Increased Breadth and Depth of Cytotoxic T Lymphocytes Responses against HIV-1-B Nef by Inclusion of Epitope Variant Sequences
Identifieur interne : 001094 ( Pmc/Corpus ); précédent : 001093; suivant : 001095Increased Breadth and Depth of Cytotoxic T Lymphocytes Responses against HIV-1-B Nef by Inclusion of Epitope Variant Sequences
Auteurs : Morgane Rolland ; Nicole Frahm ; David C. Nickle ; Nebojsa Jojic ; Wenjie Deng ; Todd M. Allen ; Christian Brander ; David E. Heckerman ; James I. MullinsSource :
- PLoS ONE [ 1932-6203 ] ; 2011.
Abstract
Different vaccine approaches cope with HIV-1 diversity, ranging from centralized1–4 to variability-encompassing5–7antigens. For all these strategies, a concern remains: how does HIV-1 diversity impact epitope recognition by the immune system? We studied the relationship between HIV-1 diversity and CD8+ T Lymphocytes (CTL) targeting of HIV-1 subtype B Nef using 944 peptides (10-mers overlapping by nine amino acids (AA)) that corresponded to consensus peptides and their most common variants in the HIV-1-B virus population. IFN-γ ELISpot assays were performed using freshly isolated PBMC from 26 HIV-1-infected persons. Three hundred and fifty peptides elicited a response in at least one individual. Individuals targeted a median of 7 discrete regions. Overall, 33% of responses were directed against viral variants but not elicited against consensus-based test peptides. However, there was no significant relationship between the frequency of a 10-mer in the viral population and either its frequency of recognition (Spearman's correlation coefficient ρ = 0.24) or the magnitude of the responses (ρ = 0.16). We found that peptides with a single mutation compared to the consensus were likely to be recognized (especially if the change was conservative) and to elicit responses of similar magnitude as the consensus peptide. Our results indicate that cross-reactivity between rare and frequent variants is likely to play a role in the expansion of CTL responses, and that maximizing antigenic diversity in a vaccine may increase the breadth and depth of CTL responses. However, since there are few obvious preferred pathways to virologic escape, the diversity that may be required to block all potential escape pathways may be too large for a realistic vaccine to accommodate. Furthermore, since peptides were not recognized based on their frequency in the population, it remains unclear by which mechanisms variability-inclusive antigens (i.e., constructs enriched with frequent variants) expand CTL recognition.
Url:
DOI: 10.1371/journal.pone.0017969
PubMed: 21464919
PubMed Central: 3065451
Links to Exploration step
PMC:3065451Le document en format XML
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Nef by Inclusion of Epitope Variant
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<affiliation><nlm:aff id="aff4"><addr-line>Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain</addr-line>
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<sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Increased Breadth and Depth of
Cytotoxic T Lymphocytes Responses against HIV-1-B
Nef by Inclusion of Epitope Variant
Sequences</title>
<author><name sortKey="Rolland, Morgane" sort="Rolland, Morgane" uniqKey="Rolland M" first="Morgane" last="Rolland">Morgane Rolland</name>
<affiliation><nlm:aff id="aff1"><addr-line>Department of Microbiology, University of Washington, Seattle, Washington, United States of America</addr-line>
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<author><name sortKey="Frahm, Nicole" sort="Frahm, Nicole" uniqKey="Frahm N" first="Nicole" last="Frahm">Nicole Frahm</name>
<affiliation><nlm:aff id="aff2"><addr-line>Massachussets General Hospital, Harvard Medical School, Boston, Massachusetts, United States of America</addr-line>
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<author><name sortKey="Nickle, David C" sort="Nickle, David C" uniqKey="Nickle D" first="David C." last="Nickle">David C. Nickle</name>
<affiliation><nlm:aff id="aff1"><addr-line>Department of Microbiology, University of Washington, Seattle, Washington, United States of America</addr-line>
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<author><name sortKey="Jojic, Nebojsa" sort="Jojic, Nebojsa" uniqKey="Jojic N" first="Nebojsa" last="Jojic">Nebojsa Jojic</name>
<affiliation><nlm:aff id="aff3"><addr-line>AIDS Research Institute IrsiCaixa - HIVACAT, Hospital Germans Trias i Pujol, Badalona, Barcelona, Spain</addr-line>
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<author><name sortKey="Deng, Wenjie" sort="Deng, Wenjie" uniqKey="Deng W" first="Wenjie" last="Deng">Wenjie Deng</name>
<affiliation><nlm:aff id="aff1"><addr-line>Department of Microbiology, University of Washington, Seattle, Washington, United States of America</addr-line>
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<author><name sortKey="Allen, Todd M" sort="Allen, Todd M" uniqKey="Allen T" first="Todd M." last="Allen">Todd M. Allen</name>
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<author><name sortKey="Brander, Christian" sort="Brander, Christian" uniqKey="Brander C" first="Christian" last="Brander">Christian Brander</name>
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</nlm:aff>
</affiliation>
<affiliation><nlm:aff id="aff4"><addr-line>Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain</addr-line>
</nlm:aff>
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<author><name sortKey="Heckerman, David E" sort="Heckerman, David E" uniqKey="Heckerman D" first="David E." last="Heckerman">David E. Heckerman</name>
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<author><name sortKey="Mullins, James I" sort="Mullins, James I" uniqKey="Mullins J" first="James I." last="Mullins">James I. Mullins</name>
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<front><div type="abstract" xml:lang="en"><p>Different vaccine approaches cope with HIV-1
diversity, ranging from
centralized<sup>1–4</sup>
to
variability-encompassing<sup>5–7</sup>
antigens. For all these strategies, a concern
remains: how does HIV-1 diversity impact epitope
recognition by the immune system? We studied the
relationship between HIV-1 diversity and
CD8<sup>+</sup>
T Lymphocytes (CTL) targeting
of HIV-1 subtype B Nef using 944 peptides (10-mers
overlapping by nine amino acids (AA)) that
corresponded to consensus peptides and their most
common variants in the HIV-1-B virus population.
IFN-γ ELISpot assays were performed using
freshly isolated PBMC from 26 HIV-1-infected
persons. Three hundred and fifty peptides elicited
a response in at least one individual. Individuals
targeted a median of 7 discrete regions. Overall,
33% of responses were directed against
viral variants but not elicited against
consensus-based test peptides. However, there was
no significant relationship between the frequency
of a 10-mer in the viral population and either its
frequency of recognition (Spearman's
correlation coefficient
ρ = 0.24) or the
magnitude of the responses
(ρ = 0.16). We found that
peptides with a single mutation compared to the
consensus were likely to be recognized (especially
if the change was conservative) and to elicit
responses of similar magnitude as the consensus
peptide. Our results indicate that
cross-reactivity between rare and frequent
variants is likely to play a role in the expansion
of CTL responses, and that maximizing antigenic
diversity in a vaccine may increase the breadth
and depth of CTL responses. However, since there
are few obvious preferred pathways to virologic
escape, the diversity that may be required to
block all potential escape pathways may be too
large for a realistic vaccine to accommodate.
