Metabolomic study of water hyacinth exposed to CuCI2, FeCI3, Na2HPO4 solution by GC m

METABOLOMIC STUDY OF WATER HYACINTH
EXPOSED TO CuCl2, FeCl3 AND Na2HPO4 SOLUTIONS
BY GC-MS

HUANG XULEI

NATIONAL UNIVERSITY OF SINGAPORE
2014


METABOLOMIC STUDY OF WATER HYACINTH
EXPOSED TO CuCl2, FeCl3 AND Na2HPO4 SOLUTIONS
BY GC-MS

HUANG XULEI
(M. Sc., PEKING UNIVERSITY)

A THESIS SUBMITTED
FOR THE DEGREE OF MASTER OF SCIENCE
DEPARTMENT OF CHEMISTRY
NATIONAL UNIVERSITY OF SINGAPORE
2014


DECLARATION
I hereby declare that this thesis is my original work and it has been written by me
in its entirety, under the supervision of Prof. Sam Li Fong Yau, Chemistry
Department, National University of Singapore, between 12 August 2013 and 12
August 2014.
I have duly acknowledged all the sources of information which have been used in
the thesis.

This thesis has also not been submitted for any degree in any university
previously.

Huang Xulei

Name

8 August 2014

Signature

I

Date


ACKNOWLEDGEMENTS

First and foremost, I would like to thank my supervisor Prof. Li Fong Yau for
giving me the chance to join his group and for encouraging me to enter into the
wonderful world of analytical chemistry. His integral view on research has made a
deep impression on me and has helped me out immensely by keeping me and my
research focused and on track. I owe him lots of gratitude for having shown me the
ways of scientific research. Besides of being an excellent supervisor, Prof Li was as
close as a relative and a good friend to all the students. I am really glad that I have
come to get know Prof. Li in my life.
I would like to thank all the staffs and students in particular Dr.Liu Feng, Dr. Gan
Pei Pei, Dr. Li Ping Jing, Dr. Guo Rui, Lin Xuanhao, Lai Linke, Feng Ting, Wu Ye
and Liang Xiaojian who were in the same lab with me. Over the last year, I have
indeed enjoyed working with them. They are so kind and ready to help me when

necessary. We also discussed and shared some knowledge and information with each
other freely. Best wishes to all of them.
Finally, heartful thanks go to my family for their immense support along the way.

II


TABLE OF CONTENTS

DECLARATION .................................................................................................. I
ACKNOWLEDGEMENTS ................................................................................. II
TABLE OF CONTENTS .................................................................................... III
SUMMARY ......................................................................................................... V
LIST OF TABLES .............................................................................................. VI
LIST OF FIGURES ........................................................................................... VII
1

