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11 protocols using agilent 6550 q tof

1

Characterization Techniques for Organometallic Complexes

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Unless specified otherwise, all reactions were carried out under a dry N2 atmosphere using standard glovebox and Schlenk techniques. Anhydrous grade solvents and reagents used were obtained from Aldrich or Fisher Scientific and stored over 4 Å molecular sieves. All chemicals of analytical grade including the alkene substrates and additives are used as received from Alfa Aesar, Acros, TCI America or Fisher Scientific without further purification. FT-IR spectra were recorded on a Shimadzu 8400S instrument with solid samples under N2 using a Golden Gate ATR accessory. Elemental analyses were performed by Midwest Microlab LLC in Indianapolis in the US. 1H NMR and 13C NMR spectra were obtained at room temperature on a Bruker AV 400, 500 or 600 MHz NMR spectrometer, with chemical shifts (δ) referenced to the residual solvent signal. HR-MS data were obtained on an Agilent 6550 QToF coupled to an Agilent 1290 Infinity LC system. GC-MS analysis was obtained using a Shimadzu GCMS-QP2010S gas chromatograph mass spectrometer (column: SHRX1-5MS, thickness: 0.25 m, diameter: 0.25 mm, length: 30.0 m; conditions: 30–200 °C, 10 °C min−1, injection temperature: 100 °C; solvent cutoff: 3 min).
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2

Metabolomics Analysis of Yeast Cell Cycle

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Cells were harvested by filtration and metabolites were extracted in 70% ethanol as described in (Link et al., 2013 (link)). Metabolomics samples were analyzed by flow-injection analysis on an Agilent 6550 Q-TOF (Agilent, Santa Clara, CA) using the settings described in (Fuhrer et al., 2011 (link)). Ions were annotated to known metabolites using the KEGG sce database for S. cerevisiae (Kanehisa and Goto, 2000 (link)). If not stated otherwise, ion intensities were normalized by a univariate comparison between each individual measurement and the intensities of the 3 time points prior to release from G1 with foldchange = (log2(intensities(t)/intensities(t<0)) using a two-sample t-test, where p-values were corrected for false discovery rate as described in (Storey, 2002 ). Metabolic pathway enrichment analysis was performed using a hypergeometric test on significantly changing ions (p-value < 0.01, |log2(foldchange)| > 0.2) of this univariate comparison. To compare metabolite profiles of wild type and storage degradation mutants, we applied a repeated measure ANOVA and corrected the p-values as above for false discovery. For plotting, a 3-point moving average filter was applied on time profiles of metabolites. All metabolomics data analysis was performed using custom Matlab software (The Mathworks, Natick).
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3

Non-targeted Metabolomics Analysis Protocol

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The methanol extracts were injected in an Agilent 6550 QTOF instrument (Agilent Technologies, Santa Clara, CA, USA) and analyzed by non-targeted flow injection–time-of-flight mass spectrometry in negative mode ionization, as described [33 (link)]. Ions were annotated as previously described [16 (link)]. Given the existence of metabolites with identical molecular formula and weight, a larger number of candidate metabolites compared to ions was expected. In fact, a total of 409 ions with distinct m/z values were matched to 493 deprotonated molecules, which were then subjected to statistical analysis. Table S7 contains an overview of all metabolomics raw data, including ions, annotations, and intensities. A comparative statistical analysis was performed, according to Storey and colleagues [56 (link)], applying a two-tailed and heteroscedastic t-test, followed by the application of a false discovery rate (FDR) correction. A metabolite was considered to be significantly differentially abundant if the following requirements were satisfied: abs[log2(fold-change)] ≥ 0.5 and q-value < 0.01. Pathway enrichments were calculated using the procedure described previously, using the plant and bacterial KEGG databases [57 (link)].
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4

