Biology subjects

Park, K.

Publications and source records attributed to Park, K..

85 records · Page 5Linked to original sources

bioRxiv2020

Transfer of hepatocellular microRNA regulates cytochrome P450 2E1 in renal tubular cells

Extracellular microRNAs have been demonstrated to have the ability to enter kidney tubular cells and modify gene expression. We have used a Dicer-hepatocyte-specific microRNA conditional knock-out (Dicer-CKO) mouse to investigate functional microRNA transfer from liver to kidney under physiological conditions and in the context of drug toxicity. Dicer-CKO mice demonstrated a time-dependent decrease in the hepatocyte-derived microRNA, miR-122, in the kidney in the absence of other microRNA changes. During hepatotoxicity, miR-122 increased in kidney tubular cells; this was abolished in Dicer-CKO mice. Depletion of hepatocyte microRNAs increased expression and activity of the miR-122 target - cytochrome (CYP) P450 2E1 - in the kidney. Serum extracellular vesicles (ECVs) from mice with hepatotoxicity increased proximal tubular cell miR-122 and prevented cisplatin proximal tubular cell toxicity. miR-122 also increased in urinary ECVs during hepatotoxicity in humans. Transfer of microRNA was not restricted to liver injury - we detected miR-499 release with murine cardiac injury, and this correlated with an increase in the kidney. In summary, a physiological transfer of microRNA to the kidney exists, which is increased by liver injury. Regulation of renal drug response due to signalling by microRNA of hepatic origin represents a new paradigm for understanding and preventing nephrotoxicity.

pharmacology and toxicology↗

bioRxiv2019

Enhancing generating and collecting efficiency of single particle upconverting luminescence at low-level power excitation

Upconverting luminescent nanoparticles are photostable, non-blinking, and low chemically toxic fluorophores that are emerging as promising fluorescent probe at single-molecule level. High luminescence intensity upconversion nanoparticles (UCNPs) is achieved with highly doped rare-earth ions co-doped (20% Yb3+) using high excitation power (>2.5 MW/cm2). However, such particles are inadequate for in-vitro live-cell imaging and single-particle tracking since high excitation power can cause photodamage. Here, we compared UCNPs luminescence intensities with different dopants concentrations and presented a more efficient ([~]7x) UCNPs at low excitation power by increasing the concentrations of Yb3+ and Tm3+ dopants (NaYF4: 60% Yb3+, 8% Tm3+) and adding a core-shell structure.

biophysics↗

bioRxiv2019

Machine learning of stochastic gene network phenotypes

A recurrent challenge in biology is the development of predictive quantitative models because most molecular and cellular parameters have unknown values and realistic models are analytically intractable. While the dynamics of the system can be analyzed via computer simulations, substantial computational resources are often required given uncertain parameter values resulting in large numbers of parameter combinations, especially when realistic biological features are included. Simulation alone also often does not yield the kinds of intuitive insights from analytical solutions. Here we introduce a general framework combining stochastic/mechanistic simulation of reaction systems and machine learning of the simulation data to generate computationally efficient predictive models and interpretable parameter-phenotype maps. We applied our approach to investigate stochastic gene expression propagation in biological networks, which is a contemporary challenge in the quantitative modeling of single-cell heterogeneity. We found that accurate, predictive machine-learning models of stochastic simulation results can be constructed. Even in the simplest networks existing analytical schemes generated significantly less accurate predictions than our approach, which revealed interesting insights when applied to more complex circuits, including the extensive tunability of information propagation enabled by feedforward circuits and how even single negative feedbacks can utilize stochastic fluctuations to generate robust oscillations. Our approach is applicable beyond biology and opens up a new avenue for exploring complex dynamical systems.

systems biology↗

bioRxiv2019

Seasonal Variability and Shared Molecular Signatures of Inactivated Influenza Vaccination in Young and Older Adults

