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It is well documented that rice paddy fields act as agricultural wetlands that remove or retain nutrients; however, their associated effects on soil microbial communities are rarely reported. The present study evaluates the impact of rice variety on nutrient removal via plant uptake, nutrient retention in the soil, and bacterial associations in rice paddy fields, using a network analysis that compares the soil bacterial communities of two rice varieties. We found that the high-straw rice variety (YD-1) allows uptake of a high amount of nitrogen (N) and phosphorus (P) from paddy rice fields via harvesting, but causes less residual total N and P to remain in the soil. However, both rice varieties (YD-1 and XS-134 (Xiushui-134)) had non-significant effects on the dominant bacterial taxa. The short-term response of bacterial community diversity to rice variety is found to be mainly due to less frequently recovered species. A network analysis that incorporates soil nutrients as nodes, along with bacterial taxa, found that only one node representing the total P related to the non-dominant species had an indirect association with the rice straw biomass. The observed short-term impact of the two rice varieties (XS-134 and YD-1) on soil bacterial diversity and nutrient surplus in these agricultural wetlands is limited under a high level of fertilization.

Plant–soil microbe interactions are complex and affected by many factors including soil type, edaphic conditions, plant genotype and phenotype, and developmental stage. The rice rhizosphere microbial community composition of nine recombinant inbred lines (RILs) and their parents, Francis and Rondo, segregating for root and shoot biomass, was determined using metagenomic sequencing as a means to examine how biomass phenotype influences the rhizosphere community. Two plant developmental stages were studied, heading and physiological maturity, based on root and shoot biomass growth patterns across the selected genotypes. We used partial least squares (PLS) regression analysis to examine plant trait-driven microbial populations and identify microbial species, functions, and genes corresponding to root and shoot biomass as well as developmental stage patterns. Species identified correlated with increases in either root or shoot biomass were widely present in soil and included species involved in nitrogen cycling (Anaeromyxobacter spp.) and methane production (Methanocella avoryzae), as well as known endophytes (Bradyrhizobium spp.). Additionally, PLS analysis allowed us to explore the relationship of developmental stage with species, microbial functions, and genes. Many of the community functions and genes observed during the heading stage were representative of cell growth (e.g., carbohydrate and nitrogen metabolism), while functions correlated with physiological maturity were indicative of cell decay. These results are consistent with the hypothesis that microbial communities exist whose metabolic and gene functions correspond to plant biomass traits.

Understanding factors influencing microbial interactions, and designing methods to identify key taxa, are complex challenges for achieving microbiome-based agriculture. Here we study how grafting and the choice of rootstock influence root-associated fungal communities in a grafted tomato system. We studied three tomato rootstocks (BHN589, RST-04-106 and Maxifort) grafted to a BHN589 scion and profiled the fungal communities in the endosphere and rhizosphere by sequencing the Internal Transcribed Spacer (ITS2). The data provided evidence for a rootstock effect (explaining ~2% of the total captured variation, p < 0.01) on the fungal community. Moreover, the most productive rootstock, Maxifort, supported greater fungal species richness than the other rootstocks or controls. We then constructed a phenotype-OTU network analysis (PhONA) using an integrated machine learning and network analysis approach based on sequence-based fungal Operational Taxonomic Units (OTUs) and associated tomato yield data. PhONA provides a graphical framework to select a testable and manageable number of OTUs to support microbiome-enhanced agriculture. We identified differentially abundant OTUs specific to each rootstock in both endosphere and rhizosphere compartments. Subsequent analyses using PhONA identified OTUs that were directly associated with tomato fruit yield, and others that were indirectly linked to yield through their links to these OTUs. Fungal OTUs that are directly or indirectly linked with tomato yield may represent candidates for synthetic communities to be explored in agricultural systems.IMPORTANCEThe realized benefits of microbiome analyses for plant health and disease management are often limited by the lack of methods to select manageable and testable synthetic microbiomes. We evaluated the composition and diversity of root-associated fungal communities from grafted tomatoes. We then constructed a phenotype-OTU network analysis (PhONA) using these linear and network models. By incorporating yield data in the network, PhONA identified OTUs that were directly predictive of tomato yield, and others that were indirectly linked to yield through their links to these OTUs. Follow-up functional studies of taxa associated with effective rootstocks, identified using approaches like PhONA, could support the design of synthetic fungal communities for microbiome-based crop production and disease management. The PhONA framework is flexible for incorporation of other phenotypic data and the underlying models can readily be generalized to accommodate other microbiome or other ‘omics data.

