Agricultural soils suppressive to soilborne plant pathogens occur worldwide, and for several of these soils the biological basis of suppressiveness has been described. Two classical types of suppressiveness are known. General suppression owes its activity to the total microbial biomass in soil and is not transferable between soils. Specific suppression owes its activity to the effects of individual or select groups of microorganisms and is transferable. The microbial basis of specific suppression to four diseases, Fusarium wilts, potato scab, apple replant disease, and take-all, is discussed. One of the best-described examples occurs in take-all decline soils. In Washington State, take-all decline results from the buildup of fluorescent Pseudomonas spp. that produce the antifungal metabolite 2,4-diacetylphloroglucinol. Producers of this metabolite may have a broader role in disease-suppressive soils worldwide. By coupling molecular technologies with traditional approaches used in plant pathology and microbiology, it is possible to dissect the microbial composition and complex interactions in suppressive soils.

Phenotypic diversity within cultivated tomato (Solanum lycopersicum) is particularly evident for fruit shape and size. Four genes that control tomato fruit shape have been cloned. SUN and OVATE control elongated shape whereas FASCIATED (FAS) and LOCULE NUMBER (LC) control fruit locule number and flat shape. We investigated the distribution of the fruit shape alleles in the tomato germplasm and evaluated their contribution to morphology in a diverse collection of 368 predominantly tomato and tomato var. cerasiforme accessions. Fruits were visually classified into eight shape categories that were supported by objective measurements obtained from image analysis using the Tomato Analyzer software. The allele distribution of SUN, OVATE, LC, and FAS in all accessions was strongly associated with fruit shape classification. We also genotyped 116 representative accessions with additional 25 markers distributed evenly across the genome. Through a model-based clustering we demonstrated that shape categories, germplasm classes, and the shape genes were nonrandomly distributed among five genetic clusters (P , 0.001), implying that selection for fruit shape genes was critical to subpopulation differentiation within cultivated tomato. Our data suggested that the LC, FAS, and SUN mutations arose in the same ancestral population while the OVATE mutation arose in a separate lineage. Furthermore, LC, OVATE, and FAS mutations may have arisen prior to domestication or early during the selection of cultivated tomato whereas the SUN mutation appeared to be a postdomestication event arising in Europe.

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.

Indigenous populations of 2,4-diacetylphloroglucinol (2,4-DAPG)-producing fluorescent Pseudomonas spp. that occur naturally in suppressive soils are an enormous resource for improving biological control of plant diseases. Over 300 isolates of 2,4-DAPG-producing fluorescent Pseudomonas spp. were isolated from the rhizosphere of pea plants grown in soils that had undergone pea or wheat monoculture and were suppressive to Fusarium wilt or take-all, respectively. Representatives of seven genotypes, A, D, E, L, O, P, and Q, were isolated from both soils and identified by whole-cell repetitive sequence-based PCR (rep-PCR) with the BOXA1R primer, increasing by three (O, P, and Q) the number of genotypes identified previously among a worldwide collection of 2,4-DAPG producers. Fourteen isolates representing eight different genotypes were tested for their ability to colonize the rhizosphere of pea plants. Population densities of strains belonging to genotypes D and P were significantly greater than the densities of other genotypes and remained above log 6.0 CFU (g of root)؊1 over the entire 15-week experiment. Genetic profiles generated by rep-PCR or restriction fragment length polymorphism analysis of the 2,4-DAPG biosynthetic gene phlD were predictive of the rhizosphere competence of the introduced 2,4-DAPG-producing strains.

7On plants, microbial populations interact with each other and their host through the actions of secreted metabolites. However, the combined action of diverse organisms and their different metabolites on plant health has yet to be fully appreciated. Here, the multifactorial nature of these interactions, at the organismal and molecular level, leading to the biological control of plant diseases is reviewed. To do so, we describe in detail the ecological significance of three different classes of secondary metabolites and discuss how they might contribute to biological control. Specifically, the roles of auxin, acetoin, and phenazines are considered, because they represent very different but important types of secondary metabolites. We also describe how studies of the global regulation of bacterial secondary metabolism have led to the discovery of new genes and phenotypes related to plant health promotion. In conclusion, we describe three avenues for future research that will help to integrate these complex and diverse observations into a more coherent synthesis of bacterially mediated biocontrol of plant diseases.Diverse plant-associated bacteria can positively impact plant health and physiology in a variety of ways (19). Three wellstudied mechanisms of biological disease control and plant health promotion conferred by plant-associated bacteria have recently been reviewed (38). However, the focus on identifying and characterizing individual mechanisms has obscured the complex, multifactorial nature of biological control. So, while many different biocontrol bacteria have been identified and much has been learned about different types of plant-bacterium interactions for some of these populations, we are just beginning to appreciate the number and complexity of interactions actually taking place in situ. Indeed, many different bacteria and many different bacterial metabolites have been identified as important contributors to the biological control of plant diseases. However, we still lack a clear understanding of how the populations and activities of the diverse populations of microorganisms that colonize every plant are connected and integrated in natural and agricultural environments.Here, we review recent work that indicates the multifactorial nature of biocontrol (Fig. 1). Specifically, we review a number of the studies indicating that biocontrol arises from the combined actions of multiple bacterial populations, each expressing several different classes of bioactive metabolites under the control of multiple genes and regulons. And we highlight recent work in the authors' laboratories that begins to identify the diverse factors contributing to changes in plant growth and health status. We conclude by providing a road map for future research that will lead to a greater understanding of the complex, dynamic, and multifactorial nature of biological control phenotypes expressed by plant-associated bacteria.