Furthermore, since peptides were not recognized
based on their frequency in the population, it
remains unclear by which mechanisms
variability-inclusive antigens (i.e., constructs
enriched with frequent variants) expand CTL
recognition.</p>
</div>
</front>
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<front><journal-meta><journal-id journal-id-type="nlm-ta">PLoS One</journal-id>
<journal-id journal-id-type="iso-abbrev">PLoS ONE</journal-id>
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<issn pub-type="epub">1932-6203</issn>
<publisher><publisher-name>Public Library of
Science</publisher-name>
<publisher-loc>San Francisco, USA</publisher-loc>
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<article-meta><article-id pub-id-type="pmid">21464919</article-id>
<article-id pub-id-type="pmc">3065451</article-id>
<article-id pub-id-type="publisher-id">PONE-D-10-04063</article-id>
<article-id pub-id-type="doi">10.1371/journal.pone.0017969</article-id>
<article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject>
</subj-group>
<subj-group subj-group-type="Discipline-v2"><subject>Biology</subject>
<subj-group><subject>Immunology</subject>
<subj-group><subject>Immune Cells</subject>
<subj-group><subject>T Cells</subject>
</subj-group>
</subj-group>
<subj-group><subject>Immunologic Techniques</subject>
<subj-group><subject>Immunoassays</subject>
</subj-group>
</subj-group>
<subj-group><subject>Immune Response</subject>
</subj-group>
</subj-group>
<subj-group><subject>Microbiology</subject>
<subj-group><subject>Virology</subject>
<subj-group><subject>Immunodeficiency Viruses</subject>
<subject>Viral Evolution</subject>
<subject>Viral Immune Evasion</subject>
<subject>Viral Vaccines</subject>
</subj-group>
</subj-group>
</subj-group>
</subj-group>
<subj-group subj-group-type="Discipline-v2"><subject>Medicine</subject>
<subj-group><subject>Anatomy and Physiology</subject>
<subj-group><subject>Immune Physiology</subject>
<subj-group><subject>Antigens</subject>
</subj-group>
</subj-group>
</subj-group>
<subj-group><subject>Clinical Immunology</subject>
<subj-group><subject>Immunity</subject>
<subj-group><subject>Vaccination</subject>
<subj-group><subject>Vaccine Development</subject>
</subj-group>
</subj-group>
</subj-group>
<subj-group><subject>Immunologic Techniques</subject>
<subj-group><subject>Immunoassays</subject>
</subj-group>
</subj-group>
</subj-group>
<subj-group><subject>Infectious Diseases</subject>
<subj-group><subject>Viral Diseases</subject>
<subj-group><subject>HIV</subject>
</subj-group>
</subj-group>
</subj-group>
</subj-group>
</article-categories>
<title-group><article-title>Increased Breadth and Depth of
Cytotoxic T Lymphocytes Responses against HIV-1-B
Nef by Inclusion of Epitope Variant
Sequences</article-title>
<alt-title alt-title-type="running-head">Nef
Recognition by CTL</alt-title>
</title-group>
<contrib-group><contrib contrib-type="author" equal-contrib="yes"><name><surname>Rolland</surname>
<given-names>Morgane</given-names>
</name>
<xref ref-type="aff" rid="aff1"><sup>1</sup>
</xref>
<xref ref-type="corresp" rid="cor1"><sup>*</sup>
</xref>
<xref ref-type="author-notes" rid="fn1"><sup>¤a</sup>
</xref>
</contrib>
<contrib contrib-type="author" equal-contrib="yes"><name><surname>Frahm</surname>
<given-names>Nicole</given-names>
</name>
<xref ref-type="aff" rid="aff2"><sup>2</sup>
</xref>
<xref ref-type="author-notes" rid="fn2"><sup>¤b</sup>
</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Nickle</surname>
<given-names>David C.</given-names>
</name>
<xref ref-type="aff" rid="aff1"><sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Jojic</surname>
<given-names>Nebojsa</given-names>
</name>
<xref ref-type="aff" rid="aff3"><sup>3</sup>
</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Deng</surname>
<given-names>Wenjie</given-names>
</name>
<xref ref-type="aff" rid="aff1"><sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Allen</surname>
<given-names>Todd M.</given-names>
</name>
<xref ref-type="aff" rid="aff2"><sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Brander</surname>
<given-names>Christian</given-names>
</name>
<xref ref-type="aff" rid="aff2"><sup>2</sup>
</xref>
<xref ref-type="aff" rid="aff3"><sup>3</sup>
</xref>
<xref ref-type="aff" rid="aff4"><sup>4</sup>
</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Heckerman</surname>
<given-names>David E.</given-names>
</name>
<xref ref-type="aff" rid="aff5"><sup>5</sup>
</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Mullins</surname>
<given-names>James I.</given-names>
</name>
<xref ref-type="aff" rid="aff1"><sup>1</sup>
</xref>
</contrib>
</contrib-group>
<aff id="aff1"><label>1</label>
<addr-line>Department of Microbiology, University of Washington, Seattle, Washington, United States of America</addr-line>
</aff>
<aff id="aff2"><label>2</label>
<addr-line>Massachussets General Hospital, Harvard Medical School, Boston, Massachusetts, United States of America</addr-line>
</aff>
<aff id="aff3"><label>3</label>
<addr-line>AIDS Research Institute IrsiCaixa - HIVACAT, Hospital Germans Trias i Pujol, Badalona, Barcelona, Spain</addr-line>
</aff>
<aff id="aff4"><label>4</label>
<addr-line>Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain</addr-line>
</aff>
<aff id="aff5"><label>5</label>
<addr-line>Microsoft Research, Redmond, Washington, United States of America</addr-line>
</aff>
<contrib-group><contrib contrib-type="editor"><name><surname>Brusic</surname>
<given-names>Vladimir</given-names>
</name>
<role>Editor</role>
<xref ref-type="aff" rid="edit1"></xref>
</contrib>
</contrib-group>
<aff id="edit1">Dana-Farber Cancer Institute, United States of America</aff>
<author-notes><corresp id="cor1">* E-mail: <email>mrolland@hivresearch.org</email>
</corresp>
<fn fn-type="con"><p>Conceived and designed the experiments: MR NF
DCN NJ CB DEH JIM. Performed the experiments: MR
NF DCN NJ DEH. Analyzed the data: MR NF CB DEH
JIM. Contributed reagents/materials/analysis
tools: WD TMA. Wrote the paper: MR NF CB JIM.</p>
</fn>
<fn id="fn1" fn-type="current-aff"><label>¤a</label>
<p>Current address: Military HIV Research Program,
Henry M. Jackson Foundation, Rockville, Maryland,
United States of America</p>
</fn>
<fn id="fn2" fn-type="current-aff"><label>¤b</label>
<p>Current address: Vaccine and Infectious Disease
Institute, Fred Hutchinson Cancer Research Center,
Seattle, Washington, United States of America</p>
</fn>
</author-notes>
<pub-date pub-type="collection"><year>2011</year>
</pub-date>
<pub-date pub-type="epub"><day>28</day>
<month>3</month>
<year>2011</year>
</pub-date>
<volume>6</volume>
<issue>3</issue>
<elocation-id>e17969</elocation-id>
<history><date date-type="received"><day>19</day>
<month>10</month>
<year>2010</year>
</date>
<date date-type="accepted"><day>21</day>
<month>2</month>
<year>2011</year>
</date>
</history>
<permissions><copyright-statement>Rolland et al.</copyright-statement>
<copyright-year>2011</copyright-year>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/"><license-p>This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.</license-p>
</license>
</permissions>
<abstract><p>Different vaccine approaches cope with HIV-1
diversity, ranging from
centralized<sup>1–4</sup>
to
variability-encompassing<sup>5–7</sup>
antigens. For all these strategies, a concern
remains: how does HIV-1 diversity impact epitope
recognition by the immune system? We studied the
relationship between HIV-1 diversity and
CD8<sup>+</sup>
T Lymphocytes (CTL) targeting
of HIV-1 subtype B Nef using 944 peptides (10-mers
overlapping by nine amino acids (AA)) that
corresponded to consensus peptides and their most
common variants in the HIV-1-B virus population.
IFN-γ ELISpot assays were performed using
freshly isolated PBMC from 26 HIV-1-infected
persons. Three hundred and fifty peptides elicited
a response in at least one individual. Individuals
targeted a median of 7 discrete regions. Overall,
33% of responses were directed against
viral variants but not elicited against
consensus-based test peptides. However, there was
no significant relationship between the frequency
of a 10-mer in the viral population and either its
frequency of recognition (Spearman's
correlation coefficient
ρ = 0.24) or the
magnitude of the responses
(ρ = 0.16). We found that
peptides with a single mutation compared to the
consensus were likely to be recognized (especially
if the change was conservative) and to elicit
responses of similar magnitude as the consensus
peptide. Our results indicate that
cross-reactivity between rare and frequent
variants is likely to play a role in the expansion
of CTL responses, and that maximizing antigenic
diversity in a vaccine may increase the breadth
and depth of CTL responses. However, since there
are few obvious preferred pathways to virologic
escape, the diversity that may be required to
block all potential escape pathways may be too
large for a realistic vaccine to accommodate.
