PubMed Health⌕ Search

PubMed · 12366682

Human hematopoietic lineage commitment.

Abstract

The ultimate goal of developmental immunology is to understand the normal processes that give rise to the immune system in order to diagnose and develop effective treatments for diseases that occur as a consequence of immune system defects. Central to achieving this goal is understanding the complex interplay between microenvironmental signals and transcription factors that direct human hematopoietic differentiation and lineage commitment. The ability to isolate highly purified populations of human hematopoietic cells at critical points in differentiation make it possible to answer very specific questions about the hematopoietic process and lineage restriction. This review describes the use of surface immunophenotypes to identify human hematopoietic cells at particular points in differentiation or with particular patterns of lineage restriction. Culture models are discussed in the context of the ability to detect, characterize and determine the lineage potential of human hematopoietic stem cells and progenitors. Variations in hematopoeises that correspond to ontogeny will be examined. Potential roles for the HOX and Ikaros proteins in human lineage commitment will be considered. Also included will be discussion of a number of factors that provide challenges to experimental design, to experimental interpretation, and to the development of a comprehensive model of human hematopoiesis.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Kimberly J Payne, Gay M Crooks. 2002. Human hematopoietic lineage commitment.. https://doi.org/10.1034/j.1600-065x.2002.18705.x

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

FIERCE: reconstructing dynamic trajectories from the differentiation potency of single cells.

MOTIVATION: Since the introduction of single-cell RNA sequencing (scRNA-seq), numerous computational approaches have been developed to reconstruct dynamic cellular processes from static transcriptional profiles. These methods order cells along continuous trajectories by assessing their similarity in the gene-expression space. However, they rely on several assumptions, such as prior knowledge of the structure and directionality of the expected genealogy. These assumptions can limit their application to complex cellular systems with poorly understood developmental paths. RESULTS: To address this challenge, we introduce FIERCE (Framework for InfERence of the veloCity of Entropy), a novel computational pipeline designed to predict the changes in the differentiation potency of single cells during dynamic processes. Through a fully unsupervised approach, FIERCE enables the inference of cell lineages directly on the differentiation landscape of the biological system, thus eliminating the need for prior specification of developmental parameters. We demonstrate the efficacy of FIERCE by reconstructing three well-known mouse differentiation systems and by quantifying its accuracy on simulated data. AVAILABILITY AND IMPLEMENTATION: The FIERCE R package is available on GitHub at https://github.com/bicciatolab/FIERCE.

Cell Differentiation↗

mRNA turnover dynamics are affected by cell differentiation and loss of the cytosine methyltransferase Nsun2.

Nsun2 catalyzes 5-methylcytosine (m5C) formation in several types of RNA, including messenger RNAs (mRNAs), transfer RNAs, and other non-coding RNAs. In mRNA, m5C was reported to influence transcript stability. However, it is unclear if it has stabilizing or destabilizing effects. To address the role of Nsun2 in mRNA stability, we characterized the landscape of mRNA turnover dynamics during embryonic stem cell (ESC) differentiation in wild-type and Nsun2-mutant cells. By using an RNA labeling approach combined with thiouridine-to-cytidine-sequencing (TUC-seq), we demonstrate that mRNA synthesis and stability undergo extensive changes during normal cellular differentiation. Remarkably, a large proportion of these changes did not result in altered mRNA abundance, providing evidence for robust transcript buffering during ESC differentiation. Importantly, also the loss of Nsun2 affected mRNA turnover dynamics but not the steady-state levels of transcripts. Furthermore, our data indicate that the effect of Nsun2 on mRNA turnover was not mediated by m5C deposition in mRNA, which is corroborated by catalysis-independent effects of Nsun2 on translation in early ESC differentiation. In conclusion, this study demonstrates that differentiation as well as loss of Nsun2 can induce changes in mRNA turnover dynamics that are independent of mRNA methylation but consistent with a buffering mechanism to maintain constant RNA levels.

Cell Differentiation↗

Glucose modulates IRF6 transcription factor dimerization to enable epidermal differentiation.

Non-energetic roles for glucose are largely unclear, as is the interplay between transcription factors (TFs) and ubiquitous biomolecules. Metabolomic analyses uncovered elevation of intracellular glucose during differentiation of diverse cell types. Human and mouse tissue engineered with glucose sensors detected a glucose gradient that peaked in the outermost differentiated layers of the epidermis. Free glucose accumulation was essential for epidermal differentiation and required the SGLT1 glucose transporter. Glucose affinity chromatography uncovered glucose binding to diverse regulatory proteins, including the IRF6 TF. Direct glucose binding enabled IRF6 dimerization, DNA binding, genomic localization, and induction of IRF6 target genes, including essential pro-differentiation TFs GRHL1, GRHL3, HOPX, and PRDM1. These data identify a role for glucose as a gradient morphogen that modulates protein multimerization in cellular differentiation.

Cell Differentiation↗