Model-based meta-analysis to optimise S. aureus-targeted therapies for atopic dermatitis

Several clinical trials of Staphylococcus aureus (S. aureus)-targeted therapies for atopic dermatitis (AD) have demonstrated conflicting results regarding whether they improve AD severity scores. This study performs a model-based meta-analysis to investigate possible causes of these conflicting results and suggests how to improve the efficacies of S. aureus-targeted therapies. We developed a mathematical model that describes systems-level AD pathogenesis involving dynamic interactions between S. aureus and Coagulase Negative Staphylococcus (CoNS). Our model simulation reproduced the clinically observed detrimental effects of application of S. hominis A9 (ShA9) and flucloxacillin on AD severity and showed that these effects disappeared if the bactericidal activity against CoNS was removed. A hypothetical (modelled) eradication of S. aureus by 3.0 log10 CFU/cm2, without killing CoNS, achieved comparable EASI-75 to dupilumab. This efficacy was potentiated if dupilumab was administered in conjunction with S. aureus eradication (EASI-75 at week 16; S. aureus eradication: 66.7%, dupilumab 61.6% and combination: 87.8%). The improved efficacy was also seen for virtual dupilumab poor responders. Our model simulation suggests that killing CoNS worsens AD severity and that S. aureus-specific eradication without killing CoNS could be effective for AD patients, including dupilumab poor responders. This study will contribute to design promising S. aureus-targeted therapy

Operating Regimes of Signaling Cycles: Statics, Dynamics, and Noise Filtering

A ubiquitous building block of signaling pathways is a cycle of covalent modification (e.g., phosphorylation and dephosphorylation in MAPK cascades). Our paper explores the kind of information processing and filtering that can be accomplished by this simple biochemical circuit. Signaling cycles are particularly known for exhibiting a highly sigmoidal (ultrasensitive) input–output characteristic in a certain steady-state regime. Here, we systematically study the cycle's steady-state behavior and its response to time-varying stimuli. We demonstrate that the cycle can actually operate in four different regimes, each with its specific input–output characteristics. These results are obtained using the total quasi–steady-state approximation, which is more generally valid than the typically used Michaelis-Menten approximation for enzymatic reactions. We invoke experimental data that suggest the possibility of signaling cycles operating in one of the new regimes. We then consider the cycle's dynamic behavior, which has so far been relatively neglected. We demonstrate that the intrinsic architecture of the cycles makes them act—in all four regimes—as tunable low-pass filters, filtering out high-frequency fluctuations or noise in signals and environmental cues. Moreover, the cutoff frequency can be adjusted by the cell. Numerical simulations show that our analytical results hold well even for noise of large amplitude. We suggest that noise filtering and tunability make signaling cycles versatile components of more elaborate cell-signaling pathways

Layer dynamics of a freely standing smectic-A film

We study the hydrodynamics of a freely-standing smectic-A film in the isothermal, incompressible limit theoretically by analyzing the linearized hydrodynamic equations of motion with proper boundary conditions. The dynamic properties for the system can be obtained from the response functions for the free surfaces. Permeation is included and its importance near the free surfaces is discussed. The hydrodynamic mode structure for the dynamics of the system is compared with that of bulk systems. We show that to describe the dynamic correlation functions for the system, in general, it is necessary to consider the smectic layer displacement $u$ and the velocity normal to the layers, $v_z$, together. Finally, our analysis also provides a basis for the theoretical study of the off-equilibrium dynamics of freely-standing smectic-A films.Comment: 22 pages, 4 figure

An X-Ray Induced Structural Transition in La_0.875Sr_0.125MnO_3

We report a synchrotron x-ray scattering study of the magnetoresistive manganite La_0.875Sr_0.125MnO_3. At low temperatures, this material undergoes an x-ray induced structural transition at which charge ordering of Mn^3+ and Mn^4+ ions characteristic to the low-temperature state of this compound is destroyed. The transition is persistent but the charge-ordered state can be restored by heating above the charge-ordering transition temperature and subsequently cooling. The charge-ordering diffraction peaks, which are broadened at all temperatures, broaden more upon x-ray irradiation, indicating the finite correlation length of the charge-ordered state. Together with the recent reports on x-ray induced transitions in Pr_(1-x)Ca_xMnO_3, our results demonstrate that the photoinduced structural change is a common property of the charge-ordered perovskite manganites.Comment: 5 pages, 4 embedded EPS figures; significant changes in the data analysis mad

Elucidating the Altered Transcriptional Programs in Breast Cancer using Independent Component Analysis

The quantity of mRNA transcripts in a cell is determined by a complex interplay of cooperative and counteracting biological processes. Independent Component Analysis (ICA) is one of a few number of unsupervised algorithms that have been applied to microarray gene expression data in an attempt to understand phenotype differences in terms of changes in the activation/inhibition patterns of biological pathways. While the ICA model has been shown to outperform other linear representations of the data such as Principal Components Analysis (PCA), a validation using explicit pathway and regulatory element information has not yet been performed. We apply a range of popular ICA algorithms to six of the largest microarray cancer datasets and use pathway-knowledge and regulatory-element databases for validation. We show that ICA outperforms PCA and clustering-based methods in that ICA components map closer to known cancer-related pathways, regulatory modules, and cancer phenotypes. Furthermore, we identify cancer signalling and oncogenic pathways and regulatory modules that play a prominent role in breast cancer and relate the differential activation patterns of these to breast cancer phenotypes. Importantly, we find novel associations linking immune response and epithelial–mesenchymal transition pathways with estrogen receptor status and histological grade, respectively. In addition, we find associations linking the activity levels of biological pathways and transcription factors (NF1 and NFAT) with clinical outcome in breast cancer. ICA provides a framework for a more biologically relevant interpretation of genomewide transcriptomic data. Adopting ICA as the analysis tool of choice will help understand the phenotype–pathway relationship and thus help elucidate the molecular taxonomy of heterogeneous cancers and of other complex genetic diseases

CSO validator: improving manual curation workflow for biological pathways

Summary: Manual curation and validation of large-scale biological pathways are required to obtain high-quality pathway databases. In a typical curation process, model validation and model update based on appropriate feedback are repeated and requires considerable cooperation of scientists. We have developed a CSO (Cell System Ontology) validator to reduce the repetition and time during the curation process. This tool assists in quickly obtaining agreement among curators and domain experts and in providing a consistent and accurate pathway database

Dissimilatory Metabolism of Nitrogen Oxides in Bacteria: Comparative Reconstruction of Transcriptional Networks

Bacterial response to nitric oxide (NO) is of major importance since NO is an obligatory intermediate of the nitrogen cycle. Transcriptional regulation of the dissimilatory nitric oxides metabolism in bacteria is diverse and involves FNR-like transcription factors HcpR, DNR, and NnrR; two-component systems NarXL and NarQP; NO-responsive activator NorR; and nitrite-sensitive repressor NsrR. Using comparative genomics approaches, we predict DNA-binding motifs for these transcriptional factors and describe corresponding regulons in available bacterial genomes. Within the FNR family of regulators, we observed a correlation of two specificity-determining amino acids and contacting bases in corresponding DNA recognition motif. Highly conserved regulon HcpR for the hybrid cluster protein and some other redox enzymes is present in diverse anaerobic bacteria, including Clostridia, Thermotogales, and delta-proteobacteria. NnrR and DNR control denitrification in alpha- and beta-proteobacteria, respectively. Sigma-54-dependent NorR regulon found in some gamma- and beta-proteobacteria contains various enzymes involved in the NO detoxification. Repressor NsrR, which was previously known to control only nitrite reductase operon in Nitrosomonas spp., appears to be the master regulator of the nitric oxides' metabolism, not only in most gamma- and beta-proteobacteria (including well-studied species such as Escherichia coli), but also in Gram-positive Bacillus and Streptomyces species. Positional analysis and comparison of regulatory regions of NO detoxification genes allows us to propose the candidate NsrR-binding motif. The most conserved member of the predicted NsrR regulon is the NO-detoxifying flavohemoglobin Hmp. In enterobacteria, the regulon also includes two nitrite-responsive loci, nipAB (hcp-hcr) and nipC (dnrN), thus confirming the identity of the effector, i.e. nitrite. The proposed NsrR regulons in Neisseria and some other species are extended to include denitrification genes. As the result, we demonstrate considerable interconnection between various nitrogen-oxides-responsive regulatory systems for the denitrification and NO detoxification genes and evolutionary plasticity of this transcriptional network

Ultrafast Photoinduced Formation of Metallic State in a Perovskite-type Manganite with Short Range Charge and Orbital Order

Femtosecond reflection spectroscopy was performed on a perovskite-type manganite, Gd0.55Sr0.45MnO3, with the short-range charge and orbital order (CO/OO). Immediately after the photoirradiation, a large increase of the reflectivity was detected in the mid-infrared region. The optical conductivity spectrum under photoirradiation obtained from the Kramers-Kronig analyses of the reflectivity changes demonstrates a formation of a metallic state. This suggests that ferromagnetic spin arrangements occur within the time resolution (ca. 200 fs) through the double exchange interaction, resulting in an ultrafast CO/OO to FM switching.Comment: 4 figure

Photoinduced charge and spin dynamics in strongly correlated electron systems

Motivated by photoinduced phase transition in manganese oxides, charge and spin dynamics induced by photoirradiation are examined. We calculate the transient optical absorption spectra of the extended double-exchange model by the density matrix renormalization group (DMRG) method. A charge-ordered insulating (COI) state becomes metallic just after photoirradiation, and the system tends to recover the initial COI state. The recovery is accompanied with remarkable suppression of an antiferromagnetic correlation in the COI state. The DMRG results are consistent with recent pump-probe spectroscopy data.Comment: 5 pages, 4 figure