Quantifying the branching frequency of virtual filamentous microbes using fractal analysis

A FIJI macro for quantifying pattern in extracellular matrix

Diverse extracellular matrix patterns are observed in both normal and pathological tissue. However, most current tools for quantitative analysis focus on a single aspect of matrix patterning. Thus, an automated pipeline that simultaneously quantifies a broad range of metrics and enables a comprehensive description of varied matrix patterns is needed. To this end, we have developed an ImageJ plugin called TWOMBLI, which stands for The Workflow Of Matrix BioLogy Informatics. This pipeline includes metrics of matrix alignment, length, branching, end points, gaps, fractal dimension, curvature, and the distribution of fibre thickness. TWOMBLI is designed to be quick, versatile and easy-to-use particularly for non-computational scientists. TWOMBLI can be downloaded from https://github.com/wershofe/TWOMBLI together with detailed documentation and tutorial video. Although developed with the extracellular matrix in mind, TWOMBLI is versatile and can be applied to vascular and cytoskeletal networks. Here we present an overview of the pipeline together with examples from a wide range of contexts where matrix patterns are generated.

Advanced strategy for metabolite exploration in filamentous fungi

Filamentous fungi comprise an abundance of gene clusters that encode high-value metabolites, whereas affluent gene clusters remain silent during laboratory conditions. Complex cellular metabolism further limits these metabolite yields. Therefore, diverse strategies such as genetic engineering and chemical mutagenesis have been developed to activate these cryptic pathways and improve metabolite productivity. However, lower efficiencies of gene modifications and screen tools delayed the above processes. To address the above issues, this review describes an alternative design-construction evaluation optimization (DCEO) approach. The DCEO tool provides theoretical and practical principles to identify potential pathways, modify endogenous pathways, integrate exogenous pathways, and exploit novel pathways for their diverse metabolites and desirable productivities. This DCEO method also offers different tactics to balance the cellular metabolisms, facilitate the genetic engineering, and exploit the scalable metabolites in filamentous fungi.

Tradeoffs in hyphal traits determine mycelium architecture in saprobic fungi

The fungal mycelium represents the essence of the fungal lifestyle, and understanding how a mycelium is constructed is of fundamental importance in fungal biology and ecology. Previous studies have examined initial developmental patterns or focused on a few strains, often mutants of model species, and frequently grown under non-harmonized growth conditions; these factors currently collectively hamper systematic insights into rules of mycelium architecture. To address this, we here use a broader suite of fungi (31 species including members of the Ascomycota, Basidiomycota and Mucoromycota), all isolated from the same soil, and tested for ten architectural traits under standardized laboratory conditions. We find great variability in traits among the saprobic fungal species, and detect several clear tradeoffs in mycelial architecture, for example between internodal length and hyphal diameter. Within the constraints so identified, we document otherwise great versatility in mycelium architecture in this set of fungi, and there was no evidence of trait 'syndromes' as might be expected. Our results point to an important dimension of fungal properties with likely consequences for coexistence within local communities, as well as for functional complementarity (e.g. decomposition, soil aggregation).

Aspergillus fumigatus branching complexity in vitro: 2D images and dynamic modeling

BACKGROUND

Aspergillus fumigatus causes serious infections in humans, and its virulence correlates with hyphal growth, branching and formation of the filamentous mycelium. The filamentous mycelium is a complex structure inconvenient for quantity analysis. In this study, we monitored the branching of A. fumigatus filamentous mycelium in vitro at different points in time in order to assess the complexity degree and develop a dynamic model for the branching complexity.

METHOD

We used fractal analysis of microscopic images (FAMI) to measure the fractal dimensions (D) of the branching complexity within 24 h of incubation.

RESULTS

By photographing the filamentous mycelium dynamically and processing the images, the D variation curve of A. fumigatus complexity degree was obtained. We acquired the D variation curve which contained initial exponential period and stationary period of A. fumigatus branching. Further, the obtained data of D was modeled via the logistic model (LM) to develop a dynamic model of A. fumigatus branching for the prediction of the specific growth rate of branching value (0.23 h^-1).

CONCLUSIONS

Developed FAMI and LM models present a simple and non-destructive method of predicting the evolution of branching complexity of A. fumigatus. These models are useful as laboratory measurements for the prediction of hyphal and mycelium development, especially relevant to the pathogenesis study of aspergillosis, as well as pathogenesis of other diseases caused by moulds.

Real-time monitoring of fungal growth and morphogenesis at single-cell resolution

Development times for efficient large-scale production, utilizing fungal species, are still very long. This is mainly due to the poor knowledge of many important variables related to fungal growth and morphogenesis. We specifically addressed this knowledge gap by combining a microfluidic cultivation device with time-lapse live cell imaging. This combination facilitates (i) studying population heterogeneity at single-cell resolution, (ii) monitoring of fungal morphogenesis in a high spatiotemporal manner under defined environmental conditions, and (iii) parallelization of experiments for statistical data analysis. Our analysis of Penicillium chrysogenum, the workhorse for antibiotic production worldwide, revealed significant heterogeneity in size, vitality and differentiation times between spore, mycelium and pellets when cultivated under industrially relevant conditions. For example, the swelling rate of single spores in complex medium ( μ = 0.077 ± 0.036 h - 1 ) and the formation rate of higher branched mycelia in defined glucose medium ( μ = 0.046 ± 0.031 h - 1 ) were estimated from broad time-dependent cell size distributions, which in turn were derived from computational image analysis of 257 and 49 time-lapse series, respectively. In order to speed up the development of new fungal production processes, a deeper understanding of these heterogeneities is required and the presented microfluidic single-cell approach provides a solid technical foundation for such quantitative studies.

The Taming of the Shrew--Controlling the Morphology of Filamentous Eukaryotic and Prokaryotic Microorganisms

One of the most sensitive process characteristics in the cultivation of filamentous biological systems is their complex morphology. In submerged cultures, the observed macroscopic morphology of filamentous microorganisms varies from freely dispersed mycelium to dense spherical pellets consisting of a more or less dense, branched and partially intertwined network of hyphae. Recently, the freely dispersed mycelium form has been in high demand for submerged cultivation because this morphology enhances the growth and production of several valuable products. A distinct filamentous morphology and productivity are influenced by the environment and can be controlled by inoculum concentration, spore viability, pH value, cultivation temperature, dissolved oxygen concentration, medium composition, mechanical stress or process mode as well as through the addition of inorganic salts or microparticles, which provides the opportunity to tailor a filamentous morphology. The suitable morphology for a given bioprocess varies depending on the desired product. Therefore, the advantages and disadvantages of each morphological type should be carefully evaluated for every biological system. Because of the high industrial relevance of filamentous microorganisms, research in previous years has aimed at the development of tools and techniques to characterise their growth and obtain quantitative estimates of their morphological properties. The focus of this review is on current advances in the characterisation and control of filamentous morphology with a separation of eukaryotic and prokaryotic systems. Furthermore, recent strategies to tailor the morphology through classical biochemical process parameters, morphology and genetic engineering to optimise the productivity of these filamentous systems are discussed.

Automated analysis of filamentous microbial morphology with AnaMorf

The morphological quantification of filamentous microbes represents an important analytical technique in the optimization of bioprocesses involving such organisms, given the demonstrated links between morphology and metabolite yield. However, in many studies, much of this quantification has required some degree of manual intervention, if it has been conducted at all, burdening biotechnologists with a time-consuming process and potentially introducing bias into analyses. Here, software for the automated quantification of filamentous microbes is presented, implemented as a plug-in for the widely used, freely available image analysis package, ImageJ. The software, together with all related source code, documentation and test data, is freely available to the community via an online repository.

Fungal Morphology in Industrial Enzyme Production--Modelling and Monitoring

Filamentous fungi are widely used in the biotechnology industry for the production of industrial enzymes. Thus, considerable work has been done with the purpose of characterizing these processes. The ultimate goal of these efforts is to be able to control and predict fermentation performance on the basis of "standardized" measurements in terms of morphology, rheology, viscosity, mass transfer and productivity. However, because the variables are connected or dependent on each other, this task is not trivial. The aim of this review article is to gather available information in order to explain the interconnectivity between the different variables in submerged fermentations. An additional factor which makes the characterization of a fermentation broth even more challenging is that the data obtained are also dependent on the way they have been collected-meaning which technologies or probes have been used, and on the way the data is interpreted-i.e. which models were applied. The main filamentous fungi used in industrial fermentation are introduced, ranging from Trichoderma reesei to Aspergillus species. Due to the fact that secondary metabolites, like antibiotics, are not to be considered bulk products, organisms like e.g. Penicillium chrysogenum are just briefly touched upon for the description of some characterization techniques. The potential for development of different morphological phenotypes is discussed as well, also in view of what this could mean to productivity and-equally important-the collection of the data. An overview of the state of the art techniques for morphology characterization is provided, discussing methods that finally can be employed as the computational power has grown sufficiently in the recent years. Image analysis (IA) clearly benefits most but it also means that methods like near infrared measurement (NIR), capacitance and on-line viscosity now provide potential alternatives as powerful tools for characterizing morphology. These measuring techniques, and to some extent their combination, allow obtaining the data necessary for supporting the creation of mathematical models describing the fermentation process. An important part of this article will indeed focus on describing the different models, and on discussing their importance to fermentations of filamentous fungi in general. The main conclusion is that it has not yet been attempted to develop an overarching model that spans across strains and scales, as most studies indeed conclude that their respective results might be strain specific and not necessarily valid across scales.