Dihydroartemisinin induces caspase-8-dependent apoptosis in murine GT1-7 hypothalamic neurons.

The cytotoxicity of dihydroartemisinin (DHART; an active metabolite of artemisinin or ART) was investigated using murine GT1-7 hypothalamic neurons. A decrease in neuronal cell viability was observed in DHART-treated cells typically after 6 h of incubation. When neuronal cells were exposed to DHART for 24 h, the value of IC50 was found to be 24 ± 3.2 µM (n = 6). Based on acridine orange/ethidium bromide (dual) staining and increases in oligonucleosomal fragmentation, the cell death at lower concentrations of DHART (≤ 20 µM) was suggestive of apoptotic in nature. On the other hand, at higher concentrations of DHART (≥ 50 µM), the cell death appeared to be predominantly necrotic. A potentiation of cytotoxic effects was seen in Fe(II)-containing medium whereas inclusion of deferoxamine (chelator of Fe) attenuated such effects. This would imply that the cleavage of the endoperoxide bridge of DHART by Fe(II) and the subsequent formation of O- and C-centered radical(s) are important determinants of the cytotoxicity that was observed. The activities of caspase-3/7, caspase-8 and caspase-9 were maximally seen at 12-h after exposure to DHART. Inhibitors of caspase-8 (C8I) but not caspase-9 (C9I) reduced the DHART-induced increase in caspase-3/7 activity. A relatively higher activity of caspase-8 to that of caspase-9 and the inhibition of caspsase-3/7 activity by C8I suggest that DHART induces caspase-8-mediated apoptosis involving the extrinsic pathway. Taken together, this study demonstrates that DHART and, possibly, other ART derivatives have considerable neurotoxic potential and facilitate our understanding of these agents.

Intelligent Design of 14-3-3 Docking Proteins Utilizing Synthetic Evolution Artificial Intelligence (SYN-AI).

The ability to write DNA code from scratch will allow for the discovery of new and interesting chemistries as well as allowing the rewiring of cell signal pathways. Herein, we have utilized synthetic evolution artificial intelligence (SYN-AI) to intelligently design a set of 14-3-3 docking genes. SYN-AI engineers synthetic genes utilizing a parental gene as an evolution template. Wherein, evolution is fast-forwarded by transforming template gene sequences to DNA secondary and tertiary codes based upon gene hierarchical structural levels. The DNA secondary code allows identification of genomic building blocks across an orthologous sequence space comprising multiple genomes. Where, the DNA tertiary code allows engineering of supersecondary structures. SYN-AI constructed a library of 10 million genes that was reduced to three structurally functional 14-3-3 docking genes by applying natural selection protocols. Synthetic protein identity was verified utilizing Clustal Omega sequence alignments and Phylogeny.fr phylogenetic analysis. Wherein, we were able to confirm the three-dimensional structure utilizing I-TASSER and protein-ligand interactions utilizing COACH and Cofactor. The conservation of allosteric communications was confirmed utilizing elastic and anisotropic network models. Whereby, we utilized elNemo and ANM2.1 to confirm conservation of the 14-3-3 ζ amphipathic groove. Notably, to the best of our knowledge, we report the first 14-3-3 docking genes to be written from scratch.

Engineering cellulosic bioreactors by template assisted DNA shuffling and in vitro recombination (TADSir).

The current study focuses on development of a bioreactor engineering strategy based on exploitation of the Arabidopsis thaliana genome. Chimeric A. thaliana glycosyl hydrolase (GH) gene libraries were assembled using a novel directed evolution strategy (TADSir: template assisted DNA shuffling and in vitro recombination) that promotes DNA recombination by reassembly of DNA fragments on unique gene templates. TADSir was modeled using a set of algorithms designed to simulate DNA interactions based on nearest neighbor base stacking interactions and Gibb's free energy differences between helical coil and folded DNA states. The algorithms allow for target gene prediction and for in silica analysis of chimeric gene library composition. Further, the study investigated utilization of A. thaliana GH sequence space for bioreactor design by evolving 20 A. thaliana genes representing the GH1, GH3, GH5, GH9 and GH10 gene families. Notably, TADSir achieved streamlined engineering of Saccharomyces cerevisiae and spinach mesophyll protoplast bioreactors capable of processing CM cellulose, Avicel and xylan.