Biology subjects

Su, S.

Publications and source records attributed to Su, S..

At least 73 records · Page 4Linked to original sources

bioRxiv2021

Multiscale profiling of enzyme activity in cancer

Diverse processes in cancer are mediated by enzymes, which most proximally exert their function through their activity. Methods to quantify enzyme activity, rather than just expression, are therefore critical to our ability to understand the pathological roles of enzymes in cancer and to harness this class of biomolecules as diagnostic and therapeutic targets. Here we present an integrated set of methods for measuring specific enzyme activities across the organism, tissue, and cellular levels, which we unify into a methodological hierarchy to facilitate biological discovery. We focus on proteases for method development and validate our approach through the study of tumor progression and treatment response in an autochthonous model of Alk-mutant lung cancer. To quantitatively measure activity dynamics over time, we engineered multiplexed, peptide-based nanosensors to query protease activity in vivo. Machine learning analysis of sensor measurements revealed dramatic protease dysregulation in lung cancer, including significantly enhanced proteolytic cleavage of one peptide, S1 (Padj < 0.0001), which returned to healthy levels within three days after initiation of targeted therapy. Next, to link these organism-level observations to the in situ context, we established a multiplexed assay for on-tissue localization of enzyme activity and pinpointed S1 cleavage to endothelial cells and pericytes of the tumor vasculature. Lastly, to directly link enzyme activity measurements to cellular phenotype, we designed a high-throughput method to isolate and characterize proteolytically active cells, uncovering profound upregulation of pro-angiogenic transcriptional programs in S1-positive cells. Together, these methods allowed us to discover that protease production by angiogenic vasculature responds rapidly to targeted therapy against oncogene-addicted tumor cells, identifying a highly dynamic interplay between tumor cells and their microenvironment. This work provides a generalizable framework to functionally characterize enzyme activity in cancer.

bioengineering↗

bioRxiv2021

A positively Tuned Voltage Indicator Reveals Electrical Correlates of Calcium Activity in the Brain

Neuronal spiking activity is routinely recorded using genetically encoded calcium indicators (GECIs), but calcium imaging is limited in temporal resolution and does not report subthreshold voltage changes. Genetically encoded voltage indicators (GEVIs) offer better temporal resolution and subthreshold sensitivity, but spike detection with fast GEVIs has required specialized imaging equipment. Here, we report the ASAP4 subfamily of genetically encoded voltage indicators (GEVIs) that brighten in response to membrane depolarization, inverting the fluorescence-voltage relationship of previous ASAP GEVIs. Two variants, ASAP4b and ASAP4e, feature 128% and 178% fluorescence increases over 100-mV of depolarization, respectively, facilitating spike detection in single trials in vivo with standard 1 and 2-photon imaging systems. Simultaneous voltage and calcium imaging confirms improved temporal resolution and spike discernment by ASAP4 GEVIs. Thus, positively tuned ASAP4 voltage indicators enable recording of neuronal spiking activity using similar equipment as calcium imaging, while providing higher temporal resolution. One Sentence SummaryUpward ASAPs increase detection capability of GEVIs in vivo.

neuroscience↗

bioRxiv2021

Rapamycin attenuated zinc-induced tau phosphorylation and oxidative stress in animal model: Involvement of dual mTOR/p70S6K and Nrf2/HO-1 pathways

