Biology subjects

Wu, D.

Publications and source records attributed to Wu, D..

At least 253 records · Page 14Linked to original sources

bioRxiv2021

Small-molecule cocktails induce the differentiation of human adipose-derived mesenchymal stem cells into hepatocyte-like cells

At present, liver transplantation and hepatocyte therapy are common methods for the treatment of end-stage liver diseases, but they are restricted due to the shortage of liver donors and the safety and effectiveness of hepatocyte sources. Human adipose-derived mesenchymal stem cells (HAD-MSCs) have been applied to efficiently and stably induce phenotypic and functional liver cells or tissues in vitro due to their advantages such as wide sources and easy access to materials. In this study, the HAD-MSCs liver differentiation induction system was established and optimized based on the "cocktail method" of chemical small molecule compounds. We used HAD-MSCs as seed cells and gradually obtained mature hepatoid cells with normal phenotype and function after induction with small molecule compounds and growth factor system in vitro. The hepatoid cells induced by the two groups showed high similarity in phenotype and functional characteristics of mature hepatocytes. The differentiation system of human adipose mesenchymal stem cells into hepatocytes induced by small-molecule compounds in vitro was successfully constructed. This study will lay a foundation for the optimization of liver differentiation strategies and provide a reliable source of functional liver cells for clinical studies of liver diseases.

cell biology↗

bioRxiv2021

Distribution-based comprehensive evaluation ofmethods for differential expression analysis inmetatranscriptomics

Understanding the function of the human microbiome is important; however, the development of statistical methods specifically for the microbial gene expression (i.e., metatranscriptomics) is in its infancy. Many currently employed differential expression analysis methods have been designed for different data types and have not been evaluated in metatranscriptomics settings. To address this gap, we undertook a comprehensive evaluation and benchmarking of ten differential analysis methods for metatranscriptomics data. We used a combination of real and simulated data to evaluate performance (i.e., model fit, type I error, false discovery rate, and sensitivity) of the methods: log-normal (LN), logistic-beta (LB), MAST, DESeq2, metagenomeSeq, ANCOM-BC, LEfSe, ALDEx2, Kruskal-Wallis, and two-part Kruskal-Wallis. The simulation was informed by supragingival biofilm microbiome data from 300 preschool-age children enrolled in a study of early childhood caries (ECC), whereas validations were sought in two additional datasets from an ECC study and an inflammatory bowel disease (IBD) study. The LB test showed the highest sensitivity in both small and large samples and reasonably controlled type I error. Contrarily, MAST was hampered by inflated type I error. Upon application of the LN and LB tests in the ECC study, we found that genes C8PHV7 and C8PEV7, harbored by the lactate-producing Campylobacter gracilis, had the strongest association with childhood dental diseases. This comprehensive model evaluation offer practical guidance for selection of appropriate methods for rigorous analyses of differential expression in metatranscriptomics. Selection of an optimal method increases the possibility of detecting true signals while minimizing the chance of claiming false ones.

bioinformatics↗

bioRxiv2021

Improved Metabolite Prediction Using Microbiome Data-Based Elastic Net Models

Microbiome data are becoming increasingly available in large health cohorts yet metabolomics data are still scant. While many studies generate microbiome data, they lack matched metabolomics data or have considerable missing proportions of metabolites. Since metabolomics is key to understanding microbial and general biological activities, the possibility of imputing individual metabolites or inferring metabolomics pathways from microbial taxonomy or metagenomics is intriguing. Importantly, current metabolomics profiling methods such as the HMP Unified Metabolic Analysis Network (HUMAnN) have unknown accuracy and are limited in their ability to predict individual metabolites. To address this gap, we developed a novel metabolite prediction method, and we present its application and evaluation in an oral microbiome study. We developed ENVIM based on the Elastic Net Model (ENM) to predict metabolites using micorbiome data. ENVIM introduces an extra step to ENM to consider variable importance scores and thus achieve better prediction power. We investigate the metabolite prediction performance of ENVIM using metagenomic and metatranscriptomic data in a supragingival biofilm multi-omics dataset of 297 children ages 3-5 who were participants of a community-based study of early childhood oral health (ZOE 2.0) in North Carolina, United States. We further validate ENVIM in two additional publicly available multi-omics datasets generated from studies of gut health and vagina health. We select gene-family sets based on variable importance scores and modify the existing ENM strategy used in the MelonnPan prediction software to accommodate the unique features of microbiome and metabolome data. We evaluate metagenomic and metatranscriptomic predictors and compare the prediction performance of ENVIM to the standard ENM employed in MelonnPan. The newly-developed ENVIM method showed superior metabolite predictive accuracy than MelonnPan using metatranscriptomics data only, metagenomics data only, or both of these two. Both methods perform better prediction using gut or vagina microbiome data than using oral microbiome data for the samples corresponding metabolites. The top predictable compounds have been reported in all these three datasets from three different body sites. Enrichment of prediction some contributing species has been detected.

