Cell‐to‐cell heterogeneity emerges as consequence of metabolic cooperation in a synthetic yeast community

Abstract

Cells that grow together respond heterogeneously to stress even when they are genetically similar. Metabolism, a key determinant of cellular stress tolerance, may be one source of this phenotypic heterogeneity, however, this relationship is largely unclear. We used self‐establishing metabolically cooperating (SeMeCo) yeast communities, in which metabolic cooperation can be followed on the basis of genotype, as a model to dissect the role of metabolic cooperation in single‐cell heterogeneity. Cells within SeMeCo communities showed to be highly heterogeneous in their stress tolerance, while the survival of each cell under heat or oxidative stress, was strongly determined by its metabolic specialization. This heterogeneity emerged for all metabolite exchange interactions studied (histidine, leucine, uracil, and methionine) as well as oxidant (H2O2, diamide) and heat stress treatments. In contrast, the SeMeCo community collectively showed to be similarly tolerant to stress as wild‐type populations. Moreover, stress heterogeneity did not establish as sole consequence of metabolic genotype (auxotrophic background) of the single cell, but was observed only for cells that cooperated according to their metabolic capacity. We therefore conclude that phenotypic heterogeneity and cell to cell differences in stress tolerance are emergent properties when cells cooperate in metabolism.

Saccharomyces cerevisiae single-copy plasmids for auxotrophy compensation, multiple marker selection, and for designing metabolically cooperating communities

“…Further, we tested for copy number effects, and found that the expression of HIS3, LEU2, MET15 and URA3 from the minichromosome fully suffices the biosynthetic needs 33 . A situation in which all cells are provided with a high concentration of nutrients, as would occur with media supplementation, may also be less native to cells community where, usually, a certain fraction of cells are dependent on metabolite exchange 25, 45 . For the typical experiment, the constraints arising from segregation of a single-copy minichromosome that restores auxotrophy, are hence much smaller compared to the problems caused by the use of nutrient supplemented media and auxotrophic strain backgrounds.…”

“…It has been known for a long time that a subpopulation of plasmid free cells can co-grow alongside plasmid containing cells, despite using nutrient selection 2, 46– 48 . In our lab we have exploited this property to study metabolite exchange interactions between cells, and developed a system of self-establishing metabolically cooperating communities (SeMeCo) in which a series of auxotrophs cooperate to enable the growth of a yeast community 25, 45 . This system exploits plasmid segregation, starting from an initially self-supporting cell, that grows progressively into an increasingly heterogeneous population, which is able to proliferate on the basis of nutrient exchange occuring between yeast cells.…”

“…Finally, the uniform multiple cloning site (MCS) in the plasmid series allows for the inclusion of marker proteins, such as GFP or beta-galactosidase, to track individual cell types in SeMeCo communities, that reveal phenotypic heterogeneity at the single cell level 45 . This MCS further allows the use of these plasmids for the recombinant expression of proteins.…”

Metabolite plasticity drives carbon-nitrogen resource budgeting to enable division of labor in a clonal community

“…Hence, different cells of the community exhibit 42 metabolic interdependencies, presumably to balance out trade-offs arising from resource sharing. While 43 this concept has been demonstrated for example, in synthetically engineered systems, where required 44 metabolic dependencies are created between non-isogenic cells (Campbell et al, 2016(Campbell et al, , 2015, this has 45 been exceptionally challenging to demonstrate within a clonal community of cells. We recently 46 enables a self-organizing system based on non-limiting and limiting resources, which creates organized 70 phenotypic heterogeneity in cells.…”

Coupled metabolic‐hydrodynamic modeling enabling rational scale‐up of industrial bioprocesses

“…This reduction of global productivity can often be ascribed to the formation of a specific subpopulation of cells with vanished or discounted production capacity (Delvigne, Zune, Lara, Al‐Soud, & Sorensen, ). It has been recently reported that this cell‐to‐cell heterogeneity arises from metabolic cooperation (Campbell, Vowinckel, & Ralser, ), and metabolite dynamics in response to the extracellular environment plays a vital role in regulating biomass growth and product formation in industrial practices (A. C. Schmitz, Hartline, & Zhang, ). It is hence indispensable to understand how metabolic fluxes are intricately coordinated by complex regulatory mechanisms such as gene‐metabolite association maps (Zampieri & Sauer, ), posttranslational modifications, for example, enzyme phosphorylation or acetylation (Gerosa & Sauer, ).…”