The seasonal influenza vaccine is an important public health tool but is only effective in a subset of individuals. The identification of molecular signatures provides a mechanism to understand the drivers of vaccine-induced immunity. Most previously reported molecular signatures of influenza vaccination were derived from a single age group or season, ignoring the effects of immunosenescence or vaccine composition. Thus, it remains unclear how immune signatures of vaccine response change with age across multiple seasons. Here we profile the transcriptional landscape of young and older adults over five consecutive vaccination seasons to identify shared signatures of vaccine response as well as marked seasonal differences. Along with substantial variability in vaccine-induced signatures across seasons, we uncovered a common transcriptional signature 28 days post-vaccination in both young and older adults. However, gene expression patterns associated with vaccine-induced antibody responses were distinct in young and older adults; for example, increased expression of Killer Cell Lectin Like Receptor B1 (KLRB1; CD161) 28 days post-vaccination positively and negatively predicted vaccine-induced antibody responses in young and older adults, respectively. These findings contribute new insights for developing more effective influenza vaccines, particularly in older adults.

immunology↗

bioRxiv2019

Transcription reinitiation by recycling RNA polymerase that diffuses on DNA after releasing terminated RNA

(Abstract)Despite extensive studies on transcription mechanisms, it is unknown how termination complexes are disassembled, especially in what order the components dissociate. Our single-molecule fluorescence study unveils that RNA transcript release precedes RNA polymerase (RNAP) dissociation from DNA template in bacterial intrinsic termination of transcription much more often than concurrent dissociation. As termination is defined by release of product RNA from transcription complex, the subsequent retention of RNAP on DNA constitutes a previously unidentified stage, termed here as recycling. During the recycling stage, RNAPs one-dimensionally diffuse on DNA in downward and upward directions, and these RNAPs can initiate transcription again at nearby promoters in case of retaining a sigma factor. The efficiency of this event, termed here as reinitiation, increases with supplement of a sigma factor. In summary, after releasing RNA product at intrinsic termination, recycling RNAP diffuses on DNA template for reinitiation most times.

biophysics↗

bioRxiv2019

JuLI: accurate detection of DNA fusions in clinical sequencing for precision oncology

Accurate detection of genomic fusions by high-throughput sequencing in clinical samples with inadequate tumor purity and formalin-fixed paraffin embedded (FFPE) tissue is an essential task in precise oncology. We developed the fusion detection algorithm Junction Location Identifier (JuLI) for optimization of high-depth clinical sequencing. We implemented novel filtering steps to minimize false positives and a joint calling function to increase sensitivity in clinical setting. We comprehensively validated the algorithm using high-depth sequencing data from cancer cell lines and clinical samples and whole genome sequencing data from NA12878. We showed that JuLI outperformed state-of-the-art fusion callers in cases with high-depth clinical sequencing and rescued a driver fusion from false negative in plasma cell-free DNA. JuLI is freely available via GitHub (https://github.com/sgilab/JuLI).

bioinformatics↗

bioRxiv2018

Optogenetic activation of SST-positive interneurons restores hippocampal theta oscillation impairment induced by soluble amyloid beta oligomers in vivo

Abnormal accumulation of amyloid {beta} oligomers (A{beta}O) is a hallmark of Alzheimers disease (AD), which leads to learning and memory deficits. Hippocampal theta oscillations that are critical in spatial navigation, learning and memory are impaired in AD. Since GABAergic interneurons, such as somatostatin-positive (SST+) and parvalbumin-positive (PV+) interneurons, are believed to play key roles in the hippocampal oscillogenesis, we asked whether A{beta}O selectively impairs these SST+ and PV+ interneurons. To selectively manipulate SST+ or PV+ interneuron activity in mice with A{beta}O pathology in vivo, we co-injected A{beta}O and adeno-associated virus (AAV) for expressing floxed channelrhodopsin-2 (ChR2) into the hippocampus of SST-Cre or PV-Cre mice. Local field potential (LFP) recordings in vivo in these A{beta}O-injected mice showed a reduction in the peak power of theta oscillations and desynchronization of spikes from CA1 pyramidal neurons relative to theta oscillations compared to those in control mice. Optogenetic-activation of SST+ but not PV+ interneurons in A{beta}O-injected mice fully restored the peak power of theta oscillations and resynchronized the theta spike phases to a level observed in control mice. In vitro whole-cell voltage-clamp recordings in CA1 pyramidal neurons in hippocampal slices treated with A{beta}O revealed that short-term plasticity of SST+ interneuron inhibitory inputs to CA1 pyramidal neurons at theta frequency were selectively disrupted while that of PV+ interneuron inputs were unaffected. Together, our results suggest that dysfunction in inputs from SST+ interneurons to CA1 pyramidal neurons may underlie the impairment of theta oscillations observed in A{beta}O-injected mice in vivo. Our findings identify SST+ interneurons as a target for restoring theta-frequency oscillations in early AD.

