Biology subjects

Lee, K.

Publications and source records attributed to Lee, K..

At least 253 records · Page 14Linked to original sources

bioRxiv2020

Global reference mapping and dynamics of human transcription factor footprints

Combinatorial binding of transcription factors to regulatory DNA underpins gene regulation in all organisms. Genetic variation in regulatory regions has been connected with diseases and diverse phenotypic traits1, yet it remains challenging to distinguish variants that impact regulatory function2. Genomic DNase I footprinting enables quantitative, nucleotide-resolution delineation of sites of transcription factor occupancy within native chromatin3-5. However, to date only a small fraction of such sites have been precisely resolved on the human genome sequence5. To enable comprehensive mapping of transcription factor footprints, we produced high-density DNase I cleavage maps from 243 human cell and tissue types and states and integrated these data to delineate at nucleotide resolution ~4.5 million compact genomic elements encoding transcription factor occupancy. We map the fine-scale structure of ~1.6 million DHS and show that the overwhelming majority is populated by well-spaced sites of single transcription factor:DNA interaction. Cell context-dependent cis-regulation is chiefly executed by wholesale actuation of accessibility at regulatory DNA versus by differential transcription factor occupancy within accessible elements. We show further that the well-described enrichment of disease- and phenotypic trait-associated genetic variants in regulatory regions1,6 is almost entirely attributable to variants localizing within footprints, and that functional variants impacting transcription factor occupancy are nearly evenly partitioned between loss- and gain-of-function alleles. Unexpectedly, we find that the global density of human genetic variation is markedly increased within transcription factor footprints, revealing an unappreciated driver of cis-regulatory evolution. Our results provide a new framework for both global and nucleotide-precision analyses of gene regulatory mechanisms and functional genetic variation.

genomics↗

bioRxiv2020

Machine learning approach reveals heterogeneous responses to FAK and Rho GTPases inhibition on smooth muscle spheroid formation

Atherosclerosis and vascular injury are characterized by neointima formation caused by the aberrant accumulation and proliferation of vascular smooth muscle cells (VSMCs) within the vessel wall. Understanding how to control VSMCs would advance the effort to treat vascular disease. However, the response to treatments aimed at VSMCs is often different among patients with the same disease condition, suggesting patient-specific heterogeneity in VSMCs. Here, we present an experimental and computational method called HETEROID (Heterogeneous Spheroid), which examines the heterogeneity of the responses to drug treatments at the single-spheroid level by combining a VSMC spheroid model and machine learning (ML) analysis. First, we established a VSMC spheroid model that mimics neointima formation induced by atherosclerosis and vascular injury. We found that FAK-Rac/Rho, but not Cdc42, pathways regulate the VSMC spheroid formation through N-cadherin. Then, to identify the morphological subpopulations of drug-perturbed spheroids, we used an ML framework that combines deep learning-based spheroid segmentation and morphological clustering analysis. Our ML approach reveals that FAK, Rac, Rho, and Cdc42 inhibitors differentially affect the spheroid morphology, suggesting there exist multiple distinct pathways governing VSMC spheroid formation. Overall, our HETEROID pipeline enables detailed quantitative characterization of morphological changes in neointima formation, that occurs in vivo, by single-spheroid analysis of various drug treatments.

cell biology↗

bioRxiv2020

Exploiting evolutionary trade-offs to combat antibiotic resistance

Antibiotic resistance frequently evolves through fitness trade-offs in which the genetic alterations that confer resistance to a drug can also cause growth defects in resistant cells. Here, through experimental evolution in a microfluidics-based turbidostat, we demonstrate that antibiotic-resistant cells can be efficiently inhibited by amplifying the fitness costs associated with drug-resistance evolution. Using tavaborole-resistant E. coli as a model, we show that genetic mutations in leucyl-tRNA synthetase (that underlie tavaborole resistance) make resistant cells intolerant to norvaline, a chemical analog of leucine that is mistakenly used by tavaborole-resistant cells for protein synthesis. We then show that tavaborole-sensitive cells quickly outcompete tavaborole-resistant cells in the presence of norvaline due to the amplified cost of the molecular defect of tavaborole resistance. This finding illustrates a potentially generalizable approach for combating therapeutic resistance, prolonging the effectiveness of drugs and enabling the use of drugs that are no longer effective due to the rapid evolution of resistance.

