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ArticleComparative Metabolomics of Small Molecules SpecificallyExpressed in the Dorsal or Ventral Marginal Zones in
Vertebrate Gastrula
Yukako Suzuki 1 , Ryosuke Hayasaka 1,2 , Masako Hasebe 1 , Satsuki Ikeda 1 , Tomoyoshi Soga 1,2 ,Masaru Tomita 1,2 , Akiyoshi Hirayama 1,2 and Hiroki Kuroda 1,2, *1

2*

Citation: Suzuki, Y.; Hayasaka, R.;
Hasebe, M.; Ikeda, S.; Soga, T.;
Tomita, M.; Hirayama, A.; Kuroda, H.
Comparative Metabolomics of Small
Molecules Specifically Expressed in
the Dorsal or Ventral Marginal Zones
in Vertebrate Gastrula. Metabolites
2022, 12, 566. https://doi.org/
10.3390/metabo12060566
Academic Editors: Michal

Institute for Advanced Biosciences, Keio University, Tsuruoka 997-0052, Yamagata, Japan;
suzuki_yukako@keio.jp (Y.S.); ryosukeh@sfc.keio.ac.jp (R.H.); mhasebe@ttck.keio.ac.jp (M.H.);satsuki@ttck.keio.ac.jp (S.I.); soga@sfc.keio.ac.jp (T.S.); mt@sfc.keio.ac.jp (M.T.);
hirayama@ttck.keio.ac.jp (A.H.)
Systems Biology Program, Graduate School of Media and Governance, Keio University,
Fujisawa 252-0882, Kanagawa, Japan
Correspondence: hkuroda@sfc.keio.ac.jp; Tel.: +81-466-49-3404

Abstract: Many previous studies have reported the various proteins specifically secreted as inducers
in the dorsal or ventral regions in vertebrate gastrula. However, little is known about the effect oncell fate of small molecules below 1000 Da. We therefore tried to identify small molecules specifically expressed in the dorsal marginal zone (DMZ) or ventral marginal zone (VMZ) in vertebrate
gastrula. Small intracellular and secreted molecules were detected using explants and supernatantsamples. Hydrophilic metabolites were analyzed by capillary ion chromatography–mass spectrometry and liquid chromatography–mass spectrometry, and lipids were analyzed by supercritical fluid
chromatography–tandem mass spectrometry. In total, 190 hydrophilic metabolites and 396 lipids wereidentified. The DMZ was found to have high amounts of glycolysis- and glutathione metabolismrelated metabolites in explants, and the VMZ was richer in purine metabolism-related metabolites.
We also discovered some hydrophilic metabolites and lipids differentially contained in the DMZor VMZ. Our research would contribute to a deeper understanding of the cellular physiology that
regulates early embryogenesis.
Keywords: metabolomic analysis; Xenopus laevis; dorsal–ventral patterning; Spemann organizer;
early embryogenesis

Ciborowski, Joanna Godzien andStanislaw Deja
Received: 30 May 2022
Accepted: 17 June 2022
Published: 20 June 2022
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Copyright: © 2022 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms andconditions of the Creative Commons
Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

1. Introduction
In phylum Chordata, the spherical egg becomes a blastula stage (the embryo is calleda blastocyst at this stage in mammals), which contains many cells with pluripotency,
followed by gastrulation. Then, dynamic morphological changes in the entire embryo occur,
shaping the unique morphology of the species. To understand the early developmental
stages in phylum Chordata, the approach often chosen is to focus on three axes such asanterior–posterior, dorsal–ventral, and left–right directions and to elucidate the molecularmechanisms of each [1].
The African clawed frog (Xenopus laevis) is frequently used as an experimental modelorganism to elucidate the molecular mechanisms that control early development [2]. A
number of studies have used this experimental animal to focus on the anterior–posterior
and left–right axes, but many more studies have focused on the dorsal–ventral axis. In
this animal, during fertilization, the dorsal–ventral axis is determined by the rotation of
the surface layer starting from the point of sperm entry. The dorsal determinant, which
was present on the surface layer on the vegetal side of the egg, moves on microtubules
to the opposite side of the sperm entry point [3,4]. In other words, the dorsal–ventral

Metabolites 2022, 12, 566. https://doi.org/10.3390/metabo12060566

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Metabolites 2022, 12, 566

2 of 11axis is already determined at the one-cell stage. At the gastrula stage, part of the dorsal
region where the dorsal determinant was present gives rise to a region called the Spemannorganizer [5]. The Spemann organizer is a region that was first described by Spemann and
Mangold in 1924 [6]. They showed that when the dorsal region of an amphibian gastrula
embryo is transplanted to its opposite side, the ventral region, a secondary axis containing
neural tubes, notochord, and somites, is formed. This study provides the first evidence tosupport the idea that there is an induction center in early development that exerts a major
influence on developmental fate by acting on surrounding regions.
In the 1990s, many screening approaches comparing the genes expressed in the dorsal
and ventral regions in Xenopus laevis gastrula embryos (Xenopus gastrula) found moleculesthat are expressed and have organizer-specific induction activity in Spemann organizers.
For example, Nodal-related proteins are ligand molecules that bind to specific receptors.
In contrast, various antagonist molecules have been found such as Chordin, Noggin, andFollistatin, which are antagonists of bone morphogenetic proteins (BMPs); Frizzled-related
proteins, secreted Frizzled-related proteins (sFRPs), and Dickkopf, which are antagonistsof Wnts; and Lefty/Antivin, which is an antagonist of Nodal-related proteins [7–12]. In
addition to the above, many other molecules have been found to be expressed specificallyon the dorsal or ventral sides [2].
However, most of the molecules reported previously are peptide-based, and reportsof small molecules (<1000 Da) are extremely limited. However, protein is only one of
the five macronutrients, and non-peptide molecules are included in various hormonesand neurotransmitters in the adult body. Therefore, we assume that small non-peptidic
molecules are a non-negligible part of the early developmental stages because some small
molecules have been identified that have a significant effect on morphogenesis during
embryogenesis. For instance, serotonin (MW 176), expressed during the cleavage stage,is involved in the determination of the left–right axis [13]; retinoic acid (MW 300) andadrenaline (MW 183), expressed from gastrula to neurula, are required for posteriorization [14,15]; and γ-aminobutyric acid (GABA) (MW 103), expressed after neurula, has arole in embryonic elongation [16]. Research on metabolic activities via metabolomics inthe embryo holds great potential to raise our understanding of the developmental processes that control cell-type specification by combining with the other omics data obtainedby previous studies [17–19]. It is also significant to find dorsoventral-specific secreted
molecules, generally contained in the supernatant of cultured cells, and small moleculesthat determine cell-autonomous differentiation inside cells. In fact, some previous studies
using metabolomic analysis have reported metabolic activity differences between dorsal
and ventral cells in Xenopus embryos during the cleavage cycles [20–22]. However, to ourknowledge, there is no study focusing on Xenopus gastrula.
In this study, we therefore carried out metabolomic analyses to identify small molecules
specifically contained in the dorsal or ventral regions in vertebrate gastrula. To detectboth small molecules expressed in the dorsal marginal zone (DMZ), which includes thearea of the Spemann organizer, or expressed in the ventral marginal zone (VMZ) andsecreted from the DMZ or VMZ, capillary ion chromatography–mass spectrometry (capillary IC-MS), liquid chromatography–mass spectrometry (LC-MS), and supercritical fluid
chromatography–tandem mass spectrometry (SFC-QqQMS) were performed using two
types of samples: explants and supernatants. We found some dorsoventral-specific small
molecules in Xenopus gastrula.
2. Results
2.1. Analyses of Hydrophilic Metabolites
2.1.1. In Total, 186 and 98 Hydrophilic Metabolites Were Identified in Explants andSupernatants, Respectively
This study sought to identify the metabolites specifically contained in the DMZ or
VMZ in Xenopus gastrula. To detect them comprehensively, metabolomic analyses werecarried out using explants and supernatants. First, we performed a hydrophilic metabolome

