Biophysical analysis of the putative acetyltransferase SACOL2570 from methicillin-resistant Staphylococcus aureus.

Methicillin-resistant Staphylococcus aureus (MRSA) is a major cause of a myriad of insidious and intractable infections in humans, especially in patients with compromised immune systems and children. Here, we report the apo- and CoA-bound crystal structures of a member of the galactoside acetyltransferase superfamily from methicillin-resistant S. aureus SACOL2570 which was recently shown to be down regulated in S. aureus grown in the presence of fusidic acid, an antibiotic used to treat MRSA infections. SACOL2570 forms a homotrimer in solution, as confirmed by small-angle X-ray scattering and dynamic light scattering. The protein subunit consists of an N-terminal alpha-helical domain connected to a C-terminal LßH domain. CoA binds in the active site formed by the residues from adjacent LßH domains. After determination of CoA-bound structure, molecular dynamics simulations were performed to model the binding of AcCoA. Binding of both AcCoA and CoA to SACOL2570 was verified by isothermal titration calorimetry. SACOL2570 most likely acts as an acetyltransferase, using AcCoA as an acetyl group donor and an as-yet-undetermined chemical moiety as an acceptor. SACOL2570 was recently used as a scaffold for mutations that lead the generation of cage-like assemblies, and has the potential to be used for the generation of more complex nanostructures.

Alternaria alternata allergen Alt a 1: a unique ß-barrel protein dimer found exclusively in fungi.

BACKGROUND: Alternaria species is one of the most common molds associated with allergic diseases, and 80% of Alternaria species-sensitive patients produce IgE antibodies to a major protein allergen, Alt a 1. The structure and function of Alt a 1 is unknown. OBJECTIVE: We sought to obtain a high-resolution structure of Alt a 1 using x-ray crystallography and to investigate structural relationships between Alt a 1 and other allergens and proteins reported in the Protein Data Bank. METHODS: X-ray crystallography was used to determine the structure of Alt a 1 by using a custom-designed set of crystallization conditions. An initial Alt a 1 model was determined by the application of a Ta(6)Br(12)(2+) cluster and single-wavelength anomalous diffraction. Bioinformatic analyses were used to compare the Alt a 1 sequence and structure with that of other proteins. RESULTS: Alt a 1 is a unique ß-barrel comprising 11 ß-strands and forms a "butterfly-like" dimer linked by a single disulfide bond with a large (1345 Å(2)) dimer interface. Intramolecular disulfide bonds are conserved among Alt a 1 homologs. Currently, the Alt a 1 structure has no equivalent in the Protein Data Bank. Bioinformatics analyses suggest that the structure is found exclusively in fungi. Four previously reported putative IgE-binding peptides have been located on the Alt a 1 structure. CONCLUSIONS: Alt a 1 has a unique, dimeric ß-barrel structure that appears to define a new protein family with unknown function found exclusively in fungi. The location of IgE antibody-binding epitopes is in agreement with the structural analysis of Alt a 1. The Alt a 1 structure will allow mechanistic structure/function studies and immunologic studies directed toward new forms of immunotherapy for Alternaria species-sensitive allergic patients.

Structural and immunologic characterization of Ara h 1, a major peanut allergen.

Allergic reactions to peanuts and tree nuts are major causes of anaphylaxis in the United States. We compare different properties of natural and recombinant versions of Ara h 1, a major peanut allergen, through structural, immunologic, and bioinformatics analyses. Small angle x-ray scattering studies show that natural Ara h 1 forms higher molecular weight aggregates in solution. In contrast, the full-length recombinant protein is partially unfolded and exists as a monomer. The crystal structure of the Ara h 1 core (residues 170-586) shows that the central part of the allergen has a bicupin fold, which is in agreement with our bioinformatics analysis. In its crystalline state, the core region of Ara h 1 forms trimeric assemblies, while in solution the protein exists as higher molecular weight assemblies. This finding reveals that the residues forming the core region of the protein are sufficient for formation of Ara h 1 trimers and higher order oligomers. Natural and recombinant variants of proteins tested in in vitro gastric and duodenal digestion assays show that the natural protein is the most stable form, followed by the recombinant Ara h 1 core fragment and the full-length recombinant protein. Additionally, IgE binding studies reveal that the natural and recombinant allergens have different patterns of interaction with IgE antibodies. The molecular basis of cross-reactivity between vicilin allergens is also elucidated.

Activation Complexity: A Cognitive Impairment Tool for Characterizing Neuro-isolation.

Electroencephalography (EEG) is a method for recording electrical activity, indicative of cortical brain activity from the scalp. EEG has been used to diagnose neurological diseases and to characterize impaired cognitive states. When the electrical activity of neurons are temporally synchronized, the likelihood to reach their threshold potential for the signal to propagate to the next neuron, increases. This phenomenon is typically analyzed as the spectral intensity increasing from the summation of these neurons firing. Non-linear analysis methods (e.g., entropy) have been explored to characterize neuronal firings, but only analyze temporal information and not the frequency spectrum. By examining temporal and spectral entropic relationships simultaneously, we can better characterize how neurons are isolated, (the signal's inability to propagate to adjacent neurons), an indicator of impairment. A novel time-frequency entropic analysis method, referred to as Activation Complexity (AC), was designed to quantify these dynamics from key EEG frequency bands. The data was collected during a cognitive impairment study at NASA Langley Research Center, involving hypoxia induction in 49 human test subjects. AC demonstrated significant changes in EEG firing patterns characterize within explanatory (p < 0.05) and predictive models (10% increase in accuracy). The proposed work sets the methodological foundation for quantifying neuronal isolation and introduces new potential technique to understand human cognitive impairment for a range of neurological diseases and insults.

Uncertainty in heart rate complexity metrics caused by R-peak perturbations.

Heart rate complexity (HRC) is a proven metric for gaining insight into human stress and physiological deterioration. To calculate HRC, the detection of the exact instance of when the heart beats, the R-peak, is necessary. Electrocardiogram (ECG) signals can often be corrupted by environmental noise (e.g., from electromagnetic interference, movement artifacts), which can potentially alter the HRC measurement, producing erroneous inputs which feed into decision support models. Current literature has only investigated how HRC is affected by noise when R-peak detection errors occur (false positives and false negatives). However, the numerical methods used to calculate HRC are also sensitive to the specific location of the fiducial point of the R-peak. This raises many questions regarding how this fiducial point is altered by noise, the resulting impact on the measured HRC, and how we can account for noisy HRC measures as inputs into our decision models. This work uses Monte Carlo simulations to systematically add white and pink noise at different permutations of signal-to-noise ratios (SNRs), time segments, sampling rates, and HRC measurements to characterize the influence of noise on the HRC measure by altering the fiducial point of the R-peak. Using the generated information from these simulations provides improved decision processes for system design which address key concerns such as permutation entropy being a more precise, reliable, less biased, and more sensitive measurement for HRC than sample and approximate entropy.