Aug
11
Sun
2013
Cultural Events @ Amriteshwari Hall
Aug 11 @ 6:30 pm – 7:30 pm
Aug
12
Mon
2013
Introducing the Track, Biopropsecting and Bioengineering @ Sathyam Hall
Aug 12 @ 9:15 am – 9:20 am

banerjiProf. Asoke Banerji
Distinguished Professor, School of Biotechnology, Amrita University

 

Plenary Talk: Advances in the Development of Plant Molecular Foundries @ Sathyam Hall
Aug 12 @ 9:20 am – 9:55 am

karenKaren A. McDonald, Ph.D.
Associate Dean for Research & Graduate Studies, University of California at Davis


Advances in the Development of Plant Molecular Foundries

Plants are a vast renewable source of important natural products, and the development of genetic engineering approaches has opened up a myriad of new possibilities for extending the biosynthetic capabilities of plants by enabling the production of heterologous proteins and new metabolic pathways in whole plants, plant tissues and in-vitro systems such as plant cell cultures in bioreactors.  Although plant biotechnology has been deployed commercially for decades for improved agronomic traits of crops, the combination of new expression technologies and synthetic biology building blocks for plants, rapid and inexpensive DNA synthesis, and novel bioprocessing strategies are enabling plants and/or plant cells to be used as molecular foundries to solve some of our most important societal problems in health and energy in an environmentally-friendly way.  For example, new production platforms based on transient expression in nontransgenic plants within contained manufacturing facilities are showing enormous promise for rapid, scalable production of recombinant proteins, without the need to deploy transgenic plants and eliminating many of the environmental concerns. A soil bacterium, Agrobacterium tumefaciens, that has an inherent capability of interkingdom DNA transfer, is used to introduce the genetic instructions into plant cells.  Plant cells within the plant tissues then provide the biosynthetic machinery for transcription, translation, post-translational modifications, folding and intracellular targeting/secretion of the product.  Thus the approach combines the advantages of rapid, easy and inexpensive growth of bacteria in fermentation systems with the biosynthetic capabilities of higher eukaryotic cells which have been grown using minimal energy and resource inputs (using sunlight and natural resources).  Transgenic plant cell cultures grown in bioreactors provide an alternative approach that is also attractive, particularly for production of human and veterinary therapeutics   Biotechnology and bioprocessing engineering approaches for enhancing recombinant protein production using transient agroinfiltration and transgenic plant cell cultures will be presented with applications to human therapeutics, vaccines, and industrial enzymes.

Invited Talk: Discovery, engineering and applications of Blue Fish Protein with Red Flourescence @ Sathyam Hall
Aug 12 @ 10:00 am – 10:15 am

RamaswamyS. Ramaswamy, Ph.D.
CEO of c-CAMP, Dean, inStem, NCBS, Bangalore, India


Discovery, engineering and applications of Blue Fish Protein with Red Fluorescence

Swagatha Ghosh, Chi-Li Yu, Daniel Ferraro,  Sai Sudha, Wayne Schaefer, David T Gibson and S. Ramaswamy

Fluorescent proteins and their applications have revolutionized our understanding of biology significantly.  In spite of several years since the discovery of the classic GFP, proteins of this class are used as the standard flag bearers.  We have recently discovered a protein from the fish Sanders vitrius that shows interesting fluorescent properties – including a 280 nm stoke shift and infrared emission.  The crystal structure of the wild type protein shows that it is a tetramer.  We have engineered mutations to make a monomer with very similar fluorescent properties. We have used this protein for tissue imaging as well as for in cell-fluorescence successfully

Ramaswamy (1) Ramaswamy (2) Ramaswamy (3) Ramaswamy (4)

Invited Talk : Preclinical Outsourcing to India @ Sathyam Hall
Aug 12 @ 10:35 am – 11:00 am

ganeshGanesh Sambasivam, Ph.D.
CSO & Co-Founder, Anthem Biosciences India


Preclinical Outsourcing to India

The outsourcing segment is witnessing rapid changes with respect to the nature of work outsourced and the location. Cost is the major driver but other considerations such as infrastructure and government policies can also be important drivers for decision making. The last couple of years have been a trying time for all CROs. The global economic meltdown has hit research budgets especially hard. The new challenges facing Contract Research Organizations call for a radically revised approach and a new model that would push the boundaries of this business further and would blur the line between client and vendor further. I believe the term Contract Research Organization (CRO), is a misnomer to begin with (often confused with Clinical Research Organization), has now morphed into a new type of company viz Contract Innovation Services (CIS). Clients are no longer just happy to outsource odds and ends of the development piece but are looking to their vendors for a massive amount of innovation input. This input is increasingly across both the chemistry and discovery domains. This new paradigm calls for CIS companies to develop new platforms, create intellectual propertythat is of service to clients andinnovate processes to meet new found customer expectations.

Invited Talk: Screening flavonoids for NF-kB inhibitory effect as potential breast cancer therapy @ Sathyam Hall
Aug 12 @ 11:00 am – 11:20 am

ayyappanAyyappan Nair, Ph.D.
Head, Business Development (Technologies, Discovery Biology), Anthem Biosciences & DavosPharma, New Jersey, USA


Inhibition of NF-κB regulated gene expression by chrysoeriol suppresses tumorigenesis in breast cancer cells

Amrutha K1, Pandurangan Nanjan1, Sanu K Shaji1, Damu Sunilkumar1, Subhalakshmi K1, Rashmi U Nair1, Lakshmi Rajakrishna2, Asoke Banerji1, Ayyappan Ramesh Nair1*,2

  1. School of Biotechnology, Amrita Vishwa Vidyapeetham, Amritapuri Campus, Clappana P.O., Kollam – 690 525, Kerala, India
  2. Anthem Biosciences, No 49, Canara Bank Road, Bommasandra Industrial Area, Phase 1,  Hosur Road, Bangalore – 560 099, Karnataka, India

