Quantitative analysis of glycated proteins.

The proposed protocol presents a comprehensive approach for large-scale qualitative and quantitative analysis of glycated proteins (GP) in complex biological samples including biological fluids and cell lysates such as plasma and red blood cells. The method, named glycation isotopic labeling (GIL), is based on the differential labeling of proteins with isotopic [(13)C6]-glucose, which supports quantitation of the resulting glycated peptides after enzymatic digestion with endoproteinase Glu-C. The key principle of the GIL approach is the detection of doublet signals for each glycated peptide in MS precursor scanning (glycated peptide with in vivo [(12)C6]- and in vitro [(13)C6]-glucose). The mass shift of the doublet signals is +6, +3 or +2 Da depending on the peptide charge state and the number of glycation sites. The intensity ratio between doublet signals generates quantitative information of glycated proteins that can be related to the glycemic state of the studied samples. Tandem mass spectrometry with high-energy collisional dissociation (HCD-MS2) and data-dependent methods with collision-induced dissociation (CID-MS3 neutral loss scan) are used for qualitative analysis.

Individual Nomad Clinical Assistant: Supporting Nurses at the Point of Care.

Accessing patients' data at the point of care has the potential to ease the workflow of nurses and to improve the documentation. We have launched an initiative to develop a mobile assistant focused on managing nurses' daily intervention. The design has required the involvement of many stakeholder and has followed a user centered design process. The evaluation is planned in two stages with an increasing level of ecology. The solution is a client server application displaying a contextualized view on nurses' interventions. It allows to validate and comment each intervention presented as an item in a list. Deploying mobile client applications in healthcare is a challenging task not only from a technical point of view but also regarding organizational factors and human factors.

Repeated exposure to Ochratoxin A generates a neuroinflammatory response, characterized by neurodegenerative M1 microglial phenotype.

Neurotoxic effects of the environmentally abundant mycotoxin Ochratoxin A (OTA) were studied in histotypic 3D rat brain cell cultures, comprising all brain cell types. Cultures were exposed to nanomolar OTA concentrations and samples were collected 48h after a single exposure, or after 10 days of repeated administration. OTA-induced changes in gene- and protein expression, as well as alterations in cell morphology were assessed. Forty-eight-hour OTA exposure resulted in a disruption of the neuronal cytoskeleton and reduced expression of several oligodendrocyte-specific markers indicative of demyelination. Astrocyte disturbances were revealed by a decrease in two astrocytic proteins involved in regulation of inflammatory responses, metallothioneins I and II. Repeated OTA administration induced a neuroinflammatory response, as visualized by an increase of isolectin B4 labelled cells, increased expression of pro-inflammatory cytokines, and detection of macrophagic ED1/CD68 positive cells, as well as an upregulation of neurodegenerative M1 microglial phenotype markers. Partial recovery from OTA-induced deleterious effects on oligodendrocytes and astrocytes was achieved by co-treatment with sonic hedgehog (SHH). In addition, metallothionein I and II co-treatment partially restored OTA-induced effects on oligodendrocytes after 48h, and modulated microglial reactivity after 10 days. These results suggest that OTA-exposure affects Shh-signalling, which in turn may influence both oligodendrocytes and astrocytes. Furthermore, the primarily astrocytic proteins MTI/MTII may affect microglial activation. Thus the neuroinflammatory response appears to be downstream of OTA-induced effects on demyelination, axonal instabilities and astrocytes disturbances. In conclusion, repeated OTA-exposure induced a secondary neuroinflammatory response characterized by neurodegenerative M1 microglial activation and pro-inflammatory response that could exacerbate the neurodegenerative process.

Clustering and filtering tandem mass spectra acquired in data-independent mode.

Data-independent mass spectrometry activates all ion species isolated within a given mass-to-charge window (m/z) regardless of their abundance. This acquisition strategy overcomes the traditional data-dependent ion selection boosting data reproducibility and sensitivity. However, several tandem mass (MS/MS) spectra of the same precursor ion are acquired during chromatographic elution resulting in large data redundancy. Also, the significant number of chimeric spectra and the absence of accurate precursor ion masses hamper peptide identification. Here, we describe an algorithm to preprocess data-independent MS/MS spectra by filtering out noise peaks and clustering the spectra according to both the chromatographic elution profiles and the spectral similarity. In addition, we developed an approach to estimate the m/z value of precursor ions from clustered MS/MS spectra in order to improve database search performance. Data acquired using a small 3 m/z units precursor mass window and multiple injections to cover a m/z range of 400-1400 was processed with our algorithm. It showed an improvement in the number of both peptide and protein identifications by 8% while reducing the number of submitted spectra by 18% and the number of peaks by 55%. We conclude that our clustering method is a valid approach for data analysis of these data-independent fragmentation spectra. The software including the source code is available for the scientific community.

EasyProt--an easy-to-use graphical platform for proteomics data analysis.

High throughput protein identification and quantification analysis based on mass spectrometry are fundamental steps in most proteomics projects. Here, we present EasyProt (available at http://easyprot.unige.ch), a new platform for mass spectrometry data processing, protein identification, quantification and unexpected post-translational modification characterization. EasyProt provides a fully integrated graphical experience to perform a large part of the proteomic data analysis workflow. Our goal was to develop a software platform that would fulfill the needs of scientists in the field, while emphasizing ease-of-use for non-bioinformatician users. Protein identification is based on OLAV scoring schemes and protein quantification is implemented for both, isobaric labeling and label-free methods. Additional features are available, such as peak list processing, isotopic correction, spectra filtering, charge-state deconvolution and spectra merging. To illustrate the EasyProt platform, we present two identification and quantification workflows based on isobaric tagging and label-free methods.

Characterization of the glycated human cerebrospinal fluid proteome.

Protein glycation is a nonenzymatic modification that involves pathological functions in neurological diseases. Despite the high number of studies showing accumulation of advanced end glycation products (AGEs) at clinical stage, there is a lack of knowledge about which proteins are modified, where those modifications occur, and to what extent. The goal of this study was to achieve a comprehensive characterization of proteins modified by early glycation in human cerebrospinal fluid (CSF). Approaches based on glucose diferential labeling and mass spectrometry have been applied to evaluate the glycated CSF proteome at two physiological conditions: native glucose level and in vitro high glucose content. For both purposes, detection of glycated proteins was carried out by HCD-MS2 and CID-MS3 modes after endoproteinase Glu-C digestion and boronate affinity chromatography. The abundance of glycation was assessed by protein labeling with (13)C(6)-glucose incubation. The analysis of native glycated CSF identified 111 glycation sites corresponding to 48 glycated proteins. Additionally, the in vitro high glucose level approach detected 265 glycation sites and 101 glycated proteins. The comparison of glycation levels under native and 15 mM glucose conditions showed relative concentration increases up to ten folds for some glycated proteins. This report revealed for the first time a number of key glycated CSF proteins known to be involved in neuroinflammation and neurodegenerative disorders. Altogether, the present study contains valuable and unique information, which should further help to clarify the pathological role of glycation in central nervous system pathologies. This article is part of a Special Issue entitled: Translational Proteomics.