Tracking bacterial lineages in complex and dynamic environments with applications for growth control and persistence

Abstract

As bacteria transition from exponential to stationary phase, they change substantially in size, morphology, growth and expression profiles. These responses also vary between individual cells, but it has proved difficult to track cell lineages along the growth curve to determine the progression of events or correlations between how individual cells enter and exit dormancy. Here, we developed a platform for tracking more than 10⁵ parallel cell lineages in dense and changing cultures, independently validating that the imaged cells closely track batch populations. Initial applications show that for both Escherichia coli and Bacillus subtilis, growth changes from an 'adder' mode in exponential phase to mixed 'adder-timers' entering stationary phase, and then a near-perfect 'sizer' upon exit-creating broadly distributed cell sizes in stationary phase but rapidly returning to narrowly distributed sizes upon exit. Furthermore, cells that undergo more divisions when entering stationary phase suffer reduced survival after long periods of dormancy but are the only cells observed that persist following antibiotic treatment.

Extended Data Fig. 1 |. Operating principle of the single-cell growth-curve setup.

a, Schematic of the dual incubator setup is shown. The incubator in the left houses the growth curve setup (culture flask, shaker, and automated optical density measurement system), and the fresh media reservoir. The commercial incubator on the right houses the microscope and the microfluidic device in which cells are loaded. These two incubators are connected via an insulated duct through which the tubing that carry cells and media go from the flask to the microfluidic device. b, Detailed schematic of the flow-setup – showing the pumps, switches and liquid reservoirs. The box on the left shows the setup used for automatically washing the system before and after every run. A peristaltic pump and a 4-way switch are used to sequentially pump liquid from the reservoirs containing bleach, ethanol, and water to the culture flask or the media reservoir. The box in the center shows components that are housed in the incubator shown on the left of (a). Cells are grown in a baffled-bottom culture flask, which is placed on an orbital shaker. An inline automated OD-meter is used for continuously monitoring the optical density of the culture using a LED-photodiode pair. A set of pumps flow the culture to the OD meter and back, while another one flows it to the microfluidic device. A similar set of pumps are used on the path for fresh media, and both paths can be used interchangeably. The box on the right shows the components housed in the second incubator. These include a set of pinch valves that enable switch from culture to fresh media, and vice versa. We use five 3-way pinch-valves to make sure there is minimal delay in switch, the wash is clean and devoid of any residual bacteria from the culture, and the path is free of bubbles. This design also keeps individual paths isolated and enable wash with bleach, ethanol, and water, while the other path is in use. The media coming out of the final (rightmost) valve can be split using a manifold to flow through different flow-channels in the microfluidic device. d, A detailed schematic of the pinch valve assembly and sequences of steps involved in the media switch is shown. e, Schematic of the bubble-trap is shown to illustrate the principle of operation. Media from the culture flask is dripped into the reservoir (1) and a taken out using another tubing (2) that is placed at the liquid interface to remove bubbles and extra liquid. Due to this design, the media at the bottom of the reservoir stays essentially free of bubbles and is delivered to the mother-machine using a tubing (3) whose inlet is all the way at the bottom of the reservoir. The reservoir has transparent glass-walls (4) and the magnetic stirrer is used to prevent the culture from settling down and to keep it uniform. We use a LED (5) to shine near-IR light through the culture and monitor the transmittance using a photodiode (6) placed in the opposite direction to quantify the optical density of the culture.

Fig. 1 |. Accurate high-throughput measurement of cell-growth physiology and gene expression along the growth curve.

a, A simplified schematic depicting the growth-curve platform. The platform is based on the mother machine microfluidic device (right), in which cells under observation are grown in channels (shown in red) while liquid medium is pumped through an orthogonal flow channel. To observe growth dynamics, we flow actively growing bulk culture into the mother machine device while continuously observing its optical density (OD). As the bulk culture flows past (black cells) the red cells in the device (red) respond synchronously with the batch culture. At any point, the switch can enable flow of fresh medium, enabling observation of cells returning to optimal exponential growth. The dimensions (W, L and G in the inset) of the mother machine were highly optimized to meet the demanding requirements associated with flowing dense cultures through the flow channels. b, The optimizations made to the mother machine design have greatly improved the throughput. We can image up to 16 strains in parallel, with imaging of 705 FOVs, each containing 186 ± 1 (mean ± s.d.) lineages in under 5 min, giving a throughput of 131,072 (16 × 8,192) lineages imaged every 5 min, often for multiple days. We show a montage of 500 FOVs in the top left corner. The range of intensities present in the individual FOVs in the montage of FOVs has been increased for visualization purposes. c, Top: kymograph showing a single lineage of cells in a channel expressing a fluorescent RpoS transcriptional reporter as it goes through two consecutive rounds of growth curve (bottom). Bottom: 80 single-cell traces from a single FOV of RpoS expression (orange lines) and cell size (blue lines) as cells enter and exit from two consecutive rounds of stationary phase. Two cell-size traces and two expression traces are highlighted to illustrate high variability between the two rounds of stationary phase. The high-throughput measurements of each property enable us to measure accurate distributions of expression level and cell sizes at any time point along the growth curve. a.u., arbitrary units; OD₆₀₀, optical density at 600 nm.

Fig. 2 |. Tracking physiology and gene expression in single cells and bulk cultures.

a, The bulk dynamics observed in the flask are synced with the dynamics of single cells in the mother machine. When the optical density (black) of the culture goes through an inflection point—such as the valley in bulk growth rate (yellow), represented by the rate of change in log(OD) per minute—there is a synchronous drop in the average cell length (blue) and an increase of RpoS transcriptional activity (red) of the cells in the mother machine device. To examine how well the cells in the mother machine channels mimic the cells grown in the bulk culture, we compared the average dynamics of cells in the mother machine with snapshots from cells grown in the flask. b, Schematic of the corresponding experimental setup. c, The average trend from the cells in the mother machine are plotted as solid lines (blue, cell length; red, RpoS transcriptional activity). Simple agar pad snapshots are compared with measurements in the mother machine during the entry to stationary phase. Black, OD₆₀₀ of the culture during entry. d, During exit, snapshots were acquired with the microfluidics-assisted cell screening device28, which enables observation of very dilute cultures during exit from stationary phase. Values from individual cells are plotted as blue circles (length) and red circles (RpoS). In c and d, the shaded region (from the mother machine) and the error bars (from the agar pad) represent s.d. The average cell length from snapshots of bulk culture is generally shorter than average lengths in the mother machine, due to different age distribution, with more new cells in bulk culture compared with cells in the mother machine.

Fig. 3 |. Cell-size regulation during entry and exit from stationary phase reveals novel control principles.

a, Cell lengths of two representative bacteria are shown (log scale) as they enter stationary phase after passing through diauxic shift. Individual cells slow their growth during the diauxic shift period. However, the interdivision times do not slow down, as shown by the horizontal blue and yellow lines that mark the division times for the two traces. Both the specific growth rate (g) and splitting rate (s) can be computed from a single trace (details are presented in Supplementary Note 13). Since the data are collected every 1 min, we get a high-resolution estimate of the size at birth (L_birth) and size at division (L_div). b, Correlation between cell lengths at birth and at division are plotted during the entry to stationary phase (1.0 h from diauxic shift). The Pearson correlation coefficient (C) and the slope of the linear fit (black dotted line; S) are shown on the plot. Theoretical lines for the adder, timer and sizer models are shown as blue, purple and green lines, respectively. c, The average splitting rate and specific growth rate of the population are plotted in terms of number of doublings per minute at each time point of the experiment relative to the diauxic shift time point. During the entry to stationary phase, the cell splitting rate (red) changes gradually through the diauxic shift (dotted line), but the natural specific growth rate (blue) drops precipitously. d, Cell lengths of two bacteria during the exit from stationary phase. e, Correlation between cell length at birth and at division is shown during the exit from stationary phase. f, Summary of size-regulation analysis from 5 different growth-curve experiments. Cells behave as mixed adder–timers during entry to stationary phase (<C_entry> = 0.74) and act as sizers during exit from stationary phase (<C_exit> = 0.12) and return to exponential phase where they behave as adders (<C_exponential> = 0.50). a,d, Time stamps are shifted with respect to diauxic shift (t = 0 at diauxic shift).

Fig. 4 |. Stationary phase length distribution and survival of deep stationary phase.

a, Two sample traces highlight the differing number of divisions performed during entry and exit for large (blue) and small (orange) stationary phase cells. b, The number of divisions performed during entry (brown), exit (green) and in total from entry through exit (yellow) are plotted against stationary phase cell size binned by percentile. The mean values are plotted with error bars (s.e.m.) and a linear regression line is fit to these points. c, Cells were subjected to a stationary phase lasting one week before being provided with fresh medium. Cell length time traces for ten example cells that exited from deep stationary phase are plotted in translucent red and a sample trace is overlaid in opaque red. Traces in blue show cell length of a sample of 10 cells that did not begin dividing within 10 h of receiving fresh medium. d, The percentage of cells of a given size that began dividing within 10 h (red) and the percentage that never began dividing (blue). In c and d, x represents the smallest quantile and * marks the largest quantile. e, Kymograph showing a channel containing persister mother cells during antibiotic treatment and recovery. f, Sample traces of 258 persister cells (orange) and non-persisters (cells that chain and die during ampicillin treatment; grey). The largest (black) and smallest (red) cells in the population are highlighted. Larger cells tend to exit more quickly and are therefore vulnerable to ampicillin treatment, whereas smaller cells exit stationary phase later and survive. The blue dashed line represents the timepoint where the media was switched to antibiotic-free rich growth medium. g, Distribution of cell sizes in stationary phase for cells that eventually become persisters in stationary phase (orange) compared with the overall population (grey). Each population has been normalized independently.