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Park, J.

Publications and source records attributed to Park, J..

At least 325 records · Page 18Linked to original sources

Combined CRISPR and proteomics screening reveal a cohesin-CTCF-bound allele contributing to increased expression of RUVBL1 and prostate cancer progression

Genome-wide association studies along with expression quantitative trait loci (eQTL) mapping have identified hundreds of single nucleotide polymorphisms (SNPs) and their target genes in prostate cancer (PCa), yet functional characterization of these risk loci remains challenging. To screen for potential regulatory SNPs, we designed a CRISPRi library containing 9133 guide RNAs (gRNAs) to target 2,166 candidate SNP sites implicated in PCa and identified 117 SNPs that could regulate 90 genes for PCa cell growth advantage. Among these, rs60464856 was covered by multiple gRNAs significantly depleted in the screening (FDR<0.05). Pooled SNP association analysis in the PRACTICAL and FinnGen cohorts showed significantly higher PCa risk for the rs60464856 G allele (pvalue=1.2E-16 and 3.2E-7). Subsequent eQTL analysis revealed that the G allele is associated with increased RUVBL1 expression in multiple datasets. Further CRISPRi and xCas9 base editing proved the rs60464856 G allele leading to an elevated RUVBL1 expression. Furthermore, SILAC-based proteomic analysis demonstrated allelic binding of cohesin subunits at the rs60464856 region, where HiC dataset showed consistent chromatin interactions in prostate cell lines. RUVBL1 depletion inhibited PCa cell proliferation and tumor growth in xenograft mouse model. Gene set enrichment analysis suggested an association of RUVBL1 expression with cell-cycle-related pathways. An increased expression of RUVBL1 and activations of cell-cycle pathways were correlated with poor PCa survival in TCGA datasets. Together, our CRISPRi screening prioritized about one hundred regulatory SNPs essential for prostate cell proliferation. In combination with proteomics and functional studies, we characterized the mechanistic role of rs60464856 and RUVBL1 in PCa progression.

genetics↗

End Binding protein 1 promotes specific motor-cargo association in the cell body prior to axonal delivery of Dense Core Vesicles

Axonal transport is key to neuronal function. Efficient transport requires specific motor-cargo association in the soma, yet the mechanisms regulating this early step remain poorly understood. We found that EBP-1, the C. elegans ortholog of the canonical microtubule end binding protein EB1, promotes the specific association between kinesin-3/KIF1A/UNC-104 and Dense Core Vesicles (DCVs) prior to their axonal delivery. Using single-neuron, in vivo labelling of endogenous cargo and EBs, we observed reduced axonal abundance and reduced secretion of DCV cargo, but not other KIF1A/UNC-104 cargo, in ebp-1 mutants. This reduction could be traced back to fewer exit events from the cell body, where EBP-1 colocalized with the DCV sorting machinery at the trans Golgi, suggesting that this is the site of EBP-1 function. In addition to its microtubule binding CH domain, mammalian EB1 interacted with mammalian KIF1A in an EBH domain dependent manner, and expression of mammalian EB1 or the EBH domain was sufficient to rescue DCV transport in ebp-1 mutants. Our results suggest a model in which kinesin-3 binding and microtubule binding by EBP-1 cooperate to transiently enrich the motor near sites of DCV biogenesis to promote motor-cargo association. In support of this model, tethering either EBP-1 or a kinesin-3 KIF1A/UNC-104 interacting domain from an unrelated protein to the Golgi restored the axonal abundance of DCV proteins in ebp-1 mutants. These results uncover an unexpected role for a microtubule associated protein and provide insight into how specific kinesin-3 cargo are delivered to the axon.

cell biology↗

Multiplexed Methylated DNA Immunoprecipitation Sequencing (Mx-MeDIP-Seq) to Study DNA Methylation Using Low Amounts of DNA

