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Zhang, W.

Publications and source records attributed to Zhang, W..

At least 667 records · Page 37Linked to original sources

Phenotypic and transcriptional features of the Araliaceae species under distinct light environments

Elucidating how the plant species respond to variable light conditions is essential to understand the ecological adaptation to heterogeneous environments. Plant performance and gene regulatory network underpinning the adaptation have been well-documented in sun-grown species. In this study, we surveyed phenotypic and transcriptomic features of four shade-grown and one sun-grown woody species of the family Araliaceae under distinct light conditions. Our phenotypic comparisons demonstrate that the four shade-grown species possess lower light saturation point and higher assimilation ability of the net photosynthetic rate compared to the sun-grown species. In particular, the four shade-grown species maintain similar photosynthesis efficiency in both highlight and lowlight conditions. However, a significantly decreased photosynthesis rate was observed under lowlight condition of the sun-grown species compared to highlight condition. In addition, our leaf anatomical analyses reveal that while all the five species show different anatomical structures under distinct light conditions, the shade-grown species possess lower degree of phenotypic plasticity relative the sun-grown species. Further comparisons of the transcriptome profiling show that all the five species exhibit gene expression divergence among different light conditions. The differentially expressed genes identified in the five species are functionally related to photosynthesis, secondary metabolites and other basic metabolisms. More importantly, differential regulation of the photosynthesis- and photomorphogenesis-related genes are potentially correlated with the phenotypic responses to distinct light conditions of the five species. Our study provides new insights on how the sun- and shade-grown woody species respond to shade and sunlight environments.

ecology↗

Increasing the sensitivity, recovery, and integrality of spatially resolved proteomics by LCM-MTA

Conventional proteomic approaches neglect tissue heterogeneity and spatial localization information. Laser capture microdissection (LCM) can isolate specific cell populations or histological areas from heterogeneous tissue specimens while preserving spatial localization information. Formalin-fixed paraffin-embedded (FFPE) is currently a standardized method for long-term stable preservation of clinical tissue specimens. However, spatially resolved proteomics (SRP) studies of FFPE tissues by combined LCM and mass spectrometry (MS)-based proteomics face challenges, such as formalin-induced protein crosslinking limits protein extraction and digestion, protein loss during sample preparation, and the detectability of MS for trace tissues. Therefore, it is necessary to specifically develop SRP sample preparation methods and MS methods suitable for trace FFPE tissues. Here, we provide an SRP method suitable for trace FFPE tissues produced by LCM, termed LCM-Magnetic Trace Analysis (LCM-MTA), which can significantly increase the sensitivity, recovery, and integrality of SRP. The starting material has been reduced to about 15 cells, which resolution is comparable to existing spatially resolved transcriptome (SRT). We also apply our LCM-MTA into SRP studies on clinical colorectal cancer (CRC) tissues and accurately distinguish the functional differences of different cell types. In conclusion, LCM-MTA is a convenient, universal, and scalable method for SRP of trace FFPE tissues, which can be widely used in clinical and non-clinical research fields.

systems biology↗

Differentially expressed gene profile and relevant pathways of the inhibition of LAMP5 on MLL-rearranged leukemias

LAMP5 is a lysosome-related protein, which showed increased expression levels in MLL-r leukemia. Recent findings showed that LAMP5 is involved in MLL-fusion protein but the specific mechanism is still unclear. In our study, we aim to identify the transcriptional landscapes of the LAMP5-shRNA-treated MLL-r leukemia cells. We used the gene enrichment analyses such as KEGG and GO to further analyze the potential signaling pathways. Moreover, we constructed the PPI network and Reactome map to further identify the biological processes. We found that Lysosome and Cell Cycle are the major signaling pathways involved in the LAMP5-shRNA treated MLL-r leukemia cells. We identified the top ten interactive genes including CDK1, TOP2A, PLK1, CCNA2, ASPM, BUB1, BUB1B, CCNB1, AURKA, and KIF11. Our study may provide novel mechanisms for the treatment of MLL-r leukemia by inhibiting LAMP5.

