Tyrosine Sulfation at Antibody Light Chain CDR-1 Increases Binding Affinity and Neutralization Potency to Interleukine-4.

Structure and function of therapeutic antibodies can be modulated by a variety of post-translational modifications (PTM). Tyrosine (Tyr) sulfation is a type of negatively charged PTM that occurs during protein trafficking through the Golgi. In this study, we discovered that an anti-interleukin (IL)-4 human IgG1, produced by transiently transfected HEK293 cells, contained a fraction of unusual negatively charged species. Interestingly, the isolated acidic species exhibited a two-fold higher affinity to IL-4 and a nearly four-fold higher potency compared to the main species. Mass spectrometry (MS) showed the isolated acidic species possessed an +80-Dalton from the expected mass, suggesting an occurrence of Tyr sulfation. Consistent with this hypothesis, we show the ability to control the acidic species during transient expression with the addition of Tyr sulfation inhibitor sodium chlorate or, conversely, enriched the acidic species from 30% to 92% of the total antibody protein when the IL-4 IgG was co-transfected with tyrosylprotein sulfotransferase genes. Further MS and mutagenesis analysis identified a Tyr residue at the light chain complementarity-determining region-1 (CDRL-1), which was sulfated specifically. These results together have demonstrated for the first time that Tyr sulfation at CDRL-1 could modulate antibody binding affinity and potency to a human immune cytokine.

IL-13 Controls IL-33 Activity through Modulation of ST2.

IL-33 is a multifunctional cytokine that mediates local inflammation upon tissue damage. IL-33 is known to act on multiple cell types including group 2 innate lymphoid cells (ILC2s), Th2 cells, and mast cells to drive production of Th2 cytokines including IL-5 and IL-13. IL-33 signaling activity through transmembrane ST2L can be inhibited by soluble ST2 (sST2), which acts as a decoy receptor. Previous findings suggested that modulation of IL-13 levels in mice lacking decoy IL-13Rα2, or mice lacking IL-13, impacted responsiveness to IL-33. In this study, we used Il13 -/- mice to investigate whether IL-13 regulates IL-33 activity by modulating the transmembrane and soluble forms of ST2. In Il13 -/- mice, the effects of IL-33 administration were exacerbated relative to wild type (WT). Il13 -/- mice administered IL-33 i.p. had heightened splenomegaly, more immune cells in the peritoneum including an expanded ST2L+ ILC2 population, increased eosinophilia in the spleen and peritoneum, and reduced sST2 in the circulation and peritoneum. In the spleen, lung, and liver of mice given IL-33, gene expression of both isoforms of ST2 was increased in Il13 -/- mice relative to WT. We confirmed fibroblasts to be an IL-13-responsive cell type that can regulate IL-33 activity through production of sST2. This study elucidates the important regulatory activity that IL-13 exerts on IL-33 through induction of IL-33 decoy receptor sST2 and through modulation of ST2L+ ILC2s.

A 2-Approximation Scheme for Sorting Signed Permutations by Reversals, Transpositions, Transreversals, and Block-Interchanges.

We consider the problem of sorting signed permutations by reversals, transpositions, transreversals, and block-interchanges and give a 2-approximation scheme, called the GSB (Genome Sorting by Bridges) scheme. Our result extends 2-approximation algorithm of He and Chen [12] that allowed only reversals and block-interchanges, and also the 1.5 approximation algorithm of Hartman and Sharan [11] that allowed only transreversals and transpositions. We prove this result by introducing three bridge structures in the breakpoint graph, namely, the L-bridge, T-bridge, and X-bridge and show that they model "proper" reversals, transpositions, transreversals, and block-interchanges, respectively. We show that we can always find at least one of these three bridges in any breakpoint graph, thus giving an upper bound on the number of operations needed. We prove a lower bound on the distance and use it to show that GSB has a 2-approximation ratio. An ${\text{O(n}}^{3})$O(n3) algorithm called GSB-I that is based on the GSB approximation scheme presented in this paper has recently been published by Yu, Hao, and Leong in [17] . We note that our 2-approximation scheme admits many possible implementations by varying the order we search for proper rearrangement operations.

