Biology subjects

Kim, B.

Publications and source records attributed to Kim, B..

161 records · Page 9Linked to original sources

bioRxiv2019

An Interscholastic Network to Generate LexA Enhancer Trap Lines in Drosophila

Binary expression systems like the LexA-LexAop system provide a powerful experimental tool kit to study gene and tissue function in developmental biology, neurobiology and physiology. However, the number of well-defined LexA enhancer trap insertions remains limited. In this study, we present the molecular characterization and initial tissue expression analysis of nearly 100 novel StanEx LexA enhancer traps, derived from the StonEx1 index line. This includes 76 insertions into novel, distinct gene loci not previously associated with enhancer traps or targeted LexA constructs. Additionally, our studies revealed evidence for selective transposase-dependent replacement of a previously-undetected KP element on chromosome III within the StanEx1 genetic background during hybrid dysgenesis, suggesting a molecular basis for the over-representation of LexA insertions at the NK7.1 locus in our screen. Production and characterization of novel fly lines were performed by students and teachers in experiment-based genetics classes within a geographically diverse network of public and independent high schools. Thus, unique partnerships between secondary schools and university-based programs have produced and characterized novel genetic and molecular resources in Drosophila for open-source distribution, and provide paradigms for development of science education through experience-based pedagogy.

genetics↗

bioRxiv2018

Classifying Asian Rice Cultivars (Oryza sativa L.) into Indica and Japonica Using Logistic Regression Model with Publicly Available Phenotypic Data

This article introduces how to implement the logistic regression model (LRM) with phenotypic variables for classifying Asian rice (Oryza sativa L.) cultivars into two pivotal subpopulations, indica and japonica. This study took advantage of publicly available data attached to a previous paper. The classification accuracy was assessed using an area under curve (AUC) of a receiver operating characteristic (ROC) curve. Given 24 phenotypic variables for 280 indica/japonica accessions, the LRMs were fitted with up to six phenotypic variables of all possible combinations; the highest AUC accounts for 0.9977, obtained with six variables including panicle number per plant, seed number per panicle, florets per panicle, panicle fertility, straighthead susceptibility and blast resistance. Overall, the more variables there are, the higher the resulting AUCs are. The ultimate purpose of this study is to demonstrate the indica/japonica prediction ability of the LRM when applied to unclassified Asian rice cultivars. To estimate the indica/japonica prediction accuracy, ten-fold cross-validations were conducted 100 times with the 280 indica/japonica accessions using the LRM with parameters that yielded the highest AUC. The resulting prediction accuracy accounted for 0.9779. This suggests that the LRM promises to be a highly effective indica/japonica prediction tool using phenotypic variables in Asian cultivated rice.

systems biology↗

bioRxiv2018

CBFβ-MYH11 interferes with megakaryocyte differentiation via modulating a gene program that includes GATA2 and KLF1

The inv(16) acute myeloid leukemia associated CBF{beta}-MYH11 fusion is proposed to block normal myeloid differentiation, but whether this subtype of leukemia cells is poised for a unique cell lineage remains unclear. Here, we surveyed the functional consequences of CBF{beta} - MYH11 in primary inv(16) patient blasts, upon expression during hematopoietic differentiation in vitro and upon knockdown in cell lines by multi-omics profiling. Our results reveal that primary inv(16) AML cells share common transcriptomic signatures and epigenetic determiners with megakaryocytes and erythrocytes. Using in vitro differentiation systems, we reveal that CBF{beta}-MYH11 knockdown interferes with normal megakaryocyte maturation. Two pivotal regulators, GATA2 and KLF1, are identified to complementally occupy RUNX1 binding sites upon fusion protein knockdown, and overexpression of GATA2 partly restores megakaryocyte directed differentiation suppressed by CBF{beta}-MYH11. Together, our findings suggest that in inv(16) leukemia, the CBF{beta}-MYH11 fusion inhibits primed megakaryopoiesis by attenuating expression of GATA2/KLF1 and interfering with a balanced transcriptional program involving these two factors.

cancer biology↗

bioRxiv2018

Dosage Matters: A Randomized Controlled Trial of Rehabilitation Dose in the Chronic Phase after Stroke

