Name: estimation of plant biomass lignin content using thioglycolic acid (tga)
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We thank the Department of Plant &#38; Soil Science and Cotton Inc. for their partial support of this study.

1. Preparation of plant samples
<ol>
	<li>Collect two-month-old cotton plants from the greenhouse (Figure 1A).</li>
	<li>Flip plant pots gently to separate soil and roots with intact lateral roots by loosening the soil around the plant (Figure 1B).</li>
	<li>Wash the collected plants thoroughly in trays filled with water to remove all the dirt (for root samples) (Figure 1C).</li>
	<li>Use paper towels to dry separated root, stem, ...

<ol>
	<li>Freudenberg, K., Neish, A. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Constitutionand Biosynthesis of Lignin. , 129 (1968).</li><li>Chio, C., Sain, M., Qin, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Lignin+utilization:+A+review+of+lignin+depolymerization+from+various+aspects.">Lignin utilization: A review of lignin depolymerization from various aspects.</a> Renewable and Sustainable Energy Reviews. 107, 232-249 (2019).</li><li>Sun, Z., Fridrich, B., de Santi, A., Elangovan, S., Barta, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Bright+Side+of+Lignin+Depolymerization:+Toward+New+Platform+Chemicals.">Bright Side of Lignin Depolymerization: Toward New Platform Chemicals.</a> Chemical Reviews. 118, 614-678 (2018).</li><li>Xu, F., Sun, R. 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I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+distribution+of+lignin+in+birchwood+as+determined+by+ultraviolet+microscopy.">The distribution of lignin in birchwood as determined by ultraviolet microscopy.</a> Holzforschung. 24, 118-124 (1970).</li><li>Schultz, T. P., Templeton, M. C., McGinnis, G. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Rapid+determination+of+lignocellulose+by+diffuse+reflectance+Fourier+transform+infrared+spectrometry.">Rapid determination of lignocellulose by diffuse reflectance Fourier transform infrared spectrometry.</a> Analytical Chemistry. 57, 2867-2869 (1985).</li><li>Dence, C. W., Lin, S. Y., Dence, C. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Determination+of+Lignin.">The Determination of Lignin.</a> Methods in Lignin Chemistry. , (1992).</li><li>Adler, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Lignin+chemistry-past,+present+and+future.">Lignin chemistry-past, present and future.</a> Wood Science and Technology. 11, 169-218 (1977).</li><li>Brinkmann, K., Blaschke, L., Polle, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Comparison+of+different+methods+for+lignin+determination+as+a+basis+for+calibration+of+near-infrared+reflectance+spectroscopy+and+implications+of+lignoproteins.">Comparison of different methods for lignin determination as a basis for calibration of near-infrared reflectance spectroscopy and implications of lignoproteins.</a> Journal of Chemical Ecology. 28, 2483-2501 (2002).</li><li>Pandey, M. P., Kim, C. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Lignin+Depolymerization+and+Conversion:+A+Review+of+Thermochemical+Methods.">Lignin Depolymerization and Conversion: A Review of Thermochemical Methods.</a> Chemical Engineering &amp; Technology. 34, 29-41 (2011).</li><li>Moreira-Vilar, F. C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+acetyl+bromide+method+is+faster,+simpler+and+presents+best+recovery+of+lignin+in+different+herbaceous+tissues+than+Klason+and+thioglycolic+acid+methods.">The acetyl bromide method is faster, simpler and presents best recovery of lignin in different herbaceous tissues than Klason and thioglycolic acid methods.</a> PLoS One. 9, 110000 (2014).</li><li>Hatfield, R. D., Grabber, J., Ralph, J., Brei, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Using+the+Acetyl+Bromide+Assay+To+Determine+Lignin+Concentrations+in+Herbaceous+Plants:+Some+Cautionary+Notes.">Using the Acetyl Bromide Assay To Determine Lignin Concentrations in Herbaceous Plants: Some Cautionary Notes.</a> Journal of Agricultural and Food Chemistry. 47, 628-632 (1999).</li><li>Suzuki, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High-throughput+determination+of+thioglycolic+acid+lignin+from+rice.">High-throughput determination of thioglycolic acid lignin from rice.</a> Plant Biotechnology. 26, 337-340 (2009).</li><li>Nakatsubo, F., Tanahashi, M., Higuchi, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Acidolysis+of+Bamboo+Lignin+II+:+Isolation+and+Identification+of+Acidolysis+Products.">Acidolysis of Bamboo Lignin II : Isolation and Identification of Acidolysis Products.</a> Wood research. 53, 9-18 (1972).</li><li>Aro, T., Fatehi, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Production+and+Application+of+Lignosulfonates+and+Sulfonated+Lignin.">Production and Application of Lignosulfonates and Sulfonated Lignin.</a> ChemSusChem. 10, 1861-1877 (2017).</li><li>Frei, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Lignin:+Characterization+of+a+Multifaceted+Crop+Component.">Lignin: Characterization of a Multifaceted Crop Component.</a> The Scientific World Journal. 2013, 436517 (2013).</li><li>Lora, J. H., Glasser, W. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Recent+Industrial+Applications+of+Lignin:+A+Sustainable+Alternative+to+Nonrenewable+Materials.">Recent Industrial Applications of Lignin: A Sustainable Alternative to Nonrenewable Materials.</a> Journal of Polymers and the Environment. 10, 39-48 (2002).</li><li>Wang, R., Zhou, B., Wang, Z. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Study+on+the+Preparation+and+Application+of+Lignin-Derived+Polycarboxylic+Acids.">Study on the Preparation and Application of Lignin-Derived Polycarboxylic Acids.</a> Journal of Chemistry. 2019, 5493745 (2019).</li><li>Welker, C. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Engineering+Plant+Biomass+Lignin+Content+and+Composition+for+Biofuels+and+Bioproducts.">Engineering Plant Biomass Lignin Content and Composition for Biofuels and Bioproducts.</a> Energies. 8, 7654-7676 (2015).</li><li>Mendu, V., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Global+bioenergy+potential+from+high-lignin+agricultural+residue.">Global bioenergy potential from high-lignin agricultural residue.</a> Proceedings of the National Academy of Sciences. 109, 4014-4019 (2012).</li><li>Brinkmann, K., Blaschke, L., Polle, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Comparison+of+Different+Methods+for+Lignin+Determination+as+a+Basis+for+Calibration+of+Near-Infrared+Reflectance+Spectroscopy+and+Implications+of+Lignoproteins.">Comparison of Different Methods for Lignin Determination as a Basis for Calibration of Near-Infrared Reflectance Spectroscopy and Implications of Lignoproteins.</a> Journal of Chemical Ecology. 28, 2483-2501 (2002).</li><li>Moreira-Vilar, F. C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Acetyl+Bromide+Method+Is+Faster,+Simpler+and+Presents+Best+Recovery+of+Lignin+in+Different+Herbaceous+Tissues+than+Klason+and+Thioglycolic+Acid+Methods.">The Acetyl Bromide Method Is Faster, Simpler and Presents Best Recovery of Lignin in Different Herbaceous Tissues than Klason and Thioglycolic Acid Methods.</a> PLoS One. 9, 110000 (2014).</li><li>Iwaasa, A. D., Beauchemin, K. A., Acharya, S. N., Buchanan-Smith, J. 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Lignin plays a significant role in plant growth and development and recently has been extensively studied for biofuel, bioenergy and bioproduct applications. Lignin is rich in aromatic compounds that are stored in all vascular plant secondary cell walls. It has several industrial applications such as wood panel products, bio dispersants, flocculants, polyurethane foams and in resins of circuit boards29,30,31. Most of the lignin ...

