Stratification of asthma phenotypes by airway proteomic signatures.

BACKGROUND: Stratification by eosinophil and neutrophil counts increases our understanding of asthma and helps target therapy, but there is room for improvement in our accuracy in prediction of treatment responses and a need for better understanding of the underlying mechanisms. OBJECTIVE: We sought to identify molecular subphenotypes of asthma defined by proteomic signatures for improved stratification. METHODS: Unbiased label-free quantitative mass spectrometry and topological data analysis were used to analyze the proteomes of sputum supernatants from 246 participants (206 asthmatic patients) as a novel means of asthma stratification. Microarray analysis of sputum cells provided transcriptomics data additionally to inform on underlying mechanisms. RESULTS: Analysis of the sputum proteome resulted in 10 clusters (ie, proteotypes) based on similarity in proteomic features, representing discrete molecular subphenotypes of asthma. Overlaying granulocyte counts onto the 10 clusters as metadata further defined 3 of these as highly eosinophilic, 3 as highly neutrophilic, and 2 as highly atopic with relatively low granulocytic inflammation. For each of these 3 phenotypes, logistic regression analysis identified candidate protein biomarkers, and matched transcriptomic data pointed to differentially activated underlying mechanisms. CONCLUSION: This study provides further stratification of asthma currently classified based on quantification of granulocytic inflammation and provided additional insight into their underlying mechanisms, which could become targets for novel therapies.

Large-Scale Label-Free Quantitative Mapping of the Sputum Proteome.

Analysis of induced sputum supernatant is a minimally invasive approach to study the epithelial lining fluid and, thereby, provide insight into normal lung biology and the pathobiology of lung diseases. We present here a novel proteomics approach to sputum analysis developed within the U-BIOPRED (unbiased biomarkers predictive of respiratory disease outcomes) international project. We present practical and analytical techniques to optimize the detection of robust biomarkers in proteomic studies. The normal sputum proteome was derived using data-independent HDMSE applied to 40 healthy nonsmoking participants, which provides an essential baseline from which to compare modulation of protein expression in respiratory diseases. The "core" sputum proteome (proteins detected in ≥40% of participants) was composed of 284 proteins, and the extended proteome (proteins detected in ≥3 participants) contained 1666 proteins. Quality control procedures were developed to optimize the accuracy and consistency of measurement of sputum proteins and analyze the distribution of sputum proteins in the healthy population. The analysis showed that quantitation of proteins by HDMSE is influenced by several factors, with some proteins being measured in all participants' samples and with low measurement variance between samples from the same patient. The measurement of some proteins is highly variable between repeat analyses, susceptible to sample processing effects, or difficult to accurately quantify by mass spectrometry. Other proteins show high interindividual variance. We also highlight that the sputum proteome of healthy individuals is related to sputum neutrophil levels, but not gender or allergic sensitization. We illustrate the importance of design and interpretation of disease biomarker studies considering such protein population and technical measurement variance.

Automated protein backbone assignment using the projection-decomposition approach.

Spectral projection experiments by NMR in conjunction with decomposition analysis have been previously introduced for the backbone assignment of proteins; various pulse sequences as well as the behaviour with low signal-to-noise or chemical shift degeneracy have been illustrated. As a guide for routine applications of this combined tool, we provide here a systematic analysis on different types of proteins using welldefined run-time parameters. As a second result of this study, the backbone assignment module SHABBA was extensively rewritten and improved. Calculations on ubiquitin yielded again fully correct and nearly complete backbone and CHß assignments. For the 128 residue long azurin, missing assignments mostly affect Hα and Hß. Among the remaining backbone (plus Cß) nuclei 97.5 % could be assigned with 1.0 % differences to a reference. Finally, the new SHABBA algorithm was applied to projections recorded for a yeast histone protein domain at room temperature, where the protein is subject to partial unfolding: this leads to unobservable resonances (about a dozen missing signals in a normal 15N-HSQC) and extensive degeneracy among the resonances. From the clearly observable residues, 97.5 % of the backbone and CHßresonances could be assigned, of which only 0.8 % showed differences to published shifts. An additional study on the protein MMP20, which exhibits spectral difficulties to an even larger extent, explores the limitations of the approach.

Assignment of protein NMR spectra based on projections, multi-way decomposition and a fast correlation approach.

We present an approach for the assignment of protein NMR resonances that combines established and new concepts: (a) Based on published reduced dimensionality methods, two 5-dimensional experiments are proposed. (b) Multi-way decomposition (PRODECOMP) applied simultaneously to all acquired NMR spectra provides the assignment of resonance frequencies under conditions of very low signal-to-noise. (c) Each resulting component characterizes all spin (1/2) nuclei in a (doubly-labeled) CbetaH(n)-CalphaH-C'-NH-CalphaH-CbetaH(n) fragment in an unambiguous manner, such that sequentially neighboring components have about four atoms in common. (d) A new routine (SHABBA) determines correlations for all component pairs based on the common nuclei; high correlation values yield sequential chains of a dozen or more components. (e) The potentially error-prone peak picking is delayed to the last step, where it helps to place the component chains within the protein sequence, and thus to achieve the final backbone assignment. The approach was validated by achieving complete backbone resonance assignments for ubiquitin.

PRODECOMPv3: decompositions of NMR projections for protein backbone and side-chain assignments and structural studies.

UNLABELLED: PRODECOMP (projection decomposition) is an implementation of a multi-way decomposition algorithm for the analysis of two-dimensional projections of high-dimensional nuclear magnetic resonance spectra. The newest version, PRODECOMPv3, features a dramatic speedup, more reliable decompositions, a substantial reduction in memory demands, a new graphical user interface and integration into third-party software. These improvements extend the applicability of decompositions to novel types of NMR data on proteins, yielding backbone and side-chain assignments as well as structural information, and therewith enabling complete characterizations of proteins. AVAILABILITY: Program, short manual and an example calculation are freely available at www2.chem.gu.se/bcbp/nmr/prodecomp.html.

Formation of methane hydrate from polydisperse ice powders.

Neutron diffraction runs and gas-consumption experiments based on pressure-volume-temperature measurements are conducted to study the kinetics of methane hydrate formation from hydrogenated and deuterated ice powder samples in the temperature range of 245-270 K up to high degrees of transformation. An improved theory of the hydrate growth in a polydisperse ensemble of randomly packed ice spheres is developed to provide a quantitative interpretation of the data in terms of kinetic model parameters. This paper continues the research line of our earlier study which was limited to the monodisperse case and shorter reaction times (Staykova et al., 2003). As before, we distinguish the process of initial hydrate film spreading over the ice particle surface (stage I) and the subsequent hydrate shell growth (stage II) which includes two steps, i.e., an interfacial clathration reaction and the gas and water transport (diffusion) through the hydrate layer surrounding the shrinking ice cores. Although kinetics of hydrate formation at stage II is clearly dominated by the diffusion mechanism which becomes the limiting step at temperatures above 263 K, both steps are shown to be essential at lower temperatures. The permeation coefficient D is estimated as (1.46 +/- 0.44) x 10(-12) m2/h at 263 K with an activation energy Q(D) approximately 52.1 kJ/mol. This value is close to the energy of breaking hydrogen bonds in ice Ih and suggests that this process is the rate-limiting step in hydrate formation from ice in the slower diffusion-controlled part of the reaction.