Structurally-discovered KLF4 variants accelerate and stabilize reprogramming to pluripotency.

Non-genetically modified somatic cells can only be inefficiently and stochastically reprogrammed to pluripotency by exogenous expression of reprogramming factors. Low competence of natural reprogramming factors may prevent the majority of cells to successfully and synchronously reprogram. Here we screened DNA-interacting amino acid residues in the zinc-finger domain of KLF4 for enhanced reprogramming efficiency using alanine-substitution scanning methods. Identified KLF4 L507A mutant accelerated and stabilized reprogramming to pluripotency in both mouse and human somatic cells. By testing all the variants of L507 position, variants with smaller amino acid residues in the KLF4 L507 position showed higher reprogramming efficiency. L507A bound more to promoters or enhancers of pluripotency genes, such as KLF5, and drove gene expression of these genes during reprogramming. Molecular dynamics simulations predicted that L507A formed additional interactions with DNA. Our study demonstrates how modifications in amino acid residues of DNA-binding domains enable next-generation reprogramming technology with engineered reprogramming factors.

In silico-labeled ghost cytometry.

Characterization and isolation of a large population of cells are indispensable procedures in biological sciences. Flow cytometry is one of the standards that offers a method to characterize and isolate cells at high throughput. When performing flow cytometry, cells are molecularly stained with fluorescent labels to adopt biomolecular specificity which is essential for characterizing cells. However, molecular staining is costly and its chemical toxicity can cause side effects to the cells which becomes a critical issue when the cells are used downstream as medical products or for further analysis. Here, we introduce a high-throughput stain-free flow cytometry called in silico-labeled ghost cytometry which characterizes and sorts cells using machine-predicted labels. Instead of detecting molecular stains, we use machine learning to derive the molecular labels from compressive data obtained with diffractive and scattering imaging methods. By directly using the compressive 'imaging' data, our system can accurately assign the designated label to each cell in real time and perform sorting based on this judgment. With this method, we were able to distinguish different cell states, cell types derived from human induced pluripotent stem (iPS) cells, and subtypes of peripheral white blood cells using only stain-free modalities. Our method will find applications in cell manufacturing for regenerative medicine as well as in cell-based medical diagnostic assays in which fluorescence labeling of the cells is undesirable.

Disease-Focused Research Using Stem Cells.

In this Special Issue of Biomedicines on disease-focused research using stem cells, we cover the latest conceptual and practical advances in stem cell-based therapies and disease modeling [...].

A Role for KLF4 in Promoting the Metabolic Shift via TCL1 during Induced Pluripotent Stem Cell Generation.

Reprogramming of somatic cells into induced pluripotent stem cells (iPSCs) is accompanied by morphological, functional, and metabolic alterations before acquisition of full pluripotency. Although the genome-wide effects of the reprogramming factors on gene expression are well documented, precise mechanisms by which gene expression changes evoke phenotypic responses remain to be determined. We used a Sendai virus-based system that permits reprogramming to progress in a strictly KLF4-dependent manner to screen for KLF4 target genes that are critical for the progression of reprogramming. The screening identified Tcl1 as a critical target gene that directs the metabolic shift from oxidative phosphorylation to glycolysis. KLF4-induced TCL1 employs a two-pronged mechanism, whereby TCL1 activates AKT to enhance glycolysis and counteracts PnPase to diminish oxidative phosphorylation. These regulatory mechanisms described here highlight a central role for a reprogramming factor in orchestrating the metabolic shift toward the acquisition of pluripotency during iPSC generation.