Furthermore, since peptides were not recognized
based on their frequency in the population, it
remains unclear by which mechanisms
variability-inclusive antigens (i.e., constructs
enriched with frequent variants) expand CTL
recognition.</p>
</abstract>
<counts><page-count count="9"></page-count>
</counts>
</article-meta>
</front>
<body><sec id="s1"><title>Introduction</title>
<p>Despite setbacks in the development of CTL-based HIV vaccines
<xref rid="pone.0017969-McElrath1" ref-type="bibr">[1]</xref>
, it seems likely that this
approach will remain a crucial component of future
vaccine strategies given amassed evidence on the
critical role of the cell-mediated host immune
response against HIV-1 <xref rid="pone.0017969-Koup1" ref-type="bibr">[2]</xref>
,
<xref rid="pone.0017969-Kent1" ref-type="bibr">[3]</xref>
, <xref rid="pone.0017969-Borrow1" ref-type="bibr">[4]</xref>
,
<xref rid="pone.0017969-Klein1" ref-type="bibr">[5]</xref>
, <xref rid="pone.0017969-McMichael1" ref-type="bibr">[6]</xref>
. Certain characteristics of
CTL responses attest to their importance, e.g., the
emergence of CD8+ T lymphocytes has been
temporally linked with the decline in viremia in
early infection <xref rid="pone.0017969-Koup1" ref-type="bibr">[2]</xref>
,
<xref rid="pone.0017969-Borrow1" ref-type="bibr">[4]</xref>
; some MHC class I alleles
are associated with HIV-1 disease outcomes <xref rid="pone.0017969-Kaslow1" ref-type="bibr">[7]</xref>
, <xref rid="pone.0017969-Carrington1" ref-type="bibr">[8]</xref>
, <xref rid="pone.0017969-Frahm1" ref-type="bibr">[9]</xref>
;
CTL targeting of specific proteins/epitopes, such as
within Gag, has been associated with control of
viral load <xref rid="pone.0017969-Ogg1" ref-type="bibr">[10]</xref>
,
<xref rid="pone.0017969-Kiepiela1" ref-type="bibr">[11]</xref>
. While it is apparent that
antiviral CTL immune responses vary in their ability
to contain HIV-1 replication, there is still no
precise definition of mechanisms of protection
against HIV-1 disease progression and, as such, no
rational path toward a successful CTL-based
vaccine.</p>
<p>Post-Step trial suggestions emphasize the potential benefit
of strategies that would improve T cell breadth
<xref rid="pone.0017969-McElrath1" ref-type="bibr">[1]</xref>
. Such vaccine strategies
have been proposed, e.g., for HIV-1 the mosaic <xref rid="pone.0017969-Fischer1" ref-type="bibr">[12]</xref>
and COT+ <xref rid="pone.0017969-Nickle1" ref-type="bibr">[13]</xref>
approaches, or the epitome
for Hepatitis C <xref rid="pone.0017969-Yerly1" ref-type="bibr">[14]</xref>
.
These vaccine designs compress HIV-1 diversity to
maximize the coverage of circulating strains: the
proposed inserts include the most common variants of
HIV-1, thereby infecting strains will be more likely
to match or be genetically closer to the vaccine
antigen. The rationale is that the efficacy of
variability-inclusive vaccine will be maximized
because peptides identical between the antigen and
the breakthrough strain would be recognized by T
cells primed by the vaccine upon breakthrough
infection. Indeed, two recent studies demonstrated
that mosaic HIV-1 vaccines increased the breadth and
depth of cellular immune responses in Rhesus monkeys
<xref rid="pone.0017969-Barouch1" ref-type="bibr">[15]</xref>
, <xref rid="pone.0017969-Santra1" ref-type="bibr">[16]</xref>
,
especially in the case of bivalent mosaic HIV-1-B
Gag, Pol and Env antigens expressed by recombinant
adenovirus serotype 26 vectors <xref rid="pone.0017969-Barouch1" ref-type="bibr">[15]</xref>
.</p>
<p>Although it is agreed that HIV-1's extensive variability
is a major challenge for a successful vaccine
strategy, which must control extremely diverse viral
strains, the impact of HIV-1 diversity on CTL
targeting remains poorly understood. Our knowledge
of HIV-1 diversity and CTL recognition is mostly
derived from whole genome mapping studies of ELISpot
responses using consensus peptides and small studies
of specific epitopes in HIV-1-infected individuals
with longitudinal follow-up, particularly in the
context of CTL escape.</p>
<p>We sought to formally analyze the effect of HIV-1 diversity
on CTL targeting of Nef, as it comprises both
conserved and variable segments and is often
targeted both during acute/early and chronic
infection: several Nef peptides were recognized by
more than 40% of individuals in large cohorts
of Americans or South-Africans infected with HIV-1
subtype B and C, respectively <xref rid="pone.0017969-Kiepiela1" ref-type="bibr">[11]</xref>
, <xref rid="pone.0017969-Frahm2" ref-type="bibr">[17]</xref>
.
Based on accumulated sequence data from the Los
Alamos HIV Database (HIVDB) for HIV-1 subtype B Nef,
we synthesized peptides corresponding to the
consensus sequence and several naturally occurring
mutants. The peptide set also included all peptides
derived from a 3-gene-length Nef COT+ antigen
<xref rid="pone.0017969-Nickle1" ref-type="bibr">[13]</xref>
: with the COT+
strategy, the initial gene-length corresponds to a
Center-Of-Tree (COT) sequence <xref rid="pone.0017969-Rolland1" ref-type="bibr">[18]</xref>
then common 9-mer Nef variants are appended based on
their frequency among circulating viruses until the
pre-set length of the construct is reached. In
total, the peptide library contained 944 Nef
peptides which were tested for immune recognition in
HIV-1 infected individuals in order to assess the
impact of HIV-1 diversity on CTL recognition and to
assess the improvement in viral epitope recognition
afforded by a theoretical variability-inclusive
vaccine candidate.</p>
<p>Here, we identified novel HIV-1 Nef epitopes and showed that
there is no general relationship between the
frequency of an HIV-1 peptide among circulating
sequences and its frequency of recognition in the
cohort. These findings challenge immunogen designs
that are based on a “frequency-only”
criterion for variant inclusion and warrant further
studies into the determinants of CTL variant
recognition in HIV-1.</p>
</sec>
<sec sec-type="materials|methods" id="s2"><title>Materials and Methods</title>
<sec id="s2a"><title>Study Subjects</title>
<p>Subjects with chronic HIV infection were
recruited at three hospitals in the Boston area.
All human subject protocols were approved by the
Partners Human Research Committee, and all
subjects provided written informed consent prior
to enrollment.</p>
</sec>
<sec id="s2b"><title>HIV-1 subtype B Nef Peptides</title>
<p>Nine hundred and forty four 10-mer peptides
overlapping by 9 AA were synthesized and used in
the present study. These sequences cover the
distribution of HIV-1 B viral sequences based on a
previously described <xref rid="pone.0017969-Nickle1" ref-type="bibr">[13]</xref>
dataset of 169 sequences available in the HIVDB.
