PhD student, Indian Institute of Technology Madras (IIT Madras)


Increasing Vitamin-E content in plants by metabolic engineering and process optimization strategies


Plants are natural producers of several medicinally important high-value compounds (eg: Antimalarial drug Artemesinin). They can be grown in lab as uniform cells/tissues mimicking attributes of whole plants at a large scale in limited space under controlled conditions. This is called as plant tissue culture. We can make them produce high quantity of desired/known/novel compounds by tinkering their metabolic pathways that produce the compound and/or by optimizing process conditions (nutrient composition for their growth, environment parameters such as temperature etc.).

My Aim

Develop strategies to enhance Vitamin E content of plant cells using sunflower as a model system.

Why Vitamin E?

It is an essential(not produced in human body) dietary component of humans, the deficiency of which leads to diseases, It is sold as Vitamin E supplements. It is also used widely in cosmetics as it helps to prevent tissue damage from oxidative stress and in animal feed additives.

Why plant cells?

Chemical synthesis yields a less active than natural form of Vitamin E produced by plants. Green plants especially oilseeds are rich source of vitamin E. In particular, sunflower produces more of the active component of Vitamin E, namely alpha-tocopherol. Sunflower cells are also amenable to process optimization, vitamin E pathway engineering studies and scale-up to larger volumes

What tools do i employ?

Firstly, i use the sunflower genome (represents the genetic material) information to employ computational tools to identify gene targets - a rational genome scale modeling based approach instead of random hit and trial method for enhancing vitamin-E content. This is followed by it's experimental verification in lab which results in high vitamin E producing "metabolically engineered" sunflower cells. I use statistical bioprocess optimization studies in small volumes to further enhance the yield of Vitamin E in these cells. I finally use the optimized process for scaling up to larger volumes in bioreactors.

Future scope

This technique can be applied to further enhance other high value byproducts/compounds that make sunflower a better candidate for biofuel production/biofortification of sunflower crops


Enhanced production of nargenicin A1 and creation of a novel derivative using a synthetic biology platform.

Abstract: Nargenicin A1, an antibacterial produced by Nocardia sp. CS682 (KCTC 11297BP), demonstrates effective activity against various Gram-positive bacteria. Hence, we attempted to enhance nargenicin A1 production by utilizing the cumulative effect of synthetic biology, metabolic engineering and statistical media optimization strategies. To facilitate the modular assembly of multiple genes for genetic engineering in Nocardia sp. CS682, we constructed a set of multi-monocistronic vectors, pNV18L1 and pNV18L2 containing hybrid promoter (derived from ermE* and promoter region of neo (r) ), ribosome binding sites (RBS), and restriction sites for cloning, so that each cloned gene was under its own promoter and RBS. The multi-monocistronic vector, pNV18L2 containing transcriptional terminator showed better efficiency in reporter gene assay. Thus, multiple genes involved in the biogenesis of pyrrole moiety (ngnN2, ngnN3, ngnN4, and ngnN5 from Nocardia sp. CS682), glucose utilization (glf and glk from Zymomonas mobilis), and malonyl-CoA synthesis (accA2 and accBE from Streptomyces coelicolor A3 (2)), were cloned in pNV18L2. Further statistical optimization of specific precursors (proline and glucose) and their feeding time led to ~84.9 mg/L nargenicin from Nocardia sp. GAP, which is ~24-fold higher than Nocardia sp. CS682 (without feeding). Furthermore, pikC from Streptomyces venezuelae was expressed to generate Nocardia sp. PikC. Nargenicin A1 acid was characterized as novel derivative of nargenicin A1 produced from Nocardia sp. PikC by mass spectrometry (MS) and nuclear magnetic resonance (NMR) analyses. We also performed comparative analysis of the anticancer and antibacterial activities of nargenicin A1 and nargenicin A1 acid, which showed a reduction in antibacterial potential for nargenicin A1 acid. Thus, the development of an efficient synthetic biological platform provided new avenues for enhancing or structurally diversifying nargenicin A1 by means of pathway designing and engineering.

Pub.: 15 Jul '16, Pinned: 01 Sep '17

Critical assessment of genome-scale metabolic networks: the need for a unified standard.

Abstract: Genome-scale metabolic networks have been reconstructed for several organisms. These metabolic networks provide detailed information about the metabolism inside the cells, coupled with the genomic, proteomic and thermodynamic information. These networks are widely simulated using 'constraint-based' modelling techniques and find applications ranging from strain improvement for metabolic engineering to prediction of drug targets in pathogenic organisms. Components of these metabolic networks are represented in multiple file formats and also using different markup languages, with varying levels of annotations; this leads to inconsistencies and increases the complexities in comparing and analysing reconstructions on multiple platforms. In this work, we critically examine nearly 100 published genome-scale metabolic networks and their corresponding constraint-based models and discuss various issues with respect to model quality. One of the major concerns is the lack of annotations using standard identifiers that can uniquely describe several components such as metabolites, genes, proteins and reactions. We also find that many models do not have complete information regarding constraints on reactions fluxes and objective functions for carrying out simulations. Overall, our analysis highlights the need for a widely acceptable standard for representing constraint-based models. A rigorous standard can help in streamlining the process of reconstruction and improve the quality of reconstructed metabolic models.

