Terry Hermiston, Ph.D.
Vice President, US Biologics Research Site Head, US Innovation Center Bayer Healthcare, USA
ColoAd1 – An oncolytic adenovirus derived by directed evolution
Attempts at developing oncolytic viruses have been primarily based on rational design. However, this approach has been met with limited success. An alternative approach employs directed evolution as a means of producing highly selective and potent anticancer viruses. In this method, viruses are grown under conditions that enrich and maximize viral diversity and then passaged under conditions meant to mimic those encountered in the human cancer microenvironment. Using the “Directed Evolution” methodology, we have generated ColoAd1, a novel chimeric oncolytic adenovirus. In vitro, this virus demonstrated a >2 log increase in both potency and selectivity when compared to ONYX-015 on colon cancer cells. These results were further supported by in vivo and ex vivo studies. Importantly, these results have validated this methodology as a new general approach for deriving clinically-relevant, highly potent anti-cancer virotherapies. This virus is currently in clinical trials as a novel treatment for cancer.
Sanjeeva Srivastava, Ph.D.
Assistant Professor, Proteomics Lab, IIT-Bombay, India
Identification of Potential Early Diagnostic Biomarkers for Gliomas and Various Infectious Diseases using Proteomic Technologies
The spectacular advancements achieved in the field of proteomics research during the last decade have propelled the growth of proteomics for clinical research. Recently, comprehensive proteomic analyses of different biological samples such as serum or plasma, tissue, CSF, urine, saliva etc. have attracted considerable attention for the identification of protein biomarkers as early detection surrogates for diseases (Ray et al., 2011). Biomarkers are biomolecules that can be used for early disease detection, differentiation between closely related diseases with similar clinical manifestations as well as aid in scrutinizing disease progression. Our research group is performing in-depth analysis of alteration in human proteome in different types of brain tumors and various pathogenic infections to obtain mechanistic insight about the disease pathogenesis and host immune responses, and identification of surrogate protein markers for these fatal human diseases.
Applying 2D-DIGE in combination with MALDI-TOF/TOF MS we have analyzed the serum and tissue proteome profiles of glioblastoma multiforme; the most common and lethal adult malignant brain tumor (Gollapalli et al., 2012) (Figure 1). Results obtained were validated by employing different immunoassay-based approaches. In serum proteomic analysis we have identified some interesting proteins like haptoglobin, ceruloplasmin, vitamin-D binding protein etc. Moreover, proteomic analysis of different grades (grade-I to IV) of gliomas and normal brain tissue was performed and differential expressions of quite a few proteins such as SIRT2, GFAP, SOD, CDC42 have been identified, which have significant correlation with the tumor growth. While proteomic analysis of cerebrospinal fluid from low grade (grade I & II) vs. high grade (grade III & IV) gliomas revealed modulation of CSF levels of apolipoprotein E, dickkopf related protein 3, vitamin D binding protein and albumin in high grade gliomas. The prospective candidates identified in our studies provide a mechanistic insight of glioma pathogenesis and identification of potential biomarkers. We are also studying the role of JAK/STAT interactome and therapeutic potential of STAT3 inhibitors in gliomas using proteomics approach. Several candidates of the JAK/STAT interactome were identified with altered expression and a significant correlation was observed between STAT3 and PDK1 transcript expression level.
We have also investigated the changes in human serum proteome in different infectious diseases including falciparum and vivax malaria (Ray et al., 2012a; Ray et al., 2012b), dengue (Ray et al., 2012c) and leptospirosis (Srivastava et al., 2012). Although, quite a few serum proteins were found to be commonly altered in different infectious diseases and might be a consequence of inflammation mediated acute phase response signaling, uniquely modulated candidates were identified in each pathogenic infection indicating the some inimitable responses. Further, a panel of identified proteins consists of six candidates; serum amyloid A, hemopexin, apolipoprotein E, haptoglobin, retinol-binding protein and apolipoprotein A-I was used to build statistical sample class prediction models employing PLSDA and other classification methods to predict the clinical phenotypic classes and 91.37% overall prediction accuracy was achieved (Figure 2). ROC curve analysis was carried out to evaluate the individual performance of classifier proteins. The excellent discrimination among the different disease groups on the basis of differentially expressed proteins demonstrates the potential diagnostic implications of this analytical approach.
