Arbuscular mycorrhizal fungi and Streptomyces: brothers in arms to shape the structure and function of the hyphosphere microbiome in the early stage of interaction.

BACKGROUND: Fungi and bacteria coexist in a wide variety of environments, and their interactions are now recognized as the norm in most agroecosystems. These microbial communities harbor keystone taxa, which facilitate connectivity between fungal and bacterial communities, influencing their composition and functions. The roots of most plants are associated with arbuscular mycorrhizal (AM) fungi, which develop dense networks of hyphae in the soil. The surface of these hyphae (called the hyphosphere) is the region where multiple interactions with microbial communities can occur, e.g., exchanging or responding to each other's metabolites. However, the presence and importance of keystone taxa in the AM fungal hyphosphere remain largely unknown. RESULTS: Here, we used in vitro and pot cultivation systems of AM fungi to investigate whether certain keystone bacteria were able to shape the microbial communities growing in the hyphosphere and potentially improved the fitness of the AM fungal host. Based on various AM fungi, soil leachates, and synthetic microbial communities, we found that under organic phosphorus (P) conditions, AM fungi could selectively recruit bacteria that enhanced their P nutrition and competed with less P-mobilizing bacteria. Specifically, we observed a privileged interaction between the isolate Streptomyces sp. D1 and AM fungi of the genus Rhizophagus, where (1) the carbon compounds exuded by the fungus were acquired by the bacterium which could mineralize organic P and (2) the in vitro culturable bacterial community residing on the surface of hyphae was in part regulated by Streptomyces sp. D1, primarily by inhibiting the bacteria with weak P-mineralizing ability, thereby enhancing AM fungi to acquire P. CONCLUSIONS: This work highlights the multi-functionality of the keystone bacteria Streptomyces sp. D1 in fungal-bacteria and bacterial-bacterial interactions at the hyphal surface of AM fungi. Video Abstract.

Kinetics-based inference of environment-dependent microbial interactions and their dynamic variation.

Microbial communities in nature are dynamically evolving as member species change their interactions subject to environmental variations. Accounting for such context-dependent dynamic variations in interspecies interactions is critical for predictive ecological modeling. In the absence of generalizable theoretical foundations, we lack a fundamental understanding of how microbial interactions are driven by environmental factors, significantly limiting our capability to predict and engineer community dynamics and function. To address this issue, we propose a novel theoretical framework that allows us to represent interspecies interactions as an explicit function of environmental variables (such as substrate concentrations) by combining growth kinetics and a generalized Lotka-Volterra model. A synergistic integration of these two complementary models leads to the prediction of alterations in interspecies interactions as the outcome of dynamic balances between positive and negative influences of microbial species in mixed relationships. The effectiveness of our method was experimentally demonstrated using a synthetic consortium of two Escherichia coli mutants that are metabolically dependent (due to an inability to synthesize essential amino acids) but competitively grow on a shared substrate. The analysis of the E. coli binary consortium using our model not only showed how interactions between the two amino acid auxotrophic mutants are controlled by the dynamic shifts in limiting substrates but also enabled quantifying previously uncharacterizable complex aspects of microbial interactions, such as asymmetry in interactions. Our approach can be extended to other ecological systems to model their environment-dependent interspecies interactions from growth kinetics.IMPORTANCEModeling environment-controlled interspecies interactions through separate identification of positive and negative influences of microbes in mixed relationships is a new capability that can significantly improve our ability to understand, predict, and engineer the complex dynamics of microbial communities. Moreover, the prediction of microbial interactions as a function of environmental variables can serve as valuable benchmark data to validate modeling and network inference tools in microbial ecology, the development of which has often been impeded due to the lack of ground truth information on interactions. While demonstrated against microbial data, the theory developed in this work is readily applicable to general community ecology to predict interactions among macroorganisms, such as plants and animals, as well as microorganisms.

Using metabolic networks to predict cross-feeding and competition interactions between microorganisms.

