Biology subjects

Zhao, Z.

Publications and source records attributed to Zhao, Z..

At least 469 records · Page 26Linked to original sources

bioRxiv2020

Characterizing geographical and temporal dynamics of novel coronavirus SARS-CoV-2 using informative subtype markers

We propose an efficient framework for genetic subtyping of SARS-CoV-2, the novel coronavirus that causes the COVID-19 pandemic. Efficient viral subtyping enables visualization and modeling of the geographic distribution and temporal dynamics of disease spread. Subtyping thereby advances the development of effective containment strategies and, potentially, therapeutic and vaccine strategies. However, identifying viral subtypes in real-time is challenging: SARS-CoV-2 is a novel virus, and the pandemic is rapidly expanding. Viral subtypes may be difficult to detect due to rapid evolution; founder effects are more significant than selection pressure; and the clustering threshold for subtyping is not standardized. We propose to identify mutational signatures of available SARS-CoV-2 sequences using a population-based approach: an entropy measure followed by frequency analysis. These signatures, Informative Subtype Markers (ISMs), define a compact set of nucleotide sites that characterize the most variable (and thus most informative) positions in the viral genomes sequenced from different individuals. Through ISM compression, we find that certain distant nucleotide variants covary, including non-coding and ORF1ab sites covarying with the D614G spike protein mutation which has become increasingly prevalent as the pandemic has spread. ISMs are also useful for downstream analyses, such as spatiotemporal visualization of viral dynamics. By analyzing sequence data available in the GISAID database, we validate the utility of ISM-based subtyping by comparing spatiotemporal analyses using ISMs to epidemiological studies of viral transmission in Asia, Europe, and the United States. In addition, we show the relationship of ISMs to phylogenetic reconstructions of SARS-CoV-2 evolution, and therefore, ISMs can play an important complementary role to phylogenetic tree-based analysis, such as is done in the Nextstrain [1] project. The developed pipeline dynamically generates ISMs for newly added SARS-CoV-2 sequences and updates the visualization of pandemic spatiotemporal dynamics, and is available on Github at https://github.com/EESI/ISM and via an interactive website at https://covid19-ism.coe.drexel.edu/. Author SummaryThe novel coronavirus responsible for COVID-19, SARS-CoV-2, expanded to reportedly 8.7 million confirmed cases worldwide by June 21, 2020. The global SARS-CoV-2 pandemic highlights the importance of tracking viral transmission dynamics in real-time. Through June 2020, researchers have obtained genetic sequences of SARS-CoV-2 from over 47,000 samples from infected individuals worldwide. Since the virus readily mutates, each sequence of an infected individual contains useful information linked to the individuals exposure location and sample date. But, there are over 30,000 bases in the full SARS-CoV-2 genome--so tracking genetic variants on a whole-sequence basis becomes unwieldy. We describe a method to instead efficiently identify and label genetic variants, or "subtypes" of SARS-CoV-2. Applying this method results in a compact, 11 base-long compressed label, called an Informative Subtype Marker or "ISM". We define viral subtypes for each ISM, and show how regional distribution of subtypes track the progress of the pandemic. Major findings include (1) covarying nucleotides with the spike protein which has spread rapidly and (2) tracking emergence of a local subtype across the United States connected to Asia and distinct from the outbreak in New York, which is found to be connected to Europe.

genomics↗

bioRxiv2020

Oxytocin differentially modulates amygdala responses during top-down and bottom-up aversive anticipation

The ability to successfully regulate negative emotions such as fear and anxiety is vital for mental health. The neuropeptide oxytocin (OXT) acts as important modulator of emotion regulation, as reflected by reduced amygdala responses but increased amygdala-prefrontal cortex (PFC) functional connectivity in response to threatening stimuli. The present randomized, between-subject, placebo (PLC)-controlled pharmacological study combined intranasal administration of OXT with functional MRI during an explicit (cognitive) emotion regulation (i.e. distancing reappraisal) paradigm in 65 healthy male participants to investigate the modulatory effects of OXT on both bottom-up and top-down emotion regulation. OXT attenuated the activation in posterior insular cortex and amygdala during anticipation of top-down regulation of predictable threat stimuli in participants with high trait anxiety, providing evidence to support the anxiolytic action of OXT. In contrast, OXT enhanced amygdala activity during bottom-up anticipation of an unpredictable threat stimulus in participants with low trait anxiety. OXT may thus facilitate top-down goal-directed attention by attenuating amygdala activity in high anxiety individuals, while promote bottom-up attention/vigilance to unexpected threat by enhancing anticipatory amygdala activity in low anxiety individuals. The opposite effects of OXT on anticipatory amygdala activation in high versus low anxiety individuals may suggest a baseline anxiety level dependent mechanism via which OXT promotes optimal levels of amygdala activation during the anticipation of an imminent threat. OXT may thus have the potential to promote an adaptive balance between bottom-up and top-down attention systems depending on individual levels of pre-treatment trait anxiety levels.

