Biology subjects

Lu, C.

Publications and source records attributed to Lu, C..

At least 145 records · Page 8Linked to original sources

bioRxiv2021

Cleavage of histone H2A during embryonic stem cell differentiation destabilizes nucleosomes to counteract gene activation

Histone proteolysis is a poorly understood phenomenon in which the N-terminal tails of histones are irreversibly cleaved by intracellular proteases. During development, histone post-translational modifications are known to orchestrate gene expression patterns that ultimately drive cell fate decisions. Therefore, deciphering the mechanisms of histone proteolysis is necessary to enhance the understanding of cellular differentiation. Here we show that H2A is cleaved by the lysosomal protease Cathepsin L during ESCs differentiation. Using quantitative mass spectrometry (MS), we identified L23 to be the primary cleavage site that gives rise to the clipped form of H2A (cH2A), which reaches a maximum level of ~1% of total H2A after four days of differentiation. Using ChIP-seq, we found that preventing proteolysis leads to an increase in acetylated H2A at promoter regions in differentiated ES cells. We also identified novel readers of different acetylated forms of H2A in pluripotent ES cells, such as members of the PBAF remodeling complex. Finally, we showed that H2A proteolysis abolishes this recognition. Altogether, our data suggests that proteolysis serves as an efficient mechanism to silence pluripotency genes and destabilize the nucleosome core particle.

developmental biology↗

bioRxiv2021

Antipsychotic-induced epigenomic reorganization in frontal cortex samples from individuals with schizophrenia

Genome-wide association studies have revealed >270 loci associated with schizophrenia risk, yet these genetic factors do not seem to be sufficient to fully explain the molecular determinants behind this psychiatric condition. Epigenetic marks such as post-translational histone modifications remain largely plastic during development and adulthood, allowing a dynamic impact of environmental factors, including antipsychotic medications, on access to genes and regulatory elements. However, few studies so far have profiled cell-specific genome-wide histone modifications in postmortem brain samples from schizophrenia subjects, or the effect of antipsychotic treatment on such epigenetic marks. Here we conducted ChIP-seq analyses focusing on histone marks indicative of active enhancers (H3K27ac) and active promoters (H3K4me3), alongside RNA-seq, using frontal cortex samples from antipsychotic-free (AF) and antipsychotic-treated (AT) individuals with schizophrenia, as well as individually matched controls (n = 58). Schizophrenia subjects exhibited thousands of neuronal and non-neuronal epigenetic differences at regions that included several susceptibility genetic loci, such as NRG1, DISC1, and DRD3. By analyzing the AF and AT cohorts separately, we identified schizophrenia-associated alterations in specific transcription factors, their regulatees, and epigenomic and transcriptomic features that were reversed by antipsychotic treatment; as well as those that represented a consequence of antipsychotic medication rather than a hallmark of schizophrenia in postmortem human brain samples. Notably, we also found that the effect of age on epigenomic landscapes was more pronounced in frontal cortex of AT-schizophrenics, as compared to AF-schizophrenics and controls. Together, these data provide important evidence of epigenetic alterations in the frontal cortex of individuals with schizophrenia, and remark for the first time the impact of age and antipsychotic treatment on chromatin organization.

neuroscience↗

bioRxiv2021

Native MOWChIP-seq: Genome-wide profiles of key protein bindings reveal functional differences among various brain regions

Genome-wide profiling of interactions between genome and various functional proteins is critical for understanding regulatory processes involved in development and diseases. Conventional assays require a large number of cells and high-quality data on tissue samples are scarce. Here we optimized a low-input chromatin immunoprecipitation followed by sequencing (ChIP-seq) technology for profiling RNA polymerase II (Pol II), transcription factor (TF), and enzyme binding at the genome scale. The new approach, termed native MOWChIP-seq, produces high-quality binding profiles using 1000-50,000 cells. We used the approach to examine the binding of Pol II and two TFs (EGR1 and MEF2C) in cerebellum and prefrontal cortex of mouse brain and found that their binding profiles are highly reflective of the functional differences between the two brain regions. Our analysis reveals the potential for linking genome-wide TF or Pol II profiles with neuroanatomical origins of brain cells.

genomics↗

bioRxiv2021

Tumor PD-L1 selectively suppresses type I interferon in myeloid cells to suppress CTL recruitment to promote lung metastasis