microbiology↗

bioRxiv2021

Ultrafast amplitude modulation for molecular and hemodynamic ultrasound imaging

Ultrasound is playing an emerging role in molecular and cellular imaging thanks to new micro- and nanoscale contrast agents and reporter genes. Acoustic methods for the selective in vivo detection of these imaging agents are needed to maximize their impact in biology and medicine. Existing ultrasound pulse sequences use the nonlinearity in contrast agents response to acoustic pressure to distinguish them from mostly linear tissue scattering. However, such pulse sequences typically scan the sample using focused transmissions, resulting in a limited frame rate and restricted field of view. Meanwhile, existing wide-field scanning techniques based on plane wave transmissions suffer from limited sensitivity or nonlinear artifacts. To overcome these limitations, we introduce an ultrafast nonlinear imaging modality combining amplitude-modulated pulses, multiplane wave transmissions and selective coherent compounding. This technique achieves contrast imaging sensitivity comparable to much slower gold-standard amplitude modulation sequences and enables the acquisition of larger and deeper fields of view, while providing a much faster imaging framerate of 3.2kHz. Additionally, it enables simultaneous nonlinear and linear image formation, and allows concurrent monitoring of phenomena accessible only at ultrafast framerates, such as blood volume variations. We demonstrate the performance of this ultrafast amplitude modulation (uAM) technique by imaging gas vesicles, an emerging class of genetically encodable biomolecular contrast agents, in several in vitro and in vivo contexts. These demonstrations include the rapid discrimination of moving contrast agents and the real-time monitoring of phagolysosomal function in the mouse liver.

bioengineering↗

bioRxiv2021

Sex differences in microRNA expression in first and third trimester human placenta

Maternal and fetal pregnancy outcomes related to placental function vary based on fetal sex, which may be the result of sexually dimorphic epigenetic regulation of RNA expression. We identified sexually dimorphic miRNA expression throughout gestation in human placentae. Next-generation sequencing was used to identify miRNA expression profiles in first and third trimester uncomplicated pregnancies using tissue obtained at chorionic villous sampling (n=113) and parturition (n=47). Sequencing and differential expression (DE) analysis identified 432 mature miRNAs expressed in the first trimester female, 425 in the first trimester male, 400 in the third trimester female, and 508 in the third trimester male placenta (baseMean >10). Of these, 11 sexually dimorphic (FDR<0.05, baseMean >10) miRNAs were identified in the first and 4 miRNAs were identified in the third trimester, including miR-361-5p, significant in both trimesters, all upregulated in females. Across gestation, 207 miRNAs were DE across gestation, common to both females and males, miR-4483, the most DE across gestation. There were twice as many female-specific differences across gestation as male-specific (44 miRNAs vs 21 miRNAs), indicating that miRNA abundance across human gestation is sexually dimorphic. Pathway enrichment analysis identified significant pathways that were differentially regulated in first and third trimester as well as across gestation. This work provides the normative sex dimorphic miRNA atlas in first and third trimester, as well as the sex independent and sex specific placenta miRNA atlas across gestation which may be used to identify biomarkers of placental function and direct functional studies investigating placental sex differences. Summary SentenceSex dimorphism in miRNA expression is more pronounced in first compared to third trimester placenta, and there are twice as many female-specific gestational differences, indicating miRNA abundance across human gestation is also sexually dimorphic.

developmental biology↗

bioRxiv2021

The genetic architecture of phenotypic diversity in the betta fish (Betta splendens)

