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International audience; Summary The ectomycorrhizal (ECM) symbiosis has independently evolved from diverse types of saprotrophic ancestors. In this study, we seek to identify genomic signatures of the transition to the ECM habit within the hyper-diverse Russulaceae. We present comparative analyses of the genomic architecture and the total and secreted gene repertoires of 18 species across the order Russulales of which 13 are newly sequenced, including a representative of a saprotrophic member of Russulaceae, Gloeopeniophorella convolvens. The genomes of ECM Russulaceae are characterized by a loss of genes for plant cell-wall degrading enzymes (PCWDEs), an expansion of genome size through increased transposable element (TE) content, a reduction in secondary metabolism clusters, and an association of small secreted proteins (SSPs) with TE “nests”, or dense aggregations of TEs. Some PCWDEs have been retained or even expanded, mostly in a species-specific manner. The genome of Gloeopeniophorella convolvens possesses some characteristics of ECM genomes (e.g., loss of some PCWDEs, TE expansion, reduction in secondary metabolism clusters). Functional specialization in ectomycorrhizal decomposition may drive diversification. Accelerated gene evolution predates the evolution of the ECM habit, indicating that changes in genome architecture and gene content may be necessary to prime the evolutionary switch.

Researchers from across the four United States Department of Energy Bioenergy Research Centers (BRCs) engaged in a microbiome workshop that focused on identifying challenges and collaboration opportunities to better understand bioenergy-relevant plant–microbe interactions. The virtual workshop included hands-on educational sessions and a keynote address on current best practices in microbiome science and community microbiome standards, as well as breakout sessions aimed at identifying microbiome-related data and measurements that should be prioritized, opportunities for and barriers to integrating plant metabolites to microbiome research, and strategies for more effectively integrating microbiome data and processes into existing models. Based on participant discussion, key findings of the workshop were the need to prioritize scaling data sharing across BRCs and the broader research community and securing collaborative infrastructure in the areas of microbiome-ecosystem modeling and molecular plant–microbe interactions. This workshop review highlights additional main findings from this event, to encourage cross-site and more holistic metaanalyses while promoting wide scientific community engagement across plant microbiome sciences.

Fungal specialized metabolites include many bioactive compounds with potential applications as pharmaceuticals, agrochemical agents, and industrial chemicals. Exploring and discovering novel fungal metabolites is critical to combat antimicrobial resistance in various fields, including medicine and agriculture. Yet, identifying the conditions or treatments that will trigger the production of specialized metabolites in fungi can be cumbersome since most of these metabolites are not produced under standard culture conditions. Here, we introduce a data-driven algorithm comprising various network analysis routes to characterize the production of known and putative specialized metabolites and unknown analytes triggered by different exogenous compounds. We use bipartite networks to quantify the relationship between the metabolites and the treatments stimulating their production through two routes. The first, called the direct route, determines the production of known and putative specialized metabolites induced by a treatment. The second, called the auxiliary route, is specific for unknown analytes. We demonstrated the two routes by applying chitooligosaccharides and lipids at two different temperatures to the opportunistic human fungal pathogen Aspergillus fumigatus. We used various network centrality measures to rank the treatments based on their ability to trigger a broad range of specialized metabolites. The specialized metabolites were ranked based on their receptivity to various treatments. Altogether, our data-driven techniques can track the influence of any exogenous treatment or abiotic factor on the metabolomic output for targeted metabolite research. This approach can be applied to complement existing LC/MS analyses to overcome bottlenecks in drug discovery and development from fungi.NoticeThis manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).Author summaryTriggering silent biosynthetic gene clusters in fungi to produce specialized metabolites is a tedious process that requires assessing various environmental conditions, applications of epigenetic modulating agents, or co-cultures with other microbes. We provide a data-driven solution using network analysis, called “direct route”, to characterize the production of known and putative specialized metabolites triggered by various exogenous compounds. We also provide a “auxiliary route” to distinguish unique unknown analytes amongst the abundantly produced analytes in response to these treatments. The developed techniques can assist researchers to identify treatments or applications that could positively influence the production of a targeted metabolite or recognize unique unknown analytes that can be further fractionated, characterized, and screened for their biological activities and hence, discover new metabolites.

Arbuscular mycorrhizal symbiosis (AMS) is widespread mutualistic association between plants and fungi, which plays an essential role in nutrient exchange, enhancement in plant stress resistance, development of host, and ecosystem sustainability. Previous studies have shown that plant small secreted proteins (SSPs) are involved in beneficial symbiotic interactions. However, the role of SSPs in the evolution of AMS has not been well studied yet. In this study, we performed computational analysis of SSPs in 60 plant species and identified three AMS-specific ortholog groups containing SSPs only from at least 30% of the AMS species in this study and three AMS-preferential ortholog groups containing SSPs from both AMS and non-AMS species, with AMS species containing significantly more SSPs than non-AMS species. We found that independent lineages of monocot and eudicot plants contained genes in the AMS-specific ortholog groups and had significant expansion in the AMS-preferential ortholog groups. Also, two AMS-preferential ortholog groups showed convergent changes, between monocot and eudicot species, in gene expression in response to arbuscular mycorrhizal fungus Rhizophagus irregularis. Furthermore, conserved cis-elements were identified in the promoter regions of the genes showing convergent gene expression. We found that the SSPs, and their closely related homologs, in each of three AMS-preferential ortholog groups, had some local variations in the protein structural alignment. We also identified genes co-expressed with the Populus trichocarpa SSP genes in the AMS-preferential ortholog groups. This first plant kingdom-wide analysis on SSP provides insights on plant-AMS convergent evolution with specific SSP gene expression and local diversification of protein structures.

