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Automated imaging with ScanLag reveals previously undetectable bacterial growth phenotypes

Nature Methods volume 7, pages 737–739 (2010)Cite this article

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Abstract

We developed an automated system, ScanLag, that measures in parallel the delay in growth (lag time) and growth rate of thousands of cells. Using ScanLag, we detected small subpopulations of bacteria with dramatically increased lag time upon starvation. By screening a library of Escherichia coli deletion mutants, we achieved two-dimensional mapping of growth characteristics, which showed that ScanLag enables multidimensional screens for quantitative characterization and identification of rare phenotypic variants.

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Figure 1: Lag time and growth rate distribution measurements using ScanLag.
Figure 2: Two-dimensional mapping of the E. coli library of long deletions using ScanLag.

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Acknowledgements

We thank A. Keynan for invaluable discussions on the importance of the lag phase, D. Azulay and A. Bar-Yaacov for helpful theoretical discussions, I. Rosenshine (Hebrew University) for strains, and the National BioResource Project and National Institute of Genetics, Japan for the large and medium deletion mutants library, S. Silbert for initial software development and E. Rotem and S. Pearl for technical support and comments on the manuscript. The work was supported by the Human Frontier Science Program and by the Israel Science Foundation.

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Authors and Affiliations

  1. Racah Institute of Physics, The Hebrew University, Edmond J. Safra Campus, Givat-Ram, Jerusalem, Israel

    Irit Levin-Reisman, Orit Gefen, Ofer Fridman, Irine Ronin, David Shwa, Hila Sheftel & Nathalie Q Balaban

  2. Center for Nanoscience and Nanotechnology, The Hebrew University, Edmond J. Safra Campus, Givat-Ram, Jerusalem, Israel

    Nathalie Q Balaban

  3. Sudarsky Center for Computational Biology, The Hebrew University, Edmond J. Safra Campus, Givat-Ram, Jerusalem, Israel

    Nathalie Q Balaban

Authors
  1. Irit Levin-Reisman
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  2. Orit Gefen
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  4. Irine Ronin
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  5. David Shwa
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  6. Hila Sheftel
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  7. Nathalie Q Balaban
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Contributions

I.L.-R., O.G., I.R. and D.S. performed the research. O.F. and H.S. contributed analytical tools. N.Q.B., I.L.-R., I.R. and O.G. designed the research. N.Q.B. wrote the paper.

Corresponding author

Correspondence to Nathalie Q Balaban.

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Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–7 and Supplementary Data (PDF 383 kb)

Supplementary Video 1

A typical analysis process using ScanLag. Shown are analyses of overnight culture (left) and culture starved for 3 d (right). Colony appearance was automatically detected as soon as colonies reached a threshold size. Each colony was assigned an identifying number and an arbitrary color. The lower panels show the resulting distribution, for each plate, represented as 1-CDF (cumulative distribution function), which represents the fraction of the colonies that have not yet appeared. At the beginning of the movie, no colony has appeared yet, namely that fraction is 1, whereas at the end of the movie it is zero. (MOV 2108 kb)

Supplementary Software 1

ScanningManager software application controlling image acquisition by an array of scanners. (ZIP 534 kb)

Supplementary Software 2

TimeLapse analysis software application (Matlab) for the analysis of images and extraction of colony appearance data. (ZIP 57 kb)

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Levin-Reisman, I., Gefen, O., Fridman, O. et al. Automated imaging with ScanLag reveals previously undetectable bacterial growth phenotypes. Nat Methods 7, 737–739 (2010). https://doi.org/10.1038/nmeth.1485

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