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30 results for “Strain Evolution”
Fabric evolution and strain localisation in inherently anisotropic specimens of anisometric particles under triaxial compresion
<p>This repository contains the data and processed results of the work "<em>Fabric evolution and strain localisation in inherently anisotropic specimens of anisometric particles (lentils) under triaxial compression</em>", published in Granular Matter (https://link.springer.com/article/10.1007/s10035-022-01305-8).</p> <p>The study analyses five triaxial compression tests on cylindrical specimens made up of more than nine thousand lentils. Each specimen is prepared with a characteristic orientation (the orientation of the mould for the deposition of the lentils). Repeated x-ray tomography scanning is performed during deviatoric loading, and each scanned step is reconstructed into a 3D volume. Particles are identified in the first 3D volume (in the form of a labelled image) and tracked from the first image all the way through the test using a novel tracking algorithm, enabling the measurement of particle and contact fabric evolution, as well as strain localisation within the specimens. All the procesing is performed using <a href="https://ttk.gricad-pages.univ-grenoble-alpes.fr/spam/intro.html">spam</a> (https://ttk.gricad-pages.univ-grenoble-alpes.fr/spam/intro.html) software.</p> <p> </p> <p>The <em>Readme.md</em> file contains further details on the experimental campaign, and the structure of the repository. Please refer to the paper "<em>Fabric evolution and strain localisation in inherently anisotropic specimens of anisometric particles under triaxial compression</em>" published on<em> Granular Matter</em> for further details not found on the <em>Readme.md </em>file . Additional information/data not included in this repository is available upon request.</p>
Supplementary Data for Progressive Strain Localization with Structural Evolution of Faults and Implications for Earthquake Characteristics
<p>Fault slip measurements from geodetic imaging data (pixel offsets and InSAR) for 16 strike-slip earthquakes. </p> <p>Data columns are: Longitude, Latitude, Fault Slip (meters), 1-sigma uncertainty (meters)</p>
Strain Evolution in 2D-Digital Composites-T= 1-15 time steps.
<p>Strain Evolution in 2D - Digital Composites for first 15 time steps.</p> <p>Abaqus simulation script can be found <a href="https://github.com/M3RG-IITD/StrainEvolution">here</a></p>
Data from: Phylogenomic analysis of Wolbachia strains reveals patterns of genome evolution and recombination
<p><i>Wolbachia</i> are widespread intracellular bacteria that mediate many important biological processes in arthropod species. In this study, we identified 210 conserved single-copy genes in 33 genome-sequenced <i>Wolbachia</i> strains in the A, B, C, D, E and F supergroups. Phylogenomic analysis with these core genes indicate that all 33 <i>Wolbachia</i> strains maintain the supergroup relationship classified previously based on the multilocus sequence typing (MLST) genes. Using an interclade recombination screening method, 14 inter-supergroup recombination events were discovered in six genes (2.9%) among 210 single copy orthologs. This finding suggests a relatively low frequency of intergroup recombination. Interestingly, they have occurred not only between A and B supergroups (9 events), but also between A and E supergroups (5 events). Maintenance of such transfers suggests possible roles in <i>Wolbachia</i> infection related functions. Comparisons of strain divergence using the five genes of the MLST system show a high correlation (Pearson correlation coefficient r = 0.98) between MLST and whole genome divergences, indicating that MLST is a reliable method for identifying related strains when whole genome data are not available. The phylogenomic analysis and the identified core gene set in our study will serve as a valuable foundation for strain identification and the investigation of recombination and genome evolution in <i>Wolbachia</i>.</p>
Data for "Shear Strain Evolution Spanning the 2020 Mw6.8 Elazığ and 2023 Mw7.8/Mw7.6 Kahramanmaraş Earthquake Sequence along the East Anatolian Fault Zone" manuscript
<p>Data necessary to support the analysis presented in "Shear Strain Evolution Spanning the 2020 Mw6.8 Elazığ and 2023 Mw7.8/Mw7.6 Kahramanmaraş Earthquake Sequence along the East Anatolian Fault Zone" manuscript</p>
Phenotypic, genetic, and epigenetic data from 29 Serratia marcescens strains from an evolution experiment
<p>This dataset contains phenotypic, genetic, and epigenetic data from 29 <em>Serratia marcescens</em> strains from an evolution experiment. In a previous study (https://doi.org/10.1111/evo.12148), the bacterium <em>S. marcescens</em> was left to evolve from a common ancestor culture in replicated populations kept under different temperature regimes, and evolved clones were isolated and their phenotypes measured. Here, we randomly selected 28 evolved clones from this experiment, as well as the original reference strain, and used PacBio single molecule real-time (SMRT) sequencing to obtain genetic and epigenetic (N6-methyladenine modifications, m6A) data. The goal of our study was to obtain a detailed description of the methylation landscape of <em>S. marcescens</em> and to examine the potential contributions of genetic and epigenetic changes to phenotypic adaptation.</p>
Phenotypic, genetic, and epigenetic data from 29 Serratia marcescens strains from an evolution experiment
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Data from: Phylogenomic analysis of Wolbachia strains reveals patterns of genome evolution and recombination
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Data from: Comparative genomic analysis of nine Sphingobium strains: insights into their evolution and Hexachlorocyclohexane (HCH) degradation pathways
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Assemblies for 'Mixed strain pathogen populations accelerate the evolution of antibiotic resistance in patients'
