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Growth mechanics of a bacterial colony
Bacterial elongation (see paragraph 1.2) and adhesion (see paragraph 1.3) of individual cells can generate mechanical stress. When considered at the scale of a microcolony, the combination of these stresses may result in particular arrangements.
Evidences of mechanical stress generation
At the individual cell level, bacterial elongation can generate forces on the surrounding environment. Indeed, E. coli cells embedded in agarose were still able to elongate and deformed the agarose gel up to 1MPa [192], corresponding to forces on the order of 10 nN. Besides, adhesion forces developed by single bacteria on a surface have been measured to be on the order of 100 pN (see paragraph 1.3.1, table 1.1). This implies that bacterial elongation could generate large enough forces to disturb the adhesion of neighboring cells. Finally, bacteria-bacteria interactions –evidenced through bacterial aggregation– also seem to be an important ingredient of the mechanical description of microcolonies. This interaction has a tendency to align neighboring cells [199]. Although no direct measurement has yielded value for this interaction, optical tweezers have enabled to measure a repulsive force on the order of 10 pN between two B. subtilis cells [200]. Up to date, little work has focused on how these elements balance at the scale of a microcolony. Monolayers of E. coli cells have been studied in 1 m high channels of finite width (between 30 and 90 m). Local bacterial elongations, coupled together by lateral contacts, resulted in a long-range orientational ordering of the bacteria inside the colony, with a characteristic correlation length of the order of a dozen of cells [201, 202]. However, buckling instabilities in high pressure zones triggered rearrangements and prevented the perfect nematic order from being achieved [203]. Another study looked at the transition from 2D to 3D growth. Microcolonies were confined between a soft hydrogel and glass. In such a configuration, the colony initially develops in 2D. When the number of bacteria in the monolayer becomes large, a second layer appears on top of the first one. Both the lateral confinement from the gel and the interactions between the bacteria and the confining surfaces –modeled by friction– have been shown to play a role in this transition from 2D to 3D growth [204].
Single-cell segmentation
Single-cell resolution was achieved by segmentation of phase or correlation images to get the mask of individual bacteria (see figure 2.3a). For this purpose we developed or adapted routines that were used according to the experiment specificities.
Live segmentation for colonies of a few cells
During laser ablation experiments, we had to precisely detect the number of bacteria in the field of view after the acquisition of each frame. In order to keep a single dividing cell in the field of view, an ablation was automatically triggered as soon as two cells were detected (see paragraph 2.4.2). To monitor the number of cells, we developed a robust segmentation algorithm for the detection of a low number of cells. It was used on correlation images. The image was binarized with a variable threshold. For each value of the threshold, the number of particles was measured. For correlation images, the threshold corresponding to a local minimum in particle number gave a correct segmentation at a few cells stage (see figure 2.2). This segmentation was automatically performed during the ablation at the 2-cells stage experiments.
Post-treatment segmentation
As a first step toward the lineage obtention (see paragraph 2.2.3), a posttreatment segmentation had to be performed on raw images. Routines were developed, or adapted from preexisting codes, to process different types of images.
Correlation images were binarized with Otsu’s method to retrieve the contour of the cells.
Phase images were treated with a routine adapted from Philippe.
Nghe [209]. An approach based on watershedding was used. For force measurement images, tracers were present in the image with an intensity similar to bacteria’s. Given the mask of the colony, the use of the routine was restricted to the colony area.
These routines were included in the Schnitzcells suite developed by Michael Elowitz’s group at the California Institute of Technology (CalTech) for segmentation and tracking of bacteria [210]. The Schnitzcells suite allows a manual verification step to correct potential mistakes made by the previous algorithms since the lineage reconstruction requires a quasi-perfect segmentation of the images.
Precise length measurement and fine detection of the division
For ablation at the 3-cells stage experiments (see paragraph 2.4.3), we wanted to be able (i) to detect septation with a high temporal resolution and (ii) to measure cell lengths with a high and assessable accuracy. We developeda procedure that allowed us to achieve a better precision than Schnitzcells on phase contrast images. A first segmentation image was computed with the interactive software iLastik. Then for each image, the phase contrast profile along the main axis of the segmented particle was analyzed for each cell with a Matlab routine. On phase contrast images, on the edge of the cells, the level goes from a high value (light background) to a low value (black inside the cell). Calculating the absolute value of the derivative of this profile locally gives a peak that corresponds to the border of the cell. We developed a program to precisely determine the border positions by fitting the profile with gaussian curves. The length of the cell was given by the distance between the two peaks and the error was computed as p « 21+ « 22 , where « 1 and « 2 were the fit uncertainties on each peak determination. In order to detect septation, the profile between the cells was either fitted by one or two gaussian curves (see figure 2.6). The correct one was chosen based on fit relevance and variance arguments automatically and/or manually when the situation was atypical. We understood the transition from a single to a double gaussian as the completion of the division event.
