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Introduction Small for gestational age (SGA) may be associated with neonatal morbidity and mortality. Our understanding of the molecular pathways implicated is poor. Objectives Our aim was to determine the metabolic pathways involved in the pathophysiology of SGA and examine their variation between maternal biofluid samples. Methods Plasma (Cork) and urine (Cork, Auckland) samples were collected at 20 weeks’ gestation from nulliparous low-risk pregnant women participating in the SCOPE study. Women who delivered an SGA infant (birthweight Results Lipidomics plasma analysis revealed that 22 out of the 33 significantly altered lipids annotated were glycerophospholipids; all were detected in higher levels in SGA. Metabolomic analysis identified reduced expression of metabolites associated with detoxification (D-Glucuronic acid, Estriol-16-glucuronide), nutrient absorption and transport (Sulfolithocholic acid) pathways. Conclusions This study suggests higher levels of glycerophospholipids, and lower levels of specific urine metabolites are implicated in the pathophysiology of SGA. Further research is needed to confirm these findings in independent samples.

Introduction Preterm birth (PTB) is defined as birth occurring before 37 weeks’ gestation, affects 5–9% of all pregnancies in developed countries, and is the leading cause of perinatal mortality. Spontaneous preterm birth (sPTB) accounts for 31–50% of all PTB, but the underlying pathophysiology is poorly understood. Objective This study aimed to decipher the lipidomics pathways involved in pathophysiology of sPTB. Methods Blood samples were taken from SCreening fOr Pregnancy Endpoints (SCOPE), an international study that recruited 5628 nulliparous women, with a singleton low-risk pregnancy. Our analysis focused on plasma from SCOPE in Cork. Discovery profiling of the samples was undertaken using liquid chromatography-mass spectrometry Lipidomics, and features significantly altered between sPTB (n = 16) and Control (n = 32) groups were identified using empirical Bayes testing, adjusting for multiple comparisons. Results Twenty-six lipids showed lower levels in plasma of sPTB compared to controls (adjusted p Conclusions We report reduced levels of plasma phospholipids in sPTB. Phospholipid integrity is linked to biological membrane stability and inflammation, while storage and breakdown of lipids have previously been implicated in pregnancy complications. The contribution of phospholipids to sPTB as a cause or effect is still unclear; however, our results of differential plasma phospholipid expression represent another step in advancing our understanding of the aetiology of sPTB. Further work is needed to validate these findings in independent pregnancy cohorts.

The present paper introduces the use of a weak cation-exchange/crown ether column in the proteomics field. The 18-crown-6 ether functionality is well-known to selectively complex ammonium and monoalkylammonium ions, which should make this column highly suitable to trap peptides with free alpha-NH(2) or free epsilon-NH(2) groups from lysine side chains. This unique selection mechanism was put to the test in an N-teromics setup which aims for the enrichment of deliberately acetylated protein N-terminal peptides from a serum digest. It was demonstrated that peptides with free alpha-NH(2) groups and peptides with alpha-amino-acetylated groups can be separated from each other using this weak cation-exchange/crown ether column. The peptides of interest, bearing no free primary amines, were found to be significantly enriched in the column's flow through. At the same time a favorable coenrichment of N-glycosylated peptides was observed. To obtain more insight in the contributions of the two distinct column functionalities, i.e., the weak cation exchanger and the crown ether, the experimental data were checked against a theoretical prediction of the outcome.

Combined fractional diagonal chromatography (COFRADIC) is a novel suite of gel-free technologies for the identification of biomarkers in complex peptide mixtures. For this purpose, reversed-phase high performance liquid chromatography (HPLC) technology and, in this case, matrix assisted laser desorption /ionization- time of flight (MALDI-TOF) mass spectrometers are extensively used. The particular characteristic of COFRADIC mass spectrometry data is the high number of chromatographic fractions, over which a peptide can be scattered. This can obstruct the quantification of the peptide abundance in the biological sample, which is required for statistical analysis. On the other hand, because of the superior peptide sorting properties of the methodology, the mass spectra become less crowded. Consequently, each peptide appears in a mass spectrum as a series of peaks with peak heights proportional to the probability of occurrence of the isotopic variants of the peptide. In this manuscript, we propose an analysis strategy concerned with the preprocessing of COFRADIC mass spectra prior to a downstream statistical analysis. The preprocessing algorithm produces for each mass spectrum a peptide list by exploiting the characteristic features that should be associated with peaks corresponding to an isotopically resolved cluster of peptide peaks. This reduction step is necessary to facilitate the clustering used in a next step to assemble the validated monoisotopic peptide peaks found over several fractions into a single peptide abundance. To assess the performance of the algorithm, two technical experiments were conducted. The proposed strategy is memory and computationally efficient.

