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Lee, S.

Publications and source records attributed to Lee, S..

At least 379 records · Page 21Linked to original sources

Parkin is not required to sustain OXPHOS function in adult mammalian tissues

Loss-of-function variants in the PRKN gene encoding the ubiquitin E3 ligase PARKIN cause autosomal recessive early-onset Parkinsons disease (PD). Extensive in vitro and in vivo studies have reported that PARKIN is involved in multiple pathways of mitochondrial quality control, including mitochondrial degradation and biogenesis. However, these findings are surrounded by substantial controversy due to conflicting experimental data. In addition, the existing PARKIN-deficient mouse models have failed to faithfully recapitulate PD phenotypes. Therefore, we have investigated the mitochondrial role of PARKIN during ageing and in response to stress by employing a series of conditional Parkin knockout mice. We report that PARKIN loss does not affect oxidative phosphorylation (OXPHOS) capacity and mitochondrial DNA (mtDNA) levels in the brain, heart, and skeletal muscle of aged mice. We also demonstrate that PARKIN deficiency does not exacerbate the brain defects and the pro-inflammatory phenotype observed in mice carrying high levels of mtDNA mutations. To rule out compensatory mechanisms activated during embryonic development of Parkin-deficient mice, we generated a mouse model where loss of PARKIN was induced in adult dopaminergic (DA) neurons. Surprisingly, also these mice did not show motor impairment or neurodegeneration, and no major transcriptional changes were found in isolated midbrain DA neurons. Finally, we report a patient with compound heterozygous PRKN pathogenic variants that lacks PARKIN and has developed PD. The PARKIN deficiency did not impair OXPHOS activities or induce mitochondrial pathology in skeletal muscle from the patient. Altogether, our results argue that PARKIN is dispensable for OXPHOS function in adult mammalian tissues.

cell biology↗

Online Bayesian Optimization of Nerve Stimulation

ObjectiveIn bioelectronic medicine, neuromodulation therapies induce neural signals to the brain or organs modifying their function. Stimulation devices, capable of triggering exogenous neural signals using electrical wave forms, require a complex and multi-dimensional parameter space in order to control such wave forms. Determining the best combination of parameters (wave form optimization, or dosing) for treating a particular patients illness is therefore challenging. Comprehensive parameter searching for an optimal stimulation effect is often infeasible in a clinical setting, due to the size of the parameter space. Restricting this space, however, may lead to sub-optimal therapeutic results, reduced responder rates, and adverse effects. ApproachAs an alternative to a full parameter search, we present a flexible machine learning, data acquisition and processing framework for optimizing neural stimulation parameters requiring as few steps as possible using Bayesian optimization. Such optimization builds a model of the neural and physiological responses to stimulations enabling it to optimize stimulation parameters and to provide estimates of the accuracy of the response model. The vagus nerve innervates, among other thoracic and visceral organs, the heart, thus controlling heart rate and is therefore ideal for demonstrating the effectiveness of our approach. Main results. The efficacy of our optimization approach was first evaluated on simulated neural responses, then applied to vagus nerve stimulation intraoperatively in porcine subjects. Optimization converged quickly on parameters achieving target heart rates and optimizing neural B-fibre activations despite high intersubject variability. SignificanceAn optimized stimulation waveform was achieved in real time with far fewer stimulations than required by alternative optimization strategies, thus minimizing exposure to side effects. Uncertainty estimates helped avoiding stimulations outside a safe range. Our approach shows that a complex set of neural stimulation parameters can be optimized in real-time for a patient to achieve a personalized precision dosing.