bioinformatics↗

BCAA catabolism drives adipogenesis via an intermediate metabolite and promotes subcutaneous adipose tissue expansion during obesity

Branched-chain amino acids (BCAAs, including leucine, isoleucine, and valine) have emerged as major players in metabolic health and diseases, but the underlying mechanisms remain obscure. Here, we report that BCAA catabolism drives adipogenesis via an intermediate metabolite of leucine and promotes subcutaneous white adipose tissue (sWAT) expansion during obesity. Genetic analyses of humans and mice reveal that the BCAA catabolic pathway in WAT is strongly correlated with adipose physiology and obesity traits. Altering BCAA catabolism in mature adipocytes exerts minor effects on adiposity in mice. However, enhancing adipose BCAA catabolism via FABP4-Cre-mediated Bckdk deletion promotes diet-induced obesity while blocking adipose BCAA catabolism through Bckdha ablation does the opposite. Intriguingly, the catabolism of BCAAs elicits fat depot-specific responses and promotes sWAT extension and adipogenesis in a cell-autonomous manner. Mechanistically, BCAA catabolism drives adipocyte differentiation via an intermediate metabolite of leucine, which activates mTORC1 and polyamine synthesis from methionine to promote the expression of adipogenic master regulators. Together, these results demonstrate that BCAA catabolism promotes adipogenesis and sWAT expansion during obesity. The crosstalk between leucine and methionine metabolism driven by the catabolic intermediate highlights an unexpected regulatory role of amino acids in metabolic health and diseases.

physiology↗

SIC50: Determination of IC50 by an optimized Sobel operator and a vision transformer

As a measure of cytotoxic potency, half-maximal inhibitory concentration (IC50) is the concentration at which a drug exerts half of its maximal inhibitory effect against target cells. It can be determined by various methods that require applying additional reagents or lysing the cells. Here, we describe a label-free Sobel-edge-based method, which we name SIC50, for the evaluation of IC50. SIC50 classifies pre-processed phase-contrast images with a state-of-art vision transformer and allows for the continuous assessment of IC50 in a faster and more cost-efficient manner. We have validated this method using four drugs and 1536-well plates, as well as built a first-of-its-kind web application. We anticipate this method will assist in the high-throughput screening of chemical libraries (e.g., small molecule drugs, siRNA, and microRNA and drug discovery.

bioengineering↗

Capturing the Hierarchically Assorted Modules of Protein Interaction in the Organized Nucleome

Nuclear proteins are major constituents and key regulators of the topological organization of nucleome. To elucidate the global connectivity of nucleomic proteins and to decipher the hierarchically organized modules of protein interaction that are involved in nucleomic organization and nuclear events, both formaldehyde and CBDPS crosslinkers were applied sequentially on the in vivo prefixed nuclei to perform a double chemical crosslinking with mass spectrometry (XL-MS) analysis. The integration of dimethyl-labelling with XL-MS generated a quantitative XL-MS workflow (qXL-MS) that consequently identified 5,340 cross-linked peptides (crosslinks) from nucleome. These crosslinks were construed into 1,297 nuclear protein-protein interactions (PPIs), from which discovered were 250 and 26 novel interactors of histones and nucleolar box C/D snoRNP complex, respectively. MONET-based modulomic analysis of their Arabidopsis orthoglous PPIs constructed 27 and 24 master nuclear protein interaction modules (NPIMs) that contain the condensate-forming protein(s) and the intrinsically disordered region (IDR)-containing proteins, respectively. These NPIMs successfully captured the previously reported nuclear protein complexes and nuclear bodies in nucleome. Surprisingly, modulomic analysis showed that these NPIMs were hierarchically assorted into four communities of NPIMs in nucleome including Genome Community and Nucleolus Community. The qXL-MS-based quantitative interactomics finally revealed 17 Hormone-specific module variants participating in a broad range of nuclear events. Thus, this integrated pipeline of qXL-MS and MONET modulomics, named as CHAMPION, is capable of capturing both nuclear protein complexes and nuclear bodies, constructing the topological architecture of protein interaction modules and module variants in nucleome and probably of mapping the protein compositions of condensates. HighlightsO_LIThe formaldehyde and CBDPS crosslinkers coupled qXL-MS discovered 5,340 crosslinked peptides. These crosslinks were construed into 1,297 nuclear protein-protein interactions (PPIs), protein components of which contained 250 and 26 novel interactors of histone octamer and nucleolar box C/D snoRNP complex, respectively, in the intricately organized nucleome. C_LIO_LIThe MONET-based modulomic analysis of these crosslinks captured 95 nuclear protein interaction modules (NPIMs), a portion of which contain both the condensate-forming and the intrinsically disordered region (IDR)-containing proteins. Especially, some NPIMs captured 6 previously reported nuclear protein complexes. C_LIO_LIA number of Hormone-specific module variants were identified by modulomics upon hormone treatment using the hormone significantly up-regulated crosslinks from qXL-MS. Several PPIs and NPIMs have been substantiated with alternative biological experiments. C_LIO_LIThis CHAMPION pipeline has partitioned these NPIMs into four hierarchically and topologically organized communities in nucleome. The molecular functions of those proteins partitioned into C1 and C2 community are specialized in genome organization and nucleolar functions, respectively. C_LI