These variants included: i) peptides corresponding
to the full-length consensus subtype B 2004 Nef;
ii) peptides corresponding to the full-length COT
subtype B <xref rid="pone.0017969-Rolland1" ref-type="bibr">[18]</xref>
;
iii) 10-mers corresponding to three natural HIV-1
B sequences optimized for combined sequence
coverage (‘3-Best’) (GenBank ids:
U34603, AF004394, DQ121883), and iv) 10-mers
covering the 3-gene-length Nef COT+ HIV-1 B
antigen (the first gene length corresponds to COT,
two additional gene lengths correspond to
high-frequency peptides; COT+ peptides also
include five artificial 10-mers that are a sequel
of the COT+ design strategy) <xref rid="pone.0017969-Nickle1" ref-type="bibr">[13]</xref>
. We chose 10-AA-long
peptides to increase sensitivity for <italic>in
vitro</italic>
IFN-γ ELISpot assays and to
better discriminate responses to multiple partly
overlapping peptides from individual discrete
specificities.</p>
</sec>
<sec id="s2c"><title>Variability metrics</title>
<p>Shannon entropy. Shannon entropy was used to
score the variability at each position of an
alignment of HIV-1 circulating sequences <xref rid="pone.0017969-Shannon1" ref-type="bibr">[19]</xref>
. Five hundred and fourteen
independent Nef HIV-1 subtype B sequences were
gathered from the HIVDB. Shannon entropy values
were determined at each site in the AA-alignment
and average Shannon entropy values were calculated
for each peptide over the corresponding
positions.</p>
<p>Population frequency. We derived all unique
10-mers in the 514-sequence-dataset and defined
their population frequency, i.e., the percentage
of sequences with the precise 10-mer sequence
present in the dataset of 514 Nef sequences.</p>
</sec>
<sec id="s2d"><title>IFN-γ ELISpot assays</title>
<p>IFN-γ ELISpot assays were performed on
freshly isolated peripheral blood mononuclear
cells (PBMC) from 26 individuals. All peptides
were tested in separate wells of the Elispot
plates. Due to the large number of peptides
tested, not all blood draws yielded sufficient
PBMC to test at 100,000 cells/well, therefore
assays were run with 74,000 to 100,000 cells/well
(median 100,000 cells/well). To be scored as
positive, a response had to be greater than: a)
four times the mean background, b) the mean
background plus three standard deviations, c) five
spots per well and d) 55 spot-forming cells per
million (SFC/M).</p>
</sec>
<sec id="s2e"><title>Cross-reactivity model</title>
<p>The HIV-1-B Nef peptides that were reactive in
the ELISpot assays were compared by testing k-mers
(with k = 8, 9, 10 AA) that
had the same HIV-1 HXB2 strain coordinates; in
brief, a consensus k-mer was compared to its
variant k-mer(s), with k being of the same length
for the consensus and variant to avoid the
creation of gaps when aligning the 2 k-mers. Pairs
of peptides were tested when the database
frequency of one of the peptides was at least
ten-fold greater than that of the other k-mer. For
each given 10-mer peptide pair, cross-reactivity
was also assessed for the two pairs of 9-mers and
three pairs of 8-mers nested in the 10-mer. We
computed a cross-reactivity fraction corresponding
to the number of individuals who recognized the
less frequent peptide divided by the number of
individuals who recognized the more common one. AA
substitutions were characterized as being
conservative, semi-conservative and
non-conservative based on the Dayhoff PAM250
matrix <xref rid="pone.0017969-Dayhoff1" ref-type="bibr">[20]</xref>
.</p>
</sec>
</sec>
<sec id="s3"><title>Results</title>
<sec id="s3a"><title>Design of 944 peptides in Nef HIV-1 Subtype
B</title>
<p>Most Nef peptides are unique or very rare at the
population level. We dissected 514 Nef HIV-1 B
sequences into overlapping 10-mers and found
19,860 unique 10-mers: a small fraction of
relatively frequent peptides and a long tail of
rare 10-mers. More than 2/3 of all of these
peptides were engendered by private mutations,
i.e., 13,574 peptides were found only once in this
dataset (<xref ref-type="supplementary-material" rid="pone.0017969.s001">Figure S1</xref>
). For the
experimental assays, 944 10-mers overlapping by 9
AA had been designed to cover a fraction of the
diversity of HIV-1 subtype B Nef sequences in the
population, based on a previously described
dataset of 169 sequences <xref rid="pone.0017969-Nickle1" ref-type="bibr">[13]</xref>
.
Five synthetic peptides were integrated in the set
that were unnatural junctional peptide sequels of
the COT+ design, however, they were not
recognized in our cohort. When all peptides were
mapped along the Nef protein based on their
corresponding start positions in the HXB2
reference sequence, consensus peptides covered the
full length of Nef and a median of four additional
peptides represented the variants found for each
consensus peptide, with up to eight variants for
the three most diverse segments of Nef (<xref ref-type="supplementary-material" rid="pone.0017969.s002">Figure S2</xref>
).</p>
</sec>
<sec id="s3b"><title>Identification of novel HIV-1 Subtype B Nef
epitopes</title>
<p>The 944 Nef peptides were tested by IFN-γ
ELISpot assays using fresh PBMC from 26 HIV-1
infected persons (<xref ref-type="supplementary-material" rid="pone.0017969.s005">Table S1</xref>
). Viral
loads did not influence the recognition by
IFN-γ ELISpot assays: among untreated
subjects, there was no significant relationship
between viral load and either the number of
ELISpot responses
(r<sup>2</sup>
= 0.05;
p = 0.001) or the number of
epitopes recognized per individual
(r<sup>2</sup>
= 0.04;
p = 0.001).</p>
<p>While 944 peptides were tested by IFN-γ
ELISpot assays, only 350 elicited a response in at
least 1 individual (<xref ref-type="fig" rid="pone-0017969-g001">Figure 1</xref>
).
Considering the 38 known epitopes reported in the
HIVDB (as of August 31, 2009), 34 epitopes were
recognized in our cohort at least once and not
necessarily in the context of the originally
described HLA allele (for 10 epitopes, recognition
occurred exclusively through alleles different
from the originally described ones). Considering
that three of the not-targeted epitopes were
11-mers whose recognition could not be effectively
tested with our 10-mer peptide library, the only
previously described epitope that was not
recognized in our cohort was the
B*4001/B50-restricted epitope LEKHGAITS (Nef
37–45), although 3 individuals presented the
HLA allele B40 (only 2-digit HLA data was
available for individuals in our study).</p>
<fig id="pone-0017969-g001" position="float"><object-id pub-id-type="doi">10.1371/journal.pone.0017969.g001</object-id>
<label>Figure 1</label>
<caption><title>Distribution of reactive 10-mers and known
epitopes in Nef.</title>
<p>The number of 10-mers that were tested are
represented as gray bars. Black bars correspond to
the 10-mers that were recognized at least by one
individual in our cohort. Red bars represent known
epitopes that had previously been reported in the
HIVDB. Each bar is placed at the start position of
each 10-mer based on their HXB2 coordinates.</p>
</caption>
<graphic xlink:href="pone.0017969.g001"></graphic>
</fig>
<p>On an individual peptide basis, the median number
of ELISpot responses per subject was 21
(interquartile range (IQR) 14–41; range
1–123). Due to the multiplicity of peptide
variants tested, several responses can be scored
for the same 10-AA segment. Additionally, due to
the 1AA-offset between the peptides, the same
epitope can be found in a suite of immediately
adjacent overlapping 10-mers: for example, an
8-AA-long epitope is present in three consecutive
10-mers. In order to count only the ELISpot
responses that were reflective of an independent
CTL specificity, we scored only one response per
10-AA segment, and, if we found two or three
responses to consecutive 10-mers, we scored them
as one independent response (four consecutive
responses were counted as two independent
responses). Hence, the median number of
independent epitopes recognized per individual was
seven (IQR 4–13; range 1–32).</p>
</sec>
<sec id="s3c"><title>Benefit of a coverage-optimized peptide
set</title>
<p>To assess whether using coverage-optimized HIV-1
subtype B vaccine inserts would engender broader
and deeper CTL responses in individuals, peptides
covering three potential vaccine insert strategies
were compared: COT+, ‘3-Best’ and
consensus. A three-gene length COT+
corresponded to 561 peptides in our test set. The
‘3-Best’ natural HIV-1 Nef strains,
which were selected from the HIVDB to afford the
highest coverage of HIV-1 variability <xref rid="pone.0017969-Nickle1" ref-type="bibr">[13]</xref>
, corresponded to 522
peptides. The Nef HIV-1 subtype B 2004 consensus
and COT sequences corresponded to 197
peptides.</p>
<p>When we evaluated the number of CTL responses
corresponding to the 3 different Nef vaccine
strategies in our cohort, we found that more
peptides matching the 3-gene-length COT+ were
targeted than peptides contained in the other
strategies:
n<sub>COT+</sub>
= 221,
n<sub>‘3-best’</sub>
= 200,
n<sub>CON04</sub>
= 95,
n<sub>COT</sub>
= 96.
However, the percentage of COT+ or
‘3-best’ peptides recognized was
similar (39 and 38%, respectively) while
the fraction of HIV-1-B 2004 consensus or COT
peptides recognized was, as expected, higher
−48 and 49% of the set, respectively.
