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340 results for “plasmid”
Data for: CRISPR spacers acquired from plasmids primarily target backbone genes, making them valuable for predicting potential hosts and host range
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Biofilm formation and plasmid-mediated quinolone resistance genes at varying quinolone inhibitory concentrations in quinolone-resistant bacteria superinfecting COVID-19 inpatients
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Preliminary phylogenetic and plasmid data for microbial laccase, fluorinase, dehalogenase, and glycyl radical enzymes
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Nanopore long reads enable the first complete genome assembly of a Malaysian Vibrio parahaemolyticus isolate bearing the pVa plasmid associated with acute hepatopancreatic necrosis disease
<p>Supplemental File 1: Main genome assemblies (Unpolished Flye assembly, Polished Flye assembly, Unicycler Hybrid Assembly and Unicycler Illumina-only assembly) generated in this study for comparison and their BUSCO output.</p> <p>Supplemental File 2: Phyre2 protein modelling output of the putative MVP1 TcdA toxin</p> <p>Supplemental File 3: Phyre2 protein modelling output of the putative MVP1 TcdB toxin</p> <p>Supplemental File 4: Phyre2 protein modelling output of the putative MVP1 TccC toxin</p> <p>Supplemental File 5: InterProScan output of the NCBI-predicted MVP1 proteome.</p> <p>Supplemental Table 1: NCBI BlastN output using the <em>fuc</em> genes of <em>Vibrio parahaemolyticus</em> MVP1 as the query to search against the Vibrio reference WGS database as of 21 Oct 2019</p>
Predicting plasmid contigs from assemblies using single copy marker genes, plasmid genes, kmers
<p>Introduction: Antimicrobial resistant (AMR) genes in bacteria are often carried on plasmids. Since these plasmids can spread the AMR genes between bacteria, it is important to know if the genes are located on highly transferable plasmids or in the more stable chromosomes. Whole genome sequence (WGS) analysis makes it easy to determine if a strain contains a resistance gene, however, it is not easy to determine if the gene is located on the chromosome or on a plasmid as genome sequence assembly generally results in 50-300 DNA fragments (contigs). With our newly developed prediction tool, we analyze the composition of these contigs to predict their likely source, plasmid or chromosomal. This information can be used to determine if a resistant gene is chromosomally located or on a plasmid. The tool is optimized for 19 different bacterial species, including Campylobacter, E. coli, and Salmonella, and can also be used for metagenomic assemblies.</p> <p>Methods: The tool identifies the number of chromosomal marker genes, plasmid replication genes and plasmid typing genes using CheckM and DIAMOND Blast, and determines pentamer frequencies and contig sizes per contig. A prediction model was trained using Random Forest on an extensive set of plasmids and chromosomes from 19 different bacterial species and validated on separate test sets of known chromosomal and plasmid contigs of the different bacteria. Results: Prediction of plasmid contigs was nearly perfect when calculated based on number of correctly predicted bases, with up to 99% specificity and 99% sensitivity. Prediction of small contigs remains difficult, since these contigs consists primarily of repeated sequences present in both plasmid and chromosome, e.g. transposases.</p> <p>Conclusion: The newly developed tool is able to determine if contigs are chromosomal or plasmid with a very high specificity and sensitivity (up to 99%) and can be very useful to analyze WGS data of bacterial genomes and their antimicrobial resistance genes.</p> <p>Plasmid databases can be downloaded from: http://klif.uu.nl/download/plasmid_db/</p> <p>Data used for training can be downloaded here: http://klif.uu.nl/download/plasmid_db/trainingsets2/</p>
Plasmid Design for Tunable Two‐Enzyme Co‐Expression Promotes Whole‐Cell Production of Cellobiose
<p>We provide underlying data for the publication "Plasmid design for tunable two-enzyme co-expression promotes whole-cell production of cellobiose". Please find the abstract below.