Martin Jakubec1, Espen Bariås1, Fedor Kryuchkov2, Linda Veka Hjørnevik1, Øyvind Halskau1. 1. Faculty of Mathematics and Natural Sciences, Department of Biological Sciences, University of Bergen, PB 7803, Bergen NO 5020, Norway. 2. Faculty of Veterinary and Biosciences, Norwegian University of Life Sciences, Ullevålsveien 68, Oslo, Akershus NO 0033, Norway.
Abstract
Global lipid analysis still lags behind proteomics with respect to the availability of databases, experimental protocols, and specialized software. Determining the lipidome of cellular model systems in common use is of particular importance, especially when research questions involve lipids directly. In Parkinson's disease research, there is a growing awareness for the role of the biological membrane, where individual lipids may contribute to provoking α-synuclein oligomerisation and fibrillation. We present an analysis of the whole cell and plasma membrane lipid isolates of a neuroblastoma cell line, SH-SY5Y, a commonly used model system for research on this and other neurodegenerative diseases. We have used two complementary lipidomics methods. The relative quantities of PC, PE, SMs, CL, PI, PG, and PS were determined by 31P NMR. Fatty acid chain composition and their relative abundances within each phospholipid group were evaluated by liquid chromatography-tandem mass spectrometry. For this part of the analysis, we have developed and made available a set of Matlab scripts, LipMat. Our approach allowed us to observe several deviations of lipid abundances when compared to published reports regarding phospholipid analysis of cell cultures or brain matter. The most striking was the high abundance of PC (54.7 ± 1.9%) and low abundance of PE (17.8 ± 4.8%) and SMs (2.7 ± 1.2%). In addition, the observed abundance of PS was smaller than expected (4.7 ± 2.7%), similar to the observed abundance of PG (4.5 ± 1.8%). The observed fatty acid chain distribution was similar to the whole brain content with some notable differences: a higher abundance of 16:1 PC FA (17.4 ± 3.4% in PC whole cell content), lower abundance of 22:6 PE FA (15.9 ± 2.2% in plasma membrane fraction), and a complete lack of 22:6 PS FA.
Global lipid analysis still lags behind proteomics with respect to the availability of databases, experimental protocols, and specialized software. Determining the lipidome of cellular model systems in common use is of particular importance, especially when research questions involve lipids directly. In Parkinson's disease research, there is a growing awareness for the role of the biological membrane, where individual lipids may contribute to provoking α-synuclein oligomerisation and fibrillation. We present an analysis of the whole cell and plasma membrane lipid isolates of a neuroblastoma cell line, SH-SY5Y, a commonly used model system for research on this and other neurodegenerative diseases. We have used two complementary lipidomics methods. The relative quantities of PC, PE, SMs, CL, PI, PG, and PS were determined by 31P NMR. Fatty acid chain composition and their relative abundances within each phospholipid group were evaluated by liquid chromatography-tandem mass spectrometry. For this part of the analysis, we have developed and made available a set of Matlab scripts, LipMat. Our approach allowed us to observe several deviations of lipid abundances when compared to published reports regarding phospholipid analysis of cell cultures or brain matter. The most striking was the high abundance of PC (54.7 ± 1.9%) and low abundance of PE (17.8 ± 4.8%) and SMs (2.7 ± 1.2%). In addition, the observed abundance of PS was smaller than expected (4.7 ± 2.7%), similar to the observed abundance of PG (4.5 ± 1.8%). The observed fatty acid chain distribution was similar to the whole brain content with some notable differences: a higher abundance of 16:1 PC FA (17.4 ± 3.4% in PC whole cell content), lower abundance of 22:6 PE FA (15.9 ± 2.2% in plasma membrane fraction), and a complete lack of 22:6 PS FA.
