B cell repertoire sequencing of HIV-1 pediatric elite-neutralizers identifies multiple broadly neutralizing antibody clonotypes

IntroductionA limited subset of HIV-1 infected adult individuals typically after at least 2-3 years of chronic infection, develop broadly neutralizing antibodies (bnAbs), suggesting that highly conserved neutralizing epitopes on the HIV-1 envelope glycoprotein are difficult for B cell receptors to effectively target, during natural infection. Recent studies have shown the evolution of bnAbs in HIV-1 infected infants.MethodsWe used bulk BCR sequencing (BCR-seq) to profile the B cell receptors from longitudinal samples (3 time points) collected from a rare pair of antiretroviralnaïve, HIV-1 infected pediatric monozygotic twins (AIIMS_329 and AIIMS_330) who displayed elite plasma neutralizing activity against HIV-1.ResultsBCR-seq of both twins revealed convergent antibody characteristics including V-gene use, CDRH3 lengths and somatic hypermutation (SHM). Further, antibody clonotypes with genetic features similar to highly potent bnAbs isolated from adults showed ongoing development in donor AIIMS_330 but not in AIIMS_329, corroborating our earlier findings based on plasma bnAbs responses. An increase in SHM was observed in sequences of the IgA isotype from AIIMS_330.DiscussionThis study suggests that children living with chronic HIV-1 can develop clonotypes of HIV-1 bnAbs against multiple envelope epitopes similar to those isolated from adults, highlighting that such B cells could be steered to elicit bnAbs responses through vaccines aimed to induce bnAbs against HIV-1 in a broad range of people including children

Clonify: unseeded antibody lineage assignment from next-generation sequencing data

Defining the dynamics and maturation processes of antibody clonal lineages is crucial to understanding the humoral response to infection and immunization. Although individual antibody lineages have been previously analyzed in isolation, these studies provide only a narrow view of the total antibody response. Comprehensive study of antibody lineages has been limited by the lack of an accurate clonal lineage assignment algorithm capable of operating on next-generation sequencing datasets. To address this shortcoming, we developed Clonify, which is able to perform unseeded lineage assignment on very large sets of antibody sequences. Application of Clonify to IgG+ memory repertoires from healthy individuals revealed a surprising lack of influence of large extended lineages on the overall repertoire composition, indicating that this composition is driven less by the order and frequency of pathogen encounters than previously thought. Clonify is freely available at www.github.com/briney/clonify-python

Clonify: unseeded antibody lineage assignment from next-generation sequencing data

Defining the dynamics and maturation processes of antibody clonal lineages is crucial to understanding the humoral response to infection and immunization. Although individual antibody lineages have been previously analyzed in isolation, these studies provide only a narrow view of the total antibody response. Comprehensive study of antibody lineages has been limited by the lack of an accurate clonal lineage assignment algorithm capable of operating on next-generation sequencing datasets. To address this shortcoming, we developed Clonify, which is able to perform unseeded lineage assignment on very large sets of antibody sequences. Application of Clonify to IgG+ memory repertoires from healthy individuals revealed a surprising lack of influence of large extended lineages on the overall repertoire composition, indicating that this composition is driven less by the order and frequency of pathogen encounters than previously thought. Clonify is freely available at www.github.com/briney/clonify-python

Commonality despite exceptional diversity in the baseline human antibody repertoire

In principle, humans can produce an antibody response to any non-self-antigen molecule in the appropriate context. This flexibility is achieved by the presence of a large repertoire of naive antibodies, the diversity of which is expanded by somatic hypermutation following antigen exposure$^{1}$. The diversity of the naive antibody repertoire in humans is estimated to be at least 10$^{12}$ unique antibodies$^{2}$. Because the number of peripheral blood B cells in a healthy adult human is on the order of 5 × 10$^{9}$, the circulating B cell population samples only a small fraction of this diversity. Full-scale analyses of human antibody repertoires have been prohibitively difficult, primarily owing to their massive size. The amount of information encoded by all of the rearranged antibody and T cell receptor genes in one person-the 'genome' of the adaptive immune system-exceeds the size of the human genome by more than four orders of magnitude. Furthermore, because much of the B lymphocyte population is localized in organs or tissues that cannot be comprehensively sampled from living subjects, human repertoire studies have focused on circulating B cells$^{3}$. Here we examine the circulating B cell populations of ten human subjects and present what is, to our knowledge, the largest single collection of adaptive immune receptor sequences described to date, comprising almost 3 billion antibody heavy-chain sequences. This dataset enables genetic study of the baseline human antibody repertoire at an unprecedented depth and granularity, which reveals largely unique repertoires for each individual studied, a subpopulation of universally shared antibody clonotypes, and an exceptional overall diversity of the antibody repertoire

Human Peripheral Blood Antibodies with Long HCDR3s Are Established Primarily at Original Recombination Using a Limited Subset of Germline Genes

<div><p>A number of antibodies that efficiently neutralize microbial targets contain long heavy chain complementarity determining region 3 (HCDR3) loops. For HIV, several of the most broad and potently neutralizing antibodies have exceptionally long HCDR3s. Two broad potently neutralizing HIV-specific antibodies, PG9 and PG16, exhibit secondary structure. Two other long HCDR3 antibodies, 2F5 and 4E10, protect against mucosal challenge with SHIV. Induction of such long HCDR3 antibodies may be critical to the design of an effective vaccine strategy for HIV and other pathogens, however it is unclear at present how to induce such antibodies. Here, we present genetic evidence that human peripheral blood antibodies containing long HCDR3s are not primarily generated by insertions introduced during the somatic hypermutation process. Instead, they are typically formed by processes occurring as part of the original recombination event. Thus, the response of B cells encoding antibodies with long HCDR3s results from selection of unusual clones from the naïve repertoire rather than through accumulation of insertions. These antibodies typically use a small subset of D and J gene segments that are particularly suited to encoding long HCDR3s, resulting in the incorporation of highly conserved genetic elements in the majority of antibody sequences encoding long HCDR3s.</p> </div

Amino acid residues in J_H6 and RF2 of D3-3 germline gene segments are critical to binding and neutralization of HIV by long HCDR3-containing antibodies PG9 and PG16.