Thus, if a single protein length peptide set is
used, consensus or COT peptides are optimal for
detecting responses, yet the breadth of T cell
responses is extended with the use of
coverage-optimized peptides.</p>
</sec>
<sec id="s3d"><title>Increased ELISpot recognition using epitope
variants albeit with diminishing returns</title>
<p>We analyzed how each 10-mer segment of HXB2 was
recognized to evaluate whether recognition was due
to the consensus peptide, one or more variant
peptide(s) or a combination of consensus and
variants. We rank-ordered peptides based on their
frequency in the database calling ‘variant
1’ the peptides corresponding to the most
common epitopic variant (after the consensus)
found in circulating sequences, ‘variant
2’ corresponds to the second most frequent
peptides, and so on. <xref ref-type="fig" rid="pone-0017969-g002">Figure 2</xref>
represents
whether and how each of the 203 10-AA stretches
covering HXB2 was recognized. One hundred and
thirty seven segments were recognized, while 66
segments were not recognized in our cohort despite
the use of multiple variants. <xref ref-type="fig" rid="pone-0017969-g002">Figure 2A</xref>
highlights two highly immunogenic regions
(centered around positions 80 and 130) that
elicited responses to both consensus and variant
peptides. Consensus peptides were more often
recognized than variant peptides: 91 of 203
consensus peptides or 45% were recognized
(<xref ref-type="table" rid="pone-0017969-t001">Table 1</xref>
). The percentage of recognition
dropped with the frequency of the variants in the
circulating population: to 41% for
‘variant 1’ peptides and to 26%
for ‘variant 4’ peptides. The
recognition of ‘variants 5, 6, 7’ or
‘variants absent in the database’
(i.e., none of the 514 sequences in the dataset
included these variants) did not appear to
correlate with their frequency in the population:
none of the variant 7 peptides were recognized,
while 16 of the 43 (37%) variant peptides
absent in circulating sequences were
recognized.</p>
<fig id="pone-0017969-g002" position="float"><object-id pub-id-type="doi">10.1371/journal.pone.0017969.g002</object-id>
<label>Figure 2</label>
<caption><title>Distribution of reactive consensus and
variant 10-mer peptides.</title>
<p>Colored blocks correspond to the 10-mers that
were recognized, while the 10-mers that were
tested are outlined in black. Recognition of
peptides is figured using a gradient of colors:
consensus peptides are figured in burgundy and
variant peptides follow a gradient from the most
conserved (in orange) to the most rare (in
purple), while peptides not found in a database of
514 sequences are in black. Each block represents
the start position of the 10-mers based on their
HXB2 coordinates. Panel A shows all the peptides
recognized, panel B represents for each individual
only the most frequent peptide recognized at each
position (i.e., if an individual recognized the
consensus peptide and variants 1 and 4, only the
recognition through the consensus is figured).</p>
</caption>
<graphic xlink:href="pone.0017969.g002"></graphic>
</fig>
<table-wrap id="pone-0017969-t001" position="float"><object-id pub-id-type="doi">10.1371/journal.pone.0017969.t001</object-id>
<label>Table 1</label>
<caption><title>ELISpot recognition of consensus and
variant peptides.</title>
</caption>
<alternatives><graphic id="pone-0017969-t001-1" xlink:href="pone.0017969.t001"></graphic>
<table frame="hsides" rules="groups"><colgroup span="1"><col align="left" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
</colgroup>
<thead><tr><td colspan="10" align="left" rowspan="1">Counting all
responses</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1">Cons.</td>
<td align="left" rowspan="1" colspan="1">Var. 1</td>
<td align="left" rowspan="1" colspan="1">Var. 2</td>
<td align="left" rowspan="1" colspan="1">Var. 3</td>
<td align="left" rowspan="1" colspan="1">Var. 4</td>
<td align="left" rowspan="1" colspan="1">Var. 5</td>
<td align="left" rowspan="1" colspan="1">Var. 6</td>
<td align="left" rowspan="1" colspan="1">Var. 7</td>
<td align="left" rowspan="1" colspan="1">Absent</td>
</tr>
</thead>
<tbody><tr><td align="left" rowspan="1" colspan="1">Peptides recognized</td>
<td align="left" rowspan="1" colspan="1">91</td>
<td align="left" rowspan="1" colspan="1">81</td>
<td align="left" rowspan="1" colspan="1">65</td>
<td align="left" rowspan="1" colspan="1">40</td>
<td align="left" rowspan="1" colspan="1">24</td>
<td align="left" rowspan="1" colspan="1">14</td>
<td align="left" rowspan="1" colspan="1">6</td>
<td align="left" rowspan="1" colspan="1">0</td>
<td align="left" rowspan="1" colspan="1">16</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Peptides not recognized</td>
<td align="left" rowspan="1" colspan="1">112</td>
<td align="left" rowspan="1" colspan="1">115</td>
<td align="left" rowspan="1" colspan="1">110</td>
<td align="left" rowspan="1" colspan="1">99</td>
<td align="left" rowspan="1" colspan="1">68</td>
<td align="left" rowspan="1" colspan="1">28</td>
<td align="left" rowspan="1" colspan="1">10</td>
<td align="left" rowspan="1" colspan="1">4</td>
<td align="left" rowspan="1" colspan="1">43</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Peptides tested</td>
<td align="left" rowspan="1" colspan="1">203</td>
<td align="left" rowspan="1" colspan="1">196</td>
<td align="left" rowspan="1" colspan="1">175</td>
<td align="left" rowspan="1" colspan="1">139</td>
<td align="left" rowspan="1" colspan="1">92</td>
<td align="left" rowspan="1" colspan="1">42</td>
<td align="left" rowspan="1" colspan="1">16</td>
<td align="left" rowspan="1" colspan="1">4</td>
<td align="left" rowspan="1" colspan="1">59</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">% peptides recognized</td>
<td align="left" rowspan="1" colspan="1">44.83</td>
<td align="left" rowspan="1" colspan="1">41.33</td>
<td align="left" rowspan="1" colspan="1">37.14</td>
<td align="left" rowspan="1" colspan="1">28.78</td>
<td align="left" rowspan="1" colspan="1">26.09</td>
<td align="left" rowspan="1" colspan="1">33.33</td>
<td align="left" rowspan="1" colspan="1">37.50</td>
<td align="left" rowspan="1" colspan="1">0.00</td>
<td align="left" rowspan="1" colspan="1">27.12</td>
</tr>
</tbody>
</table>
<table frame="hsides" rules="groups"><colgroup span="1"><col align="left" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
</colgroup>
<thead><tr><td colspan="10" align="left" rowspan="1">Counting responses
to the consensus and additional responses afforded
by the addition of variants</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1">Cons.</td>
<td align="left" rowspan="1" colspan="1">Var. 1</td>
<td align="left" rowspan="1" colspan="1">Var. 2</td>
<td align="left" rowspan="1" colspan="1">Var. 3</td>
<td align="left" rowspan="1" colspan="1">Var. 4</td>
<td align="left" rowspan="1" colspan="1">Var. 5</td>
<td align="left" rowspan="1" colspan="1">Var. 6</td>
<td align="left" rowspan="1" colspan="1">Var. 7</td>
<td align="left" rowspan="1" colspan="1">Absent</td>
</tr>
</thead>
<tbody><tr><td align="left" rowspan="1" colspan="1">Peptides recognized</td>
<td align="left" rowspan="1" colspan="1">91</td>
<td align="left" rowspan="1" colspan="1">50</td>
<td align="left" rowspan="1" colspan="1">33</td>
<td align="left" rowspan="1" colspan="1">12</td>
<td align="left" rowspan="1" colspan="1">10</td>
<td align="left" rowspan="1" colspan="1">5</td>
<td align="left" rowspan="1" colspan="1">1</td>
<td align="left" rowspan="1" colspan="1">0</td>
<td align="left" rowspan="1" colspan="1">10</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Peptides not recognized</td>
<td align="left" rowspan="1" colspan="1">112</td>
<td align="left" rowspan="1" colspan="1">146</td>
<td align="left" rowspan="1" colspan="1">142</td>
<td align="left" rowspan="1" colspan="1">127</td>
<td align="left" rowspan="1" colspan="1">82</td>
<td align="left" rowspan="1" colspan="1">37</td>
<td align="left" rowspan="1" colspan="1">15</td>
<td align="left" rowspan="1" colspan="1">4</td>
<td align="left" rowspan="1" colspan="1">49</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Peptides tested</td>
<td align="left" rowspan="1" colspan="1">203</td>
<td align="left" rowspan="1" colspan="1">196</td>
<td align="left" rowspan="1" colspan="1">175</td>
<td align="left" rowspan="1" colspan="1">139</td>
<td align="left" rowspan="1" colspan="1">92</td>
<td align="left" rowspan="1" colspan="1">42</td>
<td align="left" rowspan="1" colspan="1">16</td>
<td align="left" rowspan="1" colspan="1">4</td>
<td align="left" rowspan="1" colspan="1">59</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">% peptides recognized</td>
<td align="left" rowspan="1" colspan="1">44.83</td>
<td align="left" rowspan="1" colspan="1">25.51</td>
<td align="left" rowspan="1" colspan="1">18.86</td>
<td align="left" rowspan="1" colspan="1">8.63</td>
<td align="left" rowspan="1" colspan="1">10.87</td>
<td align="left" rowspan="1" colspan="1">11.90</td>
<td align="left" rowspan="1" colspan="1">6.25</td>
<td align="left" rowspan="1" colspan="1">0.00</td>
<td align="left" rowspan="1" colspan="1">16.95</td>
</tr>
</tbody>
</table>
</alternatives>
</table-wrap>
<p>To better characterize the coverage enhancement
afforded by inclusion of variant peptides, we
scored responses to a 10-mer only once for each
individual, i.e., if an individual responded to
the consensus we did not count responses to the
other variants tested. <xref ref-type="fig" rid="pone-0017969-g002">Figure 2B</xref>
reveals
the sparsity of the reactivity afforded by some
variants, underlining that variant peptides do not
elicit the same degree of recognition in the
population as consensus peptides. <xref ref-type="table" rid="pone-0017969-t001">Table
1</xref>
shows that although 41% of variant
1 peptides were recognized, only 25% of
these peptides elicited responses in individuals
who did not recognize the consensus. With the
decrease in frequency of the variants, there was a
diminishing number of new responses observed.