2. Results
2.1. Analyses of Hydrophilic Metabolites
2.1.1. In Total, 186 and 98 Hydrophilic Metabolites Were Identified in Explants andSupernatants, Respectively
Metabolites 2022, 12, 566

This study sought to identify the metabolites specifically contained in the DMZ
3 ofor11
VMZ in Xenopus gastrula. To detect them comprehensively, metabolomic analyses werecarried out using explants and supernatants. First, we performed a hydrophilic metabo‐lomeanalysisby capillaryand LC‐MS,
resultingin the detectionof 186and 98 me‐
analysisby capillary
IC-MSIC‐MSand LC-MS,
resultingin the detectionof 186 and
98 metabolites
tabolitesin
explants
andsupernatants,
respectively.
Ofthese,
94
metabolites
were com‐in explants and supernatants, respectively. Of these, 94 metabolites were common
to
mon
to
both
samples.
Ninety‐two
metabolites,
including
amino
acids
such
as
both samples. Ninety-two metabolites, including amino acids such as His, Met,His,
Ser,Met,andSer, asandTrpasasdeoxynucleotides,
well as deoxynucleotides,
weretouniqueto explants.
In contrast,
four me‐Trp
wellwere uniqueexplants.
In contrast,
four metabolites
tabolites(2‐oxoadipic
acid,
diethanolamine,
hexylamine,andN‐acetylmuramic
acid)
were
(2-oxoadipic acid, diethanolamine, hexylamine, and N-acetylmuramic acid) were uniquetouniqueto supernatants.
Scatterof the 94 hydrophilicthat weresupernatants.
Scatter plotsof theplots
94 hydrophilic
metabolitesmetabolites
that were common
tocommonexplants
toand supernatants
showed correlationa significant
correlation
betweenthetwo typesof
andexplants
supernatants
showed a significant
betweenthe twotypes ofsamples(DMZ,
2 = 0.6421, p <2 0.001; VMZ, R2 = 0.6517, p < 0.001; Figure 1).
2
samples(DMZ,
R
R = 0.6421, p < 0.001; VMZ, R = 0.6517, p < 0.001; Figure 1).

Figure 1. Correlations of the hydrophilic metabolites in explants and supernatants.

2.1.2. The
The DMZ
DMZ andand thethe VMZVMZ Had,Had, Respectively,
Respectively, High2.1.2.
High Amounts
Amounts ofof GlycolysisGlycolysis‐ andandGlutathione Metabolism-Related Metabolites and Purine Metabolism-Related Metabolites
Glutathione
Metabolism‐Related
Metabolites
andPurineMetabolism‐Related
Metabo‐in Explants
lites in Explants
Next, we investigated the differences in the amounts of hydrophilic metabolites in the
we investigatedthe differencesin the ofamountsof hydrophilic
metabolites
in
DMZNext,
and VMZ
in each sample.
For the purpose
direct visualcomparison,
the z-score
theDMZ andVMZ
in each sample.
For thepurposecomparison,thez‐normalized
dataof hydrophilic
metabolites
in theDMZ ofanddirect
VMZvisualin the explants
(DMZ
and
score
normalized
dataofhydrophilic
metabolites
in
the
DMZ
and
VMZ
in
the
explants
VMZ explants) were analyzed by unsupervised principal component analysis (PCA). As a
(DMZ
VMZ andexplants)
analyzedby unsupervised
principal
component
analysis
result, andthe DMZVMZ weregroupswere separated
by principal
component
3 (Figure
2A).
(PCA).
Asaresult,
the
DMZ
and
VMZ
groupswere
separatedbyprincipal
component3
Hence, to discover the metabolites that have an influence on the differences in the DMZ(Figure2A).
Hence,
todiscoverthemetabolites
that
have
an
influenceonthedifferences
and VMZ explants, partial least squares-discriminant analysis (PLS-DA) was performed,
inthe
DMZ and
VMZ explants,
partial (VIP)
least squares‐discriminant
analysiswasandvariable
importancein projection
scores were calculated(Figure(PLS‐DA)
2B). Explants
performed,
andvariableinto
importanceprojection(VIP) scores
were calculated(Figure2B).
samples wereclassified
the DMZinand
VMZ groups
by hierarchicalclustering
analysis
Explants
samples
were
intobythe
DMZ
and(Figure
VMZ groups
hierarchicalcluster‐
(HCA)
using
the top
15classified
metabolites
VIP
scores2C). Ofbythesemetabolites,
2,3inganalysis (HCA)acid,using
the top 15 metabolitescadaverine,by VIP scores(Figure2C). Ofthese me‐diphosphoglyceric
5-methylthioadenosine,choline,fructose
6-phosphate,tabolites,
2,3‐diphosphoglyceric
acid, 5‐methylthioadenosine,
cadaverine,
glucose 1-phosphate,glucose 6-phosphate,
glucuronic acid, heptanoic
acid,choline,
NADH,fruc‐andtose 6‐phosphate,glucose1‐phosphate,glucose6‐phosphate,
glucuronic
heptanoic
putrescine
were moreabundantin the DMZ,
whereascysteic acid,
guanine,acid,hypoxanthine,
and Tyrwereandmoreabundant
in morethe VMZ.
The HCA
resultswhereas
indicatedthat acid,the DMZacid,
NADH,
putrescinewereabundantin the DMZ,
cysteic
gua‐
had highamounts ofandglycolysisglutathione
metabolites
and thenine,
hypoxanthine,
Tyr wereandmoreabundantmetabolism-related
in the VMZ. The HCA
results indicatedVMZ
hadhighhadpurinemetabolites
in explants(Figure 2D–F). These
that theDMZ
highmetabolism-related
amounts of glycolysis‐
and glutathione
metabolism‐relatedme‐metabolites
highlycontributed
tothediscrimination
between
the
DMZ
and
VMZ
explants.
tabolites and the VMZ had high purine metabolism‐related metabolites in explants (Fig‐
Furtheranalysisthat notonly
the metabolites
in Figure2D butthe
most
of
ure
2D–F).
These foundmetabolites
highlycontributed
to the shown
discrimination
betweenDMZ
the otherinvolvedin glycolysis
moretheactivein the DMZ
thanin theand
VMZ metabolites
explants. Further
analysisfound thatwere
not onlymetabolites
shownin Figure
VMZ
FigureS1). The
concentrationsof cadaverine
hypoxanthine
2D but(Supplementary
most of the othermetabolites
involvedin glycolysis
were moreand
activein the DMZ
were
also
different between
theDMZ
and VMZ of
explants(FDRandadjustedthan inthesignificantly
VMZ (Supplementary
Figure S1).
The
concentrations
cadaverinehypo‐
p < 0.05). The results obtained by gas chromatography–mass spectrometry (GC-MS) also
demonstrated that hypoxanthine and guanine were specifically contained in the VMZ
explants (Supplementary Figure S2).

Metabolites 2022, 12, x FOR PEER REVIEWMetabolites 2022, 12, 566

4 of 12xanthine were also significantly different between the DMZ and VMZ explants (FDR ad‐
justed p < 0.05). The results obtained by gas chromatography–mass spectrometry (GC‐MS)
also demonstrated that hypoxanthine and guanine were specifically contained in the VMZ 4 of 11
explants (Supplementary Figure S2).

Figure 2. Identification of hydrophilic metabolites differentially expressed between the DMZ and

Figure2. Identification of hydrophilic metabolites differentially expressed between the DMZ and
VMZ in explants (DMZ and VMZ explants). (A) Principal component analysis (PCA) score visual‐
VMZ
in(DMZ between
and VMZ
Principal
component
analysis
(PCA)
score
visualizing
izing explants
the relationshiptheexplants).
DMZ (red(A)circle)and VMZ(blue triangle)
explantsusinghydro‐
philicmetabolites.
The
contribution
ratios
were
14.9%
and
13%
for
PC2
and
PC3,
respectively.
(B)
the relationship between the DMZ (red circle) and VMZ (blue triangle) explants using hydrophilic
Partialleastsquares–discriminant
analysis(PLS‐DA)
score
plots
for
the
DMZ
(red
circle)and
VMZ
metabolites. The contribution ratios were 14.9% and 13% for PC2 and PC3, respectively. (B) Partial(blue triangle) explants. (C) Hierarchical clustering analysis (HCA) for the top 15 metabolites byleast squares–discriminant analysis (PLS-DA) score plots for the DMZ (red circle) and VMZ (bluevariable importance in projection (VIP) scores in explants. Rows display the metabolite, and col‐triangle)
explants.the(C)sample.
Hierarchicalclustering
analysislow(HCA)
for arethe displayed
top 15 metabolites
by variableumns represent
Metabolites
with relatively
contents
in blue,importancein projection(VIP)
scoreshighin explants.
displayinthe
metabolite,
and columns
whereas metabolites
withrelatively
contents Rows
are displayedred.
The brightnessof each represent
corresponds
to the magnitudeof the low
differencecomparedwith the meanvalue.
The number
thecolor
sample.
Metabolites
with relatively
contents
are displayedin blue,
whereasmetabolites
with relatively high contents are displayed in red. The brightness of each color corresponds to themagnitude of the difference compared with the mean value. The number at the end of each sample
name corresponds to samples made from the same embryos. (D–F) Comparison of the concentrationsof metabolites that differed notably between the DMZ and VMZ explants. Symbols represent eachsample, and the bar graph indicates the mean ± SD (n = 6, each sample from 20 explants). * FDRadjusted p < 0.05 (Welch’s t-test, Benjamini–Hochberg procedure). (D) Bar graphs of the metabolites
involved in glycolysis in the top 15 metabolites by VIP scores. (E) Bar graphs of the metabolites
involved in glutathione metabolism in the top 15 metabolites by VIP scores. (F) Bar graphs of themetabolites involved in purine metabolism in the top 15 metabolites by VIP scores.