Abstract:  A large number of effective cancer-preventing compounds inhibit the activation of nuclear factor-κ B (NF-κB).  It has been previously demonstrated that some flavonoids that are a vital component of our diet inhibits this pathway. As a consequence, many flavonoids inhibit genes involved in various aspects of tumorigenesis and have thus emerged as potential chemopreventive candidates for cancer treatment. We studied the effect of 17 different flavonoids, including the highly evaluated quercetin on the NF-κB pathway, and on the expression of MMP-9 and COX-2 (two NF-κB regulated genes involved in metastasis) in the highly invasive human breast cancer cell line MDA-MB-231.  The findings suggest that not all the quercetin like flavone backbone compounds inhibit the NF-κB pathway, and that the highly hydoxylated flavonols quercetagetin and gossypetin did not inhibit this pathway, nor did it inhibit the expression of MMP-9 and COX-2.  This indicates a correlation between inhibition of NF-κB and subsequent suppression of these NF-κB regulated genes. Here, we also report the novel observation that the not so well characterized methoxylated flavone chrysoeriol inhibited the NF-κB pathway, and was most potent in reducing the expression of MMP-9 and COX-2.  Based on these observations, the cellular effects of chrysoeriol were evaluated in MDA-MB-231.  Chrysoeriol caused cell cycle arrest at G2/M, inhibited migration and invasion, and caused cell death of macrophages that contributed to migration of these cancer cells.  These effects of chrysoeriol make it a potential therapeutic candidate for breast cancer metastasis.

Ayyappan

 

Invited Talk: Alternative renewable resources: Issues and perspectives for India – the case of transport fuels @ Sathyam Hall
Aug 12 @ 11:25 am – 11:45 am

ashokAshok Pandey, Ph.D.
Scientist F & Head, Biotechnology Division, National Institute for Interdisciplinary Science and Technology-CSIR), Thiruvananthapuram, India


Alternative renewable resources: Issues and perspectives for India – the case of transport fuels

With the increase in the urbanization way of life and also more and more dependence on materialistic life, there is substantial growing demand for the energy. The science and technological policy of the India has looked several avenues to fulfill this demand through alternative resources such as solar energy, wind energy, tidal energy, bioenergy, etc. The demand for the transport sector is largely met through the import (~70%). Biofuels, in particular bioethanol from lignocellulosic biomass offer attractive possibilities in this regard.

The sugar platform which generates ethanol is considered to be the most valuable solution to the transport fuel demand. Bioethanol can be generated from grains as well as from lignocellulosic plant material by their saccharification to sugars and subsequent fermentation of the sugars to produce ethanol. Bio-ethanol as a transportation fuel is attractive since it is more energy efficient than gasoline and produces less emissions.  The benefits of developing biomass to ethanol technology(s) include: increased national energy security, reduction in GHG emissions, use of renewable resources, economic benefits and creation of employment and the foundation of a carbohydrate based chemical industry. However, the utilization of lignocellulosic biomass for fuel generation has not been given the sort of attention it ought to receive. It is known that the technology for ethanol production from biomass has to evolve greatly for an economical commercial scale utilization of the renewable biomass resources. Biomass requires extensive processing involving multiple steps for hydrolysis and fermentation of the raw material for producing ethanol. Feed stock availability, pretreatment, saccharification, fermentation and ethanol recovery are all factors which influence the production of ethanol and which needs R&D efforts for overall improvement of the production economics.

Bioconversion of lignocellulosic biomass (LB) can contribute significantly to the production of organic chemicals also. LB is also considered to be the only foreseeable source of energy. LB is mainly composed of (dry wt basis): cellulose, 40-60; hemicellulose, 20-40; and lignin, 10-25%. Most efficient method of biomass hydrolysis is through enzymatic saccharification5 using cellulases and hemicellulases. Fungal cellulases (FCs) have proved to be a better candidate than other microbial cellulases, with their secreted free cellulase complexes comprising all three components of cellulase [endoglucanases, exoglucanases and cellobiases (glucosidases).

The Centre for Biofuels at NIIST, Trivandrum, India aims ultimately to develop technologies and processes which will address the nation’s need for making fuel ethanol from the renewable resource: biomass.  It is proposed to direct R&D activities at the major requirements of a biomass-ethanol technology, which include production of cellulases, hydrolysis of biomass, and ethanol fermentation.   Viable technologies for each of these processes will contribute to the overall process development for fuel alcohol production from cheap and renewable biomass resources.

The lecture would present perspectives on bioethanol from lignocellulosic feedstocks.

References

  1. Biofuels- Alternative Feedstocks and Conversion Processes, Editors-  Ashok Pandey, C Larroche, SC Ricke, CG Dussap & E Gnansounou, Academic Press, Elsevier Inc; San Diego, USA, p629 (2011) ISBN: 978-0-12-385099-7
  2. Handbook of Plant-Based Biofuels, Editor- Ashok Pandey, CRC Press, Francis & Taylors, Boca Raton, USA, p 297 (2008) ISBN 978-q-5602-2175-3
  3. Biofuels II, Special issue of Journal of Scientific & Industrial Research, Guest Editors- E Gnansounou, C Larroche and Ashok Pandey, 67(11), 837-1040 (2008) ISSN: 0022-4456
  4. Biofuels, Special issue of Journal of Scientific & Industrial Research, Guest Editors- C Larroche and Ashok Pandey, 64(11), 797-988 (2005) ISSN: 0022-4456

Ashok Pandey

Invited Talk: Strategies for Diseases/Target Selection for Drug Discovery and a Multi-Targeted Approach to Metabolic Disorder @ Sathyam Hall
Aug 12 @ 11:45 am – 12:10 pm

PradipPradip K. Bhatnagar, Ph.D.
Former President & Head, Daiichi Sankyo Life Science Research Centre, India


Strategies for Diseases/Target Selection for Drug Discovery and a Multi-Targeted Approach to Metabolic Disorder

Drug discovery and development is a high risk and expensive undertaking.  Although, technologies, such as, bioinformatics, genomics, high throughput screening and computer-aided design have helped identify targets, biomarkers, lead candidates and reduced the time required for  advancing an idea from  bench to clinic, but it still takes 10-12 years and costs approximately one billion dollars to bring a drug to market globally. Therefore, it is imperative that the strategies to reduce the risk and increase efficiency are carefully selected. In this presentation I would discuss strategies for selecting potential diseases, targets and provide an example of multi-targeted approach to metabolic disorder.