Keywords: Diagnostic biomarkers, Gliomas, Infectious Diseases, Proteomics, Serum proteome
Acknowledgments: This disease biomarker discovery research was supported by Department of Biotechnology, India grant (No. BT/PR14359/MED/30/916/2010), Board of Research in Nuclear Sciences (BRNS) DAE young scientist award (2009/20/37/4/BRNS) and a startup grant 09IRCC007 from the IIT Bombay. The active support from Advanced Center for Treatment Research and Education in Cancer (ACTREC), Tata Memorial Hospital (TMH), and Seth GS Medical College and KEM Hospital Mumbai, India in clinical sample collection process is gratefully acknowledged.
References :
- Ray S, Reddy PJ, Jain R, Gollapalli K. Moiyadi A, Srivastava S. Proteomic technologies for the identification of disease biomarkers in serum: advances and challenges ahead. Proteomics 11: 2139-61, 2011.
- Gollapalli K, Ray S, Srivastava R, Renu D, Singh P, Dhali S, Dikshit JB, Srikanth R, Moiyadi A, Srivastava S. Investigation of serum proteome alterations in human glioblastoma multiforme. Proteomics 12(14): 2378-90, 2012.
- Ray S, Renu D, Srivastava R, Gollapalli K, Taur S, Jhaveri T, Dhali S, Chennareddy S, Potla A, Dikshit JB, Srikanth R, Gogtay N, Thatte U, Patankar S, Srivastava S. Proteomic investigation of falciparum and vivax malaria for identification of surrogate protein markers. PLoS One 7(8): e41751, 2012a.
- Ray S, Kamath KS, Srivastava R, Raghu D, Gollapalli K, Jain R, Gupta SV, Ray S, Taur S, Dhali S, Gogtay N, Thatte U, Srikanth R, Patankar S, Srivastava S. Serum proteome analysis of vivax malaria: An insight into the disease pathogenesis and host immune response. J Proteomics 75(10): 3063-80, 2012b.
- Srivastava R, Ray S, Vaibhav V, Gollapalli K, Jhaveri T, Taur S, Dhali S, Gogtay N, Thatte U, Srikanth R, Srivastava S. Serum profiling of leptospirosis patients to investigate proteomic alterations. J Proteomics 76: 56-68, 2012.
- Ray S, Srivastava R, Tripathi K, Vaibhav V, Srivastava S. Serum proteome changes in dengue virus-infected patients from a dengue-endemic area of India: towards new molecular targets? OMICS 16(10): 527-36, 2012c.
* Correspondence: Dr. Sanjeeva Srivastava, Department of Biosciences and Bioengineering, IIT Bombay, Mumbai 400 076, India: E-mail: sanjeeva@iitb.ac.in; Phone: +91-22-2576-7779, Fax: +91-22-2572-3480
![Figure 1 (a) Differentially expressed proteins in GBM identified using 2D-DIGE. Representative 2D- DIGE image to compare serum proteome of HC and GBM patients. GBM and HC samples were labeled with Cy3 and Cy5 respectively, while the protein reference pool (internal standard) was labeled with Cy2. Graphical and 3D fluorescence intensity representations of few selected statistically significant (p < 0.05) differentially expressed proteins in GBM patients identified in biological variation analysis (BVA) using DeCyder 2D software. (b) Involvement of different essential physiological pathways with differentially expressed proteins in GBM. Members of multiple essential physiological processes including cell growth and proliferation, vitamin D metabolism, lipoprotein metabolism and transport, oxidative stress regulation, complement cascade, and platelet activation found to be modulated in the GBM patients (Gollapalli et al., Proteomics 2012).](http://www.amritabioquest.org/conference/2013/wp-content/uploads/sites/2/2015/02/sanjeeva.jpg)
![Figure 2 (a) Western blot analysis of haptoglobin (HP), serum amyloid A (SAA), and clusterin (CLU) from serum samples of healthy control (HC) [n = 12], falciparum malaria (FM) [n = 12], vivax malaria (VM) [n = 12], Leptospirosis (Lep) [n = 6], dengue fever [DF] [n = 6] and non infectious disease control (NIDC:GBM) [n = 12]. Representative blots of the target proteins are depicted along with their respective relative abundance volumes (volume X 104). All the data are represented as mean ± SE. (b) Discrimination of malaria from dengue, leptospirosis and GBM using PLS-DA analysis. PLS-DA scores Plot for FM (blue spheres, n = 8), VM (green spheres, n = 8), DF (red spheres, n = 6), Lep (grey spheres, n = 6) and GBM (brown spheres, n = 8) samples based on 6 differentially expressed proteins (serum amyloid A, hemopexin, apolipoprotein E, haptoglobin, retinol-binding protein and apolipoprotein A-I) identified using DIGE. The axes of the plot indicate PLSDA latent variables t0-t2.](http://www.amritabioquest.org/conference/2013/wp-content/uploads/sites/2/2015/02/sanjeeva-2.jpg)
Nader Pourmand, Ph.D.
