Biology subjects

Lv, J.

Publications and source records attributed to Lv, J..

52 records · Page 3Linked to original sources

bioRxiv2021

ASFV pD345L protein negatively regulates NF-kB signaling through inhibiting IKK kinase activity

NF-{kappa}B is a critical transcription factor in immediate early viral infection, including African swine fever virus (ASFV), playing an important role in inflammation response and expression of antiviral genes. ASFV encodes for more than 151 proteins by its own transcription machinery and possesses a great capacity to evade or subvert antiviral innate immune responses. A couple of such viral proteins have been reported, but many remain unknown. Here, we showed that pD345L, an ASFV-encoded lambda-like exonuclease, is an inhibitor of cGAS/STING mediated NF-{kappa}B signaling by blocking IKK/{beta} kinase activity. Specifically, we showed that overexpression of pD345L suppresses cGAS/STING induced IFN{beta} and NF-{kappa}B activation, resulting in decreased transcription of IFN{beta} and several pro-inflammatory cytokines, including IL-1, IL-6, IL-8, and TNF. In addition, we showed that pD345L targeted at or downstream of IKK and upstream of p65. Importantly, we found that pD345L associates with KD and HLH domains of IKK and LZ domain of IKK{beta}, and thus interrupts their kinase activity on downstream substrate I{kappa}B. Finally, we showed that pD345L inhibition of NF-{kappa}B signaling was independent of its exonuclease activity. Taken together, we concluded that pD345L blocks IKK /{beta} kinase activity by protein-protein interaction and thus disrupts cGAS/STING mediated NF-{kappa}B signaling. ImportanceAfrican Swine Fever (ASF) is one of the most devastating and economically significant swine diseases caused by African swine fever virus (ASFV). Since expanding of ASFV affected areas into Asian countries, especially China, an effective vaccine is urgently needed more than ever. Therefore, it is of great significance to understand the interaction between ASFV infection and host immune responses. The NF-{kappa}B signaling plays a central role in innate and acquired immune responses. Activation of I{kappa}B kinase (IKK) complex is a key step of both canonical and non-canonical NF-{kappa}B pathways, and is commonly targeted by different viruses. But no ASFV protein has been shown to regulate IKK yet. In this study, we demonstrated that pD345L blocks IKK/{beta} kinase activity by protein-protein interaction and thus disrupts cGAS/STING mediated NF-{kappa}B signaling. It has been shown that conventional vaccine development approaches are proven to be inapplicable to ASFV. Neither subunit nor DNA vaccine provides efficient protection. Gene deleted live-attenuated vaccine candidates render adequate protection, but establishment of chronic or persistent infection in vaccinated animals and risk of recombination with filed strains are key challenges. To overcome these, one potential strategy would be generation of replication-defective viruses. As a lambda-like exonuclease, pD345L plays a critical role in ASFV replication and ASFV deficient in D345L cannot be rescued. Given the dual role of pD345L in virus replication and immune evasion, it may serve as a potential target for replication-defective virus vaccine development.

microbiology↗

bioRxiv2021

Accommodating site variation in neuroimaging data using hierarchical and Bayesian models

AO_SCPLOWBSTRACTC_SCPLOWThe potential of normative modeling to make individualized predictions from neuroimaging data has enabled inferences that go beyond the case-control approach. However, site effects are often confounded with variables of interest in a complex manner and can bias estimates of normative models, which has impeded the application of normative models to large multi-site neuroimaging data sets. In this study, we suggest accommodating for these site effects by including them as random effects in a hierarchical Bayesian model. We compared the performance of a linear and a non-linear hierarchical Bayesian model in modeling the effect of age on cortical thickness. We used data of 570 healthy individuals from the ABIDE (autism brain imaging data exchange) data set in our experiments. In addition, we used data from individuals with autism to test whether our models are able to retain clinically useful information while removing site effects. We compared the proposed single stage hierarchical Bayesian method to several harmonization techniques commonly used to deal with additive and multiplicative site effects using a two stage regression, including regressing out site and harmonizing for site with ComBat, both with and without explicitly preserving variance related to age and sex as biological variation of interest. In addition, we made predictions from raw data, in which site has not been accommodated for. The proposed hierarchical Bayesian method showed the best predictive performance according to multiple metrics. Beyond that, the resulting z-scores showed little to no residual site effects, yet still retained clinically useful information. In contrast, performance was particularly poor for the regression model and the ComBat model in which age and sex were not explicitly modeled. In all two stage harmonization models, predictions were poorly scaled, suffering from a loss of more than 90 % of the original variance. Our results show the value of hierarchical Bayesian regression methods for accommodating site variation in neuroimaging data, which provides an alternative to harmonization techniques. While the approach we propose may have broad utility, our approach is particularly well suited to normative modelling where the primary interest is in accurate modelling of inter-subject variation and statistical quantification of deviations from a reference model. 1 HighlightsO_LIDevelopment and presentation of normative modeling approach based on hierarchical Bayesian modeling that can be applied to large multi-site neuroimaging data sets. C_LIO_LIComparison of performance of Hierarchical Bayesian model including site as predictor to several common ways to harmonize for multi-site effects. C_LIO_LIPresentation of normative modeling as site correction tool. C_LI

