New insights into the maize disease lesion mimics-conferred defense response revealed by integrated transcriptomics and metabolomics analysis
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA623523 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:We performed integrated transcriptomics and metabolomics analysis on three dominant Les mutants Les4, Les10 and Les17.
2021-05-12 | GSE148220 | GEO
Project description:Liver Cancer Evolution - Lesion segregation
| PRJEB37808 | ENA
Project description:Bearded lizard lesion investigation
| PRJEB25832 | ENA
Project description:Tibetan sheep microbiome and metabolomics
| PRJEB36249 | ENA
Project description:Sciatic nerve crush (SNC) triggers sterile inflammation within the distal nerve and deafferented dorsal root ganglia (DRGs). Granulocytes and pro-inflammatory Ly6Chigh monocytes infiltrate the nerve first, and rapidly give way to Ly6C- inflammation-resolving macrophages. Inflammation in DRGs is dominated by tissue resident macrophages, with little contribution from hematogenous leukocytes. Single-cell transcriptomics analysis of injured nerve identified six macrophage subpopulations, repair Schwann cells, and mesenchymal cells as the main cell types. Macrophages at the nerve crush site are distinct from macrophages associated with degenerating nerve fibers. Monocytes and macrophages in the injured nerve “eat” cell corpses of apoptotic leukocytes and thereby promote an anti-inflammatory milieu. Myeloid cells in the injured nerve, but not DRGs, strongly express the receptor for the chemokine GM-CSF. In the absence of GM-CSF, conditioning-lesion induced regeneration of DRG neuron central projections is abolished. Thus, a carefully orchestrated immune response in the nerve is required for conditioning-lesion induced neurorepair.
2021-03-17 | GSE153240 | GEO
Project description:Gene expression analysis of motor cortex after spinal C3 lesion
2016-07-01 | GSE76679 | GEO
Project description:Multiple sclerosis (MS) is an inflammatory disease of the central nervous system characterised by myelin loss and progressive neurodegeneration. To better understand MS lesion initiation and progression, we generated spatial gene activity maps of white (WM) and grey matter (GM) MS lesions. In different MS lesion types, we detected novel transcriptional domains, including an identifiable rim around active WM lesions. These active lesion rims were characterised by changes in astrocytic, oligodendrocytic, and microglial gene activity. Furthermore, we identified three novel WM lesion trajectories, predicting how normal appearing WM could progress into WM lesions, with lesion rims, active lesion cores, and mixed active/inactive lesion cores as potential outcomes. Our findings offer new insights into MS lesion progression, and the dynamic molecular and cellular processes that underlie MS.
2024-08-05 | GSE208747 | GEO
Project description:The interplay between pathogens and hosts has been studied for decades using targeted approaches such as the analysis of mutants and host immunological responses. Although much has been learned from such studies, they focus on individual pathways and fail to reveal the global effects of infection on the host. To alleviate this issue, high-throughput methods such as transcriptomics and proteomics have been used to study host-pathogen interactions. Recently, metabolomics was established as a new method to study changes in the biochemical composition of host tissues. We report a metabolomics study of Salmonella enterica serovar Typhimurium infection. We used Fourier Transform Ion Cyclotron Resonance Mass Spectrometry with Direct Infusion to reveal that dozens of host metabolic pathways are affected by Salmonella in a murine infection model. In particular, multiple host hormone pathways are disrupted. Our results identify unappreciated effects of infection on host metabolism and shed light on mechanisms used by Salmonella to cause disease, and by the host to counter infection. Female C57BL/6 mice were infected with Salmonella enterica serovar Typhimurium SL1344 cells by oral gavage. Feces and livers were collected and metabolites extracted using acetonitrile. For experiments with feces, samples were collected from 4 mice before and after infection. For liver experiments, 11 uninfected and 11 infected mice were used. Samples were combined into 3 groups of 3-4 mice each, resulting in the analysis of 3 group samples of uninfected and 3 of infected mice. Extracts were infused into a 12-T Apex-Qe hybrid quadrupole-FT-ICR mass spectrometer equipped with an Apollo II electrospray ionization source, a quadrupole mass filter and a hexapole collision cell. Raw mass spectrometry data were processed as described elsewhere (Han et al. 2008. Metabolomics. 4:128-140 [PMID 19081807]). To identify differences in metabolite composition between uninfected and infected samples, we filtered the list of masses for metabolites which were present on one set of samples but not the other. Additionally, we calculated the ratios between averaged intensities of metabolites from uninfected and infected mice. To assign possible metabolite identities, monoisotopic neutral masses of interest were queried against MassTrix (http://masstrix.org). Masses were searched against the Mus musculus database within a mass error of 3 ppm. Data were analyzed by unpaired t tests with 95% confidence intervals.
2011-02-08 | E-GEOD-21720 | biostudies-arrayexpress
Project description:This series represents samples of multiple myeloma patients with bone lytic lesion by MRI. Keywords = multiple myeloma Keywords = osteolytic lesions Keywords = MRI Keywords = osteoblast Keywords = mesenchymal stem cell Keywords = Wnt signaling Keywords = DKK1 Keywords: other
2004-01-01 | GSE754 | GEO
Project description:This series represents samples of multiple myeloma patients without bone lytic lesion by MRI. Keywords = multiple myeloma Keywords = osteolytic lesions Keywords = MRI Keywords = osteoblast Keywords = mesenchymal stem cell Keywords = Wnt signaling Keywords = DKK1 Keywords: other
2004-01-01 | GSE753 | GEO