Exploiting geometric similarity for statistical quantification of fluorescence spatial patterns in bacterial colonies.

BACKGROUND: Currently the combination of molecular tools, imaging techniques and analysis software offer the possibility of studying gene activity through the use of fluorescent reporters and infer its distribution within complex biological three-dimensional structures. For example, the use of Confocal Scanning Laser Microscopy (CSLM) is a regularly-used approach to visually inspect the spatial distribution of a fluorescent signal. Although a plethora of generalist imaging software is available to analyze experimental pictures, the development of tailor-made software for every specific problem is still the most straightforward approach to perform the best possible image analysis. In this manuscript, we focused on developing a simple methodology to satisfy one particular need: automated processing and analysis of CSLM image stacks to generate 3D fluorescence profiles showing the average distribution detected in bacterial colonies grown in different experimental conditions for comparison purposes. RESULTS: The presented method processes batches of CSLM stacks containing three-dimensional images of an arbitrary number of colonies. Quasi-circular colonies are identified, filtered and projected onto a normalized orthogonal coordinate system, where a numerical interpolation is performed to obtain fluorescence values within a spatially fixed grid. A statistically representative three-dimensional fluorescent pattern is then generated from this data, allowing for standardized fluorescence analysis regardless of variability in colony size. The proposed methodology was evaluated by analyzing fluorescence from GFP expression subject to regulation by a stress-inducible promoter. CONCLUSIONS: This method provides a statistically reliable spatial distribution profile of fluorescence detected in analyzed samples, helping the researcher to establish general correlations between gene expression and spatial allocation under differential experimental regimes. The described methodology was coded into a MATLAB script and shared under an open source license to make it accessible to the whole community.

Dynamics of Pseudomonas putida biofilms in an upscale experimental framework.

Exploitation of biofilms for industrial processes requires them to adopt suitable physical structures for rendering them efficient and predictable. While hydrodynamics could be used to control material features of biofilms of the platform strain Pseudomonas putida KT2440 there is a dearth of experimental data on surface-associated growth behavior in such settings. Millimeter scale biofilm patterns formed by its parental strain P. putida mt-2 under different Reynolds numbers (Re) within laminar regime were analyzed using an upscale experimental continuous cultivation assembly. A tile-scan image acquisition process combined with a customized image analysis revealed patterns of dense heterogeneous structures at Re = 1000, but mostly flattened coverings sparsely patched for Re < 400. These results not only fix the somewhat narrow hydrodynamic regime under which P. putida cells form stable coatings on surfaces destined for large-scale processes, but also provide useful sets of parameters for engineering catalytic biofilms based on this important bacterium as a cell factory.

Technical upgrade of an open-source liquid handler to support bacterial colony screening.

The optimization of genetically engineered biological constructs is a key step to deliver high-impact biotechnological applications. The use of high-throughput DNA assembly methods allows the construction of enough genotypic variants to successfully cover the target design space. This, however, entails extra workload for researchers during the screening stage of candidate variants. Despite the existence of commercial colony pickers, their high price excludes small research laboratories and budget-adjusted institutions from accessing such extensive screening capability. In this work we present COPICK, a technical solution to automatize colony picking in an open-source liquid handler Opentrons OT-2. COPICK relies on a mounted camera to capture images of regular Petri dishes and detect microbial colonies for automated screening. COPICK's software can then automatically select the best colonies according to different criteria (size, color and fluorescence) and execute a protocol to pick them for further analysis. Benchmark tests performed for E. coli and P. putida colonies delivers a raw picking performance over pickable colonies of 82% with an accuracy of 73.4% at an estimated rate of 240 colonies/h. These results validate the utility of COPICK, and highlight the importance of ongoing technical improvements in open-source laboratory equipment to support smaller research teams.

Quantitative assessment of morphological traits of planktonic bacterial aggregates.

The efficiency of multi-strain planktonic flocs of bacteria as biocatalytic agents in aqueous media depends to a considerable extent on their three-dimensional aggregation patterns. Yet, numerical methodologies for full characterization of such heterogeneous biomass structures are largely missing. In this work we present a descriptive methodology for quantitatively portraying and identifying suspended cell clumps formed by planktonic bacteria. In order to benchmark the procedure, we tackled the behavior of cells of the environmental and biotechnologically robust species Pseudomonas putida whose surfaces were decorated with genetically encoded adhesins. Upon induction, such adhesins promoted specific inter-bacterial attachment leading to controllable and tractable floc formation in suspension. Microscopy and flow cytometry data were then gathered and further analyzed by means of a distinct metric set. Applying these parameters permitted creating comparable clumping footprints for every sample at both single-cell and population level. The hereby described approach provides a rigorous frame for following the assembly and organization of complex microbial communities as planktonic flocs.

An automated DIY framework for experimental evolution of Pseudomonas putida.