INTRODUCTION ......................................................................................... 1

1.1

INTRODUCTION TO METABOLOMICS ........................................................ 1

1.2

PLANT METABOLOMICS................................................................................ 3

1.2.1 PLANT METABOLOMICS IN RESPONSE TO ABIOTIC STRESSES .......... 5
1.3

HEAVY METAL ACCUMULATION IN WATER HYACINTH ...................... 14

1.4

BASIS AND SIGNIFICANCE OF DISSERTATION ....................................... 15

2

MATERIALS AND METHODS ..................................................................17

2.1

MATERIALS..................................................................................................... 17

2.2

INSTRUMENTS AND REAGENTS ................................................................ 17

2.3

SAMPLE EXTRACTION AND DERIVATIZATION ...................................... 18
III


2.4

GC-MS ANALYSIS .......................................................................................... 18

2.5

DATA ANALYSIS ............................................................................................. 18

3

RESULTS AND DISCUSSION ....................................................................20

3.1

GC RESULTS ANALYSIS ............................................................................... 20

3.2

IDENTIFIED COMPOUNDS ........................................................................... 25

3.3

PCA ANALYSIS ............................................................................................... 32

3.4

WEAKNESS AND PROSPECT OF THE STUDY .......................................... 37

4

CONCLUSION ............................................................................................39

BIBLIOGRAPHY...............................................................................................41

IV

SUMMARY
It is generally accepted that water hyacinth is capable of adsorbing excessive heavy
metals, but the metal adsorption mechanism in the metabolic level is unknown. In this
study, the water hyacinth plants were cultured in 0.3 mmol FeCl3, 1.2 mmol CuCl2
and 3.46 mmol Na2HPO4 solution for 15 days, respectively. The metabolic profiles of
roots, stems and leaves of water hyacinth were determined by GC-MS and further
analyzed by PCA method. Results showed that plants suffered severe damage under
FeCl3 exposure but were tolerable to Na2HPO4 exposure. Metabolites levels in stems
and leaves increased but decreased in roots under CuCl2 exposure. Leaves and stems
of the four differently treated plants could be distinctly separated in three-dimensional
PCA, while roots could only be separated between control group and the treated
groups individually by two-dimensional PCA. Levels of D-glucopyranose,
L-threonine, Butanoic acid and 9H-Purin-6-amine significantly increased in treated
plants and acted as osmoprotectants. This study provided an overall perspective of
metabolites change in water hyacinth for mechanism of metal accumulation.

V


LIST OF TABLES
Table 1 Advantages and disadvantages of NMR and MS for metabolomics study. ... 3
Table 2 (a)Identified compounds in leaves of control and Na2HPO4, FeCl3, CuCl2
exposed samples in sequence of retention time (RT) and the corresponding peak
areas. The peak areas were normalized to the mean response calculated for the
control of each measured batch (±standard error). ................................................ 25
Table 2 (b)Identified compounds in stem of control and Na2HPO4, FeCl3, CuCl2
exposed samples in sequence of retention time (RT) and the corresponding peak
areas. The peak areas were normalized to the mean response calculated for the
control of each measured batch (±standard error). ................................................ 25

Table 2 (c) Identified compounds in root of control and Na2HPO4, FeCl3, CuCl2
exposed samples in sequence of retention time (RT) and the corresponding peak
areas. The peak areas were normalized to the mean response calculated for the
control of each measured batch (±standard error). ................................................... 25

VI


LIST OF FIGURES
Figure 1. GC results of leaves pretreated by (a) wet grinding and (b) dry grinding
in the control group ....................................................................................... 20
Figure 2. GC results of stems pretreated by (a) wet grinding and (b) dry grinding
in the control group ........................................................................................ 21
Figure 3. GC results of roots pretreated by (a) wet grinding and (b) dry grinding
in the control group ........................................................................................ 22
Figure 4. GC results of leaf in the control group (a) before cultivation and (b)
after cultivation .............................................................................................. 23
Figure 5. GC results of (a) leaf, (b) stem and (c) root in the control group after
cultivation ...................................................................................................... 24
Figure 6. Three-dimensional PCA of the metabolic profiles of (a)leaf, (b) stem
and (c) root in control and the exposed samples. ........................................... 33
Figure 7. Two-dimensional PCA of the metabolic profiles in roots of (a) control
vs Na2HPO4 treated group, (b) control vs FeCl3 treated group and (c) control
vs CuCl2 treated group ................................................................................... 35

VII


1 Introduction
1.1 Introduction to metabolomics

Metabolomics is a science for living systems (including cell, tissue and organism)
research through examining metabolic responses or time-course variation of living
systems when they are subjected to stimulation or disturbance. Based on group
indicators, the goal of metabolomics as a branch of systems biology is information
modeling and system integration via high-throughput detection and data processing.
Metabolomics is another important research area in systems biology following after
genomics, transcriptomics and proteomics. The focus of metabolomics is metabolites
variation of small molecules with molecular weight smaller than 1000 in metabolism,
reflecting metabolic responses variation of cells or tissues subjected to outside stimuli
or genetic modification.
The living organism is a dynamic system regulated by multi-factors integratively.
In the biological information transport chain from genes to traits, organisms need to
constantly adjust their own complex metabolic network to maintain normal dynamic
balance within system or between system and external environment. The existence of
DNA, mRNA and protein provides a material basis for the biological processes, while
metabolic substances and metabolic phenotype reflect a biological event that has
happened. The metabolic substances and metabolic phenotype are the comprehensive
result of genotype and environment combination, and direct embodiment of
physiological and biochemical function status in a biological system. Therefore, as an
important component of systems biology, metabolic groups can better reflect the
system phenotype.
1