Background and PurposeFor stroke rehabilitation, task-specific training in animal models and human rehabilitation trials is considered important to trigger inherent neuroplasticity, promote motor learning, and functional recovery. Little is known, however, about what constitutes an effective dosage of therapy.\n\nMethodsThis is a parallel group, four arm, single blind, phase I, randomized control trial of four dosages of upper extremity therapy delivered in an outpatient setting during the chronic phase after stroke. Participants were randomized into groups that varied in total dosage of therapy (i.e., 0, 15, 30, or 60 hours). Seven hundred and four participants were assessed for eligibility, 50 were eligible to enroll, 45 were randomized, 44 participated and 41 completed the study. Planned primary analyses used linear mixed effects regression to model baseline to post-intervention changes in the Motor Activity Log-Quality of Movement rating (MALQ) and the Wolf Motor Function Test (WMFT) time score as a function of therapy dosage. A series of hierarchical models were constructed using the MALQ and WMFT.\n\nResultsWe observed a significant dose response curve: the greater the dosage of training, the greater the change in MALQ, with the dose by week slope parameter of 0.0045 ({Delta}MAL/hour/week; p = 0.0011; 95% CI = [0.0019; 0.0071]). Over the 3 weeks of therapy, this corresponds to a gain of 0.81 in MALQ for the 60 hour dose.\n\nConclusionsFor mild-to-moderately impaired stroke survivors, the dosage of a patient-centered, task specific motor therapy was shown to systematically influence the gain in quality of arm use in the natural environment, but not functional capacity as measured in the laboratory. We highlight the importance of recovery outcomes that capture arm use vs. functional capacity.\n\nClinical Trial RegistrationURL: http://www.clinicaltrials.gov. Unique identifier: NCT 01749358

clinical trials↗

bioRxiv2018

Dihydropyrimidinase protects from DNA replication stress caused by cytotoxic metabolites.

Metabolic alterations support cellular transformation. Noticeably, cellular transformation and cancer progression is associated with accumulation of dihydrouracil and dihydrothymine. However, it remains elusive how dihydropyrimidine metabolites affect cellular phenotypes. Dihydropyrimidines are degraded by dihydropyrimidinase (DHP). This zinc metalloenzyme is upregulated in solid tumors but not in the corresponding normal tissues. Here we show that DHP silencing in transformed cell lines is cytotoxic. Increasing the level of dihydropyrimidines inhibited DNA replication and transcription. It induced replication stress signaling by ATR and p53 stabilization. Remarkably, cells lacking DHP accumulated DNA-protein crosslinks (DPCs). Among DPCs, covalently trapped translesion DNA polymerase {eta} contributed to the cytotoxicity of dihydropyrimidines. Furthermore, we show that the plant flavonoid dihydromyricetin inhibits the activity of recombinant human DHP. Cellular treatment with dihydromyricetin triggered DPCs-dependent DNA replication stress. This study defines dihydropyrimidines as potentially cytotoxic metabolites that may offer an opportunity for therapeutic-targeting of DHP activity in solid tumors.

cancer biology↗

bioRxiv2018

Real-time experimental control using network-based parallel processing

Modern neuroscience research often requires the coordination of multiple processes such as stimulus generation, real-time experimental control, as well as behavioral and neural measurements. The technical demands required to simultaneously manage these processes with high temporal fidelity limits the number of labs capable of performing such work. Here we present an open-source network-based parallel processing framework that eliminates these barriers. The Real-Time Experimental Control with Graphical User Interface (REC-GUI) framework offers multiple advantages: (i) a modular design agnostic to coding language(s) and operating system(s) that maximizes experimental flexibility and minimizes researcher effort, (ii) simple interfacing to connect measurement and recording devices, (iii) high temporal fidelity by dividing task demands across CPUs, and (iv) real-time control using a fully customizable and intuitive GUI. Testing results demonstrate that the REC-GUI framework facilitates technically demanding, behavior-contingent neuroscience research. Sample code and hardware configurations are downloadable, and future developments will be regularly released.

neuroscience↗

bioRxiv2018

The aryl hydrocarbon receptor and interferon gamma generate antiviral states via transcriptional repression

The aryl hydrocarbon receptor (AhR) is a ligand-dependent transcription factor whose activation induces the expression of numerous genes, with many effects on cells. However, AhR activation is not known to affect the replication of viruses. We show that AhR activation in macrophages causes a block to HIV-1 and HSV-1 replication. We find that AhR activation transcriptionally represses cyclin-dependent kinase (CDK)1/2 and their associated cyclins, thereby reducing SAMHD1 phosphorylation, cellular dNTP levels and both HIV-1 and HSV-1 replication. Remarkably, a different antiviral stimulus, interferon gamma (IFN-{gamma}), that induces a largely non-overlapping set of genes, also transcriptionally represses CDK1, CDK2 and their associated cyclins, resulting in similar dNTP depletion and antiviral effects. Concordantly, the SIV Vpx protein provides complete and partial resistance to the antiviral effects of AhR and IFN-{gamma}, respectively. Thus, distinct antiviral signaling pathways converge on CDK/cyclin repression, causing inhibition of viral DNA synthesis and replication.

