Inference of Epidemiological Dynamics Based on Simulated Phylogenies Using Birth-Death and Coalescent Models

Quantifying epidemiological dynamics is crucial for understanding and forecasting the spread of an epidemic. The coalescent and the birth-death model are used interchangeably to infer epidemiological parameters from the genealogical relationships of the pathogen population under study, which in turn are inferred from the pathogen genetic sequencing data. To compare the performance of these widely applied models, we performed a simulation study. We simulated phylogenetic trees under the constant rate birth-death model and the coalescent model with a deterministic exponentially growing infected population. For each tree, we re-estimated the epidemiological parameters using both a birth-death and a coalescent based method, implemented as an MCMC procedure in BEAST v2.0. In our analyses that estimate the growth rate of an epidemic based on simulated birth-death trees, the point estimates such as the maximum a posteriori/maximum likelihood estimates are not very different. However, the estimates of uncertainty are very different. The birth-death model had a higher coverage than the coalescent model, i.e. contained the true value in the highest posterior density (HPD) interval more often (2–13% vs. 31–75% error). The coverage of the coalescent decreases with decreasing basic reproductive ratio and increasing sampling probability of infecteds. We hypothesize that the biases in the coalescent are due to the assumption of deterministic rather than stochastic population size changes. Both methods performed reasonably well when analyzing trees simulated under the coalescent. The methods can also identify other key epidemiological parameters as long as one of the parameters is fixed to its true value. In summary, when using genetic data to estimate epidemic dynamics, our results suggest that the birth-death method will be less sensitive to population fluctuations of early outbreaks than the coalescent method that assumes a deterministic exponentially growing infected population.     

Experimental Study on Localized Surface Plasmon Mode Hybridization in the Near and Mid Infrared

We investigate plasmon excitations within a regular grating of double-layered gold/insulator nanoparticles in the infrared and visible spectral region. Provided a flat gold film as substrate, strong coupling between the localized surface plasmon modes and their image-like excitations in the metal is observed. The interaction results in a strong red shift of the plasmon mode as well as the splitting of the modes into levels of different angular momenta, often referred to as plasmon hybridization. The diameters of the nanoparticles are designed in a way that the splitting of the resonances occurs in the spectral region between 0.1 and 1 eV, thus being accessible using an infrared microscope. Moreover, we investigated the infrared absorption signal of gratings that contain two differently sized nanoparticles. The interaction between two autonomous localized surface plasmon excitations is investigated by analyzing their crossing behavior. In contrast to the interaction between localized surface plasmons and propagating plasmon excitations which results in pronounced anticrossing, the presented structures show no interaction between two autonomous localized surface plasmons. Finally, plasmon excitations of the nanostructured surfaces in the visible spectral region are demonstrated through photographs acquired at three different illumination angles. The change in color of the gratings demonstrates the complex interaction between propagating and localized surface plasmon modes.     

A novel stable isotope labelling assisted workflow for improved untargeted LC–HRMS based metabolomics research

Many untargeted LC–ESI–HRMS based metabolomics studies are still hampered by the large proportion of non-biological sample derived signals included in the generated raw data. Here, a novel, powerful stable isotope labelling (SIL)-based metabolomics workflow is presented, which facilitates global metabolome extraction, improved metabolite annotation and metabolome wide internal standardisation (IS). The general concept is exemplified with two different cultivation variants, (1) co-cultivation of the plant pathogenic fungi Fusarium graminearum on non-labelled and highly ¹³C enriched culture medium and (2) experimental cultivation under native conditions and use of globally U-¹³C labelled biological reference samples as exemplified with maize and wheat. Subsequent to LC–HRMS analysis of mixtures of labelled and non-labelled samples, two-dimensional data filtering of SIL specific isotopic patterns is performed to better extract truly biological derived signals together with the corresponding number of carbon atoms of each metabolite ion. Finally, feature pairs are convoluted to feature groups each representing a single metabolite. Moreover, the correction of unequal matrix effects in different sample types and the improvement of relative metabolite quantification with metabolome wide IS are demonstrated for the F. graminearum experiment. Data processing employing the presented workflow revealed about 300 SIL derived feature pairs corresponding to 87–135 metabolites in F. graminearum samples and around 800 feature pairs corresponding to roughly 350 metabolites in wheat samples. SIL assisted IS, by the use of globally U-¹³C labelled biological samples, reduced the median CV value from 7.1 to 3.6 % for technical replicates and from 15.1 to 10.8 % for biological replicates in the respective F. graminearum samples.     

