Literature DB >> 18463692

Comparison of immunogen designs that optimize peptide coverage: reply to Fischer et al.

David C Nickle, Nebojsa Jojic, David Heckerman, Vladimir Jojic, Darko Kirovski, Morgane Rolland, Sergei Kosakovsky Pond, James I Mullins.   

Abstract

Entities:  

Mesh:

Substances:

Year:  2008        PMID: 18463692      PMCID: PMC2217581          DOI: 10.1371/journal.pcbi.0040025

Source DB:  PubMed          Journal:  PLoS Comput Biol        ISSN: 1553-734X            Impact factor:   4.475


× No keyword cloud information.
In our paper “Coping with Viral Diversity in HIV Vaccine Design” [1], we presented several approaches to incorporate viral variability within vaccine immunogens, including judicious choice of natural strains. Most of our approaches included at least one collinear gene length corresponding to the Center-of-Tree (COT) sequence, which has near-optimal peptide coverage for a single gene. Inclusion of a COT sequence and optimizing the rest of the immunogen for coverage, as suggested in [2], yielded a construct (COT+) with the greatest coverage of peptide diversity, minimally sacrificing peptide coverage in comparison with unconstrained diversity optimization. Fischer et al. [3] introduced mosaics—a different approach to increasing coverage while maintaining collinearity using an optimization algorithm based on simulated recombination. In their response to Nickle et al. [1], Fischer et al. [4] suggest that maintaining full collinearity of viral gene sequences with native viral proteins is the only tractable approach to producing immunogens inclusive of viral variability. This claim was based on the observation that mosaics had slightly higher coverage than COT+ at 3× and 4× strain lengths, despite the fact that all mosaic components are constrained to be collinear with the full gene. However, as we pointed out, a variety of optimization algorithms can be used to perform coverage optimization, with computationally intensive approaches typically yielding better results. Figure 1 compares the coverage of mosaics with COT+ constructs produced by two optimization algorithms—the simple greedy extension described in Nickle et al. [1], which can be implemented in hours and run in seconds on any modern personal computer, and the more complex combinatiorial optimization approach of [5] run for one day on a cluster of 300 PCs. We also include the coverage of a construct optimized without any collinearity constraints, derived using the Kirovski et al. [5] algorithm. The coverage of COT+ created by combinatorial optimization is greater than that of mosaics, especially at larger lengths where even the simple greedy algorithm surpasses the mosaic coverage. Furthermore, the optimized COT+ coverage is almost identical to the coverage of constructs optimized with no collinearity constraints, indicating that the price for imposing a constraint on the immunogen to include a single virus-like strain is small.
Figure 1

Comparison of Peptide Coverage Scores Achievable with Different Immunogen Formats and Algorithms

In (A) and (B), we show the coverage for Gag and Nef, respectively, as a function of immunogen gene length for different immunogen formats. Natural strains: a cocktail of natural HIV sequences optimized for breadth of diversity by Gibbs sampling. Mosaics: a cocktail of constructs collinear with natural strains optimized by the code developed by Fischer et al. [3]. Greedy COT+: COT+ sequences were optimized by a simple greedy algorithm described by Jojic et al. [2,13] and Nickle et al. [1]. Optimized COT+: a stochastic combinatorial optimization of COT+ using the algorithm of Kirovski et al. [5], run on a 300 node Windows HPC cluster for one day. Unconstrained: a sequence optimized for coverage with the Kirovski algorithm without regard to gene collinearity. To emphasize that some of the constructs can be optimized at fractional lengths, those results are shown by lines (since points on the line are achievable), while the constructs consisting of an integer number of strains are shown as dots only.