Lipids play a critical role in many cell
processes including regulation of transcription,[1] protein and metabolites distribution,[2] energy metabolism,[3] cell apoptosis
induction,[4] and protein folding and misfolding.[5,6] However, in many cases, we still lack basic knowledge of the cell
lipid composition, and how it varies as a function of the subcellular
compartment or cell state. This deficiency is in part caused by the
great diversity displayed by lipid species in cells. The combination
of headgroups and fatty acid chains (FA), each with different lengths
and levels of saturation, give rise to thousands of possible lipid
species in the phospholipid class alone. The analytical problem is
exacerbated when accurate quantitative data is also sought.[7,8]The lipidomic gap in knowledge is evident for the neuroblastoma
cell line SH-SY5Y. This cell line is of human origin, catecholaminergic,
easy to maintain, and reported to be differentiable into a neuron,
like a phenotype.[9] These properties have
led SH-SY5Y to be the cellular model of choice when studying neurodegenerative
diseases like Alzheimer’s disease, amyotrophic lateral sclerosis,
and, in particular, Parkinson’s disease (PD).[9,10] Lipids are implicated in all these diseases,[11,12] and for PD, this connection is particularly strong.[13] α-Synuclein, a key protein of PD pathology, is thought
to be a regulator of vesicle recycling in presynaptic terminals through
reversibly contacting the lipid membrane in a carefully timed fashion.[14] Moreover, its misfolding is influenced by particular
lipids and the physical state of the membrane, which in turn affects
its rate of oligomerization.[15] Given the
diverse and robust evidence for the role of lipids in α-Synuclein
pathology, it is then disconcerting to realize that lipid the composition
of one of the vital cell models used in PD research, SH-SY5Y, is still
not yet known in detail.We, therefore, focus on the determination
of the phospholipid content of the whole cell and plasma membrane
(PM)-enriched SH-SY5Y cell isolates. First, we have determined the
abundance of individual phospholipid headgroups by 31P
NMR using approaches similar to those developed by Bosco et al.[16] Then, we have determined the FA composition
of individual lipid headgroups by LC–MS/MS with an iterative
exclusion technique.[7] By this method, we
have generated large amounts of data, which is required to be processed
on a batch-to-batch basis. To achieve this in an expedient and informative
way, we have automated the approach for liquid chromatography–tandem
mass spectrometry (LC–MS/MS) by developing a script in Matlab.
This script, designated as LipMat, is able to (i) build libraries
of predicted lipid fragmentations based on information collected from
the literature and based on user input, (ii) find possible lipid species
by comparing intact m/z values and
by scoring MS2 fragments, and (iii) do semiquantitative FA abundance
analysis from MS1 spectra chromatograms.
Results and Discussion
It has been shown that the phospholipid
composition in the eukaryotic cell is highly variable. It differs
between organisms and cell types or between healthy and diseased states
of a cell.[17−21] The current state of knowledge regarding the lipidome of eukaryotic
cells starts to be insufficient when specific cell types are considered
and is often completely absent in many cases. Recent reports concerning
the importance of phospholipids in the development and progress of
PD[22−25] has led to our current goal: to perform a mutually supportive NMR
and LC–MS/MS phospholipid analysis of a cell model system commonly
used in PD research, the SH-SY5Yneuroblastoma cell line.The
phospholipid content of the whole cell was isolated using a method
we have previously established.[26] For PM
isolation, we have employed a modified method of sucrose gradient
separation[27,28] (Figure S1). Upon assessing the purity of the PM fraction using Western blot,
we observed contamination of calnexin (a marker for the endoplasmic
reticulum[29,30]). However, there was a much lower presence
of β-actin (cytoskeletal marker[31]) and almost no nucleophosmin (nuclear marker;[32]Figure S2). We therefore concluded
that our approach provided us with PM-enriched samples.We then
used 31P NMR to analyze the phospholipid content of whole
cell SH-SY5Ylipid isolates (Figure ). To ensure consistency of measurement, we have used
the CUBO solvent (named after the primary authors of the original
work, Culeddu and Bosco) for all solution NMR experiments. The CUBO
solvent is a ternary mixture of dimethylformamide, trimethylamine,
and guanidine hydrochloride, and it has a well-documented good chemical
shift reproducibility and chemical stability for work with phospholipids.[33−36]
Figure 1
31P NMR phospholipid analysis of SH-SY5Y whole cell and plasma
membrane lipid isolates. (A) Example of lipid assignment after deconvolution
of spectra. The highest abundant lipid, PC, is used for axis calibration,
and it is set to 0 ppm. (B) Abundance of identified phospholipids
in the whole cell isolates (blue) and PM isolate (red) of SH-SY5Y.