evolutionary biology↗

bioRxiv2020

Viscous medium-based crystal support in sample holder for fixed-target serial femtosecond crystallography

Serial femtosecond crystallography (SFX) enables the determination of a room-temperature crystal structure of macromolecules without causing radiation damage, as well as provides time-resolved molecular dynamics data in pump-probe experiments. Fixed-target SFX (FT-SFX) can minimize sample consumption and physical effects to crystals during sample delivery. Various types of sample holders have been developed and applied in FT-SFX; however, no sample holder has been developed that can universally mount crystals of various sizes and shapes. Here, we introduce a viscous media-based crystal support in a sample holder for FT-SFX. Crystal samples were embedded in viscous media such as gelatin and agarose, which were enclosed in a polyimide film. In the vertically placed sample holder, the viscous medium stably supported crystals between the two polyimide films without crystal sinking due to gravity. Using this method, we performed FT-SFX experiments with glucose isomerase and lysozyme embedded in gelatin and agarose, respectively. The room-temperature crystal structures of glucose isomerase and lysozyme were successfully determined at 1.75 and 1.80 [A] resolutions, respectively. Viscous media used in this experiment showed negligible background scattering in data processing. This method is useful for delivering crystal samples of various sizes and shapes in FT-SFX experiments.

biophysics↗

bioRxiv2019

Binary and analog variation of synapses between cortical pyramidal neurons

Learning from experience depends at least in part on changes in neuronal connections. We present the largest map of connectivity to date between cortical neurons of a defined type (L2/3 pyramidal cells), which was enabled by automated analysis of serial section electron microscopy images with improved handling of image defects. We used the map to identify constraints on the learning algorithms employed by the cortex. Previous cortical studies modeled a continuum of synapse sizes (Arellano et al. 2007) by a log-normal distribution (Loewenstein, Kuras, and Rumpel 2011; de Vivo et al. 2017; Santuy et al. 2018). A continuum is consistent with most neural network models of learning, in which synaptic strength is a continuously graded analog variable. Here we show that synapse size, when restricted to synapses between L2/3 pyramidal cells, is well-modeled by the sum of a binary variable and an analog variable drawn from a log-normal distribution. Two synapses sharing the same presynaptic and postsynaptic cells are known to be correlated in size (Sorra and Harris 1993; Koester and Johnston 2005; Bartol et al. 2015; Kasthuri et al. 2015; Dvorkin and Ziv 2016; Bloss et al. 2018; Motta et al. 2019). We show that the binary variables of the two synapses are highly correlated, while the analog variables are not. Binary variation could be the outcome of a Hebbian or other synaptic plasticity rule depending on activity signals that are relatively uniform across neuronal arbors, while analog variation may be dominated by other influences. We discuss the implications for the stability-plasticity dilemma.

neuroscience↗

bioRxiv2019

Rapid antimicrobial susceptibility test using spatiotemporal analysis of laser speckle dynamics of bacterial colonies

Antimicrobial susceptibility testing (AST) is crucial for providing appropriate choices and doses of antibiotics to patients. However, standard ASTs require a time-consuming incubation of about 16-20 h for visual accumulation of bacteria, limiting the use of AST for an early prescription. In this study, we propose a rapid AST based on laser speckle formation (LSF) that enables rapid detection of bacterial growth, with the same sample preparation protocol as in solid-based ASTs. The proposed method exploits the phenomenon that well-grown bacterial colonies serve as optical diffusers, which convert a plane-wave laser beam into speckles. The generation of speckle patterns indicates bacterial growth at given antibiotic concentrations. Speckle formation is evaluated by calculating the spatial autocorrelation of speckle images, and bacterial growth is determined by tracking the autocorrelation value over time. We demonstrated the performance of the proposed method for several combinations of bacterial species and antibiotics to achieve the AST in 2-4.5 hours. Furthermore, we also demonstrated the sensitivity of the technique for low bacterial density. The proposed method can be a powerful tool for rapid, simple, and low-cost AST. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=160 SRC="FIGDIR/small/853168v1_ufig1.gif" ALT="Figure 1"> View larger version (48K): org.highwire.dtl.DTLVardef@8ee314org.highwire.dtl.DTLVardef@de47c5org.highwire.dtl.DTLVardef@13a0103org.highwire.dtl.DTLVardef@118ad36_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2019

Quantitative trait loci (QTL) underlying phenotypic variation in bioethanol-related processes in Neurospora crassa.

