Morphological quantification of filamentous fungal development using membrane immobilization and automatic image analysis

Analysis of the emerging physical network in young mycelia

Filamentous fungi develop intricate hyphal networks that support mycelial foraging and transport of resources. These networks have been analyzed recently using graph theory, enabling the development of models that seek to predict functional traits. However, attention has focused mainly on mature colonies. Here, we report the extraction and analysis of the graph corresponding to Trichoderma atroviride mycelia only a few hours after conidia germination. To extract the graph for a given mycelium, a mosaic conformed of multiple bright-field, optical microscopy images is digitally processed using freely available software. The resulting graphs are characterized in terms of number of nodes and edges, average edge length, total mycelium length, hyphal growth unit, maximum edge length and mycelium diameter, for colonies between 8 h and 14 h after conidium germination. Our results show that the emerging hyphal network grows first by hyphal elongation and branching, and then it transitions to a stage where hyphal-hyphal interactions become significant. As a tangled hyphal network develops with decreasing hyphal mean length, the mycelium maintains long (∼2 mm) hyphae-a behavior that suggests a combination of aggregated and dispersed architectures to support foraging. Lastly, analysis of early network development in Podospora anserina reveals striking similarity with T. atroviride, suggesting common mechanisms during initial colony formation in filamentous fungi.

Computation-aided studies related to the induction of specialized metabolite biosynthesis in microbial co-cultures: An introductory overview

Co-cultivation is an effective method of inducing the production of specialized metabolites (SMs) in microbial strains. By mimicking the ecological interactions that take place in natural environment, this approach enables to trigger the biosynthesis of molecules which are not formed under monoculture conditions. Importantly, microbial co-cultivation may lead to the discovery of novel chemical entities of pharmaceutical interest. The experimental efforts aimed at the induction of SMs are greatly facilitated by computational techniques. The aim of this overview is to highlight the relevance of computational methods for the investigation of SM induction via microbial co-cultivation. The concepts related to the induction of SMs in microbial co-cultures are briefly introduced by addressing four areas associated with the SM induction workflows, namely the detection of SMs formed exclusively under co-culture conditions, the annotation of induced SMs, the identification of SM producer strains, and the optimization of fermentation conditions. The computational infrastructure associated with these areas, including the tools of multivariate data analysis, molecular networking, genome mining and mathematical optimization, is discussed in relation to the experimental results described in recent literature. The perspective on the future developments in the field, mainly in relation to the microbiome-related research, is also provided.

TaSYP137 and TaVAMP723, the SNAREs Proteins from Wheat, Reduce Resistance to Blumeria graminis f. sp. tritici

SNARE protein is an essential factor driving vesicle fusion in eukaryotes. Several SNAREs have been shown to play a crucial role in protecting against powdery mildew and other pathogens. In our previous study, we identified SNARE family members and analyzed their expression pattern in response to powdery mildew infection. Based on quantitative expression and RNA-seq results, we focused on TaSYP137/TaVAMP723 and hypothesized that they play an important role in the interaction between wheat and Blumeria graminis f. sp. Tritici (Bgt). In this study, we measured the expression patterns of TaSYP132/TaVAMP723 genes in wheat post-infection with Bgt and found that the expression pattern of TaSYP137/TaVAMP723 was opposite in resistant and susceptible wheat samples infected by Bgt. The overexpression of TaSYP137/TaVAMP723 disrupted wheat's defense against Bgt infection, while silencing these genes enhanced its resistance to Bgt. Subcellular localization studies revealed that TaSYP137/TaVAMP723 are present in both the plasma membrane and nucleus. The interaction between TaSYP137 and TaVAMP723 was confirmed using the yeast two-hybrid (Y2H) system. This study offers novel insights into the involvement of SNARE proteins in the resistance of wheat against Bgt, thereby enhancing our comprehension of the role of the SNARE family in the pathways related to plant disease resistance.