Comparison of Peptide Coverage Scores Achievable with Different Immunogen Formats and Algorithms

In (A) and (B), we show the coverage for Gag and Nef, respectively, as a function of immunogen gene length for different immunogen formats. Natural strains: a cocktail of natural HIV sequences optimized for breadth of diversity by Gibbs sampling. Mosaics: a cocktail of constructs collinear with natural strains optimized by the code developed by Fischer et al. [3]. Greedy COT+: COT+ sequences were optimized by a simple greedy algorithm described by Jojic et al. [2,13] and Nickle et al. [1]. Optimized COT+: a stochastic combinatorial optimization of COT+ using the algorithm of Kirovski et al. [5], run on a 300 node Windows HPC cluster for one day. Unconstrained: a sequence optimized for coverage with the Kirovski algorithm without regard to gene collinearity. To emphasize that some of the constructs can be optimized at fractional lengths, those results are shown by lines (since points on the line are achievable), while the constructs consisting of an integer number of strains are shown as dots only. Fischer and colleagues also argued that COT+ creates unnatural peptide sequences by concatenation. However, similar concatenation of their mosaics would have produced about 18 unnatural 9-mer peptides. Furthermore, the COT+ approach can be tuned to both penalize the introduction of unnatural peptides on concatenation, and to define the number of segments to be separately expressed, and thus reduce the requirement for concatenation. Several additional inferences were made in the response by Fischer et al. that should be commented upon. First, COT+ may, of course, be optimized for arbitrary HIV clades or combinations of clades, but the publication of our paper in PLoS Computational Biology reflects our focus on approaches to immunogen design rather than on the production of an exhaustive series of constructs. Also, just as in the mosaic approach, COT+ can be optimized to exclude rare variants (referred to as smoothing in our paper). Fischer et al. also discussed disappointing unpublished findings on the immunogenicity induced against Nef by a construct obtained by fusing a full-length Gag gene and the central portion of the Nef gene. However, these results can only be fairly assessed in light of what would be expected for the full-length Nef protein, and in the case of cellular immune responses, in the context of the same MHC specificities. However, these controls were not provided. We certainly agree that there are substantial challenges to the establishment of a multivalent CD8 response, yet multiple strategies have been and are being devised to overcome this important problem. For example, different groups have shown that CD8+ T cell responses can be successfully elicited against CD8+ T cell epitope strings when they are separated by short linker sequences and not in the context of the native protein, implying that they can be processed and presented in vivo [6-11]. Finally, despite 25 years of AIDS research and intensive yet uniformly failed efforts to develop an AIDS vaccine, the scientific community is poorly positioned to determine which, if any, approach to vaccine immunogen design will prove successful. Thus, arguing over methodologies developed with the same goal of incorporating variability has little significance as long as we do not know whether maximizing variability or inclusion of the entire full-length viral proteins are valid strategies. It may very well be that removing certain epitopes could be a more judicious approach than an overall epitope maximization strategy [12]. Indeed, the flexibility afforded by the COT+ approach, which is not limited to full-length proteins, may well prove superior to immunization with full-length viral protein immunogens.
  10 in total

1.  HIV vaccine development by computer assisted design: the GAIA vaccine.

Authors:  Anne S De Groot; Luisa Marcon; Elizabeth A Bishop; Daniel Rivera; Michele Kutzler; David B Weiner; William Martin
Journal:  Vaccine       Date:  2005-03-18       Impact factor: 3.641

2.  Development of a synthetic consensus sequence scrambled antigen HIV-1 vaccine designed for global use.

Authors:  Scott A Thomson; Angel B Jaramillo; Maryanne Shoobridge; Kerrie J Dunstan; Beth Everett; Charani Ranasinghe; Stephen J Kent; Ke Gao; Jill Medveckzy; Rosemary A Ffrench; Ian A Ramshaw
Journal:  Vaccine       Date:  2005-09-07       Impact factor: 3.641

3.  Polyvalent vaccines for optimal coverage of potential T-cell epitopes in global HIV-1 variants.

Authors:  Will Fischer; Simon Perkins; James Theiler; Tanmoy Bhattacharya; Karina Yusim; Robert Funkhouser; Carla Kuiken; Barton Haynes; Norman L Letvin; Bruce D Walker; Beatrice H Hahn; Bette T Korber
Journal:  Nat Med       Date:  2006-12-24       Impact factor: 53.440

4.  Induction of multifunctional human immunodeficiency virus type 1 (HIV-1)-specific T cells capable of proliferation in healthy subjects by using a prime-boost regimen of DNA- and modified vaccinia virus Ankara-vectored vaccines expressing HIV-1 Gag coupled to CD8+ T-cell epitopes.