Twenty-nine percent of variants 3 and 26%
of variant 4 peptides were recognized, allowing
the detection of responses in 9 and 11%
more individuals, respectively (who had not
recognized the consensus or more frequent
variants).</p>
<p>In summary, each additional variant level tested
yielded smaller increases in the overall spectrum
of recognition. <xref ref-type="fig" rid="pone-0017969-g003">Figure 3</xref>
shows the
proportion of responses to the 203 segments
(n = 137) that were
identified by recognition of consensus
(n = 91) or variant
(n = 46) peptides. Of the
variant peptide responses, 18 were elicited by
‘variants 1’, 12 more responses were
detected using the second most common variants,
while identification of the last 16 responses
required seven more levels of variation.</p>
<fig id="pone-0017969-g003" position="float"><object-id pub-id-type="doi">10.1371/journal.pone.0017969.g003</object-id>
<label>Figure 3</label>
<caption><title>Distribution of responses between consensus
and variant 10-mers.</title>
<p>The pie chart represents the 137 HIV-1 segments
that were recognized in our cohort and the
proportion of these that were recognized through
the consensus 10-mers or through any of the
variant peptides.</p>
</caption>
<graphic xlink:href="pone.0017969.g003"></graphic>
</fig>
</sec>
<sec id="s3e"><title>Similar magnitudes of ELISpot responses
against consensus or variant peptides</title>
<p>We compared the average magnitude of responses
toward the consensus and variant peptides.
Ninety-one consensus peptides were recognized with
an average magnitude of 292 SFC/M
(median = 180 SFC/M), while
246 variant peptides were recognized with an
average magnitude of 243 SFC/M
(median = 170 SFC/M). Hence,
the consensus and variant epitopes elicited
responses of similar magnitudes
(p = 0.15) (<xref ref-type="supplementary-material" rid="pone.0017969.s003">Figure S3</xref>
).</p>
<p>Next, we analyzed the magnitude of responses for
pairs of consensus plus variant peptides, i.e.,
the average magnitude found for the consensus
peptide was compared to the average magnitude
elicited by the different variant peptides
beginning at the same position (irrespective of
whether the individual was able to elicit
responses against both consensus and variant
forms). There were 73 paired sets of
consensus/variant(s) that were recognized in the
cohort. The average magnitude elicited by the
consensus (318 SFC/M) or the variant peptides (261
SFC/M) were not significantly different:
p = 0.80 (<xref ref-type="fig" rid="pone-0017969-g004">Figure
4</xref>
).</p>
<fig id="pone-0017969-g004" position="float"><object-id pub-id-type="doi">10.1371/journal.pone.0017969.g004</object-id>
<label>Figure 4</label>
<caption><title>Magnitude of IFN-γ ELISpot responses
toward consensus and variant for paired sets of
peptides.</title>
<p>Responses of decreasing magnitude between the
consensus and variant peptide are figured in blue,
responses of increasing magnitude are figured in
red.</p>
</caption>
<graphic xlink:href="pone.0017969.g004"></graphic>
</fig>
<p>Last, we analyzed the magnitude of responses on
an individual basis, focusing on individuals who
mounted responses toward both the consensus and
one or more of the variant peptides. Of the 91
peptides that were recognized using consensus
peptides, variants of 44 of these were recognized
by at least one individual (and up to 11
individuals). There was no significant difference
in the magnitude of the responses elicited for the
consensus or for a variant
(p = 0.70).</p>
</sec>
<sec id="s3f"><title>Peptides that matched the subjects'
HIV-1 sequences elicited responses of higher
magnitude</title>
<p>We compared the sequence of the peptides
recognized by ELISpot to <italic>nef</italic>
gene
sequences from the infected individual, which were
available for five individuals. When the
subject's sequence matched the peptide
sequence, the ELISpot response had a higher
magnitude than when there was a mismatch between
the peptide sequences and the individual's
virus (<xref ref-type="fig" rid="pone-0017969-g005">Figure 5</xref>
). There
was a trend toward a decrease in the magnitude of
responses with an increase of peptide/virus
mismatches. The average magnitude of ELISpot
responses was not significantly different if
peptides exactly matched or had one mutation with
the individual's sequences
(p = 0.413), whereas the
magnitude of the response was significantly lower
when there were two
(p = 0.002) or three
(p = 0.039) mismatches.</p>
<fig id="pone-0017969-g005" position="float"><object-id pub-id-type="doi">10.1371/journal.pone.0017969.g005</object-id>
<label>Figure 5</label>
<caption><title>Magnitude of IFN-γ ELISpot responses
toward peptides that do or do not match each
individual's HIV-1 sequence.</title>
<p>The graph shows the magnitude of ELISpot
responses as a function of the number of mutations
between the peptide tested and the
individual's autologous HIV-1 consensus
sequence. This analysis was performed for the five
individuals in our cohort from whom HIV-1
sequences were available.</p>
</caption>
<graphic xlink:href="pone.0017969.g005"></graphic>
</fig>
</sec>
<sec id="s3g"><title>Lack of relationship between HIV-1-B Nef
sequence diversity and CTL targeting</title>
<p>We next examined the relationship between the
ELISpot recognition and the database variability
of the HIV-1 segments that were recognized. We
calculated the average Shannon Entropy for each
10-AA segment over the Nef protein based on an
alignment of 514 known, independent sequences. The
HIV-1 segments that were recognized were more
conserved (i.e., with lower Shannon Entropy) than
those that were never recognized (<xref ref-type="supplementary-material" rid="pone.0017969.s004">Figure S4</xref>
;
p<0.0001). Since Shannon Entropy is a measure
of HIV-1 variability for each segment of a protein
alignment, it assigns an identical entropy value
for every 10-mer mapped to the same segment of
HIV, i.e., it does not discriminate all the
specific 10-mer-variants that have the same HXB2
coordinates.</p>
<p>Thus, we chose an alternative way to evaluate the
impact of HIV-1diversity on ELISpot reactivity
using a peptide-specific metric. Based on 514
independent Nef HIV-1 subtype B sequences, we
calculated the population frequency of each unique
peptide derived from this dataset, i.e., the
percentage of sequences with the specific 10-mer.
We found no relationship between the population
frequency of a 10-mer and CTL targeting (<xref ref-type="fig" rid="pone-0017969-g006">Figure
6</xref>
). There was no relationship between the
frequency of a 10-mer in the population and its
frequency of recognition among individuals:
r<sup>2</sup>
= 0.0599
(p<0.0001; Spearman's correlation
coefficient ρ was 0.2349, p<0.0001) (<xref ref-type="fig" rid="pone-0017969-g006">Figure
6A</xref>
). Likewise, there was no relationship
between the frequency of a 10-mer in the
population and the magnitude of the ELISpot
responses:
r<sup>2</sup>
= 0.0256
(p = 0.0027; Spearman's
correlation coefficient
ρ = 0.1570,
p = 0.0032) (<xref ref-type="fig" rid="pone-0017969-g006">Figure
6B</xref>
). These results were confirmed when
using a more recent and larger dataset of 1184
independent HIV-1 subtype B sequences (curated
from sequences available at the HIVDB in Dec.