neuroscience↗

bioRxiv2020

LZTR1 inactivation promotes MAPK/ ERK pathway activation in glioblastoma by stabilizing oncoprotein RIT1

Large-scale sequencing studies on glioblastoma have identified numerous genetic alterations. Leucine-zipper-like transcription regulator 1 (LZTR1) is inactivated by non-synonymous mutations and copy number losses, suggesting that it is a tumor suppressor in glioblastoma. However, how LZTR1 mutations contribute to glioblastoma pathogenesis remains poorly understood. Here, we revealed that LZTR1, as an adaptor of the CUL3 E3 ubiquitin ligase complex, recognizes and triggers ubiquitin-dependent degradation of oncoprotein RIT1, a RAS-like GTPase. Wild-type LZTR1 suppresses glioblastoma cell proliferation and migration by inactivating the MAPK/ERK signaling pathway in a RIT1-dependent manner. However, the effects were abrogated by the glioblastoma-associated LZTR1 mutations. Our findings revealed the underlying molecular mechanism of LZTR1 mutations-driven glioblastoma, and provide novel therapeutic target for LZTR1 mutations-driven glioblastoma.

cancer biology↗

bioRxiv2020

Novel and potent inhibitors targeting DHODH, a rate-limiting enzyme in de novo pyrimidine biosynthesis, are broad-spectrum antiviral against RNA viruses including newly emerged coronavirus SARS-CoV-2

Emerging and re-emerging RNA viruses occasionally cause epidemics and pandemics worldwide, such as the on-going outbreak of coronavirus SARS-CoV-2. Existing direct-acting antiviral (DAA) drugs cannot be applied immediately to new viruses because of virus-specificity, and the development of new DAA drugs from the beginning is not timely for outbreaks. Thus, host-targeting antiviral (HTA) drugs have many advantages to fight against a broad spectrum of viruses, by blocking the viral replication and overcoming the potential viral mutagenesis simultaneously. Herein, we identified two potent inhibitors of DHODH, S312 and S416, with favorable drug-like and pharmacokinetic profiles, which all showed broad-spectrum antiviral effects against various RNA viruses, including influenza A virus (H1N1, H3N2, H9N2), Zika virus, Ebola virus, and particularly against the recent novel coronavirus SARS-CoV-2. Our results are the first to validate that DHODH is an attractive host target through high antiviral efficacy in vivo and low virus replication in DHODH knocking-out cells. We also proposed the drug combination of DAA and HTA was a promising strategy for anti-virus treatment and proved that S312 showed more advantageous than Oseltamivir to treat advanced influenza diseases in severely infected animals. Notably, S416 is reported to be the most potent inhibitor with an EC50 of 17nM and SI value >5882 in SARS-CoV-2-infected cells so far. This work demonstrates that both our self-designed candidates and old drugs (Leflunomide/Teriflunomide) with dual actions of antiviral and immuno-repression may have clinical potentials not only to influenza but also to COVID-19 circulating worldwide, no matter such viruses mutate or not.

microbiology↗

bioRxiv2020

Multimodal mapping of neural activity and cerebral blood flow reveals long-lasting neurovascular dissociations after small-scale strokes

Neurovascular coupling, the close spatial and temporal relationship between neural activity and hemodynamics, is disrupted in pathological brain states. To understand the altered neurovascular relationship in brain disorders, longitudinal, simultaneous mapping of neural activity and hemodynamics is critical yet challenging to achieve. Here, we employ a multimodal neural platform in a mouse model of stroke and realize long-term, spatially-resolved tracking of intracortical neural activity and cerebral blood flow in the same brain regions. We observe a pronounced neurovascular dissociation that occurs immediately after small-scale strokes, becomes the most severe a few days after, lasts into chronic periods, and varies with the level of ischemia. Neuronal deficits extend spatiotemporally whereas restoration of cerebral blood flow occurs sooner and reaches a higher relative value. Our findings reveal the neurovascular impact of mini-strokes and inform the limitation of neuroimaging techniques that infer neural activity from hemodynamic responses.

