Biology subjects

Hong, L.

Publications and source records attributed to Hong, L..

At least 73 records · Page 4Linked to original sources

bioRxiv2023

PIC recruitment by synthetic reader-actuators to polycomb-silenced genes blocks triple-negative breast cancer invasion

Scientists have used small molecule inhibitors and genetic knockdown of gene-silencing polycomb repressive complexes (PRC1/2) to determine if restoring the expression of tumor suppressor genes can block proliferation and invasion of cancer cells. A major limitation of this approach is that inhibitors can not restore key transcriptional activators that are mutated in many cancers, such as p53 and members of the BRAF SWI/SNF complex. Furthermore, small molecule inhibitors can alter the activity of, rather than inhibit, the polycomb enzyme EZH2. While chromatin has been shown to play a major role in gene regulation in cancer, poor clinical results for polycomb chromatin-targeting therapies for diseases like triple-negative breast cancer (TNBC) could discourage further development of this emerging avenue for treatment. To overcome the limitations of inhibiting polycomb to study epigenetic regulation, we developed an engineered chromatin protein to manipulate transcription. The synthetic reader-actuator (SRA) is a fusion protein that directly binds a target chromatin modification and regulates gene expression. Here, we report the activity of an SRA built from polycomb chromodomain and VP64 modules that bind H3K27me3 and subunits of the Mediator complex, respectively. In SRA-expressing BT-549 cells, we identified 122 upregulated differentially expressed genes (UpDEGs, [≥] 2-fold activation, adjusted p < 0.05). On-target epigenetic regulation was determined by identifying UpDEGs at H3K27me3-enriched, closed chromatin. SRA activity induced activation of genes involved in cell death, cell cycle arrest, and the inhibition of migration and invasion. SRA-expressing BT-549 cells showed reduced spheroid size in Matrigel over time, loss of invasion, and activation of apoptosis. These results show that Mediator-recruiting regulators broadly targeted to silenced chromatin activate silenced tumor suppressor genes and stimulate anti-cancer phenotypes. Therefore further development of gene-activating epigenetic therapies might benefit TNBC patients.

synthetic biology↗

bioRxiv2022

Extracellular matrix stiffness regulates fibroblast differentiation by influencing DNA methyltransferase 1 expression through microtubule polymerization

Cells sense physical cues, such as changes in extracellular matrix (ECM) stiffness, and translate these stimuli into biochemical signals that control various aspects of cellular behavior, thereby facilitating physiological and pathological processes in various organs. Evidence from multiple studies suggests that the anterior vaginal wall stiffness is higher in POP patients than in non-POP patients. Our experiments found that the expression of -smooth muscle actin (-SMA) in the anterior vaginal wall of patients with POP was increased, and the expression of DNMT1 was decreased. We used polyacrylamide gel to simulate matrix stiffening in vitro, and substrate stiffening induced the high expression of myofibroblast markers -SMA and CTGF in L929 cells. Inhibition of DNMT1 promotes fibroblast differentiation into myofibroblasts in vitro. The results of bioinformatics analysis showed that the expression of DNMT1 was significantly correlated with microtubule polymerization-related proteins. The experiment showed that the microtubule polymerization inhibitor nocodazole could eliminate the decrease of DNMT1 expression in fibroblasts induced by high stiffness. We conclude that fibroblasts sense an increase in the stiffness of the surrounding matrix and regulate fibroblast differentiation by regulating the expression of DNA methyltransferase 1 (DNMT1) through the regulation of microtubule polymerization. This study may help to elucidate the complex crosstalk between vaginal fibroblasts and their surrounding matrix in both healthy and pathological conditions, and provide new insights into the implications of potentially targeted phenotypic regulation mechanisms in material-related therapeutic applications.

cell biology↗

bioRxiv2022

RACK1 may participate in placental development via regulating proliferation and migration of trophoblast cell in pigs following intrauterine growth restriction