DNA methylation is an epigenetic mark that has a crucial role in regulating gene expression. Aberrant DNA methylation results in severe diseases in humans, such as cancer, autoimmune disease, atherosclerosis, and cardiovascular diseases. Whole-genome bisulfite sequencing and methylated DNA immunoprecipitation are available to study DNA methylation changes, but they are typically used on a few samples at a time. Here, we developed a novel method called Multiplexed Methylated DNA Immunoprecipitation Sequencing (Mx-MeDIP-Seq), that can be used to analyze many DNA samples in parallel, requiring only small amounts of input DNA. In this method, 10 different DNA samples were fragmented, purified, barcoded, and pooled prior to immunoprecipitation. In a head-to-head comparison, we observed 99% correlation between MeDIP-Seq performed individually or combined as Mx-MeDIP-Seq. Moreover, multiplexed MeDIP led to more than 95% normalized percent recovery and a 25-fold enrichment ratio by qPCR, like the enrichment of the conventional method. This technique was successfully performed with as little as 25 ng of DNA, equivalent to 3400 to 6200 cells. Up to 10 different samples were processed simultaneously in a single run. Overall, the Mx-MeDIP-Seq method is cost-effective with faster processing to analyze DNA methylome, making this technique more suitable for high-throughput DNA methylome analysis.

genomics↗

The C. elegans Anchor Cell Transcriptome: Ribosome Biogenesis Drives Cell Invasion through Basement Membrane

Cell invasion through basement membrane (BM) barriers is important in development, immune function, and cancer progression. As invasion through BM is often stochastic, capturing gene expression profiles of cells actively transmigrating BM in vivo remains elusive. Using the stereotyped timing of C. elegans anchor cell (AC) invasion, we generated an AC transcriptome during BM breaching. Through a focused RNAi screen of transcriptionally enriched genes, we identified new invasion regulators, including TCTP (Translationally Controlled Tumor Protein). We also discovered gene enrichment of ribosomal proteins. AC-specific RNAi, endogenous ribosome labeling, and ribosome biogenesis analysis revealed a burst of ribosome production occurs shortly after AC specification, which drives the translation of proteins mediating BM removal. Ribosomes also strongly localize to the ACs endoplasmic reticulum (ER) and the endomembrane system expands prior to invasion. We show that AC invasion is sensitive to ER stress, indicating a heightened requirement for translation of ER trafficked proteins. These studies reveal key roles for ribosome biogenesis and endomembrane expansion in cell invasion through BM and establish the AC transcriptome as a resource to identify mechanisms underlying BM transmigration.

cell biology↗

Cdkn2a regulates beige fat maintenance through BECN1-mediated autophagy

A potential therapeutic target to curb the obesity and diabetes epidemic is thermogenic beige adipocytes. However, beige adipocytes quickly transition into white adipocytes upon removing stimuli. Here, we define the critical role of Cdkn2a as a molecular pedal for the beige-to-white transition. Beige adipocytes lacking Cdkn2a exhibit prolonged lifespan, and mice are more resistant to diet-induced obesity, along with enhanced energy expenditure and improved glucose tolerance. Mechanistic studies demonstrate that Cdkn2a promotes the expression and activity of BECN1 by directly binding to its mRNA and its negative regulator BCL2L1, activating autophagy and accelerating the beige-to-white transition. Notably, reactivating autophagy by pharmacological or genetic methods abolishes beige adipocyte maintenance induced by Cdkn2a-ablation. Furthermore, hyperactive BECN1 alone significantly accelerates the beige-to-white transition. Collectively, these findings show that Cdkn2a-mediated autophagy serves as a brake system for beige adipocyte maintenance and is a highly promising target for anti-obesity and anti-diabetes therapy. HighlightsO_LICdkn2a ablation promotes beige fat maintenance and ameliorates diet-induced obesity C_LIO_LILoss of Cdkn2a retains beige adipocytes by inhibiting BECN1-mediated autophagy C_LIO_LICdkn2a modulates BECN1 by binding to its mRNA and its inhibitor BCL2L1, respectively C_LIO_LIHyperactive BECN1 is sufficient to accelerate the beige-to-white transition C_LI

cell biology↗

Genomic heterogeneity and ploidy identify patients with intrinsic resistance to PD-1 blockade in metastatic melanoma