Pub.: 01 Mar '15, Pinned: 01 Sep '17

Effect of elicitors and precursors on azadirachtin production in hairy root culture of Azadirachta indica.

Abstract: The present study involved strategies for enhancement in in vitro azadirachtin (commercially used biopesticide) production by hairy root cultivation of Azadirachta indica. Improvement in the azadirachtin production via triggering its biosynthetic pathway in plant cells was carried out by the exogenous addition of precursors and elicitors in the growth medium. Among the different abiotic stress inducers (Ag(+), Hg(+2), Co(+2), Cu(+2)) and signal molecules (methyl jasmonate and salicylic acid) tested, salicylic acid at 15 mg l(-1) of concentration was found to enhance the azadirachtin yield in the hairy roots to the maximum (up to 4.95 mg g(-1)). Similarly, among the different biotic elicitors tested (filter-sterilized fungal culture filtrates of Phoma herbarium, Alternaria alternata, Myrothecium sp., Fusarium solani, Curvularia lunata, and Sclerotium rolfsii; yeast extract; and yeast extract carbohydrate fraction), addition of filter-sterilized fungal culture filtrate of C. lunata (1 % v/v) resulted in maximum azadirachtin yield enhancement in hairy root biomass (up to 7.1 mg g(-1)) with respect to the control (3.3 mg g(-1)). Among all the biosynthetic precursors studied (sodium acetate, cholesterol, squalene, isopentynyl pyrophosphate, mavalonic acid lactone, and geranyl pyrophosphate), the overall azadirachtin production (70.42 mg l(-1) in 25 days) was found to be the highest with cholesterol (50 mg l(-1)) addition as an indirect precursor in the medium.

Pub.: 21 Dec '13, Pinned: 01 Sep '17

Reconstruction of Arabidopsis metabolic network models accounting for subcellular compartmentalization and tissue-specificity.

Abstract: Plant metabolic engineering is commonly used in the production of functional foods and quality trait improvement. However, to date, computational model-based approaches have only been scarcely used in this important endeavor, in marked contrast to their prominent success in microbial metabolic engineering. In this study we present a computational pipeline for the reconstruction of fully compartmentalized tissue-specific models of Arabidopsis thaliana on a genome scale. This reconstruction involves automatic extraction of known biochemical reactions in Arabidopsis for both primary and secondary metabolism, automatic gap-filling, and the implementation of methods for determining subcellular localization and tissue assignment of enzymes. The reconstructed tissue models are amenable for constraint-based modeling analysis, and significantly extend upon previous model reconstructions. A set of computational validations (i.e., cross-validation tests, simulations of known metabolic functionalities) and experimental validations (comparison with experimental metabolomics datasets under various compartments and tissues) strongly testify to the predictive ability of the models. The utility of the derived models was demonstrated in the prediction of measured fluxes in metabolically engineered seed strains and the design of genetic manipulations that are expected to increase vitamin E content, a significant nutrient for human health. Overall, the reconstructed tissue models are expected to lay down the foundations for computational-based rational design of plant metabolic engineering. The reconstructed compartmentalized Arabidopsis tissue models are MIRIAM-compliant and are available upon request.

Pub.: 21 Dec '11, Pinned: 31 Aug '17

Statistical medium optimization for enhanced azadirachtin production in hairy root culture of Azadirachta indica

Abstract: Azadirachtin, a well-known biopesticide, is a secondary metabolite extracted from the seeds of Azadirachta indica. In the present study, azadirachtin was produced in hairy roots of A. indica, generated by Agrobacterium rhizogenes-mediated transformation of leaf explants. Liquid cultures of A. indica hairy roots were developed with a liquid-to-flask volume ratio of 0.15. The kinetics of growth and azadirachtin production were established in a basal plant growth medium containing MS medium major and minor salts, Gamborg’s medium vitamins, and 30 g l−1 sucrose. The highest azadirachtin accumulation in the hairy roots (up to 3.3 mg g−1) and azadirachtin production (∼44 mg l−1) was obtained on Day 25 of the growth cycle, with a biomass production of 13.3 g l−1 dry weight. To enhance the production of azadirachtin, a Plackett–Burman experimental design protocol was used to identify key medium nutrients and concentrations to support high root biomass production and azadirachtin accumulation in hairy roots. The optimal nutrients and concentrations were as follows: 40 g l−1 sucrose, 0.19 g l−1 potassium dihydrogen phosphate, 3.1 g l−1 potassium nitrate, and 0.41 g l−1 magnesium sulfate. Concentrations were determined by a central composite design protocol and verified in shake-flask cultivation. The optimized medium composition yielded a root biomass production of 14.2 g l−1 and azadirachtin accumulation of 5.2 mg g−1, which was equivalent to an overall azadirachtin production of 73.84 mg l−1, 68% more than that obtained under non-optimized conditions.