The process of metabolomics analysis includes sample preparation, data collection,
data analysis and interpretation. The sample preparation is composed of sample
extraction, pretreatment and compounds separation. After extracted by water or
organic solvent, samples are commonly pretreated using solid-phase microextraction,
solid-phase extraction and affinity chromatographic methods. Then compounds are
separated

via

electrophoresis

gas

chromatography,

methods,

etc.

Such

liquid

chromatography

separation

and

analysis

and

capillary

methods

as

chromatography, mass spectrometry (MS), nuclear magnetic resonance (NMR),
infrared spectroscopy, coulometric analysis, ultraviolet absorption, fluorescent
scattering, radioactivity detection and light scattering and their combinations are all
applied in the metabolomics study. Among them, the NMR technology, especially the
hydrogen spectrum (1H NMR), chromatography and MS become the main analysis
tools, due to the universality of 1H NMR for hydrogen metabolites, and high
resolution and high flux of chromatography, and universality, high sensitivity and
specificity of MS. Later period of Metabolomics research is to interpretate the
biological significance of data based on data analysis and interpretation with the aid
of bioinformatics platform. Constantly used methods by far include multiple
regression, discriminant analysis, principal component analysis, hierarchical cluster
analysis, factor analysis and canonical analysis, etc.
NMR and MS based approaches in metabolomics have their own advantages and
disadvantages, respectively (Table 1). The advantages of NMR involve high
reproducibility, minimal sample preparation, short analysis time and low cost per
sample, while MS has the advantages of high sensitivity, availability for targeted
analysis, cheaper instrument cost. Choosing whether NMR or MS for metabolomics
study depends on the purpose of the study, the research object and the instrument
2


availability.
Table 1 Advantages and disadvantages of NMR and MS for metabolomics study.

NMR

MS

Sensitivity

Low

High

Reproducibility

Very high

Average

Number of detectable
metabolites

30-100

300-1000+ (depending on whether
GC-MS or LC-MS is used)

Targeted analysis

Not optimal
analysis

targeted

Better for targeted analysis than NMR

Sample preparation

Minimal sample preparation
required

More complex sample preparation
required

Tissue extraction

Not required. Tissues can be
analyzed directly

Requires tissue extraction

Sample analysis time

Fast. The whole sample can be
analyzed in one measurement

Takes longer than NMR. Requires
different chromatography techniques
for depending on type of metabolites
analyzed

Instrument Cost

More expensive and occupies
more space than MS

Cheaper and occupies less space than
NMR

Sample Cost

Low cost per sample

High cost per sample

for

1.2 Plant metabolomics
In 1999, Nicholson team put forward the concept of metabonomics [1]. So far they
have done a lot of fruitful work in disease diagnosis and drug screening and so on ([2];
[3]; [4]). Fiehn [5] put forward the concept of metabolomics and correlated
metabolites to biological gene function for the first time. Afterwards, many plants
chemists had been carrying out research on plant metabolomics.
3


The application of metabolomics in plant research mainly included following
aspects: (1) plant metabolites of certain species. Such researches usually focused on a
certain plant, selected a particular organ or tissue, analyzed the metabolites
qualitatively and quantitatively, studied comprehensively on changes of metabolites
types and contents in different periods or different parts, and further speculated the
corresponding metabolic pathways and metabolic networks through these changes; (2)
phenotype Metabolomics of different genotypes plants. Such researches usually
studied two or more than two plants (including normal controls and genetically
modified plants), comparing and identifying different genotypes plants using
metabolomics, as comparison of difference between the mutant or genetically