Alzheimers disease is pathologically featured by abnormal accumulation of amyloid-beta plaque, neurofibrillary tangles, oxidative stress, neuroinflammation, and neurodegeneration. Metal dysregulation including excessive zinc released by presynaptic neurons plays an important role in tau pathology and oxidase activation. The activities of mammalian target of rapamycin (mTOR)/ ribosomal S6 protein kinase (p70S6K) are elevated in the brains of patients with Alzheimers disease. Zinc induces tau hyperphosphorylation via mTOR/P70S6K activation in vitro. However, the involvement of mTOR/P70S6K pathway in zinc-induced oxidative stress, tau degeneration, synaptic and cognitive impairment, has not been fully elucidated in vivo. Here we assessed in the effect of pathological concentration of zinc in SH-SY5Y cells by using biochemical assays and immunofluorescence staining. Rats (n = 18, male) were lateral ventricularly-injected with zinc and treated with rapamycin (intraperitoneal injection) for one week and assessed using Morris water maze. Evaluation of the oxidative stress, tau phorsphylation and synaptic impairment were performed using the hippocampus tissue of the rats by biochemical assays and immunofluorescence staining. Results from Morris water maze showed that the capacity of spatial memory is impaired in zinc-treated rats. Zinc sulfate significantly increased the levels of P-mTOR Ser2448, P-p70S6K Thr389, and P-tau Ser356, and decreased levels of Nrf2 and HO{square}1 in SH-SY5Y cells and in zinc-treated rats compared with control groups. Increased expressions of reactive oxygen species were observed in zinc sulfate-induced SH-SY5Y cells as well as in the hippocampus of zinc-injected rats. Rapamycin, an inhibitor of mTOR, rescued the zinc-induced increases in mTOR/p70S6K activations, tau phosphorylation and oxidative stress, as well as Nrf2/HO{square}1 inactivation, cognitive impairment and synaptic impairment reduced the expression of synapse-related proteins in zinc-injected rats. In conclusion, our findings imply that rapamycin prevents zinc-induced cognitive impairment and protects neurons from tau pathology, oxidative stress and synaptic impairment, by decreasing mTOR/p70S6K hyperactivity and increasing Nrf2/HO {square} 1 activity.

neuroscience↗

bioRxiv2021

Dashboard-style interactive plots for RNA-seq analysis are R Markdown ready with Glimma 2.0

Glimma 1.0 introduced intuitive, point-and-click interactive graphics for differential gene expression analysis. Here, we present a major update to Glimma which brings improved inter-activity and reproducibility using high-level visualisation frame-works for R and JavaScript. Glimma 2.0 plots are now readily embeddable in R Markdown, thus allowing users to create reproducible reports containing interactive graphics. The revamped multidimensional scaling plot features dashboard-style controls allowing the user to dynamically change the colour, shape and size of sample points according to different experimental conditions. Interactivity was enhanced in the MA-style plot for comparing differences to average expression, which now supports selecting multiple genes, export options to PNG, SVG or CSV formats and includes a new volcano plot function. Feature-rich and user-friendly, Glimma makes exploring data for gene expression analysis more accessible and intuitive and is available on Bioconductor and GitHub.

bioinformatics↗

bioRxiv2021

Benchmarking UMI-based single cell RNA-sequencing preprocessing workflows

Single-cell RNA sequencing (scRNA-seq) technologies and associated analysis methods have undergone rapid development in recent years. This includes methods for data preprocessing, which assign sequencing reads to genes to create count matrices for downstream analysis. Several packaged preprocessing workflows have been developed that aim to provide users with convenient tools for handling this process. How different preprocessing workflows compare to one another and influence downstream analysis has been less well studied. Here, we systematically benchmark the performance of 9 end-to-end preprocessing workflows (Cell Ranger, Optimus, salmon alevin, kallisto bustools, dropSeqPipe, scPipe, zUMIs, celseq2 and scruff) using datasets with varying levels of biological complexity generated on the CEL-Seq2 and 10x Chromium platforms. We compare these workflows in terms of their quantification properties directly and their impact on normalization and clustering by evaluating the performance of different method combinations. We find that lowly expressed genes are discordant between workflows and observe that some workflows have systematic biases towards particular classes of genomics features. While the scRNA-seq preprocessing workflows compared varied in their detection and quantification of genes across datasets, after downstream analysis with performant normalization and clustering methods, almost all combinations produced clustering results that agreed well with the known cell type labels that provided the ground truth in our analysis. In summary, the choice of preprocessing method was found to be less influential than other steps in the scRNA-seq analysis process. Our study comprehensively compares common scRNA-seq preprocessing workflows and summarizes their characteristics to guide workflow users.

bioinformatics↗

bioRxiv2021

Cooperative herbivory between two important pests of rice

Normally, when different species of herbivorous arthropods feed on the same plant this leads to fitness reducing competition. We found this to be uniquely different for two of Asias most destructive rice pests, the brown planthopper and the rice striped stem borer. Both insects directly and indirectly benefit from jointly attacking the same host plant. Double infestation improved plant quality, particularly for the stemborer because the planthopper fully suppresses caterpillar-induced production of proteinase inhibitors. It also drastically reduced the risk of egg parasitism, due to diminished parasitoid attraction. Females of both pests have adapted their oviposition behaviour accordingly. Their strong preference for plants infested by the other species even overrides their avoidance of plants already attacked by conspecifics. This uncovered cooperation between herbivores is telling of the exceptional adaptations resulting from the evolution of plant-insect interactions, and points out mechanistic vulnerabilities that can be targeted to control two major pests.

