Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Whole-cell modeling in yeast predicts compartment-specific proteome constraints that drive metabolic strategies

ABSTRACT: Our comprehensive model identifies condition-dependent and compartment-specific constraints that can explain metabolic strategies and protein expression profiles from growth rate optimization, providin a framework to understand metabolic adaptation in eukaryal cells.

INSTRUMENT(S): LTQ Orbitrap Velos

ORGANISM(S): Saccharomyces Cerevisiae (baker's Yeast)

TISSUE(S): Cell Culture

SUBMITTER: Manuel Garcia-Albornoz

LAB HEAD: Simon Hubbard

PROVIDER: PXD030003 | Pride | 2022-01-24

REPOSITORIES: Pride

ACCESS DATA

Json Xml

Publications

Whole-cell modeling in yeast predicts compartment-specific proteome constraints that drive metabolic strategies.

Elsemman Ibrahim E IE Rodriguez Prado Angelica A Grigaitis Pranas P Garcia Albornoz Manuel M Harman Victoria V Holman Stephen W SW van Heerden Johan J Bruggeman Frank J FJ Bisschops Mark M M MMM Sonnenschein Nikolaus N Hubbard Simon S Beynon Rob R Daran-Lapujade Pascale P Nielsen Jens J Teusink Bas B

Nature communications 20220210 1

When conditions change, unicellular organisms rewire their metabolism to sustain cell maintenance and cellular growth. Such rewiring may be understood as resource re-allocation under cellular constraints. Eukaryal cells contain metabolically active organelles such as mitochondria, competing for cytosolic space and resources, and the nature of the relevant cellular constraints remain to be determined for such cells. Here, we present a comprehensive metabolic model of the yeast cell, based on its ...[more]

PMID: 35145105

Similar Datasets

RNAseq of yeast cells sampled during the lag (10% glucose consumption), mid-exponential (75% glucose consumed) and post-exponential phases (>99% glucose consumed)

Project description:The aim of the study was to identify regulatory elements of promoters associated with glucose-dependent gene expression profiles. For the transcriptome analysis an overnight culture of log-phase S. cerevisiae CEN.PK-113-7D grown in Delft medium was inoculated into a 500mL Delft medium at a starting OD of 0.03We carried out biological triplicate sampling from a 1 ltr BioStat Q bioreactor at 30 degrees with 800rpm agitation, with controlled aeration and pH maintained at 6 using 2M NaOH.

2019-04-01 | E-MTAB-7657 | biostudies-arrayexpress

Functional and cellular constraints that shaped the PPARg binding landscape in human and mouse macrophages

Project description:This SuperSeries is composed of the following subset Series: GSE25137: Functional and cellular constraints that shaped the PPARg binding landscape in human and mouse macrophages: human expression GSE25426: Functional and cellular constraints that shaped the PPARg binding landscape in human and mouse macrophages: human ChIP-Seq Refer to individual Series

2011-12-01 | E-GEOD-25608 | biostudies-arrayexpress

Proteome re-allocation in amino acid supplemented S. cerevisiae using TMT-based quantitative proteomics

Project description:In recent years, more attention in systems biology has been given to the concept of protein constraints and the cell’s necessity to allocate its proteome between important processes. From this point of view, attempts to elucidate cellular maximum capacity of growth as a function of protein availability has been investigated. Elucidating the possibility of optimizing cell proliferation, by tailoring proteome allocation. To experimentally investigate this concept further we cultivated Saccharomyces cerevisiae in bioreactors with or without amino acid supplementation and performed proteomics to analyze global changes in proteome allocation, during anaerobic as well as aerobic growth on glucose. Analysis of proteomic data implies that proteome mass is mainly being re-allocated from amino acid biosynthetic processes into translation, in regard to absolute levels of change, accompanied by an increased growth rate during supplementation. Similar findings were obtained from both aerobic and anaerobic cultivations, and subsequently independent of the two examined metabolic states. Indicating the possibility of increasing growth rate through freeing up proteome mass and increasing proteome allocation towards translational machinery.

