Biology subjects

Park, J. H.

Publications and source records attributed to Park, J. H..

70 records · Page 4Linked to original sources

bioRxiv2020

Enabling out-of-clinic human immunity studies via single-cell profiling of capillary blood

An individuals immune system is driven by both genetic and environmental factors that vary over time. To better understand the temporal and inter-individual variability of gene expression within distinct immune cell types, we developed a platform that leverages multiplexed single-cell sequencing and out-of-clinic capillary blood extraction to enable simplified, cost-effective profiling of the human immune system across people and time at single-cell resolution. Using the platform, we detect widespread differences in cell type-specific gene expression between subjects that are stable over multiple days. SummaryIncreasing evidence implicates the immune system in an overwhelming number of diseases, and distinct cell types play specific roles in their pathogenesis.1,2 Studies of peripheral blood have uncovered a wealth of associations between gene expression, environmental factors, disease risk, and therapeutic efficacy.4 For example, in rheumatoid arthritis, multiple mechanistic paths have been found that lead to disease, and gene expression of specific immune cell types can be used as a predictor of therapeutic non-response.12 Furthermore, vaccines, drugs, and chemotherapy have been shown to yield different efficacy based on time of administration, and such findings have been linked to the time-dependence of gene expression in downstream pathways.21,22,23 However, human immune studies of gene expression between individuals and across time remain limited to a few cell types or time points per subject, constraining our understanding of how networks of heterogeneous cells making up each individuals immune system respond to adverse events and change over time.

bioengineering↗

bioRxiv2019

Designing signaling environments to steer transcriptional diversity in neural progenitor cell populations

Stem and progenitor populations within developing embryos are diverse, composed of different subpopulations of precursor cells with varying developmental potential. How these different subpopulations are coordinately regulated by their signaling environments is not well understood. In this paper we develop a framework for controlling progenitor population structure in cell culture using high-throughput single cell mRNA-seq and computational analysis. We find that the natural transcriptional diversity of neural stem cell populations from the developing mouse brain collapses during in vitro culture. Cell populations are depleted of committed neuroblast progenitors and become dominated by a single pre-astrocytic cell population. By analyzing the response of neural stem cell populations to forty combinatorial signaling conditions, we demonstrate that signaling environments can restructure cell populations by modulating the relative abundance of pre-astrocytic and pre-neuronal subpopulations according to a simple log-linear model. Our work demonstrates that single-cell RNA-seq can be applied to learn how to modulate the diversity of stem cell populations, providing a new strategy for population-level stem cell control. HighlightsO_LINatural progenitor diversity in the brain collapses during in vitro culture to a single progenitor type C_LIO_LILoss of progenitor diversity alters fate potential of cells during differentiation C_LIO_LILarge scale single-cell signaling screen identifies signals that reshape population structure towards neuronal cell types C_LIO_LISignals regulate population structure according to a simple log-linear model C_LI GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=89 SRC="FIGDIR/small/890087v3_ufig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@e5286corg.highwire.dtl.DTLVardef@c0e69borg.highwire.dtl.DTLVardef@640b20org.highwire.dtl.DTLVardef@16779e_HPS_FORMAT_FIGEXP M_FIG C_FIG

systems biology↗

bioRxiv2019

Ratiometric bioluminescent sensors towards in vivo imaging of bacterial signaling