2009) (data not shown). Regarding the breadth of
the CTL response, peptides that were common in the
population, i.e., consensus-like, were recognized
by an important proportion of our cohort –
with up to 9 individuals recognizing the same
peptide.</p>
<fig id="pone-0017969-g006" position="float"><object-id pub-id-type="doi">10.1371/journal.pone.0017969.g006</object-id>
<label>Figure 6</label>
<caption><title>Population frequency of HIV-1-B Nef
peptides and IFN-γ ELISpot responses.</title>
<p>The frequency of each unique 10-mer in a
dataset of 514 independent Nef HIV-1 subtype B
sequences is shown. Peptide reactivity data
generated by IFN-γ ELISpot assays done on 26
HIV-1 infected individuals were used to analyze
the relationship between the population frequency
of a peptide and either its frequency of
recognition in the cohort (7A – left panel)
or the magnitude of the IFN-γ ELISpot
responses γ ELISpot response it elicited (7B
– right panel).</p>
</caption>
<graphic xlink:href="pone.0017969.g006"></graphic>
</fig>
</sec>
<sec id="s3h"><title>Cross-reactivity among CTL responses</title>
<p>It is particularly striking that peptides that
were rare in the population, i.e., found in less
than 5% of circulating HIV-1 sequences,
also elicited ELISpot responses in a number of
individuals. For example, a 10-mer found in
0.78% of circulating sequences was
recognized by 14 individuals (54% of our
cohort). There was a striking example of a peptide
(PGIRYP<italic><underline>I</underline>
</italic>
TFG)
found in 0.39% of database sequences that
was nonetheless recognized by six individuals
(average magnitude across the six
individuals = 250 SFC/M),
while the consensus epitope was not recognized
(PGIRYPLTFG). To evaluate potential
cross-reactivity between variant peptides, we
examined pairs of peptides in which one peptide
was found at least ten times more often among
circulating sequences than the other peptide. The
idea is that, in such situations, the reacting
rare peptide is likely to be cross-reactive. <xref ref-type="fig" rid="pone-0017969-g007">Figure
7</xref>
shows the fraction of epitopes that
putatively cross-react as a function of the number
of AA differences between the two epitopes. We
found that epitopes with a single AA substitution
were likely to be recognized, and that recognition
rates decreased as the number of AA changes
increased. Furthermore, we found that the peptides
are more likely to cross react if the AA changes
were conservative (p = 0.03,
0.0044, 0.14 for 8, 9, and 10 mers,
respectively).</p>
<fig id="pone-0017969-g007" position="float"><object-id pub-id-type="doi">10.1371/journal.pone.0017969.g007</object-id>
<label>Figure 7</label>
<caption><title>Cross-reactivity among HIV-1-B Nef
peptides.</title>
<p>The fraction of peptides that cross-react is
represented as a function of the number of AA
differences between the two peptides. For a pair
of peptides (with the same HXB2 coordinates), the
fraction of peptides that cross-react corresponds
to the number of individuals who recognized both
peptides divided by the number of individuals who
recognized the more common one.</p>
</caption>
<graphic xlink:href="pone.0017969.g007"></graphic>
</fig>
</sec>
</sec>
<sec id="s4"><title>Discussion</title>
<p>Using a variation-encompassing library of 944 10-AA-long
peptides that recapitulated much of the diversity
found among circulating HIV-1 subtype B Nef
peptides, we identified IFN-γ expressing
responses against 350 peptides, including all but
one of the known optimal epitopes in Nef, and
revealed many novel epitope specificities after
testing a set of only 26 HIV-1 infected individuals.
The peptide library consisted of consensus 10-mers
overlapping by 9 AA spanning the entire Nef protein
and multiple variants covering the range of Nef
diversity found in HIV-1-B infected individuals
– with up to 8 peptidic variants for a
consensus 10-mer. Our results suggest that
variability-inclusive vaccine antigens, such as
mosaic or COT+, can expand the breadth and
depth of CTL responses, as shown recently in
macaques <xref rid="pone.0017969-Barouch1" ref-type="bibr">[15]</xref>
,
<xref rid="pone.0017969-Santra1" ref-type="bibr">[16]</xref>
.</p>
<p>We demonstrated recognition of 297 Nef peptides in addition
to the 53 (optimally-defined or not) epitopes that
had previously been recorded in the HIVDB –
underlining that our understanding of the
determinants of epitope recognition is fairly
limited. It is particularly significant that this is
found for the oft-targeted Nef protein, suggesting
that our knowledge of epitopes in more variable
proteins such as Env is probably even more limited,
as previously indicated <xref rid="pone.0017969-Liu1" ref-type="bibr">[21]</xref>
. The
26 individuals in this cohort targeted a median of 7
discrete epitopic regions in Nef (up to 32 for one
individual), illustrating the common targeting of
Nef peptides in chronically-infected individuals as
previously reported <xref rid="pone.0017969-Frahm2" ref-type="bibr">[17]</xref>
.
The cross-sectional nature of our cohort and the
availability of HIV-1 sequence data for only five
individuals did not allow us to make inferences on
the biological effectiveness of the responses we
observed; indeed, we did not see any relationship
between the viral loads of the individuals and the
number of CTL responses they mounted or their
magnitude. So far, CTL responses to Nef have not
been associated with control of viral replication
<xref rid="pone.0017969-Kiepiela1" ref-type="bibr">[11]</xref>
, rather they have been
associated to higher viral loads compared to
responses to Gag which have been associated to lower
viremia <xref rid="pone.0017969-Ogg1" ref-type="bibr">[10]</xref>
,
<xref rid="pone.0017969-Kiepiela1" ref-type="bibr">[11]</xref>
.</p>
<p>Overall, reactive peptides were more likely to correspond to
more conserved portions of the HIV-1-B Nef protein -
the 350 peptides that elicited ELISpot responses
corresponded to viral regions of significantly lower
Shannon entropy than the HIV-1 regions encompassing
the 594 peptides that were not recognized
(p<0.0001). Although many CTL responses were
detected towards segments of lower Shannon entropy,
highly variable segments were also immunodominant
targets – in such cases only certain variants
of a 10-AA-long viral segment could be recognized.
Therefore, we used a measure of diversity that was
specific for each 10-mer variant corresponding to
the frequency of occurrence of each peptide among
circulating HIV-1-B sequences based on a dataset of
514 recorded Nef sequences obtained from HIV-1-B
infected individuals (using only independent
sequences). We found no relationship between the
frequency of a peptide and either the frequency of
recognition in our cohort or the magnitude of the
responses elicited.</p>
<p>We found that using a variability-enhanced peptide set
increased the breadth and depth of CTL responses,
suggesting that variability-inclusive vaccine
strategies could elicit broader recognition of
epitopes. Indeed, use of mosaic antigens was
recently shown to enhance cellular immune responses
in vaccinated monkeys <xref rid="pone.0017969-Barouch1" ref-type="bibr">[15]</xref>
,
<xref rid="pone.0017969-Santra1" ref-type="bibr">[16]</xref>
. In variability-enhanced
antigens, inclusion of common variants is favored
and rare peptides are specifically excluded from the
vaccine insert since these approaches were developed
to compress HIV-1 variability in a vaccine insert of
practical size (e.g., 2 to 4 gene lengths). The
hypothesis is that common variants would be more
likely to be found in infecting strains. We tested
the recognition of all the peptides that would be
included in 3 vaccine inserts and found that
maximizing coverage in the vaccine insert using the
COT+ method was useful to increase the number
of peptides recognized. However, the mechanism
behind the enhanced breadth appears different from a
linear increase in recognition of epitopes due to
increased-coverage of the viral diversity found
among circulating HIV-1-B sequences. While a
consensus peptide was generally the most likely to
be recognized, unique or very rare peptides were
also recognized. Of the 203 10-mer segments spanning
Nef, 91 were recognized using consensus peptides and
46 additional segments were recognized using
variants only (i.e., when the consensus was
negative). We observed diminishing returns in
epitope recognition as additional levels of
variation (stratified by their population frequency)
were tested. Interestingly, in the recent mosaic
vaccine studies in monkeys, Santra et al. <xref rid="pone.0017969-Santra1" ref-type="bibr">[16]</xref>
, using quadrivalent
antigens, reported a weaker enhancement of T cell
responses than did Barouch et al. <xref rid="pone.0017969-Barouch1" ref-type="bibr">[15]</xref>
(using bivalent antigens).