Metabolites 2022, 12, 566

explants. Symbols represent each sample, and the bar graph indicates the mean ± SD (n = 6, eachsample from 20 explants). * FDR adjusted p < 0.05 (Welch’s t‐test, Benjamini–Hochberg procedure).
(D) Bar graphs of the metabolites involved in glycolysis in the top 15 metabolites by VIP scores.
(E) Bar graphs of the metabolites involved in glutathione metabolism in the top 15 metabolites by
VIP scores. (F) Bar graphs of the metabolites involved in purine metabolism in the top 15 metabo‐lites by VIP scores.
5 of 112.1.3. Hypoxanthine, Guanine, and Glucuronic Acid Were Differentially Expressed
between the DMZ and VMZ in the Two Types of Samples
2.1.3. Hypoxanthine, Guanine, and Glucuronic Acid Were Differentially Expressed
Differences
inand
the VMZ
levelsinofthehydrophilic
betweenthe DMZ
Two Typesmetabolites
of Samples in the DMZ and VMZ explants
are shownin
Figure2.
Wetherefore
carriedout
PLS‐DA to
the VMZ
characteristics
Differences in the levels of hydrophilic metabolites
in investigate
the DMZ and
explants
ofhydrophilic
metabolites
inthesupernatants
of
the
DMZ
and
VMZ
samples(DMZ andare shown in Figure 2. We therefore carried out PLS-DA to investigate the characteristics
VMZ
supernatants)(Figurein3A).
The top 15 metabolites
VIP
scoresin supernatantsofhydrophilic
metabolites
the supernatantsof the DMZby
and
VMZ
samples(DMZ andwereselected
similarly
toexplants,
andconsequently,
theDMZ
contained
relatively
VMZ supernatants) (Figure 3A). The top 15 metabolites by VIP scores in supernatants
higherconcentrationsofAla,
β‐ala,
ATP,
betaine,carnitine,
citricacid,
CTP,
diethanola‐
were selected similarly to explants, and consequently, the DMZ contained relatively higher
mine, glucuronic
acid,β-ala,and ATP,
GTP.betaine,
In contrast,
the citric
VMZacid,contained
relatively moreglu1‐
concentrationsof Ala,carnitine,
CTP, diethanolamine,
methylhistamine,
α‐methylserine,
cysteine
sulfinic
acid,
guanine,hypoxanthine,andpy‐curonic acid, and GTP. In contrast, the VMZ contained relatively more 1-methylhistamine,
ruvicacid comparedto theDMZacid,(Supplementary
Table S1). Ofandthese,
hypoxanthine,gua‐
α-methylserine,
cysteine
sulfinic
guanine, hypoxanthine,
pyruvic
acid comparednine,
glucuronic
acid were
included
the top
15 metabolites
by VIP
scoresin ex‐
totheandDMZ(Supplementary
Table
S1). Of in
these,
hypoxanthine,
guanine,andglucuronic
plantsas well(Figureacid
were
includedin 3B).
the top 15 metabolites by VIP scores in explants as well (Figure 3B).

Figure 3.
metabolites
identified
in in
superna‐Figure3. Comparative
Comparativeanalysis
analysisofofthe
thecharacteristic
characteristichydrophilichydrophilic
metabolites
identified
supertants.
(A)
PLS‐DA
score
plots
for
the
supernatants
of
the
DMZ
(red
circle)
and
VMZ
(blue
natants. (A) PLS-DA score plots for the supernatants of the DMZ (red circle) and VMZ (blue triangle)
triangle)
samples (DMZ and VMZ supernatants) based on hydrophilic metabolite data. (B) Comparison ofsamples (DMZ and VMZ supernatants) based on hydrophilic metabolite data. (B) Comparison of
hypoxanthine, guanine, and glucuronic acid concentrations in the DMZ and VMZ supernatants.
hypoxanthine, guanine, and glucuronic acid concentrations in the DMZ and VMZ supernatants.
Symbols represent each sample and the bar graph indicates the mean ± SD (n = 6, each sample from
Symbols
represent each sample and the bar graph indicates the mean ± SD (n = 6, each sample from
20 explants).
20 explants).

2.2. Lipidomic
2.2.
Lipidomic Analyses
AnalysesFor
further
investigation, analyses
the explants
explants andand supernatants
supernatants were
were
For further investigation,
analyses ofof lipids
lipids inin theconducted
using
SFC‐QqQMS.
In
total,
396
and95
lipidsbelonging
to
14
lipid
classes
were
conducted using SFC-QqQMS. In total, 396 and 95 lipids belonging to 14 lipid classes
detectedinexplants
andsupernatants,
respectively.
The
301
lipidsidentified
onlyinwere detected in explants and supernatants, respectively. The 301 lipids identified onlyex‐
inplants contained
explants
containeddiacylglycerol
diacylglycerol(DAG),(DAG),phosphatidylethanolamine
phosphatidylethanolamine(PE),(PE), phosphatidyl‐
phosphatidylcholine (PC),choline(PC), triacylglycerol
triacylglycerol (TAG),(TAG), andand alkenyl‐acyl
alkenyl-acyl phosphatidylethanolamine
phosphatidylethanolamine (PE(PE (p)).
(p)).
Moreover,all95
lipidsdetectedinsupernatants
overlapped
with
those
in
explants,
andMoreover, all 95 lipids detected in supernatants overlapped with those in explants, and
22
2=2
their
levelswereadequately
correlated
(DMZ,
R
=
0.8992,p<0.001;
VMZ,
R
0.8461,p<their levels were adequately correlated (DMZ, R = 0.8992, p < 0.001; VMZ, R = 0.8461,
0.001;
Figure4A).
p < 0.001; Figure 4A).
we evaluatedevaluatedthe
therelationshiprelationshipbetweencontentof eachin ex‐
Next, webetweenthethecontentof eachlipidlipid
classclassin explants
plantsand supernatants.
The contents
TAG (DMZ,
VMZ, 51.8%)
PC (DMZ,
andsupernatants.
The contentsof TAGof(DMZ,
54.9%; 54.9%;
VMZ, 51.8%)
and PCand(DMZ,
23.3%;
23.3%;24.2%)
VMZ, 24.2%)
were relatively
in explants,
whereasTAG (DMZ,
VMZ,
were relatively
higher higher
in explants,
whereasthat ofthat
TAGof(DMZ,
80.1%;80.1%;
VMZ,
VMZ, 93.2%)
was higher
in supernatants(FigureA comparison
the proportion
of
93.2%)
was higher
in supernatants(Figure4B). A4B).
comparisonof theofproportionof each
each
lipid
class
in
the
total
lipid
content
showedthattheamountsofhexosylceramide
lipid class in the total lipid content showed that the amounts of hexosylceramide (HexCer)(HexCer)times;
times)and ceramide(Cer) 2.7
(DMZ,
2.7VMZ,
times; 1.6
VMZ,
1.6
(DMZ,
7.7(DMZ,
times;7.7
VMZ,
11 VMZ,
times)11
andceramide(Cer) (DMZ,
times;
times)
were more than 1.5 times in supernatants than in explants. However, the levels of PC(DMZ, 0.032 times; VMZ, 0.013 times), PE (DMZ, 0.055 times; VMZ, 0.023 times), phosphatidylinositol (PI) (DMZ, 0.056 times; VMZ, 0.021 times), and sphingomyelin (SM) (DMZ,
0.10 times; VMZ, 0.029 times) were less than one-tenth of their levels in supernatants thanin explants (Figure 4C). Interestingly, the ratio of DAG (DMZ, 1.5 times; VMZ, 0.35 times)
and cholesterol (DMZ, 1.8 times; VMZ, 0.44 times) was markedly different between the
DMZ and VMZ. Finally, the lipids detected in the DMZ or VMZ regions were examined.
In supernatants, 10 and 17 lipids were identified only in the DMZ or VMZ, respectively(Table 1).