Bioethanol production from lignocellulosic biomass has received increasing attention over the past decade. Many attempts have been made to reduce the cost of bioethanol production by combining the separate steps of the process into a single-step process known as consolidated bioprocessing. This requires identification of organisms that can efficiently decompose lignocellulose to simple sugars and ferment the pentose and hexose sugars liberated to ethanol. There have been many attempts in engineering laboratory strains by adding new genes or modifying genes to expand the capacity of an industrial microorganism. There has been less attention in improving bioethanol-related processes utilizing natural variation existing in the natural ecotypes. In this study, we sought to identify genomic loci contributing to variation in saccharification of cellulose and fermentation of glucose in the fermenting cellulolytic fungus Neurospora crassa through quantitative trait loci (QTL) analysis. We identified one major QTL contributing to fermentation of glucose and multiple putative QTLs underlying saccharification. Understanding the natural variation of the major QTL gene would provide new insights in developing industrial microbes for bioethanol production.

microbiology↗

bioRxiv2019

A Single-Cell Immune Atlas of Triple Negative Breast Cancer Reveals Novel Immune Cell Subsets

Triple-negative breast cancer (TNBC) represents the most aggressive breast cancer subtype, which recently attracts great interest for immune therapeutic development. In this context, in-depth understanding of TNBC immune landscape is highly demanded. Here we report single-cell RNA sequencing results of 9683 tumor-infiltrated immune cells isolated from 14 treatment naive TNBC tumors, where 22 immune cell subsets, including T cells, macrophages, B cells, and DCs have been characterized. We identify a new T cell subset, CD8+CXCL8+ naive T cell, which associates with poor survival. A novel immune cell subset comprised of TCR+ macrophages, is found to be widely distributed in TNBC tumors. Further analyses reveal an up-regulation of molecules associated with TCR signaling and cytotoxicity in these immune cells, indicating TCR signaling activation. Altogether, our study provides a valuable resource to understand the immune ecosystem of TNBC. The novel immune cell subsets reported herein might be functionally important in cancer immunity.\n\nSIGNIFICANCEThis work demonstrates a single-cell transcriptome atlas of immune cells in treatment naive TNBC tumors, revealing novel immune cell subsets. This study provides a valuable resource to understand the immune ecosystem of TNBC, which will be helpful for the immunotherapeutic strategy design of TNBC.

immunology↗

bioRxiv2019

Exploring novel probiotic mechanisms of Streptococcus A12 with functional genomics

Health-associated biofilms in the oral cavity are composed of a diverse group of microbial species that can foster an environment that is less favorable for the outgrowth of dental caries pathogens, like Streptococcus mutans. A novel oral bacterium, designated Streptococcus A12, was previously isolated from supragingival dental plaque of a caries-free individual, and was shown to interfere potently with the growth and virulence properties of S. mutans. Here, we apply functional genomics to begin to identify molecular mechanisms used by A12 to antagonize, and to resist the antagonistic factors of, S. mutans. Using bioinformatics, genes that could encode factors that enhance the ability of A12 to compete with S. mutans were identified. Selected genes, designated as potential competitive factors (pcf), were deleted. Certain mutant derivatives showed a reduced capacity to compete with S. mutans compared to the parental strain. The A12 pcfO mutant lost the ability to inhibit comX-inducing peptide (XIP) signaling by S. mutans, while mutants in the pcfFEG locus were impaired in sensing of, and were more sensitive to, the lantibiotic nisin. Loss of PcfV, annotated as a colicin V biosynthetic protein, resulted in diminished antagonism of S. mutans. Collectively, the data provide new insights into the complexities and variety of factors that affect biofilm ecology and virulence. Continued exploration of the genomic and physiologic factors that distinguish commensals from truly beneficial members of the oral microbiota will lead to a better understanding of the microbiome and new approaches to promote oral health.\n\nImportanceAdvances in defining the composition of health-associated biofilms have highlighted the important role for beneficial species in maintaining health. Comparatively little, however, has been done to address the genomic and physiological basis underlying the probiotic mechanisms of beneficial commensals. In this study, we explored the ability of a novel oral bacterial isolate, Streptococcus A12, to compete with the dental pathogen Streptococcus mutans, using various gene products with diverse functions. A12 displayed enhanced competitiveness by: i) disrupting intercellular communication pathways of S. mutans, ii) sensing and resisting antimicrobial peptides, and iii) producing factors involved in the production of a putative antimicrobial compound. Research on the probiotic mechanisms employed by Streptococcus A12 is providing essential insights into how beneficial bacteria may help maintain oral health, which will aid in the development of biomarkers and therapeutics that can improve the practice of clinical dentistry.

