Browse
Submit Data
Databases
API
Help

Dataset Information

19 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Environmental and genetic determinants of colony morphology in yeast.

ABSTRACT: Nutrient stresses trigger a variety of developmental switches in the budding yeast Saccharomyces cerevisiae. One of the least understood of such responses is the development of complex colony morphology, characterized by intricate, organized, and strain-specific patterns of colony growth and architecture. The genetic bases of this phenotype and the key environmental signals involved in its induction have heretofore remained poorly understood. By surveying multiple strain backgrounds and a large number of growth conditions, we show that limitation for fermentable carbon sources coupled with a rich nitrogen source is the primary trigger for the colony morphology response in budding yeast. Using knockout mutants and transposon-mediated mutagenesis, we demonstrate that two key signaling networks regulating this response are the filamentous growth MAP kinase cascade and the Ras-cAMP-PKA pathway. We further show synergistic epistasis between Rim15, a kinase involved in integration of nutrient signals, and other genes in these pathways. Ploidy, mating-type, and genotype-by-environment interactions also appear to play a role in the controlling colony morphology. Our study highlights the high degree of network reuse in this model eukaryote; yeast use the same core signaling pathways in multiple contexts to integrate information about environmental and physiological states and generate diverse developmental outputs.

SUBMITTER: Granek JA

PROVIDER: S-EPMC2809765 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Quantitative analysis of colony morphology in yeast.

Project description:Microorganisms often form multicellular structures such as biofilms and structured colonies that can influence the organism's virulence, drug resistance, and adherence to medical devices. Phenotypic classification of these structures has traditionally relied on qualitative scoring systems that limit detailed phenotypic comparisons between strains. Automated imaging and quantitative analysis have the potential to improve the speed and accuracy of experiments designed to study the genetic and molecular networks underlying different morphological traits. For this reason, we have developed a platform that uses automated image analysis and pattern recognition to quantify phenotypic signatures of yeast colonies. Our strategy enables quantitative analysis of individual colonies, measured at a single time point or over a series of time-lapse images, as well as the classification of distinct colony shapes based on image-derived features. Phenotypic changes in colony morphology can be expressed as changes in feature space trajectories over time, thereby enabling the visualization and quantitative analysis of morphological development. To facilitate data exploration, results are plotted dynamically through an interactive Yeast Image Analysis web application (YIMAA; http://yimaa.cs.tut.fi) that integrates the raw and processed images across all time points, allowing exploration of the image-based features and principal components associated with morphological development.

| S-EPMC3996921 | biostudies-literature

Identification of a complex genetic network involved in Saccharomyces cerevisiae colony morphology

Project description:When grown on solid substrates, different microorganisms often form colonies with very specific morphologies. Whereas the pioneers of microbiology often used colony morphology to discriminate between species and strains, the phenomenon has not received much recent attention. In this study, we use a genome-wide assay in the model yeast Saccharomyces cerevisiae to identify all genes that affect colony morphology. We show that several major signaling cascades, including the MAPK, TORC, SNF1 and RIM101 pathways play a role, indicating that morphological changes are a reaction to changing environments. Other genes that affect colony morphology are involved in protein sorting and epigenetic regulation. Interestingly, the screen reveals only few genes that are likely to play a direct role in establishing colony morphology, one notable exception being FLO11, a gene encoding a cell-surface adhesin that has already been implicated in colony morphology, biofilm formation, and invasive and pseudohyphal growth. Using a series of modified promoters to tune FLO11 expression, we confirm the central role of Flo11 and show that differences in FLO11 expression result in distinct colony morphologies. Together, our results provide a first comprehensive looks at the complex genetic network that underlies the diversity in the morphologies of yeast colonies.

2012-04-28 | GSE36151 | GEO

Identification of a complex genetic network involved in Saccharomyces cerevisiae colony morphology

2012-04-27 | E-GEOD-36151 | biostudies-arrayexpress

Identification of a complex genetic network underlying Saccharomyces cerevisiae colony morphology.

