Biology subjects

Smith, N.

Publications and source records attributed to Smith, N..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

Resolving DJ-1 Glyoxalase Catalysis Using Mix-and-Inject Serial Crystallography at a Synchrotron

DJ-1 (PARK7) is an intensively studied protein whose cytoprotective activities are dysregulated in multiple diseases. DJ-1 has been reported as having two distinct enzymatic activities in defense against reactive carbonyl species that are difficult to distinguish in conventional biochemical experiments. Here, we establish the mechanism of DJ-1 using a synchrotron-compatible version of mix-and-inject-serial crystallography (MISC), which was previously performed only at XFELs, to directly observe DJ-1 catalysis. We designed and used new diffusive mixers to collect time-resolved Laue diffraction data of DJ-1 catalysis at a pink beam synchrotron beamline. Analysis of structurally similar methylglyoxal-derived intermediates formed through the DJ-1 catalytic cycle shows that the enzyme catalyzes nearly two turnovers in the crystal and defines key aspects of its glyoxalase mechanism. In addition, DJ-1 shows allosteric communication between a distal site at the dimer interface and the active site that changes during catalysis. Our results rule out the widely cited deglycase mechanism for DJ-1 action and provide an explanation for how DJ-1 produces L-lactate with high chiral purity.

biochemistry↗

bioRxiv2024

HumanIslets: An integrated platform for human islet data access and analysis

Comprehensive molecular and cellular phenotyping of human islets can enable deep mechanistic insights for diabetes research. We established the Human Islet Data Analysis and Sharing (HI-DAS) consortium to advance goals in accessibility, usability, and integration of data from human islets isolated from donors with and without diabetes at the Alberta Diabetes Institute (ADI) IsletCore. Here we introduce HumanIslets.com, an open resource for the research community. This platform, which presently includes data on 547 human islet donors, allows users to access linked datasets describing molecular profiles, islet function and donor phenotypes, and to perform various statistical and functional analyses at the donor, islet and single-cell levels. As an example of the analytic capacity of this resource we show a dissociation between cell culture effects on transcript and protein expression, and an approach to correct for exocrine contamination found in hand-picked islets. Finally, we provide an example workflow and visualization that highlights links between type 2 diabetes status, SERCA3b Ca2+-ATPase levels at the transcript and protein level, insulin secretion and islet cell phenotypes. HumanIslets.com provides a growing and adaptable set of resources and tools to support the metabolism and diabetes research community.

systems biology↗

bioRxiv2024

Connectomic Analysis of Mitochondria in the Central Brain of Drosophila

Mitochondria are integral to the metabolism and cell biology of a neuron. Electron microscopy images of fly brain volumes, taken for connectomics, can be analyzed for mitochondria as well as the cells and synapses already reported. Here, from the Drosophila Hemibrain connectome dataset, we extract, classify, and measure approximately 6 million mitochondria, with the majority located among more than 20 thousand neurons and over 5500 cell types. Each mitochondrion is annotated with its location, orientation, voxel size, and appearance (dark and dense, light and sparse, or medium), and each synapse is linked to its closest mitochondrion. Using these data, we show how the most basic characteristics of mitochondria--volume, distance from synapses, and appearance--vary considerably between cell types and between brain regions. Mitochondria are larger and closer at presynapses than at postsynapses, and presynapses typically have a mitochondrion within one micron. However, cells important for learning and memory, Kenyon cells, have unusually small and sparse mitochondria that are placed with unusual precision near only half of presynapses. We find that mitochondria occupy a greater fraction of cell volume in inhibitory neurons than excitatory cells, dopaminergic neurons have a distinct synaptic positioning of mitochondria, and that glutamatergic neurons have a high fraction of mitochondria with a light appearance. We also find that synapses with more postsynaptic partners have larger presynaptic mitochondria and more distant postsynaptic mitochondria. Finally, we have extended the data model of our public web interface, neuPrint, to record our mitochondria data as searchable subcellular components of neurons in a connectomic database. These results indicate wide-ranging principles for how mitochondrial organization varies by cell type in a dataset of unprecedented size and coverage.

neuroscience↗

bioRxiv2024

Sub-clinical glutamate receptor antagonist combinations prevent progressive demyelination.

