(116d) The Single Cell Distribution of Plasmid Copy Numbers

Plasmids are a critical piece of many bacterial genomes, and also have an important role in synthetic biology.  The ability to manipulate parameters such as gene copy number in a predictable way is desirable for many synthetic gene circuits, and it is often important for biological systems to be robust against variability in gene dosage.  The mean number of copies per cell is well known for most plasmids, and some plasmids can be present in hundreds of copies per cell.  However less is known about the cell to cell variability of plasmid copy number across a population of cells.  The shape of the single cell distribution of plasmid copy numbers can have important implications for gene expression and will help us gain insight into the underlying mechanisms that regulate plasmid copy number, namely plasmid replication and partitioning.

In order to more quantitatively understand the processes which influence plasmid copy number, we measured the single cell distribution of plasmid copy numbers for a population of E. coli harboring a high copy number plasmid containing a ColE1-like origin.  We have developed a method to analyze the plasmid content of single cells which combines FACS single cell sorting with digital PCR to count the number of plasmids in each cell.

Our results indicate that the distribution of this plasmid at the single cell level is much wider than would be expected from a simple model of binomial partitioning of the plasmids at division and is skewed towards low copy numbers.  Using our measured distribution as a guide, we develop and test theoretical models of plasmid replication and partitioning to explore the range of models which would result in a similar distribution of single cell plasmid counts.  We also implement dynamic and equilibrium models to examine how the plasmid distribution influences gene expression.  From these models, we predict the consequences of different plasmid regulatory mechanisms, such as plasmid loss rates and gene expression patterns, and test these predictions using single cell microscopy.  We demonstrate how precise measurements of single cell plasmid distributions enabled us to dissect the mechanisms and consequences of plasmid regulation.