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. 2013 Aug 27;110(35):14302-7.
doi: 10.1073/pnas.1308523110. Epub 2013 Aug 12.

Availability of public goods shapes the evolution of competing metabolic strategies

Affiliations

Availability of public goods shapes the evolution of competing metabolic strategies

Herwig Bachmann et al. Proc Natl Acad Sci U S A. .

Abstract

Tradeoffs provide a rationale for the outcome of natural selection. A prominent example is the negative correlation between the growth rate and the biomass yield in unicellular organisms. This tradeoff leads to a dilemma, where the optimization of growth rate is advantageous for an individual, whereas the optimization of the biomass yield would be advantageous for a population. High-rate strategies are observed in a broad variety of organisms such as Escherichia coli, yeast, and cancer cells. Growth in suspension cultures favors fast-growing organisms, whereas spatial structure is of importance for the evolution of high-yield strategies. Despite this realization, experimental methods to directly select for increased yield are lacking. We here show that the serial propagation of a microbial population in a water-in-oil emulsion allows selection of strains with increased biomass yield. The propagation in emulsion creates a spatially structured environment where the growth-limiting substrate is privatized for populations founded by individual cells. Experimental evolution of several isogenic Lactococcus lactis strains demonstrated the existence of a tradeoff between growth rate and biomass yield as an apparent Pareto front. The underlying mutations altered glucose transport and led to major shifts between homofermentative and heterofermentative metabolism, accounting for the changes in metabolic efficiency. The results demonstrated the impact of privatizing a public good on the evolutionary outcome between competing metabolic strategies. The presented approach allows the investigation of fundamental questions in biology such as the evolution of cooperation, cell-cell interactions, and the relationships between environmental and metabolic constraints.

Keywords: droplets; group selection; metabolic engineering; microbial diversity; r/K selection.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Fig. 1.
Fig. 1.
Serial propagation in suspension leads to the selection of mutants with increased growth rates (A). If droplets in emulsions are initially occupied with a single cell, mutants with a higher number of offspring will be able to grow to a higher cell density compared with the wild-type strain even if such mutants grow slower. If the emulsion is subsequently broken, diluted, and used to inoculate a new emulsion, one can enrich for strains with a higher number of offspring (B). In lactic acid bacteria catabolization of glucose to lactate yields two molecules of ATP and it is faster than the conversion to acetate, which yields three molecules of ATP (C). This leads to a yield/rate tradeoff, which is demonstrated by deleting the lactate dehydrogenase (ldh) of L. lactis. In a pure culture strain NZ9000 is inefficient but fast (solid black line in D), whereas the ldh negative variant NZ9010 is efficient but slow (solid red line in D) (21). In coculture the fast strain is expected to reach the maximum carrying capacity quicker than the slow growing strain and subsequently overall growth will cease (dashed lines in D). This will lead to the loss of the slow growing variant from the culture. However, growth of individual cells in emulsion rather reflects many individual growth curves of pure cultures. Therefore, serial propagation in emulsion should allow the enrichment of slow growing but efficient cells, whereas in suspension the opposite is expected. This concept was demonstrated in a competition experiment of L. lactis NZ9000 and its ldh negative derivative NZ9010 (E). See SI Appendix for details.
Fig. 2.
Fig. 2.
Enrichment of strains with increased maximum optical densities (y axis) and decreased growth rates (x axis) throughout propagation in emulsion. Strain HB60 was isolated after 22 transfers in emulsion (A). Further propagation of this culture in emulsion up to 28 (B) and 31 (C) transfers resulted in an increased fraction of strains with increased optical densities and/or decreased growth rates. The data also indicate that several clusters of new phenotypes emerge. SEs are indicated (n = 4). D shows growth curves of the wild-type M1363 (black line) and isolate HB60 (red line), which grows slower but reaches a higher cell density.
Fig. 3.
Fig. 3.
Yield/rate trajectories during selection in emulsion (dotted black line) and in suspension (solid lines). L. lactis MG1363 (black dot) was propagated in emulsion, which led to the isolation of HB60 (red dot). Subsequently HB60 was propagated in suspension for 160 generations. The solid arrows show the trajectories followed by three individual cultures of HB60 after 60, 100, and 160 generation in suspension. The dots after 100 generations are from single colonies isolated from the respective cultures, designated HB61 (green), HB62 (blue), and HB63 (turquoise). Gray dots show other isogenic isolates of MG1363 (SI Appendix, Fig. S10). SEs are indicated (n = 11).
Fig. 4.
Fig. 4.
Correlation matrix of parameters that relate to the yield/rate tradeoff. Growth rate and the maximum optical density (max OD) were obtained from growth experiments, cell number, cell size, and total cell volume from Coulter Counter measurements. The fraction of consumed substrate diverted toward lactate (percent lactate) as metabolic end product is a measure for the metabolic strategy. Throughout this paper we use optical density measurements as a proxy for biomass yield. Total cell volume (cell count × cell volume) and total protein are independent parameters for biomass yield and they confirm the validity of this assumption for the presented strains. A positive correlation of growth rate and cell size as shown here is consistent with earlier results from adaptation experiments (45). (Lower) Individual data points and a linear regression line (red). (Upper) Corresponding Pearson correlation coefficient. All correlations are significant (P < 0.01). The 22 data points in each plot are individual strains, which are all derivatives of L. lactis MG1363 and they correspond to the strains shown in SI Appendix, Fig. S10.

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