Pub.: 10 Sep '11, Pinned: 01 Sep '17

Tocopherol production in plant cell cultures.

Abstract: Tocopherols, collectively known as vitamin E, are lipophilic antioxidants, essential dietary components for mammals and exclusively synthesized by photosynthetic organisms. Of the four forms (alpha, beta, gamma and delta), alpha-tocopherol is the major vitamin E form present in green plant tissues, and has the highest vitamin E activity. Synthetic alpha-tocopherol, being a racemic mixture of eight different stereoisomers, always results less effective than the natural form (R,R,R) alpha-tocopherol. This raises interest in obtaining this molecule from natural sources, such as plant cell cultures. Plant cell and tissue cultures are able to produce and accumulate valuable metabolites that can be used as food additives, nutraceuticals and pharmaceuticals. Sunflower cell cultures, growing under heterotrophic conditions, were exploited to establish a suitable in vitro production system of natural alpha-tocopherol. Optimization of culture conditions, precursor feeding and elicitor application were used to improve the tocopherol yields of these cultures. Furthermore, these cell cultures were useful to investigate the relationship between alpha-tocopherol biosynthesis and photomixotrophic culture conditions, revealing the possibility to enhance tocopherol production by favouring sunflower cell photosynthetic properties. The modulation of alpha-tocopherol levels in plant cell cultures can provide useful hints for a regulatory impact on tocopherol metabolism.

Pub.: 19 Feb '10, Pinned: 31 Aug '17

Subcellular flux analysis of central metabolism in a heterotrophic Arabidopsis cell suspension using steady-state stable isotope labeling.

Abstract: The presence of cytosolic and plastidic pathways of carbohydrate oxidation is a characteristic feature of plant cell metabolism. Ideally, steady-state metabolic flux analysis, an emerging tool for creating flux maps of heterotrophic plant metabolism, would capture this feature of the metabolic phenotype, but the extent to which this can be achieved is uncertain. To address this question, fluxes through the pathways of central metabolism in a heterotrophic Arabidopsis (Arabidopsis thaliana) cell suspension culture were deduced from the redistribution of label in steady-state (13)C-labeling experiments using [1-(13)C]-, [2-(13)C]-, and [U-(13)C(6)]glucose. Focusing on the pentose phosphate pathway (PPP), multiple data sets were fitted simultaneously to models in which the subcellular compartmentation of the PPP was altered. The observed redistribution of the label could be explained by any one of three models of the subcellular compartmentation of the oxidative PPP, but other biochemical evidence favored the model in which the oxidative steps of the PPP were duplicated in the cytosol and plastids, with flux through these reactions occurring largely in the cytosol. The analysis emphasizes the inherent difficulty of analyzing the PPP without predefining the extent of its compartmentation and the importance of obtaining high-quality data that report directly on specific subcellular processes. The Arabidopsis flux map also shows that the potential ATP yield of respiration in heterotrophic plant cells can greatly exceed the direct metabolic requirements for biosynthesis, highlighting the need for caution when predicting flux through metabolic networks using assumptions based on the energetics of resource utilization.

Pub.: 27 Nov '09, Pinned: 01 Sep '17

Flux balance analysis of biological systems: applications and challenges.

Abstract: Systems level modelling and simulations of biological processes are proving to be invaluable in obtaining a quantitative and dynamic perspective of various aspects of cellular function. In particular, constraint-based analyses of metabolic networks have gained considerable popularity for simulating cellular metabolism, of which flux balance analysis (FBA), is most widely used. Unlike mechanistic simulations that depend on accurate kinetic data, which are scarcely available, FBA is based on the principle of conservation of mass in a network, which utilizes the stoichiometric matrix and a biologically relevant objective function to identify optimal reaction flux distributions. FBA has been used to analyse genome-scale reconstructions of several organisms; it has also been used to analyse the effect of perturbations, such as gene deletions or drug inhibitions in silico. This article reviews the usefulness of FBA as a tool for gaining biological insights, advances in methodology enabling integration of regulatory information and thermodynamic constraints, and finally addresses the challenges that lie ahead. Various use scenarios and biological insights obtained from FBA, and applications in fields such metabolic engineering and drug target identification, are also discussed. Genome-scale constraint-based models have an immense potential for building and testing hypotheses, as well as to guide experimentation.

Pub.: 17 Mar '09, Pinned: 01 Sep '17