Multiple sclerosis (MS) affects almost 3 million people globally who suffer demyelination as a series of relapses and remissions that tend towards progressive deterioration over time. The proximate cause is auto-immune attack by the adaptive immune system; therapies directed against this are effective during the relapsing-remitting phase but are less effective or ineffective during progression where other injury mechanisms may be significant. LPS- and cuprizone-induced experimental demyelination share features of progressive demyelination in MS but the underlying mechanisms are not well understood. We show here that these demyelination models can be reproduced ex vivo using short protocols, revealing that combined antagonism of two types of glutamate receptor, NMDA and AMPA, using clinically approved antagonists at sub-clinical doses, can protect against these forms of demyelination. Combined low dose therapy was subsequently shown to be effective in vivo against dietary cuprizone and experimental autoimmune-encephalomyelitis (EAE) models of demyelination and, in particular, protected the smaller myelinated axons that are the main substrate of the function loss in progressive MS.

neuroscience↗

bioRxiv2024

Far-red and sensitive sensor for monitoring real-time H2O2 dynamics with subcellular resolution and inmulti-parametric imaging applications.

H2O2 is a key oxidant in mammalian biology and a pleiotropic signaling molecule at the physiological level, and its excessive accumulation in conjunction with decreased cellular reduction capacity is often found to be a common pathological marker. Here, we present a red fluorescent Genetically Encoded H2O2 Indicator (GEHI) allowing versatile optogenetic dissection of redox biology. Our new GEHI, oROS-HT, is a chemigenetic sensor utilizing a HaloTag and Janelia Fluor (JF) rhodamine dye as fluorescent reporters. We developed oROS-HT through a structure-guided approach aided by classic protein structures and recent protein structure prediction tools. Optimized with JF635, oROS-HT is a sensor with 635 nm excitation and 650 nm emission peaks, allowing it to retain its brightness while monitoring intracellular H2O2 dynamics. Furthermore, it enables multi-color imaging in combination with blue-green fluorescent sensors for orthogonal analytes and low auto-fluorescence interference in biological tissues. Other advantages of oROS-HT over alternative GEHIs are its fast kinetics, oxygen-independent maturation, low pH sensitivity, lack of photo-artifact, and lack of intracellular aggregation. Here, we demonstrated efficient subcellular targeting and how oROS-HT can map inter and intracellular H2O2 diffusion at subcellular resolution. Lastly, we used oROS-HT with the green fluorescent calcium indicator Fluo-4 to investigate the transient effect of the anti-inflammatory agent auranofin on cellular redox physiology and calcium levels via multi-parametric, dual-color imaging.

bioengineering↗

bioRxiv2024

Structure-guided engineering of a fast genetically encoded sensor for real-time H2O2 monitoring.

Hydrogen Peroxide (H2O2) is a central oxidant in redox biology due to its pleiotropic role in physiology and pathology. However, real-time monitoring of H2O2 in living cells and tissues remains a challenge. We address this gap with the development of an optogenetic hydRogen perOxide Sensor (oROS), leveraging the bacterial peroxide binding domain OxyR. Previously engineered OxyR-based fluorescent peroxide sensors lack the necessary sensitivity or response speed for effective real-time monitoring. By structurally redesigning the fusion of Escherichia coli (E. coli) ecOxyR with a circularly permutated green fluorescent protein (cpGFP), we created a novel, green-fluorescent peroxide sensor oROS-G. oROS-G exhibits high sensitivity and fast on-and-off kinetics, ideal for monitoring intracellular H2O2 dynamics. We successfully tracked real-time transient and steady-state H2O2 levels in diverse biological systems, including human stem cell-derived neurons and cardiomyocytes, primary neurons and astrocytes, and mouse neurons and astrocytes in ex vivo brain slices. These applications demonstrate oROSs capabilities to monitor H2O2 as a secondary response to pharmacologically induced oxidative stress, G-protein coupled receptor (GPCR)-induced cell signaling, and when adapting to varying metabolic stress. We showcased the increased oxidative stress in astrocytes via A{beta}-putriscine-MAOB axis, highlighting the sensors relevance in validating neurodegenerative disease models. oROS is a versatile tool, offering a window into the dynamic landscape of H2O2 signaling. This advancement paves the way for a deeper understanding of redox physiology, with significant implications for diseases associated with oxidative stress, such as cancer, neurodegenerative disorders, and cardiovascular diseases.

bioengineering↗

bioRxiv2023

X-ray-driven chemistry and conformational heterogeneity in atomic resolution crystal structures of bacterial dihydrofolate reductases

