Bacterial Cell Colony Imaging Data 2015
The Bacterial Cell Colony Imaging Data 2015 provides a comprehensive dataset of time-lapse images of bacterial cell colonies, focusing on the symbiotic bacterium Sinorhizobium meliloti. This dataset is crucial for researchers studying cellular heterogeneity and the individuality of bacterial cells over time.
Bacterial Cell Colony Imaging Data 2015
Data Set Description
- Type: Image Files (Phase Contrast, Red, Green, Blue)
- Number of Images: 2 movies with 115 images each, 4 images per laser excitation
- Image Interval: 30 minutes
- Imaging Technique: Total Internal Reflection Fluorescence (TIRF) Microscopy
- Attribute Characteristics: High-resolution time-lapse imaging
- Date Published: 2015
- Associated Tasks: Single-cell analysis, cellular heterogeneity studies
Data are available for download under appropriate licensing.
Data Set Characteristics
| Characteristic | Details |
|---|---|
| Type | Image Files (Phase Contrast, Red, Green, Blue) |
| Number of Images | 2 movies with 460 images each (4 channels) |
| Image Interval | 30 minutes |
| Imaging Technique | Total Internal Reflection Fluorescence (TIRF) Microscopy |
| Attribute Characteristics | High-resolution time-lapse imaging |
| Date Published | 2015 |
| Associated Tasks | Single-cell analysis, cellular heterogeneity studies |
Data Sets
The dataset consists of two movies, each containing 115 images taken at 30-minute intervals. Each set of images includes four types: phase contrast, red, green, and blue, acquired using two laser sources and TIRF microscopy.
Overview of Imaging Setup and Data
- Bacterial Strain: Sinorhizobium meliloti
- Constructs: Triple fluorescence reporter cassette
- Growth Environment: Microfluidic bacterial plate
- Imaging Technique: Total Internal Reflection Fluorescence (TIRF) Microscopy using two laser sources
Significance and Applications
Individual cells in a single bacterial population may differ strikingly and even drive the health and function of the entire cell population. To study this phenomenon of individuality over time and contribute to a new understanding of cellular heterogeneity, single-cell oriented high-resolution time-lapse imaging is necessary. TIRF microscopy enables the capture of high-resolution images with reduced background fluorescence, enhancing the visibility of individual cells.
Publications
Hattab, G., Wiesmann, V., Becker, A., Munzner, T., & Nattkemper, T. W. (2018). A novel methodology for characterizing cell subpopulations in automated time-lapse microscopy. Frontiers in Bioengineering and Biotechnology, 6, 17.
doi.org/10.3389/fbioe.2018.00017
Hattab, G., & Nattkemper, T. W. (2019). SeeVis—3D space-time cube rendering for visualization of microfluidics image data. Bioinformatics, 35(10), 1802-1804.
doi.org/10.1093/bioinformatics/bty889
Hattab, G., Schlüter, J. P., Becker, A., & Nattkemper, T. W. (2017). Vicar: an adaptive and landmark-free registration of time lapse image data from microfluidics experiments. Frontiers in Genetics, 8, 69.
doi.org/10.3389/fgene.2017.00069
Schlüter, J. P., McIntosh, M., Hattab, G., Nattkemper, T. W., & Becker, A. (n.d.). Phase Contrast and Fluorescence Bacterial Time-Lapse Microscopy Image Data.
doi.org/10.4119/unibi/2777409
Schlüter, J. P., Czuppon, P., Schauer, O., Pfaffelhuber, P., McIntosh, M., & Becker, A. (2015). Classification of phenotypic subpopulations in isogenic bacterial cultures by triple promoter probing at single cell level. Journal of Biotechnology, 198, 3-14. doi.org/10.1016/j.jbiotec.2015.01.021
Data Variables
- Images: Phase contrast, red, green, and blue images of bacterial cell colonies.
- Metadata: Time stamps, laser excitation details, and other relevant imaging parameters.
Licensing
The data presented in this collection is built upon experiments and imaging techniques developed by the research team, accompanied by documented metadata, appropriate citations, and attributions to ensure proper credit and acknowledgment of the original sources.