Metabolites 2022, 12, 566

times) were more than 1.5 times in supernatants than in explants. However, the levels ofPC (DMZ, 0.032 times; VMZ, 0.013 times), PE (DMZ, 0.055 times; VMZ, 0.023 times), phos‐
phatidylinositol (PI) (DMZ, 0.056 times; VMZ, 0.021 times), and sphingomyelin (SM)
(DMZ, 0.10 times; VMZ, 0.029 times) were less than one‐tenth of their levels in superna‐tants than in explants (Figure 4C). Interestingly, the ratio of DAG (DMZ, 1.5 times; VMZ,
0.35 times) and cholesterol (DMZ, 1.8 times; VMZ, 0.44 times) was markedly different be‐
tween the DMZ and VMZ. Finally, the lipids detected in the DMZ or VMZ regions were
examined. In supernatants, 10 and 17 lipids were identified only in the DMZ or VMZ,
respectively (Table 1).

Figure 4. Lipid characteristics between the DMZ and VMZ in explants and supernatants. (A) Cor‐

6 of 11

Figure 4. Lipidcharacteristics
betweenthe DMZ
and VMZ
in explants
relationsof the lipids detected
between explants
and supernatants.
(B) Bar graphs
showing the and supernatants.
proportion
of
each
lipid
class
in
the
total
lipid
content.
(C)
Enrichmentof
lipidclasses
explants(A) Correlations of the lipids detected between explants and supernatants.in(B)Bar graphs showing
and supernatants. The x‐values are the ratios obtained by dividing the proportion in supernatants
that inlipid
explants.
Anyin
lipid
class
whoselipid
value waszero was(C)excluded.
TAG, triacylglycerol;the proportion ofbyeach
class
the
total
content.
Enrichmentof lipid classes in explants
DAG, diacylglycerol; PC, phosphatidylcholine; PE, phosphatidylethanolamine; PG, phosphatidyl‐
and supernatants.glycerol;
The x-values
are the ratios
obtained byPEdividing
the phosphatidylethan‐proportion in supernatants by
PS, phosphatidylserine;
PI, phosphatidylinositol;(p), alkenyl‐acyl
lysophosphatidylcholine;
LPE,excluded.
lysophosphatidylethanolamine;SM, sphingomyelin;
LPC, valuethat in explants. olamine;
Any lipidclass whose
was zero was
TAG, triacylglycerol; DAG,
Cer, ceramide; HexCer, hexosylceramides.
diacylglycerol; PC, phosphatidylcholine; PE, phosphatidylethanolamine; PG, phosphatidylglycerol;
PS, phosphatidylserine; PI, phosphatidylinositol; PE (p), alkenyl-acyl phosphatidylethanolamine; SM,sphingomyelin; LPC, lysophosphatidylcholine; LPE, lysophosphatidylethanolamine; Cer, ceramide;
HexCer, hexosylceramides.
Table 1. Lipids detected only in the supernatants of the DMZ or VMZ samples.
Lipid Class

