Functional characterization of HGF and its receptor C-Met in zebrafish development

Ph.DDOCTOR OF PHILOSOPH

Augmenter of Liver Regeneration (alr) Promotes Liver Outgrowth during Zebrafish Hepatogenesis

Augmenter of Liver Regeneration (ALR) is a sulfhydryl oxidase carrying out fundamental functions facilitating protein disulfide bond formation. In mammals, it also functions as a hepatotrophic growth factor that specifically stimulates hepatocyte proliferation and promotes liver regeneration after liver damage or partial hepatectomy. Whether ALR also plays a role during vertebrate hepatogenesis is unknown. In this work, we investigated the function of alr in liver organogenesis in zebrafish model. We showed that alr is expressed in liver throughout hepatogenesis. Knockdown of alr through morpholino antisense oligonucleotide (MO) leads to suppression of liver outgrowth while overexpression of alr promotes liver growth. The small-liver phenotype in alr morphants results from a reduction of hepatocyte proliferation without affecting apoptosis. When expressed in cultured cells, zebrafish Alr exists as dimer and is localized in mitochondria as well as cytosol but not in nucleus or secreted outside of the cell. Similar to mammalian ALR, zebrafish Alr is a flavin-linked sulfhydryl oxidase and mutation of the conserved cysteine in the CxxC motif abolishes its enzymatic activity. Interestingly, overexpression of either wild type Alr or enzyme-inactive AlrC131S mutant promoted liver growth and rescued the liver growth defect of alr morphants. Nevertheless, alrC131S is less efficacious in both functions. Meantime, high doses of alr MOs lead to widespread developmental defects and early embryonic death in an alr sequence-dependent manner. These results suggest that alr promotes zebrafish liver outgrowth using mechanisms that are dependent as well as independent of its sulfhydryl oxidase activity. This is the first demonstration of a developmental role of alr in vertebrate. It exemplifies that a low-level sulfhydryl oxidase activity of Alr is essential for embryonic development and cellular survival. The dose-dependent and partial suppression of alr expression through MO-mediated knockdown allows the identification of its late developmental role in vertebrate liver organogenesis

Evaluating the performance of empirical models of total electron density and whistler-mode wave amplitude in the Earth’s inner magnetosphere

Empirical models have been previously developed using the large dataset of satellite observations to obtain the global distributions of total electron density and whistler-mode wave power, which are important in modeling radiation belt dynamics. In this paper, we apply the empirical models to construct the total electron density and the wave amplitudes of chorus and hiss, and compare them with the observations along Van Allen Probes orbits to evaluate the model performance. The empirical models are constructed using the Hp30 and SME (or SML) indices. The total electron density model provides an overall high correlation coefficient with observations, while large deviations are found in the dynamic regions near the plasmapause or in the plumes. The chorus wave model generally agrees with observations when the plasma trough region is correctly modeled and for modest wave amplitudes of 10–100 pT. The model overestimates the wave amplitude when the chorus is not observed or weak, and underestimates the wave amplitude when a large-amplitude chorus is observed. Similarly, the hiss wave model has good performance inside the plasmasphere when modest wave amplitudes are observed. However, when the modeled plasmapause location does not agree with the observation, the model misidentifies the chorus and hiss waves compared to observations, and large modeling errors occur. In addition, strong (>200 pT) hiss waves are observed in the plumes, which are difficult to capture using the empirical model due to their transient nature and relatively poor sampling statistics. We also evaluate four metrics for different empirical models parameterized by different indices. Among the tested models, the empirical model considering a plasmapause and controlled by Hp* (the maximum Hp30 during the previous 24 h) and SME* (the maximum SME during the previous 3 h) or Hp* and SML has the best performance with low errors and high correlation coefficients. Our study indicates that the empirical models are applicable for predicting density and whistler-mode waves with modest power, but large errors could occur, especially near the highly-dynamic plasmapause or in the plumes

Deep learning model of hiss waves in the plasmasphere and plumes and their effects on radiation belt electrons