<p>Antibiotic resistance poses a global health threat, but the within-host drivers of resistance remain poorly understood. Pathogen populations are often assumed to be clonal within hosts, and resistance is thought to emerge due to selection for de novo variants. Here we show that mixed strain populations are common in the opportunistic pathogen <i>P. aeruginosa</i>. Crucially, resistance evolves rapidly in patients colonized by multiple strains through selection for pre-existing resistant strains. In contrast, resistance evolves sporadically in patients colonized by single strains due to selection for novel resistance mutations. However, strong trade-offs between resistance and growth rate occur in mixed strain populations, suggesting that within-host diversity can also drive the loss of resistance in the absence of antibiotic treatment. In summary, we show that the within-host diversity of pathogen populations plays a key role in shaping the emergence of resistance in response to treatment.</p>
Supplementary Information for "Evolution upon leather manufacturing: comparison of the two Halobacterium salinarum strains isolated in the early 20-th century with the twin laboratory strains NRC-1 and R1"
<p>This set of files contains Supplementary Data associated with the emerging manuscript "Evolution upon leather manufacturing: comparison of the two <em>Halobacterium salinarum</em> strains isolated in the early 20-th century with the twin laboratory strains NRC-1 and R1." by Friedhelm Pfeiffer and Mike Dyall-Smith.</p> <p>The manuscript provides a detailed comparison of the complete genome sequences from four strains of <em>Halobacterium salinarum</em>:<br> 91-R6 (NRC 34002, the type strain of <em>Halobacterium salinarum</em>);<br> 63-R2 (NRC 34001, a strain originally reported as 'cutirubra');<br> NRC-1 and R1 (two laboratory strains).</p> <p>“Supplementary Methods” extends the Methods section of the manuscript, providing additional detail.</p> <p>“Supplementary Text S1” provides additional detail for the comparison of the chromosome from strain 63-R2 to those from strains NRC-1 and R1.</p> <p>“Supplementary Text S2” provides additional details for the comparison of the chromosomes from strains 63-R2 and 91-R6.</p> <p>“Supplementary Text S3” provides additional detail for the comparison of the plasmids from strain 63-R2 to those from strains NRC-1 and R1.</p> <p> </p> <p>“Supplementary Table S4” correlates positions from “core” sequences (devoid of strain-specific mobile genetic elements) to the original genome sequences.</p>
Seasonality and strain specificity drive rapid co-evolution in a Ostreococcus-virus system from the Western Baltic Sea
<p>Marine viruses are a major driver of phytoplankton mortality and thereby influence biogeochemical cycling of carbon and other nutrients. Phytoplankton-targeting viruses are important components of ecosystem dynamics, but broad-scale experimental investigations of host-virus interactions remain scarce. Here, we investigated in detail a picophytoplankton (size 1 µm) host’s responses to infections by species-specific viruses from distinct geographical regions and different sampling seasons. Specifically, we used <em>Ostreococcus tauri </em>and<em> O. mediterraneus</em> and their viruses (size ca. 100 nm). <em>Ostreococcus</em> sp. are globally distributed and, like other picoplankton species, play an important role in coastal ecosystems at certain times of the year. Further,<em> Ostreococcus</em> sp. are model organisms, and the <em>Ostreococcus</em>-virus system is well-known in marine biology. However, only few studies have researched its evolutionary biology and the implications thereof for ecosystem dynamics. The <em>Ostreococcus</em> strains used here stem from different regions of the Southwestern Baltic Sea that vary in salinity and temperature and were obtained during several cruises spanning different sampling seasons. Using an experimental cross-infection set-up, we explicitly confirm species and strain specificity in <em>Ostreococcus</em> sp. from the Baltic Sea. Moreover, we found the timing of virus-host co-existence, was driver of infection patterns as well. In combination, these findings prove that host-virus co-evolution can be rapid in natural systems.</p>
Data from: Comparative genomic analysis of nine Sphingobium strains: insights into their evolution and hexachlorocyclohexane (HCH) degradation pathways
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Data from: Experimental evolution with a multicellular host causes diversification within and between microbial parasite populations – differences in emerging phenotypes of two different parasite strains
Host-parasite coevolution is predicted to have complex evolutionary consequences, potentially leading to the emergence of genetic and phenotypic diversity for both antagonists. However, little is known about variation in phenotypic responses to coevolution between different parasite strains exposed to the same experimental conditions. We infected Caenorhabditis elegans with one of two strains of Bacillus thuringiensis and either allowed the host and the parasite to experimentally coevolve (coevolution treatment) or allowed only the parasite to adapt to the host (one-sided parasite adaptation). By isolating single parasite clones from evolved populations, we found phenotypic diversification of the ancestral strain into distinct clones, which varied in virulence towards ancestral hosts and competitive ability against other parasite genotypes. Parasite phenotypes differed remarkably not only between the two strains, but also between and within different replicate populations, indicating diversification of the clonal population caused by selection. This study highlights that the evolutionary selection pressure mediated by a multicellular host causes phenotypic diversification, but not necessarily with the same phenotypic outcome for different parasite strains.