DMZ

VMZ

TAG 56:2
Triacylglycerol

TAG 48:4
TAG 48:5
TAG 62:10
TAG 64:12
TAG 64:13
TAG 64:17

Phosphatidylcholine

PC 16:0–20:5

Phosphatidylethanolamine

PE 16:0–22:6

Phosphatidylinositol

PI 18:0–20:5
PI 18:0–22:6

Alkenyl-Acyl Phosphatidylethanolamine

PE 16:1p–22:6
PE 18:1p–20:5
PE 18:2p–22:6

Sphingomyelin

SM d18:1–22:1

SM d18:1–18:2

Lysophosphatidylcholine

LPC 16:0
LPC 22:0

LPC 18:2

LPE 16:0
LPE 18:0
LPE 20:5

LPE 22:6

Lysophosphatidylethanolamine

Cer d18:1–22:0

Cer d18:1–16:0
Cer d18:1–18:2

Ceramide
Cholesterol

Cholesterol

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3. Discussion
Single-cell capillary electrophoresis electrospray ionization (CE-ESI)-MS has revealed
metabolic activity differences between dorsal and ventral cells in live Xenopus embryos
during the cleavage cycles [20–22]. Those studies confirmed the effect of metabolic changes
on cell differentiation. In the present study, we identified small molecules in the gastrula
period, at stage 10, and succeeded in quantifying 190 hydrophilic metabolites using explants
and supernatants. A previous report detected a core set of 48 metabolites in nearly allof their experiments, including amino acids, nucleotides, and phosphorylated sugars, in
single Xenopus eggs or embryos from stages 0 to 9 [23]. Of these 48, we could confirm thedetection of 41 metabolites, except for three that were not included in our laboratory’s
library. The remaining four metabolites, taurine, NAD+, NADP+, and acetyl-CoA, were
not detected in this study.
The DMZ was found to contain higher amounts of glycolysis- and glutathione metabolismrelated metabolites in explants (Figure 2D,E, Supplementary Figure S1). Glycolysisdependent intracellular pH controls Wnt signaling in the tail bud, which promotes thefate of paraxial mesoderm from neuromesodermal progenitors required for sustained axial
elongation [24,25]. Given this fact, the glycolytic activity could affect dorsalization via Wnt
signaling in the gastrula. Additionally, in a previous study [22], the midline dorsal-animalcells in 16-cell Xenopus embryos were noticeably richer in Ser, Gly, Thr, and urocanic acidthan the midline ventral-animal cells, whereas the ventral regions were richer in hypoxanthine compared to the dorsal regions. In the gastrula, there was no difference in the activityof the Ser–Gly–Thr pathway between the DMZ and VMZ. This might be because remodeling of core metabolic pathways occurred during the mid-blastula transition (MBT) [23].
However, interestingly, more hypoxanthine was significantly accumulated in the VMZthan the DMZ even in the gastrula, a stage after the MBT (Figures 2F and 3B). Our analyses
uncovered that hypoxanthine, guanine, and glucuronic acid were differentially active between the DMZ and VMZ in Xenopus gastrula (Figures 2C,F and 3B). Further investigationis necessary to conclude whether these metabolites are able to define cell fates.
Lipid profiling during early vertebrate development has been reported along withmetabolomics data [26–30], and it is known that PC 18:0–22:6, PE 16:0–20:4, and SM
d18:1–16:0 are, respectively, enriched in the retina, pharynx, and notochord [29]. In thiswork, we succeeded in identifying 396 lipids in Xenopus gastrula using two types ofsamples. In supernatants, the ratio of each lipid class/the total lipid content was higher
for HexCer and Cer than that in explants; but the ratio of PC, PE, PI, and SM in explants
was remarkably higher than that in supernatants (Figure 4C). A previous study reported
that tissues contained a large family of PC, and cavities that form the future gut and neuralcrest contained abundant Cer in stage-13 and stage-19 Xenopus embryos [31]. The cavities
would be similar in composition to the supernatant samples used in this work because theywould be rich in secreted substances released from cells rather than substances derived
from tissues. Given this assumption, our data support the results of the previous report.
In addition, our study discovered some lipids specifically contained in the DMZ or VMZ
in Xenopus gastrula (Table 1). These lipids can be molecular markers in the dorsal or
ventral regions.
In this study, supernatant samples were used to reduce the influence of small intracellular molecules and to detect secreted small molecules. Explants had to be cultured for
60 min to detect trace amounts of secreted small molecules, although it should be notedthat the metabolites in the supernatant may have been altered during incubation. Additionally, we could not determine whether the small molecules identified in our metabolomic
analyses affected the phenotypes or were just the results of cell differentiation in the DMZ
and VMZ. Therefore, it is necessary to conduct future functional experiments using thecandidate metabolites, which were specifically expressed in the DMZ or VMZ.
In conclusion, we identified 186 and 98 hydrophilic metabolites and 396 and 95 lipids
in explants and supernatants, respectively, using a combination of capillary IC-MS, LC-MS,and SFC-QqQMS. Glycolysis- and glutathione metabolism-related metabolites were more

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active in the DMZ explants, whereas purine metabolism-related metabolites were more
active in the VMZ explants. As a result of comparing the data between explants andsupernatants, hypoxanthine, guanine, and glucuronic acid were differentially contained
between the DMZ and VMZ in the two types of samples. Furthermore, dorsoventralspecific lipids were found. To our knowledge, this is the first study to show large metabolite
data for small molecules in Xenopus gastrula. Our research would contribute to a deeper
understanding of the cellular physiology that regulates early embryogenesis.
4. Materials and Methods
4.1. Embryo Manipulations
Xenopus embryos were obtained by in vitro fertilization. The details of in vitro fertilization are described in Ohata et al., 2014 [32]. Twenty DMZs or VMZs per sample weredissected at stage 10 in 1× SS (Steinberg’s solution). 1× SS was prepared by diluting
10× SS to a concentration of one-tenth with ultrapure water, adding 0.1 g/L of kanamycin
sulfate (Sigma-Aldrich, St. Louis, MO, USA), and then autoclaving. 10× SS contained
580 mmol/L NaCl, 6.7 mmol/L KCl, 3.4 mmol/L Ca(NO3 )2 , 8.3 mmol/L MgSO4 , and
0.1 g/L kanamycin sulfate and was adjusted to pH 7.4 using sodium hydroxide. Dissected samples were washed with 0.5× SS, and most of the yolk-rich regions were removed.
0.5× SS was prepared by diluting 10× SS to a concentration of one-twentieth with ultrapure
water. The DMZs and VMZs were each put into 100 µL of 0.5× SS in 1.5 mL siliconizedtubes and cultured for 60 min at 22 ◦ C. After that, 50 µL of the supernatant was collected
as a supernatant sample. Samples of explants or supernatants were immediately stored at–80 ◦ C (n = 6). In a 1.5 mL siliconized tube, 50 µL of 0.5× SS, an uncultured medium wasadditionally used as the blank of supernatant samples (n = 6). It was also stored at –80 ◦ C
after placing it at 22 ◦ C for 60 min to keep the same condition.
4.2. Extraction of Hydrophilic Metabolites and Lipids
For metabolite extraction, 1 mL of the mixture of methanol (FUJIFILM Wako Pure
Chemicals Corp., Osaka, Japan), chloroform (FUJIFILM Wako Pure Chemicals Corp.), andmilli-Q water (Merck KGaA, Gernsheim, Germany) (10:5:3) containing internal standards(IS) was added to each sample. Five microliters of IS for hydrophilic metabolites wascomposed of 100 µmol/L methionine sulfone (FUJIFILM Wako Pure Chemicals Corp.),tryptophan-13 C11 , 15 N2 (TAIYO NIPPON SANSO Corp., Tokyo, Japan), and camphor
10-sulfonic acid (FUJIFILM Wako Pure Chemicals Corp.). For lipids, 5 µL of IS comprised
the mouse SPLASH® LIPIDOMIX® Mass Spec Internal Standard (Avanti Polar Lipids,
Alabaster, AL, USA) and the internal standard mix. The details of the composition are
described previously [33].
After using a vortex mixer for 1 min, the solution was moved to a 1.5 mL microcentrifuge tube. It was sonicated for 5 min and centrifuged (16,000× g, 5 min, 4 ◦ C). Eighthundred microliters of the upper layer was transferred to a 2 mL microcentrifuge tube, andthen the supernatant was mixed well with 220 µL of chloroform and milli-Q water followedby centrifugation (16,000× g, 3 min, 4 ◦ C). Five hundred microliters of the aqueous layerand 400 µL of the organic layer were, respectively, transferred to new tubes. The subsequent
steps, including dryness, were conducted as previously described [33].
4.3. Analyses of Hydrophilic Metabolites
The analytical methods of anionic metabolites by capillary IC-MS were the same as
those represented in Hirayama et al., 2020 [34]. Cationic metabolites were measured using
LC-MS according to previously described methods with some modifications [35]. Briefly,
LC-MS was performed using an Agilent 1290 Infinity LC system (Agilent Technologies,
Santa Clara, CA, USA) equipped with a Q Exactive Orbitrap MS system (Thermo Fisher
Scientific, Waltham, MA, USA). Separation of cationic metabolites was performed on a
HILIC-Z column (150 × 2.1mm, 2.7 µm; Agilent Technologies). The injection volume was
1 µL, and the column temperature was maintained at 40 ◦ C. The mobile phase consisted