For plasma PM samples, we have only observed the three most abundant
lipid species (PC, PE, and SMs). This was caused by the low sample
mass used for analysis.
31P NMR phospholipid analysis of SH-SY5Y whole cell and plasma
membrane lipid isolates. (A) Example of lipid assignment after deconvolution
of spectra. The highest abundant lipid, PC, is used for axis calibration,
and it is set to 0 ppm. (B) Abundance of identified phospholipids
in the whole cell isolates (blue) and PM isolate (red) of SH-SY5Y.
For plasma PM samples, we have only observed the three most abundant
lipid species (PC, PE, and SMs). This was caused by the low sample
mass used for analysis.In accordance with other studies, the most abundant
phospholipid was PC. However, the abundance was higher than that reported
for human erythrocytes (∼30%)[20] or
yeast (∼15%).[37] With 54.7 ±
1.9% of total abundance, PC is by far the most common phospholipid
in SH-SY5Y. This is also in agreement with lipidomics analysis of
human plasma where PC showed up as the most abundant phospholipid.
However, this study did not further explore the FA profiles of lipid
species quantified.[8] We have observed some
difference in the fraction of PE and PS when we compare the SH-SY5Y
cell to brain matter. For whole brain extracts, the reported content
of PE and PS is ∼30% of brain phospholipids,[38−42] yet for SH-SY5Y, the amount of PE and PS is 17.8
± 4.8 and 4.7 ± 2.6%, respectively. Another interesting
result is the relatively low abundance of SMs (2.7 ± 1.2%) when
compared to CL (8.0 ± 1.4%). The only source of CL in the eukaryotic
cell is the mitochondria, while almost all of the SMs is present only
in the PM. This suggests that SH-SY5Y is especially energetically
active. Moreover, based on the amount of SMs, SH-SY5Y appears to have
a lower PM surface than differentiated neurons in vivo, as the only
source of SMs in cells is PM. Both of these observations reflect the
carcinogenic properties of the nondifferentiated SH-SY5Y cell line.We also strived to secure PM-specific quantitative data using NMR.
However, after PM isolation from the SH-SY5Y cell, we did not obtain
sufficient quantities of lipids for a complete 31P NMR
analysis. We have observed just three of the most abundant phospholipids
in the PM-enriched fraction: PC, PE, and SMs. Although not complete
with respect to minor lipid species, they suggest that almost all
SMs in SH-SY5Y is localized in the PM. It is also apparent and not
unexpected that 31P NMR, although potentially straightforward
and informative, suffers from lack of sensitivity when little material
is available. In our case, working with samples containing ∼30
μg of lipids on a modern 600 MHz instrument fitted with a cryogenically
cooled probe did not detect lipid species of low relative abundance.
Increasing the number of scans did not seem to affect this, suggesting
that the weakest resonances were not detectable at any receiver gain
setting.The detection limit of mass spectrometry is significantly
lower than that of NMR,[43] and we therefore
proceeded with LC–MS/MS analysis of the FA chains of all phospholipids
identified by 31P NMR. Prior to the main experiments, the
liquid chromatography conditions were optimized to obtain the elution
of phospholipid as narrow peaks. We used an iterative exclusion protocol[7] to filter out abundant ions as well as background
signals. Our custom-built LipMat script written in Matlab was then
used for further processing (Figure ).