neuroscience↗

Using neural biomarkers to personalize dosing of vagus nerve stimulation

BackgroundVagus nerve stimulation (VNS) is an established therapy for treating a variety of chronic diseases, such as epilepsy, depression, obesity, and for stroke rehabilitation. However, lack of precision and side-effects have hindered its efficacy and extension to new conditions. ObjectiveTo achieve a better understanding of the relationship between VNS parameters and neural and physiological responses to enable the design of personalized dosing procedures to improve precision and efficacy of VNS therapies. MethodsWe used biomarkers from recorded evoked neural activity and short-term physiological responses (throat muscle, cardiac and respiratory activity) to understand the response to a wide range of VNS parameters in anaesthetised pigs. Using signal processing, Gaussian processes (GP) and parametric regression models we analyse the relationship between VNS parameters and neural and physiological responses. ResultsFirstly, we observe inter-subject variability for both neural and physiological responses. Secondly, we illustrate how considering multiple stimulation parameters in VNS dosing can improve the efficacy and precision of VNS therapies. Thirdly, we describe the relationship between different VNS parameters and the evoked neural activity and show how spatially selective electrodes can be used to improve fibre recruitment. Fourthly, we provide a detailed exploration of the relationship between the activations of neural fibre types and different physiological effects, and show that recordings of evoked neural activity are powerful biomarkers for predicting the short-term physiological effects of VNS. Finally, based on these results, we discuss how recordings of evoked neural activity can help design VNS dosing procedures that optimize short-term physiological effects safely and efficiently. ConclusionUnderstanding of evoked neural activity during VNS provide powerful biomarkers that could improve the precision, safety and efficacy of VNS therapies.

neuroscience↗

Nanoprojectile Secondary Ion Mass Spectrometry Enables Multiplexed Analysis of Individual Hepatic Extracellular Vesicles

Extracellular vesicles (EVs) are nanoscale lipid bilayer particles secreted by cells. EVs may carry markers of the tissue of origin and its disease state which makes them incredibly promising for disease diagnosis and surveillance. While the armamentarium of EV analysis technologies is rapidly expanding, there remains a strong need for multiparametric analysis with single EV resolution. Nanoprojectile (NP) secondary ion mass spectrometry (NP-SIMS) relies on bombarding a substrate of interest with individual gold NPs resolved in time and space. Each projectile creates an impact crater of 10-20 nm in diameter while molecules emitted from each impact are mass analyzed and recorded as individual mass spectra. We demonstrate the utility of NP-SIMS for analysis of single EVs derived from normal liver cells (hepatocytes) and liver cancer cells. EVs were captured on antibody (Ab)-functionalized gold substrate then labeled with Abs carrying lanthanide (Ln) MS tags (Ab@Ln). These tags targeted four markers selected for identifying all EVs, and specific to hepatocytes or liver cancer. NP-SIMS was used to detect Ab@Ln-tags co-localized on the same EV and to construct scatter plots of surface marker expression for thousands of EVs with the capability of categorizing individual EVs. Additionally, NP-SIMS revealed information about the chemical nano-environment where targeted moieties co-localized. Our approach allowed analysis of population heterogeneity with single EV resolution and distinguishing between hepatocyte and liver cancer EVs based on surface marker expression. NP-SIMS holds considerable promise for multiplexed analysis of single EVs and may become a valuable tool for identifying and validating EV biomarkers of cancer and other diseases.

bioengineering↗

Proteome-Wide Association Studies for Blood Lipids and Comparison with Transcriptome-Wide Association Studies

Blood lipid traits are treatable and heritable risk factors for heart disease, a leading cause of mortality worldwide. Although genome-wide association studies (GWAS) have discovered hundreds of variants associated with lipids in humans, most of the causal mechanisms of lipids remain unknown. To better understand the biological processes underlying lipid metabolism, we investigated the associations of plasma protein levels with total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL), and low-density lipoprotein cholesterol (LDL) in blood. We trained protein prediction models based on samples in the Multi-Ethnic Study of Atherosclerosis (MESA) and applied them to conduct proteome-wide association studies (PWAS) for lipids using the Global Lipids Genetics Consortium (GLGC) data. Of the 749 proteins tested, 42 were significantly associated with at least one lipid trait. Furthermore, we performed transcriptome-wide association studies (TWAS) for lipids using 9,714 gene expression prediction models trained on samples from peripheral blood mononuclear cells (PBMCs) in MESA and 49 tissues in the Genotype-Tissue Expression (GTEx) project. We found that although PWAS and TWAS can show different directions of associations in an individual gene, 40 out of 49 tissues showed a positive correlation between PWAS and TWAS signed p-values across all the genes, which suggests a high-level consistency between proteome-lipid associations and transcriptome-lipid associations.

