Rohit Manchanda, Ph.D.
Professor, Biomedical Engineering Group, IIT-Bombay, India
Modelling the syncytial organization and neural control of smooth muscle: insights into autonomic physiology and pharmacology
We have been studying computationally the syncytial organization and neural control of smooth muscle in order to help explain certain puzzling findings thrown up by experimental work. This relates in particular to electrical signals generated in smooth muscles, such as synaptic potentials and spikes, and how these are explicable only if three-dimensional syncytial biophysics are taken fully into account. In this talk, I shall provide an illustration of outcomes and insights gleaned from such an approach. I shall first describe our work on the mammalian vas deferens, in which an analysis of the effects of syncytial coupling led us to conclude that the experimental effects of a presumptive gap junction uncoupler, heptanol, on synaptic potentials were incompatible with gap junctional block and could best be explained by a heptanol-induced inhibition of neurotransmitter release, thus compelling a reinterpretation of the mechanism of action of this agent. I shall outline the various lines of evidence, based on indices of syncytial function, that we adduced in order to reach this conclusion. We have now moved on to our current focus on urinary bladder biophysics, where the questions we aim to address are to do with mechanisms of spike generation. Smooth muscle cells in the bladder exhibit spontaneous spiking and spikes occur in a variety of distinct shapes, making their generation problematic to explain. We believe that the variety in shapes may owe less to intrinsic differences in spike mechanism (i.e., in the complement of ion channels participating in spike production) and more to features imposed by syncytial biophysics. We focus especially on the modulation of spike shape in a 3-D coupled network by such factors as innervation pattern, propagation in a syncytium, electrically finite bundles within and between which the spikes spread, and some degree of pacemaker activity by a sub-population of the cells. I shall report two streams of work that we have done, and the tentative conclusions these have enabled us to reach: (a) using the NEURON environment, to construct the smooth muscle syncytium and endow it with synaptic drive, and (b) using signal-processing approaches, towards sorting and classifying the experimentally recorded spikes.
Ajith 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.
Jaap 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.
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.
Sudarslal S, Ph.D.
Associate Professor, School of Biotechnology, Amrita University
Electrospray ionization ion trap mass spectrometry for cyclic peptide characterization
There has been considerable interest in the isolation and structural characterization of bioactive peptides produced by bacteria and fungi. Most of the peptides are cyclic depsipeptides characterized by the presence of lactone linkages and β-hydroxy fatty acids. Occurrence of microheterogeneity is another remarkable property of these peptides. Even if tandem mass spectrometers are good analytical tools to structurally characterize peptides and proteins, sequence analysis of cyclic peptides is often ambiguous due to the random ring opening of the peptides and subsequent generation of a set of linear precursor ions with the same m/z. Here we report combined use of chemical derivatization and multistage fragmentation capability of ion trap mass spectrometers to determine primary sequences of a series of closely related cyclic peptides.
![Delegate Talk: Bioanalytical Characterization of Therapeutic Proteins @ Amriteshwari Hall | Vallikavu | Kerala | India](http://www.amritabioquest.org/conference/2013/wp-content/uploads/sites/2/2015/02/bioanalt.jpg)
Ravindra Gudihal, Suresh Babu C V
Bioanalytical Characterization of Therapeutic Proteins
The characterization of therapeutic proteins such as monoclonal antibody (mAb) during different stages of manufacturing is crucial for timely and successful product release. Regulatory agencies require a variety of analytical technologies for comprehensive and efficient protein analysis. Electrophoresis-based techniques and liquid chromatography (LC) either standalone or coupled to mass spectrometry (MS) are at the forefront for the in-depth analysis of protein purity, isoforms, stability, aggregation, posttranslational modifications, PEGylation, etc. In this presentation, a combination of various chromatographic and electrophoretic techniques such as liquid-phase isoelectric focusing, microfluidic and capillary-based electrophoresis (CE), liquid chromatography (LC) and combinations of those with mass spectrometry techniques will be discussed. We present a workflow based approach to the analysis of therapeutic proteins. In successive steps critical parameters like purity, accurate mass, aggregation, peptide sequence, glycopeptide and glycan analysis are analyzed. In brief, the workflow involved proteolytic digestion of therapeutic protein for peptide mapping, N-Glycanase and chemical labeling reaction for glycan analysis, liquid-phase isoelectric focusing for enrichment of charge variants followed by a very detailed analysis using state of the art methods such as CE-MS and LC-MS. For the analysis of glycans, we use combinations of CE-MS and LC-MS to highlight the sweet spots of these techniques. CE-MS is found to be more useful in analysis of highly sialylated glycans (charged glycans) while nano LC-MS seems to be better adapted for analysis of neutral glycans. These two techniques can be used to get complementary data to profile all the glycans present in a given protein. In addition, microfluidic electrophoresis was used as a QC tool in initial screening for product purity, analysis of papain digestion fragments of mAb, protein PEGylation products, etc. The described workflow involves multiple platforms, provides an end to end solution for comprehensive protein characterization and aims at reducing the total product development time.