ORIGINAL PAPER

Towards lignin-protein crosslinking: amino acid adductsof a lignin model quinone methide

Brett G. Diehl • Heath D. Watts •

James D. Kubicki • Matthew R. Regner •

John Ralph • Nicole R. Brown

Received: 12 December 2013 / Accepted: 22 January 2014 / Published online: 29 January 2014

� Springer Science+Business Media Dordrecht 2014

Abstract The polyaromatic structure of lignin has

long been recognized as a key contributor to the

rigidity of plant vascular tissues. Although lignin

structure was once conceptualized as a highly net-

worked, heterogeneous, high molecular weight poly-

mer, recent studies have suggested a very different

configuration may exist in planta. These findings,

coupled with the increasing attention and interest in

efficiently utilizing lignocellulosic materials for green

materials and energy applications, have renewed

interest in lignin chemistry. Here we focus on quinone

methides (QMs)—key intermediates in lignin poly-

merization—that are quenched via reaction with cell-

wall-available nucleophiles. Reactions with alcohol

and uronic acid groups of hemicelluloses, for example,

can lead to lignin-carbohydrate crosslinks. Our work is

a first step toward exploring potential QM reactions

with nucleophilic groups in cell wall proteins. We

conducted a model compound study wherein the lignin

model compound guaiacylglycerol-b-guaiacyl ether 1,

was converted to its QM 2, then reacted with amino

acids bearing nucleophilic side-groups. Yields for the

QM-amino acid adducts ranged from quantitative in

the case of QM-lysine 3, to zero (no reaction) in the

cases of QM-threonine (Thr) 10 and QM-hydroxypro-

line (Hyp) 11. The structures of the QM-amino acidElectronic supplementary material The online version ofthis article (doi:10.1007/s10570-014-0181-y) contains supple-mentary material, which is available to authorized users.

B. G. Diehl (&)

Department of Agricultural and Biological Engineering,

The Pennsylvania State University, 226 Forest Resources

Building, University Park, PA 16802, USA

e-mail: bgd115@psu.edu

H. D. Watts

Department of Geosciences, The Pennsylvania State

University, 305 Deike Building, University Park,

PA 16802, USA

e-mail: hdw115@psu.edu

J. D. Kubicki

Department of Geosciences and the Earth and

Environmental Systems Institute, The Pennsylvania State

University, 335 Deike Building, University Park,

PA 16802, USA

e-mail: jdk7@psu.edu

M. R. Regner � J. Ralph

Department of Biochemistry and DOE Great Lakes

Bioenergy Research Center, Wisconsin Energy Institute,

Madison, WI 53726, USA

e-mail: mregner@gmail.com

J. Ralph

e-mail: jralph@wisc.edu

N. R. Brown

Department of Agricultural and Biological Engineering,

The Pennsylvania State University, 209 Agricultural

Engineering Building, University Park, PA 16802, USA

e-mail: nrb10@psu.edu

123

Cellulose (2014) 21:1395–1407

DOI 10.1007/s10570-014-0181-y

adducts were confirmed via 1D and 2D nuclear

magnetic resonance (NMR) spectroscopy and density

functional theory (DFT) calculations, thereby extend-

ing the lignin NMR database to include amino acid

crosslinks. Some of the QM-amino acid adducts

formed both syn- and anti-isomers, whereas others

favored only one isomer. Because the QM-Thr 10 and

QM-Hyp 11 compounds could not be experimentally

prepared under conditions described here but could

potentially form in vivo, we used DFT to calculate

their NMR shifts. Characterization of these model

adducts extends the lignin NMR database to aid in the

identification of lignin-protein linkages in more com-

plex in vitro and in vivo systems, and may allow for

the identification of such linkages in planta.

Keywords Nuclear magnetic resonance

spectroscopy � Lignin � Protein � Quinone

methide � Amino acid � Crosslinking � Density

functional theory

Introduction

Plant cell walls are composed of a network of

interacting polymers, namely cellulose, hemicellu-

loses, pectins, lignin, and structural proteins (Cos-

grove 2005; McQueen-Mason and Cosgrove 1994). Of

these, lignin is the major aromatic component, derived

from monolignols—phenylpropanoid units whose

biosynthesis exhibits incredible plasticity (Boerjan

et al. 2003; Ralph et al. 2004a, b; Vanholme et al.

2010). Lignin’s mode of polymerization is unique

among the cell wall polymers. Resonance stabilized

radicals are enzymatically generated from the mono-

lignols, and as the radical-bearing structures couple

combinatorially, a heterogeneous polymer containing

many types of inter-unit linkages forms. The variety of

the inter-unit linkages contributes notable recalci-

trance to the plant cell wall, stymying not only natural

degradation, but also affecting the economics of many

industrial sectors, including the pulp and paper

industry, the developing biofuels industry, agricultural

industries, and chemical industries, which all seek

higher value products from lignin (Chapple et al.

2007; Chen and Dixon 2008; Jung 1989; Jung and

Allen 1995; Li et al. 2008; Stewart et al. 2006).

Inter-unit linkages are not, however, the sole factor

influencing lignin’s recalcitrance in planta. Lignin may

be crosslinked with other polymers in the plant wall.

Hydroxyl and uronic acid groups of polysaccharides

bear mildly nucleophilic groups that can react with a key

lignin intermediate—the a-carbon of quinone methides

(QMs) (Balakshin et al. 2011; Leary 1980; Miyagawa

et al. 2012; Ralph et al. 2009; Toikka et al. 1998; Yuan

et al. 2011). These QMs form each time a monolignol

radical couples at its b-position and, because b-coupling

is prevalent, the importance of QMs in lignin structure

cannot be understated. In certain cases, particularly b-5-

and b-b-coupling, QM intermediates are quickly

trapped intramolecularly, producing phenylcoumaran

and resinol units (Leary 1980; Ralph et al. 2009).

However, in the case of the predominant b-O-4-

coupling, which produces b-ether linkages, the QM’s

a-carbon becomes susceptible to external nucleophilic

attack (Fig. 1) (Leary 1980; Ralph et al. 2009). This

reactivity of the QM is the focus of the current study.