The Betta fish displays a remarkable variety of phenotypes selected during domestication. However, the genetic basis underlying these traits remain largely unexplored. Here, we report a high-quality genome assembly and re-sequencing of 727 individuals representing diverse morphologies of the betta fish. We show that current breeds have a complex domestication history with extensive introgression with wild species. Using GWAS, we identify the genetic basis of multiple traits, including several coloration phenotypes, sex-determination which we map to DMRT1, and the long-fin phenotype which maps to KCNJ15. We identify a polygenic signal related to aggression with many similarities to human psychiatric traits, involving genes such as CACNB2 and DISC1. Our study provides a resource for developing the Betta fish as a genetic model for morphology and behavior in vertebrates.

genetics↗

bioRxiv2021

The Impact of Control Interface on Features of Heart Rate Variability

AO_SCPLOWBSTRACTC_SCPLOWShared human-robot control for assistive machines can improve the independence of individuals with motor impairments. Monitoring elevated levels of workload can enable the assistive autonomy to adjust the control-sharing in an assist-as-needed way, to achieve a balance between user fatigue, stress and independent control. In this work, we aim to investigate how heart-rate variability features can be utilized to monitor elevated levels of mental workload while operating a powered wheelchair, and how that utilization might vary under different control interfaces. To that end, we conducted a 22 person study with three commercial interfaces. Our results show that the validity and reliability of using the ultra-short-term heart-rate variability features as predictors for workload indeed are affected by the type of interface in use.

bioengineering↗

bioRxiv2021

A generalized kinetic model describes ion-permeation mechanisms in various ion channels

Ion channels conduct various ions across biological membranes to maintain the membrane potential, to transmit the electrical signals, and to elicit the subsequent cellular responses by the signaling ions. Ion channels differ in their capabilities to select and conduct ions, which can be studied by the patch-clamp recording method that compares the current traces responding to the test voltage elicited at different conditions. In these experiments, the current-voltage curves are usually fitted by a sigmoidal function containing the Boltzmann factor. This equation is quite successful in fitting the experimental data in many cases, but it also fails in several others. Regretfully, some useful information may be lost in these data, which otherwise can reveal the ion-permeation mechanisms. Here we present a generalized kinetic model that captures the essential features of the current-voltage relations and describes the simple mechanism of the ion permeation through different ion channels. We demonstrate that this model is capable to fit various types of the patch-clamp data and explain their ion-permeation mechanisms.

biophysics↗

bioRxiv2021

Endothelial restoration of CAD GWAS gene PLPP3 by nanomedicine suppresses YAP/TAZ activity and reduces atherosclerosis in vivo

Genome-wide association studies (GWAS) have suggested new molecular mechanisms in vascular cells driving atherosclerotic diseases such as coronary artery disease (CAD) and ischemic stroke (IS). Nevertheless, a major challenge to develop new therapeutic approaches is to spatiotemporally manipulate these GWAS-identified genes in specific vascular tissues in vivo. YAP (Yes-associated protein) and TAZ (transcriptional coactivator with PDZ-binding motif) have merged as critical transcriptional regulators in cells responding to biomechanical stimuli, such as in athero-susceptible endothelial cells activated by disturbed flow (DF). The molecular mechanisms by which DF activates while unidirectional flow (UF) inactivates YAP/TAZ remain incompletely understood. Recent studies demonstrated that DF and genetic predisposition (risk allele) of CAD/IS locus 1p32.2 converge to reduce phospholipid phosphatase 3 (PLPP3) expression in vascular endothelium. Restoration of endothelial PLPP3 in vivo, although remains challenging and unexplored, is hypothesized to reduce atherosclerosis. We devised a nanomedicine system integrating nanoparticles and Cdh5 promoter-driven plasmids to successfully restore PLPP3 expression in activated endothelium, resulting in suppressed YAP/TAZ activity and reduced DF-induced atherosclerosis in mice. Mechanistically, our studies discovered a molecular paradigm by which CAD/IS GWAS gene PLPP3 inactivates YAP/TAZ by reducing lysophosphatidic acid (LPA)-induced myosin II and ROCK in endothelium under UF. These results highlight a new mechanistic link between GWAS and YAP/TAZ mechano-regulation and moreover, establish a proof of concept of vascular wall-based therapies employing targeted nanomedicine to manipulate CAD/IS GWAS genes in vivo.