neuroscience↗

bioRxiv2020

A simple magnetic nanoparticles-based viral RNA extraction method for efficient detection of SARS-CoV-2

1The ongoing outbreak of the novel coronavirus disease 2019 (COVID-19) originating from Wuhan, China, draws worldwide concerns due to its long incubation period and strong infectivity. Although RT-PCR-based molecular diagnosis techniques are being widely applied for clinical diagnosis currently, timely and accurate diagnosis are still limited due to labour intensive and time-consuming operations of these techniques. To address the issue, herein we report the synthesis of poly (amino ester) with carboxyl groups (PC)-coated magnetic nanoparticles (pcMNPs), and the development of pcMNPs-based viral RNA extraction method for the sensitive detection of COVID-19 causing virus, the SARS-CoV-2. This method combines the lysis and binding steps into one step, and the pcMNPs-RNA complexes can be directly introduced into subsequent RT-PCR reactions. The simplified process can purify viral RNA from multiple samples within 20 min using a simple manual method or an automated high-throughput approach. By identifying two different regions (ORFlab and N gene) of viral RNA, a 10-copy sensitivity and a strong linear correlation between 10 and 105 copies of SARS-CoV-2 pseudovirus particles are achieved. Benefitting from the simplicity and excellent performances, this new extraction method can dramatically reduce the turn-around time and operational requirements in current molecular diagnosis of COVID-19, in particular for the early clinical diagnosis.

molecular biology↗

bioRxiv2020

The Taste of Blood in Mosquitoes

Blood-feeding mosquitoes survive by feeding on nectar for metabolic energy, but to develop eggs, females require a blood meal. Aedes aegypti females must accurately discriminate between blood and nectar because detection of each meal promotes one of two mutually exclusive feeding programs characterized by distinct sensory appendages, meal sizes, digestive tract targets, and metabolic fates. We investigated the role of the syringe-like blood-feeding appendage, the stylet, and discovered that sexually dimorphic stylet neurons are the first to taste blood. Using pan-neuronal GCaMP calcium imaging, we found that blood is detected by four functionally distinct classes of stylet neurons, each tuned to specific blood components associated with diverse taste qualities. Furthermore, the stylet is specialized to detect blood over nectar. Stylet neurons are insensitive to nectar-specific sugars and responses to glucose, the sugar found in both blood and nectar, depend on the presence of additional blood components. The distinction between blood and nectar is therefore encoded in specialized neurons at the very first level of sensory detection in mosquitoes. This innate ability to recognize blood is the basis of vector-borne disease transmission to millions of people world-wide.

neuroscience↗

bioRxiv2020

Dynamics of mcr-1 prevalence and mcr-1-positive Escherichia coli after the cessation of colistin use as a feed additive for animals in China: a prospective cross-sectional and whole genome sequencing based molecular epidemiological study

