Spectroscopy and SEM imaging reveal endosymbiont-dependent components changes in germinating kernel through direct and indirect coleorhiza-fungus interactions under stress

Microbiome-Driven Proline Biogenesis in Plants under Stress: Perspectives for Balanced Diet to Minimize Depression Disorders in Humans

According to the World Health Organization (WHO), depression is a leading cause of disability worldwide and a major contributor to the overall global burden of mental disorders. An increasing number of studies have revealed that among 20 different amino acids, high proline consumption is a dietary factor with the strongest impact on depression in humans and animals, including insects. Recent studies acknowledged that gut microbiota play a key role in proline-related pathophysiology of depression. In addition, the multi-omics approach has alleged that a high level of metabolite proline is directly linked to depression severity, while variations in levels of circulating proline are dependent on microbiome composition. The gut–brain axis proline analysis is a gut microbiome model of studying depression, highlighting the critical importance of diet, but nothing is known about the role of the plant microbiome–food axis in determining proline concentration in the diet and thus about preventing excessive proline intake through food consumption. In this paper, we discuss the protocooperative potential of a holistic study approach combining the microbiota–gut–brain axis with the microbiota–plant–food–diet axis, as both are involved in proline biogenesis and metabolism and thus on in its effect on mood and cognitive function. In preharvest agriculture, the main scientific focus must be directed towards plant symbiotic endophytes, as scavengers of abiotic stresses in plants and modulators of high proline concentration in crops/legumes/vegetables under climate change. It is also implied that postharvest agriculture—including industrial food processing—may be critical in designing a proline-balanced diet, especially if corroborated with microbiome-based preharvest agriculture, within a circular agrifood system. The microbiome is suggested as a target for selecting beneficial plant endophytes in aiming for a balanced dietary proline content, as it is involved in the physiology and energy metabolism of eukaryotic plant/human/animal/insect hosts, i.e., in core aspects of this amino acid network, while opening new venues for an efficient treatment of depression that can be adapted to vast groups of consumers and patients. In that regard, the use of artificial intelligence (AI) and molecular biomarkers combined with rapid and non-destructive imaging technologies were also discussed in the scope of enhancing integrative science outcomes, agricultural efficiencies, and diagnostic medical precisions.

Effective Methods Based on Distinct Learning Principles for the Analysis of Hyperspectral Images to Detect Black Sigatoka Disease

Current chemical methods used to control plant diseases cause a negative impact on the environment and increase production costs. Accurate and early detection is vital for designing effective protection strategies for crops. We evaluate advanced distributed edge intelligence techniques with distinct learning principles for early black sigatoka disease detection using hyperspectral imaging. We discuss the learning features of the techniques used, which will help researchers improve their understanding of the required data conditions and identify a method suitable for their research needs. A set of hyperspectral images of banana leaves inoculated with a conidial suspension of black sigatoka fungus (Pseudocercospora fijiensis) was used to train and validate machine learning models. Support vector machine (SVM), multilayer perceptron (MLP), neural networks, N-way partial least square-discriminant analysis (NPLS-DA), and partial least square-penalized logistic regression (PLS-PLR) were selected due to their high predictive power. The metrics of AUC, precision, sensitivity, prediction, and F1 were used for the models' evaluation. The experimental results show that the PLS-PLR, SVM, and MLP models allow for the successful detection of black sigatoka disease with high accuracy, which positions them as robust and highly reliable HSI classification methods for the early detection of plant disease and can be used to assess chemical and biological control of phytopathogens.