bioinformatics↗

bioRxiv2021

Prediction of occult tumor progression via platelet RNAs in a mouse melanoma model: a potential new platform of cancer screening for early detection of cancer

Cancer screening provides the opportunity to detect cancer early, ideally before symptom onset and metastasis, and offers an increased opportunity for a better prognosis. The ideal biomarkers for cancer screening should discriminate individuals who have not developed invasive cancer yet but are destined to do so from healthy subjects1,2. However, most cancers lack effective screening recommendations. Therefore, further studies on novel screening strategies are urgently required. Here, our proof-of-concept study shows blood platelets could be a platform for liquid biopsy-based early cancer detection. By using a simple suboptimal inoculation melanoma mouse model, we identified differentially expressed RNAs in platelet signatures of mice injected with a suboptimal number of cancer cells (eDEGs) compared with mice with macroscopic melanomas and negative controls. These RNAs were strongly enriched in pathways related to immune response and regulation. Moreover, 36 genes selected from the eDEGs via bioinformatics analyses were verified in a mouse validation cohort via quantitative real-time PCR. LASSO regression was employed to generate the prediction models with gene expression signatures as the best predictors for occult tumor progression in mice. The prediction models showed great diagnostic efficacy and predictive value in our murine validation cohort, and could discriminate mice with occult tumors from control group (area under curve (AUC) of 0.935 (training data) and 0.912 (testing data)) (gene signature including Cd19, Cdkn1a, S100a9, Tap1, and Tnfrsf1b) and also from macroscopic tumor group (AUC of 0.920 (training data) and 0.936 (testing data)) (gene signature including Ccr7, Cd4, Kmt2d, and Ly6e). Our study provides evidence for potential clinical relevance of blood platelets as a platform for liquid biopsy-based early detection of cancer. Furthermore, the eDEGs are mostly immune-related, not tumor-specific. Hence it is possible platelets-based liquid biopsy could enable simultaneous early detection of cancers from multiple organs of origin3. It is also feasible to determine the origin of cancer since platelet profiles are influenced by tumor type3.

cancer biology↗

bioRxiv2021

FOD-Net: A Deep Learning Method for Fiber Orientation Distribution Angular Super Resolution

Mapping the human connectome using fiber-tracking permits the study of brain connectivity and yields new insights into neuroscience. However, reliable connectome reconstruction using diffusion magnetic resonance imaging (dMRI) data acquired by widely available clinical protocols remains challenging, thus limiting the connectome / tractography clinical applications. Here we develop fiber orientation distribution (FOD) network (FOD-Net), a deep-learning-based framework for FOD angular super-resolution. Our method enhances the angular resolution of FOD images computed from common clinical-quality dMRI data, to obtain FODs with quality comparable to those produced from advanced research scanners. Super-resolved FOD images enable superior tractography and structural connectome reconstruction from clinical protocols. The method was trained and tested with high-quality data from the Human Connectome Project (HCP) and further validated with a local clinical 3.0T scanner. Using this method, we improve the angular resolution of FOD images acquired with typical single-shell low-angular-resolution dMRI data (e.g., 32 directions, b = 1000 s/mm2) to approximate the quality of FODs derived from time-consuming, multi-shell high-angular-resolution dMRI research protocols. We also demonstrate tractography improvement, removing spurious connections and bridging missing connections. We further demonstrate that connectomes reconstructed by super-resolved FODs achieve comparable results to those obtained with more advanced dMRI acquisition protocols, on both HCP and clinical 3.0T data. Advances in deep-learning approaches used in FOD-Net facilitate the generation of high quality tractography / connectome analysis from existing clinical MRI environments. Our code is freely available at https://github.com/ruizengalways/FOD-Net.

