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2,180 results for “Recombination”
Recombinant Expression and Chemical Amidation of Isotopically Labeled Native Melittin
<p><strong>Table S1. </strong>Amidated cationic membrane-lytic and antimicrobial peptides. There are myriad cationic membrane-lytic and antimicrobial peptides consisting of a C-terminal amidation post-translational modification that are of high interest to researchers and which our recombinant expression followed by chemical amidation could be immediately applied to. Below is a short representative list of such peptides.</p> <p><strong>Table S2</strong>. Melittin backbone chemical shifts (ppm). Deuterium isotope shift corrections were applied to all chemical shifts and pressure corrections were applied to the pressure denatured monomer chemical shifts. All shifts were measured on a 1.0-mM <sup>2</sup>H,<sup>13</sup>C,<sup>15</sup>N-labeled melittin sample in 25-mM potassium phosphate buffer, pH 7.0, 50-mM NaCl, 3% D2O. The folded tetramer peaks were measured at atmospheric pressure, while the pressure denatured monomer resonances were measured at 2.25 kbar. </p> <p><strong>Table S3.</strong> Melittin experimental <sup>15</sup>N-<sup>1</sup>H isotropic J-couplings, (J+<em><sup>1</sup>D<sub>NH</sub></em>) anisotropic couplings and <em><sup>1</sup>D<sub>NH</sub></em> residual dipolar couplings. All couplings and errors are reported in Hz. Isotropic J-couplings were not measured for G3 and A4. In these cases, an average J-coupling of -93.3 Hz was used with an uncertainty of 1.1 Hz..</p> <p><strong>Table S4</strong>. Analysis of the AlphaFold-Multimer structural models with respect to the melittin RDCs measured with the Pf1 alignment media. SVD fitting of the RDC alignment tensor parameters was done for residues 3-23 in the AF-M models and residues 3-25 in the 2MLT crystal structure. The AF-M model confidence score is a prediction of the similarity between the AF-M model and the true oligomeric structure. The RMSD listed in the final column is the backbone RMSD between the AF-M structural models and the 2MLT X-ray crystal structure tetramer for residues 1-23.</p> <p><strong>Table S5</strong>. Analysis of the AlphaFold-Multimer structural models with respect to the melittin RDCs measured with a stretched polyacrylamide gel alignment media. SVD fitting of the RDC alignment tensor parameters was done for residues 4-23 in the AF-M models and residues 4-25 in the 2MLT crystal structure. The AF-M model confidence score is a prediction of the similarity between the AF-M model and the true oligomeric structure. The RMSD listed in the final column is the backbone RMSD between the AF-M structural models and the 2MLT X-ray crystal structure tetramer for residues 1-23.</p> <p><strong>Table S6.</strong> RDC based ranking of melittin AlphaFold-Multimer structural models and the 2MLT crystal structure. Models are ranked according to the average Q factor in the two alignment media used in this study: Pf1 and a positively charged stretched polyacrylamide gel. The AF-M model confidence score is a prediction of the similarity between the AF-M model and the true oligomeric structure. The RMSD listed in the final column is the backbone RMSD between the AF-M structural models and the 2MLT X-ray crystal structure tetramer for residues 1-23.</p> <p> <strong>Table S7</strong>. 2MLT crystal structure and AlphaFold-Multimer atomic coordinates. The X-ray crystal structure was retrieved from the protein data bank (PDB), then it was symmetry expanded into a tetramer, residues were renumbered as described in <em>3.3.3 Comparison of <sup>1</sup>D<sub>NH</sub> couplings with the crystal structure and AlphaFold-Multimer model,</em> and finally protons were added to the structure with DYNAMO. The C-terminus column lists the C-terminal modifications for the AF-M structures in comparison to melittin’s native -CONH<sub>2</sub> C-terminus. </p> <p>Atomic coordinates in the form of .pdb files for all RDC SVD fitting done in this study:</p> <table> <tbody> <tr> <td>2mlt.pdb</td> </tr> <tr> <td>af1.pdb</td> </tr> <tr> <td>af2.pdb</td> </tr> <tr> <td>af3.pdb</td> </tr> <tr> <td>af4.pdb</td> </tr> <tr> <td>af5.pdb</td> </tr> <tr> <td>afd1.pdb</td> </tr> <tr> <td>afd2.pdb</td> </tr> <tr> <td>afd3.pdb</td> </tr> <tr> <td>afd4.pdb</td> </tr> <tr> <td>afd5.pdb</td> </tr> <tr> <td>afg1.pdb</td> </tr> <tr> <td>afg2.pdb</td> </tr> <tr> <td>afg3.pdb</td> </tr> <tr> <td>afg4.pdb</td> </tr> <tr> <td>afg5.pdb</td> </tr> <tr> <td>afk1.pdb</td> </tr> <tr> <td>afk2.pdb</td> </tr> <tr> <td>afk3.pdb</td> </tr> <tr> <td>afk4.pdb</td> </tr> <tr> <td>afk5.pdb</td> </tr> <tr> <td>afr1.pdb</td> </tr> <tr> <td>afr2.pdb</td> </tr> <tr> <td>afr3.pdb</td> </tr> <tr> <td>afr4.pdb</td> </tr> <tr> <td>afr5.pdb</td> </tr> </tbody> </table> <p> </p>
Sexual recombination and temporal gene flow maintain host resistance and genetic diversity
