|
| Status |
Public on May 08, 2019 |
| Title |
Bps_acute_Disease [7800220062_D] |
| Sample type |
RNA |
| |
|
| Source name |
Bps_acute_Disease
|
| Organism |
Mus musculus |
| Characteristics |
mouse strain: C57BL/6
mouse model: Burkholderia pseudomallei - acute
condition: Disease
infection protocol: Burkholderia pseudomallei strain 576 originally isolated from a melioidosis patient was provided by Dr. T. Pitt (Health Protection Agency, London, UK). Female C57BL/6 mice were infected intranasally with 50 ml containing 2,500 colony forming units (acute model) of B. pseudomallei derived from cryopreserved stocks diluted in pyrogen-free saline. Control uninfected mice received 50 ml pyrogen-free saline only. Lung samples were collected from individual infected and control treated mice on day 3 post infection.
tissue: lung
|
| Extracted molecule |
total RNA |
| Extraction protocol |
Tissues were collected in TRI-Reagent (Sigma-Aldrich) (for Toxoplasma gondii samples –tissues were collected and samples were stored in RNAlater (Ambion), and then transferred to TRI-Reagent). Total RNA was extracted using the RiboPure™ Kit (Ambion).
|
| Label |
biotin
|
| Label protocol |
cRNA was prepared from 200 ng tissue total RNA using the Illumina TotalPrep RNA Amplification Kit (Ambion). Quality was checked using an RNA 6000 Nano kit (Agilent) using a BioAnalyzer 2100 (Agilent). Biotinylated cRNA samples were randomized.
|
| |
|
| Hybridization protocol |
1.5 µg cRNA was then hybridized to Mouse WG-6 v2.0 bead chips (Illumina) according to the manufacturer’s protocols.
|
| Scan protocol |
Standard Illumina scanning protocol
|
| Description |
raw data file: MRC22.txt
Disease samples from Burkholderia pseudomallei - acute infection model
|
| Data processing |
Microarray data was processed in GeneSpring GX v14.8 (Agilent Technologies). Flags were used to filter out the probe sets that did not result in a ‘present’ call in at least 10% of the samples, with the ‘present’ lower cut-off of 0.99. Signal values were then set to a threshold level of 10, log2 transformed, and per-chip normalised using 75th percentile shift algorithm. Next, per-gene normalisation was applied by dividing each messenger RNA transcript by the median intensity of all the samples. Next, transcripts were filtered to select the most variable probes: those that had a minimum of 1.5-fold expression change compared with the median intensity across all samples, in greater than 10% of all samples.
|
| |
|
| Submission date |
Sep 12, 2018 |
| Last update date |
May 08, 2019 |
| Contact name |
Akul Singhania |
| E-mail(s) |
[email protected]
|
| Phone |
+442037963319
|
| Organization name |
The Francis Crick Institute
|
| Street address |
1 Midland Road
|
| City |
London |
| ZIP/Postal code |
NW1 1AT |
| Country |
United Kingdom |
| |
|
| Platform ID |
GPL17543 |
| Series (2) |
| GSE119849 |
Global transcriptional profiling unveils the interferon network in blood and tissues across different diseases [microarray_lung_6] |
| GSE119856 |
Global transcriptional profiling unveils the interferon network in blood and tissues across different diseases |
|
