scholarly journals Bacterial genospecies that are not ecologically coherent: population genomics of Rhizobium leguminosarum

Open Biology ◽  
2015 ◽  
Vol 5 (1) ◽  
pp. 140133 ◽  
Author(s):  
Nitin Kumar ◽  
Ganesh Lad ◽  
Elisa Giuntini ◽  
Maria E. Kaye ◽  
Piyachat Udomwong ◽  
...  
Keyword(s):  
Rhizobium Leguminosarum ◽  
Bacterial Population ◽  
Population Genomics ◽  
Bacterial Species ◽  
Core Gene ◽  
Biological Species ◽  
Ecological Groups ◽  
Genetic Isolation ◽  
Taxonomic Framework ◽  
Core Genes

Biological species may remain distinct because of genetic isolation or ecological adaptation, but these two aspects do not always coincide. To establish the nature of the species boundary within a local bacterial population, we characterized a sympatric population of the bacterium Rhizobium leguminosarum by genomic sequencing of 72 isolates. Although all strains have 16S rRNA typical of R. leguminosarum , they fall into five genospecies by the criterion of average nucleotide identity (ANI). Many genes, on plasmids as well as the chromosome, support this division: recombination of core genes has been largely within genospecies. Nevertheless, variation in ecological properties, including symbiotic host range and carbon-source utilization, cuts across these genospecies, so that none of these phenotypes is diagnostic of genospecies. This phenotypic variation is conferred by mobile genes. The genospecies meet the Mayr criteria for biological species in respect of their core genes, but do not correspond to coherent ecological groups, so periodic selection may not be effective in purging variation within them. The population structure is incompatible with traditional ‘polyphasic taxonomy′ that requires bacterial species to have both phylogenetic coherence and distinctive phenotypes. More generally, genomics has revealed that many bacterial species share adaptive modules by horizontal gene transfer, and we envisage a more consistent taxonomic framework that explicitly recognizes this. Significant phenotypes should be recognized as ‘biovars' within species that are defined by core gene phylogeny.

scholarly journals Heterogeneity among estimates of the core genome and pan-genome in different pneumococcal populations

2017 ◽  
Author(s):  
Andries J van Tonder ◽  
James E Bray ◽  
Keith A Jolley ◽  
Sigríður J Quirk ◽  
Gunnsteinn Haraldsson ◽  
...  
Keyword(s):  
Bacterial Population ◽  
Core Genome ◽  
Bacterial Species ◽  
Essential Point ◽  
Genetic Lineages ◽  
The Core ◽  
Pan Genome ◽  
Single Dataset ◽  
Genomic Regions ◽  
Core Genes

AbstractBackgroundUnderstanding the structure of a bacterial population is essential in order to understand bacterial evolution, or which genetic lineages cause disease, or the consequences of perturbations to the bacterial population. Estimating the core genome, the genes common to all or nearly all strains of a species, is an essential component of such analyses. The size and composition of the core genome varies by dataset, but our hypothesis was that variation between different collections of the same bacterial species should be minimal. To test this, the genome sequences of 3,121 pneumococci recovered from healthy individuals in Reykjavik (Iceland), Southampton (United Kingdom), Boston (USA) and Maela (Thailand) were analysed.ResultsThe analyses revealed a ‘supercore’ genome (genes shared by all 3,121 pneumococci) of only 303 genes, although 461 additional core genes were shared by pneumococci from Reykjavik, Southampton and Boston. Overall, the size and composition of the core genomes and pan-genomes among pneumococci recovered in Reykjavik, Southampton and Boston were very similar, but pneumococci from Maela were distinctly different. Inspection of the pan-genome of Maela pneumococci revealed several >25 Kb sequence regions that were homologous to genomic regions found in other bacterial species.ConclusionsSome subsets of the global pneumococcal population are highly heterogeneous and thus our hypothesis was rejected. This is an essential point of consideration before generalising the findings from a single dataset to the wider pneumococcal population.

scholarly journals ProkEvo: an automated, reproducible, and scalable framework for high-throughput bacterial population genomics analyses

2020 ◽  
Author(s):  
Natasha Pavlovikj ◽  
Joao Carlos Gomes-Neto ◽  
Jitender S. Deogun ◽  
Andrew K. Benson
Keyword(s):  
Case Studies ◽  
High Throughput ◽  
Bacterial Population ◽  
Population Genomics ◽  
Bacterial Species ◽  
Population Based ◽  
Epidemiological Surveillance ◽  
Specific Gene ◽  
Genotype Frequencies ◽  
Population Scale

