Common and distant structural characteristics of feruloyl esterase families from Aspergillus oryzae.

Abstract

Feruloyl esterases (FAEs) are important biomass degrading accessory enzymes due to their capability of cleaving the ester links between hemicellulose and pectin to aromatic compounds of lignin, thus enhancing the accessibility of plant tissues to cellulolytic and hemicellulolytic enzymes. FAEs have gained increased attention in the area of biocatalytic transformations for the synthesis of value added compounds with medicinal and nutritional applications. Following the increasing attention on these enzymes, a novel descriptor based classification system has been proposed for FAEs resulting into 12 distinct families and pharmacophore models for three FAE sub-families have been developed.
The feruloylome of Aspergillus oryzae contains 13 predicted FAEs belonging to six sub-families based on our recently developed descriptor-based classification system. The three-dimensional structures of the 13 FAEs were modeled for structural analysis of the feruloylome. The three genes coding for three enzymes, viz., A.O.2, A.O.8 and A.O.10 from the feruloylome of A. oryzae, representing sub-families with unknown functional features, were heterologously expressed in Pichia pastoris, characterized for substrate specificity and structural characterization through CD spectroscopy. Common feature-based pharamacophore models were developed according to substrate specificity characteristics of the three enzymes. The active site residues were identified for the three expressed FAEs by determining the titration curves of amino acid residues as a function of the pH by applying molecular simulations.
Our findings on the structure-function relationships and substrate specificity of the FAEs of A. oryzae will be instrumental for further understanding of the FAE families in the novel classification system. The developed pharmacophore models could be applied for virtual screening of compound databases for short listing the putative substrates prior to docking studies or for post-processing docking results to remove false positives. Our study exemplifies how computational predictions can complement to the information obtained through experimental methods.

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Common and Distant Structural Characteristics of
Feruloyl Esterase Families from Aspergillus oryzae
D. B. R. K. Gupta Udatha1, Valeria Mapelli1, Gianni Panagiotou1,2,3, Lisbeth Olsson1*
1Department of Chemical and Biological Engineering, Industrial Biotechnology, Chalmers University of Technology, Gothenburg, Sweden, 2Center for Biological
Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Lyngby, Denmark, 3Novo Nordisk Foundation Center for Biosustainability, Technical
University of Denmark, Hørsholm, Denmark
Abstract
Background: Feruloyl esterases (FAEs) are important biomass degrading accessory enzymes due to their capability of
cleaving the ester links between hemicellulose and pectin to aromatic compounds of lignin, thus enhancing the accessibility
of plant tissues to cellulolytic and hemicellulolytic enzymes. FAEs have gained increased attention in the area of biocatalytic
transformations for the synthesis of value added compounds with medicinal and nutritional applications. Following the
increasing attention on these enzymes, a novel descriptor based classification system has been proposed for FAEs resulting
into 12 distinct families and pharmacophore models for three FAE sub-families have been developed.
Methodology/Principal Findings: The feruloylome of Aspergillus oryzae contains 13 predicted FAEs belonging to six sub-
families based on our recently developed descriptor-based classification system. The three-dimensional structures of the 13
FAEs were modeled for structural analysis of the feruloylome. The three genes coding for three enzymes, viz., A.O.2, A.O.8
and A.O.10 from the feruloylome of A. oryzae, representing sub-families with unknown functional features, were
heterologously expressed in Pichia pastoris, characterized for substrate specificity and structural characterization through
CD spectroscopy. Common feature-based pharamacophore models were developed according to substrate specificity
characteristics of the three enzymes. The active site residues were identified for the three expressed FAEs by determining
the titration curves of amino acid residues as a function of the pH by applying molecular simulations.
Conclusions/Significance: Our findings on the structure-function relationships and substrate specificity of the FAEs of
A. oryzae will be instrumental for further understanding of the FAE families in the novel classification system. The developed
pharmacophore models could be applied for virtual screening of compound databases for short listing the putative
substrates prior to docking studies or for post-processing docking results to remove false positives. Our study exemplifies
how computational predictions can complement to the information obtained through experimental methods.
Citation: Udatha DBRKG, Mapelli V, Panagiotou G, Olsson L (2012) Common and Distant Structural Characteristics of Feruloyl Esterase Families from Aspergillus
oryzae. PLoS ONE 7(6): e39473. doi:10.1371/journal.pone.0039473
Editor: Aleksey Porollo, University of Cincinnati College of Medicine, United States of America
Received January 30, 2012; Accepted May 21, 2012; Published June 22, 2012
Copyright: ? 2012 Udatha et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: Financial support for this research was provided by the Swedish Research Council (Vetenskapsra ˚det Grant no: 2008-2955). The funders had no role in
study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: lisbeth.olsson@chalmers.se
Introduction
Feruloyl esterases (FAEs) have gained importance in biofuel,
medicine and food industries due to their capability of hydrolyzing
carbohydrate esters in wood polymers and synthesizing high
added-value molecules through esterification and transesterifica-
tion reactions [1–3]. Even though FAEs possess a common
characteristic feature of the Ser-His-Asp triad forming the active
site, variations in amino acid sequences forming surface loops and
additional domains allow them to accommodate different aromatic
substrates. By using the sequence properties of FAEs, Udatha et al.
[4] proposed a new classification system with common functional
characteristics for each of the 12 predicted FAE families. Briefly,
FAE-related sequences of fungal, bacterial and plant origin have
been collected and clustered using self-organizing maps followed
by k-means clustering into distinct groups based on amino acid
composition and physico-chemical composition descriptors de-
rived from the respective amino acid sequence. A Support Vector
Machine (SVM) model has been developed for the classification of
new FAEs into the pre-assigned clusters. Pharmacophore models
for the new FAE families have been designed for which sufficient
information of known substrates existed. The development of
pharmacophore models based on substrate spectra for specific
FAE sub-families is expected to be a crucial tool for designing the
application of members of the particular sub-family to completely
novel and targeted substrates. Virtual screening with the de-
veloped pharmacophores of chemical and natural compound
databases could reveal unique opportunities for FAEs-based-
biocatalysis for synthesis of compounds with altered or improved
bioactive properties. However, a detailed understanding of the
structural factors responsible for stability and activity of FAE
families is still not available.
In the present work we predicted that Aspergillus oryzae possesses
thirteen FAEs that fall into six different FAE sub-families (Table 1),
and we collectively designated them as the ‘feruloylome’. Out of
the 13 members, three FAEs have been partially characterized
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[5,6]. The structural characterization of these enzymes and the
connection with their functionality remains to be mapped.
Although significant partial characterization experimental work
has been reported on FAEs [1,5,7–11], computational studies to
understand FAE structural characteristics have not emerged yet.
Recent work has demonstrated that various structural bioinfor-
matics tools such as homology modeling and molecular dynamics
simulations can provide information to gain insights of protein/
receptor functional elements [12–16]. Due to absence of crystal
structures for the A. oryzae feruloylome members, we exploited
here a combined approach of molecular modeling and molecular
dynamics simulations to investigate the structural features of FAEs.
Identifying the residues involved in the catalytic mechanism and
understanding the environment of the enzyme binding pocket
would expand our toolbox for targeted engineering. Furthermore,
we expressed and investigated the structure-function relationships
of three feruloylome members by collecting experimental data
determining the substrate specificity towards 15 substrates and
enzyme activity as a function of pH using Circular Dichroism (CD)
spectroscopy.
Methods
Sequences
Nucleotide and amino acid sequence information were retrieved
from the National Center for Biotechnology Information [17].
The gene sequences, mRNA sequences and amino acid sequences
for the feruloylome of Aspergillus oryzae are available in the
Supporting Information S1.
In Silico Analysis
Primary structure analysis of the FAE amino acid sequences was
performed using ProtParam, by computing various physical and
chemical parameters including the molecular weight, theoretical
pI, extinction coefficient and absorbance for a user entered
sequence [18]. The amino acid sequences were analyzed for the
presence of native signal peptide using the SignalP 3.0 server,
which predicts the presence and location of signal peptide cleavage
sites in amino acid sequences based on a combination of several
artificial neural networks and hidden Markov models [19–21].
The summary of calculated physico-chemical parameters and
post-translational modification analysis of the mature FAEs are
given in Table S1. Three-dimensional atomic models for the
A. oryzae feruloylome sequences were modeled from multiple
threading alignments [22] and iterative structural assembly
simulations using I-TASSER algorithm [23–26]. Structure re-
finement of modeled structures was carried out using the
Discovery Studio software suite version 3.0 (Accelrys Inc, USA).
