Resonance assignment for a particularly challenging protein based on systematic unlabeling of amino acids to complement incomplete NMR data sets

NMR-based structure determination of a protein requires the assignment of resonances as indispensable first step. Even though heteronuclear through-bond correlation methods are available for that purpose, challenging situations arise in cases where the protein in question only yields samples of limited concentration and/or stability. Here we present a strategy based upon specific individual unlabeling of all 20 standard amino acids to complement standard NMR experiments and to achieve unambiguous backbone assignments for the fast precipitating 23 kDa catalytic domain of human aprataxin of which only incomplete standard NMR data sets could be obtained. Together with the validation of this approach utilizing the protein GB1 as a model, a comprehensive insight into metabolic interconversion ("scrambling”) of NH and CO groups in a standard Escherichia coli expression host is provided.     

The SH2 Domain Interaction Landscape

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Highlights? The recognition specificity of 70 SH2 domains is probed ? Recognition specificity diverges faster than sequence ? PepspotDB is a database of protein interactions mediated by SH2 domains     

Analysing diversity and community structures using PCR‐RFLP: a new software application

Restriction fragment length polymorphism tools is an R application which supports a complete workflow of polymerase chain reaction‐restriction fragment length polymorphism (PCR‐RFLP), dealing with the problems which accompany analysis when PCR‐RFLP is used in diversity studies. Large numbers of different RFLP samples obtained from multiple electrophoresis runs might lead to limitations or misidentifications due to the need for band matching in most existing software applications. Due to the common problem of variation in the density of bands (i.e. distances between bands or visual intensity) in the electropherograms, it is desirable to have options for handling samples with uncertain or faint bands. As a further step in the workflow, scientists often use DNA sequencing to identify individual genotypes, so that the use of specific software to combine these tasks might be helpful. With this background, we here present an application that supports a complete workflow, starting with the analysis of single species samples by PCR‐RFLP, to PCR‐RFLP genotype identification based on a reference data set and DNA sequencing followed by similarity analysis. RFLPtools is a freely available, platform‐independent application which provides analysis functions for DNA fragment molecular weights (e.g. by RFLP analysis), including similarity calculations without the need for band matching. As it is written for the statistical software R, other statistical analyses might also be easily applied.     

Opto-Mechanical Coupling in Interfaces under Static and Propagative Conditions and Its Biological Implications

Fluorescent dyes are vital for studying static and dynamic patterns and pattern formation in cell biology. Emission properties of the dyes incorporated in a biological interface are known to be sensitive to their local environment. We report that the fluorescence intensity of dye molecules embedded in lipid interfaces is indeed a thermodynamic observable of the system. Opto-mechanical coupling of lipid-dye system was measured as a function of the thermodynamic state of the interface. The corresponding state diagrams quantify the thermodynamic coupling between intensity I and lateral pressure π. We further demonstrate that the coupling is conserved upon varying the temperature T. Notably, the observed opto-mechanical coupling is not limited to equilibrium conditions, but also holds for propagating pressure pulses. The non-equilibrium data show, that fluorescence is especially sensitive to dynamic changes in state such as the LE-LC phase transition. We conclude that variations in the thermodynamic state (here π and T, in general pH, membrane potential V, etc also) of lipid membranes are capable of controlling fluorescence intensity. Therefore, interfacial thermodynamic state diagrams of I should be obtained for a proper interpretation of intensity data.     

