ArticlePLoS computational biology2014
Yeast mating and image-based quantification of spatial pattern formation.
Article in PLoS computational biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed, 33 citations in OpenAlex.
- Optogenetic control of pheromone gradients and mating behavior in budding yeast.Life science alliance · 2025Article
- LC-MS/MS quantification of bacterial and fungal signal peptides via direct injection: a case study of cross-kingdom communication.Analytical and bioanalytical chemistry · 2025Article
- Pheromone Response and Mating Behavior in Fission Yeast.Microbiology and molecular biology reviews : MMBR · 2022Review
- Selective Moonlighting Cell-Penetrating Peptides.Pharmaceutics · 2021Article
- Asymmetric mating behavior of isogamous budding yeast.Science advances · 2021Article
- Microbial competition reduces metabolic interaction distances to the low µm-range.The ISME journal · 2021Article
- Chemotropism among populations of yeast cells with spatiotemporal resolution in a biofabricated microfluidic platform.Biomicrofluidics · 2020Article
- Quantitative analysis of the yeast pheromone pathway.Yeast (Chichester, England) · 2019Article
- Spatial modeling of the membrane-cytosolic interface in protein kinase signal transduction.PLoS computational biology · 2018Article
- Dynamics of cell wall elasticity pattern shapes the cell during yeast mating morphogenesis.Open biology · 2016Article
- Sensory input attenuation allows predictive sexual response in yeast.Nature communications · 2016Article
- Modelling of Yeast Mating Reveals Robustness Strategies for Cell-Cell Interactions.PLoS computational biology · 2016Article
- Hydrophobin-Based Surface Engineering for Sensitive and Robust Quantification of Yeast Pheromones.Sensors (Basel, Switzerland) · 2016Article
- Local Pheromone Release from Dynamic Polarity Sites Underlies Cell-Cell Pairing during Yeast Mating.Current biology : CB · 2016Article
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Corrections and comments
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Authors and funding
6 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Communication between cells is a ubiquitous feature of cell populations and is frequently realized by secretion and detection of signaling molecules. Direct visualization of the resulting complex gradients between secreting and receiving cells is often impossible due to the small size of diffusing molecules and because such visualization requires experimental perturbations such as attachment of fluorescent markers, which can change diffusion properties. We designed a method to estimate such extracellular concentration profiles in vivo by using spatiotemporal mathematical models derived from microscopic analysis. This method is applied to populations of thousands of haploid yeast cells during mating in order to quantify the extracellular distributions of the pheromone α-factor and the activity of the aspartyl protease Bar1. We demonstrate that Bar1 limits the range of the extracellular pheromone signal and is critical in establishing α-factor concentration gradients, which is crucial for effective mating. Moreover, haploid populations of wild type yeast cells, but not BAR1 deletion strains, create a pheromone pattern in which cells differentially grow and mate, with low pheromone regions where cells continue to bud and regions with higher pheromone levels and gradients where cells conjugate to form diploids. However, this effect seems to be exclusive to high-density cultures. Our results show a new role of Bar1 protease regulating the pheromone distribution within larger populations and not only locally inside an ascus or among few cells. As a consequence, wild type populations have not only higher mating efficiency, but also higher growth rates than mixed MATa bar1Δ/MATα cultures. We provide an explanation of how a rapidly diffusing molecule can be exploited by cells to provide spatial information that divides the population into different transcriptional programs and phenotypes.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.