines employed at the National Renewable Energy Lab. These pipelines have enabled the efficient assessment of thousands of plants while decreasing experimental time and costs through reductions in labor and consumables.

Introduction

As the global supply of non-renewable fuels and their associated products declines, scientists have been challenged to create similar fuels and chemicals from plant-derived sources¹. A key aspect of this work is determining which species of plants may be suitable for the production of biofuels and biomaterials^2,3. Typically, these feedstocks are evaluated for lignin, cellulose, and hemicellulose content; as well as their susceptibility to deconstruction (recalcitrance) through thermal, mechanical, and/or chemical pretreatment with or without subsequent enzyme saccharification. More detailed analyses are used to determine the specific composition of the lignin and hemicellulose fractions as well as optimal enzyme activities needed. Transgenic modifications of plants that do not intrinsically possess ideal traits for biochemical or thermochemical conversion to desired commodities have provided researchers with a greatly expanded source of potential feedstocks⁴. The standard analytical methods for quantifying the chemical traits of a plant, while quite useful for small sample sets, are unsuited for the rapid screening of hundreds or thousands of samples^5-7. The HTP methods described herein have been developed to rapidly and efficiently evaluate large numbers of biomass variants for changes in cell wall recalcitrance to thermochemical and/or enzymatic degradation.

It is critical to understand that the HTP screening assays described herein have not been designed to maximize conversion or yield. The objective is to determine relative differences in the intrinsic recalcitrance of related biomass samples. As a result, many of the analysis steps differ from the “typical” biomass conversion assays, where the objective is to obtain maximum conversion rate or extent. For example, lower pretreatment severities and shorter enzyme hydrolysis times are used to maximize differences between samples. In most cases, relatively high enzyme loadings are used to reduce differences due to experimental variation in enzyme activity, which could skew the results significantly.

Rapid techniques for determining the composition of plant cell-walls and the monomeric sugars liberated following enzymatic saccharification include robotics, customized, thermochemically compatible 96-well plates, and modifications of standard laboratory methods^8-11 and instrumental protocols, such as vibrational spectroscopy (infrared (IR), near-infrared (NIR), or Raman) and nuclear magnetic resonance (NMR)^12-17. These methodologies are key to isolating feedstocks with high cellulose or low lignin contents, or those expected to yield the highest glucose, xylose, ethanol, etc. These methods have enabled downscaled analyses that employ smaller quantities of biomass and consumables, leading to reductions in experimental expense¹⁸. Another feature of this methodological approach is that various experimental conditions can be rapidly, and in some cases simultaneously, evaluated. For example, a variety of different pretreatment strategies or enzyme cocktails can be tested, allowing the most optimal experimental parameters to be quickly identified and employed. Popular feedstocks, such as corn stover⁹, poplar^8,10, sugarcane bagasse⁸, and switchgrass⁸ have been successfully evaluated using these HTP methods.

Total lignin and lignin monomeric composition are also commonly quantified biomass traits. Reductions in lignin content have been shown to increase the enzymatic digestibility of polysaccharides^19,20. The role that the lignin monomeric ratio (often reported as syringyl/guaiacyl (S/G) content) plays in the deconstruction of the plant cell wall is still under investigation. Some reports have indicated that reductions in the S/G ratio led to increased glucose yields following hydrolysis²¹, while other studies unveil the opposite trend^19,22. High throughput methods for evaluating lignin and its monomers include vibrational spectroscopy (IR, NIR, and Raman^23-26) coupled with multivariate analysis, and pyrolysis molecular beam mass spectrometry (pyMBMS)^27,28.

When developing HTP methods for screening biomass, several integral considerations need to be kept in mind. One key aspect is the complexity of the method. What is the required skill level for the technique? Chemometric analyses, for example, require specific skills for constructing, evaluating, and maintaining predictive models. The standard methods exhibit undesirable preparatory or data analysis steps or employ toxic reagents. Development of the models is an ongoing process where new data is incorporated into the model over time to increase the model’s robustness. Another consideration is the cost-savings and decreased experimental analysis times of the proposed high-throughput methods. If the method is quite rapid, but very costly, it may not be a feasible technique for many labs to adopt. The methods illustrated in this manuscript are variants of standardized techniques, modified to amplify the throughput capabilities. These protocols quantitatively measure the biomass traits of interest without necessitating the development of predictive models. This is a key attribute of these techniques, since predictive methods, while exhibiting strong correlations with the standard analyses used to develop the models, are not as accurate as actually measuring the quantity of interest for the samples. Whereas the methods used are essentially scaled down versions of standard bench-scale analytical methods, accuracy and precision are traded for speed and throughput. Mostly, this outcome is due to higher errors in small volume pipetting and weighing; as well as increased sample heterogeneity as sample size is decreased. While large sample sets can be screened and compared, great care must be exercised when making comparisons between separate campaigns and to bench-scale results.

