Biology subjects

Shen, M.

Publications and source records attributed to Shen, M..

At least 73 records · Page 4Linked to original sources

bioRxiv2022

Single-cell Transcriptomic Analysis of Systemic Autoinflammatory Diseases with Anti-TNFα Therapy

Systemic autoinflammatory diseases (SAIDs) are a group of rare diseases characterized by recurrent or continuous inflammation, typically accompanied by genetic variants. Good responses to anti-TNF therapy were observed in SAIDs patients. However, the mechanisms underlying the disease flare and the response to TNF blocking therapy have not been fully elucidated. Here, we use single-cell RNA sequencing technology to describe the transcriptomic profile of PBMCs and PMNs in SAIDs patients both before and after anti-TNF treatment. We found that interferon responses are involved in the active phase of the disease. After anti-TNF therapy, we observed remission from clinical symptoms while unexpected elevation of TNF and IL-1, indicating that these inflammatory cytokines are not positively correlated with disease activity. Trajectory analysis showed that inhibition of macrophage differentiation, rather than reduction of the inflammatory cytokines, as the potential mechanism of anti-TNF treatment response in SAIDs.

immunology↗

bioRxiv2022

DEED: A Dataset for Dream-related Emotion Research

Emotion is closely related to human cognition and behaviour. In recent years, scholars have conducted extensive research on emotion in waking state based on electroencephalography (EEG) and achieved certain results. However, Emotional activity continues after sleep, with a concentrated response of sleep emotions in dreams. Sleep emotions are concentrated in dreams, which can better reflect a series of real physical and psychological states of the human body. Currently, there is no publicly available dataset for the assessment of dream mood. Therefore, we present a physiological dataset Dream Emotion Evaluation Dataset (DEED) for the assessment of dream mood, which recorded EEG signals from 38 participants over 89 whole sleep nights and 533 dream segments(after exclusion of unqualified nights, those dream segments are extracted from 82 whole sleep nights). We studied the correlations between the subjective ratings and the EEG signals and brain network patterns for dream emotions. In addition, the relationship between the asymmetry of left and right brain bands and positive and negative dream emotions was studied. The machine learning algorithm was also used to classify different emotional EEG, which confirmed the validity of the dataset. In the meantime, we encourage other researchers to explore the underlying neural mechanisms involved in sleep.

neuroscience↗

bioRxiv2022

Micropatterned Organoids Enable Modeling of the Earliest Stages of Human Cardiac Vascularization

Although model organisms have provided insight into the earliest stages of cardiac vascularization, we know very little about this process in humans. Here we show that spatially micropatterned human pluripotent stem cells (hPSCs) enable in vitro modeling of this process, corresponding to the first three weeks of in vivo human development. Using four hPSC fluorescent reporter lines, we create cardiac vascular organoids (cVOs) by identifying conditions that simultaneously give rise to spatially organized and branched vascular networks within endocardial, myocardial, and epicardial cells. Using single-cell transcriptomics, we show that the cellular composition of cVOs resembles that of a 6.5 post-conception week (PCW) human heart. We find that NOTCH and BMP pathways are upregulated in cVOs, and their inhibition disrupts vascularization. Finally, using the same vascular-inducing factors to create cVOs, we produce hepatic vascular organoids (hVOs). This suggests there is a conserved developmental program for creating vasculature within different organ systems. Graphic Abstract O_FIG O_LINKSMALLFIG WIDTH=159 HEIGHT=200 SRC="FIGDIR/small/499233v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@17b265org.highwire.dtl.DTLVardef@1c1113eorg.highwire.dtl.DTLVardef@531c18org.highwire.dtl.DTLVardef@596bd2_HPS_FORMAT_FIGEXP M_FIG C_FIG

developmental biology↗

bioRxiv2022

Integrative single-cell analysis of cardiogenesis identifies developmental trajectories and non-coding mutations in congenital heart disease

