Strategy for improved characterization of human metabolic phenotypes using a COmbined Multi-block Principal components Analysis with Statistical Spectroscopy (COMPASS).

MOTIVATION: Large-scale population omics data can provide insight into associations between gene-environment interactions and disease. However, existing dimension reduction modelling techniques are often inefficient for extracting detailed information from these complex datasets. RESULTS: Here, we present an interactive software pipeline for exploratory analyses of population-based nuclear magnetic resonance spectral data using a COmbined Multi-block Principal components Analysis with Statistical Spectroscopy (COMPASS) within the R-library hastaLaVista framework. Principal component analysis models are generated for a sequential series of spectral regions (blocks) to provide more granular detail defining sub-populations within the dataset. Molecular identification of key differentiating signals is subsequently achieved by implementing Statistical TOtal Correlation SpectroscopY on the full spectral data to define feature patterns. Finally, the distributions of cross-correlation of the reference patterns across the spectral dataset are used to provide population statistics for identifying underlying features arising from drug intake, latent diseases and diet. The COMPASS method thus provides an efficient semi-automated approach for screening population datasets. AVAILABILITY AND IMPLEMENTATION: Source code is available at https://github.com/cheminfo/COMPASS. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A Cross-Sectional and Longitudinal Analysis of Pre-Diagnostic Blood Plasma Biomarkers for Early Detection of Pancreatic Cancer.

Pancreatic ductal adenocarcinoma (PDAC) is a major cause of cancer death that typically presents at an advanced stage. No reliable markers for early detection presently exist. The prominent tumor stroma represents a source of circulating biomarkers for use together with cancer cell-derived biomarkers for earlier PDAC diagnosis. CA19-9 and CEA (cancer cell-derived biomarkers), together with endostatin and collagen IV (stroma-derived) were examined alone, or together, by multivariable modelling, using pre-diagnostic plasma samples (n = 259 samples) from the Northern Sweden Health and Disease Study biobank. Serial samples were available for a subgroup of future patients. Marker efficacy for future PDAC case prediction (n = 154 future cases) was examined by both cross-sectional (ROC analysis) and longitudinal analyses. CA19-9 performed well at, and within, six months to diagnosis and multivariable modelling was not superior to CA19-9 alone in cross-sectional analysis. Within six months to diagnosis, CA19-9 (AUC = 0.92) outperformed the multivariable model (AUC = 0.81) at a cross-sectional level. At diagnosis, CA19-9 (AUC = 0.995) and the model (AUC = 0.977) performed similarly. Longitudinal analysis revealed increases in CA19-9 up to two years to diagnosis which indicates a window of opportunity for early detection of PDAC.

Metabolic response patterns in brain microdialysis fluids and serum during interstitial cisplatin treatment of high-grade glioma.

BACKGROUND: High-grade gliomas are associated with poor prognosis. Tumour heterogeneity and invasiveness create challenges for effective treatment and use of systemically administrated drugs. Furthermore, lack of functional predictive response-assays based on drug efficacy complicates evaluation of early treatment responses. METHODS: We used microdialysis to deliver cisplatin into the tumour and to monitor levels of metabolic compounds present in the tumour and non-malignant brain tissue adjacent to tumour, before and during treatment. In parallel, we collected serum samples and used multivariate statistics to analyse the metabolic effects. RESULTS: We found distinct metabolic patterns in the extracellular fluids from tumour compared to non-malignant brain tissue, including high concentrations of a wide range of amino acids, amino acid derivatives and reduced levels of monosaccharides and purine nucleosides. We found that locoregional cisplatin delivery had a strong metabolic effect at the tumour site, resulting in substantial release of glutamic acid, phosphate, and spermidine and a reduction of cysteine levels. In addition, patients with long-time survival displayed different treatment response patterns in both tumour and serum. Longer survival was associated with low tumour levels of lactic acid, glyceric acid, ketoses, creatinine and cysteine. Patients with longer survival displayed lower serum levels of ketohexoses, fatty acid methyl esters, glycerol-3-phosphate and alpha-tocopherol, while elevated phosphate levels were seen in both tumour and serum during treatment. CONCLUSION: We highlight distinct metabolic patterns associated with high-grade tumour metabolism, and responses to cytotoxic cisplatin treatment.

