Arrhythmogenic cardiomyopathy related DSG2 mutations affect desmosomal cadherin binding kinetics

Dieding M, Debus JD, Kerkhoff R, et al. Arrhythmogenic cardiomyopathy related DSG2 mutations affect desmosomal cadherin binding kinetics. Scientific Reports. 2017;7(1): 13791.Cadherins are calcium dependent adhesion proteins that establish the intercellular mechanical contact by bridging the gap to adjacent cells. Desmoglein-2 (Dsg2) is a specific cadherin of the cell-cell contact in cardiac desmosomes. Mutations in the DSG2-gene are regarded to cause arrhythmogenic (right ventricular) cardiomyopathy (ARVC) which is a rare but severe heart muscle disease. The molecular pathomechanisms of the vast majority of DSG2 mutations, however, are unknown. Here, we investigated the homophilic binding of wildtype Dsg2 and two mutations which are associated with ARVC. Using single molecule force spectroscopy and applying Jarzynski's equality we determined the kinetics and thermodynamics of Dsg2 homophilic binding. Notably, the free energy landscape of Dsg2 dimerization exposes a high activation barrier which is in line with the proposed strand-swapping binding motif. Although the binding motif is not directly affected by the mutations the binding kinetics differ significantly from the wildtype. Furthermore, we applied a dispase based cell dissociation assay using HT1080 cell lines over expressing Dsg2 wildtype and mutants, respectively. Our molecular and cellular results consistently demonstrate that Dsg2 mutations can heavily affect homophilic Dsg2 interactions. Furthermore, the full thermodynamic and kinetic description of Dsg2 dimerization provides a consistent model of the so far discussed homophilic cadherin binding

Prospectus, February 1, 1984

TOOTH FAIRY PROMOTES DENTAL HEALTH; News Digest; Vote today or tomorrow for StuGo senators; PC Happenings: Parenting programs on TV, Jackson prints donated to Parkland; Letter to the editor; Get involved!!; Experience the uniqueness of people; Letter to the Editor; Student Government candidate platforms; Counseling center; A new look at the library; Story Shop stimulates young writers; Mechanics services at Parkland College; Life Science: largest division at Parkland; Dental hygiene service; Shop around for new phones; Dental clinic accepting new patients; Question: What is a friend? ; Classifieds; Kinks perform in State of Confusion ; Coppola\u27s \u27One from the Heart\u27 worth seeing; Machines star in series; Rodgers is still going strong; The Kinks still have what it takes to sound good; Parkland art collection valid part of education; Formigoni reaches out with color and space; Hubler talks about Champaign; Placement office finds jobs; What Is Art?; Cobras ease to victory; Men edge the Blue Knights; Track--two national qualifiershttps://spark.parkland.edu/prospectus_1984/1033/thumbnail.jp

Pro-Inflammatory S100A8 and S100A9 Proteins: Self-Assembly into Multifunctional Native and Amyloid Complexes

S100A8 and S100A9 are EF-hand Ca2+ binding proteins belonging to the S100 family. They are abundant in cytosol of phagocytes and play critical roles in numerous cellular processes such as motility and danger signaling by interacting and modulating the activity of target proteins. S100A8 and S100A9 expression levels increased in many types of cancer, neurodegenerative disorders, inflammatory and autoimmune diseases and they are implicated in the numerous disease pathologies. The Ca2+ and Zn2+-binding properties of S100A8/A9 have a pivotal influence on their conformation and oligomerization state, including self-assembly into homo- and heterodimers, tetramers and larger oligomers. Here we review how the unique chemical and conformational properties of individual proteins and their structural plasticity at the quaternary level account for S100A8/A9 functional diversity. Additional functional diversification occurs via non-covalent assembly into oligomeric and fibrillar amyloid complexes discovered in the aging prostate and reproduced in vitro. This process is also regulated by Ca2+and Zn2+-binding and effectively competes with the formation of the native complexes. High intrinsic amyloid-forming capacity of S100A8/A9 proteins may lead to their amyloid depositions in numerous ailments characterized by their elevated expression patterns and have additional pathological significance requiring further thorough investigation

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives