Different Resource Allocation in a Bacillus subtilis Population Displaying Bimodal Motility.

To cope with sudden changes in their environment, bacteria can use a bet-hedging strategy by dividing the population into cells with different properties. This so-called bimodal or bistable cellular differentiation is generally controlled by positive feedback regulation of transcriptional activators. Due to the continuous increase in cell volume, it is difficult for these activators to reach an activation threshold concentration when cells are growing exponentially. This is one reason why bimodal differentiation is primarily observed from the onset of the stationary phase, when exponential growth ceases. An exception is the bimodal induction of motility in Bacillus subtilis, which occurs early during exponential growth. Several mechanisms have been put forward to explain this, including double-negative feedback regulation and the stability of the mRNA molecules involved. In this study, we used fluorescence-assisted cell sorting (FACS) to compare the transcriptomes of motile and nonmotile cells and noted that expression of ribosomal genes is lower in motile cells. This was confirmed using an unstable green fluorescent protein (GFP) reporter fused to the strong ribosomal rpsD promoter. We propose that the reduction in ribosomal gene expression in motile cells is the result of a diversion of cellular resources to the synthesis of the chemotaxis and motility systems. In agreement with this, single-cell microscopic analysis showed that motile cells are slightly shorter than nonmotile cells, an indication of slower growth. We speculate that this growth rate reduction can contribute to the bimodal induction of motility during exponential growth. IMPORTANCE To cope with sudden environmental changes, bacteria can use a bet-hedging strategy and generate different types of cells within a population-so-called bimodal differentiation. For example, a Bacillus subtilis culture can contain both motile and nonmotile cells. In this study, we compared the gene expression between motile and nonmotile cells. It appeared that motile cells express fewer ribosomes. To confirm this, we constructed a ribosomal promoter fusion that enabled us to measure expression of this promoter in individual cells. This reporter fusion confirmed our initial finding. The reallocation of cellular resources from ribosome synthesis toward synthesis of the motility apparatus results in a reduction in growth. Interestingly, this growth reduction has been shown to stimulate bimodal differentiation.

Effect of Genome Position on Heterologous Gene Expression in Bacillus subtilis: An Unbiased Analysis.

A fixed gene copy number is important for the in silico construction of engineered synthetic networks. However, the copy number of integrated genes depends on their genomic location. This gene dosage effect is rarely addressed in synthetic biology. Two studies in Escherichia coli presented conflicting data on the impact of gene dosage. Here, we investigate how genome location and gene orientation influences expression in Bacillus subtilis. An important difference with the E. coli studies is that we used an unbiased genome integration approach mediated by random transposon insertion. We found that there is a strong gene dosage effect in fast growing B. subtilis cells, which can amount to a 5-fold difference in gene expression. In contrast, gene orientation with respect to DNA replication direction does not influence gene expression. Our study shows that gene dosage should be taken into account when designing synthetic circuits in B. subtilis and presumably other bacteria.

When Phase Contrast Fails: ChainTracer and NucTracer, Two ImageJ Methods for Semi-Automated Single Cell Analysis Using Membrane or DNA Staining.

Within bacterial populations, genetically identical cells often behave differently. Single-cell measurement methods are required to observe this heterogeneity. Flow cytometry and fluorescence light microscopy are the primary methods to do this. However, flow cytometry requires reasonably strong fluorescence signals and is impractical when bacteria grow in cell chains. Therefore fluorescence light microscopy is often used to measure population heterogeneity in bacteria. Automatic microscopy image analysis programs typically use phase contrast images to identify cells. However, many bacteria divide by forming a cross-wall that is not detectable by phase contrast. We have developed 'ChainTracer', a method based on the ImageJ plugin ObjectJ. It can automatically identify individual cells stained by fluorescent membrane dyes, and measure fluorescence intensity, chain length, cell length, and cell diameter. As a complementary analysis method we developed 'NucTracer', which uses DAPI stained nucleoids as a proxy for single cells. The latter method is especially useful when dealing with crowded images. The methods were tested with Bacillus subtilis and Lactococcus lactis cells expressing a GFP-reporter. In conclusion, ChainTracer and NucTracer are useful single cell measurement methods when bacterial cells are difficult to distinguish with phase contrast.