immunology↗

bioRxiv2018

Cohesin interacts with a panoply of splicing factors required for cell cycle progression and genomic organization

The cohesin complex regulates sister chromatid cohesion, chromosome organization, gene expression, and DNA repair. Here we report that endogenous human cohesin interacts with a panoply of splicing factors and RNA binding proteins, including diverse components of the U4/U6.U5 tri-snRNP complex and several splicing factors that are commonly mutated in cancer. The interactions are enhanced during mitosis, and the interacting splicing factors and RNA binding proteins follow the cohesin cycle and prophase pathway of regulated interactions with chromatin. Depletion of cohesin-interacting splicing factors results in stereotyped cell cycle arrests and alterations in genomic organization. These data support the hypothesis that splicing factors and RNA binding proteins control cell cycle progression and genomic organization via regulated interactions with cohesin and chromatin.\n\nOne Sentence SummaryEndogenous tagging reveals that cohesin interacts with diverse chromatin-bound splicing factors that regulate cell cycle progression and genomic organization in human cells.

cell biology↗

bioRxiv2018

Thymidylate synthase maintains the de-differentiated state of aggressive breast cancers

Cancer cells frequently boost nucleotide metabolism (NM) to support their increased proliferation, but the consequences of elevated NM on tumor de-differentiation are mostly unexplored. Here, we identified a role for thymidylate synthase (TS), a NM enzyme and established drug target, in cancer cell de-differentiation and investigated its clinical significance in breast cancer (BC). In vitro, TS knockdown increased the population of CD24+ differentiated cells, and attenuated migration and sphere-formation. RNA-seq profiling indicated a repression of epithelial-to-mesenchymal transition (EMT) signature genes upon TS knockdown, and TS-deficient cells showed an increased ability to invade and metastasize in vivo, consistent with the occurrence of a partial EMT phenotype. Mechanistically, TS enzymatic activity was found essential for the maintenance of the EMT/stem-like state by fueling a DPYD-dependent pyrimidine catabolism. In patient tissues, TS levels were found significantly higher in poorly differentiated and in triple negative BC (TNBC), and strongly correlated with worse prognosis. The present study provides the rationale to study in-depth the role of NM at the crossroads of proliferation and differentiation, and depicts new avenues for the design of novel drug combinations for the treatment of BC.

cancer biology↗

bioRxiv2018

Causal Evidence for the Dependence of the Magnitude Effect on Dorsolateral Prefrontal Cortex

Impulsivity refers to the tendency to insufficiently consider alternatives or to overvalue rewards that are available immediately. Impulsivity is a hallmark of human decision making with well documented health and financial ramifications. Numerous contextual changes and framing manipulations powerfully influence impulsivity. One of the most robust such phenomenon is the finding that people are more patient as the values of choice options are increased. This magnitude effect has been related to cognitive control mechanisms in the dorsal lateral prefrontal cortex (dlPFC). We used repetitive transcranial magnetic stimulation (rTMS) to transiently disrupt dlPFC neural activity. This manipulation dramatically reduced the magnitude effect, establishing causal evidence that the magnitude effect depends on dlPFC.

neuroscience↗

bioRxiv2018

A direct glia-to-neuron natural transdifferentiation ensures nimble sensory-motor coordination of male mating behaviour

The coordinated execution of innate, stereotyped sexual behaviours, such as courtship and mating, requires sexually dimorphic sensory-motor circuits that are genetically specified during development (reviewed in [1-3]). Studies in the nematode Caenorhabditis elegans, in which the development and function of neural circuits can be interrogated with single cell resolution, have revealed two general developmental mechanisms underlying sexual dimorphism in the nervous system. The first involves the acquisition of sexually dimorphic features in sex-shared neurons during sexual maturation, which include changes in terminal gene expression, such as odorant receptors, neurotransmitters and synaptic regulators [4-10]. The second mechanism involves the generation of sex-specific neurons [11-13]. This requires sex-specific cell death [14]or neurogenesis events resulting from extensive sex differences in the cell division patterns and neurodevelopmental programmes of post-embryonic cell lineages (reviewed in [3]). Here we identify a third, novel way to generate sexual dimorphism in the nervous system. We find that during sexual maturation (L4 stage), a class of sex-shared glial cells acquires sexually dimorphic function by undergoing a direct glia-to-neuron transdifferentiation that results in the production of male-specific neurons. This plasticity is regulated cell-intrinsically by the sex-determination pathway. These previously unnoticed neurons, which we term PHDs, are putative proprioceptors that regulate male locomotion during specific steps of mating. One of these steps is a novel readjustment movement performed when intromission becomes difficult to achieve. Our results reveal sex-specific direct transdifferentiation as a novel mechanism for generating sex-specific neurons and also show the importance of proprioceptive feedback during the complex steps of mating for successful reproduction.