Understanding the interactions between microorganisms and their impact on bacterial behavior at the community level is a key research topic in microbiology. Different methods, relying on experimental or mathematical approaches based on the diverse properties of bacteria, are currently employed to study these interactions. Recently, the use of metabolic networks to understand the interactions between bacterial pairs has increased, highlighting the relevance of this approach in characterizing bacteria. In this study, we leverage the representation of bacteria through their metabolic networks to build a predictive model aimed at reducing the number of experimental assays required for designing bacterial consortia with specific behaviors. Our novel method for predicting cross-feeding or competition interactions between pairs of microorganisms utilizes metabolic network features. Machine learning classifiers are employed to determine the type of interaction from automatically reconstructed metabolic networks. Several algorithms were assessed and selected based on comprehensive testing and careful separation of manually compiled data sets obtained from literature sources. We used different classification algorithms, including K Nearest Neighbors, XGBoost, Support Vector Machine, and Random Forest, tested different parameter values, and implemented several data curation approaches to reduce the biological bias associated with our data set, ultimately achieving an accuracy of over 0.9. Our method holds substantial potential to advance the understanding of community behavior and contribute to the development of more effective approaches for consortia design.IMPORTANCEUnderstanding bacterial interactions at the community level is critical for microbiology, and leveraging metabolic networks presents an efficient and effective approach. The introduction of this novel method for predicting interactions through machine learning classifiers has the potential to advance the field by reducing the number of experimental assays required and contributing to the development of more effective bacterial consortia.

Minorities drive growth resumption in cross-feeding microbial communities.

Microbial communities are fundamental to life on Earth. Different strains within these communities are often connected by a highly connected metabolic network, where the growth of one strain depends on the metabolic activities of other community members. While distributed metabolic functions allow microbes to reduce costs and optimize metabolic pathways, they make them metabolically dependent. Here, we hypothesize that such dependencies can be detrimental in situations where the external conditions change rapidly, as they often do in natural environments. After a shift in external conditions, microbes need to remodel their metabolism, but they can only resume growth once partners on which they depend have also adapted to the new conditions. It is currently not well understood how microbial communities resolve this dilemma and how metabolic interactions are reestablished after an environmental shift. To address this question, we investigated the dynamical responses to environmental perturbation by microbial consortia with distributed anabolic functions. By measuring the regrowth times at the single-cell level in spatially structured communities, we found that metabolic dependencies lead to a growth delay after an environmental shift. However, a minority of cells-those in the immediate neighborhood of their metabolic partners-can regrow quickly and come to numerically dominate the community after the shift. The spatial arrangement of a microbial community is thus a key factor in determining the communities' ability to maintain metabolic interactions and growth in fluctuating conditions. Our results suggest that environmental fluctuations can limit the emergence of metabolic dependencies between microorganisms.

Spatial-temporal dynamics of a microbial cooperative behavior resistant to cheating.

Much of our understanding of bacterial behavior stems from studies in liquid culture. In nature, however, bacteria frequently live in densely packed spatially-structured communities. How does spatial structure affect bacterial cooperative behaviors? In this work, we examine rhamnolipid production-a cooperative and virulent behavior of Pseudomonas aeruginosa. Here we show that, in striking contrast to well-mixed liquid culture, rhamnolipid gene expression in spatially-structured colonies is strongly associated with colony specific growth rate, and is impacted by perturbation with diffusible quorum signals. To interpret these findings, we construct a data-driven statistical inference model which captures a length-scale of bacterial interaction that develops over time. Finally, we find that perturbation of P. aeruginosa swarms with quorum signals preserves the cooperating genotype in competition, rather than creating opportunities for cheaters. Overall, our data demonstrate that the complex response to spatial localization is key to preserving bacterial cooperative behaviors.

The role of competition versus cooperation in microbial community coalescence.