Intensification of bioprocesses with filamentous microorganisms

Many industrial biotechnological processes use filamentous microorganisms to produce platform chemicals, proteins, enzymes and natural products. Product formation is directly linked to their cellular morphology ranging from dispersed mycelia over loose clumps to compact pellets. Therefore, the adjustment and control of the filamentous cellular morphology pose major challenges for bioprocess engineering. Depending on the filamentous strain and desired product, optimal morphological shapes for achieving high product concentrations vary. However, there are currently no overarching strain- or product-related correlations to improve process understanding of filamentous production systems. The present book chapter summarizes the extensive work conducted in recent years in the field of improving product formation and thus intensifying biotechnological processes with filamentous microorganisms. The goal is to provide prospective scientists with an extensive overview of this scientifically diverse, highly interesting field of study. In the course of this, multiple examples and ideas shall facilitate the combination of their acquired expertise with promising areas of future research. Therefore, this overview describes the interdependence between filamentous cellular morphology and product formation. Moreover, the currently most frequently used experimental techniques for morphological structure elucidation will be discussed in detail. Developed strategies of morphology engineering to increase product formation by tailoring and controlling cellular morphology and thus to intensify processes with filamentous microorganisms will be comprehensively presented and discussed.

A Comprehensive Survey with Quantitative Comparison of Image Analysis Methods for Microorganism Biovolume Measurements

With the acceleration of urbanization and living standards, microorganisms play an increasingly important role in industrial production, bio-technique, and food safety testing. Microorganism biovolume measurements are one of the essential parts of microbial analysis. However, traditional manual measurement methods are time-consuming and challenging to measure the characteristics precisely. With the development of digital image processing techniques, the characteristics of the microbial population can be detected and quantified. The applications of the microorganism biovolume measurement method have developed since the 1980s. More than 62 articles are reviewed in this study, and the articles are grouped by digital image analysis methods with time. This study has high research significance and application value, which can be referred to as microbial researchers to comprehensively understand microorganism biovolume measurements using digital image analysis methods and potential applications.

Temperature-responsive regulation of the fermentation of hypocrellin A by Shiraia bambusicola (GDMCC 60438)

BACKGROUND

Hypocrellin A (HA) is a perylene quinone pigment with high medicinal value that is produced by Shiraia bambusicola Henn. (S. bambusicola) and Hypocrella bambusae (Berk. & Broome) Sacc. (Ascomycetes) with great potential in clinical photodynamic therapy. Submerged cultivation of S. bambusicola is a popular technique for HA production. However, there is not much research on how temperature changes lead to differential yields of HA production.

RESULTS

The temperature regulation of submerged fermentation is an efficient approach to promote HA productivity. After a 32 °C fermentation, the HA content in the mycelia S. bambusicola (GDMCC 60438) was increased by more than three- and fivefold when compared to that at 28 °C and 26 °C, respectively. RNA sequencing (RNA-seq) analysis showed that the regulation of the expression of transcription factors and genes essential for HA biosynthesis could be induced by high temperature. Among the 496 differentially expressed genes (DEGs) explicitly expressed at 32 °C, the hub genes MH01c06g0046321 and MH01c11g0073001 in the coexpression network may affect HA biosynthesis and cytoarchitecture, respectively. Moreover, five genes, i.e., MH01c01g0006641, MH01c03g0017691, MH01c04g0029531, MH01c04g0030701 and MH01c22g0111101, potentially related to HA synthesis also exhibited significantly higher expression levels. Morphological observation showed that the autolysis inside the mycelial pellets tightly composted intertwined mycelia without apparent holes.

CONCLUSIONS

The obtained results provide an effective strategy in the submerged fermentation of S. bambusicola for improved HA production and reveal an alternative regulatory network responsive to the biosynthesis metabolism of HA in response to environmental signals.

A truncated CC-NB-ARC gene TaRPP13L1-3D positively regulates powdery mildew resistance in wheat via the RanGAP-WPP complex-mediated nucleocytoplasmic shuttle

A wheat RPP13-like isoform interacting with WPP1 contributes to quantitative and/or basal resistance to powdery mildew (Blumeria graminis f. sp. tritici) by restricting the development of Bgt conidia. Plant disease resistance (R) genes confer an ability to resist infection by pathogens expressing specific avirulence genes. Recognition of Peronospora parasitica 13-like (RPP13-like) genes belong to the nucleotide-binding site and leucine-rich repeat (NBS-LRR) superfamily and play important roles in resistance to various plant diseases. Previously, we detected a TaRPP13-like gene located on chromosome 3D (TaRPP13L1-3D) in the TaSpl1 resided region, which is strongly induced by the cell death phenotype (Zhang et al. 2021). Here, we investigated the expression and functional role of TaRPP13L1-3D in wheat responding to fungal stress. TaRPP13L1-3D encoded a typical NB-ARC structure characterized by Rx-N and P-loop NTPase domains. TaRPP13L1-3D transcripts were strongly upregulated in wheat by powdery mildew (Blumeria graminis f. sp. tritici; Bgt) and stripe rust (Puccinia striiformis f. sp. tritici; Pst) infection although opposing expression patterns were observed in response to wheat-Bgt in incompatible and compatible backgrounds. Overexpression of TaRPP13L1-3D enhanced disease resistance to Bgt, accompanied by upregulation of the defense-related marker genes encoding phytoalexin-deficient4 (PAD4), thaumatin-like protein (TLP) and chitinase 8-like protein (Chi8L), while silencing of TaRPP13L1-3D disrupted the resistance to Bgt infection. Subcellular localization studies showed that TaRPP13L1-3D is located in both the plasma membrane and nucleus, while yeast-two-hybrid (Y2H) assays indicated that TaRPP13L1-3D interacts with WPP domain-containing protein 1 (TaWPP1). This indicates that TaRPP13L1-3D shuttles between the nucleus and cytoplasm membrane via a mechanism that is mediated by the RanGAP-WPP complex in nuclear pores. This insight into TaRPP13L1-3D will be useful in dissecting the mechanism of fungal resistance in wheat, and understanding the interaction between R gene expression and pathogen defense.

Assessing sugarcane brown rust resistance using Image analysis

Image analysis provides an accurate and precise method of pest evaluation. This work's objective was to compare the usefulness of the ImageJ® 1.43u image processor and visual estimation as methods to characterize brown rust lesions and estimate the resistance of new sugarcane cultivars. For this, leaves images of 10 cultivars were captured, and the parameters quantity, most regular size of the pustules, and leaf area affected were determined. The data were correlated with the eight control (standard) genotypes' evaluations to obtain a classification of disease resistance. The results showed that the software's determinations were the most accurate, although all the methods were reliable for rating the reaction to brown rust. Therefore, it is proposed to move away from visual disease assessment toward a system based on digital image analysis.

HyLength: a semi-automated digital image analysis tool for measuring the length of roots and fungal hyphae of dense mycelia

In plant-fungus phenotyping, determining fungal hyphal and plant root lengths by digital image analysis can reduce labour and increase data reproducibility. However, the degree of software sophistication is often prohibitive and manual measuring is still used, despite being very time-consuming. We developed the HyLength tool for measuring the lengths of hyphae and roots in in vivo and in vitro systems. The HyLength was successfully validated against manual measures of roots and fungal hyphae obtained from all systems. Compared with manual methods, the HyLength underestimated Medicago sativa roots in the in vivo system and Rhizophagus irregularis hyphae in the in vitro system by about 12 cm per m and allowed to save about 1 h for a single experimental unit. As regards hyphae of R. irregularis in the in vivo system, the HyLength overestimated the length by about 21 cm per m compared with manual measures, but time saving was up to 20.5 h per single experimental unit. Finally, with hyphae of Aspergillus oryzae, the underestimation was about 8 cm per m with a time saving of about 10 min for a single germinating spore. By benchmarking the HyLength against the AnaMorf plugin of the ImageJ/Fiji, we found that the HyLength performed better for dense fungal hyphae, also strongly reducing the measuring time. The HyLength can allow measuring the length over a whole experimental unit, eliminating the error due to sub-area selection by the user and allowing processing a high number of samples. Therefore, we propose the HyLength as a useful freeware tool for measuring fungal hyphae of dense mycelia.

