Ko-Wei Lin

MARCKS Regulation of Mucin Secretion by Airway Epithelium in Vitro: Interaction with Chaperones

We have reported previously that myristoylated alanine-rich C kinase substrate (MARCKS) is a key regulatory molecule controlling mucin secretion by airway epithelial cells in vitro and in vivo. The results of those studies supported a mechanism whereby MARCKS, upon phosphorylation by protein kinase C (PKC), translocates from plasma membrane to cytoplasm, where its binding to membranes of intracellular mucin granules is a key component of the secretory pathway. It remains unknown how MARCKS is targeted to and/or preferentially attaches to mucin granule membranes. We hypothesized that the chaperone cysteine string protein (CSP) may play an important role in this process. CSP was shown to associate with membranes of intracellular mucin granules in well-differentiated normal human bronchial epithelial (NHBE) cells in vitro, as determined by ultrastructural immunohistochemistry and Western blotting of isolated granule membranes. CSP in these cells complexed with MARCKS, as shown by co-immunoprecipitation. Given reported associations between CSP and a second chaperone, heat shock protein 70 (HSP70), a role for HSP70 in the MARCKS-dependent secretory mechanism also was investigated. HSP70 appeared to form a trimeric complex with MARCKS and CSP associated with mucin granule membranes within airway epithelial cells. Transfection of the HBE1 human bronchial epithelial cell line with siRNAs targeting sequences of MARCKS, CSP, or HSP70 resulted, in each case, in significant knockdown of expression of these proteins and subsequent attenuation of mucin secretion. The results provide the first evidence that CSP and HSP70, and their interactions with MARCKS, are involved in mucin secretion.

Surfactant Protein D-Mediated Decrease of Allergen-Induced Inflammation Is Dependent upon CTLA4

Pulmonary surfactant protein D (SP-D), a member of the collectin family, is an innate immune molecule critical for defense that can also modulate adaptive immune responses. We previously showed that SP-D–deficient mice exhibit enhanced allergic responses and that SP-D induction requires lymphocytes. Thus, we postulated that SP-D may decrease adaptive allergic responses through interaction with T cells. In this study, we used two forms of SP-D, a dodecamer and a shorter fragment containing the trimeric neck and carbohydrate recognition domains (SP-D NCRD). Both forms decreased immune responses in vitro and in a murine model of pulmonary inflammation. SP-D NCRD increased transcription of CTLA4, a negative regulator of T cell activation, in T cells. SP-D NCRD no longer decreased lymphoproliferation and IL-2 cytokine production when CTLA4 signals were abrogated. Administration of SP-D NCRD in vivo no longer decreased allergen induced responses when CTLA4 was inhibited. Our results indicate that SP-D decreases allergen responses, an effect that may be mediated by increase of CTLA4 in T cells.

MARCKS and Related Chaperones Bind to Unconventional Myosin V Isoforms in Airway Epithelial Cells

We have shown previously that myristoylated alanine-rich C kinase substrate (MARCKS) is a key regulatory molecule in the process of mucin secretion by airway epithelial cells, and that part of the secretory mechanism involves intracellular associations of MARCKS with specific chaperones: heat shock protein 70 (Hsp70) and cysteine string protein (CSP). Here, we report that MARCKS also interacts with unconventional myosin isoforms within these cells, and further molecular interactions between MARCKS and these chaperones/cytoskeletal proteins are elucidated. Primary human bronchial epithelial cells and the HBE1 cell line both expressed myosin V and VI proteins, and both MARCKS and CSP were shown to bind to myosin V, specifically Va and Vc. This binding was enhanced by exposing the cells to phorbol-12-myristate-13-acetate, an activator of protein kinase C and stimulator of mucin secretion. Binding of MARCKS, Hsp70, and CSP was further investigated by His-tagged pull down assays of purified recombinant proteins and multiple transfections of HBE1 cells with fusion proteins (MARCKS-HA; Flag-Hsp70; c-Myc-CSP) and immunoprecipitation. The results showed that MARCKS binds directly to Hsp70, and that Hsp70 binds directly to CSP, but that MARCKS binding to CSP appears to require the presence of Hsp70. Interrelated binding(s) of MARCKS, chaperones, and unconventional myosin isoforms may be integral to the mucin secretion process.