bioengineering↗

bioRxiv2020

Species-resolved sequencing of low-biomass microbiomes by 2bRAD-M

Microbiome samples with low microbial biomass or severe DNA degradation remain challenging for amplicon-based (e.g., 16S/18S-rRNA) or whole-metagenome sequencing (WMS) approaches. Here, we introduce 2bRAD-M, a highly reduced and cost-effective metagenome-sequencing strategy which only sequences ~1% of metagenome and can simultaneously produce species-level bacterial, archaeal, and fungal profiles for low-biomass and highly degraded samples. For mock communities, 2bRAD-M can accurately generate species-level taxonomic profiles for otherwise hard-to-sequence samples with (i) low biomass of merely 1 pg of total DNA, (ii) high host DNA contamination (99%), and (iii) severely fragmented DNA (50-bp) from degraded samples. Tests of 2bRAD-M on stool, skin and environment-surface samples deliver successful reconstruction of comprehensive, high-resolution microbial profiles with agreement across 16S-rRNA, WMS and existing literature. In addition, it enables microbial profiling in formalin-fixed paraffin-embedded (FFPE) cervical tissue samples which were recalcitrant to conventional approaches due to the low amount and heavy degradation of microbial DNA, and discriminated healthy tissue, pre-invasive cancer and invasive cancer via species-level microbial profiles with 91.1% accuracy. Therefore, 2bRAD-M greatly expands the reach of microbiome sequencing.

microbiology↗

bioRxiv2020

LncRNA H19X is required for placenta development and angiogenesis through regulating a noncoding RNA regulatory network

H19X is a lncRNA specifically expressed in the placenta, whose expression is induced by hypoxia. H19X overexpression promoted trophoblast proliferation and invasion, while its knockdown or knockout inhibited trophoblast proliferation and invasion. Mechanistically, we demonstrated that reciprocal regulation exists with miR-424/miR-503 in the control of genes related to placental development and angiogenesis, including VEGF and VEGFR2. H19X inhibited ubiquitination of PIWIL1, thereby maintaining its stability and homeostatic expression of piRNAs. PIWIL1 overexpression rescued the defects of cell behavior caused by H19X KO. H19X deletion led to compromised HIF-1A/HIF-2A expression, which was correlated with the dysregulation of downstream genes under hypoxic conditions. CRISPR/Cas-9 knockout of H19X in animals led to defective placenta differentiation and compromised embryo development under hypoxic conditions. Western blotting showed reduced expression levels of PIWIL1 as well as angiogenesis marker genes, including VEGF and VEGFR2, in H19X KO mice. Thus, this study provides evidence of an unexpected link among lncRNA, miRNA, PIWIL1-related piRNA, and angiogenesis in placentation, the dysregulation of which leads to poor placental development and embryo loss under hypoxic conditions.

developmental biology↗

bioRxiv2020

MACMIC Reveals Dual Role of CTCF in Epigenetic Regulation of Cell Identity Genes

Numerous studies of relationship between epigenomic features have focused on their strong correlation across the genome, likely because such relationship can be easily identified by many established methods for correlation analysis. However, two features with little correlation may still colocalize at many genomic sites to implement important functions. There is no bioinformatic tool for researchers to specifically identify such feature pair. Here, we develop a method to identify feature pair in which two features have maximal colocalization but minimal correlation (MACMIC) across the genome. By MACMIC analysis of 3,385 feature pairs in 15 cell types, we reveal a dual role of CTCF in epigenetic regulation of cell identity genes. Although super-enhancers are associated with activation of target genes, only a subset of super-enhancers colocalized with CTCF regulate cell identity genes. At super-enhancers colocalized with CTCF, the CTCF is required for the active marker H3K27ac in cell type requiring the activation, and also required for the repressive marker H3K27me3 in other cell types requiring the repression. Our work demonstrates the biological utility of the MACMIC analysis and reveals a key role for CTCF in epigenetic regulation of cell identity.

bioinformatics↗

bioRxiv2020

Up-Regulation of αCaMKII Impairs Cued Fear Extinction and NMDAR-Dependent LTD in the Lateral Amygdala

