Animals were housed and handled following national guidelines and as approved by our animal ethics committee.
BALB/c mice were bred and maintained under specific pathogen-free (SPF) conditions by the Department of Molecular Parasitology, Humboldt University Berlin, Berlin, Germany. Infection of mice with HB was carried out by oral gavage with 200 L3 stage larvae in distilled water.
Mice were narcotized and bled either by cardiac or retro-orbital puncture at the age of 8 weeks. Blood samples were collected from healthy SPF-BALB/c mice (n = 15), which were then infected with HB. Blood was collected at three time points post infection (dpi): at 10 dpi (n = 15), 14 dpi (n = 13) and 18 dpi (n = 15). The blood was allowed to clot at room temperature and centrifuged. The supernatant was stored at -20°C.
The 13 human monoclonal antibodies were kindly provided by the group of Hedda Wardemann (Max Planck Institute for Infection Biology, Berlin, Germany). Ten different Ig gene sequences of IgG+ memory B cells from 2 healthy human donors, PN and VB, (PN115, PN138, PN16, PN89, VB1, VB142, VB161, VB176, VB18, VB4)  and three further ones from 3 other human donors ED38 , eiJB40 and mGO53  were expressed as detailed in .
Random peptide library
The peptide library consists of 255 different 14-mer peptides. Their sequence was designed with a random generator. Repetitions of three or more consecutive amino acids were not allowed.
Peptide synthesis and microarray design
The peptide library was displayed in five identical sub-arrays on each slide purchased from JPT Peptide Technologies GmbH, Berlin, Germany. Furthermore, TAMRA-derived peptides, as internal fluorescence control, and mouse-IgM, mouse-IgG, human-IgM and human-IgG as secondary antibody controls, were included on each sub-array. Peptide microarrays were stored at 4°C.
Antibody binding assays
The microarrays were briefly immersed in 100% v/v ethanol, washed three times with T-PBS (phosphate buffered saline containing 0.05% w/v Tween20), three times with deionized water and dried by centrifugation. Since the microarray surfaces had been pre-treated to minimize unspecific binding of the target antibodies, no blocking step was required prior to incubation. All incubations were performed using a five-well adhesive incubation chamber (Multiwell GeneFrameTM, ABgene Germany, Hamburg, Germany) with a total assay volume of 45μL per well. Serum was diluted 1:10 in T-PBS and monoclonal antibodies were applied in a concentration of 10μg/mL. We showed in a technological case study that approximately 10μg/ml of antibody are best for reliable signal intensity measurements . The concentration of IgM in in the serum of healthy SPF BALB/c mice was found to be around 0.50 mg/ml , which yields 50μg/ml for a 1:10 dilution. The diluted sera are thus within the optimal binding range. After incubation for four hours at room temperature, the microarrays were washed three times with T-PBS and three times with deionized water. Serum-antibody binding was detected with polyclonal goat anti-mouse IgM-Alexa Fluor 546 and polyclonal goat anti-mouse IgG-Alexa Fluor 647 (Invitrogen Ltd, Paisley, UK), simultaneously.
Monoclonal antibody binding was detected with polyclonal goat anti-human IgG Alexa Fluor 647 (Invitrogen Ltd, Paisley, UK). Secondary antibodies were diluted in T-PBS (20μg/mL, 300μL) and incubated for one hour at room temperature. The microarrays were washed three times with T-PBS, three times with deionized water, rinsed with running deionized water and dried by centrifugation. Water, ethanol and PBS were filtered.
Fluorescence signals were measured on a GenePix microarray scanner (Molecular Devices GmbH, Ismaning, Germany) with a 532 nm laser using green (~ 550-600 nm) emission filters and with 635 nm laser using red (~ 650-690 nm) emission filters. An image file was generated at a resolution of 10μ
m using the scanner-associated GenePix®
Pro software. Signal intensities were quantified with Genespotter™ software (MicroDiscovery GmbH, Berlin, Germany). Genespotter provides a fully automated grid-finding function, resulting in a reproducible read-out procedure. Signal intensities for each spot were calculated from a circular region around the center of the spot. Spots were examined for auto-fluorescence, but no relevant correlation between peptide composition and the fluorescence of clean microarrays was observed. Measured raw signal intensities were logtransformed (log(I)). Subsequently, the signal arising from the polyclonal secondary antibody was removed according to the linear model:
By PLS-based computation of the intercepts, β
0 and β
1, we replaced log(I) with the resulting PLS-computed, mean-centered and scaled-to-unit variance residuals ε for further analysis. The results reported in the main text of this paper are based exclusively on the calculated normalized residuals.
The two-sided, non-paired Wilcoxon rank sum test was used to compute all p-values. P-values were regarded as significant when p < 0.05. Association between variables was assessed by Pearson correlation (r) unless otherwise stated.
Generation of simulated signal intensities with a mathematical model
Peptides and antibody binding sites were modeled as strings. Binding strengths between antibodies and the various amino acid residues of a peptide, referred to as assigned AAWS
, were sampled from the uniform distribution on the closed interval 0. A binding site on an antibody
was simulated in a similar fashion with a random number from the closed interval [-1, 1] for every sequential position and scaled such that
. The binding association between peptide
was calculated by
Based on the interpretation of the binding association as being negatively linearly proportional to the standard Gibbs free energy change of reaction, Δ
, the binding affinity K
, that is, the thermodynamic equilibrium association constant for antibody k
binding peptide i
, is defined as shown in Equation 4
Similar to a bit string model approach in , our approach to calculating K
assumes additivity in free energy of binding, an assumption that is supported by experimental results [48, 49]. The signal intensity that we measure on the array is assumed to be proportional to the ratio of bound-to-total surface of the peptide spot, S
. An expression for this quantity, based on the law of mass action, can be obtained from classical Langmuir adsorption theory  resulting in Equation 2 with R = 8.314472, T = 273.15 + 25, β
0 = 0 and β
1 = RT.
At last, signal intensities were log-transformed, mean-centered, and scaled to unit variance. If Gaussian noise (
(μ = 0, σ = 0.01)) was introduced into simulated signal intensities, the noise term was introduced before logarithmic transformation of the data. We showed that, for monoclonal antibodies, visibly fluorescent spots have at least a K-value of 107M-1 .
Partial least squares regression
All calculations involving PLS were carried out with the pls package  for the R statistical programming environment .
The predictive performance is defined as:
is the left-out test data set, the signal intensity of which is predicted (
) from the remaining training data set. The left-out test data represented randomly chosen 10% of the total data set.
Principal component analysis
Principal component analysis was performed using the pcaMethods R-package .