LC/MS/MS method for analysis of E₂ series prostaglandins and isoprostanes

15-series prostaglandins (PGE₂s) and isoprostanes (isoPGE₂s) are robust biomarkers of oxidative stress, possess potent biological activity, and may be derived through cyclooxygenase or free radical pathways. Thus, their quantification is critical in understanding many biological processes where PG, isoPG, or oxidative stress are involved. LC/MS/MS methods allow a highly selective, sensitive, simultaneous analysis for prostanoids without derivatization. However, the LC/MS/MS methods currently used do not allow for simultaneous separation of the major brain PGE₂/D₂ and isoPGE₂ without derivatization and multiple HPLC separations. The developed LC/MS/MS method allows for the major brain PGE₂/PGD₂/isoPGE₂ such as PGE₂, entPGE₂, 8-isoPGE₂, 11β-PGE₂, PGD₂, and 15(R)-PGD₂ to be separated and quantified without derivatization. The method was validated by analyzing free and esterified isoPGE₂ in mouse brains fixed with head-focused microwave irradiation before or after global ischemia. Using the developed method, we report for the first time the esterified isoPGE₂ levels in brain tissue under basal conditions and upon global ischemia and demonstrate a nonreleasable pool of esterified isoPG upon ischemia. In addition, we demonstrated that PGE₂s found esterified in the sn-2 position in phospholipids are derived from a free radical nonenzymatic pathway under basal conditions. Our method for brain PG analysis provides a high level of selectivity to detect changes in brain PG and isoPG mass under both basal and pathological conditions.     

caBIG™ VISDA: Modeling, visualization, and discovery for cluster analysis of genomic data

Background

We sketch our species identification tool for palm sized computers that helps knowledgeable observers with census activities. An algorithm turns an identification matrix into a minimal length series of questions that guide the operator towards identification. Historic observation data from the census geographic area helps minimize question volume. We explore how much historic data is required to boost performance, and whether the use of history negatively impacts identification of rare species. We also explore how characteristics of the matrix interact with the algorithm, and how best to predict the probability of observing a previously unseen species.

Results

Point counts of birds taken at Stanford University's Jasper Ridge Biological Preserve between 2000 and 2005 were used to examine the algorithm. A computer identified species by correctly answering, and counting the algorithm's questions. We also explored how the character density of the key matrix and the theoretical minimum number of questions for each bird in the matrix influenced the algorithm. Our investigation of the required probability smoothing determined whether Laplace smoothing of observation probabilities was sufficient, or whether the more complex Good-Turing technique is required.

Conclusion

Historic data improved identification speed, but only impacted the top 25% most frequently observed birds. For rare birds the history based algorithms did not impose a noticeable penalty in the number of questions required for identification. For our dataset neither age of the historic data, nor the number of observation years impacted the algorithm. Density of characters for different taxa in the identification matrix did not impact the algorithms. Intrinsic differences in identifying different birds did affect the algorithm, but the differences affected the baseline method of not using historic data to exactly the same degree. We found that Laplace smoothing performed better for rare species than Simple Good-Turing, and that, contrary to expectation, the technique did not then adversely affect identification performance for frequently observed birds.     

BAMarray™: Java software for Bayesian analysis of variance for microarray data

Background  

DNA microarrays open up a new horizon for studying the genetic determinants of disease. The high throughput nature of these arrays creates an enormous wealth of information, but also poses a challenge to data analysis. Inferential problems become even more pronounced as experimental designs used to collect data become more complex. An important example is multigroup data collected over different experimental groups, such as data collected from distinct stages of a disease process. We have developed a method specifically addressing these issues termed Bayesian ANOVA for microarrays (BAM). The BAM approach uses a special inferential regularization known as spike-and-slab shrinkage that provides an optimal balance between total false detections and total false non-detections. This translates into more reproducible differential calls. Spike and slab shrinkage is a form of regularization achieved by using information across all genes and groups simultaneously.     