modified plants and normal wild-type plants, or difference between tissue-cultured
Metabolomics and the wild-type. This category of studies played an important role in
evaluation of the efficacy of genetic modification or tissue culture and screening of
good varieties; (3) metabolomics of certain ecotypes plants. Such researches usually
chose the same type of plants under different ecological environment, and studied the
effect of habitat on plant metabolites; (4) plant autoimmune response after external
stimulation. In such researches, changes of plant metabolites were induced by
exogenous chemicals stimuli, physical or biological stimuli and were monitored and
comprehensively analyzed by metabolomics method; (5) application in gene function
research. Metabolic products are the final products of gene expression and tiny
changes in gene expression level may lead to massive changes of metabolites.
Previous determination of rise and fall of gene expression level through visible
phenotypic change takes long time, and sometimes gene expression changes cannot
cause phenotypic change, while the content of certain metabolites in plant body has
already changed significantly. Using of metabolomics method can judge the change of
4


gene expression level, so as to deduce the function of genes and their metabolic flux.
A lot of research results have been made in the plant metabolomics research. Fiehn
[5] analyzed the petiole vascular and leaf extract of Cucurbita maxima using GC-MS
and obtained more than 400 peaks. By comparison with the mass spectrum database,
he preliminarily identified 90 compounds, and compared the differences on
metabolites in sugar and amino acid composition between petiole and leaf; Tiessen et
al. (2002) [6] conducted Metabolomic analysis of Solanum tuberosum tuber using
high performance liquid chromatography (HPLC). They determined the quantity
change of a series of substrates, intermediates, enzyme and products in the starch
synthesis approach. Then through comparison research between the wild and
heterologous adenosine diphosphate glucose focal phosphorylase (AGPase)
transgenic potatoes, they proposed a new regulating mechanism in the starch synthesis

approach; Maier, etc (1999) [7] studied the effect of Glomus intraradices on
Nicotiana tabacum root metabolism, compared the metabolites difference between
tobacco roots with and without Glomus intraradices. To sum up, Metabolomics
technology is an ideal platform for plant metabolism study.

1.2.1 Plant metabolomics in response to abiotic stresses

Recently many scientific research institutions carried out metabolomics studies on
abiotic stress responses of plants. Through qualitative and quantitative analysis of
plant metabolites under stress environment via modern detection and analysis
methods, the variation trend and rule of plant metabolites over time can be monitored.
The integration of various omics platforms such as genomics, proteomics and
metabolomics is also a powerful toolkit [8]. Combination of all these information
5


helps to study responses of biological systems to genes or environment changes as a
whole. For example, one can judge the level where metabolites change happens,
helping people uncover the mysterious and complex mechanism of plant stress
response. These stress factors include water deficit, excessive high or low temperature,
phosphorus and sulfur deficit, excessive salt and heavy metals and so on.
(1) Drought stress
Water is one of the important factors that affect plant growth and development. The
harmful effect on plant due to less environmental moisture is called drought stress.
In order to study the contribution of different wine grape (Vitis vinifera) fruit
organization to the wine quality and the influence of drought stress on wine quality,
Grimplet (2009) [9] determined protein with specific differences in fruit (peel and
fruit pulp) and tissue of wine grape planted under condition of enough moisture and
dry environment. Using two-dimensional gel electrophoresis (2-d PAGE) technology,
1047 proteins in fruits were detected, among which 90 were differentially expressed

in peel and fruit, while 695 proteins were detected in seeds, among which 163
proteins showed almost no difference in the seed and pee expression spectrum.
Drought stress changed abundance of about 7% skin protein, but showed little effect
on seed protein expression. In the selected 32 small molecule metabolites to be
determined, about 50% showed differences in the peel and seeds organizations, while
under drought stress condition 7 compounds were affected in accumulation within
grape fruits. The metabolic fingerprinting results provided new inspiration for
studying the effect of drought on the main compounds related to wine flavor and
aroma in grape. Deluc etc. (2009) [10] studied the metabolomics and transcriptome of
two different strains of grape Cabernet Sauvignon and Chardonnay under long-term
6


