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Nguyen, T.

Publications and source records attributed to Nguyen, T..

At least 235 records · Page 13Linked to original sources
bioRxiv2020

TINC - a method to dissect transcriptional complexes at single locus resolution - reveals novel Nanog regulators in mouse embryonic stem cells

Cellular identity is ultimately controlled by transcription factors (TFs), which bind to specific regulatory elements (REs) within the genome to regulate gene expression and cell fate changes. While recent advances in genome-wide epigenetic profiling techniques have significantly increased our understanding of which REs are utilized in which cell type, it remains largely unknown which TFs and cofactors interact with these REs to modulate gene expression. A major hurdle in dissecting the whole composition of a multi-protein complex formed at a specific RE is the shortage of appropriate techniques. We have developed a novel method termed TALE-mediated Isolation of Nuclear Chromatin (TINC). TINC utilizes epitope-tagged TALEs to isolate a specific genomic region from the mammalian genome and includes a nuclei isolation and chromatin enrichment step for increased specificity. Upon cross-linking of the cells and isolation of the chromatin, the target region is purified based on affinity purification of the TALE and associated nucleic acid and protein molecules can be subjected to further analyses. A key TF in the pluripotency network and therefore in embryonic stem cells (ESCs) is NANOG. It is currently not fully understood how Nanog expression is regulated and consequently it remains unclear how the ESC state is maintained. Using TINC we dissected the protein complex formed at the Nanog promoter in mouse ESCs and identified many known and numerous novel factors.

genomics↗
bioRxiv2020

Self-cutting and integrating CRISPR plasmids (SCIPs) enable targeted genomic integration of large genetic payloads for rapid cell engineering

Since observations that CRISPR nucleases function in mammalian cells, many strategies have been devised to adapt them for genetic engineering. Here, we investigated self-cutting and integrating CRISPR-Cas9 plasmids (SCIPs) as easy-to-use gene editing tools that insert themselves at CRISPR-guided locations. SCIPs demonstrated similar expression kinetics and gene disruption efficiency in mouse (EL4) and human (Jurkat) cells, with stable integration in 3-6% of transfected cells. Clonal sequencing analysis indicated that integrants showed bi- or mono-allelic integration of entire CRISPR plasmids in predictable orientations and with limited indel formation. Interestingly, including longer homology arms (HAs) (500 bp) in varying orientations only modestly increased knock-in efficiency ([~]2-fold). Using a SCIP-payload design (SCIPpay) which liberates a promoter-less sequence flanked by HAs thereby requiring perfect homology-directed repair (HDR) for transgene expression, longer HAs resulted in higher integration efficiency and precision of the payload but did not affect integration of the remaining plasmid sequence. As proofs-of-concept, we used SCIPpay to 1) insert a gene fragment encoding tdTomato into the CD69 locus of Jurkat cells, thereby creating a cell line that reports T cell activation, and 2) insert a chimeric antigen receptor (CAR) gene into the TRAC locus. Here, we demonstrate that SCIPs function as simple, efficient, and programmable tools useful for generating gene knock-out/knock-in cell lines and suggest future utility in knock-in site screening/optimization, unbiased off-target site identification, and multiplexed, iterative, and/or library-scale automated genome engineering.

bioengineering↗
bioRxiv2020

Dentate gyrus population activity during immobility drives formation of precise memories

The hippocampal dentate gyrus is an important relay conveying sensory information from the entorhinal cortex to the hippocampus proper. During exploration, the dentate gyrus has been proposed to act as a pattern separator. However, the dentate gyrus also shows structured activity during immobility and sleep. The properties of these activity patterns at cellular resolution, and their role in hippocampal-dependent memory processes have remained unclear. Using dual-color in-vivo two-photon Ca2+ imaging, we show that in immobile mice dentate granule cells generate sparse, synchronized activity patterns associated with entorhinal cortex activation. These population events are structured and modified by changes in the environment; and they incorporate place- and speed cells. Importantly, they recapitulate population patterns evoked during self-motion. Using optogenetic inhibition during immobility, we show that granule cell activity during immobility is required to form dentate gyrus-dependent spatial memories. These data suggest that memory formation is supported by dentate gyrus replay of population codes of the current environment.