 

Invited Talk: Biology of plant infection by Magnaporthe oryzae @ Sathyam Hall
Aug 12 @ 12:10 pm – 12:30 pm

bharatBharat B. Chattoo, Ph.D.
Professor, Faculty of Science M.S.University of Baroda, India


Biology of plant infection by Magnaporthe oryzae

The rice blast disease caused by the ascomycetous  fungus  Magnaporthe oryzae is a major constraint in rice production. Rice-M.oryzae is also emerging as a good model patho-system to investigate how the fungus invades and propagates within the host. Identification and characterisation of genes critical for fungal pathogenesis provides opportunities to explore their use as possible targets for development of strategies for combating fungal infection and to better understand the complex process of host-pathogen interaction.

We have used insertional mutagenesis and RNAi based approaches to identify pathogenesis related genes in this fungus. A large number of mutants were isolated using Agrobacterium tumefaciens mediated transformation (ATMT). Characterisation of several interesting mutants is in progress. We have identified a novel gene, MGA1, required for the development of appressoria. The mutant mga1 is unable to infect and is impaired in glycogen and lipid mobilization required for appressorium development. The glycerol content in the mycelia of the mutant was significantly lower as compared to wild type and it was unable to tolerate hyperosmotic stress. A novel ABC transporter was identified in this fungus. The abc4 mutant did not form functional appressoria, was non-pathogenic and showed increased sensitivity to certain antifungal molecules implying the role of ABC4 in multidrug resistance (MDR). Another mutant MoSUMO (MGG_05737) was isolated  using a Split Marker technique; the mutant showed defects in growth, germination and infection. Immuno-fluorescence microscopy revealed that MoSumo is localized to septa in mycelia and nucleus as well as septa in spores. Two Dimensional Gel Electrophoresis showed differences in patterns of protein expression between Wild Type B157 and MoΔSumo mutant.  We also isolated and charaterised mutants in MoALR2 (MGG_08843) and MoMNR2 (MGG_09884). Our results indicate that both MoALR2 and MoMNR2 are Mg2+ transporters, and the reduction in the levels of CorA transporters caused defects in surface hydrophobicity, cell wall stress tolerance, sporulation, appressorium formation and infection are mediated through changes in the key signaling cascades in the knock-down transformants. (Work supported by the Department of Biotechnology, Government of India)

 

 

Plenary Talk: Nano-biotechnology: Omega-3 Oils and Nanofibres @ Sathyam Hall
Aug 12 @ 1:30 pm – 2:05 pm

collinColin Barrow, Ph.D.
Chair in Biotechnology, School of Life & Environmental Sciences, Deakin University, Australia


Nano-biotechnology: Omega-3 Oils and Nanofibres

The health benefits of long-chain omega-3 fatty acids are well established, especially for eicosapentaenoic acid (EPA) and docosapentaenoic acid (DHA) from fish and microbial sources. In fact, a billion dollar market exists for these compounds as nutritional supplements, functional foods and pharmaceuticals. This presentation will describe some aspects of our omega-3 biotechnology research that are at the intersection of Nano-biotechnology and oil chemistry. These include the use of lipases for the concentration of omega-3 fats, through immobilization of these lipases on nanoparticles, and the microencapsulation and stabilization of omega-3 oils for functional foods. I will also describe some of our work on the enzymatic production of resolvins using lipoxygenases, and the fermentation of omega-3 oils from marine micro-organisms. Finally, I will describe some of our work on the formation of amyloid fibrils and graphene for various applications in nano-biotechnology.

 

Invited Talk: Nanobioengineering of implant materials for improved cellular response and activity @ Sathyam Hall
Aug 12 @ 2:05 pm – 2:30 pm

deepthyDeepthy Menon, Ph.D.
Associate Professor, Centre for Nanosciences & Molecular Medicine, Health Sciences Campus, Amrita University, Kochi, India


Nanobioengineering of implant materials for improved cellular response and activity

Deepthy Menon, Divyarani V V, Chandini C Mohan, Manitha B Nair, Krishnaprasad C & Shantikumar V Nair

Abstract

Current trends in biomaterials research and development include the use of surfaces with topographical features at the nanoscale (dimensions < 100 nm), which influence biomolecular or cellular level reactions in vitro and in vivo. Progress in nanotechnology now makes it possible to precisely design and modulate the surface properties of materials used for various applications in medicine at the nanoscale. Nanoengineered surfaces, owing to their close resemblance with extracellular matrix, possess the unique capacity to directly affect protein adsorption that ultimately modulates the cellular adhesion and proliferation at the site of implantation. Taking advantage of this exceptional ability, we have nanoengineered metallic surfaces of Titanium (Ti) and its alloys (Nitinol -NiTi), as well as Stainless Steel (SS) by a simple hydrothermal method for generating non-periodic, homogeneous nanostructures. The bio- and hemocompatibility of these nanotextured metallic surfaces suggest their potential use for orthopedic, dental or vascular implants. The applicability of nanotextured Ti implants for orthopedic use was demonstrated in vivo in rat models, wherein early-stage bone formation at the tissue-implant interface without any fibrous tissue intervention was achieved. This nanoscale topography also was found to critically influence bacterial adhesion in vitro, with decreased adherence of staphylococcus aureus. The same surface nanotopography also was found to provide enhanced proliferation and functionality of vascular endothelial cells, suggesting its prospective use for developing an antithrombotic stent surface for coronary applications. Clinical SS & NiTi stents were also modified based on this strategy, which would offer a suitable solution to reduce the probability of late stent thrombosis associated with bare metallic stents. Thus, we demonstrate that nanotopography on implant surfaces has a critical influence on the fate of cells, which in turn dictates the long term success of the implant.

Acknowledgement: Authors gratefully acknowledge the financial support from Department of Biotechnology, Government of India through the Bioengineering program.

Deepthy

Delegate Talk: Development of a Phototrophic Microbial Fuel Cell with sacrificial electrodes and a novel proton exchange matrix @ Sathyam Hall
Aug 12 @ 2:40 pm – 2:55 pm

ajithAjith Madhavan
Assistant Professor, School of Biotechnology, Amrita University


Development of a Phototrophic Microbial Fuel Cell with sacrificial electrodes and a novel proton exchange matrix

If micro organisms can solve Sudoku and possibly have feelings, who is to say that they cannot also solve the planet’s energy crisis? Mr. Madhavan employs micro organisms to produce energy using microbial fuel cell (MFC). Micro organisms go through a series of cycles and pathways in order to survive, including the Electron Transport Pathway (ETP) in which bacteria release electrons which can be tapped as energy. In a two-chambered MFC, micro organisms interact with an anode in one chamber and in the presence of an oxidizing agent in the cathodic chamber scavenges electrons from the cathode. The two chambers are connected by an external circuit and connected to a load. In between the two chambers is a proton exchange membrane (PEM) which transports protons from the second chamber to the first and acts as a barrier for electrons. Therefore, a renewable source of energy can be maintained by just providing your bacterial culture with the proper nutrients to thrive and remain happy and satisfied (assuming they have emotions).

