Spectrometry Data Research Articles

GC-MS metabolomics analysis of mesenchymal stem cells treated with copper oxide nanoparticles

Human exposure to copper oxide (CuO) nanoparticles (NPs) is rapidly increasing and for this reason reliable toxicity test systems are urgently needed. Recently, the acute cytotoxicity of CuO NPs using the new toxicity test based on human bone marrow mesenchymal stem cells (hBMMSCs) has been evaluated. It was shown that CuO NPs are much more toxic when compared to CuO microparticles (MPs). Several studies associate CuO toxicity to a possible alteration of reactive oxygen species (ROS) system. Unluckily, the mechanism that causes the toxicity is still not clear. In this work, the polar metabolite pool of treated cells, at the corresponding IC50 value, for CuO micro and NPs has been studied by gas chromatography coupled to mass spectrometry (GC-MS) and multivariate statistical data analysis. By the same means, differences due to different treatments, on samples, were investigated. Results of discriminant analysis were considered with the aim of finding the relevant metabolites unique for each class. Serine, glyceric acid, and succinic acid were upregulated on samples treated with CuO microparticles, while glutamine was the only discriminant metabolite for the class of samples treated with nanoparticles.

Zero-order metoprolol pharmacokinetics after therapeutic doses: severe toxicity and cardiogenic shock

Objective: Acute beta-blocker overdose can cause severe cardiac dysfunction. Chronic toxicity is rare but potentially severe. We report therapeutic dosing of metoprolol resulting in unusual pharmacokinetics and toxicity, given high-dose insulin therapy for treatment.Case details: A 90-year-old female presented with hypotension, tachycardia and severe cardiac dysfunction after commencing a rapidly increasing metoprolol dose of 250 mg split daily. She was admitted to intensive care and given high-dose insulin therapy (10 U/kg/h), noradrenaline, adrenaline and dobutamine for severe cardiac dysfunction (cardiac index, 0.76 L/min/m2). She developed acute renal failure, ischaemic hepatitis and disseminated intravascular coagulopathy. Inotropes and high-dose insulin were weaned over four days with complete recovery. Metoprolol was quantified with liquid chromatography-tandem mass spectrometry and concentration-time data were analysed using MONOLIX® vs 4.3 (www.lixoft.com). Admission metoprolol concentration was 2.39 μg/mL (therapeutic reference range: 0.035–0.5 μg/mL). Data best fitted a one compartmental model with Michaelis–Menten kinetics and zero order elimination at high concentrations. Final parameter estimates were V, 63.4 L, maximum rate [Vm], 9.57 mg h−1, Michaelis constant [Km], 1.97 mg L−1. Predicted elimination half-life decreased from 20 h over time until there was first order elimination with a half-life 9 h.Conclusion: The time course of cardiac dysfunction was longer than acute overdose but consistent with prolonged zero order elimination of metoprolol, suggesting the patient was a poor CYP2D6 metaboliser. High-dose insulin euglycaemia appeared to be effective in combination with vasoconstrictors/inotropes.

Editorial: Metabolome Informatics and Statistics: Current State and Emerging Trends

