Resolution of Th/Tc17-driven inflammation during anti-TNFα treatment of rheumatoid arthritis reveals a unique immune biomarker profiling pattern.

Rheumatoid arthritis (RA) is a chronic multisystem disease with a complex immunopathology. Its inflammatory state is dominated by pro-inflammatory cytokines such as TNFα and activated Th1/Th17. Only proportion of patients achieve clinical remission despite potent biologics targeting these pathways. This study investigated the resolution of inflammation in RA patients (naïve for biologics) receiving TNFα inhibitors (TNFi) and evaluated the biological mechanisms behind treatment response and assessed them using clinical scoring systems. The majority showed a good clinical response after six months (6M) and a significant drop in DAS28-CRP (P ≤ .002), CDAI (P ≤ .0001) and RheumXpert (P ≤ .0001). Before treatment, the patients demonstrated a chronic innate and adaptive inflammatory state. The improved clinical condition was reflected with a decrease in Th17/Tc17 (P ≤ .05) and an increase in Tregs after 6M (P ≤ .05). Using a logistic regression model on serum data, IL-6, IL-18, IL-21, IL-22, IFNγ and TNFα were identified as the main contributing biomarkers in the chronic inflammatory state of RA. A specific test score (STS) was defined and converted to a single cytokine composite test score (CCTS), which showed the disease outcome on a scale 0-100, providing sensitivity and specificity of ≥90%. Thus, the immunological complexity in RA is driven by a complex interplay of pro-inflammatory cytokines and effector T-cell response dominated by Th17/Tc17. In addition, the resolution of inflammation could be linked to a partially Treg-driven homeostatic innate immune response. Therefore, a more complex therapeutic approach against the above markers might be of value to obtain full clinical remission in the future.

A comparison of platelet quality between platelets from healthy donors and hereditary hemochromatosis donors over seven-day storage.

BACKGROUND: Therapeutic phlebotomy is the standard treatment of hereditary hemochromatosis (HH), the most common genetic disease in people of Northern European descent. Red cell concentrates from HH donors have been reported safe for transfusion, but little data is available on the storage properties of platelet concentrates from HH donors. STUDY DESIGN AND METHODS: Whole blood was collected from 10 healthy individuals and 10 newly diagnosed HH patients with elevated serum ferritin. Platelet-rich plasma (PRP) was prepared and split into four 20-mL units. Platelet quality tests were performed on days 0, 1, 3, 5, and 7 of storage, including platelet aggregation (ADP, arachidonic acid, collagen, and epinephrine agonists), blood gas analysis, flow cytometry (CD41, CD42b, and CD62P expression), and ELISA (sCD40L and sCD62p in supernatant). RESULTS: Mean serum ferritin levels were higher in HH patients than in controls (847.5 vs 45.8 ng/mL, P < .001). Overall, no difference in quality test results was observed between the two study groups over 7-day storage (P > .05), including blood gas analysis, platelet aggregation, and expression of surface (CD62p and CD42b) and secreted (sCD62P and sCD40L) activation markers. Expected alterations in metabolic (CO2 and glucose decrease, O2 and lactate increase, P < .001) and platelet activation markers (CD42b decrease, CD62P increase, P < .05) over time were observed in both groups. CONCLUSION: Although these findings indicate that platelets of individuals with HH are comparable to platelets from healthy donors, more extensive studies are needed before definite conclusions can be drawn.

Predicting the open conformations of protein kinases using molecular dynamics simulations.

Protein kinases (PK) control phosphorylation in eukaryotic cells, and thereby regulate metabolic pathways, cell cycle progression, apoptosis, and transcription. Consequently, there is significant interest in manipulating PK activity and treat diseases by using small-molecule drugs. All PK catalytic domains undergo large conformational changes as a result of substrate binding and phosphorylation. The "closed" state of a PK catalytic domain is the only state able to phosphorylate the target substrate, which makes the two other observed states (the "open" and the "intermediate" states) interesting drug targets. We investigate whether molecular dynamics (MD) simulations starting from the closed state of the catalytic domain of protein kinase A (C-PKA) can be used to produce realistic structures representing the intermediate and/or open conformation of C-PKA, because this would allow for drug docking calculations and drug design using MD snapshots. We perform 36 ten-nanosecond MD simulations starting from the closed conformation [PDB ID: ATP] of C-PKA in various liganded and phosphorylated states. The results show that MD simulations are capable of reproducing the open conformation of C-PKA with good accuracy within 1 ns of simulation as measured by Cα root mean square deviations (RMSDs) and RMSDs of atoms defining the ATP-binding pocket. Importantly, we are able to show that even without knowledge of the structure of the open form of C-PKA, we can identify the MD snapshots resembling the open conformation most using the open structure of a different PK displaying only 23% sequence identity to C-PKA.

Calculating pKa values in the cAMP-dependent protein kinase: the effect of conformational change and ligand binding.

The conformational change observed upon ligand binding and phosphorylation for the cAMP-dependent protein kinase (protein kinase A-PKA) is of high importance for the regulation of its activity. We calculate pKa values and net charges for 18 3D structures of PKA in various conformations and liganded states to examine the role of electrostatics in ligand binding and activation. We find that the conformational change of PKA takes place without any significant net proton uptake/release at all pH values, thus indicating that PKA has evolved to reduce any pH-dependent barriers to the conformational motion. We furthermore find that the binding of ligands induces large changes in the net charge of PKA at most pH values, but significantly, we find that the net charge difference at physiological pH is close to zero, thus indicating that the active-site pKa values have been preorganized for substrate binding. We are unable to unequivocally resolve the identity of the groups responsible for determining the pH-activity profile of PKA but speculate that the titration of Lys 168 or the titration of ATP itself could be responsible for the loss of activity at high pH values. Finally, we examine the effect of point mutations on the pKa values of the PKA catalytic residues and find these to be relatively insensitive to both noncharge-altering and charge-altering mutations.

Capturing, sharing and analysing biophysical data from protein engineering and protein characterization studies.

Large amounts of data are being generated annually on the connection between the sequence, structure and function of proteins using site-directed mutagenesis, protein design and directed evolution techniques. These data provide the fundamental building blocks for our understanding of protein function, molecular biology and living organisms in general. However, much experimental data are never deposited in databases and is thus 'lost' in journal publications or in PhD theses. At the same time theoretical scientists are in need of large amounts of experimental data for benchmarking and calibrating novel predictive algorithms, and theoretical progress is therefore often hampered by the lack of suitable data to validate or disprove a theoretical assumption. We present PEAT (Protein Engineering Analysis Tool), an application that integrates data deposition, storage and analysis for researchers carrying out protein engineering projects or biophysical characterization of proteins. PEAT contains modules for DNA sequence manipulation, primer design, fitting of biophysical characterization data (enzyme kinetics, circular dichroism spectroscopy, NMR titration data, etc.), and facilitates sharing of experimental data and analyses for a typical university-based research group. PEAT is freely available to academic researchers at http://enzyme.ucd.ie/PEAT.

Improving the analysis of NMR spectra tracking pH-induced conformational changes: removing artefacts of the electric field on the NMR chemical shift.

pH-induced chemical shift perturbations (CSPs) can be used to study pH-dependent conformational transitions in proteins. Recently, an elegant principal component analysis (PCA) algorithm was developed and used to study the pH-dependent structural transitions in bovine beta-lactoglobulin (betaLG) by analyzing its NMR pH-titration spectra. Here, we augment this analysis method by filtering out changes in the NMR chemical shift that stem from effects that are electrostatic in nature. Specifically, we examine how many CSPs can be explained by purely electrostatic effects arising from titrational events in betaLG. The results show that around 20% of the amide nuclei CSPs in betaLG originate exclusively from "through-space" electric field effects. A PCA of NMR data where electric field artefacts have been removed gives a different picture of the pH-dependent structural transitions in betaLG. The method implemented here is well suited to be applied on a whole range of proteins, which experience at least one pH-dependent conformational change. Proteins 2010. (c) 2009 Wiley-Liss, Inc.