Quantifying two-dimensional filamentous and invasive growth spatial patterns in yeast colonies

The top-view, two-dimensional spatial patterning of non-uniform growth in a Saccharomyces cerevisiae yeast colony is considered. Experimental images are processed to obtain data sets that provide spatial information on the cell-area that is occupied by the colony. A method is developed that allows for the analysis of the spatial distribution with three metrics. The growth of the colony is quantified in both the radial direction from the centre of the colony and in the angular direction in a prescribed outer region of the colony. It is shown that during the period of 100-200 hours from the start of the growth of the colony there is an increasing amount of non-uniform growth. The statistical framework outlined in this work provides a platform for comparative quantitative assays of strain-specific mechanisms, with potential implementation in inferencing algorithms used for parameter-rate estimation.Benjamin J. Binder, Joanna F. Sundstrom, Jennifer M. Gardner, Vladimir Jiranek, Stephen G. Olive

TAMMiCol: Tool for analysis of the morphology of microbial colonies.

Many microbes are studied by examining colony morphology via two-dimensional top-down images. The quantification of such images typically requires each pixel to be labelled as belonging to either the colony or background, producing a binary image. While this may be achieved manually for a single colony, this process is infeasible for large datasets containing thousands of images. The software Tool for Analysis of the Morphology of Microbial Colonies (TAMMiCol) has been developed to efficiently and automatically convert colony images to binary. TAMMiCol exploits the structure of the images to choose a thresholding tolerance and produce a binary image of the colony. The images produced are shown to compare favourably with images processed manually, while TAMMiCol is shown to outperform standard segmentation methods. Multiple images may be imported together for batch processing, while the binary data may be exported as a CSV or MATLAB MAT file for quantification, or analysed using statistics built into the software. Using the in-built statistics, it is found that images produced by TAMMiCol yield values close to those computed from binary images processed manually. Analysis of a new large dataset using TAMMiCol shows that colonies of Saccharomyces cerevisiae reach a maximum level of filamentous growth once the concentration of ammonium sulfate is reduced to 200 μM. TAMMiCol is accessed through a graphical user interface, making it easy to use for those without specialist knowledge of image processing, statistical methods or coding

Characterizing the shape patterns of dimorphic yeast pseudohyphae

© 2018 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.Pseudohyphal growth of the dimorphic yeast Saccharomyces cerevisiae is analysed using two-dimensional top-down binary images. The colony morphology is characterized using clustered shape primitives (CSPs), which are learned automatically from the data and thus do not require a list of predefined features or a priori knowledge of the shape. The power of CSPs is demonstrated through the classification of pseudohyphal yeast colonies known to produce different morphologies. The classifier categorizes the yeast colonies considered with an accuracy of 0.969 and standard deviation 0.041, demonstrating that CSPs capture differences in morphology, while CSPs are found to provide greater discriminatory power than spatial indices previously used to quantify pseudohyphal growth. The analysis demonstrates that CSPs provide a promising avenue for analysing morphology in high-throughput assays

Diffusion-Limited Growth of Microbial Colonies.

The emergence of diffusion-limited growth (DLG) within a microbial colony on a solid substrate is studied using a combination of mathematical modelling and experiments. Using an agent-based model of the interaction between microbial cells and a diffusing nutrient, it is shown that growth directed towards a nutrient source may be used as an indicator that DLG is influencing the colony morphology. A continuous reaction-diffusion model for microbial growth is employed to identify the parameter regime in which DLG is expected to arise. Comparisons between the model and experimental data are used to argue that the bacterium Bacillus subtilis can undergo DLG, while the yeast Saccharomyces cerevisiae cannot, and thus the non-uniform growth exhibited by this yeast must be caused by the pseudohyphal growth mode rather than limited nutrient availability. Experiments testing directly for DLG features in yeast colonies are used to confirm this hypothesis

