Direct Correlation between Motile Behavior and Protein Abundance in Single Cells

Abstract

Understanding how stochastic molecular fluctuations affect cell behavior requires the quantification of both behavior and protein numbers in the same cells. Here, we combine automated microscopy with in situ hydrogel polymerization to measure single-cell protein expression after tracking swimming behavior. We characterized the distribution of non-genetic phenotypic diversity in Escherichia coli motility, which affects single-cell exploration. By expressing fluorescently tagged chemotaxis proteins (CheR and CheB) at different levels, we quantitatively mapped motile phenotype (tumble bias) to protein numbers using thousands of single-cell measurements. Our results disagreed with established models until we incorporated the role of CheB in receptor deamidation and the slow fluctuations in receptor methylation. Beyond refining models, our central finding is that changes in numbers of CheR and CheB affect the population mean tumble bias and its variance independently. Therefore, it is possible to adjust the degree of phenotypic diversity of a population by adjusting the global level of expression of CheR and CheB while keeping their ratio constant, which, as shown in previous studies, confers functional robustness to the system. Since genetic control of protein expression is heritable, our results suggest that non-genetic diversity in motile behavior is selectable, supporting earlier hypotheses that such diversity confers a selective advantage.

Statistical parameter inference of bacterial swimming strategies

“…In the following we mention some further directions, where our method of inference can be applied or needs to be extented. Recent experimental techniques allow to record tracks of length of the order of 100 s [12,15]. Such long tracks are in the range of the minimal amount of data needed so that our inference technique is applicable (see appendix F).…”

“…Its well known run-and-tumble swimming motion and chemotaxis strategy has been thoroughly studied [2][3][4][5][6][7]. Nowadays, modern imaging techniques allow for high-throughput recording of bacterial trajectories [8][9][10][11][12][13][14][15]. The method of labeling flagella by fluorescent markers allows to unravel the diverse swimming mechanisms of microorganisms [16,17].…”

Recent Advances and Future Prospects in Bacterial and Archaeal Locomotion and Signal Transduction

“…These extended runs are found to be beneficial in the absence of any gradient, allowing the population to sample a larger volume more effectively (79). Another clear illustration is the observation of individual trajectories of swimming bacteria, which shows substantial cell-to-cell variability (82) in parameters such as swimming speed, average turning angle, and effective rotational diffusion coefficient. Large data sets obtained by high-throughput 3D tracking (84) reveal that the variations in these parameters are not entirely random but display substantial correlations with each other.…”

“…Single-cell FRET imaging (described above) enabled the measurement of CheY-P activity in individual cells, showing that these differences give rise to phenotypic variations (65,82). For example, the response to ligand stimuli was found to be highly variable from cell to cell, which can be explained in terms of variability in the Tar/Tsr receptor expression ratio.…”

“…In other words, changing the standard deviation of a distribution can have as large an effect on performances as changing its mean. Both the shape and the mean can be independently affected (82), suggesting that both are under selection pressure from evolution (85).…”