New microbial communities often arise through the mixing of two or more separately assembled parent communities, a phenomenon that has been termed "community coalescence". Understanding how the interaction structures of complex parent communities determine the outcomes of coalescence events is an important challenge. While recent work has begun to elucidate the role of competition in coalescence, that of cooperation, a key interaction type commonly seen in microbial communities, is still largely unknown. Here, using a general consumer-resource model, we study the combined effects of competitive and cooperative interactions on the outcomes of coalescence events. To do so, we simulate coalescence events between pairs of communities with different degrees of competition for shared carbon resources and cooperation through cross-feeding on leaked metabolic by-products (facilitation). We also study how structural and functional properties of post-coalescence communities evolve when they are subjected to repeated coalescence events. We find that in coalescence events, the less competitive and more cooperative parent communities contribute a higher proportion of species to the new community because of their superior ability to deplete resources and resist invasions. Consequently, when a community is subjected to repeated coalescence events, it gradually evolves towards being less competitive and more cooperative, as well as more speciose, robust and efficient in resource use. Encounters between microbial communities are becoming increasingly frequent as a result of anthropogenic environmental change, and there is great interest in how the coalescence of microbial communities affects environmental and human health. Our study provides new insights into the mechanisms behind microbial community coalescence, and a framework to predict outcomes based on the interaction structures of parent communities.

A novel Trichoderma asperellum strain DQ-1 promotes tomato growth and induces resistance to gray mold caused by Botrytis cinerea.

Gray mold caused by Botrytis cinerea is a major cause of economic losses during tomato production. In this study, we obtained 23 Trichoderma strains from tomato rhizosphere soil and their inhibitory effects on B. cinerea and the promoting effects on tomato growth were determined. Among them, the inhibition rate of strain DQ-1 on B. cinerea was 88.56%; compared with the control group, after treatment with strain DQ-1, the seeds germination rate and root length of tomato increased by 5.55 and 37.86%. The induced disease resistance of strain DQ-1 was evaluated by pot experiments. The disease incidence (DI) and disease severity index (DSI) of tomato pre-inoculated with strain DQ-1 and then inoculated with B. cinerea were reduced by 38 and 64% compared with the control. Furthermore, we detected the expression levels of tomato disease resistance related genes PR2 and TPX, ethylene pathway related genes ETR1 and CTR1 and jasmonic acid pathway related genes LOX1 and PAL in challenging and non-challenging inoculation treatments. The results showed that the tomato treated with strain DQ-1 triggered the system acquired resistance (SAR) and induced systemic resistance (ISR) pathway, thereby enhancing the disease resistance of tomato. Then the strain DQ-1 was identified as Trichoderma asperellum based on morphological characteristics and phylogenetic information. This study suggests that the novel T. asperellum strain DQ-1 can be a potential candidate for the biological control of gray mold in tomato.

Oral Microbiome Alterations and SARS-CoV-2 Saliva Viral Load in Patients with COVID-19.

Bacterial-viral interactions in saliva have been associated with morbidity and mortality for respiratory viruses such as influenza and SARS-CoV. However, such transkingdom relationships during SARS-CoV-2 infection are currently unknown. Here, we aimed to elucidate the relationship between saliva microbiota and SARS-CoV-2 in a cohort of newly hospitalized COVID-19 patients and controls. We used 16S rRNA sequencing to compare microbiome diversity and taxonomic composition between COVID-19 patients (n = 53) and controls (n = 59) and based on saliva SARS-CoV-2 viral load as measured using reverse transcription PCR (RT-PCR). The saliva microbiome did not differ markedly between COVID-19 patients and controls. However, we identified significant differential abundance of numerous taxa based on saliva SARS-CoV-2 viral load, including multiple species within Streptococcus and Prevotella. IMPORTANCE Alterations to the saliva microbiome based on SARS-CoV-2 viral load indicate potential biologically relevant bacterial-viral relationships which may affect clinical outcomes in COVID-19 disease.

Microbial Interactions Drive Distinct Taxonomic and Potential Metabolic Responses to Habitats in Karst Cave Ecosystem.