bioengineering↗

bioRxiv2021

Diverse Hotspot Thermal Profiling Methods Detect Phosphorylation-Dependent Changes in Protein Stability

Hotspot thermal profiling (HTP) methods utilize modified-peptide level information in order to interrogate proteoform-specific stability inside of live cells. The first demonstration of HTP involved the integration of phosphopeptide enrichment into a TMT-based, single-LC separation thermal profiling workflow1. Here we present a new label-fractionate-enrich (LFE)-HTP method that involves high-pH reverse phase fractionation of TMT-labeled peptides prior to phosphopeptide enrichment, followed by peptide detection and quantitation using multi-notch LC-MS3. We find that LFE-HTP, while more resource intensive, improves the depth and precision of (phospho)proteoform coverage relative to the initial published HTP workflow. The fraction of detected phosphorylation sites that are significantly perturbed in this new dataset are consistent with those seen in our previous study, as well as those published by others, when compared head-to-head with the same analysis pipelines. Likewise, many hotspot phosphorylation sites identified in our paper are consistently reproduced by LFE-HTP as well as other modified HTP methods. The LFE-HTP dataset contains many novel hotspot phosphorylation sites that regulate the stability of diverse proteins, including phosphosites in the central glycolytic enzyme Aldolase A that are associated with monomer-to-oligomer formation, enzymatic activity and metabolic regulation in cancer cells. Our comparative analyses confirm that several variants of the HTP method can track modified proteoforms in live cells to detect and prioritize PTM-dependent changes in protein stability that may be associated with function.

biochemistry↗

bioRxiv2021

Decitabine Reactivation of FoxM1-Dependent Endothelial Regeneration and Vascular Repair for Potential Treatment of Elderly ARDS and COVID-19 Patients

Aging is a major risk factor of high incidence and increased mortality of acute respiratory distress syndrome (ARDS) and COVID-19. We repot that aging impairs the intrinsic FoxM1-dependent endothelial regeneration and vascular repair program and causes persistent lung injury and high mortality following sepsis. Therapeutic gene transduction of FOXM1 in vascular endothelium or treatment with FDA-approved drug Decitabine was sufficient to reactivate FoxM1-dependent lung endothelial regeneration in aged mice, reverse aging-impaired resolution of inflammatory injury, and promote survival. In COVID-19 lung autopsy samples, FOXM1 expression was not induced in vascular endothelial cells of elderly patients in contrast to mid-age patients. Thus, Decitabine reactivation of FoxM1-dependent vascular repair represents a potential effective therapy for elderly COVID-19 and non-COVID-19 ARDS patients.

molecular biology↗

bioRxiv2021

Genetic characteristics of human papillomavirus type 16, 18, 52 and 58 in southern China

Persistent infections of high-risk human papillomaviruses (HPVs) are the leading cause of cervical cancers. We collected cervical exfoliated cell samples from females in Changsha city, Hunan Province and obtained 358 viral genomes of four major HPV types, including HPV 16 (n=82), 18 (n=35), 52 (n=121) and 58 (n=100). The lineage/sublineage distribution of the four HPVs confirmed previous epidemiological reports, with the predominant prevailing sublineage as A4 (50%), A1 (37%) and A3 (13%) for HPV16, A1 (83%) for HPV18, B2 (86%) for HPV52 and A1 (65%), A3 (19%) and A2 (12%) for HPV58. We also identified two potentially novel HPV18 sublineages, i.e. A6 and A7. Virus mutation analysis further revealed the presence of HPV16 and HPV58 strains associated with potentially high oncogenicity. These findings expanded our knowledge on the HPV genetic diversity in China, providing valuable evidence to facilitate HPV DNA screening, vaccine effectiveness evaluation and control strategy development.

genomics↗

bioRxiv2021

Quantatitive Analysis of Conserved Sites on the SARS-CoV-2 Receptor-Binding Domain to Promote Development of Universal SARS-Like Coronavirus Vaccines