Congenital heart defects, the most common birth disorders, are the clinical manifestation of anomalies in fetal heart development - a complex process involving dynamic spatiotemporal coordination among various precursor cell lineages. This complexity underlies the incomplete understanding of the genetic architecture of congenital heart diseases (CHDs). To define the multi-cellular epigenomic and transcriptional landscape of cardiac cellular development, we generated single-cell chromatin accessibility maps of human fetal heart tissues. We identified eight major differentiation trajectories involving primary cardiac cell types, each associated with dynamic transcription factor (TF) activity signatures. We identified similarities and differences of regulatory landscapes of iPSC-derived cardiac cell types and their in vivo counterparts. We interpreted deep learning models that predict cell-type resolved, base-resolution chromatin accessibility profiles from DNA sequence to decipher underlying TF motif lexicons and infer the regulatory impact of non-coding variants. De novo mutations predicted to affect chromatin accessibility in arterial endothelium were enriched in CHD cases versus controls. We used CRISPR-based perturbations to validate an enhancer harboring a nominated regulatory CHD mutation, linking it to effects on the expression of a known CHD gene JARID2. Together, this work defines the cell-type resolved cis-regulatory sequence determinants of heart development and identifies disruption of cell type-specific regulatory elements as a component of the genetic etiology of CHD.

genomics↗

bioRxiv2022

A cocktail containing two synergetic antibodies broadly neutralizes SARS-CoV-2 and its variants including Omicron BA.1 and BA.2

Neutralizing antibodies (NAbs) can prevent and treat infections caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, continuously emerging variants, such as Omicron, have significantly reduced the potency of most known NAbs. The selection of NAbs with broad neutralizing activities and the identification of conserved critical epitopes are still urgently needed. Here, we identified an extremely potent antibody (55A8) by single B-cell sorting from convalescent SARS-CoV-2-infected patients that recognized the receptor-binding domain (RBD) in the SARS-CoV-2 spike (S) protein. 55A8 could bind to wild-type SARS-CoV-2, Omicron BA.1 and Omicron BA.2 simultaneously with 58G6, a NAb previously identified by our group. Importantly, an antibody cocktail containing 55A8 and 58G6 (2-cocktail) showed synergetic neutralizing activity with a half-maximal inhibitory concentration (IC50) in the picomolar range in vitro and prophylactic efficacy in hamsters challenged with Omicron (BA.1) through intranasal delivery at an extraordinarily low dosage (25 g of each antibody daily) at 3 days post-infection. Structural analysis by cryo-electron microscopy (cryo-EM) revealed that 55A8 is a Class III NAb that recognizes a highly conserved epitope. It could block angiotensin-converting enzyme 2 (ACE2) binding to the RBD in the S protein trimer via steric hindrance. The epitopes in the RBD recognized by 55A8 and 58G6 were found to be different and complementary, which could explain the synergetic mechanism of these two NAbs. Our findings not only provide a potential antibody cocktail for clinical use against infection with current SARS-CoV-2 strains and future variants but also identify critical epitope information for the development of better antiviral agents.

immunology↗

bioRxiv2022

Target Class Profiling of Small Molecule Methyltransferases

Target class profiling (TCP) is a chemical biology approach to investigating understudied biological target classes. TCP is achieved by developing a generalizable assay platform and screening curated compound libraries to interrogate the chemical biological space of members of an enzyme family with clinical and biological importance. In this work we took a TCP approach to investigate inhibitory activity across a set of small molecule methyltransferases, a subclass of methyltransferase enzymes, with the goal of creating a launchpad to explore this largely understudied target class. Using the representative enzymes nicotinamide N-methyltransferase (NNMT), phenylethanolamine N-methyltransferase (PNMT), histamine N-methyltransferase (HNMT), glycine N-methyltransferase (GNMT), catechol O-methyltransferase (COMT), and guanidinoacetate N-methyltransferase (GAMT), we optimized high-throughput screening (HTS)-amenable assays to screen 27,574 unique small molecules against all targets. From this dataset we identified a novel inhibitor which selectively inhibits the small molecule methyltransferase HNMT, and demonstrated how this platform approach can be leveraged for a targeted drug discovery campaign using the example of HNMT.

biochemistry↗

bioRxiv2022

A Suite of TMPRSS2 Assays for Screening Drug Repurposing Candidates as Potential Treatments of COVID-19