Dihydrofolate reductase (DHFR) catalyzes the NADPH-dependent reduction of dihydrofolate to tetrahydrofolate. Bacterial DHFRs are targets of several important antibiotics as well as model enzymes for the role of protein conformational dynamics in enzyme catalysis. We collected 0.93 [A] resolution X-ray diffraction data from both Bacillus subtilis (Bs) and E. coli (Ec) DHFRs bound to folate and NADP+. These oxidized ternary complexes should not be able to perform chemistry, however electron density maps suggest hydride transfer is occurring in both enzymes. Comparison of low- and high-dose EcDHFR datasets show that X-rays drive partial production of tetrahydrofolate. Hydride transfer causes the nicotinamide moiety of NADP+ to move towards the folate as well as correlated shifts in nearby residues. Higher radiation dose also changes the conformational heterogeneity of Met20 in EcDHFR, supporting a solvent gating role during catalysis. BsDHFR has a different pattern of conformational heterogeneity and an unexpected disulfide bond, illustrating important differences between bacterial DHFRs. This work demonstrates that X-rays can drive hydride transfer similar to the native DHFR reaction and that X-ray photoreduction can be used to interrogate catalytically relevant enzyme dynamics in favorable cases.

biochemistry↗

bioRxiv2023

A benzoxazolylurea inhibits VraS and enhances antimicrobials against vancomycin intermediate-resistant Staphylococcus aureus

Vancomycin intermediate-resistant Staphylococcus aureus (VISA) is a pathogen of concern. VraS, a histidine kinase, facilitates the VISA phenotype. Here, we reveal a benzoxazolylurea that directly inhibits VraS and enhances vancomycin to below the clinical breakpoint against an archetypal VISA strain. To the best of our knowledge, this is the first direct VraS inhibitor ever reported that shows significant enhancement of vancomycin against VISA.

pharmacology and toxicology↗

bioRxiv2023

Post-glacial recolonization and multiple scales of secondary contact contribute to contemporary Atlantic salmon (Salmo salar) genomic variation in North America.

AimIn northern environments, periods of isolation during Pleistocene glaciations and subsequent recolonization and secondary contact have had a significant influence on contemporary diversity of many species. The recent advent of high-resolution genomic analyses allows unprecedented power to resolve genomic signatures of such events in northern species. Here, we provide the highest resolution genomic characterization of Atlantic salmon in North America to infer glacial refugia and the geographic scales of postglacial secondary contact. LocationNorth America. TaxonAtlantic salmon, Salmo salar. MethodsSamples were collected for 5455 individuals from 148 populations encompassing the majority of Atlantic salmons native range in North America, from Labrador to Maine. Individuals were genotyped using a 220K SNP array aligned to the Atlantic salmon (Salmo salar) genome. Spatial genetic structure (PCA, k-means clustering, admixture) was evaluated in conjunction with genomic comparisons of identified lineages to infer the refugia during the last glacial maximum and regions of secondary contact following recolonization. ResultsSpatial genomic analyses identified three phylogeographic groups, consistent with the northward recolonization from two southern glacial refugia in North America (a western Maritime lineage and an eastern Newfoundland and Labrador lineage), with subsequent differentiation of the eastern lineage into two separate groups. Secondary contact among these North American groups was present within the northern Gulf of St. Lawrence and evidence of trans-Atlantic secondary contact was detected within the eastern Newfoundland and Labrador lineage. Comparison of groups from insular Newfoundland with those from mainland Labrador suggests genomic regions displaying high differentiation were characterized by elevated European admixture, suggesting a possible role of European secondary contact in population divergence. Main ConclusionsThese findings present the first evidence suggesting that genomic diversity in extant North American Atlantic salmon populations has resulted from allopatric isolation in two glacial refugia followed by both regional and trans-Atlantic recolonization and secondary contact and demonstrate the power of genomic tools to resolve historical drivers of diversity in wild populations.

evolutionary biology↗

bioRxiv2023

Changes in an Enzyme Ensemble During Catalysis Observed by High Resolution XFEL Crystallography