Digital Image Analysis for Morphological State Characterization of a Culture of Filamentous Microorganisms in Production of Antibiotics

The paper deals with the application of specific methods of digital image analysis for the monitoring of morphological changes in cultures of filamentous microorganisms. First, a sequence of digital image preprocessing and processing steps is proposed for the treatment of microscopic images of a filamentous culture. The preprocessing step include band pass filtering by the Difference of Gaussians filter featuring a novel approach to the task of parameters tuning, as well as the optimization of image porosity and image objects separation quality. In the processing step, the resulting enhanced images are subject to morphological state characterization using a set of several standard and modified morphological parameters. Descriptions of morphological states of different complexity are then discussed varying from the standard set of mean values of parameters to the set of parameters in their full histogram of value frequencies (distribution) form. For such complex descriptions also new fashions of graphical representation of results without loss of information are compared. The potential of the proposed full description of morphological behavior of the culture is demonstrated using a set of microscopic images taken during an industrial antibiotics production cultivation using a microorganism belonging into the Streptomyces genus. Finally, the cluster analysis is proposed for further automatic quantitative classification and interpretation of complex description of metabolic states.

Live Monitoring and Analysis of Fungal Growth, Viability, and Mycelial Morphology Using the IncuCyte NeuroTrack Processing Module

Pathogenic fungi remain a major cause of infectious complications in immunocompromised patients. Microscopic techniques are crucial for our understanding of fungal biology, host-pathogen interaction, and the pleiotropic effects of antifungal drugs on fungal cell growth and morphogenesis. Taking advantage of the morphological similarities of neuronal cell networks and mycelial growth patterns, we employed the IncuCyte time-lapse microscopy system and its NeuroTrack image analysis software package to study growth and branching of a variety of pathogenic yeasts and molds. Using optimized image processing definitions, we validated IncuCyte NeuroTrack analysis as a reliable and efficient tool for translational applications such as antifungal efficacy evaluation and coculture with host immune effector cells. Hence, the IncuCyte system and its NeuroTrack module provide an appealing platform for efficient in vitro studies of antifungal compounds and immunotherapeutic strategies in medical mycology.

Efficient live-imaging methods are pivotal to understand fungal morphogenesis, especially as it relates to interactions with host immune cells and mechanisms of antifungal drugs. Due to the notable similarities in growth patterns of neuronal cells and mycelial networks, we sought to repurpose the NeuroTrack (NT) processing module of the IncuCyte time-lapse microscopy system as a tool to quantify mycelial growth and branching of pathogenic fungi. We showed the robustness of NT analysis to study Candida albicans and five different molds and confirmed established characteristics of mycelial growth kinetics. We also documented high intra- and interassay reproducibility of the NT module for a spectrum of spore inocula and culture periods. Using GFP-expressing Aspergillus fumigatus and Rhizopus arrhizus, the feasibility of fluorescence-based NT analysis was validated. In addition, we performed proof-of-concept experiments of NT analysis for several translational applications such as studying the morphogenesis of a filamentation-defective C. albicans mutant, the effects of different classes of antifungals (polyenes, azoles, and echinocandins), and coculture with host immune cells. High accuracy was found, even at high immune cell-to-fungus ratios or in the presence of fungal debris. For antifungal efficacy studies, addition of a cytotoxicity dye further refined IncuCyte-based analysis, facilitating real-time determination of fungistatic and fungicidal activity in a single assay. Complementing conventional MIC-based assays, NT analysis is an appealing method to study fungal morphogenesis and viability in the context of antifungal compound screening and evaluation of novel immune therapeutics.

Warming weakens facilitative interactions between decomposers and detritivores, and modifies freshwater ecosystem functioning

Warming is among the major drivers of changes in biotic interactions and, in turn, ecosystem functioning. The decomposition process occurs in a chain of facilitative interactions between detritivores and microorganisms. It remains unclear, however, what effect warming may have on the interrelations between detritivores and microorganisms, and the consequences for the functioning of natural freshwater ecosystems. To address these gaps, we performed a field experiment using tank bromeliads and their associated aquatic fauna. We manipulated the presence of bacteria and detritivorous macroinvertebrates (control, "bacteria," and "bacteria + macroinvertebrates") under ambient and warming scenarios, and analyzed the effects on the microorganisms and ecosystem functioning (detritus mass loss, colored dissolved organic matter, and nitrogen flux). We applied antibiotic solution to eliminate or reduce bacteria from control bromeliads. After 60 days incubation, bacterial density was higher in the presence than in the absence of macroinvertebrates. In the absence of macroinvertebrates, temperature did not influence bacterial density. However, in the presence of macroinvertebrates, bacterial density decreased by 54% with warming. The magnitude of the effects of organisms on ecosystem functioning was higher in the combined presence of bacteria and macroinvertebrates. However, warming reduced the overall positive effects of detritivores on bacterial density, which in turn, cascaded down to ecosystem functioning by decreasing decomposition and nitrogen flux. These results show the existence of facilitative mechanisms between bacteria and detritivores in the decomposition process, which might collapse due to warming. Detritivores seem to contribute to nutrient cycling as they facilitate bacterial populations, probably by increasing nutrient input (feces) in the ecosystem. However, increased temperature mitigated these beneficial effects. Our results add to a growing research body that shows that warming can affect the structure of aquatic communities, and highlight the importance of considering the interactive effects between facilitation and climatic drivers on the functioning of freshwater ecosystems.