bioinformatics↗

Development of highly potent non-covalent inhibitors of SARS-CoV-2 3CLpro

The SARS-CoV-2 virus is the causal agent of the ongoing pandemic of coronavirus disease 2019 (COVID-19). There is an urgent need for potent, specific antiviral compounds against SARS-CoV-2. The 3C-like protease (3CLpro) is an essential enzyme for the replication of SARS-CoV-2 and other coronaviruses, and thus is a target for coronavirus drug discovery. Nearly all inhibitors of coronavirus 3CLpro reported so far are covalent inhibitors. Here, we report the development of specific, non-covalent inhibitors of 3CLpro. The most potent one, WU-04, effectively blocks SARS-CoV-2 replications in human cells with EC50 values in the 10-nM range. WU-04 also inhibits the 3CLpro of SARS-CoV and MERS-CoV with high potency, indicating that it is a pan-inhibitor of coronavirus 3CLpro. WU-04 showed anti-SARS-CoV-2 activity similar to that of PF-07321332 (Nirmatrelvir) in K18-hACE2 mice when the same dose was administered orally. Thus, WU-04 is a promising drug candidate for coronavirus treatment. One-Sentence SummaryA oral non-covalent inhibitor of 3C-like protease effectively inhibits SARS-CoV-2 replication.

microbiology↗

Neutralization of Omicron BA.4/BA.5 and BA.2.75 by Booster Vaccination or BA.2 Breakthrough Infection Sera

Many new Omicron sub-lineages have been reported to evade neutralizing antibody response, including BA.2, BA.2.12.1, BA.4 and BA.5. Most recently, another emerging sub-lineage BA.2.75 has been reported in multiple countries. In this study, we constructed a comprehensive panel of pseudoviruses (PsVs), including wild-type, Delta, BA.1, BA.1.1, BA.2, BA.3, BA.2.3.1, BA.2.10.1, BA.2.12.1, BA.2.13, BA.2.75 and BA.4/BA.5, with accumulate coverage reached 91% according to the proportion of sequences deposited in GISAID database since Jan 1st, 2022. We collected serum samples from healthy adults at day14 post homologous booster with BBIBP-CorV, or heterologous booster with ZF2001, primed with two doses of BBIBP-CorV, or from convalescents immunized with three-dose inactivated vaccines prior to infection with Omicron BA.2, and tested their neutralization activity on this panel of PsVs. Our results demonstrated that all Omicron sub-lineages showed substantial evasion of neutralizing antibodies induced by vaccination and infection, although BA.2.75 accumulated the largest number of mutations in its spike, BA.4 and BA.5 showed the strongest serum escape. However, BA.2 breakthrough infection could remarkably elevated neutralization titers against all different variants, especially titers against BA.2 and its derivative sub-lineages.