Mr. Madhavan has done extensive work on such MFCs and has experimented with various micro organisms and substrates to achieve high energy production. The phototropic MFC Mr. Madhavan designed using Synechococcus elongates using waste water as a substrate was able to generate approximately 10 mȦ and 1 volt of electricity. Other research in this area has even shown that using human urine can be used as a substrate for certain bacteria to produce enough energy to charge a mobile phone.

Although this microbial technology seems to be the “next big thing” (despite their small size) when it comes to renewable energy sources there is still a lot of work to be done before these bacteria batteries hit the market. As of now the MFCs are still much less efficient than solar cells and the search for the perfect bacteria and substrate continues.

Delegate Talk: “Molecular and physicochemical characterization of rhamnolipid biosurfactant produced by Pseudomonas sp JSK6″ @ Sathyam Hall
Aug 12 @ 3:00 pm – Aug 13 @ 3:10 am
Delegate Talk: “Molecular and physicochemical characterization of rhamnolipid biosurfactant produced by Pseudomonas sp JSK6″ @ Sathyam Hall | Vallikavu | Kerala | India

Ganesh Kumar S, Kalimuthu K, Solomon Robinson David Jebakumar, Vimalan J


Molecular and physicochemical characterization of rhamnolipid biosurfactant produced by Pseudomonas sp JSK6

Interest in microbial surfactants like rhamnolipids has been progressively increasing in recent years due to their diversity, biodegradability and possibility of large scale production (Pinzon et al. 2013). However, traditional engineering by random and targeted genetic alteration, process design and recombinant strategies in rhamnolipid production were not studied in detail. Based on the environmental conditions, wide diversity of rhamnolipid congeners and homologues was produced in various bacterial strains (Abdel-Mawgoud et al. 2010). In this study, a biosurfactant producing bacterial strain, Pseudomonas sp. JSK6 was isolated from hydrocarbons contaminated sites at Madurai district of South India. The isolate produced mixture of both mono and di-rhamnolipids with excellent surfactant properties. The critical micelle concentration (CMC) of the produced rhamnolipids was 30 mg/L. The emulsification index of 56.4% with diesel and 55.3% with kerosene was quite stable after 24 h. The culture condition optimisation showed that highest rhamnolipid (1.6 g/L) production was achieved at pH 7 and 35◦C. The rhamnolipid was stable over a wide range of temperature (upto 100◦C) and pH (upto 10). The enzyme rhamnosyltransferase-1 which is responsible for biosynthesis of mono-rhamnolipid is encoded by the rhIAB genes, which are organized in rhlABRI operon. From the isolate JSK6, mono-rhamnolipid encoding gene cluster rhlABRI (4.3 kb) was successfully amplified and sequenced by primer walking. The sequence analysis showed that the rhlABRI gene cluster was perfectly organized in the strain JSK6. The rhamnolipid produced by strain JSK6 was analysed in NMR and LC-ESI-MS for structural characterisation. The chemical shifts in 1HNMR (0.86 ppm, 1.267 ppm, 2.546 ppm, 4.134ppm and 5.427 ppm) and 13CNMR (14.466ppm, 23.004–34.951ppm, 171.833ppm and 174.056ppm) and ESI-MS analysis suggested that extracted biosurfactant was present as mono-rhamnolipid and di-rhamnolipid as ten different homologues. This study concluded that the isolate JSK6 is a potential strain with capabilities to produce rhamnolipid biosurfactants with unique physicochemical properties. Cloning of rhlABRI gene cluster of strain JSK6 in a suitable expression system for large scale production is under progress.

Delegate Talk: “Transgenic Sesamum indicum plants for alpha linolenic acid production” @ Sathyam Hall
Aug 12 @ 3:10 pm – 3:15 pm
Delegate Talk: “Transgenic Sesamum indicum plants for alpha linolenic acid production” @ Sathyam Hall | Vallikavu | Kerala | India

Muthulakshmi Chellamuthu, Pratik Pusadkar, Kokiladevi Eswaran and Selvi Subramanian.


“Transgenic Sesamum indicum plants for alpha linolenic acid production”

Sesame, Sesamum indicum L. is an important oilseed crop widely cultivated in India. It yields high quality premium oil and stable against prolonged storage and heating. In cultivated sesame, seed oil content ranged from 40.4% to 59.8% (Hiremath et al. 2007). Fatty acids of sesame oil are mainly oleic (32.7–53.9%), linoleic (39.3–59%) palmitic (8.3–10.9%) and stearic (3.4–6.0%) acids. Alpha linolenic acid (ALA) is an essential fatty acid; dietary consumption of ALA is associated with the primary and secondary prevention of coronary heart disease (Covington 2004). Sesame oil is preferred for its flavor, taste and medicinal properties but it lacks the essential ALA. This study attempts to alter the desaturation pattern of sesame oil to produce ALA using transgenic approaches. A bifunctional Δ12/ω3 fatty acid desaturase gene was isolated from Fusarium moniliforme. Sesamum seed specific promoter was isolated from the oleic acid desaturase gene SeFAD2. Two gene constructs, one with just the active promoter region and another up to −660 region along with the one large intron within the 5\’-untranslated region were developed. A high yielding (880 kg/ha) and high oil content (54%) sesame variety SVPR1 was used in transformation. Agrobacterium mediated transformation method were used. Plant regeneration was successful in direct organogenesis methods but we are standardizing indirect organogenesis method also. Some regenerated transformed tissues were tested for GUS assay and PCR.