Figure 2
Schematic of LipMat processing. For file preparation,
MS convert can be used to convert the raw file into mzxml.[57] LipMat can further process mzxml files by extracting
MS2 and MS1 spectra. The lipid fragmentation library is generated
using the user input specifying the length of FA chains and number
of double bonds. The analysis starts with comparing intact ion masses
with the library. In the case of a hit, the MS2 spectrum is loaded
and scored based on the presence of corresponding lipid fragments
and their intensity. Afterward, retention time is analyzed, and the
MS1 spectrum is searched for the elution peak of assigned lipid species.
Generated outputs include lipid fragmentation figures, chromatogram
plots, and table output with identified lipid species and their respective
scoring.
Schematic of LipMat processing. For file preparation,
MS convert can be used to convert the raw file into mzxml.[57] LipMat can further process mzxml files by extracting
MS2 and MS1 spectra. The lipid fragmentation library is generated
using the user input specifying the length of FA chains and number
of double bonds. The analysis starts with comparing intact ion masses
with the library. In the case of a hit, the MS2 spectrum is loaded
and scored based on the presence of corresponding lipid fragments
and their intensity. Afterward, retention time is analyzed, and the
MS1 spectrum is searched for the elution peak of assigned lipid species.
Generated outputs include lipid fragmentation figures, chromatogram
plots, and table output with identified lipid species and their respective
scoring.The LipMat identifies the presence of individual
lipids by comparing MS2 fragmentation spectra with the literature
and in silico prediction (see the Experimental Section for more information and Figure S3).
The lipid species deemed robustly detected by using a scoring function
(sum of eqs and 2; Experimental Section) were
then selected for MS1 search of the intact lipid m/z (Table S2). Because
of the high overlap of m/z in different
lipid species, only the area of retention time, where the lipid species
was identified, was searched in this way. An additional retention
offset of 1 min was added, so it would be possible to observe complete
elution of a given peak. This leads to a reconstruction of chromatograms
(Figure S4) for the elution of individual
lipid species and to relative quantification of FA within each headgroup
(Figure S5).Using a combination
of 31P NMR and the LC–MS/MS method described herein,
we have successfully identified phospholipid abundances as well as
the FA chain composition for whole cell isolates (Figure ) and plasma membrane-enriched
samples (Figure ).
The most abundant lipid, PC, was well ionized, and we had a low detection
limit for positive mode MS runs. The diversity of PC FAs was low,
as almost 75% of all PClipids in the SH-SY5Y cell are composed of
two of the four FA chains (18:1, 16:0, 16:1, 18:0, or 14:0). Similar
observations were also made for the PM-enriched isolate where 16:0
FAs were particularly abundant. We also noted that the 16:1 PC FA
chain (17.4 ± 3.4% in the whole cell sample) deviates from other
reports of brain composition, where 16:1 FA accounts for fewer than
3% of the PC content.[38,44,45]
Figure 3
Analysis
of headgroup abundance and fatty acid distribution in the whole cell
lipid isolate of SH-SY5Y. The pie plot represents phospholipid abundance
of lipid headgroups as measured by 31P NMR. The text around
represents lipid species identified by LC–MS/MS. Bar plots
for PC, PE, and PI represent individual FA abundance within each headgroup
as evaluated by the LipMat script. Only lipid species with Stotal > 30 were taken into account. For the
rest of the lipid headgroups (PS, PG, SM, and CL), we were unable
to identify relative FA chain abundance.
Figure 4
Analysis of headgroup abundance and fatty acid distribution
of the PM lipid fraction of SH-SY5Y. The pie plot represents phospholipid
abundance of lipid headgroups as measured by 31P NMR. The
text around represents lipid species identified by LC–MS/MS.
Bar plots for PC and PE represent individual FA abundance within each
headgroup as evaluated by the LipMat script. Only lipid species with Stotal > 30 were taken into account. For SMs,
we were unable to identify relative FA chain abundance.