The Editorial on the Research Topic Metabolome Informatics and Statistics: Current State and Emerging Trends Metabolomics has developed tremendously since the term “metabolome” was coined almost 20 years ago (Oliver et al., 1998). Once the domain of few laboratories, it is now a core capability at most major universities and research institutions. An important developmental indicator for any scientific discipline is the maturity of its informatics – the functional diversity and efficacy of computational and statistical approaches, software tools, databases, and data exchange standards that help transform raw data into understanding. The 13 articles from 81 authors in this frontiers research topic provide a snapshot of the current state of these platforms. Metabolomics offers unique challenges for software developers. One of the most fundamental is the development of databases enabling the structures and properties of metabolites to be queried in ways that enhance research. In this research topic, Johnson and Lange review the development of open-access spectral reference databases to aid natural product identification. Maeda describes 3DMET1 – a database of metabolite three-dimensional (3D) structures – using software to convert 2D representations of 3D structures from printed articles to 3D digital structure models. The diversity of analytical techniques used in metabolomics is wider than in other omics disciplines, and the list of relevant technologies continues to grow. Thus, each technique is typically associated with a swathe of literature describing specialized computational methods and software tools, and there is always demand for new software to support new methods. The review article “Analytical methods in untargeted metabolomics: state of the art in 2015” provides a useful overview of this area (Alonso et al.). For the processing of liquid chromatography mass spectrometry (LC-MS) data, Tsugawa et al. describe multiple reaction monitoring (MRM)-DIFF – a powerful pipeline for MRM-based analysis of lipidomic samples on LC-triple quadrupole MS instruments. As a demonstration of novel approaches for LC-MS peak identification, van der Hooft et al. describe how an analysis of high resolution MSn fragmentation spectra using freely available MAGMa software2 could be used to annotate peaks of 50 different acylcarnitines in human urine. For gas chromatography-MS (GC-MS) metabolomics data processing, Kuich et al. introduce Maui-VIA – a GUI-based tool that streamlines the visual curation of peak identifications and quantifications. Also for GC-MS, Franceschi et al. describe MetaDB, a web application providing an user-friendly web interface and laboratory information system (LIMS)-like handling of workflow metadata to metaMS – their R-based data processing pipeline for untargeted quantitative GC/MS metabolomics. Trutschel et al. demonstrate that the joint analysis of multiple dependent signals from the same metabolite (e.g., multiple fragments) using multivariate statistical tests can provide enhanced statistical power to detect differential metabolite abundance than the typical univariate analysis of single signals. Another exciting area of metabolome informatics and statistics is the development of computational approaches to assist biological interpretation. Sun et al. discuss the potential to derive quantitative information about causality networks responsible for metabolome dynamics from metabolomics data and metabolic models by inverse Jacobian estimation. Kessler et al. demonstrate machine learning-based classification of crops as having been “organically” or “non-organically” grown. Uppal et al. present MetabNet – an R package to detect associations between metabolites of interest and peaks detected in LC-MS experiments for the purposes of detecting likely metabolic pathway connections. Finally, Carroll et al. (2010) presented PhenoMeter – a tool for functionally annotating query metabolic phenotypes by matching them against the MetabolomeExpress phenotypic reference database just as BLAST searches are used to annotate nucleotide or protein sequences (Carroll et al.). With so many metabolomics datasets in the literature and the rate of data generation increasing, the need to systematically index and annotate them has never been more urgent. To this end, Metabolonote3 of Ara et al. takes the innovative approach of using a Wiki style interface to facilitate community-based metadata annotation of metabolomics datasets from the literature, delocalizing the burden of this work. The metadata handling functions of the MetaDB pipeline described by Franceschi et al. also aim to streamline the annotation of datasets while supporting the standard ISA-Tab format for dissemination through the MetaboLights4 data repository (Haug et al., 2012). Metabolome informatics and statistics is incredibly broad and fast moving, and this research topic can therefore offer only a cross-sectional sample of developments at one point in time. The cutting edge developments of the future will be built upon those of the present and in a field as rapidly evolving as metabolomics, it is particularly critical and challenging to ensure one’s own work builds upon and benefits from the efforts of others as much as possible. We hope the reader finds this research topic a useful contemporary reference to the field that informs and inspires exciting future innovations and collaborations that help realize the full potential of metabolomics.

Comparison of two feature selection methods for the separability analysis of intertidal sediments with spectrometric datasets in the German Wadden Sea

The spectral features of intertidal sediments are all influenced by the same biophysical properties, such as water, salinity, grain size or vegetation and therefore they are hard to separate by using only multispectral sensors. This could be shown by a previous study of Jung et al. (2015). A more detailed analysis of their characteristic spectral feature has to be carried out to understand the differences and similarities. Spectrometry data (i.e., hyperspectral sensors), for instance, have the opportunity to measure the reflection of the landscape as a continuous spectral pattern for each pixel of an image built from dozen to hundreds of narrow spectral bands. This reveals a high potential to measure unique spectral responses of different ecological conditions (Hennig et al., 2007).In this context, this study uses spectrometric datasets to distinguish between 14 different sediment classes obtained from a study area in the German Wadden Sea. A new feature selection method is proposed (Jeffries-Matusita distance bases feature selection; JMDFS), which uses the Euclidean distance to eliminate the wavelengths with the most similar reflectance values in an iterative process. Subsequent to each iteration, the separation capability is estimated by the Jeffries-Matusita distance (JMD). Two classes can be separated if the JMD is greater than 1.9 and if less than four wavelengths remain, no separation can be assumed. The results of the JMDFS are compared with a state-of-the-art feature selection method called ReliefF. Both methods showed the ability to improve the separation by achieving overall accuracies greater than 82%. The accuracies are 4%–13% better than the results with all wavelengths applied. The number of remaining wavelengths is very diverse and ranges from 14 to 213 of 703. The advantage of JMDFS compared with ReliefF is clearly the processing time. ReliefF needs 30min for one temporary result. It is necessary to repeat the process several times and to average all temporary results to achieve a final result. In this study 50 iterations were carried out, which makes four days of processing. In contrast, JMDFS needs only 30min for a final result.

