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Background: Attenuated Listeria monocytogenes (Lm) has been widely used as a vaccine vector in the prevention and treatment of pathogen infection and tumor diseases. In addition, previous studies have proved that the attenuated Lm can protect zebrafish from Vibrio infections, indicating that the attenuated Lm has a good application prospect in the field of aquatic vaccines. However, the limitation mainly lies in the lack of a set of well-characterized natural promoters for the expression of target antigens in attenuated Lm., Results: In our study, candidate strong promoters were identified through RNA-seq analysis, and characterized in Lm through enhanced green fluorescent protein (EGFP). Nine native promoters that showed stronger activities than that of the known strong promoter P 36 under two tested temperatures (28 and 37 °C) were selected from the set, and P 29 with the highest activity was 24-fold greater than P 36 . Furthermore, we demonstrated that P 29 could initiate EGFP expression in ZF4 cells and zebrafish embryos., Conclusions: This well-characterized promoter library can be used to fine-tune the expression of different proteins in Lm. The availability of a well-characterized promoter toolbox of Lm is essential for the analysis of yield increase for biotechnology applications., (© 2021. The Author(s).)

Background: T-lymphoma invasion and metastasis-inducing protein 1 (Tiam1) has been implicated in tumor occurrence and progression. Recent studies have shown that high expression levels of Tiam1 protein appear to be associated with the progression of numerous human tumors. This study attempted to explore the role of Tiam1 protein in tumor progression and the prognostic evaluation of breast cancer., Methods: The localization of the Tiam1 protein was determined in the MDA-MB-231 breast cancer cell line using immunofluorescence (IF) staining. In addition, a total of 283 breast tissue samples, including 153 breast cancer tissues, 67 ductal carcinoma in situ (DCIS) and 63 adjacent non-tumor breast tissues, were analyzed by immunohistochemical (IHC) staining of the Tiam1 protein. The correlation between Tiam1 expression and clinicopathological characteristics was evaluated by Chi-square test and Fisher's exact tests. Disease-free survival (DFS) and 10-year overall survival (OS) rates were calculated by the Kaplan-Meier method. Additionally, univariate and multivariate analyses were performed by the Cox proportional hazards regression models., Results: Tiam1 protein showed a mainly cytoplasmic staining pattern in breast cancer cells; however, nuclear staining was also observed. Tiam1 protein expression was significantly higher in breast cancers (42.5 %, 65/153) and DCIS (40.3 %, 27/67) than in adjacent non-tumor tissues (12.7 %, 8/63). In addition, Tiam1 associated with tumor stage and Ki-67 expression, but negatively correlated with receptor tyrosine-protein kinase erbB-2 (Her2) expression. Moreover, survival analyses showed that DFS and 10-year OS rates were significantly lower in breast cancer patients with high Tiam1 expression than those with low Tiam1 expression. Univariate analysis suggested that molecular types, clinical stage, Her2 expression levels and Tiam1 expression levels were also significantly associated with DFS and 10-year OS rates of breast cancer patients. Furthermore, multivariate analysis suggested that Tiam1 expression is a significant independent prognostic factor along with tumor stage in patients with breast cancer., Conclusions: Tiam1 expression is frequently up-regulated in breast cancer. Tiam1 expression correlated with clinicopathological parameters, suggesting that it may be a useful prognostic biomarker and potential therapeutic target for patients with breast cancer.

Background: As a member of the tumor necrosis factor receptor (TNFR) protein superfamily, equine lentivirus receptor 1 (ELR1) has been shown to be expressed in various equine cells that are permissive for equine infectious anemia virus (EIAV) replication. The EIAV Tat protein (eTat) activates transcription initiated at the viral long terminal repeat (LTR) promoter through a unique mechanism that requires the recruitment of the equine cyclin T1 (eCT1) cofactor into the viral TAR RNA target element. In vitro studies have demonstrated that mouse fibroblast cell lines (e.g., NIH 3T3 cells) that express the EIAV receptor ELR1 and eCT1 support the productive replication of EIAV. Therefore, we constructed transgenic eCT1- and ELR1-expressing mice to examine whether they support in vivo EIAV replication., Findings: For the first time, we constructed mice transgenic for ELR1 and eCT1. Real-time reverse transcription polymerase chain reaction (RT-PCR) and Western blot analysis confirmed that ELR1 and eCT1 were expressed in the transgenic mouse tissues, particularly in the intestines, spleen and lymph nodes. Consistent with the results of EIAV infection in NIH 3T3 cells expressing ELR1 and eCT1, mouse embryonic fibroblasts (MEFs) from the transgenic mice could support EIAV replication. More importantly, this virus could infect and replicate in mouse blood monocyte-derived macrophages (mMDMs). Macrophages are the principle target cell of EIAV in its natural hosts. Furthermore, after the transgenic mice were inoculated with EIAV, the virus could be detected not only in the plasma of the circulating blood but also in multiple organs, among which, the spleen and lymph nodes were the predominant sites of EIAV replication. Finally, we found that consistent with high viral replication levels, the relevant pathological changes occurred in the spleen and lymph nodes., Conclusions: Our results show that mice transgenic for ELR1 and eCT1 are susceptible to EIAV infection and replication. Further, EIAV infection can cause lesions on the spleen and lymph nodes, similar to those frequently observed in horses, the natural hosts. Therefore, ELR1 and eCT1 are essential in vivo for EIAV invasion and replication.