Effective altruism is an ethical framework for identifying the greatest potential benefits from investments. Here, we apply effective altruism concepts to maximize research benefits through identification of priority stakeholders, pathosystems, and research questions and technologies. Priority stakeholders for research benefits may include smallholder farmers who have not yet attained the minimal standards set out by the United Nations Sustainable Development Goals; these farmers would often have the most to gain from better crop disease management, if their management problems are tractable. In wildlands, prioritization has been based on the risk of extirpating keystone species, protecting ecosystem services, and preserving wild resources of importance to vulnerable people. Pathosystems may be prioritized based on yield and quality loss, and also factors such as whether other researchers would be unlikely to replace the research efforts if efforts were withdrawn, such as in the case of orphan crops and orphan pathosystems. Research products that help build sustainable and resilient systems can be particularly beneficial. The “value of information” from research can be evaluated in epidemic networks and landscapes, to identify priority locations for both benefits to individuals and to constrain regional epidemics. As decision-making becomes more consolidated and more networked in digital agricultural systems, the range of ethical considerations expands. Low-likelihood but high-damage scenarios such as generalist doomsday pathogens may be research priorities because of the extreme potential cost. Regional microbiomes constitute a commons, and avoiding the “tragedy of the microbiome commons” may depend on shifting research products from “common pool goods” to “public goods” or other categories. We provide suggestions for how individual researchers and funders may make altruism-driven research more effective. [Formula: see text] Copyright © 2020 The Author(s). This is an open access article distributed under the CC BY 4.0 International license .

Network models of soil and plant microbiomes provide new opportunities for enhancing disease management, but also challenges for interpretation. We present a framework for interpreting microbiome networks, illustrating how observed network structures can be used to generate testable hypotheses about candidate microbes affecting plant health. The framework includes four types of network analyses. “General network analysis” identifies candidate taxa for maintaining an existing microbial community. “Host-focused analysis” includes a node representing a plant response such as yield, identifying taxa with direct or indirect associations with that node. “Pathogen-focused analysis” identifies taxa with direct or indirect associations with taxa known a priori as pathogens. “Disease-focused analysis” identifies taxa associated with disease. Positive direct or indirect associations with desirable outcomes, or negative associations with undesirable outcomes, indicate candidate taxa. Network analysis provides characterization not only of taxa with direct associations with important outcomes such as disease suppression, biofertilization, or expression of plant host resistance, but also taxa with indirect associations via their association with other key taxa. We illustrate the interpretation of network structure with analyses of microbiomes in the oak phyllosphere, and in wheat rhizosphere and bulk soil associated with the presence or absence of infection by Rhizoctonia solani.

Huanglongbing (HLB), caused by Candidatus Liberibacter asiaticus (CLas), an uncultured α-proteobacterium, is the most destructive disease of citrus trees worldwide. In previous studies, trunk injections of penicillin reduced CLas titers and HLB symptoms in citrus. However, antibiotic effects on the whole plant microbial community, which include effects on taxa that interact with CLas, have not yet been addressed. In this study, we investigated the effects of penicillin injection (0, 1000, and 6000 mg L−1) on rhizospheric and endophytic bacterial communities of grapefruit trees in field and greenhouse experiments through culture-independent high-throughput sequencing. DNA extractions from petioles and roots were subjected to 16S rRNA high-throughput sequencing, and reads were clustered by sequence similarity into operational taxonomic units (OTUs). Principal coordinates analysis based on weighted-UniFrac distances did not reveal differences in bacterial communities among treatments in any of the sample sources. However, pairwise linear discriminant analysis indicated significant differences in relative abundance of some taxa (including CLas) among treatments. Network analysis showed that penicillin produced major changes in root bacterial community structure by affecting interspecific microbial associations. This study provides new knowledge of the effect of antimicrobial treatments on interspecific relationships in citrus microbial communities.

Plant pathology must address a number of challenges, most of which are characterized by complexity. Network analysis offers useful tools for addressing complex systems and an opportunity for synthesis within plant pathology and between it and relevant disciplines such as in the social sciences. We discuss applications of network analysis, which ultimately may be integrated together into more synthetic analyses of how to optimize plant disease management systems. The analysis of microbiome networks and tripartite phytobiome networks of host-vector-pathogen interactions offers promise for identifying biocontrol strategies and anticipating disease emergence. Linking epidemic network analysis with social network analysis will support strategies for sustainable agricultural development and for scaling up solutions for disease management. Statistical tools for evaluating networks, such as Bayesian network analysis and exponential random graph models, have been underused in plant pathology and are promising for informing strategies. We conclude with research priorities for network analysis applications in plant pathology.

Poly (ADP-Ribose) polymerase-1 (PARP-1) is involved in the DNA repairing system by sensing and signaling the presence of DNA damage. Inhibition of PARP-1 is tested in combination with DNA damaging agents such as topoisomerase I inhibitors or ionizing radiations (RT) for the treatment of glioblastoma (GBM). Disruption of p53, widely prevalent in GBMs, plays a major role in DNA repairing system. The current study investigates whether p53 activity has an effect on the sensitivity of human GBM cells to PARP-1 inhibitors in combination with topoisomerase I inhibitor topotecan (TPT) and/or RT. Human GBM cell lines carrying a different functional status of p53 were treated with PARP-1 inhibitor NU1025, in combination with TPT and/or RT. Cytotoxic effects were examined by analyzing the antiproliferative activity, the cell cycle perturbations, and the DNA damage induced by combined treatments. PARP inhibition enhanced the antiproliferative activity, the cell cycle perturbations and the DNA damage induced by both TPT or RT in GBM cells. These effects were influenced by the p53 activity: cells carrying an active p53 were more sensitive to the combination of PARP inhibitor and RT, while cells carrying an inactive p53 displayed a higher sensitivity to the combination of PARP inhibitor and TPT. Our study suggests that p53 activity influences the differential sensitivity of GBM cells to combined treatments of TPT, RT, and PARP inhibitors. © 2014 International Society for Advancement of Cytometry.