Impaired fear extinction is one of the hallmark symptoms of post-traumatic stress disorder (PTSD). The roles of CaMKII have been not extensively studied in fear extinction and LTD. Here, we found PTSD susceptible mice exhibited significant up-regulation of CaMKII in the lateral amygdala (LA). Consistently, increasing CaMKII in LA profoundly not only caused PTSD-like symptoms such as impaired fear extinction and anxiety-like behaviors, but also attenuated NMDAR-dependent LTD at thalamo-LA synapses, reduced GluA1-Ser845/Ser831 dephosphorylation and AMPAR internalization. Suppressing the elevated CaMKII to normal level could completely reverse both PTSD-like symptoms and the impairments in LTD, GluA1-Ser845/Ser831 dephosphorylation and AMPAR internalization. Intriguingly, deficits in AMPAR internalization and GluA1-Ser845/Ser831 dephosphorylation were detected not only after impaired fear extinction, but also after attenuated LTD Our results demonstrate for the first time GluA1-Ser845/Ser831 dephosphorylation and AMPAR internalization are molecular links between LTD and fear extinction, and suggest CaMKII may be a potential molecular determinant of PTSD.

neuroscience↗

bioRxiv2020

Individual deviations from normative models of brain structure in a large cross-sectional schizophrenia cohort

BackgroundThe heterogeneity of schizophrenia has defied efforts to derive reproducible and definitive anatomical maps of structural brain changes associated with the disorder. We aimed to map deviations from normative ranges of brain structure for individual patients and evaluate whether the loci of individual deviations recapitulated group-average brain maps of schizophrenia pathology. MethodsFor each of 48 white matter tracts and 68 cortical regions, normative percentiles of variation in fractional anisotropy (FA) and cortical thickness (CT) were established using diffusion-weighted and structural MRI from healthy adults (n=195). Individuals with schizophrenia (n=322) were classified as either within the normative range for healthy individuals of the same age and sex (5-95% percentiles), infra-normal (<5% percentile) or supra-normal (>95% percentile). Repeating this classification for each tract and region yielded a deviation map for each individual. ResultsCompared to the healthy comparison group, the schizophrenia group showed widespread reductions in FA and CT, involving virtually all white matter tracts and cortical regions. Paradoxically, however, no more than 15-20% of patients deviated from the normative range for any single tract or region, whereas 79% of patients showed infra-normal deviations for at least one locus (healthy individuals: 59{+/-}2%, p<0.001). Higher polygenic risk for schizophrenia associated with a greater number of regions with infra-normal deviations in CT (r=-0.17, p=0.006). ConclusionsAnatomical loci of schizophrenia-related changes are highly heterogeneous across individuals to the extent that group-consensus pathological maps are not representative of most individual patients. Normative modeling can aid in parsing schizophrenia heterogeneity and guiding personalized interventions.

neuroscience↗

bioRxiv2019

Assessment of the optimum fertilizer rates and planting density for soybean production in China

Fertilization rate and planting density are important factors affecting crop yield. A large number of soybean [Glycine max (L.) Merr] field experimental data (1998-2017) were collected through different database sources to evaluate the optimum fertilizer rate and planting density for high yield of spring and summer soybean in China. The yield of spring and summer soybean gradually increased over year, with their average yields were 2610 and 2724 kg ha-1, respectively. Based on the fitted quadratic curve, the optimal rate of nitrogen (N), phosphorus (P), and potassium (K) fertilizers for high yield of summer soybean was 96 kg N ha-1, 80 kg P2O5 ha-1, and 126 kg K2O ha-1, and the corresponding yields were 3038, 2801 and 2305 kg ha-1, respectively. The optimal rate of N, P and K fertilizers for spring soybean was 71 kg N ha-1, 108 kg P2O5 ha-1 and 74 kg K2O ha-1, and the corresponding yields were 2932, 2834 and 2678 kg ha-1, respectively. The optimum density was 27x104 and 34x104 plants ha-1 under high yield for summer and spring soybean, respectively. Stepwise regression analysis showed that the P fertilizer had the greatest influence on the spring soybean yield followed by K fertilizer and planting density. For summer soybean, population density had the major effect on yield followed by P fertilizer. Overall, the P fertilization and planting density should be payed attention to increase soybean yield in different regions of China.