The most time-consuming steps involve the physical manipulation of the biomass. Grinding samples may take several min per sample, including cleaning out the mill between samples. Manually loading, unloading, and cleaning hoppers and filling and emptying tea bags and sample bags is also very labor intensive. While each step may take a minute or more, doing thousands of samples may take many hours or even days. The robots can load a typical reactor plate with biomass in about 3 to 4 hr or 6 to 8 plates day^-1 robot^-1. This situation depends on the precision parameters used as well as the type and amount of biomass to be tested. Filling reactor plates with water, dilute acid, or enzyme is quickly done using a liquid handling robot. Pretreatment of a plate stack (1 to 20 reactor plates) takes between 1 and 3 hr when assembly, cool down, and disassembly is included. Enzyme hydrolysis takes 3 days and the sugar analysis requires about 1 hr of prep time plus 10 min per reactor plate to complete the assay and read the results. A weekly schedule of set pretreatment and analysis days accommodates a reasonable work schedule, minimizing odd-hour and weekend efforts for the human component of the assay and allows for processing ~800 to 1,000 samples per week on an ongoing basis. The maximum throughput depends on several factors, mainly how much hardware (robots, reactors plates, etc.) and how much “software” (i.e., staffing) are available to do the manual work. The practical upper limit is 2,500 to 3,000 samples/week; however, that output requires 7 day-a-week operation and multiple student interns and technicians. In comparison, 3,000 samples by HPLC would require approximately 125 days of sample analysis plus the additional labor of manually weighing samples into reactors and filtering samples prior to analysis.

