Integrating signals from the T-cell receptor and the interleukin-2 receptor

T cells orchestrate the adaptive immune response, making them targets for immunotherapy. Although immunosuppressive therapies prevent disease progression, they also leave patients susceptible to opportunistic infections. To identify novel drug targets, we established a logical model describing T-cell receptor (TCR) signaling. However, to have a model that is able to predict new therapeutic approaches, the current drug targets must be included. Therefore, as a next step we generated the interleukin-2 receptor (IL-2R) signaling network and developed a tool to merge logical models. For IL-2R signaling, we show that STAT activation is independent of both Src- and PI3-kinases, while ERK activation depends upon both kinases and additionally requires novel PKCs. In addition, our merged model correctly predicted TCR-induced STAT activation. The combined network also allows information transfer from one receptor to add detail to another, thereby predicting that LAT mediates JNK activation in IL-2R signaling. In summary, the merged model not only enables us to unravel potential cross-talk, but it also suggests new experimental designs and provides a critical step towards designing strategies to reprogram T cells.     

Functional connectivity analyses in imaging genetics: considerations on methods and data interpretation

Functional magnetic resonance imaging (fMRI) can be combined with genotype assessment to identify brain systems that mediate genetic vulnerability to mental disorders ("imaging genetics"). A data analysis approach that is widely applied is "functional connectivity". In this approach, the temporal correlation between the fMRI signal from a pre-defined brain region (the so-called "seed point") and other brain voxels is determined. In this technical note, we show how the choice of freely selectable data analysis parameters strongly influences the assessment of the genetic modulation of connectivity features. In our data analysis we exemplarily focus on three methodological parameters: (i) seed voxel selection, (ii) noise reduction algorithms, and (iii) use of additional second level covariates. Our results show that even small variations in the implementation of a functional connectivity analysis can have an impact on the connectivity pattern that is as strong as the potential modulation by genetic allele variants. Some effects of genetic variation can only be found for one specific implementation of the connectivity analysis. A reoccurring difficulty in the field of psychiatric genetics is the non-replication of initially promising findings, partly caused by the small effects of single genes. The replication of imaging genetic results is therefore crucial for the long-term assessment of genetic effects on neural connectivity parameters. For a meaningful comparison of imaging genetics studies however, it is therefore necessary to provide more details on specific methodological parameters (e.g., seed voxel distribution) and to give information how robust effects are across the choice of methodological parameters.     

Schizotypy and behavioural adjustment and the role of neuroticism

Objective

In the present study the relationship between behavioural adjustment following cognitive conflict and schizotypy was investigated using a Stroop colour naming paradigm. Previous research has found deficits with behavioural adjustment in schizophrenia patients. Based on these findings, we hypothesized that individual differences in schizotypy, a personality trait reflecting the subclinical expression of the schizophrenia phenotype, would be associated with behavioural adjustment. Additionally, we investigated whether such a relationship would be explained by individual differences in neuroticism, a non-specific measure of negative trait emotionality known to be correlated with schizotypy.

Methods

106 healthy volunteers (mean age: 25.1, 60% females) took part. Post-conflict adjustment was measured in a computer-based version of the Stroop paradigm. Schizotypy was assessed using the Schizotypal Personality Questionnaire (SPQ) and Neuroticism using the NEO-FFI.

Results

We found a negative correlation between schizotypy and post-conflict adjustment (r = −.30, p<.01); this relationship remained significant when controlling for effects of neuroticism. Regression analysis revealed that particularly the subscale No Close Friends drove the effect.

Conclusion

Previous findings of deficits in cognitive control in schizophrenia patients were extended to the subclinical personality expression of the schizophrenia phenotype and found to be specific to schizotypal traits over and above the effects of negative emotionality.     

Glycosylation of Candida albicans Cell Wall Proteins Is Critical for Induction of Innate Immune Responses and Apoptosis of Epithelial Cells

C. albicans is one of the most common fungal pathogen of humans, causing local and superficial mucosal infections in immunocompromised individuals. Given that the key structure mediating host-C. albicans interactions is the fungal cell wall, we aimed to identify features of the cell wall inducing epithelial responses and be associated with fungal pathogenesis. We demonstrate here the importance of cell wall protein glycosylation in epithelial immune activation with a predominant role for the highly branched N-glycosylation residues. Moreover, these glycan moieties induce growth arrest and apoptosis of epithelial cells. Using an in vitro model of oral candidosis we demonstrate, that apoptosis induction by C. albicans wild-type occurs in early stage of infection and strongly depends on intact cell wall protein glycosylation. These novel findings demonstrate that glycosylation of the C. albicans cell wall proteins appears essential for modulation of epithelial immunity and apoptosis induction, both of which may promote fungal pathogenesis in vivo.     

Hormonal therapies and meningioma: Is there a link?

Background: The aetiology of meningiomas is largely unknown although hormones have been suggested to play a role. Methods: A cohort study was performed to evaluate hormone-related factors associated with meningioma. Patients (12–89 years) with a first diagnosis of meningioma (January 1996–June 2008) were identified from The Health Improvement Network UK primary care database and age- and sex-matched to controls (n = 10 000) from the same cohort. Odds ratios (ORs) were calculated following a nested case control analysis using unconditional logistic regression. Results: In total, 745 patients with meningioma were identified from a study population of 2 171 287. No significantly increased risk of meningioma was found among female users of oral contraceptives (OR: 1.15; CI: 0.67–1.98), hormone replacement therapy (OR: 0.99; CI: 0.73–1.35) or low-dose cyproterone acetate (CPA; OR: 1.51; CI: 0.33–6.86) compared with non-users. There was a significantly increased risk of meningioma among male users of androgen analogues (OR: 19.09; CI: 2.81–129.74) and among users of high-dose CPA (OR: 6.30; CI: 1.37–28.94) compared with non-users, however there were only three cases currently using these drugs. No significant association was found between meningioma and prostate, breast, or genital cancers. Conclusions: Our results do not support a role for exogenous hormone use by females in meningioma development. The risk in males was only observed with high-dose, short-term (<1 year) therapy. Impact: While hormonal cancers and therapies are not associated with meningioma in females, the risk in males requires further investigation.     

Simulated Evolution of Signal Transduction Networks

Signal transduction is the process of routing information inside cells when receiving stimuli from their environment that modulate the behavior and function. In such biological processes, the receptors, after receiving the corresponding signals, activate a number of biomolecules which eventually transduce the signal to the nucleus. The main objective of our work is to develop a theoretical approach which will help to better understand the behavior of signal transduction networks due to changes in kinetic parameters and network topology. By using an evolutionary algorithm, we designed a mathematical model which performs basic signaling tasks similar to the signaling process of living cells. We use a simple dynamical model of signaling networks of interacting proteins and their complexes. We study the evolution of signaling networks described by mass-action kinetics. The fitness of the networks is determined by the number of signals detected out of a series of signals with varying strength. The mutations include changes in the reaction rate and network topology. We found that stronger interactions and addition of new nodes lead to improved evolved responses. The strength of the signal does not play any role in determining the response type. This model will help to understand the dynamic behavior of the proteins involved in signaling pathways. It will also help to understand the robustness of the kinetics of the output response upon changes in the rate of reactions and the topology of the network.     

Characterization of potato plants with reduced StSYR1 expression

Vesicle fusion processes in plants are important for both development and stress responses. Transgenic potato plants with reduced expression of SYNTAXIN-RELATED1 (StSYR1), a gene encoding the potato homolog of Arabidopsis PENETRATION1 (AtPEN1), display spontaneous necrosis and chlorosis at later stages of development. In accordance with this developmental defect, tuber number, weight and overall yield are significantly reduced in StSYR1-RNAi lines. Enhanced resistance of StSYR1-RNAi plants to Phytophthora infestans, the causal agent of late blight disease of potato, correlates with enhanced levels of salicylic acid, whereas levels of 12-oxophytodienoic acid and jasmonic acid are unaltered. Cultured cells of StSYR1-RNAi lines secrete at least two compounds which are not detectable in the supernatant of control cells, suggesting an involvement of StSYR1 in secretion processes to the apoplast.