Molecular Characterization and Expression Analysis of ftr01, ftr42, and ftr58 in Zebrafish (Danio rerio)

Tripartite motif(TRIM) proteins were shown to play an important role in innate antiviral immunity. FinTRIM(ftr) is a new subset of TRIM genes that do not possess obvious orthologs in higher vertebrates. However, little is known about its function. In this study, we used bioinformatic analysis to examine the phylogenetic relationships and conserved domains of zebrafish(Danio rerio) ftr01, ftr42, and ftr58, as well as qualitative real-time PCR to examine their expression patterns in zebrafish embryonic fibroblast(ZF4) cells and zebrafish tissues. Sequence analysis showed that the three finTRIMs are highly conserved, and all contain a RING domain, B-box domain, and SPRY-PRY domain. In addition, ftr42 and ftr58 had one coiled-coil domain(CCD), whereas ftr01 had two CCDs. Tissue expression analysis revealed that the m RNA level of ftr01 was the highest in the liver, whereas those of ftr42 and ftr58 were the highest in the gill; the expression of thesefinTRIMs was clearly upregulated not in the eyes, but in the liver, spleen, kidney, gill, and brain of zebrafish following spring viremia of carp virus(SVCV) infection. Similarly, the expression of these three finTRIM genes also increased in ZF4 cells after SVCV infection. Our study revealed that ftr01, ftr42, and ftr58 may play an important role in antiviral immune responses, and these findings validate the need for more in-depth research on the finTRIM family in the future.     

Resolving Cell Fate Decisions during Somatic Cell Reprogramming by Single-Cell RNA-Seq

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Demethylation of the Protein Phosphatase PP2A Promotes Demethylation of Histones to Enable Their Function as a Methyl Group Sink

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Classification of established atopic dermatitis in children with the in vivo imaging methods

Atopic dermatitis (AD) is a cutaneous disease resulting from a defective barrier and dysregulated immune response. The severity scoring of atopic dermatitis (SCORAD) is used to classify AD. Noninvasive imaging approaches supplementary to SCORAD were investigated. Cr:forsterite laser‐based microscopy was employed to analyze endogenous third‐harmonic generation (THG) and second‐harmonic generation (SHG) signals from skin. Imaging parameters were compared between different AD severities. Three‐dimensional reconstruction of imaged skin layers was performed. Finally, statistic models from quantitative imaging parameters were developed for predicting disease severity. Our data demonstrate that THG signal intensity of lesional skin in AD were significantly increased and was positively correlated with AD severity. Characteristic gray level co‐occurrence matrix (GLCM) values were observed in more severe AD. In the 3D reconstruction video, individual dermal papilla and obvious fibrosis in the upper papillary dermis were easily identified. Our estimation models could predict the disease severity of AD patients with an accuracy of nearly 85%. The THG signal intensity and characteristic GLCM patterns are associated with AD severity and can serve as quantitative predictive parameters. Our imaging approach can be used to identify the histopathological changes of AD objectively, and to complement the SCORAD index, thus improving the accuracy of classifying AD severity.      

Detecting oxygen consumption in the proximity of Saccharomyces cerevisiae cells using self-assembled fluorescent nanosensors

We describe a strategy for the preparation and self-assembly of fluorescent nanosensors onto Saccharomyces cerevisiae cell surfaces for dynamically measuring oxygen concentration in the proximity of living cells. Amine functionalized polystyrene nanobeads were impregnated with an oxygen-sensitive ruthenium(II) complex and the beads' surface was coated with polyethylenimine. The resulting nanosensors were assembled on individual S. cerevisiae cells in a controlled manner at physiological pH for continuously monitoring oxygen consumption. This approach exemplifies a general scheme for assembling fluorescent nanosensors on cells for the non-invasive, reversible, and real-time measurement of other physiologically relevant processes, such as the efflux of protons and carbon dioxide, or the influx of glucose.     

Ginsenoside Rb3 attenuates skin flap ischemia-reperfusion damage by inhibiting STING-IRF3 signaling

Journal of Molecular Histology - We investigate the protective effect of ginsenoside Rb3 on skin flap microvasculature following ischemia-reperfusion (I/R) injury and its regulatory mechanism. We...     

High NEK2 confers to poor prognosis and contributes to cisplatin-based chemotherapy resistance in nasopharyngeal carcinoma

Nasopharyngeal carcinoma (NPC) is a common malignant tumor in southern China and Southeast Asia, but the molecular mechanism of its pathogenesis is poorly understood. Our previous work demonstrated that NEK2 is overexpressed in multiple cancers. However, how NEK2 involves in NPC development remains to be elucidated. In this study, we firstly identified NEK2, located at +1q32-q33, a late event in NPC pathogenesis, overexpressed in the stage III-IV and paired sequential recurrent patients with NPC by immunohistochemistry. Furthermore, Kaplan-Meier analysis indicated high NEK2 conferred an inferior overall survival in NPC. In addition, cisplatin experiments with cell counting kit-8, colony formation, and a xenograft mice model of NPC demonstrated that NEK2 contributed to proliferation and cisplatin resistance in vitro and in vivo. On the contrary, downregulation of NEK2 by short hairpin RNA inhibited NPC cell growth and increased the sensitivity of cisplatin treatment in vitro. Thus, increased expression of NEK2 protein could not be predicted for poor survival but used as a novel biomarker for recurrence of NPC. Targeting NEK2 has the potential to eradicate the cisplatin-based chemotherapy resistant NPC cells.     

Scalable remote homology detection and fold recognition in massive protein networks

The global connectivities in very large protein similarity networks contain traces of evolution among the proteins for detecting protein remote evolutionary relations or structural similarities. To investigate how well a protein network captures the evolutionary information, a key limitation is the intensive computation of pairwise sequence similarities needed to construct very large protein networks. In this article, we introduce label propagation on low-rank kernel approximation (LP-LOKA) for searching massively large protein networks. LP-LOKA propagates initial protein similarities in a low-rank graph by Nyström approximation without computing all pairwise similarities. With scalable parallel implementations based on distributed-memory using message-passing interface and Apache-Hadoop/Spark on cloud, LP-LOKA can search protein networks with one million proteins or more. In the experiments on Swiss-Prot/ADDA/CASP data, LP-LOKA significantly improved protein ranking over the widely used HMM-HMM or profile-sequence alignment methods utilizing large protein networks. It was observed that the larger the protein similarity network, the better the performance, especially on relatively small protein superfamilies and folds. The results suggest that computing massively large protein network is necessary to meet the growing need of annotating proteins from newly sequenced species and LP-LOKA is both scalable and accurate for searching massively large protein networks.