Cell-specific proteome analyses of human bone marrow reveal molecular features of age-dependent functional decline
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ABSTRACT:
PROVIDER: PRJNA474673 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR7225060.fastq.gz | Fastqsanger.gz | |||
| SRR7225070.fastq.gz | Fastqsanger.gz | |||
| SRR7225080.fastq.gz | Fastqsanger.gz | |||
| SRR7225090.fastq.gz | Fastqsanger.gz | |||
| SRR7225100.fastq.gz | Fastqsanger.gz |
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Project description:Cell-specific proteome analyses of human bone marrow reveal molecular features of age-dependent functional decline [single cells]
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Project description:Cell-specific proteome analyses of human bone marrow reveal molecular features of age-dependent functional decline [cell populations]
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Project description:Diminishing potential to replace damaged tissues is a hallmark for ageing of somatic stem cells, but the mechanisms leading to ageing remain elusive. We present a proteome-wide atlas of age-associated alterations in human haematopoietic stem and progenitor cells (HPCs) along with five other cell types that constitute the bone marrow niche. For each, the abundance of a large fraction of the ~12,000 proteins identified was assessed in a cohort of healthy human subjects from different age. As the HPCs became older, pathways in central carbon metabolism exhibited features reminiscent of the Warburg effect where glycolytic intermediates are rerouted towards anabolism. Simultaneously, altered abundance of early regulators of HPC differentiation revealed a reduced functionality and a bias towards myeloid differentiation at the expense of lymphoid development. Ageing caused significant alterations in the bone marrow niche too, such as functionality of the pathways involved in HPC homing and lineage differentiation. The data represents a valuable resource for further in-depth mechanistic analyses, and for validation of knowledge gained from animal models.
2018-07-19 | GSE115348 | GEO
Project description:Diminishing potential to replace damaged tissues is a hallmark for ageing of somatic stem cells, but the mechanisms leading to ageing remain elusive. We present a proteome-wide atlas of age-associated alterations in human haematopoietic stem and progenitor cells (HPCs) along with five other cell types that constitute the bone marrow niche. For each, the abundance of a large fraction of the ~12,000 proteins identified was assessed in a cohort of healthy human subjects from different age. As the HPCs became older, pathways in central carbon metabolism exhibited features reminiscent of the Warburg effect where glycolytic intermediates are rerouted towards anabolism. Simultaneously, altered abundance of early regulators of HPC differentiation revealed a reduced functionality and a bias towards myeloid differentiation at the expense of lymphoid development. Ageing caused significant alterations in the bone marrow niche too, such as functionality of the pathways involved in HPC homing and lineage differentiation. The data represents a valuable resource for further in-depth mechanistic analyses, and for validation of knowledge gained from animal models.
2018-07-19 | GSE114961 | GEO
Project description:Diminishing potential to replace damaged tissues is a hallmark for ageing of somatic stem cells, but the mechanisms remain elusive. Here, we present proteome-wide atlases of age-associated alterations in human haematopoietic stem and progenitor cells (HPCs) and five other cell populations that constitute the bone marrow niche. For each, the abundance of a large fraction of the ~12,000 proteins identified is assessed in 59 human subjects from different ages. As the HPCs become older, pathways in central carbon metabolism exhibit features reminiscent of the Warburg effect, where glycolytic intermediates are rerouted towards anabolism. Simultaneously, altered abundance of early regulators of HPC differentiation reveals a reduced functionality and a bias towards myeloid differentiation. Ageing causes alterations in the bone marrow niche too, and diminishes the functionality of the pathways involved in HPC homing. The data represent a valuable resource for further analyses, and for validation of knowledge gained from animal models.
| S-EPMC6167374 | biostudies-literature
Project description:This SuperSeries is composed of the SubSeries listed below.
2018-07-19 | GSE115353 | GEO
Project description:Aging is associated with the decline of protein, cell, and organ function. Here, we use an integrated approach to characterize gene expression, bulk translation, and cell biology in the brains and livers of young and old rats. We identify 468 differences in protein abundance between young and old animals. The majority are a consequence of altered translation output, that is, the combined effect of changes in transcript abundance and translation efficiency. In addition, we identify 130 proteins whose overall abundance remains unchanged but whose sub-cellular localization, phosphorylation state, or splice-form varies. While some protein-level differences appear to be a generic property of the rats’ chronological age, the majority are specific to one organ. These may be a consequence of the organ’s physiology or the chronological age of the cells within the tissue. Taken together, our study provides an initial view of the proteome at the molecular, sub-cellular, and organ level in young and old rats.
