Biology subjects

Cahill, M. K.

Publications and source records attributed to Cahill, M. K..

4 recordsLinked to original sources

bioRxiv2026

Library docking for Cannabinoid-2 Receptor ligands

Cannabinoid receptors are therapeutically promising GPCRs that are also interesting test systems for structure-based methods, which have targeted them previously. Here we used the CB2 receptor as a template to explore several topical questions in library docking. Whereas an earlier campaign against the CB1 receptor led to potent but relatively non-selective ligands, here we found that targeting interactions with polar, orthosteric site residues led to subtype-selective ligands. Docking hit rate and especially hit affinity improved in moving from a 7 million to a 2.6 billion molecule library. Similar to earlier studies, docking against active and inactive states of the receptor did not reliably bias toward the discovery of agonists or inverse agonists. Cryo-EM structures of two of the new agonists, each in a different chemotype, superposed well on the docking predictions. Correspondingly, structure-based optimization led to 10- to 140-fold improvements within three different series, also consistent with well-behaved ligand families. Hit rates with a fully enumerated 2.6 billion molecule library resembled those of an implied 11 billion molecule library from a building-block method, consistent with the latters ability to explore this space, though higher affinities were discovered from the fully enumerated set. Overall, eight diverse families of ligands, with potencies <100 nM and mostly unrelated to previously known ligands were found. Implications for future studies are considered.

biochemistry↗

bioRxiv2023

Network-level encoding of local neurotransmitters in cortical astrocytes

Summary ParagraphAstrocytes--the most abundant non-neuronal cell type in the mammalian brain--are crucial circuit components that respond to and modulate neuronal activity via calcium (Ca2+) signaling1-8. Astrocyte Ca2+ activity is highly heterogeneous and occurs across multiple spatiotemporal scales: from fast, subcellular activity3,4 to slow, synchronized activity that travels across connected astrocyte networks9-11. Furthermore, astrocyte network activity has been shown to influence a wide range of processes5,8,12. While astrocyte network activity has important implications for neuronal circuit function, the inputs that drive astrocyte network dynamics remain unclear. Here we used ex vivo and in vivo two-photon Ca2+ imaging of astrocytes while mimicking neuronal neurotransmitter inputs at multiple spatiotemporal scales. We find that brief, subcellular inputs of GABA and glutamate lead to widespread, long-lasting astrocyte Ca2+ responses beyond an individual stimulated cell. Further, we find that a key subset of Ca2+ activity--propagative events--differentiates astrocyte network responses to these two major neurotransmitters, and gates responses to future inputs. Together, our results demonstrate that local, transient neurotransmitter inputs are encoded by broad cortical astrocyte networks over the course of minutes, contributing to accumulating evidence across multiple model organisms that significant astrocyte-neuron communication occurs across slow, network-level spatiotemporal scales13-15. We anticipate that this study will be a starting point for future studies investigating the link between specific astrocyte Ca2+ activity and specific astrocyte functional outputs, which could build a consistent framework for astrocytic modulation of neuronal activity.

neuroscience↗

bioRxiv2023

A Photoactivatable Norepinephrine for Probing Adrenergic Neural Circuits

Norepinephrine (NE) is a critical neuromodulator that mediates a wide range of behavior and neurophysiology, including attention, arousal, plasticity, and memory consolidation. A major source of NE is the brainstem nucleus the locus coeruleus (LC), which sends widespread projections throughout the central nervous system (CNS). Efforts to dissect this complex noradrenergic circuitry have driven the development of many tools that detect endogenous NE or modulate widespread NE release via LC activation and inhibition. While these tools have enabled research that elucidates physiological roles of NE, additional tools to probe these circuits with a higher degree of spatial precision could enable a finer delineation of function. Here, we describe the synthesis and chemical properties of a photo-activatable NE, [Ru(bpy)2(PMe3)(NE)]PF6 (RuBi-NE). We validate the one-photon (1P) release of NE using whole-cell patch clamp electrophysiology in acute mouse brain slices containing the LC. We show that a 10 ms pulse of blue light, in the presence of RuBi-NE, briefly modulates the firing rate of LC neurons via -2 adrenergic receptors. The development of a photo-activatable NE that can be released with light in the visible spectrum provides a new tool for fine-grained mapping of complex noradrenergic circuits, as well as the ability to probe how NE acts on non-neuronal cells in the CNS.

neuroscience↗

bioRxiv2018

An event-based paradigm for analyzing fluorescent astrocyte activity uncovers novel single-cell and population-level physiology

Recent work examining astrocytic physiology centers on fluorescence imaging approaches, due to development of sensitive fluorescent indicators and observation of spatiotemporally complex calcium and glutamate activity. However, the field remains hindered in fully characterizing these dynamics, both within single cells and at the population-level, because of the insufficiency of current region-of-interest-based approaches to describe activity that is often spatially unfixed, size-varying, and propagative. Here, we present a paradigm-shifting analytical framework that releases astrocyte biologists from ROI-based tools. Astrocyte Quantitative Analysis (AQuA) software enables users to take an event-based approach to accurately capture and quantify the irregular activity observed in astrocyte imaging datasets. We apply AQuA to a range of ex vivo and in vivo imaging data, and uncover previously undescribed physiological phenomena in each. Since AQuA is data-driven and based on machine learning principles, it can be applied across model organisms, fluorescent indicators, experimental modes, and imaging resolutions and speeds, enabling researchers to elucidate fundamental astrocyte physiology.

neuroscience↗