Endophytic fungi or endophytes exist widely inside the healthy tissues of living plants, and are important components of plant micro-ecosystems Over the long period of evolution, some co-existing endophytes and their host plants have established a special relationship with one and another, which can significantly influence the formation of metabolic products in plants, then affect quality and quantity of crude drugs derived from medicinal plants This paper will focus on the increasing knowledge of relationships between endophytic fungi and medicinal plants through reviewing of published research data obtained from the last 30 years The analytical results indicate that the distribution and population structure of endophytes can be considerably affected by factors, such as the genetic background, age, and environmental conditions of their hosts On the other hand, the endophytic fungi can also confer profound impacts on their host plants by enhancing their growth, increasing their fitness, strengthening their tolerances to abiotic and biotic stresses, and promoting their accumulation of secondary metabolites All the changes are very important for the production of bioactive components in their hosts Hence, it is essential to understand such relationships between endophytic fungi and their host medicinal plants Such knowledge can be well exploited and applied for the production of better and more drugs from medicinal plants

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A Friendly Relationship between Endophytic Fungi and Medicinal Plants: A Systematic Review.

A critical review on exploiting the pharmaceutical potential of plant endophytic fungi.

In a natural ecosystem, the plant is in a symbiotic relationship with beneficial endophytes contributing huge impact on its host plant. Therefore, exploring beneficial endophytes and understanding its interaction is a prospective area of research. The present work aims to characterize the fungal endophytic communities associated with healthy maize and rice plants and to study the deterministic factors influencing plant growth and biocontrol properties against phytopathogens, viz, Pythium ultimum, Sclerotium oryzae, Rhizoctonia solani, and Pyricularia oryzae. A total of 123 endophytic fungi was isolated using the culture-dependent approach from different tissue parts of the plant. Most dominating fungal endophyte associated with both the crops belong to genus Fusarium, Sarocladium, Aspergillus, and Penicillium and their occurrence was not tissue specific. The isolates were screened for in vitro plant growth promotion, stress tolerance, disease suppressive mechanisms and based on the results, each culture from both the cereal crops was selected for further study. Acremonium sp. (ENF 31) and Penicillium simplicisssum (ENF22), isolated from maize and rice respectively could potentially inhibit the growth of all the tested pathogens with 46.47 ± 0.16 mm to 60.09 ± 0.04 mm range zone of inhibition for ENF31 and 35.48 ± 0.14 to 62.29 ± 0.15 mm for ENF22. Both significantly produce the defensive enzymes, ENF31 could tolerate a wide range of pH from 2 to 12, very important criteria, for studying plant growth in different soil types, especially acidic as it is widely prevalent here, making more land unsuitable for cultivation. ENF22 grows in pH range 3-12, with 10% salt tolerating ability, another factor of consideration. Study of root colonization during 7th to 30th days of growth phase reveals that ENF31 could colonize pleasantly in rice, though a maize origin, ranging from 1.02 to 1.21 log10 CFU/g root and in maize, it steadily colonizes ranging from 0.95 to 1.18 log10 CFU, while ENF22 could colonize from 0.98 to 1.24 Log10CFU/g root in rice and 1.01 to 1.24Log10CFU/g root in maize, just the reverse observed in Acremonium sp. Therefore, both the organism has the potency of a promising Bio-resource agent, that we must definitely explore to fill the gap in the agriculture industry.

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Functional Characterization of Endophytic Fungal Community Associated with Oryza sativa L. and Zea mays L.

It is known that plant-based ethnomedicine represented the foundation of modern pharmacology and that many pharmaceuticals are derived from compounds occurring in plant extracts. This track still stimulates a worldwide investigational activity aimed at identifying novel bioactive products of plant origin. However, the discovery that endophytic fungi are able to produce many plant-derived drugs has disclosed new horizons for their availability and production on a large scale by the pharmaceutical industry. In fact, following the path traced by the blockbuster drug taxol, an increasing number of valuable compounds originally characterized as secondary metabolites of plant species belonging to the Spermatophyta have been reported as fermentation products of endophytic fungal strains. Aspects concerning sources and bioactive properties of these compounds are reviewed in this paper.

Plant Bioactive Metabolites and Drugs Produced by Endophytic Fungi of Spermatophyta

Sequential extraction, characterization and antioxidant activity of polysaccharides from Fritillaria pallidiflora Schrenk

Exopolysaccharides from the fungal endophytic Fusarium sp. A14 isolated from Fritillaria unibracteata Hsiao et KC Hsia and their antioxidant and antiproliferation effects.

