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Bacillus cereus sensu lato (Bcsl) strains are widely explored due to their capacity to antagonize a broad range of plant pathogens. These include B. cereus sp. UW85, whose antagonistic capacity is attributed to the secondary metabolite Zwittermicin A (ZwA). We recently isolated four soil and root-associated Bcsl strains (MO2, S−10, S-25, LSTW-24) that displayed different growth profiles and in-vitro antagonistic effects against three soilborne plant pathogens models: Pythium aphanidermatum (oomycete) Rhizoctonia solani (basidiomycete), and Fusarium oxysporum (ascomycete). To identify genetic mechanisms potentially responsible for the differences in growth and antagonistic phenotypes of these Bcsl strains, we sequenced and compared their genomes, and that of strain UW85 using a hybrid sequencing pipeline. Despite similarities, specific Bcsl strains had unique secondary metabolite and chitinase-encoding genes that could potentially explain observed differences in in-vitro chitinolytic potential and anti-fungal activity. Strains UW85, S-10 and S-25 contained a (~500 Kbp) mega-plasmid that harbored the ZwA biosynthetic gene cluster. The UW85 mega-plasmid contained more ABC transporters than the other two strains, whereas the S-25 mega-plasmid carried a unique cluster containing cellulose and chitin degrading genes. Collectively, comparative genomics revealed several mechanisms that can potentially explain differences in in-vitro antagonism of Bcsl strains toward fungal plant pathogens.

Bacteria are social organisms that interact extensively within and between species while responding to external stimuli from their environments. Designing synthetic microbial communities can enable efficient and beneficial microbiome implementation in many areas. However, in order to design an efficient community, one must consider the interactions between their members. Using a reductionist approach, we examined pairwise interactions of three related Pseudomonas species in various microenvironments including plant roots and inert surfaces. Our results show that the step between monoculture and co-culture is already very complex. Monoculture root colonization patterns demonstrate that each isolate occupied a particular location on wheat roots, such as root tip, distance from the tip, or scattered along the root. However, pairwise colonization outcomes on the root did not follow the bacterial behavior in monoculture, suggesting various interaction patterns. In addition, we show that interspecies interactions on a microscale on inert surface take part in co-culture colonization and that the interactions are affected by the presence of root extracts and depend on its source. The understanding of interrelationships on the root may contribute to future attempts to manipulate and improve bacterial colonization and to intervene with root microbiomes to construct and design effective synthetic microbial consortia.

Plant hosts recruit and maintain a distinct root-associated microbiota based on host and bacterium traits. However, past studies disregarded microbial strain-host specificity and spatial micro-heterogeneity of the root compartment. Using genetic manipulation, confocal laser scanning microscopy, real-time quantitative PCR, and genome sequencing we characterized the colonization patterns of three Pseudomonas spp. isolates native to wheat roots, on the micro-scale. Namely, isolates P. fluorescens NT0133, P. stutzeri NT124, and P. stutzeri NT128. All three isolates preferentially colonized wheat over cucumber roots that served as control for host specificity. Furthermore, not only had the isolates strong host specificity but each isolate had a distinct spatial distribution on the root, all within a few millimeters. Isolate P. stutzeri-NT0124 preferentially colonized root tips, whereas P. fluorescens-NT0133 showed a preference for zones distant from the tip. In contrast, isolate P. stutzeri-NT0128 had no preference for a specific niche on the root. While all isolates maintained genetic potential for motility and biofilm formation their phenotype varied significantly and corresponded to their niche preference. These results demonstrate the importance of spatial colonization patterns, governed by both niche and bacterial characteristics which will have great importance in future attempts to manipulate the plant microbiome by constructing synthetic microbial consortia.

Advances in metagenomics enable high resolution description of complex bacterial communities in their natural environments. Consequently, conceptual approaches for community level functional analysis are in high need. Here, we introduce a framework for a metagenomics-based analysis of community functions. Environment-specific gene catalogs, derived from metagenomes, are processed into metabolic-network representation. By applying established ecological conventions, network-edges (metabolic functions) are assigned with taxonomic annotations according to the dominance level of specific groups. Once a function-taxonomy link is established, prediction of the impact of dominant taxa on the overall community performances is assessed by simulating removal or addition of edges (taxa associated functions). This approach is demonstrated on metagenomic data describing the microbial communities from the root environment of two crop plants – wheat and cucumber. Predictions for environment-dependent effects revealed differences between treatments (root vs. soil), corresponding to documented observations. Metabolism of specific plant exudates (e.g., organic acids, flavonoids) was linked with distinct taxonomic groups in simulated root, but not soil, environments. These dependencies point to the impact of these metabolite families as determinants of community structure. Simulations of the activity of pairwise combinations of taxonomic groups (order level) predicted the possible production of complementary metabolites. Complementation profiles allow formulating a possible metabolic role for observed co-occurrence patterns. For example, production of tryptophan-associated metabolites through complementary interactions is unique to the tryptophan-deficient cucumber root environment. Our approach enables formulation of testable predictions for species contribution to community activity and exploration of the functional outcome of structural shifts in complex bacterial communities. Understanding community-level metabolism is an essential step toward the manipulation and optimization of microbial function. Here, we introduce an analysis framework addressing three key challenges of such data: producing quantified links between taxonomy and function; contextualizing discrete functions into communal networks; and simulating environmental impact on community performances. New technologies will soon provide a high-coverage description of biotic and a-biotic aspects of complex microbial communities such as these found in gut and soil. This framework was designed to allow the integration of high-throughput metabolomic and metagenomic data toward tackling the intricate associations between community structure, community function, and metabolic inputs.

The genus Aeromonas is ubiquitous in aquatic environments encompassing a broad range of fish and human pathogens. Aeromonas strains are known for their enhanced capacity to acquire and exchange antibiotic resistance genes and therefore, are frequently targeted as indicator bacteria for monitoring antimicrobial resistance in aquatic environments. This study evaluated temporal trends in Aeromonas diversity and antibiotic resistance in two adjacent semi-intensive aquaculture facilities to ascertain effects of antibiotic treatment on antimicrobial resistance. In the first facility, sulfadiazine-trimethoprim was added prophylactically upon fingerling stocking and water column-associated Aeromonas were monitored periodically over an eleven-month fish-fattening cycle to assess temporal dynamics in taxonomy and antibiotic resistance. In the second facility, Aeromonas were isolated from fish skin ulcers sampled over a three-year period and from pond water samples to assess associations between pathogenic strains to those in the water column. A total of 1200 Aeromonas spp. were isolated, initially screened for sulfadiazine resistance and further screened against five additional antibiotics. In both facilities, strong correlations were observed between sulfadiazine resistance and trimethoprim and tetracycline resistances, whereas correlations between sulfadiazine resistance and ceftriaxone, gentamycin and chloramphenicol resistances were low. Abundance of multi-drug resistant strains as well as sul1, tetA and intI1 gene-harboring strains was significantly higher in profiles sampled during the fish cycle than those isolated prior to stocking and these genes were extremely abundant in the pathogenic strains. Five phylogenetically-distinct Aeromonas clusters were revealed using partial rpoD gene sequence analysis. Interestingly, prior to fingerling stocking the diversity of water column strains was high, and representatives from all five clusters were identified, including an A. salmonicida cluster that harbored all characterized fish skin ulcer samples. Subsequent to stocking diversity was much lower and most water column isolates in both facilities segregated into an A. veronii-associated cluster. This study demonstrated a strong correlation between aquaculture, Aeromonas diversity and antibiotic resistance. It provides strong evidence for linkage between prophylactic and systemic use of antibiotics in aquaculture and the propagation of antibiotic resistance.