Second messenger signaling networks allow cells to sense and adapt to changing environmental conditions. In bacteria, the nearly ubiquitous second messenger molecule cyclic di-GMP coordinates diverse processes such as motility, biofilm formation, and virulence. In bacterial pathogens, these signaling networks allow the bacteria to survive changing environment conditions that are experienced during infection of a mammalian host. While studies have examined the effects of cyclic di-GMP levels on virulence in these pathogens, it has previously not been possible to visualize cyclic di-GMP levels in real time during the stages of host infection. Towards this goal, we generate the first ratiometric, chemiluminescent biosensor scaffold that selectively responds to c-di-GMP. By engineering the biosensor scaffold, a suite of Venus-YcgR-NLuc (VYN) biosensors is generated that provide extremely high sensitivity (KD < 300 pM) and large BRET signal changes (up to 109%). As a proof-of-concept that VYN biosensors can image cyclic di-GMP during host infection, we show that the VYN biosensors function in the context of a tissue phantom model, with only [~]103-104 biosensor-expressing cells required for the measurement. Furthermore, the stable BRET signal suggests that the sensors could be used for long-term imaging of cyclic di-GMP dynamics during host infection. The VYN sensors developed here can serve as robust in vitro diagnostic tools for high throughput screening, as well as genetically encodable tools for monitoring the dynamics of c-di-GMP in live cells, and lay the groundwork for live cell imaging of c-di-GMP dynamics in bacteria during host infection, and other complex environments.

synthetic biology↗

bioRxiv2019

C9orf72-associated arginine-rich dipeptide repeats induce RNA-dependent accumulation of Staufen in nucleus

Accumulation of RNA in the nucleus is one of the pathological features of C9orf72-associated amyotrophic lateral sclerosis and frontotemporal dementia (C9-ALS/FTD), yet its potential toxic cellular consequences remain largely undefined. RNA accumulated in the nucleus may interact with and increase nuclear localization of RNA-binding proteins (RBPs). Here, we show in C9-ALS/FTD Drosophila melanogaster model that Staufen, a double-stranded RBP normally localized in cytoplasm, accumulates in the nucleus, which is in contrast to many nuclear-localized RBPs, such as TDP-43 and FUS, whose cytoplasmic accumulation is thought to be a pathological hallmark of ALS/FTD. We found that in Drosophila neurons expressing arginine-rich dipeptide repeat proteins (DPRs), Staufen accumulated in the nucleus in an RNA-dependent manner. In the nucleus, Staufen localized closely to, and potentially interacts with, heterochromatin and nucleolus in Drosophila C4 da neurons expressing poly(PR), a proline-arginine (PR) DPR. PR toxicity in C4 da neurons increased Fibrillarin staining in the nucleolus, which was enhanced by stau heterozygous mutation. Furthermore, knockdown of fib exacerbated retinal degeneration mediated by PR toxicity, which suggests that increased amount of Fibrillarin by stau heterozygous mutation is protective. Heterozygotic mutation of stau could also mitigate retinal degeneration and rescue viability of flies exhibiting PR toxicity. Taken together, our data show that nuclear accumulation of cytoplasmic protein, such as Staufen, may also be an important pathological feature of C9-ALS/FTD.\n\nAuthor summaryCytoplasmic accumulation of nuclear RNA-binding proteins (RBPs) is one of the common pathological features of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). In C9orf72-associated ALS/FTD fly model, we found that Staufen, a double-stranded (ds) RBP normally localized mostly in cytoplasm, accumulates in the nucleus in an RNA-dependent manner. Next, we checked wherein the nucleus Staufen accumulates and found that Staufen partially co-localizes with heterochromatin and nucleolus. Interestingly, the expression of Fibrillarin, a nucleolar protein, was significantly increased by C9orf72-derived PR toxicity and further augmented by reduction in stau dosage, the gene encoding Staufen. When we knocked down fib, the gene encoding Fibrillarin, PR-induced retinal degeneration was exacerbated. This indicates that increased Fibrillarin expression by stau dosage reduction is protective. Furthermore, when we reduced stau dosage in flies presenting PR toxicity, their retinal degeneration and viability were largely rescued. Based on these data, we suggest that nuclear accumulation of Staufen is an important feature of C9-ALS/FTD and suggest that reducing stau dosage is a promising therapeutic target.