immunology↗

MetaTiME: Meta-components of the Tumor Immune Microenvironment

Recent advances in single-cell RNA sequencing have revealed heterogeneous cell types and gene expression states in the non-cancerous cells in tumors. The integration of multiple scRNA-seq datasets across tumors can reveal common cell types and states in the tumor microenvironment (TME). We developed a data driven framework, MetaTiME, to overcome the limitations in resolution and consistency that result from manual labelling using known gene markers. Using millions of TME single cells, MetaTiME learns meta-components that encode independent components of gene expression observed across cancer types. The meta-components are biologically interpretable as cell types, cell states, and signaling activities. By projecting onto the MetaTiME space, we provide a tool to annotate cell states and signature continuums for TME scRNA-seq data. Leveraging epigenetics data, MetaTiME reveals critical transcriptional regulators for the cell states. Overall, MetaTiME learns data-driven meta-components that depict cellular states and gene regulators for tumor immunity and cancer immunotherapy.

genomics↗

Neuronal dynamics of the default mode network and anterior insular cortex: Intrinsic properties and modulation by salient stimuli

The default mode network (DMN) is closely associated with self-referential mental functions and its dysfunction is implicated in many neuropsychiatric disorders. However, the neurophysiological properties and task-based functional organization of the rodent DMN are poorly understood, limiting its translational utility. Here, we combine fiber-photometry with fMRI and computational modeling to characterize dynamics of putative rodent DMN nodes and their interactions with the anterior insular cortex (AI) of the salience network. We reveal neuronal activity changes in AI and DMN nodes prior to fMRI-derived DMN activations and uncover cyclical transition patterns between spatiotemporal neuronal activity states. Finally, we demonstrate that salient oddball stimuli suppress the DMN and enhance AI neuronal activity, and that the AI causally inhibits the retrosplenial cortex, a prominent DMN node. These findings elucidate previously unknown properties regarding the neurobiological foundations of the rodent DMN and its modulation by salient stimuli, paving the way for future translational studies. HighlightsO_LIConcurrent measurement of neuronal (GCaMP) and fMRI signals in retrosplenial, cingulate, prelimbic, and anterior insula cortices C_LIO_LIGCaMP signals reveal neuronal antagonism between AI and fMRI-derived DMN activation and deactivation C_LIO_LIGCaMP signals reveal salient oddball stimuli-induced suppression of prelimbic, cingulate and retrosplenial cortices, and activation of anterior insular cortex C_LIO_LIAnterior insular cortex causally inhibits retrosplenial cortex during processing of salient oddball stimuli C_LIO_LIFindings delineate neurofunctional organization of the rodent DMN and provide a more informed model for translational studies C_LI

neuroscience↗

Fat Extract Modulates Calcium Signaling and Protects Against Hyperactive Osteoclastogenesis in Bone Remodeling with Antioxidant Capacity

Osteoclasts are cells which are primarily involved in bone remodeling and osteolytic bone diseases. Hyperactive osteoclastogenesis leads to pathological bone loss and microarchitectural deterioration, particularly in postmenopausal osteoporosis. However, given the limitations of current first-line osteoclast inhibitors, there is an urgent need for a novel antiresorptive agent with higher efficiency and fewer side effects. Cell-free fat extract (CEFFE) is the liquid fraction obtained from human adipose tissues, which are enriched with a variety of cytokines and growth factors. This study aims to explore its pharmaceutical effect on hyperactive osteoclast formation in vivo and in vitro. CEFFE exhibits excellent potentials to attenuate osteoclast-associated bone loss in an ovariectomy (OVX) mouse model and to inhibit RANKL-induced osteoclastogenesis in primary bone marrow-derived monocytes. Furthermore, the cationic protein fraction of CEFFE (CEFFE-Cation) is identified as the main inhibitory component in osteoclast formation assay. Excessive reactive oxygen species (ROS) production is the main cause of osteoclast overactivation. According to LC-MS/MS analysis, the CEFFE-Cation fraction mainly consists of various antioxidant enzymes, extracellular matrix, and secreted cytokines, which endow it with a superior antioxidant capacity. Ca2+ signaling contributes to osteoclast maturation. In addition to scavenging ROS, CEFFE-Cation is also capable of mitigating Ca2+ oscillation, calcineurin activation, and subsequent NFATc1 nuclear translocation during osteoclastogenesis. Overall, this study elucidates the promising translational potential of CEFFE as a next-generation personalized antiresorptive agent for osteolytic bone disease treatment.