genomics↗

Neuronal SNCA transcription during Lewy body formation

BackgroundMisfolded -synuclein (-syn) is believed to contribute to neurodegeneration in Lewy body disease (LBD) based on considerable evidence including a gene-dosage effect observed in relation to point mutations and multiplication of SNCA in familial Parkinsons disease. A contradictory concept proposes early loss of the physiological -syn as the major driver of neurodegeneration. There is a paucity of data on SNCA transcripts in various -syn immunoreactive cytopathologies. MethodsSNCA transcripts in neurons without and with various -syn immunoreactive cytopathologies in the substantia nigra and amygdala in LBD (n = 5) were evaluated using RNAscope combined with immunofluorescence for disease-associated -syn. Single-nucleus RNA sequencing was performed to elucidate cell-type specific SNCA expression in non-diseased frontal cortex (n = 3). ResultsSNCA transcripts in neurons with punctate -syn immunoreactivity were preserved both in the substantia nigra and amygdala but were reduced in neurons with compact -syn inclusions. Only single SNCA transcripts were detected in astrocytes with or without -syn immunoreactivity in the amygdala. Single-nucleus RNA sequencing revealed that excitatory and inhibitory neurons, oligodendrocyte progenitor cells, oligodendrocytes, and homeostatic microglia expressed SNCA transcripts, while expression was largely absent in astrocytes and microglia. ConclusionsThe preserved cellular SNCA expression in the more abundant non-Lewy body type -syn cytopathologies provides a pool for local protein production that can aggregate and serve as a seed for misfolded -syn. Successful segregation of disease-associated -syn is associated with the exhaustion of SNCA production in the terminal cytopathology, the Lewy body. Our observations support a therapeutic strategy incorporating a finely tuned dual approach targeting the elimination of misfolded -syn along with the reduction of the SNCA transcription to avoid feeding of pathological -syn seeding.

pathology↗

Double open syntaxin and UNC-18 P334A mutation leads to excitatory-inhibitory imbalance and impairs multiple aspects of C. elegans behavior

SNARE and Sec/Munc18 proteins are essential in synaptic vesicle exocytosis. Open form t-SNARE syntaxin and UNC-18 P334A are well-studied exocytosis-enhancing mutants. Here we investigate the interrelationship between the two mutations by generating double mutants in various genetic backgrounds in C. elegans. While each single mutation rescued the motility of CAPS/unc-31 and synaptotagmin/snt-1 mutants significantly, double mutations unexpectedly worsened motility or lost their rescuing effects. Electrophysiological analyses revealed that simultaneous mutations of open syntaxin and gain-of-function P334A UNC-18 induces a strong imbalance of excitatory over inhibitory transmission. In liposome fusion assays performed with mammalian proteins, the enhancement of fusion caused by the two mutations individually was abolished when the two mutations were introduced simultaneously, consistent with what we observed in C. elegans. We conclude that open syntaxin and P334A UNC-18 do not have additive beneficial effects, and this extends to C. elegans characteristics such as motility, growth, offspring bared, body size, and exocytosis, as well as liposome fusion in vitro. Our results also reveal unexpected differences between the regulation of exocytosis in excitatory versus inhibitory synapses.

neuroscience↗

PP2A Dephosphorylates Phytochrome-Interacting Factor 3 to Modulate Photomorphogenesis in Arabidopsis