Although vaccines have been successfully developed and approved against SARS-CoV-2, it is still valuable to perform studies on conserved antigenic sites for preventing possible pandemic-risk of other SARS-like coronavirus in the future and prevalent SARS-CoV-2 variants. By antibodies obtained from convalescent COVID-19 individuals, receptor binding domain (RBD) were identified as immunodominant neutralizing domain that efficiently elicits neutralizing antibody response with on-going affinity mature. Moreover, we succeeded to define a quantitative antigenic map of neutralizing sites within SARS-CoV-2 RBD, and found that sites S2, S3 and S4 (new-found site) are conserved sites and determined as subimmunodominant sites, putatively due to their less accessibility than SARS-CoV-2 unique sites. P10-6G3, P07-4D10 and P05-6H7, respectively targeting S2, S3 and S4, are relatively rare antibodies that also potently neutralizes SARS-CoV, and the last mAbs performing neutralization without blocking S protein binding to receptor. Further, we have tried to design some RBDs to improve the immunogenicity of conserved sites. Our studies, focusing on conserved antigenic sites of SARS-CoV-2 and SARS-CoV, provide insights for promoting development of universal SARS-like coronavirus vaccines therefore enhancing our pandemic preparedness.

immunology↗

bioRxiv2021

Unbalanced dietary patterns contribute to the pathogenesis of precocious puberty by affecting gut microbiota and host metabolites

Precocious puberty (PP) mostly stems from endocrine disorders. However, its triggering factors, especially for the early onset of partial PP, and the associated pathogenic mechanisms remain ambiguous. In this study, a systematic analysis in the form of a questionnaire of lifestyles, gut microbiome, and serum metabolome data was carried out to examine the pathogenesis of PP in a cohort comprised of 200 girls, with or without PP. The analysis revealed substantial alterations in gut microbiota, serum metabolites, as well as lifestyle patterns in the PP group, which were characterized by an elevated abundance of {beta}-glucuronidase-producing and butyrate-producing bacteria, and excessive lipid concentration with decreased levels of organic nitrogen compounds in the serum of the participants. These differential microbes and metabolites tend to be reliable non-invasive diagnostic biomarkers aiding the early diagnosis of PP and exhibit a strong discriminative power (AUC = 0.93 and AUC = 0.97, respectively). Furthermore, the microbial biomarkers were confirmed in an independent validation cohort (n = 83, AUC = 0.85). Moreover, structural equation modeling revealed that unhealthy dietary habits were the primary contributors for the alteration of gut microbiota and serum metabolites, triggering the imbalance in the host hormones that leads to premature physical development. Our study determines a causal relationship among the gut microbiota, host metabolites, diet, and clinical characteristics of preadolescent girls who experienced early onset of PP, and formulates non-invasive diagnostic tools demonstrating excellent performance for the early detection of PP.

microbiology↗

bioRxiv2021

Callosal fiber length scales with brain size according to functional lateralization, evolution, and development

Brain size significantly impacts the organization of white matter fibers. Fiber length scaling - the degree to which fiber length varies according to brain size - was overlooked. We investigated how fiber lengths within the corpus callosum, the most prominent white matter tract, vary according to brain size. The results showed substantial variation in length scaling among callosal fibers, replicated in two large healthy cohorts ([~]2000 individuals). The underscaled callosal fibers mainly connected the precentral gyrus and parietal cortices, whereas the overscaled callosal fibers mainly connected the prefrontal cortices. The variation in such length scaling was biologically meaningful: larger scaling corresponded to larger neurite density index but smaller fractional anisotropy values; cortical regions connected by the callosal fibers with larger scaling were more lateralized functionally as well as phylogenetically and ontogenetically more recent than their counterparts. These findings highlight an interaction between interhemispheric communication and organizational and adaptive principles underlying brain development and evolution. Significance StatementBrain size varies across evolution, development, and individuals. Relative to small brains, the neural fiber length in large brains is inevitably increased, but the degree of such increase may differ between fiber tracts. Such a difference, if it exists, is valuable for understanding adaptive neural principles in large versus small brains during evolution and development. The present study showed a substantial difference in the length increase between the callosal fibers that connect the two hemispheres, replicated in two large healthy cohorts. Altogether, our study demonstrates that reorganization of interhemispheric fibers length according to brain size is intrinsically related to fiber composition, functional lateralization, cortical myelin content, evolutionary and developmental expansion.

