Additional file 7: of BALDR: a computational pipeline for paired heavy and light chain immunoglobulin reconstruction in single-cell RNA-seq data

Sequences from nested RT-PCR. The Ig chains obtained from Sanger sequencing of nested RT-PCR. (XLSX 62 kb

Additional file 5: of BALDR: a computational pipeline for paired heavy and light chain immunoglobulin reconstruction in single-cell RNA-seq data

Somatic hypermutations in human single-cell datasets. The number of somatic hypermutations for AW2_AW3 plasmablast and VH CD19+ Lin– single cells compared to the IMGT germline sequences. (XLSX 19 kb

Additional file 6: of BALDR: a computational pipeline for paired heavy and light chain immunoglobulin reconstruction in single-cell RNA-seq data

Percentage of immunoglobulin reads in human plasmablasts and CD19+ Lin– B cells. The percentage of Ig reads is calculated by dividing the number of reads mapping to the top model to the total number of reads for AW2-AW3 plasmablast dataset and VH CD19+ Lin– B cell dataset. (XLSX 23 kb

Additional file 4: of BALDR: a computational pipeline for paired heavy and light chain immunoglobulin reconstruction in single-cell RNA-seq data

Discordant reconstructions for AW2_AW3 dataset IgH chains. The V, D, J genes, CDR3 sequences, and complete reconstructed sequence are shown for discordant IgH reconstructions along with annotations for Ig reconstruction with Unfiltered methods and the PCR sequence. Also included are models that were filtered in the BALDR pipeline, as they were not predicted to be productive. (XLSX 18 kb

Additional file 3: of BALDR: a computational pipeline for paired heavy and light chain immunoglobulin reconstruction in single-cell RNA-seq data

Clonal assignments for human single-cell datasets. The single cells were assigned to clonal families based on the V, J and CDR length for paired IGH and IgL chains. (XLSX 46 kb

Additional file 2: of BALDR: a computational pipeline for paired heavy and light chain immunoglobulin reconstruction in single-cell RNA-seq data

Results of Ig reconstruction using BALDR. The V(D)J gene annotations, CDR3 sequences, the number of reads mapping to the Ig chain using bowtie2, whether the chain is productive, and the complete sequences are shown for the Ig chains reconstructed using BALDR pipeline for all the human datasets (AW2-AW3 (SE151) plasmablast dataset with and without in silico read normalization, plasmablast AW1 (PE101, PE75, PE50, SE101, SE75, and SE50), the VH (PE76) CD19+ Lin– B cell dataset, and the AW2-AW3 (SE50) for IG_mapped+Unmapped method) and the rhesus macaque datasets (BL8, BL6.1, and BL6.2). When the RT-PCR sequence is available, the V(D)J genes and the CDR3 sequence are also shown for the corresponding chains, and concordance between the BALDR reconstructed chains and the RT-PCR sequence is indicated. The results for Ig reconstruction using the BASIC method are also shown along with matching RT-PCR for AW2-AW3 (SE101 and SE50), VH (PE76), and AW1 (PE101, PE75, PE50, SE101, SE75, and SE50) datasets. (XLSX 2190 kb

Additional file 1; of BALDR: a computational pipeline for paired heavy and light chain immunoglobulin reconstruction in single-cell RNA-seq data

Supplementary figures and tables. (PDF 8130 kb

Higher avidities and neutralization capacities observed for monoclonal antibodies from SLE patients.

<p>(A) Monoclonal antibodies generated from plasmablasts isolated from subjects were tested for virus binding by ELISA. Binding avidities (K_D) were estimated by Scatchard plot analyses of ELISA data. K_D values of pooled antibodies are shown. Medians were compared using Mann-Whitney test. (B) The distribution of K_D values is shown by subject. Each bar graph represents the median of the avidities of antibodies (represented by symbol) for each subject. The red dotted line represents the global median avidity of all SLE and control influenza-positive antibodies. (C) Avidities of 53 influenza-positive antibodies from SLE patients and 27 from controls were measured by SPR. Correlation between approximated K_D values from virus ELISA data and K_D values measured by SPR is shown. Black symbols are antibodies from SLE patients while blue are those from controls. Correlation was determined by Spearman’s correlation test. (D-E) Influenza-positive antibodies were serially diluted and tested in the standard HAI assay (D) and microneutralization (E) for functional capability. Medians were compared using Mann-Whitney test. (D) Minimum antibody concentration effective at inhibiting hemagglutination is plotted for each HAI-positive antibody. (E) Same as (D), except for microneutralization. Results are representative of at least three independent replicates.</p

Heavy and light chain gene features of influenza-specific antibodies from SLE patients and controls.

<p>(A) Pie charts show the proportion of clonally related sequences in the influenza-positive antibodies from SLE patients and controls. (B) Number of somatic mutations in VH and VK chain gene sequences of influenza-positive antibodies is plotted. For each graph, in the left panel, each symbol represents an individual antibody, while in the right panel; each symbol is the average number of mutations of all the antibodies for each individual. (C) Proportion of influenza-positive antibodies with different variable heavy (VH) CDR3 lengths (number of amino acids). (D) Proportion of pooled antibodies with different joining region JH, VH, VK and JK gene identities. (E) Isoelectric points of VH chain CDR3 gene segments of influenza-positive antibodies from SLE patients and controls. The left panel shows each symbol representing an individual antibody, while in the right, each symbol is the average of all the antibodies for each individual. Means were compared in B and E using unpaired t-test. Chi-squared test was used to compare the frequency of the individual categories between SLE and controls (* p < 0.05) in C and D.</p

Distinct serum cytokine profiles seen in subjects with high avidity antibodies and models discussing the production of high affinity antibodies in context of autoimmunity.

<p>(A) The levels of various cytokines in the serum of subjects, measured by multiplex bead assay, are shown on a graded color scale. Cytokines are grouped according to their major roles in immune responses and subjects are ranked by the median avidity of each subject as shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125618#pone.0125618.g001" target="_blank">Fig 1D</a>. Serum cytokine levels were normalized by the minimum (blue) and maximum (red) values within each dataset. (B) The affinity-risk model postulates that individuals who have the propensity to make high affinity responses will have higher risk for autoimmunity, especially if primary B cell tolerance mechanisms are also disrupted and the naïve B cell population is more self-reactive than normal. Thicker red arrows indicate greater probability of the event. (C) The autoreactivity-risk model proposes that anergy (or other factors) may be contribute to the increased activation threshold of self-reactive B cells in SLE patients so that only B cells with high enough affinity for the antigen are activated, thus skewing the response towards a higher affinity B cell response.</p