Transcriptomics

Dataset Information

0

Effects of Lipocalin 2 (Lcn2), iron, and the bacterial siderophore Enterobactin on A549 respiratory cell gene expression


ABSTRACT: Iron is essential for many cellular processes and is required by bacteria for replication. To acquire iron from the host, pathogenic Gram-negative bacteria secrete siderophores, including Enterobactin (Ent). However, Ent is bound by the host protein Lipocalin 2 (Lcn2), preventing bacterial reuptake of aferric or ferric Ent. In two experiments we treated A549 (lung cancer cell line) cells with Lcn2, Ent, and iron, alone and in combination. In experiment 1, biological duplicates of 4 conditions were used: PBS control, Lcn2, Lcn2+Ent, and Lcn2+Ent+iron. In experiment 2, 4 biological replicates of 4 conditions were used: PBS control, Ent, iron, and Ent+iron. Targets made from the samples were hybridized to Affymetrix Human Gene 1.0 ST arrays to measure transcript abundances. The RMA algorithm was used to estimate transcript levels. Replicate samples were exchangeable, so we fit one-way ANOVA models to log2-transformed data separately to each experiment, and tested for pairwise differences between groups in each experiment, as well as asking if the Ent vs. PBS differences were larger or smaller than the Ent+iron vs. iron differences (Ent by iron interactions). We report results for 29096 probe-sets that were not annotated as positive or negative controls on the array. A supplementary Excel workbook is provided that contains the estimated expression level, some probe-set annotation, and simple statistical analysis for each probe-set. It may be convenient for some users, however obtaining newer probe-set annotation may be advisable.

ORGANISM(S): Homo sapiens

PROVIDER: GSE54962 | GEO | 2014/07/03

SECONDARY ACCESSION(S): PRJNA238171

REPOSITORIES: GEO

Dataset's files

Source:
Action DRS
Other
Items per page:
1 - 1 of 1

Similar Datasets

2014-07-03 | E-GEOD-54962 | biostudies-arrayexpress
2021-04-29 | PXD023712 | Pride
2020-07-16 | GSE144848 | GEO
2020-07-16 | GSE150660 | GEO
2012-12-13 | GSE32523 | GEO
2024-09-02 | BIOMD0000000734 | BioModels
2023-07-06 | MSV000092364 | MassIVE
2012-02-06 | E-GEOD-28242 | biostudies-arrayexpress
2015-08-04 | GSE67695 | GEO
2021-04-02 | GSE156079 | GEO