Biofilm image reconstruction for assessing structural parameters

Impact of Fe2+ and Shear Stress on the Development and Mesoscopic Structure of Biofilms-A Bacillus subtilis Case Study

Bivalent cations are known to affect the structural and mechanical properties of biofilms. In order to reveal the impact of Fe²⁺ ions within the cultivation medium on biofilm development, structure and stability, Bacillus subtilis biofilms were cultivated in mini-fluidic flow cells. Two different Fe²⁺ inflow concentrations (0.25 and 2.5 mg/L, respectively) and wall shear stress levels (0.05 and 0.27 Pa, respectively) were tested. Mesoscopic biofilm structure was determined daily in situ and non-invasively by means of optical coherence tomography. A set of ten structural parameters was used to quantify biofilm structure, its development and change. The study focused on characterizing biofilm structure and development at the mesoscale (mm-range). Therefore, biofilm replicates (n = 10) were cultivated and analyzed. Three hypotheses were defined in order to estimate the effect of Fe²⁺ inflow concentration and/or wall shear stress on biofilm development and structure, respectively. It was not the intention to investigate and describe the underlying mechanisms of iron incorporation as this would require a different set of tools applied at microscopic levels as well as the use of, i.e., omic approaches. Fe²⁺ addition influenced biofilm development (e.g., biofilm accumulation) and structure markedly. Experiments revealed the accumulation of FeO(OH) within the biofilm matrix and a positive correlation of Fe²⁺ inflow concentration and biofilm accumulation. In more detail, independent of the wall shear stress applied during cultivation, biofilms grew approximately four times thicker at 2.5 mg Fe²⁺/L (44.8 µmol/L; high inflow concentration) compared to the low Fe²⁺ inflow concentration of 0.25 mg Fe²⁺/L (4.48 µmol/L). This finding was statistically verified (Scheirer-Ray-Hare test, ANOVA) and hints at a higher stability of Bacillus subtilis biofilms (e.g., elevated cohesive and adhesive strength) when grown at elevated Fe²⁺ inflow concentrations.

Experimental Designs to Study the Aggregation and Colonization of Biofilms by Video Microscopy With Statistical Confidence

The goal of this study was to quantify the variability of confocal laser scanning microscopy (CLSM) time-lapse images of early colonizing biofilms to aid in the design of future imaging experiments. To accomplish this a large imaging dataset consisting of 16 independent CLSM microscopy experiments was leveraged. These experiments were designed to study interactions between human neutrophils and single cells or aggregates of Staphylococcus aureus (S. aureus) during the initial stages of biofilm formation. Results suggest that in untreated control experiments, variability differed substantially between growth phases (i.e., lag or exponential). When studying the effect of an antimicrobial treatment (in this case, neutrophil challenge), regardless of the inoculation level or of growth phase, variability changed as a frown-shaped function of treatment efficacy (i.e., the reduction in biofilm surface coverage). These findings were used to predict the best experimental designs for future imaging studies of early biofilms by considering differing (i) numbers of independent experiments; (ii) numbers of fields of view (FOV) per experiment; and (iii) frame capture rates per hour. A spreadsheet capable of assessing any user-specified design is included that requires the expected mean log reduction and variance components from user-generated experimental results. The methodology outlined in this study can assist researchers in designing their CLSM studies of antimicrobial treatments with a high level of statistical confidence.

Advances and opportunities in image analysis of bacterial cells and communities

The cellular morphology and sub-cellular spatial structure critically influence the function of microbial cells. Similarly, the spatial arrangement of genotypes and phenotypes in microbial communities has important consequences for cooperation, competition, and community functions. Fluorescence microscopy techniques are widely used to measure spatial structure inside living cells and communities, which often results in large numbers of images that are difficult or impossible to analyze manually. The rapidly evolving progress in computational image analysis has recently enabled the quantification of a large number of properties of single cells and communities, based on traditional analysis techniques and convolutional neural networks. Here, we provide a brief introduction to core concepts of automated image processing, recent software tools and how to validate image analysis results. We also discuss recent advances in image analysis of microbial cells and communities, and how these advances open up opportunities for quantitative studies of spatiotemporal processes in microbiology, based on image cytometry and adaptive microscope control.

Quantitative image analysis of microbial communities with BiofilmQ

Biofilms are microbial communities that represent a highly abundant form of microbial life on Earth. Inside biofilms, phenotypic and genotypic variations occur in three-dimensional space and time; microscopy and quantitative image analysis are therefore crucial for elucidating their functions. Here, we present BiofilmQ—a comprehensive image cytometry software tool for the automated and high-throughput quantification, analysis and visualization of numerous biofilm-internal and whole-biofilm properties in three-dimensional space and time.

BiofilmQ is an image cytometry software tool that enables the visualization, quantification and analysis of biofilm properties, providing insights into their structure and function.

Three-dimensional biofilm image reconstruction for assessing structural parameters

Parameters representing three-dimensional (3D) biofilm structure are quantified from confocal laser-scanning microscope (CLSM) images. These 3D parameters describe the distribution of biomass pixels within the space occupied by a biofilm; however, they lack a direct connection to biofilm activity. As a result, researchers choose a handful of parameters without there being a consensus on a standard set of parameters. We hypothesized that a select 3D parameter set could be used to reconstruct a biofilm image and that the reconstructed and original biofilm images would have similar activities. To test this hypothesis, an algorithm was developed to reconstruct a biofilm image with parameters identical to those of the original CLSM image. We introduced an objective method to assess the reconstruction algorithm by comparing the activities of the original and reconstructed biofilm images. We found that biofilm images with identical structural parameters showed nearly identical activities and substrate concentration profiles. This implies that the set containing all common structural parameters can successfully describe biofilm structure. This finding is significant, as it opens the door to the next step, of finding a smaller standard set of biofilm structural parameters that can be used to compare biofilm structure.

A Sensitive Thresholding Method for Confocal Laser Scanning Microscope Image Stacks of Microbial Biofilms

Biofilms are surface-attached microbial communities whose architecture can be captured with confocal microscopy. Manual or automatic thresholding of acquired images is often needed to help distinguish biofilm biomass from background noise. However, manual thresholding is subjective and current automatic thresholding methods can lead to loss of meaningful data. Here, we describe an automatic thresholding method designed for confocal fluorescent signal, termed the biovolume elasticity method (BEM). We evaluated BEM using confocal image stacks of oral biofilms grown in pooled human saliva. Image stacks were thresholded manually and automatically with three different methods; Otsu, iterative selection (IS), and BEM. Effects on biovolume, surface area, and number of objects detected indicated that the BEM was the least aggressive at removing signal, and provided the greatest visual and quantitative acuity of single cells. Thus, thresholding with BEM offers a sensitive, automatic, and tunable method to maintain biofilm architectural properties for subsequent analysis.

Bacillus subtilis Biofilm Development - A Computerized Study of Morphology and Kinetics

Biofilm is commonly defined as accumulation of microbes, embedded in a self-secreted extra-cellular matrix, on solid surfaces or liquid interfaces. In this study, we analyze several aspects of Bacillus subtilis biofilm formation using tools from the field of image processing. Specifically, we characterize the growth kinetics and morphological features of B. subtilis colony type biofilm formation and compare these in colonies grown on two different types of solid media. Additionally, we propose a model for assessing B. subtilis biofilm complexity across different growth conditions. GFP-labeled B. subtilis cells were cultured on agar surfaces over a 4-day period during which microscopic images of developing colonies were taken at equal time intervals. The images were used to perform a computerized analysis of few aspects of biofilm development, based on features that characterize the different phenotypes of B. subtilis colonies. Specifically, the analysis focused on the segmented structure of the colonies, consisting of two different regions of sub-populations that comprise the biofilm – a central “core” region and an “expanding” region surrounding it. Our results demonstrate that complex biofilm of B. subtillis grown on biofilm-promoting medium [standard lysogeny broth (LB) supplemented with manganese and glycerol] is characterized by rapidly developing three-dimensional complex structure observed at its core compared to biofilm grown on standard LB. As the biofilm develops, the core size remains largely unchanged during development and colony expansion is mostly attributed to the expansion in area of outer cell sub-populations. Moreover, when comparing the bacterial growth on biofilm-promoting agar to that of colonies grown on LB, we found a significant decrease in the GFP production of colonies that formed a more complex biofilm. This suggests that complex biofilm formation has a diminishing effect on cell populations at the biofilm core, likely due to a combination of reduced metabolic rate and increased levels of cell death within this region.

