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30 protocols using 6550 q tof

1

Polar Metabolite Extraction and Profiling

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For polar metabolite extraction of tissue samples, 20 mg tissue was mixed with 200 μl acetonitrile:methanol:water (40:40:20) and homogenized with a TissueLyser for 2 min. Samples were centrifuged at 15,000 g for 30 s at 4°C; the supernatants were transferred to a new tube and used for mass spectometry analysis. Analysis of metabolite extracts was performed in flow injection analysis–time-of-flight mass spectrometry on an Agilent 6550 Q-TOF instrument as previously described (Fuhrer et al., 2011 (link)). Mass spectra were recorded from a mass/charge ratio of 50–1,000 in high-resolution negative ionization mode. Ions were annotated by matching their measured mass with reference compounds derived from the Human Metabolome Database (HMDB 4.0), allowing a tolerance of 1 mD. Intensities of m/z 117.0192, annotated as succinate, were plotted for ileum tissues of WT and MafIECKO mice.
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2

Metabolomic Analysis of YY1 Knockdown

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Isolated NPCs from E11.5 cortices were transfected with siCtrl or siYy1 (n = 9, each). After 48 h, cells were harvested and washed twice with 75 mm ammonium carbonate, ph 7.4, and snap frozen in liquid nitrogen. Metabolites were extracted two times with cold acetonitrile-methanol-water (40:40:20 ratio, − 20 °C). Extracted metabolites were analyzed by flow injection–time of flight mass spectrometry on an Agilent 6550 QTOF instrument operated in the negative mode as previously described73 (link). Detectable ions were putatively annotated by matching measured mass-to-charge ratios with theoretical masses of compounds listed in the human metabolome database v3.074 (link) using a tolerance of 0.001 amu. Pathway definition of differentially abundant metabolites was performed with the Small Molecule Pathway Database75 (link). P values were calculated by two-tailed, heteroscedastic t test and were adjusted for FDR according to the Benjamini–Hochberg procedure. All calculations were done in Matlab (The Mathworks, Natick, MA).
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3

Intracellular Metabolomics Profiling of E. coli

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Intracellular metabolomics samples were taken during mid‐exponential phase at OD600s between 0.5 and 0.6 by fast filtration (sampling volume: 1 ml) (Link et al,2013) and were immediately quenched in 4 ml quenching/extraction solution (40% methanol, 40% acetonitrile, 20% H2O) at −20°C (Link et al,2012). Samples were incubated for 2 h at −20°C, subsequently dried completely at 120 μbar (Christ RVC 2‐33 CD centrifuge and Christ Alpha 2–4 CD freeze dryer), and stored at −80°C until measurements. Before measurements, samples were resuspended in 100 μl water, centrifuged for 5 min (5,000 g, 4°C) to remove residual particles, diluted 1:10 in water, and transferred to V‐bottom 96‐well plates (Thermo Fisher Scientific). Samples were measured by flow‐injection time‐of‐flight mass spectrometry with an Agilent 6550 QToF instrument operated in negative ionization mode at 4 GHz high resolution in a range of 50–1,000 m/z as described before (Sévin & Sauer, 2014). Sample processing and ion annotation was performed based on accurate mass within 0.001 Da using the KEGG E. coli database (Ogata et al,1999) as reference and accounting for single deprotonated forms of the respective metabolite (M–H+) as described before (Fuhrer et al,2011). Intensities of annotated ions were normalized to NCM3722 wild type to yield relative concentrations.
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4

UHPLC-QTOF-MS Analysis of Vegetable Extracts

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An Agilent 1290 UHPLC system (Santa Clara, CA, USA) coupled with an HSS T3 2.1 × 100 mm 1.7 µm column from Waters Corp (Milford, MA, USA) was used to perform UHPLC analysis of the vegetable extracts. Samples were mixed with distilled water, vortexed, and passed through a 0.2 µm filter. Then, a 5 µL portion of the filtrate was injected onto the column followed by elution at a flow rate of 0.5 mL/min using mobile phases A and B (0.1% formic acid in water and 0.1% formic acid in acetonitrile, respectively) at 40 °C. The following gradients were used: initial holding time 0.5 min, mobile phase B ramped up to 50% after 5 min, 95% after 6 min, held for 1 min, and re-equilibrated for 1.5 min. Compounds were identified using a diode array detector at a wavelength range of 230–640 nm in 2 nm increments and a frequency of 5 Hz. The mass spec was carried out in an Agilent 6550 QTOF (Santa Clara, CA, USA) at 200 °C, using a drying gas pressure of 18 psi, 40 psi nebulizer and 350 °C sheath gas, a pressure of 12 psi, and 3500 V capillary with a 1000 V nozzle, and ran in positive ion electrospray at a frequency of 3Hz and acquisition from 30–1700 m/z. The MS/MS was performed at a narrow quadruple setting (1.3 atomic mass units), using 10, 20, and 40 eV collision energy and 30–1700 m/z. The compounds were identified using MS/MS fragmentation patterns and quantified based on the MS peak area.
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5

Untargeted Metabolomics via Q-TOF MS

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Data was collected in positive ion polarity over mass ranges 260–1700 m/z at a scan rate of 1.5 spectra/second on a 6550 Q-TOF equipped with a nano source (Agilent Technologies) operated in MS-only mode. One-to-one mixed 12C and 13C clicked samples were acquired using the same LC method and source parameters as the pooled samples for AMRT library generation.
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6

