Yeast mating and image-based quantification of spatial pattern formation

PLoS Comput Biol. 2014 Jun 26;10(6):e1003690. doi: 10.1371/journal.pcbi.1003690. eCollection 2014 Jun.

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aspartic Acid Endopeptidases / metabolism
  • Image Processing, Computer-Assisted / methods*
  • Microscopy, Confocal / methods
  • Mutation
  • Pheromones / metabolism
  • Saccharomyces cerevisiae / chemistry
  • Saccharomyces cerevisiae / cytology
  • Saccharomyces cerevisiae / metabolism*
  • Saccharomyces cerevisiae / physiology*
  • Saccharomyces cerevisiae Proteins / metabolism

Substances

  • Pheromones
  • Saccharomyces cerevisiae Proteins
  • Aspartic Acid Endopeptidases
  • BAR1 protein, S cerevisiae

Grant support

This work was supported by a grant from the European Commission 7th Framework Programme (UNICELLSYS, Contract No. 201142), the German Research Foundation (CRC 740 “From molecules to modules” and the Berlin Mathematical School) and the International Max Planck Research School for Computational Biology and Scientific Computing. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.