Metabolites 2022, 12, 566

9 of 11of 20 mmol/L ammonium formic acid + 0.25% (v/v) formic acid (A) and 20 mmol/L ammonium formic acid + 0.25% formic acid in 90% (v/v) acetonitrile (B). The eluent flow rate
was 0.25 mL/min, and the gradient was as follows: 0–15 min, 100% to 70% B; 15–20 min,
70% to 10% B; 20–23 min, 10% B; and 23–30 min, 100% B. The Q Exactive mass spectrometer was operated in a heated ESI (HESI) positive-ion mode using the following source
parameters: auxiliary gas temperature = 300 ◦ C, auxiliary gas flow rate = 10 (arbitrary
units), spray voltage = 3.5 kV, capillary temperature = 250 ◦ C, sheath gas flow rate = 40
(arbitrary units), and S-lens = 35 (arbitrary units). The acquisition method combined two
scan events corresponding to a full MS scan mode and a parallel reaction monitoring(PRM) mode. The parameters in full MS scan mode were as follows: resolution, 35,000;
auto gain control target, 3.0 × 106 ; maximum ion injection time, 200 ms; and scan range,
50–750 m/z. Additionally, the parameters in PRM mode were as follows: resolution, 17,500;
auto gain control target, 2 × 105 ; maximum ion injection time, 100 ms; inclusion m/z list:
104.0706 (GABA), 118.0863 (Val), 132.1019 (Leu, Ile), 166.0863 (Phe), and 182.0482 (methionine sulfone).
4.4. Lipidomic Analyses
Lipids were analyzed by SFC-QqQMS based on previous studies [33,36]. Briefly, SFCQqQMS experiments were conducted using an Agilent 1260 Infinity II SFC system equippedwith an Agilent 6470A triple quadrupole LC/MS system with an Agilent jet stream (AJS) ESI
interface. Lipids were separated on an ACQUITY UPC2 Torus DEA column (3.0 × 100 mm,
1.7 µm; Waters Corp., Milford, MA, USA). Lipid classes measured were as follows: Cer,cholesterol, DAG, HexCer, lysophosphatidylcholine (LPC), lysophosphatidylethanolamine(LPE), phosphatidic acid (PA), PC, alkyl-acyl phosphatidylcholine (PC (e)), alkenyl-acyl
phosphatidylcholine (PC (p)), PE, PE (p), phosphatidylglycerol (PG), PI, phosphatidylserine(PS), SM, and TAG. The details are previously described [33]. Dynamic multiple reaction
monitoring (MRM) transition based on the previous in-house lipid MRM library was used
for the lipidomic analyses [36].
4.5. Data Analyses
The raw data obtained by capillary IC-MS and LC-MS were analyzed using theTraceFinder software (version 5.0, Thermo Fisher Scientific). MassHunter software (version
10.0, Agilent Technologies) was also used to analyze the data acquired by SFC-QqQMS.
To remove all the peaks coming from the background, the amounts of metabolites in
explants were calculated by subtracting the mol of individual metabolites identified in thetechnical blank, which were similarly pretreated and analyzed. The amounts of metabolites
in supernatants were also calculated by subtracting those in the 0.5× SS sample. The
negative values were changed to zero. The concentration when dissolved in 50 µL of water
was used in an explants sample to match the volume of a supernatant sample. The dataon metabolites detected in more than half of the samples were used (n = 6). Statisticalsignificance was determined using an FDR adjusted p-value (Welch’s t-test, BenjaminiHochberg procedure). PCA, PLS-DA, and HCA were, respectively, analyzed using JMP(version 15.0), SIMCA (version 13.0), and MeV (version 10.2). The z-score normalized data
were used for all multivariate analyses, and PCA, PLS-DA, and HCA were, respectively,
performed using a covariance matrix, the default SIMCA cross-validation procedure, andPearson’s correlation coefficient. Excel (version 16.58) was used for multiple correlation
coefficients (Pearson’s correlation coefficient, Student’s t-test). Bar graphs were made using
GraphPad Prism (version 8.4.3) and Excel.
Supplementary Materials: The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/metabo12060566/s1, S1. Materials and Methods. Figure S1:
Comparison of the concentrations of metabolites involved in glycolysis and pentose and glucuronic
acid interconversion pathways in explants. Figure S2: Identification of metabolites differentiallyexpressed between the DMZ and VMZ in explants (DMZ and VMZ explants) using GC-MS. Table S1:

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List of hydrophilic metabolites with high VIP scores (VIP scores >1.0) in supernatants. Table S2: Listof hydrophilic metabolites with high VIP scores (VIP scores >1.0) in explants.
Author Contributions: Conceptualization, Y.S. and H.K.; methodology, Y.S., R.H., A.H. and H.K.;
formal analysis, Y.S.; investigation, Y.S., R.H., M.H., S.I., A.H. and H.K.; resources, Y.S. and H.K.;
data curation, M.H. and S.I.; writing—original draft preparation, Y.S., R.H., A.H. and H.K.; writing—review and editing, Y.S., R.H., T.S., M.T., A.H. and H.K.; visualization, Y.S. and R.H.; supervision,
T.S. and M.T.; project administration, H.K.; funding acquisition, Y.S., M.T., A.H. and H.K. All authors
have read and agreed to the published version of the manuscript.
Funding: This research was funded in part by the Advanced Genome Research and Bioinformatics
Study to Facilitate Medical Innovation (GRIFIN) from the AMED (20km0405209h0003 for A.H.), by
JST FOREST Program (JPMJFR2052 for A.H.), by Yamagishi Student Project Support Program (Y.S.),and by the grants from the Yamagata prefectural government and the city of Tsuruoka.
Institutional Review Board Statement: Ethical review and approval for this study were waived by
SFC Research Ethics Committee in Keio University because the studies in this manuscript did notinclude experiments on human subjects, and the experimental animal, Xenopus laevis, was used under
Keio University Animal Experiment Regulations.
Informed Consent Statement: Not applicable.
Data Availability Statement: Data are contained in the article and supplementary materials.
Acknowledgments: Y.S. is grateful to Kanako Fukunaga for fruitful discussions and suggestions.
Conflicts of Interest: The authors declare no conflict of interest.