The mechanism underlying tumor cell PD-L1 (tPD-L1) induction of immune suppression through T cell PD-1 is well-known, but the mechanism underlying tPD-L1 induction of immune suppression via an intermediate cell is incompletely understood. We report here that tPD-L1 does not suppress cytotoxic T lymphocyte (CTL) activation and lytic function when only tumor cells and CTLs are present. Strikingly, knocking out PD-L1 in tumor cells has no effect on primary tumor growth, but significantly decreases lung metastasis in a CTL-dependent manner. Depletion of myeloid cells impaired tPD-L1 promotion of lung metastasis. Single-cell RNA sequencing revealed that tPD-L1 engages myeloid PD-1 (mPD-1) to antagonize type I interferon (IFN-I) and STAT1 signaling to repress Cxcl9 and Cxcl10 expression to impair CTL recruitment to lung metastases. Human patient response to PD-1 blockade immunotherapy correlates with IFN-I response in myeloid cells. Our data determines that the tPD-L1/mPD-1/IFN-I/STAT1/Cxcl9/10 axis controls CTL tumor infiltration in lung metastasis.

cancer biology↗

bioRxiv2021

The Hox gene Antennapedia regulates wing development through 20-hydroxyecdysone in insect

A long-standing view in the field of evo-devo is that insect forewings develop without any Hox gene input. The Hox gene Antennapedia (Antp), despite being expressed in the thoracic segments of insects, has no effect on wing development. This view has been obtained from studies in two main model species, Drosophila and Tribolium. Here, we show that partial loss of function of Antp resulted in reduced and malformed adult wings in Bombyx, Drosophila, and Tribolium. Antp mediates wing growth in Bombyx by directly regulating the ecdysteriod biosynthesis enzyme gene (shade) in the wing tissue, which leads to local production of the growth hormone 20E. In turn, 20E signaling also up-regulates Antp. Additional targets of Antp are wing cuticular protein genes CPG24, CPH28, and CPG9, essential for wing development. We propose, thus, that insect wing development occurs in an Antp-dependent manner.

developmental biology↗

bioRxiv2021

Pparg drives luminal differentiation and luminal tumor formation in the urothelium

Pparg, a nuclear receptor, is downregulated in basal subtype bladder cancers that tend to be muscle invasive and amplified in luminal subtype bladder cancers that tend to be non-muscle invasive. Bladder cancers derive from the urothelium, one of the most quiescent epithelia in the body which is composed of basal, intermediate, and superficial cells. We find that expression of an activated form of Pparg (VP16;Pparg) in basal progenitors induces formation of superficial cells in situ, that exit the cell cycle, and do not form tumors. Expression in basal progenitors that have been activated by mild injury however, results in luminal tumor formation. We find that tumors are immune deserted, which may be linked to downregulation of Nf-kb, a Pparg target. Interestingly, some luminal tumors begin to shift to basal subtype tumors with time, downregulating Pparg and other luminal markers. Our findings have important implications for treatment and diagnosis bladder cancer.

cancer biology↗

bioRxiv2021

Epigenomic and transcriptomic differences between low-grade and acute inflammation in LPS-induced murine immune cells

Chronic, low-grade inflammation has a widespread and significant impact on health, especially in Western society. While inflammation is beneficial for the removal of microbes, low-grade inflammation never resolves and can cause or worsen other diseases. The process by which low-grade inflammation occurs remains poorly understood. Here we exposed murine bone-marrow derived monocytes to chronic lipopolysaccharide (LPS) stimulation at low dose or high dose, as well as a PBS control. The cells were profiled for genome-wide H3K27ac modification and gene expression. The gene expression of TRAM-deficient and IRAK-M-deficient monocytes with LPS exposure was also analyzed. We discover that low-grade inflammation preferentially utilizes the TRAM/TRIF-dependent pathway of TLR4 signaling, and induces the expression of interferon response genes. In contrast, acute inflammation uniquely upregulates metabolic and proliferative pathways that also appear to be TRAM-dependent. The extensive differences in the epigenomic landscape between low-dose and high-dose conditions suggest the importance of epigenetic regulations in driving differential responses. Our data provide potential targets for future mechanistic or therapeutic studies.

immunology↗

bioRxiv2021

DeepLncLoc: a deep learning framework for long non-coding RNA subcellular localization prediction based on subsequence embedding