Emerging pathways in asthma: Innate and adaptive interactions☆

BACKGROUND Allergic asthma is a complex and chronic airway inflammatory disorder, and the prevalence of asthma has increased. Adaptive antigen-dependent immunity is a classical pathway of asthmatic pathology. Recent studies have focused on innate antigen-independent immunity in asthma. SCOPE OF REVIEW This review discusses updated research associating innate immunity with allergic asthma. We focus on innate molecules (Toll-like receptors and nucleotide-binding oligomerization domain-like receptors) and review studies regarding innate and adaptive interactions in allergic responses (surfactant protein D, lipopolysaccharide, and early life immune responses). We also highlight new emerging concepts in the field applicable to innate immunity and asthma. MAJOR CONCLUSIONS Innate immunity plays a key role in asthma. Understanding innate and adaptive interactions provide significant information in asthmatic research. Innate molecules not only contribute to classical pulmonary defense, but also modulate inflammatory responses. Emerging concepts in the analysis of the microbiome, microRNA and autophagy may provide new insights in searching therapeutic targets. GENERAL SIGNIFICANCE Finding specific mechanisms of innate and/or adaptive immunity in asthma are timely goals for further research. Integration of bioinformatics and systems biology tools, particularly in relation to microbiome analysis, may be helpful in providing an understanding to allergic immune responses. This article is part of a Special Issue entitled Biochemistry of Asthma.

PhenDisco: phenotype discovery system for the database of genotypes and phenotypes

The database of genotypes and phenotypes (dbGaP) developed by the National Center for Biotechnology Information (NCBI) is a resource that contains information on various genome-wide association studies (GWAS) and is currently available via NCBIs dbGaP Entrez interface. The database is an important resource, providing GWAS data that can be used for new exploratory research or cross-study validation by authorized users. However, finding studies relevant to a particular phenotype of interest is challenging, as phenotype information is presented in a non-standardized way. To address this issue, we developed PhenDisco (phenotype discoverer), a new information retrieval system for dbGaP. PhenDisco consists of two main components: (1) text processing tools that standardize phenotype variables and study metadata, and (2) information retrieval tools that support queries from users and return ranked results. In a preliminary comparison involving 18 search scenarios, PhenDisco showed promising performance for both unranked and ranked search comparisons with dbGaPs search engine Entrez. The system can be accessed at http://pfindr.net.

T Cells and Lung Injury. Impact of Rapamycin

Acute lung injury (ALI) is characterized by pulmonary inflammation and edema. Innate immune cells (e.g., neutrophils and macrophages) are major contributors to inflammation in ALI. Less is known regarding the role of T cells. We examined the effects of rapamycin on inflammation in a LPS-induced murine model of ALI. Rapamycin was administered before and after initiation of injury. Inflammatory parameters, including bronchoalveolar lavage cell counts, T cell surface markers (i.e., cytotoxic T lymphocyte antigen 4 [CTLA4] and fork head-winged helix transcription factor [Foxp3]), T cell activation (CD69), IL-6, and IL-10 were analyzed. Rapamycin significantly decreased inflammatory parameters and decreased Foxp3, CTLA4, and CD69 in CD4(+) T cells. Rapamycin administration before or after the onset of lung injury, as well as systemically or by pulmonary routes, ameliorates inflammation in ALI.

Feasibility of using Clinical Element Models (CEM) to standardize phenotype variables in the database of genotypes and phenotypes (dbGaP).

The database of Genotypes and Phenotypes (dbGaP) contains various types of data generated in Genome Wide Association Studies (GWAS). These data can be used to facilitate novel scientific discovery and to reduce cost and time for exploratory research. However, idiosyncrasies in variable names become a major barrier for reusing these data. We studied the problem of formalizing the phenotype variable descriptions using Clinical Element Models (CEM). Direct mapping of 379 phenotype names to existing CEM yielded a low rate of exact matches (N=25). However, the flexible and expressive underlying information models of CEM provided a robust means of representing 115 phenotype variable descriptions, indicating that CEMs can be successfully applied to standardize a large portion of the clinical variables contained in dbGaP.