SARS-CoV-2 is the causative viral pathogen driving the COVID-19 pandemic that prompted an immediate global response to the development of vaccines and antiviral therapeutics. For antiviral therapeutics, drug repurposing allowed for rapid movement of existing clinical candidates and therapies into human clinical trials to be tested as COVID-19 therapies. One effective antiviral treatment strategy used early in symptom onset is to prevent viral entry. SARS-CoV-2 enters ACE2-expressing cells when the receptor-binding domain of the spike protein on the surface of SARS-CoV-2 binds to ACE2 followed by cleavage at two cut sites on the spike protein. TMPRSS2 has a protease domain capable of cleaving the two cut sites; therefore, a molecule capable of inhibiting the protease activity of TMPRSS2 could be a valuable antiviral therapy. Initially, we used a fluorogenic high-throughput screening assay for the biochemical screening of 6030 compounds in NCATS annotated libraries. Then, we developed an orthogonal biochemical assay that uses mass spectrometry detection of product formation to ensure that hits from the primary screen are not assay artifacts from the fluorescent detection of product formation. Finally, we assessed the hits from the biochemical screening in a cell-based SARS-CoV-2 pseudotyped particle entry assay. Of the six molecules advanced for further studies, two are approved drugs in Japan (camostat and nafamostat), two have entered clinical trials (PCI-27483 and otamixaban), while the other two molecules are peptidomimetic inhibitors of TMPRSS2 taken from the literature that have not advanced into clinical trials (compounds 92 and 114). This work demonstrates a suite of assays for the discovery and development of new inhibitors of TMPRSS2.

biochemistry↗

bioRxiv2021

Discovery of lipid-mediated protein-protein interactions in living cells using metabolic labeling with photoactivatable clickable probes

Protein-protein interactions (PPIs) are essential and pervasive regulatory elements in cell biology. Despite development of a range of techniques to probe PPIs in living systems, there is a dearth of approaches to capture interactions driven by specific post-translational modifications (PTMs). Myristoylation is a lipid PTM added to more than 200 human proteins, where it may regulate membrane localization, stability or activity. Here we report design and synthesis of a panel of novel photocrosslinkable and clickable myristic acid analog probes, and their characterization as efficient substrates for human N-myristoyltransferases NMT1 and NMT2, both biochemically and through X-ray co-crystallography. We demonstrate metabolic incorporation of probes to label NMT substrates in cell culture and in situ intracellular photoactivation to form a covalent crosslink between modified proteins and their interactors, capturing a snapshot of interactions driven by the presence of the lipid PTM. Proteomic analyses revealed both known and multiple novel interactors of a series of myristoylated proteins, including ferroptosis suppressor protein FSP1 and spliceosome-associated RNA helicase DDX46. The concept exemplified by these probes offers an efficient approach for exploring the PTM-specific interactome, which may prove broadly applicable to other PTMs.

biochemistry↗

bioRxiv2021

A Graph Convolutional Network-based screening strategy for rapid identification of SARS-CoV-2 cell-entry inhibitors

The cell entry of SARS-CoV-2 has emerged as an attractive drug development target. We previously reported that the entry of SARS-CoV-2 depends on the cell surface heparan sulfate proteoglycan (HSPG) and the cortex actin, which can be targeted by therapeutic agents identified by conventional drug repurposing screens. However, this drug identification strategy requires laborious library screening, which is time-consuming and often limited number of compounds can be screened. As an alternative approach, we developed and trained a graph convolutional network (GCN)-based classification model using information extracted from experimentally identified HSPG and actin inhibitors. This method allowed us to virtually screen 170,000 compounds, resulting in [~]2000 potential hits. A hit confirmation assay with the uptake of a fluorescently labeled HSPG cargo further shortlisted 256 active compounds. Among them, 16 compounds had modest to strong inhibitory activities against the entry of SARS-CoV-2 pseudotyped particles into Vero E6 cells. These results establish a GCN-based virtual screen workflow for rapid identification of new small molecule inhibitors against validated drug targets. Graphical TOC Entry O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC="FIGDIR/small/471787v1_ufig1.gif" ALT="Figure 1"> View larger version (16K): org.highwire.dtl.DTLVardef@1632bc4org.highwire.dtl.DTLVardef@1ce912borg.highwire.dtl.DTLVardef@9cdc86org.highwire.dtl.DTLVardef@521712_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2021