genetics↗

bioRxiv2019

A schizophrenia risk locus alters brain metal transport and plasma glycosylation

A common missense variant in SLC39A8 is convincingly associated with schizophrenia and several additional phenotypes. Homozygous loss-of-function mutations in SLC39A8 result in undetectable serum manganese (Mn) and a Congenital Disorder of Glycosylation (CDG) due to the exquisite sensitivity of glycosyltransferases to Mn concentration. Here, we identified several Mn-related changes in human carriers of the common SLC39A8 missense allele. Analysis of structural brain MRI scans showed a dose-dependent change in the ratio of T2w to T1w signal in several regions. Comprehensive trace element analysis confirmed a specific reduction of only serum Mn, and plasma protein N-glycome profiling revealed reduced complexity and branching. N-glycome profiling from two individuals with SLC39A8-CDG showed similar but more severe alterations in branching that improved with Mn supplementation, suggesting that the common variant exists on a spectrum of hypofunction with potential for reversibility. Characterizing the functional impact of this variant will enhance our understanding of schizophrenia pathogenesis and identify novel therapeutic targets and biomarkers of disease. SummaryA common variant in the manganese transporter SLC39A8 is associated with numerous phenotypes including schizophrenia. Mealer et. al. presents an in-depth analysis of brain MRI and plasma glycomics in human carriers of the common variant, identifying several manganese-related changes with potential for diagnostic and therapeutic biomarker development.

biochemistry↗

bioRxiv2019

Albumin inhibits the activation of hepatic stellate cells by suppressing TGF-β/Smad3 signaling via IL-1β

Activated hepatic stellate cells (HSCs) play a key role in liver fibrosis and inactivating HSCs has been considered a promising therapeutic approach. We previously showed that albumin and its derivative, retinol binding protein (RBP)-albumin domain III fusion protein (named R-III), inhibit HSC activation. Here, we investigate the mode of action of albumin and R-III. NF-{kappa}B in activated HSCs was evenly distributed in the cytoplasm, but albumin expression and R-III treatment (albumin/R-III) induced NF-{kappa}B nuclear translocation via retinoic acid (RA) sequestration, resulting in increased expression of interleukin-1{beta} (IL-1{beta}). In an IL-1{beta} dependent manner, albumin/R-III inhibited Smad3 nuclear translocation via TAK1-, JNK-mediated Smad3 linker phosphorylation and decreased expression of Smad3 target genes, such as -smooth muscle actin and collagen type I. Mutation of the Smad3 linker phosphorylation sites abolished R-III effects on Smad3. In conclusion, our data suggest that the anti-fibrotic effects of albumin/R-III are due to RA sequestration which downregulates RAR-mediated signaling and also TGF-{beta}/Smad3 signaling. This mechanistic elucidation of albumin function in HSCs provides clues to understanding the frequent albumin mutations found in hepatocellular carcinoma.

molecular biology↗

bioRxiv2019

Experimental evolution reveals the genetic basis and systems biology of superoxide stress tolerance

Bacterial response to oxidative stress is of fundamental importance. Oxidative stresses are endogenous, such as reactive oxidative species (ROS) production during respiration, or exogenous in industrial biotechnology, due to culture conditions or product toxicity. The immune system inflicts strong ROS stress on invading pathogens. In this study we make use of Adaptive Laboratory Evolution (ALE) to generate two independent lineages of Escherichia coli with increased tolerance to superoxide stress by up to 500% compared to wild type. We found: 1) that the use of ALE reveals the genetic basis for and systems biology of ROS tolerance, 2) that there are only 6 and 7 mutations, respectively, in each lineage, five of which reproducibly occurred in the same genes (iron-sulfur cluster regulator iscR, putative iron-sulfur repair protein ygfZ, pyruvate dehydrogenase subunit E aceE, succinate dehydrogenase sucA, and glutamine tRNA glnX), and 3) that the transcriptome of the strain lineages exhibits two different routes of tolerance: the direct mitigation and repair of ROS damage and the up-regulation of cell motility and swarming genes mediated through phosphate starvation, which has been linked to biofilm formation and aggregation. These two transcriptomic responses can be interpreted as flight and fight phenotypes.\n\nImportanceBacteria encounter oxidative stress from multiple sources. During pathogenic infections, our bodys immune system releases ROS as a form of antimicrobial defense whilst bacteria used in industrial biotechnology are frequently exposed to genetic modifications and culture conditions which induce oxidative stress. In order to get around the bodys defences, pathogens have developed various adaptations to tolerate high levels of ROS, and these adaptive mechanisms are not always well understood. At the same time, there is a need to improve oxidative stress tolerance for industrially relevant strains in order to increase robustness and productivity. In this study we generate two strains of superoxide tolerant Escherichia coli and identify several adaptive mechanisms. These findings can be directly applied to improve production strain fitness in an industrial setting. They also provide insight into potential virulence factors in other pathogens, highlighting potential targets for antimicrobial compounds.