MotivationLong non-coding RNAs (IncRNAs) are a class of RNA molecules with more than 200 nucleotides. A growing amount of evidence reveals that subcellular localization of lncRNAs can provide valuable insights into their biological functions. Existing computational methods for predicting lncRNA subcellular localization use k-mer features to encode lncRNA sequences. However, the sequence order information is lost by using only k-mer features. ResultsWe proposed a deep learning framework, DeepLncLoc, to predict lncRNA subcellular localization. In DeepLncLoc, we introduced a new subsequence embedding method that keeps the order information of lncRNA sequences. The subsequence embedding method first divides a sequence into some consecutive subsequences, and then extracts the patterns of each subsequence, last combines these patterns to obtain a complete representation of the lncRNA sequence. After that, a text convolutional neural network is employed to learn high-level features and perform the prediction task. Compared to traditional machine learning models with k-mer features and existing predictors, DeepLncLoc achieved better performance, which shows that DeepLncLoc could effectively predict lncRNA subcellular localization. Our study not only presented a novel computational model for predicting lncRNA subcellular localization but also provided a new subsequence embedding method which is expected to be applied in other sequence-based prediction tasks. AvailabilityThe DeepLncLoc web server, source code and datasets are freely available at http://bioinformatics.csu.edu.cn/DeepLncLoc/, and https://github.com/CSUBioGroup/DeepLncLoc. Contactlimin@mail.csu.edu.cn

bioinformatics↗

bioRxiv2021

Neural Basis of the Delayed Gratification

Balancing instant gratification versus delayed, but better gratification is important for optimizing survival and reproductive success. Although psychologists and neuroscientists have long attempted to study delayed gratification through human psychological and brain activity monitoring, and animal research, little is known about its neural basis. We successfully trained mice to perform a waiting-and-water-reward delayed gratification task and used these animals in physiological recording and optical manipulation of neuronal activity during the task to explore its neural basis. Our results showed that the activity of DA neurons in ventral tegmental area (VTA) increases steadily during the waiting period. Optical activation vs. silencing of these neurons, respectively, extends or reduces the duration of waiting. To interpret this data, we developed a reinforcement learning (RL) model that reproduces our experimental observations. In this model, steady increases in DAergic activity signal the value of waiting and support the hypothesis that delayed gratification involves real-time deliberation. TEASERSustained ramping dopaminergic activation helps individuals to resist impulsivity and wait for laerger but later return.

neuroscience↗

bioRxiv2021

A positive role of task-deactivated default mode network in narrative speech comprehension

During speech comprehension, as listeners need to keep tracking the external audio streams, the default mode network (DMN) is often de-activated and anticorrelated with task-positive networks. Such a pattern has been interpreted as the suppression of the DMN to support externally-oriented cognitive processes. Taking a "two-brain" approach, the current study demonstrated that, despite exhibiting deactivation and anticorrelated with the language network and executive control network, the DMN was not suppressed but played an active role in spoken narrative comprehension. This was evidenced by significant listener-speaker neural couplings in both the posterior and anterior DMN and the positive correlation between the coupling strength and listeners speech comprehension. Moreover, we demonstrated that the functionality of posterior DMN depended on its interaction with the executive control network, rather than its level of activation. Finally, Dynamic Causal Modeling together with the two-brain results indicates the language and executive control networks, the anterior DMN, and the posterior DMN occupied the bottom, intermediate and top layers of a hierarchical system, respectively. These results suggest that the DMN may primarily serve as an internally-oriented system that cooperates with the externally-oriented networks, which may allow the transformation of external acoustic signals into internal mental representations during language comprehension.

neuroscience↗

bioRxiv2021

Whole Genome and Exome Sequencing Reference Datasets from A Multi-center and Cross-platform Benchmark Study

With the rapid advancement of sequencing technologies in the past decade, next generation sequencing (NGS) analysis has been widely applied in cancer genomics research. More recently, NGS has been adopted in clinical oncology to advance personalized medicine. Clinical applications of precision oncology require accurate tests that can distinguish tumor-specific mutations from errors or artifacts introduced during NGS processes or data analysis. Therefore, there is an urgent need to develop best practices in cancer mutation detection using NGS and the need for standard reference data sets for systematically benchmarking sequencing platforms, library protocols, bioinformatics pipelines and for measuring accuracy and reproducibility across platforms and methods. Within the SEQC2 consortium context, we established paired tumor-normal reference samples, a human triple-negative breast cancer cell line and a matched normal cell line derived from B lymphocytes. We generated whole-genome (WGS) and whole-exome sequencing (WES) data using 16 NGS library preparation protocols, seven sequencing platforms at six different centers. We systematically interrogated somatic mutations in the paired reference samples to identify factors affecting detection reproducibility and accuracy in cancer genomes. These large cross-platform/site WGS and WES datasets using well-characterized reference samples will represent a powerful resource for benchmarking NGS technologies, bioinformatics pipelines, and for the cancer genomics studies.

bioinformatics↗

bioRxiv2021

Prolonged epigenetic and synaptic plasticity alterations following single exposure to a psychedelic in mice