Lipidomic Analysis of Bacterial Strains

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High-resolution MS spectra obtained on the LTQ-Orbitrap XL were processed using Xcalibur software (Thermo Fisher Scientific, USA). Lipid species were identified using an in-house database as well as online LipidMaps and Metlin lipid databases with an MS tolerance of 10 ppm. The identification was based on accurate mass and/or retention times (RT). Tandem MS data obtained on the Agilent 6550 Q-ToF were analyzed to obtain headgroup and/or fatty acid compositions and the RT for each lipid molecular species. For MRM data obtained on the Agilent 6460 QqQ, signal intensities were compared with the intensities from the spiked internal standards (PG 14:0 for PG and Lysyl-PG 16:0 for Lysyl-PG) and the retention times for the various classes were matched. Growth-phase MRM data were normalized to the dry cell pellet weights to ensure that comparisons were made per unit weight of bacterial sample. For the growth curve study, MRM peak areas for the early-logarithmic, mid-logarithmic and late-logarithmic phases were normalized to the peak areas for the late stationary phase to obtain a fold change. These fold changes were used to generate a heat map in R. The Student’s t test was performed to determine whether differences between OG1RF, Dap21 and Dap22 strains were statistically significant. p <0.05 was considered statistically significant.
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5

Multi-omics Metabolite Profiling Workflow

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Polar metabolite detection was performed on an Agilent 6550 Q‐TOF mass spectrometer operating in negative mode. Metabolites were separated on a SeQuant ZIC‐pHILIC column (5 µM, 150 × 4.6 mm, Millipore) using a binary gradient with a 1200 series HPLC system across a 45‐min method using 20 mM ammonium carbonate (pH 9) and acetonitrile as outlined in Cobbold etal, (2016). Two independent replicates of the metabolite profiling following AMR1 and Lipin depletion were performed using the same ZIC‐pHILIC chromatography on a Thermo Q‐Exactive operating in both positive and negative mode (rapid switching) as described previously (Creek etal, 2016). Lipid extracts were analysed on an Agilent 6550 Q‐TOF using the reverse phase chromatography outlined by Bird etal (2011).
GC‐MS analysis was performed using methods previously described (Saunders etal, 2011). Metabolites were separated using a BD5 capillary column (J&W Scientific, 30 m × 250 µM × 0.25 µM) on a Hewlett Packard 6890 system (5973 EI‐quadrupole MS detector). The oven temperature gradient was 70 °C (1 min); 70°C to 295°C at 12.5°C/min, 295°C to 320°C at 25°C/min; 320°C for 2 min. MS data were acquired using scan mode with a m/z range of 50–550, threshold 150 and scan rate of 2.91 scans/second. GC retention time and mass spectra were compared with authentic standards analysed in the same batch for metabolite identification.
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6

Spectroscopic Characterization of Compounds

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The UV spectra were obtained by a Shimadzu UV-2600i spectrometer (Shimadzu, Kyoto, Japan). Optical rotations were measured by a JASCO P-2000 polarimeter (Anton Paar, Ostfildern, Germany). We recorded the HRESIMS data on Bruker microTOFQ-Q mass spectrometers (Billerica, MA, USA) and an Agilent 6550 Q-TOF (Agilent Technologies, Palo Alto, CA, USA). The NMR spectra were recorded on a Bruker AVANCE Ⅲ HD 600 MHz NMR spectrometer (Bruker BioSpin, Billerica, MA, USA) using TMS as an internal standard. The chromatographic silica gel (Qingdao Haiyang Chemical Factory, Qingdao, China), ODS (YMC Co., Ltd., Kyoto, Japan), and Sephadex LH-20 (GE Healthcare, Uppsala, Sweden). We recorded the analytical HPLC data using a Shimadzu SPD-M20A series machine equipped with a YMC C-18 column (250 mm × 4.6 mm, 5 μm). We conducted the semipreparative HPLC using a Shimadzu LC-6AD series pumping system equipped with an SPD-20A UV detector and C-18 column (20 mm × 250 mm, 5 μm; YMC Co., Ltd.). All the organic solvents were purchased from Yuwang and Laibo Chemicals Industries, Ltd., Shenyang, China.
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7

Chemical Profiling of PGWE by LC/MS

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We used LC/MS analysis to identify the chemical profiling of PGWE. Chromatographic separation of the aliquots was performed by an Agilent 1290 infinity LC (Agilent Technologies, Palo Alto, United States) using an Agilent Eclipse Plus C18 column (2.1 × 50 mm, 1.8 µm) and a mobile phase composed of 0.1% formic acid in water (A) and 0.1% formic acid in acetonitrile (B). The gradient program was as follows: 0–3 min, 5% B; 3–13 min, 5%–80% B; 13–15 min, 80% B; 15–17 min, 80%–5% B; and 17–20 min, 5% B. The flow rate was 0.3 mL/min, and the injection volume was 1 μL, which was injected into the column using a thermostatted HiP-ALS autosampler. Separated peaks were analyzed using an Agilent 6550 Q-TOF (Agilent Technologies), which provided high-resolution mass measurement. The instrument was equipped with a Jet Stream ESI source. The ESI spray voltage was set to 4000 V for positive ion mode and 3500 V for negative ion mode. Mass spectra were acquired in the 100–1000 m/z range.
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8

