Generation of Mouse-Induced Pluripotent Stem Cells by Lentiviral Transduction

Establishment of human induced trophoblast stem cells via reprogramming of fibroblasts

During early mammalian embryonic development, trophoblast cells play an essential role in establishing cell-cell interactions at the maternal-fetal interface to ensure a successful pregnancy. In a recent study, we showed that human fibroblasts can be reprogrammed into induced trophoblast stem (iTS) cells by transcription factor-mediated nuclear reprogramming using the Yamanaka factors OCT4, KLF4, SOX2 and c-MYC (OKSM) and a selection of TS cell culture conditions. The derivation of TS cells from human blastocysts or first-trimester placenta can be limited by difficulties in obtaining adequate material as well as ethical implications. By contrast, the described approach allows the generation of iTS cells from the adult cells of individuals with diverse genetic backgrounds, which are readily accessible to many laboratories around the world. Here we describe a step-by-step protocol for the generation and establishment of human iTS cells directly from dermal fibroblasts using a non-integrative reprogramming method. The protocol consists of four main sections: (1) recovery of cryopreserved human dermal fibroblasts, (2) somatic cell reprogramming, (3) passaging of reprogramming intermediates and (4) derivation of iTS cell cultures followed by routine maintenance of iTS cells. These iTS cell lines can be established in 2-3 weeks and cultured long term over 50 passages. We also discuss several characterization methods that can be performed to validate the iTS cells derived using this approach. Our protocol allows researchers to generate patient-specific iTS cells to interrogate the trophoblast and placenta biology as well as their interactions with embryonic cells in health and diseases.

Breaking constraint of mammalian axial formulae

The vertebral column of individual mammalian species often exhibits remarkable robustness in the number and identity of vertebral elements that form (known as axial formulae). The genetic mechanism(s) underlying this constraint however remain ill-defined. Here, we reveal the interplay of three regulatory pathways (Gdf11, miR-196 and Retinoic acid) is essential in constraining total vertebral number and regional axial identity in the mouse, from cervical through to tail vertebrae. All three pathways have differing control over Hox cluster expression, with heterochronic and quantitative changes found to parallel changes in axial identity. However, our work reveals an additional role for Hox genes in supporting axial elongation within the tail region, providing important support for an emerging view that mammalian Hox function is not limited to imparting positional identity as the mammalian body plan is laid down. More broadly, this work provides a molecular framework to interrogate mechanisms of evolutionary change and congenital anomalies of the vertebral column.

Vertebral column length and shape exhibits remarkable robustness within a species but diversity across species. Here the authors reveal the molecular logic constraining vertebral number in mouse and a novel role for posterior Hox genes in this context.

Recent trends in stem cell-based therapies and applications of artificial intelligence in regenerative medicine

Stem cells are undifferentiated cells that can self-renew and differentiate into diverse types of mature and functional cells while maintaining their original identity. This profound potential of stem cells has been thoroughly investigated for its significance in regenerative medicine and has laid the foundation for cell-based therapies. Regenerative medicine is rapidly progressing in healthcare with the prospect of repair and restoration of specific organs or tissue injuries or chronic disease conditions where the body’s regenerative process is not sufficient to heal. In this review, the recent advances in stem cell-based therapies in regenerative medicine are discussed, emphasizing mesenchymal stem cell-based therapies as these cells have been extensively studied for clinical use. Recent applications of artificial intelligence algorithms in stem cell-based therapies, their limitation, and future prospects are highlighted.