systems biology↗

bioRxiv2019

Innate immune recognition of a bacterial MAMP leads to conditional activation of pro- or anti-inflammatory responses

Microbe-associated molecular patterns (MAMPs) are recognized by pattern recognition receptors (PRRs) of the innate immune system. Flagellin, the primary component of bacterial flagella, is recognized by membrane TLR5 and cytoplasmic NLRC4 receptors, which promote a vigorous pro-inflammatory response typically associated with bacterial infection. However, herein, we report that the nature of the flagellin-induced response is highly dependent on the physiological state of the tissue. Specifically, in the steady state, epithelial cell detection of flagellin orchestrates an anti-inflammatory response mediated by IL-33-dependent type 2 regulatory T cells while, in the context of injury, it induces a pro-inflammatory response mediated by myeloid cells, IL-18 and Th17 cells. Likewise, in the absence of infection, bacterial symbionts expressing high levels of flagellin induce a type 2 response. These data demonstrate that, depending on the inflammatory state of the milieu, MAMPs can function both as immunogens or tolerogens.

immunology↗

bioRxiv2019

Rqc2 levels alter CAT tail composition, function, and toxicity in S. cerevisiae

The Ribosome-associated Quality Control (RQC) pathway co-translationally marks incomplete polypeptides from stalled translation with two signals that trigger their proteasome-mediated degradation. The E3 ligase Ltn1 adds ubiquitin and Rqc2 directs the large ribosomal subunit to append carboxy-terminal alanine and threonine residues (CAT tails). When excessive amounts of incomplete polypeptides evade Ltn1, CAT-tailed proteins accumulate and can self-associate into aggregates. CAT tail aggregation has been hypothesized to either protect cells by sequestering potentially toxic incomplete polypeptides or harm cells by disrupting protein homeostasis. To distinguish between these possibilities, we modulated CAT tail aggregation in Saccharomyces cerevisiae with genetic and chemical tools to analyze CAT tails in aggregated and un-aggregated states. We found that enhancing CAT tail aggregation induces proteotoxic stress and antagonizes degradation of CAT-tailed proteins, while inhibiting aggregation reverses these effects. Our findings suggest that CAT tail aggregation harms RQC-compromised cells and that preventing aggregation can mitigate this toxicity.

cell biology↗

bioRxiv2019

Electronic Health Records Based Prediction of Future Incidence of Alzheimers Disease Using Machine Learning

Nationwide population-based cohort provides a new opportunity to build a completely automated risk prediction model based on individuals history of health and healthcare beyond existing risk prediction models. We tested the possibility of machine learning models to predict future incidence of Alzheimers disease (AD) using large-scale administrative health data. From the Korean National Health Insurance Service database between 2002 and 2010, we obtained de-identified health data in elders above 65 years (N=40,736) containing 4,894 unique clinical features including ICD-10 codes, medication codes, laboratory values, history of personal and family illness, and socio-demographics. To define incident AD two operational definitions were considered: "definite AD" with diagnostic codes and dementia medication (n=614) and "probable AD" with only diagnosis (n=2,026). We trained and validated a random forest, support vector machine, and logistic regression to predict incident AD in 1,2,3, and 4 subsequent years. For predicting future incidence of AD in balanced samples (bootstrapping), the machine learning models showed reasonable performance in 1-year prediction with AUC of 0.775 and 0.759, based on "definite AD" and "probable AD" outcomes, respectively; in 2-year, 0.730 and 0.693; in 3-year, 0.677 and 0.644; in 4-year, 0.725 and 0.683. The results were similar when the entire (unbalanced) samples were used. Important clinical features selected in logistic regression included hemoglobin level, age, and urine protein level. This study may shed a light on the utility of the data-driven machine learning model based on large-scale administrative health data in AD risk prediction, which may enable better selection of individuals at risk for AD in clinical trials or early detection in clinical settings.