The Prepare Protein protocol package in Discovery Studio suite
was used for inserting missing atoms in incomplete residues,
modeling missing loop regions [27], deleting alternate conforma-
tions (disorder), standardizing atom names, and protonating
titratable residues using predicted pKs [28]. The Side-Chain
Refinement protocol was used for each structure to optimize the
protein side-chain conformation based on systematic searching of
side-chain conformation and CHARMM Polar H energy mini-
mization [29] using the ChiRotor algorithm [30]. Smart
Minimizer algorithm was used for the minimization process which
performs 1000 steps of Steepest Descent with a RMS gradient
tolerance of 3, followed by Conjugate Gradient minimization for
faster convergence towards a local minimum [31]. Structure
evaluations were carried out using DOPE, which is an atomic
based statistical potential in MODELER package for model
evaluation and structure prediction [32]. Structure verifications
were carried out using VerifyProtein-Profiles-3D that allows
evaluating the fitness of a protein sequence in its current 3D
environment [33].
Gene Cloning, Expression and Purification
Genes and vectors.
as described earlier [34] was a kind gift from Department of
Systems Biology-DTU. DNase treatment of the RNA sample and
further RNA cleanup were performed according to the manu-
facturer’s instructions using RNase-Free DNase Set and RNeasy
Mini Kit, respectively (QIAGEN Nordic, Sweden). Quality and
quantity of the RNA samples were determined by using
a BioPhotometer (Eppendorf, Germany). The purified RNA was
stored at 280uC until further processing. The primers were
designed to amplify the mature-protein coding sequences exclud-
ing the signal peptide. cDNA synthesis was carried out using the
Transcriptor One-Step RT-PCR Enzyme Mix (Roche Diagnostics
GmbH, Germany). Purification of the cDNA from the RT-PCR
product mixture was performed using the QIAquick PCR
Purification Kit according to the manufacturer’s protocol (QIA-
GEN Nordic, Sweden). Primers were designed using the
OligoCalc tool [35] and Clone Manager software version 9
(Scientific & Educational Software, USA). The list of oligo
nucleotide primers used is given in the Table S2. The plasmid
pPICZa-C vector (Invitrogen, UK) was used for cloning and
expression in Pichia pastoris.
Cloning.
Restriction of purified cDNA from Transcriptor
One-Step RT-PCR and restriction of pPICZa-C vector were
carried out with respective restriction enzymes (Fermentas,
Lithuania) reported in Table S2. Purification of restricted DNA
molecules was performed using the QIAquick PCR Purification
Kit (QIAGEN Nordic, Sweden). The genes were cloned into the
pPICZa-C vector (Invitrogen, UK), which includes the a-factor
signal sequence for secretion of proteins, c-myc epitope and 6-His
tag to the c-terminal of each recombinant protein. Ligation of
respective restricted vectors and restricted inserts was carried out
using T4 DNA Ligase according to the manufacturer’s protocol
(Fermentas, Lithuania). Isolation of plasmid constructs from
transformed E. coli cells was carried out using GenElute HP
The RNA isolated from Aspergillus oryzae
Table 1. Feruloylome members of Aspergillus oryzae.
ID1
GI number and Protein
accession
Amino acid
lengthSub-family2
A.O.1gi|83776083|dbj|BAE66202.1| 446FEF 4A
A.O.2gi|83768497|dbj|BAE58634.1|573FEF 4A
A.O.3gi|83770997|dbj|BAE61129.1|525FEF 4B
A.O.4gi|169768564|ref|XP_001818752.1|281 FEF 6B
A.O.5 gi|169783734|ref|XP_001826329.1|307FEF 6B
A.O.6gi|83776294|dbj|BAE66413.1| 516FEF 7A
A.O.7gi|83775577|dbj|BAE65697.1|514FEF 7A
A.O.8gi|83771599|dbj|BAE61730.1|524FEF 7A
A.O.9gi|83769703|dbj|BAE59838.1|502FEF 7A
A.O.10gi|83775432|dbj|BAE65552.1|588FEF 12B
A.O.11gi|83766949|dbj|BAE57089.1| 526 FEF 4B
A.O.12gi|83769004|dbj|BAE59141.1| 529 FEF 11A
A.O.13gi|83766486|dbj|BAE56626.1| 540 FEF 12B
1For convenience the ID designations were used throughout the article.