ecology↗

bioRxiv2021

CD36 family members are TCR-independent ligands for CD1 antigen-presentingmolecules

CD1c presents lipid-based antigens to CD1c-restricted T cells which are thought to be a major component of the human T cell pool. The study of CD1c-restricted T cells, however, is hampered by the presence of an abundantly expressed CD1c-binding partner on blood cells distinct to the T cell receptor (TCR), confounding analysis of TCR-mediated CD1c tetramer staining. Here, we identify the CD36 family (CD36, CD36-L1 and CD36-L2) as novel ligands for CD1c, CD1b and CD1d proteins, and show that CD36 is the receptor responsible for non-TCR-mediated CD1c tetramer staining of blood cells. Moreover, CD36-blockade enables tetramer-based identification of CD1c-restricted T cells and clarifies identification of CD1b- and CD1d-restricted T cells. We use this technique to characterise CD1c-restricted T cells ex vivo and show diverse phenotypic features, TCR repertoire and antigen-specific subsets. Accordingly, this work will enable further studies into the biology of CD1 and human CD1-restricted T cells. One Sentence SummaryCD1 molecules bind CD36 family members and blockade of this interaction facilitates the study of CD1-restricted T cells.

immunology↗

bioRxiv2021

NanoMethViz: an R/Bioconductor package for visualizing long-read methylation data

MotivationA key benefit of long-read nanopore sequencing technology is the ability to detect modified DNA bases, such as 5-methylcytosine. Tools for effective visualization of data generated by this platform to assess changes in methylation profiles between samples from different experimental groups remains a challenge. ResultsTo make visualization of methylation changes more straightforward, we developed the R/Bioconductor package NanoMethViz. Our software can handle methylation calls generated from a range of different methylation callers and manages large datasets using a compressed data format. To fully explore the methylation patterns in a dataset, NanoMethViz allows plotting of data at various resolutions. At the sample-level, we use multidimensional scaling to look at the relationships between methylation profiles in an unsupervised way. We visualize methylation profiles of classes of features such as genes or CpG islands by scaling them to relative positions and aggregating their profiles. At the finest resolution, we visualize methylation patterns across individual reads along the genome using the spaghetti plot, allowing users to explore particular genes or genomic regions of interest. In summary, our software makes the handling of methylation signal more convenient, expands upon the visualization options for nanopore data and works seamlessly with existing methylation analysis tools available in the Bioconductor project. Our software is available at https://bioconductor.org/packages/NanoMethViz.

bioinformatics↗

bioRxiv2020

Analysis of Intermolt and Postmolt Transcriptomes Provides Insight into Molecular Mechanisms of the Red Swamp Crayfish, Procambarus Clarkii Molting

In the present study, we explored expression changes in the transcriptomes of two molting stages (post-molt (M) and Intermolt (NM)) of the red swamp crayfish. A total of 307608398 clean reads, with an average length of 145bp were obtained. Further clustering and assembly of the transcripts generated 139100 unigenes. The results were searched against the NCBI, NR, KEGG, Swissprot, and KOG databases, in order to annotate gene descriptions, associate them with gene ontology terms, and assign them to pathways. Several genes and other factors involved in a number of molecular events critical for molting, such as energy requirements, hormonal regulation, immune response, and exoskeleton formation were identified, evaluated, and characterized. The information presented here provides a basic understanding of the molecular mechanisms underlying the crayfish molting process, with respect to energy requirements, hormonal regulation, immune response, and skeletal related activities during post-molt stage and the intermolt stage.

genomics↗

bioRxiv2020

Cryo-EM structure of the MgtE Mg2+ channel pore domain in Mg2+-free conditions reveals cytoplasmic pore opening

MgtE is a Mg2+ channel conserved in organisms ranging from prokaryotes to eukaryotes, including humans, and plays an important role in Mg2+ homeostasis. The previously determined MgtE structures in the Mg2+-bound, closed state and structure-based functional analyses of MgtE revealed that the binding of Mg2+ ions to the MgtE cytoplasmic domain induces channel inactivation to maintain Mg2+ homeostasis. However, due to the lack of a structure of the MgtE channel, including its transmembrane domain in Mg2+-free conditions, the pore-opening mechanism of MgtE has remained unclear. Here, we determined the cryoelectron microscopy (cryo-EM) structure of the MgtE-Fab complex in the absence of Mg2+ ions. The Mg2+-free MgtE transmembrane domain structure and its comparison with the Mg2+-bound, closed-state structure, together with functional analyses, showed the Mg2+-dependent pore opening of MgtE on the cytoplasmic side and revealed the kink motions of the TM2 and TM5 helices at the glycine residues, which are important for channel activity. Overall, our work provides structure-based mechanistic insights into the channel gating of MgtE.