Monitoring Mycoparasitism of Clonostachys rosea against Botrytis cinerea Using GFP

Clonostachys rosea is an important mycoparasite, with great potential for controlling numerous plant fungal diseases. Understanding the mechanisms and modes of action will assist the development and application of this biocontrol fungus. In this study, the highly efficient C. rosea 67-1 strain was marked with the green fluorescent protein (GFP), and the transformant possessed the same biological characteristics as the wild-type strain. Fungal interactions with Botrytis cinerea during co-culture and encounter on tomato leaves were assessed by fluorescence confocal and electron microscopy. The results indicated that once the two fungi met, the hyphae of C. rosea grew alongside those of B. cinerea, then attached tightly to the host and developed special structures, via which the biocontrol fungus penetrated the host and absorbed nutrients, eventually disintegrating the cells of the pathogen. Mycoparasitism to B. cinerea was also observed on tomato leaves, suggesting that C. rosea can colonize on plants and act following the invasion of the pathogenic fungus.

Scaling-up production of plant endophytes in bioreactors: concepts, challenges and perspectives

The benefit of microorganisms to humans, animals, insects and plants is increasingly recognized, with intensified microbial endophytes research indicative of this realization. In the agriculture industry, the benefits are tremendous to move towards sustainable crop production and minimize or circumvent the use of chemical fertilizers and pesticides. The research leading to the identification of potential plant endophytes is long and arduous and for many researchers the challenge is ultimately in scale-up production. While many of the larger agriculture and food industries have their own scale-up and manufacturing facilities, for many in academia and start-up companies the next steps towards production have been a stumbling block due to lack of information and understanding of the processes involved in scale-up fermentation. This review provides an overview of the fermentation process from shake flask cultures to scale-up and the manufacturing steps involved such as process development optimization (PDO), process hazard analysis (PHA), pre-, in- and post-production (PIP) challenges and finally the preparation of a technology transfer package (TTP) to transition the PDO to manufacturing. The focus is on submerged liquid fermentation (SLF) and plant endophytes production by providing original examples of fungal and bacterial endophytes, plant growth promoting Penicillium sp. and Streptomyces sp. bioinoculants, respectively. We also discuss the concepts, challenges and future perspectives of the scale-up microbial endophyte process technology based on the industrial and biosafety research platform for advancing a massive production of next-generation biologicals in bioreactors.

Fungi Inhabiting the Wheat Endosphere

Wheat production is influenced by changing environmental conditions, including climatic conditions, which results in the changing composition of microorganisms interacting with this cereal. The group of these microorganisms includes not only endophytic fungi associated with the wheat endosphere, both pathogenic and symbiotic, but also those with yet unrecognized functions and consequences for wheat. This paper reviews the literature in the context of the general characteristics of endophytic fungi inhabiting the internal tissues of wheat. In addition, the importance of epigenetic regulation in wheat-fungus interactions is recognized and the current state of knowledge is demonstrated. The possibilities of using symbiotic endophytic fungi in modern agronomy and wheat cultivation are also proposed. The fact that the current understanding of fungal endophytes in wheat is based on a rather small set of experimental conditions, including wheat genotypes, plant organs, plant tissues, plant development stage, or environmental conditions, is recognized. In addition, most of the research to date has been based on culture-dependent methods that exclude biotrophic and slow-growing species and favor the detection of fast-growing fungi. Additionally, only a few reports of studies on the entire wheat microbiome using high-throughput sequencing techniques exist. Conducting comprehensive research on the mycobiome of the endosphere of wheat, mainly in the context of the possibility of using this knowledge to improve the methods of wheat management, mainly the productivity and health of this cereal, is needed.

Tremellomycetes Yeasts in Kernel Ecological Niche: Early Indicators of Enhanced Competitiveness of Endophytic and Mycoparasitic Symbionts against Wheat Pathobiota