Modeling of Magnetite Nanoparticles Behavior under Conditions of Microcirculation and Analysis of In Vivo Toxicity.

The behavior of magnetite nanoparticles was studied in the cell chip microcapillaries. No aggregation of magnetite nanoparticles under conditions of long-term circulation was noted. Biodistribution and toxicity of magnetite nanoparticles (14 nm) and aminated magnetite after their intragastric administration to mice were studied in vivo. According to mass spectrometry and microscopy data, accumulation of nanoparticles occurred mainly in the liver cells.

Glyco-centric lectin magnetic bead array (LeMBA) - proteomics dataset of human serum samples from healthy, Barrett׳s esophagus and esophageal adenocarcinoma individuals.

This data article describes serum glycoprotein biomarker discovery and qualification datasets generated using lectin magnetic bead array (LeMBA) – mass spectrometry techniques, “Serum glycoprotein biomarker discovery and qualification pipeline reveals novel diagnostic biomarker candidates for esophageal adenocarcinoma” [1]. Serum samples collected from healthy, metaplastic Barrett׳s esophagus (BE) and esophageal adenocarcinoma (EAC) individuals were profiled for glycoprotein subsets via differential lectin binding. The biomarker discovery proteomics dataset consisting of 20 individual lectin pull-downs for 29 serum samples with a spiked-in internal standard chicken ovalbumin protein has been deposited in the PRIDE partner repository of the ProteomeXchange Consortium with the data set identifier PRIDE: PXD002442. Annotated MS/MS spectra for the peptide identifications can be viewed using MS-Viewer (〈http://prospector2.ucsf.edu/prospector/cgi-bin/msform.cgi?form=msviewer〉) using search key “jn7qafftux”. The qualification dataset contained 6-lectin pulldown-coupled multiple reaction monitoring-mass spectrometry (MRM-MS) data for 41 protein candidates, from 60 serum samples. This dataset is available as a supplemental files with the original publication [1].

APT mass spectrometry and SEM data for CdTe solar cells.

Atom probe tomography (APT) data acquired from a CAMECA LEAP 4000 XHR for the CdS/CdTe interface for a non-CdCl2 treated CdTe solar cell as well as the mass spectrum of an APT data set including a GB in a CdCl2-treated CdTe solar cell are presented. Scanning electron microscopy (SEM) data showing the evolution of sample preparation for APT and scanning transmission electron microscopy (STEM) electron beam induced current (EBIC) are also presented. These data show mass spectrometry peak decomposition of Cu and Te within an APT dataset, the CdS/CdTe interface of an untreated CdTe solar cell, preparation of APT needles from the CdS/CdTe interface in superstrate grown CdTe solar cells, and the preparation of a cross-sectional STEM EBIC sample.

Validation, optimisation, and application data in support of the development of a targeted selected ion monitoring assay for degraded cardiac troponin T.

Cardiac troponin T (cTnT) fragmentation in human serum was investigated using a newly developed targeted selected ion monitoring assay, as described in the accompanying article: “Development of a targeted selected ion monitoring assay for the elucidation of protease induced structural changes in cardiac troponin T” [1]. This article presents data describing aspects of the validation and optimisation of this assay. The data consists of several figures, an excel file containing the results of a sequence identity search, and a description of the raw mass spectrometry (MS) data files, deposited in the ProteomeXchange repository with id PRIDE: PXD003187.

LC–MS/MS and NMR characterization of forced degradation products of mirabegron

ABSTRACTA rapid, precise, and reliable liquid chromatography tandem mass spectrometry (LC–MS/MS) method has been developed for the characterization of stressed degradation products of mirabegron. It is used in the treatment of overactive bladder and administered to treat urinary symptoms such as urgency or frequency and incontinence. It also works by relaxing the muscles around bladder.Mirabegron was subjected to hydrolysis (acidic, alkaline, and neutral) and peroxidation, as per ICH-specified conditions. The drug showed degradation under stress conditions. However, it was stable to neutral conditions. A total of seven degradation products were observed and the chromatographic separation of the drug and its degradation products was achieved on X-TerraRP-8 (250 mm × 4.6 mm, i.d., 5 µm) column using 0.01 M ammonium acetate as mobile phase-A and 60:40 ratio of acetonitrile (ACN):water as mobile phase-B. The degradation products were characterized by LC–MS/MS and its fragmentation pathways were proposed. Probable possible structures were drawn based on parent and daughter molecular ions. One peroxide degradant impurity was isolated using preparative LC and characterized using liquid chromatography–mass spectrometry and NMR data.