BackgroundThe global dissemination of colistin resistance encoded by mcr-1 has been attributed to extensive use of colistin in livestock, threatening colistin efficacy in medicine. The emergence of mcr-1 in common pathogens, such as Escherichia coli, is of particular concern. Therefore, China banned the use of colistin in animal feed from May 1ST 2017. We investigated subsequent changes in mcr-1 prevalence, and the genomic epidemiology of mcr-1-positive Escherichia coli (MCRPEC). MethodsSampling was conducted pre- (October-December 2016) and post-colistin ban (October-December, 2017 and 2018, respectively). 3675 non-duplicate pig fecal samples were collected from 14 provinces (66 farms) in China to determine intervention-related changes in mcr-1 prevalence. 15193 samples were collected from pigs, healthy human volunteers, colonized and infected hospital inpatients, food and the environment in Guangzhou, to characterize source-specific mcr-1 prevalence and the wider ecological impact of the ban. From these samples, 688 MCRPEC were analyzed with whole genome sequencing (WGS), plasmid conjugation and S1-PFGE/Southern blots to characterize associated genomic changes. FindingsAfter the ban, mcr-1 prevalence decreased significantly in national pig farms, from 45{middle dot}0% (308/684 samples) in 2016, to 19{middle dot}4% (274/1416) in 2018 (p<0{middle dot}0001). This trend was mirrored in samples from most sources in Guangzhou (overall 19{middle dot}2% [959/5003 samples] in 2016; 5{middle dot}3% [238/4489] in 2018; p<0{middle dot}0001). The population structure of MCRPEC was diverse (23 sequence clusters [SCs]); ST10 clonal complex isolates were predominant (247/688 [36%]). MCRPEC causing infection in hospitalized inpatients were genetically more distinct and appeared less affected by the ban. mcr-1 was predominantly found on plasmids (632/688 [92%]). Common mcr-1 plasmid types included IncX4, IncI2 and IncHI2 (502/656 [76.5%]); significant increases in IncI2-associated mcr-1 and a distinct lineage of mcr-1-associated IncHI2 were observed post-ban. Changes in the frequency of mcr-1-associated flanking sequences (ISApl1-negative MCRPEC), 63 core genome SNPs and 30 accessory genes were also significantly different after the ban, consistent with rapid genetic adaptation in response to changing selection pressures. InterpretationA rapid, ecosystem-wide, decline in mcr-1 was observed after banning the use of colistin in animal feed, with associated genetic changes in MCRPEC. Genomic surveillance is key to assessing and monitoring stewardship interventions. FundingNational Natural Science Foundation of China

microbiology↗

bioRxiv2020

Single-cell RNA expression profiling of ACE2, the putative receptor of Wuhan 2019-nCov

A novel coronavirus SARS-CoV-2 was identified in Wuhan, Hubei Province, China in December of 2019. According to WHO report, this new coronavirus has resulted in 76,392 confirmed infections and 2,348 deaths in China by 22 February, 2020, with additional patients being identified in a rapidly growing number internationally. SARS-CoV-2 was reported to share the same receptor, Angiotensin-converting enzyme 2 (ACE2), with SARS-CoV. Here based on the public database and the state-of-the-art single-cell RNA-Seq technique, we analyzed the ACE2 RNA expression profile in the normal human lungs. The result indicates that the ACE2 virus receptor expression is concentrated in a small population of type II alveolar cells (AT2). Surprisingly, we found that this population of ACE2-expressing AT2 also highly expressed many other genes that positively regulating viral entry, reproduction and transmission. This study provides a biological background for the epidemic investigation of the COVID-19, and could be informative for future anti-ACE2 therapeutic strategy development.

bioinformatics↗

bioRxiv2020

Isolation and long-term expansion of a single adult human renal epithelial cell with efficient kidney regeneration capacity

A wide spectrum of lethal kidney diseases involves the irreversible destruction of the tubular structures which leads to loss of renal function. A reliable technological platform to culture and transplant adult human-derived cells with nephrogenic potential offers great hope to facilitate human kidney regeneration. Here, we show that in an appropriate feeder cell-based culture system, it is feasible to isolate and long-term expand the progenitor-like SOX9+ renal epithelial cells (SOX9+ RECs) from adult mammalians. Single cell-derived SOX9+ REC lines can be established from human needle biopsy or urine samples with molecular homogeneity and genomic stability maintained during culture. Such cells grown in 3D culture system could self-organize into renal organoids composed of proximal tubular, Loop of Henle (LOH) and distal tubular cells as illustrated by single cell transcriptomic analysis. Once being transplanted into the physically injured mouse kidney, the expanded single human SOX9+ RECs incorporated into the damaged area and demonstrated capacity of regenerating functional tubules in vivo. Altogether, the ability to extensively propagate human SOX9+ REC in culture whilst concomitantly maintaining their intrinsic lineage differentiation commitment suggests their future application in regenerative medicine.

cell biology↗

bioRxiv2020

Chinese Glioma Genome Atlas (CGGA): A Comprehensive Resource with Functional Genomic Data for Chinese Glioma Patients