While the introduction of immune checkpoint blockade (ICB) has dramatically improved clinical outcomes for patients with advanced melanoma, a significant proportion of patients develop resistance to therapy, and mechanisms of resistance are poorly elucidated in most cases. Further, while combination ICB has higher response rates and improved progression free survival compared to single agent therapy in the front line setting, there is significantly increased toxicity with combination ICB, and biomarkers to identify patients who would disproportionately benefit from combination therapy vs aPD-1 ICB are poorly characterized. To understand resistance mechanisms to single vs combination ICB therapy, we analyze whole-exome-sequencing (WES) of pre-treatment tumor and matched normals of 4 cohorts (n=140) of previously ICB-naive aPD-1 ICB treated patients. We find that high intratumoral genomic heterogeneity and low ploidy identify patients with intrinsic resistance to aPD-1 ICB. Comparing to a melanoma cohort from a pre-targeted therapy and ICB time period ("untreated" cohort), we find that genomic heterogeneity specifically predicts response and survival in the ICB treated cohorts, but not in the untreated cohort, while ploidy is also prognostic of overall survival in the "untreated" (by targeted therapy or ICB) group. To establish clinically actionable predictions, we optimize a simple decision tree using genomic ploidy and heterogeneity to identify with high confidence (90% PPV) a subset of patients with intrinsic resistance to and significantly worse survival on aPD1 ICB treatment. We then validate this model in independent cohorts, and further show that a significant proportion of patients predicted to have intrinsic resistance to single agent aPD-1 ICB respond to combination ICB, which suggests that nominated patients may benefit disproportionately from combination ICB. We further show that the features and predictions of the model are independent of known clinical features and previously nominated molecular biomarkers. These findings highlight the clinical and biological importance of genomic heterogeneity and ploidy, and sets a concrete framework towards clinical actionability, broadly advancing precision medicine in oncology.

cancer biology↗

Prior expectation enhances sensorimotor behavior by modulating population tuning and subspace activity in the sensory cortex

Prior knowledge facilitates our perception and goal-directed behaviors in the dynamic world, particularly when sensory input is lacking or noisy. However, the neural mechanisms underlying the improvement in sensorimotor behaviors by prior expectations remain unknown. In this study, we examine the neural activity in the middle temporal (MT) area of visual cortex while monkeys perform a smooth pursuit eye movement task with prior expectation of the visual targets motion direction. Prior expectations discriminately reduce the MT neural responses depending on their preferred directions, only when the sensory evidence is weak. This response reduction effectively sharpens neural population direction tuning. Simulations with a realistic MT population demonstrate that sharpening the tuning explains both the biases and variabilities in smooth pursuit, thus suggesting that neural computations in the sensory area alone can underpin the integration of prior knowledge and sensory evidence. State-space analysis further supports this by revealing neural signals of prior expectation in the MT population activity that correlate with behavioral changes.

neuroscience↗

A Multimodal Atlas of Tumor Metabolism Reveals the Architecture of Gene-Metabolite Co-regulation

Tumor metabolism is controlled by coordinated changes in metabolite abundance and gene expression, but simultaneous quantification of metabolites and transcripts in primary tissue is rare. To overcome this limitation and study gene-metabolite coregulation in cancer, we assembled the Cancer Atlas of Metabolic Profiles (cAMP) of metabolomic and transcriptomic data from 988 tumor/normal specimens spanning 11 cancer types. Meta-analysis of the cAMP revealed two classes of Gene-Metabolite Interactions (GMIs) that transcended cancer types. The first corresponded to a small number of gene-metabolite pairs engaged in direct enzyme-substrate interactions, identifying putative metabolite-pool-size-controlling genes. A second class of GMIs represented a small number of hub metabolites, including quinolinate and NAD+, which correlated to many genes specifically expressed on immune cell populations. These results provide evidence that gene-metabolite coregulation in human tissue arises, in part, from both mechanistic interactions between genes/metabolites, and from metabolic remodeling in specific immune microenvironments.

cancer biology↗

BLEND: A Fast, Memory-Efficient, and Accurate Mechanism to Find Fuzzy Seed Matches in Genome Analysis