Comprehensive metabolomics analysis of prostate cancer tissue in relation to tumor aggressiveness and TMPRSS2-ERG fusion status.

BACKGROUND: Prostate cancer (PC) can display very heterogeneous phenotypes ranging from indolent asymptomatic to aggressive lethal forms. Understanding how these PC subtypes vary in their striving for energy and anabolic molecules is of fundamental importance for developing more effective therapies and diagnostics. Here, we carried out an extensive analysis of prostate tissue samples to reveal metabolic alterations during PC development and disease progression and furthermore between TMPRSS2-ERG rearrangement-positive and -negative PC subclasses. METHODS: Comprehensive metabolomics analysis of prostate tissue samples was performed by non-destructive high-resolution magic angle spinning nuclear magnetic resonance (1H HR MAS NMR). Subsequently, samples underwent moderate extraction, leaving tissue morphology intact for histopathological characterization. Metabolites in tissue extracts were identified by 1H/31P NMR and liquid chromatography-mass spectrometry (LC-MS). These metabolomics profiles were analyzed by chemometric tools and the outcome was further validated using proteomic data from a separate sample cohort. RESULTS: The obtained metabolite patterns significantly differed between PC and benign tissue and between samples with high and low Gleason score (GS). Five key metabolites (phosphocholine, glutamate, hypoxanthine, arginine and α-glucose) were identified, who were sufficient to differentiate between cancer and benign tissue and between high to low GS. In ERG-positive PC, the analysis revealed several acylcarnitines among the increased metabolites together with decreased levels of proteins involved in ß-oxidation; indicating decreased acyl-CoAs oxidation in ERG-positive tumors. The ERG-positive group also showed increased levels of metabolites and proteins involved in purine catabolism; a potential sign of increased DNA damage and oxidative stress. CONCLUSIONS: Our comprehensive metabolomic analysis strongly indicates that ERG-positive PC and ERG-negative PC should be considered as different subtypes of PC; a fact requiring different, sub-type specific treatment strategies for affected patients.

Plasma Micro-RNA Alterations Appear Late in Pancreatic Cancer.

OBJECTIVES: The aim of this research was to study whether plasma microRNAs (miRNA) can be used for early detection of pancreatic cancer (PC) by analyzing prediagnostic plasma samples collected before a PC diagnosis. BACKGROUND: PC has a poor prognosis due to late presenting symptoms and early metastasis. Circulating miRNAs are altered in PC at diagnosis but have not been evaluated in a prediagnostic setting. METHODS: We first performed an initial screen using a panel of 372 miRNAs in a retrospective case-control cohort that included early-stage PC patients and healthy controls. Significantly altered miRNAs at diagnosis were then measured in an early detection case-control cohort wherein plasma samples in the cases are collected before a PC diagnosis. Carbohydrate antigen 19-9 (Ca 19-9) levels were measured in all samples for comparison. RESULTS: Our initial screen, including 23 stage I-II PC cases and 22 controls, revealed 15 candidate miRNAs that were differentially expressed in plasma samples at PC diagnosis. We combined all 15 miRNAs into a multivariate statistical model, which outperformed Ca 19-9 in receiver-operating characteristics analysis. However, none of the candidate miRNAs, individually or in combination, were significantly altered in prediagnostic plasma samples from 67 future PC patients compared with 132 matched controls. In comparison, Ca 19-9 levels were significantly higher in the cases at <5 years before diagnosis. CONCLUSION: Plasma miRNAs are altered in PC patients at diagnosis, but the candidate miRNAs found in this study appear late in the course of the disease and cannot be used for early detection of the disease.