Lignin is one of the vital load-bearing components of plant cell walls and the second most abundant polymer on Earth1. Chemically, lignin is a crosslinked heteropolymer made up of high molecular weight complex phenolic compounds that form a natural renewable source of aromatic polymers and synthesis of biomaterials2,3. This natural polymer plays significant roles in plant growth, development, survival, mechanical support, cell wall rigidity, water transport, mineral transport, lodging resistance, tissue and organ development, deposition of energy, and protection from biotic and abiotic stresses4,5,6,7. Lignin is primarily composed of three different monolignols: coniferyl, sinapyl and p-coumaryl alcohols that are derived from the phenyl propanoid pathway8,9. The amount of lignin and the composition of monomers vary based on the plant species, the tissue/organ type, and different stages of plant development10. Lignin is broadly classified into softwood, hardwood, and grass lignin based on the source and monolignol composition. Softwood is primarily composed of 95% coniferyl alcohol with 4% p-coumaryl and 1% sinapyl alcohols. Hardwood has coniferyl and sinapyl alcohols in equal proportions, while grass lignin is composed of various proportions of coniferyl, sinapyl and p-coumaryl alcohols11,12. The composition of monomers is critical as it determines the lignin strength, decomposition, and degradation of the cell wall as well as determining molecular structure, branching, and crosslinking with other polysaccharides13,14.
Lignin research is gaining importance in foraging, textile industries, paper industries, and for bioethanol, biofuel, and bio-products due to its low cost and high abundance15,16. Various chemical methods (e.g., acetyl bromide, acid detergents, Klason, and permanganate oxidation) along with instrumental methods (e.g., near infrared (NIR) spectroscopy, nuclear magnetic resonance (NMR) spectroscopy, and ultraviolet (UV) spectrophotometry) were used for lignin quantification9,17. The analysis methods of lignin are generally classified based on electromagnetic radiation, gravimetry, and solubility. The principle behind lignin estimation by&#160;electromagnetic radiation was based on the&#160;chemical property of lignin by which it absorbs light at specific wavelengths. These results were estimated based on the principle that lignin has a stronger UV absorbance than carbohydrates. In 1962, Bolker and Somerville used potassium chloride pellets to estimate lignin content in wood18. However, this method has drawbacks in the estimation of lignin content from herbaceous samples due to the presence of non-lignin phenolic compounds and the absence of an appropriate extinction coefficient. In 1970, Fergus and Goring found that the guaiacyl and syringyl compound absorption maxima were at 280 nm and 270 nm, which corrected the extinction coefficient issue of the Bolker and Somerville method19. Later, infrared spectroscopy, a highly sensitive technique for characterizing phenolics, was also used for lignin estimation with a small amount of plant biomass samples. One example of such technology&#160;was diffuse-reflectance Fourier transform spectrophotometry. This method, however, lacks a proper standard similar to the UV method20. Later, the lignin content was estimated by NIRS (near infrared spectroscopy) and NMR (nuclear magnetic resonance spectroscopy). Though, there are disadvantages in these methods, they do not alter the chemical structure of lignin, retaining its purity20.
The gravimetric Klason method is a direct and the most reliable analytical method for lignin estimation of woody stems. The basis for gravimetric lignin estimation is the hydrolysis/solubilization of non-lignin compounds and the collection of insoluble lignin for gravimetry21. In this method, the carbohydrates are removed by hydrolysis of the biomass with concentrated H2SO4 to extract lignin residue20,22. The lignin content estimated by this method is known as acid insoluble lignin or Klason lignin. Application of the Klason method depends on the plant species, the tissue type and the cell wall type. The presence of variable amounts of non-lignin components such as tannins, polysaccharides and proteins, results in proportional differences in the estimation of acid insoluble/soluble lignin contents. Hence, the Klason method is only recommended for lignin estimation of high-lignin content biomass such as woody stems17,23. Solubility methods such as acetyl bromide (AcBr), acid-insoluble lignin, and thioglycolic acid (TGA) are most commonly used methods for estimation of the lignin content from various plant biomass sources. Kim et al. established two methods for lignin extraction by solubilization. The first method extracts lignin as an insoluble residue by solubilizing cellulose and hemicellulose, while the second method separates lignin in the soluble fraction, leaving cellulose and hemicellulose as the insoluble residue24.
