Strange India All Strange Things About India and world


  • 1.

    Wei, C.-J. et al. Next-generation influenza vaccines: opportunities and challenges. Nat. Rev. Drug Discov. 19, 239–252 (2020).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 2.

    Ueda, G. et al. Tailored design of protein nanoparticle scaffolds for multivalent presentation of viral glycoprotein antigens. eLife 9, e57659 (2020).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 3.

    Kanekiyo, M. & Graham, B. S. Next-generation influenza vaccines. Cold Spring Harb. Perspect. Med. a038448 (2020).

  • 4.

    Iuliano, A. D. et al. Estimates of global seasonal influenza-associated respiratory mortality: a modelling study. Lancet 391, 1285–1300 (2018).

    PubMed 
    Article 

    Google Scholar 

  • 5.

    Flannery, B. et al. Interim estimates of 2017-18 seasonal influenza vaccine effectiveness – United States, February 2018. MMWR Morb. Mortal. Wkly. Rep. 67, 180–185 (2018).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 6.

    Ellebedy, A. H. et al. Induction of broadly cross-reactive antibody responses to the influenza HA stem region following H5N1 vaccination in humans. Proc. Natl Acad. Sci. USA 111, 13133–13138 (2014).

    ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 7.

    Andrews, S. F. et al. Immune history profoundly affects broadly protective B cell responses to influenza. Sci. Transl. Med. 7, 316ra192 (2015).

    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 8.

    Tan, H.-X. et al. Subdominance and poor intrinsic immunogenicity limit humoral immunity targeting influenza HA stem. J. Clin. Invest. 129, 850–862 (2019).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 9.

    Yassine, H. M. et al. Hemagglutinin-stem nanoparticles generate heterosubtypic influenza protection. Nat. Med. 21, 1065–1070 (2015).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 10.

    Impagliazzo, A. et al. A stable trimeric influenza hemagglutinin stem as a broadly protective immunogen. Science 349, 1301–1306 (2015).

    ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 11.

    Corbett, K. S. et al. Design of nanoparticulate group 2 influenza virus hemagglutinin sstem antigens that activate unmutated ancestor B cell receptors of broadly neutralizing antibody lineages. mBio 10, e02810-18 (2019).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 12.

    Boyoglu-Barnum, S. et al. Glycan repositioning of influenza hemagglutinin stem facilitates the elicitation of protective cross-group antibody responses. Nat. Commun. 11, 791 (2020).

    ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 13.

    Steel, J. et al. Influenza virus vaccine based on the conserved hemagglutinin stalk domain. mBio 1, e00018-10 (2010).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 14.

    Bommakanti, G. et al. Design of an HA2-based Escherichia coli expressed influenza immunogen that protects mice from pathogenic challenge. Proc. Natl Acad. Sci. USA 107, 13701–13706 (2010).

    ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 15.

    Krammer, F., Pica, N., Hai, R., Margine, I. & Palese, P. Chimeric hemagglutinin influenza virus vaccine constructs elicit broadly protective stalk-specific antibodies. J. Virol. 87, 6542–6550 (2013).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 16.

    Marcandalli, J. et al. Induction of potent neutralizing antibody responses by a designed protein nanoparticle vaccine for respiratory syncytial virus. Cell 176, 1420–1431.e17 (2019).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 17.

    Kanekiyo, M. et al. Self-assembling influenza nanoparticle vaccines elicit broadly neutralizing H1N1 antibodies. Nature 499, 102–106 (2013).

    ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 18.

    López-Sagaseta, J., Malito, E., Rappuoli, R. & Bottomley, M. J. Self-assembling protein nanoparticles in the design of vaccines. Comput. Struct. Biotechnol. J. 14, 58–68 (2015).

    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 19.

    Tokatlian, T. et al. Innate immune recognition of glycans targets HIV nanoparticle immunogens to germinal centers. Science 363, 649–654 (2019).

    ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 20.

    Kanekiyo, M. et al. Mosaic nanoparticle display of diverse influenza virus hemagglutinins elicits broad B cell responses. Nat. Immunol. 20, 362–372 (2019).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 21.

    Cohen, A. A. et al. Mosaic nanoparticles elicit cross-reactive immune responses to zoonotic coronaviruses in mice. Science 371, 735–741 (2021).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 22.

    Georgiev, I. S. et al. Two-component ferritin nanoparticles for multimerization of diverse trimeric antigens. ACS Infect. Dis. 4, 788–796 (2018).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 23.

    Cohen, A. A. et al. Construction, characterization, and immunization of nanoparticles that display a diverse array of influenza HA trimers. PLoS ONE 16, e0247963 (2021).

  • 24.

    King, N. P. et al. Accurate design of co-assembling multi-component protein nanomaterials. Nature 510, 103–108 (2014).

    ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 25.

    Bale, J. B. et al. Accurate design of megadalton-scale two-component icosahedral protein complexes. Science 353, 389–394 (2016).

    ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 26.

    Martín, J. et al. Studies of the binding properties of influenza hemagglutinin receptor-site mutants. Virology 241, 101–111 (1998).