Gliomas are the most common and malignant intracranial tumours in adults. Recent studies have shown that functional genomics greatly aids in the understanding of the pathophysiology and therapy of glioma. However, comprehensive genomic data and analysis platforms are relatively limited. In this study, we developed the Chinese Glioma Genome Atlas (CGGA, http://www.cgga.org.cn), a user-friendly data portal for storage and interactive exploration of multi-dimensional functional genomic data that includes nearly 2,000 primary and recurrent glioma samples from Chinese cohorts. CGGA currently provides access to whole-exome sequencing (286 samples), messenger RNA sequencing (1,018 samples) and microarray (301 samples), DNA methylation microarray (159 samples), and microRNA microarray (198 samples) data, as well as detailed clinical data (e.g., WHO grade, histological type, critical molecular genetic information, age, sex, chemoradiotherapy status and survival data). In addition, we developed an analysis tool to allow users to browse mutational, mRNA/microRNA expression, and DNA methylation profiles and perform survival and correlation analyses of specific glioma subtypes. CGGA greatly reduces the barriers between complex functional genomic data and glioma researchers who seek rapid, intuitive, and high-quality access to data resources and enables researchers to use these immeasurable data sources for biological research and clinical application. Importantly, the free provision of data will allow researchers to quickly generate and provide data to the research community.

genomics↗

bioRxiv2020

A mathematical model for simulating the transmission of Wuhan novel Coronavirus

As reported by the World Health Organization, a novel coronavirus (2019-nCoV) was identified as the causative virus of Wuhan pneumonia of unknown etiology by Chinese authorities on 7 January, 2020. In this study, we developed a Bats-Hosts-Reservoir-People transmission network model for simulating the potential transmission from the infection source (probable be bats) to the human infection. Since the Bats-Hosts-Reservoir network was hard to explore clearly and public concerns were focusing on the transmission from a seafood market (reservoir) to people, we simplified the model as Reservoir-People transmission network model. The basic reproduction number (R0) was calculated from the RP model to assess the transmissibility of the 2019-nCoV.

systems biology↗

bioRxiv2020

Mechanical Instability of Adherens Junctions Overrides Intrinsic Quiescence of Hair Follicle Stem Cells

Vinculin, a mechanotransducer associated with both adherens junctions (AJ) and focal adhesions (FA) plays a central role in force transmission through these cell-cell and cell-substratum contacts. Here we describe the conditional knock out (KO) of vinculin in murine skin. Remarkably, we find that the loss of vinculin function results in the loss of bulge stem cell (BuSC) quiescence. We demonstrate that vinculin KO cells are impaired in force generation resulting in mechanically weak AJs. Mechanistically, vinculin functions by keeping -catenin in a stretched conformation, which in turn regulates the retention of YAP1, another potent mechanotransducer and regulator of cell proliferation, to the junctions. Conditional KO of -catenin specifically in the BuSCs further corroborates the importance of stable AJs in the maintenance of quiescence and stemness. Altogether, our data provides definitive mechanistic insights into the hitherto unexplored regulatory link between the mechanical stability of cell-junctions and the maintenance of BuSC quiescence.

cell biology↗

bioRxiv2019

DrivAER: Identification of driving transcriptional programs in single-cell RNA sequencing data

Single cell RNA sequencing (scRNA-seq) unfolds complex transcriptomic data sets into detailed cellular maps. Despite recent success, there is a pressing need for specialized methods tailored towards the functional interpretation of these cellular maps. Here, we present DrivAER, a machine learning approach that scores annotated gene sets based on their relevance to user-specified outcomes such as pseudotemporal ordering or disease status. We demonstrate that DrivAER extracts the key driving pathways and transcription factors that regulate complex biological processes from scRNA-seq data.

bioinformatics↗

bioRxiv2019

Specific hippocampal interneurons shape consolidation of recognition memory

A complex array of different inhibitory interneurons tightly controls hippocampal activity, but how such diversity specifically impacts on memory processes is scantly known. We found that a small subclass of type-1 cannabinoid receptor (CB1)-expressing hippocampal interneurons determines episodic-like memory consolidation by linking dopamine D1 receptor signaling to GABAergic transmission. Mice lacking CB1 in D1-positive cells (D1-CB1-KO) displayed impaired long-term, but not short-term, object recognition memory. Re-expression of CB1 in hippocampal, but not striatal, D1-positive cells rescued this memory impairment. Learning induced a facilitation of in vivo hippocampal long-term potentiation (LTP), which was abolished in mutant mice. Chemogenetic and pharmacological experiments revealed that both CB1-mediated memory and associated LTP facilitation involves the local control of GABAergic inhibition in a D1-dependent manner. This study reveals that CB1-/D1-expressing interneurons shape hippocampal circuits to sustain recognition memory, thereby identifying a mechanism linking the diversity of hippocampal interneurons to specific behavioral and cognitive outcomes.

