|
| Status |
Public on Oct 11, 2024 |
| Title |
MOC_1779:pip:800.00000uM:90min:PA14:MOC_1779_2:r1 |
| Sample type |
SRA |
| |
|
| Source name |
PA14
|
| Organism |
Pseudomonas aeruginosa UCBPP-PA14 |
| Characteristics |
cell line: PA14
pert id: pip
pert iname: Piperacillin
pert dose: 800
pert dose_unit: uM
pert idose: 800.00000uM
pert time: 90
pert time_unit: min
pert itime: 90min
pert type: poscon
category: antimicrobial_reference_set
project id: MOC_1779
replicate id: r1
project plate_id_384well: MOC_1779_2
strain id: PA14
weak_signal: FALSE
|
| Treatment protocol |
Cells were treated at 37°C without shaking in a humidity chamber. In the case of the RNA-Seq Time Trial, cells were treated for 30, 60, 90, and 120 minutes. In the case of all other RNA-Seq experiments, cells were treated for 90 minutes.
|
| Growth protocol |
Bacterial cultures were grown with shaking (37°C, 250rpm) to mid-log phase, and 30uL of cultures were mixed with equal volume of 2X compound working solution, yielding final conditions containing 1x108 CFU/mL bacteria and with compounds (or vehicle) in 0.5% (v/v) DMSO or water in LB.
|
| Extracted molecule |
total RNA |
| Extraction protocol |
At the end of the incubation period, samples were mixed with 30uL of 3X RNAgem Blue Buffer (Zygem, Charlottesville VA), and chemically lysed by incubation in a thermocycler at 75°C for 10 minutes. Total RNA was then extracted using the Direct-zol kit (Zymo Research, Irvin CA), and RNA quality and quantity were analyzed using the RNA ScreenTape with the 2200 TapeStation (Agilent, Santa Clara CA).
RNA-Seq libraries were prepared using the RNA TagSeq protocol previously described (Shishkin, A. et al. Nature methods. 2015. https://doi.org/10.1038/nmeth.3313)
|
| |
|
| Library strategy |
RNA-Seq |
| Library source |
transcriptomic |
| Library selection |
cDNA |
| Instrument model |
Illumina NovaSeq 6000 |
| |
|
| Description |
moc1430_1779_0066_0110_2kd_counts_manuscript.csv
moc1430_1779_0066_0110_2kd_modzscore_ref_set.csv
|
| Data processing |
BWA to align reads to reference
QC & filter samples with low counts and genes with low counts
DESeq2 to identify weak and robust transcriptional signals
VST function from DESeq2 for variance stabilization of counts
Calculate moderated z-scores using custom scripts, based on previously published scripts (Subramanian, A. et al. Cell. 2017. https://doi.org/10.1016/j.cell.2017.10.049)
Assembly: NC_0088463.1 (UCBPP-PA14)
Supplementary files format and content: comma separated file with counts for each sample
Supplementary files format and content: comma separated file with moderated z-score values for each treatment condition (replicates collapsed)
|
| |
|
| Submission date |
Dec 20, 2023 |
| Last update date |
Oct 11, 2024 |
| Contact name |
Keith Romano |
| Organization name |
Massachusetts General Hospital
|
| Department |
Molecular Biology
|
| Lab |
Hung Lab
|
| Street address |
185 Cambridge St.
|
| City |
Boston |
| ZIP/Postal code |
02114 |
| Country |
USA |
| |
|
| Platform ID |
GPL27892 |
| Series (1) |
| GSE251671 |
Perturbation-Specific Transcriptional Mapping for unbiased target elucidation of antibiotics |
|
| Relations |
| BioSample |
SAMN38978047 |
| SRA |
SRX22977244 |
