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Memory and modularity in cell-fate decision making

Nature volume 503, pages 481–486 (2013)Cite this article

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Abstract

Genetically identical cells sharing an environment can display markedly different phenotypes. It is often unclear how much of this variation derives from chance, external signals, or attempts by individual cells to exert autonomous phenotypic programs. By observing thousands of cells for hundreds of consecutive generations under constant conditions, we dissect the stochastic decision between a solitary, motile state and a chained, sessile state in Bacillus subtilis. We show that the motile state is ‘memoryless’, exhibiting no autonomous control over the time spent in the state. In contrast, the time spent as connected chains of cells is tightly controlled, enforcing coordination among related cells in the multicellular state. We show that the three-protein regulatory circuit governing the decision is modular, as initiation and maintenance of chaining are genetically separable functions. As stimulation of the same initiating pathway triggers biofilm formation, we argue that autonomous timing allows a trial commitment to multicellularity that external signals could extend.

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Figure 1: Tracking cell-fate switching in Bacillus subtilis.
Figure 2: Dynamics of cell-fate switching.
Figure 3: Memoryless initiation of chaining.
Figure 4: SlrR executes a stereotyped chaining program.

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Acknowledgements

We thank A. Lindner for sharing an early version of the microfluidic mother machine with our groups. We thank Y. Chai for discussions and C. Saenz, V. Lien, S. Hickman, J. Tresback and J. Deng for technical help with microfluidic fabrication. This work was performed in part at the Harvard Medical School Microfluidics Facility and in part at the Center for Nanoscale Systems (CNS), a member of the National Nanotechnology Infrastructure Network (NNIN), which is supported by the National Science Foundation under NSF award no. ECS-0335765. CNS is part of Harvard University. This work was supported by grants from the NIH to R.L. (GM18568) and J.P (GM081563).

Author information

Author notes

  1. Thomas M. Norman and Nathan D. Lord: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Systems Biology, Harvard Medical School, Boston, 02115, Massachusetts, USA

    Thomas M. Norman, Nathan D. Lord & Johan Paulsson

  2. Department of Molecular and Cellular Biology, Harvard University, Cambridge, 02138, Massachusetts, USA

    Richard Losick

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Contributions

T.M.N. and N.D.L. designed and fabricated the microfluidic device, cloned strains and collected the data. All authors were involved in conceiving the study, analysing results and writing the paper. J.P. and R.L. are corresponding authors.

Corresponding authors

Correspondence to Johan Paulsson or Richard Losick.

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Extended data figures and tables

Extended Data Figure 1 Ageing behaviour is independent of choice of threshold.

Initially, the duration of a chaining event was called as the time between when matrix expression was first detectable to when flagellin expression began to increase. However, to compare chains (in strain TMN1157) and pulses (in strain TMN1158), we examined whether it was possible to call the end point using only the matrix reporter, as flagellin expression does not fall during pulses. In both methods, the beginning of a chain was called as the time when the matrix signal was first detectable above background fluctuations (∼0.033 arbitrary fluorescence units, AU; see Supplementary Information). a, To call the end of a chain using only the matrix signal, various thresholds were applied. The figure plots the difference in chain duration between this single reporter method for different thresholds and the two reporter method. A threshold of 0.15 AU called the duration of chaining to within 20 min of the two-reporter method and was used throughout the text to call the end of the events. b, To show that the primary conclusions are unchanged by the choice of threshold, the ageing curves for the chained state are plotted for all thresholds shown in the previous panel. As the motile state is extremely long in comparison to the chained state, properties of the motile state are completely insensitive to how we called chains.

Extended Data Figure 2 Cell growth is homogeneous in time.

Sliding window average of division time plotted as a function of time (in strain TMN1158). Each point in the curve represents the average of all division times that occurred within a 250-min window. The grey shaded area denotes ±1 standard deviation, whereas the red shaded error denotes ±1 standard error of the mean. A flat trend indicates that conditions in the device do not change in time.

Extended Data Figure 3 Chaining incidence is constant in time.

Histogram of the number of chaining events observed in successive 330-min windows in the experiment described in Fig. 2 of the main text. As the number of observed lineages was constant throughout the experiment, these measurements reflect the average chaining rate in each window. A flat trend occurs when this average rate is constant in time, and thus that the factors controlling the switching decision have reached stationarity. Chains occurring early in our experiments were excluded from subsequent analysis to avoid any transient effects associated with adapting to growth in the device (Supplementary Information).

Extended Data Figure 4 Successive visits to the chained state are uncorrelated.

Scatter plot of the durations of sequential visits to the chained state within each wild-type lineage (440 events), analogous to Fig. 2b for the motile state. Note that some points fall on top of each other owing to the discrete nature of the measurements.

Extended Data Figure 5 SlrR is expressed strongly only in chains.

Average expression traces of slrR during chains (blue curve, 25 events) and pulses (green curve, 14 events) seen in strain TMN1180 (PtapA-cfp PslrR-mKate2 hagA233V). AU, arbitrary units.

Extended Data Figure 6 Chaining program is independent of cellular state.