A fast and sensitive HPLC–MS/MS analysis and preliminary pharmacokinetic characterization of ergone in rats

A fast and sensitive HPLC–APCI-MS/MS method was developed for the determination of ergosta-4,6,8(14),22-tetraen-3-one (ergone) in rat plasma. The plasma sample containing ergone and ergosterol (internal standard) were simply treated with acetone to precipitate and remove proteins and the isolated supernatants were directly injected into the HPLC–APCI-MS/MS system. Chromatographic separation was performed on a 1.8 μm Zorbax SB-C18 column (100 mm × 3.0 mm) with a 97:3 (v/v) mixed solution of methanol and 0.1% aqueous formic acid being used as mobile phase. Quantification was performed by multiple selected reactions monitoring (MRM) of the transitions with (m/z)⁺ 393–268 for ergone and (m/z)⁺ 379–69 for the IS. The method was validated in the concentration range of 5–1600 ng/mL for ergone. The precision of the assay (RSD%) was less than 10.5% at all concentrations levels within the tested range and adequate accuracy, and the limit of detection was 1.5 ng/mL. The absolute recoveries of both ergone and ergosterol from the plasma were more than 95%. The developed method has been successfully applied to the pharmacokinetic study of the drug in SD rats.     

Modified protocols for rapid carrot genomic DNA extraction and AFLP™ analysis using silver stain or radioisotopes

AFLP^™ is one of the most frequently used techniques for identification of molecular markers. We have modified the procedures for genomic DNA extraction, AFLP product generation and silver staining in order to speed up analyses and screen large numbers of plant samples. Using this protocol, we were able to achieve an 82% reduction of costs without compromising the reliability and quality of data gathered.     

Metabolomic and elemental analysis of camel and bovine urine by GC–MS and ICP–MS

Recent studies from the author’s laboratory indicated that camel urine possesses antiplatelet activity and anti-cancer activity which is not present in bovine urine. The objective of this study is to compare the volatile and elemental components of bovine and camel urine using GC–MS and ICP–MS analysis. We are interested to know the component that performs these biological activities. The freeze dried urine was dissolved in dichloromethane and then derivatization process followed by using BSTFA for GC–MS analysis. Thirty different compounds were analyzed by the derivatization process in full scan mode. For ICP–MS analysis twenty eight important elements were analyzed in both bovine and camel urine. The results of GC–MS and ICP–MS analysis showed marked difference in the urinary metabolites. GC–MS evaluation of camel urine finds a lot of products of metabolism like benzene propanoic acid derivatives, fatty acid derivatives, amino acid derivatives, sugars, prostaglandins and canavanine. Several research reports reveal the metabolomics studies on camel urine but none of them completely reported the pharmacology related metabolomics. The present data of GC–MS suggest and support the previous studies and activities related to camel urine.     

Assigning precursor–product ion relationships in indiscriminant MS/MS data from non-targeted metabolite profiling studies

Tandem mass spectrometry using precursor ion selection (MS/MS) is an invaluable tool for structural elucidation of small molecules. In non-targeted metabolite profiling studies, instrument duty cycle limitations and experimental costs have driven efforts towards alternate approaches. Recently, researchers have begun to explore methods for collecting indiscriminant MS/MS (idMS/MS) data in which the fragmentation process does not involve precursor ion isolation. While this approach has many advantages, importantly speed, sensitivity and coverage, confident assignment of precursor–product ion relationships is challenging, which has inhibited broad adoption of the technique. Here, we present an approach that uses open source software to improve the assignment of precursor–product relationships in idMS/MS data by appending a dataset-wide correlational analysis to existing tools. The utility of the approach was demonstrated using a dataset of standard compounds spiked into a malt-barley background, as well as unspiked human serum. The workflow was able to recreate idMS/MS spectra which are highly similar to standard MS/MS spectra of authentic standards, even in the presence of a complex matrix background. The application of this approach has the potential to generate high quality idMS/MS spectra for each detectable molecular feature, which will streamline the identification process for non-targeted metabolite profiling studies.     