plant biology↗

bioRxiv2019

3D association of ER, PR and Her2 at protein levels to aid sub-grouping of breast cancer patients in routine clinical practice

Treatments of patients with solid tumors frequently rely on the relative and semi-quantitative assessment of tissue protein biomarkers by immunohistochemistry (IHC). The perspective of transition to absolute and quantitative assessment of tissue biomarkers is hindered by lack of a suitable method, especially for Formalin Fixed Paraffin Embedded (FFPE) tissues. In this study, we explored the feasibility of Quantitative Dot Blot (QDB) method as a universal platform to quantitate tissue biomarkers as absolute and continuous variables in FFPE samples by measuring unprecedentedly the protein levels of Estrogen Receptor (ER), Progesterone Receptor (PR), Her2 and Ki67 simultaneously in 1048 FFPE samples. When using measured Her2, ER and PR levels as coordinates to develop 3D scatterplot, we observed a distinct distribution pattern of the samples with natural segregation of three groups as the likely phenotypical projection of known intrinsic subtypes. Thus, we have achieved a major milestone in this transition by identifying the first practice method for daily clinical practice, and one clinical usage in 3D subtyping of samples for prediction and prognosis. This study may serve as basis for a new field of Quantitative Diagnosis where diagnosis, prognosis and prediction are derived from database analysis of protein biomarkers as absolute and continuous variables.

pathology↗

bioRxiv2019

Developing a routine lab test for absolute quantification of Her2 in Formalin Fixed Paraffin Embedded (FFPE) breast cancer tissues using Quantitative Dot Blot (QDB) method

While the transition from current prevailing method of relative and semi-quantitative assessment of solid tumor biomarkers to their absolute quantitation promises improved objectivity, consistency and accuracy in daily clinical practice, this transition is hindered by lacking of suitable technique, especially for Formalin Fixed Paraffin Embedded (FFPE) tissue samples. In this retrospective study, Quantitative Dot Blot (QDB) method was adopted to measure Her2 levels absolutely and quantitatively at protein level using 2X15 m FFPE breast cancer tissue slices collected sequentially and non-selectively from local hospital. Her2 levels measured from 332 samples using two diagnostic antibodies respectively were strongly correlated (r=0.963, p=0.0000). When the result was evaluated with results from IHC or FISH analysis using Receiving Operating Characteristics (ROC) analysis, we were able to achieve 100% sensitivity (95% CI: 95.6% to 100%) and 99.3% specificity (95% CI: 96.14% to 99.98%) with results from IHC analysis using 0.267 nmole/g as cutoff, and 93.02% sensitivity (95%CI: 80.94% to 98.54%) and 93.68% specificity (95% CI: 86.76% to 97.65%) with results from FISH analysis using 0.261 nmole/g as cutoff. Thus, QDB method is demonstrated to provide objective and consistent assessment of Her2 levels in FFPE samples with comparable results from both IHC and FISH analyses. It is also the first method to achieve absolute quantitation of tissue biomarkers in FFPE samples to meet daily clinical need.

pathology↗

bioRxiv2018

Apigenin relaxes rat intrarenal arteries: involvement of Cl- channels and K+ channels

The vasodilator effect of apigenin (API) was demonstrated in a number of vascular beds. We aimed to characterize the vasospasmolytic and electrophysiological effects of apigenin (API) in intrarenal arteries (IRAs). The vascular tone of male rat isolated IRAs was recorded with a myograph. Transmembrane Cl- currents through Ca2+-activated Cl- channels (CaCCs), K+ currents through voltage-gated K+ (Kv) channels and inwardly rectifier K+ (Kir) channels were recorded with patch clamp in the freshly isolated arterial smooth muscle cells (ASMCs). Preincubation with API (10-100 M) concentration-dependently depressed the contractions induced by KCl, 9,11-dideoxy-9,11-methanoepoxy prostaglandin F2 (U46619), phenylephrine and vasopressin without significant preference and the IC50 values were 13.27-26.26 M. Acute application of API elicited instant relaxations in the IRAs precontracted with these vasoconstrictors and the RC50 values were 5.80-24.33 M. API relaxation was attenuated by chloride deprivation, CaCC blockers, Kv blocker and nitric oxide synthase inhibitor, but not by Kir blocker and cyclooxygenase inhibitor. At 10-100 M, API depressed CaCC currents and Kir currents while enhanced Kv currents of IRA ASMCs. The present results demonstrate that API counteracts various vasoconstrictors noncompetitively and nonspecifically and suggest that modulation of CaCCs, Kv and Kir channels of IRA ASMCs is involved in its vasospasmolytic effects.

