A Robust High Throughput Platform to Generate Functional Recombinant Monoclonal Antibodies Using Rabbit B Cells from Peripheral Blood

<div><p>We have developed a robust platform to generate and functionally characterize rabbit-derived antibodies using B cells from peripheral blood. The rapid high throughput procedure generates a diverse set of antibodies, yet requires only few animals to be immunized without the need to sacrifice them. The workflow includes (i) the identification and isolation of single B cells from rabbit blood expressing IgG antibodies, (ii) an elaborate short term B-cell cultivation to produce sufficient monoclonal antigen specific IgG for comprehensive phenotype screens, (iii) the isolation of VH and VL coding regions via PCR from B-cell clones producing antigen specific and functional antibodies followed by the sequence determination, and (iv) the recombinant expression and purification of IgG antibodies. The fully integrated and to a large degree automated platform (demonstrated in this paper using IL1RL1 immunized rabbits) yielded clonal and very diverse IL1RL1-specific and functional IL1RL1-inhibiting rabbit antibodies. These functional IgGs from individual animals were obtained at a short time range after immunization and could be identified already during primary screening, thus substantially lowering the workload for the subsequent B-cell PCR workflow. Early availability of sequence information permits one to select early-on function- and sequence-diverse antibodies for further characterization. In summary, this powerful technology platform has proven to be an efficient and robust method for the rapid generation of antigen specific and functional monoclonal rabbit antibodies without sacrificing the immunized animal.</p></div

Concordance of VL and VH sequences of single <i>E. coli</i> colonies derived from pool-cloning shown for 8 different B-cell clones (ASCs).

<p>Concordance of VL and VH sequences of single <i>E. coli</i> colonies derived from pool-cloning shown for 8 different B-cell clones (ASCs).</p

Results of the primary screening using primary supernatants (SN) of the B-Cell Cloning workflow containing monoclonal rabbit antibodies.

<p>The statistically confirmed thresholds were rabbit IgG >0.013 µg/ml, human IL1RL1 binding >OD (optical density) 0.195, human Fc binding ≤OD 0.125, cynomolgus IL1RL1 binding >OD 0.184, murine IL1RL1 binding >OD 0.164, and biochemical human IL1RL1:IL33 inhibition ≥40%.</p

Yield of IL1RL1-specific rabbit antibodies.

<p>Scatter Plots depicting the yield of the primary screening using all 7644 supernatants: (<b>A</b>) Human IL1RL1 binding (unit: optical density (OD)) versus IgG concentration; (<b>B</b>) human IL1RL1 binding versus cynomolgus IL1RL1 binding or versus (<b>C</b>) murine IL1RL1 binding. Scatter Plot showing the correlation of the biochemical inhibition assay with the cellular inhibition assay: (<b>D</b>) Threshold ≥40% inhibition, RSq: 0.36, (<b>E</b>) magnification of <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0086184#pone-0086184-g003" target="_blank">Figure 3D</a> using the threshold of >90% inhibition, RSq: 0.9. The statistically confirmed cut off values for the calculation of the percentages were as follows: rabbit IgG-positive >0.013 µg/ml, human IL1RL1-positive >OD 0.195, human Fc-positive ≤OD 0.125, cynomolgus IL1RL1-positive >OD 0.184, murine IL1RL1-positive >OD 0.164. Green are the supernatants deriving from the pre-incubation only scenario and red are the SN after the protein panning step. The diamond, the circle and the cross indicate the three different animals. (<b>F</b>) Result of the two dimensional binding matrix identifying different binding epitopes on human IL1RL1. The colored numbers indicate different antigen specific antibodies. The black numbers describe the three antibody groups. The degree of antibody competition in the matrix is depicted by a 3-colour scale with green, black, red color indicating highest competition, mid or lowest competition, respectively.</p

Analysis of the VH-VDJ and VK-VJ sequences to assess clonality and diversity of the recombinant rabbit antibodies.

<p>The distribution of the (A) CDR-H3 length (amino acid count) and of the (B) amino acid replacement frequency within the VH region in comparison to VHa1 and VHa3 allotype germ line sequences. Dark grey: VH1a1 germ line gene; light grey: VH1a3 germ line gene. (C) Clustering of the rabbit antibodies according to their CDR-H3 and CDR-L3 sequence similarity. The bold numbers indicate the rabbits.</p

Comparison of the classical and the ligation-independent expression cloning workflows.

<p>Comparison of the classical and the ligation-independent expression cloning workflows.</p

Functionality and sequence diversity of the recombinant antibodies per animals and bleeds.

*<p>”Functional” refers to the biochemical IL1RL1:IL33 inhibition assay with a cut off of ≥40% inhibition.</p

Influence of the improvements of the B-cell handling and the B-cell cultivation.

<p>(<b>A</b>) Percentage of IgG-producing B-cell clones per total wells and (<b>B</b>) average IgG concentration over all IgG-positive wells after +/− pre-incubation in medium and +/− centrifugation post sorting. For each parameter 368 wells were analyzed. (<b>C</b>) Percentage of IgG-producing B-cell clones (ASCs) per total wells and (<b>D</b>) average IgG concentration over all IgG-positive wells after using +/− SAC in a dilution of 1∶20000 during B-cell cultivation. For each parameter 252 wells were analyzed. (<b>E</b>) Percentage of IgG-producing B-cell clones per total wells, (<b>F</b>) average IgG concentration over all IgG-positive wells, as well as percentage of antigen specific B-cell clones (<b>G</b>) per total wells and (<b>H</b>) per IgG-producing B-cell clones after +/− protein panning. For each parameter around 3500 wells were analyzed. The error bars represent the standard deviation. The cut off value of IgG-positive wells was >0.013 µg/ml IgG and of human IL1RL1-positive wells was>OD 0.195.</p

ROC plots for comparison of 3D classifiers to sequence-based prediction shows significant decrease of false-positive rates.

<p>Evaluation of different statistical methods is compared with only sequence-based prediction. For statistical classification methods, average numbers of false-positive and false-negative Asn/Asp residues are results of 40 rounds of Monte Carlo cross validation. TPR (true positive rate)  =  number of true positives divided by number of positives. FPR (false positive rate)  =  number of false positives divided by number of negatives. Tree, rpart, PP (Pipeline Pilot) tree, and RandomForest are recursive partitioning algorithms; svm, ksvm are support vector machine algorithms; rda is a regularized discriminant analysis algorithm; nnet is a neural network; sequence-based corresponds to prediction based on sequence motifs NG, NS, NT, and DG, DS, DT, DD, DH. The Pipeline Pilot tree, shown as a yellow circle, was selected as prediction algorithm, at pruning level 4. <b>A</b>: Asp model; <b>B</b>: Asn model. Panels <b>C</b> and <b>D</b> show a zoom view of the panels A and B, respectively. The numerical values shown in these graphs can be found in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0100736#pone.0100736.s005" target="_blank">Table S3</a>.</p

ROC plot for comparison of different pruning levels of decision trees.

<p>Decision trees were pruned automatically as implemented in Pipeline Pilot. Average numbers of false-positive and false-negative Asn/Asp residues are results of 40 rounds of Monte Carlo cross validation. TPR (true positive rate)  =  number of true positives divided by number of positives. FPR (false positive rate)  =  number of false positives divided by number of negatives. Trees 1-3 and 5-6 are shown as spheres, tree 4 as a black triangle. Tree 1 is the un-pruned tree model. Tree 4 was selected for prediction.</p