<p>Infectious disease can threaten host populations. Hosts can rapidly evolve resistance during epidemics, with this evolution often modulated by fitness trade-offs (e.g., between resistance and fecundity). However, many organisms switch between asexual and sexual reproduction, and this shift in reproductive strategy can also alter how resistance in host populations persists through time. Recombination can shuffle alleles selected for during an asexual phase, uncoupling the combinations of alleles that facilitated resistance to parasites and altering the distribution of resistance phenotypes in populations. Furthermore, in host species that produce diapausing propagules (e.g., seeds, spores, or resting eggs) after sex, accumulation of propagules into and gene flow out of a germ bank introduce allele combinations from past populations. Thus, recombination and gene flow might shift populations away from the trait distribution reached after selection by parasites. To understand how recombination and gene flow alter host population resistance, we tracked the genotypic diversity and resistance distributions of two wild populations of cyclical parthenogens. In one population, resistance and genetic diversity increased after recombination whereas, in the other, recombination did not shift already high resistance and genetic diversity. In both lakes, resistance remained high after temporal gene flow. This observation surprised us: due to costs to resistance imposed by a fecundity-resistance trade-off, we expected that high population resistance would be a transient state that would be eroded through time by recombination and gene flow. Instead, low resistance was the transient state, while recombination and gene flow re-established or maintained high resistance to this virulent parasite. We propose this outcome may have been driven by the joint influence of fitness trade-offs, genetic slippage after recombination, and temporal gene flow via the egg bank.</p>
Data from: Recombination as an enforcement mechanism of prosocial behavior in cooperating bacteria
<p>Prosocial behavior is ubiquitous despite the relative fitness costs carried by cooperative individuals. However, the stability of cooperation in populations is fragile, and often maintained through enforcement. We propose that homologous recombination provides such a mechanism in bacteria. Using an agent-based model of recombination in a population of bacteria playing a public goods game, we demonstrate how changes in recombination rate affect the proportion of cooperating cells. In our model, recombination converts cells to a different strategy, either freeloading (cheaters) or cooperation, based on the strategies of neighboring cells and the recombination rate. Increasing the recombination rate expands the parameter space in which cooperators dominate freeloaders. However, increasing the recombination rate alone is neither sufficient nor necessary. Intermediate benefits of cooperation, lower population viscosity, and higher population size can promote cooperation in a population of cheater strains. Our findings demonstrate how recombination influences the persistence of cooperative behavior in bacteria. </p>
Large mass hierarchies from strongly-coupled dynamics---Recombined data release
<p>This release contains data associated with the publication <a href="https://arxiv.org/abs/1605.04258">Large mass hierarchies from strongly-coupled dynamics</a> (<a href="https://doi.org/10.1007/JHEP06(2016)114">JHEP 06 (2016) 114</a>).</p> <p>Compared to <a href="https://doi.org/10.5281/zenodo.13128485">the raw data release</a>, it makes the following changes:</p> <ul> <li>The two CSV files present in <a href="https://doi.org/10.5281/zenodo.13128485">the raw data release</a> are combined, with a common column schema. Since not all data were retained from all steps of the original computation, some of these data have been recomputed.</li> <li>The lattice data plotted in Figs. 2 and 3 of <a href="https://doi.org/10.1007/JHEP06(2016)114">the paper</a> are also included, and plotted by the Mathematica notebook.</li> </ul> <p>It comprises five files:</p> <ul> <li><code>README.md</code>: containing this summary and further details of the contents of each file.</li> <li><code>su2_adjoint_lattice_data.csv</code>: the data for the points plotted in Figures 2 and 3 of <a href="https://doi.org/10.1007/JHEP06(2016)114">the paper</a>. Masses of the scalar and tensor glueball, extracted from Monte Carlo ensembles of SU(2) with adjoint fermions.</li> <li><code>sigmamodel.csv</code>: the data shown in Figures 4 and 5 of <a href="https://doi.org/10.1007/JHEP06(2016)114">the paper</a>. The mass of the composite spin-0 and spin-2 states, computed for , as a function of , normalised to the mass of the lightest scalar or tensor.</li> <li><code>DataRelease.nb</code>: A Mathematica notebook that will take the above three files and generate plots similar to thsoe shown in <a href="https://doi.org/10.1007/JHEP06(2016)114">the paper</a>. This has been tested using Mathematica 14.0.</li> <li><code>unify_lmh_2016.zip</code>: A Snakemake and Python workflow to take the data from <a href="https://doi.org/10.5281/zenodo.13128485">the raw data release</a>, some data released as part of <a href="https://doi.org/10.5281/zenodo.12802810">the analysis workflow for arXiv:2408.00171</a>, and some previously unpublished data included in the archive, and generate the two CSV files above. Includes a <code>README.md</code> file containing more information about how to run the workflow.</li> </ul>
A Study to Learn if Recombinant Human Parathyroid Hormone [rhPTH(1-84)] Can Improve Symptoms and Metabolic Control in Adults With Hypoparathyroidism (BALANCE)
ClinicalTrials.gov study NCT03324880. IPD Sharing: YES. Countries: 13. Publications: 1.
