Biology subjects

Li, B.

Publications and source records attributed to Li, B..

At least 37 records · Page 2Linked to original sources

bioRxiv2018

Rhizosphere microbes and host plant genotype influence the plant metabolome and reduce insect herbivory

O_LIRhizosphere microbes affect plant performance, including plant resistance against insect herbivores; yet, the relative influence of rhizosphere microbes vs. plant genotype on herbivory levels and on metabolites related to defense remains unclear.\nC_LIO_LIIn Boechera stricta, we tested the effects of rhizosphere microbes and plant genotype on herbivore resistance, the primary metabolome, and select secondary metabolites.\nC_LIO_LIPlant populations differed significantly in the concentrations of 6 glucosinolates (GLS), secondary metabolites known to provide herbivore resistance in the Brassicaceae, and the population with lower GLS levels experienced ~60% higher levels of aphid (Aphis spp.) attack; no effect was observed of GLS on damage by a second herbivore, flea beetles (Altica spp.). Rhizosphere microbiome (intact vs. disrupted) had no effect on plant GLS concentrations. However, aphid number and flea beetle damage were respectively ~3-fold and 7-fold higher among plants grown in the disrupted rhizosphere microbiome treatment, and distinct (as estimated from 16s rRNA amplicon sequencing) intact native microbiomes also differed in their effects on herbivore damage. These differences may be attributable to shifts in primary metabolic pathways.\nC_LIO_LIThe findings suggest that rhizosphere microbes can play a greater role than plant genotype in defense against insect herbivores, and act through mechanisms independent of plant genotype.\nC_LI

plant biology↗

bioRxiv2018

CagY-dependent regulation of type IV secretion in Helicobacter pylori is associated with alterations in integrin binding

Strains of Helicobacter pylori that cause ulcer or gastric cancer typically express a type IV secretion system (T4SS) encoded by the cag pathogenicity island (PAI). CagY is an ortholog of VirB10 that, unlike other VirB10 orthologs, has a large middle repeat region (MRR) with extensive repetitive sequence motifs, which undergo CD4+ T cell-dependent recombination during infection of mice. Recombination in the CagY MRR reduces T4SS function, diminishes the host inflammatory response, and enables the bacteria to colonize at a higher density. Since CagY is known to bind human 5{beta}1 integrin, we tested the hypothesis that recombination in the CagY MRR regulates T4SS function by modulating binding to 5{beta}1 integrin. Using a cell-free microfluidic assay, we found that H. pylori binding to 5{beta}1 integrin under shear flow is dependent on the CagY MRR, but independent of the presence of the T4SS pili, which are only formed when H. pylori is in contact with host cells. Similarly, expression of CagY in the absence of other T4SS genes was necessary and sufficient for whole bacterial cell binding to 5{beta}1 integrin. Bacteria with variant cagY alleles that reduced T4SS function showed comparable reduction in binding to 5{beta}1 integrin, though CagY was still expressed on the bacterial surface. We speculate that cagY-dependent modulation of H. pylori T4SS function is mediated by alterations in binding to 5{beta}1 integrin, which in turn regulates the host inflammatory response so as to maximize persistent infection.\n\nIMPORTANCEInfection with H. pylori can cause peptic ulcers, and is the most important risk factor for gastric cancer, the third most common cause of cancer death worldwide. The major H. pylori virulence factor that determines whether infection causes disease or asymptomatic colonization is the type IV secretion system (T4SS), a sort of molecular syringe that injects bacterial products into gastric epithelial cells and alters host cell physiology. We previously showed that recombination in CagY, an essential T4SS component, modulates the function of the T4SS. Here we found that these recombination events produce parallel changes in specific binding to 5{beta}1 integrin, a host cell receptor that is essential for T4SS-dependent translocation of bacterial effectors. We propose that CagY-dependent binding to 5{beta}1 integrin acts like a molecular rheostat that alters T4SS function and modulates the host immune response to promote persistent infection.

microbiology↗

bioRxiv2018

Collective feature selection to identify crucial epistatic variants

BackgroundMachine learning methods have gained popularity and practicality in identifying linear and non-linear effects of variants associated with complex disease/traits. Detection of epistatic interactions still remains a challenge due to the large number of features and relatively small sample size as input, thus leading to the so-called \"short fat data\" problem. The efficiency of machine learning methods can be increased by limiting the number of input features. Thus, it is very important to perform variable selection before searching for epistasis. Many methods have been evaluated and proposed to perform feature selection, but no single method works best in all scenarios. We demonstrate this by conducting two separate simulation analyses to evaluate the proposed collective feature selection approach.\n\nResultsThrough our simulation study we propose a collective feature selection approach to select features that are in the \"union\" of the best performing methods. We explored various parametric, non-parametric, and data mining approaches to perform feature selection. We choose our top performing methods to select the union of the resulting variables based on a user-defined percentage of variants selected from each method to take to downstream analysis. Our simulation analysis shows that non-parametric data mining approaches, such as MDR, may work best under one simulation criteria for the high effect size (penetrance) datasets, while non-parametric methods designed for feature selection, such as Ranger and Gradient boosting, work best under other simulation criteria. Thus, using a collective approach proves to be more beneficial for selecting variables with epistatic effects also in low effect size datasets and different genetic architectures. Following this, we applied our proposed collective feature selection approach to select the top 1% of variables to identify potential interacting variables associated with Body Mass Index (BMI) in ~44,000 samples obtained from Geisingers MyCode Community Health Initiative (on behalf of DiscovEHR collaboration).\n\nConclusionsIn this study, we were able to show that selecting variables using a collective feature selection approach could help in selecting true positive epistatic variables more frequently than applying any single method for feature selection via simulation studies. We were able to demonstrate the effectiveness of collective feature selection along with a comparison of many methods in our simulation analysis. We also applied our method to identify non-linear networks associated with obesity.

bioinformatics↗

bioRxiv2018

A statistical framework for cross-tissue transcriptome-wide association analysis

Transcriptome-wide association analysis is a powerful approach to studying the genetic architecture of complex traits. A key component of this approach is to build a model to predict (impute) gene expression levels from genotypes from samples with matched genotypes and expression levels in a specific tissue. However, it is challenging to develop robust and accurate imputation models with limited sample sizes for any single tissue. Here, we first introduce a multi-task learning approach to jointly impute gene expression in 44 human tissues. Compared with single-tissue methods, our approach achieved an average 39% improvement in imputation accuracy and generated effective imputation models for an average 120% (range 13%-339%) more genes in each tissue. We then describe a summary statistic-based testing framework that combines multiple single-tissue associations into a single powerful metric to quantify overall gene-trait association at the organism level. When our method, called UTMOST, was applied to analyze genome wide association results for 50 complex traits (Ntotal=4.5 million), we were able to identify considerably more genes in tissues enriched for trait heritability, and cross-tissue analysis significantly outperformed single-tissue strategies (p=1.7e-8). Finally, we performed a cross-tissue genome-wide association study for late-onset Alzheimers disease (LOAD) and replicated our findings in two independent datasets (Ntotal=175,776). In total, we identified 69 significant genes, many of which are novel, leading to novel insights on LOAD etiologies.

genetics↗

bioRxiv2018

Phosphorothioate-modified DNA oligonucleotides inactivate CRISPR-Cpf1 mediated genome editing

CRISPR-Cpf1, a microbial adaptive immune system discovered from Prevotella and Francisella 1, employs a single-stranded CRISPR RNA (crRNA) to induce double stranded DNA breaks1. To modulate genome editing activity of Cpf1 in human cells, we designed a series of crRNA variants including DNA-crRNA and RNA-crRNA duplexes, and identified that phosphorothioate (PS)-modified DNA-crRNA duplex completely blocked the function of Cpf1 mediated gene editing. More importantly, without prehybridization, this PS-modified DNA was able to regulate Cpf1 activity in a time-and dose-dependent manner. Mechanistic studies indicate that PS-modified DNA oligonucleotides hinder the binding between Cpf1-crRNA complex and target DNA substrate. Consequently, phosphorothioate-modified DNA oligonucleotides provide a tunable platform to inactivate Cpf1 mediated genome editing.