pharmacology and toxicology↗

bioRxiv2017

Base-resolution mapping reveals distinct m1A methylome in nuclear- and mitochondrial-encoded transcripts

Gene expression can be post-transcriptionally regulated via dynamic and reversible RNA modifications. N1-methyladenosine (m1A) is a recently identified mRNA modification; however, little is known about its precise location, regulation and function. Here, we develop a base-resolution m1A profiling method, based on m1A-induced misincorporation during reverse transcription, and report distinct classes of m1A methylome in the human transcriptome. m1A in 5-UTR, particularly those at the first nucleotide of mRNA, associate with increased translation efficiency. A different subset of m1A exhibit a GUUCRA tRNA-like motif, are evenly distributed in the transcriptome and are dependent on the methyltransferase TRMT6/61A. Additionally, we show for the first time that m1A is prevalent in the mitochondrial-encoded transcripts. Manipulation of m1A level via TRMT61B, a mitochondria-localizing m1A methyltransferase, demonstrates that m1A in mitochondrial mRNA interferes with translation. Collectively, our approaches reveal distinct classes of m1A methylome and provide a resource for functional studies of m1A-mediated epitranscriptomic regulation.

biochemistry↗

bioRxiv2017

Brain-behavior patterns define a dimensional biotype in medication-naïve adults with attention-deficit hyperactivity disorder

BackgroundChildhood-onset attention-deficit hyperactivity disorder (ADHD) in adults is clinically heterogeneous and commonly presents with different patterns of cognitive deficits. It is unclear if this clinical heterogeneity expresses a dimensional or categorical difference in ADHD.\n\nMethodsWe first studied differences in functional connectivity in multi-echo resting-state functional magnetic resonance imaging (rs-fMRI) acquired from 80 medication-naive adults with ADHD and 123 matched healthy controls. We then used canonical correlation analysis (CCA) to identify latent relationships between symptoms and patterns of altered functional connectivity (dimensional biotype) in patients. Clustering methods were implemented to test if the individual associations between resting-state brain connectivity and symptoms reflected a non-overlapping categorical biotype.\n\nResultsAdults with ADHD showed stronger functional connectivity compared to healthy controls, predominantly between the default-mode, cingulo-opercular and subcortical networks. CCA identified a single mode of brain-symptom co-variation, corresponding to an ADHD dimensional biotype. This dimensional biotype is characterized by a unique combination of altered connectivity correlating with symptoms of hyperactivity-impulsivity, inattention, and intelligence. Clustering analyses did not support the existence of distinct categorical biotypes of adult ADHD.\n\nConclusionsOverall, our data advance a novel finding that the reduced functional segregation between default-mode and cognitive control networks supports a clinically important dimensional biotype of childhood-onset adult ADHD. Despite the heterogeneity of its presentation, our work suggests that childhood-onset adult ADHD is a single disorder characterized by dimensional brain-symptom mediators.

neuroscience↗

bioRxiv2017

Deficiency of Voltage-gated Proton Channel Hv1 Leads to hypoinsulinaemia, hyperglycemia and glucose intolerance in mice

Here, we demonstrate that the voltage-gated proton channel Hv1 represents a regulatory mechanism for insulin secretion of pancreatic islet {beta} cell. In vivo, Hv1-de[fi]cient mice display hyperglycemia and glucose intolerance due to reduced insulin secretion, but normal peripheral insulin sensitivity. In vitro, islets of Hv1-de[fi]cient and heterozygous mice, INS-1 (832/13) cells with siRNA-mediated knockdown of Hv1 exhibit a marked defect in glucose- and K+-induced insulin secretion. Hv1 de[fi]ciency decreases both insulin and proinsulin contents, and limits glucose-induced Ca2+ entry and membrane depolarization. Furthermore, loss of Hv1 increases insulin-containing granular pH and decreases cytosolic pH. In addition, histologic studies show a decrease in {beta} cell mass in islets of Hv1-deficient mice. Collectively, our results indicate that Hv1 supports insulin secretion in the {beta} cell by calcium entry, membrane depolarization and intracellular pH regulation.

cell biology↗