The phytochrome (phy) family of sensory photoreceptors modulates developmental programs in response to ambient light. phys control gene expression in part by directly interacting with the bHLH class of transcription factors, phytochrome-interacting factors (PIFs), and inducing their rapid phosphorylation and degradation. Several kinases have been shown to phosphorylate PIFs and promote their degradation. However, the phosphatases that dephosphorylate PIFs are less investigated. Here we describe the identification of four regulatory subunits of Arabidopsis protein phosphatase 2A (PP2A) family (B, B{beta}, B and B{beta}) that interacted with PIF3 in yeast-two-hybrid, in vitro and in vivo assays. The pp2ab{beta} and b{beta}/b{beta} displayed short hypocotyls, while the overexpression of the B subunits induced longer hypocotyls compared to wild type under red light. The light-induced degradation of PIF3 was faster in b{beta}/b{beta} quadruple mutant compared to wild type. Consistently, immunoprecipitated PP2A A and B subunits directly dephosphorylated PIF3-MYC in vitro. RNA-seq analyses showed that B and B{beta} alter global gene expression in response to red light. PIFs (PIF1, PIF3, PIF4 and PIF5) are epistatic to these four B subunits in regulating hypocotyl elongation under red light. Collectively, these data show an essential function of PP2A in dephosphorylating PIF3 to modulate photomorphogenesis in Arabidopsis.

developmental biology↗

VISTA: An integrated framework for structural variant discovery

Structural variation (SV), refers to insertions, deletions, inversions, and duplications in human genomes. With advances in whole genome sequencing (WGS) technologies, a plethora of SV detection methods have been developed. However, dissecting SVs from WGS data remains a challenge, with the majority of SV detection methods prone to a high false-positive rate, and no existing method able to precisely detect a full range of SVs present in a sample. Previous studies have shown that none of the existing SV callers can maintain high accuracy across various SV lengths and genomic coverages. Here, we report an integrated structural variant calling framework, VISTA (Variant Identification and Structural Variant Analysis) that leverages the results of individual callers using a novel and robust filtering and merging algorithm. In contrast to existing consensus-based tools which ignore the length and coverage, VISTA overcomes this limitation by executing various combinations of top-performing callers based on variant length and genomic coverage to generate SV events with high accuracy. We evaluated the performance of VISTA on using comprehensive gold-standard datasets across varying organisms and coverage. We benchmarked VISTA using the Genome-in-a-Bottle (GIAB) gold standard SV set, haplotype-resolved de novo assemblies from The Human Pangenome Reference Consortium (HPRC)1,2, along with an in-house PCR-validated mouse gold standard set. VISTA maintained the highest F1 score among top consensus-based tools measured using a comprehensive gold standard across both mouse and human genomes. VISTA also has an optimized mode, where the calls can be optimized for precision or recall. VISTA-optimized is able to attain 100% precision and the highest sensitivity among other variant callers. In conclusion, VISTA represents a significant advancement in structural variant calling, offering a robust and accurate framework that outperforms existing consensus-based tools and sets a new standard for SV detection in genomic research.

bioinformatics↗

Optimization of Shoot Regeneration and Application of CRISPR/Cas9 Gene Editing to Cultivated Strawberry

Efficient methods of plant transformation and tissue culture are essential to CRISPR/Cas-based gene editing of crops, but neither is well established in cultivated octoploid strawberry (F xananassa). In the present study, a method for shoot regeneration was established and optimized for two strawberry cultivars commercially grown in Florida, Sweet Sensation(R) Florida 127 FL127) and Florida Brilliance (FB). Runner segments at the tip, node, and petiole obtained from greenhouse-grown plants were used as explants for comparisons of shoot regeneration rate. FL127 showed the highest frequency of shoot regeneration to a basal Murashige and Skoog media (MS) containing 1 mg{middle dot}L-1 of TDZ, 0.05 mg{middle dot}L-1 of BA, and 0.05 mg{middle dot}L-1 of 2,4-D, while FB showed the best response to a lower concentration of BA (0.01 mg{middle dot}L-1) in the same media type. The average conversion frequencies of somatic embryos into shoot regenerations from the runner tips (RT) were 42.8% in FL127 and 56.9% in FB, respectively, with RT being the most prolific in shoot generation for both cultivars. Using these optimized tissue conditions, Agrobacterium-mediated CRISPR/Cas9 gene editing was conducted to evaluate the efficiency of transformation and knockout mutations in the phytoene desaturase (FaPDS) gene of FL127. A total of 234 explants treated with Agrobacterium resulted in an 80.3% regeneration efficiency, with 13.3% of regenerated plants exhibiting partial or complete albino phenotypes. Amplicon sequencing of edited progeny revealed substitutions, insertions, and deletions at the gRNA target sites or flanking regions of all FaPDS homoeologous copies. Our results provide effective methods of tissue culture and transformation for the efficient application of CRISPR-mediated gene editing in cultivated strawberry.

