Single-cell growth inference of Corynebacterium glutamicum reveals asymptotically linear growth

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    Evaluation Summary:

    The paper presents a method for inferring the growth dynamics of bacteria from noisy single-cell data and applies this to C. glutamicum. Applying the method to experiments three phases of growth during the cell cycle are identified, including a dominant period of linear growth, which is interpreted in terms of a growth mode that is limited by polar cell wall synthesis.

    (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. The reviewers remained anonymous to the authors.)

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Abstract

Regulation of growth and cell size is crucial for the optimization of bacterial cellular function. So far, single bacterial cells have been found to grow predominantly exponentially, which implies the need for tight regulation to maintain cell size homeostasis. Here, we characterize the growth behavior of the apically growing bacterium Corynebacterium glutamicum using a novel broadly applicable inference method for single-cell growth dynamics. Using this approach, we find that C. glutamicum exhibits asymptotically linear single-cell growth. To explain this growth mode, we model elongation as being rate-limited by the apical growth mechanism. Our model accurately reproduces the inferred cell growth dynamics and is validated with elongation measurements on a transglycosylase deficient ΔrodA mutant. Finally, with simulations we show that the distribution of cell lengths is narrower for linear than exponential growth, suggesting that this asymptotically linear growth mode can act as a substitute for tight division length and division symmetry regulation.

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  1. Evaluation Summary:

    The paper presents a method for inferring the growth dynamics of bacteria from noisy single-cell data and applies this to C. glutamicum. Applying the method to experiments three phases of growth during the cell cycle are identified, including a dominant period of linear growth, which is interpreted in terms of a growth mode that is limited by polar cell wall synthesis.

    (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. The reviewers remained anonymous to the authors.)

  2. Reviewer #1 (Public Review):

    The paper by Messelink analyzes the cell growth of the bacterium Corynebacterium glutamicum by tracking the length of individual bacteria in a microfluidic device and analyzing the data with a new inference method. Analysis of cell growth has been established as a useful tool to get insight into fundamental biological processes including the coordination of biosynthetic pathways, DNA replication and cell division, and ageing. The complication of such analysis is that single-cell growth data is noisy and cell not only show a range of growth rates, but also a range of lengths at birth and at division. One goal is thus to characterize the cell size (here: length L) as a function of the time since birth (t) and the length at birth (lb), from which growth starts, L(t,lb). One approach is to consider bins of birth length and then determine the average growth curve for each bin, L(t | lb), i.e. conditioned on birth length. Here the authors chose a new, complementary approach and consider instead the length as a function of birth length, conditional on a given cell age, L (lb | t). Since the relation turns out to be linear, a linear fit provides an accurate dependence on birth length, the less well sampled of the two parameters and thus a good description of L(t, lb), which is then analyzed further.

    This is a great method of analysis and the authors use it to identify several phases of growth. Initially, the length growth rate of C. glutamicum increases and then is constant, indicating linear length growth. In the final phase, cells start to divide, in particular, the faster growing ones, making the interpretation of the data more difficult.

    The linear growth is then interpreted in terms of a model based on cell wall synthesis at the pole, which is supported by a simple calculations as well as behavior of some mutants.

    While the results of the paper are nice and the inference method used here is very promising, the framing of the discussion is in some places less convincing. The authors argue that their results go against a commonly accepted paradigm of exponential growth, which appears greatly exaggerated. There is a long history of debate about linear versus exponential growth, so even though some prominent recent results have supported exponential growth, I think the idea of a dominant paradigm here is a straw man and ignores the history of the subject. There is no reason not to expect a variety of growth patterns in different microbes, given their diversity in many other features. Rather than viewing the growth pattern described here as one that contradicts a consensus, I would see it as an indication of such diversity.

    The part that remains somewhat unsatisfying about this work is the treatment of the late phase of growth, in which analysis is difficult due to the division of cells that removes fast growing cells from the sampled population. The authors solve this issue by analyzing growth only up to the point where the first cell divides. However, they appear to suggest that linear growth continues beyond that, for which some more support would be desirable.

  3. Reviewer #2 (Public Review):

    The work tracks single-cell growth trajectories of the bacterieum C. glutamicum and uses quantitative analysis methods to probe growth rate within the cell-cycle. The growth is found to be asymptotically linear, with the onset of linear growth not corresponding to the onset of septum formation. However, the paper supports a model where polar cell-growth is rate-limiting. The authors find a reasonable agreement between the hypothesized RAG model and the elongation rate vs time plots obtained from the experiments.