Spatial alanine metabolism determines local growth dynamics of Escherichia coli colonies

Abstract

Bacteria commonly live in spatially structured biofilm assemblages, which are encased by an extracellular matrix. Metabolic activity of the cells inside biofilms causes gradients in local environmental conditions, which leads to the emergence of physiologically differentiated subpopulations. Information about the properties and spatial arrangement of such metabolic subpopulations, as well as their interaction strength and interaction length scales are lacking, even for model systems like Escherichia coli colony biofilms grown on agar-solidified media. Here, we use an unbiased approach, based on temporal and spatial transcriptome and metabolome data acquired during E. coli colony biofilm growth, to study the spatial organization of metabolism. We discovered that alanine displays a unique pattern among amino acids and that alanine metabolism is spatially and temporally heterogeneous. At the anoxic base of the colony, where carbon and nitrogen sources are abundant, cells secrete alanine via the transporter AlaE. In contrast, cells utilize alanine as a carbon and nitrogen source in the oxic nutrient-deprived region at the colony mid-height, via the enzymes DadA and DadX. This spatially structured alanine cross-feeding influences cellular viability and growth in the cross-feeding-dependent region, which shapes the overall colony morphology. More generally, our results on this precisely controllable biofilm model system demonstrate a remarkable spatiotemporal complexity of metabolism in biofilms. A better characterization of the spatiotemporal metabolic heterogeneities and dependencies is essential for understanding the physiology, architecture, and function of biofilms.

Microbial mutualism generates multistable and oscillatory growth dynamics

“…The bacteria are described by a number concentration b with subscripts aer and an for aerobes and anaerobes, respectively. Genome sequencing and metabolic profiling of such communities indicate that the consumption and secretion of only a small number of metabolites often drives experimental outcomes [3][4][5]7,13,94 -providing a clue that the full network of metabolic interactions could be dramatically simplified while still generating realistic community behaviors. Hence, inspired by 2 , we focus on the case in which the anaerobes take up an exogenously-supplied complex carbohydrate (teal) that cannot be accessed by the aerobes, breaking it down into simple sugar molecules (green) that they either directly consume for their growth or liberate to be consumed by the entire microbial community; for simplicity, we do not con-sider any other compounds, such as short-chain fatty acids, that may also liberated upon carbohydrate breakdown.…”

“…This network of interactions can give rise to fascinating emergent behaviors whose occurrence is remarkably consistent across diverse communities. For example, a common finding is that microbial communities can have multiple stable states, each characterized by its own unique composition of the different coexisting species, and each of which is stable under different environmental conditions [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15] . In some cases, these states are multistable-i.e., multiple stable states can arise under identical conditions-leading, for example, to hysteretic behavior in which the state of the community depends not just on current conditions, but also on the history of how they were established [2][3][4]9,[16][17][18][19][20][21][22][23][24][25][26] .…”

“…For example, a common finding is that microbial communities can have multiple stable states, each characterized by its own unique composition of the different coexisting species, and each of which is stable under different environmental conditions [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15] . In some cases, these states are multistable-i.e., multiple stable states can arise under identical conditions-leading, for example, to hysteretic behavior in which the state of the community depends not just on current conditions, but also on the history of how they were established [2][3][4]9,[16][17][18][19][20][21][22][23][24][25][26] . Multistability can also lead to dynamic behavior in which the community continually fluctuates between multiple states, often with periodic oscillations 8,13,15,19,[27][28][29][30][31][32][33] .…”

“…And if so, are there simple biophysical principles that describe these behaviors and the conditions under which they arise? Prior experiments on model two-species communities of aerobes and anaerobes in bioreactors 2,3,27,89 provide useful guidance in addressing these questions. In particular, this prior work demonstrated experimentally that such communities can indeed exhibit multistability, hysteresis, and time-dependent behaviors.…”

The many faces of the unusual biofilm activator RemA

“…[26,27] Furthermore, different chemical (e.g., oxygen, water, salt, and nutrients) and mechanical gradients formed within the biofilm generate heterogeneous microenvironments leading to special cellular adaptation responses of the individual cell. [20,23] In contrast to single cells, a biofilm can be seen as a collection of highly differentiated microorganisms that cooperate for the common good of the population through interconnected cellular responses and developmental programs. However, there is also intense competition between members of the biofilm.…”