Hiss waves play an important role in removing energetic electrons from Earth’s radiation belts by precipitating them into the upper atmosphere. Compared to plasmaspheric hiss that has been studied extensively, the evolution and effects of plume hiss are less understood due to the challenge of obtaining their global observations at high cadence. In this study, we use a neural network approach to model the global evolution of both the total electron density and the hiss wave amplitudes in the plasmasphere and plume. After describing the model development, we apply the model to a storm event that occurred on 14 May 2019 and find that the hiss wave amplitude first increased at dawn and then shifted towards dusk, where it was further excited within a narrow region of high density, namely, a plasmaspheric plume. During the recovery phase of the storm, the plume rotated and wrapped around Earth, while the hiss wave amplitude decayed quickly over the nightside. Moreover, we simulated the overall energetic electron evolution during this storm event, and the simulated flux decay rate agrees well with the observations. By separating the modeled plasmaspheric and plume hiss waves, we quantified the effect of plume hiss on energetic electron dynamics. Our simulation demonstrates that, under relatively quiet geomagnetic conditions, the region with plume hiss can vary from L = 4 to 6 and can account for up to an 80% decrease in electron fluxes at hundreds of keV at L > 4 over 3 days. This study highlights the importance of including the dynamic hiss distribution in future simulations of radiation belt electron dynamics

Deletion of the WD40 Domain of LRRK2 in Zebrafish Causes Parkinsonism-Like Loss of Neurons and Locomotive Defect

LRRK2 plays an important role in Parkinson's disease (PD), but its biological functions are largely unknown. Here, we cloned the homolog of human LRRK2, characterized its expression, and investigated its biological functions in zebrafish. The blockage of zebrafish LRRK2 (zLRRK2) protein by morpholinos caused embryonic lethality and severe developmental defects such as growth retardation and loss of neurons. In contrast, the deletion of the WD40 domain of zLRRK2 by morpholinos targeting splicing did not induce severe embryonic developmental defects; rather it caused Parkinsonism-like phenotypes, including loss of dopaminergic neurons in diencephalon and locomotion defects. These neurodegenerative and locomotion defects could be rescued by over-expressing zLRRK2 or hLRRK2 mRNA. The administration of L-dopa could also rescue the locomotion defects, but not the neurodegeneration. Taken together, our results demonstrate that zLRRK2 is an ortholog of hLRRK2 and that the deletion of WD40 domain of zLRRK2 provides a disease model for PD

Preliminary safety assessment of oridonin in zebrafish

Context: Oridonin, isolated from the leaves of Isodon rubescens (Hemsl.) H.Hara (Lamiaceae), has good antitumor activity. However, its safety in vivo is still unclear. Objective: To investigate the preliminary safety of oridonin in zebrafish. Materials and methods: Embryo, larvae and adult zebrafish (n = 40) were used. Low, medium and high oridonin concentrations (100, 200 and 400 mg/L for embryo; 150, 300 and 600 mg/L for larvae; 200, 400 and 800 mg/L for adult zebrafish) and blank samples were administered. At specific stages of zebrafish development, spontaneous movement, heartbeat, hatching rate, etc., were recorded to assess the developmental effects of oridonin. VEGFA, VEGFR2 and VEGFR3 gene expression were also examined. Results: Low-dose oridonin increased spontaneous movement and hatching rate with median effective doses (ED50) of 115.17 mg/L at 24 h post-fertilization (hpf) and 188.59 mg/L at 54 hpf, but these values decreased at high doses with half maximal inhibitory concentrations (IC50) of 209.11 and 607.84 mg/L. Oridonin decreased heartbeat with IC50 of 285.76 mg/L at 48 hpf, and induced malformation at 120 hpf with half maximal effective concentration (EC50) of 411.94 mg/L. Oridonin also decreased body length with IC50 of 324.78 mg/L at 144 hpf, and increased swimming speed with ED50 of 190.98 mg/L at 120 hpf. The effects of oridonin on zebrafish embryo development may be attributed to the downregulation of VEGFR3 gene expression. Discussions and conclusions: Oridonin showed adverse effects at early stages of zebrafish development. We will perform additional studies on mechanism of oridonin based on VEGFR3