Growth assays between glass and agarose
In order to understand how adhesion could influence the morphogenesis of microcolonies, we imaged the growth of bacterial monoclonal colonies confined between a glass coverslip and a LB-agarose gel which provides nutrients. In this configuration, we carried out different assays at distinct stages of a microcolony formation: asymmetric adhesion assays on isolated cells (see paragraph 2.3.1); reorganization assays, after the first division (see paragraph 2.3.2); finally, the growth of the microcolony could be recorded to larger stages with single cell resolution (see paragraph 2.3.3). The strain of interest (see appendix A) was inoculated in LB from glycerol stocks and grown overnight at 37°C, 200 rpm. The day after, 2 L of a diluted solution were seeded on a 1% LB-agrose pad, prepared as described in appendix B.1. The sample was sealed with a glass coverslip through which colonies were imaged. The dilution factor from the saturated culture was chosen according to the experiment requirements: 104-fold for a single colony in a field of view, 100 to 1000-fold for several isolated cells in a field of view. Unless mentioned otherwise, all experiments were carried at 34°C.
Asymmetric adhesion assays
More than 10 cells per field were tracked over 10 different locations in the sample. Phase contrast images were recorded every 3 minutes with the custom microscope (see section 2.1) until every present cell had undergone at least one division. Every image was then analyzed with Schnitzcells (see paragraphs 2.2.2 and 2.2.3) in order to measure the cell elongation L and the position of the center of mass of the bacteria XCD!M with time. For each cell, we fitted the elongation L versus the displacement projected over the axis of the cell Xk CDMwith a linear law Xk CDM = A L. The slope A of this fit gave the asymmetry parameter. Typically, the fit was computed over 20 points.
Reorganization following the first division assays
For each experiment, one field of view with 1 to 3 isolated cells was imaged in phase contrast with the custom microscope (see section 2.1). Before any division, the growth of single cells was recorded with a 30 seconds frequency (low frequency). As soon as one cell was close to complete division, subsecond acquisition (high frequency) was switched on manually in order to image the reorganization 4. After reorganization, the low frequency acquisition was resumed until a second bacterium in the same field of view started to form a septum or until every bacterium had undergone a second division.
The high frequency was limited by the acquisition program and the average frequency over one minute could be calculated afterwards. Typical values ranged from 0.65 to 1 second. For all experiments, each microcolony growth was separately analyzed with Schnitzcells (see paragraphs 2.2.2 and 2.2.3) in order to measure the length, position and displacement of the cells.
Table of contents :
Acknowledgements
Abstract
Foreword
1 Introduction
1.1 The biofilm, a sessile bacterial colony
1.1.1 Context
1.1.2 Biofilm physiology
1.1.3 Biofilm formation
1.2 The bacterial cell cycle
1.2.1 Elongation
1.2.2 Septation
1.3 Bacterial adhesion
1.3.1 Usual adhesion assays
1.3.2 Surface proteins implied in adhesion
1.4 Growth mechanics of a bacterial colony
1.4.1 Evidences of mechanical stress generation
1.4.2 Our approach
2 Materials and methods
2.1 Microscopy
2.2 Image analysis
2.2.1 Colony segmentation
2.2.2 Single-cell segmentation
2.2.3 Tracking
2.2.4 Precise length measurement and fine detection of the division
2.2.5 Morphological parameters
2.3 Growth assays between glass and agarose
2.3.1 Asymmetric adhesion assays
2.3.2 Reorganization following the first division assays
2.3.3 Microcolony growth assays
2.4 Laser ablation
2.4.1 Set-up
2.4.2 Ablation at the 2-cells stage
2.4.3 Ablation at the 3-cells stage
2.5 Traction force microscopy
2.5.1 Adaptation of the technique to prokaryotic cells study .
2.5.2 Experimental procedure
2.5.3 Tracking of beads and calculation of forces
2.5.4 Calibration of the gel stability
3 Results and interpretation
3.1 One and two cells stage
3.1.1 Asymmetric adhesion
3.1.2 Adhesion dynamics of pre-existing poles
3.1.3 Buckling following the first division
3.2 Single-cell dynamics and colony organization
3.2.1 Centrifugal displacements driven by uniform growth within the colony
3.2.2 Organization of bacteria inside a microcolony
3.3 Cell-substrate adhesion
3.3.1 Spatio-temporal dynamics
3.3.2 Rupture of adhesive bonds
3.3.3 Evidence for polar adhesion asymmetry in growing colonies
3.3.4 Strength of adhesins
3.4 Adhesion contribution in the morphogenesis
3.4.1 Influence on morphology
3.4.2 Role of adhesion in the transition from planar to a terraced colony
3.4.3 Adaptation to the environmental challenge
Conclusion and perspectives
A Bacterial strains used in this project
B Experimental protocols
B.1 Agarose/glass sample preparation protocol
B.2 Force measurement protocol
C Growth rate and bacterial size quantification
C.1 Colonies growing between agarose and glass
C.2 Colonies growing between agarose and polyacrylamide
D Preliminary experiments
D.1 Cell length measurements during septation
D.2 Reflection Interference Contrast Microscopy
E French summary / Résumé en français
E.1 Résumé global
E.2 Avant-propos
E.3 Chapitre 1 : Introduction
E.4 Chapitre 2 : Matériels et méthodes
E.5 Chapitre 3 : Résultats et interprétations
E.6 Conclusion et perspectives