neuroscience↗
bioRxiv2020

Chemokine Signatures Of Pathogen-Specific T Cells I: Effector T Cells

The choreography of complex immune responses, including the priming, differentiation, and modulation of specific effector T cell populations generated in the immediate wake of an acute pathogen challenge, is in part controlled by chemokines, a large family of mostly secreted molecules involved in chemotaxis and other patho/physiological processes. T cells are both responsive to varied chemokine cues and a relevant source for certain chemokines themselves. Yet the actual range, regulation, and role of effector T cell-derived chemokines remains incompletely understood. Here, using different in vivo models of viral and bacterial infection as well as protective vaccination, we have defined the entire spectrum of chemokines produced by pathogen-specific CD8+ and CD4+T effector cells, and delineated several unique properties pertaining to the temporospatial organization of chemokine expression patterns, synthesis and secretion kinetics, and cooperative regulation. Collectively, our results position the "T cell chemokine response" as a notably prominent, largely invariant yet distinctive force at the forefront of pathogen-specific effector T cell activities, and establish novel practical and conceptual approaches that may serve as a foundation for future investigations into role of T cell-produced chemokines in infectious and other diseases.

immunology↗
bioRxiv2020

Quantitative trait loci mapped for TCF21 binding, chromatin accessibility and chromosomal looping in coronary artery smooth muscle cells reveal molecular mechanisms of coronary disease loci

BackgroundTo investigate the epigenetic and transcriptional mechanisms of coronary artery disease (CAD) risk, as well as the functional regulation of chromatin structure and function, we have created a catalog of genetic variants associated with three stages of transcriptional cis-regulation in primary human coronary artery vascular smooth muscle cells (HCASMC). ResultsTo this end, we have used a pooling approach with HCASMC lines to map regulatory variation that mediates binding of the CAD associated transcription factor TCF21 with ChIPseq studies (bQTLs), variation that regulates chromatin accessibility with ATACseq studies (caQTLs), and chromosomal looping with HiC methods (clQTLs). We show significant overlap of the QTLs, and their relationship to smooth muscle specific genes and the binding of smooth muscle transcription factors. Further, we use multiple analyses to show that these QTLs are highly associated with CAD GWAS loci and correlated to lead SNPs in these loci where they show allelic effects. We have verified with genome editing that identified functional variants can regulate both chromatin accessibility and chromosomal looping, providing new insights into functional mechanisms regulating chromatin state and chromosomal structure. Finally, we directly link the disease associated TGF{beta}1-SMAD3 pathway to the CAD associated FN1 gene through a response QTL that modulates both chromatin accessibility and chromosomal looping. ConclusionsTogether, these studies represent the most thorough mapping of multiple QTL types in a highly disease relevant primary cultured cell type, and provide novel insights into their functional overlap and mechanisms that underlie these genomic features and their relationship to disease risk.

genomics↗
bioRxiv2020

Reconstruction of motor control circuits in adult Drosophila using automated transmission electron microscopy

Many animals use coordinated limb movements to interact with and navigate through the environment. To investigate circuit mechanisms underlying locomotor behavior, we used serial-section electron microscopy (EM) to map synaptic connectivity within a neuronal network that controls limb movements. We present a synapse-resolution EM dataset containing the ventral nerve cord (VNC) of an adult female Drosophila melanogaster. To generate this dataset, we developed GridTape, a technology that combines automated serial-section collection with automated high-throughput transmission EM. Using this dataset, we reconstructed 507 motor neurons, including all those that control the legs and wings. We show that a specific class of leg sensory neurons directly synapse onto the largest-caliber motor neuron axons on both sides of the body, representing a unique feedback pathway for fast limb control. We provide open access to the dataset and reconstructions registered to a standard atlas to permit matching of cells between EM and light microscopy data. We also provide GridTape instrumentation designs and software to make large-scale EM data acquisition more accessible and affordable to the scientific community.

neuroscience↗
bioRxiv2019

Automatic Detection of Synaptic Partners in a Whole-Brain Drosophila EM Dataset

The study of neural circuits requires the reconstruction of neurons and the identification of synaptic connections between them. To scale the reconstruction to the size of whole-brain datasets, semi-automatic methods are needed to solve those tasks. Here, we present an automatic method for synaptic partner identification in insect brains, which uses convolutional neural networks to identify post-synaptic sites and their pre-synaptic partners. The networks can be trained from human generated point annotations alone and require only simple post-processing to obtain final predictions. We used our method to extract 244 million putative synaptic partners in the fifty-teravoxel full adult fly brain (FAFB) electron microscopy (EM) dataset and evaluated its accuracy on 146,643 synapses from 702 neurons with a total cable length of 312 mm in four different brain regions. The predicted synaptic connections can be used together with a neuron segmentation to infer a connectivity graph with high accuracy: between 92% and 96% of edges linking connected neurons are correctly classified as weakly connected (less than five synapses) and strongly connected (at least five synapses). Our synaptic partner predictions for the FAFB dataset are publicly available, together with a query library allowing automatic retrieval of up- and downstream neurons.

