Egidio D’Angelo, MD, Ph.D.
Full Professor of Physiology & Director, Brain Connectivity Center, University of Pavia, Italy
Realistic modeling: new insight into the functions of the cerebellar network
Realistic modeling is an approach based on the careful reconstruction of neurons synapses starting from biological details at the molecular and cellular level. This technique, combined with the connection topologies derived from histological measurements, allows the reconstruction of precise neuronal networks. Finally, the advent of specific software platforms (PYTHON-NEURON) and of super-computers allows large-scale network simulation to be performed in reasonable time. This approach inverts the logics of older theoretical models, which anticipated an intuition on how the network might work. In realistic modeling, network properties “emerge” from the numerous biological properties embedded into the model.
This approach is illustrated here through an outstanding application of realistic modeling to the cerebellar cortex network. The neurons (over 105) are reproduced at a high level of detail generating non-linear network effects like population oscillations and resonance, phase-reset, bursting, rebounds, short-term and long-term plasticity, spatiotemporal redistrbution of input patterns. The model is currently being used in the context of he HUMAN BRAIN PROJECT to investigate the cerebellar network function.
Correspondence should be addressed to
Dr. EgidioD’Angelo,
Laboratory of Neurophysiology
Via Forlanini 6, 27100 Pavia, Italy
Phone: 0039 (0) 382 987606
Fax: 0039 (0) 382 987527
dangelo@unipv.it
Acknowledgments
This work was supported by grants from European Union to ED (CEREBNET FP7-ITN238686, REALNET FP7-ICT270434) and by grants from the Italian Ministry of Health to ED (RF-2009-1475845).
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.
Manzoor K, Ph.D.
Professor, Centre for Nanoscience & Molecular Medicine, Amrita University
Targeting aberrant cancer kinome using rationally designed nano-polypharmaceutics
Manzoor Koyakutty, Archana Ratnakumary, Parwathy Chandran, Anusha Ashokan, and Shanti Nair
`War on Cancer’ was declared nearly 40 years ago. Since then, we made significant progress on fundamental understanding of cancer and developed novel therapeutics to deal with the most complex disease human race ever faced with. However, even today, cancer remains to be the unconquered `emperor of all maladies’. It is well accepted that meaningful progress in the fight against cancer is possible only with in-depth understanding on the molecular mechanisms that drives its swift and dynamic progression. During the last decade, emerging new technologies such as nanomedicine could offer refreshing life to the `war on cancer’ by way of providing novel methods for molecular diagnosis and therapy.
In the present talk, we discuss our approaches to target critically aberrant cancer kinases using rationally designed polymer-protein and protein-protein core-shell nanomedicines. We have used both genomic and proteomic approaches to identify many intimately cross-linked and complex aberrant protein kinases behind the drug resistance and uncontrolled proliferation of refractory leukemic cells derived from patients. Small molecule inhibitors targeted against oncogenic pathways in these cells were found ineffective due to the involvement of alternative survival pathways. This demands simultaneous inhibition more than one oncogenic kinases using poly-pharmaceutics approach. For this, we have rationally designed core-shell nanomedicines that can deliver several small molecules together for targeting multiple cancer signalling. We have also used combination of small molecules and siRNA for combined gene silencing together with protein kinase inhibition in refractory cancer cells. Optimized nanomedicines were successfully tested in patient samples and found enhanced cytotoxicity and molecular specificity in drug resistant cases.
Nano-polypharmaceutics represents a new generation of nanomedicines that can tackle multiple cancer mechanisms simultaneously. Considering the complexity of the disease, such therapeutic approaches are not simply an advantage, but indispensable.
Acknowledgements:
We thank Dept. of Biotechnology and Dept. Of Science and Technology,Govt. of India for the financial support through `Thematic unit of Excellence in Medical NanoBiotechnology’ and `Nanomedicine- RNAi programs’.
Lalitha 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.