Protocol

1. High-throughput Determination of Glucose and Xylose Yields Following Enzymatic Saccharification^9,29

1. Sample Preparation (Grinding, De-starching, Extraction, Pretreatment)
   1. Grind at least 300 mg of each biomass sample using a Wiley mill, such that the particles pass through a 20 mesh (850 µm) screen. Transfer to anti-static zip-top bags (typically bar-coded) and record sample information to the barcode database.
   2. Add approximately 250 mg or more of the ground biomass from anti-static bag to a numbered (with pencil, do not use ink or marker) tea-bag, carefully roll up the teabags, being sure to fold the ends over the biomass to prevent loss during de-starching and extraction.
   3. Wrap the teabag closed using tin-coated copper wire. Record the teabag number for each barcoded sample.
   4. Prepare de-starching enzyme solution from commercial enzymes (typically, 0.25% (v/v) glucoamylase (~1,600 AGU/L) and 1.5% (v/v) alpha-amylase (~2,900 KNU-S/L) in 0.1 M sodium acetate (pH 5.0)). Prepare 16 ml per g of bulk biomass or 500 ml per 120 teabag samples. Note: Loadings capable of removing starch from ground biomass should be determined empirically by testing for starch after digestion with a range of enzyme loadings and ratios.
   5. In a plastic container, add 16 ml of de-starching enzyme solution per 1 g of bulk ground biomass. For a batch de-starching protocol, add 120 teabags to 500 ml of the buffer-enzyme solution.
   6. Incubate in a shaker at 55 °C for 24 (± 4) hr, at 120 rpm to remove possible starch.
   7. After the de-starching incubation, rinse and soak the biomass in several liters of deionized water for 30 min. Repeat this process two additional times to remove buffer salts that can cause bumping (formation of gas bubbles in the solution that can result in a sudden and violent rise in the level of the solution, causing hot liquid ethanol to cascade out of the reaction vessel) during the extraction.
   8. Following the exhaustive rinsing of the de-starched biomass, place the teabags into the Soxhlet column for extraction. No thimble is required for this step.
   9. Set up the Soxhlet reflux, using 95% ethanol and extract the samples for 24 hr.
   10. Remove the teabags from the Soxhlet reactor and spread out in a single layer on a flat tray.
   11. Allow the samples to dry overnight at room temperature in a fume hood.
   12. Unroll the teabags and return the dried biomass to original barcoded anti-static bags.
       Note: The anti-static bags are efficient at reducing static electricity in the biomass, improving the handling characteristics. If other storage options are used, additional biomass may be needed due to the biomass clinging to the side of the storage container.
   13. Transfer at least 50 mg of the dried biomass to a barcoded hopper (using more material is better for accurate dispensing). Scan barcodes of anti-static bags and the receiving hopper to ensure accurate sample tracking.
   14. Load hoppers onto solids weighing robot, paying close attention to the order of the samples in the racks. Load enough reactor plates to contain all the samples and select the dispensing protocol based on the number of plates used.
   15. Robotically weigh 5 mg of the dried samples (± 0.3 mg) into acid-resistant stainless steel 96-well plates. Weigh out 3 replicates of each sample distributed around the plate to minimize any localized variations.
   16. Include 8 control biomass samples of a well-characterized biomass standard material in order to track assay performance. For multiple plates, the use of multiple standard biomass hoppers will minimize particle size drift caused by sieving in the hoppers over repeated dispensing cycles.
       Note: In each plate, there should be 24 samples with 3 replicates, 4 blanks consisting of deionized water and enzyme, and 8 controls, using the previously characterized standard biomass. The 3 corner wells of each of the 4 corners of the plate are reserved for the sugar standards.
   17. Check blank and sugar standard wells for errant biomass particles and remove if present.
   18. Add 250 µl of deionized water to each well, and seal the plates with silicone adhesive-backed polytetrafluoroethylene (PTFE) tape.
   19. Using a 1/8” soldering iron tip, pierce the PTFE tape at each steam port (117 total) for each plate. Use an empty plate stacked on sealed reactor plate as a guide and to restrict PTFE film movement.
   20. Clamp the plates tightly with 0.031” thick glass-reinforced PTFE gaskets (pre-punched with holes for steam ports) between plates and empty plates on top and bottom of stack. Pretreat the samples using a steam reactor set to 180 °C for 17.5 min, or other temperature/time combinations based on desired severity.
   21. Cool reactor plates to 50 °C by flooding with deionized water.
2. Enzymatic Saccharification
   1. Prepare an enzymatic saccharification solution consisting of 8% (v/v) enzyme solution in 1.0 M sodium citrate, pH 5.0. Prepare 5 ml per reactor plate. Note: Dilution required should be determined based on activity and protein content of the specific stock enzyme solution.
   2. When the plates are cool, centrifuge them in a swinging bucket rotor at 1,500 x g for 20 min. Remove sealing film. Note: These plates are heavy and the centrifuge specifications should be checked for compatibility.
   3. Add 40 µl of the 8% enzyme stock solution to each well (70 mg enzyme per g biomass).
   4. Reseal with new PTFE tape. Place sealed plate into magnetic plate clamp.
   5. Gently mix the samples by inversion (at least 15 times), and incubate at 50 °C for 70 hr.
   6. When the saccharification has concluded, mix by inversion and centrifuge the plates at 1,500 x g for 20 min.
3. Sugar Assay
   1. Prepare a set of 6 glucose and xylose combined calibration standards in 0.014 M citrate buffer (pH 5.0) ranging from 0 to 0.750 mg/ml (0, 0.2, 0.3, 0.45, 0.65, and 0.75 mg/ml recommended) and 0 to 0.600 mg/ml (0, 0.1, 0.2, 0.35, 0.45, and 0.6 mg/ml recommended) for glucose and xylose, respectively.
   2. Prepare the glucose oxidase/peroxidase (GOPOD) and xylose dehydrogenase (XDH) reagents according to instructions in the kit.
   3. Using a pipette, remove 200 µl of liquid from the 4 corner wells and edge wells adjacent to the corner wells (12 total wells) of the reactor plate.
   4. Using a pipette, dispense 180 µl deionized water to each well of a 96-well polystyrene flat-bottom dilution plate. Do not add water to the 12 sugar standard and corner wells (remove those tips if using a 96-channel head).
   5. Using a pipette, dispense 180 µl GOPOD reagent to each well of the glucose assay plate.
   6. Using a pipette, dispense 180 µl XDH reagent to each well of the xylose assay plate.
   7. Using a pipette, transfer 20 µl hydrolysate aliquots from the 96-well reactor plate to the dilution plate. Pipet from the upper section of the wells to avoid biomass solids and residual liquid in corner wells. Mix by trituration for at least 10 cycles.
   8. Using a pipette, transfer 110 µl of sugar standards, in duplicate, to the corner wells of the dilution plate.
   9. Using a pipette, transfer 20 µl aliquots from the dilution plate to the glucose and xylose assay plates. Mix by trituration.
   10. Incubate the glucose and xylose assay plates at room temperature for 30 min. Carefully break any surface bubbles before reading. A heat gun briefly passed over the surface of the plate works well.
   11. Using an ultraviolet/visible 96-well plate reader, set the measured wavelength to 510 nm and record the absorbance against a reagent blank. This measurement monitors the formation of quinonimine, which is proportional to glucose concentration. The glucose concentration is calculated from the calibration curve based on the calibration standards prepared in 1.3.1.
   12. Using an ultraviolet/visible 96-well plate reader, set the measured wavelength to 340 nm and record the absorbance. This measurement monitors the reduction of NAD⁺ to NADH, which is proportional to xylose concentration. The xylose concentration is calculated from the calibration curve based on the calibration standards prepared in 1.3.1.

