Biology subjects

Lee, I.

Publications and source records attributed to Lee, I..

71 records · Page 4Linked to original sources

bioRxiv2020

Human reference gut microbiome comprising 5,414 prokaryotic species, including newly assembled genomes from under-represented Asian metagenomes

Metagenome sampling bias for geographical location and lifestyle is partially responsible for the incomplete catalog of reference genomes of gut microbial species. Here, we present a substantially expanded microbiome catalog, the Human Reference Gut Microbiome (HRGM). Incorporating newly assembled 29,082 genomes from 845 fecal samples collected from three under-represented Asian countries--Korea, India, and Japan--the HRGM contains 232,098 non-redundant genomes of 5,414 representative prokaryotic species, >103 million unique proteins, and >274 million single-nucleotide variants. This is an over 10% increase from the largest reference database. The newly assembled genomes were enriched for members of the Bacteroidaceae family, including species associated with high-fiber and seaweed-rich diet. Single-nucleotide variant density was positively associated with the speciation rate of gut commensals. Ultra-deep sequencing facilitated the assembly of genomes of low-abundance taxa, and deep sequencing (>20 million read pairs) was needed for the profiling of low-abundance taxa. Importantly, the HRGM greatly improved the taxonomic and functional classification of sequencing reads from fecal samples. Finally, mapping homologous sequences for human auto-antigens onto the HRGM genomes revealed the association of commensal bacteria with high cross-reactivity potential with autoimmunity. The HRGM (www.mbiomenet.org/HRGM/) will facilitate the identification and functional analysis of disease-associated gut microbiota.

microbiology↗

bioRxiv2020

Kv1.2 contributes to pattern separation by regulating the hippocampal CA3 neuronal ensemble size

Kv1.2 expression in rodent CA3 pyramidal cells (CA3-PC) is polarized to distal apical dendrites, and regulate the synaptic responses to perforant pathway (PP) inputs. Accordingly, Kv1.2 haploinsufficiency (Kcna2+/-) in CA3-PCs, but not Kv1.1 (Kcna1+/-), lowered the threshold for long-term potentiation at PP-CA3 synapses. The Kcna2+/- mice, but not Kcna1+/-, displayed impairments in contextual fear discrimination task. The size and overlap of CA3 ensembles activated by the first visits to slightly different contexts were not different between wildtype and Kcna2+/- mice, but these ensemble parameters diverged over training days between genotypes, suggesting abnormal plastic changes in the CA3 network of Kcna2+/- mice. Eventually, the Kcna2+/- mice exhibited larger ensemble size and overlap upon retrieval of two contexts, compared to wildtype or Kcna1+/- mice. These results suggest that Kv1.2 subunits prevent promiscuous plastic changes at PP-CA3 synapses, and contribute to sparse representation of memories and pattern separation in the CA3 network.

neuroscience↗

bioRxiv2020

Computational Study of Ions and Water Permeation and Transportation Mechanisms of the SARS-CoV-2 Pentameric E Protein Channel

Coronavirus disease 2019 (COVID-19) is caused by a novel coronavirus (SARS-CoV-2) and represents the causative agent of a potentially fatal disease that is of public health emergency of international concern. Coronaviruses, including SARS-CoV-2, encode an envelope (E) protein, which is a small, hydrophobic membrane protein; the E protein of SARS-CoV-2 has high homology with that of severe acute respiratory syndrome coronavirus. (SARS-CoV) In this study, we provide insights into the function of the SARS-CoV-2 E protein channel and the ion and water permeation mechanisms on the basis of combined in silico methods. Our results suggest that the pentameric E protein promotes the penetration of monovalent ions through the channel. Analysis of the potential mean force (PMF), pore radius and diffusion coefficient reveals that Leu10 and Phe19 are the hydrophobic gates of the channel. In addition, the pore demonstrated a clear wetting/dewetting transition with monovalent cation selectivity under transmembrane voltage, which indicates that it is a hydrophobic voltage-dependent channel. Overall, these results provide structural-basis insights and molecular-dynamic information that are needed to understand the regulatory mechanisms of ion permeability in the pentameric SARS-CoV-2 E protein channel.

