Stomatal closure during drought inhibits carbon uptake and may reduce a tree\'s defensive capacity. Limited carbon availability during drought may increase a tree\'s mortality risk, particularly if drought constrains trees\' capacity to rapidly produce defenses during biotic attack. We parameterized a new model of conifer defense using physiological data on carbon reserves and chemical defenses before and after a simulated bark beetle attack in mature Pinus edulis under experimental drought. Attack was simulated using inoculations with a consistent bluestain fungus (Ophiostoma sp.) of Ips confusus, the main bark beetle colonizing this tree, to induce a defensive response. Trees with more carbon reserves produced more defenses but measured phloem carbon reserves only accounted for c. 23% of the induced defensive response. Our model predicted universal mortality if local reserves alone supported defense production, suggesting substantial remobilization and transport of stored resin or carbon reserves to the inoculation site. Our results show that de novo terpene synthesis represents only a fraction of the total measured phloem terpenes in P. edulis following fungal inoculation. Without direct attribution of phloem terpene concentrations to available carbon, many studies may be overestimating the scale and importance of de novo terpene synthesis in a tree\'s induced defense response.

True morels (Morchella) are globally renowned medicinal and edible mushrooms. White mold disease caused by fungi is the main disease of Morchella, which has the characteristics of wide incidence and strong destructiveness. The disparities observed in the isolation rates of different pathogens indicate their varying degrees of host adaptability and competitive survival abilities. In order to elucidate its potential mechanism, this study, the pathogen of white mold disease from Dafang county, Guizhou Province was isolated and purified, identified as Pseudodiploöspora longispora by morphological, molecular biological and pathogenicity tests. Furthermore, high-quality genome of P. longisporus (40.846 Mb) was assembled N50 of 3.09 Mb, predicts 7381 protein-coding genes. Phylogenetic analysis of single-copy homologous genes showed that P. longispora and Zelopaecilomyces penicillatus have the closest evolutionary relationship, diverging into two branches approximately 50 (44.3-61.4) MYA. Additionally, compared with the other two pathogens causing Morchella disease, Z. penicillatus and Cladobotryum protrusum, it was found that they had similar proportions of carbohydrate enzyme types and encoded abundant cell wall degrading enzymes, such as chitinase and glucanase, indicating their important role in disease development. Moreover, the secondary metabolite gene clusters of P. longispora and Z. penicillatus show a high degree of similarity to leucinostatin A and leucinostatin B (peptaibols). Furthermore, a gene cluster with synthetic toxic substance Ochratoxin A was also identified in P. longispora and C. protrusum, indicating that they may pose a potential threat to food safety. This study provides valuable insights into the genome of P. longispora, contributing to pathogenicity research.

The fungus Parastagonospora nodorum causes septoria nodorum blotch on wheat. The role of the fungal Velvet-family transcription factor VeA in P. nodorum development and virulence was investigated here. Deletion of the P. nodorum VeA ortholog, PnVeA, resulted in growth abnormalities including pigmentation, abolished asexual sporulation and highly reduced virulence on wheat. Comparative RNA-Seq and RT-PCR analyses revealed that the deletion of PnVeA also decoupled the expression of major necrotrophic effector genes. In addition, the deletion of PnVeA resulted in an up-regulation of four predicted secondary metabolite (SM) gene clusters. Using liquid-chromatography mass-spectrometry, it was observed that one of the SM gene clusters led to an accumulation of the mycotoxin alternariol. PnVeA is essential for asexual sporulation, full virulence, secondary metabolism and necrotrophic effector regulation.

Pseudomonas protegens can generally produce multiple antibiotics including pyoluteorin (Plt), 2,4-diacetylphloroglucinol (DAPG), and pyrrolnitrin (Prn). In this study, we discovered and characterized a quorum sensing (QS) system, PpqI/R, in P. protegens H78. PpqI/R, encoded by two open reading frames (ORFs) (H78_01960/01961) in P. protegens H78 genome, is a LuxI/R-type QS system. Four long-chain acyl homoserine lactone (AHL) signaling molecules, 3-OH-C10-HSL, 3-OH-C12-HSL, C12-HSL, and 3-OH-C14-HSL, are produced by H78. Biosynthesis of these AHLs is catalyzed by PpqI synthase and activated by the PpqR regulator in H78 and in Escherichia coli when heterologously expressed. PpqR activates ppqI expression by targeting the lux box upstream of the ppqI promoter in cooperation with corresponding AHLs. The four aforementioned AHLs exhibited different capabilities to induce ppqI promoter expression, with 3-OH-C12-HSL showing the highest induction activity. In H78 cells, ppqI/R expression is activated by the two-component system GacS/A and the RNA chaperone Hfq. Differential regulation of the PpqI/R system in secondary metabolism has a negative effect on DAPG biosynthesis and ped operon (involved in volatile organic compound biosynthesis) expression. In contrast, Plt biosynthesis and prn operon expression were positively regulated by PpqI/R. In summary, PpqI/R, the first characterized QS system in P. protegens, is activated by GacS/A and Hfq and controls the expression of secondary metabolites, including antibiotics.