Enzymes populate ensembles of structures with intrinsically different catalytic proficiencies that are difficult to experimentally characterize. We use time-resolved mix-and-inject serial crystallography (MISC) at an X-ray free electron laser (XFEL) to observe catalysis in a designed mutant (G150T) isocyanide hydratase (ICH) enzyme that enhances sampling of important minor conformations. The active site exists in a mixture of conformations and formation of the thioimidate catalytic intermediate selects for catalytically competent substates. A prior proposal for active site cysteine charge-coupled conformational changes in ICH is validated by determining structures of the enzyme over a range of pH values. A combination of large molecular dynamics simulations of the enzyme in crystallo and time-resolved electron density maps shows that ionization of the general acid Asp17 during catalysis causes additional conformational changes that propagate across the dimer interface, connecting the two active sites. These ionization-linked changes in the ICH conformational ensemble permit water to enter the active site in a location that is poised for intermediate hydrolysis. ICH exhibits a tight coupling between ionization of active site residues and catalysis-activated protein motions, exemplifying a mechanism of electrostatic control of enzyme dynamics.

biochemistry↗

bioRxiv2023

Scalable and efficient DNA sequencing analysis on different compute infrastructures aiding variant discovery

DNA variation analysis has become indispensable in many aspects of modern biomedicine, most prominently in the comparison of normal and tumor samples. Thousands of samples are collected in local sequencing efforts and public databases requiring highly scalable, portable, and automated workflows for streamlined processing. Here, we present nf-core/sarek 3, a well-established, comprehensive variant calling and annotation pipeline for germline and somatic samples. It is suitable for any genome with a known reference. We present a full rewrite of the original pipeline showing a significant reduction of storage requirements by using the CRAM format and runtime by increasing intra-sample parallelization. Both are leading to a 70% cost reduction in commercial clouds enabling users to do large-scale and cross-platform data analysis while keeping costs and CO2 emissions low. The code is available at https://nf-co.re/sarek.

bioinformatics↗

bioRxiv2023

Machine Learning Ensemble Directed Engineering of Genetically Encoded Fluorescent Calcium Indicators.

Real-time monitoring of biological activity can be achieved through the use of genetically encoded fluorescent indicators (GEFIs). GEFIs are protein-based sensing tools whose biophysical characteristics can be engineered to meet experimental needs. However, GEFIs are inherently complex proteins with multiple dynamic states, rendering optimization one of the most challenging problems in protein engineering. Most GEFIs are engineered through trial-and-error mutagenesis, which is time and resource-intensive and often relies on empirical knowledge for each GEFI. We applied an alternative approach using machine learning to efficiently predict the outcomes of sensor mutagenesis by analyzing established libraries that link sensor sequences to functions. Using the GCaMP calcium indicator as a scaffold, we developed an ensemble of three regression models trained on experimentally derived GCaMP mutation libraries. We used the trained ensemble to perform an in silico functional screen on a library of 1423 novel, untested GCaMP variants. The mutations were predicted to significantly alter the fluorescent response, and off-rate kinetics were advanced for verification in vitro. We found that the ensembles predictions of novel variants biophysical characteristics closely replicated what we observed of the variants in vitro. As a result, we identified the novel ensemble-derived GCaMP (eGCaMP) variants, eGCaMP and eGCaMP+, that achieve both faster kinetics and larger fluorescent responses upon stimulation than previously published fast variants. Furthermore, we identified a combinatorial mutation with extraordinary dynamic range, eGCaMP2+, that outperforms the tested 6th, 7th, and 8th generation GCaMPs. These findings demonstrate the value of machine learning as a tool to facilitate the efficient prescreening of mutants for functional characteristics. By leveraging the learning capabilities of our ensemble, we were able to accelerate the identification of promising mutations and reduce the experimental burden associated with screening an entire library. Machine learning tools such as this have the potential to complement emerging high-throughput screening methodologies that generate massive datasets, which can be tedious to analyze manually. Overall, these findings have significant implications for developing new GEFIs and other protein-based tools, demonstrating the power of machine learning as an asset in protein engineering.