Similar methods employed in lignin estimation based on the solubility are thioglycolic acid (TGA) and acetyl bromide (AcBr) methods25. Both TGA and acetyl bromide methods estimate the lignin content by measuring the absorbance of the solubilized lignin at 280 nm; however, the AcBr method degrades xylans during the process of lignin solubilization and shows a false increase in the lignin content26. The thioglycolate (TGA) method is the more reliable method, as it depends on specific bonding with the thioether groups of benzyl alcohol groups of lignin with TGA. The TGA bound lignin is precipitated under acidic conditions using HCl, and the lignin content is estimated using its absorbance at 280 nm27. The TGA method has additional advantages of less structural modifications, a soluble form of lignin estimation, less interference from non-lignin components, and precise estimation of lignin due to specific bonding with TGA.
This TGA method is modified based on the kind of plant biomass sample used for lignin content estimation. Here, we modified and adapted the rapid TGA method of rice straws27 to cotton tissues to estimate the lignin content. Briefly, the dried powdered plant samples were subjected to protein solubilization buffer and methanol extraction to remove proteins and the alcohol soluble fraction. The alcohol insoluble residue was treated with TGA and precipitated lignin under acidic conditions. A lignin standard curve was generated using commercial bamboo lignin and a regression line (y = mx+c) was obtained. The &#34;x&#34; value uses average absorbance values of lignin at 280 nm, while &#34;m&#34; and &#34;c&#34; values were entered from the regression line to calculate unknown lignin concentration in cotton plant biomass samples. This method is divided into five phases: 1) preparation of plant samples; 2) washing the samples with water and methanol; 3) treatment of the pellet with TGA and acid to precipitate lignin; 4) precipitation of lignin; and 5) the standard curve preparation and lignin content estimation of the sample. The first two phases are primarily focused on the plant material preparation followed by water, PSB (protein solubilization buffer) and methanol extractions to obtain the alcohol insoluble material. Then, it was treated with TGA (thioglycolic acid) and HCl to form a complex with lignin in the third phase. At the end, HCl was used to precipitate lignin, which was dissolved in sodium hydroxide to measure its absorbance at 280 nm28.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>BioSpectrophotometer kinetic</td>
			<td>Eppendorf kinetic</td>
			<td>6136000010</td>
			<td>For measuring absorbance at 280 nm</td>
		</tr>
		<tr>
			<td>Centrifuge</td>
			<td>Eppendorf</td>
			<td>5424</td>
			<td>For centrifuging&#160; samples</td>
		</tr>
		<tr>
			<td>Commercial bamboo lignin</td>
			<td>Aldrich</td>
			<td>1002171289</td>
			<td>Used in the preparation of the standard curve</td>
		</tr>
		<tr>
			<td>Distilled water</td>
			<td>Fischer Scientific</td>
			<td>16690382</td>
			<td>Used in the protocol</td>
		</tr>
		<tr>
			<td>Falcon tubes</td>
			<td>VWR</td>
			<td>734-0448</td>
			<td>Containers for solutions</td>
		</tr>
		<tr>
			<td>Freezer mill</td>
			<td>Spex Sample Prep</td>
			<td>68-701-15</td>
			<td>For fine grinding of plant tissue samples</td>
		</tr>
		<tr>
			<td>Heat block/ Thermal mixer</td>
			<td>Eppendorf</td>
			<td>13527550</td>
			<td>For temperature controlled steps during lignin extraction</td>
		</tr>
		<tr>
			<td>Hotplate stirrer</td>
			<td>Walter</td>
			<td>WP1007-HS</td>
			<td>Used for preparation of solutions</td>
		</tr>
		<tr>
			<td>Hydrochloric acid (HCL)</td>
			<td>Sigma</td>
			<td>221677</td>
			<td>Used in the protocol</td>
		</tr>
		<tr>
			<td>Incubator</td>
			<td>Fisherbrand</td>
			<td>150152633</td>
			<td>For thorough drying of plant tissue samples</td>
		</tr>
		<tr>
			<td>Measuring scale</td>
			<td>Mettler toledo</td>
			<td>30243386</td>
			<td>For measuring plant tissue weight, standards and microfuge tubes</td>
		</tr>
		<tr>
			<td>Methanol (100 %)</td>
			<td>Fischer Scientific</td>
			<td>67-56-1</td>
			<td>Used in the protocol</td>
		</tr>
		<tr>
			<td>Microfuge tubes (2 mL)</td>
			<td>Microcentrifuge</td>
			<td>Z628034-500EA</td>
			<td>Containers for extraction of lignin</td>
		</tr>
		<tr>
			<td>Plant biomass gerinder</td>
			<td>Hanchen</td>
			<td>Amazon</td>
			<td>Used for crushing dried samples</td>
		</tr>
		<tr>
			<td>pH meter</td>
			<td>Fisher Scientific</td>
			<td>AE150</td>
			<td>Measuring pH for solutions prepared for lignin extraction</td>
		</tr>
		<tr>
			<td>Temperature controlled incubator/oven</td>
			<td>Fisher Scientific</td>
			<td>15-015-2633</td>
			<td>Used in the protocol</td>
		</tr>
		<tr>
			<td>Thioglycolic acid (TGA)</td>
			<td>Sigma Aldrich</td>
			<td>68-11-1</td>
			<td>Used in the protocol</td>
		</tr>
		<tr>
			<td>Vacuum dryer</td>
			<td>Eppendorf</td>
			<td>22820001</td>
			<td>Used for drying samples</td>
		</tr>
		<tr>
			<td>Vortex mixer</td>
			<td>Eppendorf</td>
			<td>3340001</td>
			<td>For proper mixing of samples</td>
		</tr>
	</tbody>
</table>

