Biology subjects

Choi, J.

Publications and source records attributed to Choi, J..

11 recordsLinked to original sources

bioRxiv2018

RefSoil+: A reference for antimicrobial resistance genes on soil plasmids

Plasmids harbor transferable genes that contribute to the functional repertoire of microbial communities, yet their contributions to metagenomes are often overlooked. Environmental plasmids have the potential to spread antibiotic resistance to clinical microbial strains. In soils, high microbiome diversity and high variability in plasmid characteristics present a challenge for studying plasmids. To improve understanding of soil plasmids, we present RefSoil+, a database containing plasmid sequences from 922 soil microorganisms. Soil plasmids were relatively larger than other described plasmids, which is a trait associated with plasmid mobility. There was no relationship between chromosome size and plasmid size or number, suggesting that these genomic traits are independent in soil. Soil-associated plasmids, but not chromosomes, had fewer antibiotic resistance genes than other microorganisms. These data suggest that soils may offer limited opportunity for plasmid-mediated transfer of described antibiotic resistance genes. RefSoil+ can serve as a baseline for the diversity, composition, and host-associations of plasmid-borne functional genes in soil, a utility that will be enhanced as the database expands. Our study improves understanding of soil plasmids and provides a resource for assessing the dynamics of the genes that they carry, especially genes conferring antibiotic resistances.\n\nImportanceSoil-associated plasmids have the potential to transfer antibiotic resistance genes from environmental to clinical microbial strains, which is a public health concern. A specific resource is needed to aggregate knowledge of soil plasmid characteristics so that the content, host-associations, and dynamics of antibiotic resistance genes can be assessed and then tracked between the environment and the clinic. Here, we present RefSoil+, a database of soil-associated plasmids. RefSoil+ presents a contemporary snapshot of antibiotic resistance genes in soil that can serve as a reference as novel plasmids and transferred antibiotic resistances are discovered. Our study broadens our understanding of plasmids in soil and provides a community resource for investigating clinic-environment dynamics of important plasmid-associated genes, including antibiotic resistance genes.

microbiology↗

bioRxiv2018

Critical role of miR-10b in BRafV600E dependent anchorage independent growth and invasion of melanoma cells

Recent high-throughput-sequencing of cancer genomes has identified oncogenic mutations in the BRaf genetic locus as one of the critical events in melanomagenesis. BRaf encodes a serine/threonine kinase that regulates the MAPK/ERK kinase (MEK) and extracellular signal-regulated kinase (ERK) protein kinase cascade. In normal cells, the activity of BRaf is tightly regulated and is required for cell growth and survival. BRaf gain-of-function mutations in melanoma frequently lead to unrestrained growth, enhanced cell invasion and increased viability of cancer cells. Although it is clear that the invasive phenotypes of BRaf mutated melanoma cells are stringently dependent on BRaf-MEK-ERK activation, the downstream effector targets that are required for oncogenic BRaf-mediated melanomagenesis are not well defined. miRNAs have regulatory functions towards the expression of genes that are important in carcinogenesis. We observed that miR-10b expression correlates with the presence of the oncogenic BRaf (BRafV600E) mutation in melanoma cells. While expression of miR-10b enhances anchorage-independent growth of BRaf wild-type melanoma cells, miR-10b silencing decreases BRafV600E cancer cell invasion in vitro. Importantly, the expression of miR-10b is required for BRafV600E-mediated anchorage-independent growth and invasion of melanoma cells in vitro. Taken together our results suggest that miR-10b is an important mediator of oncogenic BRafV600E activity in melanoma.

cancer biology↗

bioRxiv2018

Identification of deleterious and regulatory genomic variations in known asthma loci

BackgroundCandidate gene and genome-wide association studies have identified hundreds of asthma risk loci. The majority of associated variants, however, are not known to have any biological function and are believed to represent markers rather than true causative mutations. We hypothesized that many of these associated markers are in linkage disequilibrium (LD) with the elusive causative variants.\n\nMethodsWe compiled a comprehensive list of 447 asthma-associated variants previously reported in candidate gene and genome-wide association studies. Next, we identified all sequence variants located within the 304 unique genes using whole-genome sequencing data from the 1000 Genomes Project. Then, we calculated the LD between known asthma variants and the sequence variants within each gene. LD variants identified were then annotated to determine those that are potentially deleterious and/or functional (i.e. coding or regulatory effects on the encoded transcript or protein).\n\nResultsWe identified 10,048 variants in LD (r2 > 0.6) with known asthma variants. Annotations of these LD variants revealed that several have potentially deleterious effects including frameshift, alternate splice site, stop-lost, and missense. Moreover, 24 of the LD variants have been reported to regulate gene expression as expression quantitative trait loci (eQTLs).\n\nConclusionsThis study is proof of concept that many of the genetic loci previously associated with complex diseases such as asthma are not causative but represent markers of disease, which are in LD with the elusive causative variants. We hereby report a number of potentially deleterious and regulatory variants that are in LD with the reported asthma loci. These reported LD variants could account for the original association signals with asthma and represent the true causative mutations at these loci.