biophysics↗

bioRxiv2020

Comprehensive characterization of single cell full-length isoforms in human and mouse with long-read sequencing

Alternative splicing shapes the phenotype of cells in development and disease. Long-read RNA-sequencing recovers full-length transcripts but has limited throughput at the single-cell level. Here we developed single-cell full-length transcript sequencing by sampling (FLT-seq), together with the computational pipeline FLAMES to overcome these issues and perform isoform discovery and quantification, splicing analysis and mutation detection in single cells. With FLT-seq and FLAMES, we performed the first comprehensive characterization of the full-length isoform landscape in single cells of different types and species and identified thousands of unannotated isoforms. We found conserved functional modules that were enriched for alternative transcript usage in different cell populations, including ribosome biogenesis and mRNA splicing. Analysis at the transcript-level allowed data integration with scATAC-seq on individual promoters, improved correlation with protein expression data and linked mutations known to confer drug resistance to transcriptome heterogeneity. Our methods reveal previously unseen isoform complexity and provide a better framework for multi-omics data integration.

genomics↗

bioRxiv2020

Activatable zymography probes enable in situ localization of protease dysregulation in cancer

Recent years have seen the emergence of conditionally activated diagnostics and therapeutics that leverage protease-cleavable peptide linkers to enhance their specificity for cancer. However, due to a lack of methods to measure and localize protease activity directly within the tissue microenvironment, the design of protease-activated agents has been necessarily empirical, yielding suboptimal results when translated to patients. To address the need for spatially resolve d protease activity profiling in cancer, we developed a new class of in situ probes that can be applied to fresh-frozen tissue sections in a manner analogous to immunofluorescence staining. These activatable zymography probes (AZPs) detected dysregulated protease activity in human prostate cancer biopsy samples, enabling disease classification. We then leveraged AZPs within a generalizable framework to design conditional cancer diagnostics and therapeutics, and demonstrated the power of this approach in the Hi-Myc mouse model of prostate cancer, which models features of early pathogenesis. Multiplexed screening against barcoded substrates yielded a peptide, S16, that was robustly and specifically cleaved by tumor-associated metalloproteinases in the Hi-Myc model. In situ labeling with an AZP incorporating S16 revealed a potential role of metalloproteinase dysregulation in proliferative, pre-malignant Hi-Myc prostatic glands. Last, we incorporated S16 into an in vivo imaging probe that, after systemic administration, perfectly classified diseased and healthy prostates, supporting the relevance of ex vivo activity assays to in vivo translation. We envision AZPs will enable new insights into the biology of protease dysregulation in cancer and accelerate the development of conditional diagnostics and therapeutics for multiple cancer types.

bioengineering↗

bioRxiv2020

Immune Classification of Clear Cell Renal Cell Carcinoma

ABSTRACTSince the outcome of treatments, particularly immunotherapeutic interventions, depends on the tumor immune micro-environment (TIM), several experimental and computational tools such as flow cytometry, immunohistochemistry, and digital cytometry have been developed and utilized to classify TIM variations. In this project, we identify immune pattern of clear cell renal cell carcinomas (ccRCC) by estimating the percentage of each immune cell type in 526 renal tumors using the new powerful technique of digital cytometry. The results, which are in agreement with the results of a large-scale mass cytometry analysis, show that the most frequent immune cell types in ccRCC tumors are CD8+ T-cells, macrophages, and CD4+ T-cells. Saliently, unsupervised clustering of ccRCC primary tumors based on their relative number of immune cells indicates the existence of four distinct groups of ccRCC tumors. Tumors in the first group consist of approximately the same numbers of CD8+ T-cells, CD4+ T-cells, and macrophages, while tumors in the second group have a significantly high number of macrophages compared to any other immune cell type (P-value< 0.01). The third group of ccRCC tumors have a significantly higher number of CD8+ T-cells than any other immune cell type (P-value< 0.01), while tumors in the group 4 have approximately the same numbers of macrophages and CD4+ T-cells and a significantly smaller number of CD8+ T-cells than CD4+ T-cells (P-value< 0.01). Moreover, there is a high positive correlation between the expression levels of IFNG and PDCD1 and the percentage of CD8+ T-cells, and higher stage and grade of tumors have a substantially higher percentage of CD8+ T-cells. Furthermore, the primary tumors of patients, who are tumor free at the last time of follow up, have a significantly higher percentage of mast cells (P-value< 0.01) compared to the patients with tumors for all groups of tumors except group 3.Competing Interest StatementThe authors have declared no competing interest.View Full Text