Background: Public resources of chemical compound are in a rapid growth both in quantity and the types of data-representation. To comprehensively understand the relationship between the intrinsic features of chemical compounds and protein targets is an essential task to evaluate potential protein-binding function for virtual drug screening. In previous studies, correlations were proposed between bioactivity profiles and target networks, especially when chemical structures were similar. With the lack of effective quantitative methods to uncover such correlation, it is demanding and necessary for us to integrate the information from multiple data sources to produce an comprehensive assessment of the similarity between small molecules, as well as quantitatively uncover the relationship between compounds and their targets by such integrated schema., Results: In this study a multi-view based clustering algorithm was introduced to quantitatively integrate compound similarity from both bioactivity profiles and structural fingerprints. Firstly, a hierarchy clustering was performed with the fused similarity on 37 compounds curated from PubChem. Compared to clustering in a single view, the overall common target number within fused classes has been improved by using the integrated similarity, which indicated that the present multi-view based clustering is more efficient by successfully identifying clusters with its members sharing more number of common targets. Analysis in certain classes reveals that mutual complement of the two views for compound description helps to discover missing similar compound when only single view was applied. Then, a large-scale drug virtual screen was performed on 1267 compounds curated from Connectivity Map (CMap) dataset based on the fused similarity, which obtained a better ranking result compared to that of single-view. These comprehensive tests indicated that by combining different data representations; an improved assessment of target-specific compound similarity can be achieved., Conclusions: Our study presented an efficient, extendable and quantitative computational model for integration of different compound representations, and expected to provide new clues to improve the virtual drug screening from various pharmacological properties. Scripts, supplementary materials and data used in this study are publicly available at http://lifecenter.sgst.cn/fusion/.

Background: Gene-set analysis evaluates the expression of biological pathways, or a priori defined gene sets, rather than that of individual genes, in association with a binary phenotype, and is of great biologic interest in many DNA microarray studies. Gene Set Enrichment Analysis (GSEA) has been applied widely as a tool for gene-set analyses. We describe here some critical problems with GSEA and propose an alternative method by extending the individual-gene analysis method, Significance Analysis of Microarray (SAM), to gene-set analyses (SAM-GS)., Results: Using a mouse microarray dataset with simulated gene sets, we illustrate that GSEA gives statistical significance to gene sets that have no gene associated with the phenotype (null gene sets), and has very low power to detect gene sets in which half the genes are moderately or strongly associated with the phenotype (truly-associated gene sets). SAM-GS, on the other hand, performs very well. The two methods are also compared in the analyses of three real microarray datasets and relevant pathways, the diverging results of which clearly show advantages of SAM-GS over GSEA, both statistically and biologically. In a microarray study for identifying biological pathways whose gene expressions are associated with p53 mutation in cancer cell lines, we found biologically relevant performance differences between the two methods. Specifically, there are 31 additional pathways identified as significant by SAM-GS over GSEA, that are associated with the presence vs. absence of p53. Of the 31 gene sets, 11 actually involve p53 directly as a member. A further 6 gene sets directly involve the extrinsic and intrinsic apoptosis pathways, 3 involve the cell-cycle machinery, and 3 involve cytokines and/or JAK/STAT signaling. Each of these 12 gene sets, then, is in a direct, well-established relationship with aspects of p53 signaling. Of the remaining 8 gene sets, 6 have plausible, if less well established, links with p53., Conclusion: We conclude that GSEA has important limitations as a gene-set analysis approach for microarray experiments for identifying biological pathways associated with a binary phenotype. As an alternative statistically-sound method, we propose SAM-GS. A free Excel Add-In for performing SAM-GS is available for public use.

Background: Though the CXCR2 chemokine receptor is known to play a key role in cancer growth and response to therapy, a direct link between expression of CXCR2 in tumor progenitor cells during induction of tumorigenesis has not been established. Methods: To characterize the role of CXCR2 during melanoma tumorigenesis, we generated tamoxifen-inducible tyrosinase-promoter driven BrafV600E/Pten−/−/Cxcr2−/− and NRasQ61R/INK4a−/−/Cxcr2−/− melanoma models. In addition, the effects of a CXCR1/CXCR2 antagonist, SX-682, on melanoma tumorigenesis were evaluated in BrafV600E/Pten−/− and NRasQ61R/INK4a−/− mice and in melanoma cell lines. Potential mechanisms by which Cxcr2 affects melanoma tumorigenesis in these murine models were explored using RNAseq, mMCP-counter, ChIPseq, and qRT-PCR; flow cytometry, and reverse phosphoprotein analysis (RPPA). Results: Genetic loss of Cxcr2 or pharmacological inhibition of CXCR1/CXCR2 during melanoma tumor induction resulted in key changes in gene expression that reduced tumor incidence/growth and increased anti-tumor immunity. Interestingly, after Cxcr2 ablation, Tfcp2l1, a key tumor suppressive transcription factor, was the only gene significantly induced with a log2 fold-change greater than 2 in these three different melanoma models. Conclusions: Here, we provide novel mechanistic insight revealing how loss of Cxcr2 expression/activity in melanoma tumor progenitor cells results in reduced tumor burden and creation of an anti-tumor immune microenvironment. This mechanism entails an increase in expression of the tumor suppressive transcription factor, Tfcp2l1, along with alteration in the expression of genes involved in growth regulation, tumor suppression, stemness, differentiation, and immune modulation. These gene expression changes are coincident with reduction in the activation of key growth regulatory pathways, including AKT and mTOR. [ABSTRACT FROM AUTHOR]