</p> <p>Catalyst development for biochemical cascade reactions often follows a “whole cell approach” in which a single microbial cell is made to express all of the required enzyme activities. Although attractive in principle, the approach can encounter limitations when efficient overall flux from substrate to product necessitates precise balancing between the individual activities. Here, we show effective integration of major design strategies from synthetic biology to a coherent development of plasmid vectors enabling tunable two‐enzyme co‐expression in <em>E. coli </em>, for the purpose of whole‐cell production of cellobiose. Flux efficiency in the transformation of sucrose and glucose into cellobiose by a parallel (countercurrent) cascade of disaccharide phosphorylases requires the enzyme co‐expression cope with large differences in the specific activity of cellobiose phosphorylase (14 U mg<sup>−1</sup>) and sucrose phosphorylase (122 U mg<sup>−1</sup>). Comparing mono‐ and bicistronic co‐expression strategies, we analyze genetic elements controlling transcription, transcription‐translation coupling or plasmid replication for effect on activity, and also stable producibility, of the whole cell catalyst. We discover a key role of the <em>bom </em>(basis of mobility) site for plasmid stability dependent on the origin of replication and demonstrate the importance of RBS (ribosome binding site) strength for balanced bicistronic co‐expression. Whole cell catalysts show high specific rates (460 μmol cellobiose min<sup>−1</sup> g<sup>−1</sup> dry cells) and performance metrics (30 g L<sup>−1</sup>; ∼82% yield; 3.8 g L<sup>−1</sup> h<sup>−1</sup> overall productivity) promising for cellobiose production.</p>
Plasmid- and strain-specific factors drive variation in ESBL-plasmid spread in vitro and in vivo
<p>Horizontal gene transfer, mediated by conjugative plasmids, is a major driver of the global rise of antibiotic resistance. However, the relative contributions of factors that underlie the spread of plasmids and their roles in conjugation in vivo are unclear. To address this, we investigated the spread of clinical Extended Spectrum Beta-Lactamase (ESBL)-producing plasmids in the absence of antibiotics in vitro and in the mouse intestine. We hypothesised that plasmid properties would be the primary determinants of plasmid spread and that bacterial strain identity would also contribute. We found clinical Escherichia coli strains natively associated with ESBL-plasmids conjugated to three distinct E. coli strains and one Salmonella enterica serovar Typhimurium strain. Final transconjugant frequencies varied across plasmid, donor, and recipient combinations, with qualitative consistency when comparing transfer in vitro and in vivo in mice. In both environments, transconjugant frequencies for these natural strains and plasmids covaried with the presence/absence of transfer genes on ESBL-plasmids and were affected by plasmid incompatibility. By moving ESBL-plasmids out of their native hosts, we showed that donor and recipient strains also modulated transconjugant frequencies. This suggests that plasmid spread in the complex gut environment of animals and humans can be predicted based on in vitro testing and genetic data.</p>
A versatile plasmid architecture for mammalian synthetic biology (VAMSyB)
<p>Data underlying the figures in the publication “A versatile plasmid architecture for mammalian synthetic biology (VAMSyB)”, published in <em>Metabolic Engineering</em>, <strong>2021</strong>, 66, 41–50. <a href="https://doi.org/10.1016/j.ymben.2021.04.003">https://doi.org/10.1016/j.ymben.2021.04.003</a></p> <p>Table of contents:</p> <p><strong>1. Dataset 1</strong>; Excel file with the curated data underlying the figures.</p> <p><strong>Figure 1.</strong> (F) Comparison of promoters cloned in the tier-1 scaffold, including minimal promoters (PTKmin, Pmin, PCMVmin-2, PMLP, and PCMVmin-1) and constitutive promoters (PTK, PSV40, PmPGK1, PhCMV, PhEF1a, and PRPBSA) was assessed in terms of SEAP production. (G-H) Modulation of the rtTA-based tet-ON system with different (G) minimal promoters and (H) suppressor (TS) 5’UTR sequences or destabilizing ribozymes (sTRSV and env140) in the 3’UTR was assessed in terms of SEAP production.</p> <p><strong>Figure 2.</strong> (C-D) Expression characterization of each cassette of the tier-2 construct is tested by inserting expression cassettes controlled by the moderately strong phospho-glycerate kinase (PmPGK1) or strong human cytomegalovirus-derived (PhCMV) promoter. (C) Expression comparison of each cassette of the tier-2 construct tested individually was assessed in terms of Nluc production. (D) Characterization of interference between promoters of different strengths (PhCMV and PmPGK1) encoded in individual constructs or cloned into a single tier-2 construct. PhCMV expression was assessed in terms of SEAP production and PmPGK1 expression was assessed in terms of Nluc production. The reporters were transfected individually, cotransfected (+), or expressed from the same plasmid (|). (E) Characterization of interference between a constitutive promoter (PmPGK1) and an inducible promoter (PCRE). PmPGK1 driving firefly luciferase (Fluc) and a synthetic inducible cAMP-responsive (PCRE) promoter driving Nluc were cloned into different expression cassettes of a single tier-2 construct. Levels of Nluc activity are normalized to Fluc activity. (G-J) Generation of a single tier-2 construct encoding four different well-established