neuroscience↗

bioRxiv2018

Evaluating Tumor Evolution via Genomic Profiling of Individual Tumor Spheroids in a Malignant Ascites from a Patient with Ovarian Cancer Using a Laser-aided Cell Isolation Technique

BackgroundEpithelial ovarian cancer (EOC) is a silent but mostly lethal gynecologic malignancy. Most patients present with malignant ascites and peritoneal seeding at diagnosis. In the present study, we used a laser-aided isolation technique to investigate the clonal relationship between the primary tumor and tumor spheroids found in the malignant ascites of an EOC patient. Somatic alteration profiles of ovarian cancer-related genes were determined for eight spatially separated samples from primary ovarian tumor tissues and ten tumor spheroids from the malignant ascites using next-generation sequencing.\n\nResultsWe observed high levels of intra-tumor heterogeneity (ITH) in copy number alterations (CNAs) and single-nucleotide variants (SNVs) in the primary tumor and the tumor spheroids. As a result, we discovered that tumor cells in the primary tissues and the ascites were genetically different lineages. We categorized the CNAs and SNVs into clonal and subclonal alterations according to their distribution among the samples. Also, we identified focal amplifications and deletions in the analyzed samples. For SNVs, a total of 171 somatic mutations were observed, among which 66 were clonal mutations present in both the primary tumor and the ascites, and 61 and 44 of the SNVs were subclonal mutations present in only the primary tumor or the ascites, respectively.\n\nConclusionsBased on the somatic alteration profiles, we constructed phylogenetic trees and inferred the evolutionary history of tumor cells in the patient. The phylogenetic trees constructed using the CNAs and SNVs showed that two branches of the tumor cells diverged early from an ancestral tumor clone during an early metastasis step in the peritoneal cavity. Our data support the monophyletic spread of tumor spheroids in malignant ascites.

cancer biology↗

bioRxiv2017

miCloud: a plug and play, on-premises bioinformatics cloud, providing seamless integration with Illumina genome sequencers

Benchtop genome sequencers such as the Illumina MiSeq or MiniSeq [1], [2] are revolutionizing genomics research for smaller, independent laboratories, by enabling access to low-cost Next Generation Sequencing (NGS) technology in-house. These benchtop genome sequencing instruments require only standard laboratory equipment, in addition to minimal time for sample preparation. However, post-sequencing bioinformatics data analysis still presents a significant bottleneck, for research laboratories lacking specialized software and technical data analysis skills on their teams. While bioinformatics computes clouds providing solutions following a Software as a Service (SaaS) are available ([3]-[6], review in [7]), currently, there are only a few options which are user-friendly for non-experts while at the same time are also low-cost or free. One primary example is Illumina BaseSpace [8] that is very easy to access by non-experts, and also offers an integrated solution where data are streamed directly from the MiSeq sequencing instrument to the cloud. Once the data is on the BaseSpace cloud, users can access a range of bioinformatics applications with pre-installed algorithms through an intuitive web interface. Nonetheless, BaseSpace can be a costly solution as a yearly subscription depending on whether the user is associated with an academic or private institution, ranges in price from $999 - $4,999. Additional \"iCredits\" [9] might need to be purchased for frequent users that exhaust the base credit allowance as part of the subscription. Considering the reduction of computer hardware cost in recent years, a multi-core Intel Xeon server with 64 GigaByte (GB) of memory and multiple TeraByte (TB) of storage is priced less than the yearly subscription to Basespace [10], and similarly when compared to renting compute cycles from providers such as Amazon Web Services (AWS) [11]. Furthermore, the current generation of laptops usually come with 6-10 GigaBytes (GB) of memory and 1 TeraByte (TB) of storage, providing enough computational capacity to analyze data from small NGS experiments [12] that include only a few samples.

