Brucella sp.
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA742519 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:We focused on whether transposon mutagenesis in Brucella abortus could induce difference in the trascriptional responses of RAW 264.7 cell infection model compared to the wild strain infected RAW 264.7 cells. The function of genes in Brucella abortus was analyzed through the identified differences in gene expression between RAW 264.7 cell infected with wild and mutant strains.
2016-03-16 | GSE79264 | GEO
Project description:We focused on whether transposon mutagenesis in Brucella abortus could induce difference in the trascriptional responses of RAW 264.7 cell infection model compared to the wild strain infected RAW 264.7 cells. The function of genes in Brucella abortus was analyzed through the identified differences in gene expression between RAW 264.7 cell infected with wild and mutant strains. We analyzed altered transcription in RAW 264.7 cells at 0, 6, 12, and 24 h following the infection with 10 MOI of Brucella abortus wild and mutant strains.
2016-03-16 | E-GEOD-79264 | biostudies-arrayexpress
Project description:Gene expression analysis of wild-type and STING knock-out mouse bone marrow-derived macrophages (mBMDM) infected with Brucella abortus or transfected with Brucella abortus DNA. Genes whose expression are affected by Brucella abortus in a STING-dependent manner will be identified and signaling pathways regulated by STING will be elucidated.
2017-11-06 | GSE96071 | GEO
Project description:ChIP-seq analysis of GcrA atypical transcription factor in Brucella abortus
2019-09-03 | GSE136733 | GEO
Project description:Brucella abortus ChipSeq analysis of BvrR
2020-11-10 | E-MTAB-9740 | biostudies-arrayexpress
Project description:Brucella abortus 2308 Raw sequence reads
| PRJNA765312 | ENA
Project description:We describe the isolation of sufficient Brucella abortus RNA from primary host cell environment using modified reported methods for RNA-seq analysis, and simultaneously characterize the transcriptional profiles of intracellular B. abortus and bone marrow-derived macrophages (BMM) from BALB/c mice at 24 h (replicative phase) post-infection.
2017-07-08 | GSE100914 | GEO
Project description:Goal: High-throughput sequencing-by-synthesis (Illumina) RNA sequencing technology was carried out with an aim to gain deeper understanding of immune host protective mechanisms. Here, RNA-seq was applied to understand the differential gene expression profile of mice spleen following immunization with Brucella abortus S19∆per mutant (perosamine synthetase gene mutant of Brucella abortus S19) in comparison to mock immunized mice spleen (PBS inoculated). Methods: RNA-seq data of 15th day post immunized mice spleen (with Brucella abortus S19∆per) and PBS control mice were generated by deep sequencing ( in duplicate) using IlluminaNextSeq 500 . The sequence reads that passed quality filters were analyzed for transcript abundance using RSEM package (RNA-Seq by Expectation Maximization) (Li and Dewey, 2011). Breifly, the RSEM package generated a reference sequence based on given mouse transcript annotations (Mus_musculus.GrCm38.83.chr.gtf.gz). The Bowtie allignmet tool available within the package was used to calculate expected counts (number of mapped reads) using quality trimmed reads and reference sequence. Finally, the expected counts estimated by RSEM were fed into different DE package tools, such as DESeq2 (Love et al., 2014), edgeR (Robinson et al., 2010) and EBSeq (Leng et al., 2013) in order to identify differentially expressed genes across spleen samples (B. abortus S19∆per versus (vs) PBS control. Functional annotation of differently expressed genes were carried out using g:Profiler (Reimandet al., 2016; http://biit.cs.ut.ee/gprofiler/). Results: A mean of 37.58 million processed reads (range: 30.51 million to 51.79 million reads per individual RNA-seq library) were generated during the experiment. The expected counts generated by the RSEM package followed by differential analysis calculation using different DE packages identified a total of 1917 differentially expressed genes (DEGs), of which 968 and 949 genes were up- and down-regulated respectively. Functional annotation revealed 545 significantly enriched genes to be associated with immune system processes within the total 1917 differentially expressed genes. Further analysis revealed 21 genes showing significant expression were also in MHC-I and MHC-II antigen processing and presentation pathway during S19∆per immunization. Conclusions:The RNA-seq data revealed the coordinated up-regulation of MHC-I and MHC-II processing pathways providing insights into the molecular mechanism of immune protection conferred by B. abortus S19∆per in mice at day 15 post immunization and might aid in the development of new attenuated vaccine strains with improved efficacy.
2019-10-09 | GSE121040 | GEO
Project description:Brucellosis, an important bacterial zoonosis caused by Brucella species, has drawn increased attention around the world. As an intracellular pathogen, the ability of Brucella to deal with stress within the host cell is closely related to its virulence. The survival pressure on Brucella within a phagosome is considered similar to that during the stationary phase. Here, label-free proteomics approach was used to study the adaptive response of Brucella abortus (B. abortus) in the stationary stage. 182 down-regulated and 140 up-regulated proteins were found in the stationary-phase B. abortus. B. abortus adapted to adverse environmental changes by regulating virulence, reproduction, transcription, translation, stress response, and energy production. In addition, both logarithmic and stationary-phase B. abortus were treated with short-term starvation. The logarithmic-phase B. abortus restricted cell reproduction and energy utilization in response to nutritional stress. Additionally, the expression levels of some virulence-related proteins were identified as being significantly regulated during the transition from logarithmic to stationary phase or under starvation treatment, such as Type IV secretion system protein (T4SS), VjbR, and integration host factor (IHF). Altogether, we outlined adaptive mechanisms that B. abortus could employ during the growth and compared the differences between logarithmic and stationary-phase B. abortus in response to starvation.
2021-09-09 | PXD020869 | Pride