neuroscience↗

bioRxiv2018

Optimal diameter reduction ratio of acinar airways in human lungs

In the airway network of a human lung, the airway diameter gradually decreases through multiple branching. The diameter reduction ratio of the conducting airways that transport gases without gas exchange is 0.79, but this reduction ratio changes to 0.94 in acinar airways beyond transitional bronchioles. While the reduction in the conducting airways was previously rationalized on the basis of Murrays law, our understanding of the design principle behind the acinar airways has been far from clear. Here we elucidate that the change in gas transfer mode is responsible for the transition in the diameter reduction ratio. The oxygen transfer rate per unit surface area is maximized at the observed geometry of acinar airways, which suggests the minimum cost for the construction and maintenance of the acinar airways. The results revitalize and extend the framework of Murrays law over an entire human lung.

bioengineering↗

bioRxiv2018

Structural capture of an intermediate transport state of a CLC Cl-/H+ antiporter

The CLC family proteins are involved in a variety of cellular processes, where chloride homeostasis needs to be controlled. Two distinct classes of CLC proteins, Cl- channels and Cl-/H+ antiporters, have been functionally and structurally investigated over the last several decades. Recent studies have revealed that the conformational heterogeneity of the critical glutamate residue, Gluex could explain the transport cycle of CLC-type Cl-/H+ antiporters. However, the presence of multiple conformations of the Gluex has been suggested from combined structural snapshots of two different CLC antiporters. Thus, we aimed to investigate the presence of these three intermediate conformations in CLC-ec1, the most deeply studied CLC at both functional and structural levels. By comparing crystal structures of E148D, E148A mutant and wildtype CLC-ec1 with varying anion concentrations, we suggest that the Gluex indeed take at least three distinct conformational states in a single CLC antiporter, CLC-ec1.

biochemistry↗

bioRxiv2018

Development of an imaging toolbox to assess the therapeutic potential and biodistribution of macrophages in a mouse model of multiple organ dysfunction

Cell-based regenerative medicine therapies require robust preclinical safety, efficacy, biodistribution and engraftment data prior to clinical testing. To address these challenges, we have developed an imaging toolbox comprising multi-spectral optoacoustic tomography and ultrasonography, which allows the degree of kidney, liver and cardiac injury and the extent of functional recovery to be assessed non-invasively in a mouse model of multi-organ dysfunction. This toolbox allowed us to determine the therapeutic effects of adoptively transferred M2 macrophages. Using bioluminescence imaging, we could then investigate the association between amelioration and biodistribution. Macrophage therapy improved kidney and liver function to a limited extent, but did not ameliorate histological damage. No improvement in cardiac function was observed. Biodistribution analysis showed that macrophages homed and persisted in the injured kidneys and liver, but did not populate the heart. Our data suggest that the limited improvement observed in kidney and liver function could be mediated by M2 macrophages.

pharmacology and toxicology↗

bioRxiv2018

The impact of 10-valent Pneumococcal Conjugate Vaccine on the incidence of radiologically-confirmed pneumonia and clinically-defined pneumonia in Kenyan children.