bioengineering↗

bioRxiv2018

Electron transfer dictates metabolic reprogramming in proliferating cells under hypoxia

Metabolic reprogramming extensively occurs in proliferating cancer cells. This phenomenon occurs highly heterogeneously, but its origin has remained unclear. Here we use a physicochemical concept of free electron potential (FEP) and its equation of state to profile metabolites. We demonstrate that FEP change between substrates and products exactly reflects electrons dissipated in a metabolic transformation. Based on the law of conservation of electron in chemical reactions, a function of FEP change for central metabolism in proliferating cells are further derived, and it can accurately predict metabolic behaviors under hypoxia by maximizing the cellular FEP change to consume electrons. Therefore, enabling electron transfer dictates metabolic reprogramming in hypoxic cells, which underlies the major findings in cancer metabolism and is supported by our experiments. Importantly, our model established on FEP helps to reveal a combination of promising targets to inhibit tumor growth under hypoxia by blocking electron consumption, and could also guide future studies on cancer metabolism under hypoxia.

biochemistry↗

bioRxiv2017

Scalable volumetric imaging for ultrahigh-speed brain mapping at synaptic resolution

We describe a new light-sheet microscopy method for fast, large-scale volumetric imaging. Combining synchronized scanning illumination and oblique imaging over cleared, thick tissue sections in smooth motion, our approach achieves high-speed 3D image acquisition of an entire mouse brain within 2 hours, at a resolution capable of resolving synaptic spines. It is compatible with immunofluorescence labeling, enabling flexible cell-type specific brain mapping, and is readily scalable for large biological samples such as primate brain.

neuroscience↗

bioRxiv2017

Collective cell migration without proliferation: density determines cell velocity and wave velocity

Collective cell migration contributes to morphogenesis, wound healing or tumor metastasis. Culturing epithelial monolayers on a substrate enables to quantify such tissue migration. By using narrow strips, we stabilise the front shape; by inhibiting cell division, we limit density increase and favor steady migration; by using long strips, we observe a confined cell monolayer migrating over days. A coherent collective movement propagates over millimeters; cells spread and density decreases from the monolayer bulk toward the front. Cell velocity ([~]micrometer per minute) increases linearly with cell radius, and does not depend explicitly on the distance to the front. Over ten periods of backwards propagating velocity waves, with wavelength [~]millimeter, are detected with a signal-to-noise ratio enabling for quantitative spatio-temporal analysis. Their velocity ([~]ten micrometers per minute) is ten times the cell velocity; it increases linearly with the cell radius. Their period ([~]two hours) is spatially homogeneous, and increases with the front density. When we inhibit the formation of lamellipodia, cell velocity drops while waves either disappear, or have a smaller amplitude and slower period. Our phenomenological model assumes that both cell and wave velocities are related with the activity of lamellipodia, and that the local stretching in the monolayer bulk modulates traction stresses. We find that parameter values close to the instability limit where waves appear yield qualitative and quantitative predictions compatible with experiments, including the facts that: waves propagate backwards; wave velocity increases with cell radius; lamellipodia inhibition attenuates, slows down or even suppresses the waves. Together, our experiments and modelling evidence the importance of lamellipodia in collective cell migration and waves.

biophysics↗

bioRxiv2017

A systems approach to refine disease taxonomy by integrating phenotypic and molecular networks