Analysis
of headgroup abundance and fatty acid distribution in the whole cell
lipid isolate of SH-SY5Y. The pie plot represents phospholipid abundance
of lipid headgroups as measured by 31P NMR. The text around
represents lipid species identified by LC–MS/MS. Bar plots
for PC, PE, and PI represent individual FA abundance within each headgroup
as evaluated by the LipMat script. Only lipid species with Stotal > 30 were taken into account. For the
rest of the lipid headgroups (PS, PG, SM, and CL), we were unable
to identify relative FA chain abundance.Analysis of headgroup abundance and fatty acid distribution
of the PM lipid fraction of SH-SY5Y. The pie plot represents phospholipid
abundance of lipid headgroups as measured by 31P NMR. The
text around represents lipid species identified by LC–MS/MS.
Bar plots for PC and PE represent individual FA abundance within each
headgroup as evaluated by the LipMat script. Only lipid species with Stotal > 30 were taken into account. For SMs,
we were unable to identify relative FA chain abundance.SMs was the second most abundant lipid detected
in the positive mode. Even at lower concentrations, we could observe
a diverse array of SMs hits. However, we were unable to identify the
exact SMsFA acid composition because most observed SMlipid species
lacked FA-specific fragments. The two lipid species that could be
identified were SM d18:1/24:1 and SM d18:1/24:0, and these were both
observed in whole cell and PM fraction samples.In the whole
cell samples, all the PE FA chains were 18:1, 18:0, or 16:0. However,
in the PM-enriched samples, we observed a higher variability of different
PE species (Figure ) and disproportional FA lengths. One PE FA had a length of 18:0,
while others were composed of long unsaturated chains (22:6, 20:4,
or 20:1).The PG lipid abundance was too low to perform FA distribution
analysis. However, four FA chains were identified repeatedly within
the PG lipid headgroup (16:0, 18:1, 20:3, and 20:4). Both PI and PS
were much worse ionizers, and we therefore detected only a few lipid
species from each headgroup repeatedly, namely, PI 18:0/20:4, PI 18:0/20:3,
and PS 18:0/18:1. However, we did not identify any docosahexaenoic
acid FA (22:6) in the whole cell sample regardless of the fact that
this FA is reported in high abundance (>25%) of brain matter for
both PS and PE.[38,44,45] Yet, PE 22:6 was present in the PM sample with an abundance of 15.9
± 2.2%. This suggests that all 22:6 PE FAs are located in the
plasma membrane and that the presence of this FA was masked by other
more abundant PE FAs in the whole cell samples. This underscores the
importance of sample fractionation in order to provide a complete
and reliable picture of the cell lipidome.
Conclusions
We have analyzed the phospholipid composition
of SH-SY5Y cells by NMR and LC–MS/MS using the customizable
and highly flexible LipMat script for Matlab software. Compared to
the phospholipid composition of the brain, there exist notable differences,
which should be taken into account when SH-SY5Y is used as a model
for studying neurodegeneration or brain lipid metabolism. The most
striking differences are a relatively low abundance of PE and PS,
higher occurrence of 16:1 PC FA, and missing 22:6 FA for PS.
Experimental Section
Reagents and Chemicals
Lipids were purchased from Avanti
Polar Lipids Inc. (Alabaster, Alamaba, US). These were all used without
further purification. The following primary antibodies were used:
β-actin (AC-15) and Na+/K+ ATPase α
(H-3) from Santa Cruz Biotechnology (Texas, USA), nucleophosmin (FC-61991)
from Thermo Fisher Scientific (Massachusetts, USA), and calnexin from
Abcam (Cambridge, UK). Lipase inhibitors (FIDI, U73122, and D609)
were acquired from Tocris Bioscience Ltd. (Bristol Somerset, UK).
Growth medium, solvents, and fine chemicals were purchased from Sigma
Aldrich (Germany) and used as described in the separate experimental
sections, vide infra.
SH-SY5Y Cultivation
SH-SY5Y cells (a generous gift
from Prof. Kari Fladmark) were cultured in Dulbecco’s modified
Eagle’s medium with high glucose supplemented with 10% fetal
bovine serum and 1% penicillin–streptomycin in a humidified
atmosphere at 310 K and 5% CO2.