Clinical evidence suggests a potential therapeutic effect of classic psychedelics for the treatment of depression. The most outstanding and distinct characteristic is the rapid and sustained antidepressant action with one single exposure to the drug. However, the biological substrates and key mediators of psychedelics enduring action remain unknown. Here, we show that a single administration of the psychedelic DOI produced fast-acting effects on frontal cortex dendritic spine structure and acceleration of fear extinction via the 5-HT2A receptor. Additionally, a single dose of DOI led to changes in chromatin organization particularly at enhancer regions of genes involved in synaptic assembly that stretched for days after the psychedelic exposure. DOI-induced alterations in neuronal epigenome overlapped with genetic loci associated with schizophrenia, depression and attention deficit hyperactivity disorder. Together, these data support the notion that epigenetic-driven changes in synaptic plasticity operate as the mechanistic substrate of psychedelics long-lasting antidepressant action but also warn on the limitations in individuals with underlying risk for psychosis.

neuroscience↗

bioRxiv2021

The effects of hydroelectric dam construction on spatial-temporal changes of land use land cover in Bui National Park, Ghana

The construction of hydroelectric dams in forest reserves has become a matter of concern for biodiversity conservationists. Visibly among which is the potential to cause changes in climate and land cover and subsequently affect fauna and flora composition. Spatio-temporal changes of climate and land cover in the Bui National Park was analyzed using indices calculations of the landscape based on land cover maps obtained from Landsat satellite images for pre-and post-dam construction periods. Significant changes in land cover following the dam construction were observed. Notable changes include the built-up areas and water body, which recorded an increase of 315.64 % and 4593.43 % respectively, while the forest area decreased. Significant reduction in rainfall (U = 24,{rho} < 0.05) and increase in temperature (U = 22.5,{rho} < 0.05) were observed between the pre-and post-dam construction periods. Increased human activities such as illegal mining, indiscriminate tree felling, uncontrolled cattle grazing and charcoal production within the reserve results from inadequate monitoring and law enforcement after the dam construction could likely compound the changes in land cover.

ecology↗

bioRxiv2021

Impact of Meteorological factors on wheat growth period and irrigation water requirement --A case study of the Beijing-Tianjin-Hebei region in China

This study analyzes the irrigation water requirement of wheat in the growth stage in the Beijing-Tianjin-Hebei region under the changes of meteorological factors conditions, using the growth period data, and meteorological data from 80 meteorological stations, from 2000 to 2019. The results show that: (1) The annual average precipitation, average wind speed, and average relative humidity of the growth period in the Beijing-Tianjin-Hebei region show a downward variation trend, while the temperature variation shows an upward trend. Moreover, relative humidity and radiation exhibit a negative spatial correlation. (2) Wheat irrigation water requirement in the Beijing-Tianjin-Hebei region gradually decreases from north to south and east to west. However, the eastern region shows a gradually increasing trend, while the western region shows a decreasing trend. (3) Meteorological factors are negatively correlated with irrigation water requirement, potential evapotranspiration, effective precipitation, and relative humidity, and significantly positively correlated with sunshine hours, average temperature, and wind speed. The overall variation in irrigation water requirement has the highest correlation with potential evapotranspiration. However, the yearly variations in regional irrigation water requirement are dependent on factors such as wind speed, relative humidity, and radiation.

plant biology↗

bioRxiv2020

AlphaTracker: A Multi-Animal Tracking and Behavioral Analysis Tool

The advancement of behavioral analysis in neuroscience has been aided by the development of computational tools1,2. Specifically, computer vision algorithms have emerged as a powerful tool to elevate behavioral research3,4. Yet fully automatic analysis of social behavior remains challenging in two ways. First, existing tools to track and analyze behavior often focus on single animals, not multiple, interacting animals. Second, many available tools are not developed for novice users and require programming experience to run. Here, we unveil a computer vision pipeline called AlphaTracker, which requires minimal hardware requirements and produces reliable tracking of multiple unmarked animals. An easy-to-use user interface further enables manual inspection and curation of results. We demonstrate the practical, real-time advantages of AlphaTracker through the study of multiple, socially-interacting mice.

animal behavior and cognition↗

bioRxiv2020

Prokaryotic virus Host Predictor: a Gaussian model for host prediction of prokaryotic viruses in metagenomics