Formation of 6-aryl-2-methyl-4-oxo-N,N’-diphenyl-2-cyclohexene-1,3-dicarboxamides from acetoacetanilide and aromatic aldehydes catalyzed by a mixture of aryl amines and iodine

Reactions of acetoacetanilide with aromatic aldehydes in ethanol at room temperature in the presence of molecular iodine and arylamine afford to 6-aryl-2-methyl-4-oxo-N,N’-diphenyl-2-cyclohexene-1,3-dicarboxamides. The structure of obtained compounds was confirmed by mass spectrometry, IR and NMR spectroscopy data.

Enhancing Throughput of Glutathione Adduct Formation Studies and Structural Identification Using a Software-Assisted Workflow Based on High-Resolution Mass Spectrometry (HRMS) Data

Enhancing Throughput of Glutathione Adduct Formation Studies and Structural Identification Using a Software-Assisted Workflow Based on High-Resolution Mass Spectrometry (HRMS) Data

Abstract 203: Visualization of drug delivery by using high resolution microscopic mass spectrometry

Abstract Pharmacokinetic (PK) and pharmacodynamic (PD) studies are important to evaluate the efficacy and toxicity of the drugs. In these analyses, tissue homogenates are generally used for the quantification by high-performance liquid chromatography (HPLC) or liquid chromatography mass spectrometry (LC-MS). However, they lack the information regarding the drug distribution in a specific anatomical area. The information of the drug distribution allows us to optimize the drug design enabling more efficient targeted delivery. We studied the tissue distribution of paclitaxel (PTX) and its micellar formulation (NK105) using a microscopic mass spectroscopy (MMS). A MMS in which a microscope is coupled with an atmospheric pressure matrix-assisted laser desorption/ionization (MALDI) and quadruple ion trap time-of-flight (TOF) analyser was used. The matrix-coated drug sample is ionised and then separated on the basis of its mass-to-charge ratio (m/z). Images were acquired from imaging mass spectrometry (IMS) or tandem mass spectrometry (MS/MS) data. (1) We established the drug imaging system with enhanced resolution and sensitivity. In the analysis, MS and MS/MS were used for quantification and validation, respectively. (2) NK105 showed much stronger antitumor effects on a human pancreatic cancer BxPC3 xenograft than PTX. In the drug imaging, we demonstrated that NK105 delivered more PTX to the whole tumor tissue (including the center lesion). In the mouse model, PTX caused the peripheral neurotoxicity but NK105 did not. Multiple high drug-signal areas surrounding and inside the caudal nerve were observed in the case of PTX, whereas the signals after NK105 injection were significantly low. We succeeded in visualising the EPR (Enhanced Permeability and Retention) effect using MMS. The data obtained by the drug imaging may be useful for facilitating DDS-drug design. The significance of microscopic mass spectrometry with high resolution in the visualisation of drug distribution. Sci Rep. 3:3050. 2013. Citation Format: Masahiro Yasunaga, Masaru Furuta, Koretsugu Ogata, Yoshikatsu Koga, Yasuhiro Matsumura. Visualization of drug delivery by using high resolution microscopic mass spectrometry. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 203. doi:10.1158/1538-7445.AM2015-203

Abstract 1647: Novel transcriptional inhibitors for the inhibition of melanoma growth