Whole Cell Lipid Extraction
Whole cell lipid extraction
was performed based on a modified version of a previously published
method.[26] An overview of whole cell lipid
sample preparation and plasma membrane isolation is provided in Supplementary Figure S1. Briefly, SH-SY5Y cells were harvested
into phosphate-buffered saline (PBS) and pelleted by centrifugation
(900g, 5 min, and 277 K). The supernatant was removed,
and the pellet resuspended using 1 mL of PBS. To this, 330 μL
of guanidine chloride and thiourea mix (3:0.75 molar ratio) was added,
and the final mixture was vortexed and stored at 193 K until further
use. The frozen material was freeze-dried and stored at 253 K until
lipid extraction. For the extraction, the powdered material was resuspended
in an organic extraction mixture (3:1 dichloromethane/methanol with
0.5 mg/mL triethylammonium chloride (TEAC)). Milli-Q water was added
(1:1 by volume), and the mixture was transferred into a separating
funnel where it was diluted with methanol until a monophasic solution
was formed. The solution was agitated briefly and made biphasic again
by the addition of more dichloromethane. The denser organic phase
was collected using a separating funnel. The water fraction was washed
three more times with dichloromethane. Collected organic fractions
were pooled and concentrated in vacuo and stored in the form of a
dry lipid layer under nitrogen in the dark at 253 K until analysis.
Plasma Membrane-Enriched Lipid Sample Preparation
The
protocol used in this study was modified from two existing protocols.[27,28] Cells from 5 × 150 mm plates were harvested by trypsinization,
pelleted and washed twice with ice-cold PBS, and centrifuged (900g, 4 min, and 277 K). Hypotonic buffer (2 mL, 10 mM Tris,
and pH 7.8) with FUD (0.1 mL of a concentrated stock of F191 (200
μM), U73122 (1 mM), and D609 (1.5 mM) in a solution of DMSO/water
(1:9)) was layered over the cell pellet and removed immediately. The
cell pellet was then resuspended using 6 mL of hypotonic buffer and
rested on ice for 4 min. After the incubation, 15 mL of H2O was mixed into the suspension. The resulting cell suspension was
subsequently incubated for 3 min on ice before the cells were passed
through a hypodermic syringe 12 times and afterward centrifuged (1000g, 1 min, and 277 K). The pellet was washed with washing
buffer (10 mM Tris, pH 7.5, 2.5 mM MgCl2, 2.5 mM CaCl2, 10 mM NaCl, and FUD) and centrifuged (1000g, 1 min, and 277 K). The supernatants from the two centrifugation
steps were pooled and diluted with hypotonic buffer. The plasma membrane
was isolated by loading the homogenate onto a sucrose gradient consisting
of 30% (w/v) and 45% (w/v) sucrose solutions and centrifuged (3270g, 30 min, and 277 K). The PM-enriched fraction was collected
and diluted with hypotonic buffer and centrifuged (3270g, 20 min, and 277 K). The pellet was resuspended in 500 μL
of GTCU (6 M guanidinium chloride/1.5 M thiourea). The resuspension
was freeze-dried within the same day, and the resulting material was
then stored at 253 K until lipid extraction could be performed using
the same approach as for the whole cell samples.
