Rescue of myocytes and locomotion through AAV2/9-2YF intracisternal gene therapy in a rat model of creatine transporter deficiency.

Creatine deficiency syndromes (CDS), caused by mutations in GATM (AGAT), GAMT, and SLC6A8, mainly affect the central nervous system (CNS). CDS show brain creatine (Cr) deficiency, intellectual disability with severe speech delay, behavioral troubles, epilepsy, and motor dysfunction. AGAT/GAMT-deficient patients lack brain Cr synthesis but express the Cr transporter SLC6A8 at the blood-brain barrier and are thus treatable by oral supplementation of Cr. In contrast, no satisfactory treatment has been identified for Cr transporter deficiency (CTD), the most frequent of CDS. We used our Slc6a8Y389C CTD rat model to develop a new AAV2/9-2YF-driven gene therapy re-establishing the functional Slc6a8 transporter in rat CNS. We show, after intra-cisterna magna AAV2/9-2YF-Slc6a8-FLAG vector injection of postnatal day 11 pups, the transduction of Slc6a8-FLAG in cerebellum, medulla oblongata, and spinal cord as well as a partial recovery of Cr in these brain regions, together with full prevention of locomotion defaults and impairment of myocyte development observed in Slc6a8Y389 C/y male rats. While more work is needed to correct those CTD phenotypes more associated with forebrain structures, this study is the first demonstrating positive effects of an AAV-driven gene therapy on CTD and thus represents a very encouraging approach to treat the so-far untreatable CTD.

Report from the HarmoSter study: impact of calibration on comparability of LC-MS/MS measurement of circulating cortisol, 17OH-progesterone and aldosterone.

OBJECTIVES: Liquid chromatography-tandem mass spectrometry (LC-MS/MS) is recommended for measuring circulating steroids. However, assays display technical heterogeneity. So far, reproducibility of corticosteroid LC-MS/MS measurements has received scant attention. The aim of the study was to compare LC-MS/MS measurements of cortisol, 17OH-progesterone and aldosterone from nine European centers and assess performance according to external quality assessment (EQA) materials and calibration. METHODS: Seventy-eight patient samples, EQA materials and two commercial calibration sets were measured twice by laboratory-specific procedures. Results were obtained by in-house (CAL1) and external calibrations (CAL2 and CAL3). We evaluated intra and inter-laboratory imprecision, correlation and agreement in patient samples, and trueness, bias and commutability in EQA materials. RESULTS: Using CAL1, intra-laboratory CVs ranged between 2.8-7.4%, 4.4-18.0% and 5.2-22.2%, for cortisol, 17OH-progesterone and aldosterone, respectively. Trueness and bias in EQA materials were mostly acceptable, however, inappropriate commutability and target value assignment were highlighted in some cases. CAL2 showed suboptimal accuracy. Median inter-laboratory CVs for cortisol, 17OH-progesterone and aldosterone were 4.9, 11.8 and 13.8% with CAL1 and 3.6, 10.3 and 8.6% with CAL3 (all p<0.001), respectively. Using CAL1, median bias vs. all laboratory-medians ranged from -6.6 to 6.9%, -17.2 to 7.8% and -12.0 to 16.8% for cortisol, 17OH-progesterone and aldosterone, respectively. Regression lines significantly deviated from the best fit for most laboratories. Using CAL3 improved cortisol and 17OH-progesterone between-method bias and correlation. CONCLUSIONS: Intra-laboratory imprecision and performance with EQA materials were variable. Inter-laboratory performance was mostly within specifications. Although residual variability persists, adopting common traceable calibrators and RMP-determined EQA materials is beneficial for standardization of LC-MS/MS steroid measurements.

Exudative glutamine losses contribute to high needs after burn injury.

BACKGROUND: Burnpatients characteristically have increased energy, glucose, and protein requirements. Glutamine supplementation is strongly recommended during early-phase treatment and is associated with improved immunity, wound healing, and reduced mortality. This study evaluated if early burn exudative losses might contribute to higher supplementation needs. METHODS: Patients admitted to the burn intensive care unit (ICU) had exudate collection from tight bandages applied to arms or legs during the first week (exudate aliquot twice daily). Seven amino acids (alanine, arginine, cystEine, glutamine, leucine, lysine, and methionine) were quantified by liquid chromatography-mass spectrometry. Descriptive analysis of all results is provided as median and interquartile range or in value ranges. RESULTS: Eleven patients aged 19-77 years, presenting with burns on 18%-70% of the body surface, with a median simplified acute physiology score II of 33 (range, 16-56) were included during the study period. The highest amino acid losses were observed during the first 3 days with an important interpatient and intrapatient variability. Glutamine and alanine losses were highest, followed by leucine and lysine in all patients; amino acid exudate concentrations were in the range of normal plasma concentrations and were stable over time. Total glutamine losses were correlated to the burned surface (r2 = 0.552, P = .012), but not to enteral glutamine supplements. CONCLUSIONS: The study shows significant exudative losses during early-stage burn recovery and particularly for glutamine and alanine. Glutamine loss generally decreased with wound closure, the subsequent decline of exudation, and the evolving size of burn surfaces.

