Genetic Susceptibility to Non-Necrotizing Erysipelas/Cellulitis

Background

Bacterial non-necrotizing erysipelas and cellulitis are often recurring, diffusely spreading infections of the skin and subcutaneous tissues caused most commonly by streptococci. Host genetic factors influence infection susceptibility but no extensive studies on the genetic determinants of human erysipelas exist.

Methods

We performed genome-wide linkage with the 10,000 variant Human Mapping Array (HMA10K) array on 52 Finnish families with multiple erysipelas cases followed by microsatellite fine mapping of suggestive linkage peaks. A scan with the HMA250K array was subsequently performed with a subset of cases and controls.

Results

Significant linkage was found at 9q34 (nonparametric multipoint linkage score (NPL_all) 3.84, p = 0.026), which is syntenic to a quantitative trait locus for susceptibility to group A streptococci infections on chromosome 2 in mouse. Sequencing of candidate genes in the 9q34 region did not conclusively associate any to erysipelas/cellulitis susceptibility. Suggestive linkage (NPL_all>3.0) was found at three loci: 3q22-24, 21q22, and 22q13. A subsequent denser genome scan with the HMA250K array supported the 3q22 locus, in which several SNPs in the promoter of AGTR1 (Angiotensin II receptor type I) suggestively associated with erysipelas/cellulitis susceptibility.

Conclusions

Specific host genetic factors may cause erysipelas/cellulitis susceptibility in humans.     

Information-Theoretic Analysis of the Dynamics of an Executable Biological Model

To facilitate analysis and understanding of biological systems, large-scale data are often integrated into models using a variety of mathematical and computational approaches. Such models describe the dynamics of the biological system and can be used to study the changes in the state of the system over time. For many model classes, such as discrete or continuous dynamical systems, there exist appropriate frameworks and tools for analyzing system dynamics. However, the heterogeneous information that encodes and bridges molecular and cellular dynamics, inherent to fine-grained molecular simulation models, presents significant challenges to the study of system dynamics. In this paper, we present an algorithmic information theory based approach for the analysis and interpretation of the dynamics of such executable models of biological systems. We apply a normalized compression distance (NCD) analysis to the state representations of a model that simulates the immune decision making and immune cell behavior. We show that this analysis successfully captures the essential information in the dynamics of the system, which results from a variety of events including proliferation, differentiation, or perturbations such as gene knock-outs. We demonstrate that this approach can be used for the analysis of executable models, regardless of the modeling framework, and for making experimentally quantifiable predictions.     

Multiple functional domains are involved in tomosyn regulation of exocytosis

Tomosyn is a cytoplasmic protein that was shown to bind to Syntaxin1 and SNAP-25 through an R-SNARE domain, forming a complex that is almost identical in structure to the neuronal SNARE complex. Tomosyn inhibits exocytosis in various cell types and these effects were attributed to direct competition between tomosyn's SNARE domain and Synaptobrevin/VAMP. In the present study, we investigated the contribution of different domains of tomosyn to its activity. We show that a tomosyn mutant that lacks the entire SNARE domain is a potent inhibitor of vesicle priming, similar to the full-length tomosyn. The SNARE domain of tomosyn failed to inhibit exocytosis, indicating that this domain is not required for the inhibition. In contrast, over-expression of a N-terminally truncated mutant did not lead to inhibition of exocytosis although this mutant still bound to Syntaxin. Our results indicate that tomosyn can inhibit exocytosis independently of its SNARE interaction with Syntaxin and that the integrity of the WD40-domain is crucial for tomosyn's inhibitory function. Furthermore, we demonstrate that the entire N-terminal region of tomosyn, the WD40-repeats and the linker, is required for tomosyn's inhibitory effect.     