pathology↗

Coevolution-based prediction of key allosteric residues for protein function regulation

Allostery is fundamental to many biological processes. Due to the distant regulation nature, how allosteric mutations, modifications and effector binding impact protein function is difficult to forecast. In protein engineering, remote mutations cannot be rationally designed without large scale experimental screen. Allosteric drugs have raised much attention due to their high specificity and possibility of overcoming existing drug-resistant mutations. However, optimization of allosteric compounds remains challenging. Here, we developed a novel computational method KeyAlloSite to predict allosteric site and to identify key allosteric residues (allo-residues) based on the evolutionary coupling model. We found that protein allosteric sites are strongly coupled to orthosteric site compared to non-functional sites. We further inferred key allo-residues by pairwise comparing the difference of evolutionary coupling scores of each residue in the allosteric pocket with the functional site. Our predicted key allo-residues are in accordance with previous experimental studies for typical allosteric proteins like BCR-ABL1, Tar and PDZ3, as well as key cancer mutations. We also showed that KeyAlloSite can be used to predict key allosteric residues distant from the catalytic site that are important for enzyme catalysis. Our study demonstrates that weak coevolutionary couplings contain important information of protein allosteric regulation function. KeyAlloSite can be applied in studying the evolution of protein allosteric regulation, designing and optimizing allosteric drugs, performing functional protein design and enzyme engineering.

biochemistry↗

Multi-Molecular Hyperspectral PRM-SRS Imaging

Lipids play crucial roles in many biological processes under physiological and pathological conditions. Mapping spatial distribution and examining metabolic dynamics of different lipids in cells and tissues in situ are critical for understanding aging and diseases. Commonly used imaging methods, including mass spectrometry-based technologies or labeled imaging techniques, tend to disrupt the native environment of cells/tissues and have limited spatial or spectral resolution, while traditional optical imaging techniques still lack the capacity to distinguish chemical differences between lipid subtypes. To overcome these limitations, we developed a new hyperspectral imaging platform that integrates a Penalized Reference Matching algorithm with Stimulated Raman Scattering (PRM-SRS) microscopy. With this new approach, we directly visualized and identified multiple lipid species in cells and tissues in situ with high chemical specificity and subcellular resolution. High density lipoprotein (HDL) particles containing non-esterified cholesterol was observed in the kidney, indicating that these pools of cholesterol are ectopic deposits, or have yet to be enriched. We detected a higher Cholesterol to phosphatidylethanolamine (PE) ratio inside the granule cells of hippocampal samples in old mice, suggesting altered membrane lipid synthesis and metabolism in aging brains. PRM-SRS imaging also revealed subcellular distributions of sphingosine and cardiolipin in the human brain sample. Compared with other techniques, PRM-SRS demonstrates unique advantages, including faster data processing and direct user-defined visualization with enhanced chemical specificity for distinguishing clinically relevant lipid subtypes in different organs and species. Our method has broad applications in multiplexed cell and tissue imaging.

bioengineering↗

Bioinformatics analysis of immune-related prognostic genes and immunotherapy in renal clear cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is an immunogenic tumor and investigating the immunorelated genes is of great significance. To investigate the immunoprognostic genes of ccRCC, we analyzed the data assimilated from a public database (The Cancer Genome Atlas (TCGA) database and the gene expression omnibus (GEO) database) using bioinformatics. Then, a immunoprognosis model was constructed to identify 4 hub genes with moderate predictive values for the prognosis of ccRCC patients. Interestingly, these 4 genes were associated with the prognosis of ccRCC patients based on Oncomine and Gena Expression Profiling Interactive Analysis (GEPIA) databases. The correlation analysis between the immune infiltrate, immune checkpoints, and immunotherapy and this immunoprognosis model showed that immune infiltrate and could predict the immunotherapy effects. We also conducted a quantitative real-time polymerase chain reaction analysis and found that the expressions of 3 hub genes were associated with tumor progression (P<0.1). In conclusion, 4 genes that may serve as potential biomarkers in ccRCC were identified with respect to prognosis.