neuroscience↗
bioRxiv2019

Predicting cellular position in the Drosophila embryo from Single-Cell Transcriptomics data

Single-cell RNA-seq technologies are rapidly evolving but while very informative, in standard scRNAseq experiments the spatial organization of the cells in the tissue of origin is lost. Conversely, spatial RNA-seq technologies designed to keep the localization of the cells have limited throughput and gene coverage. Mapping scRNAseq to genes with spatial information increases coverage while providing spatial location. However, methods to perform such mapping have not yet been benchmarked. To bridge the gap, we organized the DREAM Single-Cell Transcriptomics challenge focused on the spatial reconstruction of cells from the Drosophila embryo from scRNAseq data, leveraging as gold standard genes with in situ hybridization data from the Berkeley Drosophila Transcription Network Project reference atlas. The 34 participating teams used diverse algorithms for gene selection and location prediction, while being able to correctly localize rare subpopulations of cells. Selection of predictor genes was essential for this task and such genes showed a relatively high expression entropy, high spatial clustering and the presence of prominent developmental genes such as gap and pair-ruled genes and tissue defining markers.

systems biology↗
bioRxiv2019

Fast and precise single-cell data analysis using hierarchical autoencoder

A primary challenge in single-cell RNA sequencing (scRNA-seq) studies comes from the massive amount of data and the excess noise level. To address this challenge, we introduce a hierarchical autoencoder that reliably extracts representative information of each cell. In an extensive analysis, we demonstrate that the approach vastly outperforms state-of-the-art techniques in many research sub-fields of scRNA-seq analysis, including cell segregation through unsupervised learning, visualization of transcriptome landscape, cell classification, and pseudo-time inference.

bioinformatics↗
bioRxiv2019

SIDT2 RNA transporter promotes lung and gastrointestinal tumor development

RNautophagy is a newly-described type of selective autophagy whereby cellular RNAs are transported into lysosomes for degradation. This process involves the transmembrane protein SIDT2, which transports double-stranded RNA (dsRNA) across the endolysosomal membrane. We previously demonstrated that SIDT2 is a transcriptional target of p53, but its role in tumorigenesis - if any - is unclear. Unexpectedly, we show here that Sidt2-/- mice with concurrent oncogenic KrasG12D activation develop significantly fewer tumors than littermate controls in a mouse model of lung adenocarcinoma (LUAD). Consistent with this observation, loss of SIDT2 also leads to enhanced survival and delayed tumor development in an Apcmin/+ mouse model of intestinal cancer. Within the intestine, Apcmin/+;Sidt2-/- mice display accumulation of dsRNA in association with increased phosphorylation of eIF2 and JNK as well as elevated rates of apoptosis. Taken together, our data demonstrate a role for SIDT2 - and by extension RNautophagy - in promoting tumor development.

cancer biology↗
bioRxiv2019

Dynamic changes in RNA-chromatin interactome promote endothelial dysfunction

Chromatins are pervasively attached by RNAs. Here, we asked whether global RNA-chromatin contacts are altered in a given cell type in a disease context, and whether these alterations impact gene expression and cell function. In endothelial cells (ECs) treated by high-glucose and TNF, we employed single-cell RNA-sequencing and in situ mapping of RNA-genome interaction (iMARGI) assay to delineate temporal changes in transcriptome and RNA-chromatin interactome. ECs displayed dramatic and heterogeneous changes in single cell transcriptome, accompanied by a dynamic and strong increase in inter-chromosomal RNA-DNA interactions, particularly among super enhancers (SEs). These SEs overlap with genes contributing to inflammatory response and endothelial mesenchymal transition (EndoMT), two key aspects of endothelial dysfunction. Perturbation of a high-glucose and TNF-activated interaction involving SEs overlapping LINC00607 and SERPINE1 attenuated the pro-inflammatory and pro-EndoMT gene induction and EC dysfunction. Our findings highlight RNA-chromatin contacts as a crucial regulatory feature in biological and disease processes, exemplified by endothelial dysfunction, a major mediator of numerous diseases.