The crosslinking of lignin with cell wall constitu-

ents other than hemicelluloses has not been well

investigated. Cell wall structural proteins, including

glycine-rich proteins (GRPs), proline-rich proteins

(PRPs), and hydroxyproline-rich glycoproteins

(HRGPs), all contain amino acid residues with nucle-

ophilic side-chains that could react with lignin QMs

(Harrak et al. 1991; Jose and Puigdomenech 1993;

Fig. 1 Formation of b-ether QMs via radical coupling, and their rearomatization during lignin polymerization. L lignin polymer, Nuc

nucleophile (e.g., H2O, and also here Cys, Lys, His, Asp, Glu, Tyr or Ser), R = H or OCH3

1396 Cellulose (2014) 21:1395–1407

123

Kieliszewski et al. 2011; Ryser et al. 1997). Cell wall

proteins vary in quantity among species and cell types,

ranging from as low as 1–2 to 20 % on a dry weight

basis in wild type plants (Albersheim et al. 2010;

Cassab and Varner 1988). In Whitmore 1978a, b, 1982

showed evidence for the formation of lignin-protein

linkages in isolated cell walls of slash pine. Further

literature sources suggest that structural proteins may

crosslink with lignin, or possibly even nucleate, or

provide a template for, lignin structure, but these ideas

have not been adequately tested (Albersheim et al.

2010; Beat et al. 1989; Boerjan et al. 2003; Cassab and

Varner 1988; Harrak et al. 1991). If true, this

mechanism could provide spatial and temporal control

over lignin deposition and architecture (Beat et al.

1989). Furthermore, it has recently been suggested

that over-expression of cell wall proteins could result

in increased lignin-protein linkage formation, which

may affect cell wall physical and chemical properties,

for example increased sugar extractability (Liang et al.

2008; Xu et al. 2013). However, identifying such

linkages in planta would be difficult without first

determining diagnostic lignin-protein spectroscopic

signatures under simpler, more controlled conditions.

As a first step toward investigating potential lignin-

protein linkages in planta, we conducted a model

compound study to characterize products formed when

the lignin model compound guaiacylglycerol-b-guaia-

cyl ether 1 was converted to its QM 2, then reacted with

amino acids bearing nucleophilic side-groups (Fig. 2).

Thiols, amines, acids and alcohols have been shown to

quench QMs in a diverse array of systems. The thiol

group of glutathione reacts with an o-QM generated

from the flavonoid, quercetin (Awad et al. 2000); the

thiol group of cysteine (Cys) reacts with the relatively

unreactive p-QM, 2,6-di-tert-butyl-4-methylene-2,5-

cyclohexadienone (Bolton et al. 1997); and thiols and

thiolates react with QMs derived from anthracyclines

(Ramakrishnan and Fisher 1983). Similarly, amines

have been shown to trap lignin QMs (Ralph and Young

1983). A wide array of acid- and hydroxyl-containing

compounds react with p-QMs (Leary et al. 1977), and

primary (and to a much lesser extent, secondary)

hydroxyl groups of carbohydrates may react with QM

2 (Toikka et al. 1998). However, similar nucleophile-

QM adducts have not been characterized in lignin-

protein systems.

The nucleophilic amino acids investigated here—

Cys, lysine (Lys), histidine (His), aspartic acid (Asp),

glutamic acid (Glu), tyrosine (Tyr), serine (Ser), thre-

onine (Thr) and hydroxyproline (Hyp)—occur in plant

cell wall structural proteins and may react to form

lignin-protein crosslinks in vivo (Jose and Puigdomen-

ech 1993; Kieliszewski et al. 2011). Because cell wall

proteins are thought to exist in the wall prior to

lignification, the a-amine and a-acid groups of the

amino acids were protected to mimic their inclusion

within a peptide. This allowed reactions of the nucle-

ophilic side-chains to be determined without the com-

plication of competing reactions from the terminal a-

amine and a-acid groups. The QM-amino acid adducts

(Fig. 3) were characterized by nuclear magnetic reso-

nance (NMR) spectroscopy, density functional theory

(DFT), mass spectrometry, and UV/Visible (UV/Vis)

spectrophotometry. The characterization of these model

adducts extends the lignin NMR database to aid in the

identification of lignin-protein linkages in more com-

plex in vitro and in vivo systems (Ralph et al. 2004a, b).

Experimental

Materials

All chemicals used in the preparation of compounds 1

and 2, and lignin dehydrogenation polymer (DHP),

Fig. 2 Guaiacylglycerol-b-

guaiacyl ether 1 and its

derived quinone methide

(QM) 2

Cellulose (2014) 21:1395–1407 1397

123

Fig. 3 Lignin-cysteine

(QM-Cys) 3, lignin-lysine

(QM-Lys) 4, lignin-histidine

(QM-His) 5, lignin-aspartic

acid (QM-Asp) 6, lignin-

glutamic acid (QM-Glu) 7,

lignin-serine (QM-Ser) 8,

lignin-Tyrosine (QM-Tyr)

9, lignin-threonine

(QM-Thr) 10, and lignin-

hydroxyproline (QM-Hyp)

11 adducts derived from

QM 2

1398 Cellulose (2014) 21:1395–1407

123

were purchased from Sigma. All amino acids used in

the preparation of compounds 3-9 were purchased

from Sigma with the exception of Boc-L-His methyl

ester, which was purchased from Indofine Chemical

Company.

Model compound preparations

Compound 1 was prepared according to previous

methods, as was its QM analog (2) (Kawai et al.

1999; Landucci et al. 1981; Ralph and Young 1983).

Protected amino acids (1.05 eq) were added directly to

the anhydrous solution of 2 in dichloromethane at room

temperature. In the case of Lys, which was obtained as

Na-acetyl-L-Lys methyl ester hydrochloride, triethyl-

amine (*5 eq) was added in order to deprotonate the

terminal amine and facilitate dissolution. NMR was

used to show that triethylamine was not reactive

towards the QM. A stir bar was added, the flask was

stoppered, and the atmosphere was rendered inert by

alternating between vacuum and dry nitrogen several

times. The reaction was monitored visually; dissipation

of the yellow hue indicated consumption of the QM.

Intermittently, the reaction was also monitored by TLC

(1:1 ethyl acetate/hexanes). Lys and His reacted with

the QM within minutes, while other amino acids reacted

more slowly with the QM and were allowed to stir

overnight (Cys, Asp, Glu, Tyr) or for several days (Ser,

Thr, Hyp), again, with intermittent monitoring by TLC.