cancer biology↗

Deep generative modeling and clustering of single cell Hi-C data

Deciphering 3D genome conformation is important for understanding gene regulation and cellular function at a spatial level. The recent advances of single cell Hi-C technologies have enabled the profiling of the 3D architecture of DNA within individual cell, which allows us to study the cell-to-cell variability of 3D chromatin organization. Computational approaches are in urgent need to comprehensively analyze the sparse and heterogeneous single cell Hi-C data. Here, we proposed scDEC-Hi-C, a new framework for single cell Hi-C analysis with deep generative neural networks. scDEC-Hi-C outperforms existing methods in terms of single cell Hi-C data clustering and imputation. Moreover, the generative power of scDEC-Hi-C could help unveil the heterogeneity of chromatin architecture across different cell types. We expect that scDEC-Hi-C could shed light on deepening our understanding of the complex mechanism underlying the formation of chromatin contacts. scDEC-Hi-C is freely available at https://github.com/kimmo1019/scDEC-Hi-C. Key pointsO_LIscDEC-Hi-C provides an end-to-end framework based on autoencoder and deep generative model to comprehensively analyze single cell Hi-C data, including low-dimensional embedding and clustering. C_LIO_LIThrough a series of experiments including single cell Hi-C data clustering and structural difference identification, scDEC-Hi-C demonstrates suprioir performance over existing methods. C_LIO_LIIn the downstream analysis of chromatin loops from single cell Hi-C data, scDEC-Hi-C is capable of significantly enhancing the ability for identifying single cell chromatin loops by data imputation. C_LI

bioinformatics↗

FOXP2 confers oncogenic effects in prostate cancer through activating MET signalling

Identification oncogenes is fundamental to revealing the molecular basis of cancer. Here, we found that FOXP2 is overexpressed in human prostate cancer cells and prostate tumors, but its expression is absent in normal prostate epithelial cells and low in benign prostatic hyperplasia. To date, little is known regarding the link of FOXP2 to prostate cancer. We observed that high FOXP2 expression and frequent amplification are significantly associated with high Gleason score. Ectopic expression of FOXP2 induces malignant transformation of mouse NIH3T3 fibroblasts and human prostate epithelial cell RWPE-1. Conversely, FOXP2 knockdown suppresses the proliferation of prostate cancer cells. Transgenic overexpression of FOXP2 in the mouse prostate causes prostatic intraepithelial neoplasia. Overexpression of FOXP2 aberrantly activates oncogenic MET signalling and inhibitors targeting MET signalling effectively reverts the FOXP2-induced oncogenic phenotype. Additionally, the novel recurrent FOXP2-CPED1 fusion identified in prostate tumors results in high expression of truncated FOXP2, which exhibit a similar capacity for malignant transformation. Together, our data demonstrate for the first time that FOXP2 is an oncogene involved in tumorigenicity of prostate.

cancer biology↗

In-depth investigation of microRNA-mediated cross-kingdom regulation between Asian honey bee and microsporidian