A high throughput screening assay for inhibitors of SARS-CoV-2 pseudotyped particle entry

Effective small molecule therapies to combat the SARS-CoV-2 infection are still lacking as the COVID-19 pandemic continues globally. High throughput screening assays are needed for lead discovery and optimization of small molecule SARS-CoV-2 inhibitors. In this work, we have applied viral pseudotyping to establish a cell-based SARS-CoV-2 entry assay. Here, the pseudotyped particles (PP) contain SARS-CoV-2 spike in a membrane enveloping both the murine leukemia virus (MLV) gag-pol polyprotein and luciferase reporter RNA. Upon addition of PP to HEK293-ACE2 cells, the SARS-CoV-2 spike protein binds to the ACE2 receptor on the cell surface, resulting in priming by host proteases to trigger endocytosis of these particles, and membrane fusion between the particle envelope and the cell membrane. The internalized luciferase reporter gene is then expressed in cells, resulting in a luminescent readout as a surrogate for spike-mediated entry into cells. This SARS-CoV-2 PP entry assay can be executed in a biosafety level 2 containment lab for high throughput screening. From a collection of 5,158 approved drugs and drug candidates, our screening efforts identified 7 active compounds that inhibited the SARS-CoV-2-S PP entry. Of these seven, six compounds were active against live replicating SARS-CoV-2 virus in a cytopathic effect assay. Our results demonstrated the utility of this assay in the discovery and development of SARS-CoV-2 entry inhibitors as well as the mechanistic study of anti-SARS-CoV-2 compounds. Additionally, particles pseudotyped with spike proteins from SARS-CoV-2 B.1.1.7 and B.1.351 variants were prepared and used to evaluate the therapeutic effects of viral entry inhibitors.

pharmacology and toxicology↗

bioRxiv2021

Determining molecular archetype composition and expression from bulk tissues with unsupervised deconvolution

Complex tissues are composite ecological systems whose components interact with each other to create a unique physiological or pathophysiological state distinct from that found in other tissue microenvironments. To explore this ground yet dynamic state, molecular profiling of bulk tissues and mathematical deconvolution can be jointly used to characterize heterogeneity as an aggregate of molecularly distinct tissue or cell subtypes. We first introduce an efficient and fully unsupervised deconvolution method, namely the Convex Analysis of Mixtures - CAM3.0, that may aid biologists to confirm existing or generate novel scientific hypotheses about complex tissues in many biomedical contexts. We then evaluate the CAM3.0 functional pipelines using both simulations and benchmark data. We also report diverse case studies on bulk tissues with unknown number, proportion and expression patterns of the molecular archetypes. Importantly, these preliminary results support the concept that expression patterns of molecular archetypes often reflect the interactive not individual contributions of many known or novel cell types, and unsupervised deconvolution would be more powerful in uncovering novel multicellular or subcellular archetypes.

bioinformatics↗

bioRxiv2021

A hybrid in silico approach reveals novel inhibitors of multiple SARS-CoV-2 variants

The National Center for Advancing Translational Sciences (NCATS) has been actively generating SARS-CoV-2 high-throughput screening data and disseminates it through the OpenData Portal (https://opendata.ncats.nih.gov/covid19/). Here, we provide a hybrid approach that utilizes NCATS screening data from the SARS-CoV-2 cytophatic effect reduction assay to build predictive models, using both machine learning and pharmacophore-based modeling. Optimized models were used to perform two iterative rounds of virtual screening to predict small molecules active against SARS-CoV-2. Experimental testing with live virus provided 100 (~16% of predicted hits) active compounds (Efficacy > 30%, IC50 [≤] 15 M). Systematic clustering analysis of active compounds revealed three promising chemotypes which have not been previously identified as inhibitors of SARS-CoV-2 infection. Further analysis identified allosteric binders to host receptor angiotensin-converting enzyme 2, which were able to inhibit the entry of pseudoparticles bearing spike protein of wild type SARS-CoV-2 as well as South African B.1.351 and UK B.1.1.7 variants.

cell biology↗

bioRxiv2021

Ultrapotent SARS-CoV-2 neutralizing antibodies with protective efficacy against newly emerged mutational variants