The International Classification of Diseases (ICD) relies on clinical features and lags behind the current understanding of the molecular specificity of disease pathobiology, necessitating approaches that incorporate growing biomedical data for classifying diseases to meet the needs of precision medicine. Our analysis revealed that the heterogeneous molecular diversity of disease chapters and the blurred boundary between disease categories in ICD should be further investigated. Here, we propose a new classification of diseases (NCD) by developing an algorithm that predicts the additional categories of a disease by integrating multiple networks consisting of disease phenotypes and their molecular profiles. With statistical validations from phenotype-genotype associations and interactome networks, we demonstrate that NCD improves disease specificity owing to its overlapping categories and polyhierarchical structure. Furthermore, NCD captures the molecular diversity of diseases and defines clearer boundaries in terms of both phenotypic similarity and molecular associations, establishing a rational strategy to reform disease taxonomy.

bioinformatics↗

bioRxiv2017

Generation of Mouse-Zebrafish Hematopoietic Tissue Chimeric Embryos for Hematopoiesis and Host-Pathogen Interaction Studies

Xenografts of the hematopoietic system are extremely useful as disease models and for translational research. Zebrafish xenografts have been widely used to monitor blood cancer cell dissemination and homing due to the optical clarity of embryos and larvae, which allow unrestricted in vivo visualization of migratory events. To broaden the scope of xenotransplantation studies in zebrafish, we have developed a technique that transiently generates hematopoietic tissue chimeras by transplanting murine bone marrow cells into zebrafish blastulae. This procedure leads to mammalian cell integration into the fish developmental hematopoietic program. Monitoring zebrafish chimeras at different time points post fertilization using in vivo time-lapse and confocal imaging showed murine cell co-localization with developing primitive and definitive hematopoietic tissues, intravasation into fish circulation, and dynamic hematopoietic cell-vascular endothelial and hematopoietic cell-niche interactions. Immunohistochemistry assays performed in chimeric animals showed that, after engraftment, murine cells expressed antigens related to i) hematopoietic stem and progenitor cells, ii) active cell proliferation, and iii) myeloid cell lineages. Lastly, xenografted zebrafish larvae infected with Klebsiella pneumoniae showed murine immune cells trafficking to bacterial foci and interacting with bacterial cells. Overall, these results show that mammalian bone marrow cells xenografted in zebrafish integrate into the host hematopoietic system revealing highly conserved molecular mechanisms of hematopoiesis between zebrafish and mammals. In addition, this procedure introduces a useful and simple method that improves and broadens the scope of hematopoietic tissue xenotransplantation studies in zebrafish.

developmental biology↗

bioRxiv2017

The DEAD box RNA helicase Ddx39a is essential for myocyte and lens development in zebrafish

RNA helicases from the DEAD-box family are found in almost all organisms and have important roles in RNA metabolism including RNA synthesis, processing and degradation. The function and mechanism of action of most of these helicases in animal development and human disease are largely unexplored. In a zebrafish mutagenesis screen to identify genes essential for heart development we identified a zebrafish mutant, which disrupts the gene encoding the RNA helicase DEAD-box 39a (ddx39a).Homozygous ddx39a mutant embryos exhibit profound cardiac and trunk muscle dystrophy, along with lens abnormalities caused by abrupt terminal differentiation of cardiomyocyte, myoblast and lens fiber cells. Further investigation indicated that loss of ddx39a hindered mRNA splicing of members of the kmt2 gene family, leading to mis-regulation of structural gene expression in cardiomyocyte, myoblast and lens fiber cells. Taken together, these results show that Ddx39a plays an essential role in establishment of proper epigenetic status during cell differentiation.

developmental biology↗

bioRxiv2017

Identification of Cancer-associated Metabolic Vulnerabilities by Modeling Multi-objective Optimality in Metabolism

