DocumentCode :
2774736
Title :
Modeling Arsenic Accumulation in Plants
Author :
Mandal, Abul ; Lundh, Dan ; Nahar, Noor ; Bentol, Hoda ; Bari, Abdul ; Johnson-Brousseau, Sheila ; Ghosh, Sibdas
Author_Institution :
Syst. Biol. Res. Center, Univ. of Skvode, Högskolevägen, Sweden
fYear :
2011
fDate :
19-20 Feb. 2011
Firstpage :
133
Lastpage :
137
Abstract :
Rice growing regions plagued by arsenic-contaminated soils and irrigation water do not have a viable option for producing arsenic-free crops. For instance, in Bangladesh every year more than 30 million people are affected from rice-derived arsenic contamination that contributes to arsenic levels known to cause health-related illnesses. Our strategy is to genetically-modify molecular mechanisms involved in the localization of arsenic to divert it to the non-edible parts of the plant. To identify viable candidate genes, we employed data mining, an in silico analysis based on searching existing genomic databases and in the genetic model plant Arabidopsis thaliana. To assist our investigation, we constructed a kinetic model to outline strategies for developing genetically-modified plants exhibiting a significant reduction in arsenic concentration in the edible parts (straw and grain). This model contains equations for uptake, metabolism and sequestration of different types of arsenic (As (V), As (III,) MMAA and DMAA). The model was implemented using XPP and validated against existing data from the literature. From these analyses, we identified four candidate genes that are involved either in uptake, transport or cellular localization of arsenic in plants. But we found only one gene implicated in arsenic metabolism in rice. In parallel, we identified available T-DNA insertion mutants to determine the effects of these genes on arsenic accumulation. Results obtained from in silico data-mining, kinetic modeling, and assays with T-DNA insertion mutants will be used to design gene cloning experiments to study the target genes in yeast, E. coli, and Arabidopsis heterologous systems. Upon confirmation of the effectiveness of these candidates, vectors containing the target genes will be constructed for transformation into rice. The new rice varieties produced will be tested under field conditions to assess their effectiveness at reducing or eliminating arsenic from the edible p- rts of the rice plant.
Keywords :
agriculture; arsenic; crops; data mining; health and safety; Arabidopsis thaliana genetic model plant; As; Bangladesh; arsenic accumulation modeling; arsenic-free crops; data mining; genomic databases; molecular mechanism modification; plant grain; plant straw; rice plant; rice variety; rice-derived arsenic contamination; Biochemistry; Equations; Kinetic theory; Mathematical model; Metals; Soil; Systems biology; arsenic accumulation; arsenic metabolism; arsenic uptake; data-mining; rice;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Emerging Applications of Information Technology (EAIT), 2011 Second International Conference on
Conference_Location :
Kolkata
Print_ISBN :
978-1-4244-9683-9
Type :
conf
DOI :
10.1109/EAIT.2011.91
Filename :
5734934
Link To Document :
بازگشت