Accumulating mutations in the SARS-CoV-2 Spike (S) protein can increase the possibility of immune escape, challenging the present COVID-19 prophylaxis and clinical interventions. Here, 3 receptor binding domain (RBD) specific monoclonal antibodies (mAbs), 58G6, 510A5 and 13G9, with high neutralizing potency blocking authentic SARS-CoV-2 virus displayed remarkable efficacy against authentic B.1.351 virus. Each of these 3 mAbs in combination with one neutralizing Ab recognizing non-competing epitope exhibited synergistic effect against authentic SARS-CoV-2 virus. Surprisingly, structural analysis revealed that 58G6 and 13G9, encoded by the IGHV1-58 and the IGKV3-20 germline genes, both recognized the steric region S470-495 on the RBD, overlapping the E484K mutation presented in B.1.351. Also, 58G6 directly bound to another region S450-458 in the RBD. Significantly, 58G6 and 510A5 both demonstrated prophylactic efficacy against authentic SARS-CoV-2 and B.1.351 viruses in the transgenic mice expressing human ACE2 (hACE2), protecting weight loss and reducing virus loads. These 2 ultrapotent neutralizing Abs can be promising candidates to fulfill the urgent needs for the prolonged COVID-19 pandemic.

immunology↗

bioRxiv2021

Maintenance of Bound or Independent Features in Visual Working Memory is Task-dependent

Over the last decade, seemingly conflicting results were obtained regarding the question of whether features of an object are stored separately, or bound together, in visual working memory. Many of these studies are based on an implicit assumption about a default, or fixed, mode of working memory storage. In contrast, here we asked whether the anticipated memory probes used in a given experiment might determine the format in which information is maintained in working memory, consistent with its task-oriented function. In order to test this flexible maintenance hypothesis, we recorded EEG while subjects performed a delayed-match-to-sample task with different requirements and load. In Experiment 1, by contrasting conditions with and without the requirement of maintaining bound features, we found significant differences in EEG signals recorded in central-parietal channels while controlling for differences in visual stimulation. Such difference was confirmed by multivariate pattern analysis (MVPA). Moreover, behavior results, topographical distributions and cross-contrast MVPA decoding jointly suggested that this effect is not the same as task load effect. These results were confirmed in Experiment 2 with an independent group of subjects with the same paradigm, providing reliable evidence that the format of object maintenance in visual working memory could be flexibly shaped by the current task.

neuroscience↗

bioRxiv2021

Characterization and tissue localization of zebrafish homologs of the human ABCB1 multidrug transporter

Given its similarities with mammalian systems, the zebrafish has emerged as a potential model to study the blood-brain barrier (BBB). Capillary endothelial cells at the human BBB express high levels of P-glycoprotein (P-gp, encoded by the ABCB1 gene) and ABCG2 (encoded by the ABCG2 gene). However, little information has been available about ATP-binding cassette transporters expressed at the zebrafish BBB. In this study, we focus on the characterization and tissue localization of two genes that are similar to human ABCB1, zebrafish abcb4 and abcb5. Cytotoxicity assays with stably-transfected cell lines revealed that zebrafish Abcb5 cannot efficiently transport the substrates doxorubicin and mitoxantrone compared to human P-gp and zebrafish Abcb4. Additionally, zebrafish Abcb5 did not transport the fluorescent probes BODIPY-ethylenediamine or LDS 751, while they were readily transported by Abcb4 and P-gp. A high-throughput screen conducted with 90 human P-gp substrates confirmed that zebrafish Abcb4 has overlapping substrate specificity with P-gp. Basal ATPase activity of zebrafish Abcb4 and Abcb5 was comparable to that of human P-gp. In the brain vasculature, RNAscope probes to detect abcb4 colocalized with staining by the P-gp antibody C219, while abcb5 was not detected. Zebrafish abcb4 also colocalized with claudin-5 expression in brain endothelial cells. Abcb4 and Abcb5 had different tissue localizations in multiple zebrafish tissues, consistent with different functions. The data suggest that zebrafish Abcb4 most closely phenocopies P-gp and that the zebrafish may be a viable model to study the role of the multidrug transporter P-gp at the BBB.

