Deep Proteomic Deconvolution of Interferons and HBV Transfection Effects on a Hepatoblastoma Cell Line

Interferons are commonly utilized in the treatment of chronic hepatitis B virus (HBV) infection but are not effective for all patients. A deep understanding of the limitations of interferon treatment requires delineation of its activity at multiple "omic"levels. While myriad studies have characterized the transcriptomic effects of interferon treatment, surprisingly, few have examined interferon-induced effects at the proteomic level. To remedy this paucity, we stimulated HepG2 cells with both IFN-α and IFN-λ and performed proteomic analysis versus unstimulated cells. Alongside, we examined the effects of HBV transfection in the same cell line, reasoning that parallel IFN and HBV analysis might allow determination of cases where HBV transfection counters the effects of interferons. More than 6000 proteins were identified, with multiple replicates allowing for differential expression analysis at high confidence. Drawing on a compendium of transcriptomic data, as well as proteomic half-life data, we suggest means by which transcriptomic results diverge from our proteomic results. We also invoke a recent multiomic study of HBV-related hepatocarcinoma (HCC), showing that despite HBV\u27s role in initiating HCC, the regulated proteomic landscapes of HBV transfection and HCC do not strongly align. Special focus is applied to the proteasome, with numerous components divergently altered under IFN and HBV-transfection conditions. We also examine alterations of other protein groups relevant to HLA complex peptide display, unveiling intriguing alterations in a number of ubiquitin ligases. Finally, we invoke genome-scale metabolic modeling to predict relevant alterations to the metabolic landscape under experimental conditions. Our data should be useful as a resource for interferon and HBV researchers

Expanded metabolite coverage of Saccharomyces cerevisiae extract through improved chloroform/methanol extraction and tert-butyldimethylsilyl derivatization

AbstractWe present an improved extraction and derivatization protocol for GC–MS analysis of amino/non-amino acids in Saccharomyces cerevisiae. Yeast cells were extracted with chloroform: aqueous-methanol (1:1, v/v) and the resulting non-polar and polar extracts combined and dried for derivatization. Polar and non-polar metabolites were derivatized using tert-butyldimethylsilyl (t-BDMS) dissolved in acetonitrile. Using microwave treatment of the samples, the derivatization process could be completed within 2 h (from >20 h of the conventional method), providing fully derivatized metabolites that contain multiple derivatizable organic functional groups. This results in a single derivative from one metabolite, leading to increased accuracy and precision for identification and quantification of the method. Analysis of combined fractions allowed the method to expand the coverage of detected metabolites from polar metabolites i.e. amino acids, organic acids and non-polar metabolites i.e. fatty alcohols and long-chain fatty acids which are normally non detectable. The recoveries of the extraction method was found at 88 ± 4%, RSD, N = 3 using anthranilic acid as an internal standard. The method promises to be a very useful tool in various aspects of biotechnological applications i.e. development of cell factories, metabolomics profiling, metabolite identification, 13C-labeled flux analysis or semi-quantitative analysis of metabolites in yeast samples

UPLC-ESI-MRM/MS for Absolute Quantification and MS/MS Structural Elucidation of Six Specialized Pyranonaphthoquinone Metabolites From Ventilago harmandiana

Pyranonaphthoquinones (PNQs) are important structural scaffolds found in numerous natural products. Research interest in these specialized metabolites lies in their natural occurrence and therapeutic activities. Nonetheless, research progress has thus far been hindered by the lack of analytical standards and analytical methods for both qualitative and quantitative analysis. We report here that various parts of Ventilago harmandiana are rich sources of PNQs. We developed an ultraperformance liquid chromatography-electrospray ionization multiple reaction monitoring/mass spectrometry method to quantitatively determine six PNQs from leaves, root, bark, wood, and heartwood. The addition of standards in combination with a stable isotope of salicylic acid-D-6 was used to overcome the matrix effect with average recovery of 82% +/- 1% (n = 15). The highest concentration of the total PNQs was found in the root (11,902 mu g/g dry weight), whereas the lowest concentration was found in the leaves (28 mu g/g dry weight). Except for the root, PNQ-332 was found to be the major compound in all parts of V. harmandiana, accounting for similar to 48% of the total PNQs quantified in this study. However, PNQ-318A was the most abundant PNQ in the root sample, accounting for 27% of the total PNQs. Finally, we provide novel MS/MS spectra of the PNQs at different collision induction energies: 10, 20, and 40 eV (POS and NEG). For structural elucidation purposes, we propose complete MS/MS fragmentation pathways of PNQs using MS/MS spectra at collision energies of 20 and 40 eV. The MS/MS spectra along with our discussion on structural elucidation of these PNQs should be very useful to the natural products community to further exploring PNQs in V. harmandiana and various other sources

Functional expression and characterization of five wax ester synthases in Saccharomyces cerevisiae and their utility for biodiesel production