Delegate Talk: Protoplast fusion and transformation: A tool for activation of latent gene clusters @ Sathyam Hall
Aug 12 @ 3:15 pm – 3:35 pm
Delegate Talk: Protoplast fusion and transformation: A tool for activation of latent gene clusters @ Sathyam Hall | Vallikavu | Kerala | India

Abhijeet Kate, Arpana G Panicker, Diana Writer, Giridharan P, Keshav K V Ramamoorthy, Saji George, Shailendra K Sonawane


Protoplast fusion and transformation: A tool for activation of latent gene clusters

In the quest to discover new bioactive leads for unmet medical needs, actinomycetes present a treasure trove of undiscovered molecules. The ability of actinomycetes to produce antibiotics and other bioactive secondary metabolites has been underestimated due to sparse studies of cryptic gene clusters. These gene clusters can be tapped to explore scaffolds hidden in them. The up-regulation of the dormant genes is one of the most important areas of interest in the bioactive compounds discovery from microbial resources. Genome shuffling is a powerful tool for the activation of such gene clusters. Lei Yu, et al.1, reported enhancement of the lactic acid production in Lactobacillus rhamnosus through genome shuffling brought about by protoplast fusion. D. A. Hopwood et al.2 suggested that an interspecific recombination between strains producing different secondary metabolites, generate producers of ‘hybrid’ antibiotics. They also mentioned that an intraspecific fusion of actinomycetes protoplast bring about random and high frequency recombination. Protoplasts can also be used as recipients for isolated DNA, again in the presence of polyethylene glycol (PEG). In our study we had undertaken random genome shuffling by protoplast fusion of two, rather poorly expressed actinomycetes strains A (Figure 1) & B (Figure 2), mediated by PEG; and also by naked DNA transformation of Strain A protoplast with the DNA of Strain B. We generated eight protoplast fusants and seven transformants from parents considering their morphological difference from the two parent strains. These 15 recombinants were checked for their same colony morphologies for five generations to ensure phenotypic stability. Antibiotic resistance pattern was established by using antibiotic octodisc to generate a marker profile of the recombinants and the parent strains. Eight fusants (AP-18, AP-25, AP-2, AP-11, AP-14, AP-19, AP-11 and AP-27) and four transformants (TAP-30, TAP-31, TAP-32 and TAP-33) (Table 1) have shown a different antibiotic sensitivity pattern as compared to the parent strains. We envisage that these recombinants harbor shuffled gene clusters. To support array of conditions to express such shuffled/cryptic genes the recombinants were fermented in 11 different nutrient stress variants. The extracts generated were subjected to metabolite profiling by HPLC-ELSD, bioactivity screening for cytotoxicity and anti-infective capabilities. Two fusants AP-11 (Figure 3) and AP-25; one transformant TAP-32 (in growth media MBA-5 and MBA-7) displayed antifungal activity unlike parent strains (Table 2) Fusant AP-11 (Table 5) exhibited significant cell growth inhibition of five different cancer cell lines. The parents Strain A and Strain B did not exhibit any cell growth inhibition of these cell lines (Table 5). The metabolite profiling of fusant AP-11 and transformant TAP-32 was done by HPLC-ELSD. AP-11 showed the presence of five additional peaks (Figure 5 & Figure 6); TAP-32 extract from medium MBA-5 (Figure 7 & Figure 8) showed the presence of four additional peaks and TAP-32 extract from MBA-7 (Figure 9 & Figure 10) showed 14 additional peaks as compared to parent strains in similar medium and media controls. The study indicated that protoplast fusion and transformation have not only caused morphological changes but also shuffled genes responsible for synthesis of bioactive molecules. Further characterization of these new peaks is warranted.

Delegate Talk: Biocatalytic Role of Eukaryotic Rieske Oxygenases, DAF-36 and Nvd @ Sathyam Hall
Aug 12 @ 3:35 pm – 3:50 pm
Delegate Talk: Biocatalytic Role of Eukaryotic Rieske Oxygenases, DAF-36 and Nvd @ Sathyam Hall | Vallikavu | Kerala | India

Sathya Srinivasachari and Ramaswamy Subramanian


Biocatalytic Role of Eukaryotic Rieske Oxygenases, DAF-36 and Nvd

Rieske non-heme iron oxygenases (RO) constitute a well-studied class of enzymes in prokaryotes. The oxygenase component, together with a reductase and sometimes a ferredoxin, form a multicomponent RO system. In prokaryotes, ROs activate relatively inert carbon-carbon bonds to initiate the aerobic catabolism of aromatic compounds. They carry out a variety of reactions, such as dihydroxylation, monohydroxylation, desaturation, sulfoxidation, and dealkylation in stereo and regio- specific manner. The versatility of these enzymes makes them useful for large-scale biosynthesis of chiral compounds. Although the structure and function of different prokaryotic ROs have been extensively characterized, similar studies of eukaryotic ROs have not been reported. The structural information of these enzymes can help us to manipulate and modify these enzymes to improve the efficiency as a biocatalyst. Several conserved genes that encode predicted ROs in eukaryotic systems have been identified. Here, we focus on two of these: DAF-36 from C. elegans (nematode worm) and Neverland (Nvd) from D. melanogaster (fruit-fly). DAF-36 and Nvd play a major role in the early stages of steroid hormone biosynthesis, primarily in the conversion of cholesterol of dehydrocholesterol. It is noteworthy that the proposed RO-catalyzed reaction is oxygen-dependent desaturation and monohydroxylation, neither of which is well characterized even in prokaryotes. In our study, we will first determine the structure of these proteins using X-ray crystallography. Following this, we will measure the specific activity and thermodynamic parameters of the ROs (both wildtype and mutated) using steady-state kinetic and isothermal titration calorimetry (ITC) experiments. These experiments will provide information on how and why the active site of the enzymes and the orientation of substrate control the regio- and stereo-selectivity of the products. These studies will help us engineer these enzymes and design biocatalysts to catalyze a variety of chiral organic transformations that can be of relevance to pharmaceutical companies.

POSTER SESSION: Bioprospecting and Bioengineering @ Poster Corridor 2: First Floor Lobby Area
Aug 12 @ 4:30 pm – 8:00 pm
Aug
13
Tue
2013
Introducing the Track: Bioinformatics & Computational Biology @ Sathyam Hall
Aug 13 @ 9:10 am – 9:15 am

9083583257_671719d5edShyam Diwakar, Ph.D.
Assistant Professor, Amrita School of Biotechnology

Plenary Talk: Modeling strategy based on Petri-nets @ Sathyam Hall
Aug 13 @ 9:20 am – 10:00 am

jaapJaap Heringa, Ph.D.
Director & Professor of Bioinformatics, IBIVU VU University Amsterdam, The Netherlands


Modeling strategy based on Petri-nets

In my talk I will introduce a formal modeling strategy based on Petri-nets, which are a convenient means of modeling biological processes. I will illustrate the capabilities of Petri-nets as reasoning vehicles using two examples: Haematopoietic stem cell differentiation in mice, and vulval development in C. elegance. The first system was modeled using a Boolean implementation, and the second using a coarse-grained multi-cellular Petri-net model. Concepts such as the model state space,  attractor states, and reasoning to adapt the model to the biological reality will be discussed.

