Upinder S. Bhalla, Ph.D.
Professor & Dean, NCBS, Bengaluru, India
Watching the network change during the formation of associative memory
The process of learning is measured through behavioural changes, but it is of enormous interest to understand its cellular and network basis. We used 2-photon imaging of hippocampal CA1 pyramidal neuron activity in mice to monitor such changes during the acquisition of a trace conditioning task. One of the questions in such learning is how the network retains a trace of a brief conditioned stimulus (a sound), until the arrival of a delayed unconditioned stimulus (a puff of air to the eye). During learning, the mice learn to blink when the tone is presented, well before the arrival of the air puff.
The mice learnt this task in 20-50 trials. We observed that in this time-frame the cells in the network changed the time of their peak activity, such that their firing times tiled the interval between sound and air puff. Thus the cells seem to form a relay of activity. We also observed an evolution in functional connectivity in the network, as measured by groupings of correlated cells. These groupings were stable till the learning protocol commenced, and then changed. Thus we have been able to observe two aspects of network learning: changes in activity (relay firing), and changes in connectivity (correlation groups).
Krishnakumar Menon, Ph.D.
Associate Professor, Centre for Nanosciences & Molecular Medicine, Amrita University, Kochi, India
A Far-Western Clinical Proteomics Approach to Detect Molecules of Clinical and Pathological Significance in the Neurodegenerative Disease Multiple Sclerosis.
Multiple Sclerosis (MS), an autoimmune neurodegenerative disorder of the central nervous system. The disease affects young adults at their prime age leading to severe debilitation over several years. Despite advances in MS research, the cause of the disease remains elusive. Thus, our objective is to identify novel molecules of pathological and diagnostic significance important in the understanding, early diagnosis and treatment of MS. Biological fluids such as cerebrospinal fluid (CSF), that bathe the brain serve as a potential source for the identification of pathologically significant autoantibody reactivity in MS. In this regard, we report the development of an unbiased clinical proteomics approach for the detection of reactive CSF molecules that target brain proteins from patients with MS. Proteins of myelin and myelin-axolemmal complexes were separated by two-dimensional gel electrophoresis, blotted onto membranes and probed separately with biotinylated unprocessed CSF samples. Protein spots that reacted specifically to MS-CSF’s were further analyzed by matrix assisted laser desorption ionization-time-of-flight time-of-flight mass spectrometry. In addition to previously reported proteins found in MS, we have identified several additional molecules involved in mitochondrial and energy metabolism, myelin gene expression and/or cytoskeletal organization. Among these identified molecules, the cellular expression pattern of collapsin response mediator protein-2 and ubiquitin carboxy-terminal hydrolase L1 were investigated in human chronic-active MS lesions by immunohistochemistry. The observation that in multiple sclerosis lesions phosphorylated collapsin response mediator protein-2 was increased, whereas Ubiquitin carboxy-terminal hydrolase L1 was down-regulated, not only highlights the importance of these molecules in the pathology of this disease, but also illustrates the use of our approach in attempting to decipher the complex pathological processes leading to multiple sclerosis and other neurodegenerative diseases. Further, we show that in clinicaly isolated syndrome (CIS), we could identify important molecules that could serve as an early diagnostic biomarker in MS.
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).
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.
Michelle Hermiston, MD, Ph.D.
Assistant Professor, Department of Pediatrics University of California San Francisco, USA
Interrogating Signaling Networks at the Single Cell Level In Primary Human Patient Samples
Multiparameter phosphoflow cytometry is a highly sensitive proteomic approach that enables monitoring of biochemical perturbations at the single cell level. By combining antisera to cell surface markers and key intracellular proteins, perturbations in signaling networks, cell survival and apoptosis mediators, cell cycle regulators, and/or modulators of other cellular processes can be analyzed in a highly reproducible and sensitive manner in the basal state and in response to stimulation or drug treatment. Advantages of this approach include the ability to identify the biochemical consequences of genetic and/or epigenetic changes in small numbers of cells, to map potential interplay between various signaling networks simultaneously in a single cell, and to interrogate potential mechanisms of drug resistance or response in a primary patient sample. Application of this technology to patients with acute lymphoblastic leukemia or the autoimmune disease systemic lupus erythematosus (SLE) will be discussed.
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.
Gokul Das, Ph.D.
Co-Director, Breast Disease Site Research Group, Roswell Park Cancer Institute, Buffalo, NY
Probing Estrogen Receptor−Tumor Suppressor p53 Interaction in Cancer: From Basic Research to Clinical Trial
Tumor suppressor p53 and estrogen receptor have opposite roles in the onset and progression of breast cancer. p53 responds to a variety of cellular of stresses by restricting the proliferation and survival of abnormal cells. Estrogen receptor plays an important role in normal mammary gland development and the preservation of adult mammary gland function; however, when deregulated it becomes abnormally pro-proliferative and greatly contributes to breast tumorigenesis. The biological actions of estrogens are mediated by two genetically distinct estrogen receptors (ERs): ER alpha and ER beta. In addition to its expression in several ER alpha-positive breast cancers and normal mammary cells, ER beta is usually present in ER alpha-negative cancers including triple-negative breast cancer. In spite of genetically being wild type, why p53 is functionally debilitated in breast cancer has remained unclear. Our recent finding that ER alpha binds directly to p53 and inhibits its function has provided a novel mechanism for inactivating genetically wild type p53 in human cancer. Using a combination of proliferation and apoptosis assays, RNAi technology, quantitative chromatin immunoprecipitation (qChIP), and quantitative real-time PCR (qRT-PCR), in situ proximity ligation assay (PLA), and protein expression analysis in patient tissue micro array (TMA), we have demonstrated binding of ER alpha to p53 and have delineated the domains on both the proteins necessary for the interaction. Importantly, ionizing radiation inhibits the ER-p53 interaction in vivo both in human cancer cells and human breast tumor xenografts in mice. In addition, antiestrogenstamoxifen and faslodex/fulvestrant (ICI 182780) disrupt the ER-p53 interaction and counteract the repressive effect of ER alpha on p53, whereas 17β-estradiol (E2) enhances the interaction. Intriguingly, E2 has diametrically opposite effects on corepressor recruitment to a p53-target gene promoter versus a prototypic ERE-containing promoter. Thus, we have uncovered a novel mechanism by which estrogen could be providing a strong proliferative advantage to cells by dual mechanisms: enhancing expression of ERE-containing pro-proliferative genes while at the same time inhibiting transcription of p53-dependent anti-proliferative genes. Consistently, ER alpha enhances cell cycle progression and inhibits apoptosis of breast cancer cells. Correlating with these observations, our retrospective clinical study shows that presence of wild type p53 in ER-positive breast tumors is associated with better response to tamoxifen therapy. These data suggest ER alpha-p53 interaction could be one of the mechanisms underlying resistance to tamoxifen therapy, a major clinical challenge encountered in breast cancer patients. We have launched a prospective clinical trial to analyze ER-p53 interaction in breast cancer patient tumors at Roswell Park Cancer Institute. Our more recent finding that ER beta has opposite functions depending on the mutational status of p53 in breast cancer cells is significant in understanding the hard-to-treat triple-negative breast cancer and in developing novel therapeutic strategies against it. Our integrated approach to analyze ER-p53 interaction at the basic, translational, and clinical research levels has major implications in the diagnosis, prognosis, and treatment of breast cancer.