Effect of Tenofovir on Nucleotidases and Cytokines in HIV-1 Target Cells

Tenofovir (TFV) has been widely used for pre-exposure prophylaxis of HIV-1 infection with mixed results. While the use of TFV in uninfected individuals for prevention of HIV-1 acquisition is actively being investigated, the possible consequences of TFV exposure for the HIV-target cells and the mucosal microenvironment are unknown. In the current study, we evaluated the effects of TFV treatment on blood-derived CD4⁺ T cells, monocyte-derived macrophages and dendritic cells (DC). Purified HIV-target cells were treated with different concentrations of TFV (0.001-1.0 mg/ml) for 2 to 24hr. RNA was isolated and RT-PCR was performed to compare the levels of mRNA expression of nucleotidases and pro-inflammatory cytokine genes (MIP3α, IL-8 and TNFα) in the presence or absence of TFV. We found that TFV increases 5’-ecto-nucleotidase (NT5E) and inhibits mitochondrial nucleotidase (NT5M) gene expression and increases 5’ nucleotidase activity in macrophages. We also observed that TFV stimulates the expression and secretion of IL-8 by macrophages, DC, and activated CD4⁺ T cells and increases the expression and secretion of MIP3α by macrophages. In contrast, TFV had no effect on TNFα secretion from macrophages, DC and CD4⁺ T cells. Our results demonstrate that TFV alters innate immune responses in HIV-target cells with potential implications for increased inflammation at mucosal surfaces. As new preventive trials are designed, these findings should provide a foundation for understanding the effects of TFV on HIV-target cells in microbicide trials.     

Does the position of the electron-donating nitrogen atom in the ring system influence the efficiency of a dye-sensitized solar cell? A computational study

Electronic structure of the XeOF₂ molecule and its two complexes with HX (X= F, Cl, Br, I) molecules have been studied in the gas phase using quantum chemical topology methods: topological analysis of electron localization function (ELF), electron density, ρ(r), reduced gradient of electron density |RDG(r)| in real space, and symmetry adapted perturbation theory (SAPT) in the Hilbert space. The wave function has been approximated by the MP2 and DFT methods, using APF-D, B3LYP, M062X, and B2PLYP functionals, with the dispersion correction as proposed by Grimme (GD3). For the Xe-F and Xe=O bonds in the isolated XeOF₂ molecule, the bonding ELF-localization basins have not been observed. According to the ELF results, these interactions are not of covalent nature with shared electron density. There are two stable F₂OXe^…HF complexes. The first one is stabilized by the F-H^…F and Xe^…F interactions (type I) and the second by the F-H^…O hydrogen bond (type II). The SAPT analysis confirms the electrostatic term, E_elst ⁽¹⁾ and the induction energy, E_ind ⁽²⁾ to be the major contributors to stabilizing both types of complexes.

     

Humanized mouse G6 anti-idiotypic monoclonal antibody has therapeutic potential against IGHV1-69 germline gene-based B-CLL

In 10–20% of the cases of chronic lymphocytic leukemia of B-cell phenotype (B-CLL), the IGHV1-69 germline is utilized as VH gene of the B cell receptor (BCR). Mouse G6 (MuG6) is an anti-idiotypic monoclonal antibody discovered in a screen against rheumatoid factors (RFs) that binds with high affinity to an idiotope expressed on the 51p1 alleles of IGHV1-69 germline gene encoded antibodies (G6-id⁺). The finding that unmutated IGHV1-69 encoded BCRs are frequently expressed on B-CLL cells provides an opportunity for anti-idiotype monoclonal antibody immunotherapy. In this study, we first showed that MuG6 can deplete B cells encoding IGHV1-69 BCRs using a novel humanized GTL mouse model. Next, we humanized MuG6 and demonstrated that the humanized antibodies (HuG6s), especially HuG6.3, displayed ～2-fold higher binding affinity for G6-id⁺ antibody compared to the parental MuG6. Additional studies showed that HuG6.3 was able to kill G6-id⁺ BCR expressing cells and patient B-CLL cells through antibody-dependent cell-mediated cytotoxicity (ADCC) and complement-dependent cytotoxicity (CDC). Finally, both MuG6 and HuG6.3 mediate in vivo depletion of B-CLL cells in NSG mice. These data suggest that HuG6.3 may provide a new precision medicine to selectively kill IGHV1-69-encoding G6-id⁺ B-CLL cells.     

Genetics of barley tiller and leaf development

In cereals, tillering and leaf development are key factors in the concept of crop ideotype, introduced in the 1960 s to enhance crop yield, via manipulation of plant architecture. In the present review, we discuss advances in genetic analysis of barley shoot architecture,focusing on tillering, leaf size and angle. We also discuss novel phenotyping techniques, such as 2 D and 3 D imaging, that have been introduced in the era of phenomics, facilitating reliable trait measurement. We discuss the identification of genes and pathways that are involved in barley tillering and leaf development,highlighting key hormones involved in the control of plant architecture in barley and rice. Knowledge on genetic control of traits related to plant architecture provides useful resources for designing ideotypes for enhanced barley yield and performance.     

A distance-type measure approach to the analysis of copy number variation in DNA sequencing data

Background

The next generation sequencing technology allows us to obtain a large amount of short DNA sequence (DNA-seq) reads at a genome-wide level. DNA-seq data have been increasingly collected during the recent years. Count-type data analysis is a widely used approach for DNA-seq data. However, the related data pre-processing is based on the moving window method, in which a window size need to be defined in order to obtain count-type data. Furthermore, useful information can be reduced after data pre-processing for count-type data.

Results

In this study, we propose to analyze DNA-seq data based on the related distance-type measure. Distances are measured in base pairs (bps) between two adjacent alignments of short reads mapped to a reference genome. Our experimental data based simulation study confirms the advantages of distance-type measure approach in both detection power and detection accuracy. Furthermore, we propose artificial censoring for the distance data so that distances larger than a given value are considered potential outliers. Our purpose is to simplify the pre-processing of DNA-seq data. Statistically, we consider a mixture of right censored geometric distributions to model the distance data. Additionally, to reduce the GC-content bias, we extend the mixture model to a mixture of generalized linear models (GLMs). The estimation of model can be achieved by the Newton-Raphson algorithm as well as the Expectation-Maximization (E-M) algorithm. We have conducted simulations to evaluate the performance of our approach. Based on the rank based inverse normal transformation of distance data, we can obtain the related z-values for a follow-up analysis. For an illustration, an application to the DNA-seq data from a pair of normal and tumor cell lines is presented with a change-point analysis of z-values to detect DNA copy number alterations.

Conclusion

Our distance-type measure approach is novel. It does not require either a fixed or a sliding window procedure for generating count-type data. Its advantages have been demonstrated by our simulation studies and its practical usefulness has been illustrated by an experimental data application.