Invited Talk: Interpretation of Genomic Variation – Identifying Rare Variations Leading to Disease @ Sathyam Hall
Aug 13 @ 10:20 am – 10:40 am

SrinivasanRajgopal Srinivasan, Ph.D.
Principal Scientist & Head Bio IT R&D, TCS Innovation Labs, India


Interpretation of Genomic Variation – Identifying Rare Variations Leading to Disease

Genome sequencing technologies are generating an abundance of data on human genetic variations. A big challenge lies in interpreting the functional relevance of such variations, especially in clinical settings. A first step in understanding the clinical relevance of genetic variations is to annotate the variants for region of occurrence, degree of conservation both within and across species, pattern of variation across related individuals, novelty of the variation and know effects of related variations.  Several tools already exist for this purpose. However, these tools have their strengths and weaknesses. A second issue is the development of algorithms, which, given a rich annotation of variants are able to prioritize the variants as being relevant to the phenotype under investigation.

In my talk I will detail work that has been done in our labs to address both of the above problems. I will also illustrate the application of these tools that helped identify a rare mutation in the ATM gene leading to a diagnosis of AT in two infants.

 

 

Invited Talk @ Sathyam Hall
Aug 13 @ 10:45 am – 11:15 am

ajayAjay Shah, Ph.D.
Director, Research Informatics, City of Hope , CA, USA


 

Invited Talk: A cost-effective approach to Protein Structure-guided Drug Discovery: Aided by Bioinformatics, Chemoinformatics and computational chemistry @ Sathyam Hall
Aug 13 @ 11:15 am – 11:40 am

kalKal Ramnarayan, Ph.D.
Co-founder President & Chief Scientific Officer, Sapient Discovery, San Diego, CA, USA


A cost-effective approach to Protein Structure-guided Drug Discovery: Aided by Bioinformatics, Chemoinformatics and computational chemistry

With the mapping of the human genome completed almost a decade ago, efforts are still underway to understand the gene products (i.e., proteins) in the human biological and disease pathways.  Deciphering such information is very important for the discovery and development of small molecule drugs as well as protein therapeutics for various human diseases for which no cure exists.  As an example, with more than 500 members, the kinase family of protein targets continues to be an important and attractive class for drug discovery.  While how many of the members in this family are actually druggable is still to be established, there are several ongoing efforts on this class of proteins across a broad spectrum of disease categories.  Even though in general the protein structural topology might looks similar, there are issues with respect selectivity of identified small molecule inhibitors when, the lead molecule discovery is carried out at the ATP binding site.  As an added complexity, allosteric modulators are needed for some of the members, but the actual site for such modulation on the protein target can not resolved with uncertainty.  In this presentation we will describe a bioinformatics and computational based platform for small molecule discovery for protein targets that are involved in protein-protein interactions as well as targets like kinases and phosphatases.  We will describe a computational approach in which we have used an informatics based platform with several hundred kinases to sort through in silico and identify inhibitors that are likely to be highly selective in the lead generation phase.  We will discuss the implication of this approach on the drug discovery of the kinase and phosphatase classes in general and independent of the disease category.

 

Invited Talk: Rare disease diagnostic platform @ Sathyam Hall
Aug 13 @ 11:40 am – 12:20 pm

PrashantPrashanth Athri, Ph.D.
Senior Specialist, Strand Life Sciences, Bengaluru, India


Rare disease diagnostic platform

At Strand, genomic sequencing combined with bioinformatic analysis have provided discriminative diagnosis in the case of rare genetic disorders. Inspired by these cases, we are building an integrated software that combines curated literature content and bioinformatics databases with a clinically oriented user interface to substantially compress time taken to determine likely candidate genetic variants in a Diagnostic Odyssey. At the back end we employ various algorithms that systematically query our diverse knowledgebase to provide the clinicians a comprehensive, and possibly multidimensional, annotation of the variant in the context of disease.

 

Plenary Talk: Interspike Interval Distribution of Neuronal Model with distributed delay: Emergence of unimodal, bimodal and Power law @ Sathyam Hall
Aug 13 @ 1:20 pm – 2:00 pm

karmeshuKarmeshu, Ph.D.
Dean & Professor, School of Computer & Systems Sciences & School of Computational & Integrative Sciences, Jawaharlal Nehru University, India.


Interspike Interval Distribution of Neuronal Model with distributed delay: Emergence of unimodal, bimodal and Power law

The study of interspike interval distribution of spiking neurons is a key issue in the field of computational neuroscience. A wide range of spiking patterns display unimodal, bimodal  ISI patterns including power law behavior. A challenging problem is to understand the biophysical mechanism which can generate  the empirically observed patterns. A neuronal model with distributed delay (NMDD) is proposed and is formulated as an integro-stochastic differential equation which corresponds to a non-markovian process. The widely studied IF and LIF models become special cases of this model. The NMDD brings out some interesting features when excitatory rates are close to inhibitory  rates rendering the drift close to zero. It is interesting that NMDD model with gamma type memory kernel can also account for bimodal ISI pattern. The mean delay of the memory kernels plays a significant role in bringing out the transition from unimodal to bimodal  ISI distribution. It is interesting to note that when a collection of neurons group together and fire together, the ISI distribution exhibits  power law.