neuroscience↗

bioRxiv2019

Revealing acquired resistance mechanisms of kinase-targeted drugs using an on-the-fly, function-site interaction fingerprint approach

Although kinase-targeted drugs have achieved significant clinical success, they are frequently subject to the limitations of drug resistance, which has become a primary vulnerability to targeted drug therapy. Therefore, deciphering resistance mechanisms is an important step in designing more efficacious, anti-resistant, drugs. Here we studied two FDA-approved kinase drugs: Crizotinib and Ceritinib, which are first- and second-generation anaplastic lymphoma kinase (ALK) targeted inhibitors, to unravel drug-resistance mechanisms. We used an on-the-fly, function-site interaction fingerprint (on-the-fly Fs-IFP) approach by combining binding free energy surface calculations with the Fs-IFPs. Establishing the potentials of mean force and monitoring the atomic-scale protein-ligand interactions, before and after the L1196M-induced drug resistance, revealed insights into drug-resistance/anti-resistant mechanisms. Crizotinib prefers to bind the wild type ALK kinase domain, whereas Ceritinib binds more favorably to the mutated ALK kinase domain, in agreement with experimental results. We determined that ALK kinase-drug interactions in the region of the front pocket are associated with drug resistance. Additionally, we find that the L1196M mutation does not simply alter the binding modes of inhibitors, but also affects the flexibility of the entire ALK kinase domain. Our work provides an understanding of the mechanisms of ALK drug resistance, confirms the usefulness of the on-the-fly Fs-IFP approach and provides a practical paradigm to study drug-resistance mechanisms in prospective drug discovery.

biochemistry↗

bioRxiv2019

Fine-tuning Polygenic Risk Scores with GWAS Summary Statistics

Polygenic risk scores (PRSs) have wide applications in human genetics research. Notably, most PRS models include tuning parameters which improve predictive performance when properly selected. However, existing model-tuning methods require individual-level genetic data as the training dataset or as a validation dataset independent from both training and testing samples. These data rarely exist in practice, creating a significant gap between PRS methodology and applications. Here, we introduce PUMAS (Parameter-tuning Using Marginal Association Statistics), a novel method to fine-tune PRS models using summary statistics from genome-wide association studies (GWASs). Through extensive simulations, external validations, and analysis of 65 traits, we demonstrate that PUMAS can perform a variety of model-tuning procedures (e.g. cross-validation) using GWAS summary statistics and can effectively benchmark and optimize PRS models under diverse genetic architecture. On average, PUMAS improves the predictive R2 by 205.6% and 62.5% compared to PRSs with arbitrary p-value cutoffs of 0.01 and 1, respectively. Applied to 211 neuroimaging traits and Alzheimers disease, we show that fine-tuned PRSs will significantly improve statistical power in downstream association analysis. We believe our method resolves a fundamental problem without a current solution and will greatly benefit genetic prediction applications.

genetics↗

bioRxiv2019

Establishment of morphological atlas of Caenorhabditis elegans embryo with cellular resolution using deep-learning-based 4D segmentation

Cell lineage consists of cell division timing, cell migration and cell fate, which are highly reproducible during the development of some nematode species, including C. elegans. Due to the lack of high spatiotemporal resolution of imaging technique and reliable shape-reconstruction algorithm, cell morphology have not been systematically characterized in depth over development for any metazoan. This significantly inhibits the study of space-related problems in developmental biology, including cell segregation, cell-cell contact and cell shape change over development. Here we develop an automated pipeline, CShaper, to help address these issues. By quantifying morphological parameters of densely packed cells in developing C. elegans emrbyo through segmentation of fluorescene-labelled membrance, we generate a time-lapse framework of cellular shape and migration for C. elegans embryos from 4-to 350-cell stage, including a full migration trajectory, morphological dynamics of 226 cells and 877 reproducible cell-cell contacts. In combination with automated cell tracing, cell-fate associated cell shape change becomes within reach. Our work provides a quantitative resource for C. elegans early development, which is expected to facilitate the research such as signaling transduction and cell biology of division.

developmental biology↗