bioengineering↗

bioRxiv2023

DNA Repair Function Scores for 2172 Variants in the BRCA1 Amino-Terminus

Single nucleotide variants are the most frequent type of sequence changes detected in the genome and these are frequently variants of uncertain significance (VUS). VUS are changes in DNA for which disease risk association is unknown. Thus, methods that classify the functional impact of a VUS can be used as evidence for variant interpretation. In the case of the breast and ovarian cancer specific tumor suppressor protein, BRCA1, pathogenic missense variants frequently score as loss of function in an assay for homology-directed repair (HDR) of DNA double-strand breaks. We previously published functional results using a multiplexed assay for 1056 amino acid substitutions residues 2-192 in the amino terminus of BRCA1. In this study, we have re-assessed the data from this multiplexed assay using an improved analysis pipeline. These new analysis methods yield functional scores for more variants in the first 192 amino acids of BRCA1, plus we report new results for BRCA1 amino acid residues 193-302. We now present the functional classification of 2172 BRCA1 variants in BRCA1 residues 2-302 using the multiplexed HDR assay. Comparison of the functional determinations of the missense variants with clinically known benign or pathogenic variants indicated 93% sensitivity and 100% specificity for this assay. The results from BRCA1 variants tested in this assay are a resource for clinical geneticists for evidence to evaluate VUS in BRCA1. AUTHOR SUMMARYMost missense substitutions in BRCA1 are variants of unknown significance (VUS), and individuals with a VUS in BRCA1 cannot know from genetic information alone whether this variant predisposes to breast or ovarian cancer. We apply a multiplexed functional assay for homology directed repair of DNA double strand breaks to assess variant impact on this important BRCA1 protein function. We analyzed 2172 variants in the amino-terminus of BRCA1 and demonstrate that variants that are known as pathogenic have a loss of function in the DNA repair assay. Conversely, variants that are known to be benign are functionally normal in the multiplexed assay. We suggest that these functional determinations of BRCA1 variants can be used to augment the information that clinical cancer geneticists provide to patients who have a VUS in BRCA1.

cancer biology↗

bioRxiv2022

Genomic and machine learning-based screening of aquaculture associated introgression into at-risk wild North American Atlantic salmon (Salmo salar) populations.

The negative genetic impacts of gene flow from domestic to wild populations can be dependent on the degree of domestication and exacerbated by the magnitude of pre-existing genetic differences between wild populations and the domestication source. Recent evidence of European ancestry within North American aquaculture Atlantic salmon (Salmo salar) has elevated the potential impact of escaped farmed salmon on often at-risk wild North American salmon populations. Here we compare the ability of single nucleotide polymorphism (SNP) and microsatellite (SSR) marker panels of different sizes (7-SSR, 100-SSR, and 220K-SNP) to detect introgression of European genetic information into North American wild and aquaculture populations. Linear regression comparing admixture predictions for a set of individuals common to the three data sets showed that the 100-SSR panel and 7-SSR panels replicated the full 220K-SNP-based admixture estimates with low accuracy (r2 of 0.64 and 0.49 respectively). Additional tests explored the effects of individual sample size and marker number, which revealed that ~300 randomly selected SNPs could replicate the 220K-SNP admixture predictions with greater than 95% fidelity. We designed a custom SNP panel (301-SNP) for European admixture detection in future monitoring work and then developed and tested a Python package, SalmonEuAdmix (https://github.com/CNuge/SalmonEuAdmix), that uses a deep neural network to make de novo estimates of individuals European admixture proportion without the need to conduct complete admixture analysis utilizing baseline samples. The results demonstrate the mobilization of targeted SNP panels and machine learning in support of at-risk species conservation and management.

genomics↗

bioRxiv2022

Environmental and genetic drivers of population differences in SARS-CoV-2 immune responses

Humans display vast clinical variability upon SARS-CoV-2 infection1-3, partly due to genetic and immunological factors4. However, the magnitude of population differences in immune responses to SARS-CoV-2 and the mechanisms underlying such variation remain unknown. Here we report single-cell RNA-sequencing data for peripheral blood mononuclear cells from 222 healthy donors of various ancestries stimulated with SARS-CoV-2 or influenza A virus. We show that SARS-CoV-2 induces a weaker, but more heterogeneous interferon-stimulated gene activity than influenza A virus, and a unique pro-inflammatory signature in myeloid cells. We observe marked population differences in transcriptional responses to viral exposure that reflect environmentally induced cellular heterogeneity, as illustrated by higher rates of cytomegalovirus infection, affecting lymphoid cells, in African-descent individuals. Expression quantitative trait loci and mediation analyses reveal a broad effect of cell proportions on population differences in immune responses, with genetic variants having a narrower but stronger effect on specific loci. Additionally, natural selection has increased immune response differentiation across populations, particularly for variants associated with SARS-CoV-2 responses in East Asians. We document the cellular and molecular mechanisms through which Neanderthal introgression has altered immune functions, such as its impact on the myeloid response in Europeans. Finally, colocalization analyses reveal an overlap between the genetic architecture of immune responses to SARS-CoV-2 and COVID-19 severity. Collectively, these findings suggest that adaptive evolution targeting immunity has also contributed to current disparities in COVID-19 risk.