When TLC revealed that the reaction had reached

equilibrium the mixture was evaporated to dryness. In

the case of Lys (compound 4), the reaction went to

completion (complete consumption of the QM) and the

crude products were evaporated to dryness and charac-

terized without further purification. Compounds 3 and

6-9 were purified via flash chromatography using silica

gel and 1:1 ethyl acetate/hexanes as eluent. In the case

of QM-His (5), the product could not be chromato-

graphically separated (a range of eluent solvent systems

were attempted) from a-O-aryl products formed pre-

sumably due to self-dimerization of the QM (2);

however, mass spec and 2D NMR techniques were still

able to confirm the identity of the QM-His product. In

the case of QM-Ser (8), the product could not be fully

separated from unreacted Ser. The neat Ser shifts as

well as the shifts of compound 8 are labeled in the NMR

spectra (see online resource).

Lignin guaiacyl-based DHP was prepared accord-

ing to a previously published method (Terashima et al.

1995). The DHP was characterized via HSQC NMR as

described below and was found to contain shifts

typical of native lignin and DHP (Capanema et al.

2004; Kim and Ralph 2010). The DHP NMR spectrum

was then used as a reference against which diagnostic

NMR shifts of the lignin-protein model compounds

could be compared.

Nuclear magnetic resonance spectroscopy

NMR spectra (see online resource) were collected in

both acetone-d6 and DMSO-d6/pyridine-d5 (4:1 v/v,

500 ul). DMSO-d6/pyridine-d5 was chosen because it

is a preferred solvent for NMR of lignin DHP, milled

wood lignin (MWL), and whole cell walls; using the

same solvent system allows for accurate shift com-

parisons (Kim and Ralph 2010). In general, negligible

shift migration was observed between the two solvent

systems. NMR spectra were acquired on Bruker DPX-

300 (300 MHz 1H resonance freq.), DRX-400

(400 MHz 1H resonance freq.), AV-III-500

(500 MHz 1H resonance freq.) with a cryogenically-

cooled probe and inverse probe geometry (i.e., proton

coils closest to sample), AV-III-600 (500 MHz 1H

resonance freq.) with a cryogenically cooled probe,

and AV-III-850 (850 MHz 1H resonance freq.) with a

cryogenically-cooled probe. Spectral processing was

performed in Bruker’s Topspin 3.1 software. Standard

Bruker pulse programs were employed: 1H (8-16

scans), 13C (5 k-10 k scans), HMQC (Bruker pulse

program ‘inv4gptp’, 64 scans), and HMBC (Bruker

pulse program ‘inv4gslplrnd’, 64 scans). Spectra were

calibrated to the central solvent peaks (acetone: 2.05/

29.8 ppm; dimethyl sulfoxide: 2.50/39.5 ppm). In the

case of lignin DHP, NMR spectra were acquired on a

Bruker Biospin (Billerica, MA, USA) AVANCE 500

(500 MHz 1H resonance freq.) spectrometer fitted

with a cryogenically-cooled gradient probe having

inverse geometry, i.e., with the proton coils closest to

the sample. Spectra were processed with Bruker’s

Topspin 3.1 software, using the central solvent peak as

internal reference (dH/dC: dimethyl sulfoxide

(DMSO), 2.50/39.5 ppm). The synthetic lignin DHP

(*50 mg) was placed in an NMR tube (ID: 4.1 mm),

swollen homogeneously in DMSO-d6/pyridine-d5 (4:1

v/v, 500 ll) with the aid of ultrasonication (*3 h), and

then subjected to adiabatic 2D-HSQC (‘hsqcetgp-

sisp2.2’) experiments using the parameters described

by Mansfield et al. (2012). Processing used typical

Cellulose (2014) 21:1395–1407 1399

123

matched Gaussian apodization in F2 (LB = -0.3,

GB = 0.001), and squared cosine-bell and one level of

linear prediction (32 coefficients) in F1 (Mansfield

et al. 2012).

Mass spectrometry

Exact masses for compounds 3-9 (see online resource)

were calculated using ChemBioDraw Ultra 13.0. Mass

spectrometric analysis was performed on a Waters

LCT Premier time-of-flight (TOF) mass spectrometer

(Waters Corporation (Micromass Ltd.), Manchester,

UK), using MassLynxTM software Version 4.0. Sam-

ples were introduced using a Waters 2695 high

performance liquid chromatograph. Sample analysis

utilized flow injection analysis (FIA). The mobile

phase used was 90 % acetonitrile (LC–MS grade) and

10 % aqueous ammonium acetate (10 mM). The flow

rate was 0.25 mL/min. The nitrogen drying gas

temperature was set to 300 �C at a flow of 7 L/min.

The capillary voltage was 2,200 V. The mass spec-

trometer was set to scan from 100 to 1,000 m/z in

positive ion mode, using electrospray ionization (ESI).

Computational methods

Eight conformational isomers of QM-Cys, QM-Thr,

and QM-Hyp, and sixteen conformational isomers of

QM-His were built using Materials Studio 6.0 (Ac-

celrys Inc., San Diego, CA). Although many addi-

tional conformers were generated during the

conformational search, most of the low-energy con-

formers attained redundant structures and energies

upon minimization with DFT calculations (Hohenberg

and Kohn 1964; Kohn and Sham 1965); therefore, the

high-energy conformers and those that produced

redundant structures after DFT minimization were

eliminated from the test set. The low-energy conform-

ers each exhibited two distinct dihedral angles; these

dihedral angles were C4A-Ca-S-C1Cys and Cb-Cc-OB-

C4B for model 3 (Fig. 3), and C4A-Ca-N1(or N3)-

C2His and Cb-Cc-OB-C4B for model 5a or 5b (Fig. 3).

The conformational isomers that exhibited low rela-

tive energies were used for the subsequent DFT energy

minimizations and their structures (bond lengths, bond

angles, and torsion angles) were allowed to relax

during the DFT calculations.