Study of Recombinant Protein Vaccines With Adjuvant as a Primary Series and as a Booster Dose Against COVID-19 in Adults 18 Years of Age and Older
ClinicalTrials.gov study NCT04762680. IPD Sharing: YES. Countries: 7. Publications: 2.
Study With Quadrivalent Recombinant Influenza Vaccine (RIV4) in Participants 9 Through 49 Years of Age.
ClinicalTrials.gov study NCT05513053. IPD Sharing: YES. Countries: 4. Publications: 1.
A Study of PEGylated Recombinant Factor VIII (BAX855) in Previously Untreated Young Children With Severe Hemophilia A
ClinicalTrials.gov study NCT02615691. IPD Sharing: YES. Countries: 23. Publications: 1.
A Study of Rucaparib Versus Physician's Choice of Therapy in Participants With Metastatic Castration-resistant Prostate Cancer and Homologous Recombination Gene Deficiency
ClinicalTrials.gov study NCT02975934. IPD Sharing: YES. Countries: 12. Publications: 3.
Pharmacokinetics, Safety and Efficacy of Recombinant Von Willebrand Factor (rVWF) in the Treatment of Bleeding Episodes in Von Willebrand Disease (VWD)
ClinicalTrials.gov study NCT01410227. IPD Sharing: YES. Countries: 16. Publications: 1.
Efficacy and Safety Study of a Recombinant Protein-Free Manufactured Factor VIII (rAHF-PFM) in Previously Untreated Hemophilia A Patients
ClinicalTrials.gov study NCT00157157. IPD Sharing: YES. Countries: 10. Publications: 2.
Study Describing the Immunogenicity and Safety of Quadrivalent Recombinant Influenza Vaccine (RIV4) Versus a Licensed Quadrivalent-inactivated Influenza Vaccine (IIV4) (Fluarix® Quadrivalent) in Parti
ClinicalTrials.gov study NCT05144945. IPD Sharing: YES. Countries: 1. Publications: 1.
Study of Recombinant Protein Vaccine Formulations Against COVID-19 in Healthy Adults 18 Years of Age and Older
ClinicalTrials.gov study NCT04537208. IPD Sharing: YES. Countries: 1. Publications: 2.
A Phase 3 Open-label Interventional Study of Intravenous Recombinant Coagulation Factor VIII Fc-von Willebrand Factor-XTEN Fusion Protein, Efanesoctocog Alfa (BIVV001), in Patients With Severe Hemophi
ClinicalTrials.gov study NCT04161495. IPD Sharing: YES. Countries: 19. Publications: 5.
Immunogenicity and Safety of Dengue Tetravalent Vaccine (TDV) and Recombinant 9-valent Human Papillomavirus Vaccine (9vHPV) in Participants Aged ≥9 to <15 Years
ClinicalTrials.gov study NCT04313244. IPD Sharing: YES. Countries: 1. Publications: 3.
A Safety, Tolerability, and Pharmacokinetics Study of a Single Intravenous Injection of Recombinant Coagulation Factor VIII Fc - Von Willebrand Factor - XTEN Fusion Protein (rFVIIIFc-VWF-XTEN) (BIVV00
ClinicalTrials.gov study NCT03205163. IPD Sharing: YES. Countries: 2. Publications: 1.
A Study of Rucaparib in Patients With Metastatic Castration-resistant Prostate Cancer and Homologous Recombination Gene Deficiency
ClinicalTrials.gov study NCT02952534. IPD Sharing: YES. Countries: 12. Publications: 4.
Study of Monovalent and Bivalent Recombinant Protein Vaccines Against COVID-19 in Adults 18 Years of Age and Older
ClinicalTrials.gov study NCT04904549. IPD Sharing: YES. Countries: 11. Publications: 1.
A Open-label Study Investigating the Safety and Tolerability of NPSP558, a Recombinant Human Parathyroid Hormone (rhPTH [1-84]), for the Treatment of Adults With Hypoparathyroidism - A Clinical Extens
ClinicalTrials.gov study NCT01297309. IPD Sharing: YES. Countries: 1. Publications: 5.
Study Investigating a PEGylated Recombinant Factor VIII (BAX 855) for Hemophilia A (PROLONG-ATE Study)
ClinicalTrials.gov study NCT01736475. IPD Sharing: YES. Countries: 20. Publications: 1.
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