2020-08-05 | PXD018361 | Pride

High-throughput laboratory evolution reveals global evolutionary constraints for antibiotic resistance

Project description:Understanding constraints which shape antibiotic resistance is key for predicting and controlling drug resistance. Here, we performed high-throughput laboratory evolution of Escherichia coli. The transcriptome, resistance, and genomic profiles for the evolved strains in 48 environments were quantitatively analyzed. By analyzing the quantitative datasets through interpretable machine learning techniques, the emergence of low dimensional phenotypic states within the 192 strains was observed. Further analysis revealed the underlying biological processes responsible for the distinct states. We also report a novel constraint which leads to decelerated evolution. These findings bridge the genotypic, gene expression, and drug resistance space, and lead to a comprehensive understanding of constraints for antibiotic resistance.

2020-10-12 | GSE137348 | GEO

Targets and genomic constraints of ectopic Dnmt3b expression

Project description:Targets and genomic constraints of ectopic Dnmt3b expression

| PRJNA483553 | ENA

Inheritance of gene expression level and selective constraints on trans- and cis-regulatory changes in yeast

Project description:Gene expression evolution can be caused by changes in cis- or trans-regulatory elements or both. As cis and trans regulation operate through different molecular mechanisms, cis and trans mutations may show different inheritance patterns and may be subjected to different selective constraints. To investigate these issues, we obtained and analyzed gene expression data from two Saccharomyces cerevisiae strains and their hybrid, using high-throughput sequencing. Our data indicate that compared to other types of genes, those with antagonistic cis-trans interactions are more likely to exhibit over- or under-dominant inheritance of expression level. Moreover, in accordance with previous studies, genes with trans variants tend to have a dominant inheritance pattern while cis variants are enriched for additive inheritance. In addition, cis regulatory differences contribute more to expression differences between species than within species, whereas trans regulatory differences show a stronger association between divergence and polymorphism. Our data indicate that in the trans component of gene expression differences genes subjected to weaker selective constraints tend to have an excess of polymorphism over divergence compared to those subjected to stronger selective constraints. In contrast, in the cis component, this difference between genes under stronger and weaker selective constraint is mostly absent. To explain these observations, we propose that purifying selection more strongly shapes trans polymorphism than cis polymorphism. Study the gene expression patterns in two strains of yeast (BY and RM)

2013-11-10 | E-GEOD-46838 | biostudies-arrayexpress

Developmental constraints shape the evolution of the nematode mid-developmental transition

Project description:Evolutionary theory assumes that genetic variation is uniform and gradual in nature, yet morphological and gene expression studies have revealed that different life-stages exhibit distinct levels of cross-species conservation. In particular, a stage in mid-embryogenesis is highly conserved across species of the same phylum, suggesting that this stage is subject to developmental constraints, either by increased purifying selection or by a strong mutational bias. An alternative explanation, however, holds that the same ‘hourglass’ pattern of variation may result from increased positive selection at the earlier and later stages of development. To distinguish between these scenarios, we examined gene expression variation in a population of the nematode C. elegans using an experimental design that eliminated the influence of positive selection. By measuring gene expression for all genes throughout development in twenty strains, we found that variations were dramatically uneven throughout development, with a significant depletion during mid-embryogenesis. In particular, the family of homeodomain transcription factors, whose expression generally coincides with mid-embryogenesis, evolved under high constraint. Our data further shows that genes responsible for the integration of germ layers during morphogenesis are the most constrained class of genes. Together, these results provide the first evidence for developmental constraints as the mechanism underlying the hourglass model of animal evolution. Understanding the pattern and mechanism of developmental constraints provides a framework to understand how evolutionary processes have interacted with embryogenesis and led to the diversity of animal life on earth.

2017-04-04 | GSE87528 | GEO

Response to different types of stress converge in mitochondrial metabolism

Project description:The budding yeast Saccharomyces cerevisiae was used to study 9 different stress conditions in chemostat conditions at constant specific growth rate.

2016-03-01 | E-MTAB-4044 | biostudies-arrayexpress

Inheritance of gene expression level and selective constraints on trans- and cis-regulatory changes in yeast

2013-11-10 | GSE46838 | GEO

Evaluation of the role of functional constraints on the integrity of an ultra conserved region in the genus Drosophila

Project description:Our results indicate that even in highly rearranged genomes like those of Diptera, unusually high levels of gene order conservation cannot be systematically attributed to functional constraints, which points to mechanisms more subtle and diverse than previously thought.

2011-08-03 | GSE31120 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data