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Lipidomics Data Supplementary to: Phospholipid composition strongly affects the assembly of β barrel proteins into purified bacterial outer membranes

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DataCite Commons2025-12-03 更新2026-02-09 收录
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https://figshare.com/articles/dataset/Lipidomics_Data_Supplementary_to_Phospholipid_composition_strongly_affects_the_assembly_of_barrel_proteins_into_purified_bacterial_outer_membranes/30780602
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Generation of whole cell and purified OM samples for OMP, LPS and lipidomics analysis Four independent cultures of each E. coli strain transformed with pJH114 were grown in 150 mL LB+MC and BAM expression was induced for 45 min as described above. At the end of the induction period, the OD600 was recorded and two 5 mL aliquots of each culture were pelleted as whole cell (WC) samples and 100 mL of each culture was used to purify native OMs using the sarkosyl method described above. All of the purified OMs were divided into two equal aliquots, and the samples were flash frozen and stored at -80° C. One set of aliquots from the WC and purified OM samples from each strain was used for lipidomics analysis while the other set of aliquots was used to measure LPS and OMP levels. Sample preparation for lipidomics analysis For all liquid chromatography mass spectrometry (LCMS) methods LCMS-grade solvents were used. For lipidomics method development and analysis, ~5x109 bacteria or native OMs from ~5x1010 of bacteria were immersed in 0.4 mL ice-cold methanol. Water (0.4 mL) and chloroform (0.4 mL) were then added to each sample. Samples were shaken for 20 min under refrigeration and centrifuged at 16,000 x g for 20 min at 4o C. A portion of the bottom (organic) phase (330 µL) was collected and dried down under vacuum. Samples were resuspended in an equivalent volume of 5 µg/mL butylated hydroxytoluene in 6:1 isopropanol:methanol. A composite quality control and method development sample was constructed by mixing a portion of the WC samples from all examined strains. PL profiling by Liquid Chromatography Tandem Mass Spectrometry (LC-MS/MS) LCMS grade water, methanol, isopropanol and acetic acid were purchased from Fisher Scientific. All lipids were separated by headgroup class with a Waters XBridge Amide column (2.5 μm, 3 mm X 100 mm) on a LD40 X3 UHPLC (Shimadzu) using a 9 min binary gradient from 5% 12 mM ammonium acetate in water pH 7.5 in acetonitrile to 50% 12 mM ammonium acetate in water pH 7.5 in acetonitrile. In our method, all lipids were detected in negative polarity on a 7500 QTrap mass spectrometer (AB Sciex Pte. Ltd.) using a multiple reaction monitoring (MRM) strategy based on the hydride [M-1]- parent ion (or the dihydride [M-2H]-2 for cardiolipin) and a daughter fatty acid ion for each lipid target. For diacyl PLs, the higher mass fatty acid ion was used when the fatty acids were not equivalent. For cardiolipin, lipid/fatty acid target pairs were calculated so that for each isobaric pool of cardiolipins with the same total number of acyl carbons and degrees of unsaturation, a signal was prepared for each potential fatty acid that could occupy a position in the molecule. Thus, the acyl content for each isobaric pool of cardiolipins could be measured but individual, isomerically pure cardiolipin species could not be quantified with confidence. PL classes present in E. coli were determined based on a consensus of reports in the literature. The classes that we targeted include PE, PG, CL, LPE, LPG, and free fatty acids (FA). Theoretical MRMs were first constructed for each lipid class for all possible combinations of fatty acids measured previously in E. coli via fatty acid methyl-ester (FAMES) analysis or suggested by previous untargeted lipidomic profiling. Based on those previous reports our list included FA12:0, FA14:0, FA14:1, FA15:0, FA16:0, FA16:1, FA17:0, FAcy17:0, FA18:0, FA18:1, FA19:0, FAcy19:0 and FA20:0. It should be noted that a similar method was developed by Berezhonoy et. al. (2022), but the details of the method were not made available and the CL series was not included. The theoretical method including all possible acyl chain combinations was tested by injection of a method development mixed sample featuring portions of all strains examined here. MRM presence was initially assessed without scheduling to establish adequate retention time windows for each lipid class. Due to retention time coelution between PGs and CLs, certain candidate CL signals could not be resolved from potential isotope interference with PG signals. Likewise, all PG signals could not be fully isolated from CL in-source degradation. Mixed signals that could originate from either PG or CL were maintained in both the CL and PG series. If conclusions from method use relied on individual lipid signals and not class-wide behavior, it would have been essential to cross check signals for potential lack of specificity. Cardiolipin distribution was compared to results described in previous reports to ensure consistency with the expected hierarchy in E. coli. Following test injections, the theoretical method was refined to include only targets with a signal to noise ratio greater than 3, and retention time scheduling was implemented to maximize sensitivity and datapoints per peak (see Table S1). Lipidomics LC-MS/MS data processing All signals were integrated using SciexOS 3.1 (AB Sciex Pte. Ltd.). Signals with >50% missing values were discarded and remaining missing values were replaced with the lowest registered signal value. Signals with an average intensity, after total sum normalization, across the dataset below 30,000 counts were excluded. Signals with a Quality Control (QC) coefficient of variance >30% were discarded.
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2025-12-03
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