microbiology↗

bioRxiv2019

Spatial genome re-organization between fetal and adult hematopoietic stem cells

Fetal hematopoietic stem cells (HSCs) undergo a developmental switch to become adult HSCs. The functional properties of the HSCs change dramatically during this switch, including their cycling behavior, hematopoietic lineage outputs and proliferation rate. The relationship between three-dimensional (3D) genome organization, epigenomic state, and transcriptome is poorly understood during this critical developmental transition. Here we conducted a comprehensive survey of the 3D genome, epigenome and transcriptome of fetal and adult HSCs in mouse. We found that chromosomal compartments and topologically associating domains (TAD) are largely conserved between fetal and adult HSCs. However, there is a global trend of increased compartmentalization and TAD boundary strength in adult HSCs. In contrast, dynamics of intra-TAD chromatin interactions is much higher and more widespread, involving over a thousand gene promoters and distal enhancers. Such dynamic interactions target genes involved in cell cycle, metabolism, and hematopoiesis. These developmental-stage-specific enhancer-promoter interactions appear to be mediated by different sets of transcription factors in fetal and adult HSCs, such as TCF3 and MAFB in fetal HSCs, versus NR4A1 and GATA3 in adult HSCs. Loss-of-function studies of TCF3 confirms the role of TCF3 in mediating condition-specific enhancer-promoter interactions and gene regulation in fetal HSCs. In summary, our data suggest that the fetal-to-adult transition is accompanied by extensive changes in intra-TAD chromatin interactions that target genes underlying the phenotypic differences between fetal and adult HSCs.

molecular biology↗

bioRxiv2019

Environmental chemical diethylhexyl phthalate alters intestinal microbiota community structure and metabolite profile in mice

Exposure to environmental chemicals during windows of development is a potentially contributing factor in gut microbiota dysbiosis, and linked to chronic diseases and developmental disorders. We used a community-level model of microbiota metabolism to investigate the effects of diethylhexyl phthalate (DEHP), a ubiquitous plasticizer implicated in neurodevelopmental disorders, on the composition and metabolite outputs of gut microbiota in young mice. Administration of DEHP by oral gavage increased the abundance of Lachnoclostridum, while decreasing Akkermansia, Odoribacter, and Clostridium sensu stricto. Addition of DEHP to in vitro cultured cecal microbiota increased the abundance of Alistipes, Paenibacillus, and Lachnoclostridium. Untargeted metabolomics showed that DEHP broadly altered the metabolite profile in the culture. Notably, DEHP enhanced the production of p-cresol, while inhibiting butyrate synthesis. Metabolic model-guided correlation analysis indicated that the likely sources of p-cresol are Clostridium species. Our results suggest that DEHP can directly modify the microbiota to affect production of bacterial metabolites linked with neurodevelopmental disorders.\n\nImportanceSeveral previous studies have pointed to environmental chemical exposure during windows of development as a contributing factor in neurodevelopmental disorders, and correlated these disorders with microbiota dysbiosis, little is known about how the chemicals specifically alter the microbiota to interfere with development. The findings reported in this paper unambiguously establish that a pollutant linked with neurodevelopmental disorders can directly modify the microbiota to promote the production of a potentially toxic metabolite (p-cresol) that has also been correlated with neurodevelopmental disorders. Further, we use a novel modeling strategy to identify the responsible enzymes and bacterial sources of this metabolite. To the best of our knowledge, the present study is the first to characterize the functional consequence of phthalate exposure on a developed microbiota. Our results suggest that specific bacterial pathways could be developed as diagnostic and therapeutic targets against health risks posed by ingestion of environmental chemicals.