Application of liquid chromatography-tandem mass spectrometry (LC–MS/MS) for the analysis of stable isotope enrichments of phenylalanine and tyrosine

Whole-body protein synthesis and breakdown are measured by a combined tracer infusion protocol with the stable isotope amino acids l-[ring-²H₅]-phenylalanine, l-[ring-²H₂]-tyrosine and l-[ring-²H₄]-tyrosine that enable the measurement of the phenylalanine to tyrosine conversion rate. We describe a liquid chromatography–tandem mass spectrometry (LC–MS/MS) method for the measurement of very low tracer–tracee ratios (TTR) of the amino acids l-phenylalanine and l-tyrosine in human plasma. TTR calibration curves of the tracers l-[ring-²H₅]-phenylalanine, l-[ring-²H₂]-tyrosine and l-[ring-²H₄]-tyrosine were linear (r² > 0.99) in the range between 0.01% and 5.0% TTR and lowest measurable TTR for the tracers was 0.01% at a physiological concentration of 60 μM. The method was applied successfully to plasma samples from a clinical study reaching a steady state enrichment plateau (mean ± SD) of 3.33 ± 0.19% for l-[ring-²H₅]-phenylalanine, 2.40 ± 0.43% for l-[ring-²H₂]-tyrosine and 0.29 ± 0.07% for l-[ring-²H₄]-tyrosine, respectively. The LC–MS/MS method can be applied for measurement of very low plasma enrichments of phenylalanine and tyrosine for the determination of whole-body protein synthesis and breakdown rates in humans.     

Chromatographic profiling and identification of two new iridoid-indole alkaloids by UPLC–MS and HPLC-SPE-NMR analysis of an antimalarial extract from Nauclea pobeguinii

The total 80% EtOH extract of stem bark of Nauclea pobeguinii (Rubiaceae), which is active against uncomplicated falciparum malaria as shown in previous clinical studies, was analysed by means of UPLC–MS and HPLC-SPE-NMR. Apart from the main constituent, strictosamide, a series of minor constituents was identified, including two new iridoid-indole alkaloids, i.e. naucleidinic acid and 19-O-methyl-3,14-dihydroangustoline, together with 8 known iridoid-indole alkaloids, i.e. naucleidinal, magniflorine, naucleofficine D, two diastereoisomers of 3,14-dihydroangustoline, strictosidine, desoxycordifoline, 3α,5α-tetrahydrodeoxycordifoline lactam, and a phenol glycoside 3,4,5-trimethoxyphenol β-d-apiofuranosyl-(1-6)-β-d-glucopyranoside (kelampayoside A).     

Biodegradation of p-nitrophenol by Pseudomonas aeruginosa HS-D38 and analysis of metabolites with HPLC–ESI/MS

Pseudomonas aeruginosa strain HS-D38 was capable of mineralizing p-nitrophenol (PNP) as the sole source of carbon, nitrogen and energy. Degradation of 200 mg L^?1 PNP was examined in different media including: (i) MSM (mineral salts medium, no carbon and nitrogen source); (ii) addition of 1% ammonium chloride as additional nitrogen source (ANM); and (iii) addition of 1% glucose as a carbon source (ACM). Complete degradation of 200 mg L^?1 PNP was achieved in 12 h in MSM. Additional ammonium chloride accelerated the PNP degradation, but additional glucose inhibited this process. This strain metabolized as high concentration as 300 and 500 mg L^?1 of PNP in 14 h and 24 h, respectively, in MSM. The degradation was accompanied by release of stoichiometric amount of nitrate from PNP. During the bacterial growth on PNP, hydroquinone and 1,2,4-benzenetriol were observed as the key degradation intermediates by using a combination of techniques, including HPLC–DAD and LC–ESI/MS compared with the authentic standards. These results indicated that PNP was degraded via a hydroquinone pathway.     

Multidimensional protein fractionation of blood proteins coupled to data-independent nanoLC–MS/MS analysis

In order to exploit human blood as a source of protein disease biomarkers, robust analytical methods are needed to overcome the inherent molecular complexity of this bio-fluid. We present the coupling of label-free SAX chromatography and IMAC to a data-independent nanoLC–MS/MS (nanoLC–MS^E) platform for analysis of blood plasma and serum proteins. The methods were evaluated using protein standards added at different concentrations to two groups of samples. The results demonstrate that both techniques enable accurate protein quantitation using low sample volumes and a minimal number of fractions. Combining both methods, 883 unique proteins were identified, of which 423 proteins showed high reproducibility. The two approaches resulted in identification of unique molecular signatures with an overlap of approximately 30%, thus providing complimentary information on sub-proteomes. These methods are potentially useful for systems biology, biomarker discovery, and investigation of phosphoproteins in blood.     

