Biology subjects

Lin, D.

Publications and source records attributed to Lin, D..

At least 127 records · Page 7Linked to original sources

bioRxiv2020

X-ray Structure of Main Protease of the Novel Coronavirus SARS-CoV-2 Enables Design of α-Ketoamide Inhibitors

A novel coronavirus has been identified as the causative agent of a massive outbreak of atypical pneumonia originating at Wuhan, Hubei province, China. Involved in the formation of the coronavirus replication complex, the viral main protease (Mpro, also called 3CLpro) represents an attractive target for therapy. We determined the crystal structure of the unliganded Mpro at 1.75 [A] resolution and used this structure to guide optimization of a series of alpha-ketoamide inhibitors. The main goal of the optimization efforts was improvement of the pharmacokinetic properties of the compounds. We further describe 1.95- and 2.20-[A] crystal structures of the complex between the enzyme and the most potent alpha-ketoamide optimized this way. These structures will form the basis for further development of these compounds to antiviral drugs.

biochemistry↗

bioRxiv2020

Alpha-ketoamides as broad-spectrum inhibitors of coronavirus and enterovirus replication

The main protease of coronaviruses and the 3C protease of enteroviruses share a similar active-site architecture and a unique requirement for glutamine in the P1 position of the substrate. Because of their unique specificity and essential role in viral polyprotein processing, these proteases are suitable targets for the development of antiviral drugs. In order to obtain near-equipotent, broad-spectrum antivirals against alphacoronaviruses, betacoronaviruses, and enteroviruses, we pursued structure-based design of peptidomimetic -ketoamides as inhibitors of main and 3C proteases. Six crystal structures of protease:inhibitor complexes were determined as part of this study. Compounds synthesized were tested against the recombinant proteases as well as in viral replicons and virus-infected cell cultures; most of them were not cell-toxic. Optimization of the P2 substituent of the -ketoamides proved crucial for achieving near-equipotency against the three virus genera. The best near-equipotent inhibitors, 11u (P2 = cyclopentylmethyl) and 11r (P2 = cyclohexylmethyl), display low-micromolar EC50 values against enteroviruses, alphacoronaviruses, and betacoronaviruses in cell cultures. In Huh7 cells, 11r exhibits three-digit picomolar activity against Middle East Respiratory Syndrome coronavirus.

biochemistry↗

bioRxiv2020

Improved subspecies identification in clinical Mycobacterium abscessus complex isolates using whole genome sequence

Mycobacterium abscessus complex, which is frequently reported causing a variety of skin and soft tissues diseases in humans, is composed of three subspecies, namely M. abscessus subsp. abscessus, M. abscessus subsp. massiliense and M. abscessus subsp. bolletii. Currently, the differentiation of these three subspecies in clinical isolates still largely depend on single gene identification methods like the genes namely hsp65, 16s with a limited accuracy. This study confirmed the limitations of the single gene based method in the subspecies identification. We performed a comprehensive analysis of MABC genomes in the NCBI database and tried to build an accurate and user-friendly identify method. Here, we describe an improved assay for Mycobacterium abscessus complex fast identification using WGS data, based on the identities of rpoB, erm(41) and rpls. Comprehensive analysis has been performed to compare our software results with the traditional method. The result showed that the method built-in this study could 100% identification the subspecies for the Mycobacterium abscessus complex in the public genome database (893 genomes from NCBI database and 6 clinical isolates from this study). Because this software can be easily integrated into a routine workflow to quickly and precisely provide subspecies-level identification and discrimination MABC different subspecies in clinical isolates by WGS. This assay will facilitate accurate molecular identification of species from the MABC complex in a variety of clinical specimens and diagnostic contexts.

microbiology↗

bioRxiv2019

Structural brain architectures match intrinsic functional networks and vary across domains: A study from 15000+ individuals

Brain structural networks have been shown to consistently organize in functionally meaningful architectures covering the entire brain. However, to what extent brain structural architectures match the intrinsic functional networks in different functional domains remains under explored. In this study, based on independent component analysis, we revealed 45 pairs of structural-functional (S-F) component maps, distributing across 9 functional domains, in both a discovery cohort (n=6005) and a replication cohort (UK Biobank, n=9214), providing a well-match multimodal spatial map template for public use. Further network module analysis suggested that unimodal cortical areas (e.g. somatomotor and visual networks) indicate higher S-F coherence, while heteromodal association cortices, especially the frontoparietal network (FPN), exhibit more S-F divergence. Collectively, these results suggest that the expanding and maturing brain association cortex demonstrates a higher degree of changes compared to unimodal cortex, which may lead to higher inter-individual variability and lower S-F coherence.