bioinformatics↗

bioRxiv2018

How cancer patients perceive clinical trials (CTs) in the era of CTs: Current perceptional status and differences between common and rare cancers

BackgroundAs perception have been recently highlighted as critical determinants of clinical trials (CTs) in cancer patients, we evaluated current perceptional status of CTs in cancer patients, focusing on differences between common and rare cancers.\n\nMaterials & MethodsFrom November 2015 to May 2017, we prospectively surveyed patients who have received anti-cancer treatment at Asan Medical Center using the PARTAKE questionnaires.\n\nResultsAmong 333 respondents, 70.9% and 29.1% had common and rare cancers, respectively. While 87.7% and 75.3% of patients answered that they heard of and knew about CTs, willingness to participate in CTs was expressed only in approximately 56% of patients although willingness was significantly correlated with awareness and perception. Surprisingly, patients with rare cancers showed significantly lower levels of awareness and perception (64.2% vs 79.9%, p=0.003 and 77.3% vs 91.9%, p<0.001), and consequently less willingness (47.4% vs 58.9%, p=0.06) compared to patients with common cancers. In addition, cancer patients still harbored fear with concerns about safety and reward, and substantial ignorance and mistrust about voluntariness of CTs, which was more predominant in patients with rare cancers.\n\nConclusionsPresent study identified relatively less willingness of CTs in cancer patients compared with generally favorable perception, and highlighted relative perceptional poverty in patients with rare cancers than those with common cancers. Further education and encouragement by research and public entities seem essential to raise motivation of CTs in cancer patients beyond good perception, especially for the patients with rare cancers.

epidemiology↗

bioRxiv2018

Towards Decoding the Metabolic Plasticity in Cancer: Coupling of Gene Regulation and Metabolic Pathways

Metabolic plasticity enables cancer cells to switch their metabolism phenotypes between glycolysis and oxidative phosphorylation (OXPHOS) during tumorigenesis and metastasis. However, it is still largely unknown how cancer cells orchestrate gene regulation to balance their glycolysis and OXPHOS activities for better survival. Here, we establish a theoretical framework to model the coupling of gene regulation and metabolic pathways in cancer. Our modeling results demonstrate a direct association between the activities of AMPK and HIF-1, master regulators of OXPHOS and glycolysis respectively, with the activities of three metabolic pathways: glucose oxidation, glycolysis and fatty acid oxidation (FAO). Guided by the model, we develop metabolic pathway signatures to quantify the activities of glycolysis, FAO and the citric acid cycle of tumor samples by evaluating the expression levels of enzymes involved in corresponding processes. The association of AMPK/HIF-1 activity with metabolic pathway activity, predicted by the model and verified by analyzing the gene expression and metabolite abundance data of patient samples, is further validated by in vitro studies of aggressive triple negative breast cancer cell lines.

systems biology↗

bioRxiv2018

Dissecting heterogeneous cell-populations across signaling and diseaseconditions with PopAlign

Single-cell measurement techniques can now probe gene expression in heterogeneous cell populations from the human body across a range of environmental and physiological conditions. However, new mathematical and computational methods are required to represent and analyze gene expression changes that occur in complex mixtures of single cells as they respond to signals, drugs, or disease states. Here, we introduce a mathematical modeling platform, PopAlign, that automatically identifies subpopulations of cells within a heterogeneous mixture, and tracks gene expression and cell abundance changes across subpopulations by constructing and comparing probabilistic models. Probabilistic models provide a low-error, compressed representation of single cell data that enables efficient large-scale computations. We apply PopAlign to analyze the impact of 40 different immunomodulatory compounds on a heterogeneous population of donor-derived human immune cells as well as patient-specific disease signatures in multiple myeloma. PopAlign scales to comparisons involving tens to hundreds of samples, enabling large-scale studies of natural and engineered cell populations as they respond to drugs, signals or physiological change.