BackgroundPneumococcal conjugate vaccines (PCV) are highly protective against invasive pneumococcal disease caused by vaccine serotypes but the burden of pneumococcal disease in developing countries is dominated by pneumonia, most of which is non-bacteraemic. We examined the impact of PCV on pneumonia incidence.\n\nMethodsWe linked prospective hospital surveillance for clinically-defined WHO severe or very-severe pneumonia at Kilifi County Hospital from 2002-2015 to population surveillance at Kilifi Health and Demographic Surveillance System, comprising 45,000 children aged <5 years. Chest radiographs were read according to a WHO standard. A 10-valent pneumococcal non-typeable Haemophilus influenzae protein D conjugate vaccine (PCV10) was introduced in Kenya in January 2011. In Kilifi, there was a catch-up campaign for children aged <5 years. We estimated the impact of PCV10 on pneumonia incidence through interrupted time series analysis accounting for seasonal and temporal trends.\n\nFindingsThe incidence of admission with clinically-defined pneumonia in 2002/3 was 21{middle dot}7/1000/year in children aged 2-59 months. This declined progressively over 13 years. By the end of March 2011, 61{middle dot}1% of children aged 2-11 months received [≥]2 doses and 62{middle dot}3% of children aged 12-59 months received [≥]1 dose of PCV10. Adjusted incidence rate ratios for admissions with radiologically-confirmed pneumonia, clinically-defined pneumonia, and diarrhoea (control condition), associated with PCV10 introduction, were 0{middle dot}52 (95% CI 0{middle dot}32-0{middle dot}86), 0{middle dot}73 (95% CI 0{middle dot}54-0{middle dot}97) and 0{middle dot}63, (95% CI 0{middle dot}31-1{middle dot}26), respectively. The annual incidence of clinically-defined pneumonia in December 2010 was 12{middle dot}2/1000; this was reduced by 3{middle dot}3/1000 with PCV10 introduction.\n\nInterpretationOver 13 years, hospitalisations for clinically-defined pneumonia declined progressively at Kilifi County Hospital but fell abruptly by 27% in association with PCV10 introduction. The incidence of radiologically-confirmed pneumonia fell by 48%. The burden of childhood pneumonia in Kilifi, Kenya, has been reduced substantially by PCV10.\n\nFundingGavi, Wellcome Trust

epidemiology↗

bioRxiv2018

BALLI: Bartlett-Adjusted Likelihood-based LInear Model Approach for Identifying Differentially Expressed Gene with RNA-seq Data

MotivationTranscriptomic profiles can improve our understanding of the phenotypic molecular basis of biological research, and many statistical methods have been proposed to identify differentially expressed genes under two or more conditions with RNA-seq data. However, statistical analyses with RNA-seq data often suffer from small sample sizes, and global variance estimates of RNA expression levels have been utilized as prior distributions for gene-specific variance estimates, making it difficult to generalize the methods to more complicated settings. We herein proposed a Bartlett-Adjusted Likelihood based LInear mixed model approach (BALLI) to analyze more complicated RNA-seq data. The proposed method estimates the technical and biological variances with a linear mixed effect model, with and without adjusting small sample bias using Bartletts corrections.\n\nResultsWe conducted extensive simulations to compare the performance of BALLI with those of existing approaches (edgeR, DESeq2, and voom). Results from the simulation studies showed that BALLI correctly controlled the type-1 error rates at the various nominal significance levels, and produced better statistical power and precision estimates than those of other competing methods in various scenarios. Furthermore, BALLI was robust to variation of library size. It was also successfully applied to Holstein milk yield data, illustrating its practical value.\n\nAvailability and ImplementationBALLI is implemented as R package and freely available at http://healthstat.snu.ac.kr/software/balli/.\n\nContactwon1@snu.ac.kr\n\nSupplementary InformationSupplementary data are available at Bioinformatics online

bioinformatics↗

bioRxiv2017

Comprehensive Molecular Characterization of Mitochondrial Genomes in Human Cancers

Mitochondria are essential cellular organelles that play critical roles in cancer development. Through International Cancer Genome Consortium, we performed a multidimensional characterization of mitochondrial genomes using the whole-genome sequencing data of ~2,700 patients across 37 cancer types and related RNA-sequencing data. Our analysis presents the most definitive mutational landscape of mitochondrial genomes including a novel hypermutated case. We observe similar mutational signatures across cancer types, suggesting powerful endogenous mutational processes in mitochondria. Truncating mutations are remarkably enriched in kidney, colorectal and thyroid cancers and associated with the activation of critical signaling pathways. We find frequent somatic nuclear transfers of mitochondrial DNA (especially in skin and lung cancers), some of which disrupt therapeutic target genes (e.g., ERBB2). The mitochondrial DNA copy number shows great variations within and across cancers and correlates with clinical variables. Co-expression analysis highlights the function of mitochondrial genes in oxidative phosphorylation, DNA repair, and cell cycle; and reveals their connections with clinically actionable genes. Our study, including an open-access data portal, lays a foundation for understanding the interplays between the cancer mitochondrial and nuclear genomes and translating mitochondrial biology into clinical applications.

genomics↗