Phosphoinositides
(PIPx) play central roles in membrane dynamics
and signal transduction of key functions like cellular growth, proliferation,
differentiation, migration, and adhesion. They are highly regulated
through a network of distinct phosphatidylinositol phosphates consisting
of seven groups and three regioisomers in two groups (PIP and PIP2),
which arise from phosphorylation at 3′, 4′, and 5′
positions of the inositol ring. Numerous studies have revealed the
importance of both fatty acyl chains, degree of phosphorylation, and
phosphorylation positions under physiological and pathological states.
However, a comprehensive analytical method that allows differentiation
of all regioisomeric forms with different acyl side chains and degrees
of phosphorylation is still lacking. Here, we present an integrated
comprehensive workflow of PIPx analysis utilizing a chiral polysaccharide
stationary phase coupled with electrospray ionization high-resolution
mass spectrometry with a data independent acquisition technique using
the SWATH technology. Correspondingly, a targeted data mining strategy
in the untargeted comprehensively acquired MS and MS/MS data was developed.
This powerful highly selective method gives a full picture of PIPx
profiles in biological samples. Herein, we present for the first time
the full PIPx profiles of NIST SRM1950 plasma, Pichia pastoris lipid extract, and HeLa cell extract, including profile changes
upon treatment with potential PI3K inhibitor wortmannin. We also illustrate
using this inhibitor that measurements of the PIPx profile averaged
over the distinct regioisomers by analytical procedures, which cannot
differentiate between the individual PIPx isomers, can easily lead
to biased conclusions.
Fatty acyl-coenzyme
As (acyl-CoAs) are of central importance in
lipid metabolism pathways. Short-chain acyl-CoAs are usually part
of metabolomics, and medium- to (very) long-chain acyl-CoAs are focus
of lipidomics studies. However, owing to the specific complex and
amphiphilic nature contributed by fatty acyl chains and hydrophilic
CoA moiety, lipidomic analysis of acyl-CoAs is still challenging,
especially in terms of sample preparation and chromatographic coverage.
In this work, we propose a derivatization strategy of acyl-CoAs based
on phosphate methylation. After derivatization, full coverage (from
free CoA to C25:0-CoA) and good peak shape in liquid chromatography
were achieved. At the same time, analyte loss due to the high affinity
of phosphate groups to glass and metallic surfaces was resolved, which
is beneficial for routine analysis in large-scale lipidomics studies.
A sample preparation method based on mixed-mode SPE was developed
to optimize extraction recoveries and allow optimal integration of
the derivatization process in the analytical workflow. LC-MS/MS was
performed with targeted data acquisition by SRM transitions, which
were constructed based on similar fragmentation rules observed for
all methylated acyl-CoAs. To achieve accurate quantification, uniformly 13C-labeled metabolite extract from yeast cells was taken as
internal standards. Odd-chain and stable isotope-labeled acyl-CoAs
were used as surrogate calibrants in the same matrix. LOQs were between
16.9 nM (short-chain acyl-CoAs) and 4.2 nM (very-long-chain acyl-CoAs).
This method was validated in cultured cells and was applied in HeLa
cells and human platelets of coronary artery disease patients. It
revealed distinct acyl-CoA profiles in HeLa cells and platelets. The
results showed that this method can effectively detect acyl-CoAs in
biological samples. Considering their central importance in many de novo lipid biosynthesis and remodeling processes, this
targeted method offers a valid foundation for future lipidomics analysis
of acyl-CoA profiles in biological samples, particularly those concerning
metabolic syndrome.
Inositol and inositol phosphates (IPx) are central metabolites. Their accurate quantitative analysis in complex biological samples is challenging due to lengthy sample preparation procedures, sample losses by strong adsorption to surfaces, and unpredictable matrix effects. Currently, U 13 C-inositol and U 13 C-IPx are not available from commercial sources. In this study, we developed a method that is capable of generating U 13 C-inositol and U 13 C-IPx. An inositol-independent cell line L929S was cultured in inositol-free medium supplemented with U 13 C-glucose. Inositol contamination in FBS was observed as the critical parameter for labeling efficiency (LE). A balance between cell growth and LE was achieved by adopting a two-step labeling strategy. In the first step, a LE of 90% could be obtained by normal cell growth in the long-term. Cells were then cultured in a second step in ultralabeling medium for improved LE for a short duration before harvesting. The generated U 13 Canalogs were of high isotopic purity (>99%). Utilized as internal standards spiked before sample preparation in biological applications, U 13 Canalogs can effectively compensate sample loss during sample preparation as well as the matrix effect during electrospray ionization. An exemplary pharmacological study was conducted with phospholipase C inhibitor and activator to document the great utility of the prepared stable isotope-labeled internal standards in elucidating the PLC-dependent IP code. U 13 CIPx are used as internal standards to generate quantitative profiles of IPx in HeLa cell samples after treatment with PLC inhibitor and activator. This established method generating U 13 Canalogs is cost-effective, robust, and reproducible, which can facilitate quantitative studies of inositol and IPx in biological scenarios.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.