Generating the hash values of short subsequences, called seeds, enables quickly identifying similarities between genomic sequences by matching seeds with a single lookup of their hash values. However, these hash values can be used only for finding exact-matching seeds as the conventional hashing methods assign distinct hash values for different seeds, including highly similar seeds. Finding only exact-matching seeds causes either 1) increasing the use of the costly sequence alignment or 2) limited sensitivity. We introduce BLEND, the first efficient and accurate mechanism that can identify both exact-matching and highly similar seeds with a single lookup of their hash values, called fuzzy seed matches. BLEND 1) utilizes a technique called SimHash, that can generate the same hash value for similar sets, and 2) provides the proper mechanisms for using seeds as sets with the SimHash technique to find fuzzy seed matches efficiently. We show the benefits of BLEND when used in read overlapping and read mapping. For read overlapping, BLEND is faster by 2.4x-83.9x (on average 19.3x), has a lower memory footprint by 0.9x-14.1 x (on average 3.8x), and finds higher quality overlaps leading to accurate de novo assemblies than the state-of-the-art tool, minimap2. For read mapping, BLEND is fasterby 0.8x-4.1x (on average 1.7x) than minimap2. Source code is available at https://github.com/CMU-SAFARI/BLEND.

bioinformatics↗

Balance-directed protein engineering of IsPETase enhances both PET hydrolysis activity and thermostability

A mesophilic PETase from Ideonella sakaiensis (IsPETase) has been shown to exhibit high PET hydrolysis activity, but its low thermostability limits its industrial applications. We herein developed an engineering strategy for IsPETase to enhance PET hydrolysis activity, thermostability, and protein folding of the enzyme. Balance-directed Z1-PETase variant outperforms the stability-directed Z2-PETase variant under both mesophilic and thermophilic conditions, although Z2-PETase exhibits higher thermostability than Z1-PETase. The Z1-PETase is also superior to Fast-PETase, Dura-PETase, and LC-CICCG in terms of depolymerization rate regardless of temperature conditions we tested. Thus, maintaining a balance between PET hydrolysis activity and thermostability is essential for the development of high-performance PET hydrolases. In a pH-stat bioreactor, Z1-PETase depolymerized >90% of both transparent and colored post-consumer PET powders within 24 and 8 hours at 40{degrees}C and 55{degrees}C, respectively, demonstrating that the balance-directed IsPETase variant produced herein may be applicable in the bio-recycling of PET.

bioengineering↗

Brain-wide representations of behavior spanning multiple timescales and states in C. elegans

Changes in an animals behavior and internal state are accompanied by widespread changes in activity across its brain. However, how neurons across the brain encode behavior and how this is impacted by state is poorly understood. We recorded brain-wide activity and the diverse motor programs of freely-moving C. elegans and built probabilistic models that explain how each neuron encodes quantitative features of the animals behavior. By determining the identities of the recorded neurons, we created, for the first time, an atlas of how the defined neuron classes in the C. elegans connectome encode behavior. Many neuron classes have conjunctive representations of multiple behaviors. Moreover, while many neurons encode current motor actions, others encode recent actions. Changes in behavioral state are accompanied by widespread changes in how neurons encode behavior, and we identify these flexible nodes in the connectome. Our results provide a global map of how the cell types across an animals brain encode its behavior.

neuroscience↗

Intertumoral lineage diversity and immunosuppressive transcriptional programs in well-differentiated gastroenteropancreatic neuroendocrine tumors

Neuroendocrine tumors (NETs) are rare cancers that may arise in the gastrointestinal tract and pancreas. The fundamental mechanisms driving gastroenteropancreatic (GEP) NET growth remain incompletely elucidated; however, the heterogeneous clinical behavior of GEP-NETs suggests that both cellular lineage dynamics and tumor microenvironment influence tumor pathophysiology. Here, we investigated the single-cell transcriptomes of tumor and immune cells from patients with gastroenteropancreatic NETs. Malignant GEP-NET cells expressed genes and regulons associated with normal, gastrointestinal endocrine cell differentiation and fate determination stages. While tumor and lymphoid compartments sparsely expressed immunosuppressive targets, infiltrating myeloid cells were enriched for alternative immunotherapy pathways including VSIR, Tim3/Gal9, and SIGLEC10. Finally, analysis of paired primary and metastatic tissue specimens from small intestinal NETs demonstrated transcriptional transformation between the primary tumor and its distant metastasis. Our findings highlight the transcriptomic heterogeneity that distinguishes the cellular landscapes of GEP-NET anatomic subtypes and reveal potential avenues for future precision medicine therapeutics.