plant biology↗

Nutrient levels control root growth responses to high ambient temperature in plants

Global warming will lead to significantly increased temperatures on earth. Plants respond to high ambient temperature with altered developmental and growth programs, termed thermomorphogenesis. Here we show that thermomorphogenesis is conserved in Arabidopsis, soybean, and rice and that it is linked to a decrease in the levels of the two macronutrients nitrogen and phosphorus. We also find that low external levels of these nutrients abolish root growth responses to high ambient temperature. We show that in Arabidopsis, this is due to the function of the transcription factor ELONGATED HYPOCOTYL 5 (HY5) and its transcriptional regulation of the transceptor NITRATE TRANSPORTER 1.1 (NRT1.1). Soybean and Rice homologs of these genes are expressed consistently with a conserved role in regulating temperature responses in a nitrogen and phosphorus level dependent manner. Overall, our data show that root thermomorphogenesis is a conserved feature in species of the two major groups of angiosperms, monocots and dicots, that it leads to a reduction of nutrient levels in the plant, and that it is dependent on sufficient environmental nutrient supply, a regulatory process mediated by the HY5-NRT1.1 module.

plant biology↗

Pathogenic entero- and salivatypes harbour changes in microbiome virulence and antimicrobial resistance genes with increasing chronic liver disease severity

Background & AimsLife-threatening complications of cirrhosis are triggered by bacterial infections, with the ever-increasing threat of antimicrobial resistance (AMR). Alterations in the gut microbiome in decompensated cirrhosis (DC) and acute-on-chronic liver failure (ACLF) are recognised to influence clinical outcomes, whilst the role of the oral microbiome is still being explored. Our aims were to simultaneously interrogate the gut and oral micro- and mycobiome in cirrhotic patients, and assess microbial community structure overlap in relation to clinical outcomes, as well as alterations in virulence factors and AMR genes. Methods18 healthy controls (HC), 20 stable cirrhotics (SC), 50 DC, 18 ACLF and 15 with non-liver sepsis (NLS) i.e. severe infection but without cirrhosis, were recruited at a tertiary liver centre. Shotgun metagenomic sequencing was undertaken from saliva (S) and faecal (F) samples (paired where possible). Salivatypes and enterotypes based on clustering of genera were calculated and compared in relation to cirrhosis severity and in relation to specific clinical parameters. Virulence and antimicrobial resistance genes (ARGs) were evaluated in both oral and gut niches, and distinct resistotypes identified. ResultsSpecific saliva- and enterotypes revealed a greater proportion of pathobionts with concomitant reduction in autochthonous genera with increasing cirrhosis severity, and in those with hyperammonemia. Overlap between oral and gut microbiome communities was observed and was significantly higher in DC and ACLF vs SC and HCs, independent of antimicrobial, beta-blocker and acid suppressant use. Two distinct gut microbiome clusters [ENT2/ENT3] harboured genes encoding for the phosphoenolpyruvate:sugar phosphotransferase system (PTS) system and other virulence factors in patients with DC and ACLF. Substantial numbers of ARGs (oral: 1,218 and gut: 672) were detected with 575 ARGs common to both sites. The cirrhosis resistome was significantly different to HCs, with three and four resistotypes identified for the oral and gut microbiome, respectively. DiscussionOral and gut microbiome profiles differ significantly with increasing severity of cirrhosis, with progressive dominance of pathobionts and loss of commensals. DC and ACLF have significantly worse microbial diversity than NLS, despite similar antimicrobial exposure, supporting the additive patho-biological effect of cirrhosis. The degree of microbial community overlap between sites, frequency of virulence factors and presence of ARGs, all increment significantly with hepatic decompensation. These alterations may predispose to higher infection risk, poorer response to antimicrobial therapy and worsening outcomes, and provide the rationale for developing non-antibiotic-dependent microbiome-modulating therapies.