Lipidomic Analysis of Extracellular Vesicles

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For extraction of both the free phospholipids (FFP) and free fatty acids (FFA), 200 μL of chilled butanol/methanol (1:1, v/v) containing FFP internal standards, was added to dried EV samples. Samples were vortexed for 20 s, sonicated at 4°C for 1 h and shaken at room temperature for 30 min, respectively. Then, samples were centrifuged twice at 14,000 × g, 4°C for 10 min. For the FFP panel, 100 μL supernatant was collected for LC‐MS analysis. For the FFA panel, 50 μL supernatant was collected and mixed with 50 μL 1 μM FA 18:0 13C18 internal standard for LC‐MS analysis. LC‐MS/MS was conducted using an Agilent 6495C‐2 (Agilent, USA) for the FFP panel and Agilent 6550QTOF (Agilent, USA) for the FFA panel as previously described.
20 (link) Quantification data was extracted using Agilent MassHunter Quantitative Analysis (QQQ) and (QTOF) softwares for the FFP and FFA panels, respectively. The data were manually checked to ensure that the software integrated the right peaks. This analysis was performed by the Singapore Lipidomics Incubator, Department of Biochemistry, YLL School of Medicine, National University of Singapore, Singapore.
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9

Chromatographic Separation of Tumor Tissues

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After the preparation of the samples and fatty acid standards (described in the Supplementary Materials), chromatographic separation of the tumor tissues was performed with an Agilent 1290 Infinity LC (Agilent Technologies, Walbronn, Germany) using an Acquity UPLC BEH C8 column (50 × 2.1 mm, 1.7 µm particle size, Waters) at 40 °C. Gradient elution of solvent A was water–methanol (97:3, v/v) with 10 mM ammonium acetate and 15 mM acetic acid (pH 4) and solvent B was 100% methanol. The gradient program was set to the following: 5–50% B (0–5 min), 50–90% B (5–17 min), 90% B (17–20 min), and the column was then equilibrated with 5% B for 3 min at a flow rate of 0.3 mL/min. All samples and calibration standards (1 µL each) were injected into the column using a Thermostated HiP-ALS autosampler. The HPLC system was interfaced with the MS system, which was an Agilent 6550 Q-TOF (Agilent Technologies, Walbronn, Germany) equipped with a jet stream ESI source operating in negative ion mode. The ESI spray voltage was set to 3500 V (Vcap). Mass spectra were acquired at a scan rate of 1.0 spectra/s with a mass range of 100–1200 m/z. The procedure was controlled using Q-TOF Quantitative Analysis software (Version B 07.00, Agilent Technologies, Walbronn, Germany).
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10

Peptide Characterization by LC-MS/MS

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Purified peptide suspension was injected into a HPLC-chip (Polaris-HR-Chip-3C18) using a capillary pump with a flow at 1.5 μL/min, 2 μL. Peptides were eluted from the C18 column and into an online Agilent 6550 Q-TOF (Agilent Technologies, USA). A two-hour gradient generating by a 1200 series nano pump (Agilent Technologies, USA) with the nano flow at 300 nl/min was conducted for LC-MS/MS.
The elution gradient started with 5% (v/v) solution B (0.1% (v/v) formic acid in acetonitrile), following gradients 5 to 6% in 6 min, 6-22% in 84 min, 22-35% in 5 min, 35-90% in 3 min, remained 90% for 4 min, 90-5% in 2 min. Parameters setting for mass spectrum acquisition were previously reported by Duncan et al., (Duncan et al., 2017) . Briefly, data dependent mode and a scan range from 300 to 1750 mz was used for MS acquisition. MS data was collected at eight spectra per second and MS/MS data was collected at four spectra per second. Ions were dynamically excluded for 6 sec following fragmentation. In total, MS data for 36 samples were successfully collected. The primary MS data files are available via ProteomeXchange with identifier PXD021706.
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