synthetic gene switches: (G) the doxycycline-regulated rtTA system, (H) the doxycycline-regulated tTA system, (I) the vanillic acid-regulated VanA system, and (J) the phloretin-regulated TtgA system were all assessed in terms of SEAP production</p> <p> </p> <p><strong>Figure 3. </strong>(C) Characterization of polyclonal stable cell lines generated with the tier-3 PB and SB constructs encoding Tet-responsive inducible SEAP-p2A-iRFP670 in the first cassette (A1), constitutively expressed rtTA in the second cassette (A2), and constitutively expressed YPet-p2A-PuroR in the third cassette (A3) demonstrated dose-dependent induction of SEAP expression in response to doxycycline. (F) Characterization of polyclonal stable cell lines generated with the tier-3 lentiviral constructs encoding Tet-responsive inducible SEAP-p2A-iRFP670 in the first cassette (A1), constitutively expressed rtTA in the second cassette (A2), and constitutively expressed YPet-p2A-PuroR in the third cassette (A3) show dose-dependent induction of SEAP expression in response to doxycycline. (J) Characterization monoclonal lines generated with the CRISPR tier-3 constructs encoding Tet-responsive inducible SEAP-p2A-iRFP670 in the first cassette (A1), constitutively expressed rtTA in the second cassette (A2) show dose-dependent induction of SEAP expression in response to doxycycline.</p> <p> </p> <p><strong>Figure S1.</strong> Characterization of functional genetic elements that can reduce interference between promoters of different strengths (PhCMV and PmPGK1) encoded in a single tier-2 construct. PhCMV-driven expression was assessed in terms of SEAP production and PmPGK1-driven expression was assessed in terms of Nluc production. The reporters were transfected individually, cotransfected (+), or expressed from the same plasmid (|). Functional genetic elements, including a plasmid backbone spacer sequence [spacer], a synthetic poly(A) signal/transcriptional pause site derived from a commercial vector [pGL3], a co-transcriptional cleavage element [CoTC], a transcriptional termination sequence derived from the human β-globin gene [Tactb], or an insulator sequence consisting of two repeats of chicken hypersensitive site 4 [2xcHS4] were introduced directly 5’ of the PmPGK1-NLuc expression cassette encoded in either the (A) A2 or (B) A3 insertion site.</p> <p> </p> <p><strong>Figure S2. </strong>Selection of high-performing sub-populations derived from polyclonal stable cell lines generated with the tier-3 PiggyBac (PB; pcTS50), Sleeping Beauty (SB; pcTS51), or lentiviral (Lenti; pcVH38) construct as presented in Figure 3. The polyclonal stable cell lines were induced with doxycycline for 48 h and then sorted based on iRFP670 expression to isolated high-expressing clones. (A-B) The sorted PB generated sub-populations were assayed for (A) dose-dependent induction of SEAP, as well as (B) iRFP670 reporter mean fluorescence intensity (MFI) output in response to doxycycline. (D-E) The sorted SB generated sub-populations were assayed for (D) dose-dependent induction of SEAP expression, as well as (E) iRFP670 reporter MFI output in response to doxycycline. (G-H) The sorted lentiviral generated sub-population was assayed for (G) dose-dependent induction of SEAP expression, as well as (H) iRFP670 reporter MFI output in response to doxycycline.</p>
Data from: Ecological and genetic determinants of plasmid distribution in Escherichia coli
Bacterial plasmids are important carriers of virulence and antibiotic resistance genes. Nevertheless, little is known of the determinants of plasmid distribution in bacterial populations. Here the factors affecting the diversity and distribution of the large plasmids of Escherichia coli were explored in cattle grazing on semi-natural grassland, a set of populations with low frequencies of antibiotic resistance genes. Critically, the population genetic structure of bacterial hosts was chararacterized. This revealed structured E. coli populations with high diversity between sites and individuals but low diversity within cattle hosts. Plasmid profiles, however, varied considerably within the same E. coli genotype. Both ecological and genetic factors affected plasmid distribution: plasmid profiles were affected by site, E. coli diversity, E. coli genotype and the presence of other large plasmids. Notably 3/26 E. coli serotypes accounted for half the observed plasmid-free isolates indicating that within species variation can substantially affect carriage of the major conjugative plasmids. The observed population structure suggest that most of the opportunities for within species plasmid transfer occur between different individuals of the same genotype and support recent experimental work indicating that plasmid–host coevolution, and epistatic interactions on fitness costs are likely to be important in determining occupancy.