Metabolomic profiling identifies distinct phenotypes for ASS1 positive and negative GBM.

BACKGROUND: Tumour cells have a high demand for arginine. However, a subset of glioblastomas has a defect in the arginine biosynthetic pathway due to epigenetic silencing of the rate limiting enzyme argininosuccinate synthetase (ASS1). These tumours are auxotrophic for arginine and susceptible to the arginine degrading enzyme, pegylated arginine deiminase (ADI-PEG20). Moreover, ASS1 deficient GBM have a worse prognosis compared to ASS1 positive tumours. Since altered tumour metabolism is one of the hallmarks of cancer we were interested to determine if these two subtypes exhibited different metabolic profiles that could allow for their non-invasive detection as well as unveil additional novel therapeutic opportunities. METHODS: We looked for basal metabolic differences using one and two-dimensional gas chromatography-time-of-flight mass spectrometry (1D/2D GC-TOFMS) followed by targeted analysis of 29 amino acids using liquid chromatography-time-of-flight mass spectrometry (LC-TOFMS). We also looked for differences upon arginine deprivation in a single ASS1 negative and positive cell line (SNB19 and U87 respectively). The acquired data was evaluated by chemometric based bioinformatic methods. RESULTS: Orthogonal partial least squares-discriminant analysis (OPLS-DA) of both the 1D and 2D GC-TOFMS data revealed significant systematic difference in metabolites between the two subgroups with ASS1 positive cells generally exhibiting an overall elevation of identified metabolites, including those involved in the arginine biosynthetic pathway. Pathway and network analysis of the metabolite profile show that ASS1 negative cells have altered arginine and citrulline metabolism as well as altered amino acid metabolism. As expected, we observed significant metabolite perturbations in ASS negative cells in response to ADI-PEG20 treatment. CONCLUSIONS: This study has highlighted significant differences in the metabolome of ASS1 negative and positive GBM which warrants further study to determine their diagnostic and therapeutic potential for the treatment of this devastating disease.

Correction to: Metabolomic profiling identifies distinct phenotypes for ASS1 positive and negative GBM.

In the original publication of this article [1], published on 8 February 2018, it was noticed that the acknowledgement of the source of the drug ADI-PEG20 was missing.

Gene expression and fiber type variations in repeated vastus lateralis biopsies.

INTRODUCTION: Muscle sample collection can introduce variation in any measured variable due to inter- and intramuscle variation. We investigated the variation in gene expression and fiber type composition after repeated biopsy sampling from the vastus lateralis muscle. METHODS: Six subjects donated 3 tissue samples each. One hour after baseline sampling from 1 vastus lateralis muscle, samples from both vastus lateralis muscles were obtained. RESULTS: The fiber type composition differed between biopsies taken from the same leg. There were no within-subject differences in gene expression between the 3 biopsies. Multivariate analysis supports a model in which gene expression differs significantly between individuals but is not affected by repeated muscle biopsy sampling from the same subject. CONCLUSION: One vastus lateralis muscle sample per subject is sufficient to establish a reliable baseline for comparing gene expression representing selected pathways over time within the same individual.

Blood Metabolomic Predictors of 1-Year Outcome in Subarachnoid Hemorrhage.

BACKGROUND: Delayed neurological deficit (DND) is the most important cause of morbidity and mortality in patients with subarachnoid hemorrhage (SAH) whose aneurysms have been secured. However, the methods currently used to predict the development of DND, such as trans-cranial Doppler or levels biochemical markers in blood and cerebrospinal fluid are not very accurate. METHOD: Venous blood was drawn from 50 patients with SAH, admitted to the neurosurgical department Umeå University Hospital, at day 1-3 and day 7 after the bleed. The clinical status of the patients was followed up approximately 1 year after this episode and classified according to the Glasgow Outcome Score (GOS). RESULTS: Results showed considerable differences in blood metabolomic patterns between day 1-3 and 7 after the hemorrhage. Fifty-six out of 98 metabolites could be identified from our in-house library and 17 of these metabolites changed significantly from day 1-3 to 7 after the bleed. One of these, myo-inositol, was predictive of clinical outcome even after correction for multiple testing. An estimation of the diagnostic accuracy of high levels of this substance in predicting good outcome (GOS 4-5) yielded a sensitivity of .763 and a specificity of .5 at the optimal cut off point. CONCLUSIONS: SAH is an event with a profound effect on blood metabolomics profiles. Myo-inositol might be an interesting compound for future study to focus on in the search for metabolic markers in venous blood of delayed neurological deterioration in SAH patients.

