Targeted nucleases have provided researchers with the ability to manipulate virtually any genomic sequence, enabling the facile creation of isogenic cell lines and animal models for the study of human disease, and promoting exciting new possibilities for human gene therapy. Here we review three foundational technologies—clustered regularly interspaced short palindromic repeats (CRISPR)-CRISPR-associated protein 9 (Cas9), transcription activator-like effector nucleases (TALENs), and zinc-finger nucleases (ZFNs). We discuss the engineering advances that facilitated their development and highlight several achievements in genome engineering that were made possible by these tools. We also consider artificial transcription factors, illustrating how this technology can complement targeted nucleases for synthetic biology and gene therapy.

Human adipose-derived mesenchymal stem cells-conditioned medium (ADSC-CM) contains cytokines and growth factors that can facilitate the regeneration and repair of various tissues and organs. In the present study, the protective activity of ADSC-CM treatment was investigated in UVB-irradiated human keratinocyte cell line HaCaTs and normal human dermal fibroblasts (NHDFs). It was found that ADSC-CM can modulate the expression of the signaling molecules in the early UVB responsive signaling pathways, including mitogen activated protein kinases (MAPKs), activator protein 1 (AP-1), and nuclear factor kappa B (NF-κB). In addition, ADSC-CM treatment could upregulate antioxidant response element (ARE) such as phase II gene heme oxygenase-1 (HO-1) and increase the expression of collagen synthesis enhancer gene transforming growth factor-β (TGF-β). The expression of matrix metalloproteinase-1 (MMP-1) and procollagen type I synthesis inhibitors such as interleukin-6 (IL-6) was also found to be suppressed upon ADSC-CM treatment. Taken together, our study illustrates the anti-photoaging activities of ADSC-CM in cell-based models.

Designing protein mutants with both high stability and activity is a critical yet challenging task in protein engineering. Here, we introduce PRIME, a deep learning model, which can suggest protein mutants with improved stability and activity without any prior experimental mutagenesis data for the specified protein. Leveraging temperature-aware language modeling, PRIME demonstrated superior predictive ability compared to current state-of-the-art models on the public mutagenesis dataset across 283 protein assays. Furthermore, we validated PRIME’s predictions on five proteins, examining the impact of the top 30 to 45 single-site mutations on various protein properties, including thermal stability, antigen-antibody binding affinity, and the ability to polymerize nonnatural nucleic acid or resilience to extreme alkaline conditions. More than 30% of PRIME-recommended mutants exhibited superior performance compared to their premutation counterparts across all proteins and desired properties. We developed an efficient and effective method based on PRIME to rapidly obtain multisite mutants with enhanced activity and stability. Hence, PRIME demonstrates broad applicability in protein engineering.

Safe, efficient, and broadly applicable methods for delivering site-specific nucleases into cells are needed in order for targeted genome editing to reach its full potential for basic research and medicine. We previously reported that zinc-finger nuclease (ZFN) proteins have the innate capacity to cross cell membranes and induce genome modification via their direct application to human cells. Here, we show that incorporation of tandem nuclear localization signal (NLS) repeats into the ZFN protein backbone enhances cell permeability nearly 13-fold and that single administration of multi-NLS ZFN proteins leads to genome modification rates of up to 26% in CD4⁺ T cells and 17% in CD34⁺ hematopoietic stem/progenitor cells. In addition, we show that multi-NLS ZFN proteins attenuate off-target effects and that codelivery of ZFN protein pairs facilitates dual gene modification frequencies of 20–30% in CD4⁺ T cells. These results illustrate the applicability of ZFN protein delivery for precision genome engineering.