2According to descriptor based FAE classification system [4].
doi:10.1371/journal.pone.0039473.t001
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plasmid miniprep kit (SIGMA-ALDRICH, USA) and confirma-
tion of the clones was done by restriction analysis. Correct
insertion of the FAE-encoding genes and absence of mutations
were checked by DNA sequencing (Eurofins MWG operon,
Germany).
Media and strains.
The Escherichia coli strain TOP10
(Invitrogen, UK) was used as intermediate host for cloning and
plasmid amplification and was grown on LB-medium [36] under
appropriate selective conditions (zeocin 25 mg?L21). For expres-
sion of recombinant proteins the protease-deficient P. pastoris strain
SMD1168H (Invitrogen, UK) was transformed with pPICZa-C/
FAE constructs and positive clones were selected on selective
YPDS medium (Sorbitol 182.2 g?L21; yeast extract 10 g?L21;
peptone 20 g?L21; dextrose10 g?L21; 25 mg?L21
Expression experiments were carried out in Buffered Glycerol-
Complex Medium (BMGY) and Buffered Methanol-Complex
Medium (BMMY) during induction phase. The complex expres-
sion media, prepared in 100 mM potassium phosphate buffer
(pH 6.0), contained 1% w/v yeast extract, 2% w/v peptone,
1.34% w/v Yeast Nitrogen Base, 461025% w/v biotin, 1% v/v
glycerol and 1% v/v methanol in case of BMGY and BMMY,
respectively.
Transformation of P. pastoris.
of the pPICZa-C/FAE constructs in the genome of P. pastoris,
respective constructs were linearized using the PmeI restriction
enzyme followed by purification of the linearized constructs prior
to transformation. Transformations of P. pastoris with respective
constructs were carried out by electroporation according to the
manufacturer’s protocol (Invitrogen, UK). To test integration of
respective vector construct into the genome, direct PCR Screening
of 12 Pichia clones for each type of insert was performed using two
sets of primers. The first set contains 5’AOX1 primer and 3’primer
(Table S2) of the respective insert; the second set contains 3’AOX1
primer and 5’primer (Table S2) of the respective insert. The PCR
zeocin).
To promote the integration
products obtained from respective primer sets were analyzed on
agarose gel.
Screening of colonies for highly expressing P. pastoris
transformants.
Six positive colonies of each transformation
were picked and small-scale expression trials were performed.
Respective transformants were pre-cultured overnight in 50 mL
BMGY medium (in 500 ml baffled flasks) at 30uC and 220 rpm
overnight. Cells were harvested and diluted in 150 mL BMMY
medium to a final OD600of 1.0. Cultures were grown in 1L baffled
flasks at 30uC and 220 rpm for 96 hours and methanol was added
to a concentration of 0.5% every 24 hours. Samples were taken
periodically and the supernatants were analyzed for FAE activity
in the extracellular medium.
Purification of recombinant feruloyl esterase.
hours of incubation, respective liquid cultures of P. pastoris were
filtered using 0.2 mm bottle-top vacuum filters (Nalge Nunc
International, USA). The filtrate was pre-equilibrated with
20 mM Imidazole and loaded onto Ni SepharoseTM6 Fast
Flow resin (GE Healthcare, USA), which was pre-equilibrated
with buffer I (20 mM sodium phosphate buffer, 500 mM NaCl,
pH 7.4). The resin was washed with buffer II (20 mM sodium
phosphate buffer, 500 mM NaCl, 20 mM Imidazole, pH 7.4),
and the target protein was eluted with buffer III (20 mM
sodium phosphate buffer, 500 mM NaCl, 500 mM Imidazole,
pH 7.5). Buffer exchange was performed using a 10 kDa
AmiconRUltra (Millipore, Ireland) centrifugal filters to remove
the imidazole. The protein concentration was determined by the
Bradford method using bovine serum albumin as a standard
[37]. Molecular weight of expressed FAEs was checked by SDS-
PAGE using TGX precast gels of 4–15% resolving gel (Bio-
Rad, USA). Protein bands were visualized by SYPRO ruby
protein gel stain (Invitrogen, UK).
After 96
Table 2. Cross-structure statistics for 3D structure alignment of FEF family members of A.oryzae feruloylome.