drought and seasonal drought. Studies showed different metabolic pathway changes
for two strains of grape in the response to drought stress. For Cabernet Sauvignon, the
glutamic acid and proline synthesis pathways and some important intermediate steps
in styrene acrylic acid synthesis pathway can be activated by drought stress, while for
Chardonnay under drought stress, styrene acrylic acid, carotenoids and isoprenoid
synthesis pathways were activated. Both stress responses involved influence on
abscisic acid metabolic pathway. These metabolic products changes had a great
influence on fruit and wine flavor.
Mane etc. (2009) [11] conducted metabolic profile analysis and biomass and yield
comparison of two genotypes Andean potato (Solanum tuberosum ssp. Andigena Juz
& Buk Hawkes) Sullu and Ccompis. Results showed that although the tuber yield of
the two genotypes potatoes was not obviously affected, the aboveground biomass of
Ccompis reduced and Sullu biomass was not affected. Sucrose and and trehalose in
regulatory molecules accumulated in Sullu blade, while in Ccompis blade, the
oligosaccharide family way of cottonseed sugar was activated, and low level change
of sucrose and a small amount of stress-related trehalose change. Proline and related
gene expression level improved, and the expression amount of which in Sullu is 3

times more than Ccompis. To sum up, the yield of two genotypes plants showed no
obvious change under drought condition, but the biomass accumulation and
metabolite changes were obviously different.
(2) Temperature stress
Plant response to temperature in growth and development has three basic points:
lowest temperature, optimum temperature and maximum temperature. The harmful
effect on plant caused by too low or too high temperature is called temperature stress.
7


Shulaev et al. (2008) [12] reviewed in detail plant metabolomics under temperature
stress. The metabolic fingerprinting technology is used to explore response of
Arabidopsis thaliana plants (Arabidopsis) to temperature stress. Kaplan et al. (2004)
[13] studied metabolic fingerprint of Arabidopsis thaliana plant under high and low
temperature environment using GC-MS technology and found a series of small
molecule metabolites related to high temperature and low temperature or both. The
metabolite changes associated with low temperature were the most significant, but to
our surprise, most of the metabolites produced under thermal stress would also be
produced under cold stress, among which many metabolites were not considered to be
related to the temperature stress in previous studies. In subsequent research work
([14]), these metabolic fingerprint data were integrated in order to study the adaptive
mechanism of Arabidopsis thaliana plants to low temperature. Results showed that
only part of the metabolites change were related to transcriptomics change, while the
rest of metabolites change was not directly related to transcriptomics change. It can be
concluded through the above research that in the process of plant response to cold
stress, the metabolites not directly related to transcriptomic changes played an
important role in temperature response of Arabidopsis thaliana plants.
Cook et al. (2004) [15] compared metabolic fingerprint of Arabidopsis thaliana
plants with different cold resistance abilities and excessive expression (CBF)
(C-repeat/dehydration responsive element-binding factor) using GC-MS technology.

Results showed that metabolism of Arabidopsis thaliana obviously changed in the
process of cold stress responses, and that CBF pathway played an important role in
the adaptation of low temperature environment in Arabidopsis.
Morsy et al. (2007) [16] studied the sugar metabolomics of cold stress and high salt
stress response for two genotypes rice with different cold resistance abilities. Using
8


HPLC method, the authors quantitatively analyzed the soluble saccharide compounds
of cold resistance and cold non-resistance rice, and found that accumulation of soluble
saccharide of the two genotypes rice under cold stress was different. For cold resistant
rice, galactose and raffinose accumulated under cold stress environment, while the
content of these two kinds of sugar showed a downward trend in the other genotype
rice. The two genotypes rice also showed different saccharide metabolism
characteristics under high salt stress environment.
(3) Salt stress
The adverse effect on plant caused by too many soluble salts in the soil is called
salt stress. Metabolomics technology was used to identify metabolites change of
tomato (Solanum lycopersicum) under salt stress. Johnson et al. (2003) [17] selected
two tomato strains with different salt sensitivity Edkawy and Simge F1 for research,
and found that the relative growth rate of Simge F1 under salt stress significantly
decreased, while that of Edkawy was not affected. Using Fourier transform infrared
spectrum (FT-IR), the fresh tomato fruit extracts from control group and salt stress
group were analyzed. The obtained data was processed by PCA and discriminant
function analysis (DFA), respectively. PCA method could not distinguish the fruit
difference between control group and high salt treatment group, while DFA method
could distinguish between two different genotypes and fruits of different genotypes in
control group and high salt treatment group. Genetic algorithm (GA) model was used
to identify possible important functional groups in FT-IR spectrugram for salt stress
response. These functional groups included saturated nitrile compounds, unsaturated

nitriles cyanide compounds and strong NH2 radicals peaks and other nitrogen
compounds, etc.

