Metabolic heterogeneity and cross-feeding within isogenic yeast populations captured by DILAC

Abstract

Genetically identical cells are known to differ in many physiological parameters such as growth rate and drug tolerance. Metabolic specialization is believed to be a cause of such phenotypic heterogeneity, but detection of metabolically divergent subpopulations remains technically challenging. We developed a proteomics-based technology, termed differential isotope labelling by amino acids (DILAC), that can detect producer and consumer subpopulations of a particular amino acid within an isogenic cell population by monitoring peptides with multiple occurrences of the amino acid. We reveal that young, morphologically undifferentiated yeast colonies contain subpopulations of lysine producers and consumers that emerge due to nutrient gradients. Deconvoluting their proteomes using DILAC, we find evidence for in situ cross-feeding where rapidly growing cells ferment and provide the more slowly growing, respiring cells with ethanol. Finally, by combining DILAC with fluorescence-activated cell sorting, we show that the metabolic subpopulations diverge phenotypically, as exemplified by a different tolerance to the antifungal drug amphotericin B. Overall, DILAC captures previously unnoticed metabolic heterogeneity and provides experimental evidence for the role of metabolic specialization and cross-feeding interactions as a source of phenotypic heterogeneity in isogenic cell populations.

Spatiotemporal development of growth and death zones in expanding bacterial colonies driven by emergent nutrient dynamics

“…We thus believe the approaches and findings here represent important first steps towards a systemic quantitative understanding of more complex biofilms that also involve EPS formation and cell differentiation (59,62). Indeed, colony-forming microorganisms can exploit the obligatory nutrient gradients formed at different locations and time in developing colonies as spatiotemporal cues to signal the development of more complex spatial structures and temporal growth patterns (11,(63)(64)(65)(66)(67)(68).…”

The molecular landscape of cellular metal ion biology

“…In addition to its scale, a key factor that distinguishes our study from previous work addressing metal biology systematically, is that we utilised prototrophic strains and minimal media formulations that lack amino acid supplements. As a result, our experimental setup takes into account that one of the primary functions of metal ions is as cofactors in enzymes that catalyse key reactions in biosynthetic metabolism, many of which are feedback inhibited in rich growth media 79 . These combined efforts yielded a much more comprehensive picture about the role of the metal ion concentrations in cellular networks and revealed a remarkable interdependence of cellular processes and their metallomic environment, at the scale of the proteome.…”

A transient burst of mutations occurs during the normal development of yeast colonies

“…For example, the noise in gene expression of RAD27 or RAD52 can lead to heterogeneity in recombination rate in an isogenic population 57 . Furthermore, the complex reprogramming of the genetic networks and the formation of differentiated cell populations during the colony development lead to the formation of metabolically active and stress-resistant cells as well as starving and stress-sensitive cells [58][59][60][61][62][63][64][65] . The mutator subpopulations could also arise during the transition from one metabolism to another, indeed, spike of reactive oxygen species (ROS) had been observed during the change of carbon source or the passage to anoxia 66,67 .…”