AbstractWhole Genome Sequence (WGS) data from bacterial species is used for a variety of applications ranging from basic microbiological research, diagnostics, and epidemiological surveillance. The availability of WGS data from hundreds of thousands of individual isolates of individual microbial species poses a tremendous opportunity for discovery and hypothesis-generating research into ecology and evolution of these microorganisms. Scalability and user-friendliness of existing pipelines for population-scale inquiry, however, limit applications of systematic, population-scale approaches. Here, we present ProkEvo, an automated, scalable, and open-source framework for bacterial population genomics analyses using WGS data. ProkEvo was specifically developed to achieve the following goals: 1) Automation and scaling of complex combinations of computational analyses for many thousands of bacterial genomes from inputs of raw Illumina paired-end sequence reads; 2) Use of workflow management systems (WMS) such as Pegasus WMS to ensure reproducibility, scalability, modularity, fault-tolerance, and robust file management throughout the process; 3) Use of high-performance and high-throughput computational platforms; 4) Generation of hierarchical population-based genotypes at different scales of resolution based on combinations of multi-locus and Bayesian statistical approaches for classification; 5) Detection of antimicrobial resistance (AMR) genes, putative virulence factors, and plasmids from curated databases and association with genotypic classifications; and 6) Production of pan-genome annotations and data compilation that can be utilized for downstream analysis. The scalability of ProkEvo was measured with two datasets comprising significantly different numbers of input genomes (one with ~2,400 genomes, and the second with ~23,000 genomes). Depending on the dataset and the computational platform used, the running time of ProkEvo varied from ~3-26 days. ProkEvo can be used with virtually any bacterial species and the Pegasus WMS facilitates addition or removal of programs from the workflow or modification of options within them. All the dependencies of ProkEvo can be distributed via conda environment or Docker image. To demonstrate versatility of the ProkEvo platform, we performed population-based analyses from available genomes of three distinct pathogenic bacterial species as individual case studies (three serovars of Salmonella enterica, as well as Campylobacter jejuni and Staphylococcus aureus). The specific case studies used reproducible Python and R scripts documented in Jupyter Notebooks and collectively illustrate how hierarchical analyses of population structures, genotype frequencies, and distribution of specific gene functions can be used to generate novel hypotheses about the evolutionary history and ecological characteristics of specific populations of each pathogen. Collectively, our study shows that ProkEvo presents a viable option for scalable, automated analyses of bacterial populations with powerful applications for basic microbiology research, clinical microbiological diagnostics, and epidemiological surveillance.

scholarly journals ProkEvo: an automated, reproducible, and scalable framework for high-throughput bacterial population genomics analyses

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11376
Author(s):  
Natasha Pavlovikj ◽  
Joao Carlos Gomes-Neto ◽  
Jitender S. Deogun ◽  
Andrew K. Benson
Keyword(s):  
Population Structure ◽  
Case Studies ◽  
High Throughput ◽  
Bacterial Population ◽  
Population Genomics ◽  
Bacterial Species ◽  
Epidemiological Surveillance ◽  
Specific Gene ◽  
Population Structure Analysis ◽  
Population Scale