The previously reported COmbined FRActional DIagonal Chromatography (COFRA-DIC) methodology, in which a subset of peptides representative for their parent proteins are sorted, is particularly powerful for whole proteome analysis. This peptide-centric technology is built around diagonal chromatography, where peptide separations are crucial. This paper presents high efficiency peptide separations, in which four 250 x 2.1 mm, 5 microm Zorbax 300SB-C18 columns (total length 1 m) were coupled at operating temperatures of 60'C using a dedicated LC oven and conventional LC equipment. The high efficiency separations were combined with the COFRADIC procedure. This extremely powerful combination resulted, for the analysis of serum, in an increase in the uniquely identified peptide sequences by a factor of 2.6, compared to the COFRADIC procedure on a 25 cm column. This is a reflection of the increased peak capacity obtained on the 1 m column, which was calculated to be a factor 2.7 higher than on the 25 cm column. Besides more efficient sorting, less ion suppression was noticed.

Breen et al. (Electrophoresis 2000; 21: 2243) proposed a method for finding monoisotopic peptide peaks in mass spectra based on an approximation of the distribution of different isotopic variants of a peptide by a Poisson distribution. They developed the method using all protein sequences from the SWISS-PROT database. We investigate the suitability of this method to predict the isotopic distribution in an environment which enriches for peptides carrying sulphur. More specifically, we focus on mass spectra obtained by a COmbined FRActional DIagonal Chromatography (COFRADIC) approach, developed by Gevaert et al. (Nature Biotechnology 2003; 21: 566), targeting a specific subset of peptides, in this case the N-terminal peptides. One can therefore ask whether the original results of Breen et al. apply to spectra generated by the particular COFRADIC method. We investigate whether the proposed approximation holds for N-terminal peptides. We also evaluate whether ignoring sulphur atoms while developing the approximation, as proposed by Breen et al., does not increase the risk of missing monoisotopic peaks corresponding to sulphur-containing peptides. Finally, we check the sensitivity of the quality of the approximation to optimization criteria used in the development process. The results are not simply restricted to a COFRADIC setting but are also applicable more generally, for any method which enriches for sulphur-containing peptides. Copyright © 2007 John Wiley & Sons, Ltd.

Several studies have been published in which holistic approaches were used to characterise the proteome and transcriptome of human platelets. The key intent being that a deeper understanding of the normal and aberrant physiological functions of platelets can only be achieved if most biomolecular building blocks are mapped. Here we present the application of recently developed novel technologies that overcome some of the shortcomings of gel-based proteomics. Central in our approach is the so-called combined fractional diagonal chromatography (COFRADIC)-technology in which sets of representative peptides are sorted in a diagonal RP chromatographic system through a specific modification of their side chain. In this study we combined three different COFRADIC sorting techniques to analyse the proteome of human platelets. Methionyl, cysteinyl and amino terminal peptides were isolated and analysed by MS/MS. Merging the peptide identifications obtained after database searching resulted in a core set of 641 platelet proteins, which comprises the largest set identified today. In comparison to previously published platelet proteomes, we identified 404 novel platelet proteins containing a high number of hydrophobic membrane proteins and hypothetical proteins. Furthermore we discuss the observed characteristics and potential benefits of each of the different COFRADIC technologies for proteome analysis and highlight important issues that need to be considered when searching sequence databases using data obtained in peptide-centric, non-gel proteomics studies.

We report upon a novel procedure to specifically isolate cysteine-containing peptides from a complex peptide mixture. Cysteines are converted to hydrophobic residues by mixed disulfide formation with Ellman's reagent. Proteins are subsequently digested with trypsin and the generated peptide mixture is a first time fractionated by reverse-phase high-performance liquid chromatography. Cysteinyl-peptides are isolated out of each primary fraction by a reduction step followed by a secondary peptide separation on the same column, performed under identical conditions as for the primary separation. The reducing agent removes the covalently attached group from the cysteine side chain, making cysteine-peptides more hydrophilic and, thereby, such peptides can be specifically collected during the secondary separation and are finally used to identify their precursor proteins using automated liquid chromatography tandem mass spectrometry. We show that this procedure efficiently isolates cysteine-peptides, making the sample mixture less complex for further analysis. This method was applied for the analysis of the proteomes of human platelets and enriched human plasma. In both proteomes, a significant number of low abundance proteins were identified next to extremely abundant ones. A dynamic range for protein identification spanning 4-5 orders of magnitude is demonstrated.