Data from: Experimental evolution of Legionella pneumophila in mouse macrophages leads to strains with altered determinants of environmental survival
The Gram-negative bacterium, Legionella pneumophila, is a protozoan parasite and accidental intracellular pathogen of humans. We propose a model in which host cycling through multiple protozoan hosts in the environment holds L. pneumophila in a state of evolutionary stasis as a broad host-range pathogen. Using an experimental evolution approach, we tested this hypothesis by restricting L. pneumophila to growth within mouse macrophages for hundreds of generations. Whole-genome resequencing and high-throughput genotyping identified several parallel adaptive mutations and population dynamics that led to improved replication within macrophages. Based on these results, we provide a detailed view of the population dynamics of an experimentally evolving bacterial population, punctuated by frequent instances of transient clonal interference and selective sweeps. Non-synonymous point mutations in the flagellar regulator, fleN, resulted in increased uptake and broadly increased replication in both macrophages and amoebae. Mutations in multiple steps of the lysine biosynthesis pathway were also independently isolated, resulting in lysine auxotrophy and reduced replication in amoebae. These results demonstrate that under laboratory conditions, host restriction is sufficient to rapidly modify L. pneumophila fitness and host range. We hypothesize that, in the environment, host cycling prevents L. pneumophila host-specialization by maintaining pathways that are deleterious for growth in macrophages and other hosts.
Data for "Evolution upon leather manufacturing: comparison of the two Halobacterium salinarum strains isolated in the early 20-th century with the twin laboratory strains NRC-1 and R1"
<p>This set of files contains data associated with the emerging manuscript<br> "Evolution upon leather manufacturing: comparison of the two<br> Halobacterium salinarum strains isolated in the early 20-th century<br> with the twin laboratory strains NRC-1 and R1."<br> by Friedhelm Pfeiffer and Mike Dyall-Smith.</p> <p>The manuscript provides a detailed comparison of the complete genome<br> sequences from four strains of Halobacterium salinarum:<br> 91-R6 (NRC 34002, the type strain of Halobacterium salinarum);<br> 63-R2 (NRC 34001, a strain originally reported as 'cutirubra');<br> NRC-1 and R1 (two laboratory strains).</p> <p>A detailed comparison of the complete genome sequences of three strains<br> (excluding 63-R2) has been previously reported:<br> Microbiologyopen (2020) 9: e974 (doi: 10.1002/mbo3.974; PMID:31797576).</p> <p>The 'seq_' series of files contains newly reported sequences of<br> episomal plasmids (pHcu190, pHcu229) and plasmid integrants into<br> the chromosome (contigDRAFT1, contigDRAFT2) from strain 63-R2.</p> <p>There are two versions for pHcu229, as this plasmid could only<br> be partially assembled (_asAssembled, 170458 bp) but could be<br> completed in silico (_inSilicoCompleted, 229124 bp).</p> <p>The 'tagMGE_' series of files contains the sequences of all<br> replicons (the main chromosome and all plasmids) with markup<br> of all mobile genetic elements (MGEs) for each of the<br> four strains of Halobacterium salinarum.</p> <p>The file dbHsAllStrainsTotal.fasta contains the complete sequences<br> of the chromosomes and plasmids in a single file.</p> <p>The dbHsAllStrainsCore.fasta contains the same set of sequences but<br> with strain-specific copies of mobile genetic elements removed. This<br> version was generated to facilitate inter-strain sequence comparison.<br> </p>
Data from: Experimental evolution with a multicellular host causes diversification within and between microbial parasite populations – differences in emerging phenotypes of two different parasite strains
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Data from: Experimental evolution of Legionella pneumophila in mouse macrophages leads to strains with altered determinants of environmental survival
Open the record for dataset details and reuse information.
HT-SuperSAGE of the gut tissue of a Vip3A-resistant Heliothis virescens F. (Lepidoptera: Noctuidae) strain provides insights into its evolution and toxin adaptation
GEO Series GSE72228. Heliothis virescens. 2 samples. Type: Expression profiling by high throughput sequencing.
Repairing growth of a genome-reduced strain using adaptive laboratory evolution and targeted gene knock-in
GEO Series GSE221155. Escherichia coli. 61 samples. Type: Expression profiling by high throughput sequencing.
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OpenNeuro
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