Column-switching HPLC–MS/MS analysis of ropivacaine in serum,ultrafiltrate and drainage blood for validating the safety of blood reinfusion

A high-performance liquid chromatography–tandem mass spectrometry (HPLC–MS–MS) method, using back-flush column-switching was developed for total drug concentrations of ropivacaine in serum and drainage blood in the measuring range 0.1–10 μg/mL. Samples were diluted with internal standard (²H₇-ropivacaine) and extraction buffer, centrifuged and injected directly onto a BioTrap 500 MS extraction column. Using a time programmed six-port valve switch, ropivacaine was back-flushed onto a Zorbax SB-Aq analytical column, gradient eluted and finally detected after electro spray ionisation and multiple reaction monitoring (MRM) of the transitions m/z 275 → m/z 126 and m/z 282 → m/z 133 for ropivacaine and ²H₇-ropivacaine, respectively. Accuracy (bias-%) was −1.5 to 5.8% and intermediate precision (C.V.) was 1.4–3.1%. The low sample amount required (10 μL), high specificity and short run time (6 min) makes it very suitable for determination of ropivacaine. Using the same methodology as described above and 200 μL ultrafiltrate, the free drug concentrations of ropivacaine in serum could be precisely determined with a C.V. below 3%. The method was used to investigate the safety of reinfusion of drainage blood after knee and hip arthroplasty when ropivacaine (Naropin^®) was used for local analgesia. Data for 30 patients are summarised.     

Clinical data and molecular analysis of Mycobacterium tuberculosis isolates from drug-resistant tuberculosis patients in Goiás, Brazil

Drug resistance is one of the major concerns regarding tuberculosis (TB) infection worldwide because it hampers control of the disease. Understanding the underlying mechanisms responsible for drug resistance development is of the highest importance. To investigate clinical data from drug-resistant TB patients at the Tropical Diseases Hospital, Goiás (GO), Brazil and to evaluate the molecular basis of rifampin (R) and isoniazid (H) resistance in Mycobacterium tuberculosis. Drug susceptibility testing was performed on 124 isolates from 100 patients and 24 isolates displayed resistance to R and/or H. Molecular analysis of drug resistance was performed by partial sequencing of the rpoB and katGgenes and analysis of the inhA promoter region. Similarity analysis of isolates was performed by 15 loci mycobacterial interspersed repetitive unit-variable number tandem repeat (MIRU-VNTR) typing. The molecular basis of drug resistance among the 24 isolates from 16 patients was confirmed in 18 isolates. Different susceptibility profiles among the isolates from the same individual were observed in five patients; using MIRU-VNTR, we have shown that those isolates were not genetically identical, with differences in one to three loci within the 15 analysed loci. Drug-resistant TB in GO is caused by M. tuberculosis strains with mutations in previously described sites of known genes and some patients harbour a mixed phenotype infection as a consequence of a single infective event; however, further and broader investigations are needed to support our findings.     

Identifying anti-HSV compounds from unrelated plants using NMR and LC–MS metabolomic analysis

Introduction

Plants have been used to treat various ailments and diseases, including viral infections. Often activity is reported after screening plants traditionally used, without identifying the active principles.

Objectives

This study investigated the use of metabolomics to identify common compound groups or compounds from unrelated plants, but with similar reported biological activity. Plants with anti-viral activities against Herpes Simplex Virus (HSV), Cytomegalovirus (CMV) and Human Immunodeficiency Virus (HIV) were collected and analysed. A few non-active plants, with no reported anti-viral activity were included as control samples.

Methods

1H-NMR and LC–MS metabolomic analysis were conducted, to determine the chemical similarity between plants with similar activity using SIMCA and XCMS online.

Results

Plants with anti-HSV, anti-HIV and anti-CMV activity, presented specific clusters, with the non-active samples separating from the active samples. The anti-HSV group presented a clear contribution plot and chlorogenic acid was identified by NMR. LC–MS metabolomic analysis confirmed the NMR results and furthermore identified several chlorogenic acid isomers including the main substructures of chlorogenic acids.

Conclusion

Metabolomic analysis on unrelated plants with similar activity can be used to identify the active compound groups or compounds, thereby eliminating the need for screening of plants to determine biological activity, additionally providing information on possible active principles. The two analytical methods identified chlorogenic acids and its building blocks as common and important compounds within plants with anti-HSV activity. Intensified research on plants containing chlorogenic acids should be the focus of future research for development of accessible anti-HSV treatments.