Precursor ion scanning for detection and structural characterization of heterogeneous glycopeptide mixtures

AbstractThe structure of N-linked glycans is determined by a complex, anabolic, intracellular pathway but the exact role of individual glycans is not always clear. Characterization of carbohydrates attached to glycoproteins is essential to aid understanding of this complex area of biology. Specific mass spectral detection of glycopeptides from protein digests may be achieved by on-line HPLC-MS, with selected ion monitoring (SIM) for diagnostic product ions generated by cone voltage fragmentation, or by precursor ion scanning for terminal saccharide product ions, which can yield the same information more rapidly. When glycosylation is heterogeneous, however, these approaches can result in spectra that are complex and poorly resolved. We have developed methodology, based around precursor ion scanning for ions of high m/z, that allows site specific detection and structural characterization of glycans at high sensitivity and resolution. These methods have been developed using the standard glycoprotein, fetuin, and subsequently applied to the analysis of the N-linked glycans attached to the scrapie-associated prion protein, PrPSc. These glycans are highly heterogeneous and over 30 structures have been identified and characterized site specifically. Product ion spectra have been obtained on many glycopeptides confirming structure assignments. The glycans are highly fucosylated and carry Lewis X or sialyl Lewis X epitopes and the structures are in-line with previous results. [Abbreviations: Hex–Hexose, C6H12O6 carbohydrates, including mannnose and galactose; HexNAc—N-acetylhexosamine, C8H15NO6 carbohydrates, including N-acetylglucosamine and N-acetylgalactosamine; GlcNAc—N-acetylglucosamine; GalNAc—N-acetylgalactosamine; Fuc–Fucose; NeuAC—N-acetylneuraminic acid or sialic acid; TSE—Transmissible Spongiform Encephalopathy.

Formation of Phase Space Holes and Clumps

It is shown that the formation of phase space holes and clumps in kinetically driven, dissipative systems is not restricted to the near threshold regime, as previously reported and widely believed. Specifically, we observe hole-clump generation from the edges of an unmodulated phase space plateau, created via excitation, phase mixing and subsequent dissipative decay of a linearly unstable bulk plasma mode in the electrostatic bump-on-tail model. This has now allowed us to elucidate the underlying physics of the hole-clump formation process for the first time. Holes and clumps develop from negative energy waves that arise due to the sharp gradients at the interface between the plateau and the nearly unperturbed, ambient distribution and destabilize in the presence of dissipation in the bulk plasma. We confirm this picture by demonstrating that the formation of such nonlinear structures in general does not rely on a "seed" wave, only on the ability of the system to generate a plateau. In addition, we observe repetitive cycles of plateau generation and erosion, the latter due to hole-clump formation and detachment, which appear to be insensitive to initial conditions and can persist for a long time. We present an intuitive discussion of why this continual regeneration occurs

Evolutionary Search and Theoretical Study of Silicene Grain Boundaries' Mechanical Properties

Defects such as grain boundaries (GBs) are almost inevitable during the synthesis process of 2D materials. To take advantage of the fascinating properties of 2D materials, understanding the nature and impact of various GB structures on the pristine 2D sheet is crucial. In this work, using an evolutionary algorithm search, we predict a wide variety of silicene GB structures with very different atomic structures compared to those found in graphene or hexagonal boron-nitride. Twenty-one GBs with the lowest energy were validated by density functional theory (DFT) - a majority of which were previously unreported to our best knowledge. Based on the diversity of the GB predictions, we found that the formation energy and mechanical properties can be dramatically altered by adatoms positions within a GB and certain types of atomic structures, such as four-atom rings. To study the mechanical behavior of these GBs, we apply strain to the GB structures stepwise and use DFT calculations to investigate the mechanical properties of 9 representative structures. It is observed that GB structures based on pentagon-heptagon pairs are likely to have similar or higher in-plane stiffness and strength compared with the zigzag orientation of pristine silicene. However, an adatom located at the hollow site of a heptagon ring can significantly deteriorate the mechanical strength. For all the structures, the in-plane stiffness and strength were found to decrease with increasing formation energy. For the failure behavior of GB structures, it was found that GB structures based on pentagon-heptagon pairs have failure behavior similar to graphene. We also found that the GB structures with atoms positioned outside of the 2D plane tend to experience phase transitions before failure. Utilizing the evolutionary algorithm, we locate diverse silicene GBs and obtain useful information for their mechanical properties.Comment: 25 pages, 9 figure

Seasonality of Social Behaviour Among Immature Belugas (Delphinapterus leucas) in Managed Care

Belugas ( Delphinapterus leucas ) in managed care have been reported to show seasonal variation in socio-sexual behaviour, hormone levels and respiration rates; however, little is known about the social interactions of wild belugas when they are not in summer, near-shore congregations. To better understand if belugas show seasonal variation in social interactions, this study recorded the behaviour of 10 belugas (five females, five males, ranging from birth to 10 years of age) housed in managed care. Social interactions typically peaked in the summer months but persisted at very low levels during the rest of the year. Sea - sonal variation was most dramatic for socio-sexual behaviour but was generally mirrored in pattern by agonistic and affiliative interactions. Subjects closer to maturity displayed more seasonal variation than younger subjects, and males displayed more seasonal variation compared to females. The peak in social interactions found in this study aligns rather closely with wild belugas’ sum - mer, near-shore congregations, where belugas have increased opportunities for socializing. Although belugas in managed care do not experience a seasonal change in habitat, they do show seasonal changes in social behaviour, which are likely driven by seasonal fluctuations in hormone levels. It is therefore expected that wild beluga populations would show similar behavioural pat - terns if they were observed throughout the remainder of the year. This research has applications for belugas in managed care and may provide a framework for understanding the social behaviour of wild belugas

DNA cruciform arms nucleate through a correlated but non-synchronous cooperative mechanism

Inverted repeat (IR) sequences in DNA can form non-canonical cruciform structures to relieve torsional stress. We use Monte Carlo simulations of a recently developed coarse-grained model of DNA to demonstrate that the nucleation of a cruciform can proceed through a cooperative mechanism. Firstly, a twist-induced denaturation bubble must diffuse so that its midpoint is near the centre of symmetry of the IR sequence. Secondly, bubble fluctuations must be large enough to allow one of the arms to form a small number of hairpin bonds. Once the first arm is partially formed, the second arm can rapidly grow to a similar size. Because bubbles can twist back on themselves, they need considerably fewer bases to resolve torsional stress than the final cruciform state does. The initially stabilised cruciform therefore continues to grow, which typically proceeds synchronously, reminiscent of the S-type mechanism of cruciform formation. By using umbrella sampling techniques we calculate, for different temperatures and superhelical densities, the free energy as a function of the number of bonds in each cruciform along the correlated but non-synchronous nucleation pathways we observed in direct simulations.Comment: 12 pages main paper + 11 pages supplementary dat

Non-Equilibrium Reaction Rates in the Macroscopic Chemistry Method for DSMC Calculations

The Direct Simulation Monte Carlo (DSMC) method is used to simulate the flow of rarefied gases. In the Macroscopic Chemistry Method (MCM) for DSMC, chemical reaction rates calculated from local macroscopic flow properties are enforced in each cell. Unlike the standard total collision energy (TCE) chemistry model for DSMC, the new method is not restricted to an Arrhenius form of the reaction rate coefficient, nor is it restricted to a collision cross-section which yields a simple power-law viscosity. For reaction rates of interest in aerospace applications, chemically reacting collisions are generally infrequent events and, as such, local equilibrium conditions are established before a significant number of chemical reactions occur. Hence, the reaction rates which have been used in MCM have been calculated from the reaction rate data which are expected to be correct only for conditions of thermal equilibrium. Here we consider artificially high reaction rates so that the fraction of reacting collisions is not small and propose a simple method of estimating the rates of chemical reactions which can be used in the Macroscopic Chemistry Method in both equilibrium and non-equilibrium conditions. Two tests are presented: (1) The dissociation rates under conditions of thermal non-equilibrium are determined from a zero-dimensional Monte-Carlo sampling procedure which simulates ‘intra-modal’ non-equilibrium; that is, equilibrium distributions in each of the translational, rotational and vibrational modes but with different temperatures for each mode; (2) The 2-D hypersonic flow of molecular oxygen over a vertical plate at Mach 30 is calculated. In both cases the new method produces results in close agreement with those given by the standard TCE model in the same highly nonequilibrium conditions. We conclude that the general method of estimating the non-equilibrium reaction rate is a simple means by which information contained within non-equilibrium distribution functions predicted by the DSMC method can be included in the Macroscopic Chemistry Method

The effect of organelle discovery upon sub-cellular protein localisation.

Prediction of protein sub-cellular localisation by employing quantitative mass spectrometry experiments is an expanding field. Several methods have led to the assignment of proteins to specific subcellular localisations by partial separation of organelles across a fractionation scheme coupled with computational analysis. Methods developed to analyse organelle data have largely employed supervised machine learning algorithms to map unannotated abundance profiles to known protein–organelle associations. Such approaches are likely to make association errors if organelle-related groupings present in experimental output are not included in data used to create a protein–organelle classifier. Currently, there is no automated way to detect organelle-specific clusters within such datasets. In order to address the above issues we adapted a phenotype discovery algorithm, originally created to filter image-based output for RNAi screens, to identify putative subcellular groupings in organelle proteomics experiments. We were able to mine datasets to a deeper level and extract interesting phenotype clusters for more comprehensive evaluation in an unbiased fashion upon application of this approach. Organelle-related protein clusters were identified beyond those sufficiently annotated for use as training data. Furthermore, we propose avenues for the incorporation of observations made into general practice for the classification of protein–organelle membership from quantitative MS experiments. Biological significance Protein sub-cellular localisation plays an important role in molecular interactions, signalling and transport mechanisms. The prediction of protein localisation by quantitative mass-spectrometry (MS) proteomics is a growing field and an important endeavour in improving protein annotation. Several such approaches use gradient-based separation of cellular organelle content to measure relative protein abundance across distinct gradient fractions. The distribution profiles are commonly mapped in silico to known protein–organelle associations via supervised machine learning algorithms, to create classifiers that associate unannotated proteins to specific organelles. These strategies are prone to error, however, if organelle-related groupings present in experimental output are not represented, for example owing to the lack of existing annotation, when creating the protein–organelle mapping. Here, the application of a phenotype discovery approach to LOPIT gradient-based MS data identifies candidate organelle phenotypes for further evaluation in an unbiased fashion. Software implementation and usage guidelines are provided for application to wider protein–organelle association experiments. In the wider context, semi-supervised organelle discovery is discussed as a paradigm with which to generate new protein annotations from MS-based organelle proteomics experiments. This article is part of a Special Issue entitled: New Horizons and Applications for Proteomics [EuPA 2012]

Photosynthetic acclimation of Nannochloropsis oculata investigated by multi-wavelength chlorophyll fluorescence analysis

Multi-wavelength chlorophyll fluorescence analysis was utilised to examine the photosynthetic efficiency of the biofuel-producing alga Nannochloropsis oculata, grown under two light regimes; low (LL) and high (HL) irradiance levels. Wavelength dependency was evident in the functional absorption cross-section of Photosystem II (σII(λ)), absolute electron transfer rates (ETR(II)), and non-photochemical quenching (NPQ) of chlorophyll fluorescence in both HL and LL cells. While σII(λ) was not significantly different between the two growth conditions, HL cells upregulated ETR(II) 1.6-1.8-fold compared to LL cells, most significantly in the wavelength range of 440-540nm. This indicates preferential utilisation of blue-green light, a highly relevant spectral region for visible light in algal pond conditions. Under these conditions, the HL cells accumulated saturated fatty acids, whereas polyunsaturated fatty acids were more abundant in LL cells. This knowledge is of importance for the use of N. oculata for fatty acid production in the biofuel industry. © 2014 Elsevier Ltd

Large Scale Structures a Gradient Lines: the case of the Trkal Flow

A specific asymptotic expansion at large Reynolds numbers (R)for the long wavelength perturbation of a non stationary anisotropic helical solution of the force less Navier-Stokes equations (Trkal solutions) is effectively constructed of the Beltrami type terms through multi scaling analysis. The asymptotic procedure is proved to be valid for one specific value of the scaling parameter,namely for the square root of the Reynolds number (R).As a result large scale structures arise as gradient lines of the energy determined by the initial conditions for two anisotropic Beltrami flows of the same helicity.The same intitial conditions determine the boundaries of the vortex-velocity tubes, containing both streamlines and vortex linesComment: 27 pages, 2 figure