Authors:  Nilu Goonetilleke; Stephen Moore; Len Dally; Nicola Winstone; Inese Cebere; Abdul Mahmoud; Susana Pinheiro; Geraldine Gillespie; Denise Brown; Vanessa Loach; Joanna Roberts; Ana Guimaraes-Walker; Peter Hayes; Kelley Loughran; Carole Smith; Jan De Bont; Carl Verlinde; Danii Vooijs; Claudia Schmidt; Mark Boaz; Jill Gilmour; Pat Fast; Lucy Dorrell; Tomas Hanke; Andrew J McMichael
Journal:  J Virol       Date:  2006-05       Impact factor: 5.103

5.  Expansion after epitope peptide exposure in vitro predicts cytotoxic T lymphocyte epitope dominance hierarchy in lymphocytes of vaccinated mamu-a*01+ rhesus monkeys.

Authors:  Ramu A Subbramanian; William A Charini; Marcelo J Kuroda; Michael Seaman; Heng Chhay; Michelle A Lifton; Darci A Gorgone; Jörn E Schmitz; Angela Carville; Norman L Letvin
Journal:  AIDS Res Hum Retroviruses       Date:  2006-05       Impact factor: 2.205

6.  Magnitude and diversity of cytotoxic-T-lymphocyte responses elicited by multiepitope DNA vaccination in rhesus monkeys.

Authors:  Ramu A Subbramanian; Marcelo J Kuroda; William A Charini; Dan H Barouch; Cristina Costantino; Sampa Santra; Jörn E Schmitz; Kristi L Martin; Michelle A Lifton; Darci A Gorgone; John W Shiver; Norman L Letvin
Journal:  J Virol       Date:  2003-09       Impact factor: 5.103

Review 7.  Therapeutic immunization for the control of HIV-1: where are we now?

Authors:  Lucy Dorrell
Journal:  Int J STD AIDS       Date:  2006-07       Impact factor: 1.359

8.  Coping with viral diversity in HIV vaccine design.

Authors:  David C Nickle; Morgane Rolland; Mark A Jensen; Sergei L Kosakovsky Pond; Wenjie Deng; Mark Seligman; David Heckerman; James I Mullins; Nebojsa Jojic
Journal:  PLoS Comput Biol       Date:  2007-04-27       Impact factor: 4.475

9.  Coping with viral diversity in HIV vaccine design: a response to Nickle et al.

Authors:  Will Fischer; H X Liao; Barton F Haynes; Norman L Letvin; Bette Korber
Journal:  PLoS Comput Biol       Date:  2008-01       Impact factor: 4.475

Review 10.  HIV-1 group M conserved elements vaccine.

Authors:  Morgane Rolland; David C Nickle; James I Mullins
Journal:  PLoS Pathog       Date:  2007-11       Impact factor: 6.823

  10 in total
  12 in total

1.  DNA Prime-Boost Vaccine Regimen To Increase Breadth, Magnitude, and Cytotoxicity of the Cellular Immune Responses to Subdominant Gag Epitopes of Simian Immunodeficiency Virus and HIV.

Authors:  Xintao Hu; Antonio Valentin; Frances Dayton; Viraj Kulkarni; Candido Alicea; Margherita Rosati; Bhabadeb Chowdhury; Rajeev Gautam; Kate E Broderick; Niranjan Y Sardesai; Malcolm A Martin; James I Mullins; George N Pavlakis; Barbara K Felber
Journal:  J Immunol       Date:  2016-10-12       Impact factor: 5.422

2.  Conservation of HIV-1 T cell epitopes across time and clades: validation of immunogenic HLA-A2 epitopes selected for the GAIA HIV vaccine.