BackgroundViruses are ubiquitous biological entities, estimated to be the largest reservoirs of unexplored genetic diversity on Earth. Full functional characterization and annotation of newly-discovered viruses requires tools to enable taxonomic assignment, the range of hosts, and biological properties of the virus. Here we focus on prokaryotic viruses, which include phages and archaeal viruses, and for which identifying the viral host is an essential step in characterizing the virus, as the virus relies on the host for survival. Currently, the method for determining the viral host is either to culture the virus, which is low-throughput, time-consuming, and expensive, or to computationally predict the viral hosts, which needs improvements at both accuracy and usability. Here we develop a Gaussian model to predict hosts for prokaryotic viruses with better performances than previous computational methods. ResultsWe present here Prokaryotic virus Host Predictor (PHP), a software tool using a Gaussian model, to predict hosts for prokaryotic viruses using the differences of Ae-mer frequencies between viral and host genomic sequences as features. PHP gave a host prediction accuracy of 34% (genus level) on the VirHostMatcher benchmark dataset and a host prediction accuracy of 35% (genus level) on a new dataset containing 671 viruses and 60,105 prokaryotic genomes. The prediction accuracy exceeded that of two alignment-free methods (VirHostMatcher and WIsH, 28%-34%, genus level). PHP also outperformed these two alignment-free methods much (24%-38%vs 18%-20%, genus level) when predicting hosts for prokaryotic viruses which cannot be predicted by the BLAST-based or the CRISPR-spacer-based methods alone. Requiring a minimal score for making predictions (thresholding) and taking the consensus of the top 30 predictions further improved the host prediction accuracy of PHP. ConclusionsThe Prokaryotic virus Host Predictor software tool provides an intuitive and user-friendly API for the Gaussian model described herein. This work will facilitate the rapid identification of hosts for newly-identified prokaryotic viruses in metagenomic studies. Author SummaryProkaryotic viruses which include phages and archaeal viruses play an important role in balancing the global ecosystem by regulating the composition of bacteria and archaea in water and soil. Identifying the viral host is essential for characterizing the virus, as the virus relies on the host for survival. Currently, the method for determining the viral host is either to culture the virus which is low-throughput, time-consuming, and expensive, or to computationally predict the viral hosts which needs improvements at both accuracy and usability. This study developed a Gaussian model to predict hosts for prokaryotic viruses with better performances than previous computational methods. It will contribute to the rapid identification of hosts for prokaryotic viruses in metagenomic studies, and will extend our knowledge of virus-host interactions.

bioinformatics↗

bioRxiv2020

Pluripotent stem cell derived models of neurological diseases reveal early transcriptional heterogeneity

BackgroundMany neurodegenerative diseases (NDs) develop only later in life, when cells in the nervous system lose their structure or function. In genetic forms of NDs, this late onset phenomenon remains largely unexplained. ResultsAnalyzing single cell RNA sequencing (scRNA-seq) from Alzheimers disease (AD) patients, we find increased transcriptional heterogeneity in AD excitatory neurons. We hypothesized that transcriptional heterogeneity precedes ND pathologies. To test this idea experimentally, we used juvenile forms (72Q; 180Q) of Huntingtons disease (HD) iPSCs, differentiated them into committed neuronal progenitors, and obtained single cell expression profiles. We show a global increase in gene expression variability in HD. Autophagy genes become more stable, while energy and actin-related genes become more variable in the mutant cells. Knocking-down several differentially-variable genes resulted in increased aggregate formation, a pathology associated with HD. We further validated the increased transcriptional heterogeneity in CHD8+/- cells, a model for autism spectrum disorder. ConclusionsOverall, our results suggest that although NDs develop over time, transcriptional regulation imbalance is present already at very early developmental stages. Therefore, an intervention aimed at this early phenotype may be of high diagnostic value.

molecular biology↗

bioRxiv2020

Evolution of the SARS-CoV-2 proteome in three dimensions (3D) during the first six months of the COVID-19 pandemic

Three-dimensional structures of SARS-CoV-2 and other coronaviral proteins archived in the Protein Data Bank were used to analyze viral proteome evolution during the first six months of the COVID-19 pandemic. Analyses of spatial locations, chemical properties, and structural and energetic impacts of the observed amino acid changes in >48,000 viral proteome sequences showed how each one of the 29 viral study proteins have undergone amino acid changes. Structural models computed for every unique sequence variant revealed that most substitutions map to protein surfaces and boundary layers with a minority affecting hydrophobic cores. Conservative changes were observed more frequently in cores versus boundary layers/surfaces. Active sites and protein-protein interfaces showed modest numbers of substitutions. Energetics calculations showed that the impact of substitutions on the thermodynamic stability of the proteome follows a universal bi-Gaussian distribution. Detailed results are presented for six drug discovery targets and four structural proteins comprising the virion, highlighting substitutions with the potential to impact protein structure, enzyme activity, and functional interfaces. Characterizing the evolution of the virus in three dimensions provides testable insights into viral protein function and should aid in structure-based drug discovery efforts as well as the prospective identification of amino acid substitutions with potential for drug resistance.

molecular biology↗