Intrauterine growth restriction (IUGR) is a severe complication in swine production. Placental insufficiency is responsible for inadequate fetal growth, but the specific etiology of placental dysfunction-induced IUGR in pigs remains poorly understood. In this work, placenta samples supplying the lightest-weight (LW) and mean-weight (MW) pig fetuses in the litter at day 65 (D65) of gestation were collected, and the relationship between fetal growth and placental morphologies and functions was investigated using histomorphological analysis, RNA sequencing, quantitative polymerase chain reaction, and in-vitro experiment in LW and MW placentas. Results showed that the folded structure of the epithelial bilayer of LW placentas followed a poor and incomplete development compared with that of MW placentas. A total of 632 differentially expressed genes (DEGs) were screened out between the LW and MW placentas, and RACK1 was found to be downregulated in LW placentas. The DEGs were mainly enriched in translation, ribosome, protein synthesis, and mTOR signaling pathway according to GO and KEGG enrichment analyses. In-vitro experiments indicated that the decreased RACK1 in LW placentas may be involved in abnormal development of placental folds (PFs) by inhibiting the proliferation and migration of porcine trophoblast cells. Taken together, these results revealed that RACK1 may be a vital regulator in the development of PFs via regulating trophoblast ribosome function, proliferation, and migration in pigs.

genetics↗

bioRxiv2022

Pupil-linked phasic arousal relates to the reduction of response inhibition: inferences from a simultaneous pupillometry and EEG-fMRI study

Attention reorienting is a critical cognitive function which drives how we respond to novel and unexpected stimuli. In recent years, arousal has been linked to attention reorienting. The timing and spatial organization of the interactions between the arousal and reorienting systems, however, remain only partially revealed. Here, we investigate the dynamics between the two systems through simultaneous recordings of pupillometry, EEG, and fMRI of healthy human subjects while they performed an auditory target detection task. We used pupil diameter and activity in the noradrenergic locus coeruleus to infer arousal, and found these measures linked to distinct cortical activity at various temporal stages of the reorienting response. Specifically, our results provide the first demonstration in humans of how phasic pupil-linked arousal relates to the reduction of response inhibition, an inference which otherwise would remain hidden without the help of simultaneous multi-modal acquisitions.

neuroscience↗

bioRxiv2022

Interpretable RNA Foundation Model from Unannotated Data for Highly Accurate RNA Structure and Function Predictions

Non-coding RNA structure and function are essential to understanding various biological processes, such as cell signaling, gene expression, and post-transcriptional regulations. These are all among the core problems in the RNA field. With the rapid growth of sequencing technology, we have accumulated a massive amount of unannotated RNA sequences. On the other hand, expensive experimental observatory results in only limited numbers of annotated data and 3D structures. Hence, it is still challenging to design computational methods for predicting their structures and functions. The lack of annotated data and systematic study causes inferior performance. To resolve the issue, we propose a novel RNA foundation model (RNA-FM) to take advantage of all the 23 million non-coding RNA sequences through self-supervised learning. Within this approach, we discover that the pre-trained RNA-FM could infer sequential and evolutionary information of non-coding RNAs without using any labels. Furthermore, we demonstrate RNA-FMs effectiveness by applying it to the downstream secondary/3D structure prediction, SARS-CoV-2 genome structure and evolution prediction, protein-RNA binding preference modeling, and gene expression regulation modeling. The comprehensive experiments show that the proposed method improves the RNA structural and functional modelling results significantly and consistently. Despite only being trained with unlabelled data, RNA-FM can serve as the foundational model for the field.

bioinformatics↗

bioRxiv2022

Single-Cell RNA-seq of Heart Reveals Intercellular Communication Drivers of Myocardial Fibrosis in Diabetic Mice

