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Therapeutic genome editing technology has been widely used as a powerful tool for directly correcting genetic mutations in target pathological tissues and cells to cure of diseases. The modification of specific genomic sequences can be achieved by utilizing programmable nucleases, such as Meganucleases, zinc finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs), and the clustered regularly-interspaced short palindromic repeat-associated nuclease Cas9 (CRISPR/Cas9). However, given the properties, such as large size, negative charge, low membrane penetrating ability, as well as weak tolerance for serum, and low endosomal escape, of these nucleases genome editing cannot be successfully applied unless in vivo delivery of related programmable nucleases into target organisms or cells is achieved. Here, we look back at delivery strategies having been used in the in vivo delivery of three main genome editing nucleases, followed by methodologies currently undergoing testing in clinical trials, and potential delivery strategies provided by analyzing characteristics of nucleases and commonly used vectors.

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Triptolide (TP), an active component isolated from Tripterygiumwilfordii Hook F, has therapeutic potential against rheumatoid arthritis (RA). However, the underlying molecular mechanism has not been fully elucidated. The aim of this study is to investigate the mechanisms of TP acting on RA by combining bioinformatics analysis with experiment validation. The human protein targets of TP and the human genes of RA were found in the PubChem database and NCBI, respectively. These two dataset were then imported into Ingenuity Pathway Analysis (IPA) software online, and then the molecular network of TP on RA could be set up and analyzed. After that, both in vitro and in vivo experiments were done to further verify the prediction. The results indicated that the main canonical signal pathways of TP protein targets networks were mainly centered on cytokine and cellular immune signaling, and triggering receptors expressed on myeloid cells (TREM)-1 signaling was searched to be the top one shared signaling pathway and involved in the cytokine and cellular immune signaling. Further in vitro experiments indicated that TP not only remarkably lowered the levels of TREM-1 and DNAX-associated protein (DAP)12, but also significantly suppressed the activation of janus activating kinase (JAK)2 and signal transducers and activators of transcription (STAT)3. The expression of tumor necrosis factor (TNF)-α, interleukin (IL)-1β and IL-6 in lipopolysaccharides (LPS)-stimulated U937 cells also decreased after treatment with TP. Furthermore, TREM-1 knockdown was able to interfere with the inhibition effects of TP on these cytokines production. In vivo experiments showed that TP not only significantly inhibited the TREM-1 mRNA and DAP12 mRNA expression, and activation of JAK2 and STAT3 in ankle of rats with collagen-induced arthritis (CIA), but also remarkably decreased production of TNF-α, IL-1β and IL-6 in serum and joint. These findings demonstrated that TP could modulate the TREM1 signal pathway to inhibit the inflammatory response in RA.

Chronic heart failure (CHF), as a progressive clinical syndrome, is characterized by failure of enough blood supply from the heart to meet the body's metabolic demands, and there is intense interest in identifying novel biomarkers that could make contributions to the diagnosis of CHF. Metabolomics, compared with current diagnostic approaches, could investigate many metabolic perturbations within biological systems. The overarching goal of the work discussed here is to apply a high-throughput approach to identify metabolic signatures and plasma diagnostic biomarkers underlying CHF by 1H-NMR spectroscopy. Plasma samples from 39 patients with CHF and 15 controls were analyzed by NMR spectroscopy. After processing the data, orthogonal partial least square discriminant analysis (OPLS-DA) was performed. The statistical model revealed good explained variance and predictability, and the diagnostic performance assessed by leave-one-out analysis exhibited 92.31% sensitivity and 86.67% specificity. The OPLS-DA score plots of spectra revealed good separation between case and control on the level of metabolites, and multiple biochemical changes indicated hyperlipidemia, alteration of energy metabolism and other potential biological mechanisms underlying CHF. It was concluded that the NMR-based metabolomics approach demonstrated good performance to identify diagnostic plasma markers and provided new insights into metabolic process related to CHF.