Computational modeling of the genome-wide metabolic network is essential for designing new therapeutics targeting cancer-associated metabolic disorder, which is a hallmark of human malignancies. However, previous studies generally assumed that metabolic fluxes of cancer cells are subjected to the maximization of biomass production, despite the wide existence of trade-offs among multiple metabolic objectives. To address this issue, we developed a multi-objective model of cancer metabolism with algorithms depicting approximate Pareto surfaces and incorporating multiple omics datasets. To validate this approach, we built individualized models for NCI-60 cancer cell lines, and accurately predicted cell growth rates and other biological consequences of metabolic perturbations in these cells. By analyzing the landscape of approximate Pareto surface, we identified a list of metabolic targets essential for cancer cell proliferation and the Warburg effect, and further demonstrated their close association with cancer patient survival. Finally, metabolic targets predicted to be essential for tumor progression were validated by cell-based experiments, confirming this multi-objective modelling method as a novel and effective strategy to identify cancer-associated metabolic vulnerabilities.

systems biology↗

bioRxiv2017

Spatiotemporal DNA Methylome Dynamics of the Developing Mammalian Fetus

Genetic studies have revealed an essential role for cytosine DNA methylation in mammalian development. However, its spatiotemporal distribution in the developing embryo remains obscure. Here, we profiled the methylome landscapes of 12 mouse tissues/organs at 8 developmental stages spanning from early embryogenesis to birth. Indepth analysis of these spatiotemporal epigenome maps systematically delineated ~2 million methylation variant regions and uncovered widespread methylation dynamics at nearly one-half million tissue-specific enhancers, whose human counterparts were enriched for variants involved in genetic diseases. Strikingly, these predicted regulatory elements predominantly lose CG methylation during fetal development, whereas the trend is reversed after birth. Accumulation of non-CG methylation within gene bodies of key developmental transcription factors coincided with their transcriptional repression during later stages of fetal development. These spatiotemporal epigenomic maps provide a valuable resource for studying gene regulation during mammalian tissue/organ progression and for pinpointing regulatory elements involved in human developmental diseases.

genomics↗

bioRxiv2017

Unravelling the genomic basis and evolution of the pea aphid male wing dimorphism

Wing dimorphisms have long served as models for examining the ecological and evolutionary tradeoffs associated with alternative morphologies [1], yet the mechanistic basis of morph determination remains largely unknown. Here we investigate the genetic basis of the pea aphid (Acyrthosiphon pisum) wing dimorphism, wherein males exhibit one of two alternative morphologies that differ dramatically in a set of correlated traits that inclused the presence or absence of wings [2-4]. Unlike the environmentally-induced asexual female aphid wing polyphenism [5], the male wing polymorphism is genetically determined by a single uncharacterized locus on the X chromosome called aphicarus (\"aphid\" plus \"Icarus\", api) [6, 7]. Using recombination and association mapping, we localized api to a 130kb region of the pea aphid genome. No nonsynonymous variation in coding sequences strongly associated with the winged and wingless phenotypes, indicating that api is likely a regulatory change. Gene expression level profiling revealed an aphid-specific gene from the region expressed at higher levels in winged male embryos, coinciding with the expected stage of api action. Comparison of the api region across biotypes (pea aphid populations specialized to different host plants that began diverging ~16,000 years ago [8, 9]) revealed that the two alleles were likely present prior to biotype diversification. Moreover, we find evidence for a recent selective sweep of a wingless allele since the biotypes diversified. In sum, this study provides insight into how adaptive, complex traits evolve within and across natural populations.

