Addressing accuracy and precision issues in iTRAQ quantitation

iTRAQ (isobaric tags for relative or absolute quantitation) is a mass spectrometry technology that allows quantitative comparison of protein abundance by measuring peak intensities of reporter ions released from iTRAQ-tagged peptides by fragmentation during MS/MS. However, current data analysis techniques for iTRAQ struggle to report reliable relative protein abundance estimates and suffer with problems of precision and accuracy. The precision of the data is affected by variance heterogeneity: low signal data have higher relative variability; however, low abundance peptides dominate data sets. Accuracy is compromised as ratios are compressed toward 1, leading to underestimation of the ratio. This study investigated both issues and proposed a methodology that combines the peptide measurements to give a robust protein estimate even when the data for the protein are sparse or at low intensity. Our data indicated that ratio compression arises from contamination during precursor ion selection, which occurs at a consistent proportion within an experiment and thus results in a linear relationship between expected and observed ratios. We proposed that a correction factor can be calculated from spiked proteins at known ratios. Then we demonstrated that variance heterogeneity is present in iTRAQ data sets irrespective of the analytical packages, LC-MS/MS instrumentation, and iTRAQ labeling kit (4-plex or 8-plex) used. We proposed using an additive-multiplicative error model for peak intensities in MS/MS quantitation and demonstrated that a variance-stabilizing normalization is able to address the error structure and stabilize the variance across the entire intensity range. The resulting uniform variance structure simplifies the downstream analysis. Heterogeneity of variance consistent with an additive-multiplicative model has been reported in other MS-based quantitation including fields outside of proteomics; consequently the variance-stabilizing normalization methodology has the potential to increase the capabilities of MS in quantitation across diverse areas of biology and chemistry.

Neurological consequences of diabetic ketoacidosis at initial presentation of type 1 diabetes in a prospective cohort study of children

OBJECTIVE To investigate the impact of new-onset diabetic ketoacidosis (DKA) during child- hood on brain morphology and function. RESEARCH DESIGN AND METHODS Patients aged 6–18 years with and without DKA at diagnosis were studied at four time points: <48 h, 5 days, 28 days, and 6 months postdiagnosis. Patients under- went magnetic resonance imaging (MRI) and spectroscopy with cognitive assess- ment at each time point. Relationships between clinical characteristics at presentation and MRI and neurologic outcomes were examined using multiple linear regression, repeated-measures, and ANCOVA analyses. RESULTS Thirty-six DKA and 59 non-DKA patients were recruited between 2004 and 2009. With DKA, cerebral white matter showed the greatest alterations with increased total white matter volume and higher mean diffusivity in the frontal, temporal, and parietal white matter. Total white matter volume decreased over the first 6 months. For gray matter in DKA patients, total volume was lower at baseline and increased over 6 months. Lower levels of N-acetylaspartate were noted at base- line in the frontal gray matter and basal ganglia. Mental state scores were lower at baseline and at 5 days. Of note, although changes in total and regional brain volumes over the first 5 days resolved, they were associated with poorer delayed memory recall and poorer sustained and divided attention at 6 months. Age at time of presentation and pH level were predictors of neuroimaging and functional outcomes. CONCLUSIONS DKA at type 1 diabetes diagnosis results in morphologic and functional brain changes. These changes are associated with adverse neurocognitive outcomes in the medium term.

Structural analysis of human CCR2b and primate CCR2b by molecular modeling and molecular dynamics simulation

CCR2b, a chemokine receptor for MCP-1, -2, -3, -4, plays an important role in a variety of diseases involving infection, inflammation, and/or injury, as well as being a coreceptor for HIV-1 infection. Two models of human CCR2b (hCCR2b) were generated by h

Structural and functional characterization of the human CCR5 receptor in complex with HIV gp120 envelope glycoprotein and CD4 receptor by molecular modeling studies

The entry of human immunodeficiency virus (HIV) into cells depends on a sequential interaction of the gp120 envelope glycoprotein with the cellular receptors CD4 and members of the chemokine receptor family. The CC chemokine receptor CCR5 is such a receptor for several chemokines and a major coreceptor for the entry of R5 HIV type-1 (HIV-1) into cells. Although many studies focus on the interaction of CCR5 with HIV-1, the corresponding interaction sites in CCR5 and gp120 have not been matched. Here we used an approach combining protein structure modeling, docking and molecular dynamics simulation to build a series of structural models of the CCR5 in complexes with gp120 and CD4. Interactions such as hydrogen bonds, salt bridges and van der Waals contacts between CCR5 and gp120 were investigated. Three snapshots of CCR5-gp120-CD4 models revealed that the initial interactions of CCR5 with gp120 are involved in the negatively charged N-terminus (Nt) region of CCR5 and positively charged bridging sheet region of gp120. Further interactions occurred between extracellular loop2 (ECL2) of CCR5 and the base of V3 loop regions of gp120. These interactions may induce the conformational changes in gp120 and lead to the final entry of HIV into the cell. These results not only strongly support the two-step gp120-CCR5 binding mechanism, but also rationalize extensive biological data about the role of CCR5 in HIV-1 gp120 binding and entry, and may guide efforts to design novel inhibitors.

Studies on nitric oxide synthase activity in haemocytes of shrimps Fenneropenaeus chinensis and Marsupenaeus japonicus after white spot syndrome virus infection

The nitric oxide synthase (NOS) activity in the haemocytes of shrimps Fenneropenaeus chinensis (Osbeck) and Marsupenaeus japonicus (Bate) was Studied after white spot syndrome virus (WSSV) infection to determine its characteristics in response to virus infection. First, the NOS activity in haemocytes of shrimps was determined by the means of NBT reduction and changes in cell conformation. And the variations of NOS activity in shrimps after challenge with WSSV intramuscularly were evaluated through the analysis Of L-citrulline and total nitrite/nitrate (both as NO derivates) concentrations. The result showed that NOS activity in the haemocytes of F chinensis increased slightly from 0 to 12 h postchallenge, indicated by the variations Of L-Citrulline (from 11.15 +/- 0.10 to 12.08 +/- 0.64 mu M) and total nitrite/nitrate concentrations (from 10.45 +/- 0.65 to 12.67 +/- 0.52 mu M). Then it decreased sharply till the end of the experiment (84 h postchallenge), the concentrations Of L-Citrulline and total nitrite/nitrate at 84 It were 1.58 +/- 0.24 and 2.69 +/- 0.70 mu M, respectively. The LPS-stimulated NOS activity kept constant during the experiment. However, in M. japonicus, the NOS activity kept increasing during the first 72 It postchallenge, the concentrations Of L-Citrulline and total nitrite/nitrate increased from 7.82 +/- 0.77 at 0 h to 10.79 +/- 0.50 mu M at 72 h, and from 8.98 +/- 0.43 at 0 h to 11.20 +/- 0.37 mu M at 72 h, respectively. Then it decreased till the end of the experiment (216 h postchallenge), and the concentrations of L-Citrulline and total nitrite/nitrate at 216 h were 5.66 +/- 0.27 and 4.68 +/- 0.16 mu M, respectively. More importantly, an apparent increase of I-PS-stimulated NOS activity was observed in M japonicus at 48 h postchallenge, which was about 4 times higher than that in the control group of health shrimps. In correspondence with the difference of NOS activity between the two species of shrimps, the Cumulative mortalities of the shrimps were also different. All shrimps of F. chinensis in the mortality experiment died in 66 h, much more quickly than M. japonicus, Whose accumulative mortality reached 100% after 240 h. Data here reported let us hypothesize that NOS activity in the haemocytes of shrimps F chinensis and M. japonicus responses to WSSV infection differently, and this might be one of the reasons for the different susceptibility of F chinensis and M. japonicus to WSSV infection. (c) 2005 Elsevier Inc. All rights reserved.

Investigation of micro-devices for neurobiological applications

The aim of this project is to integrate neuronal cell culture with commercial or in-house built micro-electrode arrays and MEMS devices. The resulting device is intended to support neuronal cell culture on its surface, expose specific portions of a neuronal population to different environments using microfluidic gradients and stimulate/record neuronal electrical activity using micro-electrode arrays. Additionally, through integration of chemical surface patterning, such device can be used to build neuronal cell networks of specific size, conformation and composition. The design of this device takes inspiration from the nervous system because its development and regeneration are heavily influenced by surface chemistry and fluidic gradients. Hence, this device is intended to be a step forward in neuroscience research because it utilizes similar concepts to those found in nature. The large part of this research revolved around solving technical issues associated with integration of biology, surface chemistry, electrophysiology and microfluidics. Commercially available microelectrode arrays (MEAs) are mechanically and chemically brittle making them unsuitable for certain surface modification and micro-fluidic integration techniques described in the literature. In order to successfully integrate all the aspects into one device, some techniques were heavily modified to ensure that their effects on MEA were minimal. In terms of experimental work, this thesis consists of 3 parts. The first part dealt with characterization and optimization of surface patterning and micro-fluidic perfusion. Through extensive image analysis, the optimal conditions required for micro-contact printing and micro-fluidic perfusion were determined. The second part used a number of optimized techniques and successfully applied these to culturing patterned neural cells on a range of substrates including: Pyrex, cyclo-olefin and SiN coated Pyrex. The second part also described culturing neurons on MEAs and recording electrophysiological activity. The third part of the thesis described integration of MEAs with patterned neuronal culture and microfluidic devices. Although integration of all methodologies proved difficult, a large amount of data relating to biocompatibility, neuronal patterning, electrophysiology and integration was collected. Original solutions were successfully applied to solve a number of issues relating to consistency of micro printing and microfluidic integration leading to successful integration of techniques and device components.

Stochastic protein folding simulation in the three-dimensional HP-model

We present results from three-dimensional protein folding simulations in the HP-model on ten benchmark problems. The simulations are executed by a simulated annealing-based algorithm with a time-dependent cooling schedule. The neighbourhood relation is determined by the pull-move set. The results provide experimental evidence that the maximum depth D of local minima of the underlying energy landscape can be upper bounded by D < n(2/3). The local search procedure employs the stopping criterion (In/delta)(D/gamma) where m is an estimation of the average number of neighbouring conformations, gamma relates to the mean of non-zero differences of the objective function for neighbouring conformations, and 1-delta is the confidence that a minimum conformation has been found. The bound complies with the results obtained for the ten benchmark problems. (c) 2008 Elsevier Ltd. All rights reserved.

Nitric oxide-A novel therapeutic for cancer.

Much research over the past two decades has focussed on understanding the complex interactions of nitric oxide (NO()) in both physiological and pathological processes. As with many other aspects of NO() biology, its precise role in tumour pathophysiology has been the cause of intense debate and we now know that it participates in numerous signalling pathways that are crucial to the malignant character of cancer. The available experimental evidence highlights contrasting pro- and anti-tumour effects of NO() expression, which appear to be reconciled by consideration of the concentrations involved. This review addresses the complexities of the role of NO() in cancer, whilst evaluating various experimental approaches to NO()-based cancer therapies, including both inhibition of nitric oxide synthases, and overexpression of NO() using donor drugs or nitric oxide synthase gene transfer. The evidence provided strongly supports a role for manipulation of tumour NO() either as a stand-alone therapy or in combination with conventional treatments to achieve a significant therapeutic gain.

Population-based local search for protein folding simulation in the MJ energy model and cubic lattices

We present experimental results on benchmark problems in 3D cubic lattice structures with the Miyazawa-Jernigan energy function for two local search procedures that utilise the pull-move set: (i) population-based local search (PLS) that traverses the energy landscape with greedy steps towards (potential) local minima followed by upward steps up to a certain level of the objective function; (ii) simulated annealing with a logarithmic cooling schedule (LSA). The parameter settings for PLS are derived from short LSA-runs executed in pre-processing and the procedure utilises tabu lists generated for each member of the population. In terms of the total number of energy function evaluations both methods perform equally well, however. PLS has the potential of being parallelised with an expected speed-up in the region of the population size. Furthermore, both methods require a significant smaller number of function evaluations when compared to Monte Carlo simulations with kink-jump moves. (C) 2009 Elsevier Ltd. All rights reserved.

Ranking of microRNA target prediction scores by Pareto front analysis

Over the past ten years, a variety of microRNA target prediction methods has been developed, and many of the methods are constantly improved and adapted to recent insights into miRNA-mRNA interactions. In a typical scenario, different methods return different rankings of putative targets, even if the ranking is reduced to selected mRNAs that are related to a specific disease or cell type. For the experimental validation it is then difficult to decide in which order to process the predicted miRNA-mRNA bindings, since each validation is a laborious task and therefore only a limited number of mRNAs can be analysed. We propose a new ranking scheme that combines ranked predictions from several methods and - unlike standard thresholding methods - utilises the concept of Pareto fronts as defined in multi-objective optimisation. In the present study, we attempt a proof of concept by applying the new ranking scheme to hsa-miR-21, hsa-miR-125b, and hsa-miR-373 and prediction scores supplied by PITA and RNAhybrid. The scores are interpreted as a two-objective optimisation problem, and the elements of the Pareto front are ranked by the STarMir score with a subsequent re-calculation of the Pareto front after removal of the top-ranked mRNA from the basic set of prediction scores. The method is evaluated on validated targets of the three miRNA, and the ranking is compared to scores from DIANA-microT and TargetScan. We observed that the new ranking method performs well and consistent, and the first validated targets are elements of Pareto fronts at a relatively early stage of the recurrent procedure. which encourages further research towards a higher-dimensional analysis of Pareto fronts. (C) 2010 Elsevier Ltd. All rights reserved.

Structural information content of networks: Graph entropy based on local vertex functionals

In this paper we define the structural information content of graphs as their corresponding graph entropy. This definition is based on local vertex functionals obtained by calculating-spheres via the algorithm of Dijkstra. We prove that the graph entropy and, hence, the local vertex functionals can be computed with polynomial time complexity enabling the application of our measure for large graphs. In this paper we present numerical results for the graph entropy of chemical graphs and discuss resulting properties. (C) 2007 Elsevier Ltd. All rights reserved.