Dataset Information

T-cell differentiation of multipotent hematopoietic cell line EML in the OP9-DL1 coculture system.

ABSTRACT: Multipotent hematopoietic cell line EML can differentiate into myeloid, erythroid, megakaryocytic, and B-lymphoid lineages, but it remained unknown whether EML cells have T-cell developmental potential as well. The goal of this study was to determine whether the coculture with OP9 stromal cells expressing Notch ligand Delta-like 1 (OP9-DL1) could induce differentiation of EML cells into T-cell lineage.EML cells were cocultured with control OP9 or OP9-DL1 stromal cells in the presence of cytokines (stem cell factor, interleukin-7, and Fms-like tyrosine kinase 3 ligand). Their T-cell lineage differentiation was assessed through flow cytometry and reverse transcription polymerase chain reaction expression analysis of cell surface markers and genes characterizing and associated with specific stages of T-cell development.The phenotypic, molecular, and functional analysis has revealed that in EML/OP9-DL1 cocultures with cytokines, but not in control EML/OP9 cocultures, EML cell line undergoes T-cell lineage commitment and differentiation. In OP9-DL1 cocultures, EML cell line has differentiated into cells that 1) resembled double-negative, double-positive, and single-positive stages of T-cell development; 2) initiated expression of GATA-3, Pre-Talpha, RAG-1, and T-cell receptor-Vbeta genes; and 3) produced interferon-gamma in response to T-cell receptor stimulation.These results support the notion that EML cell line has the capacity for T-cell differentiation. Remarkably, induction of T-lineage gene expression and differentiation of EML cells into distinct stages of T-cell development were very similar to previously described T-cell differentiation of adult hematopoietic stem cells and progenitors in OP9-DL1 cocultures. Thus, EML/OP9-DL1 coculture could be a useful experimental system to study the role of particular genes in T-cell lineage specification, commitment, and differentiation.

SUBMITTER: Kutlesa S

PROVIDER: S-EPMC3072798 | biostudies-other | 2009 Aug

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

T-cell differentiation of multipotent hematopoietic cell line EML in the OP9-DL1 coculture system.

Kutlesa Snjezana S Zayas Jennifer J Valle Alexandra A Levy Robert B RB Jurecic Roland R

Experimental hematology 20090515 8

<h4>Objective</h4>Multipotent hematopoietic cell line EML can differentiate into myeloid, erythroid, megakaryocytic, and B-lymphoid lineages, but it remained unknown whether EML cells have T-cell developmental potential as well. The goal of this study was to determine whether the coculture with OP9 stromal cells expressing Notch ligand Delta-like 1 (OP9-DL1) could induce differentiation of EML cells into T-cell lineage.<h4>Materials and methods</h4>EML cells were cocultured with control OP9 or O ...[more]

PMID: 19447159

Similar Datasets

Project description:Regenerative tissues such as the skin epidermis, the intestinal mucosa or the hematopoietic system are organized in a hierarchical manner with stem cells building the top of this hierarchy. Somatic stem cells harbor the highest self-renewal activity and generate a series of multipotent progenitors which differentiate into lineage committed progenitors and subsequently mature cells. In this report, we applied an in-depth quantitative proteomic approach to analyze and compare the full proteomes of ex vivo isolated and FACS-sorted populations highly enriched for either multipotent hematopoietic stem/progenitor cells (HSPCs, Lin(neg)Sca-1(+)c-Kit(+)) or myeloid committed precursors (Lin(neg)Sca-1(-)c-Kit(+)). By employing stable isotope dimethyl labeling and high-resolution mass spectrometry, more than 5000 proteins were quantified. From biological triplicate experiments subjected to rigorous statistical evaluation, 893 proteins were found differentially expressed between multipotent and myeloid committed cells. The differential protein content in these cell populations points to a distinct structural organization of the cytoskeleton including remodeling activity. In addition, we found a marked difference in the expression of metabolic enzymes, including a clear shift of specific protein isoforms of the glycolytic pathway. Proteins involved in translation showed a collective higher expression in myeloid progenitors, indicating an increased translational activity. Strikingly, the data uncover a unique signature related to immune defense mechanisms, centering on the RIG-I and type-1 interferon response systems, which are installed in multipotent progenitors but not evident in myeloid committed cells. This suggests that specific, and so far unrecognized, mechanisms protect these immature cells before they mature. In conclusion, this study indicates that the transition of hematopoietic stem/progenitors toward myeloid commitment is accompanied by a profound change in processing of cellular resources, adding novel insights into the molecular mechanisms at the interface between multipotency and lineage commitment.

