Transcriptomic profiling of human bone marrow non-hematopoietic cells
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE190965 | GEO | 2023/03/12
REPOSITORIES: GEO
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Project description:Thiele2013 - Bone marrow hematopoietic cells
The model of bone marrow hematopoietic cells metabolism is derived from the community-driven global reconstruction of human metabolism (version 2.02, MODEL1109130000
).
This model is described in the article:
A community-driven global reconstruction of human metabolism.
Thiele I, et al
.
Nature Biotechnology
Abstract:
Multiple models of human metabolism have been reconstructed, but each represents only a subset of our knowledge. Here we describe Recon 2, a community-driven,
consensus 'metabolic reconstruction', which is the most comprehensive representation of human metabolism that is applicable to computational modeling. Compared
with its predecessors, the reconstruction has improved topological and functional features, including ~2x more reactions and ~1.7x more unique metabolites. Using
Recon 2 we predicted changes in metabolite biomarkers for 49 inborn errors of metabolism with 77% accuracy when compared to experimental data. Mapping metabolomic
data and drug information onto Recon 2 demonstrates its potential for integrating and analyzing diverse data types. Using protein expression data, we automatically
generated a compendium of 65 cell type-specific models, providing a basis for manual curation or investigation of cell-specific metabolic properties. Recon 2 will
facilitate many future biomedical studies and is freely available at http://humanmetabolism.org/.
This model is hosted on BioModels Database
and identified by: MODEL1310110030
.
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curated and annotated resource for published quantitative kinetic models
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2005-01-01 | MODEL1310110030 | BioModels
Project description:We performed fate tracing of Gli1+ cells in homeostasis. Sorted cells were subjected to scRNAseq and integrated with non-hematopoietic cells from mice with myelofibrosis induced by either ThPO- or JAK2V617F-overexpression. Gli1+tdTom+ cells largely overlap with pro-fibrotic adipogenic and osteogenic MSCs, which show a strong upregulation of ECM related transcripts. Additionally, a subgroup of Gli1+tdTom+ cells shows similarity with bone marrow SCPs.
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Project description:Human bone marrow stromal cells (BMSCs) are key elements of the hematopoietic environment and they play a central role in bone and bone marrow physiology. However, how key BMSC functions are regulated is largely unknown. We analyzed the role of the immediate early response transcription factor EGR1 as key BMSC regulator and found that EGR1 was highly expressed in prospectively-isolated primary BMSCs, downregulated upon culture, and lower in non-CFU-F-containing CD45neg BM cells. Furthermore, EGR1 expression was lower in proliferative regenerating adult and fetal primary cells compared to adult steady-state BMSCs. Accordingly, EGR1 overexpression markedly decreased BMSC proliferation but considerably improved hematopoietic stroma support function as indicated by an increased production of transplantable CD34+CD90+ hematopoietic stem cells in expansion co-cultures. The improvement of BMSC stroma support function was mediated by increased expression of hematopoietic supporting genes, such as VCAM1 and CCL28. On the other hand, EGR1 knockdown increased ROS-mediated BMSC proliferation, and clearly reduced BMSC hematopoietic stroma support potential. These findings thus show that EGR1 is a key BMSC transcription factor with a dual role in regulating proliferation and hematopoietic stroma support function that is controlling a genetic program to coordinate the specific functions of BMSC in their different biological contexts.
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Project description:Characterization of murine non-hematopoietic Gli1+ bone marrow cells in homeostasis
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Project description:The paper describes a model of tumor invasion to bone marrow.
Created by COPASI 4.26 (Build 213)
This model is described in the article:
Modeling invasion of metastasizing cancer cells to bone marrow utilizing ecological principles
Kun-Wan Chen, Kenneth J Pienta
Theoretical Biology and Medical Modelling 2011, 8:36
Abstract:
Background: The invasion of a new species into an established ecosystem can be directly compared to the steps involved in cancer metastasis. Cancer must grow in a primary site, extravasate and survive in the circulation to then intravasate into target organ (invasive species survival in transport). Cancer cells often lay dormant at their metastatic site for a long period of time (lag period for invasive species) before proliferating (invasive spread). Proliferation in the new site has an impact on the target organ microenvironment (ecological impact) and eventually the human host (biosphere impact).
Results: Tilman has described mathematical equations for the competition between invasive species in a structured habitat. These equations were adapted to study the invasion of cancer cells into the bone marrow microenvironment as a structured habitat. A large proportion of solid tumor metastases are bone metastases, known to usurp hematopoietic stem cells (HSC) homing pathways to establish footholds in the bone marrow. This required accounting for the fact that this is the natural home of hematopoietic stem cells and that they already occupy this structured space. The adapted Tilman model of invasion dynamics is especially valuable for modeling the lag period or dormancy of cancer cells.
Conclusions: The Tilman equations for modeling the invasion of two species into a defined space have been modified to study the invasion of cancer cells into the bone marrow microenvironment. These modified equations allow a more flexible way to model the space competition between the two cell species. The ability to model initial density, metastatic seeding into the bone marrow and growth once the cells are present, and movement of cells out of the bone marrow niche and apoptosis of cells are all aspects of the adapted equations. These equations are currently being applied to clinical data sets for verification and further refinement of the models.
To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models .
To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide.
Please refer to CC0 Public Domain Dedication for more information.
2019-08-13 | BIOMD0000000793 | BioModels