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Date
2017Type
- Doctoral Thesis
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Abstract
Individuality and collective behavior are two terms that the general public might not readily associate with bacteria, yet both concepts have become central in recent studies of bacterial populations. Bacteria in clonal populations share the same genetic information, yet they can differ substantially in their phenotype. This is partly due to cells adapting their phenotype to local environmental differences. However, the stochastic nature of gene expression can lead to phenotypic heterogeneity even in homogenous environments, a con- cept that is known as bacterial individuality. Furthermore, bacteria do not live in isolation, but rather interact with other members of their population. By exchanging molecules through the environment cells can affect each other’s activities. These interactions can have important consequences: they allow cells to achieve functionality at the level of the group that is not available to cells in isolation. Interactions can thus give rise to emergent collective behavior.
Both phenotypic differentiation and intercellular interactions can take place in well mixed systems (as will be shown in Chapter 4), however both are much more pronounced in spatially structured environments. The uptake and release of molecules by cells living in these structured environments can quickly generate gradi- ents in environmental conditions that promote phenotypic differentiation (as will be shown in Chapter 3). Furthermore, the sharing of a micro-environment can facilitate intercellular interactions (as will be shown in Chapter 2).
The central theme addressed in these thesis is the question of how the behavior of a cell is affected by the presence of other cells in the population. Specifically, I will address the following three questions: i) how can clonal population arrange their activities in space? ii) how can interactions between cells give rise to collec- tive behavior? and iii) what are the functional consequences of these two processes?
In Chapter 2 I asked the question if and how cells can arrange their activities in space. To address this ques- tion we used fluorescent reporters and time-lapse microscopy to follow the growth and gene expression dynamics in Escherichia coli microcolonies. We found that the gene expression dynamics of neighboring cells were strongly correlated for genes involved in stress response and metabolism. Using a newly developed statistical approach we showed that these spatial correlations had three main causes: i) lineage history de- pendence; ii) emergent gradients in environmental conditions; and iii) local intercellular interactions. Taken together, our data showed that expression patterns in bacterial colonies were highly non-random.
In Chapter 3 I studied how emergent gradients in nutrients can cause phenotypic differentiation. We inves- tigated the consequences of this differentiation for the ability of the population to respond to changes in the environment. We grew E. coli cells in two-dimensional growth chambers in microfluidic devices under glucose limiting conditions. We found evidence that the population diversified in metabolically distinct sub- populations that engaged in a cross-feeding interaction. Furthermore, we showed that the different sub- populations varied strongly in their response to a change in nutrient conditions. Taken together, our data
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showed that by modifying their environment cells could generate a highly structured and phenotypically diverse population.
In Chapter 4 I studied how interactions between cells can affect their ability to survive periods of antibiotic exposure. We studied E. coli populations that produce colicin, a toxic protein (bacteriocin) that is thought to play an important role in inter-strain warfare. Here we showed that colicins can also lead to tolerance to an- tibiotic exposure. Importantly, we found that cells only became tolerant when they could take up colicin produced by clonemates; intracellularly produced colicin did not have any measurable effect. The tolerance to antibiotics is thus an emergent property of the population.
In all three chapters we observed that interactions between cells led to emergent behavior at the population level. Emergent behavior can have important consequences for bacterial populations: it can create function- ality at the level of the group that is not available to cells living in isolation. Chapter 5 addresses the question of how such emergent behavior could have evolved. Show more
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https://doi.org/10.3929/ethz-b-000247119Publication status
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Publisher
ETH ZurichSubject
MICROBIOLOGY; Quantitative Biology; Single cell analysisOrganisational unit
03743 - Ackermann, Martin / Ackermann, Martin
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