<p>Abstract</p> <p>Background</p> <p>Wax ester synthases (WSs) can synthesize wax esters from alcohols and fatty acyl coenzyme A thioesters. The knowledge of the preferred substrates for each WS allows the use of yeast cells for the production of wax esters that are high-value materials and can be used in a variety of industrial applications. The products of WSs include fatty acid ethyl esters, which can be directly used as biodiesel.</p> <p>Results</p> <p>Here, heterologous WSs derived from five different organisms were successfully expressed and evaluated for their substrate preference in <it>Saccharomyces cerevisiae</it>. We investigated the potential of the different WSs for biodiesel (that is, fatty acid ethyl esters) production in <it>S. cerevisiae</it>. All investigated WSs, from <it>Acinetobacter baylyi </it>ADP1, <it>Marinobacter hydrocarbonoclasticus </it>DSM 8798, <it>Rhodococcus opacus </it>PD630, <it>Mus musculus </it>C57BL/6 and <it>Psychrobacter arcticus </it>273-4, have different substrate specificities, but they can all lead to the formation of biodiesel. The best biodiesel producing strain was found to be the one expressing WS from <it>M. hydrocarbonoclasticus </it>DSM 8798 that resulted in a biodiesel titer of 6.3 mg/L. To further enhance biodiesel production, acetyl coenzyme A carboxylase was up-regulated, which resulted in a 30% increase in biodiesel production.</p> <p>Conclusions</p> <p>Five WSs from different species were functionally expressed and their substrate preference characterized in <it>S. cerevisiae</it>, thus constructing cell factories for the production of specific kinds of wax ester. WS from <it>M. hydrocarbonoclasticus </it>showed the highest preference for ethanol compared to the other WSs, and could permit the engineered <it>S. cerevisiae </it>to produce biodiesel.</p

Method development for the determination of arsenic-containing fatty acids by GCMS

Der erste Teil dieser Arbeit beschreibt die Entwicklung einer GCMS-Methode für die Bestimmung von Fettsäuren in Nahrungsergänzungsmitteln aus Fischöl. Die Methode wurde durch Analyse des Standardreferenzmaterials NIST SRM 1588b ?Organics in cod liver oil? validiert. Die Resultate zeigen keine signifikanten Unterschiede (p?0,05) zwischen experimentellen und zertifizierten Werten der meisten Fettsäuren. Die Methode wurde daraufhin für die Analyse von 25 Fischölen angewendet, wobei die ermittelten Fettsäuremuster zur Unterscheidung der Qualität herangezogen wurden. Das hieraus entwickelte ?S-Diagramm? wurde zur schnellen Qualitätskontrolle verschiedener am Markt erhältlicher Fischöle verwendet. Im zweiten Teil wird die Methodenentwicklung für die Bestimmung von Arsenolipiden (Arsenolipidkarbonsäuren) in Fischöl mit GCMS beschrieben. Der Arsenfettsäuremethylester (As-FAME) 360 [(CH3)2As(CH2)14COOCH3] stellte sich, im Vergleich zu As-FAME 376 und As-FAME 392, als beste Wahl für die Analyse mit GCMS heraus. Als Reduktionsmittel zur Umwandlung des As-FAME 376 in den As-FAME 360 wurde Dithiothreitol verwendet. Bei der Methylierung des synthetisch hergestellten Arsenfettsäurestandards 362 [(CH3)2(O)As(CH2)14COOH] in den Methylester 376 stellte sich Trimethylsilyldiazomethan als bestes Reagenz heraus (Umwandlungsgrad 98-110% (n=3)). Flüssig-Flüssigextraktion (Hexan/Wasser) wurde für die Abtrennung des As-FAME 360 von den Dithiothreitol-Rückständen verwendet. Nach der Optimierung verschiedener Parameter wurde die entwickelte Methode an einem kommerziell erhältlichen Kabeljauleberöl getestet. Die Probe wurde vor der GCMS Messung durch Lösungsmittelpartitionierung (Methanol/Wasser) aufgereinigt. Dadurch konnte der As-FAME 362 in der Probe identifiziert und quantifiziert werden (1,52 0,31 g As g-1 in Öl (n=3)). Eine direkte Messung dieses Arsenolipids im unbehandelten Fischöl konnte jedoch aufgrund des hohen Anteils an normalen Fettsäuren nicht durchgeführt werden.The first section of this thesis established a simple method for the determination of fatty acids in fish oil supplements by GCMS. The method was validated by analyzing the standard reference material 1588b organics in cod liver oil. Results showed no significant differences (p?0.05) between the experimental and certified values for most fatty acids. The method was applied to 25 fish oils and their fatty acid profiles could be used to identify quality differences of the fish oils. The ?S?diagram? was constructed from those fatty acid profiles to facilitate rapid scanning and categorizing of the different fish oil supplements. This diagram is potentially useful for rapid screening of the quality of such supplements. The second section focused on method development for the determination of arsenolipids (arsenolipid carboxylic acids) in fish oils by GCMS. The arsenolipid methyl ester (As-FAME) 360 [(CH3)2As(CH2)14COOCH3] was found to be the most appropriate analogue for analysis by GCMS when compared to As-FAME 376 [(CH3)2(O)As(CH2)14COOCH3] and As-FAME 392 [(CH3)2(S)As(CH2)14COOCH3]. Dithiothreitol (DTT) was selected as reducing agent for the preparation of As-FAME 360 from As-FAME 376. For the sample preparation, trimethylsilyldiazomethane was found to be an effective methylating agent to convert the arsenolipid carboxylic 362 synthesized standard [(CH3)2(O)As(CH2)14COOH] to As-FAME 376, providing yields of 98?110% (n=3). Liquid?liquid partitioning (hexane/water) was used to separate the As-FAME 360 from the DTT residues. After optimization of several parameters, the method was applied to a cod liver oil sample. The sample was purified by solvent partitioning with methanol/hexane, before derivatisation and GCMS analysis. In this way, the As-FAME 362 was identified in cod liver oil at a concentration of 1.52 0.31 ?g As g?1 in oil (n=3). A direct measurement of this arsenolipid in crude fish oil was not possible due to the high content of normal fatty acids.Sakda KhoomrungZsfassung in dt. SpracheGraz, Univ., Diss., 2011OeBB(VLID)21580