PTK 7 Is a Transforming Gene and Prognostic Marker for Breast Cancer and Nodal Metastasis Involvement

Protein Tyrosin Kinase 7 (PTK7) is upregulated in several human cancers; however, its clinical implication in breast cancer (BC) and lymph node (LN) is still unclear. In order to investigate the function of PTK7 in mediating BC cell motility and invasivity, PTK7 expression in BC cell lines was determined. PTK7 signaling in highly invasive breast cancer cells was inhibited by a dominant-negative PTK7 mutant, an antibody against the extracellular domain of PTK7, and siRNA knockdown of PTK7. This resulted in decreased motility and invasivity of BC cells. We further examined PTK7 expression in BC and LN tissue of 128 BC patients by RT-PCR and its correlation with BC related genes like HER2, HER3, PAI1, MMP1, K19, and CD44. Expression profiling in BC cell lines and primary tumors showed association of PTK7 with ER/PR/HER2-negative (TNBC-triple negative BC) cancer. Oncomine data analysis confirmed this observation and classified PTK7 in a cluster with genes associated with agressive behavior of primary BC. Furthermore PTK7 expression was significantly different with respect to tumor size (ANOVA, p = 0.033) in BC and nodal involvement (ANOVA, p = 0.007) in LN. PTK7 expression in metastatic LN was related to shorter DFS (Cox Regression, p = 0.041). Our observations confirmed the transforming potential of PTK7, as well as its involvement in motility and invasivity of BC cells. PTK7 is highly expressed in TNBC cell lines. It represents a novel prognostic marker for BC patients and has potential therapeutic significance.     

A Novel Antibody against Human Properdin Inhibits the Alternative Complement System and Specifically Detects Properdin from Blood Samples

The complement system is an essential part of the innate immune system by acting as a first line of defense which is stabilized by properdin, the sole known positive regulator of the alternative complement pathway. Dysregulation of complement can promote a diversity of human inflammatory diseases which are treated by complement inhibitors. Here, we generated a novel blocking monoclonal antibody (mAb) against properdin and devised a new diagnostic assay for this important complement regulator. Mouse mAb 1340 specifically detected native properdin from human samples with high avidity. MAb 1340 inhibited specifically the alternative complement mediated cell lysis within a concentration range of 1–10 µg/mL. Thus, in vitro anti-properdin mAb 1340 was up to fifteen times more efficient in blocking the complement system as compared to anti-C5 or anti-Ba antibodies. Computer-assisted modelling suggested a three-dimensional binding epitope in a properdin-C3(H₂O)-clusterin complex to be responsible for the inhibition. Recovery of properdin in a newly established sandwich ELISA using mAb 1340 was determined at 80–125% for blood sample dilutions above 1∶50. Reproducibility assays showed a variation below 25% at dilutions less than 1∶1,000. Systemic properdin concentrations of healthy controls and patients with age-related macular degeneration or rheumatic diseases were all in the range of 13–30 µg/mL and did not reveal significant differences. These initial results encourage further investigation into the functional role of properdin in the development, progression and treatment of diseases related to the alternative complement pathway. Thus, mAb 1340 represents a potent properdin inhibitor suitable for further research to understand the exact mechanisms how properdin activates the complement C3-convertase and to determine quantitative levels of properdin in biological samples.     

Tree Species Traits but Not Diversity Mitigate Stem Breakage in a Subtropical Forest following a Rare and Extreme Ice Storm

Future climates are likely to include extreme events, which in turn have great impacts on ecological systems. In this study, we investigated possible effects that could mitigate stem breakage caused by a rare and extreme ice storm in a Chinese subtropical forest across a gradient of forest diversity. We used Bayesian modeling to correct stem breakage for tree size and variance components analysis to quantify the influence of taxon, leaf and wood functional traits, and stand level properties on the probability of stem breakage. We show that the taxon explained four times more variance in individual stem breakage than did stand level properties; trees with higher specific leaf area (SLA) were less susceptible to breakage. However, a large part of the variation at the taxon scale remained unexplained, implying that unmeasured or undefined traits could be used to predict damage caused by ice storms. When aggregated at the plot level, functional diversity and wood density increased after the ice storm. We suggest that for the adaption of forest management to climate change, much can still be learned from looking at functional traits at the taxon level.     

Analyzing Genome-Wide Association Studies with an FDR Controlling Modification of the Bayesian Information Criterion

The prevailing method of analyzing GWAS data is still to test each marker individually, although from a statistical point of view it is quite obvious that in case of complex traits such single marker tests are not ideal. Recently several model selection approaches for GWAS have been suggested, most of them based on LASSO-type procedures. Here we will discuss an alternative model selection approach which is based on a modification of the Bayesian Information Criterion (mBIC2) which was previously shown to have certain asymptotic optimality properties in terms of minimizing the misclassification error. Heuristic search strategies are introduced which attempt to find the model which minimizes mBIC2, and which are efficient enough to allow the analysis of GWAS data. Our approach is implemented in a software package called MOSGWA. Its performance in case control GWAS is compared with the two algorithms HLASSO and d-GWASelect, as well as with single marker tests, where we performed a simulation study based on real SNP data from the POPRES sample. Our results show that MOSGWA performs slightly better than HLASSO, where specifically for more complex models MOSGWA is more powerful with only a slight increase in Type I error. On the other hand according to our simulations GWASelect does not at all control the type I error when used to automatically determine the number of important SNPs. We also reanalyze the GWAS data from the Wellcome Trust Case-Control Consortium and compare the findings of the different procedures, where MOSGWA detects for complex diseases a number of interesting SNPs which are not found by other methods.