This study characterized the root-associated fungal (RAF) communities inhabiting Eustachys petraea and Panicum maximum , two tropical and weedy grass species on an island off the coast of Honduras, Central America. Media-based analyses revealed that fungi colonizing these grasses exhibited similar morphotypes (albeit in different proportions). Conversely, molecular-based analyses suggested that the community of fungal OTUs were dissimilar, with several OTUs commonly present on only one plant and no AMF sequences present in either plant species. When compared to various datasets of RAF obtained from the North American mainland (with similar methods), the Honduran grasses harbored a different set of fungal OTUs. Interestingly, some cosmopolitan taxonomic clades commonly encountered on the mainland were also isolated in Honduras, though based on ITS rDNA the fungi were only related distantly to those on the mainland. Additional work is necessary to determine how the RAF communities change over geographic distance and whether invasive grasses are constitutionally set up to accept relationships with a different suite of RAF species.

Root-associated fungal endophytes are vital component of root microbiome as some mitigate their host’s abiotic and biotic stress. We characterized root-associated fungal endophytes in cereal grains and their progenitors grown on two different soil-types. We aimed at determining how clay and desert soil affects the colonization of root fungal community. Both culture-dependent and culture-independent methods were employed to identify endophytes that successfully colonized greenhouse-grown host plants. The Internal Transcriber Spacer region of fungal ribosomal DNA was utilized for identification purposes. This study revealed soil as a prominent factor influencing the composition of microfungal communities inhabiting the roots of maize (Zea mays subsp. mays) and its conspecific progenitor, teosinte (Zea mays subsp. parviglumis). Similar results were found in wheat (Triticum aestivum subsp. aestivum) and its progenitor (Triticum monococcum subsp. monococcum). The multidimensional comparisons of Morisita-Horn similarity values of fungal colonists of various host plant taxa indicated that soil plays a primary role in shaping the root fungal community; a secondary effect was plant host identity, even when the plant host is a conspecific. Future studies focused on characterizing root endophytes in other cereal grains, and studying the effect of edaphic factors on fungal colonization, can ultimately contribute to crop productivity.

This paper reports the use of molecular methods to characterize the coprophilous fungal communities (CFC) that inhabit the dung of four species of mammalian herbivores at two sites, Sevilleta National Wildlife Refuge (SNWR) in New Mexico and Wind Cave National Park (WCNP) in South Dakota. Results reveal that CFC from domesticated cattle (Bos taurus) at SNWR, and bison (Bison bison) and black-tailed prairie dogs (Cynomys ludovicianus) at WCNP were diverse but dominated primarily by members within eight taxonomic orders, including the rarely cultured and anaerobic order Neocallimastigales. In addition, 7.7% (138 of 1,788) of the sequences obtained from all dung samples were at least 97% similar to root-associated fungal (RAF) sequences previously described from blue grama (Bouteloua gracilis), a common forage grass found throughout North America and growing at both study sites. In contrast, 95.8% (295 of 308) of the sequences and four of the total seven operational taxonomic units obtained from pronghorn antelope (Antilocapra americana) dung belonged to the Pleosporalean order. We hypothesize that some herbivore vectors disperse non-systemic (non-clavicipitaceous) fungal endophytes. These dispersal events, it is argued, are most likely to occur via herbivores that occasionally forage and masticate root tissue, especially in arid regions where aboveground vegetation is sparse. The results of this study suggest that some (possibly many) members of the RAF community can expand their ecological role to include colonizing dung.

Diverse communities of Root-Associated Fungal (RAF) species, including Dark Septate Endophytes (DSE), inhabit grasses in semiarid soils. These aridlands are often distinguished by large but variable precipitation events (monsoons). We sought to compare the composition and fungal load of the RAF community inhabiting the roots of Sporobolus cryptandrus, a dominant forage grass, exposed to variable precipitation events. We used a rainfall manipulation experiment at the Sevilleta National Wildlife Refuge (SNWR) to examine the abundance and composition of the RAF communities using molecular and microscopic techniques. Molecular data reveals that the RAF communities are dominated by Ascomycetes and few sequences were related to Arbuscular Mycorrhizal Fungi (AMF). The most dominant group (Paraphaeosphaeria spp.) clearly increased in abundance in response to water amendments and the addition of similar volumes of water appeared to increase similarity among the RAF communities, irrespective of size and distribution of precipitation events. Microscopic examinations of the roots also revealed an increased fungal load when exposed to elevated moisture, irrespective of rainfall frequency. We suggest that the increase in these cosmopolitan and abundant groups of Ascomycete fungi, in part, represents a common but complicated strategy of water translocation in a variety of soil types, similar to that proposed and shown in the arbuscular mycorrhizal fungi (AMF). Additional work should examine whether many (or most) members of the Ascomycete RAF also can facultatively broker water in the larger biological network in the soil.