neuroscience↗

bioRxiv2021

Taking full advantage of modelling to better assess environmental risk due to xenobiotics

In the European Union, more than 100,000 man-made chemical substances are awaiting an environmental risk assessment (ERA). Simultaneously, ERA of chemicals has now entered a new era. Indeed, recent recommendations from regulatory bodies underline a crucial need for the use of mechanistic effect models, allowing assessments that are not only ecologically relevant, but also more integrative, consistent and efficient. At the individual level, toxicokinetic-toxicodynamic (TKTD) models are particularly encouraged for the regulatory assessment of pesticide-related risks on aquatic organisms. In this paper, we first propose a brief review of classical dose-response models to put into light the on-line MOSAIC tool offering all necessary services in a turnkey web platform whatever the type of data to analyze. Then, we focus on the necessity to account for the time-dimension of the exposure by illustrating how MOSAIC can support a robust calculation of bioaccumulation factors. At last, we show how MOSAIC can be of valuable help to fully complete the EFSA workflow regarding the use of TKTD models, especially with GUTS models, providing a user-friendly interface for calibrating, validating and predicting survival over time under any time-variable exposure scenario of interest. Our conclusion proposes a few lines of thought for an even easier use of modelling in ERA. Graphical art O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=82 SRC="FIGDIR/small/436474v3_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@d98a72org.highwire.dtl.DTLVardef@1066b4org.highwire.dtl.DTLVardef@c6eef3org.highwire.dtl.DTLVardef@71c528_HPS_FORMAT_FIGEXP M_FIG C_FIG

ecology↗

bioRxiv2021

Apoptotic Extracellular Vesicles (ApoEVs) Safeguard Liver Homeostasis and Regeneration via Assembling an ApoEV-Golgi Organelle

Apoptosis is an integral physiological cell death process that occurs frequently and generates a huge number of apoptotic extracellular vesicles (apoEVs). However, whether apoEVs are necessary for maintaining organ homeostasis remains unclear. Here, we show that circulatory apoEVs engraft in liver and undergo specialized internalization by hepatocytes (HCs) based on surface signature of galactose and N-acetylgalactosamine. Furthermore, apoEVs rescue liver injury in apoptotic-deficient Fas mutant and Caspase-3 knockout mice, which is exerted by restoring the featured hepatic ploidy homeostasis. Surprisingly, apoEVs form a chimeric organelle complex with recipient Golgi apparatus via SNARE-mediated membrane interaction, which consequently facilitates microtubule organization and HC cytokinesis. Notably, through Golgi recovery and ploidy transition, apoEVs contribute to liver regeneration and protect against acute hepatic failure. Collectively, these results identify a previously unrecognized role for apoEVs and the specific mechanisms by which they safeguard liver homeostasis, and suggest the potential of apoEV-based therapy for liver disorders.

cell biology↗

bioRxiv2021

Connectome-based individual prediction of cognitive behaviors via the graph propagation network reveals directed brain network topology

The brain connectome supports the information flow underlying human cognitions and should reflect the individual variability in human cognitive behaviors. Various studies have utilized the brain connectome to predict individual differences in human behaviors. However, traditional studies viewed the brain connectome feature as a vector of one dimension, a method which neglects topological structures of the brain connectome. To utilize topological properties of the brain connectome, we proposed that graph neural network which combines graph theory and neural network can be adopted. Different from previous node-driven graph neural networks that parameterize on the node feature transformation, we designed an edge-driven graph neural network named graph propagation network that parameterizes on the information propagation within the brain connectome. We compared various models in predicting the individual total cognition based on the resting-state functional connectome. The edge-driven graph propagation network showed the highest prediction accuracy and outperformed the node-driven graph neural network and traditional partial least square regression. The graph propagation network also revealed a directed network topology encoding the information flow, indicating that the high-level association cortices are responsible for the information integration underlying the total cognition. These results suggest that the edge-driven graph propagation network can better explore the topological structure of the brain connectome and can serve as a new method to associate the brain connectome and human behaviors.

neuroscience↗