Eight of the QM-His models exhibited a CaQM–

N1His bond and eight models exhibited CaQM–N3His

bond; these models allowed us to determine which

CaQM–NHis bond was occurring and to determine if an

observed chemical shift (a13C) at 78.8 ppm was due to

a C–N bond. Each set of eight models (i.e., compound

3 (QM-Cys), compound 5a (QM-His(N3)), compound

5b (QM-His(N1)), compound 10 (QM-Thr), or com-

pound 11 (QM-Hyp)) contained two of each of the

stereoisomers (R,R), (S,S), (R,S), and (S,R), where the

former two stereoisomers are syn and the latter two

stereoisomers are anti. These models were built to

determine if the calculated NMR chemical shifts could

differentiate the observed shifts for the syn and anti

stereoisomers of QM-His and QM-Cys. Experimental

NMR shifts for QM-Thr and QM-Hyp were not

obtained because Thr and Hyp did not react with the

QM; however, we reported the calculated shifts for

these compounds (below) as potential references for

other researchers to use.

Each model was energy-minimized without sym-

metry or atomic constraints using the DFT (Hohenberg

and Kohn 1964; Kohn and Sham 1965) method M05-

2X (Zhao et al. 2006), coupled with the

6-311??G(2df,2p) basis set (Clark et al. 1983;

Krishnan et al. 1980; Papajak et al. 2011) using the

program Gaussian 09 (Frisch et al. 2009). Note that the

dihedral angles were not constrained during the energy

minimization calculations. Following the geometry

optimization calculations, frequency calculations

assured that each model attained a potential energy

surface (PES) minimum, where no imaginary fre-

quencies were present (Frisch et al. 2009).

Subsequent gauge-independent atomic orbital

(GIAO) (Buhl et al. 1999; Cheeseman et al. 1996;

Karadakov 2008; Lodewyk et al. 2012; Schrecken-

bach and Ziegler 1995; Wolinski et al. 1990) calcu-

lations using Gaussian 09 at the mPW1PW91/6-

31G(d) theory level provided the NMR magnetic

shielding tensors (a13C and a1H) for the energy-

minimized structures (Adamo and Barone 1998; Buhl

et al. 1999; Cheeseman et al. 1996; Karadakov 2008;

Lodewyk et al. 2012; Schreckenbach and Ziegler

1995; Wolinski et al. 1990). Because our experiments

were conducted in dimethylsulfoxide (DMSO), the

GIAO calculations were also performed in a dielectric

continuum of DMSO using a self-consistent reaction

field (SCRF) (Gogonea 1998) and the integral equa-

tion formalism variant of the polarized continuum

model (IEFPCM) (Cances et al. 1997). Note that the

structures were not energy minimized within the

1400 Cellulose (2014) 21:1395–1407

123

polarized continuum because prior work showed that

doing so did not improve the precision of the

calculations (Watts et al. 2011). A multi-standard

NMR method using benzene for sp2-hybridized C- and

H-atoms, and methanol for sp3-hybridized C- and

H-atoms led to the a13C and a1H results (Sarotti and

Pellegrinet 2009, 2012; Watts et al. 2011). Benzene

and methanol were energy minimized using M05-2X/

6-311??G(2df,2p) and underwent subsequent GIAO

calculations using mPW1PW91/6-31G(d).

The precision of the multi-standard method

versus the single-standard method (e.g., tetrameth-

ylsilane as the standard) is illustrated when com-

paring single-standard results recently reported by

Mostaghni et al. (2013) with the multi-standard

results of Watts et al. (2011). Both groups reported

the d13C for b-O-4-linkages in lignin model com-

pounds; however, the mean unsigned errors, root-

mean-squared errors, and maximum errors reported

by Mostaghni et al. (2013) were approximately 10,

12 and 23 ppm, whereas those reported by Watts

et al. (2011) were approximately 2, 3 and 8 ppm.

Therefore, the multi-standard method produced

results that were more precise than those produced

by the single-standard method for lignin model

compounds with b-O-4-linkages.

For each C- or H-nucleus, we used dcalcx = rref -

rcalc ? dref to calculate the chemical shift of each H-

and C-nucleus of interest (dcalcx ) in the GG-amino acid

models (Sarotti and Pellegrinet 2009, 2012). Here, rref

is the calculated tensor of the C- or H- nucleus of the

standard (i.e., methanol or benzene), rcalc is the

calculated tensor of the nucleus of interest from the

GG-amino acid model, and dref is the experimental

chemical shift of the C- and H-nuclei in benzene or

methanol dissolved in DMSO (Gottlieb et al. 1997;

Gottlieb et al. 1997). The chemical shifts for each C-

and H-nucleus was thermodynamically weighted

using the relative, calculated Gibbs free energy of

each model to account for the thermodynamic abun-

dance of each model (Barone et al. 2002). The

calculated d13C and d1H results were then correlated

with their respective NMR data.

To compare the precision of the calculated results

with the data, the mean unsigned errors (MUE), root-

mean squared errors (RMSE), and maximum errors

were calculated. There were 18 data and result points

for model 3, 5a, and 5b that were used to calculate

these statistics.

Results and discussion

Preparation of quinone methide-amino acid

adducts

A lignin b-ether QM 2 was prepared cleanly from

guaiacylglycerol-b-guaiacyl ether 1, as previously

described (Kawai et al. 1999; Landucci et al. 1981;

Ralph and Young 1983). One of nine amino acids

bearing a nucleophilic side-group was then added to

the QM, with each reaction monitored by thin layer

chromatography. It was observed that amino acids

with amine-containing side-chains (Lys and His)

reacted with the QM quickly (within minutes),

whereas thiol-, acid-, and hydroxyl-containing amino

acids reacted slowly (over hours or days). In the case

of the secondary hydroxyl-containing amino acids

(Thr and Hyp) no cross-coupling was observed (i.e.,

compounds 10 and 11 did not form), despite attempts

to catalyze the cross-coupling reaction. Products were

purified via column chromatography and yields ranged

from quantitative in the case of compound 3 (QM-Lys)

to zero (no reaction) in the cases of compounds 10 and

11 (QM-Thr and QM-Hyp); product yield data is

reported in the electronic supplement. Cross-coupling

reactions were carried out in dichloromethane to

produce the desired lignin-protein adducts.

Solution-state NMR of compounds 3-9 and density

functional theory calculations for compounds 10

and 11

Reaction products were characterized using solution-

state 1D 1H and 13C NMR, as well as 2D heteronuclear

multiple quantum coherence (HMQC) and heteronu-

clear multiple-bond correlation (HMBC) experiments.