Diabetes-induced cardiomyopathy is characterized by myocardial fibrosis as a main pathology. In-depth study of cardiac heterogeneity and cell-to-cell interactions will help to reveal the pathogenesis of diabetic myocardial fibrosis and provide potential targets for the treatment of this disease. Here, we insighted into the intercellular communication drivers underlying myocardial fibrosis in mouse heart with high-fat-diet (HFD)/streptozotocin (STZ)-induced diabetes at single-cell resolution. Intercellular and protein-protein interaction networks of fibroblasts and macrophages, endothelial cells, as well as fibroblasts and epicardial cells reveal critical changes in ligand-receptor interactions such as Pdgf(s)-Pdgfra and Efemp1-Egfr, which promote the development of a profibrotic microenvironment during diabetes progression and confirm that specific inhibition of Pdgfra axis can significantly improve diabetic myocardial fibrosis. We further identified the phenotypically distinct Hrchi and Postnhi fibroblast subpopulations that are associated with pathological extracellular matrix remodeling, of which Hrchi fibroblasts are the most profibrogenic under diabetic conditions. Finally, we validated the role of Itgb1 hub gene mediated intercellular communication drivers of diabetic myocardial fibrosis in Hrchi fibroblasts, and confirmed the result by AAV9-mediated Itgb1 knockdown in the heart of diabetic mice. In summary, cardiac cell mapping provides novel insights into intercellular communication drivers underlying pathological extracellular matrix remodeling during diabetic myocardial fibrosis.

cell biology↗

bioRxiv2022

Nucleotide resolution genetic mapping in pigs by publicly accessible whole genome imputation

Genetic mapping to identify genes and alleles associated with or causing economically important quantitative trait variation in livestock animals such as pigs is a major goal in the genetic improvement animals. Despite recent advances in high throughput genotyping technologies, resolution of genetic mapping in pigs remains poor due in part to the low density of genotyped variant sites. In this study, we overcame this limitation by developing a reference haplotype panel for pigs based on 2,259 whole genome sequenced animals representing 44 pig breeds. We optimized the imputation procedure to achieve an average concordance rate in excess of 97%, non-reference concordance rate 91%, and r2 0.89. We demonstrated that genotype imputation using this resource can dramatically improve resolution of genetic mapping. Finally, we developed a public web server (swimgeno.org) to allow the pig genetics community to fully utilize this resource. We expect the resource and server to significantly facilitate genetic mapping and accelerate genetic improvement in pigs.

genomics↗

bioRxiv2022

A cooperative switch within the KaiC hexamer revealed by cryo-EM

The circadian clock of cyanobacteria is based on an approximately 24h rhythm in the phosphorylation level of KaiC, a hexameric ATPase. This oscillation can be reconstituted in vitro by incubating three proteins together with ATP. Like all chemical oscillators, this system must include a nonlinear, or switch-like, feedback loop, whose nature has been unclear. Here, by using single particle cryo-EM at near-atomic resolution we identified two major conformational states of KaiC subunits, denoted as the exposed state and the buried state, which may provide a structural basis of how the KaiC hexamer changes its conformation during the (day-night) phosphorylation-dephosphorylation cycle. We classify the abundance and pattern of exposed and buried states within hexamers for more than 160,000 KaiC particles. The statistics of the spatial arrangement of the two states in hexamers can be quantitatively fit by a simple statistical physics model with an interaction energy between neighboring subunits and a local field that depends on phosphorylation state. Our study shows that phosphorylation shifts the probability of each conformation and reveals that there is substantial cooperativity between neighboring subunits, which can allow a KaiC hexamer to respond in an ultrasensitive, switch-like manner to changes in the phosphorylation level.

biophysics↗

bioRxiv2022

Spatiotemporal dissociation of brain network connectivity in salience processing: A simultaneous pupillometry-EEG-fMRI study

The processing of salient stimuli involves a wide range of both bottom-up and top-down processes. Previous neuroimaging studies have identified multiple brain areas and networks for salience processing, including the salience network (SN), dorsal attention network (DAN), and the locus coeruleus-norepinephrine (LC-NE) neuromodulatory system. However, interactions among these networks and the cortico-subcortical systems in salience processing remain unclear. Here, we simultaneously recorded pupillometry, electroencephalogram (EEG), and functional magnetic resonance imaging (fMRI) during an auditory oddball paradigm. Using EEG-informed fMRI analysis, we temporally dissociated the target stimulus evoked activation, allowing us to identify the cascades of cortical areas associated with salience processing. Furthermore, functional connectivity analysis uncovered spatiotemporal functional network organizations of these salience processing neural correlates. Using pupillometry as a psychophysiological marker of LC-NE activity, we also assessed brain-pupil relationships. With state-space modeling of target modulated effective connectivity, we found that the target evoked pupillary response is associated with the network causal couplings from late to early subsystems, as well as the network switching initiated by the SN. These findings indicate that the SN might cooperate with pupil-indexed brainstem neuromodulatory systems, such as the LC-NE system, in the reorganization and dynamic switching of cortical networks, and shed light on the implications of their integrative framework in various cognitive processes and neurological diseases.