biophysics↗

bioRxiv2020

Prediction of LncRNA Encoded Small Peptides inGlioma and The Oligomer Channel Functional AnalysisUsing in Silico Approaches

Glioma is lethal malignant brain cancers, many reports have shown that abnormalities in the behavior of water and ion channels play an important role in regulating glioma proliferation, migration, apoptosis and differentiation. Recently, new studies have suggested that some long noncoding RNAs (lncRNAs) containing small open reading frames (smORFs), can encode small peptides and form oligomers for water or ion regulation. However, because these peptides are difficult to identify, their functional mechanisms are far from being clearly understood. In this study, we used bioinformatic methods and softwares to identify and evaluate lncRNAs in gliomas that may encode small transmembrane peptides. Combining ab initio homology modeling, molecular dynamics simulations and energetic calculations, we constructed a predictive model and predicted the oligomer channel activity of peptides by identifying the lncRNA ORFs. We found that one key hub lncRNA, DLEU1, which contains two smORFs (ORF1 and ORF8) could encode small peptides that form pentameric channels. The mechanics of water and ion (Na + and Cl-) transport through this pentameric channel were simulated. The potential of mean force (PMF) of the H2O molecules along the two ORF-encoded peptide channels indicated that the energy barrier was different between ORF1 and ORF8. The ORF1-encoded peptide pentamer acted as a self-assembled water channel but not as an ion channel, and the ORF8 neither permeating ions nor water. This work provides new methods and theoretical support for further elucidation of the function of lncRNA-encoded small peptides and their role in cancer. Additionally, it provides a theoretical basis for drug development.

biophysics↗

bioRxiv2020

Traceback of Core Transcription Factors for Soybean Root Growth Maintenance under Water Deficit

Some crops inhibit shoot growth but maintain root growth under water-deficit conditions. Unraveling the molecular mechanisms of root plasticity under water deficit conditions in plants remains a major challenge. We developed an efficient platform for identifying core transcription factors (TFs) that collectively regulate each other and/or themselves in response to water stress, and exploring their interconnected regulatory circuitry involved in root growth maintenance under water deficit in soybean. We performed multi-species phylogenetic footprinting combined with spatial-temporal transcriptome analysis of soybean (Glycine max) roots under water deficit to identify conserved motifs that function in the water-stress response. Using these functional conserved cis-motifs, we applied a new approach to trace back motifs-associated core TFs ingroup as signal mediators, which mediate signaling between abiotic and endogenous stimuli. We integrated a co-functional TF-TF network and conserved motif-centered TF-DNA networks to construct a core TF network defined by mutual cross-regulation among core TFs. We found that core TF ARG (Abscisic acid response element binding factor-like Root Growth regulator) represses BRG (Brassinosteroid enhanced expression-like Root Growth regulator) expression through binding to its promoter at a conserved binding site. ARG and BRG antagonistically regulate Phytochrome-interacting factor-like Root Growth regulator (PRG) and combinatorially regulate some other core TFs. These core TFs form complex regulatory circuits to integrate light and multiple hormone signaling pathways and maintain root growth in response to varying degrees of water stress. Our study provides valuable information to unravel the complicated mechanisms of molecular networks involved in the regulation of root growth under water deficit.

plant biology↗

bioRxiv2019

GHSR-1a is not Required for Ghrelin's Anti-inflammatory and Fat-sparing Effects in Cancer Cachexia

