Biology subjects

Udaondo, Z.

Publications and source records attributed to Udaondo, Z..

7 recordsLinked to original sources

bioRxiv2026

An orphan LuxR regulator controls plant developmental reprogramming during interaction with Novosphingobium resinovorum HR1a

Rhizoremediation depends on productive plant/pollutant-degrading microorganism interactions, yet the bacterial regulatory mechanisms that shape host responses remain poorly understood. We investigated the role of the previously uncharacterized orphan LuxR874 from the polycyclic aromatic hydrocarbon (PAH) degrading bacterium Novosphingobium resinovorum HR1a, in the modulation of plant physiology. Bacterial transcriptomics revealed that LuxR874 controls the expression of genes associated with aromatic and sugar metabolism, and acylCoA related functions. Inactivation of luxR874 altered bacterial responses without affecting root colonization, suggesting that this regulator contributes to the physiological state required to elicit host responses. In gnotobiotic systems, HR1a induced a root phenotype characterized by reduced primary root elongation, increased root thickness, and enhanced root hair formation. These alterations were attenuated in the luxR874 mutant and restored by complementation despite similar colonization levels among strains. Plant RNA-seq analyses revealed extensive host transcriptional reprogramming, including activation of developmental regulators, hormone associated pathways, cell wall remodeling genes, and oxidative stress responses. In contrast, plants inoculated with the luxR874 mutant displayed a weaker transcriptional response resembling the non-inoculated state. Functional analyses supported LuxR874-dependent activation of reactive oxygen species and ethylene related pathways. Our results reveal an unexpected role for an orphan LuxR regulator in coordinating multi-level responses during a rhizoremediation-relevant plant microbe interaction.

molecular biology↗

bioRxiv2025

Turnip mosaic virus drives selective filtering and community reassembly in the Arabidopsis thaliana root microbiome in a genotype-specific manner

Plant root microbiomes play a central role in plant health, yet their responses to viral infection remain poorly understood. Here, we investigated how Turnip mosaic virus (TuMV) alters root-associated bacterial and fungal communities in two Arabidopsis thaliana genotypes (Col-0 and Mar-12) grown in natural soils. Using 16S and ITS amplicon sequencing, we assessed changes in diversity, taxonomic composition, enriched microbial taxa, and co-occurrence network structure to distinguish between plant-mediated recruitment ("cry-for-help") and pathogen-induced dysbiosis. TuMV infection caused a pronounced reduction in bacterial diversity and a restructuring of bacterial community composition, whereas fungal communities remained largely stable. Viral infection also led to genotype-specific shifts in enriched bacterial genera, with opportunistic and stress-tolerant taxa proliferating differently in each genotype. Despite the initial perturbation, bacterial networks recovered connectivity and, in some cases, reached higher complexity than those of healthy plants, indicating strong microbial resilience. Together, these results reveal that TuMV infection acts as a selective filter on bacterial, but not fungal, root communities and that the surviving taxa can reorganize into functional networks. Our study provides one of the most comprehensive assessments of virus-induced microbiome restructuring and highlights the importance of host genotype in shaping microbial responses to biotic stress.

plant biology↗

bioRxiv2025

Effect of diesel contamination on bacterial populations in a pristine soil during rhizoremediation

Background and aimsContamination of soils with hydrocarbons such as diesel is of major concern as use and transport increases. In order to obtain a better understanding of how soil microorganisms face diesel during rhizoremediation of a natural soil will help us improve remediation processes. MethodsWe conducted microcosm experiments with a pristine soil contaminated or not with diesel and planted with clover, clover/ryegrass or non-planted controls. We measured the aromatic fraction of diesel by HPLC-DAD along time under the different experimental conditions and determined the bacterial communities in soil and the rhizosphere by amplicon sequencing of the 16S rRNA gene. ResultsThe presence of clover accelerates the disappearance of the aromatic components of diesel but not significantly so. The bacterial diversity is lowered by diesel contamination although this decline is mitigated by the presence of plants. Bacterial community structure is mostly affected by soil type and then by diesel contamination. Actinobacteriota and Gemmatimonadota decline while Firmicutes, Bacteroidota and Proteobacteria increase with diesel contamination and in the rhizosphere. Amplified sequence variants (ASVs) belonging to Novosphingobium and Sphingomonas are especially abundant in diesel contaminated bulk soil and ASVs belonging to Azospirillum, Rhizobium, Ohtaekwangia Faecalibacterium, and Subdoligranulum are especially abundant in diesel contaminated rhizosphere. ConclusionClover helps dissipate diesel aromatic compounds faster from a pristine soil. Clover and ryegrass mitigate the decline of bacterial diversity in soil due to diesel contamination and certain bacterial taxa which are enriched with the contaminant are identified which may play a role to remediate diesel contamination.