Cross-structure statistics: RMSD1
Cross-structure statistics: Sequence Identity2
FEF StructureA.O.1 A.O.2A.O.3A.O.11 FEFStructureA.O.1 A.O.2A.O.3A.O.11
FEF 4A.O.11.862 3.7553.893 FEF 4 A.O.10.396 0.123 0.123
A.O.2 1.862 3.5483.694A.O.2 0.3960.160 0.144
A.O.33.755 3.548 2.707A.O.30.1230.1600.299
A.O.113.8933.6942.707 A.O.110.1230.1440.299
A.O.4A.O.5A.O.4A.O.5
FEF 6A.O.43.380FEF 6A.O.40.142
A.O.53.380A.O.50.142
A.O.6A.O.7A.O.8A.O.9A.O.6A.O.7A.O.8A.O.9
FEF 7A.O.63.0773.0343.369FEF 7A.O.60.2290.1930.188
A.O.73.0773.3883.722A.O.70.2290.1770.234
A.O.83.0343.3881.887A.O.80.1930.1770.323
A.O.93.3693.7221.887A.O.90.1880.2340.323
A.O.10A.O.13 A.O.10 A.O.13
FEF 12 A.O.103.583 FEF 12A.O.100.191
A.O.133.583 A.O.130.191
1RMSD stands for the Root Mean Square Deviation, calculated between Ca-atoms of matched residues at best 3D superposition of the query and target structures.
RMSD is presented in angstroms. In simple words, RMSD gives you an idea how separated, at best 3D superposition, a ‘‘typical’’ pair of matched Ca-atoms is.
2Sequence identity is a quality characteristic of Ca-alignment. It is calculated from structure (3D), rather than sequence alignment. Therefore, two almost identical
sequences may be estimated at low sequence identity if they fold into slightly different structures.
doi:10.1371/journal.pone.0039473.t002
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Figure 1. Regions of similar SSEs among the FEF family members shown as ribbon structures. Structurally similar regions are colored
whereas dissimilar regions are depicted in grey. (A) Structural similarity in the secondary structure elements of FEF 4 family members. (B) Structural
The Feruloylome of Aspergillus oryzae
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Enzyme Activity Assay
The assay was based on a previously reported spectrophoto-
metric method for determination of FAE activity recommended by
Biocatalysts Limited, Wales, UK [38,39]. The absorption spectra
(FLUOstar Omega, BMG LABTECH, Germany) of the methyl
esters of cinnamic acids and their hydrolysis products was
monitored at 240–600 nm and their absorption maxima were
determined [40]. FAE activity was expressed in milliUnits (mU);
1 mU was equal to 1 nmol of ferulic acid or respective cinnamic
acid released in 1 ml of the reaction medium after 1 min of
incubation [38]. The assays were done in triplicates and Kmvalues
were calculated using SigmaPlot for Windows, Version 12.0
(Systat Software Inc, USA).
The expressed recombinant FAEs were tested against 15 methyl
cinnamate esters (obtained from Aapin Chemicals, UK) viz.,
Methyl ferulate or Methyl 4-hydroxy-3-methoxy cinnamate
(MFA), Methyl caffeate or Methyl 3,4-dihydroxy cinnamate
(MCA), Methyl p-coumarate or Methyl 4-hydroxy cinnamate
(MPC), Methyl sinapate or Methyl 4-hydroxy-3,5-dimethoxy
cinnamate (MSA), Methyl 2-hydroxy cinnamate (M2C), Methyl
3-hydroxy cinnamate (M3C), Methyl cinnamate (MC), Methyl
3,4,5-trimethoxy cinnamate (MTM), Methyl 2-methoxy cinna-
mate (M2M), Methyl 3-methoxy cinnamate (M3M), Methyl 4-
methoxy cinnamate (M4M), Methyl 3,4-dimethoxy cinnamate
(M34DC), Methyl 3,5-dimethoxy cinnamate (M35DC), Methyl 3-
hydroxy-4-methoxy cinnamate (M34MC) and Methyl 4-hydroxy-
3-methoxy phenyl propionate (M43PP).
Circular Dichroism Spectroscopy
The far-UV Circular Dichroism (CD) measurements were
carried on a ChirascanTMCD Spectrometer equipped with
a thermostated cell holder (Applied Photophysics Limited, UK).
