Research

Our current focus of studies at the Computational Neurophysiology Lab, Department of Biosciences and Bioengineering, IIT Bombay is towards investigating the cellular level biophysical mechanisms in the bladder that give rise to different facets of bladder function such as bladder contractility, sensory transduction and control of bladder function via known neural pathways. Any deviation from the physiology that underlies bladder function results in Urinary Incontinence. Urinary Incontinence or loss of bladder control is a pathophysiological condition that has its basis in the altered cellular physiology of the components that comprise the bladder wall resulting in symptoms which include bladder overactivity as well as increased neural input to the central nervous system via the afferent pathways. The underlying causes of Urinary Incontinence are varied and severely impact the quality of life both physiologically as well as psychologically.  The aim of our research is to study the bladder biophysics in order to delineate the bladder function at cellular and tissue level by developing biophysically detailed computational models that mimic different aspects of bladder activity. The larger aim of our work is to then use our know how to unravel possible mechanisms that underlie bladder pathophysiology.

The composite bladder wall consists of three primary layers, namely, the detrusor smooth muscle, the lamina propria and the bladder epithelium (Urothelium). These tissue layers are further composed of structurally and functionally unique components such as smooth muscle cells (SMC), afferent nerve endings (A Delta and C fibers), efferent nerve endings, myofibroblasts, interstitial cells of Cajal (ICC), epithelial cells (umbrella cells) etc.  These individual components form networks based on their regions of localization and there exist pathways via which they can interact with each other, structurally and functionally. Our current modeling approach includes constructing models for these individual components by endowing them with as many experimentally established mechanisms as possible so as to render them rich in biophysical detail. Typical cellular level mechanisms include ion channels (voltage, mechanical, temperature, ligand gated), pumps, gap junctions, intracellular calcium dynamics etc. Further, once a sufficiently detailed model for individual components is constructed, our approach then extends to determining their behavior in a network of cells by constructing appropriate models for the same. Finally, our aim is to integrate the various models for the sub components outlined above to create a master model akin to a virtual laboratory that would mimic different aspects of bladder function giving insights into its physiology as well as pathophysiology.

The modeling work being carried out in the lab is broadly subdivided into five domains, namely, (i) modeling of the smooth muscle cells in a syncytial network; (ii) modeling of ionic mechanisms in SMC and intracellular calcium dynamics; (iii) modeling of the reflex pathways involved in bladder control (afferent and efferent); (iv) modeling of sensory transduction pathways in bladder epithelia and lamina propria (ICCs); (v) Classification of the action potentials in SMCs using signal processing techniques.

Modeling of the smooth muscle cells in a syncytial network – Detrusor smooth muscle (DSM) is the primary contractile tissue of the bladder. It is composed of SMCs which are interconnected via gap junctions to form a “syncytium”. Electrical activity recorded in SMCs is varied and atypical. The complexity of electrical activity in SMC is most often attributed to (a) the distributed pattern of innervation and (b) electrical coupling of SMCs to form a 3d cellular network. Models developed / currently under development in the lab for this sub-domain is aimed at understanding the generation of Action Potentials, their spread in a 3D network and the role of neurotransmission underlying their generation and propagation. The models developed use coupled ODEs in a compartmental modeling approach implemented on the platform NEURON. This technique of modeling offers an adaptable and extensible platform in which electrical signaling in smooth muscle can be rigorously and effectively examined.

Modeling of ionic mechanisms in SMC and intracellular calcium dynamics – The SMCs are electrically excitable cells. The excitability is endowed by the variety of ion channels such as voltage-gated calcium and potassium channels, calcium dependent potassium channels etc. present on the plasma membrane of SMCs. The interplay between the dynamics of these channels in response to physiological perturbation results in the generation of spontaneous action potentials and spontaneous depolarizations. Our ionic channel mechanisms are typically modeled using the Hodgkin Huxley formalism. Incorporation of calcium dynamics in our models is key to throwing light on not only the contractility of SMCs but also their role in influencing ion channel dynamics. Typical mechanisms involved in calcium dynamics include IP3 and ryanodine receptors, SERCA, PMCA and NCX pumps whose combined interplay gives rise to both intra-cellular as well as inter-cellular calcium signals.  Our computational models developed/ under development in-house provides a powerful tool to investigate ionic mechanisms underlying spike generation in DSM and the associated bladder contractility.

Modeling of the reflex pathways involved in bladder control: Afferent Mechanisms – Urinary bladder is under autonomic control by the sympathetic and parasympathetic nervous system. Its sensory component -- which includes the Dorsal Root Ganglion (DRG) neurons and its receptors, conduct information on various stimuli e.g. bladder stretch, volume, temperature, presence of irritants such as capsaicin etc. In pathological conditions, the electrical activity of these neurons change but its correlation with diseases is not properly understood. A DRG neuron model has been developed which incorporates ion channels, pumps, exchangers and some intracellular mechanisms. It faithfully mimics the electrical activity captured in experimental recordings from the bladder DRG neuron.

Modeling of sensory transduction pathways in bladder epithelia and lamina propria (ICC) – The urothelium is known to mediate sensory stimuli to the underlying layers of the bladder wall. Some of the stimuli transduced include stretch, volume, pH, temperature, nociception etc. The urothelium also releases ATP, ACh and NO in response to these stimuli which bind to specific receptors on the interstitial cells of Cajal and the afferent nerve endings relaying these locally generated signals to the CNS as well as underlying layers of the bladder wall. Modeling work carried out in this sub domain includes temperature receptors (TRP), acid sensing ion channels (ASICs), mechanosensitive channels (MSCs) as well as purinergic receptors (P2X, P2Y) and muscarinic receptors.  Also, under development is a model for the ICC where we aim to study and establish its role in signal modulation, signal transduction and neurotransmission. Our aim is to integrate these models with the models for smooth muscle cells and DRG neurons as applicable, in order to study their role in modulating smooth muscle activity as well as mimicking the firing activity seen in bladder afferents.

Classification of the action potentials in SMCs using signal processing techniques – As part of a collaborative effort between our lab (Computational Neurophysiology Lab, IIT Bombay) and Dr. Keith Brain's lab (Pharmacy, Pharmacology and Therapeutics, University of Birmingham), with the help of British council (UKIERI) grant, we obtained 47 intracellular recordings from the mouse detrusor smooth muscle tissue. Our investigation into these voltage signals involves identification of different types of electrical activities observable from the detrusor SMCs and developing algorithms to perform feature extraction and classification. Using our algorithms, with the help of the detected features, it was possible to automatically label the signals. The errors present in the labels were rectified using a python based tool "AP Xplore" which was developed in house. The labelled signals thus obtained are used for testing the hypotheses and draw insights about the syncytial environment in which the cells are located.