Regulation of Cytotoxic T Lymphocyte Antigen 4 by Cyclic AMP

Recent studies indicate that cyclic AMP (cAMP) induces cytotoxic T lymphocyte antigen (CTLA) 4. CTLA4 is expressed in T cells, and is a negative regulator of T cell activation. CTLA4 expression is regulated by T cell receptor plus CD28 (adaptive immune signaling) at both the transcriptional and post-transcriptional level. Here, we examine the pathways by which cAMP regulates CTLA4 expression, focusing on transcriptional activation. Elevating intracellular cAMP levels by cell-permeable cAMP analogs, the adenylyl cyclase activator, forskolin, or phosphodiesterase inhibitors increases CTLA4 mRNA expression in EL4 murine T cells and primary CD4(+) T cells. Activation of protein kinase A (using the protein kinase A-selective agonist, N6-phenyladenosine-cAMP), but not exchange proteins activated by cAMP (using the exchange proteins activated by cAMP-selective 8-pCPT-2Me-cAMP), increases CTLA4 promoter activity. Mutation constructs of the CTLA4 promoter uncover an enhancer binding site located within the -150 to -130 bp region relative to the transcription start site. Promoter analysis and chromatin immunoprecipitation assays suggest that cAMP response element-binding is a putative transcription factor induced by cAMP. We have previously shown that CTLA4 mediates decreased pulmonary inflammation in an LPS-induced murine model of acute lung injury (ALI). We observed that LPS can induce CTLA4 transcription via the same cAMP-inducible promoter region. The immunosuppressant, rapamycin, decreases cAMP and LPS-induced CTLA4 transcription in vitro. In vivo, LPS induces cAMP accumulation in bronchoalveolar lavage fluid, bronchoalveolar lavage cells, and lung tissues in ALI. We demonstrate that rapamycin decreases cAMP accumulation and CTLA4 expression in ALI. Together, these data suggest that cAMP may negatively regulate pulmonary inflammatory responses in vivo and in vitro by altering CTLA4 expression.

Demographics Identification: Variable Extraction Resource (DIVER)

Lack of standardization in representing phenotype data generated in different studies is a major barrier to data reuse for cross study analyses. To address this issue, we developed DIVER, a tool that identifies and standardizes demographic variables in dbGaP, based on simple natural language processing and standardized terminology mapping. In its evaluation using variables (N=3,565) from a range of pulmonary studies in dbGaP, DIVER proved to be an effective approach to standardizing dbGaP variables by successfully identifying demographic variables with high rates of recall and precision (98% and 94%, respectively). In addition, DIVER correctly modeled 79% of the identified demographic variables at the core semantic level. Examination of variables that DIVER could not handle shed light on where our tool needs enhancement so it can further improve its semantic modeling accuracy. DIVER is an important component of a system for phenotype discovery in dbGaP studies.

Text Categorization of Heart, Lung, and Blood Studies in the Database of Genotypes and Phenotypes (dbGaP) Utilizing n-grams and Metadata Features

The database of Genotypes and Phenotypes (dbGaP) allows researchers to understand phenotypic contribution to genetic conditions, generate new hypotheses, confirm previous study results, and identify control populations. However, effective use of the database is hindered by suboptimal study retrieval. Our objective is to evaluate text classification techniques to improve study retrieval in the context of the dbGaP database. We utilized standard machine learning algorithms (naive Bayes, support vector machines, and the C4.5 decision tree) trained on dbGaP study text and incorporated n-gram features and study metadata to identify heart, lung, and blood studies. We used the χ2 feature selection algorithm to identify features that contributed most to classification performance and experimented with dbGaP associated PubMed papers as a proxy for topicality. Classifier performance was favorable in comparison to keyword-based search results. It was determined that text categorization is a useful complement to document retrieval techniques in the dbGaP