QUANTITATIVE ANALYSIS AND IMAGING-BASED INSIGHTS INTO THE CHARACTERISTICS AND MECHANISMS OF YEAST PATTERN FORMATION

Biofilm formation is a common lifestyle adapted by bacteria and fungi in response to various environmental stresses. Bacterial and fungal biofilms adhering to medical devices convey resistance to antibiotics or biocides, causing high rates of clinical infections. Microorganisms are protected from harsh environmental conditions by reduced stress penetration through the complex biofilm architecture with distinct patterns. Although the molecular regulations of surface patterning have been well characterized in bacteria, the mechanisms underlying the complex pattern formation in eukaryotic biofilms remain unclear. This dissertation aims to investigate the salient features of robust colony expansion in yeast biofilms and the processes driving the complex pattern development. Various salient features of Saccharomyces cerevisiae colony expansion, such as of the change of size, shape, and surface pattern properties were analyzed quantitatively for various combinations of agar and sugar concentrations. I found that the size and irregularity of the FLO11 expressing colony, and wavelength of the pattern were all monotonically decreasing with agar density. These trends were consistent regardless of sugar sources. Using a mathematical model, I also demonstrated that the differential expansion pattern between the center and the edge of the colony due to the spatial differences in glucose concentration affected the convexity of the expansion curve. I found that pattern formation in S. cerevisiae was not caused by localized cell death as in Bacillus subtilis biofilms. Using quantitative measurement and physical models, I found that the surface pattern of S. cerevisiae was consistent with hierarchical wrinkling, determined by the physicochemical properties and thickness of the layered structures of the yeast biofilm and the viscoelastic agar. Furthermore, I found that two-dimensional expansion conferred a competitive advantage for FLO11 sectors during head-to-head competition with flo11Δ cells. Overall these results suggested that two-dimensionality of expansion conveyed by FLO11 directs rapid colony expansion with high irregularity at the rim, hierarchical wrinkling pattern, and competitive advantage during head-to-head competition

The Aspergillus nidulans Galf biosynthesis pathway is a promising drug target

Human systemic fungal infections are increasing, and causing high morbidity and mortality. Treatment is challenging because fungi share many metabolic pathways with mammals. Current antifungals are losing effectiveness due to drug resistance. In immunocompromised patients Aspergillus fumigatus causes systemic aspergillosis, the most important airborne fungal disease. Mortality from aspergillosis exceeds 50% even with aggressive treatment. We need novel antifungal drug targets. Fungal cell wall components are promising targets for antifungal therapy as they are essential for fungi and absent from humans. The sugar galactofuranose (Galf) is a 5-memberd ring form of galactose that is found in the cell walls of many fungi, but not in mammals. I used molecular biology and microscopy techniques to characterize Galf biosynthesis enzymes in the model species A. nidulans. I studied three enzymes that catalyze sequential steps in Galf biosynthesis: UgmA, UgtA and UgeA. UDP-galactopyranose mutase (UgmA) creates UDP-galactofuranose (UDP-Galf) from UDP galactopyranose (UDP-Galp) in the cytoplasm. The UDP-Galf transporter (UgtA) moves UDP Galf into membrane bound organelles for incorporation into cell wall compartments. Upstream of UgmA, UDP-glucose/galactose epimerase (UgeA) interconverts UDP-glucose into UDP-Galp, the UgmA substrate. Neither UgmA nor UgtA has a human counterpart; UgeA is in the Leloir galactose metabolism pathway that found in many organisms from bacteria to humans. None of UgeA, UgmA and UgtA is essential for viability of A. nidulans, but deleting any one of them substantially reduces colony growth and sporulation (Figure i). Wild type and Galf defective strains (ugeAΔ, ugmAΔ; and ugtAΔ) were quantified for colony growth, cell morphometry, spore formation and germination, as well as wall architecture. The abundance of these proteins was regulated using the alcA promoter. Galf content was assessed by immunolocalization in the Galf defective strains, showing that those strains lacked immunodetectable Galf. Gene products were localized with fluorescent protein tags; both UgmA and UgeA were cytoplasmic, whereas UgtA was Golgi localized. Wall surfaces were imaged and force-probed using transmission electron microscopy and atomic force microscopy. Overall, Galf deletion strains had aberrant wall maturation, and poorly consolidated surfaces. Our results indicate that Galf is necessary for abundant sporulation, wild type growth and full maturation of Aspergillus cell wall. Galf deletion strains were assessed for sensitivity to antifungal agents in clinical use. They were significantly more sensitive to caspofungin and amphotericin B that target cell wall synthesis and cell membrane chemistry, respectively. Thus, anti-Galf drugs (once created) may be useful in combination with existing antifungal drugs. In summary, Galf biosynthesis pathway appears to be promising as an antifungal drug development target

The Mycelium as a network

The characteristic growth pattern of fungal mycelia as an interconnected network has a major impact on how cellular events operating on a micron scale affect colony behavior at an ecological scale. Network structure is intimately linked to flows of resources across the network that in turn modify the network architecture itself. This complex interplay shapes the incredibly plastic behavior of fungi and allows them to cope with patchy, ephemeral resources, competition, damage, and predation in a manner completely different from multicellular plants or animals. Here, we try to link network structure with impact on resource movement at different scales of organization to understand the benefits and challenges of organisms that grow as connected networks. This inevitably involves an interdisciplinary approach whereby mathematical modeling helps to provide a bridge between information gleaned by traditional cell and molecular techniques or biophysical approaches at a hyphal level, with observations of colony dynamics and behavior at an ecological level

Mathematical Modelling of Pattern Formation in Yeast Biofilms

We use mathematical modelling and experiments to investigate yeast biofilm growth and pattern formation. Biofilms are sticky communities of cells and fluid residing on surfaces. As yeast biofilms are a leading cause of hospital-acquired infections, researchers have developed methods of growing them on semi-solid agar. These biofilms initially form a thin circular shape, before transitioning to a non-uniform floral morphology. To quantify biofilm growth, we use a radial statistic the measure expansion speed, and an angular pair correlation function to quantify petal formation. These spatial statistics enable comparison between experiments and mathematical model predictions. Our motivation is to improve understanding of the physical mechanisms governing biofilm formation. One hypothesised mechanism is nutrient-limited growth, in which movement and consumption of nutrients drives growth and generates patterns. Another hypothesis is that yeast biofilms expand by sliding motility, where cell proliferation and weak biofilm–substratum adhesion drive growth. Mathematical modelling enables us to investigate the contribution of each hypothesised mechanism to biofilm growth and pattern formation. We use a reaction–diffusion system with non-linear, degenerate cell diffusion to model nutrient-limited biofilm growth. This model admits sharp-fronted travelling wave solutions that advance with constant speed, an assumption consistent with experimental data. To investigate whether the reaction–diffusion model can explain petal formation, we consider the linear stability of planar travelling wave solutions to transverse perturbations. There is good agreement between the theory and experimental data, suggesting that nutrient-limited growth can explain floral pattern formation. Next, we introduce biofilm mechanics by deriving a two-phase fluid model. We treat the biofilm as a mixture of cells and an extracellular matrix, and obtain governing equations from mass and momentum conservation. Since yeast biofilm height is small compared to their radius, we use the thin-film approximation in two scaling regimes to simplify the model. The extensional flow regime involves weak biofilm–substratum adhesion, and models expansion by sliding motility. In contrast, the lubrication regime involves strong biofilm– substratum adhesion, and large pressure and surface tension. We compute axisymmetric numerical solutions to both thin-film models to investigate how mechanics affects biofilm growth. There is good agreement between the extensional flow model and experimental data, suggesting that sliding motility can explain expansion speed. Parameter sensitivity analyses show that increased nutrient supply and biomass production rates generate faster expansion. The effect of surface tension, which represents the strength of cell–cell adhesion, is the key difference between the two regimes. In the extensional flow model, surface tension inhibits ridge formation close to the leading edge, but does not affect expansion speed. In contrast, surface tension generates radial expansion in the lubrication regime. Since the thin-film models enable us to predict biofilm height and nutrient uptake explicitly, they provide a more detailed description of biofilm growth than the reaction–diffusion model. However, their complexity makes it more difficult to use linear stability analysis to investigate two-dimensional patterns. This problem, and alternative expansion mechanisms such as osmotic swelling and agar deformation, provide avenues for future work.Thesis (Ph.D.) -- University of Adelaide, School of Mathematical Sciences, 201