Origin Localization in three Gram Positive Bacteria - veeninglab/BactMAP GitHub Wiki
Download dataset
Download a .zip of this collection here
Do the tutorial
You can use this dataset to recreate figure 4 of our preprint (coming soon). Find the tutorial here
General Organization
This dataset is made up of three image analysis subsets:
- Bacillus subtilis with tetR-mCherry/oriC::tetO
- Streptococcus pneumoniae with parB(p)-m(sf)GFP/oriC-parS
- Staphylococcus aureus with parB-m(sf)GFP
All three sets contain fluorescence microscopy images of these strains (saved as 8-bit .TIFFs) as the files generated by phase-contrast segmentation & spot detection. To save disk space, only the fluorescence channel image stack is included in the dataset. If you would like to use the phase-contrast images as well, please contact me directly.
Growth conditions & Microscopy settings
The growth conditions & microscopy settings are described in our preprint.
Segmentation & Spot detection
For all three subsets, ISBatch’s Single Molecule BioPhysics FIJI plugin was used to detect fluorescent spots. For this, the “peakfitter” option in the plugin was used to detect single spots in each image.For the detection of cells, three different segmentation programs were used:
The Bacillus subtilis cells were segmented using ObjectJ and ChainTracer. For this, phase contrast images where used to detect the cells & far-red images with MitoTracker Far Red staining were used to detect the septa. After this, wrongly detected septa and non-detected septa were corrected using the ChainTracer interactive interface. Using the setting file object_settings.ojj (included in dataset), the bounding box coordinates of the bacilli were saved in a tab-delimited .txt-file (bsubtilis_box.txt, included in dataset).
The Streptococcus pneumoniae cells were segmented using Morphometrics. The settings used were saved as Morphometrics_prefs.MAT (included in dataset). The output containing the cell contours (MK387_phase_18-Apr-2019_CONTOURS.MAT) was saved.
The Staphylococcus aureus cells were segmented using SuperSegger. The best existing constants were tested and 60xBay was used to do the segmentation based on phase-contrast. After segmentation, the septa were assessed manually and corrected for when necessary.
Overview of files:
Files in the Bacillus subtilis-dataset:
| File | Type | Description |
|---|---|---|
| bacillus_RFP | 8-bit TIF | RFP (mCherry) channel image stack |
| bsubtilis_box | tab-delimited txt | output of ChainTracer (objectJ) analysis containing the coordinates of the minimal bounding box of each cell |
| ChainTracer03k | objectJ-file (.ojj) | settings file used to run ChainTracer in imageJ |
| objectJ_settings | objectJ-file (.ojj) | settings file used to save the whole bounding-box |
| RRB01_peakfitter_RFP | CSV | output of ISBatch’s PeakFitter option with fluorescent peak coordinates |
Files in the Streptococcus pneumoniae-dataset:
| File | Type | Description |
|---|---|---|
| MK387_GFP | 8-bit TIF | Image stack of GFP-channel (oriC-GFP) |
| MK387_phase_18-Apr-2019_CONTOURS | .MAT (matlab file) | Output of morphometrics containing cell contours |
| Morphometrics_prefs | .MAT (matlab file) | Morphometrics parameters used |
| peakfitter_GFP | CSV | output of ISBatch’s PeakFitter option with fluorescent peak coordinates |
Files in the Staphylococcus aureaus-dataset:
| File/Folder | Type | Description |
|---|---|---|
| raw_im | Folder containing TIFs | separate TIF images as used by SuperSegger for segmentation |
| xy0 to xy6 | Folder containing matlab files “cellxxx” and “clist” | Cell file: cell information & mask for each cell, listed per image frame (xy). Clist: summary of cell information of one image frame (xy) in one file. |
| CONST | .MAT (matlab file) | the parameter set used for segmentation |
| peakfitter_GFP | tab-delimited txt | output of ISBatch’s PeakFitter option with fluorescent peak coordinates |
| Stack_parB_GFP | 8-bit TIF stack | image stack with GFP channel (parB-GFP) |