Biology subjects

Turu, G.

Publications and source records attributed to Turu, G..

4 recordsLinked to original sources

bioRxiv2023

ArreSTick Motif is Responsible for GPCR-beta-Arrestin Binding Stability and Extends Phosphorylation-Dependent beta-arrestin Interactions to Non-Receptor Proteins

The binding and function of {beta}-arrestins are regulated by specific phosphorylation motifs present in G protein-coupled receptors (GPCRs). However, the exact arrangement of phosphorylated amino acids responsible for establishing a stable interaction remains unclear. To investigate this pattern, we employed a 1D sequence convolution model trained on a dataset of GPCRs that have established {beta}-arrestin binding properties. This approach allowed us to identify the amino acid pattern required for GPCRs to form stable interactions with {beta}-arrestins. This motif was named "arreSTick." Our data show that the model predicts the strength of the coupling between GPCRs and {beta}-arrestins with high accuracy, as well as the specific location of the interaction within the receptor sequence. Furthermore, we show that the arreSTick pattern is not limited to GPCRs, and is also present in numerous non-receptor proteins. Using a proximity biotinylation assay and mass spectrometry analysis, we demonstrate that the arreSTick motif controls the interaction between numerous non-receptor proteins and {beta}-arrestins. For example, the HIV-1 Tat Specific Factor 1 (HTSF1 or HTATSF1), a nuclear transcription factor, contains the arreSTick pattern, and our data show that its subcellular localization is influenced by its coupling to {beta}-arrestin2. Our findings unveil a broader regulatory role for {beta}-arrestins in phosphorylation-dependent interactions, extending beyond GPCRs to encompass non-receptor proteins as well.

biochemistry↗

bioRxiv2023

Receptor endocytosis orchestrates the spatiotemporal bias of β-arrestin signaling

The varying efficacy of biased and balanced agonists is generally explained by the stabilization of different active receptor conformations. In this study, systematic profiling of transducer activation of AT1 angiotensin receptor agonists revealed that the extent and kinetics of {beta}-arrestin binding exhibit substantial ligand-dependent differences, which however completely disappear upon the inhibition of receptor internalization. Even weak partial agonists for the {beta}- arrestin pathway acted as full or near full agonists, if receptor endocytosis was prevented, indicating that receptor conformation is not an exclusive determinant of {beta}-arrestin recruitment. The ligand-dependent variance in {beta}-arrestin translocation at endosomes was much larger than it was at the plasma membrane, showing that ligand efficacy in the {beta}-arrestin pathway is spatiotemporally determined. Experimental investigations and mathematical modeling demonstrated how multiple factors concurrently shape the effects of agonists on endosomal receptor-{beta}-arrestin binding and thus determine the extent of bias. Among others, ligand dissociation rate and G protein activity have particularly strong impact on receptor-{beta}-arrestin interaction, and their effects are integrated at endosomes. Our results highlight that endocytosis forms a key spatiotemporal platform for biased GPCR signaling and can aid the development of more efficacious functionally-selective compounds. One Sentence summaryAgonist-specific differences in {beta}-arrestin recruitment are mainly determined by the ligand dissociation rate and G protein activation at the endosomes.

cell biology↗

bioRxiv2017

Mapping nonapoptotic caspase activity with a transgenic reporter in mice

The protease caspase-3 is a key mediator of apoptotic programmed cell death. But weak or transient caspase activity can contribute to neuronal differentiation, axonal pathfinding, and synaptic long-term depression. Despite the importance of sublethal, or nonapoptotic, caspase activity in neurodevelopment and neural plasticity, there has been no simple method for mapping and quantifying nonapoptotic caspase activity in rodent brains. We therefore generated a transgenic mouse expressing a highly sensitive and specific fluorescent reporter of caspase activity, with peak signal localized to the nucleus. As a proof of concept, we first obtained evidence that nonapoptotic caspase activity influences neurophysiology in an amygdalar circuit. Then focusing on the amygdala, we were able to quantify a sex-specific persistent elevation in caspase activity in females after restraint stress. This simple in vivo caspase activity reporter will facilitate systems-level studies of apoptotic and nonapoptotic phenomena in behavioral and pathological models. Significance StatementCaspase-3 is an enzyme that can cause cell death when highly active but can also perform important cellular functions, such as maturation and structural changes, when only weakly or transiently active. Despite the importance of this nonlethal type of caspase activity, there is no straightforward method to measure it in live rodents. We therefore developed mice that have a fluorescent reporter that is sensitive enough to detect nonlethal caspase activity. Surprisingly, we found that weak caspase activity influences the synchrony of neuronal firing across different brain regions. We also observed increased caspase activity in female mice after severe stress. This simple caspase activity reporter can subserve multiple applications in behavior and pathology research.

neuroscience↗

bioRxiv2016

Reverse-engineering human olfactory perception from chemical features of odor molecules

Despite 25 years of progress in understanding the molecular mechanisms of olfaction, it is still not possible to predict whether a given molecule will have a perceived odor, or what olfactory percept it will produce. To address this stimulus-percept problem for olfaction, we organized the crowd-sourced DREAM Olfaction Prediction Challenge. Working from a large olfactory psychophysical dataset, teams developed machine learning algorithms to predict sensory attributes of molecules based on their chemoinformatic features. The resulting models predicted odor intensity and pleasantness with high accuracy, and also successfully predicted eight semantic descriptors (\"garlic\", \"fish\", \"sweet\", \"fruit\", \"burnt\", \"spices\", \"flower\", \"sour\"). Regularized linear models performed nearly as well as random-forest-based approaches, with a predictive accuracy that closely approaches a key theoretical limit. The models presented here make it possible to predict the perceptual qualities of virtually any molecule with an impressive degree of accuracy to reverse-engineer the smell of a molecule.\n\nOne Sentence SummaryResults of a crowdsourcing competition show that it is possible to accurately predict and reverse-engineer the smell of a molecule.

neuroscience↗