estimation of plant biomass lignin content using thioglycolic acid (tga)

Lignin is a natural polymer that is the second most abundant polymer on Earth after cellulose. Lignin is mainly deposited in plant secondary cell walls and is an aromatic heteropolymer primarily composed of three monolignols with significant industrial importance. Lignin plays an important role in plant growth and development, protects&#160;from biotic and abiotic stresses, and in the quality of animal fodder, the wood, and industrial lignin products. Accurate estimation of lignin content is essential for both fundamental understanding of the lignin biosynthesis and industrial applications of biomass. The thioglycolic acid (TGA) method is a highly reliable method of estimating the total lignin content in the plant biomass. This method estimates the lignin content by forming thioethers with the benzyl alcohol groups of lignin, which are soluble in alkaline conditions and insoluble in acidic conditions. The total lignin content is estimated using a standard curve generated from commercial bamboo lignin.

Two different cotton experimental lines were compared for differences in their lignin contents in different tissues. The extracted lignin content of each sample was measured at 280 nm and recorded its respective absorbance values. The average absorbance values of each biological replicate were compared against the regression line of the lignin standard curve (Table 2, Figure 3C). The regression line, y = mx + c, is used to calculate the unknown lignin content of the extracte...

Watch this Scientific Journal Video about Estimation of Plant Biomass Lignin Content using Thioglycolic Acid TGA at JoVE.com

Estimation of Plant Biomass Lignin Content using Thioglycolic Acid TGA

Here, we present a modified TGA method for estimation of lignin content in herbaceous plant biomass. This method estimates the lignin content by forming specific thioether bonds with lignin and presents an advantage over the Klason method, as it requires a relatively small sample for lignin content estimation.

Estimation of Plant Biomass Lignin Content using Thioglycolic Acid (TGA)

Lignin is a natural polymer that is the second most abundant polymer on Earth after cellulose. Lignin is mainly deposited in plant secondary cell walls ...