The geological role of microorganisms has been widely studied in the karst cave ecosystem. However, microbial interactions and ecological functions in such a dark, humid, and oligotrophic habitat have received far less attention, which is crucial to understanding cave biogeochemistry. Herein, microorganisms from weathered rock and sediment along the Heshang Cave depth were analyzed by random matrix theory-based network and Tax4Fun functional prediction. The results showed that although the cave microbial communities have spatial heterogeneity, differential habitats drove the community structure and diversity. Actinobacteria were predominant in weathered rock, whereas Proteobacteria dominated the sediment. The sediment communities presented significantly higher alpha diversities due to the relatively abundant nutrition from the outside by the intermittent stream. Consistently, microbial interactions in sediment were more complex, as visualized by more nodes and links. The abundant taxa presented more positive correlations with other community members in both of the two networks, indicating that they relied on promotion effects to adapt to the extreme environment. The keystones in weathered rock were mainly involved in the biodegradation of organic compounds, whereas the keystone Nitrospira in sediment contributed to carbon/nitrogen fixation. Collectively, these findings suggest that microbial interactions may lead to distinct taxonomic and functional communities in weathered rock and sediment in the subsurface Heshang Cave. IMPORTANCE In general, the constant physicochemical conditions and limited nutrient sources over long periods in the subsurface support a stable ecosystem in karst cave. Previous studies on cave microbial ecology were mostly focused on community composition, diversity, and the relationship with local environmental factors. There are still many unknowns about the microbial interactions and functions in such a dark environment with little human interference. Two representative habitats, including weathered rock and sediment in Heshang Cave, were selected to give an integrated insight into microbial interactions and potential functions. The cooccurrence network, especially the subnetwork, was used to characterize the cave microbial interactions in detail. We demonstrated that abundant taxa primarily relied on promotion effects rather than inhibition effects to survive in Heshang Cave. Keystone species may play important metabolic roles in sustaining ecological functions. Our study provides improved understanding of microbial interaction patterns and community ecological functions in the karst cave ecosystem.

Network mapping of root-microbe interactions in Arabidopsis thaliana.

Understanding how plants interact with their colonizing microbiota to determine plant phenotypes is a fundamental question in modern plant science. Existing approaches for genome-wide association studies (GWAS) are often focused on the association analysis between host genes and the abundance of individual microbes, failing to characterize the genetic bases of microbial interactions that are thought to be important for microbiota structure, organization, and function. Here, we implement a behavioral model to quantify various patterns of microbe-microbe interactions, i.e., mutualism, antagonism, aggression, and altruism, and map host genes that modulate microbial networks constituted by these interaction types. We reanalyze a root-microbiome data involving 179 accessions of Arabidopsis thaliana and find that the four networks differ structurally in the pattern of bacterial-fungal interactions and microbiome complexity. We identify several fungus and bacterial hubs that play a central role in mediating microbial community assembly surrounding A. thaliana root systems. We detect 1142 significant host genetic variants throughout the plant genome and then implement Bayesian networks (BN) to reconstruct epistatic networks involving all significant SNPs, of which 91 are identified as hub QTLs. Results from gene annotation analysis suggest that most of the hub QTLs detected are in proximity to candidate genes, executing a variety of biological functions in plant growth and development, resilience against pathogens, root development, and abiotic stress resistance. This study provides a new gateway to understand how genetic variation in host plants influences microbial communities and our results could help improve crops by harnessing soil microbes.

Fungal social influencers: secondary metabolites as a platform for shaping the plant-associated community.

Fungal secondary metabolites (FSMs) are capable of manipulating plant community dynamics by inhibiting or facilitating the establishment of co-habitating organisms. Although production of FSMs is not crucial for survival of the producer, their absence can indirectly impair growth and/or niche competition of these fungi on the plant. The presence of FSMs with no obvious consequence on the fitness of the producer leaves questions regarding ecological impact. This review investigates how fungi employ FSMs as a platform to mediate fungal-fungal, fungal-bacterial and fungal-animal interactions associated with the plant community. We discuss how the biological function of FSMs may indirectly benefit the producer by altering the dynamics of surrounding organisms. We introduce several instances where FSMs influence antagonistic- or alliance-driven interactions. Part of our aim is to decipher the meaning of the FSM 'language' as it is widely noted to impact the surrounding community. Here, we highlight the contribution of FSMs to plant-associated interaction networks that affect the host either broadly or in ways that may have previously been unclear.

Bacterial Community Analysis and Potential Functions of Core Taxa in Different Parts of the Fungus Cantharellus cibarius.