neuroscience↗

bioRxiv2021

fastMSA: Accelerating Multiple Sequence Alignment with Dense Retrieval on Protein Language

Evolutionarily related sequences provide information for the protein structure and function. Multiple sequence alignment, which includes homolog searching from large databases and sequence alignment, is efficient to dig out the information and assist protein structure and function prediction, whose efficiency has been proved by AlphaFold. Despite the existing tools for multiple sequence alignment, searching homologs from the entire UniProt is still time-consuming. Considering the success of AlphaFold, foreseeably, large-scale multiple sequence alignments against massive databases will be a trend in the field. It is very desirable to accelerate this step. Here, we propose a novel method, fastMSA, to improve the speed significantly. Our idea is orthogonal to all the previous accelerating methods. Taking advantage of the protein language model based on BERT, we propose a novel dual encoder architecture that can embed the protein sequences into a low-dimension space and filter the unrelated sequences efficiently before running BLAST. Extensive experimental results suggest that we can recall most of the homologs with a 34-fold speed-up. Moreover, our method is compatible with the downstream tasks, such as structure prediction using AlphaFold. Using multiple sequence alignments generated from our method, we have little performance compromise on the protein structure prediction with much less running time. fastMSA will effectively assist protein sequence, structure, and function analysis based on homologs and multiple sequence alignment.

bioinformatics↗

bioRxiv2020

Kinetic model of small RNA-mediated regulation suggests that a small RNA can regulate co-transcriptionally

Small RNAs (sRNAs) are important regulators of gene expression in bacteria, particularly during stress responses. Many genetically and biochemically well characterized sRNAs regulate gene expression post-transcriptionally, by affecting translation and degradation of the target mRNA after they bind to their targets through base pairing. However, how regulation at each of these levels quantitatively contributes to the overall efficacy of sRNA-mediated regulation is not well understood. Here we present a general approach combining imaging and mathematical modeling to determine kinetic parameters at different levels of sRNA-mediated gene regulation. Unexpectedly, our data reveal that certain previously characterized sRNAs are able to regulate some targets co-transcriptionally, rather strictly post-transcriptionally, and suggest that sRNA-mediated regulation can occur early in the mRNAs lifetime, perhaps as soon as the sRNA binding site is transcribed. In addition, our data suggest several important kinetic steps that may determine the efficiency and differential regulation of multiple mRNA targets by an sRNA. Particularly, binding of sRNA to the target mRNA is likely the rate-limiting step and may dictate the regulation hierarchy observed within an sRNA regulon.

biophysics↗

bioRxiv2020

A giant cell enhancer achieves cell-type specificity through activation via TCP and repression by Dof transcription factors

Proper pattern formation relies on the tight coordination of cell fate specification and cell cycle regulation in growing tissues. How this can be organized at enhancers that activate gene expression necessary for differentiation is not well understood. One such example is the patterning of the Arabidopsis thaliana sepal epidermis where giant cell fate specification is associated with the endoreduplication cell cycle. Previously, we identified an enhancer region capable of driving giant cell-specific expression. In this study, we use the giant cell enhancer as a model to understand the regulatory logic that promotes cell-type specific expression. Our dissection of the enhancer revealed that giant cell specificity is achieved primarily through the combination of two elements: an activator and a repressor. TCP transcription factors are involved in activation of non-specific expression throughout the epidermis with higher expression in endoreduplicated giant cells than small cells. Dof transcription factors act via the second element to repress activity of the enhancer and limit expression to giant cells. Thus, we find that cell-type specific expression emerges from the combined activities of two broadly acting enhancer elements.

plant biology↗

bioRxiv2020

Scalable and flexible gene-environment interaction analysis in millions of samples