Metabolomic analysis of extreme freezing tolerance in Siberian spruce (Picea obovata).

Siberian spruce (Picea obovata) is one of several boreal conifer species that can survive at extremely low temperatures (ELTs). When fully acclimated, its tissues can survive immersion in liquid nitrogen. Relatively little is known about the biochemical and biophysical strategies of ELT survival. We profiled needle metabolites using gas chromatography coupled with mass spectrometry (GC-MS) to explore the metabolic changes that occur during cold acclimation caused by natural temperature fluctuations. In total, 223 metabolites accumulated and 52 were depleted in fully acclimated needles compared with pre-acclimation needles. The metabolite profiles were found to develop in four distinct phases, which are referred to as pre-acclimation, early acclimation, late acclimation and fully acclimated. Metabolite changes associated with carbohydrate and lipid metabolism were observed, including changes associated with increased raffinose family oligosaccharide synthesis and accumulation, accumulation of sugar acids and sugar alcohols, desaturation of fatty acids, and accumulation of digalactosylglycerol. We also observed the accumulation of protein and nonprotein amino acids and polyamines that may act as compatible solutes or cryoprotectants. These results provide new insight into the mechanisms of freezing tolerance development at the metabolite level and highlight their importance in rapid acclimation to ELT in P. obovata.

Impact of probiotic feeding during weaning on the serum lipid profile and plasma metabolome in infants.

The gut microbiome interacts with the host in the metabolic response to diet, and early microbial aberrancies may be linked to the development of obesity and metabolic disorders later in life. Probiotics have been proposed to affect metabolic programming and blood lipid levels, although studies are lacking in infants. Here, we report on the lipid profile and global metabolic response following daily feeding of probiotics during weaning. A total of 179 healthy, term infants were randomised to daily intake of cereals with (n 89) or without (n 90) the addition of Lactobacillus paracasei ssp. paracasei F19 (LF19) 108 colony-forming units per serving from 4 to 13 months of age. Weight, length and skinfold thickness were monitored. Venous blood was drawn at 5·5 and 13 months of age for analysis of the serum lipid profile. In a subsample, randomly selected from each group, GC-time-of-flight/MS was used to metabolically characterise plasma samples from thirty-seven infants. A combination of multi- and univariate analysis was applied to reveal differences related to LF19 treatment based on 228 putative metabolites, of which ninety-nine were identified or classified. We observed no effects of probiotic feeding on anthropometrics or the serum lipid profile. However, we detected significantly lower levels of palmitoleic acid (16 : 1) (P< 0·05) and significantly higher levels of putrescine (P< 0·01) in LF19-treated infants. Palmitoleic acid is a major MUFA strongly linked to visceral obesity, while putrescine is a polyamine with importance for gut integrity. Whether the observed differences will have long-term health consequences are being followed.

Altered plasma metabolite levels can be detected years before a glioma diagnosis.