Modulation of the IL-33/IL-13 Axis in Obesity by IL-13Rα2.

In obesity, IL-13 overcomes insulin resistance by promoting anti-inflammatory macrophage differentiation in adipose tissue. Endogenous IL-13 levels can be modulated by the IL-13 decoy receptor, IL-13Rα2, which inactivates and depletes the cytokine. In this study, we show that IL-13Rα2 is markedly elevated in adipose tissues of obese mice. Mice deficient in IL-13Rα2 had high expression of IL-13 response markers in adipose tissue, consistent with increased IL-13 activity at baseline. Moreover, exposure to the type 2 cytokine-inducing alarmin, IL-33, enhanced serum and tissue IL-13 concentrations and elevated tissue eosinophils, macrophages, and type 2 innate lymphoid cells. IL-33 also reduced body weight, fat mass, and fasting blood glucose levels. Strikingly, however, the IL-33-induced protection was greater in IL-13Rα2-deficient mice compared with wild-type littermates, and these changes were largely attenuated in mice lacking IL-13. Although IL-33 administration improved the metabolic profile in the context of a high fat diet, it also resulted in diarrhea and perianal irritation, which was enhanced in the IL-13Rα2-deficient mice. Weight loss in this group was associated with reduced food intake, which was likely related to the gastrointestinal effects. These findings outline both potentially advantageous and deleterious effects of a type 2-skewed immune response under conditions of metabolic stress, and identify IL-13Rα2 as a critical checkpoint in adipose tissues that limits the protective effects of the IL-33/IL-13 axis in obesity.

Therapeutic activity of an interleukin-4/interleukin-13 dual antagonist on oxazolone-induced colitis in mice.

Interleukin-4 (IL-4) and IL-13 are critical drivers of immune activation and inflammation in ulcerative colitis, asthma and other diseases. Because these cytokines may have redundant function, dual targeting holds promise for achieving greater efficacy. We have recently described a bifunctional therapeutic targeting IL-4 and IL-13 developed on a novel protein scaffold, generated by combining specific binding domains in an optimal configuration using appropriate linker regions. In the current study, the bifunctional IL-4/IL-13 antagonist was evaluated in the murine oxazolone-induced colitis model, which produces disease with features of ulcerative colitis. The bifunctional IL-4/IL-13 antagonist reduced body weight loss throughout the 7-day course of the model, and ameliorated the increased colon weight and decreased colon length that accompany disease. Colon tissue gene expression was modulated in accordance with the treatment effect. Concentrations of serum amyloid P were elevated in proportion to disease severity, making it an effective biomarker. Serum concentrations of the bifunctional IL-4/IL-13 antagonist were inversely proportional to disease severity, colon tissue expression of pro-inflammatory genes, and serum amyloid P concentration. Taken together, these results define a panel of biomarkers signifying engagement of the IL-4/IL-13 pathway, confirm the T helper type 2 nature of disease in this model, and demonstrate the effectiveness of dual cytokine blockade.

BBH-LS: an algorithm for computing positional homologs using sequence and gene context similarity.

BACKGROUND: Identifying corresponding genes (orthologs) in different species is an important step in genome-wide comparative analysis. In particular, one-to-one correspondences between genes in different species greatly simplify certain problems such as transfer of function annotation and genome rearrangement studies. Positional homologs are the direct descendants of a single ancestral gene in the most recent common ancestor and by definition form one-to-one correspondence. RESULTS: In this work, we present a simple yet effective method (BBH-LS) for the identification of positional homologs from the comparative analysis of two genomes. Our BBH-LS method integrates sequence similarity and gene context similarity in order to get more accurate ortholog assignments. Specifically, BBH-LS applies the bidirectional best hit heuristic to a combination of sequence similarity and gene context similarity scores. CONCLUSION: We applied our method to the human, mouse, and rat genomes and found that BBH-LS produced the best results when using both sequence and gene context information equally. Compared to the state-of-the-art algorithms, such as MSOAR2, BBH-LS is able to identify more positional homologs with fewer false positives.