9


More detailed plant research in salt stress response was the time-course
metabolomics study by Kim et al. (2007) [18] at Arabidopsis thaliana cells in high salt
culture. The metabolic fingerprint metabolomics of Arabidopsis cells after treatment
by 100 mmol.L-1 NaCl for 0.5, 1, 2, 4, 12, 24, 48 and 72 h separately were determined
using LC-MS and GC-MS. The data was analyzed by PCA and self-organizing map.
Results showed that short-term metabolism change of plant cells in salt stress
response included induction of methylation cycle which provided methyl, induction of
hydroxyl methyl amine circulation which induced lignin synthesis, and 3-armour
amino acid synthesis; while long-term metabolism changes included influence on
glycolysis and sucrose metabolism, and co-reduction of methylation system.
Cramer et al. (2007) [19] compared the difference of grapevine (Vitis vinifera
‘Cabemet Sauvignon’) metabolites change between response to salt stress and drought
stress using GC-MS and anion exchange chromatography-ultraviolet detector method.
They found that in response to salt stress, the content of sugar, aspartic acid, succinic
acid and fumaric acid in plant declined, while the content of proline, asparagine, malic
acid and fructose etc. was relatively higher. Compared with response to salt stress, the
content of glucose, malic acid and proline was higher in response to drought stress.
Gong et al. (2005) [20] also compared metabolites difference between salt-tolerant
plants (Thellungiella halophila) and Arabidopsis thaliana by combination of GC-MS
metabolic fingerprint with biochip technology. They found obvious differences
between metabolites of the two species. Compared with Arabidopsis thaliana, salt
mustard maintained higher levels of metabolites whether in high salt environment or
general environment. Analysis of Arabidopsis thaliana showed that glucose, proline
and possible polysaccharide significantly increased in Arabidopsis thaliana plants

under 150 mmol.L-1 salt stress. While in salt mustard, salt stress induced fairly
10


complex metabolic response. Not only many metabolites levels were higher before
salt stress, but also the content of many sugars, sugar alcohol, organic acid and
phosphate after induction showed apparent change.
(4) Sulfur and phosphorus stress
In addition to the above abiotic stresses, plants are also subjected to other
environmental stresses, such as sulfur stress and phosphorus stress.
Recently, many studies involved metabolomics research of plants subjected to
sulfur, and phosphorus stress. Nikiforova et al. ([21, 22]) analyzed Arabidopsis
thaliana plants under sulfur stress using GC-MS and LC-MS techniques. They
detected 134 known compounds and a series of unknown compounds in Arabidopsis
thaliana related to sulfur stress, and made dynamic monitoring of these compounds,
thus successfully rebuilt metabolic network of sulfur stress response in Arabidopsis
thaliana. Then, metabolic network data was consolidated with transcriptomics data of
sulfur stress response in Arabidopsis thaliana, therefore the relationship between gene
expression and metabolite changes under sulfur stress was obtained.
The combination of Metabolomics and proteomics was also applied in the study of
leguminous plants under phosphorus stress. Hernandez et al. (2007) [23] made
metabolic profile analysis of roots of leguminous plant with sufficient phosphorus and
insufficient phosphorus using GC-TOF-MS, and identified a series of metabolic
products related to the phosphorus stress, many of which (including amino acids,
polyols and sugars) increased in content in response to phosphorus stress.
(5) Heavy metal stress
Several studies have investigated the metal stress responses in various plants. As a
frequent farmland contaminant, cadmium was intensively studied in regards to metal
11