MSight: an image analysis software for liquid chromatography-mass spectrometry.

Images obtained from high-throughput mass spectrometry (MS) contain information that remains hidden when looking at a single spectrum at a time. Image processing of liquid chromatography-MS datasets can be extremely useful for quality control, experimental monitoring and knowledge extraction. The importance of imaging in differential analysis of proteomic experiments has already been established through two-dimensional gels and can now be foreseen with MS images. We present MSight, a new software designed to construct and manipulate MS images, as well as to facilitate their analysis and comparison.

Peptide mass fingerprinting peak intensity prediction: extracting knowledge from spectra.

Matrix-assisted laser desorption/ionization-time of flight mass spectrometry has become a valuable tool in proteomics. With the increasing acquisition rate of mass spectrometers, one of the major issues is the development of accurate, efficient and automatic peptide mass fingerprinting (PMF) identification tools. Current tools are mostly based on counting the number of experimental peptide masses matching with theoretical masses. Almost all of them use additional criteria such as isoelectric point, molecular weight, PTMs, taxonomy or enzymatic cleavage rules to enhance prediction performance. However, these identification tools seldom use peak intensities as parameter as there is currently no model predicting the intensities based on the physicochemical properties of peptides. In this work, we used standard datamining methods such as classification and regression methods to find correlations between peak intensities and the properties of the peptides composing a PMF spectrum. These methods were applied on a dataset comprising a series of PMF experiments involving 157 proteins. We found that the C4.5 method gave the more informative results for the classification task (prediction of the presence or absence of a peptide in a spectra) and M5' for the regression methods (prediction of the normalized intensity of a peptide peak). The C4.5 result correctly classified 88% of the theoretical peaks; whereas the M5' peak intensities had a correlation coefficient of 0.6743 with the experimental peak intensities. These methods enabled us to obtain decision and model trees that can be directly used for prediction and identification of PMF results. The work performed permitted to lay the foundations of a method to analyze factors influencing the peak intensity of PMF spectra. A simple extension of this analysis could lead to improve the accuracy of the results by using a larger dataset. Additional peptide characteristics or even PMF experimental parameters can also be taken into account in the datamining process to analyze their influence on the peak intensity. Furthermore, this datamining approach can certainly be extended to the tandem mass spectrometry domain or other mass spectrometry derived methods.

Molecular scanner experiment with human plasma: improving protein identification by using intensity distributions of matching peptide masses.

The development of high throughput utilities to identify proteins is a major challenge in present research in the field of proteomics. One such utility, the molecular scanner, uses proteins separated by two-dimensional polyacrylamide gel electrophoresis that are digested in the gel and during transfer onto a collecting membrane. After adding a matrix, the membrane is inserted into a matrix-assisted laser desorption/ionization-time of flight mass spectrometer and a peptide mass fingerprint (PMF) is measured for every scanned site. Since the spacing between scanned sites is much smaller than the size of the most abundant protein spots, there is a certain redundancy in the data that was used in an earlier experiment with Escherichia coli [1] to improve mass calibration and PMF identification results. It was observed that the signal intensity of a peptide mass as a function of the position on the membrane showed similar patterns if peptides stemmed from the same protein. Taking account of these similarities a clustering algorithm was used to find lists of experimental masses with similar intensity distributions, which provided clearer identification of the corresponding proteins. Here, these methods are applied to a human plasma scan, where proteins were highly modified and less separated. The presence of very abundant proteins like albumin and immunoglobulins added another difficulty. The calibration of the initial PMFs was not satisfactory and masses had to be recalibrated. After discarding chemical noise, the membrane was partitioned into regions and for each region protein identification was carried out separately. A new scoring method was used, where the PMF score was multiplied by a factor that measures the similarity of matching peptides. This method proved to be more robust than the method developed in [1] if the region where a protein was found had an extended, nonspherical shape and strong overlap with regions of other proteins. Many proteins annotated on the SWISS-2D PAGE human plasma master gel could be clearly identified and many interesting properties were observed.

Challenges in mass spectrometry.

Report of the round table discussionThe reported MS round table took place within the ProteomeValley Technology Fair during the Swiss Proteomics Society 2001 Congress. It was organised by the Swiss Proteomics Society (SPS) in collaboration with FontisMedia (http://www.fontismedia. com). It was scheduled November 22(nd), 2001 from 16:40 to 18:00 at the Geneva University Hospital. The objective of the MS round table was to bring together two kinds of specialists in mass spectrometry: those who develop and commercialise MS equipment and those who use it as a tool in proteomic sciences. Six expert users and six representatives of leading MS instrument companies were thus invited to actively participate in this round table and share their points of view. The main objectives of this round table were not only to share experiences, but also to share dreams regarding MS technology and discuss the actual limits. It also focused on what MS users presently expect from MS producers and what are the current priorities in terms of development, for the benefit of all parties. Although it was one of the final events of the meeting, this MS round table attracted an audience of some fifty participants of the congress who were actively involved in the debate.