 

Invited Talk: Nanoscale Simulations – Tackling Form and Formulation Challenges in Drug Development and Drug Delivery @ Sathyam Hall
Aug 13 @ 2:15 pm – 2:40 pm

lalithaLalitha Subramanian, Ph.D.
Chief Scientific Officer & VP, Services at Scienomics, USA


Nanoscale Simulations – Tackling Form and Formulation Challenges in Drug Development and Drug Delivery

Lalitha Subramanian, Dora Spyriouni, Andreas Bick, Sabine Schweizer, and Xenophon Krokidis Scienomics

The discovery of a compound which is potent in activity against a target is a major milestone in Pharmaceutical and Biotech industry. However, a potent compound is only effective as a therapeutic agent when it can be administered such that the optimal quantity is transported to the site of action at an optimal rate. The active pharmaceutical ingredient (API) has to be tested for its physicochemical properties before the appropriate dosage form and formulation can be designed. Some of the commonly evaluated parameters are crystal forms and polymorphs, solubility, dissolution behavior, stability, partition coefficient, water sorption behavior, surface properties, particle size and shape, etc. Pharmaceutical development teams face the challenge of quickly and efficiently determining a number of properties with small quantities of the expensive candidate compounds. Recently the trend has been to screen these properties as early as possible and often the candidate compounds are not available in sufficient quantities. Increasingly, these teams are leveraging nanoscale simulations similar to those employed by drug discovery teams for several decades. Nanoscale simulations are used to predict the behavior using very little experimental data and only if this is promising further experiments are done. Another aspect where nanoscale simulations are being used in drug development and drug delivery is to get insights into the behavior of the system so that process failures can be remediated and formulation performance can be improved. Thus, the predictive screening and the in-depth understanding leads to experimental efficiency resulting in far-reaching business impacts.

With specific examples, this talk will focus on the different types of nanoscale simulations used to predict properties of the API in excipients and also provide insight into system behavior as a function of shelf life, temperature, mechanical stress, etc.

Invited Talk: Applying Machine learning for Automated Identification of Patient Cohorts @ Sathyam Hall
Aug 13 @ 2:40 pm – 3:05 pm

SriSairamSrisairam Achuthan, Ph.D.
Senior Scientific Programmer, Research Informatics Division, Department of Information Sciences, City of Hope, CA, USA


Applying Machine learning for Automated Identification of Patient Cohorts

Srisairam Achuthan, Mike Chang, Ajay Shah, Joyce Niland

Patient cohorts for a clinical study are typically identified based on specific selection criteria. In most cases considerable time and effort are spent in finding the most relevant criteria that could potentially lead to a successful study. For complex diseases, this process can be more difficult and error prone since relevant features may not be easily identifiable. Additionally, the information captured in clinical notes is in non-coded text format. Our goal is to discover patterns within the coded and non-coded fields and thereby reveal complex relationships between clinical characteristics across different patients that would be difficult to accomplish manually. Towards this, we have applied machine learning techniques such as artificial neural networks and decision trees to determine patients sharing similar characteristics from available medical records. For this proof of concept study, we used coded and non-coded (i.e., clinical notes) patient data from a clinical database. Coded clinical information such as diagnoses, labs, medications and demographics recorded within the database were pooled together with non-coded information from clinical notes including, smoking status, life style (active / inactive) status derived from clinical notes. The non-coded textual information was identified and interpreted using a Natural Language Processing (NLP) tool I2E from Linguamatics.

Delegate Talk: VARANT: The Variant Annotation Tool @ Sathyam Hall
Aug 13 @ 3:05 pm – 3:20 pm
Delegate Talk: VARANT: The Variant Annotation Tool @ Sathyam Hall | Vallikavu | Kerala | India

Kunal Kundu, Sushma Motamarri, Uma Sunderam, Steven E. Brenner and Rajgopal Srinivasan.


VARANT: The Variant Annotation Tool

Genome sequencing technologies are generating an abundance of data on human genetic variations. A big challenge lies in interpreting the functional relevance of such variations, especially in clinical settings. A first step in understanding the clinical relevance of genetic variations is to annotate the variants for region of occurrence, degree of conservation both within and across species, pattern of variation across related individuals, novelty of the variation and know effects of related variations. Several tools already exist for this purpose. However, these tools have their strengths and weaknesses. We will present an open-source tool, VARANT, written in the python programming language, that is easily extended to incorporate newer annotations.

A detailed variant annotation places variants in context, highlights significant findings and prioritizes candidates for further analysis. With this outlook we developed VARANT to annotate, prioritize and visualize variants. VARANT has 5 levels of annotation – genomic position based, gene based, untranslated region (UTR) based, mutation effect prediction and gene level disease association. The databases used for annotations have been compiled from several sources. The genomic position based annotation comprises of tagging variants present in dbSNP and 1000 Genomes projects, GWAS variants, variants in functionally constrained region and variants overlapping epigenetic signals. The gene-based annotation includes, the distance from splice sites for intronic variants; gene, transcript, amino acid change and splicing silencer and enhancers information for exonic variants. UTR based annotations comprise of UTR functional sites like miRNA binding site, internal ribosomal entry site, variations and deletions in UTR5-Coding Sequence(CDS) boundary, exon-intron boundary and CDS-UTR3 boundary.Mutation effect predictions are incorporated from PolyPhen2 and SIFT. Thus, a detailed annotation with VARANT captures multiple biological aspects of a variant and helps in filtering variants based on disease context. The input and output of VARANT is the universal Variant Call Format, with facilities to export the annotations to popular formats such as comma/tab separated values and MS Excel. Using a desktop computer with single core and 4GB RAM VARANT annotates over 50,000 variants/minute and can be readily parallelized. Being an exhaustive annotator with good performance using modest computational hardware, VARANT is a useful annotation tool for analyzing genomic variants. Furthermore, the tool includes facilities to update the underlying data sources in an automated fashion, and is easily extended to add additional annotations. VARANT also provides an interface to visualize variants in an annotated VCF file and to filter variants interactively based on annotation features like – region, mutation effect etc, and inheritance models. In addition to annotation, there are ongoing efforts to incorporate a variant prioritization module using the annotated features as well as inheritance information.

Delegate Talk: Efficient gene prioritization @ Sathyam Hall
Aug 13 @ 3:25 pm – 3:35 pm
Delegate Talk: Efficient gene prioritization @ Sathyam Hall | Vallikavu | Kerala | India

Bhadrachalam Chitturi, Balaji Raghavachari and Donghyun Kim


Efficient gene prioritization

The gene prioritization, GP, problem seeks to identify the most promising genes among several candidate genes. In genetics, gene related conditions are typically associated with chromosomal regions, say with GWAS. These associations yield lists of candidate genes. A priori, some genes i.e. seed genes, are associated with a specific disease D; additional genes that are implicated via associations constitute the potential candidates. Thus, most promising novel candidates for D are sought. In network based approach, a protein protein interaction network, i.e. NP , and a set S of seed genes constitute the prior knowledge. We treat a gene and the protein that it encodes identically. Various GP algorithms based on guilt by association are run on the NP to predict novel candidates [1–6]. They rank a new candidate gene by its estimated association to D.