Director, UCSC Genome Technology Center,University of California, Santa Cruz
Biosensor and Single Cell Manipulation using Nanopipettes
Approaching sub-cellular biological problems from an engineering perspective begs for the incorporation of electronic readouts. With their high sensitivity and low invasiveness, nanotechnology-based tools hold great promise for biochemical sensing and single-cell manipulation. During my talk I will discuss the incorporation of electrical measurements into nanopipette technology and present results showing the rapid and reversible response of these subcellular sensors to different analytes such as antigens, ions and carbohydrates. In addition, I will present the development of a single-cell manipulation platform that uses a nanopipette in a scanning ion-conductive microscopy technique. We use this newly developed technology to position the nanopipette with nanoscale precision, and to inject and/or aspirate a minute amount of material to and from individual cells or organelle without comprising cell viability. Furthermore, if time permits, I will show our strategy for a new, single-cell DNA/ RNA sequencing technology that will potentially use nanopipette technology to analyze the minute amount of aspirated cellular material.
D. Narasimha Rao, Ph.D.
Professor, Dept of Biochemistry, Indian Institute of Science, Bangalore, India
Genomics of Restriction-Modification Systems
Restriction endonucleases occur ubiquitously among procaryotic organisms. Up to 1% of the genome of procaryotic organisms is taken up by the genes for these enzymes. Their principal biological function is the protection of the host genome against foreign DNA, in particular bacteriophage DNA. Restriction-modification (R-M) systems are composed of pairs of opposing enzyme activities: an endonuclease and a DNA methyltransferase (MTase). The endonucleases recognise specific sequences and catalyse cleavage of double-stranded DNA. The modification MTases catalyse the addition of a methyl group to one nucleotide in each strand of the recognition sequence using S-adenosyl-L-methionine (AdoMet) as the methyl group donor. Based on their molecular structure, sequence recognition, cleavage position and cofactor requirements, R-M systems are generally classified into three groups. In general R-M systems restrict unmodified DNA, but there are other systems that specifically recognise and cut modified DNA. More than 3500 restriction enzymes have been discovered so far. With the identification and sequencing of a number of R-M systems from bacterial genomes, an increasing number of these have been found that do not seem to fit into the conventional classification.
It is well documented that restriction enzyme genes always lie close to their cognate methyltransferase genes. Analysis of the bacterial and archaeal genome sequences shows that MTase genes are more common than one would have expected on the basis of previous biochemical screening. Frequently, they clearly form part of a R-M system, because the adjacent open reading frames (ORFs) show similarity to known restriction enzyme genes. Very often, though, the adjacent ORFs have no homologs in the GenBank and become candidates either for restriction enzymes with novel specificities or for new examples of previously uncloned specificities. Sequence-dependent modification and restriction forms the foundation of defense against foreign DNAs and thus RM systems may serve as a tool of defense for bacterial cells. RM systems however, sometimes behave as discrete units of life, and any threat to their maintenance, such as a challenge by a competing genetic element can lead to cell death through restriction breakage in the genome, thus providing these systems with a competitive advantage. The RM systems can behave as mobile-genetic elements and have undergone extensive horizontal transfer between genomes causing genome rearrangements. The capacity of RM systems to act as selfish, mobile genetic elements may underlie the structure and function of RM enzymes.
The similarities and differences in the different mechanisms used by restriction enzymes will be discussed. Although it is not clear whether the majority of R-M systems are required for the maintenance of the integrity of the genome or whether they are spreading as selfish genetic elements, they are key players in the “genomic metabolism” of procaryotic organisms. As such they deserve the attention of biologists in general. Finally, restriction enzymes are the work horses of molecular biology. Understanding their enzymology will be advantageous to those who use these enzymes, and essential for those who are devoted to the ambitious goal of changing the properties of these enzymes, and thereby make them even more useful.
![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](http://www.amritabioquest.org/conference/2013/wp-content/uploads/sites/2/2015/02/bicb.jpg)
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.