Adipose tissue (AT) atrophy is a hallmark of cancer cachexia contributing to increased morbidity/mortality. Ghrelin has been proposed as a treatment for cancer cachexia partly by preventing AT atrophy. However, the mechanisms mediating ghrelins effects are incompletely understood, including the extent to which its only known receptor, GHSR-1a, is required for these effects. This study characterizes the pathways involved in AT atrophy in the Lewis Lung Carcinoma (LLC)-induced cachexia model and those mediating the effects of ghrelin in Ghsr+/+ and Ghsr-/- mice. We show that LLC causes AT atrophy by inducing anorexia, and increasing AT inflammation, thermogenesis and energy expenditure. These changes were greater in Ghsr-/-. Ghrelin administration prevented LLC-induced anorexia only in Ghsr+/+, but prevented WAT inflammation and atrophy in both genotypes, although its effects were greater in Ghsr+/+. LLC-induced increases in BAT inflammation, WAT and BAT thermogenesis, and energy expenditure were not affected by ghrelin. In conclusion, ghrelin ameliorates WAT inflammation, fat atrophy and anorexia in LLC-induced cachexia. GHSR-1a is required for ghrelins orexigenic effect but not for its anti-inflammatory or fat-sparing effects.

cancer biology↗

bioRxiv2019

Comprehensive analysis of structural variants in breast cancer genomes using single molecule sequencing

Improved identification of structural variants (SVs) in cancer can lead to more targeted and effective treatment options as well as advance our basic understanding of disease progression. We performed whole genome sequencing of the SKBR3 breast cancer cell-line and patient-derived tumor and normal organoids from two breast cancer patients using 10X/Illumina, PacBio, and Oxford Nanopore sequencing. We then inferred SVs and large-scale allele-specific copy number variants (CNVs) using an ensemble of methods. Our findings demonstrate that long-read sequencing allows for substantially more accurate and sensitive SV detection, with between 90% and 95% of variants supported by each long-read technology also supported by the other. We also report high accuracy for long-reads even at relatively low coverage (25x-30x). Furthermore, we inferred karyotypes from these data using our enhanced RCK algorithm to present a more accurate representation of the mutated cancer genomes, and find hundreds of variants affecting known cancer-related genes detectable only through long-read sequencing. These findings highlight the need for long-read sequencing of cancer genomes for the precise analysis of their genetic instability.

bioinformatics↗

bioRxiv2019

The fasciola cinereum of the hippocampus is important in the acquisition, but not the retrieval, of visual contextual memory

The fasciola cinereum (FC) is a subregion of the hippocampus that has received relatively little research attention compared with other hippocampal subregions with respect to anatomical characteristics and functional significance. Here, we show that the FC exhibits clear anatomical borders with CA1. The FC consists of granule cells, but adult neurogenesis was not found. The FC receives inputs from the lateral entorhinal cortex and perirhinal cortex while projecting to the crest of the dentate gyrus (DG). Neurotoxic lesioning of the FC using colchicine impaired the acquisition, but not retrieval, of visual contextual memory in rats. FC lesions also impaired place recognition and object-in-place memory. Place cells in the FC showed robust place fields but fired only transiently in their fields compared with those in CA1. Our findings suggest that the FC may play critical roles in learning a novel environment by facilitating pattern separation in the DG of the hippocampus.

neuroscience↗

bioRxiv2019

Individual Variation in Brain Network Topology is Linked to Schizophrenia Symptomatology

BackgroundResting state fMRI (rsfMRI) demonstrates that the brain is organized into distributed networks. Numerous studies have examined links between psychiatric symptomatology and network functional connectivity. Traditional rsfMRI analyses assume that the spatial organization of networks is invariant between individuals. This dogma has recently been overturned by the demonstration that networks show significant variation between individuals. We tested the hypothesis that previously observed relationships between schizophrenia negative symptom severity and network connectivity are actually due to individual differences in network spatial organization.\n\nMethods44 participants diagnosed with schizophrenia underwent rsfMRI scans and clinical assessments. A multivariate pattern analysis determined how whole brain functional connectivity correlates with negative symptom severity at the individual voxel level.\n\nResultsBrain connectivity to a region of the right dorso-lateral pre-frontal cortex correlates with negative symptom severity. This finding results from individual differences in the topographic distribution of two networks: the default mode network (DMN) and the task positive network (TPN). Both networks demonstrate strong (r[~]0.49) and significant (p<0.001) relationships between topography and symptom severity. For individuals with low symptom severity, this critical region is part of the DMN. In highly symptomatic individuals, this region is part of the TPN.\n\nConclusionPreviously overlooked individual variation in brain organization is tightly linked to differences in schizophrenia symptom severity. Recognizing critical links between network topography and pathological symptomology may identify key circuits that underlie cognitive and behavioral phenotypes. Individual variation in network topography likely guides different responses to clinical interventions that rely on anatomical targeting (e.g. TMS).