Bidirectional best hit r-window gene clusters.

BACKGROUND: Conserved gene clusters are groups of genes that are located close to one another in the genomes of several species. They tend to code for proteins that have a functional interaction. The identification of conserved gene clusters is an important step towards understanding genome evolution and predicting gene function. RESULTS: In this paper, we propose a novel pairwise gene cluster model that combines the notion of bidirectional best hits with the r-window model introduced in 2003 by Durand and Sankoff. The bidirectional best hit (BBH) constraint removes the need to specify the minimum number of shared genes in the r-window model and improves the relevance of the results. We design a subquadratic time algorithm to compute the set of BBH r-window gene clusters efficiently. CONCLUSION: We apply our cluster model to the comparative analysis of E. coli K-12 and B. subtilis and perform an extensive comparison between our new model and the gene teams model developed by Bergeron et al. As compared to the gene teams model, our new cluster model has a slightly lower recall but a higher precision at all levels of recall when the results were ranked using statistical tests. An analysis of the most significant BBH r-window gene cluster show that they correspond to known operons.

Gene team tree: a hierarchical representation of gene teams for all gap lengths.

The identification of spatially co-located gene clusters is an important step towards understanding genome evolution and function. Gene team is a popular model for conserved gene clusters that constrains the maximum distance between adjacent genes in the same cluster. Existing algorithms for finding gene teams require the specification of the maximum allowed distance, delta. However, determining suitable values of delta is non-trivial, due to varying rates of rearrangement and differences in the distribution of genes across multiple genomes. Instead of trying to determine a single best value of delta, we propose constructing the Gene Team Tree, a compact representation of gene teams for all values of delta. The teams computed can then be verified/scored using application specific methods. Our algorithm for computing the GTT extends existing gene team mining algorithms without increasing their time complexity. We compute the GTT for E. coli K-12 and B. subtilis and show that E. coli K-12 operons are modelled by gene teams with different values of delta. We demonstrate the scalability of our method and the trade-off involved when comparing more than two genomes, through a comparative study using five gamma-proteobacteria genomes. Lastly, we describe how to compute the GTT for multi-chromosomal genomes and illustrate by computing the GTT for the human and mouse genomes. An implementation of the algorithms described in this article and the datasets used in the experiments can be downloaded from http://www.comp.nus.edu.sg/~leonghw/GTT .

High-throughput, cell-free, liposome-based approach for assessing in vitro activity of lipid kinases.

Lipid kinases are central players in lipid signaling pathways involved in inflammation, tumorigenesis, and metabolic syndrome. A number of these kinase targets have proven difficult to investigate in higher throughput cell-free assay systems. This challenge is partially due to specific substrate interaction requirements for several of the lipid kinase family members and the resulting incompatibility of these substrates with most established, homogeneous assay formats. Traditional, cell-free in vitro investigational methods for members of the lipid kinase family typically involve substrate incorporation of [gamma-32P] and resolution of signal by thin-layer chromatography (TLC) and autoradiograph densitometry. This approach, although highly sensitive, does not lend itself to high-throughput testing of large numbers of small molecules (100 s to 1 MM+). The authors present the development and implementation of a fully synthetic, liposome-based assay for assessing in vitro activity of phosphatidylinositol-5-phosphate-4-kinase isoforms (PIP4KIIbeta and alpha) in 2 commonly used homogeneous technologies. They have validated these assays through compound testing in both traditional TLC and radioactive filterplate approaches as well as binding validation using isothermic calorimetry. A directed library representing known kinase pharmacophores was screened against type IIbeta phosphatidylinositol-phosphate kinase (PIPK) to identify small-molecule inhibitors. This assay system can be applied to other types and isoforms of PIPKs as well as a variety of other lipid kinase targets.