Full spectral assignments for compounds 3-9 can be

accessed in the online resource. Interpretation of these

results is consistent with structures 3-9 (Fig. 3),

indicating that Cys, Lys, His, Asp, Glu, Ser and Tyr

all add to QM 2 in vitro. DFT was used to predict NMR

shifts for compounds 10 (QM-Thr) and 11 (QM-Hyp),

which did not form under the synthetic conditions

employed here.

Table 1 shows the lignin a and b 1H and 13C shifts

for compounds 3-11. The c-shifts of these compounds

are almost entirely degenerate and are therefore

considered non-diagnostic. Because Thr and Hyp are

abundant in cell wall structural proteins (especially

Cellulose (2014) 21:1395–1407 1401

123

hyp, which can account for up to 33 % of the amino

acid profiles of some structural proteins), the authors

perceived that estimations of the QM-Thr and QM-

Hyp NMR chemical shifts could still be useful. Thus,

NMR shifts for compounds 10 and 11 were calculated

using DFT. As a control, DFT was also used to

calculate NMR shifts for compounds 3 and 5 (see

Fig. 1 of the online resource), showing comparison to

experimental results. Calculated 13C shifts were

generally in agreement with experimentally observed

shifts. For example, calculated 13C a-shifts overesti-

mated the observed shifts by only 0.8–3.1 ppm.

Calculated 13C b-shifts overestimated the observed

shifts by 5.4–9.8 ppm. Similar discrepancies in DFT

calculated b-shifts of b-ether compounds have been

previously reported, and further work is necessary to

refine these calculations (Watts et al. 2011). Calcu-

lated 1H shifts consistently underestimated the exper-

imentally observed shifts by about 0.5–1 ppm (online

resource Fig. 1). Thus, the calculated 1H shifts for

compounds 10 and 11 are not reproducing the

observed 1H shifts; however it could be possible with

future work to develop a method to correlate the

calculated and experimental 1H shifts, because of the

consistent underestimation of the experimental 1H

shifts by the calculated shifts. Lodewyk et al. (2012)

described a method for using empirical scaling factors

to obtain improved correlation between experimental

and calculated 1H and 13C shifts; however, doing so is

beyond the scope of the present work. In addition to

the use of scaling factors, further research to develop

multi-standard methods that are based on DFT results

is necessary. This work could require the development

and assessment of DFT methods, as well as basis sets

to obtain methods to calculate 1H shifts more

precisely.

Figure 4 highlights the location of diagnostic

HMQC NMR peak contours of the lignin-amino acid

adducts overlaid on the spectrum of a synthetic lignin

(a so-called dehydrogenation polymer, or DHP).

Differences in chemical shifts among the lignin-amino

acid adducts are most salient for the a-positions and,

as expected, less for those from the b-positions. Most

of the lignin-amino acid shifts are readily distinguish-

able from correlations of native structures in lignin;

however, the a-shifts of compound 4 (QM-Lys) are

degenerate with phenylcoumaran c-shifts. In this case,

identifying a lignin-Lys crosslink may be possible by

observing the lignin-Lys b-shifts. The a- and b-shifts

of compound 9 (QM-Tyr) are degenerate with benzyl

Table 1 1H and 13C NMR chemical shifts for lignin-amino acid adducts

Compound a-shifts b-shifts

Experimental Calculated Experimental Calculated1H/13C 1H/13C 1H/13C 1H/13C

3 (QM-Cys)a 4.3/50.3 3.8/53.4 4.7/81.8 3.7/89.6

4.4/50.6 3.5/52.9 4.6/81.7 4.0/87.1

4 (QM-Lys) 3.9/63.0 4.2/85.9

5 (QM-His)b 5.7/60.2 5.0/61.0 5.0/80.2 3.9/90.0

6 (QM-Asp)a 6.0/74.8 4.7/81.4

6.1/75.1 4.6/82.7

7 (QM-Glu)a 6.0/74.2 4.7/81.6

6.1/74.7 4.6/82.6

8 (QM-Ser)a 4.6/80.9 4.4/82.5

4.6/80.7 4.4/82.9

9 (QM-Tyr) 5.5/78.3 4.7/82.7

10 (QM-Thr)c n/a 4.4/70.7 4.3/73.7 n/a 3.2/88.5

3.4/90.4

11 (QM-Hyp)c n/a 4.7/80.5 4.6/78.7 n/a 3.2/87.7

3.6/90.9

a Products exhibited two stereoisomers, shifts for the major isomer are shown first; b only the calculated shifts of anti-5b are shown,

see the electronic supplement for calculated shifts of additional isomers of 5; c syn-isomer shifts are shown first

1402 Cellulose (2014) 21:1395–1407

123

aryl ether linkages (so called a-O-aryl linkages)

sometimes observed in synthetic and native lignin

polymers. These lignin–lignin linkages form when

QMs are quenched by phenolic moieties, and degen-

eracy is not surprising given the structural similarities

among Tyr and the lignin monomers, p-coumaryl,

coniferyl, and sinapyl alcohols. This may make it

difficult to distinguish lignin-Tyr crosslinking from

lignin–lignin a-O-aryl linkages in native lignins.

Though not depicted graphically, the lignin-peptide

linkages described herein are largely free from overlap

with previously described polysaccharide shifts in

both angiosperms and gymnosperms. However, a few

of the lignin-amino acid shifts may overlap with

signatures attributed to lignin-carbohydrate linkages.

For example, the a-shifts of compounds 6 and 7

exhibit degeneracy with lignin-carbohydrate benzyl

esters (a-shifts at 6.1/75.0 ppm) due to structural

similarity (Balakshin et al. 2011; Toikka et al. 1998).

Likewise, the a-shifts of 8 and 11 exhibit degeneracy

with lignin-carbohydrate benzyl ethers (a-shifts

located at 4.6/80.5 ppm) (Balakshin et al. 2011;

Toikka et al. 1998). Thus, caution should be exercised

when attempting to discern certain lignin-protein and

lignin-carbohydrate linkages using 1D and 2D NMR

techniques. The results of the current study indicate

that NMR identification of lignin-protein linkages,

especially linkages of the benzyl thioether and benzyl

amine types, should be possible in whole cell walls or

lignin extracts provided the linkages are adequately

abundant (Kim and Ralph 2010; Mansfield et al.

2012).