Asian honey bee Apis cerana is the original host for Nosema ceranae, a unicellular fungal parasite that causes bee nosemosis throughout the world. Currently, interaction between A. cerana and N. ceranae is largely unknown. Here, based on our previously gained high-quality RNA-seq and small RNA-seq data from N. ceranae-infected A. c. cerana workers midguts and clean spores, differentially expressed mRNAs (DEmiRNAs) in N. ceranae targeted by DEmiRNAs in host midguts and A. c. cerana DEmRNAs targeted by microsporidian DEmiRNAs were predicted using bioinformatics, and then target DEmRNAs in microsporidian and host were annotated and investigated, with a focus on targets involved in N. ceranae glycolysis/glyconeogenesis and virulence factors as well as A. c. cerana energy mechanism and immune response. Its found that 97 down-regulated (60 up-regulated) mRNAs in NcCKM vs NcTM1 were potentially targeted by eight up-regulated (six down-regulated) miRNAs in AcCKMI1 vs AcTMI1, 44 down-regulated (15 up-regulated) mRNAs in NcCKM vs NcTM2 were putative targets of seven up-regulated (two down-regulated) miRNAs in AcCKMI2 vs AcTMI2. Additionally, miR-60-y and miR-676-y were found to up-regulate in AcCKMI1 vs AcTMI1 and target genes engaged in spore wall protein and glycolysis/gluconeogenesis, while miR-60-y in AcCKMI1 vs AcTMI1 was up-regulated and potentially targeted a glycolysis/gluconeogenesis-associated gene. Comparatively, 343 down-regulated (138 up-regulated) mRNAs in AcCKM1 vs AcTM1 were putative targets of 121 up-regulated (112 down-regulated) miRNAs in NcCKMI vs NcTMI1, 247 down-regulated (110 up-regulated) mRNAs were putatively targeted by 110 up-regulated (104 down-regulated) miRNAs in NcCKMI vs NcTMI2. Further analysis showed that 31 up-regulated miRNAs in NcCKMI vs NcTMI1 potentially targeted 12 down-regulated mRNAs in AcCKM1 vs AcTM1, which were involved in five immune-related pathways such as phagasome and Jak-STAT signaling pathway, whereas nine up-regulated miRNAs in NcCKMI vs NcTMI2 putatively targeted five down-regulated mRNAs in AcCKM2 vs AcTM2, which were engaged in three immune-related pathways including endocytosis, lysosomes, and regulation of autophagy. In addition, miR-21-x was observed to up-regulate in NcCKMI vs NcTMI1 and target a oxidative phosphorylation-related gene. Finally, potential targeting relationship between two host DEmiRNAs-microsporidian DEmRNAs pairs and two microsporidian DEmiRNAs-host DEmRNAs pairs were verified on basis of RT-qPCR. Our findings not only lay a foundation for exploring the molecular mechanism underlying cross-kingdom regulation between A. c. cerana workers and N. ceranae, but also offer valuable insights into Asian honey bee-microsporidian interaction.

pathology↗

Liver Endothelium Microenvironment Promotes HER3-mediated Cell Growth in Pancreatic ductal adenocarcinoma

[~]90% metastatic pancreatic ductal adenocarcinoma (mPDAC) occurs in the liver, and the 5-year survival rate for patients with mPDAC is only at 3%. We previously reported that liver endothelial cells (ECs) secreted soluble factors to promote colorectal cancer cell survival in a paracrine fashion. However, the effects of liver ECs on mPDAC have not been elucidated. In this study, we used primary ECs from non-neoplastic liver tissues. We treated PDAC cells with conditioned medium (CM) from liver ECs, with CM from PDAC as controls, and determined that liver EC-secreted factors increased PDAC cell growth. Using an unbiased receptor tyrosine kinase array, we identified human epidermal growth factor receptor 3 (HER3, also known as ErbB3) as a key mediator in EC-induced growth in PDAC cells that have HER3 expression (HER3 +ve). We found that EC-secreted neuregulins activated the HER3-AKT signaling axis, and that depleting neuregulins from EC CM or blocking HER3 with an antibody, seribantumab, attenuated EC-induced proliferation in HER3 +ve PDAC cells, but not in cells without HER3 expression. Furthermore, we determined that EC CM increased PDAC xenograft growth in vivo, and that seribantumab blocked EC-induced growth in xenografts with HER3 expression. These findings elucidated a paracrine role of liver ECs in promoting PDAC cell growth, and identified the HER3-AKT axis as a key mediator in EC-induced functions in PDAC cells with HER3 expression. Implicationsover 70% mPDAC express HER3. This study suggests the potential of using HER3-targeted therapies for treating patients with HER3 +ve mPDAC.

cancer biology↗