cancer biology↗

Transcriptional control of motor pool formation and motor circuit connectivity by the LIM-HD protein Isl2

The fidelity of motor control requires the precise positional arrangement of motor pools and the establishment of synaptic connections between these pools. In the developing spinal cord, motor nerves project to specific target muscles and receive proprioceptive input from the muscles via the sensorimotor circuit. LIM-homeodomain transcription factors are known to successively restrict specific motor neuronal fates during neural development; however, it remains unclear to what extent they contribute to limb-based motor pools and locomotor circuits. Here, we showed in mice that deletion of Isl2 resulted in scattered motor pools, primarily in the median motor column and lateral LMC (LMCl) populations, and lacked Pea3 expression in the hindlimb motor pools, accompanied by reduced terminal axon branching and disorganized neuromuscular junctions. Transcriptomic analysis of Isl2- deficient spinal cords revealed that a variety of genes involved in motor neuron differentiation, axon development, and synapse organization were downregulated in hindlimb motor pools. Moreover, the loss of Isl2 impaired sensorimotor connectivity and hindlimb locomotion. Together, our studies indicate that Isl2 plays a critical role in organizing motor pool position and sensorimotor circuits in hindlimb motor pools.

neuroscience↗

Spatial regulation of the glycocalyx component Podocalyxin is a switch for pro-metastatic function

The glycocalyx component and sialomucin Podocalyxin (PODXL) is required for normal tissue development by promoting apical membranes to form between cells, triggering lumen formation. Elevated PODXL expression is also associated with metastasis and poor clinical outcome in multiple tumour types. How PODXL presents this duality in effect remains unknown. We identify an unexpected function of PODXL as a decoy receptor for Galectin-3 (GAL3), whereby the PODXL-GAL3 interaction releases GAL3 repression of integrin-based invasion. Differential cortical targeting of PODXL, regulated by ubiquitination, is the molecular mechanism controlling alternate fates. Both PODXL high versus low surface levels occur in parallel subpopulations within cancer cells. Orthotopic intraprostatic xenograft of PODXL-manipulated cells or those with different surface levels of PODXL define that this axis controls metastasis in vivo. Clinically, interplay between PODXL-GAL3 stratifies prostate cancer patients with poor outcome. Our studies define the molecular mechanisms and context in which PODXL promotes invasion and metastasis.

cell biology↗

A Peptide-Centric Quantitative Proteomics Dataset for the Phenotypic Assessment of Alzheimer's Disease

Alzheimers disease (AD) is a looming public health disaster with limited interventions. Alzheimers is a complex disease that can present with or without causative mutations and can be accompanied by a range of age-related comorbidities. This diverse presentation makes it difficult to study molecular changes specific to AD. To better understand the molecular signatures of disease we constructed a unique human brain sample cohort inclusive of autosomal dominant AD dementia (ADD), sporadic ADD, and those without dementia but with high AD histopathologic burden, and cognitively normal individuals with no/minimal AD histopathologic burden. All samples are clinically well characterized, and brain tissue was preserved postmortem by rapid autopsy. Samples from four brain regions were processed and analyzed by data-independent acquisition LC-MS/MS. Here we present a high-quality quantitative dataset at the peptide and protein level for each brain region. Multiple internal and external control strategies were included in this experiment to ensure data quality. All data are deposited in the ProteomeXchange repositories and available from each step of our processing.

neuroscience↗

Phenotypic alteration of low-density granulocytes in people with pulmonary post-acute sequalae of SARS-CoV-2 infection