Adduct isomer determination

Of purely fundamental interest, we attempted to

resolve the stereochemistry of the products by the

use of DFT, but these efforts were largely unsuccess-

ful. For example, in the case of QM-Cys, 3, the root

mean-squared error (RMSE) between experimental

Fig. 4 HSQC NMR

spectrum of a lignin DHP

with overlaid a- and b-

correlation data from

compounds 3–11represented by red (a) and

blue squares (b). (Color

figure online)

Cellulose (2014) 21:1395–1407 1403

123

and calculated shifts was too large to reliably assign

the isomers (Table 2). Although it may have been

possible to improve the DFT results through the

addition of conformational isomers, the added com-

putational cost may not have reduced the calculated

RMSE to experimental uncertainty levels. Hence

additional attempts to resolve stereoisomers (com-

pounds 6, 7, 8) were abandoned; likewise, DFT was

not used to identify which stereoisomer was produced

in 4 and 9 (only one product was observed in each

case). Previously, addition of primary amines were

shown (via diagnostic NMR of tetrahydro-1,3-oxazine

derivatives) to strongly ([90 %) favor formation of

the syn-isomer (Ralph and Young 1983), so product 4

is likely syn.

Two a-13C NMR chemical shifts were observed for

compound 3, likely resulting from the formation of

both syn and anti stereoisomers. DFT calculated a-13C

NMR shifts are shown for both of these potential

stereoisomers. RMSEs between observed and calcu-

lated shifts were too large to reliably assign the

experimentally observed isomers.

In the case of 5 (QM-His), one a-shift was

observed, occurring at 5.7/60.2 ppm. The His system

is an interesting one to consider given the tautomer-

ization in the His imidazole group and the potential for

various regio-isomeric products (Nagy et al. 2005). In

the HMQC and HMBC spectra (see online resource)

the a-1H shows correlations to positions 2 and 5 of the

imidazole ring, though a-1H correlations to position 5

are weak and partially degenerate with correlations to

carbon A6. The NMR results suggest the formation of

both compounds 5a and 5b, resulting from either N1 or

N3 addition, but quantification of these compounds via

NMR was rendered impossible due to the aforemen-

tioned shift degeneracy. The calculated Gibbs free

energy-based Boltzmann factors in the gas-phase

suggested that compound 5b is thermodynamically

prevalent relative to compound 5a (93.5–6.5 %,

respectively), and prior work by Watts et al. (2011)

suggested that models with greater thermodynamic

abundance generally provided a-13C results that were

better correlated with experimental NMR data.

Conclusions

This study is the first to report on the synthesis of

lignin-protein model compounds and contributes to

the growing lignin NMR database. QM-amino acid

adducts were synthesized and characterized. Namely,

Cys, Lys, His, Asp, Glu, Ser, Tyr, Thr, and Hyp were

reacted with a lignin model QM—an important

intermediate in lignification. The selected QM 2

represents the structure and reactivity of QMs native

to lignin. The amino acids were selected because of

their nucleophilic side-groups; furthermore, these

amino acids are common in plant cell wall structural

proteins and represent functional groups (amines,

thiols, acids, and alcohols) that are known to react with

QMs (Awad et al. 2000; Bolton et al. 1997; Rama-

krishnan and Fisher 1983). The selected amino acids

quenched the QM with varying efficiencies (in gen-

eral, amine [ thiol [ acid [ hydroxyl) under neutral

organic solvent conditions. The secondary alcohols

(Thr, Hyp) did not react under the selected conditions,

but DFT calculations allowed for the prediction of

diagnostic NMR shifts for these lignin-protein

adducts. Although DFT was used to predict NMR

chemical shifts of lignin-protein crosslinks, the cal-

culated chemical shifts did not display the level of

accuracy required to distinguish stereoisomers. Future

studies are needed to improve the correlation between

these DFT calculations and experimentally observed

shifts.

Using the results from the lignin-protein model

compounds to identify any lignin-protein crosslinks in

planta is our goal. Based on the results herein, lignin-

protein NMR shifts should be well dispersed and, in

most cases, distinct even within the complex NMR

spectra of polymerized lignin (Fig. 4). This suggests

that the linkages may be detectable in planta if they

exist in significant quantities. This may well be

unlikely in most wild type plants due to the relatively

low abundance of cell wall proteins. However, in cases

of cell wall protein up-regulation, for example as

described by Liang et al. (2008) and Xu et al. (2013),

lignin-protein linkages are proposed to be prevalent

and perhaps important towards altering cell wall

Table 2 Observed and DFT calculated a-13C NMR chemical

shifts for compound 3

a-13C chemical shifts (ppm)

Observed Calculated RMSE

50.27 52.90–(3, syn) 2.7

50.60 53.40–(3, anti) 2.8

1404 Cellulose (2014) 21:1395–1407

123

physical and chemical properties. Thus, the ability to

conclusively identify and characterize these linkages

is crucial, and we provide a first step towards

achieving this goal.

Acknowledgments This research was supported as part of The

Center for Lignocellulose Structure and Formation, an Energy

Frontier Research Center funded by the US Department of

Energy, Office of Science, Office of Basic Energy Sciences under

Award Number DE-SC0001090, and the DOE Great Lakes

Bioenergy Research Center (DOE Office of Science BER DE-

FC02-07ER64494). The authors would like to thank and

acknowledge the Center for Lignocellulose Structure and

Formation (CLSF) and the members thereof. Student

fellowships were provided by the USDA National Needs

Program and the National Science Foundation. The authors

would like to thank Dr. Alan Benesi and Dr. Wenbin Luo for

assistance in acquiring NMR spectra of the lignin model

compounds, Dr. James Miller for acquiring mass spec data, and

Dr. Josh Stapleton for providing assistance with UV/Vis. The

primary author would also like to acknowledge Paul Munson and

Curtis Frantz for valuable discussion, and valuable interactions

with Dan Gall and other members of the Wisconsin lab.

References

Adamo C, Barone V (1998) Exchange functionals with

improved long-range behavior and adiabatic connection

methods without adjustable parameters: the mPW and

mPW1PW models. J Chem Phys 108:664–675

Albersheim P, Darvill A, Roberts K, Sederoff R, Staehelin A

(2010) Principles of cell wall architecture and assembly.