Antiangiogenic effects of oridonin

Abstract Background Oridonin, the major terpene found in Rabdosia rubescens (Henmsl.) Hara, is widely used as a dietary supplement and therapeutic drug. Oridonin has been proven to possess good anti-tumour activity, but little is known about its effect on angiogenesis. The aim of this study was to investigate the antiangiogenic effects of oridonin in vivo and in vitro and prove that oridonin anti-tumour activity is based on suppressing angiogenesis. Methods In vitro, the antiangiogenesis effect was studied by proliferation, apoptosis, migration, invasion, and tube formation experiments on human umbilical vascular endothelial cells (HUVECs). In vivo, using the Tg (fli1: GFP) zebrafish model, the embryonic vasculogenesis and postnatal regeneration were evaluated. The vascular endothelial growth factor (VEGF) signalling pathway gene expressions were assessed by reverse transcription-polymerase chain reaction (RT-PCR). Furthermore, the inhibition effects on tumour growth and metastasis were observed using a xenograft zebrafish tumour model and xenograft nude mouse tumour model. Angiogenesis was assayed by immunostaining with cluster of differentiation 31. Importantly, the proteins were identified as being differentially expressed in an in vivo model by two-dimensional electrophoresis-mass spectrometry (2D–MS) and western blot (WB). Results The results indicated that oridonin inhibited HUVEC proliferation, migration, invasion, and tube formation and induced cell apoptosis. Oridonin inhibited zebrafish angiogenesis during embryonic development and tail fin regeneration. RT-PCR showed that oridonin decreased the VEGFA, VEGFR2, and VEGFR3 expressions in zebrafish, while the TP53 expression increased. Moreover, oridonin had strong effects on tumour growth and metastasis in vivo. 2D–MS identified a total of 50 proteins differentially expressed (17 up-expressed, 28 down-expressed). Lastly, WB showed that Claudin 1, Claudin 4, and Claudin 7 were closely related to tumour growth and metastasis. Conclusion This study demonstrated that oridonin could inhibit tumour growth and metastasis, which mainly based on oridonin antiangiogenic effects. Claudin 1, Claudin 4, and Claudin 7 were the main contributors to the mechanism

XCO₂ Super-Resolution Reconstruction Based on Spatial Extreme Random Trees

Carbon dioxide (CO2) is currently the most harmful greenhouse gas in the atmosphere. Obtaining long-term, high-resolution atmospheric column CO2 concentration (XCO2) datasets is of great practical significance for mitigating the greenhouse effect, identifying and controlling carbon emission sources, and achieving carbon cycle management. However, mainstream satellite observations provide XCO2 datasets with coarse spatial resolution, which is insufficient to support the needs of higher-precision research. To address this gap, in this study, we integrate spatial information with the extreme random trees model and develop a new machine learning model called spatial extreme random trees (SExtraTrees) to reconstruct a 1 km spatial resolution XCO2 dataset for China from 2016 to 2020. The results indicate that the predictive ability of spatial extreme random trees is more stable and has higher fitting accuracy compared to other methods. Overall, XCO2 in China shows an increasing trend year by year, with the spatial distribution revealing significantly higher XCO2 levels in eastern coastal regions compared to western inland areas. The contributions of this study are primarily in the following areas: (1) Considering the spatial heterogeneity of XCO2 and combining spatial features with the advantages of machine learning, we construct the spatial extreme random trees model, which is verified to have high predictive accuracy. (2) Using the spatial extreme random trees model, we reconstruct high-resolution XCO2 datasets for China from 2016 to 2020, providing data support for carbon emission reduction and related decision making. (3) Based on the generated dataset, we analyze the spatiotemporal distribution patterns of XCO2 in China, thereby improving emission reduction policies and sustainable development measures

The landscape of the long non-coding RNAs in developing mouse retinas

Abstract Background The long non-coding RNAs (lncRNAs) are critical regulators of diverse biological processes. Nevertheless, a global view of its expression and function in the mouse retina, a crucial model for neurogenesis study, still needs to be made available. Results Herein, by integrating the established gene models and the result from ab initio prediction using short- and long-read sequencing, we characterized 4,523 lncRNA genes (MRLGs) in developing mouse retinas (from the embryonic day of 12.5 to the neonatal day of P28), which was so far the most comprehensive collection of retinal lncRNAs. Next, derived from transcriptomics analyses of different tissues and developing retinas, we found that the MRLGs were highly spatiotemporal specific in expression and played essential roles in regulating the genesis and function of mouse retinas. In addition, we investigated the expression of MRLGs in some mouse mutants and revealed that 97 intergenic MRLGs might be involved in regulating differentiation and development of retinal neurons through Math5, Isl1, Brn3b, NRL, Onecut1, or Onecut2 mediated pathways. Conclusions In summary, this work significantly enhanced our knowledge of lncRNA genes in mouse retina development and provided valuable clues for future exploration of their biological roles