pharmacology and toxicology↗

bioRxiv2021

Prediction of occult tumor progression via platelet RNAs in a mouse melanoma model: a potential new platform of cancer screening for early detection of cancer

Cancer screening provides the opportunity to detect cancer early, ideally before symptom onset and metastasis, and offers an increased opportunity for a better prognosis. The ideal biomarkers for cancer screening should discriminate individuals who have not developed invasive cancer yet but are destined to do so from healthy subjects1,2. However, most cancers lack effective screening recommendations. Therefore, further studies on novel screening strategies are urgently required. Here, our proof-of-concept study shows blood platelets could be a platform for liquid biopsy-based early cancer detection. By using a simple suboptimal inoculation melanoma mouse model, we identified differentially expressed RNAs in platelet signatures of mice injected with a suboptimal number of cancer cells (eDEGs) compared with mice with macroscopic melanomas and negative controls. These RNAs were strongly enriched in pathways related to immune response and regulation. Moreover, 36 genes selected from the eDEGs via bioinformatics analyses were verified in a mouse validation cohort via quantitative real-time PCR. LASSO regression was employed to generate the prediction models with gene expression signatures as the best predictors for occult tumor progression in mice. The prediction models showed great diagnostic efficacy and predictive value in our murine validation cohort, and could discriminate mice with occult tumors from control group (area under curve (AUC) of 0.935 (training data) and 0.912 (testing data)) (gene signature including Cd19, Cdkn1a, S100a9, Tap1, and Tnfrsf1b) and also from macroscopic tumor group (AUC of 0.920 (training data) and 0.936 (testing data)) (gene signature including Ccr7, Cd4, Kmt2d, and Ly6e). Our study provides evidence for potential clinical relevance of blood platelets as a platform for liquid biopsy-based early detection of cancer. Furthermore, the eDEGs are mostly immune-related, not tumor-specific. Hence it is possible platelets-based liquid biopsy could enable simultaneous early detection of cancers from multiple organs of origin3. It is also feasible to determine the origin of cancer since platelet profiles are influenced by tumor type3.

cancer biology↗

bioRxiv2021

Large field of view-spatially resolved transcriptomics at nanoscale resolution

Spatially resolved transcriptomic technologies are promising tools to study cell fate decisions in a physical microenvironment, which is fundamental for enhancing our knowledge of mammalian development. However, the imbalance between resolution, transcript capture and field of view of current methodologies precludes their systematic application to analyze relatively large and three-dimensional mid- and late-gestation mammalian embryos. Here, we combined DNA nanoball (DNB) patterned arrays and tissue RNA capture to create SpaTial Enhanced REsolution Omics-sequencing (Stereo-seq). This approach allows transcriptomic profiling of large histological sections with high resolution and sensitivity. We have applied Stereo-seq to study the kinetics and directionality of transcriptional variation in a time course of mouse organogenesis. We used this information to gain insight into the molecular basis of regional specification, neuronal migration and differentiation in the developing brain. Furthermore, we mapped the expression of a panel of developmental disease-related loci on our global transcriptomic maps to define the spatiotemporal windows of tissue vulnerability. Our panoramic atlas constitutes an essential resource to investigate longstanding questions concerning normal and abnormal mammalian development.

cell biology↗

bioRxiv2020

Non-covalent TMPRSS2 inhibitors identified from virtual screening

The SARS-CoV-2 pandemic has prompted researchers to pivot their efforts to finding antiviral compounds and vaccines. In this study, we focused on the human host cell transmembrane protease serine 2 (TMPRSS2), which plays an important role in the viral life cycle by cleaving the spike protein to initiate membrane fusion. TMPRSS2 is an attractive target and has received attention for the development of drugs against SARS and MERS. Starting with comparative structural modeling and binding model analysis, we developed an efficient pharmacophore-based approach and applied a large-scale in silico database screening for small molecule inhibitors against TMPRSS2. The hits were evaluated in the TMPRSS2 biochemical assay and the SARS-CoV-2 pseudotyped particle (PP) entry assay. A number of novel inhibitors were identified, providing starting points for further development of drug candidates for the treatment of COVID-19.

bioinformatics↗