Western Blot Analysis
Samples collected from PM isolations
were resuspended in 1X RIPA buffer (150 mM NaCl, 5 mM EDTA, 1% NP-40,
0.5% sodium deoxycholate, 0.1% SDS, 50 mM Tris, and pH 8.0), sonicated,
and centrifuged (17,000g, 5 min, and 277 K). The
total protein concentration was measured using a standard BCA assay,[46] and the protein composition of the samples was
analyzed using 10% SDS-polyacrylamide gels and subsequently transferred
to a nitrocellulose membrane. The membrane was blocked for 1 h with
7% dry milk in PBS with Tween-20 (0.05%, v/v) and incubated overnight
at 277 K with primary antibodies to Na+/K+ ATPase
(1:5000), nucleophosmin (1:10000), calnexin (1:1000), and β-actin
(1:1000). The primary antibodies were detected using HRP-conjugated
secondary antibodies (1:10000, 1 h, and 293 K). Protein bands were
visualized using the SuperSignal West Femto Maximum Sensitivity Substrate
(Thermo Fisher, USA), and images were collected with a Molecular Imager
ChemiDoc XRS + imaging system and the ImageLab software version 3.0
(Bio-Rad, USA).
Solution-Phase 31P NMR
Dried lipid films
were dissolved in the Culeddu-Bosco “CUBO” solvent system.[16] Data acquisition was similar to our previously
published work[26] using a Bruker BioSpin
NEO600 spectrometer equipped with a cryogenic probe operating at 300
K for all data. 31P spectra were acquired at 242.93 MHz
using inverse-gated proton decoupling with 3072 scans per sample and
a spectral width of 54.16 ppm. An overall recovery delay of 8 s was
used, a setting that ensured full relaxation of the 31P
nuclei between scans. Data were processed using an exponential line
broadening window function of 1.0 Hz prior to Fourier transform followed
by manual phase correction and automatic baseline correction. The
spectra were calibrated by setting the most abundant phospholipid
signal in the sample, phosphatidylcholine (PC), to 0 ppm. All peaks
were then deconvoluted. The peak assignment to individual phospholipids
was done according to a previously published work.[26,33,47] The analyses were done using TopSpin 4.0.1.
A total of four independent whole cell sample and three plasma membrane
sample 31P spectra were collected.
LC–MS/MS Experimental Setup
Accurate mass LC–MS
and MS/MS was performed on a Thermo Q-Exactive mass spectrometer and
a Dionex Ultimate 3000 UPLC (Thermo Fisher, USA). Dry lipid mixtures
from the whole cell and PM-enriched extractions were dissolved in
a mixture of water, dichloromethane, and acetonitrile (2:2:1) with
10 mM ammonium acetate. The analytes were then separated on a UPLC
C18 column (1.7 μm particle size, Waters, USA) at 318 K at a
rate of 0.4 mL/min; an injection volume of 20 μL was used. Mobile
phase A consisted of 40% acetonitrile and 60% water, mobile phase
B consisted of 10% acetonitrile and 90% isopropanol, and both phases
were supplemented with 10 mM ammonium acetate. Lipid separation was
then achieved using a multistep gradient from 40 to 100% of solvent
B in 17 min (full gradient provided in Table S1).Ions were monitored both in positive and negative Full MS/data-dependent
Top 5 mode. The full MS scan range was 300–2000 m/z with a resolution of 140,000 at m/z = 200. Data-dependent peaks were fragmented using
a normalized collision energy of 24, and the resulting MS2 spectrum
was collected with a resolution of 17,500 at m/z = 200, an isolation window of 0.4 m/z, and the dynamic exclusion parameter set to “auto”.
Each run was repeated three times for each mode using dynamic exclusion
of previously analyzed ions.[7] Three biologically
independent samples of SH-SY5Y whole cell samples were analyzed three
times for each mode (positive or negative), that is, 18 LC–MS/MS
runs in total. The PM has been analyzed with just two iterative exclusions,
a total of 12 LC–MS/MS runs.
Lipid Analysis by LipMat Scripts
For MS/MS analysis,
we have built highly flexible customizable scripts using Matlab 2017b
software. LipMat script was tested on Avanti Lipid MAPS standards:
12:0-13:0 PC, 17:0-14:1 PC, 17:1 LPC, 12:0-13:0 PE, 17:0-14:1 PE,
17:0-20:4 PE, 12:0-13:0 PG, 12:0-13:0 PI, 17:0-14:1 PI, 17:0-20:4
PI, 12:0-13:0 PS, 17:0-14:1 PS, 17:0-20:4 PS, and cardiolipin mix
1. The LipMat script and fragmentation patterns of Avanti standards
are freely available on GitHub: https://github.com/MarJakubec/LipMat.