genomics↗
bioRxiv2019

GraphDTA: prediction of drug-target binding affinity using graph convolutional networks

The development of new drugs is costly, time consuming, and often accompanied with safety issues. Drug repurposing can avoid the expensive and lengthy process of drug development by finding new uses for already approved drugs. In order to repurpose drugs effectively, it is useful to know which proteins are targeted by which drugs. Computational models that estimate the interaction strength of new drug--target pairs have the potential to expedite drug repurposing. Several models have been proposed for this task. However, these models represent the drugs as strings, which is not a natural way to represent molecules. We propose a new model called GraphDTA that represents drugs as graphs and uses graph neural networks to predict drug--target affinity. We show that graph neural networks not only predict drug--target affinity better than non-deep learning models, but also outperform competing deep learning methods. Our results confirm that deep learning models are appropriate for drug--target binding affinity prediction, and that representing drugs as graphs can lead to further improvements. Availability of data and materialsThe proposed models are implemented in Python. Related data, pre-trained models, and source code are publicly available at https://github.com/thinng/GraphDTA. All scripts and data needed to reproduce the post-hoc statistical analysis are available from https://doi.org/10.5281/zenodo.3603523. ContactThin.Nguyen@deakin.edu.au

bioinformatics↗
bioRxiv2019

Detecting Direct Oral Anticoagulants in Trauma Patients using Liquid Chromatography-Mass Spectrometry: a Novel Approach to Medication Reconciliation

BackgroundAccurate medication reconciliation in trauma patients is essential but difficult. Currently there is no established clinical method of detecting direct oral anticoagulants (DOACs) in trauma patients. We hypothesized that a liquid chromatography-mass spectrometry (LCMS) based assay can be used to accurately detect DOACs in trauma patients upon hospital arrival.\n\nMethodsPlasma samples were collected from 356 patients who provided informed consent including-10 healthy controls, 19 known positive or negative controls and 327 trauma patients over 65 years of age who were evaluated at our large, urban Level 1 Trauma Center. The assay methodology was developed in healthy and known controls to detect apixaban, rivaroxaban and dabigatran using LCMS and then applied to 327 samples from trauma patients. Standard medication reconciliation processes in the electronic medical record documenting DOAC usage was compared with LCMS results to determine overall accuracy, sensitivity, specificity and positive and negative predictive values (PPV, NPV) of the assay.\n\nResultsOf 356 patients, 39 were on DOACs (10.96%): 21 were on Apixaban, 14 on rivaroxaban and 4 on dabigatran. The overall accuracy of the assay for detecting any DOAC was 98.60%, with a sensitivity of 94.87% and specificity of 99.06%, (PPV 92.50% and NPV 99.37%). The assay detected apixaban with a sensitivity of 90.48% and specificity of 99.11% (PPV 86.36% and NPV 99.40%). There were three false positive results and two false negative LCMS results for apixaban. Dabigatran and rivaroxaban were detected with 100% sensitivity and specificity.\n\nConclusionsThis LCMS-based assay was highly accurate in detecting DOACs in trauma patients. Further studies need to confirm the clinical efficacy of this LCMS assay and its value for medication reconciliation in trauma patients.\n\nStudy type: diagnostic test\n\nBasic Science paper: therefore does not require a level of evidence.

pharmacology and toxicology↗
bioRxiv2019

Evolution and expansion of multidrug resistant malaria in Southeast Asia: a genomic epidemiology study