microbiology↗

bioRxiv2019

Air mass source determines airborne microbial diversity at the ocean-atmosphere interface of the Great Barrier Reef marine ecosystem

The atmosphere is the least understood biome on Earth despite its critical role as a microbial transport medium. The influence of surface cover on composition of airborne microbial communities above marine systems is unclear. Here we report evidence for a dynamic microbial presence at the ocean-atmosphere interface of a major marine ecosystem, the Great Barrier Reef, and identify that recent air mass trajectory over an oceanic or continental surface associated with observed shifts in airborne bacterial and fungal diversity. Relative abundance of shared taxa between air and coral microbiomes varied between 2.2-8.8% and included those identified as part of the core coral microbiome. We propose that this variable source of atmospheric inputs may in part contribute to the diverse and transient nature of the coral microbiome.

microbiology↗

bioRxiv2019

Biological Filtering and Substrate Promiscuity Prediction for Annotating Untargeted Metabolomics

Mass spectrometry coupled with chromatography separation techniques provides a powerful platform for untargeted metabolomics. Determining the chemical identities of detected compounds however remains a major challenge. Here, we present a novel computational workflow, termed Expanded Metabolic Model Annotation (EMMA), that aims to strike a balance between discovering previously uncharacterized metabolites and the computational burden of annotation. EMMA engineers a candidate set, a listing of putative chemical identities to be used during annotation, through an expanded metabolic model (EMM). An EMM includes not only canonical substrates and products of enzymes already cataloged in a database through a reference metabolic model, but also metabolites that can form due to substrate promiscuity. EMMA was applied to untargeted LC-MS data collected from cultures of Chinese hamster ovary (CHO) cells and murine cecal microbiota. EMM metabolites matched, on average, to 23.92% of measured masses, providing a > 7-fold increase in the candidate set size when compared to a reference metabolic model. Many metabolites suggested by EMMA are not catalogued in PubChem. For the CHO cell, we experimentally confirmed the presence of 4-hydroxy-phenyllactate, a metabolite predicted by EMMA that has not been previously identified as part of CHO cell metabolism.

bioengineering↗

bioRxiv2019

Link clustering explains non-central essential genes in protein interaction networks

Essential genes (EGs) often form central nodes in protein-protein interaction (PPI) networks. However, many reports have shown that numerous EGs are non-central, suggesting that another principle governs gene essentiality. We propose link clustering as a distinct indicator of the essentiality for non-central nodes. Specifically, in various human and yeast PPI networks, we found that 29 to 47% of EGs were better characterized by link clustering than by centrality. Such non-central EGs with clustered links have significant impacts on communities at lower hierarchical levels, suggesting that their essentiality derives from functional dependency among relevant local neighbors, rather than their implication on global connectivity. Moreover, these non-central EGs exhibited several distinct characteristics: they tend to be younger and fast-evolving, and likely change their essentiality across different human cell lines and between human and mouse than central-EGs. Author summaryThe centrality in network structure was thought to be the cause of gene essentiality, as it conveys nodes importance in given networks. However, many essential genes are also found to be non-central, which leads us to ask whether a principle other than centrality may govern gene essentiality. Here we demonstrate that link clustering conveying functional dependency between nodes is the other principle characterizing gene essentiality. The link clustering explains numerous essential genes that are non-central, which are distinct from central ones regarding their molecular function and evolution. Our results clearly establish a two-dimensional principle governing gene essentiality.

systems biology↗

bioRxiv2019

Multi-ATOM: Ultrahigh-throughput single-cell quantitative phase imaging with subcellular resolution