ChirascanTMCD Spectrometer is endowed with photon flux for
a 1 nm bandwidth in excess of 1013per second for all UV
wavelengths from 360 nm to 180 nm. During CD spectroscopy
analysis, respective purified 66His N-terminally tagged recombi-
nant proteins (0.5 mg/mL) were resuspended in the corresponding
buffer (pH 3.0–pH 11.0) and analysed at room temperature
(,25uC). UV CD spectra between 185 and 250 nm were collected
with a data pitch of 0.1 nm, bandwidth of 2.0 nm and scanning
speed of 50 nm/min [41]. Each sample was measured in triplicate,
and data between 190–240 nm were analyzed using the K2D2
method. K2D2 method uses a self-organized map of spectra from
proteinswithknownstructuretodeduceamapofproteinsecondary
structure that is used to develop the predictions [42–44].
Molecular Simulations and Amino Acid Titration Curves
CHARMM (Chemistry at HARvard Molecular Mechanics) was
used to perform molecular simulations. Calculations of protein
ionization and residue pK to obtain amino acid titration curves in
the present study were performed using an implementation of the
Generalized Born solvation model in CHARMM and the atomic
parameters were taken from either CHARMM or CHARMM
polar hydrogen force fields (Discovery Studio 3.0, Accelrys Inc,
USA). The side-chains of certain amino acid residues viz., Asp,
Glu, Arg, Lys, His, Tyr, Cys, and the N-termini and C-termini of
each protein chain, are titratable. Using the theory developed by
Bashford and Karplus [45], the pK of a titratable residue in
a protein structure can be predicted from the pK of the model
compounds based on the electrostatic interactions of this residue to
the other residues.
Results and Discussion
Protein Model Structures of the A. oryzae Feruloylome
Our effort in finding structure-function relationships in FAEs
requires three-dimensional protein structures, hence several
homology-model structures were derived each having a C-score.
C-score is a confidence score that gives an estimate of the quality
of predicted models and is calculated based on the significance of
threading template alignments and the convergence parameters of
the structure assembly simulations. C-score is typically in the range
of (25,2), where a C-score of higher value signifies a model with
a high confidence and vice-versa [23,24,26]. All modeled
structures of A. oryzae feruloylome were in the specified C-score
range. The Protein Data Bank (PDB) structures used for multi
template modeling and their respective secondary structure
alignments are given in the Supporting Information S2. The
coordinates of the model structures with high C-scores were
submitted to the Protein Model DataBase (PMBD) [46]. The
solvent surface rendering (probe radius of 1.4) of the modeled
structures colored according to the secondary structure elements
and respective PMDB accession codes is given in Figure S1. The
verification scores viz., DOPE (Discrete Optimized Protein
Energy) score, DOPE-HR score, Verify score and the potential
energies of the modeled structures (see Table S3) revealed high
quality of the models.
similarity in the secondary structure elements of FEF 6 family members. (C) Structural similarity in the secondary structure elements of FEF 7 family
members. (D) Structural similarity in the secondary structure elements of FEF 12 family members.
doi:10.1371/journal.pone.0039473.g001
Table 3. Substrate specificity of characterized FAEs that
belong to five different sub-families for the methyl esters of
a series of 15 substituted cinnamic acids. Kmis expressed as
mM.
FEF 12AFEF 4BFEF 4A FEF 4A FEF 7AFEF 12B
AnFAEA1TsFAEC2AnFAEB1A.O.2A.O.8 A.O.10
MFA 0.720.04 1.321.391.72 2.14
MCA ND
,0.0050.22 2.361.95 3.02
MPCND 0.01 0.0141.51ND ND
MSA0.45 0.37 ND ND7.06 6.44
M2C ND0.015ND 1.733.991.64
M3CND 0.0250.55 2.552.12 2.21
MC ND0.118 0.79 3.141.03ND
MTM1.63ND ND ND1.92 3.8
M2MND ND0.720.73 ND0.67
M3M1.990.301 NDND10.75
M4M NDND0.310.55 3.48ND
M34DC1.360.626 ND NDND0.4
M35DC0.920.075 ND ND4.754.06
M34MC ND0.5330.851.472.571.77
M43PP2.080.0163.178.646.247.25
ND, Not Detected.
1Values taken from Topakas et al [65].
2Values taken from Vafiadi et al [66].
doi:10.1371/journal.pone.0039473.t003
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