neuroscience↗

bioRxiv2019

Single-cell transcriptome analysis revealed a role of the transcription factor TOX in promoting CD8+ T-cell exhaustion in cancer

BackgroundT cells exhibit heterogeneous functional states in the tumor microenvironment. Immune checkpoint inhibitors (ICIs) can reinvigorate only the stem cell-like progenitor exhausted T cells, which suggests that inhibiting the exhaustion progress will improve the efficacy of immunotherapy. Thus, regulatory factors promoting T-cell exhaustion could serve as potential targets for delaying the process and improving ICI efficacy. MethodsWe analyzed the single-cell transcriptome data derived from human melanoma and non-small cell lung cancer (NSCLC) samples and classified the tumor-infiltrating (TI) CD8+ T-cell population based on PDCD1 (PD-1) levels, i.e. PDCD1-high and PDCD1-low cells. Additionally, we identified differentially expressed genes as candidate factors regulating intra-tumoral T-cell exhaustion. The co-expression of candidate genes with immune checkpoint (IC) molecules in the TI CD8+ T cells was confirmed by single-cell trajectory and flow-cytometry analyses. The loss-of-function effect of the candidate regulator was examined by a cell-based knockdown assay. The clinical effect of the candidate regulator was evaluated based on the overall survival and anti-PD-1 responses. ResultsWe retrieved many known factors for regulating T-cell exhaustion among the differentially expressed genes between PDCD1-high and PDCD1-low subsets of the TI CD8+ T cells in human melanoma and NSCLC. TOX was the only transcription factor (TF) predicted in both tumor types. TOX levels tend to increase as CD8+ T cells become more exhausted. Flow-cytometry analysis revealed a correlation between TOX expression and severity of intra-tumoral T-cell exhaustion. TOX knockdown in the human TI CD8+ T cells resulted in downregulation of PD-1, TIM-3, TIGIT, and CTLA-4, which suggests that TOX promotes intra-tumoral T-cell exhaustion by upregulating IC proteins in cancer. Finally, the TOX level in the TI T cells was found to be highly predictive of overall survival and anti-PD-1 efficacy in melanoma and NSCLC. ConclusionsWe predicted the regulatory factors involved in T-cell exhaustion using single-cell transcriptome profiles of human TI lymphocytes. TOX promoted intra-tumoral CD8+ T-cell exhaustion via upregulation of IC molecules. This suggested that TOX inhibition can potentially impede T-cell exhaustion and improve ICI efficacy. Additionally, TOX expression in the TI T cells can be used for patient stratification during anti-tumor treatments, including anti-PD-1 immunotherapy.

cancer biology↗

bioRxiv2019

NGSEA: network-based gene set enrichment analysis for interpreting gene expression phenotypes with functional gene sets

Gene set enrichment analysis (GSEA) is a popular tool to identify underlying biological processes in clinical samples using their gene expression phenotypes. GSEA measures the enrichment of annotated gene sets that represent biological processes for differentially expressed genes (DEGs) in clinical samples. GSEA may be suboptimal for functional gene sets, however, because DEGs from the expression dataset may not be functional genes per se but dysregulated genes perturbed by bona fide functional genes. To overcome this shortcoming, we developed network-based GSEA (NGSEA), which measures the enrichment score of functional gene sets using the expression difference of not only individual genes but also their neighbors in the functional network. We found that NGSEA outperformed GSEA in identifying pathway gene sets for matched gene expression phenotypes. We also observed that NGSEA substantially improved the ability to retrieve known anti-cancer drugs from patient-derived gene expression data using drug-target gene sets compared with another method, Connectivity Map. We also repurposed FDA-approved drugs using NGSEA and experimentally validated budesonide as a chemical with anti-cancer effects for colorectal cancer. We, therefore, expect that NGSEA will facilitate both pathway interpretation of gene expression phenotypes and anti-cancer drug repositioning. NGSEA is freely available at www.inetbio.org/ngsea.