HyphaTracker: An ImageJ toolbox for time-resolved analysis of spore germination in filamentous fungi

The dynamics of early fungal development and its interference with physiological signals and environmental factors is yet poorly understood. Especially computational analysis tools for the evaluation of the process of early spore germination and germ tube formation are still lacking. For the time-resolved analysis of conidia germination of the filamentous ascomycete Fusarium fujikuroi we developed a straightforward toolbox implemented in ImageJ. It allows for processing of microscopic acquisitions (movies) of conidial germination starting with drift correction and data reduction prior to germling analysis. From the image time series germling related region of interests (ROIs) are extracted, which are analysed for their area, circularity, and timing. ROIs originating from germlings crossing other hyphae or the image boundaries are omitted during analysis. Each conidium/hypha is identified and related to its origin, thus allowing subsequent categorization. The efficiency of HyphaTracker was proofed and the accuracy was tested on simulated germlings at different signal-to-noise ratios. Bright-field microscopic images of conidial germination of rhodopsin-deficient F. fujikuroi mutants and their respective control strains were analysed with HyphaTracker. Consistent with our observation in earlier studies the CarO deficient mutant germinated earlier and grew faster than other, CarO expressing strains.

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.

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.

Characterization and control of fungal morphology for improved production performance in biotechnology

Filamentous fungi have been widely applied in industrial biotechnology for many decades. In submerged culture processes, they typically exhibit a complex morphological life cycle that is related to production performance--a link that is of high interest for process optimization. The fungal forms can vary from dense spherical pellets to viscous mycelia. The resulting morphology has been shown to be influenced strongly by process parameters, including power input through stirring and aeration, mass transfer characteristics, pH value, osmolality and the presence of solid micro-particles. The surface properties of fungal spores and hyphae also play a role. Due to their high industrial relevance, the past years have seen a substantial development of tools and techniques to characterize the growth of fungi and obtain quantitative estimates on their morphological properties. Based on the novel insights available from such studies, more recent studies have been aimed at the precise control of morphology, i.e., morphology engineering, to produce superior bio-processes with filamentous fungi.

A novel method for fast and statistically verified morphological characterization of filamentous fungi

Along with productivity and physiology, morphological growth behavior is the key parameter in bioprocess design for filamentous fungi. Despite complex interactions between fungal morphology, broth viscosity, mixing kinetics, transport characteristics and process productivity, morphology is still commonly tackled only by empirical trial-and-error techniques during strain selection and process development procedures. In fact, morphological growth characteristics are investigated by computational analysis of only a limited number of pre-selected microscopic images or via manual evaluation of images, which causes biased results and does not allow any automation or high-throughput quantification. To overcome the lack of tools for fast, reliable and quantitative morphological analysis, this work introduces a method enabling statistically verified quantification of fungal morphology in accordance with Quality by Design principles. The novel, high-throughput method presented here interlinks fully automated recording of microscopic images with a newly developed evaluation approach reducing the need for manual intervention to a minimum. Validity of results is ensured by concomitantly testing the acquired sample for representativeness by statistical inference via bootstrap analysis. The novel approach for statistical verification can be equally applied as control logic to automatically proceed with morphological analysis of a consecutive sample once user defined acceptance criteria are met. Hence, analysis time can be reduced to an absolute minimum. The quantitative potential of the developed methodology is demonstrated by characterizing the morphological growth behavior of two industrial Penicillium chrysogenum production strains in batch cultivation.