Whole Genome Sequence (WGS) data from bacterial species is used for a variety of applications ranging from basic microbiological research, diagnostics, and epidemiological surveillance. The availability of WGS data from hundreds of thousands of individual isolates of individual microbial species poses a tremendous opportunity for discovery and hypothesis-generating research into ecology and evolution of these microorganisms. Flexibility, scalability, and user-friendliness of existing pipelines for population-scale inquiry, however, limit applications of systematic, population-scale approaches. Here, we present ProkEvo, an automated, scalable, reproducible, and open-source framework for bacterial population genomics analyses using WGS data. ProkEvo was specifically developed to achieve the following goals: (1) Automation and scaling of complex combinations of computational analyses for many thousands of bacterial genomes from inputs of raw Illumina paired-end sequence reads; (2) Use of workflow management systems (WMS) such as Pegasus WMS to ensure reproducibility, scalability, modularity, fault-tolerance, and robust file management throughout the process; (3) Use of high-performance and high-throughput computational platforms; (4) Generation of hierarchical-based population structure analysis based on combinations of multi-locus and Bayesian statistical approaches for classification for ecological and epidemiological inquiries; (5) Association of antimicrobial resistance (AMR) genes, putative virulence factors, and plasmids from curated databases with the hierarchically-related genotypic classifications; and (6) Production of pan-genome annotations and data compilation that can be utilized for downstream analysis such as identification of population-specific genomic signatures. The scalability of ProkEvo was measured with two datasets comprising significantly different numbers of input genomes (one with ~2,400 genomes, and the second with ~23,000 genomes). Depending on the dataset and the computational platform used, the running time of ProkEvo varied from ~3-26 days. ProkEvo can be used with virtually any bacterial species, and the Pegasus WMS uniquely facilitates addition or removal of programs from the workflow or modification of options within them. To demonstrate versatility of the ProkEvo platform, we performed a hierarchical-based population structure analyses from available genomes of three distinct pathogenic bacterial species as individual case studies. The specific case studies illustrate how hierarchical analyses of population structures, genotype frequencies, and distribution of specific gene functions can be integrated into an analysis. Collectively, our study shows that ProkEvo presents a practical viable option for scalable, automated analyses of bacterial populations with direct applications for basic microbiology research, clinical microbiological diagnostics, and epidemiological surveillance.

scholarly journals The genomic architecture of introgression among sibling species of bacteria

2019 ◽  
Author(s):  
Maria Izabel A Cavassim ◽  
Sara Moeskjær ◽  
Camous Moslemi ◽  
Bryden Fields ◽  
Asger Bachmann ◽  
...  
Keyword(s):  
Gene Transfer ◽  
Rhizobium Leguminosarum ◽  
Root Nodules ◽  
Bacterial Species ◽  
Core Gene ◽  
Conjugative Plasmid ◽  
Conjugative Transfer ◽  
Recombination Rates ◽  
Transfer Genes ◽  
Selective Forces

AbstractBackgroundGene transfer between bacterial species is an important mechanism for adaptation. For example, sets of genes that confer the ability to form nitrogen-fixing root nodules on host plants have frequently moved betweenRhizobiumspecies. It is not clear, though, whether such transfer is exceptional, or if frequent inter-species introgression is typical. To address this, we sequenced the genomes of 196 isolates of theRhizobium leguminosarumspecies complex obtained from root nodules of white clover (Trifolium repens).ResultsCore gene phylogeny placed the isolates into five distinct genospecies that show high intra-genospecies recombination rates and remarkably different demographic histories. Most gene phylogenies were largely concordant with the genospecies, indicating that recent gene transfer between genospecies was rare. In contrast, very similar symbiosis gene sequences were found in two or more genospecies, suggesting recent horizontal transfer. The replication and conjugative transfer genes of the plasmids carrying the symbiosis genes showed a similar pattern, implying that introgression occurred by conjugative plasmid transfer. The only other regions that showed strong phylogenetic discordance with the genospecies classification were two small chromosomal clusters, one neighbouring a conjugative transfer system. Phage-related sequences were observed in the genomes, but appeared to have very limited impact on introgression.ConclusionsIntrogression among these closely-related species has been very limited, confined to the symbiosis plasmids and a few chromosomal islands. Both introgress through conjugative transfer, but have been subject to different types of selective forces.

scholarly journals Defining the Rhizobium leguminosarum Species Complex

Genes ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 111 ◽  
Author(s):  
J. Peter W. Young ◽  
Sara Moeskjær ◽  
Alexey Afonin ◽  
Praveen Rahi ◽  
Marta Maluk ◽  
...  
Keyword(s):  
Ribosomal Rna ◽  
Species Complex ◽  
Rhizobium Leguminosarum ◽  
Housekeeping Genes ◽  
Single Species ◽  
Natural Unit ◽  
Genome Sequences ◽  
Distinct Entity ◽  
Type Strains ◽  
Core Genes