evolutionary biology↗

bioRxiv2017

An insula-central amygdala circuit for behavioral inhibition

Predicting which substances are suitable for consumption during foraging is critical for animals to survive. While food-seeking behavior is extensively studied, the neural circuit mechanisms underlying avoidance of potentially poisonous substances remain poorly understood. Here we examined the role of the insular cortex (IC) to central amygdala (CeA) circuit in the establishment of such avoidance behavior. Using anatomic tracing approaches combined with optogenetics-assisted circuit mapping, we found that the gustatory region of the IC sends direct excitatory projections to the lateral division of the CeA (CeL), making monosynaptic excitatory connections with distinct populations of CeL neurons. Specific inhibition of neurotransmitter release from the CeL-projecting IC neurons prevented mice from acquiring the \"no-go\" response, while leaving the \"go\" response largely unaffected in a tastant (sucrose/quinine)-reinforced \"go/no-go\" task. Furthermore, selective activation of the IC-CeL pathway with optogenetics drove unconditioned lick suppression in thirsty animals, induced aversive responses, and was sufficient to instruct conditioned action suppression in response to a cue predicting the optogenetic activation. These results indicate that activity in the IC-CeL circuit is necessary for establishing anticipatory avoidance responses to an aversive tastant, and is also sufficient to drive learning of such anticipatory avoidance. This function of the IC-CeL circuit is likely important for guiding avoidance of substances with unpleasant tastes during foraging in order to minimize the chance of being poisoned.\n\nSignificance StatementThe ability to predict which substances are suitable for consumption is critical for survival. Here we found that activity in the insular cortex (IC) to central amygdala (CeA) circuit is necessary for establishing avoidance responses to an unpleasant tastant, and is also sufficient to drive learning of such avoidance responses. These results suggest that the IC-CeA circuit is critical for behavioral inhibition in anticipation of potentially poisonous substances during foraging.

neuroscience↗

bioRxiv2017

Transcriptome Deconvolution of Heterogeneous Tumor Samples with Immune Infiltration

Transcriptomic deconvolution in cancer and other heterogeneous tissues remains challenging. Available methods lack the ability to estimate both component-specific proportions and expression profiles for individual samples. We present DeMixT, a new tool to deconvolve high dimensional data from mixtures of more than two components. DeMixT implements an iterated conditional mode algorithm and a novel gene-set-based component merging approach to improve accuracy. In a series of experimental validation studies and application to TCGA data, DeMixT showed high accuracy. Improved deconvolution is an important step towards linking tumor transcriptomic data with clinical outcomes. An R package, scripts and data are available: https://github.com/wwylab/DeMixT/.

bioinformatics↗

bioRxiv2017

Specific Virus-Host Genome Interactions Revealed By Tethered Chromosome Conformation Capture

Viruses have evolved a variety of mechanisms to interact with host cells for their adaptive benefits, including subverting host immune responses and hijacking host DNA replication/transcription machineries [1-3]. Although interactions between viral and host proteins have been studied extensively, little is known about how the vial genome may interact with the host genome and how such interactions could affect the activities of both the virus and the host cell. Since the three-dimensional organization of a genome can have significant impact on genomic activities such as transcription and replication, we hypothesize that such structure-based regulation of genomic functions also applies to viral genomes depending on their association with host genomic regions and their spatial locations inside the nucleus. Here, we used Tethered Chromosome Conformation Capture (TCC) to investigate viral-host genome interactions between the adenovirus and human lung fibroblast cells. We found viral-host genome interactions were enriched in certain active chromatin regions and chromatin domains marked by H3K27me3. The contacts by viral DNA seems to impact the structure and function of the host genome, leading to remodeling of the fibroblast epigenome. Our study represents the first comprehensive analysis of viral-host interactions at the genome structure level, revealing unexpectedly specific virus-host genome interactions. The non-random nature of such interactions indicates a deliberate but poorly understood mechanism for targeting of host DNA by foreign genomes.

microbiology↗

bioRxiv2017

Transcriptomic Correlates Of Neuron Electrophysiological Diversity

How neuronal diversity emerges from complex patterns of gene expression remains poorly understood. Here we present an approach to understand electrophysiological diversity through gene expression by integrating transcriptomics with intracellular electrophysiology. Using a brain-wide dataset of 34 neuron types, we identified 420 genes whose expression levels significantly correlated with variability in one or more of 11 electrophysiological parameters. The majority of these correlations were consistent in an independent sample of 12 visual cortex cell types. Many associations reported here have the potential to provide new insights into how neurons generate functional diversity, and correlations of ion channel genes like Gabrd and Scn1a (Nav1.1) with resting potential and spiking frequency are consistent with known causal mechanisms. These results suggest that despite the complexity linking gene expression to electrophysiology, there are likely some general principles that govern how individual genes establish phenotypic diversity across very different cell types.

neuroscience↗