Polyphenols are natural compounds which are plant-based bioactive molecules, and have been the subject of growing interest in recent years. Characterized by multiple varieties, polyphenols are mostly found in fruits and vegetables. Currently, many diseases are waiting for a cure or a solution to reduce their symptoms. However, drug or other chemical strategies have limitations for using a treatment agent or still detection tool of many diseases, and thus researchers still need to investigate preventive or improving treatment. Therefore, it is of interest to elucidate polyphenols, their bioactivity effects, supplementation, and consumption. The disadvantage of polyphenols is that they have a limited bioavailability, although they have multiple beneficial outcomes with their bioactive roles. In this context, several different strategies have been developed to improve bioavailability, particularly liposomal and nanoparticles. As nutrition is one of the most important factors in improving health, the inclusion of plant-based molecules in the daily diet is significant and continues to be enthusiastically researched. Nutrition, which is important for individuals of all ages, is the key to the bioactivity of polyphenols.

Secondary metabolites produced by fungi are well known for their biological properties, which play important roles in medicine. These metabolites aid in managing infections and treating chronic illnesses, thereby contributing substantially to human health improvement. Despite this extensive knowledge, the vast biodiversity and biosynthetic potential of fungi is still largely unexplored, highlighting the need for further research in natural products. In this review, several secondary metabolites of fungal origin are described, emphasizing novel structures and skeletons. The detection and characterization of these metabolites have been significantly facilitated by advancements in analytical systems, particularly modern hyphenated liquid chromatography/mass spectrometry. These improvements have primarily enhanced sensitivity, resolution, and analysis flow velocity. Since the in vitro production of novel metabolites is often lower than the re-isolation of known metabolites, understanding chromatin-based alterations in fungal gene expression can elucidate potential pathways for discovering new metabolites. Several protocols for inducing metabolite production from different strains are discussed, demonstrating the need for uniformity in experimental procedures to achieve consistent biosynthetic activation.

BACKGROUND: Gemmatimonadota bacteria are widely distributed in nature, but their metabolic potential and ecological roles in marine environments are poorly understood.
RESULTS: Here, we obtained 495 metagenome-assembled genomes (MAGs), and associated viruses, from coastal to deep-sea sediments around the world. We used this expanded genomic catalog to compare the protein composition and update the phylogeny of these bacteria. The marine Gemmatimonadota are phylogenetically different from those previously reported from terrestrial environments. Functional analyses of these genomes revealed these marine genotypes are capable of degradation of complex organic carbon, denitrification, sulfate reduction, and oxidizing sulfide and sulfite. Interestingly, there is widespread genetic potential for secondary metabolite biosynthesis across Gemmatimonadota, which may represent an unexplored source of novel natural products. Furthermore, viruses associated with Gemmatimonadota have the potential to \"hijack\" and manipulate host metabolism, including the assembly of the lipopolysaccharide in their hosts.
CONCLUSIONS: This expanded genomic diversity advances our understanding of these globally distributed bacteria across a variety of ecosystems and reveals genetic distinctions between those in terrestrial and marine communities. Video Abstract.