Atherogenic, enlarged, and dysfunctional HDL in human PLTP/apoA-I double transgenic mice

In low density lipoprotein receptor (LDLR)-deficient mice, overexpression of human plasma phospholipid transfer protein (PLTP) results in increased atherosclerosis. PLTP strongly decreases HDL levels and might alter the antiatherogenic properties of HDL particles. To study the potential interaction between human PLTP and apolipoprotein A-I (apoA-I), double transgenic animals (hPLTPtg/hApoAItg) were compared with hApoAItg mice. PLTP activity was increased 4.5-fold. Plasma total cholesterol and phospholipid were decreased. Average HDL size (analyzed by gel filtration) increased strongly, hPLTPtg/hApoAItg mice having very large, LDL-sized, HDL particles. Also, after density gradient ultracentrifugation, a substantial part of the apoA-I-containing lipoproteins in hPLTPtg/hApoAItg mice was found in the LDL density range. In cholesterol efflux studies from macrophages, HDL isolated from hPLTPtg/hApoAItg mice was less efficient than HDL isolated from hApoAItg mice. Furthermore, it was found that the largest subfraction of the HDL particles present in hPLTPtg/hApoAItg mice was markedly inferior as a cholesterol acceptor, as no labeled cholesterol was transferred to this fraction. In an LDLR-deficient background, the human PLTP-expressing mouse line showed a 2.2-fold increased atherosclerotic lesion area. These data demonstrate that the action of human PLTP in the presence of human apoA-I results in the formation of a dysfunctional HDL subfraction, which is less efficient in the uptake of cholesterol from cholesterol-laden macrophages.     

Estimating genealogies from unlinked marker data: a Bayesian approach

An issue often encountered in statistical genetics is whether, or to what extent, it is possible to estimate the degree to which individuals sampled from a background population are related to each other, on the basis of the available genotype data and some information on the demography of the population. In this article, we consider this question using explicit modelling of the pedigrees and gene flows at unlinked marker loci, but then restricting ourselves to a relatively recent history of the population, that is, considering the genealogy at most some tens of generations backwards in time. As a computational tool we use a Markov chain Monte Carlo numerical integration on the state space of genealogies of the sampled individuals. As illustrations of the method, we consider the question of relatedness at the level of genes/genomes (IBD estimation), using both simulated and real data.     

Protein engineering: opportunities and challenges

The extraordinary properties of natural proteins demonstrate that life-like protein engineering is both achievable and valuable. Rapid progress and impressive results have been made towards this goal using rational design and random techniques or a combination of both. However, we still do not have a general theory on how to specify a structure that is suited to a target function nor can we specify a sequence that folds to a target structure. There is also overreliance on the Darwinian blind search to obtain practical results. In the long run, random methods cannot replace insight in constructing life-like proteins. For the near future, however, in enzyme development, we need to rely on a combination of both.     

How Anacetrapib Inhibits the Activity of the Cholesteryl Ester Transfer Protein? Perspective through Atomistic Simulations

Cholesteryl ester transfer protein (CETP) mediates the reciprocal transfer of neutral lipids (cholesteryl esters, triglycerides) and phospholipids between different lipoprotein fractions in human blood plasma. A novel molecular agent known as anacetrapib has been shown to inhibit CETP activity and thereby raise high density lipoprotein (HDL)-cholesterol and decrease low density lipoprotein (LDL)-cholesterol, thus rendering CETP inhibition an attractive target to prevent and treat the development of various cardiovascular diseases. Our objective in this work is to use atomistic molecular dynamics simulations to shed light on the inhibitory mechanism of anacetrapib and unlock the interactions between the drug and CETP. The results show an evident affinity of anacetrapib towards the concave surface of CETP, and especially towards the region of the N-terminal tunnel opening. The primary binding site of anacetrapib turns out to reside in the tunnel inside CETP, near the residues surrounding the N-terminal opening. Free energy calculations show that when anacetrapib resides in this area, it hinders the ability of cholesteryl ester to diffuse out from CETP. The simulations further bring out the ability of anacetrapib to regulate the structure-function relationships of phospholipids and helix X, the latter representing the structural region of CETP important to the process of neutral lipid exchange with lipoproteins. Altogether, the simulations propose CETP inhibition to be realized when anacetrapib is transferred into the lipid binding pocket. The novel insight gained in this study has potential use in the development of new molecular agents capable of preventing the progression of cardiovascular diseases.