Bacteria currently included in Rhizobium leguminosarum are too diverse to be considered a single species, so we can refer to this as a species complex (the Rlc). We have found 429 publicly available genome sequences that fall within the Rlc and these show that the Rlc is a distinct entity, well separated from other species in the genus. Its sister taxon is R. anhuiense. We constructed a phylogeny based on concatenated sequences of 120 universal (core) genes, and calculated pairwise average nucleotide identity (ANI) between all genomes. From these analyses, we concluded that the Rlc includes 18 distinct genospecies, plus 7 unique strains that are not placed in these genospecies. Each genospecies is separated by a distinct gap in ANI values, usually at approximately 96% ANI, implying that it is a ‘natural’ unit. Five of the genospecies include the type strains of named species: R. laguerreae, R. sophorae, R. ruizarguesonis, “R. indicum” and R. leguminosarum itself. The 16S ribosomal RNA sequence is remarkably diverse within the Rlc, but does not distinguish the genospecies. Partial sequences of housekeeping genes, which have frequently been used to characterize isolate collections, can mostly be assigned unambiguously to a genospecies, but alleles within a genospecies do not always form a clade, so single genes are not a reliable guide to the true phylogeny of the strains. We conclude that access to a large number of genome sequences is a powerful tool for characterizing the diversity of bacteria, and that taxonomic conclusions should be based on all available genome sequences, not just those of type strains.

scholarly journals NodC-based evaluation of the occurrence of bacteria in nodules of Pisum sativum isolated on YEM agar

2019 ◽  
Vol 70 (1) ◽  
pp. 59-67
Author(s):  
Anna Lenart-Boroń ◽  
Tadeusz Zając ◽  
Piotr Mateusz Boroń ◽  
Agnieszka Klimek-Kopyra
Keyword(s):  
Pisum Sativum ◽  
Rhizobium Leguminosarum ◽  
Reference Strain ◽  
Root Nodules ◽  
Bacterial Species ◽  
Soil Science ◽  
Associated Bacteria ◽  
Plant Cultivation ◽  
Yeast Extract Mannitol ◽  
Diverse Community

SummaryThe bacterial nodulation (nod) genes are essential in the formation process of root nodules. This study was aimed to verify the occurrence of nodule-associated bacteria in two pea varieties (“Tarchalska” and “Klif ”) inoculated withRhizobiuminoculants – Nitragine™ and a noncommercial one produced by the Polish Institute of Soil Science and Plant Cultivation (IUNG). The number of colonies isolated on yeast extract mannitol (YEM) agar from the nodules of “Klif ” inoculated with IUNG inoculants was significantly higher than the number of colonies isolated from other variants. Species identification was based on sequencing of 16S rDNA, which revealed that despite careful sterilization of nodules, sequences of other bacterial species were detected. Among them, one sequence belonged toRhizobium leguminosarum(isolated from IUNG inoculant). To assess the presence of nodulation-capableRhizobium, amplification of thenodCgene was performed, which revealed that of 29 samples, 19 were positive. The remaining isolates, including reference strain and bacteria isolated from Nitragine™, lacked this gene. The results show that pea nodules harbor a very diverse community of bacteria. The lack ofnodCgene in some strains isolated from plants inoculated with Nitragine™ and with IUNG inoculant proves that even ifR. leguminosarumare abundant, they may not be efficient in nodulation.

scholarly journals Population Genomics of Bacterial Plant Pathogens

2020 ◽  
pp. PHYTO-09-20-041
Author(s):  
Christina Straub ◽  
Elena Colombi ◽  
Honour C. McCann
Keyword(s):  
Plant Pathology ◽  
Open Access ◽  
Genetic Basis ◽  
Plant Pathogens ◽  
Bacterial Population ◽  
Population Genomics ◽  
Agricultural Practices ◽  
Critical Importance ◽  
Transmission Pathways ◽  
Open Access Article

Population genomics is transforming our understanding of pathogen biology and evolution, and contributing to the prevention and management of disease in diverse crops. We provide an overview of key methods in bacterial population genomics and describe recent work focusing on three topics of critical importance to plant pathology: (i) resolving pathogen origins and transmission pathways during outbreak events, (ii) identifying the genetic basis of host specificity and virulence, and (iii) understanding how pathogens evolve in response to changing agricultural practices. [Formula: see text] Copyright © 2020 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .

Microflora of Meloidogyne egg masses: species composition, population density and effect on the biocontrol agent Verticillium chlamydosporium (Goddard)

Nematology ◽  
2001 ◽  
Vol 3 (8) ◽  
pp. 729-734 ◽  
Author(s):  
C.J.(Hans) Kok ◽  
Artemis Papert ◽  
C.B.(Chula) Bok-A-Bin
Keyword(s):  
Bacterial Population ◽  
Biocontrol Agent ◽  
Bacterial Species ◽  
Antagonistic Activity ◽  
Parasitic Fungus ◽  
Egg Mass ◽  
Egg Masses ◽  
Soil Suppressiveness ◽  
Verticillium Chlamydosporium

AbstractEgg masses of Meloidogyne fallax from tomato and potato growing in soil from a nematode suppressive and a nonsuppressive field sustained bacterial population densities two to three orders of magnitude higher than those of the rhizosphere soil. BIOLOG metabolic profiling identified 16 bacterial species from egg masses. Results further indicated 20 species not listed in the BIOLOG database. 122 isolates of bacteria and 19 isolates of fungi from M. fallax or M. hapla were tested for in vitro antagonism against the nematode egg parasitic fungus Verticillium chlamydosporium: 23% of the bacteria and 74% of the fungi showed antagonistic activity. Pseudomonads showed an overall stronger antagonistic activity than the other bacteria. Our conclusions are that Meloidogyne egg masses are a densely populated microbial niche and that their microflora may well be an important factor in determining the success of nematode antagonists. However, we could not find a relationship between the egg mass microflora and differences in soil suppressiveness between the sample sites.

Deep learning with evolutionary and genomic profiles for identifying cancer subtypes

2019 ◽  
Vol 17 (03) ◽  
pp. 1940005 ◽  
Author(s):  
Chun-Yu Lin ◽  
Peiying Ruan ◽  
Ruiming Li ◽  
Jinn-Moon Yang ◽  
Simon See ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Deep Learning ◽  
Evolutionary Conservation ◽  
Core Gene ◽  
Breast Cancer Subtypes ◽  
Gene Set ◽  
Cancer Subtypes ◽  
The Core ◽  
Cancer Types ◽  
Core Genes

Cancer subtype identification is an unmet need in precision diagnosis. Recently, evolutionary conservation has been indicated to contain informative signatures for functional significance in cancers. However, the importance of evolutionary conservation in distinguishing cancer subtypes remains largely unclear. Here, we identified the evolutionarily conserved genes (i.e. core genes) and observed that they are primarily involved in cellular pathways relevant to cell growth and metabolisms. By using these core genes, we developed two novel strategies, namely a feature-based strategy (FES) and an image-based strategy (IMS) by integrating their evolutionary and genomic profiles with the deep learning algorithm. In comparison with the FES using the random set and the strategy using the PAM50 classifier, the core gene set-based FES achieved a higher accuracy for identifying breast cancer subtypes. The IMS and FES using the core gene set yielded better performances than the other strategies, in terms of classifying both breast cancer subtypes and multiple cancer types. Moreover, the IMS is reproducible even using different gene expression data (i.e. RNA-seq and microarray). Comprehensive analysis of eight cancer types demonstrates that our evolutionary conservation-based models represent a valid and helpful approach for identifying cancer subtypes and the core gene set offers distinguishable clues of cancer subtypes.

scholarly journals Isolation, Characterization, and Identification of Bacterial Population from Textile and Tannery Effluents of Bangladesh

2016 ◽  
Vol 29 (2) ◽  
pp. 84-88
Author(s):  
A Hakim ◽  
S Hoque ◽  
SM Ullah
Keyword(s):  
Bacterial Population ◽  
Bacterial Species ◽  
Bacterial Count ◽  
Rrna Gene ◽  
Bacterial Isolates ◽  
Tannery Effluents ◽  
Bacterial Composition ◽  
Degrading Bacteria ◽  
Diagnostic Characteristics ◽  
Metal Treatment

Ten effluent samples from two different sites located at Hazaribagh tannery belt and Dhaka EPZ, Savar were collected. This study aimed to compare the bacterial composition isolated from tannery and textile effluents and to investigate the occurrence of metal toxicity tolerant and dye degrading bacteria and to select the potential strains for the use in bioremediation. The average bacterial count of HT and DETDE varied in between 3.35×106 and 5.45×106 cfu/mL and 4.8×106 and 7.75×106cfu/mL, respectively. A total of 12 bacterial isolates were characterized as strains of Bacillus, Staphylococcus, and Pseudomonas. A few, however, were re-cultured on other recommended media for verification of diagnostic characteristics. Maximum numbers of bacterial species were isolated from textile effluent. The results showed that a Gram-positive bacillus with a yellow pigment was considered as a major group of the population. Among them three isolates were identified based on alignments of partial sequence of 16S rRNA gene. These are also being used in different wastewater and metal treatment plants all over the world.Bangladesh J Microbiol, Volume 29, Number 2, Dec 2012, pp 84-88

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