2. High-throughput Determination of Total Lignin and Lignin Monomeric Content Using pyMBMS ²⁸

1. Sample Preparation
   1. Grind and extract the biomass using the methods described in steps 1.1.1, and 1.1.6-1.1.8. This includes grinding and extracting of a set of standards to use as experimental controls.
      Note: The pyMBMS measurements are not particle-size dependent, so if only using the pyMBMS protocol, biomass preparation should be carried out to allow the sample to fit in the sample holder, <4 mm.
   2. Using a small spatula dispense approximately 4 mg (3 to 5 mg preferred) of the prepared biomass into an 80 µl stainless steel cup designed for the auto-sampler.
   3. Ensure that at least 10% of the samples being analyzed are control standards such as those available from the National Institute of Standards and Technology (sugarcane bagasse-8491; poplar-8492; pine-8493; or wheat straw-8494). The standard can also be any species analogous to the samples to be analyzed that have already been characterized using standard methods.
   4. Randomly load the samples into the auto-sampler cups using tweezers to avoid bias due to possible spectrometer drift over time. Note: A typical randomization of the samples would include the measurement of all samples once, followed by a re-randomization of the order of the samples for a duplicate measurement. Randomization programs are available online.
   5. Using a standard hole-punch, manually produce glass filter discs from type A/D glass fiber sheets, with no binder. Hold the round glass fiber filter with tweezers, center it over the sample cup, and push into the sample using a 3.5 mm Allen wrench to confine the material in each cup during the experiment.
2. Instrumental Protocol
   1. Calibrate the mass spectrometer using a known standard that has peak intensities over the entire range of compounds that may exist for the experimental samples. For typical biomass samples, use perfluorotributylamine (PFTBA).
   2. Set the helium carrier gas flow rate to 0.9 L/min using a gas flow meter.
   3. Set the auto-sampler furnace to a pyrolysis temperature of 500 °C and the interface temperature to 350 °C using the auto-sampler software. Note: A 1/8” stainless steel heated transfer line wrapped in heat tape that connects the auto-sampler to the mass spectrometer is controlled using a heat controller at 250 °C.
   4. Begin data acquisition on the mass spectrometer and wait at least 60 sec to obtain sufficient data for background spectra collection.
   5. Start the automated auto-sampler method with the specifications from 2.2.2. Note: The auto-sampler drops each sample individually into the auto-sampler furnace. The total data acquisition time is approximately 1.5 min; however, pyrolysis of a typical 4 mg sample is complete after 30 sec.
   6. Record total ion content (TIC) of each sample using mass spectrometer software at 0.5 sec scan rate. Record intensities between m/z 30 to 450.
      Note: Typical biomass compounds use soft ionization at 17 eV. The instrument can record larger intervals from m/z 1 to 1,000; however, scan rate will be limited by computer CPU power.
   7. Remove background from the spectra using the manual enhance feature in the software. Note: A 60 scan portion of the baseline at the beginning of data collection is used to calculate an average background value. This average background spectra is removed from the experimental sample spectra automatically in the mass spectrometer software.
   8. Import the single column text file created by the mass spectrometer software containing the spectral data for each sample, into a database program and combine all the samples into one database. Add any applicable metadata to the spreadsheet. Import the formatted data (spreadsheet/CSV file) into a statistical software package and mean normalize the spectra to account for variation in the pyrolyzed sample masses.
   9. Use a statistical software package to perform a principal component analysis (PCA) using the spectral data to analyze grouping of the replicated standard samples used in the measurements, as well as to evaluate which peaks are integral to the classification of chemical compounds in the loadings plot²⁸.
      Note: PCA groups the samples based on the similarity of their spectra, and allows a check of the standards to gauge experimental error due to instrument drift during the run.
   10. To calculate the lignin syringyl (S)/guaiacyl (G) ratio, sum the areas of the S peaks (m/z = 154, 167, 168, 182, 194, 208, and 210) and divide by the sum of G peaks at 124, 137, 138, 150, 164, and 178.
   11. To calculate the total lignin content, sum the lignin peaks with m/z = 120, 124, 137, 138, 150, 152, 154, 164, 167, 178, 180, 182, 194, and 210.
   12. Calculate a correction factor for scaling the pyMBMS measurement to a standard method for estimating total lignin, such as Klason lignin. Divide the Klason lignin value of the individual standard by the total lignin content measured for that standard sample using pyMBMS.
   13. Apply this correction factor to all like-species in the data set. Repeat for each type of biomass analyzed. Note: The correction factor can vary significantly based on the S/G of the biomass analyzed.