cancer biology↗

bioRxiv2020

The long and the short of it: unlocking nanopore long-read RNA sequencing data with short-read tools

Application of Oxford Nanopore Technologies long-read sequencing platform to transcriptomic analysis is increasing in popularity. However, such analysis can be challenging due to small library sizes and high sequence error, which decreases quantification accuracy and reduces power for statistical testing. Here, we report the analysis of two nanopore sequencing RNA-seq datasets with the goal of obtaining gene-level and isoform-level differential expression information. A dataset of synthetic, spliced, spike-in RNAs ("sequins") as well as a mouse neural stem cell dataset from samples with a null mutation of the epigenetic regulator Smchd1 were analysed using a mix of long-read specific tools for preprocessing together with established short-read RNA-seq methods. We used limma-voom to perform differential gene expression analysis, and the novel FLAMES pipeline to perform isoform identification and quantification, followed by DRIMSeq and limma-diffSplice (with stageR) to perform differential transcript usage analysis. We compared results from the sequins dataset to the ground truth, and results of the mouse dataset to a previous short-read study on equivalent samples. Overall, our work shows that transcriptomic analysis of long-read nanopore data using short-read software and methods that are already in wide use can yield meaningful results.

bioinformatics↗

bioRxiv2020

Comparison of SARS-CoV-2 spike protein binding to human, pet, farm animals, and putative intermediate hosts ACE2 and ACE2 receptors

The emergence of a novel coronavirus, SARS-CoV-2, resulted in a pandemic. Here, we used recently released X-ray structures of human ACE2 bound to the receptor-binding domain (RBD) of the spike protein (S) from SARS-CoV-2 to predict its binding to ACE2 proteins from different animals, including pets, farm animals, and putative intermediate hosts of SARS-CoV-2. Comparing the interaction sites of ACE2 proteins known to serve or not serve as receptor allows to define residues important for binding. From the 20 amino acids in ACE2 that contact S up to seven can be replaced and ACE2 can still function as the SARS-CoV-2 receptor. These variable amino acids are clustered at certain positions, mostly at the periphery of the binding site, while changes of the invariable residues prevent S-binding or infection of the respective animal. Some ACE2 proteins even tolerate the loss or the acquisition of N-glycosylation sites located near the S-interface. Of note, pigs and dogs which are not or not effectively infected, respectively, have only a few changes in the binding site have relatively low levels of ACE2 in the respiratory tract. Comparison of the RBD of S of SARS-CoV-2 with viruses from bat and pangolin revealed that the latter contains only one substitution, whereas the bat virus exhibits five. However, ACE2 of pangolin exhibit seven changes relative to human ACE2, a similar number of substitutions is present in ACE2 of bats, raccoon, and civet suggesting that SARS-CoV-2 may not especially adapted to ACE2 of any of its putative intermediate hosts. These analyses provide new insight into the receptor usage and animal source/origin of SARS-COV-2. IMPORTANCESARS-CoV-2 is threatening people worldwide and there are no drugs or vaccines available to mitigate its spread. The origin of the virus is still unclear and whether pets and livestock can be infected and transmit SARS-CoV-2 are important and unknown scientific questions. Effective binding to the host receptor ACE2 is the first prerequisite for infection of cells and determines the host range. Our analysis provides a framework for the prediction of potential hosts of SARS-CoV-2. We found that ACE2 from species known to support SARS-CoV-2 infection tolerate many amino acid changes indicating that the species barrier might be low. However, the lower expression of ACE2 in the upper respiratory tract of some pets and livestock means more research and monitoring should be done to explore the animal source of infection and the risk of potential cross-species transmission. Finally, the analysis also showed that SARS-CoV-2 may not specifically adapted to any of its putative intermediate hosts.

bioinformatics↗

bioRxiv2020

Accurate Diagnosis of Colorectal Cancer Based on Histopathology Images Using Artificial Intelligence

