Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Multi-omics and genome-scale modeling reveal a metabolic shift during C. elegans ageing

ABSTRACT: Multi-omics and genome-scale modeling reveal a metabolic shift during C. elegans ageing

PROVIDER: PRJNA514750 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR8435660.fastq.gz	Fastqsanger.gz
	SRR8435670.fastq.gz	Fastqsanger.gz
	SRR8435680.fastq.gz	Fastqsanger.gz
	SRR8435690.fastq.gz	Fastqsanger.gz
	SRR8435661.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 45

Similar Datasets

Multi-omics and genome-scale modeling reveal a metabolic shift during C. elegans ageing

Project description:We conducted a time series of transcriptomics measurements during normal ageing in C. elegans in two non-reproductive strains (fem and gem) during normal ageing (days 1 to 10 of adulthood) and used this together with a multi-omics modelling pipeline to explore the changes that take place due to ageing.

2019-01-11 | GSE124994 | GEO

Multi-Omics and Genome-Scale Modeling Reveal a Metabolic Shift During <i>C. elegans</i> Aging.

Project description:In this contribution, we describe a multi-omics systems biology study of the metabolic changes that occur during aging in Caenorhabditis elegans. Sampling several time points from young adulthood until early old age, our study covers the full duration of aging and include transcriptomics, and targeted MS-based metabolomics. In order to focus on the metabolic changes due to age we used two strains that are metabolically close to wild-type, yet are conditionally non-reproductive. Using these data in combination with a whole-genome model of the metabolism of C. elegans and mathematical modeling, we predicted metabolic fluxes during early aging. We find that standard Flux Balance Analysis does not accurately predict in vivo measured fluxes nor age-related changes associated with the Citric Acid cycle. We present a novel Flux Balance Analysis method where we combined biomass production and targeted metabolomics information to generate an objective function that is more suitable for aging studies. We validated this approach with a detailed case study of the age-associated changes in the Citric Acid cycle. Our approach provides a comprehensive time-resolved multi-omics and modeling resource for studying the metabolic changes during normal aging in C. elegans.

| S-EPMC6372924 | biostudies-literature

Dynamic multi-omics and mechanistic modeling approach uncovers novel mechanisms of kidney fibrosis progression

Project description:Kidney fibrosis, characterized by excessive extracellular matrix (ECM) deposition, is a progressive disease that, despite affecting 10% of the population, lacks specific treatments and suitable biomarkers. Aimed at unraveling disease mechanisms and identifying potential therapeutic targets, this study presents a comprehensive, time-resolved multi-omics analysis of kidney fibrosis using an in vitro model system based on human kidney PDGFRβ+ mesenchymal cells. Using computational network modeling we integrated transcriptomics, proteomics, phosphoproteomics, and secretomics with imaging of the extracellular matrix (ECM). We quantified over 14,000 biomolecules across seven time points following TGF-β stimulation, revealing distinct temporal patterns in the expression and activity of known and potential novel renal fibrosis markers and modulators. The resulting time-resolved multi-omic network models allowed us to propose mechanisms related to fibrosis progression through early transcriptional reprogramming. Using siRNA knockdowns and phenotypic assays, we validated predictions and elucidated regulatory mechanisms underlying kidney fibrosis. Notably, we demonstrate that several early-activated transcription factors, including FLI1 and E2F1, act as negative regulators of collagen deposition and propose underlying molecular mechanisms. This work advances our understanding of the pathogenesis of kidney fibrosis and provides a valuable resource for the organ fibrosis research community.

2024-11-07 | E-MTAB-14521 | biostudies-arrayexpress

An integrated organoid omics map extends modeling potential of kidney disease

Project description:An integrated organoid omics map extends modeling potential of kidney disease

| PRJNA883395 | ENA

Time-course in rice leaves of the temperature shift experiment

2012-12-07 | GSE36595 | GEO

Time-course in rice leaves of the temperature shift experiment

Project description:Time-course transcriptional profiling of rice leaf of the temperature shift experiment in a growth chamber. This experiment was performed to validate the results of field transcriptomic modeling. Rice leaves (cv. Norin8) were collected at 2:00 and 14:00 on the day -1, 2, 4 and 6 from the temperature shift (diurnal cycle temperature condition to continuous temperature condition). Two biological replicates for each sampling time point.

2012-12-07 | E-GEOD-36595 | biostudies-arrayexpress

Intermittent Hypoxia ageing

Project description:Intermittent Hypoxia ageing

| PRJNA263964 | ENA

Omics analysis with modeling reveals global adaptation of Aspergillus niger to hypoxic condition

Project description:Omics analysis with modeling reveals global adaptation of Aspergillus niger to hypoxic condition

| PRJNA431301 | ENA

Modeling Hepatoblastoma

Project description:Modeling Hepatoblastoma

| PRJNA749045 | ENA

Dynamic multi-omics and mechanistic modeling approach uncovers novel mechanisms of kidney fibrosis progression

Project description:Dynamic multi-omics and mechanistic modeling approach uncovers novel mechanisms of kidney fibrosis progression