A growing body of evidence has substantiated the significance of quantitative phase imaging (QPI) in enabling cost-effective and label-free cellular assay, which provides useful insights into understanding biophysical properties of cells and their roles in cellular functions. However, available QPI modalities are limited by the loss of imaging resolution at high throughput and thus run short of sufficient statistical power at the single cell precision to define cell identities in a large and heterogeneous population of cells - hindering their utility in mainstream biomedicine and biology. Here we present a new QPI modality, coined multi-ATOM that captures and processes quantitative label-free single-cell images at ultra-high throughput without compromising sub-cellular resolution. We show that multi-ATOM, based upon ultrafast phase-gradient encoding, outperforms state-of-the-art QPI in permitting robust phase retrieval at a QPI throughput of >10,000 cell/sec, bypassing the need for interferometry which inevitably compromises QPI quality under ultrafast operation. We employ multi-ATOM for large-scale, label-free, multi-variate, cell-type classification (e.g. breast cancer sub-types, and leukemic cells versus peripheral blood mononuclear cells) at high accuracy (>94%). Our results suggest that multi-ATOM could empower new strategies in large-scale biophysical single-cell analysis with applications in biology and enriching disease diagnostics.

bioengineering↗

bioRxiv2018

Microbial dispersal limitation to isolated soil habitats in the McMurdo Dry Valleys of Antarctica

Dispersal is a critical yet poorly understood factor underlying macroecological patterns in microbial communities. Airborne microbial transport is assumed to occupy a central role in determining dispersal outcomes and extra-range dispersal has important implications for predicting ecosystem resilience and response to environmental change. One of the most pertinent biomes in this regard is Antarctica given its geographic isolation and vulnerability to climate change and human disturbance. Here we report the first characterisation of microbial diversity in near-ground and high-altitude air above a typical Antarctic Dry Valley as well as that of underlying soil microbial communities. We found that persistent airborne inputs were unable to fully explain local soil community assembly. Comparison with airborne microbial diversity from non-polar sources suggests that strong selection occurs during atmospheric transport resulting in regionally isolated airborne inputs and highly specialized soil communities where fungi displayed greater isolation than bacteria from non-polar sources. Overall microbial communities from this isolated Antarctic ecosystem displayed limited connectivity to the global microbial pool. Our findings provide critical insights to forecast the potential outcomes for microbial communities of climate change-mediated shifts in air circulation to the Dry Valleys, the largest ice-free region of Antarctica.

microbiology↗

bioRxiv2018

Real-time monitoring of bacterial growth and fast antimicrobial susceptibility tests exploiting multiple light scattering

AbstractAntimicrobial susceptibility test (AST) is widely used to provide the minimum inhibitory concentration of bacteria, and crucial to provide appropriate uses of antibiotics and to address the issue of drug-resistance bacteria. However, ASTs require the time-consuming incubation about 16-20 h for the visual determination of the growth of bacterial colonies, which has been a major obstacle to on-site applications of ASTs. In this study, we propose a rapid and non-invasive method based on laser speckles to evaluate the bacterial growth movements in real time, thus reducing the time for the agar dilution method. With a simple configuration compatible with conventional agar plates, the analysis of laser speckle from samples enables the early detection of the presence of growth as well as its detailed history of the colony-forming movement on agar plates. Using the samples prepared through the same procedure as the agar dilution method, we obtained the AST results at least 4-8 hours earlier than the conventional method without compromising the accuracy. This technique does not require for the use of exogenous agents, but works for most bacteria regardless of their species. Furthermore, the distinctive responses of several species to microbial agents were revealed through the present technique supporting a comprehensive analysis of the effect of the antibiotics. The findings suggest that this new method could be a useful tool for rapid, simple, and low-cost ASTs in addition to providing the historical information of the bacterial growth on agar plates.

microbiology↗

bioRxiv2018

Deep-learning-based label-free segmentation of cell nuclei in time-lapse refractive index tomograms

In order to identify cell nuclei, fluorescent proteins or staining agents has been widely used. However, use of exogenous agents inevitably prevents from long-term imaging of live cells and rapid analysis, and even interferes with intrinsic physiological conditions. In this work, we proposed a method of label-free segmentation of cell nuclei in optical diffraction tomography images by exploiting a deep learning framework. The proposed method was applied for precise cell nucleus segmentation in two, three, and four-dimensional label-free imaging. A novel architecture with optimised training strategies was validated through cross-modality and cross-laboratory experiments. The proposed method would bring out broad and immediate biomedical applications with our framework publicly available.

biophysics↗