Lignin is a complex heteropolymer made up of three monolignols. It is the second most abundant polymer on earth next to cellulose. Here, we demonstrate thioglycolic acid method, which is the most reliable method for the estimation of lignin content.This method is based on the principle that lignin binds to thioglycolic acid through thioether bonds. Further, we divided this protocol into five phases. In the first phase, we prepare the plant material.In the second phase, we isolate the alcohol insoluble extract. In the third phase, we precipitate lignin using thioglycolic acid and acidic conditions. In the fourth phase, we prepare lignin standard curve using industrial bamboo lignin.Finally, in the fifth phase, we estimate the lignin content using the standard curve prepared in the fourth phase. Plant material is collected, flipped the pots to separate the roots, washed them thoroughly in water, air dried for two days, transferred them into labeled containers and incubated them in the incubator at 49 degrees centigrade for one week to 10 days. Using scissors, the tissue is further cut into 1 mm to 3 mm size pieces.Alternatively biomass grinder is used to crush the plant tissues. Use the root tissue Turn on the biomass grinder collect the crushed powder into pre-labeled containers. Similarly, repeat for the stem tissue and leaf tissue.The crushed powder is loaded into the grinding vase which are then placed in the freezer mill And run the freezer mill at the rate of 10 CP speed for three cycles. Weigh 20 mg of the ground tissue powder and transfer to a pre made 2ml tube. Make a note of the empty tube and the tube with tissue powder and the tissue powder in your lab notebook.Incubate the tubes with cap open at 60 degrees centigrade for one hour. After incubation, add 1.8 ml of water to each sample vortex centrifuge at 15, 000 RPM for 10 minutes. Discard the supernatant Add 1.8 ml of methanol.Vortex and incubate in a preheated 60 degrees centigrade block for 20 minutes After incubation centrifuge at 15, 000 RPM for 10 minutes. Repeat this step one more time. After centrifugation discard the supernatant and dry the pellets in the vacuum dryer for two to three hours or until the pallet is completely dry.Measure and record the weight of each tube in your lab notebook for the estimation of lignin content at the end. Also include positive control industrial bamboo lignin at this point starting from 0.5 mg to 4 mg in triplicates. Add 1 ml of 3 normal hydrochloric acid, along with hundred microliters of glycolic acid to each sample Vortex and incubate at 80 degrees centigrade for 3 hours.After 3 hours incubation transfer them to a rack and allow it to cool for 10 minutes. then centrifuge at 15, 000 RPM for 10 minutes. After centrifugation, the color of the solution looks like this.Discard the supernatant. Add 1 ml of water. Vortex Centrifuge at 15, 000 RPM for 10 minutes.Discard the supernatant. Add 1 ml of 1 normal sodium hydroxide. Vortex and incubate at 37 degrees centigrade shaker overnight.After overnight incubation centrifuge the tubes at 15, 000 RPM for 10 minutes. Transfer the supernatant fresh pre-labeled 2 ml tubes add 200 microliters of concentrated hydrochloric acid to the supernatant. Mix them by gentle inversion as shown here.Incubate them in the refrigerator at 4 degrees centigrade overnight. After incubation centrifuge at 15, 000 RPM for 10 minutes. Discard the supernatant.Add 1 ml of sodium hydroxide. Vortex and incubate in the shaker at room temperature for 10 to 15 minutes. Use spectrophotometer to collect the absorbance readings 280 nanometers, Take 2 microliters of sodium hydroxide as blank since the lignin precipitated is dissolved in sodium hydroxide.Make the blank to zero. Similarly, repeat for the samples. Use two microliters of each sample to collect the absorbance readings in your lab notebook.Take three readings for each sample for three technical replicates. In the first column, we have the sample number. In the second column, we have biological replicates where R1, R2, R3 represent three biological replicates of one experimental line.In the third column, we averaged the absorbance readings obtained at 280 nanometers. We calculated the lignin content in the fourth column using the formula y=mx-c where x is the average OD.m and c values are plotted from the regression line of the standard curve prepared. Fifth column is the weight after the methanol and water washes.So this is the way that is used for the estimation of lignin content in mg. So we divide the value obtained in the fourth column by fifth column to obtain the value per mg of lignin content in the sixth column. And this value is multiplied by 1000 in order to obtain per gram cell wall weight.And the percent lignin content is calculated by dividing this value by 1000 and multiplying by 100. Finally, we obtain the average lignin by averaging the lignin of three biological replicates of each experimental line which will be compared with average of another experimental line in the form of a bar graph to understand the differences in the lignin content. We can also apply student t-test to test their level of significance.In column A, we have commercial bamboo lignin, and then the weight of the bamboo lignin that was taken before TGA and their respective absorbance readings at 280 nanometers. These values in table A were used to plot a scattered graph in column B, which gives us the regression line with m and c values. In C, we compared the values obtained by using the standard curve and the industrial bamboo lignin experimental line one and two were compared in the form of a bar graph and the result is they show difference between each other.

estimation-of-plant-biomass-lignin-content-using-thioglycolic-acid-tga

Research

JoVE Journal

Biochemistry

Combining Raman Imaging and Multivariate Analysis to Visualize Lignin, Cellulose, and Hemicellulose in the Plant Cell Wall

The application of Raman imaging to plant biomass is increasing because it can offer spatial and compositional information on aqueous solutions. The analysis does not usually require extensive sample preparation; structural and chemical information can be obtained without labeling. However, each Raman image contains thousands of spectra; this raises difficulties when extracting hidden information, especially for components with similar chemical structures. This work introduces a multivariate analysis to address this issue. The protocol establishes a general method to visualize the main components, including lignin, cellulose, and hemicellulose within the plant cell wall. In this protocol, procedures for sample preparation, spectral acquisition, and data processing are described. It is highly dependent upon operator skill at sample preparation and data analysis. By using this approach, a Raman investigation can be performed by a non-specialist user to acquire high-quality data and meaningful results for plant cell wall analysis.