bioinformatics↗

bioRxiv2018

Whole genome sequencing identifies high-impact variants in well-known pharmacogenomic genes

More than 1,100 genetic loci have been correlated with drug response outcomes but disproportionately few have been translated into clinical practice. One explanation for the low rate of clinical implementation is that the majority of associated variants may be in linkage disequilibrium (LD) with the causal variants, which are often elusive. This study aims to identify and characterize likely causal variants within well-established pharmacogenomic genes using next-generation sequencing data from the 1000 Genomes Project. We identified 69,319 genetic variations within 160 pharmacogenomic genes, of which 8,207 variants are in strong LD (r2 > 0.8) with known pharmacogenomic variants. Of the latter, 8 are coding or structural variants predicted to have high-impact, with 19 additional missense variants that are predicted to have moderate-impact. In conclusion, we identified putatively functional variants within known pharmacogenomics loci that could account for the association signals and represent the missing causative variants underlying drug response phenotypes.

bioinformatics↗

bioRxiv2018

Activation of RIG-I-mediated antiviral signaling triggers autophagy through the MAVS-TRAF6-Beclin-1 signaling axis

Autophagy has been implicated in innate immune responses against various intracellular pathogens. Recent studies have reported that autophagy can be triggered by pathogen recognizing sensors, including Toll-like receptors and cyclic guanosine monophosphate-adenosine monophosphate synthase, to participate in innate immunity. In the present study, we examined whether the RIG-I signaling pathway, which detects viral infections by recognizing viral RNA, triggers the autophagic process. The introduction of polyI:C into the cytoplasm, or Sendai virus infection, significantly induced autophagy in normal cells but not in RIG-I-deficient cells. PolyI:C transfection or Sendai virus infection induced autophagy in the cells lacking type-I interferon signaling. This demonstrated that the effect was not due to interferon signaling. RIG-I-mediated autophagy diminished by the deficiency of mitochondrial antiviral signaling protein (MAVS) or tumor necrosis factor receptor-associated factor (TRAF)6, showing that the RIG-I-MAVS-TRAF6 signaling axis was critical for RIG-I-mediated autophagy. We also found that Beclin-1 was translocated to the mitochondria, and it interacted with TRAF6 upon RIG-I activation. Furthermore, Beclin-1 underwent K63-polyubiquitination upon RIG-I activation, and the ubiquitination decreased in TRAF6-deficient cells. This suggests that the RIG-I-MAVS-TRAF6 axis induced K63-linked polyubiquitination of Beclin-1, which has been implicated in triggering autophagy. Collectively, the results of this study show that the recognition of viral infection by RIG-I is capable of inducing autophagy to control viral replication. As deficient autophagy increases the type-I interferon response, the induction of autophagy by the RIG-I pathway might also contribute to preventing an excessive interferon response as a negative-feedback mechanism.\n\nImportanceMammalian cells utilize various innate immune sensors to detect pathogens. Among those sensors, RIG-I recognizes viral RNA to detect intracellular viral replication. Although cells experience diverse physiological changes upon viral infection, studies to understand the role of RIG-I signaling have focused on the induction of type-I interferon. Autophagy is a process that sequesters cytosolic regions and degrades the contents to maintain cellular homeostasis. Autophagy participates in the immune system, and has been known to be triggered by some innate immune sensors, such as TLR4 and cGAS. We demonstrated that autophagy can be triggered by the activation of RIG-I. In addition, we also proved that MAVS-TRAF6 downstream signaling is crucial for the process. Beclin-1, a key molecule in autophagy, is translocated to mitochondria, where it undergoes K63-ubiquitination in a TRAF6-dependent manner upon RIG-I activation. As autophagy negatively regulates RIG-I-mediated signaling, the RIG-I-mediated activation of autophagy may function as a negative-feedback mechanism.