bioinformatics↗

bioRxiv2017

The Anatomical Tracings of Lesions After Stroke (ATLAS) Dataset - Release 1.1

Stroke is the leading cause of adult disability worldwide, with up to two-thirds of individuals experiencing long-term disabilities. Large-scale neuroimaging studies have shown promise in identifying robust biomarkers (e.g., measures of brain structure) of long-term stroke recovery following rehabilitation. However, analyzing large rehabilitation-related datasets is problematic due to barriers in accurate stroke lesion segmentation. Manually-traced lesions are currently the gold standard for lesion segmentation on T1-weighted MRIs, but are labor intensive and require anatomical expertise. While algorithms have been developed to automate this process, the results often lack accuracy. Newer algorithms that employ machine-learning techniques are promising, yet these require large training datasets to optimize performance. Here we present ATLAS (Anatomical Tracings of Lesions After Stroke), an open-source dataset of 304 T1-weighted MRIs with manually segmented lesions and metadata. This large, diverse dataset can be used to train and test lesion segmentation algorithms and provides a standardized dataset for comparing the performance of different segmentation methods. We hope ATLAS release 1.1 will be a useful resource to assess and improve the accuracy of current lesion segmentation methods.

neuroscience↗

bioRxiv2017

Multiple conserved cell adhesion protein interactions mediate neural wiring of a sensory circuit in C. elegans

Nervous system function relies on precise synaptic connections. A number of widely-conserved cell adhesion proteins are implicated in cell recognition between synaptic partners, but how these proteins act as a group to specify a complex neural network is poorly understood. Taking advantage of known connectivity in C. elegans, we identified and studied cell adhesion genes expressed in three interacting neurons in the mating circuits of the adult male. Two interacting pairs of cell surface proteins independently promote fasciculation between sensory neuron HOA and its postsynaptic target interneuron AVG: BAM-2/neurexin-related in HOA binds to CASY-1/calsyntenin in AVG; SAX-7/L1CAM in sensory neuron PHC binds to RIG-6/contactin in AVG. A third, basal pathway results in considerable HOA-AVG fasciculation and synapse formation in the absence of the other two. The features of this multiplexed mechanism help to explain how complex connectivity is encoded and robustly established during nervous system development.

neuroscience↗

bioRxiv2017

Fast functional annotation of metagenomic shotgun data by DNA alignment to a microbial gene catalog

BackgroundMetagenomic shotgun sequencing is becoming increasingly popular to study microbes associated with the human body and in environmental samples. A key goal of shotgun metagenomic sequencing is to identify gene functions and metabolic pathways that differ between samples or conditions. However, current methods to identify function in the large number of reads in a high-throughput sequence data file rely on the computationally intensive and low stringency approach of mapping each read to a generic database of proteins or reference microbial genomes.\n\nResultsWe have developed an alternative analysis approach for shotgun metagenomic sequence data utilizing Bowtie2 DNA-DNA alignment of the reads to a database of well annotated genes compiled from human microbiome data. This method is rapid, and provides high stringency matches (>90% DNA sequence identity) of shotgun metagenomics reads to genes with annotated functions. We demonstrate the use of this method with synthetic data, Human Microbiome Project shotgun metagenomic data sets, and data from a study of liver disease. Differentially abundant KEGG gene functions can be detected in these experiments.\n\nConclusionsFunctional annotation of metagenomic shotgun sequence reads can be accomplished by rapid DNA-DNA matching to a custom database of microbial sequences using the Bowtie2 sequence alignment tool. This method can be used for a variety of microbiome studies and allows functional analysis which is otherwise computationally demanding. This rapid annotation method is freely available as a Galaxy workflow within a Docker image.

bioinformatics↗

bioRxiv2017

Bio-Docklets: Virtualization Containers for Single-Step Execution of NGS Pipelines.

BackgroundProcessing of Next-Generation Sequencing (NGS) data requires significant technical skills, involving installation, configuration, and execution of bioinformatics data pipelines, in addition to specialized post-analysis visualization and data mining software. In order to address some of these challenges, developers have leveraged virtualization containers, towards seamless deployment of preconfigured bioinformatics software and pipelines on any computational platform.\n\nFindingsWe present an approach for abstracting the complex data operations of multi-step, bioinformatics pipelines for NGS data analysis. As examples, we have deployed two pipelines for RNAseq and CHIPseq, pre-configured within Docker virtualization containers we call Bio-Docklets. Each Bio-Docklet exposes a single data input and output endpoint and from a user perspective, running the pipelines is as simple as running a single bioinformatics tool. This is achieved through a \"meta-script\" that automatically starts the Bio-Docklets, and controls the pipeline execution through the BioBlend software library and the Galaxy Application Programming Interface (API). The pipelne output is post-processed using the Visual Omics Explorer (VOE) framework, providing interactive data visualizations that users can access through a web browser.\n\nConclusionsThe goal of our approach is to enable easy access to NGS data analysis pipelines for nonbioinformatics experts, on any computing environment whether a laboratory workstation, university computer cluster, or a cloud service provider. Besides end-users, the Bio-Docklets also enables developers to programmatically deploy and run a large number of pipeline instances for concurrent analysis of multiple datasets.

bioinformatics↗