<p>The HCDR3 amino acid sequences of HIV-specific mAbs PG9 and PG16 are shown aligned to the amino acid sequences of germline D3-3 and J_H6 genes. Dashes in the alignments indicate conservation with the respective PG antibody. Residues shown to be critical to binding or neutralization of HIV, defined as ≥10-fold decrease in either binding or neutralization when mutagenized <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0036750#pone.0036750-Pancera1" target="_blank">[5]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0036750#pone.0036750-Pejchal2" target="_blank">[24]</a> are indicated by filled circles.</p

Skewed germline gene usage in antibodies containing long or very long HCDR3s.

<p>Peripheral blood antibody sequences from Group 1 (n = 4) and Group 2 (n = 3) healthy donors were assembled into the following three groups by HCDR3 length: (1) all HCDR3s, which contains all sequences of any HCDR3 length; (2) long HCDR3s, which contains only sequences with a HCDR3 length ≥24 amino acids; and (3) very long HCDR3s, which contains only sequences with a HCDR3 length ≥28 amino acids. The frequency of each germline variable gene family, diversity gene family, and joining gene was determined for each HCDR3 length group. The mean frequency ± SEM is shown. All HCDR3 lengths were calculated using the IMGT numbering system. The p values were determined using a two-way ANOVA with Bonferroni post-tests. All statistically significant differences are indicated. * = p<0.05, ** = p<0.01, *** = p<0.001.</p

Increased HCDR3 length does not correlate with affinity maturation events.

<p>(A) Peripheral blood antibody sequences were grouped by mutation frequency and the percent of sequences in each group that contained codon-length (non-frameshift) insertions was calculated for each donor. All values for healthy donors from Group 1 (n = 4) and Group 2 (n = 3) are shown in the left panel, with the mean percentage ± SEM shown for each mutation value. In the right panel, sequences from Group 1 healthy donors were segregated by B cell subset, and the best-fit linear regression for each subset is shown. (B) Peripheral blood antibody sequences were grouped by HCDR3 length (in amino acids) and the mean number of mutations for each HCDR3 length group was calculated for each donor. As in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0036750#pone-0036750-g001" target="_blank">Figure 1A</a>, the left panel shows the mean ± SEM for all donors in Group 1 and Group 2. The right panel shows the best-fit linear regression of each B cell subset for Group 1 donors. The percent of sequences within each HCDR3 length group containing non-frameshift insertions also was calculated. In the left panel, the mean percentage ± SEM for all donors in Group 1 and Group 2 is shown. In the right panel, the best-fit linear regression of each B cell subset is shown for Group 1 donors. (C) Peripheral blood antibody sequences from Group 1 healthy donors were grouped by donor into naïve and memory subsets and the percent of sequences containing long HCDR3s (≥24 amino acids in length, or two standard deviations above the mean HCDR3 length). The percentages for each donor are shown, with the mean ± SEM. (D) The donor groups from <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0036750#pone-0036750-g001" target="_blank">Figure 1C</a> were analyzed for the frequency of very long HCDR3s (≥28 amino acids in length, <i>i.e.</i>, three standard deviations above the mean HCDR3 length). The percentages for each donor are shown, with the mean ± SEM. The p values were determined using a one-way ANOVA. All statistically significant differences are indicated. * = p<0.05, ** = p<0.01, *** = p<0.001.</p

Correction: Tissue-Specific Expressed Antibody Variable Gene Repertoires.

[This corrects the article DOI: 10.1371/journal.pone.0100839.]

Long HCDR3s preferentially use reading frames (RF) that result in reduced hydrophobicity.

<p>(A) Peripheral blood antibody sequences from Group 1 and Group 2 healthy donors (left panel) or HIV-infected donors (right panel) were assembled into three HCDR3 length groups: (1) all HCDR3s; (2) HCDR3s of at least 24 amino acids; and (3) HCDR3s of at least 28 amino acids. (B) The percentage of sequences within each HCDR3 group using reading frame 2 of the diversity gene (RF2) was calculated for each HCDR3 length group. Non-linear regression analysis produced a sigmoidal curve of best fit (r² = 0.84). (C) Sequences that do not encode the joining gene J_H6 (top panel) or do encode J_H6 (bottom panel) were grouped by HCDR3 length and RF2 use within each HCDR3 length group was determined. The mean frequency ± SEM is shown. Non-linear regression analysis produced a sigmoidal curve of best fit. (D) The percentage of hydrophobic residues was calculated for each reading frame of every functional (lacking stop codons) diversity gene in the D2 and D3 germline gene families. The mean percentage ± SEM is shown for each reading frame. The RF2 hydrophobicity of the diversity genes which were shown to be increased in long HCDR3s are indicated by filled circles. The p values were determined using a Student’s two-tailed t-test. (E) The grand average of hydropathicity (GRAVY) was calculated for each functional reading frame of each D2 and D3 gene. A positive GRAVY score indicates hydrophobicity, and a negative GRAVY score indicates hydrophilicity. The mean GRAVY score ± SEM is shown for each reading frame. The RF2 GRAVY scores of the diversity genes that were shown to be increased in long HCDR3s are indicated by filled circles. The p values were determined using Student’s two-tailed t-test. All statistically significant differences are indicated. * = p<0.05, ** = p<0.01, *** = p<0.001.</p