Structure and biological functions of IL-31 and IL-31 receptors

Division of Medical Cell Biology, College of Life Sciences, Sichuan University, Chengdu, PR China.
Cytokine & growth factor reviews (Impact Factor: 5.36). 11/2008; 19(5-6):347-56. DOI: 10.1016/j.cytogfr.2008.08.003
Source: PubMed


Interleukin-31, produced mainly by activated CD4(+) T cells, is a newly discovered member of the gp130/IL-6 cytokine family. Unlike all the other family members, IL-31 does not engage gp130. Its receptor heterodimer consists of a unique gp130-like receptor chain IL-31RA, and the receptor subunit OSMRbeta that is shared with another family member oncostatin M (OSM). Binding of IL-31 to its receptor activates Jak/STAT, PI3K/AKT and MAPK pathways. IL-31 acts on a broad range of immune- and non-immune cells and therefore possesses potential pleiotropic physiological functions, including regulating hematopoiesis and immune response, causing inflammatory bowel disease, airway hypersensitivity and dermatitis. This review summarizes the recent findings on the biological characterization and physiological roles of IL-31 and its receptors.

1 Follower
10 Reads
  • Source
    • "Recent studies have shown that IL-31RA forms a functional receptor complex for IL-31 together with the beta subunit of oncostatin M receptor (OSMRß). IL-31 might be involved in controlling keratinocyte differentiation and proliferation and also has a number of effects that point to a role in the regulation of immune responses in skin [8] [11]. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Primary localized cutaneous amyloidosis (PLCA) is a chronic skin disorder, caused by amyloid material deposition in the upper dermis. Autosomal dominant PLCA has been mapped earlier to pathogenic missense mutations in the OSMR gene, which encodes the oncostatin M receptor ß subunit (OSMRß). OSMRß is interleukin-6 family cytokine receptors and possesses two ligands, oncostatin M and interleukin-31, which both have biologic roles in inflammation and keratinocyte cell proliferation, differentiation, and apoptosis. Here, we identified a new OSMR mutation in a Kurdish family for the first time. Blood samples were taken from all the affected individuals in the family. DNA extraction was performed using salting out technique. Primers were designed for intron flanking individual exons of OSMR gene which were subjected to direct sequencing after PCR amplification for each sample. Sequencing showed a C/T substitution at position 613 in the proband. This mutation results in an L613S (leucine 613 to serine) amino acid change. The identified mutation was observed in all affected family members but not in 100 ethnically matched healthy controls. Elucidating the molecular basis of familial PLCA provides new insight into mechanisms of itch in human skin and may lead to new therapeutic targets for pruritus.
    BioMed Research International 06/2014; 2014:653724. DOI:10.1155/2014/653724 · 3.17 Impact Factor
  • Source
    • "Several studies have reported associations with SCS/CM with genetic markers on chromosome 20 (Sodeland et al., 2011; Meredith et al., 2012; Sahana et al., 2013) with many of them overlapping or nearby the regions detected in this study. Nevertheless, a number of possible candidate genes have been identified including the IL31Rα gene which acts as part of a receptor complex for the IL-31 cytokine in the activation of signaling pathways including the JAK-STAT and MAPK pathways which can initiate a wide range of immunological processes (Zhang et al., 2008; Cornelissen et al., 2012). The detection of a QTL region in close proximity to a number of genes of the complement system also looks promising given the importance of the complement system in both host innate and adaptive immunity. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Mastitis is an inflammation-driven disease of the bovine mammary gland that occurs in response to physical damage or infection and is one of the most costly production-related diseases in the dairy industry worldwide. We performed a genome-wide association study (GWAS) to identify genetic loci associated with somatic cell score (SCS), an indicator trait of mammary gland inflammation. A total of 702 Holstein-Friesian bulls were genotyped for 777,962 single nucleotide polymorphisms (SNPs) and associated with SCS phenotypes. The SCS phenotypes were expressed as daughter yield deviations (DYD) based on a large number of progeny performance records. A total of 138 SNPs on 15 different chromosomes reached genome-wide significance (corrected p-value ≤ 0.05) for association with SCS (after correction for multiple testing). We defined 28 distinct QTL regions and a number of candidate genes located in these QTL regions were identified. The most significant association (p-value = 1.70 × 10−7) was observed on chromosome 6. This QTL had no known genes annotated within it, however, the Ensembl Genome Browser predicted the presence of a small non-coding RNA (a Y RNA gene) in this genomic region. This Y RNA gene was 99% identical to human RNY4. Y RNAs are a rare type of non-coding RNA that were originally discovered due to their association with the autoimmune disease, systemic lupus erythematosus. Examining small-RNA sequencing (RNAseq) data being generated by us in multiple different mastitis-pathogen challenged cell-types has revealed that this Y RNA is expressed (but not differentially expressed) in these cells. Other QTL regions identified in this study also encoded strong candidate genes for mastitis susceptibility. A QTL region on chromosome 13, for example, was found to contain a cluster of β-defensin genes, a gene family with known roles in innate immunity. Due to the increased SNP density, this study also refined the boundaries for several known QTL for SCS and mastitis.
    Frontiers in Genetics 11/2013; 4:229. DOI:10.3389/fgene.2013.00229
  • Source
    • "Among the top 25 genes obtained by integrating CN gains with somatic mutations were known DLBCL-associated oncogenes such as PIM1 [26], CARD11 [27], MYC, EZH2 [28], and BCL2 [29]. In addition, the analysis identified KLHL6 (a target of CN gains in 23% of cases and mutations in 8%), a gene involved in BCR signaling and germinal center formation in mice [30], IL31 (CN gains in 18% of cases and mutations in 3%), a gene involved in the activation of JAK/STAT, PI3K/AKT and MAPK signaling [31], and LRP1 (gained in 24% of cases and mutated in 3%), a gene promoting cancer cell invasion [32]. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Background Most tumors are the result of accumulated genomic alterations in somatic cells. The emerging spectrum of alterations in tumors is complex and the identification of relevant genes and pathways remains a challenge. Furthermore, key cancer genes are usually found amplified or deleted in chromosomal regions containing many other genes. Point mutations, on the other hand, provide exquisite information about amino acid changes that could be implicated in the oncogenic process. Current large-scale genomic projects provide high throughput genomic data in a large number of well-characterized tumor samples. Methods We define a Bayesian approach designed to identify candidate cancer genes by integrating copy number and point mutation information. Our method exploits the concept that small and recurrent alterations in tumors are more informative in the search for cancer genes. Thus, the algorithm (Mutations with Common Focal Alterations, or MutComFocal) seeks focal copy number alterations and recurrent point mutations within high throughput data from large panels of tumor samples. Results We apply MutComFocal to Diffuse Large B-cell Lymphoma (DLBCL) data from four different high throughput studies, totaling 78 samples assessed for copy number alterations by single nucleotide polymorphism (SNP) array analysis and 65 samples assayed for protein changing point mutations by whole exome/whole transcriptome sequencing. In addition to recapitulating known alterations, MutComFocal identifies ARID1B, ROBO2 and MRS1 as candidate tumor suppressors and KLHL6, IL31 and LRP1 as putative oncogenes in DLBCL. Conclusions We present a Bayesian approach for the identification of candidate cancer genes by integrating data collected in large number of cancer patients, across different studies. When trained on a well-studied dataset, MutComFocal is able to identify most of the reported characterized alterations. The application of MutComFocal to large-scale cancer data provides the opportunity to pinpoint the key functional genomic alterations in tumors.
    BMC Systems Biology 03/2013; 7(1):25. DOI:10.1186/1752-0509-7-25 · 2.44 Impact Factor
Show more


10 Reads
Available from