Metabolic Modeling of Pectobacterium parmentieri SCC3193 Provides Insights into Metabolic Pathways of Plant Pathogenic Bacteria

Impact of Homologous Recombination on Core Genome Evolution and Host Adaptation of Pectobacterium parmentieri

Homologous recombination is a major force mechanism driving bacterial evolution, host adaptability, and acquisition of novel virulence traits. Pectobacterium parmentieri is a plant bacterial pathogen distributed worldwide, primarily affecting potatoes, by causing soft rot and blackleg diseases. The goal of this investigation was to understand the impact of homologous recombination on the genomic evolution of P. parmentieri. Analysis of P. parmentieri genomes using Roary revealed a dynamic pan-genome with 3,742 core genes and over 55% accessory genome variability. Bayesian population structure analysis identified 7 lineages, indicating species heterogeneity. ClonalFrameML analysis displayed 5,125 recombination events, with the lineage 4 exhibiting the highest events. fastGEAR analysis identified 486 ancestral and 941 recent recombination events ranging from 43 bp to 119 kb and 36 bp to 13.96 kb, respectively, suggesting ongoing adaptation. Notably, 11% (412 genes) of the core genome underwent recent recombination, with lineage 1 as the main donor. The prevalence of recent recombination (double compared to ancient) events implies continuous adaptation, possibly driven by global potato trade. Recombination events were found in genes involved in vital cellular processes (DNA replication, DNA repair, RNA processing, homeostasis, and metabolism), pathogenicity determinants (type secretion systems, cell-wall degrading enzymes, iron scavengers, lipopolysaccharides (LPS), flagellum, etc.), antimicrobial compounds (phenazine and colicin) and even CRISPR-Cas genes. Overall, these results emphasize the potential role of homologous recombination in P. parmentieri's evolutionary dynamics, influencing host colonization, pathogenicity, adaptive immunity, and ecological fitness.

Development of a multiplex TaqMan qPCR targeting unique genomic regions for the specific and sensitive detection of Pectobacterium species and P. parmentieri

AIM

The newly defined species P. parmentieri has emerged as an aggressive pathogen that causes soft rot and blackleg diseases on potato and has been widely disseminated across the globe, jeopardizing the productivity and potato food safety. The implementation of a fast and accurate detection tool is imperative to control, monitor and prevent further spread of these pathogens. The objective of this work was to develop a specific and sensitive multiplex TaqMan qPCR to detect P. parmentieri and distinguish it from all known Pectobacterium species. A universal internal control (UIC) was included to enhance the reliability of the assay.

METHODS AND RESULTS

A comparative genomics approach was used to identify O-acetyltransferase and the XRE family transcriptional regulator as specific targets for primers/probe design for the detection of the Pectobacterium genus and P. parmentieri, respectively. Specificity was assessed with 35 and 25 strains included inclusivity and exclusivity panels, respectively, isolated from different geographic locations and sources. The assay specifically detected all 35 strains of Pectobacterium sp. and all 15 P. parmentieri strains. No cross-reactivity was detected during assay validation. Our assay detected up to 10 fg genomic DNA and 1 CFU ml^-1 bacterial culture. No change in the detection threshold (1 CFU ml^-1 ) was observed in spiked assays after adding host tissue to the reactions. The assay was validated with naturally and artificially infected host tissues and soil rhizosphere samples. All infected plant samples containing the target pathogens were accurately amplified.

CONCLUSION

The presented multiplex TaqMan qPCR diagnostic assay is highly specific, sensitive, reliable for the detection of Pectobacterium species and P. parmentieri with no false positives or false negatives.

SIGNIFICANCE AND IMPACT

The developed assay can be adopted for multiple purposes such as seed certification programs, surveillance, biosecurity, microbial forensics, quarantine, border protection, inspections, and epidemiology.

Uncovering the Role of Metabolism in Oomycete-Host Interactions Using Genome-Scale Metabolic Models

Metabolism is the set of biochemical reactions of an organism that enables it to assimilate nutrients from its environment and to generate building blocks for growth and proliferation. It forms a complex network that is intertwined with the many molecular and cellular processes that take place within cells. Systems biology aims to capture the complexity of cells, organisms, or communities by reconstructing models based on information gathered by high-throughput analyses (omics data) and prior knowledge. One type of model is a genome-scale metabolic model (GEM) that allows studying the distributions of metabolic fluxes, i.e., the "mass-flow" through the network of biochemical reactions. GEMs are nowadays widely applied and have been reconstructed for various microbial pathogens, either in a free-living state or in interaction with their hosts, with the aim to gain insight into mechanisms of pathogenicity. In this review, we first introduce the principles of systems biology and GEMs. We then describe how metabolic modeling can contribute to unraveling microbial pathogenesis and host-pathogen interactions, with a specific focus on oomycete plant pathogens and in particular Phytophthora infestans. Subsequently, we review achievements obtained so far and identify and discuss potential pitfalls of current models. Finally, we propose a workflow for reconstructing high-quality GEMs and elaborate on the resources needed to advance a system biology approach aimed at untangling the intimate interactions between plants and pathogens.

The metabolic shift in highly and weakly virulent Dickeya solani strains is more affected by temperature than by mutations in genes encoding global virulence regulators

Global warming may shortly increase the risk of disease development on plants. Significant differences in the metabolic activity screened with Phenotype Microarray at 22°C and 28°C were observed between D. solani strains with high and low virulence level. Highly virulent D. solani was characterized by a higher number of metabolized compounds and a faster metabolism and was more tolerant to non-favorable pH and osmolarity. Metabolic phenotyping showed for the first time that the mutation in pecT gene, which encodes a global repressor of virulence, affects several pathways of the basic cell metabolism. PecT mutants had a higher maceration capacity of potato tissue and showed a higher pectinolytic activity than the wild-type strains. On the contrary, mutation in expI gene, which encoded the signaling molecules synthase crucial for quorum sensing, had an insignificant effect on the cell metabolism, although it slightly reduced the potato tissue maceration. The ability to utilize most of the tested compounds was higher at 28°C, while the survival at non-favorable pH and osmolarity was higher at 22°C. These results proved that the temperature of incubation had the most significant impact on the D. solani metabolic profiles.

Exploration of Plant-Microbe Interactions for Sustainable Agriculture in CRISPR Era

Plants and microbes are co-evolved and interact with each other in nature. Plant-associated microbes, often referred to as plant microbiota, are an integral part of plant life. Depending on the health effects on hosts, plant-microbe (PM) interactions are either beneficial or harmful. The role of microbiota in plant growth promotion (PGP) and protection against various stresses is well known. Recently, our knowledge of community composition of plant microbiome and significant driving factors have significantly improved. So, the use of plant microbiome is a reliable approach for a next green revolution and to meet the global food demand in sustainable and eco-friendly agriculture. An application of the multifaceted PM interactions needs the use of novel tools to know critical genetic and molecular aspects. Recently discovered clustered regularly interspaced short palindromic repeats (CRISPR)/Cas-mediated genome editing (GE) tools are of great interest to explore PM interactions. A systematic understanding of the PM interactions will enable the application of GE tools to enhance the capacity of microbes or plants for agronomic trait improvement. This review focuses on applying GE techniques in plants or associated microbiota for discovering the fundamentals of the PM interactions, disease resistance, PGP activity, and future implications in agriculture.