physiology↗

NaV1.6 inhibition drives the efficacy of voltage-gated sodium channel inhibitors to prevent electrically induced seizures in both wild type and Scn8aN1768D/+ gain-of-function mice

Inhibitors of voltage-gated sodium channels (NaVs) are important anti-epileptic drugs, but the contribution of specific channel isoforms is unknown since available inhibitors are nonselective. We created a series of compounds with diverse selectivity profiles enabling block of NaV1.6 alone or together with NaV1.2. Mice with a heterozygous gain-of-function mutation (N1768D/+) in Scn8a (encoding NaV1.6) responded with a tonic-clonic seizure to a mild 6 Hz stimulus that was innocuous to wild-type mice. Pharmacologic inhibition of NaV1.6 in Scn8aN1768D/+ mice prevented seizures. Inhibitors were also effective in a direct current maximal electroshock seizure assay in wild-type mice. NaV1.6 inhibition correlated with efficacy in both models, even without inhibition of other CNS NaV isoforms. Our data suggest NaV1.6 inhibition is a driver of efficacy for NaV inhibitor anti-seizure medicines. Selective NaV1.6 inhibitors may provide targeted therapies for human Scn8a developmental and epileptic encephalopathies and better tolerated treatments for idiopathic epilepsies. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=199 SRC="FIGDIR/small/551823v2_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@39c09borg.highwire.dtl.DTLVardef@19413b8org.highwire.dtl.DTLVardef@9aa226org.highwire.dtl.DTLVardef@b9207_HPS_FORMAT_FIGEXP M_FIG C_FIG

pharmacology and toxicology↗

Prediction of metabolites associated with somatic mutations in cancers by using genome-scale metabolic models and mutation data

BackgroundOncometabolites, often generated as a result of a gene mutation, show pro-oncogenic function when abnormally accumulated in cancer cells. Identification of such mutation-associated metabolites will facilitate developing treatment strategies for cancers, but is challenging due to a large number of metabolites in a cell and the presence of multiple genes associated with cancer development. ResultsHere we report the development of a computational workflow that predicts metabolite-gene-pathway sets (MGPs). MGPs present metabolites and metabolic pathways significantly associated with specific somatic mutations in cancers. The computational workflow uses both cancer patient-specific genome-scale metabolic models (GEMs) and mutation data to generate MGPs. A GEM is a computational model that predicts reaction fluxes at a genome scale, and can be constructed in a cell-specific manner by using omics data (e.g., RNA-seq). The computational workflow is first validated by comparing the resulting metabolite-gene (MG) pairs with multi-omics data (i.e., mutation data, RNA-seq data, and metabolome data) from 17 acute myeloid leukemia samples and 21 renal cell carcinoma samples collected in this study. The computational workflow is further validated by evaluating the MGPs predicted for 18 cancer types, by using RNA-seq data publicly available, in comparison with the reported studies. Therapeutic potential of the resulting MGPs is also discussed. ConclusionsValidation of the MGP-predicting computational workflow indicates that a decent number of metabolites and metabolic pathways appear to be significantly associated with specific somatic mutations. The computational workflow and the resulting MGPs will help identify novel oncometabolites, and also suggest cancer treatment strategies.

systems biology↗

Learning high-dimensional reaction coordinates of fast-folding proteins using State Predictive Information Bottleneck and Bias Exchange Metadynamics