This protocol aims to present a general method to visualize lignin, cellulose, and hemicellulose in plant cell walls using Raman imaging and multivariate analysis.

The application of Raman imaging to plant biomass is increasing because it can offer spatial and compositional information on aqueous solutions. The ...

Determination of the Glycogen Content in Cyanobacteria

Cyanobacteria accumulate glycogen as a major intracellular carbon and energy storage&#160;during photosynthesis. Recent developments in research have highlighted complex mechanisms of glycogen metabolism, including the diel cycle of biosynthesis and catabolism, redox regulation, and the involvement of non-coding RNA. At the same time, efforts are being made to redirect carbon from glycogen to desirable products in genetically engineered cyanobacteria to enhance product yields. Several methods are used to determine the glycogen contents in cyanobacteria, with variable accuracies and technical complexities. Here, we provide a detailed protocol for the reliable determination of the glycogen content in cyanobacteria that can be performed in a standard life science laboratory. The protocol entails the selective precipitation of glycogen from the cell lysate and the enzymatic depolymerization of glycogen to generate glucose monomers, which are detected by a glucose oxidase-peroxidase (GOD-POD) enzyme coupled assay. The method has been applied to Synechocystis sp. PCC 6803 and Synechococcus sp. PCC 7002, two model cyanobacterial species that are widely used in metabolic engineering. Moreover, the method successfully showed differences in the glycogen contents between the wildtype and mutants defective in regulatory elements or glycogen biosynthetic genes.

Here, we present a reliable and easy assay to measure the glycogen content in cyanobacterial cells. The procedure entails precipitation, selectable depolymerization, and the detection of glucose residues. This method is suitable for both wildtype and genetically engineered strains and can facilitate the metabolic engineering of cyanobacteria.

Cyanobacteria accumulate glycogen as a major intracellular carbon and energy storage&#160;during photosynthesis. Recent developments in research have ...

High Throughput, Absolute Determination of the Content of a Selected Protein at Tissue Levels Using Quantitative Dot Blot Analysis (QDB)

Lacking a convenient, quantitative, high throughput immunoblot method for absolute determination of the content of a specific protein at cellular and tissue level significantly hampers the progress in proteomic research. Results derived from currently available immunoblot techniques are also relative, preventing any efforts to combine independent studies with a large-scale analysis of protein samples. In this study, we demonstrate the process of quantitative dot blot analysis (QDB) to achieve absolute quantification in a high throughput format. Using a commercially available protein standard, we are able to determine the absolute content of capping actin protein, gelsolin-like (CAPG) in protein samples prepared from three different mouse tissues (kidney, spleen, and prostate) together with a detailed explanation of the experimental details. We propose the QDB analysis as a convenient, quantitative, high throughput immunoblot method of absolute quantification of individual proteins at the cellular and tissue level. This method will substantially aid biomarker validation and pathway verification in various areas of biological and biomedical research.

High Throughput, Absolute Determination of the Content of a Selected Protein at Tissue Levels Using Quantitative Dot Blot Analysis QDB

Here we demonstrate a detailed process of quantitative dot blot analysis (QDB) by determining the absolute content of a targeted protein, capping actin protein, gelsolin-like (CAPG), in three different mouse tissues. We demonstrate a high throughput, convenient, quantitative immunoblot technique for biomarker validation at the cellular and tissue level.

Lacking a convenient, quantitative, high throughput immunoblot method for absolute determination of the content of a specific protein at cellular and ...

Spectrophotometric Determination of Phycobiliprotein Content in Cyanobacterium Synechocystis

This is a simple protocol for the quantitative determination of phycobiliprotein content in the model cyanobacterium Synechocystis. Phycobiliproteins are the most important components of phycobilisomes, the major light-harvesting antennae in cyanobacteria and several algae taxa. The phycobilisomes of Synechocystis contain two phycobiliproteins: phycocyanin and allophycocyanin. This protocol describes a simple, efficient, and reliable method for the quantitative determination of both phycocyanin and allophycocyanin in this model cyanobacterium. We compared several methods of phycobiliprotein extraction and spectrophotometric quantification. The extraction procedure as described in this protocol was also successfully applied to other cyanobacteria strains such as Cyanothece sp., Synechococcuselongatus, Spirulina sp., Arthrospira sp., and Nostoc sp., as well as to red algae Porphyridium cruentum. However, the extinction coefficients of specific phycobiliproteins from various taxa can differ and it is, therefore, recommended to validate the spectrophotometric quantification method for every single strain individually. The protocol requires little time and can be performed in any standard life science laboratory since it requires only standard equipment.

