Ontology highlight
ABSTRACT:
PROVIDER: PRJNA898602 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR22221858_1.fastq.gz | Fastqsanger.gz | |||
| SRR22221858_2.fastq.gz | Fastqsanger.gz | |||
| SRR22221859_1.fastq.gz | Fastqsanger.gz | |||
| SRR22221859_2.fastq.gz | Fastqsanger.gz | |||
| SRR22221860_1.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 30 |
Similar Datasets
Project description:Transcriptome profiling identified genes and pathways associated with arsenic toxicity and tolerance in Arabidopsis
2015-06-01 | E-GEOD-31977 | ExpressionAtlas
Project description:Transcriptome sequencing of tomato roots exposed to nickel toxicity
| PRJNA952142 | ENA
Project description:Transcriptome sequencing of tomato roots exposed to copper toxicity
| PRJNA895212 | ENA
Project description:Transcriptome sequencing of human hepatocellular carcinoma
2025-01-24 | E-GEOD-33294 | ExpressionAtlas
Project description:In the present study, we employed the RNA sequencing platform to examine the molecular response of zebrafish liver to arsenic exposure and carry out detailed transcriptomic analyses for further understanding of molecular toxicity. We found that several important biological processes were perturbed by arsenic exposure, including oxidation reduction, translation, iron ion transport, cell redox and homeostasis, as well as related pathways in metabolism and diseases. Furthermore, as there are currently no biomarker genes available for predicting arsenic exposure, we took the advantage of RNA sequencing platform to identify most suitable biomarker genes from top responsive genes to arsenic exposure. We first validated these top responsive genes by RT-qPCR in zebrafish and then in Japanese medaka (Oryzias latipes) at individual fish level for more robustly responsive genes across different fish species. Transcriptome profiling of arsenic-treated sample and control sample were generated by deep sequencing using 3' RNA-SAGE on the SOLiD system.
2013-09-04 | E-GEOD-48427 | biostudies-arrayexpress
Project description:Transcription profiling by array of Arabidopsis roots exposed to roots of Hieracium pilosella to study root-root interactions
2015-11-26 | E-MTAB-1582 | ExpressionAtlas
Project description:Talemi2014 - Arsenic toxicity and
detoxification mechanisms in yeast
The model implements arsenite (AsIII)
transport regulation, its distribution within main cellular AsIII
pools and detoxification. The intracellular As pools considered are
free AsIII (AsIIIin), protein-bound AsIII (AsIIIprot), glutathione
conjugated AsIII (AsGS3) and vacuolar sequestered AsIII (vAsGS3).
This model is described in the article:
Mathematical modelling of
arsenic transport, distribution and detoxification processes in
yeast.
Talemi SR, Jacobson T, Garla V,
Navarrete C, Wagner A, Tamás MJ, Schaber J.
Mol. Microbiol. 2014 Jun; 92(6):
1343-1356
Abstract:
Arsenic has a dual role as causative and curative agent of
human disease. Therefore, there is considerable interest in
elucidating arsenic toxicity and detoxification mechanisms. By
an ensemble modelling approach, we identified a best
parsimonious mathematical model which recapitulates and
predicts intracellular arsenic dynamics for different
conditions and mutants, thereby providing novel insights into
arsenic toxicity and detoxification mechanisms in yeast, which
could partly be confirmed experimentally by dedicated
experiments. Specifically, our analyses suggest that: (i)
arsenic is mainly protein-bound during short-term (acute)
exposure, whereas glutathione-conjugated arsenic dominates
during long-term (chronic) exposure, (ii) arsenic is not stably
retained, but can leave the vacuole via an export mechanism,
and (iii) Fps1 is controlled by Hog1-dependent and
Hog1-independent mechanisms during arsenite stress. Our results
challenge glutathione depletion as a key mechanism for arsenic
toxicity and instead suggest that (iv) increased glutathione
biosynthesis protects the proteome against the damaging effects
of arsenic and that (v) widespread protein inactivation
contributes to the toxicity of this metalloid. Our work in
yeast may prove useful to elucidate similar mechanisms in
higher eukaryotes and have implications for the use of arsenic
in medical therapy.
This model is hosted on
BioModels Database
and identified by:
BIOMD0000000547.
To cite BioModels Database, please use:
BioModels Database:
An enhanced, curated and annotated resource for published
quantitative kinetic models.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to
the public domain worldwide. Please refer to
CC0
Public Domain Dedication for more information.
2024-09-02 | BIOMD0000000547 | BioModels