A minimal model of peptide binding predicts ensemble properties of serum antibodies.

BACKGROUND: The importance of peptide microarrays as a tool for serological diagnostics has strongly increased over the last decade. However, interpretation of the binding signals is still hampered by our limited understanding of the technology. This is in particular true for arrays probed with antibody mixtures of unknown complexity, such as sera. To gain insight into how signals depend on peptide amino acid sequences, we probed random-sequence peptide microarrays with sera of healthy and infected mice. We analyzed the resulting antibody binding profiles with regression methods and formulated a minimal model to explain our findings. RESULTS: Multivariate regression analysis relating peptide sequence to measured signals led to the definition of amino acid-associated weights. Although these weights do not contain information on amino acid position, they predict up to 40-50% of the binding profiles' variation. Mathematical modeling shows that this position-independent ansatz is only adequate for highly diverse random antibody mixtures which are not dominated by a few antibodies. Experimental results suggest that sera from healthy individuals correspond to that case, in contrast to sera of infected ones. CONCLUSIONS: Our results indicate that position-independent amino acid-associated weights predict linear epitope binding of antibody mixtures only if the mixture is random, highly diverse, and contains no dominant antibodies. The discovered ensemble property is an important step towards an understanding of peptide-array serum-antibody binding profiles. It has implications for both serological diagnostics and B cell epitope mapping.

Affinity maturation of B cells involves not only a few but a whole spectrum of relevant mutations.

Affinity maturation of B lymphocytes within germinal centers involves both diversification of their B-cell receptors (BCRs) by somatic hypermutation (SHM) and a crucial receptor-mediated selection step. However, in contrast to recent advances in revealing the molecular mechanism of SHM, the fundamentals of the selection process are still poorly understood, i.e. it is often not clear how and how many mutations contribute to improving a BCR during the response against a given antigen. A general drawback in assessing the mutations relevant to the selection process is the difficult task of rating the relative contributions of selection and intrinsic biases to the experimentally observed mutation patterns of BCRs. The approach proposed here is premised on statistical comparison of the frequency distributions of nucleotide substitutions as observed in datasets of hypermutated BCRs against their frequency distribution expected under the null hypothesis of no selection. Thereby, we show that the spectrum of mutations relevant to maturation of canonical anti-(4-hydroxy-3-nitrophenyl)acetyl BCRs is much broader than previously acknowledged, going beyond the scope of single key mutations. Moreover, our results suggest that maturation not only involves selection by means of affinity but likewise expression and stabilization of BCRs.

Systems Analysis Reveals High Genetic and Antigen-Driven Predetermination of Antibody Repertoires throughout B Cell Development.

Antibody repertoire diversity and plasticity is crucial for broad protective immunity. Repertoires change in size and diversity across multiple B cell developmental stages and in response to antigen exposure. However, we still lack fundamental quantitative understanding of the extent to which repertoire diversity is predetermined. Therefore, we implemented a systems immunology framework for quantifying repertoire predetermination on three distinct levels: (1) B cell development (pre-B cell, naive B cell, plasma cell), (2) antigen exposure (three structurally different proteins), and (3) four antibody repertoire components (V-gene usage, clonal expansion, clonal diversity, repertoire size) extracted from antibody repertoire sequencing data (400 million reads). Across all three levels, we detected a dynamic balance of high genetic (e.g., >90% for V-gene usage and clonal expansion in naive B cells) and antigen-driven (e.g., 40% for clonal diversity in plasma cells) predetermination and stochastic variation. Our study has implications for the prediction and manipulation of humoral immunity.

Retinol-binding protein 4 and its membrane receptor STRA6 control adipogenesis by regulating cellular retinoid homeostasis and retinoic acid receptor α activity.

Retinoids are vitamin A (retinol) derivatives and complex regulators of adipogenesis by activating specific nuclear receptors, including the retinoic acid receptor (RAR) and retinoid X receptor (RXR). Circulating retinol-binding protein 4 (RBP4) and its membrane receptor STRA6 coordinate cellular retinol uptake. It is unknown whether retinol levels and the activity of RAR and RXR in adipocyte precursors are linked via RBP4/STRA6. Here, we show that STRA6 is expressed in precursor cells and, dictated by the apo- and holo-RBP4 isoforms, mediates bidirectional retinol transport that controls RARα activity and subsequent adipocyte differentiation. Mobilization of retinoid stores in mice by inducing RBP4 secretion from the liver activated RARα signaling in the precursor cell containing the stromal-vascular fraction of adipose tissue. Retinol-loaded holo-RBP4 blocked adipocyte differentiation of cultured precursors by activating RARα. Remarkably, retinol-free apo-RBP4 triggered retinol efflux that reduced cellular retinoids, RARα activity, and target gene expression and enhanced adipogenesis synergistically with ectopic STRA6. Thus, STRA6 in adipocyte precursor cells links nuclear RARα activity to the circulating RBP4 isoforms, whose ratio in obese mice was shifted toward limiting the adipogenic potential of their precursors. This novel cross talk identifies a retinol-dependent metabolic function of RBP4 that may have important implications for the treatment of obesity.