NanoSIMS for biological applications: Current practices and analyses

Secondary ion mass spectrometry (SIMS) has become an increasingly utilized tool in biologically relevant studies. Of these, high lateral resolution methodologies using the NanoSIMS 50/50L have been especially powerful within many biological fields over the past decade. Here, the authors provide a review of this technology, sample preparation and analysis considerations, examples of recent biological studies, data analyses, and current outlooks. Specifically, the authors offer an overview of SIMS and development of the NanoSIMS. The authors describe the major experimental factors that should be considered prior to NanoSIMS analysis and then provide information on best practices for data analysis and image generation, which includes an in-depth discussion of appropriate colormaps. Additionally, the authors provide an open-source method for data representation that allows simultaneous visualization of secondary electron and ion information within a single image. Finally, the authors present a perspective on the future of this technology and where they think it will have the greatest impact in near future.

Quantifying element incorporation in multispecies biofilms using nanoscale secondary ion mass spectrometry image analysis

Elucidating nutrient exchange in microbial communities is an important step in understanding the relationships between microbial systems and global biogeochemical cycles, but these communities are complex and the interspecies interactions that occur within them are not well understood. Phototrophic consortia are useful and relevant experimental systems to investigate such interactions as they are not only prevalent in the environment, but some are cultivable in vitro and amenable to controlled scientific experimentation. Nanoscale secondary ion mass spectrometry (NanoSIMS) is a powerful, high spatial resolution tool capable of visualizing the metabolic activities of single cells within a biofilm, but quantitative analysis of the resulting data has typically been a manual process, resulting in a task that is both laborious and susceptible to human error. Here, the authors describe the creation and application of a semiautomated image-processing pipeline that can analyze NanoSIMS-generated data, applied to phototrophic biofilms as an example. The tool employs an image analysis process, which includes both elemental and morphological segmentation, producing a final segmented image that allows for discrimination between autotrophic and heterotrophic biomass, the detection of individual cyanobacterial filaments and heterotrophic cells, the quantification of isotopic incorporation of individual heterotrophic cells, and calculation of relevant population statistics. The authors demonstrate the functionality of the tool by using it to analyze the uptake of (15)N provided as either nitrate or ammonium through the unicyanobacterial consortium UCC-O and imaged via NanoSIMS. The authors found that the degree of (15)N incorporation by individual cells was highly variable when labeled with (15)NH4 (+), but much more even when biofilms were labeled with (15)NO3 (-). In the (15)NH4 (+)-amended biofilms, the heterotrophic distribution of (15)N incorporation was highly skewed, with a large population showing moderate (15)N incorporation and a small number of organisms displaying very high (15)N uptake. The results showed that analysis of NanoSIMS data can be performed in a way that allows for quantitation of the elemental uptake of individual cells, a technique necessary for advancing research into the metabolic networks that exist within biofilms with statistical analyses that are supported by automated, user-friendly processes.

Advancing microbial sciences by individual-based modelling

Remarkable technological advances have revealed ever more properties and behaviours of individual microorganisms, but the novel data generated by these techniques have not yet been fully exploited. In this Opinion article, we explain how individual-based models (IBMs) can be constructed based on the findings of such techniques and how they help to explore competitive and cooperative microbial interactions. Furthermore, we describe how IBMs have provided insights into self-organized spatial patterns from biofilms to the oceans of the world, phage-CRISPR dynamics and other emergent phenomena. Finally, we discuss how combining individual-based observations with IBMs can advance our understanding at both the individual and population levels, leading to the new approach of microbial individual-based ecology (μIBE).

A Generalized Spatial Measure for Resilience of Microbial Systems

The emergent property of resilience is the ability of a system to return to an original state after a disturbance. Resilience may be used as an early warning system for significant or irreversible community transition; that is, a community with diminishing or low resilience may be close to catastrophic shift in function or an irreversible collapse. Typically, resilience is quantified using recovery time, which may be difficult or impossible to directly measure in microbial systems. A recent study in the literature showed that under certain conditions, a set of spatial-based metrics termed recovery length, can be correlated to recovery time, and thus may be a reasonable alternative measure of resilience. However, this spatial metric of resilience is limited to use for step-change perturbations. Building upon the concept of recovery length, we propose a more general form of the spatial metric of resilience that can be applied to any shape of perturbation profiles (for example, either sharp or smooth gradients). We termed this new spatial measure “perturbation-adjusted spatial metric of resilience” (PASMORE). We demonstrate the applicability of the proposed metric using a mathematical model of a microbial mat.