In: Plant cell walls. Garland Science, New York, New

York, pp 227–272

Awad HM, Boersma MG, Vervoort J, Rietjens IMCM (2000)

Peroxidase-catalyzed formation of quercetin quinone

methide-glutathione adducts. Arch Biochem Biophys

378:224–233

Balakshin M, Capanema E, Gracz H, Chang H, Jameel H (2011)

Quantification of lignin-carbohydrate linkages with high-

resolution NMR spectroscopy. Planta 233:1097–1110

Barone G, Duca D, Silvestri A, Gomez-Paloma L, Riccio R,

Bifulco G (2002) Determination of the relative stereo-

chemistry of flexible organic compounds by ab initio

methods: conformational analysis and Boltzmann-aver-

aged GIAO 13C NMR chemical shifts. Chem Eur J

8(14):3240–3245

Beat K, Templeton MD, Lamb CJ (1989) Specific localization

of a plant cell wall glycine-rich protein in protoxylem cells

of the vascular system. Proc Natl Acad Sci USA

86:1529–1533

Boerjan W, Ralph J, Baucher M (2003) Lignin biosynthesis.

Ann Rev Plant Biol 54:519–546

Bolton JL, Turnipseed SB, Thompson JA (1997) Influence of

quinone methide reactivity on the alkylation of thiol and

amino groups in proteins: studies utilizing amino acid and

peptide models. Chem Biol Interact 107:185–200

Buhl M, Kaupp M, Malkina OL, Malkin VG (1999) The DFT

route to NMR chemical shifts. J Comput Chem 20:91–105

Cances E, Mennucci B, Tomasi J (1997) A new integral equa-

tion formalism for the polarizable continuum model: the-

oretical background and applications to isotropic and

anisotropic dielectrics. J Chem Phys 107(8):3032–3041

Capanema EA, Balakshin MY, Kadla JF (2004) A compre-

hensive approach for quantitative lignin characterization

by NMR spectroscopy. J Agric Food Chem 52:1850–1860

Cassab IG, Varner JE (1988) Cell wall proteins. Ann Rev Plant

Physiol Plant Mol Biol 39:321–353

Chapple C, Ladisch M, Meilan R (2007) Loosening lignin’s grip

on biofuel production. Nat Biotechnol 25:746–748

Cheeseman JR, Trucks GW, Keith TA, Frisch MJ (1996) A

comparison of models for calculating nuclear magnetic

resonance shielding tensors. J Chem Phys 104:5497–5509

Chen F, Dixon RA (2008) Genetic manipulation of lignin

biosynthesis to improve biomass characteristics for agro-

industrial processes. In Vitro Cell Dev Biol Anim 44:

S28–S29

Clark T, Chandrasekhar J, Spitznagel GW, Schleyer PVR

(1983) Efficient diffuse function-augmented basis sets for

anion calculations. III. The 3-21 ? G basis set for first-row

elements, Li–F. J Comput Chem 4(3):294–301

Cosgrove D (2005) Growth of the plant cell wall. J Nat Rev Mol

Cell Biol 6:850–861

Frisch MJ, Trucks GW, Schlegel HB, Scuseria GE, Robb MA,

Cheeseman JR, Montgomery JA (2009) Gaussian 09,

revision B01. Gaussian, Inc, Wallingford

Gogonea V (1998) Self-consistent reaction field methods: cav-

ities. In: Schleyer PVR, Schreiner PR, Allinger NL, Clark

T, Gasteiger J, Kollman P, Schaefer HF III (eds) Ency-

clopedia of computational chemistry. Wiley, New York,

pp 2560–2574

Gottlieb HE, Kotlyar V, Nudelman A (1997) NMR chemical

shifts of common laboratory solvents as trace impurities.

J Org Chem 62(21):7512–7515

Harrak H, Chamberland H, Plante M, Bellemare G, Lafontaine

JG, Tabaeizadeh Z (1991) A proline-, threonine-, and

glycine-rich protein down-regulated by drought is local-

ized in the cell wall of xylem elements. Plant Phys

121:557–564

Hohenberg P, Kohn W (1964) Inhomgeneous electron gas. Phys

Rev 136(3b):B864–B871

Jose M, Puigdomenech P (1993) Structure and expression of

genes encoding for structural proteins of the plant cell wall.

New Phytol 125:259–282

Jung HG (1989) Forage lignins and their effects on fiber

digestibility. Agron J 81:33–38

Jung HG, Allen MS (1995) Characteristics of plant cell walls

affecting intake and digestibility of forages by ruminants.

J Anim Sci 73:2774–2790

Karadakov PB (2008) Ab initio calculation of NMR shielding

constants. In: Webb GA (ed) Modern magnetic resonance.

Springer, New York, pp 63–70

Kawai S, Okita K, Sugishita K, Tanaka A, Ohashi H (1999)

Simple method for synthesizing phenolic b-O-4 dilignols.

J Wood Sci 45:440–443

Kieliszewski M, Lamport DTA, Tan L, Cannon MC (2011)

Hydroxyproline-rich glycoproteins: form and function.

Ann Plant Rev 41:321–342

Cellulose (2014) 21:1395–1407 1405

123

Kim H, Ralph J (2010) Solution-state 2D NMR of ball-milled

plant cell wall gels in DMSO-d6/pyridine-d5. Org Biomol

Chem 8:576–591

Kohn W, Sham LJ (1965) Self-consistent equations including

exchange and correlation effects. Phys Rev 140(4A):

A1133–A1138

Krishnan RBJS, Binkley JS, Seeger R, Pople JA (1980) Self-

consistent molecular orbital methods. XX. A basis set for

correlated wave functions. J Chem Phys 72:650

Landucci LL, Geddes SA, Kirk TK (1981) Synthesis of 14C

labeled 3-methoxy-4-hydroxy-a-(2-methoxy-phenoxy)-b-

hydroxypropiophenone, a lignin model compound. Holzf-

orschung 35:66–69

Leary GJ (1980) Quinone methides and the structure of lignin.