toxicity in plants.
Bailey et al. [24] analyzed NMR Metabolomics of bottle wheat grass
(Silenecucubalus) cells under high cadmium stress. PCA analysis could distinguish
the cadmium stress group and blank group. They found that the content of malic acid
and acetic acid salt increased significantly in bottle wheat grass cells under cadmium
stresses, while the content of glutamic acid and some branched chain amino acids
showed a downward trend in cadmium stress response.
Kieffer et al. [25] conducted research of proteome combined with metabolic profile
analysis on Poplar (Poplar spp.) under cadmium stress. Results showed that levels of
pigment and carbohydrates of Poplar changed in response to cadmium stress. Under
cadmium stress, the poplar showed growth inhibition and photosynthesis was also
affected. In the process of growth and development, photosynthesis products stored in
the form of hexose or other complex carbohydrates in plants, thus adjusting osmotic
pressure.
Sun et al. [26] elucidated the metabolic responses of Arabidopsis thaliana to
different cadmium concentrations (0, 5, 50 µM) for 2 weeks using GC-MS analysis.
Results showed that levels of carbohydrates, organic acids, amino acids, and other
metabolites changed under cadmium stress. Levels of Ala, b-ala, Pro, Ser, putrescine,
Suc, 4-aminobutyric acid, glycerol, raffinose and trehalose increased in the treated
plants compared to control group. Concentrations of antioxidants such as
alfa-tocopherol, campesterol, beta-sitosterol and isoflavone also significantly
increased.
Hediji et al. [27] evaluated the long-term response of tomato plants to cadmium
exposure through 1H NMR, HPLC-PDA, and colorimetric methods. The plants were
12


cultured in hydroponic conditions (0, 20, and 100 µM CdCl2) for 90 days. Results
showed that tomato plants adapted to 20 µm Cd concentration during long-term

exposure and were perturbed physiologically leading to limited growth and fruit set
abortion.
Liu et al. [28] studied the metabolites response of halophyte (Suaeda salsa)
exposed to 2, 10 and 50 µg. L-1 cadmium concentration using NMR-based
Metabolomics. After cadmium exposures, the levels of amino acids, carbohydrates,
intermediates of tricarboxylic acid cycle and osmolyte changed in the samples,
indicating increased protein degradation and disturbances in the osmotic regulation
and energy metabolism.
Grid chara (Scenedesmus) plant is an important research object for study of metal
stress and phenolic expression. Dividing the genus plant S. quadricauda into 3 groups,
Jozef et al. [29] conducted Metabolomics research after treatment of them using Cu2+,
salicylic acid and combination of Cu2+ and salicylic acid, respectively. Results showed
that content of chlorophyll, soluble protein and phenolic compounds declined in the
Cu2+ treatment group; The alicylic acid treatment group showed opposite trend; In the
Cu2+ and salicylic acid treatment group, salicylic acid could not resist the downward
trend of the three kinds of compounds under Cu2+ stress. However, the concentration
of Cu2+ did not increased in plants body, possibly due to accumulation of benzoic acid
which was related to salicylic acid.
Brassica species plants have long been regarded as metal ion collector, and widely
used in the soil remediation, but the resistance mechanism for metal ions is unclear.
Jahangir et al. [30], studied the metabolites change of turnip (Brassica rapa)
subjected to metal ions stress. The turnip was exposed to three kinds of metal ions
13


(Cu2+, Fe3+ and Mn2+) with four different concentrations (50, 100, 250 and 500
mmol.L-1). The plants sample after treatment was detected by 1H NMR and 2D-NMR,
then the data was analyzed by PCA and partial least squares (PLS). Such primary
metabolites as gluconic acid and hydroxy acid conjugate salt compounds, some
carbohydrates and amino acids can be used to distinguish plants treated by different

kinds of metal ions. Results showed that the metabolites change of plants treated by
Cu2+ and Fe3+ was greater than those treated by Mn2+. Moreover, change of metabolic
products was not only related to the species of metal ions, but also associated with the
concentration of metal ions.