Cantharellus cibarius is a widely distributed, popular, edible fungus with high nutritional and economic value. However, significant challenges persist in the microbial ecology and artificial cultivation of C. cibarius. Based on the 16S rRNA sequencing data, this study analyzed bacterial community structures and diversity of fruit bodies and rhizomorph parts of C. cibarius and mycosphere samples (collected in the Wudang District, Guiyang, Guizhou Province, China). It explored the composition and function of the core bacterial taxa. The analyzed results showed that the rhizomorph bacterial community structure was similar to mycosphere, but differed from the fruit bodies. Members of the Allorhizobium-Neorhizobium-Pararhizobium-Rhizobium complex had the highest abundance in the fruit bodies. However, they were either absent or low in abundance in the rhizomorphs and mycosphere. At the same time, members of the Burkholderia-Caballeronia-Paraburkholderia complex were abundant in the fruit bodies and rhizomorphs parts of C. cibarius, as well as mycosphere. Through functional annotation of core bacterial taxa, we found that there was an apparent trend of potential functional differentiation of related bacterial communities in the fruit body and rhizomorph: potential functional groups of core bacterial taxa in the fruit bodies centered on nitrogen fixation, nitrogen metabolism, and degradation of aromatic compounds, while those in rhizomorphs focused on aerobic chemoheterotrophy, chemoheterotrophy, defense against soil pathogens, decomposition of complex organic compounds, and uptake of insoluble inorganic compounds. The analysis of functional groups of bacteria with different structures is of great significance to understand that bacteria promote the growth and development of C. cibarius.

Latent Pathogenic Fungi in the Medicinal Plant Houttuynia cordata Thunb. Are Modulated by Secondary Metabolites and Colonizing Microbiota Originating from Soil.

Latent pathogenic fungi (LPFs) affect plant growth, but some of them may stably colonize plants. LPFs were isolated from healthy Houttuynia cordata rhizomes to reveal this mechanism and identified as Ilyonectria liriodendri, an unidentified fungal sp., and Penicillium citrinum. Sterile H. cordata seedlings were cultivated in sterile or non-sterile soils and inoculated with the LPFs, followed by the plants' analysis. The in vitro antifungal activity of H. cordata rhizome crude extracts on LPF were determined. The effect of inoculation of sterile seedlings by LPFs on the concentrations of rhizome phenolics was evaluated. The rates of in vitro growth inhibition amongst LPFs were determined. The LPFs had a strong negative effect on H. cordata in sterile soil; microbiota in non-sterile soil eliminated such influence. There was an interactive inhibition among LPFs; the secondary metabolites also regulated their colonization in H. cordata rhizomes. LPFs changed the accumulation of phenolics in H. cordata. The results provide that colonization of LPFs in rhizomes was regulated by the colonizing microbiota of H. cordata, the secondary metabolites in the H. cordata rhizomes, and the mutual inhibition and competition between the different latent pathogens.

Emergent spatiotemporal population dynamics with cell-length control of synthetic microbial consortia.

The increased complexity of synthetic microbial biocircuits highlights the need for distributed cell functionality due to concomitant increases in metabolic and regulatory burdens imposed on single-strain topologies. Distributed systems, however, introduce additional challenges since consortium composition and spatiotemporal dynamics of constituent strains must be robustly controlled to achieve desired circuit behaviors. Here, we address these challenges with a modeling-based investigation of emergent spatiotemporal population dynamics using cell-length control in monolayer, two-strain bacterial consortia. We demonstrate that with dynamic control of a strain's division length, nematic cell alignment in close-packed monolayers can be destabilized. We find that this destabilization confers an emergent, competitive advantage to smaller-length strains-but by mechanisms that differ depending on the spatial patterns of the population. We used complementary modeling approaches to elucidate underlying mechanisms: an agent-based model to simulate detailed mechanical and signaling interactions between the competing strains, and a reductive, stochastic lattice model to represent cell-cell interactions with a single rotational parameter. Our modeling suggests that spatial strain-fraction oscillations can be generated when cell-length control is coupled to quorum-sensing signaling in negative feedback topologies. Our research employs novel methods of population control and points the way to programming strain fraction dynamics in consortial synthetic biology.

Molecular trafficking between bacteria determines the shape of gut microbial community.

Complex inter-bacterial interactions largely influence the structure and function of the gut microbial community. Though several host-associated phenomena have often been shown to be involved in the stability, structure, and function of the gut microbial community, the implication of contact-dependent and contact-independent inter-bacterial interactions has been overlooked. Such interactions are tightly governed at multiple layers through several extracellular organelles, including contact-dependent inhibition (CDI), nanotubes, type VI secretion system (T6SS), and membrane vesicles (MVs). Recent advancements in molecular techniques have revealed that such extracellular organelles function beyond exhibiting competitive behavior and are also involved in manifesting cooperative behaviors. Cooperation between bacteria occurs through the sharing of several beneficial molecules including nucleic acids, proteins, metabolites, and nutrients among the members of the community, while competition occurs by means of multiple toxins. Intrinsic coordination between contact-dependent and contact-independent mechanisms collectively provides a fitness advantage and increased colonization resistance to the gut microbiota, where molecular trafficking plays a key role. This review is intended to provide a comprehensive view of the salient features of the different bacterial interactions and to highlight how microbiota deploy multifaceted organelles, for exerting both cooperative and competitive behaviors. We discuss the current knowledge of bacterial molecular trafficking and its impact on shaping the gut microbial community.

Bacillus subtilis strain BS06 protects soybean roots from Fusarium oxysporum infection.

Soybean, as a major oil crop, is one of the most widely planted crops in the world. Fusarium oxysporum causes soybean root rot, leading to great economic losses to soybean planting every year globally. Chemical fungicide for controlling soybean F. oxysporum diseases may cause environmental problems and has human health risks. Biological control methods avoid these shortcomings; however, few studies have focused on biocontrol of soybean diseases caused by F. oxysporum. Aiming at this problem, we obtained biocontrol bacteria against soybean F. oxysporum by plate confrontation method. The type of the strain with the highest biocontrol activity was identified by molecular biological methods, and then its biocontrol effects were verified through greenhouse experiments. One of our isolated strain named BS06 strain had the highest activity, which was identified as Bacillus subtilis. Our study showed that BS06 strain could effectively control soybean F. oxysporum disease and significantly reduce F. oxysporum to infect soybean roots. Compared with control and carbendazim treatments, BS06 treatment had higher root biomass, plant height, leaf chlorophyll content, stem base diameter and control efficiency. Our results indicated that BS06 could effectively protect soybean root (BS06 strain might produce substances to inhibit F. oxysporum), which was potentially useful for soybean planting.

Antifungal activity of lactic acid bacteria isolated from milk against Penicillium commune, P. nordicum, and P. verrucosum.

Penicillium spp. is considered a major spoilage fungus of cheeses. The use of lactic acid bacteria (LAB) with antifungal activity is an interesting possibility of biopreservation. In this study, the isolation and characterization of anti-Penicillium LAB from milk was carried out. Ninety-three milk samples were analysed and a total of 57 strains of LAB active against P. nordicum were isolated, mainly from goat and cow milk. Thirty-four isolates with strong activity were selected and identified, Lacticaseibacillus casei (11), L. paracasei (9) and L. rhamnosus (5) being the dominant species. The antifungal spectrum of these 34 LAB against strains of P. commune and P. verrucosum was investigated. L. casei, L. paracasei and L. rhamnosus were the most active and P. nordicum was the most susceptible fungus. Two isolates (L. casei Lc-51/3 and L. paracasei Lp-25/1) with high antifungal activity showed a moderate to high reduction on the growth of Penicillium nordicum and, in a lesser extent, of P. commune, and also a reducing effect on the ochratoxin A and cyclopiazonic acid production. In addition, these isolates demonstrated activity against several food pahogens. These findings indicate their suitability for the development of protective adjunct starters against spoilage and toxigenic microorganisms in cheese processing.

Elicitation of Streptomyces lunalinharesii secondary metabolism through co-cultivation with Rhizoctonia solani.

The concern regarding the emergence of phytopathogens strains which are resistant to conventional agrochemicals has given support to the search for alternatives on the use of chemical pesticides in agriculture. In this context, microorganisms are considered as promising sources of useful natural compounds and actinobacteria are particularly relevant since they are known to produce several bioactive metabolites. The objective of this work was to investigate the production of secondary metabolites with antifungal activity by a strain of the actinobacteria Streptomyces lunalinharesii (A54A) under axenic conditions and in co-cultivation with the phytopathogen Rhizoctonia solani. Tests to evaluate antifungal activity of the extracts indicated the presence of diffusable molecules capable of inhibiting the growth of R. solani produced by S. lunalinharesii, especially when in the presence of the fungus during fermentation. Metabolomic analyzes allowed the putative annotation of the bioactive compounds desferrioxamine E and anisomycin, in addition to the evaluation of the metabolic profile of the isolate when grown in axenic mode and in co-cultivation, while statistical analyzes enabled the comparison of such profiles and the identification of metabolites produced in greater relative quantities in the elicitation condition. Such methodologies provided the selection of unknown features with high bioactive potential for dereplication, and several metabolites of S. lunalinharesii possibly represent novel compounds.

Isolation, Identification, Biocontrol Activity, and Plant Growth Promoting Capability of a Superior Streptomyces tricolor Strain HM10.

Streptomyces is a genus with known biocontrol activity, producing a broad range of biologically active substances. Our goal was to isolate local Streptomyces species, evaluate their capacity to biocontrol the selected phytopathogens, and promote the plant growth via siderophore and indole acetic acid (IAA) production and phosphate solubilization. Eleven isolates were obtained from local soil samples in Saudi Arabia via the standard serial dilution method and identified morphologically by scanning electron microscope (SEM) and 16S rRNA amplicon sequencing. The biocontrol of phytopathogens was screened against known soil-borne fungi and bacteria. Plant growth promotion capacity was evaluated based on siderophore and IAA production and phosphate solubilization capacity. From eleven isolates obtained, one showed 99.77% homology with the type strain Streptomyces tricolor AS 4.1867, and was designated S. tricolor strain HM10. It showed aerial hyphae in SEM, growth inhibition of ten known phytopathogens in in vitro experiments, and the production of plant growth promoting compounds such as siderophores, IAA, and phosphate solubilization capacity. S. tricolor strain HM10 exhibited high antagonism against the fungi tested (i.e., Colletotrichum gloeosporides with an inhibition zone exceeding 18 mm), whereas the lowest antagonistic effect was against Alternaria solani (an inhibition zone equal to 8 mm). Furthermore, the most efficient siderophore production was recorded to strain HM8, followed by strain HM10 with 64 and 22.56 h/c (halo zone area/colony area), respectively. Concerning IAA production, Streptomyces strain HM10 was the most effective producer with a value of 273.02 µg/ml. An autochthonous strain S. tricolor HM10 should be an important biological agent to control phytopathogens and promote plant growth.

Identification of a new Talaromyces strain DYM25 isolated from the Yap Trench as a biocontrol agent against Fusarium wilt of cucumber.

Fusarium equiseti is a pathogenic fungus of plant root rot, and there are few studies on the biocontrol strains of plant wilt caused by F. equiseti. Hence, we conducted a screening and antimicrobial characterization study of marine-origin biocontrol fungi from water samples of the Yap Trench. A new Talaromyces strain DYM25 was screened from water samples of the Yap Trench in the western Pacific Ocean, and its potential as a biocontrol agent against Fusarium wilt of cucumber was studied. 18S rRNA and ITS gene sequencing verified that strain DYM25 belongs to the genus Talaromyces. The growth of F. equiseti was inhibited by strain DYM25 through the antibiosis effect. A preliminary test was first conducted to examine the bioactive stability of filtered DYM25 broth against F. equiseti under various conditions, including high temperature, UV light, alkaline environment, and the presence of metal ions, which indicated its potential as a bio-control agent. The results of the pot experiment showed that F. equiseti caused cucumber wilt, which could be mitigated using the fermentation broth of strain DYM25 (52.9 %). On the other hand, the alkaloid chromogenic reaction showed that the alkaloid salts present in the crude n-butanol extracts were most likely the major components that might have an antimicrobial effect. Therefore, Talaromyces sp. DYM25 represents a new species that can be used as a novel biocontrol agent against cucumber wilt.