SummaryWhile the existence of environmental reservoirs of human pathogens is well established, less is known about the role of nonagricultural environments in emergence, evolution, and spread of crop pathogens.Here, we analyzed phylogeny, virulence genes, host range, and aggressiveness of Pseudomonas syringae strains closely related to the tomato pathogen P. syringae pv. tomato (Pto), including strains isolated from snowpack and streams.The population of Pto relatives in nonagricultural environments was estimated to be large and its diversity to be higher than that of the population of Pto and its relatives on crops. Ancestors of environmental strains, Pto, and other genetically monomorphic crop pathogens were inferred to have frequently recombined, suggesting an epidemic population structure for P. syringae. Some environmental strains have repertoires of type III-secreted effectors very similar to Pto, are almost as aggressive on tomato as Pto, but have a wider host range than typical Pto strains.We conclude that crop pathogens may have evolved through a small number of evolutionary events from a population of less aggressive ancestors with a wider host range present in nonagricultural environments.
Abstract. Decaying vegetation was determined to be a potentially important source of atmospheric ice nucleation particles (INPs) in the early 1970s. The bacterium Pseudomonas syringae was the first microorganism with ice nucleation activity (INA) isolated from decaying leaf litter in 1974. However, the ice nucleation characteristics of P. syringae are not compatible with the characteristics of leaf litter-derived INPs since the latter were found to be sub-micron in size, while INA of P. syringae depends on much larger intact bacterial cells. Here we determined the cumulative ice nucleation spectrum and microbial community composition of the historic leaf litter sample 70-S-14 collected in 1970 that conserved INA for 48 years. The majority of the leaf litter-derived INPs were confirmed to be sub-micron in size and to be sensitive to boiling. Culture-independent microbial community analysis only identified Pseudomonas as potential INA. Culture-dependent analysis identified one P. syringae isolate, two isolates of the bacterial species Pantoea ananatis, and one fungal isolate of Mortierella alpina as having INA among 1170 bacterial colonies and 277 fungal isolates, respectively. Both Pa. ananatis and M. alpina are organisms that produce heat-sensitive sub-micron INPs. They are thus both likely sources of the INPs present in sample 70-S-14 and may represent important terrestrial sources of atmospheric INPs, a conclusion that is in line with other recent results obtained in regard to INPs from soil, precipitation, and the atmosphere.
Routine strain-level identification of plant pathogens directly from symptomatic tissue could significantly improve plant disease control and prevention. Here we tested the Oxford Nanopore Technologies (ONT) MinION sequencer for metagenomic sequencing of tomato plants either artificially inoculated with a known strain of the bacterial speck pathogen Pseudomonas syringae pv. tomato or collected in the field and showing bacterial spot symptoms caused by one of four Xanthomonas species. After species-level identification via ONT’s WIMP software and the third-party tools Sourmash and MetaMaps, we used Sourmash and MetaMaps with a custom database of representative genomes of bacterial tomato pathogens to attempt strain-level identification. In parallel, each metagenome was assembled and the longest contigs were used as query with the genome-based microbial identification Web service LINbase. Both the read-based and assembly-based approaches correctly identified P. syringae pv. tomato strain T1 in the artificially inoculated samples. The pathogen strain in most field samples was identified as a member of Xanthomonas perforans group 2. This result was confirmed by whole genome sequencing of colonies isolated from one of the samples. Although in our case metagenome-based pathogen identification at the strain level was achieved, caution still must be exercised in interpreting strain-level results because of the challenges inherent to assigning reads to specific strains and the error rate of nanopore sequencing.
Microbiomes provide critical functions that support animals, plants, and ecosystems. High‐throughput sequencing (HTS) has become an essential tool for the cultivation‐independent study of microbiomes found in diverse environments, but requires effective and meaningful controls. One such critical control is a mock microbial community, which is used as a positive control for nucleic acid extraction, marker gene amplification, and sequencing. While mock community standards can be purchased, they can be costly and often include only medically relevant microbial strains that are not expected to be major players in non‐human microbiomes. As an alternative, it is possible to design and construct a do‐it‐yourself (DIY) mock community, which can then be used as a positive control that is specifically customized to the protocol needs of a particular study system. In this article, we describe protocols to select appropriate microbial strains for the construction of a mock community. We first describe the steps to verify the identity of community members via Sanger sequencing. Then, we provide guidance on assembling and storing the DIY mock community as viable whole cells. This includes steps to create standard growth curves referenced to plate counts for each member, so that the community members can be quantified and later compared in terms of their “expected versus returned” relative contributions after sequencing. We also describe appropriate methods for the cryostorage of the fully assembled mock community as viable whole cells, so that they can be used as a unit in a microbiome analysis, from the lysis and nucleic acid extraction steps onwards. Finally, we provide an example of returned data and interpretation of DIY mock community sequences, discussing how to assess possible contamination and identify protocol biases for particular members. Overall, DIY mock communities serve to determine success and possible bias in a cultivation‐independent microbiome analysis. © 2022 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Strain identification and verification using Sanger sequencing Basic Protocol 2: Creation of glycerol stocks of each mock community strain for long‐term cryostorage Basic Protocol 3: Assessment of strain freezer viability without cryoprotectant Basic Protocol 4: Creation of standard curve to determine CFU/ml of a liquid culture as a function of optical density Basic Protocol 5: Full mock community assembly using community concentration calculations and standard curves
Poor survival on plants can limit the efficacy of Biological Control Agents (BCAs) in the field. Yet bacteria survive in the atmosphere, despite their exposure to high solar radiation and extreme temperatures. If conditions in the atmosphere are similar to, or more extreme than, the environmental conditions on the plant surface, then precipitation may serve as a reservoir of robust BCAs. To test this hypothesis, two hundred and fifty-four rain-borne isolates were screened for in vitro inhibition of Erwinia amylovora, the causal agent of fire blight, as well as of other plant pathogenic bacteria, fungi and oomycetes. Two isolates showed strong activity against E. amylovora and other plant pathogenic bacteria, while other isolates showed activity against fungal and oomycete pathogens. Survival assays suggested that the two isolates that inhibited E. amylovora were able to survive on apple blossoms and branches similarly to E. amylovora. Pathogen population size and associated fire blight symptoms were significantly reduced when detached apple blossoms were treated with the two isolates before pathogen inoculation, however, disease reduction on attached blossoms within an orchard was inconsistent. Using whole genome sequencing, the isolates were identified as Pantoea agglomerans and P. ananatis, respectively. A UV-mutagenesis screen pointed to a phenazine antibiotic D-alanylgriseoluteic acid synthesis gene cluster as being at the base of the antimicrobial activity of the P. agglomerans isolate. Our work reveals the potential of precipitation as an under-explored source of BCAs, whole genome sequencing as an effective approach to precisely identify BCAs, and UVmutagenesis as a technically simple screen to investigate the genetic basis of BCAs. More field trials are needed to determine the efficacy of the identified BCAs in fire blight control.
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