Spectrophotometric Determination of Phycobiliprotein Content in Cyanobacterium Synechocystis

Here, we present a protocol to quantitatively determine phycobiliprotein content in the cyanobacterium Synechocystis using a spectrophotometric method. The extraction procedure was also successfully applied to other cyanobacteria and algae strains; however, due to variations in pigment absorption spectra, it is necessary to test the spectrophotometric equations for each strain individually.

This is a simple protocol for the quantitative determination of phycobiliprotein content in the model cyanobacterium Synechocystis. Phycobiliproteins are ...

Affinity Purification of Chloroplast Translocon Protein Complexes Using the TAP Tag

Chloroplast biogenesis requires the import of thousands of nucleus-encoded proteins into the plastid. The import of these proteins depends on the translocon at the outer (TOC) and inner (TIC) chloroplast membranes. The TOC and TIC complexes are multimeric and probably contain yet unknown components. One of the main goals in the field is to establish the complete inventory of TOC and TIC components. For the isolation of TOC-TIC complexes and the identification of new components, the preprotein receptor TOC159 has been modified N-terminally by the addition of the tandem affinity purification (TAP) tag resulting in TAP-TOC159. The TAP-tag is designed for two sequential affinity purification steps (hence "tandem affinity"). The TAP-tag used in these studies consists of a N-terminal IgG-binding domain derived from Staphylococcus aureus Protein A (ProtA) followed by a calmodulin-binding peptide (CBP). Between these two affinity tags, a tobacco etch virus (TEV) protease cleavage site has been included. Therefore, TEV protease can be used for gentle elution of TOC159-containing complexes after binding to IgG beads. In the protocol presented here, the second Calmodulin-affinity purification step was omitted. The purification protocol starts with the preparation and solubilization of total cellular membranes. After the detergent-treatment, the solubilized membrane proteins are incubated with IgG beads for the immunoisolation of TAP-TOC159-containing complexes. Upon binding and extensive washing, TAP-TOC159 containing complexes are cleaved and released from the IgG beads using the TEV protease whereby the S. aureus IgG-binding domain is removed. Western blotting of the isolated TOC159-containing complexes can be used to confirm the presence of known or suspected TOC and TIC proteins. More importantly, the TOC159-containing complexes have been used successfully to identify new components of the TOC and TIC complexes by mass spectrometry. The protocol that we present potentially allows the efficient isolation of any membrane-bound protein complex to be used for the identification of yet unknown components by mass spectrometry.

We here present a proven and tested protocol for the purification of chloroplast protein import complexes (TOC-TIC complex) using the TAP-tag. The one-step affinity-isolation protocol can potentially be applied to any protein and be used to identify new interaction partners by mass spectrometry.

Chloroplast biogenesis requires the import of thousands of nucleus-encoded proteins into the plastid. The import of these proteins depends on the ...

Using High Content Imaging to Quantify Target Engagement in Adherent Cells

Quantitating the interaction of small molecules with their intended protein target is critical for drug development, target validation and chemical probe validation. Methods that measure this phenomenon without modification of the protein target or small molecule are particularly valuable though technically challenging. The cellular thermal shift assay (CETSA) is one technique to monitor target engagement in living cells. Here, we describe an adaptation of the original CETSA protocol, which allows for high throughput measurements while retaining subcellular localization at the single cell level. We believe this protocol offers important advances to the application of CETSA for in-depth characterization of compound-target interaction, especially in heterogeneous populations of cells.

Measurements of drug target engagement are central to effective drug development and chemical probe validation. Here, we detail a protocol for measuring drug-target engagement using high content imaging in a microplate-compatible adaption of the cellular thermal shift assay (CETSA).

Quantitating the interaction of small molecules with their intended protein target is critical for drug development, target validation and chemical probe ...

Using In Vitro Fluorescence Resonance Energy Transfer to Study the Dynamics Of Protein Complexes at a Millisecond Time Scale

Proteins are the primary operators of biological systems, and they usually interact with other macro- or small molecules to carry out their biological functions. Such interactions can be highly dynamic, meaning the interacting subunits are constantly associated and dissociated at certain rates. While measuring the binding affinity using techniques such as quantitative pull-down reveals the strength of the interaction, studying the binding kinetics provides insights on how fast the interaction occurs and how long each complex can exist. Furthermore, measuring the kinetics of an interaction in the presence of an additional factor, such as a protein exchange factor or a drug, helps reveal the mechanism by which the interaction is regulated by the other factor, providing important knowledge for the advancement of biological and medical research. Here, we describe a protocol for measuring the binding kinetics of a protein complex that has a high intrinsic association rate and can be dissociated quickly by another protein. The method uses fluorescence resonance energy transfer to report the formation of the protein complex in vitro, and it enables monitoring the fast association and dissociation of the complex in real time on a stopped-flow fluorimeter. Using this assay, the association and dissociation rate constants of the protein complex are quantified.