    PubMed 
    Article 

    Google Scholar 

  • 27.

    Whittle, J. R. R. et al. Flow cytometry reveals that H5N1 vaccination elicits cross-reactive stem-directed antibodies from multiple Ig heavy-chain lineages. J. Virol. 88, 4047–4057 (2014).

    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 28.

    Creanga, A. et al. A comprehensive influenza reporter virus panel for high-throughput deep profiling of neutralizing antibodies. Nat. Commun. https://doi.org/10.1038/s41467-021-21954-2 (2021).

  • 29.

    Corti, D. et al. A neutralizing antibody selected from plasma cells that binds to group 1 and group 2 influenza A hemagglutinins. Science 333, 850–856 (2011).

    ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 30.

    Bianchi, M. et al. Electron-microscopy-based epitope mapping defines specificities of polyclonal antibodies elicited during HIV-1 BG505 envelope trimer immunization. Immunity 49, 288–300.e8 (2018).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 31.

    Kallewaard, N. L. et al. Structure and function analysis of an antibody recognizing all influenza A subtypes. Cell 166, 596–608 (2016).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 32.

    Joyce, M. G. et al. Vaccine-induced antibodies that neutralize group 1 and group 2 influenza A viruses. Cell 166, 609–623 (2016).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 33.

    Wei, C.-J. et al. Induction of broadly neutralizing H1N1 influenza antibodies by vaccination. Science 329, 1060–1064 (2010).

    ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 34.

    Darricarrère, N. et al. Development of a Pan-H1 influenza vaccine. J. Virol. 92, e01349-18 (2018).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 35.

    Giles, B. M. & Ross, T. M. A computationally optimized broadly reactive antigen (COBRA) based H5N1 VLP vaccine elicits broadly reactive antibodies in mice and ferrets. Vaccine 29, 3043–3054 (2011).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 36.

    Broecker, F. et al. A mosaic hemagglutinin-based influenza virus vaccine candidate protects mice from challenge with divergent H3N2 strains. NPJ Vaccines 4, 31 (2019).

    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 37.

    Sun, W. et al. Development of influenza B universal vaccine candidates using the “mosaic” hemagglutinin approach. J. Virol. 93, e00333-19 (2019).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 38.

    Ng, S. et al. Novel correlates of protection against pandemic H1N1 influenza A virus infection. Nat. Med. 25, 962–967 (2019).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 39.

    Fonville, J. M. et al. Antibody landscapes after influenza virus infection or vaccination. Science 346, 996–1000 (2014).

    ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 40.

    Gostic, K. M., Ambrose, M., Worobey, M. & Lloyd-Smith, J. O. Potent protection against H5N1 and H7N9 influenza via childhood hemagglutinin imprinting. Science 354, 722–726 (2016).

    ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 41.

    Throsby, M. et al. Heterosubtypic neutralizing monoclonal antibodies cross-protective against H5N1 and H1N1 recovered from human IgM+ memory B cells. PLoS ONE 3, e3942 (2008).

    ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 42.

    Hong, M. et al. Antibody recognition of the pandemic H1N1 influenza virus hemagglutinin receptor binding site. J. Virol. 87, 12471–12480 (2013).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 43.

    Ekiert, D. C. et al. A highly conserved neutralizing epitope on group 2 influenza A viruses. Science 333, 843–850 (2011).

    ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 44.

    Iba, Y. et al. Conserved neutralizing epitope at globular head of hemagglutinin in H3N2 influenza viruses. J. Virol. 88, 7130–7144 (2014).

    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 45.

    Lee, P. S. et al. Receptor mimicry by antibody F045-092 facilitates universal binding to the H3 subtype of influenza virus. Nat. Commun. 5, 3614 (2014).

    ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 46.

    Dreyfus, C. et al. Highly conserved protective epitopes on influenza B viruses. Science 337, 1343–1348 (2012).

    ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 47.

    Wu, Y. et al. A potent broad-spectrum protective human monoclonal antibody crosslinking two haemagglutinin monomers of influenza A virus. Nat. Commun. 6, 7708 (2015).

    ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 48.

    Kwakkenbos, M. J. et al. Generation of stable monoclonal antibody-producing B cell receptor-positive human memory B cells by genetic programming. Nat. Med. 16, 123–128 (2010).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 49.

    Corti, D. et al. Cross-neutralization of four paramyxoviruses by a human monoclonal antibody. Nature 501, 439–443 (2013).

    ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 50.

    Studier, F. W. & William Studier, F. Protein production by auto-induction in high density shaking cultures. Protein Expr. Purif. 41, 207–234 (2005).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 51.

    Snijder, J. et al. Vitrification after multiple rounds of sample application and blotting improves particle density on cryo-electron microscopy grids. J. Struct. Biol. 198, 38–42 (2017).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 52.

    Suloway, C. et al. Automated molecular microscopy: the new Leginon system. J. Struct. Biol. 151, 41–60 (2005).

    CAS 
    Article 

    Google Scholar 

  • 53.