microbiology↗

bioRxiv2022

Genomic Distance-based Rapid Uncovering of Microbial Population Structures (GRUMPS): a reference free genomic data cleaning methodology

Accurate datasets are crucial for rigorous large-scale sequence-based analyses such as those performed in phylogenomics and pangenomics. As the volume of available sequence data grows and the quality of these sequences varies, there is a pressing need for reliable methods to swiftly identify and eliminate low-quality and misidentified genomes from datasets prior to analysis. Here we introduce a robust, controlled, computationally efficient method for deriving species-level population structures of bacterial species, regardless of the dataset size. Additionally, our pipeline can classify genomes into their respective species at the genus level. By leveraging this methodology, researchers can rapidly clean datasets encompassing entire bacterial species and examine the sub-species population structures within the provided genomes. These cleaned datasets can subsequently undergo further refinement using a variety of methods to yield sequence sets with varying levels of diversity that faithfully represent entire species. Increasing the efficiency and accuracy of curation of species-level datasets not only enhances the reliability of downstream analyses, but also facilitates a deeper understanding of bacterial population dynamics and evolution.

bioinformatics↗

bioRxiv2021

Insertion sequences associated with antibiotic resistance genes in Enterococcus isolates from an inpatient with prolonged bacteremia.

Insertion sequences (ISs) and other transposable elements are associated with the mobilization of antibiotic resistance determinants and the modulation of pathogenic characteristics. In this work, we aimed to investigate the association between ISs and antibiotic resistance genes, and their role in dissemination and modification of antibiotic resistance phenotype. To that end, we leveraged fully resolved Enterococcus faecium and Enterococcus faecalis genomes of isolates collected over four days from an inpatient with prolonged bacteremia. Isolates from both species harbored similar IS family content but showed significant species-dependent differences in copy number and arrangements of ISs throughout their replicons. Here, we describe two inter-specific IS-mediated recombination events, and IS-medicated excision events in plasmids of E. faecium isolates. We also characterize a novel arrangement of the IS in a Tn1546-like transposon in E. faecalis isolates likely implicated in a vancomycin genotype-phenotype discrepancy. Furthermore, an extended analysis revealed a novel association between daptomycin resistance mutations in liaSR genes and a putative composite transposon in E. faecium offering a new paradigm for the study of daptomycin-resistance and novel insights into the route of daptomycin resistance dissemination. In conclusion, our study highlights the role ISs and other transposable elements play in rapid adaptation and response to clinically relevant stresses such as aggressive antibiotic treatment in enterococci.

genomics↗

bioRxiv2019

What can we learn from over 100,000 Escherichia coli genomes?

The explosion of microbial genome sequences in public databases allows for large-scale population genomic studies of bacterial species, such as Escherichia coli. In this study, we examine and classify more than one hundred thousand E. coli and Shigella genomes. After removing outliers, a semi-automated Mash-based analysis of 10,667 assembled genomes reveals 14 distinct phylogroups. A representative genome or medoid identified for each phylogroup serves as a proxy to classify more than 95,000 unassembled genomes. This analysis shows that most sequenced E. coli genomes belong to 4 phylogroups (A, C, B1 and E2(O157)). Authenticity of the 14 phylogroups described is supported by pangenomic and phylogenetic analyses, which show differences in gene preservation between phylogroups. A phylogenetic tree constructed with 2,613 single copy core genes along with a matrix of phylogenetic profiles is used to confirm that the 14 phylogroups change at different rates of gene gain/loss/duplication. The methodology used in this work is able to identify previously uncharacterized phylogroups in E. coli species. Some of these new phylogroups harbor clonal strains that have undergone a process of genomic adaptation to the acquisition of new genomic elements related to virulence or antibiotic resistance. This is, to our knowledge, the largest E. coli genome dataset analyzed to date and provides valuable insights into the population structure of the species.

genomics↗

bioRxiv2019

Improved bacteria population structure analysis on thousands of genomes using unsupervised methods

Over ten thousand genomes of Escherichia coli are now available, and this number will continue to grow for this and other important microbial species. The first approach often used to better understand microbes is phylogenetic group analysis followed by pan-genome analysis of highly related genomes. Here, we combine sequence-based features with unsupervised clustering on up to 2,231 E. coli genomes and a total of 1,367 Clostridium difficile genomes. We show that Non-negative Matrix Factorization (NMF) can identify \"mixed\"/cryptic genomes, and can better determine inter-related genome groups and their distinguishing features (genes) relative to prior methods.

bioinformatics↗