การวิเคราะห์หาปริมาณของสารหนูรวมในตัวอย่างดินและพืชตำบลร่อนพิบูลย์ จังหวัดนครศรีธรรมราช โดยวิธีไฮดรายเจนเนอเรชันอะตอมมิกแอบซอบชันสเปกโตรเมตรี

Thesis (M.Sc., Analytical Chemistry)--Prince of Songkla University, 200

Mass spectrometry-based analysis of gut microbial metabolites of aromatic amino acids

Small molecules derived from gut microbiota have been increasingly investigated to better understand the functional roles of the human gut microbiome. Microbial metabolites of aromatic amino acids (AAA) have been linked to many diseases, such as metabolic disorders, chronic kidney diseases, inflammatory bowel disease, diabetes, and cancer. Important microbial AAA metabolites are often discovered via global metabolite profiling of biological specimens collected from humans or animal models. Subsequent metabolite identity confirmation and absolute quantification using targeted analysis enable comparisons across different studies, which can lead to the establishment of threshold concentrations of potential metabolite biomarkers. Owing to their excellent selectivity and sensitivity, hyphenated mass spectrometry (MS) techniques are often employed to identify and quantify AAA metabolites in various biological matrices. Here, we summarize the developments over the past five years in MS-based methodology for analyzing gut microbiota-derived AAA. Sample preparation, method validation, analytical performance, and statistical methods for correlation analysis are discussed, along with future perspectives

Metabolomics and Integrative Omics for the Development of Thai Traditional Medicine

In recent years, interest in studies of traditional medicine in Asian and African countries has gradually increased due to its potential to complement modern medicine. In this review, we provide an overview of Thai traditional medicine (TTM) current development, and ongoing research activities of TTM related to metabolomics. This review will also focus on three important elements of systems biology analysis of TTM including analytical techniques, statistical approaches and bioinformatics tools for handling and analyzing untargeted metabolomics data. The main objective of this data analysis is to gain a comprehensive understanding of the system wide effects that TTM has on individuals. Furthermore, potential applications of metabolomics and systems medicine in TTM will also be discussed

Improved quantification of farnesene during microbial production from Saccharomyces cerevisiae in two-liquid-phase fermentations

Organic solvents are widely used in microbial fermentations to reduce gas stripping effects and capture hydrophobic or toxic compounds. Reliable quantification of biochemical products in these overlays is highly challenging and practically difficult. Here, we present a significant improvement of identification and quantification methods for farnesene produced by Saccharomyces cerevisiae in two-liquid-phase fermentations using GC-MS and GC-FID. By increasing the polarity of the stationary phase introducing a ZB-50 column (50%-phenyl-50%-dimethylsiloxane) peak intensity could be increased and solvent carryover could be minimized. Direct quantification of farnesene in dodecane was achieved by GC-FID whereas GC-MS demonstrated to be an excellent technique for identification of known and unknown metabolites. The GC-FID is a suitable technique for direct quantification of farnesene in complex matrices as shown by the good calibration curve (R2>0.998, N=5) within the tested concentration range of 1-50 µg/mL and the reproducibility of the intensity (intraday; <10% RSD at each concentration; N=5). The limit of detection (LOD) and limit of quantification (LOQ) of the method were 0.24 and 0.80 µg/mL, respectively. Furthermore, the FID method proved to be highly stable with regard to the intensity of the calibration (N=6) when the measurements were performed across 250 samples that were derived from a dodecane overlay