Adaptive laboratory evolution (ALE) is a general and effective strategy for optimizing the design of engineered genetic circuits and upgrading metabolic phenotypes. However, the specific characteristics of each microorganism typically ask for exclusive conditions that need to be adjusted to the biological chassis at stake. In this work, we have adopted a do-it-yourself (DIY) approach to implement a flexible and automated framework for performing ALE experiments with the environmental bacterium and metabolic engineering platform Pseudomonas putida. The setup includes a dual-chamber semi-continuous log-phase bioreactor design combined with an anti-biofilm layout to manage specific traits of this bacterium in long-term cultivation experiments. As a way of validation, the prototype was instrumental for selecting fast-growing variants of a P. putida strain engineered to metabolize D-xylose as sole carbon and energy source after running an automated 42 days protocol of iterative regrowth. Several genomic changes were identified in the evolved population that pinpointed the role of RNA polymerase in controlling overall physiological conditions during metabolism of the new carbon source.

Assembly of a Custom-made Device to Study SpreadingPatterns of Pseudomonas putida Biofilms.

Biofilms are bacterial communities in the shape of exopolysaccharide matrix-encased aggregates attached onto interphases able to resist environmental aggressions. The development of bacteria in the shape of biofilms deeply affects the performance of many industrial processes which work with fluidic systems, where bacteria may settle and prosper. As a consequence industrial equipment experiments low performance issues and substantial maintenance costs. The study of how bacteria of industrial interest such as Pseudomonas putida spread in these fluidic systems is highly dependent on the chosen experimental system to retrieve such data, thus using scaled prototypes becomes an essential step towards the design of a more efficient system to handle biofilms, either to control them or to prevent them. This protocol describes how to assemble, operate and maintain a device to grow and monitor the biofilm spreading pattern of this bacterium (as a function of the fluid hydrodynamics) in a custom-made chamber larger than those typically used in laboratory environments, and how to analyze the information gathered from it in a straightforward fashion. Description of the protocol was thought to be used as a working template not only for the presented case study but for any other potential experiment in different contexts and diverse scales following similar design principles.

Stenosis triggers spread of helical Pseudomonas biofilms in cylindrical flow systems.

Biofilms are multicellular bacterial structures that adhere to surfaces and often endow the bacterial population with tolerance to antibiotics and other environmental insults. Biofilms frequently colonize the tubing of medical devices through mechanisms that are poorly understood. Here we studied the helicoidal spread of Pseudomonas putida biofilms through cylindrical conduits of varied diameters in slow laminar flow regimes. Numerical simulations of such flows reveal vortical motion at stenoses and junctions, which enhances bacterial adhesion and fosters formation of filamentous structures. Formation of long, downstream-flowing bacterial threads that stem from narrowings and connections was detected experimentally, as predicted by our model. Accumulation of bacterial biomass makes the resulting filaments undergo a helical instability. These incipient helices then coarsened until constrained by the tubing walls, and spread along the whole tube length without obstructing the flow. A three-dimensional discrete filament model supports this coarsening mechanism and yields simulations of helix dynamics in accordance with our experimental observations. These findings describe an unanticipated mechanism for bacterial spreading in tubing networks which might be involved in some hospital-acquired infections and bacterial contamination of catheters.

Physical Forces Shape Group Identity of Swimming Pseudomonas putida Cells.

The often striking macroscopic patterns developed by motile bacterial populations on agar plates are a consequence of the environmental conditions where the cells grow and spread. Parameters such as medium stiffness and nutrient concentration have been reported to alter cell swimming behavior, while mutual interactions among populations shape collective patterns. One commonly observed occurrence is the mutual inhibition of clonal bacteria when moving toward each other, which results in a distinct halt at a finite distance on the agar matrix before having direct contact. The dynamics behind this phenomenon (i.e., intolerance to mix in time and space with otherwise identical others) has been traditionally explained in terms of cell-to-cell competition/cooperation regarding nutrient availability. In this work, the same scenario has been revisited from an alternative perspective: the effect of the physical mechanics that frame the process, in particular the consequences of collisions between moving bacteria and the semi-solid matrix of the swimming medium. To this end, we set up a simple experimental system in which the swimming patterns of Pseudomonas putida were tested with different geometries and agar concentrations. A computational analysis framework that highlights cell-to-medium interactions was developed to fit experimental observations. Simulated outputs suggested that the medium is compressed in the direction of the bacterial front motion. This phenomenon generates what was termed a compression wave that goes through the medium preceding the swimming population and that determines the visible high-level pattern. Taken together, the data suggested that the mechanical effects of the bacteria moving through the medium created a factual barrier that impedes to merge with neighboring cells swimming from a different site. The resulting divide between otherwise clonal bacteria is thus brought about by physical forces-not genetic or metabolic programs.