Project description:When grown on solid substrates, different microorganisms often form colonies with very specific morphologies. Whereas the pioneers of microbiology often used colony morphology to discriminate between species and strains, the phenomenon has not received much attention recently. In this study, we use a genome-wide assay in the model yeast Saccharomyces cerevisiae to identify all genes that affect colony morphology. We show that several major signalling cascades, including the MAPK, TORC, SNF1 and RIM101 pathways play a role, indicating that morphological changes are a reaction to changing environments. Other genes that affect colony morphology are involved in protein sorting and epigenetic regulation. Interestingly, the screen reveals only few genes that are likely to play a direct role in establishing colony morphology, with one notable example being FLO11, a gene encoding a cell-surface adhesin that has already been implicated in colony morphology, biofilm formation, and invasive and pseudohyphal growth. Using a series of modified promoters for fine-tuning FLO11 expression, we confirm the central role of Flo11 and show that differences in FLO11 expression result in distinct colony morphologies. Together, our results provide a first comprehensive look at the complex genetic network that underlies the diversity in the morphologies of yeast colonies.

| S-EPMC3470922 | biostudies-literature

Genetic and environmental determinants of stress responding.

Project description:The risk for alcohol dependence throughout development is determined by both genetic and environmental factors. Genetic factors that are thought to modulate this risk act on neurobiological pathways regulating reward, impulsivity, and stress responses. For example, genetic variations in pathways using the brain signaling molecule (i.e., neurotransmitter) dopamine, which likely mediate alcohol's rewarding effects, and in two hormonal systems involved in the stress response (i.e., the hypothalamic-pituitary-adrenal axis and the corticotropin-releasing factor system) affect alcoholism risk. This liability is modified further by exposure to environmental risk factors, such as environmental stress and alcohol use itself, and the effects of these factors may be enhanced in genetically vulnerable individuals. The transition from alcohol use to dependence is the result of complex interactions of genes, environment, and neurobiology, which fluctuate throughout development. Therefore, the relevant genetic and environmental risk factors may differ during the different stages of alcohol initiation, abuse, and dependence. The complex interaction of these factors is yet to be fully elucidated, and translational studies, ranging from animal studies to research in humans, and well-characterized longitudinal studies are necessary to further understand the development of alcohol dependence.

| S-EPMC3860390 | biostudies-literature

hiPSCs with different colony morphology

Project description:Here we characterize the the proteome of iPSCs classified into three morphology groups.

2020-05-26 | PXD013481 | Pride

Yeast Colony Differentiation

Project description:Transcription profile of different layers from S.cerevisiae colonies in day 15 and day 20.

2012-02-17 | GSE35887 | GEO

Genetic and Environmental Determinants of Multicellular-like Phenotype Formation in Fission Yeast

Project description:MLP formation in S. pombe

| PRJEB69522 | ENA

Genetic basis for conversion of rough-to-smooth colony morphology in Actinobacillus actinomycetemcomitans.

Project description:The basis of the rough-to-smooth conversion of Actinobacillus actinomycetemcomitans was examined. Smooth variants often contained mutations at the flp promoter region. Replacing the mutated flp promoter with the wild-type promoter restored the rough phenotype. The expression level of the flp promoter was approximately 100-fold lower in smooth than in rough strains. Mutations of the flp promoter are a cause of the rough-to-smooth conversion.

| S-EPMC1111812 | biostudies-literature

Genetic and environmental determinants of human TCR repertoire diversity.

Project description:T cell discrimination of self and non-self is the foundation of the adaptive immune response, and is orchestrated by the interaction between T cell receptors (TCRs) and their cognate ligands presented by major histocompatibility (MHC) molecules. However, the impact of host immunogenetic variation on the diversity of the TCR repertoire remains unclear. Here, we analyzed a cohort of 666 individuals with TCR repertoire sequencing. We show that TCR repertoire diversity is positively associated with polymorphism at the human leukocyte antigen class I (HLA-I) loci, and diminishes with age and cytomegalovirus (CMV) infection. Moreover, our analysis revealed that HLA-I polymorphism and age independently shape the repertoire in healthy individuals. Our data elucidate key determinants of human TCR repertoire diversity, and suggest a mechanism underlying the evolutionary fitness advantage of HLA-I heterozygosity.

| S-EPMC7487954 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

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