This difference may be associated in part with a
decreasing effectiveness with a quadrivalent antigen
compared to a bivalent one.</p>
<p>Unique viral peptides correspond to private mutations and
represent a significant and growing proportion of
the peptides found among circulating sequences, due
to the extensive and continuously expanding
diversity of HIV-1. We found that 61 peptides found
in less than 1% of circulating sequences were
recognized by at least one individual in our cohort,
and 26 of these rare peptides were recognized by
three or more individuals (and up to 14
individuals). For example, the consensus epitope
(PGIRYPLTFG) was not recognized while its variant
PGIRYP<italic><underline>I</underline>
</italic>
TFG
(found in 0.39% of database sequences) was
recognized by six individuals. In this instance, it
might be preferable to switch the consensus peptide
for the L7I variant in a vaccine insert or peptide
set in order to augment epitope recognition. On an
individual basis, it was striking that most single
mutations led to only modest and non-significant
decreases in the amplitude of the T cell response.
We showed that ELISpot responses elicited by these
unique/rare peptides may have been due to
cross-recognition with common variants: variants one
AA away from the consensus peptides were the most
likely to react, and this was particularly true if
the AA substitution was conservative. Our data
indicates that epitope binding to T cell receptors
is promiscuous and conforms to the model proposed by
McKinney and colleagues <xref rid="pone.0017969-McKinney1" ref-type="bibr">[22]</xref>
, which demonstrated that
multiple AA changes engineered in epitopes still
permitted CTL recognition in the context
HLA-A*0201 and HLA-A*1101. The breadth of
recognition of peptide variants is likely due in
part to the promiscuity in TCR binding <xref rid="pone.0017969-Buseyne1" ref-type="bibr">[23]</xref>
; our results showed no
significant difference in the magnitude of responses
between variants, yet we could not draw conclusions
as to whether the functional profiles of the
responses differed.</p>
<p>It remains to be understood what role is played by
cross-recognition of peptides in the control of
viral replication. Knowing HIV-1's propensity
to mutate, it is likely that several variants are
generated under CTL pressure and a number of
cross-reactive responses may be remainders of immune
responses against initial or previous viral variants
– it is crucial to determine under which
conditions those variants cross-react and whether
this has an impact on the efficacy of the anti-viral
CTL response. If a multiplicity of peptides still
induced substantial CTL responses without
significantly compromising viral fitness, there may
be a high genetic barrier to abolish CTL
recognition. Hence protection by such an epitope
might be explained by the complex patterns of
mutations that are necessary for efficient
escape.</p>
<p>Whether cross-reactivity has an effect on the CTL's
ability to control viral replication is an open
question that has important implications for vaccine
design. If cross-reactivity can broaden the CTL
response elicited by a vaccine and also has a
positive impact on the control of viremia, intrinsic
cross-reactive specificities of HIV-1 should be
harnessed to develop a potentially more immunogenic
vaccine candidate as a means to confer broadly
protective immunity against multiple strains.
However, the lack of association between the
population frequency of an HIV-1 peptide and its
recognition by individuals in the cohort reported
here also suggests that an unrealistically large
vaccine antigen size may be required to protect
against the universe of viral strains capable of
establishing an infection. In addition, since a
number of responses were due to cross-reactivity
between rare and frequent peptides, we surmised that
a number of these very rare peptides, which are
unlikely to have been found in the viruses from our
infected subjects, may not induce efficacious
anti-viral responses, but rather represent decoy
responses. These results led us to discard our
variability-inclusive COT+ vaccine strategy
<xref rid="pone.0017969-Nickle1" ref-type="bibr">[13]</xref>
in favor of a
‘Conserved Elements’ (CE) vaccine design
<xref rid="pone.0017969-Rolland2" ref-type="bibr">[24]</xref>
. CE vaccines seek to focus
responses on the most conserved segments of HIV-1 in
order both to elicit CTL responses considered
obligatory for viral control and to avoid CTL
responses toward variant peptides that allow escape
without hindering viral function and that may act as
immunological decoys with no clear efficacy in terms
of viral control.</p>
</sec>
<sec sec-type="supplementary-material" id="s5"><title>Supporting Information</title>
<supplementary-material content-type="local-data" id="pone.0017969.s001"><label>Figure S1</label>
<caption><p><bold>Frequency of 3,831 10-mer peptides in a
Nef protein dataset of 514 sequences.</bold>
Five
hundred and fourteen Nef sequences were dissected
into overlapping 10-mers. The majority of the
19,800 10-mer peptides were found only once
(n = 13,574 peptides) or
twice (n = 2,455 peptides) in
the dataset and are not shown in the graph. The
graph represents the 3,831 10-mer peptides that
were found at least twice in the dataset and the
number of occurrences of each peptide is
figured.</p>
<p>(TIFF)</p>
</caption>
<media xlink:href="pone.0017969.s001.tif"><caption><p>Click here for additional data file.</p>
</caption>
</media>
</supplementary-material>
<supplementary-material content-type="local-data" id="pone.0017969.s002"><label>Figure S2</label>
<caption><p><bold>Distribution of 944 10-mers along the Nef
protein.</bold>
Gray bars represent the numbers of
10-mer peptides starting at each position along
Nef. Values for each 10-mer are represented using
their corresponding start position based on HXB2
coordinates. The black line corresponds to the
average Shannon Entropy values calculated over
overlapping 10-AA segments covering the Nef
protein, based on an alignment of 514 independent
sequences from HIV-1 subtype B.</p>
<p>(TIFF)</p>
</caption>
<media xlink:href="pone.0017969.s002.tif"><caption><p>Click here for additional data file.</p>
</caption>
</media>
</supplementary-material>
<supplementary-material content-type="local-data" id="pone.0017969.s003"><label>Figure S3</label>
<caption><p><bold>Magnitude of IFN-γ ELISpot responses
toward consensus and variant peptides.</bold>
</p>
<p>(TIFF)</p>
</caption>
<media xlink:href="pone.0017969.s003.tif"><caption><p>Click here for additional data file.</p>
</caption>
</media>
</supplementary-material>
<supplementary-material content-type="local-data" id="pone.0017969.s004"><label>Figure S4</label>
<caption><p><bold>HIV-1-B Nef variability and IFN-γ
ELISpot recognition.</bold>
Average Shannon
Entropy scores were calculated for each 10-mer
using an alignment of 514 independent sequences
from HIV-1 subtype B. Peptide-specific Shannon
Entropy values were compared based on their
recognition in IFN-γ ELISpot assays done on 26
HIV-1 infected individuals.</p>
<p>(TIFF)</p>
</caption>
<media xlink:href="pone.0017969.s004.tif"><caption><p>Click here for additional data file.</p>
</caption>
</media>
</supplementary-material>
<supplementary-material content-type="local-data" id="pone.0017969.s005"><label>Table S1</label>
<caption><p><bold>IFN-γ ELISpot responses detected
against 944 Nef peptides (10-mer) in 26
HIV-infected individuals.</bold>
</p>
<p>(XLS)</p>
</caption>
<media xlink:href="pone.0017969.s005.xls"><caption><p>Click here for additional data file.</p>
</caption>
</media>
</supplementary-material>
</sec>
</body>
<back><fn-group><fn fn-type="COI-statement"><p><bold>Competing Interests: </bold>
David E. Heckerman is an employee of Microsoft
Research. This does not alter the authors'
adherence to all the PLoS ONE policies on sharing
data and materials, as detailed online in the
guide for authors.</p>
</fn>
<fn fn-type="financial-disclosure"><p><bold>Funding: </bold>
This work was supported by an unrestricted gift
from Microsoft Research, the Bill and Melinda
Gates Foundation (43437) and by grants to MR from
amfAR (Mathilde Krim Fellowship - 107005-43-RFNT),
the Computational Biology Core of the University
of Washington Centers for AIDS Research and STD
(National Institutes of Health AI27757), and a
grant to JIM from the University of Washington
Center for AIDS Research (P30
AI27757)(bioinformatics core). These funders had
no role in study design, data collection and
analysis, decision to publish, or preparation of
the manuscript. DEH is an employee of Microsoft
Research and MR is currently employed by the Henry
M. Jackson Foundation for the Advancement of
Military Medicine (HJF) (this study was completed
prior to MR's employment at HJF).</p>
</fn>
</fn-group>
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