Mast cell adhesion to bronchial smooth muscle in asthma specifically depends on CD51 and CD44 variant 6.

BACKGROUND: Mast cells infiltrate the bronchial smooth muscle (BSM) in asthmatic patients, but the mechanism of mast cell adhesion is still unknown. The adhesion molecules CD44 (i.e. hyaluronate receptor) and CD51 (i.e. vitronectin receptor) are widely expressed and bind to many extracellular matrix (ECM) proteins. The aims of the study are (i) to identify the role of ECM in mast cell adhesion to BSM and (ii) to examine the role of CD51 and CD44 in this adhesion. METHODS: Human lung mast cells, human mast cell line (HMC-1), and BSM cells from control donors or asthmatic patients were cultured in the presence/absence of various cytokines. Mast cell-BSM interaction was assessed using (3)H-thymidine-pulsed mast cells, confocal immunofluorescence, or electron microscopy. Adhesion molecules expression and collagen production on both cell types were evaluated by quantitative RT-PCR, western blot, and flow cytometry. RESULTS: Mast cell adhesion to BSM cells mostly involved type I collagen of the ECM. Such an adhesion was increased in normal BSM cells under inflammatory condition, whereas it was maximal in asthmatic BSM cells. Blockade of either CD51 or CD44 significantly decreased mast cell adhesion to BSM. At the molecular level, protein and the transcriptional expression of type I collagen, CD51 or CD44 remained unchanged in asthmatic BSM cells or in mast cells/BSM cells under inflammatory conditions, whereas that of CD44 variant isoform 6 (v6) was increased. CONCLUSIONS: Mast cell-BSM cell adhesion involved collagen, CD44, and CD51, particularly under inflammatory conditions. CD44v6 expression is increased in asthmatic BSM cells.

Molecular genetic approaches to investigate individual variations in behavioral and neuroendocrine stress responses.

A large response range can be observed in both behavioral and neuroendocrine responses to environmental challenges. This variation can arise from central mechanisms such as those involved in the shaping of general response tendencies (temperaments) or involves only one or the other output system (behavioral vs. endocrine response). The participation of genetic factors in this variability is demonstrated by family and twin studies in humans, the comparison of inbred strains and selection experiments in animals. Those inbred strains diverging for specific traits of stress reactivity are invaluable tools for the study of the molecular bases of this genetic variability. Until recently, it was only possible to study biological differences between contrasting strains, such as neurotransmitter pathways in the brain or hormone receptor properties, in order to suggest structural differences in candidate genes. The increase of the power of molecular biology tools allows the systematic screening of significant genes for the search of molecular variants. More recently, it was possible to search for genes without any preliminary functional hypothesis (mRNA differential expression, nucleic acid arrays, QTL search). The approach known as quantitative trait loci (QTL) analysis is based on the association between polymorphic anonymous markers and the phenotypical value of the trait under study in a segregating population (such as F2 or backcross). It allows the location of chromosomal regions involved in trait variability and ultimately the identification of the mutated gene(s). Therefore, in a first step, those studies skip the 'black box' of intermediate mechanisms, but the knowledge of the gene(s) responsible for trait variability will point out to the pathway responsible for the phenotypical differences. Since variations in stress-related responses may be related to numerous pathological conditions such as behavioral and mood disorders, drug abuse, cardiovascular diseases or obesity, and production traits in farm animals, these studies can be expected to bring significant knowledge for new therapeutic approaches in humans and improved efficiency of selection in farm animals.