Distance between a pair of genes is the shortest path measured in the number of edges. Diameter of a set of genes is the longest distance between any pair of genes in terms of the number of edges. The density of a set X of genes is defined as e(X)/|X| where e(X) denotes the number of edges among genes of X and |X| denotes the number of genes of X. The set S: (i) can be of minimal size (say one), (ii) is tightly coupled in NP , i.e. has low-diameter/high-density, or (iii) is loosely coupled, i.e. has high-diameter/low-density. Similarly, the GP algorithms can be partitioned into: Type-1 that ignore the edge weights and Type-2 that employ the edge weights. However, currently, the prioritization process neither exploits the character of S nor the type of GP algorithm that is run. Given S, we compute two core networks of NP which we call NC1 and NC2 that are subnetworks of NP . The idea is to execute GP algorithms of Type-1 and Type-2 on NC1 and NC2 respectively instead of NP . Typically, NC1 and NC2 are much smaller than NP . Also, one runs several algorithms of Type-1 and Type-2 [2–4, 6] and takes consensus [6].

In general, the time to run a GP algorithm say AP on NP i.e. t1 or to compute NC1 and NC2 i.e. t2 is proportional to e(NP ) where e(NP ) e(NC1) and e(NP ) e(NC2). However, executing AP on NC1/NC2 (a much smaller network) is much more efficient than executing AP on NP . We run several GP algorithms onNC1/NC2 [6] but computeNC1/NC2 only once. So, overall our method is more efficient. Preliminary implementation results show that for several GP algorithms, the candidates identified by our method match the topmost prioritized candidates identified by the direct execution of the algorithm on NP . Overall, our method was more efficient. Based on the number of candidates that we seek and the nature of S, we can generate variants of NCx, x ∈ {1, 2}. In some cases, AP determines the appropriate variant of NCx.

Delegate Talk: Insilico Analysis of hypothetical proteins from Leishmania donovani: A Case study of a membrane protein of the MFS class reveals their plausible roles in drug resistance @ Sathyam Hall
Aug 13 @ 3:35 pm – 3:50 pm
Delegate Talk: Insilico Analysis of hypothetical proteins from Leishmania donovani: A Case study of a membrane protein of the MFS class reveals their plausible roles in drug resistance @ Sathyam Hall | Vallikavu | Kerala | India

Nitish Sathyanrayanan, Sandesh Ganji and Holenarsipur Gundurao Nagendra.


Insilico Analysis of hypothetical proteins from Leishmania donovani: A Case study of a membrane protein of the MFS class reveals their plausible roles in drug resistance

Kala-azar or visceral leishmaniais (VL), caused by protozoan parasite Leishmania donovani, is one of the leading causes of morbidity and mortality in Bihar, India (Guerin et al. 2002; Mubayi et al. 2010). The disease is transmitted to the humans mainly by the vector, Phlebotmus argentipes, commonly known as Sand fly. The majority of VL (> 90%) occurs in only six countries: Bangladesh, India, Nepal, Sudan, Ethiopia and Brazil (Chappuis et al. 2007). In the Indian subcontinent, about 200 million people are estimated to be at risk of developing VL and this region harbors an estimated 67% of the global VL disease burden. The Bihar state only has captured almost 50% cases out of total cases in Indian sub-continent (Bhunia et al. 2013). ‘Conserved hypothetical’ proteins pose a challenge not just to functional genomics, but also to biology in general (Galperin and Koonin 2004). Leishmania donovani (strain BPK282A1) genome consists of a staggering ∼65% of hypothetical proteins. These uncharacterized proteins may enable better appreciation of signalling pathways, general metabolism, stress response and even drug resistance.

Delegate Talk: Pharmacophore modeling, atom-based 3D-QSAR and molecular docking studies on Pyrimido[5,4-e][1,2,4]triazine derivatives as PLK 1 inhibitors @ Sathyam Hall
Aug 13 @ 3:55 pm – 4:10 pm
Delegate Talk: Pharmacophore modeling, atom-based 3D-QSAR and molecular docking studies on Pyrimido[5,4-e][1,2,4]triazine derivatives as PLK 1 inhibitors @ Sathyam Hall | Vallikavu | Kerala | India

Rajasekhar Chekkara, Venkata Reddy Gorla and Sobha Rani Tenkayala


Pharmacophore modeling, atom-based 3D-QSAR and molecular docking studies on Pyrimido[5,4-e][1,2,4]triazine derivatives as PLK 1 inhibitors

Polo-like kinase 1 (PLK1) is a significant enzyme with diverse biological actions in cell cycle progression, specifically mitosis. Suppression of PLK1 activity by small molecule inhibitors has been shown to inhibit cancer, being BI 2536 one of the most potent active inhibitor of PLK1 mechanism. Pharmacophore modeling, atom-based 3D-QSAR and molecular docking studies were carried out for a set of 54 compounds belonging to Pyrimido[5,4-e][1,2,4]triazine derivatives as PLK1 inhibitors. A six-point pharmacophoremodel AAADDR, with three hydrogen bond acceptors (A), two hydrogen bond donors (D) and one aromatic ring (R) was developed by Phase module of Schrdinger suite Maestro 9. The generated pharmacophore model was used to derive a predictive atom-based 3D quantitative structure-activity relationship analysis (3D-QSAR) model for the training set (r2 = 0.88, SD = 0.21, F = 57.7, N = 44) and for test set (Q2 = 0.51, RMSE = 0.41, PearsonR = 0.79, N = 10). The original set of compounds were docked into the binding site of PLK1 using Glide and the active residues of the binding site were analyzed. The most active compound H18 interacted with active residues Leu 59, Cys133 (glide score = −10.07) and in comparison of BI 2536, which interacted with active residues Leu 59, Cys133 (glide score = −10.02). The 3D-QSAR model suggests that hydrophobic and electron-withdrawing groups are essential for PLK1 inhibitory activity. The docking results describes the hydrogen bond interactions with active residues of these compounds. These results which may support in the design and development of novel PLK1 inhibitors.

POSTER SESSION: Bioinformatics and Computational Biology @ Poster Corridor 1: First Floor Lobby Area
Aug 13 @ 4:30 pm – 6:30 pm