Project description:During adult bone marrow hematopoiesis, extremely rare and dormant hematopoietic stem cells (HSCs) harbor the highest self-renewal activity within all blood cells. They give rise to active HSCs, which generate multipotent progenitors (MPPs) which differentiate into lineage-committed progenitors and subsequently mature cells. While HSCs are characterized by long-term self-renewal capacity, quiescence and multipotency, MPPs show steadily decreasing self-renewal activity, are cycling but are thought to maintain multipotency. To establish a comprehensive genome-wide landscape of expressed transcripts, we performed a quantitative transcriptome analysis by next-generation sequencing (RNA-seq) of seven ex vivo FACS-sorted mouse HSC/progenitor populations. Eleven-fold coverage of the genome was achieved, revealing quantification of > 27,000 mRNA species of which 589 long non-coding RNAs (lncRNAs) were quantified. A profile of 79 differentially expressed lncRNAs in HSC-MPPs was identified suggesting a role for these RNA species in HSC/progenitor biology. Expression clusters of transcription factors and cell adhesion molecules are identified between the different cell populations. Dormant HSCs, as identified by label-retaining assays, showed a highly differential expression profile compared to active HSCs. In addition to >200 differentially expressed cell surface receptors and lncRNAs, processes including metabolism, development, immune response, signaling (TGFb, Kit, senescence/autophagy) are distinct between the two types of HSCs. In addition, using whole cell proteome analysis of FACS-sorted HSCs and MPP1, >6,000 proteins were identified by quantitative tandem mass spectrometry. Quantification of these proteins confirmed the close relationship between these cell types also seen in their transcript profile and revealed processes such as energy metabolism, immune response and cell cycle to be modulated along early lineage progression. While MPP1/2 still show multilineage potential in reconstitution experiments, a strong lineage bias and low self-renewal potential is observed in mice reconstituted with MPP3/4. These functional differences are accompanied by complex changes in their transcriptome and is also revealed by principal component analysis. In summary, the global mRNA, lncRNA and proteome signatures uncovered here and which are complemented by functional assays, provide a comprehensive and searchable resource of the molecular make-up of the entire HSC/progenitor population present in the bone marrow. These data will provide the basis for a global understanding of stem cell biology in the adult blood system. The uploaded dataset corresponds to the quantitative proteomic comparison of HSC and MPP1, which was done in three biological replicates. Data analysis: MS raw data files were processed with MaxQuant (version 1.3.0.5) (Cox and Mann 2008). Enzyme specificity was set to trypsin/P and a maximum of two missed cleavages were allowed. Cysteine carbamidomethylation and methionine oxidation were selected as fixed and variable modifications, respectively. The derived peak list was searched using the built-in Andromeda search engine (version 1.3.0.5) in MaxQuant against the Uniprot mouse database (2013.02.20) containing 75,721 proteins to which 247 frequently observed contaminants as well as reversed sequences of all entries had been added. Initial maximal allowed mass tolerance was set to 20 ppm for peptide masses, followed by 6 ppm in the main search, and 0.5 Dalton for fragment ion masses. The minimum peptide length was set to six amino acid residues and three labeled amino acid residues were allowed. A 1% false discovery rate (FDR) was required at both the protein level and the peptide level. In addition to the FDR threshold, proteins were considered identified if they had at least one unique peptide. The protein identification was reported as an indistinguishable “protein group” if no unique peptide sequence to a single database entry was identified. The ‘match between runs’ was enabled for consecutive peptide fractions with a 2 minutes time window. The iBAQ algorithm was used for estimation of the abundance of different proteins within a single sample (proteome) (Schwanhausser 2011). For evaluation of differential protein expression between HSC and MPP1, statistical analysis was performed for the proteins quantified in all three replicates using the Limma package in R/Bioconductor (Gentleman 2004, Smyth 2004). After fitting a linear model to the data, an empirical Bayes moderated t-test was used for the protein ratios, which were weighted on log10(summed peptide intensities) in order to capture the effect that the statistical spread of unregulated proteins is much more focused for highly abundant proteins than for low abundance ones (Cox 2008). P-values were then adjusted for multiple testing with Benjamini and Hochberg's method and proteins with an adjusted p-value lower than 0.1 were considered to be differentially expressed between HSC and MPP1. Associated transcriptomics data has been deposited at ArrayExpress with accession E-MTAB-2262.

Dataset Information

T-cell differentiation of multipotent hematopoietic cell line EML in the OP9-DL1 coculture system.

Publications

T-cell differentiation of multipotent hematopoietic cell line EML in the OP9-DL1 coculture system.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets