Xiuxia Du

Identification of Cross-Linked Peptides after Click-Based Enrichment Using Sequential Collision-Induced Dissociation and Electron Transfer Dissociation Tandem Mass Spectrometry

Chemical cross-linking combined with mass spectrometry can be a powerful approach for the identification of protein-protein interactions and for providing constraints on protein structures. However, enrichment of cross-linked peptides is crucial to reduce sample complexity before mass spectrometric analysis. In addition compact cross-linkers are often preferred to provide short spacer lengths, surface accessibility to the protein complexes, and must have reasonable solubility under conditions where the native complex structure is stable. In this study, we present a novel compact cross-linker that contains two distinct features: (1) an alkyne tag and (2) a small molecule detection tag (NO(2)) to maintain reasonable solubility in water. The alkyne tag enables enrichment of the cross-linked peptides after proteolytic cleavage and coupling of an affinity tag using alkyne-azido click chemistry. Neutral loss of the small NO(2) moiety provides a secondary means of detecting cross-linked peptides in MS/MS analyses, providing additional confidence in peptide identifications. We show the labeling efficiency of this cross-linker, which we termed CLIP (click-enabled linker for interacting proteins) using ubiquitin. The enrichment capability of CLIP is demonstrated for cross-linked ubiquitin in highly complex E. coli cell lysates. Sequential collision-induced dissociation tandem mass spectrometry (CID-MS/MS) and electron transfer dissociation (ETD)-MS/MS of intercross-linked peptides (two peptides connected with a cross-linker) are also demonstrated for improved automated identification of cross-linked peptides.

Linear Discriminant Analysis-Based Estimation of the False Discovery Rate for Phosphopeptide Identifications

The development of liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) has made it possible to characterize phosphopeptides in an increasingly large-scale and high-throughput fashion. However, extracting confident phosphopeptide identifications from the resulting large data sets in a similar high-throughput fashion remains difficult, as does rigorously estimating the false discovery rate (FDR) of a set of phosphopeptide identifications. This article describes a data analysis pipeline designed to address these issues. The first step is to reanalyze phosphopeptide identifications that contain ambiguous assignments for the incorporated phosphate(s) to determine the most likely arrangement of the phosphate(s). The next step is to employ an expectation maximization algorithm to estimate the joint distribution of the peptide scores. A linear discriminant analysis is then performed to determine how to optimally combine peptide scores (in this case, from SEQUEST) into a discriminant score that possesses the maximum discriminating power. Based on this discriminant score, the p- and q-values for each phosphopeptide identification are calculated, and the phosphopeptide identification FDR is then estimated. This data analysis approach was applied to data from a study of irradiated human skin fibroblasts to provide a robust estimate of FDR for phosphopeptides. The Phosphopeptide FDR Estimator software is freely available for download at http://ncrr.pnl.gov/software/.

A Computational Strategy to Analyze Label-Free Temporal Bottom-Up Proteomics Data §

Biological systems are in a continual state of flux, which necessitates an understanding of the dynamic nature of protein abundances. The study of protein abundance dynamics has become feasible with recent improvements in mass spectrometry-based quantitative proteomics. However, a number of challenges still remain related to how best to extract biological information from dynamic proteomics data, for example, challenges related to extraneous variability, missing abundance values, and the identification of significant temporal patterns. This paper describes a strategy that addresses these issues and demonstrates its values for analyzing temporal bottom-up proteomics data using data from a Rhodobacter sphaeroides 2.4.1 time-course study.

Encoding and decoding target locations with waves in the turtle visual cortex

Visual stimuli elicit waves of activity that propagate across the visual cortex of turtles. An earlier study showed that these waves encode information about the positions of stimuli in visual space. This paper addresses the question of how this information can be decoded from the waves. Windowing techniques were used to temporally localize information contained in the wave. Sliding encoding windows were used to represent waves of activity as low dimensional temporal strands in an appropriate space. Expanding detection window (EDW) or sliding detection window (SDW) techniques were combined with statistical hypothesis testing to discriminate input stimuli. Detection based on an EDW was more reliable than detection based on a SDW. Detection performance improved at a very early stage of the cortical response as the length of the detection window is increased. The property of intrinsic noise was explicitly considered. Assuming that the noise is colored provided a more reliable estimate than did the assumption of a white noise in the cortical output.

Phosphoproteomics Profiling of Human Skin Fibroblast Cells Reveals Pathways and Proteins Affected by Low Doses of Ionizing Radiation

Background High doses of ionizing radiation result in biological damage; however, the precise relationships between long-term health effects, including cancer, and low-dose exposures remain poorly understood and are currently extrapolated using high-dose exposure data. Identifying the signaling pathways and individual proteins affected at the post-translational level by radiation should shed valuable insight into the molecular mechanisms that regulate dose-dependent responses to radiation. Principal Findings We have identified 7117 unique phosphopeptides (2566 phosphoproteins) from control and irradiated (2 and 50 cGy) primary human skin fibroblasts 1 h post-exposure. Semi-quantitative label-free analyses were performed to identify phosphopeptides that are apparently altered by radiation exposure. This screen identified phosphorylation sites on proteins with known roles in radiation responses including TP53BP1 as well as previously unidentified radiation-responsive proteins such as the candidate tumor suppressor SASH1. Bioinformatic analyses suggest that low and high doses of radiation affect both overlapping and unique biological processes and suggest a role for MAP kinase and protein kinase A (PKA) signaling in the radiation response as well as differential regulation of p53 networks at low and high doses of radiation. Conclusions Our results represent the most comprehensive analysis of the phosphoproteomes of human primary fibroblasts exposed to multiple doses of ionizing radiation published to date and provide a basis for the systems-level identification of biological processes, molecular pathways and individual proteins regulated in a dose dependent manner by ionizing radiation. Further study of these modified proteins and affected networks should help to define the molecular mechanisms that regulate biological responses to radiation at different radiation doses and elucidate the impact of low-dose radiation exposure on human health.

Quantitative phosphoproteome analysis of lysophosphatidic acid induced chemotaxis applying dual-step (18)O labeling coupled with immobilized metal-ion affinity chromatography.

Reversible protein phosphorylation is a central cellular regulatory mechanism in modulating protein activity and propagating signals within cellular pathways and networks. Development of more effective methods for the simultaneous identification of phosphorylation sites and quantification of temporal changes in protein phosphorylation could provide important insights into molecular signaling mechanisms in various cellular processes. Here we present an integrated quantitative phosphoproteomics approach and its application for comparative analysis of Cos-7 cells in response to lysophosphatidic acid (LPA) gradient stimulation. The approach combines trypsin-catalyzed (16)O/ (18)O labeling plus (16)O/ (18)O-methanol esterification for quantitation, a macro-immobilized metal-ion affinity chromatography trap for phosphopeptide enrichment, and LC-MS/MS analysis. LC separation and MS/MS are followed by neutral loss-dependent MS/MS/MS for phosphopeptide identification using a linear ion trap (LTQ)-FT mass spectrometer. A variety of phosphorylated proteins were identified and quantified including receptors, kinases, proteins associated with small GTPases, and cytoskeleton proteins. A number of hypothetical proteins were also identified as differentially expressed followed by LPA stimulation, and we have shown evidence of pseudopodia subcellular localization of one of these candidate proteins. These results demonstrate the efficiency of this quantitative phosphoproteomics approach and its application for rapid discovery of phosphorylation events associated with LPA gradient sensing and cell chemotaxis.

Encoding of Motion Targets by Waves in Turtle Visual Cortex

Visual stimuli evoke wave activity in the visual cortex of freshwater turtles. Earlier work from our laboratory showed that information about the positions of stationary visual stimuli is encoded in the spatiotemporal dynamics of the waves and that the waves can be decoded using Bayesian detection theory. This paper extends these results in three ways. First, it shows that flashes of light separated in space and time and stimuli moving with three speeds can be discriminated statistically using the waves generated in a large-scale model of the cortex. Second, it compares the coding capabilities of spike rate and spike time codes. Spike rate codes were obtained by low-pass filtering the activities of individual neurons in the model with filters of different band widths. For the moving targets used in the study, detectability using spike rate codes is immune to the choice of a specific bandwidth, indicating that a coarse filter is able to adequately discriminate targets. Spike timing codes are binary sequences indicating the precise timing of spike activity of individual neurons across the cortex. Spike time codes generally perform better than do spike rate codes. Third, the encoding process is examined in terms of the underlying cellular mechanisms that result in the initiation, propagation and cessation of the wave. The period of peak detectability corresponds to the period in which waves are propagating across the cortex

Information-theoretic analysis of turtle cortical waves

In this paper, we describe two approaches to the problem of encoding cortical waves of turtle visual cortex. The first approach relies on representing the response of individual pyramidal cells using various temporal scales (multiresolution analysis). In the second approach, we consider decomposing the visual cortex into various spatial grids. Each of these spatial grid contains several neurons and the Kullback-Leibler distance between the spiking patterns in response to different stimuli is computed. Such distance measure, we hope, would eventually be used to detect the stimuli.