Current non-gel techniques for analyzing proteomes rely heavily on mass spectrometric analysis of enzymatically digested protein mixtures. Prior to analysis, a highly complex peptide mixture is either separated on a multidimensional chromatographic system or it is first reduced in complexity by isolating sets of representative peptides. Recently, we developed a peptide isolation procedure based on diagonal electrophoresis and diagonal chromatography. We call it combined fractional diagonal chromatography (COFRADIC). In previous experiments, we used COFRADIC to identify more than 800 Escherichia coli proteins by tandem mass spectrometric (MS/MS) analysis of isolated methionine-containing peptides. Here, we describe a diagonal method to isolate N-terminal peptides. This reduces the complexity of the peptide sample, because each protein has one N terminus and is thus represented by only one peptide. In this new procedure, free amino groups in proteins are first blocked by acetylation and then digested with trypsin. After reverse-phase (RP) chromatographic fractionation of the generated peptide mixture, internal peptides are blocked using 2,4,6-trinitrobenzenesulfonic acid (TNBS); they display a strong hydrophobic shift and therefore segregate from the unaltered N-terminal peptides during a second identical separation step. N-terminal peptides can thereby be specifically collected for further liquid chromatography (LC)-MS/MS analysis. Omitting the acetylation step results in the isolation of non-lysine-containing N-terminal peptides from in vivo blocked proteins.

A novel gel-free proteomic technology was used to identify more than 800 proteins from 50 million Escherichia coli K12 cells in a single analysis. A peptide mixture is first obtained from a total unfractionated cell lysate, and only the methionine-containing peptides are isolated and identified by mass spectrometry and database searching. The sorting procedure is based on the concept of diagonal chromatography but adapted for highly complex mixtures. Statistical analysis predicts that we have identified more than 40% of the expressed proteome, including soluble and membrane-bound proteins. Next to highly abundant proteins, we also detected low copy number components such as the E. coli lactose operon repressor, illustrating the high dynamic range. The method is about 100 times more sensitive than two-dimensional gel-based methods and is fully automated. The strongest point, however, is the flexibility in the peptide sorting chemistry, which may target the technique toward quantitative proteomics of virtually every class of peptides containing modifiable amino acids, such as phosphopeptides, amino-terminal peptides, etc., adding a new dimension to future proteome research.

Introduction Screening for pre-eclampsia is a focus of prenatal care and is largely based on the use of clinical risk factors. However, current screening protocols are unfit to determine pre-eclampsia risk in 1st time pregnant women; biomarkers have the potential to address this unmet need. As single biomarkers have insufficient predictive accuracy, unbiased biomarker discoveries have been performed to identify panels of markers which when combined, have the potential pre-eclampsia prediction. Metabolite based solutions using mass spectrometry have gained significant interest as they have the potential to readily translate to clinical practice. Objectives To translate the discovery that blood-borne metabolite biomarkers stratify pregnant women early in pregnancy (∼15 weeks) to their risk of pre-eclampsia [1] into a commercial LC–MS based clinical assay. To pursue fit-for-purpose testing of the first version of the developed LC–MS pipeline followed by independent verification through a case:control study. Methods The analysis pipeline incorporated (1) a single step metabolite extraction, (2) multiplex LC-QqQ-MS assays for 40+ metabolites and (3) a dedicated data processing protocol. Case:control study testing utilised 15 weeks’ plasma samples of from 50 pregnant women who subsequently developed pre-eclampsia and 500 random control pregnancies. All participants are part of the SCOPE study [2] and were recruited in Cork, Ireland. Results For the 40+ metabolite assays: 62% had a %CV £ 15% and 82% had a %CV £ 25%. Univariate analyses using the ROC statistic showed that 7 of the metabolites tested had significant predictive power (lower limit 95% CI ROC-AUC [3] 0.5). Multivariate logistic regression analysis revealed particular combinations of metabolites which identified groups of women either at increased risk or at decreased risk for pre-eclampsia. Conclusion These findings underpin the potential of metabolite-centric multimarker panels to encapsulate a complex syndrome such as pre-eclampsia considerably in advance of any clinical manifestation. Further development steps will include performing additional case:control studies and subsequent clinical validation of this metabolite based test in the large scale European, multicentre phase IIa clinical study IMproved Pregnancy Outcomes by Early Detection (IMPROvED) which is currently recruiting 1st time pregnant women in 5 European countries [3] . Acknowledgment The authors gratefully acknowledge funding from the EU-HEALTH Project IMPROvED (305169) of the Seventh Framework Programme (FP7).