Protein-protein interactions are critical for biological systems, and studies of the binding kinetics provide insights into the dynamics and function of protein complexes. We describe a method that quantifies the kinetic parameters of a protein complex using fluorescence resonance energy transfer and the stopped-flow technique. &#160;

Proteins are the primary operators of biological systems, and they usually interact with other macro- or small molecules to carry out their biological ...

Identifying Amino Acid Overproducers Using Rare-Codon-Rich Markers

To satisfy the ever-growing market for amino acids, high-performance production strains are needed. The amino acid overproducers are conventionally identified by harnessing the competitions between amino acids and their analogs. However, this analog-based method is of low accuracy, and proper analogs for specific amino acids are limited. Here, we present an alternative strategy that enables an accurate, sensitive, and high-throughput screening of amino acid overproducers using rare-codon-rich markers. This strategy is inspired by the phenomenon of codon usage bias in protein translation, for which codons are categorized into common or rare ones based on their frequencies of occurrence in the coding DNA. The translation of rare codons depends on their corresponding rare transfer RNAs (tRNAs), which cannot be fully charged by the cognate amino acids under starvation. Theoretically, the rare tRNAs can be charged if there is a surplus of the amino acids after charging the synonymous common isoacceptors. Therefore, retarded translations caused by rare codons could be restored by feeding or intracellular overproductions of the corresponding amino acids. Under this assumption, a selection or screening system for identifying amino acid overproducers is established by replacing the common codons of the targeted amino acids with their synonymous rare alternatives in the antibiotic resistance genes or the genes encoding fluorescent or chromogenic proteins. We show that the protein expressions can be greatly hindered by the incorporation of rare codons and that the levels of proteins correlate positively with the amino acid concentrations. Using this system, overproducers of multiple amino acids can be readily screened out from mutation libraries. This rare-codon-based strategy only requires a single modified gene, and the host is less likely to escape the selection than in other methods. It offers an alternative approach for obtaining amino acid overproducers.

This study presents an alternative strategy to the conventional toxic analog-based method in identifying amino acid overproducers by using rare-codon-rich markers to achieve accuracy, sensitivity, and high-throughput simultaneously.

To satisfy the ever-growing market for amino acids, high-performance production strains are needed. The amino acid overproducers are conventionally ...

Measuring Interactions between Fluorescent Probes and Lignin in Plant Sections by sFLIM Based on Native Autofluorescence

In lignocellulosic biomass (LB), the activity of enzymes is limited by the appearance of non-specific interactions with lignin during the hydrolysis process, which maintains enzymes far from their substrate. Characterization of these complex interactions is thus a challenge in complex substrates such as LB. The method here measures molecular interactions between fluorophore-tagged molecules and native autofluorescent lignin, to be revealed by F&#246;rster resonance energy transfer (FRET). Contrary to FRET measurements in living cells using two exogenous fluorophores, FRET measurements in plants using lignin is not trivial due to its complex autofluorescence. We have developed an original acquisition and analysis pipeline with correlated observation of two complementary properties of fluorescence: fluorescence emission and lifetime. sFLIM (spectral and fluorescent lifetime imaging microscopy) provides the quantification of these interactions with high sensitivity, revealing different interaction levels between biomolecules and lignin.

This protocol describes an original setup combining spectral and fluorescence lifetime measurements to evaluate F&#246;rster resonance energy transfer (FRET) between rhodamine-based fluorescent probes and lignin polymer directly in thick plant sections.

In lignocellulosic biomass (LB), the activity of enzymes is limited by the appearance of non-specific interactions with lignin during the hydrolysis ...

Kinetic Screening of Nuclease Activity using Nucleic Acid Probes

Nucleases are a class of enzymes that break down nucleic acids by catalyzing the hydrolysis of the phosphodiester bonds that link the ribose sugars. Nucleases display a variety of vital physiological roles in prokaryotic and eukaryotic organisms, ranging from maintaining genome stability to providing protection against pathogens. Altered nuclease activity has been associated with several pathological conditions including bacterial infections and cancer. To this end, nuclease activity has shown great potential to be exploited as a specific biomarker. However, a robust and reproducible screening method based on this activity remains highly desirable.
Herein, we introduce a method that enables screening for nuclease activity using nucleic acid probes as substrates, with the scope of differentiating between pathological and healthy conditions. This method offers the possibility of designing new probe libraries, with increasing specificity, in an iterative manner. Thus, multiple rounds of screening are necessary to refine the probes&#39; design with enhanced features, taking advantage of the availability of chemically modified nucleic acids. The considerable potential of the proposed technology lies in its flexibility, high reproducibility, and versatility for the screening of nuclease activity associated with disease conditions. It is expected that this technology will allow the development of promising diagnostic tools with a great potential in the clinic.

Altered nuclease activity has been associated with different human conditions, underlying its potential as a biomarker. The modular and easy to implement screening methodology presented in this paper allows the selection of specific nucleic acid probes for harnessing nuclease activity as a biomarker of disease.

Nucleases are a class of enzymes that break down nucleic acids by catalyzing the hydrolysis of the phosphodiester bonds that link the ribose sugars. ...