Wood Sci Technol 14:21–34

Leary G, Miller IJ, Thomas W, Woolhouse AD (1977) The

chemistry of reactive lignin intermediates. Part 5. Rates of

reactions of quinone methides with water, alcohols, phe-

nols, and carboxylic acids. J Chem Soc, Perkin Trans 2

13:1737–1739

Li X, Weng JK, Chapple C (2008) Improvement of biomass

through lignin modification. Plant J 54:569–581

Liang H, Frost CJ, Wei X, Brown NR, Carlson JE, Tien M

(2008) Improved sugar release from lignocellulosic mate-

rial by introducing a tyrosine-rich cell wall peptide gene in

poplar. Clean 36(8):662–668

Lodewyk MW, Siebert MR, Tantillo DJ (2012) Computational

prediction of 1H and 13C chemical shifts: a useful tool for

natural product, mechanistic, and synthetic organic

chemistry. Chem Rev 112(3):1839–1862

Mansfield SD, Kim H, Lu F, Ralph J (2012) Whole plant cell

wall characterization using solution-state 2D NMR. Nat

Protoc 7(9):1579–1589

McQueen-Mason S, Cosgrove D (1994) Disruption of hydrogen

bonding between plant cell wall polymers by proteins that

induce wall extension. J Proc Natl Acad Sci USA

91:6574–6578

Miyagawa Y, Takemoto O, Takano T, Kamitakahara H, Na-

katsubo F (2012) Fractionation and characterization of

lignin carbohydrate complexes (LCCs) of Eucalyptus

globulus in residues left after MWL isolation. Part I:

analyses of hemicellulose-lignin fractionation (HC-L).

Holzforschung 66:459–465

Mostaghni F, Abbas T, Seyed AM (2013) Synthesis, spectro-

scopic characterization and DFT calculations of b-O-4 type

lignin model compounds. Spectrochimica Acta Part A Mol

Biomol Spec 110:430–436

Nagy PI, Tejada FR, Messer WS (2005) Theoretical studies of

the tautomeric equilibria for five-member N-heterocycles

in the gas phase and in solution. J Phys Chem 109:

22588–22602

Papajak E, Zheng J, Xu X, Leverentz HR, Truhlar DG (2011)

Perspectives on basis sets beautiful: seasonal plantings of

diffuse basis functions. J Chem Theory Comput 7(10):

3027–3034

Ralph J, Young RA (1983) Stereochemical aspects of addition

reactions involving lignin model quinone methides.

J Wood Chem Technol 3(2):161–181

Ralph J, Lundquist K, Brunow G, Lu F, Kim H, Schatz PF,

Marita JM, Hatfield RD, Ralph SA, Christensen JH (2004a)

Lignins: natural polymers from oxidative coupling of

4-hydroxyphenylpropanoids. Phytochem Rev 3:29–60

Ralph SA, Ralph J, Landucci LL (2004) NMR database of lignin

and cell wall model compounds. http://ars.usda.gov/

Services/docs.htm?docid=10491 Accessed 27 Sept 2013

Ralph J, Schatz PF, Lu F, Kim H, Akiyama T, Nelsen SF (2009)

Quinone methides in lignification. In: Rokita SE (ed)

Quinone methides. Wiley, New Jersey, pp 385–420

Ramakrishnan K, Fisher J (1983) Nucleophilic trapping of 7,11-

dideoxyanthracyclinone quinone methides. J Am Chem

Soc 105:7187–7188

Ryser U, Schorderet M, Zhao G, Studer D, Ruel K, Hauf G,

Keller B (1997) Structural cell-wall proteins in protoxylem

development: evidence for a repair process mediated by a

glycine-rich protein. Plant J 12(1):97–111

Sarotti AM, Pellegrinet SC (2009) A multi-standard approach

for GIAO 13C NMR calculations. J Org Chem 74(19):

7254–7260

Sarotti AM, Pellegrinet SC (2012) Application of the multi-

standard methodology for calculating (1)H NMR chemical

shifts. J Org Chem 77(14):6059–6065

Schreckenbach G, Ziegler T (1995) Calculation of NMR

shielding tensors using gauge-including atomic orbitals

and modern density functional theory. J Chem Phys

99(2):606–611

Stewart JJ, Kadla JF, Mansfield SD (2006) The influence of

lignin chemistry and ultrastructure on the pulping effi-

ciency of clonal aspen (Populus termuloides Michx).

Holzforschung 60:111–122

Terashima N, Atalla RH, Ralph SA, Landucci LL, Lapierre C,

Monties B (1995) New preparations of lignin polymer

models under conditions that approximate cell wall ligni-

fication. Holzforschung 49:521–527

Toikka M, Jussi S, Teleman A, Brunow G (1998) Lignin-car-

bohydrate model compounds. Formation of lignin-methyl

arabinoside and lignin-methyl galactoside benzyl ethers

via quinone methide intermediates. J Chem Soc, Perkin

Trans 1 1:3813–3818

Vanholme R, Morreel K, Ralph J, Boerjan W (2010) Lignin

biosynthesis and structure. Plant Phys 153:895–905

Watts HD, Mohamed MNA, Kubicki JD (2011) Comparison of

multistandard and TMS-standard calculated NMR shifts

for coniferyl alcohol and application of the multistandard

method to lignin dimers. J Phys Chem B 115(9):1958–1970

Whitmore FW (1978a) Lignin-carbohydrate complex formed in

isolated cell walls of callus. Phytochem 17:421–425

Whitmore FW (1978b) Lignin-protein complex catalyzed by

peroxidase. Plant Sci Lett 13:241–245

Whitmore FW (1982) Lignin-protein complex in cell walls of

Pinus elliottii: amino acid constituents. Phytochem 21(2):

315–318

Wolinski K, Hinton JF, Pulay P (1990) Efficient implementation

of the gauge-independent atomic orbital method for NMR

chemical shift calculations. J Am Chem Soc 112(23):

8251–8260

Xu Y, Chen C, Thomas TP, Azadi P, Diehl B, Tsai C, Brown N,

Carlson JE, Tien M, Liang H (2013) Wood chemistry

analysis and expression profiling of a poplar clone

expressing a tyrosine-rich peptide. Plant Cell Rep

32:1827–1841

1406 Cellulose (2014) 21:1395–1407

123

Yuan T, Sun S, Xu F, Sun R (2011) Characterization of lignin

structures and lignin-carbohydrate complex (LCC) link-

ages by quantitative 13C and 2D HSQC NMR spectros-

copy. J Agric Food Chem 59:10604–10614

Zhao Y, Shultz NE, Truhlar DG (2006) Design of density

functionals by combining the method of constraint

satisfaction with parametrization for thermochemistry,

thermochemical kinetics, and noncovalent interactions.

J Chem Theory Comput 2(2):364–382

Cellulose (2014) 21:1395–1407 1407

123