Genetic and metabolic changes in tissue and blood are reported to occur several years before glioma diagnosis. Since gliomas are currently detected late, a liquid biopsy for early detection could affect the quality of life and prognosis of patients. Here, we present a nested case-control study of 550 prediagnostic glioma cases and 550 healthy controls from the Northern Sweden Health and Disease study (NSHDS) and the European Prospective Investigation into Cancer and Nutrition (EPIC) study. We identified 93 significantly altered metabolites related to glioma development up to 8 years before diagnosis. Out of these metabolites, a panel of 20 selected metabolites showed strong disease correlation and a consistent progression pattern toward diagnosis in both the NSHDS and EPIC cohorts, and they separated future cases from controls independently of biological sex. The blood metabolite panel also successfully separated both lower-grade glioma and glioblastoma cases from controls, up to 8 years before diagnosis in patients within the NSHDS cohort and up to 2 years before diagnosis in EPIC. Pathway enrichment analysis detected metabolites related to the TCA cycle, Warburg effect, gluconeogenesis, and cysteine, pyruvate, and tyrosine metabolism as the most affected.

ALS patients with mutations in the SOD1 gene have an unique metabolomic profile in the cerebrospinal fluid compared with ALS patients without mutations.

A specific biochemical marker for early diagnosing and for monitoring disease progression in amyotrophic lateral sclerosis (ALS) will have important clinical applications. ALS is a heterogeneous syndrome with multiple subtypes with ill-defined borders. A minority of patients carries mutations in the Cu/Zn-superoxide dismutase (SOD1) gene but the disease mechanism remains unknown for all types of ALS. Using a GC-TOFMS platform we studied the cerebrospinal fluid (CSF) metabolome in 16 ALS patients with six different mutations in the SOD1 gene and compared with ALS-patients without such mutations. OPLS-DA was used for classification modeling. We find that patients with a SOD1 mutation have a distinct metabolic profile in the CSF. In particular, the eight patients homozygous for the D90A SOD1 mutation showed a distinctively different signature when modeled against ALS patients with other SOD1 mutations and sporadic and familial ALS patients without a SOD1 gene mutation. This was found irrespective of medication with riluzole and survival time. Among the metabolites that contributed most to the CSF signature were arginine, lysine, ornithine, serine, threonine and pyroglutamic acid, all found to be reduced in patients carrying a D90A SOD1 mutation. ALS-patients with a SOD1 gene mutation appear as a distinct metabolic entity in the CSF, in particular in patients with the D90A mutation, the most frequently identified cause of ALS. The findings suggest that metabolomic profiling using GC-TOFMS and multivariate data analysis may be a future tool for diagnosing and monitoring disease progression, and may cast light on the disease mechanisms in ALS.

Pharmaco-metabonomic phenotyping and personalized drug treatment.

There is a clear case for drug treatments to be selected according to the characteristics of an individual patient, in order to improve efficacy and reduce the number and severity of adverse drug reactions. However, such personalization of drug treatments requires the ability to predict how different individuals will respond to a particular drug/dose combination. After initial optimism, there is increasing recognition of the limitations of the pharmacogenomic approach, which does not take account of important environmental influences on drug absorption, distribution, metabolism and excretion. For instance, a major factor underlying inter-individual variation in drug effects is variation in metabolic phenotype, which is influenced not only by genotype but also by environmental factors such as nutritional status, the gut microbiota, age, disease and the co- or pre-administration of other drugs. Thus, although genetic variation is clearly important, it seems unlikely that personalized drug therapy will be enabled for a wide range of major diseases using genomic knowledge alone. Here we describe an alternative and conceptually new 'pharmaco-metabonomic' approach to personalizing drug treatment, which uses a combination of pre-dose metabolite profiling and chemometrics to model and predict the responses of individual subjects. We provide proof-of-principle for this new approach, which is sensitive to both genetic and environmental influences, with a study of paracetamol (acetaminophen) administered to rats. We show pre-dose prediction of an aspect of the urinary drug metabolite profile and an association between pre-dose urinary composition and the extent of liver damage sustained after paracetamol administration.

Distinct metabolic hallmarks of WHO classified adult glioma subtypes.