Authors:  Lauren Levitz; Ousmane A Koita; Kotou Sangare; Matthew T Ardito; Christine M Boyle; John Rozehnal; Karamoko Tounkara; Sounkalo M Dao; Youssouf Koné; Zoumana Koty; Soren Buus; Leonard Moise; William D Martin; Anne S De Groot
Journal:  Vaccine       Date:  2012-10-24       Impact factor: 3.641

3.  Preparing for the availability of a partially effective HIV vaccine: some lessons from other licensed vaccines.

Authors:  Robert T Chen; Dale J Hu; Eileen Dunne; Michael Shaw; James I Mullins; Supachai Rerks-Ngarm
Journal:  Vaccine       Date:  2011-07-13       Impact factor: 3.641

4.  Comparison of immune responses generated by optimized DNA vaccination against SIV antigens in mice and macaques.

Authors:  Viraj Kulkarni; Rashmi Jalah; Brunda Ganneru; Cristina Bergamaschi; Candido Alicea; Agneta von Gegerfelt; Vainav Patel; Gen-Mu Zhang; Bhabadeb Chowdhury; Kate E Broderick; Niranjan Y Sardesai; Antonio Valentin; Margherita Rosati; Barbara K Felber; George N Pavlakis
Journal:  Vaccine       Date:  2010-12-30       Impact factor: 3.641

Review 5.  Viral evolution and escape during acute HIV-1 infection.

Authors:  Christian L Boutwell; Morgane M Rolland; Joshua T Herbeck; James I Mullins; Todd M Allen
Journal:  J Infect Dis       Date:  2010-10-15       Impact factor: 5.226

6.  HIV-1 conserved elements p24CE DNA vaccine induces humoral immune responses with broad epitope recognition in macaques.

Authors:  Viraj Kulkarni; Antonio Valentin; Margherita Rosati; Morgane Rolland; James I Mullins; George N Pavlakis; Barbara K Felber
Journal:  PLoS One       Date:  2014-10-22       Impact factor: 3.240

7.  HIV-1 p24(gag) derived conserved element DNA vaccine increases the breadth of immune response in mice.

Authors:  Viraj Kulkarni; Margherita Rosati; Antonio Valentin; Brunda Ganneru; Ashish K Singh; Jian Yan; Morgane Rolland; Candido Alicea; Rachel Kelly Beach; Gen-Mu Zhang; Sylvie Le Gall; Kate E Broderick; Niranjan Y Sardesai; David Heckerman; Beatriz Mothe; Christian Brander; David B Weiner; James I Mullins; George N Pavlakis; Barbara K Felber
Journal:  PLoS One       Date:  2013-03-28       Impact factor: 3.240

Review 8.  HIV DNA Vaccine: Stepwise Improvements Make a Difference.

Authors:  Barbara K Felber; Antonio Valentin; Margherita Rosati; Cristina Bergamaschi; George N Pavlakis
Journal:  Vaccines (Basel)       Date:  2014-05-14

9.  Altered response hierarchy and increased T-cell breadth upon HIV-1 conserved element DNA vaccination in macaques.

Authors:  Viraj Kulkarni; Antonio Valentin; Margherita Rosati; Candido Alicea; Ashish K Singh; Rashmi Jalah; Kate E Broderick; Niranjan Y Sardesai; Sylvie Le Gall; Beatriz Mothe; Christian Brander; Morgane Rolland; James I Mullins; George N Pavlakis; Barbara K Felber
Journal:  PLoS One       Date:  2014-01-23       Impact factor: 3.240

10.  HIV Env conserved element DNA vaccine alters immunodominance in macaques.

Authors:  Xintao Hu; Antonio Valentin; Margherita Rosati; Siriphan Manocheewa; Candido Alicea; Bhabadeb Chowdhury; Jenifer Bear; Kate E Broderick; Niranjan Y Sardesai; Sylvie Le Gall; James I Mullins; George N Pavlakis; Barbara K Felber
Journal:  Hum Vaccin Immunother       Date:  2017-07-05       Impact factor: 3.452

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.