1.3 Heavy metal accumulation in Water Hyacinth
Water hyacinth (Eichhornia crassipes) is a perennial, floating aquatic plant with
rapid-growing capability. It is widely distributed in warm temperate, subtropical, and
tropical regions around the world. Various studies have shown that water hyacinth is
capable of adsorbing excessive heavy metals. Research by Misbahuddin and
Fariduddin [31] showed that 81% of As with 400 ppb concentration was removed by
the roots of living water hyacinth plants, and when stems and leaves of the water
hyacinth plant were involved, 100% As was removed in six hours. In Taiwan, Liao
and Chang [32] demonstrated that water hyacinth removed large amounts of lead,
copper, and zinc in a constructed wetland. The results by Soltan and Rashed [33]
showed that water hyacinth can survive in a mixture of heavy metal concentrations
(Cd, Co, Cr, Cu, Mn, Ni, Pb and Zn) up to 3 mg.L-1 and in 100 mg.L-1 Pb solution.
The uptake of metal ions from aqueous solutions by water hyacinth is a
deprotonation reaction explained by a decrease in pH. The mechanism was believed to
14


be founded on the chelation with carboxylic, amino acid and hydroxyl groups of
macrocyclic molecules, such as ionophores existed in the mitochondria of water
hyacinth. Haider et al. (1983) suggested that the uptake of chemicals by water
hyacinth might happen through the cell membrane via osmosis and diffusion. Field
studies by Ajmal et al. [34] and Zaranyika and Ndapwadza [35] had shown that
metals accumulated in the leaves and roots of water hyacinth. Cooly and Martin [36]
found that Cu and Cd accumulated more in roots than least and petioles in leaves.
Kelley et al. [37] explained that carboxylic acids were responsible for chelating the

intracellular proportion of Eu(III) in the roots. According to the study by Malik [38],
almost all heavy metal ions accumulated in the roots rather than in the shoot system of
water hyacinth. An exceptional research carried out by Zhu et al. [39] suggested that
the metal Se was transported to the upper biomass of water hyacinth. Metal
accumulation was found in the sequence of roots > stems > leaves of water hyacinth,
and there was a linear correlation between the external metal concentration and
internal metal concentration [40] for Cr, Cu, Ni, and As [41]. It was suggested that the
capability of water hyacinth in storing most heavy metals enabled the plant to avoid
toxicity of photosynthetic tissues caused by heavy metals.

1.4 Basis and significance of dissertation
Modern industries have released large amounts of heavy metals into the
environment. Among various technologies for heavy metal removal, such as
adsorption, reverse osmosis and electrochemical method etc., phytoremediation has
been regarded as a promising method due to its low cost. Water hyacinth has the
capacity of adsorbing heavy metal during growth, thus is a promising plant for
phytoremediation. Although numerous researches had been done on mechanism of
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heavy metal adsorption by water hyacinth, these studies all focused on reaction in
parts of the plant such as roots [33], or certain features of the plant, such as
reflectance [42], the complete metabolism response when water hyacinth is subjected
to heavy metal stress is unknown. The application of metabolomics method on water
hyacinth in response to heavy metal stress may provide incentive on the metabolites
pathway of the water hyacinth for heavy metal adsorption from the perspective of the
whole plant, thus building an solid scientific foundation for better application of water
hyacinth in the phytoremediation.
Previously, few studies on plant metabolomics in response to heavy metal stress
involved comparison of metabolites change of different parts of plants. This point

deserved research as different parts of plant may play different roles in the metabolites
change, subdivision of their functions could help us understand plant response to
heavy metal stress as a whole. Moreover, previous studies on plant metabolomics
mostly described metabolites response to only one kind of stress, such as drought
stress, metal stress or salt stress. Few studies involved metabolites response to two or
more kinds of stress. The comparison between metabolites responses to different
stresses may be significant, as it may help us better understand each stress response of
the same plant, so as to understand those shared responses and stress-specific
responses of the same plant.
In this article, the water hyacinth plants were exposed to CuCl2, FeCl3 and
Na2HPO4 solutions. Then we analyzed the metabolites change and differences of roots,
stems and leaves of the plants using GC-MS method and PCA analysis. The
metabolism pathways of water hyacinth in response to different heavy metal stress
were proposed.

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