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      Genomic and Genetic Diversity within the Pseudomonas fluorescens Complex

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          Abstract

          The Pseudomonas fluorescens complex includes Pseudomonas strains that have been taxonomically assigned to more than fifty different species, many of which have been described as plant growth-promoting rhizobacteria (PGPR) with potential applications in biocontrol and biofertilization. So far the phylogeny of this complex has been analyzed according to phenotypic traits, 16S rDNA, MLSA and inferred by whole-genome analysis. However, since most of the type strains have not been fully sequenced and new species are frequently described, correlation between taxonomy and phylogenomic analysis is missing. In recent years, the genomes of a large number of strains have been sequenced, showing important genomic heterogeneity and providing information suitable for genomic studies that are important to understand the genomic and genetic diversity shown by strains of this complex. Based on MLSA and several whole-genome sequence-based analyses of 93 sequenced strains, we have divided the P. fluorescens complex into eight phylogenomic groups that agree with previous works based on type strains. Digital DDH (dDDH) identified 69 species and 75 subspecies within the 93 genomes. The eight groups corresponded to clustering with a threshold of 31.8% dDDH, in full agreement with our MLSA. The Average Nucleotide Identity (ANI) approach showed inconsistencies regarding the assignment to species and to the eight groups. The small core genome of 1,334 CDSs and the large pan-genome of 30,848 CDSs, show the large diversity and genetic heterogeneity of the P. fluorescens complex. However, a low number of strains were enough to explain most of the CDSs diversity at core and strain-specific genomic fractions. Finally, the identification and analysis of group-specific genome and the screening for distinctive characters revealed a phylogenomic distribution of traits among the groups that provided insights into biocontrol and bioremediation applications as well as their role as PGPR.

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          Bacterial iron homeostasis.

          Simon C. Andrews, Andrea Robinson, Francisco Rodríguez-Quiñones (2003)
          Iron is essential to virtually all organisms, but poses problems of toxicity and poor solubility. Bacteria have evolved various mechanisms to counter the problems imposed by their iron dependence, allowing them to achieve effective iron homeostasis under a range of iron regimes. Highly efficient iron acquisition systems are used to scavenge iron from the environment under iron-restricted conditions. In many cases, this involves the secretion and internalisation of extracellular ferric chelators called siderophores. Ferrous iron can also be directly imported by the G protein-like transporter, FeoB. For pathogens, host-iron complexes (transferrin, lactoferrin, haem, haemoglobin) are directly used as iron sources. Bacterial iron storage proteins (ferritin, bacterioferritin) provide intracellular iron reserves for use when external supplies are restricted, and iron detoxification proteins (Dps) are employed to protect the chromosome from iron-induced free radical damage. There is evidence that bacteria control their iron requirements in response to iron availability by down-regulating the expression of iron proteins during iron-restricted growth. And finally, the expression of the iron homeostatic machinery is subject to iron-dependent global control ensuring that iron acquisition, storage and consumption are geared to iron availability and that intracellular levels of free iron do not reach toxic levels.
          Article 0 comments Cited 684 times – based on 0 reviews     Review now
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            Digital DNA-DNA hybridization for microbial species delineation by means of genome-to-genome sequence comparison

            Alexander Auch, Mathias von Jan, Hans-Peter Klenk … (2010)
            The pragmatic species concept for Bacteria and Archaea is ultimately based on DNA-DNA hybridization (DDH). While enabling the taxonomist, in principle, to obtain an estimate of the overall similarity between the genomes of two strains, this technique is tedious and error-prone and cannot be used to incrementally build up a comparative database. Recent technological progress in the area of genome sequencing calls for bioinformatics methods to replace the wet-lab DDH by in-silico genome-to-genome comparison. Here we investigate state-of-the-art methods for inferring whole-genome distances in their ability to mimic DDH. Algorithms to efficiently determine high-scoring segment pairs or maximally unique matches perform well as a basis of inferring intergenomic distances. The examined distance functions, which are able to cope with heavily reduced genomes and repetitive sequence regions, outperform previously described ones regarding the correlation with and error ratios in emulating DDH. Simulation of incompletely sequenced genomes indicates that some distance formulas are very robust against missing fractions of genomic information. Digitally derived genome-to-genome distances show a better correlation with 16S rRNA gene sequence distances than DDH values. The future perspectives of genome-informed taxonomy are discussed, and the investigated methods are made available as a web service for genome-based species delineation.
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              Indole-3-acetic acid in microbial and microorganism-plant signaling.