BACKGROUND: Gliomas are complex tumors with several genetic aberrations and diverse metabolic programs contributing to their aggressive phenotypes and poor prognoses. This study defines key metabolic features that can be used to differentiate between glioma subtypes, with potential for improved diagnostics and subtype targeted therapy. METHODS: Cross-platform global metabolomic profiling coupled with clinical, genetic, and pathological analysis of glioma tissue from 224 tumors-oligodendroglioma (n = 31), astrocytoma (n = 31) and glioblastoma (n = 162)-were performed. Identified metabolic phenotypes were evaluated in accordance with the WHO classification, IDH-mutation, 1p/19q-codeletion, WHO-grading 2-4, and MGMT promoter methylation. RESULTS: Distinct metabolic phenotypes separate all six analyzed glioma subtypes. IDH-mutated subtypes, expressing 2-hydroxyglutaric acid, were clearly distinguished from IDH-wildtype subtypes. Considerable metabolic heterogeneity outside of the mutated IDH pathway were also evident, with key metabolites being high expression of glycerophosphates, inositols, monosaccharides, and sugar alcohols and low levels of sphingosine and lysoglycerophospholipids in IDH-mutants. Among the IDH-mutated subtypes, we observed high levels of amino acids, especially glycine and 2-aminoadipic acid, in grade 4 glioma, and N-acetyl aspartic acid in low-grade astrocytoma and oligodendroglioma. Both IDH-wildtype and mutated oligodendroglioma and glioblastoma were characterized by high levels of acylcarnitines, likely driven by rapid cell growth and hypoxic features. We found elevated levels of 5-HIAA in gliosarcoma and a subtype of oligodendroglioma not yet defined as a specific entity, indicating a previously not described role for the serotonin pathway linked to glioma with bimorphic tissue. CONCLUSION: Key metabolic differences exist across adult glioma subtypes.

The antibacterial activity of Ga3+ is influenced by ligand complexation as well as the bacterial carbon source.

Gallium ions have previously been shown to exhibit antibacterial and antibiofilm properties. In this study, we report differential bactericidal activities of two gallium complexes, gallium desferrioxamine B (Ga-DFOB) and gallium citrate (Ga-Cit). Modeling of gallium speciation in growth medium showed that DFOB and citrate both can prevent precipitation of Ga(OH)(3), but some precipitation can occur above pH 7 with citrate. Despite this, Ga-Cit 90% inhibitory concentrations (IC(90)) were lower than those of Ga-DFOB for clinical isolates of Pseudomonas aeruginosa and several reference strains of other bacterial species. Treatment with Ga compounds mitigated damage inflicted on murine J774 macrophage-like cells infected with P. aeruginosa PAO1. Again, Ga-Cit showed more potent mitigation than did Ga-DFOB. Ga was also taken up more efficiently by P. aeruginosa in the form of Ga-Cit than in the form of Ga-DFOB. Neither Ga-Cit nor Ga-DFOB was toxic to several human cell lines tested, and no proinflammatory activity was detected in human lung epithelial cells after exposure in vitro. Metabolomic analysis was used to delineate the effects of Ga-Cit on the bacterial cell. Exposure to Ga resulted in lower concentrations of glutamate, a key metabolite for P. aeruginosa, and of many amino acids, indicating that Ga affects various biosynthesis pathways. An altered protein expression profile in the presence of Ga-Cit suggested that some compensatory mechanisms were activated in the bacterium. Furthermore, the antibacterial effect of Ga was shown to vary depending on the carbon source, which has importance in the context of medical applications of gallium.

Components acting downstream of short day perception regulate differential cessation of cambial activity and associated responses in early and late clones of hybrid poplar.