neuroscience↗

bioRxiv2019

Functional angiogenesis requires microenvironmental cues balancing endothelial cell migration and proliferation

Angiogenesis is a complex morphogenetic process that involves intimate interactions between multicellular endothelial structures and their extracellular milieu. In vitro models of angiogenesis can aid in reducing the complexity of the in vivo microenvironment and provide mechanistic insight into how soluble and physical extracellular matrix cues regulate this process. To investigate how microenvironmental cues regulate angiogenesis and the function of resulting microvasculature, we multiplexed an established angiogenesis-on-a-chip platform that affords higher throughput investigation of 3D endothelial cell sprouting emanating from a parent vessel through defined biochemical gradients and extracellular matrix. We found that two fundamental endothelial cell functions, migration and proliferation, dictate endothelial cell invasion as single cells vs. multicellular sprouts. Microenvironmental cues that elicit excessive migration speed incommensurate with proliferation resulted in microvasculature with poor barrier function and an inability to transport fluid across the microvascular bed. Restoring the balance between migration speed and proliferation rate rescued multicellular sprout invasion, providing a new framework for the design of pro-angiogenic biomaterials that guide functional microvasculature formation for regenerative therapies.

bioengineering↗

bioRxiv2019

Oxytocin Neurons Enable Social Transmission of Maternal Behavior

Maternal care is profoundly important for mammalian survival, and non-biological parents can express it after experience with infants. One critical molecular signal for maternal behavior is oxytocin, a hormone centrally released by hypothalamic paraventricular nucleus (PVN). Oxytocin enables plasticity within the auditory cortex, a necessary step for responding to infant vocalizations. To determine how this change occurs during natural experience, we continuously monitored homecage behavior of female virgin mice co-housed for days with an experienced mother and litter, synchronized with recordings from virgin PVN cells, including from oxytocin neurons. Mothers engaged virgins in maternal care by ensuring their nest presence, and demonstrated maternal behavior in self-generated pup retrieval episodes. These social interactions activated virgin PVN and gated behaviorally-relevant cortical plasticity for pup vocalizations. Thus rodents can acquire maternal behavior by social transmission, and our results describe a mechanism for adapting brains of adult caregivers to infant needs via endogenous oxytocin. One Sentence SummaryMother mice help co-housed virgins become maternal by enacting specific behaviors that activate virgin oxytocin neurons.

neuroscience↗

bioRxiv2019

Age-related Structural and Functional Variations in 5967 Individuals across the Adult Lifespan

Exploring brain changes across the human lifespan is becoming an important topic in neuroscience. Though there are multiple studies which investigated the relationship between age and brain imaging data, the results are heterogeneous due to small sample sizes and relatively narrow age ranges. Here, based on year-wise estimation of 5967 subjects from 13 to 72 years old, we aimed to provide a more precise description of adult lifespan variation trajectories of gray matter volume (GMV), structural network correlation (SNC) and functional network connectivity (FNC) using independent component analysis and multivariate linear regression model. Our results revealed the following relationships: 1)GMV linearly declined with age in most regions, while parahippocampus showed an inverted U-shape quadratic relationship with age; SNC presented a U-shape quadratic relationship with age within cerebellum, and inverted U-shape relationship primarily in the default mode network (DMN) and frontoparietal (FP) related correlation. 2) FNC tended to linearly decrease within resting-state networks (RSNs), especially in visual network and DMN. Early increase was revealed between RSNs, primarily in FP and DMN, which experienced decrease at older ages. U-shape relationship was also revealed to compensate for the cognition deficit in attention and subcortical related connectivity at late years. 3) The link between middle occipital gyrus and insula, as well as precuneus and cerebellum, exhibited similar changing trends between SNC and FNC across the adult lifespan. Collectively, these results highlight the benefit of lifespan study and provide a precise description of age-related regional variation and SNC/FNC changes based on a large dataset.

neuroscience↗

bioRxiv2019

Metabolic remodeling by TIGAR overexpression is a therapeutic target in esophageal squamous-cell carcinoma