bioinformatics↗

bioRxiv2019

Targeted Nanopore Sequencing with Cas9 for studies of methylation, structural variants and mutations

Nanopore sequencing technology can rapidly and directly interrogate native DNA molecules. Often we are interested only in interrogating specific areas at high depth, but conventional enrichment methods have thus far proved unsuitable for long reads1. Existing strategies are currently limited by high input DNA requirements, low yield, short (<5kb) reads, time-intensive protocols, and/or amplification or cloning (losing base modification information). In this paper, we describe a technique utilizing the ability of Cas9 to introduce cuts at specific locations and ligating nanopore sequencing adaptors directly to those sites, a method we term nanopore Cas9 Targeted-Sequencing (nCATS).\n\nWe have demonstrated this using an Oxford Nanopore MinION flow cell (Capacity >10Gb+) to generate a median 165X coverage at 10 genomic loci with a median length of 18kb, representing a several hundred-fold improvement over the 2-3X coverage achieved without enrichment. We performed a pilot run on the smaller Flongle flow cell (Capacity ~1Gb), generating a median coverage of 30X at 11 genomic loci with a median length of 18kb. Using panels of guide RNAs, we show that the high coverage data from this method enables us to (1) profile DNA methylation patterns at cancer driver genes, (2) detect structural variations at known hot spots, and (3) survey for the presence of single nucleotide mutations. Together, this provides a low-cost method that can be applied even in low resource settings to directly examine cellular DNA. This technique has extensive clinical applications for assessing medically relevant genes and has the versatility to be a rapid and comprehensive diagnostic tool. We demonstrate applications of this technique by examining the well-characterized GM12878 cell line as well as three breast cell lines (MCF-10A, MCF-7, MDA-MB-231) with varying tumorigenic potential as a model for cancer.\n\nContributionsTG and WT constructed the study. TG performed the experiments. TG, IL, and FS analyzed the data. TG, JG, ER, RB and AH and developed the method. TG and WT wrote the paper

genomics↗

bioRxiv2018

Simultaneous profiling of chromatin accessibility and methylation on human cell lines with nanopore sequencing

Understanding how the genome and the epigenome work together to control gene transcription has applications in our understanding of diseases such as human cancer. In this study, we combine the ability of NOMe-seq to simultaneously evaluate CpG methylation and chromatin accessibility, with long-read nanopore sequencing technology, a method we call nanoNOMe. We generated >60Gb whole-genome nanopore sequencing data for each of four human cell lines (GM12878, MCF-10A, MCF-7, MDA-MB-231) including repetitive regions inaccessible by short read sequencing. Using the long reads, we find that we can observe phased methylation and chromatin accessibility, large scale pattern changes, and genetic changes such as structural variations from a single assay.

genomics↗

bioRxiv2018

Mechanistic insights on metabolic dysfunction in PTSD: Role of glucocorticoid receptor sensitivity and energy deficit

PTSD is associated with metabolic comorbidities; however it is not clear how the neuroendocrine disturbances affect metabolism. To analyze this we employed a systems biological approach using an integrated mathematical model of metabolism, HPA axis and inflammation. We combined the metabolomics, neuroendocrine, clinical lab and cytokine data from combat-exposed veterans with and without PTSD, to characterize the differences in regulatory effects. We used the pattern of fold change in metabolites representing pathway level differences as reference for metabolic control analysis (MCA) using the model. MCA revealed parameters constituting the HPA axis, inflammation and GPCR pathway that yielded metabolic dysfunction consistent with PTSD. To support this, we performed causal analysis between regulatory components and the significantly different metabolites in our sample. Causal inference revealed that the changes in glucocorticoid receptor sensitivity were mechanistically associated with metabolic dysfunction and the effects were jointly mediated by insulin resistance, inflammation, oxidative stress and energy deficit.