Short days (SDs) in autumn induce growth cessation, bud set, cold acclimation, and dormancy in trees of boreal and temperate forests, and these responses occur earlier in northern than in southern genotypes. Nevertheless, we know little about whether this variation results from differential perception of SDs or differential downstream responses to the SD signal or a combination of the two. We compared global patterns of SD-regulated gene expression in the stems of hybrid poplar (Populus trichocarpa × Populus deltoides) clones that differ in their SD-induced growth cessation in order to address this question. The timing of cessation of cambial cell division caused by SDs differed between the clones and was coincident with the change in the pattern of expression of the auxin-regulated genes. The clones also differed in the timing of their SD-regulated changes in the transcript abundance of genes associated with cold tolerance, starch breakdown, and storage protein accumulation. By analyzing the expression of homologs of FLOWERING LOCUS T, we demonstrated that the clones differed little in their perception of SDs under the growth conditions applied but differed substantially in the downstream responses manifested in the timing and magnitude of gene expression after SD treatment. These results demonstrate the existence of factors that act downstream of SD perception and can contribute to variation in SD-regulated adaptive photoperiodic responses in trees.

Rapid and noninvasive diagnosis of the presence and severity of coronary heart disease using 1H-NMR-based metabonomics.

Although a wide range of risk factors for coronary heart disease have been identified from population studies, these measures, singly or in combination, are insufficiently powerful to provide a reliable, noninvasive diagnosis of the presence of coronary heart disease. Here we show that pattern-recognition techniques applied to proton nuclear magnetic resonance (1H-NMR) spectra of human serum can correctly diagnose not only the presence, but also the severity, of coronary heart disease. Application of supervised partial least squares-discriminant analysis to orthogonal signal-corrected data sets allows >90% of subjects with stenosis of all three major coronary vessels to be distinguished from subjects with angiographically normal coronary arteries, with a specificity of >90%. Our studies show for the first time a technique capable of providing an accurate, noninvasive and rapid diagnosis of coronary heart disease that can be used clinically, either in population screening or to allow effective targeting of treatments such as statins.

LC-MS/MS profiling for detection of endogenous steroids and prostaglandins in tissue samples.

Roles of steroid hormones, and compounds that can influence their levels in cells, are of increasing interest in e.g. cancer research, partly because resistance to hormone therapies often complicates treatment. To elucidate the processes involved, the hormones and related compounds need to be accurately measured. Reversed-phase liquid chromatography with dynamic multiple reaction monitoring mass spectrometric detection in electrospray mode is capable of providing such measurements. Therefore, LC-MS/MS was developed for sensitive, selective analysis of 11 steroid hormones, cholesterol and two prostaglandins. The effects of the tissue matrix, and solid-phase extraction (SPE) sample clean-up, on the LC-MS/MS signals of the hormones were also investigated. The results show that the developed LC-MS/MS method, following SPE clean-up to reduce matrix interference, can detect selected steroids in extracts of mouse tissues. The method provides linear measurements of the steroids at concentrations up to few ng/µL, and limits of detection in the range 0.03-0.2 pg/µL (for some compounds lower than those of previously reported methods).

Changes in the spinal cord proteome of an amyotrophic lateral sclerosis murine model determined by differential in-gel electrophoresis.

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder characterized by loss of motor neurons resulting in progressive paralysis. To date, more than 140 different mutations in the gene encoding CuZn-superoxide dismutase (SOD1) have been associated with ALS. Several transgenic murine models exist in which various mutant SOD1s are expressed. We used DIGE to analyze the changes in the spinal cord proteome induced by expression of the unstable SOD1 truncation mutant G127insTGGG (G127X) in mice. Unlike mutants used in most other models, G127X lacks SOD activity and is present at low levels, thus reducing the risk of overexpression artifacts. The mice were analyzed at their peak body weights just before onset of symptoms. Variable importance plot analysis showed that 420 of 1,800 detected protein spots contributed significantly to the differences between the groups. By MALDI-TOF MS analysis, 54 differentially regulated proteins were identified. One spot was found to be a covalently linked mutant SOD1 dimer, apparently analogous to SOD1-immunoreactive bands migrating at double the molecular weight of SOD1 monomers previously detected in humans and mice carrying mutant SOD1s and in sporadic ALS cases. Analyses of affected functional pathways and the subcellular representation of alterations suggest that the toxicity exerted by mutant SODs induces oxidative stress and affects mitochondria, cellular assembly/organization, and protein degradation.