Reconstruction of biofilm images: combining local and global structural parameters

Digitized images can be used for quantitative comparison of biofilms grown under different conditions. Using biofilm image reconstruction, it was previously found that biofilms with a completely different look can have nearly identical structural parameters and that the most commonly utilized global structural parameters were not sufficient to uniquely define these biofilms. Here, additional local and global parameters are introduced to show that these parameters considerably increase the reliability of the image reconstruction process. Assessment using human evaluators indicated that the correct identification rate of the reconstructed images increased from 50% to 72% with the introduction of the new parameters into the reconstruction procedure. An expanded set of parameters especially improved the identification of biofilm structures with internal orientational features and of structures in which colony sizes and spatial locations varied. Hence, the newly introduced structural parameter sets helped to better classify the biofilms by incorporating finer local structural details into the reconstruction process.

Linear surface roughness growth and flow smoothening in a three-dimensional biofilm model

The sessile microbial communities known as biofilms exhibit varying architectures as environmental factors are varied, which for immersed biofilms includes the shear rate of the surrounding flow. Here we modify an established agent-based biofilm model to include affine flow and employ it to analyze the growth of surface roughness of single-species, three-dimensional biofilms. We find linear growth laws for surface geometry in both horizontal and vertical directions and measure the thickness of the active surface layer, which is shown to anticorrelate with roughness. Flow is shown to monotonically reduce surface roughness without affecting the thickness of the active layer. We argue that the rapid roughening is due to nonlocal surface interactions mediated by the nutrient field, which are curtailed when advection competes with diffusion. We further argue the need for simplified models to elucidate the underlying mechanisms coupling flow to growth.

Electrochemically active biofilms: facts and fiction. A review

This review examines the electrochemical techniques used to study extracellular electron transfer in the electrochemically active biofilms that are used in microbial fuel cells and other bioelectrochemical systems. Electrochemically active biofilms are defined as biofilms that exchange electrons with conductive surfaces: electrodes. Following the electrochemical conventions, and recognizing that electrodes can be considered reactants in these bioelectrochemical processes, biofilms that deliver electrons to the biofilm electrode are called anodic, ie electrode-reducing, biofilms, while biofilms that accept electrons from the biofilm electrode are called cathodic, ie electrode-oxidizing, biofilms. How to grow these electrochemically active biofilms in bioelectrochemical systems is discussed and also the critical choices made in the experimental setup that affect the experimental results. The reactor configurations used in bioelectrochemical systems research are also described and the authors demonstrate how to use selected voltammetric techniques to study extracellular electron transfer in bioelectrochemical systems. Finally, some critical concerns with the proposed electron transfer mechanisms in bioelectrochemical systems are addressed together with the prospects of bioelectrochemical systems as energy-converting and energy-harvesting devices.

Development of 3D architecture of uropathogenic Proteus mirabilis batch culture biofilms-A quantitative confocal microscopy approach

This work studies the development of the 3D architecture of batch culture P. mirabilis biofilms on the basis of morpho-topological descriptors calculated from confocal laser scanning microscopy (CLSM) stacks with image processing routines. A precise architectonical understanding of biofilm organization on a morpho-topological level is necessary to understand emergent interactions with the environment and the appearance of functionally different progeny swarmer cells. P. mirabilis biofilms were grown on glass coverslips for seven days on LB broth and subjected to in situ immunofluorescence. Confocal image stacks were deconvolved prior to segmentation of regions of interest (ROI) that identify individual bacteria and extracellular material, followed by 3D reconstruction and calculation of different morpho-topological key descriptors. Results showed that P. mirabilis biofilm formation followed a five stage process: (i) reversible adhesion to the surface characterized by slow growth, presence of elongated bacteria, and absence of extracellular material, (ii) irreversible bacterial adhesion concomitant to decreasing elongation, and the beginning of extracellular polymer production, (iii) accelerated bacterial growth concomitant to continuously decreasing elongation and halting of extracellular polymer production, (iv) maturation of biofilm defined by maximum bacterial density, volume, minimum elongation, maximum extracellular material, and highest compaction, and (v) decreased bacterial density and extracellular material through detachment and dispersion. Swarmer cells do not play a role in P. mirabilis biofilm formation under the applied conditions. Our approach sets the basis for future studies of 3D biofilm architecture using dynamic in vivo models and different environmental conditions that assess clinical impacts of P. mirabilis biofilm.