    Tegunov, D. & Cramer, P. Real-time cryo-electron microscopy data preprocessing with Warp. Nat. Methods 16, 1146–1152 (2019).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 54.

    Ilca, S. L. et al. Localized reconstruction of subunits from electron cryomicroscopy images of macromolecular complexes. Nat. Commun. 6, 8843 (2015).

    ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 55.

    Emsley, P., Lohkamp, B., Scott, W. G. & Cowtan, K. Features and development of Coot. Acta Crystallogr. D 66, 486–501 (2010).

    CAS 
    Article 

    Google Scholar 

  • 56.

    Frenz, B. et al. Automatically fixing errors in glycoprotein structures with Rosetta. Structure 27, 134–139.e3 (2019).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 57.

    Wang, R. Y.-R. et al. Automated structure refinement of macromolecular assemblies from cryo-EM maps using Rosetta. eLife 5, e17219 (2016).

    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 58.

    Chen, V. B. et al. MolProbity: all-atom structure validation for macromolecular crystallography. Acta Crystallogr. D 66, 12–21 (2010).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 59.

    Liebschner, D. et al. Macromolecular structure determination using X-rays, neutrons and electrons: recent developments in Phenix. Acta Crystallogr. D 75, 861–877 (2019).

    CAS 
    Article 

    Google Scholar 

  • 60.

    Agirre, J. et al. Privateer: software for the conformational validation of carbohydrate structures. Nat. Struct. Mol. Biol. 22, 833–834 (2015).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 61.

    Barad, B. A. et al. EMRinger: side chain-directed model and map validation for 3D cryo-electron microscopy. Nat. Methods 12, 943–946 (2015).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 62.

    Scheres, S. H. W. & Chen, S. Prevention of overfitting in cryo-EM structure determination. Nat. Methods 9, 853–854 (2012).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 63.

    Verkerke, H. P. et al. Epitope-independent purification of native-like envelope trimers from diverse HIV-1 isolates. J. Virol. 90, 9471–9482 (2016).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 64.

    Guttman, M., Weis, D. D., Engen, J. R. & Lee, K. K. Analysis of overlapped and noisy hydrogen/deuterium exchange mass spectra. J. Am. Soc. Mass Spectrom. 24, 1906–1912 (2013).

    ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 65.

    Weis, D. D., Engen, J. R. & Kass, I. J. Semi-automated data processing of hydrogen exchange mass spectra using HX-Express. J. Am. Soc. Mass Spectrom. 17, 1700–1703 (2006).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 66.

    Martínez-Sobrido, L. et al. Hemagglutinin-pseudotyped green fluorescent protein-expressing influenza viruses for the detection of influenza virus neutralizing antibodies. J. Virol. 84, 2157–2163 (2010).

    PubMed 
    Article 
    CAS 

    Google Scholar 

  • 67.

    Gao, Q. et al. The influenza A virus PB2, PA, NP, and M segments play a pivotal role during genome packaging. J. Virol. 86, 7043–7051 (2012).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 68.

    Bloom, J. D., Gong, L. I. & Baltimore, D. Permissive secondary mutations enable the evolution of influenza oseltamivir resistance. Science 328, 1272–1275 (2010).

    ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 69.

    Kong, W.-P. et al. Protective immunity to lethal challenge of the 1918 pandemic influenza virus by vaccination. Proc. Natl Acad. Sci. USA 103, 15987–15991 (2006).

    ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 70.

    Yang, Z.-Y. et al. Immunization by avian H5 influenza hemagglutinin mutants with altered receptor binding specificity. Science 317, 825–828 (2007).

    ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 71.

    Lander, G. C. et al. Appion: an integrated, database-driven pipeline to facilitate EM image processing. J. Struct. Biol. 166, 95–102 (2009).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 72.

    Rohou, A. & Grigorieff, N. CTFFIND4: Fast and accurate defocus estimation from electron micrographs. J. Struct. Biol. 192, 216–221 (2015).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 73.

    Voss, N. R., Yoshioka, C. K., Radermacher, M., Potter, C. S. & Carragher, B. DoG Picker and TiltPicker: software tools to facilitate particle selection in single particle electron microscopy. J. Struct. Biol. 166, 205–213 (2009).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 74.

    Punjani, A., Rubinstein, J. L., Fleet, D. J. & Brubaker, M. A. cryoSPARC: algorithms for rapid unsupervised cryo-EM structure determination. Nat. Methods 14, 290–296 (2017).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 75.

    Zivanov, J. et al. New tools for automated high-resolution cryo-EM structure determination in RELION-3. eLife 7, e42166 (2018).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 76.

    Zivanov, J., Nakane, T. & Scheres, S. H. W. A Bayesian approach to beam-induced motion correction in cryo-EM single-particle analysis. IUCrJ 6, 5–17 (2019).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 77.

    Punjani, A., Zhang, H. & Fleet, D. J. Non-uniform refinement: Adaptive regularization improves single particle cryo-EM reconstruction. Nat. Methods 17, 1214–1221 (2019).

    Article 
    CAS 

    Google Scholar 



  • Source link

    Leave a Reply

    Your email address will not be published.