Biology subjects

Fischer-Le Saux, M.

Publications and source records attributed to Fischer-Le Saux, M..

3 recordsLinked to original sources

bioRxiv2022

Novel genetic traits in Xanthomonas unveiled by the complete genome sequencing of three clade-1 xanthomonads

Evolutionary early-branching xanthomonads, also referred to as clade-1 xanthomonads, include major plant pathogens, most of which colonize monocotyledonous plants. Seven species have been validly described, among them the two sugarcane pathogens Xanthomonas albilineans and Xanthomonas sacchari, and Xanthomonas translucens, which infects small grain cereals, diverse grasses, but also asparagus and pistachio trees. Single-gene sequencing and genomic approaches indicated that this clade likely contains more, yet undescribed species. In this study, we sequenced representative strains of three novel species using long-read sequencing technology. Xanthomonas sp. pv. phormiicola strain CFBP 8444 causes bacterial streak on New Zealand flax, another monocotyledonous plant. Xanthomonas sp. strain CFBP 8443 has been isolated from common bean and Xanthomonas sp. strain CFBP 8445 originated from banana. Complete assemblies of the chromosomes confirmed their unique taxonomic position within clade 1 of Xanthomonas. Genome mining revealed novel genetic traits, hitherto undescribed in other members of the Xanthomonas genus. In strain CFBP 8444, we identified genes related to the synthesis of coronatine-like compounds, a phytotoxin produced by several pseudomonads, which raises interesting questions about the evolution and pathogenicity of this pathogen. In addition, strain CFBP 8444 was found to encode a second, atypical flagellar gene cluster in addition to the canonical flagellar gene cluster. Overall, this research represents an important step toward better understanding the evolutionary history and biology of early-branching xanthomonads.

microbiology↗

bioRxiv2021

Synergy of culture-dependent molecular identification and whole-community metabarcode sequencing for characterizing the microbiota of arable crop residues

This study is the first to compare culture-dependent (strain isolation plus molecular identification) and culture-independent (whole-community metabarcode sequencing) approaches for characterizing the microbiota of crop residues. We investigated the diversity of fungal and bacterial communities in wheat and oilseed rape residues, using two different culture-dependent strategies to cover the maximum diversity for each kingdom: broad substrate sampling coupled with low-throughput isolation and diversity analysis for fungi, and reduced substrate sampling coupled with high-throughput isolation and diversity analysis for bacteria. The proportion of cultivable microorganisms was neither as low as the 1% paradigm long associated with the rhizosphere microflora, nor as high as the 50% sometimes reported for the phyllosphere microflora. It was, thus, intermediate between the values for soil and plants. This finding is consistent with residues being considered to constitute an ecotone, at the interface between soil and phyllosphere. Isolation and metabarcoding provided consistent complementary information: they revealed close community profiles, leading to the identification of several common and specific amplicon sequence variants (ASVs). The power of the culture-independent approach was thus confirmed. By contrast the culture-dependent approach was less weak than anticipated. Firstly, it provided complementary information about microbial diversity, with several ASVs not retrieved by metabarcoding being identified after isolation in the community-based culture collection. Secondly, this approach made it possible to preserve and test different taxa either individually or after the creation of synthetic communities, for deciphering the ecological functions of communities beyond merely descriptive aspects.

microbiology↗

bioRxiv2019

A rapid and simple method for assessing and representing genome sequences relatedness

AO_SCPLOWBSTRACTC_SCPLOWCoherent genomic groups are frequently used as a proxy for bacterial species delineation through computation of overall genome relatedness indices (OGRI). Average nucleotide identity (ANI) is a widely employed method for estimating relatedness between genomic sequences. However, pairwise comparisons of genome sequences based on ANI is relatively computationally intensive and therefore precludes analyses of large datasets composed of thousands of genome sequences. In this work we proposed a workflow to compute and visualize relationships between genomic sequences. A dataset containing more than 3,500 Pseudomonas genome sequences was successfully classified with an alternative OGRI based on k-mer counts in few hours with the same precision as ANI. A new visualization method based on zoomable circle packing was employed for assessing relationships among the 350 groups generated. Amendment of databases with these Pseudomonas groups greatly improved the classification of metagenomic read sets with k-mer-based classifier. The developed workflow was integrated in the user-friendly KI-S tool that is available at the following address: https://iris.angers.inra.fr/galaxypub-cfbp.

genomics↗