A multi-scale approach reveals that NFkB cRel enforces a B-cell decision to divide.
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE64156 | GEO | 2015/02/18
SECONDARY ACCESSION(S): PRJNA270331
REPOSITORIES: GEO
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Project description:The transcriptomes of individual small and large B cells after 24 h of stimulation were sequenced and genes upregulated in small or large cells were found and analyzed to provide a global charactarization of transcription patterns in growing B cells. We identified 5 large and 5 small viable B cells from images of the C1 IFC containing captured cells. We prepared libraries for the 10 individual cells, a positive bulk control (containing diluted bulk cDNA), a negative control containing only the ERCC spikeins, and a 0h bulk control.
2015-02-18 | E-GEOD-64156 | biostudies-arrayexpress
Project description:Understanding the functions of multi-cellular organs in terms of the molecular networks within each cell is an important step in the quest to predict phenotype from genotype. B-lymphocyte population dynamics, which are predictive of immune response and vaccine effectiveness, are determined by individual cells undergoing division or death seemingly stochastically. Based on tracking single-cell time-lapse trajectories of hundreds of B cells, single-cell transcriptome, and immunofluorescence analyses, we constructed an agent-based multi-modular computational model to simulate lymphocyte population dynamics in terms of the molecular networks that control NF-?B signaling, the cell cycle, and apoptosis. Combining modeling and experimentation, we found that NF-?B cRel enforces the execution of a cellular decision between mutually exclusive fates by promoting survival in growing cells. But as cRel deficiency causes growing B cells to die at similar rates to non-growing cells, our analysis reveals that the phenomenological decision model of wild-type cells is rooted in a biased race of cell fates. We show that a multi-scale modeling approach allows for the prediction of dynamic organ-level physiology in terms of intra-cellular molecular networks.
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Project description:ObjectiveDesign and build a strategy construction and evaluation software system to help stakeholders to develop viable strategies to expand (and adapt) the Chagas Platform healthcare model through the primary healthcare system in Bolivia.MethodsThe software was built based on a ranking of medical Interventions and Actions (needed to support Interventions' implementation) needed for comprehensive management of Chagas Disease in Bolivia. The ranking was performed using a Multi Criteria Decision Analysis (MCDA) methodology adapted to the WHO's building blocks framework. Data regarding the criteria and the rankings was obtained through surveys and interviews with health care professionals working on Chagas disease. The Analytical Hierarchy Process was used to construct the decision criteria weights. Data Envelopment Analysis was used to identify the Interventions that lay on the efficiency frontier of outcomes and the complexity of associated Actions. These techniques were combined with integer programing tools using the open-source software R to build a decision-making tool to assess the outcomes and complexity of any combination of Interventions and Actions. This model and tool were applied to data concerning the care of Chagas disease in Bolivia collected through surveys of experts. The tool works by loading the data from each specific context.ResultsThe initial set of Interventions and Actions recommended after analysis of the survey data was further refined through face-to-face interviews with field experts in Bolivia, resulting in a strategy of 18 Interventions and 15 Actions. Within the WHO model the Leadership and Governance building block came up as the one needing more support with Actions such as the inclusion of Chagas into Annual Municipal Operational Plans by appointing local and provincial coordinators.ConclusionThis project established the suitability of the model for constructing healthcare strategies. The model could be developed further resulting in a decision-making tool for program managers in a wide range of healthcare related issues, including neglected and/ or prevalent diseases. The tool has the potential to be used at different stages of decision making by diverse stakeholders in order to coordinate activities needed to address a health problem.
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Project description:NF-kB is a transcriptional factor that consists in homo and heterodimers of the large family of Rel subunits. Among the most important functions for NF-kB, initiation of immunological/inflammatory responses and regulation of cell proliferation/apoptosis which are the major features of severe infections. Although the role of NF-kB is crucial in host defense against pathogens, mice deficient for individual subunits of NF-kB have not been explored in murine models of polymicrobial infection. In this report, we have investigated in vivo the consequences of cRel subunit deficiency in the survival to polymicrobial infection. We have also approached the underlying mechanisms of the host defense by analyzing cytokine production, bacterial clearance and the distribution of innate and adaptive immune cells. Absence of cRel enhances mice mortality to polymicrobial sepsis. The decreased survival of cRel-/- animals upon infection is not related to altered local mechanisms of innate defense such as the peritoneal recruitment of the Gr.1+CD11b+ phagocytic cells and the bacterial clearance. However, cRel deficiency allows to altered systemic cytokine response associated to sustained loss of the lymphoïd subset CD8a+ of spleen dendritic cells, key antigen-presenting cells for the initiation of the adaptive immunity. Genome-wide analysis of the systemic host response to polymicrobial sepsis reveals inflammatory/immune and apoptotic gene signatures associated to cRel subunit. In this study we identified the NF-kB member cRel, as a key factor which plays a critical role in survival to polymicrobial sepsis and also as a regulatory transcription subunit controlling the inflammatory and the adaptive immune responses in severe infection.
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