Activating and Relaxing Music Entrains the Speed of Beat Synchronized Walking

Inspired by a theory of embodied music cognition, we investigate whether music can entrain the speed of beat synchronized walking. If human walking is in synchrony with the beat and all musical stimuli have the same duration and the same tempo, then differences in walking speed can only be the result of music-induced differences in stride length, thus reflecting the vigor or physical strength of the movement. Participants walked in an open field in synchrony with the beat of 52 different musical stimuli all having a tempo of 130 beats per minute and a meter of 4 beats. The walking speed was measured as the walked distance during a time interval of 30 seconds. The results reveal that some music is ‘activating’ in the sense that it increases the speed, and some music is ‘relaxing’ in the sense that it decreases the speed, compared to the spontaneous walked speed in response to metronome stimuli. Participants are consistent in their observation of qualitative differences between the relaxing and activating musical stimuli. Using regression analysis, it was possible to set up a predictive model using only four sonic features that explain 60% of the variance. The sonic features capture variation in loudness and pitch patterns at periods of three, four and six beats, suggesting that expressive patterns in music are responsible for the effect. The mechanism may be attributed to an attentional shift, a subliminal audio-motor entrainment mechanism, or an arousal effect, but further study is needed to figure this out. Overall, the study supports the hypothesis that recurrent patterns of fluctuation affecting the binary meter strength of the music may entrain the vigor of the movement. The study opens up new perspectives for understanding the relationship between entrainment and expressiveness, with the possibility to develop applications that can be used in domains such as sports and physical rehabilitation.     

Downregulation of Serine Protease HTRA1 Is Associated with Poor Survival in Breast Cancer

HTRA1 is a highly conserved serine protease which has been implicated in suppression of epithelial-to-mesenchymal-transition (EMT) and cell motility in breast cancer. Its prognostic relevance for breast cancer is unclear so far. Therefore, we evaluated the impact of HTRA1 mRNA expression on patient outcome using a cohort of 131 breast cancer patients as well as a validation cohort including 2809 publically available data sets. Additionally, we aimed at investigating for the presence of promoter hypermethylation as a mechanism for silencing the HTRA1 gene in breast tumors. HTRA1 downregulation was detected in more than 50% of the breast cancer specimens and was associated with higher tumor stage (p = 0.025). By applying Cox proportional hazard models, we observed favorable overall (OS) and disease-free survival (DFS) related to high HTRA1 expression (HR = 0.45 [CI 0.23–0.90], p = 0.023; HR = 0.55 [CI 0.32–0.94], p = 0.028, respectively), with even more pronounced impact in node-positive patients (HR = 0.21 [CI 0.07–0.63], p = 0.006; HR = 0.29 [CI 0.13–0.65], p = 0.002, respectively). Moreover, HTRA1 remained a statistically significant factor predicting DFS among established clinical parameters in the multivariable analysis. Its impact on patient outcome was independently confirmed in the validation set (for relapse-free survival (n = 2809): HR = 0.79 [CI 0.7–0.9], log-rank p = 0.0003; for OS (n = 971): HR = 0.63 [CI 0.48–0.83], log-rank p = 0.0009). In promoter analyses, we in fact detected methylation of HTRA1 in a small subset of breast cancer specimens (two out of a series of 12), and in MCF-7 breast cancer cells which exhibited 22-fold lower HTRA1 mRNA expression levels compared to unmethylated MDA-MB-231 cells. In conclusion, we show that downregulation of HTRA1 is associated with shorter patient survival, particularly in node-positive breast cancer. Since HTRA1 loss was demonstrated to induce EMT and cancer cell invasion, these patients might benefit from demethylating agents or histone deacetylase inhibitors previously reported to lead to HTRA1 upregulation, or from novel small-molecule inhibitors targeting EMT-related processes.     

Automated Characterization and Parameter-Free Classification of Cell Tracks Based on Local Migration Behavior