To test whether the initial state of the cell influenced the chaining program, cells (of strain TMN1195) were forced to chain with a burst of expression from an IPTG-inducible sinI gene (created by switching to medium containing 100 μM IPTG for 10 min). When some cells began to return to the motile state (3 h later), a second IPTG treatment was administered. a, Average matrix expression profiles in chains induced by single pulses of IPTG (blue curve) or two consecutive IPTG pulses (red curve). The average amount of time spent as a chain after the second IPTG treatment was similar to the time seen in the chained state after a single treatment (260 min versus 280 min, 177 and 28 events, respectively). b, Scatter plot comparing matrix expression level (in arbitrary fluorescence units, AU) at the time of the second IPTG treatment to the duration of the ensuing chain, indicating that the state of the cell at the time of treatment had no effect on the subsequent chain duration. c, 10 min (blue curve, 84 events) and 20 min (red curve, 99 events) IPTG treatments were used to induce chaining, resulting in near identical distributions of chain durations. Note that the 10-min data set contained two exceptionally long chaining events that explain the slightly higher average duration.

Extended Data Figure 7 Strongly enhanced commitment to the chained state in strains overexpressing slrR.

The figure shows an example trace of a chain made by the strain TMN1206 (PtapA-cfp Phag-mKate2 hagA233V ywrK::PslrR-slrR), which bears an additional copy of the gene for SlrR under its native promoter. In this strain, most chains last long enough that they are eventually pulled out by the flow of fresh medium running through the device. Using the time to fall-out as a lower bound for the average duration of the chaining state suggests that the chained state lasts at least ∼420 min (∼15.5 generations) in these cells. AU, arbitrary units.

Extended Data Figure 8 Variation in matrix expression rate over time during build-up phase.

As described in the main text, chaining events can be naturally broken down into a build-up period, when new synthesis dominates, and a subsequent dilution period, where new synthesis is minimal. The rate of matrix reporter expression was calculated at each time point during the build-up period for all chaining events, producing a time-varying distribution of possible expression rates. The figure plots the coefficient of variation of this distribution, showing that expression rates show a roughly constant CV of ∼0.5 over much of the build-up period. Note that most chains have ceased the build-up phase by about 250 min in, so the end of the graph is less informative. This figure should be compared with Fig. 4f, which shows that the CV in the abundance of the matrix reporter decreases over the same period due to the time averaging principle described in the main text.

Extended Data Figure 9 Dilution phase is well described by a deterministic model for exponential decay.

Scatter plot comparison of observed and predicted dilution phase durations in spontaneous chains. Expected dilution times were derived from a deterministic model for exponential decay of the reporter (Supplementary Information). Close proximity to the line y = x (red line) indicates that the data are well described by the model.

Extended Data Figure 10 Image processing used for image quantification.

a, Cells are identified using a constitutively expressed YFP construct. b, Images are rotated so that channels are oriented vertically. c, Images are contrast enhanced to better identify cell boundaries. d, Cells are preliminarily identified by edge detection. e, The mask identifying cells is improved by morphological processing. f, Mother cells are identified (highlighted in white). g, Superposition of segmented cell boundaries and rotated data YFP image.

Supplementary information

Supplementary Information

This file contains Supplementary Text and Tables and additional references – see contents page for details. (PDF 944 kb)

Motility and chaining

Cells of strain TMN547 (bearing a Phag-gfp reporter for flagellin and a PtapA-mKate2 reporter for matrix expression) were trapped in a narrow liquid layer and imaged. The left panel shows a phase contrast movie, showing a mixture of motile cells and chains. The middle and right panels, respectively, show movies of flagellin (in green) and matrix reporter (in red) expression taken of the same field. Note that the three movies were acquired sequentially due to the need for different filters and thus do not show precisely the same cells. (MOV 24515 kb)

Spontaneous switching in microfluidic channels

Cells (of strain TMN1157) were loaded into the device. The movie shows the interconversion between the motile state (marked by expression of a Phag-gfp for flagellin expression, pseudocolored green) and the chained state (marked by expression of a PtapA-mKate2 for matrix expression, pseudocolored red). (MOV 18153 kb)

Pulsing in cells mutant for Slr

Cells mutant for Slr (strain TMN1158) were loaded into the device. The top panel, which is scaled identically to Supplemental Movie 2, shows that in these cells, motility is never interrupted, leading to sustained expression of the Phag-gfp fluorescent reporter for flagellin (pseudocolored green). There are, however, periodic pulses of expression of the PtapA-mKate2 matrix reporter (pseudocolored red). Note many pulses are weak and thus difficult to see against the strong flagellin signal. The bottom panel provides a contrast-enhanced version of the movie showing only the matrix reporter. (MOV 17074 kb)

Artificial induction of chaining and pulsing

An IPTG-inducible I construct was introduced to allow artificial induction of chaining or pulsing. The movie shows the response of cells wild type (on the left, strain TMN1195) and mutant for Slr (on the right, strain TMN1196) to a 10 minute pulse of 100 μM IPTG. The top row shows a merge between flagellin (in green) and matrix (in red) reporter expression, while the bottom row shows only matrix reporter expression. (MOV 14903 kb)

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Norman, T., Lord, N., Paulsson, J. et al. Memory and modularity in cell-fate decision making. Nature 503, 481–486 (2013). https://doi.org/10.1038/nature12804

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