Data from: Hotspot mutations and ColE1 plasmids contribute to the fitness of Salmonella Heidelberg in poultry litter
Salmonella enterica subsp. enterica serovar Heidelberg (S. Heidelberg) is a clinically-important serovar linked to food-borne illness, and commonly isolated from poultry. Investigations of a large, multistate outbreak in the USA in 2013 identified poultry litter (PL) as an important extra-intestinal environment that may have selected for specific S. Heidelberg strains. Poultry litter is a mixture of bedding materials and chicken excreta that contains chicken gastrointestinal (GI) bacteria, undigested feed, feathers, and other materials of chicken origin. In this study, we performed a series of controlled laboratory experiments which assessed the microevolution of two S. Heidelberg strains (SH-2813 and SH-116) in PL previously used to raise 3 flocks of broiler chickens. The strains are closely related at the chromosome level, differing from the reference genome by 109 and 89 single nucleotide polymorphisms/InDels, respectively. Whole genome sequencing was performed on 86 isolates recovered after 0, 1, 7 and 14 days of microevolution in PL. Only strains carrying an IncX1 (37kb), 2 ColE1 (4 and 6kb) and 1 ColpVC (2kb) plasmids survived more than 7 days in PL. Competition experiments showed that carriage of these plasmids was associated with increased fitness. This increased fitness was associated with an increased copy number of IncX1 and ColE1 plasmids. Further, all Col plasmid-bearing strains had hotspot mutations in 37 loci on the chromosome and in 3 loci on the IncX1 plasmid. Additionally, we observed a decrease in susceptibility to tobramycin, kanamycin, gentamicin, neomycin and fosfomycin for Col plasmid-bearing strains. Our study demonstrates how positive selection from poultry litter can change the evolutionary path of S. Heidelberg.
Data files: A plasmid-based E. coli gene expression system with cell-to-cell variation below the extrinsic noise limit
<p>This zip archive contains flow cytometry data, microscopy data, and MATLAB code used to generate the figures in the submitted manuscript "A plasmid-based E. coli gene expression system with cell-to-cell variation below the extrinsic noise limit" (PONE-D-17-11810). Text files within the archive describe how to open files and which data corresponds to manuscript figures.</p>
Sequence-independent, site-specific incorporation of chemical modifications to generate light-activated plasmids (Source Data)
<p>Source data for Chemical Science paper "Sequence-independent, site-specific incorporation of chemical modifications to generate light-activated plasmids" DOI: 10.1039/D3SC02761A</p>
Single-Molecule FRET-Resolved Protein Dynamics - from Plasmid to Data in Six Steps
<p>SmFRET trace files of 58 yeast Hsp90 molecules (in presence of AMP-PNP) containing raw intensity values through time of acceptor emission after acceptor excitation (r_r_*), donor emission after donor excitation (o_g_*), and acceptor emission after donor excitation (r_g_*).</p>
Sequence and functional analyses of native plasmids from plant pathogenic Gammaproteobacteria: comparative genomics, conjugative mobilization and fitness effects
<p>These data tables are part of the Supplementary Material for Chapter I of the thesis titled <em>"Sequence and Functional Analyses of Native Plasmids from Plant-Pathogenic Gammaproteobacteria: Comparative Genomics, Conjugative Mobilization, and Fitness Effects."</em></p>
Plasmid database (Gradient Boosting model construction)
<p>Plasmid database used for the training and testing of the Gradient Boosting model. Plasmids present in the samples used for this step were removed from the database.</p>
Plasmid sequence of cpX
<p>Sequence of plasmid </p>
Phenotype evaluation rawdata of Acinetobacter baumannii harboring chromosomal parallel mutations or an evolved plasmid
<p>OXA-23 is the predominant carbapenemase in carbapenem-resistant <em>Acinetobacter baumannnii</em>. The co-evolutionary dynamics of <em>A. baumannii</em> and OXA-23-encoding plasmids are poorly understood. Here, we transformed <em>A. baumannnii</em> ATCC 17978 with pAZJ221, a <em>bla</em><sub>OXA-23</sub>-containing plasmid from a clinical <em>A. baumannnii</em> isolate A221, and subjected the transformant to experimental evolution in the presence of a sub-inhibitory concentration of imipenem for nearly 400 generations. We used population sequencing to track genetic changes at six time-points and evaluated phenotypic changes. Increased fitness of evolving populations, temporary duplication of <em>bla</em><sub>OXA-23</sub> in pAZJ221, interfering allele