Abstract Melanoma is one the most commonly diagnosed cancers in Australia and while treatment is generally successful if the tumor is identified early, once the disease begins to spread the prognosis is considerably worse. The recent approval of new targeted therapies (Vemurafenib, Dabrafenib and Trametinib) has improved progression-free survival for patients carrying the common V600- B-Raf mutations. However even when these inhibitors are used in combination many tumors still develop resistance and furthermore there is a lack of treatment options available for patients who do not carry the mutated form of B-Raf. Therefore there is a pressing need for new therapeutics to address this deficit. The AP-1 transcription factor family has been shown to play an important role in numerous aspects of melanoma tumorgenesis including cellular proliferation and survival, making these transcription factors attractive targets for new treatments. Therefore, a high throughput screening was performed on several libraries of chemical compounds to identify those capable of inhibiting AP-1 directed transcription in vitro. Two lead compounds (X and BT2) were identified for further testing. From these a number of analogues were produced to modify their activity. Those that showed the most improvement above the leads against several melanoma lines were selected for further testing. The in vitro activity of these compounds was characterised in detail against two human melanoma cell lines, one wild type for B-Raf and one carrying the common V600E mutation. In 2D culture both compounds inhibit melanoma cell proliferation; induce apoptosis and cell cycle arrest and inhibit clonogenic capacity. These compounds have little cytotoxicity (LDH) and retain their activity for at least a month under a variety of environmental conditions. Furthermore in 3D spheroid assays the compounds show similar levels of activity. In vivo proof-of-concept testing is underway to assess the compounds activity in immunocompetent (xenograft) and immunocompromised (allograft) model. In parallel, bioinformatics analysis of mass spectrometry, kinome and microarray data is underway to identify the exact mechanism of action and the specificity of these inhibitors. In summary, the identified compounds show promising anti-melanoma activity in vitro. They inhibit human melanoma growth and clonogenic capacity and induce apoptosis and cell cycle arrest in 2D culture at submicromolar concentrations, comparable to the clinically approved drug Tramatenib. They show little cytotoxicity and also inhibit growth in a 3D spheroid model at submicromolar concentrations. The AP-1 transcription family, in particular c-Jun, have been shown to be important players in the development of melanoma. As such, these compounds may prove to be effective treatments for melanoma irrespective of B-Raf status and warrant further investigation both in vitro and in vivo. Citation Format: Kylie M. Taylor, Ahmad MN Alhendi, Gary Halliday, Lionel Prado-Lourenço. Novel transcriptional inhibitors for the inhibition of melanoma growth. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 1647. doi:10.1158/1538-7445.AM2015-1647

Design and Synthesis of Some Carbamazepine Derivatives Using Several Strategies

In this study, is reported a straightforward route is reported for the synthesis of a series of carbamazepine derivatives using some strategies. The first stage was achieved by the reaction of carbamazepine with thiourea in the presence of pyridine to form the compound 3-(5H-dibenzo[b,f]azepin-5-yl)-2,5-dihydro-1,2,4-thiadiazol-5-amine (3). After 3 was made reacting with chloroacetyl chloride using triethylamine as catalyst to synthesis of a propanamide derivative (4). The following stage a carboxamide derivative (5) was synthesized by the reaction of 4 with benzaldehyde in basic medium. The fourth stage was achieved by the reaction of carbamazepine with ethylenediamine in presence of formaldehyde to form a new carboxamide derivative (7). Then, the compound 7 was made reacting with 2-hydroxy-1-naphthaldehyde using boric acid as catalyst to synthesis of a carbamazepine derivative (8). Finally, 8 was made reacting with 3,5- dintrobenzoic acid in the presence of dimetyhyl sulfoxide at mild conditions to form a new carbamazepine derivative 9. The structure of the compounds obtained was confirmed by elemental analysis, spectroscopy and spectrometry data. The proposed method offers some advantages such as simple procedure, low cost, and ease of workup. Keywords: Carbamazepine, synthesis, thiourea, boric acid.

PP.LB03.03

Objective:To study association of haemodynamic rates with laser correlation spectrometry (LCS) data in prescription of two treatment regimens (TR) in elderly with primary hypertension combined with coronary artery disease (CAD).Design and method:80 patients with abovementioned pathology were examine

Simulation of P-Type Doping Profile Prediction Using Different Ion Implantation and Diffusion Model

Ion implantation and subsequent diffusion are very essential stages in today's advanced VLSI (Very Large Scale Integration) semiconductor devices processing. High precision calibration of device simulation is a key procedure to ensure simulation is accurate. For this purpose, accurate prediction of the doping profiles resulted from ion implantation and diffusion will be studied using a few models of ion implantation and diffusion. We collected data of Boron as P-type ion implantation profiles using TCAD simulation software with different ion implantation models and diffusion models then compared with Secondary Ion Mass Spectrometry (SIMS) data of ion implantation profile database as experimental data. Models plays very important role in this calibration. In this paper, calibrations have done using Monte Carlo and Taurus analytical as implantation model and pd.full, pd.fermi and pd.5stream as diffusion model. All calibration simulations were simulated using Synopsys TCAD Simulation. The experimental results shown by using Monte Carlo ion implantation model with pd.5str diffusion model is close to SIMS profile.

Identification of Protein Complexes from Tandem Affinity Purification/Mass Spectrometry Data via Biased Random Walk.