BackgroundA multidrug resistant co-lineage of Plasmodium falciparum malaria, named KEL1/PLA1, spread across Cambodia c.2008-2013, causing high treatment failure rates to the frontline combination therapy dihydroartemisinin-piperaquine. Here, we report on the evolution and spread of KEL1/PLA1 in subsequent years.\n\nMethodsWe analysed whole genome sequencing data from 1,673 P. falciparum clinical samples collected in 2008-2018 from northeast Thailand, Laos, Cambodia and Vietnam. By investigating genome-wide relatedness between parasites, we inferred patterns of shared ancestry in the KEL1/PLA1 population.\n\nFindingsKEL1/PLA1 spread rapidly from 2015 into all of the surveyed countries and now exceeds 80% of the P. falciparum population in several regions. These parasites maintained a high level of genetic relatedness reflecting their common origin. However, several genetic subgroups have recently emerged within this co-lineage with diverse geographical distributions. Some of these emerging KEL1/PLA1 subgroups carry recent mutations in the chloroquine resistance transporter (crt) gene, which arise on a specific genetic background comprising multiple genomic regions.\n\nInterpretationAfter emerging and circulating for several years within Cambodia, the P. falciparum KEL1/PLA1 co-lineage diversified into multiple subgroups and acquired new genetic features including novel crt mutations. These subgroups have rapidly spread into neighbouring countries, suggesting enhanced fitness. These findings highlight the urgent need for elimination of this increasingly drug-resistant parasite co-lineage, and the importance of genetic surveillance in accelerating elimination efforts.\n\nFundingWellcome Trust, Bill & Melinda Gates Foundation, UK Medical Research Council, UK Department for International Development.\n\nResearch in context O_TEXTBOXEvidence before this studyThis study updates our previous work describing the emergence and spread of a multidrug resistant P. falciparum co-lineage (KEL1/PLA1) within Cambodia up to 2013. Since then, a regional genetic surveillance project, GenRe-Mekong, has reported that markers of dihydroartemisinin-piperaquine (DHA-PPQ) resistance have increased in frequency in neighbouring countries. A PubMed search (terms: \"artemisinin\", \"piperaquine\", \"resistance\", \"southeast asia\") for articles listed since our previous study (from 30/10/2017 to 05/01/2019) yielded 28 results, including reports of a recent sharp decline in DHA-PPQ clinical efficacy in Vietnam; the spread of genetic markers of DHA-PPQ resistance into neighbouring countries by Imwong and colleagues; and multiple reports associating mutations in the crt gene with piperaquine resistance, including newly emerging crt variants in Southeast Asia.\n\nAdded value of this studyWe analysed P. falciparum whole genomes collected up to early 2018 from Eastern Southeast Asia (Cambodia and surrounding regions), describing the fine-scale epidemiology of multiple KEL1/PLA1 genetic subgroups that have spread out from Cambodia since 2015 and taken over indigenous parasite populations in northeastern Thailand, southern and central Vietnam and parts of southern Laos. Several newly emerging crt mutations accompanied the spread and expansion of KEL1/PLA1 subgroups, suggesting an active proliferation of biologically fit, multidrug resistant parasites.\n\nImplications of all the available evidenceThe problem of P. falciparum multidrug resistance has dramatically worsened in Eastern Southeast Asia since previous reports. KEL1/PLA1 has diversified and spread widely across Eastern Southeast Asia since 2015, becoming the predominant parasite group in several regions. This may have been fuelled by continued parasite exposure to DHA-PPQ, resulting in sustained selection after KEL1/PLA1 became established. Continued drug pressure enabled the acquisition of further mutations, resulting in higher levels of resistance. These data demonstrate the value of pathogen genetic surveillance and the urgent need to eliminate these dangerous parasites.\n\nC_TEXTBOX

epidemiology↗
bioRxiv2019

A genome-wide screen for ER autophagy highlights key roles of mitochondrial metabolism and ER- resident UFMylation

Selective degradation of organelles via autophagy is critical for cellular differentiation, homeostasis, and organismal health. Autophagy of the ER (ER-phagy) is implicated in human neuropathy but is poorly understood beyond a few specialized autophagosomal receptors and remodelers. Using an ER-phagy reporter and genome-wide CRISPRi screening, we identified 200 high-confidence factors involved in human ER-phagy. We mechanistically investigated two pathways unexpectedly required for ER-phagy. First, reduced mitochondrial metabolism represses ER-phagy, which reverses the logic of general autophagy. Mitochondrial crosstalk with ER-phagy bypasses the energy sensor AMPK, instead directly impacting ULK1. Second, ER-localized UFMylation is required for ER-phagy that represses the unfolded protein response. The UFL1 ligase is brought to the ER surface by DDRGK1, analogous to PINK1-Parkin regulation during mitophagy. Our data provide insight into the unique cellular logic of ER-phagy, reveal parallels between organelle autophagies, and provide an entry point to the relatively unexplored process of degrading the ER network.

cell biology↗
bioRxiv2019

Personalized Annotation-based Networks (PAN) for the Prediction of Breast Cancer Relapse