Whole-genome sequencing has identified many amplified genes in esophageal squamous-cell carcinoma (ESCC); however, their roles and the clinical relevance have yet elucidated. Here we show TP53-induced glycolysis and apoptosis regulator (TIGAR) is a major player in ESCC progression and chemoresistance. TIGAR reprograms glucose metabolism from glycolysis to the glutamine pathway through AMP-activated kinase, and its overexpression is correlated with poor disease outcomes. Tigar knockout mice have reduced ESCC growth and tumor burden. Treatment of TIGAR-overexpressed ESCC cell xenografts and patient-derived tumor xenografts in mice with combination of glutaminase inhibitor and chemotherapeutic agents achieves significant more efficacy than chemotherapy alone. These findings shed light on an important role of TIGAR in ESCC and provide evidence for targeted treatment of TIGAR-overexpressed ESCC.\n\nSignificanceEffective and target therapies are required for ESCC, one of the most common types of digestive OR cancer. Little has been known about the biology of ESCC progression or potential molecular targets OR for treatment. Whole-genome sequencing and RNA sequencing studies in ESCC have identified OR many recurrent copy number gain genes; however, the roles and druggable relevance of these OR genes remains poorly understood. Herein we demonstrate that TIGAR overexpression leads to OR metabolic remodeling, promoting ESCC progression and resistance to chemotherapeutic agents. OR Inhibiting the glutamine pathway significantly represses TIGAR-overexpressing ESCC growth and OR enhances tumor cell sensitization to cytotoxic agents. These findings might provide the rationale OR for clinical trials testing glutamine pathway inhibitors in combination with chemotherapy in OR TIGAR-expressing ESCC.

cancer biology↗

bioRxiv2019

scClassify: hierarchical classification of cells

Cell type identification is a key computational challenge in single-cell RNA-sequencing (scRNA-seq) data. To capitalize on the large collections of well-annotated scRNA-seq datasets, we present scClassify, a hierarchical classification framework based on ensemble learning. scClassify can identify cells from published scRNA-seq datasets more accurately and more finely than in the original publications. We also estimate the cell number needed for accurate classification anywhere in a cell type hierarchy.

bioinformatics↗

bioRxiv2019

DLO Hi-C Tool for Digestion-Ligation-Only Hi-C Chromosome Conformation Capture Data Analysis

BackgroundIt is becoming increasingly important to understand the mechanism of regulatory elements on target genes in long-range genomic distance. 3C (Chromosome Conformation Capture) and its derived methods are now widely applied to investigate genome organizations and gene regulation. Digestion-Ligation-Only Hi-C (DLO Hi-C) is a new technology with high efficiency and effective cost for whole-genome chromosome conformation capture.\n\nResultsHere, we introduce DLO Hi-C Tool, a flexible and versatile pipeline for processing DLO Hi-C data from raw sequencing reads to normalized contact maps and providing quality controls for different steps. It includes more efficient iterative mapping and linker filtering. We applied DLO Hi-C Tool to different DLO Hi-C datasets, and demonstrated its ability of processing large data in multi-threading.\n\nConclusionsDLO Hi-C Tool is suitable for processing DLO Hi-C and in situ DLO Hi-C datasets. It is convenient and efficient for DLO Hi-C data processing.

bioinformatics↗

bioRxiv2019

PAG neurons encode a simplified action-selective signal during aggression

SummaryWhile the ventromedial hypothalamus, ventrolateral area (VMHvl) is now well established as a critical locus for the generation of conspecific aggression, its role is complex, with populations of neurons responding during the motivational, sensory, and action phases of aggression, and also during social interactions with the opposite sex. It has been previously unclear how the brain uses this complex multidimensional signal and generates a discrete action: the attack. Here we find that the largest posterior target of the VMHvl, the lateral periaqueductal gray (lPAG) encodes a simplified attack-selective signal during aggression. Single units in the lPAG exhibit greater selectivity for the attack action during aggression than VMHvl neurons and a subpopulation of neurons in the PAG exhibit short-latency, time-locked spiking relative to the activity of jaw muscles for biting during attack. In addition, channelrhodopsin assisted circuit mapping reveals a preferential projection from VMHvl glutamatergic cells to lPAG glutamatergic cells. Using projection-specific fiber photometry, we find that this excitatory projection conveys male-biased signals from the VMHvl to downstream glutamatergic PAG neurons that integrate ongoing male-related activity over several seconds, which suggests that action-selectivity is generated by a combination of both pre and postsynaptic filtering mechanisms.