Lipid Fragmentation Libraries
We have searched the
literature for experimental[48−54] and theoretical[55,56] lipid fragmentation patterns
of the phospholipid groups identified by 31P NMR. These
were phosphatidylcholine (PC), phosphoethanolamine (PE), phosphatidylinositol
(PI), phosphoglycerol (PG), phosphatidylserine (PS), sphingomyelin
(SMs), and cardiolipin (CL). For positive ion mode and all mentioned
lipids (M), except CL, we have included adducts of alkali metals [M
+ Met]+, where Met = Na+, K+, or Li+, or nonmetal adducts [M + Non]+ , where Non = H+, NH4+, or TEAC. For negative mode, we have included
[M + Neg]– adducts, where Neg is loss of H+, and
gain of Cl–, CHCOO–, and CH3COO–. CLs have a double negative charge,
which leads to the formation of different adducts: [CL + H+]+, [CL + Met]+, [CL – H+ + 2Met]+, and [CL –
2H+ + 3Met]+ for the positive mode and [CL – H+]–, [CL – 2H+ + Met]–, and
[CL – 2H+]2– for the negative mode.
Peak and Intensity Scoring
The precursor m/z values are compared with the intact masses of
adducts from the libraries. For each instance where a hit is found,
the script proceeds with a peak (Speak) and intensity (SIntesity) scoring for
each hit. The total score (Stotal) is
the sum of the negative log of Speak and
the negative log of Sintensity. The peak
score (Speak) provides the largest sum
of the total hit score, and it composes of a hypergeometric distribution
(eq ) used previously
by other authors to describe mass spectrometric peak distributions.[55] This function reflects the probability that
any overlap of theoretical and experimental MS2 peaks is random.where x is
the number of hits, K is the number of theoretical
MS2 fragments, n is the number of observed MS2 fragments,
and M is the size of the scanning range divided into
bins, where the number of bins is the size of the scanning range divided
by the ppm error. The ppm error is set by the user, typically to 5
ppm.The second component of the final score is the intensity
score (eq ). This is
a minor part of the final score and reflects the intensity component
of identified peaks.[55] Experimental MS2
data and the number of identified peaks are used as the input for
this value. The same number of peaks is randomly selected from the
spectra, and if the total intensity of the resulting random spectra
is lower than the total intensity of identified peaks, then one point
is added to the intensity score ratio. The process is repeated for
all possible combinations of randomly generated spectra, and the ratio
is then used to calculate Sintensity.
However, to save computing power, if there are more than six identified
peaks in the spectra, then only 500 random combinations of peaks are
selected.where x is
the number of hits, k is the number of theoretical
MS2 fragments, n is the number of observed MS2 fragments,
and i is the intensity of the identified fragments
Construction of Lipid-Specific Elution Profiles
After
the identification of possible lipid compositions, the LipMat scripts
will start to scan the MS1 spectrum. First, it will filter out nondistinguishable
lipid species. These are lipid species with the same m/z ± a user-determined defined ppm error, which
are eluted in the same retention time ± user determined retention
time offset. These lipid species are written to the LipMat output
file and subject to manual checking by the expert user. From these
nondistinguishable species, only the ones with the highest score are
processed further.The area of each defined and distinguishable
lipid species in the MS1 spectra is then calculated. The abundance
of each unique FA is calculated as a sum of the area for each FA occurrence.
The MS1 chromatogram for up to five of the most abundant lipid species
associated with each headgroup category and bar plots for up to five
of the most abundant FA are plotted and written to the LipMat output
files.
Authors: W A Pedersen; W Fu; J N Keller; W R Markesbery; S Appel; R G Smith; E Kasarskis; M P Mattson Journal: Ann Neurol Date: 1998-11 Impact factor: 10.422
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