MotivationGene-environment interaction (GEI) studies are a general framework that can be used to identify genetic variants that modify the effects of environmental, physiological, lifestyle, or treatment effects on complex traits. Moreover, accounting for GEIs can enhance our understanding of the genetic architecture of complex diseases. However, commonly-used statistical software programs for GEI studies are either not applicable to testing certain types of GEI hypotheses or have not been optimized for use in large samples. ResultsHere, we develop a new software program, GEM (Gene-Environment interaction analysis in Millions of samples), which supports the inclusion of multiple GEI terms, adjustment for GEI covariates, and robust inference, while allowing multi-threading to reduce computation time. GEM can conduct GEI tests as well as joint tests of genetic effects for both continuous and binary phenotypes. Through simulations, we demonstrate that GEM scales to millions of samples while addressing limitations of existing software programs. We additionally conduct a gene-sex interaction analysis on waist-hip ratio in 352,768 unrelated individuals from the UK Biobank, identifying 39 novel loci in the joint test that have not previously been reported in combined or sex-specific analyses. Our results demonstrate that GEM can facilitate the next generation of large-scale GEI studies and help advance our understanding of genomic contributions to complex traits. AvailabilityGEM is freely available as an open source project at https://github.com/large-scale-gxe-methods/GEM. Contactakmanning@mgh.harvard.edu, Han.Chen.2@uth.tmc.edu Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2020

Development of a COVID-19 vaccine based on the receptor binding domain displayed on virus-like particles

The ongoing coronavirus COVID-19 pandemic is caused by a new coronavirus (SARS-CoV-2) with its origin in the city of Wuhan in China. From there it has been rapidly spreading to many cities inside and outside China. Nowadays more than 33 millions with deaths surpassing 1 million have been recorded worldwide thus representing a major health issue. Rapid development of a protective vaccine against COVID-19 is therefore of paramount importance. Here we demonstrated that recombinantly expressed receptor binding domain (RBD) of the spike protein homologous to SARS binds to ACE2, the viral receptor. Higly repetitive display of RBD on immunologically optimized virus-like particles derived from cucumber mosaic virus (CuMVTT) resulted in a vaccine candidate that induced high levels of specific antibodies in mice which were able to block binding of spike protein to ACE2 and potently neutralized COVID-19 virus in vitro.

immunology↗

bioRxiv2020

Insulin dissociates by diverse mechanisms of coupled unfolding and unbinding

The protein hormone insulin exists in various oligomeric forms, and a key step in binding its cellular receptor is dissociation of the dimer. This dissociation process and its corresponding association process have come to serve as a paradigms of coupled (un)folding and (un)binding more generally. Despite its fundamental and practical importance, the mechanism of insulin dimer dissociation remains poorly understood. Here, we use molecular dynamics simulations, leveraging recent developments in umbrella sampling, to characterize the energetic and structural features of dissociation in unprecedented detail. We find that the dissociation is inherently multipathway with limiting behaviors corresponding to conformational selection and induced fit, the two prototypical mechanisms of coupled folding and binding. Along one limiting path, the dissociation leads to detachment of the C-terminal segment of the insulin B chain from the protein core, a feature believed to be essential for receptor binding. We simulate IR spectroscopy experiments to aid in interpreting current experiments and identify sites where isotopic labeling can be most effective for distinguishing the contributions of the limiting mechanisms.

biophysics↗

bioRxiv2020

A data-driven drug repositioning framework discovered a potential therapeutic agent targeting COVID-19