Results

The combined effect of the thermochemical pretreatment and subsequent enzyme saccharification is measured as a function of the mass of glucose and xylose released at the end of the assay. The results are reported in terms of milligrams of glucose and xylose released per gram of biomass. This is in stark contrast to data reported from bench-scale assays, which is usually reported as percent theoretical yield based on compositional analysis of the starting material. As it is not yet practical to carry out compositional ana...

Discussion

The key sample preparation steps for obtaining accurate and reproducible data when conducting high-throughput screening experiments are as follows:

Sugar Release Assay:

In general, samples are prepared in lots ranging from a few dozen to several thousand at a time. Each major step is typically carried out for all samples prior to moving forward in order to minimize variations in preparation between samples. De-starching was not originally part of the protocol and ca...

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
Biomek FX Automated Workstation	Beckman Coulter	Biomek FX	Automated Liquid Handler
Wiley mill	Thomas Scientific	3375E15 (Model 4), or 3383L20 (Mini-mill)
anti-static bags	Minigrip*	MGST4P02503	2.5x3", multiple suppliers available
tin-coated copper wire	McMaster-Carr	8871K84	0.016" diameter, bend-and-stay wire
tea-bags	Herbco	press n' brew teabags	3.5x5 inches
gluco-amylase	Novozymes	Spirizyme Fuel
alpha-amylase	Novozymes	Liquozyme SC DS
sodium acetate trihydrate	any chemical supplier		reagent grade
acetic acid	any chemical supplier		reagent grade
190 proof (95%) ethanol	any chemical supplier		reagent grade
hoppers	Freeslate
96-well C-276 Hastelloy plates	Aspen Machining (Lafayette, Colorado)	N/A (custom built)
1/8” soldering iron tip	Sears
silicone-adhesive backed Teflon tape	3M	5180	3" wide (36-yard rolls)
enzyme solution	Novozymes		Cellic CTec2
citric acid monohydrate	any chemical supplier
trisodium citrate dihydrate	any chemical supplier
disposable, polystyrene 96-well plates	Greiner Bio-One	655101	or equivalent; multiple suppliers available
glucose oxidase/peroxidase	Megazyme	K-Gluc	Megazyme D-glucose assay kit
xylose dehydrogenase	Megazyme	K-Xylose	Megazyme D-xylose assay kit
glucose standard solution	Megazyme	K-Gluc	Megazyme D-glucose assay kit
xylose standard solution	Megazyme	K-Xylose	Megazyme D-xylose assay kit
stainless steel sample cups	Frontier Laboratories	PY1-EC80F
glass fiber sheets	Pall	66227	8x10" sheets; circles punched with standard hole punch
Sugarcane Bagasse Whole Biomass Feedstock	NIST	8491
Eastern Cottonwood (poplar) Whole Biomass Feedstock	NIST	8492
Monterey Pine Whole Biomass Feedstock	NIST	8493
Wheat Straw Whole Biomass Feedstock	NIST	8494