Ongoing projects

In 2013, groundbreaking research by Fukata et al. (2013), MacGillavry et al. (2013), and Nair et al. (2013) unveiled a novel molecular organization of synaptic transmission, elucidating the precise arrangement of AMPA-type glutamate receptors and PSD95 scaffolding proteins. These findings, to which we made pioneering contributions, redefine synapses as intricate assemblies of nanomachines. Disruption in the organization and regulation of these nanomachines can impair synaptic transmission fidelity, impacting overall synaptic function. Our development of state-of-the-art super-resolution imaging techniques to address this intricate organization has yielded two competing models of synaptic architecture and plasticity. One model posits relatively stable structures within nanodomains, forming a nano-quantum where the number of quanta fluctuates during plasticity or synaptic restructuring (Hoze et al., 2012; Nair et al., 2013; Venkatesan et al., 2020). The second model suggests spontaneous assembly and disassembly of molecules in the synaptic space, influenced by principles of liquid-liquid phase separation at the nanoscale, affecting quantal transmission properties without predefined associations (Rajeev et al., 2022; Dhingra et al., in preparation; Netrakanti et al., in preparation). Our immediate and long-term focus will be to dissect the anatomy of nanoconnectomics using novel microscopic and analysis tools to understand Hebbian and non-Hebbian forms of plasticity at molecular scales and how these building blocks of the synapse contribute to cognitive outcomes, learning, and behavior throughout development and aging. We believe our observations will significantly contribute to a better understanding of the developing brain in both health and disease.

In the last decade, a paradigm shift has occurred in understanding the molecular and biochemical pathways implicated in Alzheimer’s Disease (AD). It has been postulated that the early onset of dementia, as seen in AD, originates at the level of individual synapses long before the manifestation of clinical symptoms. Super-resolution microscopy imaging of excitatory synapses, combined with converging evidence from biochemistry and molecular biology, confirms the involvement of APP and secretases in its canonical processing, with major scaffolding proteins that interact with them becoming concentrated and immobilized in discrete functional domains (< 100 nm in diameter) rather than diffusely distributed in the postsynaptic density (PSD), akin to the nanomachinery involved in synaptic transmission and plasticity (Kedia & Nair, 2020; Kedia et al., 2020; Kedia et al., 2021a; Kedia et al., 2021b; Belapurkar et al., 2023). This organization of APP and secretases in nanodomains selectively alters the probability of collisions on the membrane, impacting both local and global changes in the concentration of protective and detrimental proteoforms. Empirical in-silico experiments simulate diffusional collisions between APP and secretases, influencing product formation. Our data-driven model identifies molecular determinants governing synaptic amyloidogenic processing, validated across various AD models. Thus, a nanodomain comprising APP and secretases can act as a nanomachine that creates an immediate increase in the concentration of proteoforms under optimal conditions. Our ongoing efforts additionally demonstrate that these domains are indeed structural risk factors, as they are modulated by the expression of molecular risk factors, aging, and disease conditions (Kedia et al., 2021; Belapurkar et al., 2023; Mahadevaswamy et al., submitted). Super-resolution imaging confirms the existence of discrete nanodomains of APP, β-, and γ-secretases within synapses, resembling multi-protein complexes and providing the first molecular evidence of heterogeneity in the differential proteolysis of APP at a single synapse, thus confirming the recently hypothesized model for the probabilistic origin of the disease (Frisoni et al., 2022). Our goal is to modulate the nanoscale organization to customize the next generation of 'smart drugs' that will target the pre-clinical stage of this neurodegenerative disease. To the best of our knowledge, our observations have opened an underexplored territory of degenerative disorders and provided the first evidence of a prodromal "structural risk factor." We believe that paradigms that alter the nanoscale biophysical and biochemical landscape at the level of supramolecular complexes to modulate the onset of any disease, as we are focusing on, are in their infancy and are equally exciting and challenging. 

PICALM functional regions along the cell surface trap the APP molecules. Single particle tracking of APP molecules in cells expressing SEP::APP–WT and mCherry::PICALM 

Belapurkar et al., 2023 Cellular and Molecular Life Sciences

The cytoarchitecture of a neuron plays a crucial role in defining its morphology and ultrastructure. However, evaluating the nanoscale organization of filamentous actin (F-actin) in neuronal compartments has remained challenging to date (Chazeau et al., 2014; Mondal et al., 2020). We have developed an objective paradigm for analysis that employs supervised learning to comprehend the heterogeneity in the organization of F-actin in dendritic spines of primary neuronal cultures from rodents. Through this innovative acquisition and analysis paradigm for nanoscale images, we demonstrate that the actin cytoskeleton can undergo oxidative modification, resulting in altered F-actin dynamics and the cumulative content of F-actin at the spine head (Nanguneri et al., 2019; Kommaddi et al., 2019). In collaboration with Professor Vijayalakshmi Ravindranath, we have shown that overexpressing Glutaredoxin 1 (Grx1) in the brains of these mice not only reverses F-actin loss observed in APPSwe/PS1ΔE9 mice but also restores memory recall after contextual fear conditioning. This underscores the significance of posttranslational modification of the cytoskeleton as a critical event in the early pathogenesis of Alzheimer's Disease (AD), which leads to spine loss (Kommaddi et al., 2019).

Addressing intricacies involved in the dynamic molecular organization in synapses necessitates the state-of-the-art development of minimally invasive techniques enabling the observation of synaptic changes at the resolution of individual molecules. Moreover, it entails the development of automated image analysis paradigms to process the resulting flood of data. We have been at the forefront of observing synaptic nano-organization and the regulation of key molecules during short-term plasticity (Nair et al., 2013; Hoze et al., 2012). Our extensive track record includes the development and application of various microscopy paradigms to deepen our understanding of cellular neuroscience. These innovations encompass widefield lifetime imaging employing time and space correlated single-photon counting with quadrant anode detectors (Nair et al., 2006; Jose et al., 2007, 2008), real-time single-molecule super-resolution imaging and analysis (Kechkar et al., 2012; Kedia et al., 2020), and the detection and analysis of high-density single-molecule trajectories (Nair et al., 2013; Kedia et al., 2020; Rossier et al., 2012; Chazeu et al., 2013). We have also pioneered techniques such as combining single-particle tracking with optogenetics (Tanwar et al., 2021), ensemble super-resolution imaging using stochastic fluctuations of fluorescence based on reversible binding (Venkatachalapthy et al., 2019; Koltun et al., 2020), and the integration of super-resolution, nanoscale morphometry, and supervised learning (Nanguneri et al., 2019; Kommaddi et al., 2019) and understanding liquid-liquid phase separation by first-order phase transition at the nanoscale (Rajeev et al., 2022). Additionally, our expertise extends to advanced pattern recognition and rank-order analysis of nanoscale images (Venkatesan et al., 2020; Kommaddi et al., 2019). In ongoing research, we have characterized a 2D neuromorphic detector suitable for ensemble and super-resolution microscopy to achieve a spatial resolution of around 1 nm, surpassing the diffraction limit through neuron-inspired devices, reaching the super-Heisenberg limit (Mangalwedhekar et al., 2023; Mangalwedhekar et al., In preparation).