Biological events occurring on long timescales, such as protein folding, remain hard to capture with conventional molecular dynamics (MD) simulation. To overcome these limitations, enhanced sampling techniques can be used to sample regions of the free energy landscape separated by high energy barriers, thereby allowing to observe these rare events. However, many of these techniques require a priori knowledge of the appropriate reaction coordinates (RCs) that describe the process of interest. In recent years, Artificial Intelligence (AI) models have emerged as promising approaches to accelerate rare event sampling. However, integration of these AI methods with MD for automated learning of improved RCs is not trivial, particularly when working with undersampled trajectories and highly complex systems. In this study, we employed the State Predictive Information Bottleneck (SPIB) neural network, coupled with bias exchange metadynamics simulations (BE-metaD), to investigate the unfolding process of two proteins, chignolin and villin. By utilizing the high-dimensional RCs learned from SPIB even with poor training data, BE-metaD simulations dramatically accelerate the sampling of the unfolding process for both proteins. In addition, we compare different RCs and find that the careful selection of RCs is crucial to substantially speed up the sampling of rare events. Thus, this approach, leveraging the power of AI and enhanced sampling techniques, holds great promise for advancing our understanding of complex biological processes occurring on long timescales. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=139 SRC="FIGDIR/small/550401v1_ufig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@18a9296org.highwire.dtl.DTLVardef@9dc2f3org.highwire.dtl.DTLVardef@16a0cf8org.highwire.dtl.DTLVardef@1799db1_HPS_FORMAT_FIGEXP M_FIG TABLE OF CONTENT GRAPHIC C_FIG

biophysics↗

Two successive oligomeric Munc13 assemblies scaffold vesicle docking and SNARE assembly to support neurotransmitter release

The critical presynaptic protein Munc13 serves numerous roles in the process of docking and priming synaptic vesicles. Here we investigate the functional significance of two distinct oligomers of the Munc13 core domain (Munc13C) comprising C1-C2B-MUN-C2C. Oligomer interface point mutations that specifically destabilized either the trimer or lateral hexamer assemblies of Munc13C disrupted vesicle docking, trans-SNARE formation, and Ca2+-triggered vesicle fusion in vitro and impaired neurotransmitter secretion and motor nervous system function in vivo. We suggest that a progression of oligomeric Munc13 complexes couples vesicle docking and assembly of a precise number of SNARE molecules to support rapid and high-fidelity vesicle priming.

neuroscience↗

Unlocking the Role of Endothelial MPL Receptor and JAK2V617F Mutation: Insights into Cardiovascular Dysfunction in MPNs and CHIP

Patients with JAK2V617F-positive myeloproliferative neoplasms (MPNs) and clonal hematopoiesis of indeterminate potential (CHIP) are at a significantly higher risk of cardiovascular diseases (CVDs). Endothelial cells (ECs) carrying the JAK2V617F mutation can be detected in many MPN patients. Here, we investigated the impact of endothelial JAK2V617F mutation on CVD development using both transgenic murine models and human induced pluripotent stem cell lines. Our findings revealed that JAK2V617F mutant ECs promote CVDs by impairing endothelial function and undergoing endothelial-to-mesenchymal transition (EndMT). Importantly, we found that inhibiting the endothelial thrombopoietin receptor MPL suppressed JAK2V617F-induced EndMT and prevented cardiovascular dysfunction caused by mutant ECs. These findings propose that targeting the endothelial MPL receptor could be a promising therapeutic approach to manage CVD complications in patients with JAK2V617F-positive MPNs and CHIP. Further investigations into the impact of other CHIP-associated mutations on endothelial dysfunction are needed to improve risk stratification for individuals with CHIP.

cell biology↗

Petascale Homology Search for Structure Prediction

The recent CASP15 competition highlighted the critical role of multiple sequence alignments (MSAs) in protein structure prediction, as demonstrated by the success of the top AlphaFold2-based prediction methods. To push the boundaries of MSA utilization, we conducted a petabase-scale search of the Sequence Read Archive (SRA), resulting in gigabytes of aligned homologs for CASP15 targets. These were merged with default MSAs produced by ColabFold-search and provided to ColabFold-predict. By using SRA data, we achieved highly accurate predictions (GDT_TS > 70) for 66% of the non-easy targets, whereas using ColabFold-search default MSAs scored highly in only 52%. Next, we tested the effect of deep homology search and ColabFolds advanced features, such as more recycles, on prediction accuracy. While SRA homologs were most significant for improving ColabFolds CASP15 ranking from 11th to 3rd place, other strategies contributed too. We analyze these in the context of existing strategies to improve prediction.

bioinformatics↗