Tremellomycetes rDNA sequences previously detected in wheat kernels by MiSeq were not reliably assigned to a genus or clade. From comparisons of ribosomal internal transcribed spacer region (ITS) and subsequent phylogenetic analyses, the following three basidiomycetous yeasts were resolved and identified: Vishniacozymavictoriae, V. tephrensis, and an undescribed Vishniacozyma rDNA variant. The Vishniacozyma variant’s clade is evolutionarily close to, but phylogenetically distinct from, the V. carnescens clade. These three yeasts were discovered in wheat kernel samples from the Canadian prairies. Variations in relative Vishniacozyma species abundances coincided with altered wheat kernel weight, as well as host resistance to chemibiotrophic Tilletia (Common bunt—CB) and necrotrophic Fusarium (Fusarium head blight—FHB) pathogens. Wheat kernel weight was influenced by the coexistence of Vishniacozyma with endophytic plant growth-promoting and mycoparasitic biocontrol fungi that were acquired by plants. Kernels were coated with beneficial Penicillium endophyte and Sphaerodes mycoparasite, each of which had different influences on the wild yeast population. Its integral role in the kernel microbiome renders Vishniacozyma a measurable indicator of the microbiome–plant interaction. The ability of NGS technology to detect specific endophytic DNA variants and early changes in dynamics among symbionts within the kernel ecological niche enables the prediction of crop disease emergence, suggesting that advanced microbiological testing may be a potentially useful tool for both phytoprotection and more efficient wheat breeding programs.

Specific Mycoparasite-Fusarium Graminearum Molecular Signatures in Germinating Seeds Disabled Fusarium Head Blight Pathogen's Infection

Advances in Infrared (IR) spectroscopies have entered a new era of research with applications in phytobiome, plant microbiome and health. Fusarium graminearum 3-ADON is the most aggressive mycotoxigenic chemotype causing Fusarium head blight (FHB) in cereals; while Sphaerodes mycoparasitica is the specific Fusarium mycoparasite with biotrophic lifestyle discovered in cereal seeds and roots. Fourier transform infrared (FTIR) spectroscopy analyses depicted shifts in the spectral peaks related to mycoparasitism mainly within the region of proteins, lipids, also indicating a link between carbohydrates and protein regions, involving potential phenolic compounds. Especially, S. mycoparasitica contributes to significant changes in lipid region 3050–2800 cm⁻¹, while in the protein region, an increasing trend was observed for the peaks 1655–1638 cm⁻¹ (amide I) and 1549–1548 cm⁻¹ (amide II) with changes in indicative protein secondary structures. Besides, the peak extending on the region 1520–1500 cm⁻¹ insinuates a presence of aromatic compounds in presence of mycoparasite on the F. graminearum root sample. Monitoring shift in improved seed germination, fungus-fungus interface through scanning electron microscopy (SEM) and confocal laser scanning microscopy (CLSM), and FTIR molecular signatures combined with principal component analysis (PCA) proved useful tools to detect an early mycoparasitism as a vital asset of the preventive biocontrol strategy against plant pathogens.

Transgenerational role of seed mycobiome - an endosymbiotic fungal composition as a prerequisite to stress resilience and adaptive phenotypes in Triticum

Illumina-MiSeq next-generation sequencing of ITS 5.8S rRNA gene demonstrated the transgenerational transmission of fungal seed-endophytes (mycobiome) across three consecutive wheat host generations under standard-control and drought conditions in the greenhouse. Drought-stressed plants experienced a positive shift in the seed mycobiome's composition, moderated by the external acquisition of endophytic Penicillium (E+) at the seed level. Untreated (E-) and unstressed plants harbor a maximal fungal diversity of non-equilibrium ecological communities. While fungal composition in drought-stressed E- plants experienced important fluctuation, E+ plants maintained fungal ecological communities in phase equilibrium across generations. E+ plants hosted a relatively higher abundance of Ascomycota in the 2nd and 3rd seed generations of wheat, whereas higher abundance of Basidiomycota was detected in 1st generation seeds. The dynamic response of ecological communities to environmental stress is conducive to E+ plants' active recruitment of endosymbiotic consortia in seeds, benefiting host stress resilience and phenotype. In contrast, E- plants showed an erratic distribution of detected OTUs with an increased occurrence of phytopathogens and diminished plant performance under stress. The present study gives insight into the understanding of the seed-mycobiome composition and dynamics with the potential to improve plant host traits in an adverse environment.