immunology↗

bioRxiv2018

Building online genomics applications using BioPyramid

BioPyramid is a python package, which can serve as a scaffold for building an online genomics application. BioPyramid contains a number of components designed to reduce the time and effort in building such an application from scratch, including gene annotation, dataset models and visualisation tools. The user can rapidly deploy a data portal with the example dataset included, and start customising components as required. BioPyramid is implemented in python and javascript and freely available at http://github.com/jarny/biopyramid.

bioinformatics↗

bioRxiv2017

Cell-type specific eQTL of primary melanocytes facilitates identification of melanoma susceptibility genes

Most expression quantitative trait loci (eQTL) studies to date have been performed in heterogeneous tissues as opposed to specific cell types. To better understand the cell-type specific regulatory landscape of human melanocytes, which give rise to melanoma but account for <5% of typical human skin biopsies, we performed an eQTL analysis in primary melanocyte cultures from 106 newborn males. We identified 597,335 cis-eQTL SNPs prior to LD-pruning and 4,997 eGenes (FDR<0.05), which are higher numbers than in any GTEx tissue type with a similar sample size. Melanocyte eQTLs differed considerably from those identified in the 44 GTEx tissues, including skin. Over a third of melanocyte eGenes, including key genes in melanin synthesis pathways, were not observed to be eGenes in two types of GTEx skin tissues or TCGA melanoma samples. The melanocyte dataset also identified cell-type specific trans-eQTLs with a pigmentation-associated SNP for four genes, likely through its cis-regulation of IRF4, encoding a transcription factor implicated in human pigmentation phenotypes. Melanocyte eQTLs are enriched in cis-regulatory signatures found in melanocytes as well as melanoma-associated variants identified through genome-wide association studies (GWAS). Co-localization of melanoma GWAS variants and eQTLs from melanocyte and skin eQTL datasets identified candidate melanoma susceptibility genes for six known GWAS loci including unique genes identified by the melanocyte dataset. Further, a transcriptome-wide association study using published melanoma GWAS data uncovered four new loci, where imputed expression levels of five genes (ZFP90, HEBP1, MSC, CBWD1, and RP11-383H13.1) were associated with melanoma at genome-wide significant P-values. Our data highlight the utility of lineage-specific eQTL resources for annotating GWAS findings and present a robust database for genomic research of melanoma risk and melanocyte biology.

genetics↗

bioRxiv2017

Intestinal crypts recover rapidly from focal damage with coordinated motion of stem cells that is impaired by aging

Despite the continuous renewal and turnover of the small intestinal epithelium, the intestinal stem cell niche maintains a soccer ball-like, alternating pattern of stem and Paneth cells in the crypt. To study the robustness of the niche pattern, we used intravital two-photon microscopy in mice with fluorescently-labeled Lgr5+ intestinal stem cells and precisely perturbed the mosaic pattern with femtosecond laser ablation. Ablation of one to three cells initiated rapid motion of niche cells that restored the alternation in the crypt pattern within about two hours without any cell proliferation. Crypt cells then performed a coordinated dilation of the crypt lumen, which resulted in peristalsis-like motion that forced damaged cells out of the niche. Crypt cell motion was reduced with inhibition of the ROCK pathway and attenuated with old age, and both resulted in incomplete pattern recovery. This suggests that in addition to proliferation and self-renewal, motility of stem cells is critical for maintaining homeostasis. Reduction of this novel behavior of stem cells could contribute to disease and age-related changes.

physiology↗

bioRxiv2017

The FACT complex is required for DNA demethylation at heterochromatin during reproduction in Arabidopsis

The DEMETER (DME) DNA glycosylase catalyzes genome-wide DNA demethylation and is required for endosperm genomic imprinting and embryo viability. Targets of DME-mediated DNA demethylation reside in small, euchromatic, AT-rich transposons and at the boundaries of large transposons, but how DME interacts with these diverse chromatin states is unknown. The STRUCTURE SPECIFIC RECOGNITION PROTEIN 1 (SSRP1), subunit of the chromatin remodeler FAcilitates Chromatin Transactions (FACT), was previously shown to be involved in the DME-dependent regulation of genomic imprinting in Arabidopsis endosperm. Therefore, to investigate the interaction between DME and chromatin, we focused on the activity of the two FACT subunits, SSRP1 and SUPPRESSOR of TY16 (SPT16), during reproduction in Arabidopsis. We find that FACT co-localizes with nuclear DME in vivo, and that DME has two classes of target sites, the first being euchromatic and accessible to DME, but the second, representing over half of DME targets, requiring the action of FACT for DME-mediated DNA demethylation genome-wide. Our results show that the FACT-dependent DME targets are GC-rich heterochromatin domains with high nucleosome occupancy enriched with H3K9me2 and H3K27me1. Further, we demonstrate that heterochromatin-associated linker histone H1 specifically mediates the requirement for FACT at a subset of DME-target loci. Overall, our results demonstrate that FACT is required for DME targeting by facilitating its access to heterochromatin.

plant biology↗

bioRxiv2017

Natural Language Processing for Classification of Acute, Communicable Findings on Unstructured Head CT Reports: Comparison of Neural Network and Non-Neural Machine Learning Techniques

Background and PurposeTo evaluate the accuracy of non-neural and neural network models to classify five categories (classes) of acute and communicable findings on unstructured head computed tomography (CT) reports.\n\nMaterials and MethodsThree radiologists annotated 1,400 head CT reports for language indicating the presence or absence of acute communicable findings (hemorrhage, stroke, hydrocephalus, and mass effect). This set was used to train, develop, and evaluate a non-neural classifier, support vector machine (SVM), in comparisons to two neural network models using convolutional neural networks (CNN) and neural attention model (NAM) Inter-rater agreement was computed using kappa statistics. Accuracy, receiver operated curves, and area under the curve were calculated and tabulated. P-values < 0.05 was significant and 95% confidence intervals were computed.\n\nResultsRadiologist agreement was 86-94% and Cohens kappa was 0.667-0.762 (substantial agreement). Accuracies of the CNN and NAM (range 0.90-0.94) were higher than SVM (range 0.88-0.92). NAM showed relatively equal accuracy with CNN for three classes, severity, mass effect, and hydrocephalus, higher accuracy for the acute bleed class, and lower accuracy for the acute stroke class. AUCs of all methods for all classes were above 0.92.\n\nConclusionsO_LINeural network models (CNN & NAM) generally had higher accuracies compared to the non-neural models (SVM) and have a range of accuracies that comparable to the inter-annotator agreement of three neuroradiologists.\nC_LIO_LIThe NAM method adds ability to hold the algorithm accountable for its classification via heat map generation, thereby adding an auditing feature to this neural network.\nC_LI\n\nAbbreviations

neuroscience↗

bioRxiv2017

The SMuSh pathway is essential for survival during growth-induced compressive mechanical stress

Cells that proliferate within a confined environment build up mechanical compressive stress. For example, mechanical pressure emerges in the naturally space-limited tumor environment. However, little is known about how cells sense and respond to mechanical compression. We developed microfluidic bioreactors to enable the investigation of the effects of compressive stress on the growth of the genetically tractable model organism Saccharomyces cerevisiae. We used this system to determine that compressive stress is partly partly sensed through a module consisting of the mucin Msb2, and the cell wall protein Sho1, which act together as a sensor module in one of the two major osmosensing pathways in budding yeast. This signal is transmitted via the MAPKKK kinase Ste11. Thus, we term this mechanosensitive pathway the SMuSh pathway, for Ste11 through Mucin / Sho1 pathway. The SMuSh pathway delays cells in the G1 phase of the cell cycle and improves cell survival in response to growth-induced pressure. We also found that the Cell Wall Integrity (CWI) pathway contributes to the response to mechanical compressive stress. These latter results are confirmed in complimentary experiments in the accompanying manuscript from Mishra et al. When both the SMuSh and the CWI pathways are deleted, cells fail to adapt to compressive stress and all cells lyse at relatively low pressure when grown in confinement. Thus, we define a network that is essential for cell survival during growth under pressure. We term this new mechanosensory system the SCWISh (Survival through the CWI and SMuSh) network.\n\nSignificance StatementGrowth in confined environments leads to the build up of compressive mechanical stresses, which are relevant to diverse fields, from cancer to microbiology. In contrast to tensile stress, little is known about the molecular integration of compressive stresses. In this study, we elucidate the SMuSh pathway, which, together with the Cell Wall Integrity pathway, is essential for viability of the budding yeast S. cerevisiae when growing under mechanical pressure. Pressure-sensing requires the transmembrane mucin, Msb2, which is linked to the actin cortex. Our result raises the intriguing question of whether mucins, widely conserved in eukaryotes and frequently misregulated in cancers, might sense compressive stresses in other organisms, including humans.

cell biology↗