Plasma Metabolite Profiling by QTOF-MS

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Metabolites were extracted from 10 μl plasma 3 times with 70% ethanol at a temperature > 70°C. Extracts were analysed using flow injection–time‐of‐flight mass spectrometry (Agilent 6550 QTOF) operated in negative mode, as described previously (Fuhrer et al, 2011). Distinct mass‐to‐charge (m/z) ratio could be identified in each batch of samples (typically with 5,000–12,000 ions). Ions were annotated by aligning their measured mass to compounds defined by the KEGG database, allowing a tolerance of 0.001 Da. Only deprotonated ions (without adducts) were considered in the analysis. When multiple matches were identified, such as in the case of structural isomers, all candidates were retained. For enrichment analysis, metabolites with < 0.05 and log2(fold change) > 0.25 or < −0.25 follow a previously described procedure (Subramanian et al, 2005). Enrichments were considered significant when FDR < 0.05 after multiple testing corrections using the Benjamini–Hochberg post hoc test.
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7

NOD Islet LC-MS/MS Analysis

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NOD islets were prepared for LC–MS/MS analyses as described elsewhere (5 (link)). In vitro reactions and prepared NOD islets were analyzed by LC–MS/MS using an Agilent 1200 series UHPLC system with a nanoflow adapter and an Agilent 6550 Q-TOF equipped with a nano-ESI source. Online separation was accomplished by reversed-phase liquid chromatography using a Thermo Acclaim PepMap 100 C18 trap column (75 μm × 2 cm; 3 μm particles; 100 Å pores) and Thermo Acclaim PepMap RSLC C18 analytical column (75 μm inner diameter; 2 μm particles; 100 Å pores) in a trap forward-elute configuration using a water/acetonitrile gradient (buffer A: 0.1% formic acid in water; buffer B: 0.1% formic acid and 90% acetonitrile in water). A detailed description of the MS data collection was previously published (12 (link)).
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8

Agilent QToF Mass Spectrometry Protocol

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Data were acquired using an Agilent 6550 QToF instrument. Samples were ionized using an Agilent Jet Stream electrospray ionization source operated in negative mode. Gas temperature in the ion source was 150 °C with a flow rate of 14 L/min. Nebulizer pressure was 45 psig; sheath temperature was 325 °C with a gas flow rate of 12 L/min. Voltage for both capillary and nozzle was 2000 V. The funnel DC voltage was −30 V, funnel voltage drops were −100 and −50 V in the high- and low-pressure funnels, respectively. The RF voltages were 110 and 60 V in the high- and low-pressure funnels respectively. Mass spectra were acquired between 50 m/z and 1100 m/z with a rate of 2 spectra per second. Mass lock mixture was used as described in Wan et al.63 (link).
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9

LC-MS/MS Analysis of Peptides

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Samples were analyzed by LC-MS/MS using an Agilent 1200 series UHPLC system with a nanoflow adapter and an Agilent 6550 Q-TOF equipped with a nano-ESI source. Samples were separated online by reversed-phase liquid chromatography using a trap forward-elute configuration (trap column: Thermo Acclaim Pepmap 100, 75 µm x 2 cm, 3 µm particles, 100Å pores; analytical column: Thermo Acclaim Pepmap RSLC C18 analytical column, 75 µm inner diameter, 2 µm particles, 100Å pores). A water/acetonitrile gradient was used (buffer A: 0.1% formic acid in water; buffer B: 0.1% formic acid and 90% acetonitrile in water). Mass spectrometric data was collected in positive ion mode with an MS scan range of 290-1700 m/z, an MS acquisition rate of 5 spectra/sec, an MS/MS scan range of 50-1700 m/z, and a minimum MS/MS scan rate of 3 spectra/sec. Abundance dependent accumulation was enabled with a target of 80,000 counts/spectrum. Using auto-MS/MS mode, the ten most abundant precursors per cycle were selected for fragmentation (absolute threshold: 3000 counts; relative threshold: 0.01%). Singly-charged precursors were excluded.
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10

Metabolic Profile of HeLa Cells

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HeLa stable clones were seeded at density of 3 × 105 cells/well in 6-well plates. After 48 hours, cells were washed twice with 75 mM ammonium carbonate buffer (pH 7.4, 37°C) and cell metabolism was quenched by shock freezing of plates in liquid N2. Metabolites were extracted by adding 700 μl ice-cold acetonitrile/methanol/water (40:40:20, v/v). The extraction procedure was repeated twice. Scraped cells and supernatants were pooled in the same tube. To remove cell debris, tubes were centrifuged (4°C, 13’000 rpm, 2 min) and the supernatants collected were assayed by flow injection analysis using TOF MS (6550 QTOF, Agilent Technologies) operated in the negative ionization mode. High resolution mass spectra were recorded from 50–1,000 m/z and analyzed as described previously (Fuhrer et al., 2011). Detected ions were putatively annotated by accurate mass against the Human Metabolome Database version 3.6. Mass matching was done using a tolerance of m/z 0.001 and including isotopologues, common electrospray derivatives, and adducts. Differences between treatments and control cells were determined using the R/Bioconductor package limma. Supplementary Table 2 contains the full metabolomics dataset.
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