dynamics, and chromosomal locus-level parallelism were observed. To characterize genotype-to-phenotype associations, we focused on six mutations in parallel targets predicted to affect small RNAs and a cyclic dimeric (3'→5') GMP-metabolizing protein. Six isogenic mutants with or without pAZJ221 were engineered to test for the causal effects of these mutations on fitness costs and plasmid kinetics, the evolved plasmid containing two copies of <em>bla</em><sub>OXA-23</sub> was transferred to ancestral ATCC 17978. Five of the six mutations contributed to improved fitness in the presence of pAZJ221 under imipenem pressure, and all but one of them impaired plasmid conjugation ability. The duplication of <em>bla</em><sub>OXA-23</sub> contributed to host fitness under carbapenem pressure but imposed a burden on the host in antibiotic-free media relative to the unevolved pAZJ221. Overall, our study provides a framework for the co-evolution of <em>A. baumannii</em> and a clinical blaOXA-23-containing plasmid, involving early <em>bla</em><sub>OXA-23</sub> duplication followed by chromosomal adaptations.</p>
Comprehensive discovery of CRISPR-targeted terminally redundant sequences in the human gut metagenome: viruses, plasmids, and more
<p>Supplementary Table 2-1. Samples and assembly summary <br> Supplementary Table 2-2. CRISPR-targeted TR sequence summary</p>
Data from: Conjugative plasmid transfer is limited by prophages but can be overcome by high conjugation rates
<p><span><span><span><span>Antibiotic resistance spread via plasmids is a serious threat to successfully fight infections and makes understanding plasmid transfer in nature crucial to prevent the rise of antibiotic resistance. Studies addressing the dynamics of plasmid conjugation have yet neglected one omnipresent factor: prophages (viruses integrated into bacterial genomes), whose activation can kill host and surrounding bacterial cells. To investigate the impact of prophages on conjugation, we combined experiments and mathematical modelling. Using <em>E. coli</em>, prophage lambda and the multidrug-resistant plasmid RP4 we find that prophages can substantially limit the spread of conjugative plasmids. This inhibitory effect was strongly dependent on environmental conditions and bacterial genetic background. Our empirically parameterized model reproduced experimental dynamics of cells acquiring either the prophage or the plasmid well but failed to predict the number of cells acquiring both elements. This suggests more complex interactions between conjugative plasmids and prophages in sequential infections. Varying phage and plasmid infection parameters over empirically realistic ranges revealed that plasmids can overcome the negative impact of prophages through high conjugation rates. Overall, the presence of prophages introduces an additional death rate for plasmid carriers, the magnitude of which is determined in non-trivial ways by the environment, the phage and the plasmid.</span></span></span></span></p>
A tale of two plasmids: contributions of plasmid associated phenotypes to epidemiological success among Shigella
Dissemination of antimicrobial resistance (AMR) genes by horizontal gene transfer (HGT) mediated through plasmids is a major global concern. Genomic epidemiology studies have shown varying success of different AMR plasmids during outbreaks, but the underlying reasons for these differences are unclear. Here, we investigated two Shigella plasmids (pKSR100 and pAPR100) that circulated in the same transmission network but had starkly contrasting epidemiological outcomes to identify plasmid features that may have contributed to the differences. We used plasmid comparative genomics to reveal divergence between the two plasmids in genes encoding AMR, SOS response alleviation, and conjugation. Experimental analyses revealed that these genomic differences corresponded with reduced conjugation efficiencies for the epidemiologically successful pKSR100, but more extensive AMR, reduced fitness costs, and a reduced SOS response in the presence of antimicrobials, compared with the less successful pAPR100. The discrepant phenotypes between the two plasmids are consistent with the hypothesis that plasmid associated phenotypes contribute to determining the epidemiological outcome of AMR HGT and suggest that phenotypes relevant in responding to antimicrobial pressure and fitness impact may be more important than those around conjugation in this setting. Plasmid phenotypes could thus be valuable tools in conjunction with genomic epidemiology for predicting AMR dissemination.
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