systems biology↗

bioRxiv2018

Diverse Pathophysiological Processes Converge on Network Disruption in Mania

BackgroundNeuroimaging of psychiatric disease is challenged by the difficulty of establishing the causal role of neuroimaging abnormalities. Lesions that cause mania present a unique opportunity to understand how brain network disruption may cause mania in both lesions and in bipolar disorder.\n\nMethodsA literature search revealed 23 case reports with imaged lesions that caused mania in patients without history of bipolar disorder. We traced these lesions and examined resting-state functional Magnetic Resonance Imaging (rsfMRI) connectivity to these lesions and control lesions to find networks that would be disrupted specifically by mania-causing lesions. The results were then used as regions-of-interest to examine rsfMRI connectivity in patients with bipolar disorder (n=16) who underwent imaging longitudinally across states of both mania and euthymia alongside a cohort of healthy participants scanned longitudinally. We then sought to replicate these results in independent cohorts of manic (n=26) and euthymic (n=21) participants with bipolar disorder.\n\nResultsMania-inducing lesions overlap significantly in network connectivity. Mania-causing lesions selectively disrupt networks that include orbitofrontal cortex, dorsolateral prefrontal cortex, and temporal lobes. In bipolar disorder, the manic state was reflected in strong, significant, and specific disruption in network communication between these regions and regions implicated in bipolar pathophysiology: the amygdala and ventro-lateral prefrontal cortex.\n\nLimitationsThe was heterogeneity in the clinical characterization of mania causing lesions.\n\nConclusionsLesions causing mania demonstrate shared and specific network disruptions. These disruptions are also observed in bipolar mania and suggest a convergence of multiple disorders on shared circuit dysfunction to cause mania.

neuroscience↗

bioRxiv2018

Individual Variation in Brain Network Topology and Social Cognitive Ability

BackgroundSocial cognitive ability is a significant determinant of functional outcome and deficits in social cognition are a disabling symptom of psychotic disorders. The neurobiological underpinnings of social cognition are not well understood, hampering our ability to ameliorate these deficits.\n\nObjectiveUsing resting-state fMRI (functional magnetic resonance imaging) and a trans-diagnostic, data-driven analytic strategy, we sought to identify the brain network basis of emotional intelligence, a key domain of social cognition.\n\nMethodsStudy participants included 60 participants with a diagnosis of schizophrenia or schizoaffective disorder and 46 healthy comparison participants. All participants underwent a resting-state fMRI scan. Emotional Intelligence was measured using the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT). A connectome-wide analysis of brain connectivity examined how each individual brain voxels connectivity correlated with emotional intelligence using multivariate distance matrix regression (MDMR).\n\nResultsWe identified a region in the left superior parietal lobule (SPL) where individual network topology predicted emotional intelligence. Specifically, the association of this region with the Default Mode Network predicted higher emotional intelligence and association with the Dorsal Attention Network predicted lower emotional intelligence. This correlation was observed in both schizophrenia and healthy comparison participants.\n\nConclusionPrevious studies have demonstrated individual variance in brain network topology but the cognitive or behavioral relevance of these differences was undetermined. We observe that the left SPL, a region of high individual variance at the cytoarchitectonic level, also demonstrates individual variance in its association with large scale brain networks and that network topology predicts emotional intelligence.

neuroscience↗

bioRxiv2017

WheatNet: A genome-scale functional network for hexaploid bread wheat, Triticum aestivum

Gene networks provide a system-level overview of genetic organizations and enable the dissection of functional modules underlying complex traits. Here we report the generation of WheatNet, the first genome-scale functional network for T. aestivum and a companion web server (www.inetbio.org/wheatnet). WheatNet was constructed by integrating 20 distinct genomics datasets, including 156,000 wheat-specific co-expression links mined from 1,929 microarray data. A unique feature of WheatNet is that each network node represents either a single gene or a group of genes. We computationally partitioned gene groups mimicking homeologous genes by clustering 99,386 wheat genes, resulting in 20,248 gene groups comprising 63,401 genes and 35,985 individual genes. Thus, WheatNet was constructed using 56,233 nodes, and the final integrated network has 20,230 nodes and 567,000 edges. The edge information of the integrated WheatNet and all 20 component networks are available for download.

genetics↗