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Project description:Transcriptome and Proteome Mapping in the Sheep Atria Reveal Molecular Features of Atrial Fibrillation Progression
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Project description:Proctor2007 - Age related decline of proteolysis, ubiquitin-proteome system
This
is a stochastic model of the ubiquitin-proteasome system for a
generic pool of native proteins (NatP), which have a half-life of
about 10 hours under normal conditions. It is assumed that these
proteins are only degraded after they have lost their native
structure due to a damage event. This is represented in the model
by the misfolding reaction which depends on the level of reactive
oxygen species (ROS) in the cell. Misfolded proteins (MisP) are
first bound by an E3 ubiquitin ligase. Ubiquitin (Ub) is
activated by E1 (ubiquitin-activating enzyme) and then passed to
E2 (ubiquitin-conjugating enzyme). The E2 enzyme then passes the
ubiquitin molecule to the E3/MisP complex with the net effect
that the misfolded protein is monoubiquitinated and both E2 and
E3 are released. Further ubiquitin molecules are added in a
step-wise manner. When the chain of ubiquitin molecules is of
length 4 or more, the polyubiquitinated misfolded protein may
bind to the proteasome. The model also includes de-ubiquitinating
enzymes (DUB) which cleave ubiquitin molecules from the chain in
a step-wise manner. They work on chains attached to misfolded
proteins both unbound and bound to the proteasomes. Misfolded
proteins bound to the proteasome may be degraded releasing
ubiquitin. Misfolded proteins including ubiquitinated proteins
may also aggregate. Aggregates (AggP) may be sequestered
(Seq_AggP) which takes them out of harm's way or they may bind to
the proteasome (AggP_Proteasome). Proteasomes bound by aggregates
are no longer available for protein degradation.
Figure
2 and Figure 3 has been simulated using Gillespie2.
This model is described in the article:
An in silico model of the
ubiquitin-proteasome system that incorporates normal
homeostasis and age-related decline.
Proctor CJ, Tsirigotis M, Gray
DA.
BMC Syst Biol 2007; 1: 17
Abstract:
BACKGROUND: The ubiquitin-proteasome system is responsible
for homeostatic degradation of intact protein substrates as
well as the elimination of damaged or misfolded proteins that
might otherwise aggregate. During ageing there is a decline in
proteasome activity and an increase in aggregated proteins.
Many neurodegenerative diseases are characterised by the
presence of distinctive ubiquitin-positive inclusion bodies in
affected regions of the brain. These inclusions consist of
insoluble, unfolded, ubiquitinated polypeptides that fail to be
targeted and degraded by the proteasome. We are using a systems
biology approach to try and determine the primary event in the
decline in proteolytic capacity with age and whether there is
in fact a vicious cycle of inhibition, with accumulating
aggregates further inhibiting proteolysis, prompting
accumulation of aggregates and so on. A stochastic model of the
ubiquitin-proteasome system has been developed using the
Systems Biology Mark-up Language (SBML). Simulations are
carried out on the BASIS (Biology of Ageing e-Science
Integration and Simulation) system and the model output is
compared to experimental data wherein levels of ubiquitin and
ubiquitinated substrates are monitored in cultured cells under
various conditions. The model can be used to predict the
effects of different experimental procedures such as inhibition
of the proteasome or shutting down the enzyme cascade
responsible for ubiquitin conjugation. RESULTS: The model
output shows good agreement with experimental data under a
number of different conditions. However, our model predicts
that monomeric ubiquitin pools are always depleted under
conditions of proteasome inhibition, whereas experimental data
show that monomeric pools were depleted in IMR-90 cells but not
in ts20 cells, suggesting that cell lines vary in their ability
to replenish ubiquitin pools and there is the need to
incorporate ubiquitin turnover into the model. Sensitivity
analysis of the model revealed which parameters have an
important effect on protein turnover and aggregation kinetics.
CONCLUSION: We have developed a model of the
ubiquitin-proteasome system using an iterative approach of
model building and validation against experimental data. Using
SBML to encode the model ensures that it can be easily modified
and extended as more data become available. Important aspects
to be included in subsequent models are details of ubiquitin
turnover, models of autophagy, the inclusion of a pool of
short-lived proteins and further details of the aggregation
process.
This model is hosted on
BioModels Database
and identified by:
BIOMD0000000105.
To cite BioModels Database, please use:
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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.
2024-09-02 | BIOMD0000000105 | BioModels
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