neuroscience↗

bioRxiv2019

Single-cell profiles of retinal neurons differing in resilience to injury reveal neuroprotective genes

Neuronal types in the central nervous system differ dramatically in their resilience to injury or insults. Here we studied the selective resilience of mouse retinal ganglion cells (RGCs) following optic nerve crush (ONC), which severs their axons and leads to death of ~80% of RGCs within 2 weeks. To identify expression programs associated with differential resilience, we first used single-cell RNA-seq (scRNA-seq) to generate a comprehensive molecular atlas of 46 RGC types in adult retina. We then tracked their survival after ONC, characterized transcriptomic, physiological, and morphological changes that preceded degeneration, and identified genes selectively expressed by each type. Finally, using loss- and gain-of-function assays in vivo, we showed that manipulating some of these genes improved neuronal survival and axon regeneration following ONC. This study provides a systematic framework for parsing type-specific responses to injury, and demonstrates that differential gene expression can be used to reveal molecular targets for intervention.

neuroscience↗

bioRxiv2019

CoolBox: a interactive genomic data explorer for Jupyter Notebook

SummaryCoolBox is a Python package for interactive genomic data exploration based on Jupyter notebook. It provides a ggplot2-like Application Programming Interface (API) for genomic data visualization, and a Jupyter/ipywidgets based Graphical User Interface (GUI) for interactive data exploration. CoolBox is a versatile multi-omics explorer supporting most types of data formats generated by various sequencing technologies like RNA-Seq, ChIP-Seq, ChIA-PET and Hi-C.\n\nAvailability and implementationCoolBox is purely implemented with Python, and the GUI widget in Jupyter notebook is based on the ipywidgets package. It is open-source and available under GPLv3 license at https://github.com/GangCaoLab/CoolBox.

bioinformatics↗

bioRxiv2019

Parallel Group ICA + ICA: Joint Estimation of Linked Functional Network Variability and Structural Covariation with Application to Schizophrenia

There is growing evidence that rather than using a single brain imaging modality to study its association with physiological or symptomatic features, the field is paying more attention to fusion of multimodal information. However, most current multimodal fusion approaches that incorporate functional magnetic resonance imaging (fMRI) are restricted to second-level 3D features, rather than the original 4D fMRI data. This trade-off is that the valuable temporal information is not utilized during the fusion step. Here we are motivated to propose a novel approach called \"parallel group ICA+ICA\" that incorporates temporal fMRI information from GICA into a parallel ICA framework, aiming to enable direct fusion of first-level fMRI features with other modalities (e.g. structural MRI), which thus can detect linked functional network variability and structural covariations. Simulation results show that the proposed method yields accurate inter-modality linkage detection regardless of whether it is strong or weak. When applied to real data, we identified one pair of significantly associated fMRI-sMRI components that show group difference between schizophrenia and controls in both modalities. Finally, multiple cognitive domain scores can be predicted by the features identified in the linked component pair by our proposed method. We also show these multimodal brain features can predict multiple cognitive scores in an independent cohort. Overall, results demonstrate the ability of parallel GICA+ICA to estimate joint information from 4D and 3D data without discarding much of the available information up front, and the potential for using this approach to identify imaging biomarkers to study brain disorders.

bioinformatics↗

bioRxiv2019

SPARSE INFOMAX BASED ON HOYER PROJECTION AND ITS APPLICATION TO SIMULATED STRUCTURAL MRI AND SNP DATA

Independent component analysis has been widely applied to brain imaging and genetic data analyses for its ability to identify interpretable latent sources. Nevertheless, leveraging source sparsity in a more granular way may further improve its ability to optimize the solution for certain data types. For this purpose, we propose a sparse infomax algorithm based on nonlinear Hoyer projection, leveraging both sparsity and statistical independence of latent sources. The proposed algorithm iteratively updates the unmixing matrix by infomax (for independence) and the sources by Hoyer projection (for sparsity), feeding the sparse sources back as input data for the next iteration. Consequently, sparseness propagates effectively through infomax iterations, producing sources with more desirable properties. Simulation results on both brain imaging and genetic data demonstrate that the proposed algorithm yields improved pattern recovery, particularly under low signal-to-noise ratio conditions, as well as improved sparseness compared to traditional infomax.

bioengineering↗

bioRxiv2018

Network modules linking expression and methylation in prefrontal cortex of schizophrenia

Tremendous work has demonstrated the critical roles of genetics, epigenetics as well as their interplay in brain transcriptional regulations in the pathology of schizophrenia (SCZ). There is great success currently in the dissection of the genetic components underlying risk-conferring transcriptomic networks. However, the study of regulating effect of epigenetics, as a modulator of environmental factors, in the etiopathogenesis of SCZ still faces many challenges. In this work we investigated DNA methylation and gene expression from the dorsolateral prefrontal cortex (DLPFC) region of schizophrenia patients and healthy controls using weighted correlation network approaches. We identified and replicated two expression and two methylation modules significantly associated with SCZ. Among them, one pair of expression and methylation modules were significantly overlapped in the module genes which were enriched in astrocyte-associated functional pathways, and specifically expressed in astrocytes. Another two linked expression-methylation module pairs were involved aging process with module genes mostly related to oligodendrocyte development and myelination, and specially expressed in oligodendrocytes. Further examination of underlying quantitative trait loci (QTLs) showed significant enrichment in genetic risk of most psychiatric disorders for expression QTLs but not for methylation QTLs. These results support the coherence between methylation and gene expression in a network level, and suggest a combinatorial effect of genetics and epigenetics in regulating gene expression networks specific to glia cells in relation with SCZ and aging process.

neuroscience↗

bioRxiv2018

A genetically encoded fluorescent sensor for rapid and specific in vivo detection ofnorepinephrine

Norepinephrine (NE) and epinephrine (Epi), two key biogenic monoamine neurotransmitters, are involved in a wide range of physiological processes. However, their precise dynamics and regulation remain poorly characterized, in part due to limitations of available techniques for measuring these molecules in vivo. Here, we developed a family of GPCR Activation-Based NE/Epi (GRABNE) sensors with a 230% peak {Delta}F/F0 response to NE, good photostability, nanomolar-to-micromolar sensitivities, sub-second rapid kinetics, high specificity to NE vs. dopamine. Viral- or transgenic- mediated expression of GRABNE sensors were able to detect electrical-stimulation evoked NE release in the locus coeruleus (LC) of mouse brain slices, looming-evoked NE release in the midbrain of live zebrafish, as well as optogenetically and behaviorally triggered NE release in the LC and hypothalamus of freely moving mice. Thus, GRABNE sensors are a robust tool for rapid and specific monitoring of in vivo NE/Epi transmission in both physiological and pathological processes.

neuroscience↗

bioRxiv2018

Correlation between the oral microbiome and brain resting state connectivity in smokers

Recent studies have shown a critical role of the gastrointestinal microbiome in brain and behavior via the complex gut-microbiome-brain axis, however, the influence of the oral microbiome in neurological processes is much less studied, especially in response to the stimuli in the oral microenvironment such as smoking. Additionally, given the complex structural and functional networks in brain system, our knowledge about the relationship between microbiome and brain function in specific brain circuits is still very limited. In this pilot work, we leveraged next generation microbial sequencing with functional neuroimaging techniques to enable the delineation of microbiome-brain network links as well as their relationship to cigarette smoking. Thirty smokers and 30 age- and sex- matched non-smokers were recruited for measuring both microbial community and brain functional networks. Statistical analyses were performed to demonstrate the influence of smoking on the abundance of the constituents within the oral microbial community and functional network connectivity among brain regions as well as the associations between microbial shifts and the brain functional network connectivity alternations. Compared to non-smokers, we found a significant decrease in beta diversity (p = 6x10-3) in smokers and identified several classes (Betaproteobacteria, Spirochaetia, Synergistia, and Mollicutes) as having significant alterations in microbial abundance. Taxonomic analyses demonstrate that the microbiota with altered abundance are mainly involved in pathways related to cell processes, DNA repair, immune system, and neurotransmitters signaling. One brain functional network connectivity component was identified to have a significant difference between smokers and nonsmokers (p = 0.033), mainly including connectivity between brain default network and other task-positive networks. The brain functional component was also significantly associated with some smoking related oral microbiota, suggesting a potential link between smoking-induced oral microbiome dysbiosis and brain functional connectivity, possibly through immunological and neurotransmitter signaling pathways. This work is the first attempt to link oral microbiome and brain functional networks, and provides support for future work in characterizing the role of oral microbiome in mediating smoking effects on brain activity.

microbiology↗