Ontology highlight
ABSTRACT:
PROVIDER: PRJNA382079 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR5429400_1.fastq.gz | Fastqsanger.gz | |||
| SRR5429400_2.fastq.gz | Fastqsanger.gz | |||
| SRR5429410_1.fastq.gz | Fastqsanger.gz | |||
| SRR5429410_2.fastq.gz | Fastqsanger.gz | |||
| SRR5429420_1.fastq.gz | Fastqsanger.gz |
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Project description:Infection is a devastating post-surgical complication, often necessitating additional procedures and prolonged antibiotic therapy. This is especially relevant for craniotomy and prosthetic joint infections, both of which are characterized by biofilm formation on the bone or implant surface, respectively, with S. aureus representing a primary cause. The effectiveness of immune responses to these infections is predicated on both host- and pathogen-derived signals in the infection microenvironment. However, the extent to which these signals differ across distinct tissue niches and influence immune function remains relatively unknown. Using mouse models of S. aureus craniotomy and prosthetic joint infection complemented with patient samples from both infectious modalities, we show profound metabolomic, transcriptomic, and functional differences that are dependent on tissue niche. These signatures were both spatially and temporally distinct, differing not only between surgical site infections but evolving over time within a single model. These findings highlight the unique immune attributes of biofilms that are heavily influenced by the local tissue microenvironment, which will likely have important implications when designing therapeutic approaches to target specific infections.
2024-07-08 | GSE252481 | GEO
Project description:Metagenomic sequences from Joint infections Metagenome
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Project description:Staphylococcus aureus prosthetic joint infections (PJIs) are considered incurable. Unfortunately, clinical diagnostics to guide conservative vs. aggressive surgical treatment of PJI patients are not evidence-based. Developing clinical biomarkers are crucial for defining immunopathogenesis of PJIs. PJI in humanized mice is characterized by increased infection, bone osteolysis, and large numbers of proliferating CD3+/Tbet+ cells adjacent to purulent abscesses in the bone marrow. Multi-omics studies in a humanized NSG-SGM3 BLT PJI mouse indicated the role of human T cells where 1) human T cells are remarkably heterogenous in gene expression and numbers, 2) human Th1/Th17 exists as a mixed population of activated, progenitor-exhausted, and terminally-exhausted cells which exhibit increased expression of immune checkpoint proteins (LAG3, TIM-3) 2-weeks post-infection. Moreover, these proteins are upregulated in the serum and the bone marrow of S. aureus PJI patients. A multiparametric nomogram combining high serum immune checkpoint protein levels with low proinflammatory cytokine levels (IFN-g, IL-2, TNF-α, IL-17) revealed that TIM-3 was highly predictive of adverse outcomes in PJI patients (AUC=0.89). Hence, T cell impairment in the form of immune checkpoint expression and exhaustion could be a functional biomarker for S. aureus PJI disease outcome, and checkpoint blockade may benefit PJI patients.
2026-06-30 | GSE269658 | GEO
Project description:The paper describes a model of multiple myeloma.
Created by COPASI 4.26 (Build 213)
This model is described in the article:
A mathematical model of cell equilibrium and joint cell formation in multiple myeloma
M.A. Koenders, R. Saso
Journal of Theoretical Biology 390 (2016) 73–79
Abstract:
In Multiple Myeloma Bone Disease healthy bone remodelling is affected by tumour cells by means of paracrine cytokinetic signalling in such a way that osteoclast formation is enhanced and the growth of osteoblast cells inhibited. The participating cytokines are described in the literature. Osteoclast-induced myeloma cell growth is also reported. Based on existing mathematical models for healthy bone remo- delling a three-way equilibrium model is presented for osteoclasts, osteoblasts and myeloma cell populations to describe the progress of the illness in a scenario in which there is a secular increase in the cytokinetic interactive effectiveness of paracrine processes. The equilibrium state for the system is obtained. The paracrine interactive effectiveness is explored by parameter variation and the stable region in the parameter space is identified. Then recently-discovered joint myeloma–osteoclast cells are added to the model to describe the populations inside lytic lesions. It transpires that their presence expands the available parameter space for stable equilibrium, thus permitting a detrimental, larger population of osteoclasts and myeloma cells. A possible relapse mechanism for the illness is explored by letting joint cells dissociate. The mathematics then permits the evaluation of the evolution of the cell populations as a function of time during relapse.
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2024-09-02 | BIOMD0000000804 | BioModels