Safflower (Carthamus tinctorius L.) has received a significant amount of attention as a medicinal plant and oilseed crop. Gene expression studies provide a theoretical molecular biology foundation for improving new traits and developing new cultivars. Real-time quantitative PCR (RT-qPCR) has become a crucial approach for gene expression analysis. In addition, appropriate reference genes (RGs) are essential for accurate and rapid relative quantification analysis of gene expression. In this study, fifteen candidate RGs involved in multiple metabolic pathways of plants were finally selected and validated under different experimental treatments, at different seed development stages and in different cultivars and tissues for real-time PCR experiments. These genes were ABCS, 60SRPL10, RANBP1, UBCL, MFC, UBCE2, EIF5A, COA, EF1-β, EF1, GAPDH, ATPS, MBF1, GTPB and GST. The suitability evaluation was executed by the geNorm and NormFinder programs. Overall, EF1, UBCE2, EIF5A, ATPS and 60SRPL10 were the most stable genes, and MBF1, as well as MFC, were the most unstable genes by geNorm and NormFinder software in all experimental samples. To verify the validation of RGs selected by the two programs, the expression analysis of 7 CtFAD2 genes in safflower seeds at different developmental stages under cold stress was executed using different RGs in RT-qPCR experiments for normalization. The results showed similar expression patterns when the most stable RGs selected by geNorm or NormFinder software were used. However, the differences were detected using the most unstable reference genes. The most stable combination of genes selected in this study will help to achieve more accurate and reliable results in a wide variety of samples in safflower.

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Identification and Evaluation of Reference Genes for Accurate Transcription Normalization in Safflower under Different Experimental Conditions

Several studies have suggested adverse effects of particulate matter (PM) exposure on male reproductive health; few have investigated the association between PM exposure and semen quality in a large population of fertile men.We evaluated 14 parameters of semen quality in 1554 fertile men in Nanjing from 2014 to 2016. Individual exposure to particular matter ≤10 μm in diameter (PM10) and ≤ 2.5 μm in diameter (PM2.5) during key periods of sperm development (0-90, 0-9, 10-14, 15-69, and 70-90 days before semen collection) were estimated by inverse distance weighting interpolation. Associations between PM exposure and semen quality were estimated using multivariable linear regression.Higher 90-days average PM2.5 was in association with decreased sperm motility (2.21% for total motility, 1.93% for progressive motility per 10 μg/m3 increase, P < 0.001) and four quantitative aspects of sperm motion (curvilinear velocity (VCL), straight line velocity (VSL), average path velocity (VAP), and amplitude of lateral head displacement (ALH), P < 0.01). The association between PM2.5 exposure and semen quality were generally stronger for the earlier exposure window (70-90 days prior to ejaculation) than for recent exposure (0-9, 10-14, or 15-69 days). In the subgroup of men who had normal sperm parameters (n = 1019), similar results were obtained. Ninety-days PM10 exposure was associated only with decreased VCL and VAP and was not related to sperm concentration.Exposure to PM2.5 adversely affects semen quality, specifically lower sperm motility, in fertile men. 

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Association between ambient particulate matter exposure and semen quality in fertile men

Semen quality and sperm DNA methylation in relation to long-term exposure to air pollution in fertile men: A cross-sectional study.

Protein ligand docking is an indispensable tool for computational prediction of protein functions and screening drug candidates. Despite significant progress over the past two decades, it is still a challenging problem, characterized by the still limited understanding of the energetics between proteins and ligands, and the vast conformational space that has to be searched to find a satisfactory solution. In this project, we developed a novel reinforcement learning (RL) approach, the asynchronous advantage actor-critic model (A3C), to address the protein ligand docking problem. The overall framework consists of two models. During the search process, the agent takes an action selected by the actor model based on the current location. The critic model then evaluates this action and predict the distance between the current location and true binding site. Experimental results showed that in both single- and multi-atom cases, our model improves binding site prediction substantially compared to a naïve model. For the single-atom ligand, copper ion (Cu2+), the model predicted binding sites have a median root-mean-square-deviation (RMSD) of 2.39 Å to the true binding sites when starting from random starting locations. For the multi-atom ligand, sulfate ion (SO42-), the predicted binding sites have a median RMSD of 3.82 Å to the true binding sites. The ligand-specific models built in this study can be used in solvent mapping studies and the RL framework can be readily scaled up to larger and more diverse sets of ligands. 

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Feng Pan

Papers

Exopolysaccharides from the fungal endophytic Fusarium sp. A14 isolated from Fritillaria unibracteata Hsiao et KC Hsia and their antioxidant and antiproliferation effects.

Identification and Evaluation of Reference Genes for Accurate Transcription Normalization in Safflower under Different Experimental Conditions

Association between ambient particulate matter exposure and semen quality in fertile men

Semen quality and sperm DNA methylation in relation to long-term exposure to air pollution in fertile men: A cross-sectional study.

A reinforcement learning approach for protein–ligand binding pose prediction