Cell migration is the driving force behind the dynamics of many diverse biological processes. Even though microscopy experiments are routinely performed today by which populations of cells are visualized in space and time, valuable information contained in image data is often disregarded because statistical analyses are performed at the level of cell populations rather than at the single-cell level. Image-based systems biology is a modern approach that aims at quantitatively analyzing and modeling biological processes by developing novel strategies and tools for the interpretation of image data. In this study, we take first steps towards a fully automated characterization and parameter-free classification of cell track data that can be generally applied to tracked objects as obtained from image data. The requirements to achieve this aim include: (i) combination of different measures for single cell tracks, such as the confinement ratio and the asphericity of the track volume, and (ii) computation of these measures in a staggered fashion to retrieve local information from all possible combinations of track segments. We demonstrate for a population of synthetic cell tracks as well as for in vitro neutrophil tracks obtained from microscopy experiment that the information contained in the track data is fully exploited in this way and does not require any prior knowledge, which keeps the analysis unbiased and general. The identification of cells that show the same type of migration behavior within the population of all cells is achieved via agglomerative hierarchical clustering of cell tracks in the parameter space of the staggered measures. The recognition of characteristic patterns is highly desired to advance our knowledge about the dynamics of biological processes.     

Transiently Reduced PI3K/Akt Activity Drives the Development of Regulatory Function in Antigen-Stimulated Na?ve T-Cells

Regulatory T-cells (T_regs) are central for immune homeostasis and divided in thymus-derived natural T_regs and peripherally induced iT_reg. However, while phenotype and function of iT_regs are well known, a remarkable lack exists in knowledge about signaling mechanisms leading to their generation from naïve precursors in peripheral tissues. Using antigen specific naïve T-cells from mice, we investigated CD4+ CD25+ FoxP3- iT_reg induction during antigen-specific T-cell receptor (TCR) stimulation with weak antigen presenting cells (APC). We show that early signaling pathways such as ADAM-17-activation appeared similar in developing iT_reg and effector cells (T_eff) and both initially shedded CD62-L. But iT_reg started reexpressing CD62-L after 24 h while T_eff permanently downmodulated it. Furthermore, between 24 and 72 hours iT_reg presented with significantly lower phosphorylation levels of Akt-S473 suggesting lower activity of the PI3K/Akt-axis. This was associated with a higher expression of the Akt hydrophobic motif-specific phosphatase PHLPP1 in iT_reg. Importantly, the lack of costimulatory signals via CD28 from weak APC was central for the development of regulatory function in iT_reg but not for the reappearance of CD62-L. Thus, T-cells display a window of sensitivity after onset of TCR triggering within which the intensity of the PI3K/Akt signal controls entry into either effector or regulatory pathways.     

Preoperative Diffusion-Weighted Imaging of Single Brain Metastases Correlates with Patient Survival Times

Background

MRI-based diffusion-weighted imaging (DWI) visualizes the local differences in water diffusion in vivo. The prognostic value of DWI signal intensities on the source images and apparent diffusion coefficient (ADC) maps respectively has not yet been studied in brain metastases (BM).

Methods

We included into this retrospective analysis all patients operated for single BM at our institution between 2002 and 2010, in whom presurgical DWI and BM tissue samples were available. We recorded relevant clinical data, assessed DWI signal intensity and apparent diffusion coefficient (ADC) values and performed histopathological analysis of BM tissues. Statistical analyses including uni- and multivariate survival analyses were performed.

Results

65 patients (34 female, 31 male) with a median overall survival time (OS) of 15 months (range 0–99 months) were available for this study. 19 (29.2%) patients presented with hyper-, 3 (4.6%) with iso-, and 43 (66.2%) with hypointense DWI. ADCmean values could be determined in 32 (49.2%) patients, ranged from 456.4 to 1691.8*10⁻⁶ mm²/s (median 969.5) and showed a highly significant correlation with DWI signal intensity. DWI hyperintensity correlated significantly with high amount of interstitial reticulin deposition. In univariate analysis, patients with hyperintense DWI (5 months) and low ADCmean values (7 months) had significantly worse OS than patients with iso/hypointense DWI (16 months) and high ADCmean values (30 months), respectively. In multivariate survival analysis, high ADCmean values retained independent statistical significance.

Conclusions

Preoperative DWI findings strongly and independently correlate with OS in patients operated for single BM and are related to interstitial fibrosis. Inclusion of DWI parameters into established risk stratification scores for BM patients should be considered.