CRISPR/Cas has recently emerged as the most reliable system for genome engineering in various species. However, concerns about risks associated with the CRISPR/Cas technology are increasing on potential unintended DNA changes that might accidentally arise from CRISPR gene editing. Developing a system that can detect and report the presence of active CRISPR/Cas tools in biological systems is therefore very necessary. Here, we developed four real-time detection systems that can spontaneously indicate the presence of active CRISPR-Cas tools for genome editing and gene regulation including CRISPR/Cas9 nuclease, base editing, prime editing, and CRISPRa in plants. Using the fluorescence-based molecular biosensors, we demonstrated that the activities of CRISPR/Cas9 nuclease, base editing, prime editing, and CRISPRa can be effectively detected in transient expression via protoplast transformation and leaf infiltration (in

Fungi produce a wealth of pharmacologically bioactive secondary metabolites (SMs) from biosynthetic gene clusters (BGCs). It is common practice for drug discovery efforts to treat species’ secondary metabolomes as being well represented by a single or a small number of representative genomes. However, this approach misses the possibility that intraspecific population dynamics, such as adaptation to environmental conditions or local microbiomes, may harbor novel BGCs that contribute to the overall niche breadth of species. Using 94 isolates of Aspergillus flavus, a cosmopolitan model fungus, sampled from seven states in the United States, we dereplicate 7,821 BGCs into 92 unique BGCs. We find that more than 25% of pangenomic BGCs show population-specific patterns of presence/absence or protein divergence. Population-specific BGCs make up most of the accessory-genome BGCs, suggesting that different ecological forces that maintain accessory genomes may be partially mediated by population-specific differences in secondary metabolism. We use ultra-high-performance high-resolution mass spectrometry to confirm that these genetic differences in BGCs also result in chemotypic differences in SM production in different populations, which could mediate ecological interactions and be acted on by selection. Thus, our results suggest a paradigm shift that previously unrealized population-level reservoirs of SM diversity may be of significant evolutionary, ecological, and pharmacological importance. Last, we find that several population-specific BGCs from A. flavus are present in Aspergillus parasiticus and Aspergillus minisclerotigenes and discuss how the microevolutionary patterns we uncover inform macroevolutionary inferences and help to align fungal secondary metabolism with existing evolutionary theory.

Fungi produce a wealth of pharmacologically bioactive secondary metabolites (SMs) from biosynthetic gene clusters (BGCs). It is common practice for drug discovery efforts to treat species' secondary metabolomes as being well represented by a single or a small number of representative genomes. However, this approach misses the possibility that intraspecific population dynamics, such as adaptation to environmental conditions or local microbiomes, may harbor novel BGCs that contribute to the overall niche breadth of species. Using 94 isolates of Aspergillus flavus, a cosmopolitan model fungus, sampled from seven states in the United States, we dereplicate 7,821 BGCs into 92 unique BGCs. We find that more than 25% of pangenomic BGCs show population-specific patterns of presence/absence or protein divergence. Population-specific BGCs make up most of the accessory-genome BGCs, suggesting that different ecological forces that maintain accessory genomes may be partially mediated by population-specific differences in secondary metabolism. We use ultra-high-performance high-resolution mass spectrometry to confirm that these genetic differences in BGCs also result in chemotypic differences in SM production in different populations, which could mediate ecological interactions and be acted on by selection. Thus, our results suggest a paradigm shift that previously unrealized population-level reservoirs of SM diversity may be of significant evolutionary, ecological, and pharmacological importance. Last, we find that several population-specific BGCs from A. flavus are present in Aspergillus parasiticus and Aspergillus minisclerotigenes and discuss how the microevolutionary patterns we uncover inform macroevolutionary inferences and help to align fungal secondary metabolism with existing evolutionary theory.

In natural environments, bacteria preferentially live in biofilms that they build on abiotic surfaces but also on living tissues. Although fungi form extensive networks of hyphae within soils and thus could provide immense surfaces for bacteria to build biofilms and to proliferate, the extent on such phenomenon and the consequences for the fitness of both microorganisms is poorly known in soils. Here, we analyzed the process of formation of biofilms by various bacteria on hyphae of soil fungi in anin vitrosetting using confocal and electron microscopy. We showed that the ability to form biofilms on fungal hyphae is widely shared among soil bacteria. In contrast, some fungi, mainly belonging to the Ascomycete class, did not allow for the formation of bacterial biofilms on their surfaces. The formation of biofilms was also strongly modulated by the presence of tree roots and by the development of the ectomycorrhizal symbiosis, suggesting that biofilm formation does not occur randomly in soil but that it is highly regulated by several biotic factors. Finally, our study led to the unexpected finding that networks of filaments made of extracellular DNA were used to build the skeleton of biofilms by a large array of bacteria.