Systematic identification of protein complexes from protein-protein interaction networks (PPIs) is an important application of data mining in life science. Over the past decades, various new clustering techniques have been developed based on modelling PPIs as binary relations. Non-binary information of co-complex relations (prey/bait) in PPIs data derived from tandem affinity purification/mass spectrometry (TAP-MS) experiments has been unfairly disregarded. In this paper, we propose a Biased Random Walk based algorithm for detecting protein complexes from TAP-MS data, resulting in the random walk with restarting baits (RWRB). RWRB is developed based on Random walk with restart. The main contribution of RWRB is the incorporation of co-complex relations in TAP-MS PPI networks into the clustering process, by implementing a new restarting strategy during the process of random walk. Through experimentation on un-weighted and weighted TAP-MS data sets, we validated biological significance of our results by mapping them to manually curated complexes. Results showed that, by incorporating non-binary, co-membership information, significant improvement has been achieved in terms of both statistical measurements and biological relevance. Better accuracy demonstrates that the proposed method outperformed several state-of-the-art clustering algorithms for the detection of protein complexes in TAP-MS data.

Antimicrobial Activity of Fungi Strains of Trichoderma from Middle Siberia

The antibiotic activity in 42 strains of 8 species of the Trichoderma genus (T. asperellum, T. viride, T. hamatum, T. koningii, T. atroviride, T. harzianum, T. Citrinoviride, and T. longibrachiatum) isolated from different Siberian ecotops was studied. It was shown that these species differ in the degree of their antibacterial and antifungal activity. The chosen strain, T. citrinoviride TV4-1, exhibited high activity and a wide range of actions against the opportunistic and pathogenic fungi of the Aspergillus and Candida albicans genus; bacteria, including methicillin-resistant Staphylococcus aureus; and cancer cells. According to mass and I R spectrometry data and the spectrum of biological action, peptaibols are probably the most active compounds in the strain culture extracts.

Meroterpenoid Hydroquinones fromCordia globosa

Two new meroterpenoid hydroquinones,rel-(4bE,6Z,8E,9aS,10S)-1,4-dihydroxy-9a,10-dihydro-10,12-epoxy-5-methylbenzo[a]azulen-12-one andrel-(4bZ,6Z,8E,9aS,10S)-1-hydroxy-9a,10-dihydro-4,11:10,12-diepoxy-benzo[a]azulen-11,12-dione, along with the known peptide derivative (S)-N-benzoylphenylalanine-(S)-2-benzamide-3-phenylpropyl ester, were isolated from the roots of Cordia globosa. Their structures were determined by 1D and 2D nuclear magnetic resonance (NMR) spectrometry, Fourier transform infrared (FTIR) spectroscopy and high resolution atmospheric pressure chemical ionization mass spectrometry (HRAPCIMS) data analysis. The new compounds were tested against three human cancer cell lines (colon adenocarcinoma, ovarian carcinoma and glioblastoma), but none of them exhibited any activity.

Increased acute immune response during the meningo-encephalitic stage of Trypanosoma brucei rhodesiense sleeping sickness compared to Trypanosoma brucei gambiense

The host central nervous system (CNS) response to infection with Trypanosoma brucei (T. b.) gambiense or T. b. rhodesiense parasites, the causing agent of human African trypanosomiasis (HAT), is a poorly explored area. The two parasites are responsible for respectively a chronic and an acute form of HAT. In both cases, however, the disease progresses from a haemolymphatic first stage (S1) to a meningo-encephalitic second stage (S2) due to the penetration of parasites into the CNS.In the present study, we investigated and compared the cerebrospinal fluid (CSF) from S2 patients affected by either T. b. gambiense or T. b. rhodesiense HAT, using a mass spectrometry quantitative proteomics approach. Gene ontology and pathway analyses on the 222 quantified human proteins revealed a predominant activation of the innate immune and the acute phase responses in rhodesiense HAT patients. These results were further confirmed through the verification of the over-expression of two proteins involved in these mechanisms, C-reactive protein (CRP) and orosomucoid 1 (ORM1), in 126 S2 HAT patients suffering from either the chronic or the acute form of HAT. Both proteins were significantly increased (p<0.0001) in the CSF of rhodesiense HAT patients.These findings contribute in better understanding the pathophysiological mechanisms of late stage HAT caused by T. b. gambiense or T. b. rhodesiense and pave the way for further investigations on the clinical significance of CRP and ORM1.Mass spectrometry data are available via ProteomeXchange (identifier PXD001082).