genomics↗

bioRxiv2022

Disentangling the effects of eutrophication and natural variability on macrobenthic communities across French coastal lagoons

Coastal lagoons are transitional ecosystems that host a unique diversity of species and support many ecosystem services. Owing to their position at the interface between land and sea, they are also subject to increasing human impacts, which alter their ecological functioning. Because coastal lagoons are naturally highly variable in their environmental conditions, disentangling the effects of anthropogenic disturbances like eutrophication from those of natural variability is a challenging, yet necessary issue to address. Here, we analyze a dataset composed of macrobenthic invertebrate abundances and environmental variables (hydro-morphology, water, sediment and macrophytes) gathered across 29 Mediterranean coastal lagoons located in France, to characterize the main drivers of community composition and structure. Using correlograms, linear models and variance partitioning, we found that lagoon hydro-morphology (connection to the sea and lagoon surface), which affects the level of environmental variability (salinity and temperature), as well as lagoon-scale benthic habitat diversity (using macrophyte morphotypes) seemed to regulate macrofauna distribution, while eutrophication and associated stressors like low dissolved oxygen, acted upon the existing communities, mainly by reducing species richness and diversity. Furthermore, M-AMBI, a multivariate index composed of species richness, Shannon diversity and AMBI (AZTIs Marine Biotic Index) and currently used to evaluate the ecological state of French coastal lagoons, was more sensitive to eutrophication (18%) than to natural variability (9%), with nonetheless 49% of its variability explained jointly by both. To improve the robustness of benthic indicators like M-AMBI and increase the effectiveness of lagoon benthic habitat management, we call for a revision of the ecological groups at the base of the AMBI index and of the current lagoon typology which could be inspired by the lagoon-sea connection levels used in this study.

ecology↗

bioRxiv2022

Zmiz1 is required for mature β-cell function and mass expansion upon high fat feeding

Genome-wide association studies have identified hundreds of signals for type 2 diabetes (T2D), most of which confer risk through effects on gene expression. We previously identified the transcription factor ZMIZ1 as a probable effector transcript in human islets, but how altered ZMIZ1 expression impacts T2D risk is unknown. We now show that islets from carriers of the T2D-risk alleles have reduced islet insulin content and glucose-stimulated insulin secretion. To elucidate the mechanism for islet-cell dysfunction, we generated {beta}-cell-specific Zmiz1 knockout (Zmiz1{beta}KO) mice. Male and female Zmiz1{beta}KO mice were glucose intolerant with impaired insulin secretion, compared with control littermates. Transcriptomic profiling of Zmiz1{beta}KO islets identified over 500 differentially expressed genes including those involved in {beta}-cell function and maturity which we confirmed at the protein level. After high fat feeding, Zmiz1{beta}KO mice fail to expand {beta}-cell mass and become severely diabetic. Thus, Zmiz1 is required for normal glucose homeostasis and may contribute to T2D risk by maintaining a mature {beta}-cell state and allowing islet mass expansion upon metabolic stress.

physiology↗

bioRxiv2022

Redox sensing by SENP1 augments insulin secretion early after high-fat feeding in mice

Pancreatic {beta}-cells respond to metabolic stress by upregulating insulin secretion, however the underlying mechanisms remain unclear. In {beta}-cells from overweight humans without diabetes, and mice fed a high-fat diet for 2 days, insulin exocytosis and secretion are enhanced without increased Ca2+ influx. {beta}-cell RNA-seq suggests altered metabolic pathways early following HFD, where we find increased basal oxygen consumption, proton leak, but a more reduced cytosolic redox state. Increased {beta}-cell exocytosis after 2-day HFD is dependent on this reduced intracellular redox and requires the sentrin-specific SUMO-protease-1 (SENP1). Mice with either pancreas- or {beta}-cell-specific SENP1 deletion fail to up-regulate exocytosis and become rapidly glucose intolerant after 2-day HFD. Mechanistically, redox-sensing by SENP1 requires a thiol group at C535 which together with Zn+-binding suppresses basal protease activity and unrestrained {beta}-cell exocytosis and increases SENP1 sensitivity to regulation by redox signals.

cell biology↗