Low-density granulocytes (LDGs) are a distinct subset of neutrophils whose increased abundance is associated with the severity of COVID-19. However, the long-term effects of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection on LDG levels and phenotypic alteration remain unexplored. Using participants naive to SARS-CoV-2 (NP), infected with SARS-CoV-2 with no residual symptoms (NRS), and infected with SARS-CoV-2 with chronic pulmonary symptoms (PPASC), we compared LDG levels and their phenotype by measuring the expression of markers for activation, maturation, and neutrophil extracellular trap (NET) formation using flow cytometry. The number of LDGs was significantly elevated in PPASC compared to NP. Individuals infected with SARS-CoV-2 (NRS and PPASC) demonstrated increased CD10+ and CD16HI subset counts of LDGs compared to NP group. Further characterization of LDGs demonstrated that LDGs from PPASC displayed higher NET forming ability and aggregation with platelets compared to LDGs from NP and NRS. Our data demonstrates that mature neutrophils with a heightened activation phenotype remain in circulation long after initial SARS-CoV-2 infection. Persistent elevation of markers for neutrophil activation and NET formation on LDGs, as well as an enhanced proclivity for platelet-neutrophil aggregation (PNA) formation in individuals with PPASC may be associated with the development of long-term pulmonary sequelae.

immunology↗

Proteomics of resilience to Alzheimer's disease identifies brain regional soluble Aβ levels, actin filament processes, and response to injury

Resilience to Alzheimers disease (RAD) is an uncommon combination of high disease burden without dementia that may provide critical insights into limiting the clinical impact of this incurable disease. In this study, we used mass spectrometry-based proteomics to quantify regional protein differences that characterize RAD. Starting with over 700 brain donations, we identified 43 extensively annotated research participants who met stringent inclusion exclusion criteria and analyzed matched isocortical regions, hippocampus, and caudate nucleus. Differential expression analysis of 7,115 soluble proteins identified lower isocortical and hippocampal soluble A{beta} peptide levels as a significant feature of RAD. Protein co-expression analysis revealed a group of 181 densely-interacting proteins significantly associated with RAD that were enriched for actin filament-based process, cellular detoxification, and wound healing in isocortex and hippocampus. We further support our findings using data from 689 human isocortical samples from four independent external cohorts that were the closest approximations of our clinico-pathologic groups. The molecular basis of RAD, a widely replicated state in older adults for which there is no experimental model, likely holds important insights into therapeutic interventions for Alzheimers disease.

neuroscience↗

Seasonal siderophore uptake and biosynthesis associated with carbon flux at Station ALOHA

The North Pacific subtropical gyre is a globally important contributor to carbon uptake and an oligotrophic ecosystem primarily limited by nitrogen. The microbial community is also seasonally exposed to low iron due to biological consumption and seasonally variable iron delivery. In this study, we examined changes in iron uptake rates, dissolved siderophore concentrations, and siderophore biosynthesis at Station ALOHA across time (2013-2016) and depth (surface to 500 m) to observe changes in iron acquisition and internal cycling by the microbial community. The genetic potential for siderophore biosynthesis was widespread throughout the upper water column, and biosynthetic gene clusters peaked in spring and summer along with siderophore concentrations, suggesting changes in nutrient delivery, primary production, and carbon export impact iron acquisition over the seasonal cycle. Dissolved iron turnover times, calculated from iron-amended experiments conducted using surface (15 m) and mesopelagic (300 m) waters, ranged from 9-252 days. The shortest average turnover times at both depths were associated with inorganic iron additions (14{+/-}9 days) and the longest with iron bound to strong siderophores (148{+/-}225 days). Uptake rates of siderophore-bound iron were faster in the mesopelagic waters than in the surface, leading to high Fe:C uptake ratios of heterotrophic bacteria in the upper mesopelagic. The rapid cycling and high demand for Fe at 300 m suggests differences in microbial metabolism and iron acquisition in the mesopelagic compared to surface waters. Together, changes in siderophore production and consumption over the seasonal cycle suggest organic carbon availability impacts iron cycling at Station ALOHA. Scientific Significance StatementMicrobial community production in the subtropical oligotrophic North Pacific is limited by macronutrients such as nitrogen. However, dissolved iron is another important micronutrient that has seasonal inputs from dust and passing eddies, keeping the availability of iron low and episodic. Little attention has been paid to the microbial strategies for dealing with low iron to support primary production in the oligotrophic ocean, or how limited iron availability impacts the processing of sinking particulate organic carbon in this region. In this study, we explore iron cycling including siderophore production and uptake by the microbial community throughout the water column at Station ALOHA to examine how the microbial community adapts and responds to changing iron and carbon availability on seasonal timescales.

bioinformatics↗