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Small RNAs, including siRNAs, gRNAs and miRNAs, modulate gene expression and serve as potential therapies for human diseases. Delivery to target cells remains the fundamental limitation for use of these RNAs in humans. To address this challenge, we have developed a nanocapsule delivery technology that encapsulates small DNA molecules encoding RNAs into a small (30 nm) polymer nanocapsule. For proof of concept, we transduced DNA expression cassettes for three small RNAs. In one application, the DNA cassette encodes an shRNA transcriptional unit that downregulates CCR5 and protects from HIV-1 infection. The DNA cassette nanocapsules were further engineered for timed release of the DNA cargo for prolonged knockdown of CCR5. Secondly, the nanocapsules provide an efficient means for delivery of gRNAs in the CRISPR/Cas9 system to mutate integrated HIV-1. Finally, delivery of microRNA-125b to mobilized human CD34+ cells enhances survival and expansion of the CD34+ cells in culture.

Long interspersed element-1 (LINE-1 or L1) retrotransposition induces insertional mutations that can result in diseases. It was recently shown that the copy number of L1 and other retroelements is stable in induced pluripotent stem cells (iPSCs). However, by using an engineered reporter construct over-expressing L1, another study suggests that reprogramming activates L1 mobility in iPSCs. Given the potential of human iPSCs in therapeutic applications, it is important to clarify whether these cells harbor somatic insertions resulting from endogenous L1 retrotransposition. Here, we verified L1 expression during and after reprogramming as well as potential somatic insertions driven by the most active human endogenous L1 subfamily (L1Hs). Our results indicate that L1 over-expression is initiated during the reprogramming process and is subsequently sustained in isolated clones. To detect potential somatic insertions in iPSCs caused by L1Hs retotransposition, we used a novel sequencing strategy. As opposed to conventional sequencing direction, we sequenced from the 3' end of L1Hs to the genomic DNA, thus enabling the direct detection of the polyA tail signature of retrotransposition for verification of true insertions. Deep coverage sequencing thus allowed us to detect seven potential somatic insertions with low read counts from two iPSC clones. Negative PCR amplification in parental cells, presence of a polyA tail and absence from seven L1 germline insertion databases highly suggested true somatic insertions in iPSCs. Furthermore, these insertions could not be detected in iPSCs by PCR, likely due to low abundance. We conclude that L1Hs retrotransposes at low levels in iPSCs and therefore warrants careful analyses for genotoxic effects.

Human induced pluripotent stem cells (hiPSCs) provide new possibilities for regenerative therapies. In order for this potential to be achieved, it is critical to efficiently monitor the differentiation of these hiPSCs into specific lineages. Here, we describe a lentiviral reporter vector sensitive to specific microRNAs (miRNA) to show that a single vector bearing multiple miRNA target sequences conjugated to different reporters can be used to monitor hiPSC formation and subsequent differentiation from human fetal fibroblasts (HFFs). The reporter vector encodes EGFP conjugated to the targets of human embryonic stem cell (hESC) specific miRNAs (miR-302a and miR-302d) and mCherry conjugated to the targets of differentiated cells specific miRNAs (miR-142-3p, miR-155, and miR-223). The vector was used to track reprogramming of HFF to iPSC. HFFs co-transduced with this reporter vector and vectors encoding 4 reprogramming factors (OCT4, SOX2, KLF4 and cMYC) were mostly positive for EGFP (67%) at an early stage of hiPSC formation. EGFP expression gradually disappeared and mCherry expression increased indicating less miRNAs specific to differentiated cells and expression of miRNAs specific to hESCs. Upon differentiation of the hiPSC into embryoid bodies, a large fraction of these hiPSCs regained EGFP expression and some of those cells became single positive for EGFP. Further differentiation into neural lineages showed distinct structures demarcated by either EGFP or mCherry expression. These findings demonstrate that a miRNA dependent reporter vector can be a useful tool to monitor living cells during reprogramming of hiPSC and subsequent differentiation to lineage specific cells.

Involved in many diseases such as cancer, diabetes, neurodegenerative, inflammatory and respiratory disorders, G-protein-coupled receptors (GPCRs) are among the most frequent targets of therapeutic drugs. It is time-consuming and expensive to determine whether a drug and a GPCR are to interact with each other in a cellular network purely by means of experimental techniques. Although some computational methods were developed in this regard based on the knowledge of the 3D (dimensional) structure of protein, unfortunately their usage is quite limited because the 3D structures for most GPCRs are still unknown. To overcome the situation, a sequence-based classifier, called "iGPCR-drug", was developed to predict the interactions between GPCRs and drugs in cellular networking. In the predictor, the drug compound is formulated by a 2D (dimensional) fingerprint via a 256D vector, GPCR by the PseAAC (pseudo amino acid composition) generated with the grey model theory, and the prediction engine is operated by the fuzzy K-nearest neighbour algorithm. Moreover, a user-friendly web-server for iGPCR-drug was established at http://www.jci-bioinfo.cn/iGPCR-Drug/. For the convenience of most experimental scientists, a step-by-step guide is provided on how to use the web-server to get the desired results without the need to follow the complicated math equations presented in this paper just for its integrity. The overall success rate achieved by iGPCR-drug via the jackknife test was 85.5%, which is remarkably higher than the rate by the existing peer method developed in 2010 although no web server was ever established for it. It is anticipated that iGPCR-Drug may become a useful high throughput tool for both basic research and drug development, and that the approach presented here can also be extended to study other drug - target interaction networks.