              Stijn Spaepen, Jos Vanderleyden, Roseline Remans (2007)
              Diverse bacterial species possess the ability to produce the auxin phytohormone indole-3-acetic acid (IAA). Different biosynthesis pathways have been identified and redundancy for IAA biosynthesis is widespread among plant-associated bacteria. Interactions between IAA-producing bacteria and plants lead to diverse outcomes on the plant side, varying from pathogenesis to phyto-stimulation. Reviewing the role of bacterial IAA in different microorganism-plant interactions highlights the fact that bacteria use this phytohormone to interact with plants as part of their colonization strategy, including phyto-stimulation and circumvention of basal plant defense mechanisms. Moreover, several recent reports indicate that IAA can also be a signaling molecule in bacteria and therefore can have a direct effect on bacterial physiology. This review discusses past and recent data, and emerging views on IAA, a well-known phytohormone, as a microbial metabolic and signaling molecule.
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                Author and article information

                Contributors
                Boris Alexander Vinatzer: Role: Editor
                Journal
                Journal ID (nlm-ta): PLoS One
                Journal ID (iso-abbrev): PLoS ONE
                Journal ID (publisher-id): plos
                Journal ID (pmc): plosone
                Title: PLoS ONE
                Publisher: Public Library of Science (San Francisco, CA USA )
                ISSN (Electronic): 1932-6203
                Publication date (Electronic): 25 February 2016
                Publication date Collection: 2016
                Volume: 11
                Issue: 2
                Electronic Location Identifier: e0150183
                Affiliations
                [1 ]Departamento de Biología, Facultad de Ciencias, Universidad Autónoma de Madrid, c/Darwin, 2, Madrid, 28049, Spain
                [2 ]Leibniz Institute DSMZ–German Collection of Microorganisms and Cell Cultures, Inhoffenstraße 7B, 38124, Braunschweig, Germany
                Virginia Tech, UNITED STATES
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: MRN MM RR. Performed the experiments: DGS MRN JMK. Analyzed the data: DGS MRN JMK RR. Contributed reagents/materials/analysis tools: DGS MRN JMK MG MM RR. Wrote the paper: DGS MRN JMK RR.

                Article
                Publisher ID: PONE-D-15-47408
                DOI: 10.1371/journal.pone.0150183
                PMC ID: 4767706
                PubMed ID: 26915094
                SO-VID: f7c6a150-02a5-4039-b07f-a7d1e4d308b5
                Copyright © © 2016 Garrido-Sanz et al
                License:

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                Date received : 2 November 2015
                Date accepted : 10 February 2016
                Page count
                Figures: 8, Tables: 0, Pages: 30
                Funding
                Research was funded by: 1) Grant BIO2012-31634 from Ministerio de Economía y Competitividad to MM; 2) Research program MICROAMBIENTE-CM from Comunidad de Madrid, Spain to RR; 3) DGS was granted by FPU fellowship program (FPU14/03965) from Ministerio de Educación, Cultura y Deporte, Spain.
                Categories
                Subject: Research Article
                Subject: Biology and Life Sciences
                Subject: Organisms
                Subject: Bacteria
                Subject: Pseudomonas
                Subject: Pseudomonas Fluorescens
                Subject: Biology and Life Sciences
                Subject: Computational Biology
                Subject: Genome Complexity
                Subject: Biology and Life Sciences
                Subject: Genetics
                Subject: Genomics
                Subject: Genome Complexity
                Subject: Biology and Life Sciences
                Subject: Evolutionary Biology
                Subject: Evolutionary Systematics
                Subject: Phylogenetics
                Subject: Biology and Life Sciences
                Subject: Taxonomy
                Subject: Evolutionary Systematics
                Subject: Phylogenetics
                Subject: Computer and Information Sciences
                Subject: Data Management
                Subject: Taxonomy
                Subject: Evolutionary Systematics
                Subject: Phylogenetics
                Subject: Research and Analysis Methods
                Subject: Database and Informatics Methods
                Subject: Biological Databases
                Subject: Genomic Databases
                Subject: Biology and Life Sciences
                Subject: Computational Biology
                Subject: Genome Analysis
                Subject: Genomic Databases
                Subject: Biology and Life Sciences
                Subject: Genetics
                Subject: Genomics
                Subject: Genome Analysis
                Subject: Genomic Databases
                Subject: Biology and Life Sciences
                Subject: Molecular Biology
                Subject: Molecular Biology Techniques
                Subject: Molecular Biology Assays and Analysis Techniques
                Subject: Phylogenetic Analysis
                Subject: Research and Analysis Methods
                Subject: Molecular Biology Techniques
                Subject: Molecular Biology Assays and Analysis Techniques
                Subject: Phylogenetic Analysis
                Subject: Biology and Life Sciences
                Subject: Biochemistry
                Subject: Biosynthesis
                Subject: Biology and Life Sciences
                Subject: Organisms
                Subject: Bacteria
                Subject: Pseudomonas
                Subject: Biology and Life Sciences
                Subject: Genetics
                Subject: Genomics
                Subject: Plant Genomics
                Subject: Biology and Life Sciences
                Subject: Biotechnology
                Subject: Plant Biotechnology
                Subject: Plant Genomics
                Subject: Biology and Life Sciences
                Subject: Plant Science
                Subject: Plant Biotechnology
                Subject: Plant Genomics
                Subject: Biology and Life Sciences
                Subject: Genetics
                Subject: Plant Genetics
                Subject: Plant Genomics
                Subject: Biology and Life Sciences
                Subject: Plant Science
                Subject: Plant Genetics
                Subject: Plant Genomics
                Custom metadata
                Data Availability All relevant data are within the paper and its Supporting Information files.

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