Transcript Document

Genetic Response of Plants Exposed to Anti-Inf luenza Drugs
Rashid Kaveh*, Benoit Van Aken
Temple University
College of Engineering
Department of Civil and Environmental Engineering, Temple University, Philadelphia, PA
*[email protected]
Background
Results
A
B in d in g
C a t a ly t ic
Biomass and physiological effect:
O S P U p - r e g u la t e d
M o le c u la r t r a n s d u c e r
Fig. 2. A. thaliana fresh weight
after exposure to OSP and ZAN
for three weeks. OSP samples
are correlated with the applied
concentrations.
100
*
*
50
/L
0
B
20
40
60
C a t a ly t ic
T r a n s c r ip t io n f a c t o r
0
T ra n s p o rte r
1
2
N
N
M o le c u la r t r a n s d u c e r
A
A
Z
A n t io x id a n t
m
0
m
0
m
5
N
A
Z
R e c e p to r
S t r u c t u r a l m o le c u le
g
/L
g
/L
g
/L
g
m
0
1
P
Z
S
O
O
O
S
S
P
P
2
0
0
5
m
m
g
g
/L
/L
l
o
tr
n
o
C
To understand the potential physiological and transcriptional
responses of the model plant Arabidopsis thaliana (A. thaliana)
to different contamination levels of the antiviral drugs, OSP and
ZAN using whole genome expression microarray.
O S P D o w n - r e g u la t e d
T r a n s c r ip t io n f a c t o r
0
Objectives
T ra n s p o rte r
150
B io m a s s ( m g )
The anti-influenza drugs, oseltamivir phosphate (OSP) and
zanamivir (ZAN), are major medications currently used for the
treatment of influenza. These drugs have been detected in
municipal wastewater and water catchments. They are likely to
contaminate agricultural plants through irrigation with
reclamation water and/or land application of biosolids.
However, little is known about the effects of antiviral drugs on
plants at the molecular level.
Z A N U p -r e g u la te d
E n z y m e r e g u la t o r
Genetic response:
Z A N D o w n - r e g u la t e d
A n t io x id a n t
R e c e p to r
OSP
ZAN
ZAN
OSP
E le c t r o n c a r r ie r
0
20
40
60
G e n e s p e r C a te g o r y (% )
Methods
Fig. 5. Major gene ontology (GO) function categories
Toxicity testing:
A. thaliana was planted on gel medium in vented Magenta
boxes under sterile conditions. The gel contained 0, 5, 20, and
100 mg/L on OSP and ZAN, separately. Exposure length was
three weeks with incubation under 16 h/day fluorescent light.
a)
b)
c)
Fig. 1. Exposure to a) No drugs, b) OSP 20 mg/L, c) ZAN 20 mg/L.
Molecular techniques:
A. thaliana plants exposed to 20 mg/L OSP and ZAN were
chosen for transcriptional analysis. Plants were kept is
RNAlater storage solution. RNA was extracted using TRIzol®
Plus RNA Purification kit. RNA transcription to cDNA. RNA
validity testing by RT-qPCR. Microarray analysis performed
using Affimetrix Arabidopsis Gene 1.0 ST Array.
Genomic data analysis:
Data normalization by Affymetrix Gene Expression Console
with Robust Multi-Array Average normalization algorithm
BRB-ArrayTools package for statistical analysis and gene
ontology analysis, BLAST2GO®online data bases were used.
Genes up-regulated (>2)
Genes down-regulated (<0.5)
Fig. 3. Number of genes significantly up-and down-regulated by
exposure to the antiviral drugs
A
M e t a b o lic
S in g le - o r g a n is m
R e s p o n s e t o s t im u lu s
C e llu la r
D e v e lo p m e n t a l
M u lt ic e llu la r o r g a n is m a l
B io lo g ic a l r e g u la t io n
C e llu la r o r g a n iz a t io n
L o c a liz a t io n
R h y t h m ic p r o c e s s
S ig n a lin g
R e p r o d u c t io n
G ro w th
M u lt i- o r g a n is m
Im m u n e s y s t e m
O S P U p - r e g u la t e d
O S P D o w n - r e g u la t e d
0
5
10
15
20
Conclusion
Transcriptional analysis showed changes in genes expression
that may reflect oxidative stress in exposed plants. The
enzymatic functions and processes may lead to the drugs
detoxification in the plant tissue this may help phytoremediation
technologies to decrease the concentration of the drugs in the
environment.
Whole genome expression analysis may be useful for the
detection of chronic toxicity of emerging contaminants on
plants, even when short-term exposure does not result in
observable physiological effects.
B
C e llu la r
S in g le - o r g a n is m
M e t a b o lic p r o c e s s
R e s p o n s e t o s t im u lu s
B io lo g ic a l r e g u la t io n
D e v e lo p m e n t a l
M u lt ic e llu la r o r g a n is m a l
L o c a liz a t io n
C e llu la r o r g a n iz a t io n
G ro w th
M u lt i- o r g a n is m
S ig n a lin g
R e p r o d u c t io n
R h y t h m ic
Im m u n e s y s t e m
References
Z A N U p -r e g u la te d
Z A N D o w n - r e g u la t e d
0
5
10
15
20
G e n e s p e r C a te g o r y (% )
Fig. 4. Major gene ontology (GO) process categories
Hruz, T. et al. (2008). Genevestigator V3: a reference expression database
for the meta-analysis of transcriptomes. Advances in Bioinformatics, 5
pages.
Kaveh, R. et al. (2013). Changes in Arabidopsis thaliana Gene Expression
in Response to Silver Nanoparticles and Silver Ions. Environmental
Science and Technology, 10637-10644.
Acknowledgement: Dr. Yuesheng Li, Genomic facility, Fox Chase
Cancer Center, Philadelphia.