BackgroundAccurate and robust pathological image analysis for colorectal cancer (CRC) diagnosis is time-consuming and knowledge-intensive, but is essential for CRC patients treatment. The current heavy workload of pathologists in clinics/hospitals may easily lead to unconscious misdiagnosis of CRC based on their daily image analyses. MethodsBased on a state-of-the-art transfer-learned deep convolutional neural network in artificial intelligence (AI), we proposed a novel patch aggregation strategy for clinic CRC prediction/diagnosis using weakly labeled pathological whole slide image (WSI) patches. This approach was trained and validated using an unprecedented and enormously large number of 170,099 patches, >14,680 WSIs, from >9,631 subjects that covered diverse and representative clinical cases from multi-independent-sources across China, U.S., and Germany. ResultsOur innovative AI tool was consistently nearly perfectly agreed with (average Kappa-statistic 0.896) and even often better than most of the experienced expert pathologists when tested in diagnosing CRC WSIs from multi-centers. The average area under the receiver operating characteristics curve (AUC) of AI was greater than that of the pathologists (0.981 vs 0.970) and achieved the best performance among the application of other AI methods to CRC diagnosis. Our AI-generated heatmap highlights the image regions of cancer tissue/cells. ConclusionsThis first-ever generalizable AI system can handle large amounts of WSIs consistently and robustly without potential bias due to fatigue commonly experienced by clinical pathologists. Hence, it will drastically alleviate the heavy clinical burden of daily pathology diagnosis, and improve the treatment for CRC patients. This tool is generalizable to other cancer diagnosis based on image recognition.

pathology↗

bioRxiv2019

Enzalutamide-induced PTH1R-mediated TGFBR2 decrease in osteoblasts contributes to resistance in bone-metastatic prostate cancer

Over 80% of prostate cancer (PCa) patients in the United States die with bone metastases. Second-line hormonal therapies, such as enzalutamide, improve overall survival in about 50% of patients with bone metastases, but almost all responsive patients eventually develop enzalutamide resistance. Our study showed that although enzalutamide significantly inhibited the tumor growth of subcutaneously or orthotopically grafted PCa C4-2B cells, it had no effect on the bone lesion development when C4-2B tumors were grafted in the bone, suggesting a crucial role of the microenvironment in enzalutamide resistance in PCa bone metastasis. We found that enzalutamide significantly decreased the amount of the TGFBR2 (TGF-{beta} type II receptor) in osteoblasts, both in vitro and in patient samples. The osteoblast-specific knockout of Tgfbr2 significantly induced bone metastasis. We showed that the enzalutamide-induced TGFBR2 decrease in osteoblasts was mediated by increased PTH1R (parathyroid hormone/parathyroid hormone-related peptide receptor), which resulted in TGFBR2 degradation, and that blocking PTH1R rescued the TGFBR2 decrease. Furthermore, we found that PTH1R up-regulation by enzalutamide was correlated with increased Pth1r promoter occupancy by transcription factor NR2F1. Our findings highlight a potential enzalutamide-resistance mechanism through TGFBR2 decrease in osteoblasts, thus suggesting future PTH1R-blocking approaches to overcome enzalutamide resistance in PCa bone metastasis.

cancer biology↗

bioRxiv2019

Gi-Coupled Receptor Activation Potentiates Piezo2 Currents via Gβγ

SUMMARYDysregulation of mechanosensitive Piezo2 channels is a hallmark of mechanical allodynia, yet the cellular mechanisms that sensitize mechanoreceptors are still poorly understood. Activation of Gi-coupled receptors sensitizes Piezo2 currents, but whether Gi-coupled receptors regulate the activity of Piezo2 channels is not known. Here, we found that activation of Gi-coupled receptors potentiates Piezo2 currents in dorsal root ganglion (DRG) neurons and in heterologous systems, but inhibits Piezo1 currents in heterologous systems. The potentiation, or inhibition of Piezo currents is abolished when blocking G{beta}{gamma} with the c-terminal domain of the beta-adrenergic kinase ({beta}ARKct). Pharmacological inhibition of kinases downstream of G{beta}{gamma}, phosphoinositide 3-kinase (PI3K) and mitogen-activated protein kinase (MAPK), also abolished the potentiation of Piezo2 currents. Hence, our studies illustrate an indirect mechanism of action of G{beta}{gamma} to sensitize Piezo2 currents after activation of Gi-coupled receptors.

neuroscience↗