The global spread of SARS-CoV-2 requires an urgent need to find effective therapeutics for the treatment of COVID-19. We developed a data-driven drug repositioning framework, which applies both machine learning and statistical analysis approaches to systematically integrate and mine large-scale knowledge graph, literature and transcriptome data to discover the potential drug candidates against SARS-CoV-2. The retrospective study using the past SARS-CoV and MERS-CoV data demonstrated that our machine learning based method can successfully predict effective drug candidates against a specific coronavirus. Our in silico screening followed by wet-lab validation indicated that a poly-ADP-ribose polymerase 1 (PARP1) inhibitor, CVL218, currently in Phase I clinical trial, may be repurposed to treat COVID-19. Our in vitro assays revealed that CVL218 can exhibit effective inhibitory activity against SARS-CoV-2 replication without obvious cytopathic effect. In addition, we showed that CVL218 is able to suppress the CpG-induced IL-6 production in peripheral blood mononuclear cells, suggesting that it may also have anti-inflammatory effect that is highly relevant to the prevention immunopathology induced by SARS-CoV-2 infection. Further pharmacokinetic and toxicokinetic evaluation in rats and monkeys showed a high concentration of CVL218 in lung and observed no apparent signs of toxicity, indicating the appealing potential of this drug for the treatment of the pneumonia caused by SARS-CoV-2 infection. Moreover, molecular docking simulation suggested that CVL218 may bind to the N-terminal domain of nucleocapsid (N) protein of SARS-CoV-2, providing a possible model to explain its antiviral action. We also proposed several possible mechanisms to explain the antiviral activities of PARP1 inhibitors against SARS-CoV-2, based on the data present in this study and previous evidences reported in the literature. In summary, the PARP1 inhibitor CVL218 discovered by our data-driven drug repositioning framework can serve as a potential therapeutic agent for the treatment of COVID-19.

systems biology↗

bioRxiv2020

Timing of organ initiation is crucial for robust organ size

AbstractOrgans precisely regulate their size and shape to ensure proper function1-6. The contribution of organ initiation timing to final organ size and shape is often masked by compensatory adjustments to growth later in development7-9. Here we show that DEVELOPMENT RELATED MYB-LIKE1 (DRMY1) is required for both proper organ initiation timing and growth leading to robust sepal size in Arabidopsis. Within each drmy1 flower, the initiation of some sepals is variably delayed. Late-initiating sepals in drmy1 mutants remain smaller throughout development resulting in variability in sepal size. DRMY1 focuses the spatiotemporal signaling patterns of the plant hormones auxin and cytokinin, which jointly control the timing of sepal initiation. Contrary to expectation, our findings demonstrate that timing of organ initiation contributes to robust organ size throughout development.

plant biology↗

bioRxiv2019

Bayesian Modeling Reveals Ultrasensitivity Underlying Metabolic Compensation in the Cyanobacterial Circadian Clock

Mathematical models can enable a predictive understanding of mechanism in cell biology by quantitatively describing complex networks of interactions, but such models are often poorly constrained by available data. Owing to its relative biochemical simplicity, the core circadian oscillator in Synechococcus elongatus has become a prototypical system for studying how collective dynamics emerge from molecular interactions. The oscillator consists of only three proteins, KaiA, KaiB, and KaiC, and near-24-h cycles of KaiC phosphorylation can be reconstituted in vitro. Here, we formulate a molecularly-detailed but mechanistically agnostic model of the KaiA-KaiC subsystem and fit it directly to experimental data within a Bayesian parameter estimation framework. Analysis of the fits consistently reveals an ultrasensitive response for KaiC phosphorylation as a function of KaiA concentration, which we confirm experimentally. This ultrasensitivity primarily results from the differential affinity of KaiA for competing nucleotide-bound states of KaiC. We argue that the ultrasensitive stimulus-response relation is critical to metabolic compensation by suppressing premature phosphorylation at nighttime. SynopsisThis study takes a data-driven kinetic modeling approach to characterizing the interaction between KaiA and KaiC in the cyanobacterial circadian oscillator and understanding how the oscillator responds to changes in cellular metabolic conditions. O_LIAn extensive dataset of KaiC autophosphorylation measurements was gathered and fit to a detailed yet mechanistically agnostic kinetic model within a Bayesian parameter estimation framework. C_LIO_LIKaiA concentration tunes the sensitivity of KaiC autophosphorylation and the period of the full oscillator to %ATP. C_LIO_LIThe model reveals an ultrasensitive dependence of KaiC phosphorylation on KaiA concentration as a result of differential KaiA binding affinity to ADP- vs. ATP-bound KaiC. C_LIO_LIUltrasensitivity in KaiC phosphorylation contributes to metabolic compensation by suppressing premature phosphorylation at nighttime. C_LI

systems biology↗