The classification of clinical samples based on gene expression data is an important part of precision medicine. However, it has proved difficult to accurately predict survival outcomes and treatment responses for cancer patients. In this manuscript, we show how transforming gene expression data into a set of personalized (sample-specific) networks can allow us to harness existing graph-based methods to improve classifier performance. Existing approaches to personalized gene networks all have the limitation that they depend on other samples in the data and must get re-computed whenever a new sample is introduced. Here, we propose a novel method, called Personalized Annotation-based Networks (PAN), that avoids this limitation by using curated annotation databases to transform gene expression data into a graph. These databases organize genes into overlapping gene sets, called annotations, that we use to build a network where nodes represent functional terms and edges represent the similarity between them. Unlike competing methods, PANs are calculated for each sample independent of the population, making it a more efficient way to obtain single-sample networks. Using three breast cancer datasets as a case study (METABRIC and a super-set of GEO studies), we show that PAN classifiers not only predict cancer relapse better than gene features alone, but also outperform PPI and population-level graph-based classifiers. This work demonstrates the practical advantages of graph-based classification for high-dimensional genomic data, while offering a new approach to making sample-specific networks. Supplementary informationThe codes and data are available at https://github.com/thinng/PAN. ContactThuc.Le@unisa.edu.au

bioinformatics↗
bioRxiv2019

Corazonin neuroendocrine pathway orchestrates stress-associated physiology in Drosophila

Environmental factors challenge the physiological homeostasis in animals, thereby evoking stress responses. Various mechanisms have evolved to counter stress at the organism level, including regulation by neuropeptides. In recent years, much progress has been made on the mechanisms and neuropeptides that regulate responses to metabolic/nutritional stress, as well as those involved in countering osmotic and ionic stresses. Here, we identified a peptidergic pathway that links these types of regulatory functions. We uncover the neuropeptide Corazonin (Crz), previously implicated in responses to metabolic stress, as a neuroendocrine factor that inhibits the release of a diuretic hormone, CAPA, and thereby modulates the tolerance to osmotic and ionic stress. Both knockdown of Crz and acute injections of Crz peptide impact desiccation tolerance and recovery from chill-coma. Mapping of the Crz receptor (CrzR) expression identified three pairs of Capa-expressing neurons (Va neurons) in the ventral nerve cord that mediate these effects of Crz. We show that Crz acts to restore water/ion homeostasis by inhibiting release of CAPA neuropeptides via inhibition of cAMP production in Va neurons. Knockdown of CrzR in Va neurons affects CAPA signaling, and consequently increases tolerance for desiccation, ionic stress and starvation, but delays chill-coma recovery. Optogenetic activation of Va neurons stimulates excretion and simultaneous activation of Crz and CAPA-expressing neurons reduces this response, supporting the inhibitory action of Crz. Thus, Crz inhibits Va neurons to maintain osmotic and ionic homeostasis, which in turn affects stress tolerance. Earlier work demonstrated that systemic Crz signaling restores nutrient levels by promoting food search and feeding. Here we additionally propose that Crz signaling also ensures osmotic homeostasis by inhibiting release of CAPA neuropeptides and suppressing diuresis. Thus, Crz ameliorates stress-associated physiology through systemic modulation of both peptidergic neurosecretory cells and the fat body in Drosophila. Author summaryInsects are among the largest groups of animals and have adapted to inhabit almost all environments on Earth. Their success in surviving extreme conditions stems largely from their ability to withstand environmental stress, such as desiccation and cold. However, the neural mechanisms that are responsible for coordinating responses to counter these stresses are largely unknown. To address this, we delineate a neuroendocrine axis utilizing the neuropeptides Corazonin (Crz) and CAPA, that coordinate responses to metabolic and osmotic stress. We show that Crz inhibits the release of a diuretic peptide, CAPA from a set of neurosecretory cells. CAPA in turn influences osmotic and ionic balance via actions on the Malpighian tubules (the insect analogs of the kidney) and the intestine. Taken together with earlier work, our data suggest that Crz acts to restore metabolic homeostasis at starvation and osmotic homeostasis during desiccation by inhibiting release of the diuretic hormone CAPA. Hence, this work provides a mechanistic understanding of the neuroendocrine mitigation of metabolic and osmotic stress by two peptide systems.

neuroscience↗