Consento (CON) poses a significant environmental hazard as a systemic fungicide, adversely affecting the health of non-target organisms. Nitric oxide (NO), a signaling molecule, is known to play a crucial role in plant physiology and abiotic stress tolerance. However, whether NO plays any role to enhance fungicide CON tolerance in wheat seedlings is yet unclear. Therefore, we conducted a hydroponic experiment i) to investigate the morpho-physio-biochemical changes of wheat seedlings to fungicide CON stress, and ii) to examine the effects of NO and fungicide CON treatments on oxidative damage, antioxidant system, secondary metabolism and detoxification of systemic fungicide in wheat seedlings. The results showed that CON fungicide at the highest (4X) concentration significantly decreased wheat seedlings fresh weight (46.89%), shoot length (40.26%), root length (56.11%) and total chlorophyll contents (67.44%) in a dose response relationship. Moreover, CON significantly increased hydrogen peroxide, malondialdehyde, catalase, ascorbate peroxidase, glutathione-S-transferase, and peroxidase activities while decreased reduced glutathione (GSH) content. This ultimately impaired the redox homeostasis of cells, leading to oxidative damage in cell membrane. Under fungicide treatment, the addition of NO reduced the fungicide phytotoxicity, with an increase of over 60% in seedling growth. The NO application mitigated CON phytotoxicity as reflected by significantly increased chlorophyll pigments (69.88%) and decreased oxidative damage in wheat leaves. Indeed, the NO alleviatory effect was able to increase the tolerance of seedlings to fungicide, which resulted increments in antioxidant and detoxification enzymes activity, with the enhanced GSH level (78.54%). Interestingly, NO alleviated CON phytotoxicity through the phenylpropanoid pathway by enhancing the activity of secondary metabolism enzymes such as phenylalanine ammonia-lyase (47.28%), polyphenol oxidase (9%), and associated metabolites such as phenolic acids (77.62%), flavonoids (34.33%) in wheat leaves. Our study has provided evidence that NO plays a key role in the metabolism and detoxification of systemic fungicide in wheat through enhanced activity of antioxidants, detoxifications and secondary metabolic enzymes.

Fruits produce a wide variety of secondary metabolites of great economic value. Analytical measurement of the metabolites is tedious, time-consuming, and expensive. Additionally, metabolite concentrations vary greatly from tree to tree, making it difficult to choose trees for fruit collection. The current study tested whether deep learning-based models can be developed using fruit and leaf images alone to predict a metabolite\'s concentration class (high or low). We collected fruits and leaves (n = 1045) from neem trees grown in the wild across 0.6 million sq km, imaged them, and measured concentration of five metabolites (azadirachtin, deacetyl-salannin, salannin, nimbin and nimbolide) using high-performance liquid chromatography. We used the data to train deep learning models for metabolite class prediction. The best model out of the seven tested (YOLOv5, GoogLeNet, InceptionNet, EfficientNet_B0, Resnext_50, Resnet18, and SqueezeNet) provided a validation F1 score of 0.93 and a test F1 score of 0.88. The sensitivity and specificity of the fruit model alone in the test set were 83.52 ± 6.19 and 82.35 ± 5.96, and 79.40 ± 8.50 and 85.64 ± 6.21, for the low and the high classes, respectively. The sensitivity was further boosted to 92.67± 5.25 for the low class and 88.11 ± 9.17 for the high class, and the specificity to 100% for both classes, using a multi-analyte framework. We incorporated the multi-analyte model in an Android mobile App Fruit-In-Sight that uses fruit and leaf images to decide whether to \'pick\' or \'not pick\' the fruits from a specific tree based on the metabolite concentration class. Our study provides evidence that images of fruits and leaves alone can predict the concentration class of a secondary metabolite without using expensive laboratory equipment and cumbersome analytical procedures, thus simplifying the process of choosing the right tree for fruit collection.

Viral diseases pose a serious global health threat due to their rapid transmission and widespread impact. The RNA-dependent RNA polymerase (RdRp) participates in the synthesis, transcription, and replication of viral RNA in host. The current study investigates the antiviral potential of secondary metabolites particularly those derived from bacteria, fungi, and plants to develop novel medicines. Using a virtual screening approach that combines molecular docking and molecular dynamics (MD) simulations, we aimed to discover compounds with strong interactions with RdRp of five different retroviruses. The top five compounds were selected for each viral RdRp based on their docking scores, binding patterns, molecular interactions, and drug-likeness properties. The molecular docking study uncovered several metabolites with antiviral activity against RdRp. For instance, cytochalasin Z8 had the lowest docking score of -8.9 (kcal/mol) against RdRp of SARS-CoV-2, aspulvinone D (-9.2 kcal/mol) against HIV-1, talaromyolide D (-9.9 kcal/mol) for hepatitis C, aspulvinone D (-9.9 kcal/mol) against Ebola and talaromyolide D also maintained the lowest docking score of -9.2 kcal/mol against RdRp enzyme of dengue virus. These compounds showed remarkable antiviral potential comparable to standard drug (remdesivir -7.4 kcal/mol) approved to target RdRp and possess no significant toxicity. The molecular dynamics simulation confirmed that the best selected ligands were firmly bound to their respective target proteins for a simulation time of 200 ns. The identified lead compounds possess distinctive pharmacological characteristics, making them potential candidates for repurposing as antiviral drugs against SARS-CoV-2. Further experimental evaluation and investigation are recommended to ascertain their efficacy and potential.