bioinformatics↗

bioRxiv2018

Highly Multiplexed Single-Cell RNA-seq for Defining Cell Population and Transcriptional Spaces

We describe a universal sample multiplexing method for single-cell RNA-seq in which cells are chemically labeled with identifying DNA oligonucleotides. Analysis of a 96-plex perturbation experiment revealed changes in cell population structure and transcriptional states that cannot be discerned from bulk measurements, establishing a cost effective means to survey cell populations from large experiments and clinical samples with the depth and resolution of single-cell RNA-seq.

genomics↗

bioRxiv2018

Wnt signalling drives context-dependent differentiation or proliferation in neuroblastoma

Neuroblastoma is one of the commonest and deadliest solid tumours of childhood, and is thought to result from disrupted differentiation of the developing sympathoadrenergic lineage of the neural crest. Neuroblastoma exhibits intra-and intertumoural heterogeneity, with high risk tumours characterised by poor differentiation, which can be attributable to MYCN-mediated repression of genes involved in neuronal differentiation. MYCN is known to co-operate with oncogenic signalling pathways such as Alk, Akt and MEK/ERK signalling, and, together with c-MYC has been shown to be activated by Wnt signalling in various tissues. However, our previous work demonstrated that Wnt3a/Rspo2 treatment of some neuroblastoma cell lines can, paradoxically, decrease c-MYC and MYCN proteins. This prompted us to define the neuroblastoma-specific Wnt3a/Rspo2-driven transcriptome using RNA sequencing, and characterise the accompanying changes in cell biology.\n\nHere we report the identification of ninety Wnt target genes, and show that Wnt signalling is upstream of numerous transcription factors and signalling pathways in neuroblastoma. Using live-cell imaging, we show that Wnt signalling can drive differentiation of SK-N-BE(2)-C and SH-SY5Y cell-lines, but, conversely, proliferation of SK-N-AS cells. We show that cell-lines that differentiate show induction of pro-differentiation BMP4 and EPAS1 proteins, which is not apparent in the SK-N-AS cells. In contrast, SK-N-AS cells show increased CCND1, phosphorylated RB and E2F1 in response to Wnt3a/Rspo2, consistent with their proliferative response, and these proteins are not increased in differentiating lines. By meta-analysis of the expression of our 90 genes in primary tumour gene expression databases, we demonstrate discrete expression patterns of our Wnt genes in patient cohorts with different prognosis. Furthermore our analysis reveals interconnectivity within subsets of our Wnt genes, with one subset comprised of novel putative drivers of neuronal differentiation repressed by MYCN. Assessment of {beta}-catenin immunohistochemistry shows high levels of {beta}-catenin in tumours with better differentiation, further supporting a role for canonical Wnt signalling in neuroblastoma differentiation.

cancer biology↗

bioRxiv2017

Multi-scale model of the proteomic and metabolic consequences of reactive oxygen species

Catalysis using iron-sulfur clusters and transition metals can be traced back to the last universal common ancestor. The damage to metalloproteins caused by reactive oxygen species (ROS) can completely inhibit cell growth when unmanaged and thus elicits an essential stress response that is universal and fundamental in biology. We develop a computable multi-scale description of the ROS stress response in Escherichia coli. We show that this quantitative framework allows for the understanding and prediction of ROS stress responses at three levels: 1) pathways: amino acid auxotrophies, 2) networks: the systemic response to ROS stress, and 3) genetic basis: adaptation to ROS stress during laboratory evolution. These results show that we can now develop fundamental and quantitative genotype-phenotype relationships for stress responses on a genome-wide basis.

systems biology↗