Artemisinin Analogue SM934 Ameliorates Murine Experimental Autoimmune Encephalomyelitis through Enhancing the Expansion and Functions of Regulatory T Cell

Background

Artemisinin analogue SM934 was previously reported to possess immunosuppressive properties. The aim of this study was to determine the effects and the underlying mechanisms of SM934 in murine experimental autoimmune encephalomyelitis (EAE).

Methods

Female C57BL/6 mice immunized with MOG_35–55 were treated with or without SM934, then the clinical scores and other relevant parameters were assessed. Th1, Th17 and regulatory T (Treg) cell profiles were determined through ELISA, qRT-PCR, flow cytometry and BrdU incorporation assay. The effects of SM934 on Th1, Th17 and Treg cells differentiation were explored through intracellular staining and flow cytometry examination.

Results

In vivo, administration of SM934 significantly inhibited the development of EAE and suppressed the elevation of serum IL-17. Ex vivo, upon antigen-recall stimulation, IL-2, IFN-γ, IL-17 and IL-6 production were decreased, whereas IL-10 and TGF-β production were increased from the splenocytes isolated from SM934-treated mice. Consistently, both flow cytometry and qRT-PCR results showed that SM934 treatment significantly increased the Treg, while strongly suppressed the Th17 and Th1, responses in the peripheral. Furthermore, in the spinal lesion, SM934 treatment dramatically decreased the infiltration of CD4⁺ T cells, within which the Treg cells percentage was enlarged, whereas the Th17, but not Th1 percentage, was significantly decreased comparing with the vehicle-treated groups. Finally, both BrdU incorporation and in vitro Treg differentiation assays revealed that SM934 treatment could directly promote the expansion of Treg cells in vivo and in vitro.

Conclusion

Taken together, this study demonstrated that SM934 treatment could ameliorate the murine EAE disease, which might be mediated by inducing Treg differentiation and expansion.     

To Control False Positives in Gene-Gene Interaction Analysis: Two Novel Conditional Entropy-Based Approaches

Genome-wide analysis of gene-gene interactions has been recognized as a powerful avenue to identify the missing genetic components that can not be detected by using current single-point association analysis. Recently, several model-free methods (e.g. the commonly used information based metrics and several logistic regression-based metrics) were developed for detecting non-linear dependence between genetic loci, but they are potentially at the risk of inflated false positive error, in particular when the main effects at one or both loci are salient. In this study, we proposed two conditional entropy-based metrics to challenge this limitation. Extensive simulations demonstrated that the two proposed metrics, provided the disease is rare, could maintain consistently correct false positive rate. In the scenarios for a common disease, our proposed metrics achieved better or comparable control of false positive error, compared to four previously proposed model-free metrics. In terms of power, our methods outperformed several competing metrics in a range of common disease models. Furthermore, in real data analyses, both metrics succeeded in detecting interactions and were competitive with the originally reported results or the logistic regression approaches. In conclusion, the proposed conditional entropy-based metrics are promising as alternatives to current model-based approaches for detecting genuine epistatic effects.     

Genome-Wide Analysis of NAC Transcription Factors and Characterization of the Cold Stress Response in Sweet Osmanthus

Plant Molecular Biology Reporter - Sweet osmanthus (Osmanthus fragrans) is an evergreen aromatic woody tree widely used in landscaping. However, O. fragrans is very sensitive to cold stress, which...     

Genome-Wide Analysis of the Apple (Malus domestica) Cysteine-Rich Receptor-Like Kinase (CRK) Family: Annotation,Genomic Organization,and Expression Profiles in Response to Fungal Infection

Plant Molecular Biology Reporter - Cysteine-rich receptor-like kinases (CRKs) took crucial roles in plant cell growth and development, as well as environmental adaption. Apple (Malus domestica) had...     

Regulation of Focal Adhesion Kinase Activation,Breast Cancer Cell Motility,and Amoeboid Invasion by the RhoA Guanine Nucleotide Exchange Factor Net1

Net1 is a RhoA guanine nucleotide exchange factor (GEF) that is overexpressed in a subset of human cancers and contributes to cancer cell motility and invasion in vitro. However, the molecular mechanism accounting for its role in cell motility and invasion has not been described. In the present work, we show that expression of both Net1 isoforms in breast cancer cells is required for efficient cell motility. Although loss of Net1 isoform expression only partially blocks RhoA activation, it inhibits lysophosphatidic acid (LPA)-stimulated migration as efficiently as knockdown of RhoA itself. However, we demonstrate that the Net1A isoform predominantly controls myosin light-chain phosphorylation and is required for trailing edge retraction during migration. Net1A interacts with focal adhesion kinase (FAK), localizes to focal adhesions, and is necessary for FAK activation and focal adhesion maturation during cell spreading. Net1A expression is also required for efficient invasion through a Matrigel matrix. Analysis of invading cells demonstrates that Net1A is required for amoeboid invasion, and loss of Net1A expression causes cells to shift to a mesenchymal phenotype characterized by high β₁-integrin activity and membrane type 1 matrix metalloproteinase (MT1-MMP) expression. These results demonstrate a previously unrecognized role for the Net1A isoform in controlling FAK activation during planar cell movement and amoeboid motility during extracellular matrix (ECM) invasion.