References
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.

Yost, H.J. Left-right development in Xenopus and zebrafish. Semin. Cell Dev. Biol. 1998, 9, 61–66. [CrossRef] [PubMed]
De Robertis, E.M.; Gurdon, J.B. A Brief History of Xenopus in Biology. Cold Spring Harb. Protoc. 2021, 2021, pdb.top107615.
[CrossRef] [PubMed]
Gerhart, J. Evolution of the organizer and the chordate body plan. Int. J. Dev. Biol. 2001, 45, 133–153. [PubMed]
Heasman, J. Patterning the early Xenopus embryo. Development 2006, 133, 1205–1217. [CrossRef] [PubMed]
De Robertis, E.M.; Larrain, J.; Oelgeschlager, M.; Wessely, O. The establishment of Spemann’s organizer and patterning of thevertebrate embryo. Nat. Rev. Genet. 2000, 1, 171–181. [CrossRef]
Spemann, H.; Mangold, H. Induction of embryonic primordia by implantation of organizers from a different species. 1923. Int. J.
Dev. Biol. 2001, 45, 13–38.
Agius, E.; Oelgeschlager, M.; Wessely, O.; Kemp, C.; De Robertis, E.M. Endodermal Nodal-related signals and mesoderm
induction in Xenopus. Development 2000, 127, 1173–1183. [CrossRef]
De Robertis, E.M.; Kuroda, H. Dorsal-ventral patterning and neural induction in Xenopus embryos. Annu. Rev. Cell Dev. Biol.
2004, 20, 285–308. [CrossRef]
Kawano, Y.; Kypta, R. Secreted antagonists of the Wnt signalling pathway. J. Cell Sci. 2003, 116, 2627–2634. [CrossRef]
Moos, M., Jr.; Wang, S.; Krinks, M. Anti-dorsalizing morphogenetic protein is a novel TGF-beta homolog expressed in the
Spemann organizer. Development 1995, 121, 4293–4301. [CrossRef]
Piccolo, S.; Sasai, Y.; Lu, B.; De Robertis, E.M. Dorsoventral patterning in Xenopus: Inhibition of ventral signals by direct bindingof chordin to BMP-4. Cell 1996, 86, 589–598. [CrossRef]
Zimmerman, L.B.; De Jesus-Escobar, J.M.; Harland, R.M. The Spemann organizer signal noggin binds and inactivates bonemorphogenetic protein 4. Cell 1996, 86, 599–606. [CrossRef]
Fukumoto, T.; Kema, I.P.; Levin, M. Serotonin signaling is a very early step in patterning of the left-right axis in chick and frog
embryos. Curr. Biol. 2005, 15, 794–803. [CrossRef] [PubMed]
Blumberg, B.; Bolado, J., Jr.; Moreno, T.A.; Kintner, C.; Evans, R.M.; Papalopulu, N. An essential role for retinoid signaling inanteroposterior neural patterning. Development 1997, 124, 373–379. [CrossRef] [PubMed]
Mori, S.; Moriyama, Y.; Yoshikawa, K.; Furukawa, T.; Kuroda, H. β-Adrenergic signaling promotes posteriorization in Xenopus
early development. Dev. Growth Differ. 2013, 55, 350–358. [CrossRef]
Furukawa, T.; Yamasaki, Y.; Hara, Y.; Otsuki, C.; Maki, H.; Soga, T.; Moriyama, Y.; Kuroda, H. Axis elongation during Xenopus
tail-bud stage is regulated by GABA expressed in the anterior-to-mid neural tube. Int. J. Dev. Biol. 2019, 63, 37–43. [CrossRef]
Brown, H.L.; Sherburn, I.A.; Gaff, C.; Taylor, N.; Best, S. Structured approaches to implementation of clinical genomics: A scoping
review. Genet. Med. 2022, in press. [CrossRef]
Deng, M.; Wang, Y.; Yan, Y. Mining cell-cell signaling in single-cell transcriptomics atlases. Curr. Opin. Cell Biol. 2022, 76, 102101.
[CrossRef]

Metabolites 2022, 12, 566

19.
20.
21.

22.
23.
24.

25.
26.

27.
28.
29.
30.

31.
32.

33.

34.

35.

36.

11 of 11

Alexovic, M.; Sabo, J.; Longuespee, R. Automation of single-cell proteomic sample preparation. Proteomics 2021, 21, e2100198.
[CrossRef]
Onjiko, R.M.; Plotnick, D.O.; Moody, S.A.; Nemes, P. Metabolic Comparison of Dorsal versus Ventral Cells Directly in the Live
8-cell Frog Embryo by Microprobe Single-cell CE-ESI-MS. Anal. Methods 2017, 9, 4964–4970. [CrossRef]
Onjiko, R.M.; Portero, E.P.; Moody, S.A.; Nemes, P. In Situ Microprobe Single-Cell Capillary Electrophoresis Mass Spectrometry:
Metabolic Reorganization in Single Differentiating Cells in the Live Vertebrate (Xenopus laevis) Embryo. Anal. Chem. 2017, 89,
7069–7076. [CrossRef] [PubMed]
Onjiko, R.M.; Moody, S.A.; Nemes, P. Single-cell mass spectrometry reveals small molecules that affect cell fates in the 16-cellembryo. Proc. Natl. Acad. Sci. USA 2015, 112, 6545–6550. [CrossRef] [PubMed]
Vastag, L.; Jorgensen, P.; Peshkin, L.; Wei, R.; Rabinowitz, J.D.; Kirschner, M.W. Remodeling of the metabolome during early frog
development. PLoS ONE 2011, 6, e16881. [CrossRef]
Oginuma, M.; Moncuquet, P.; Xiong, F.; Karoly, E.; Chal, J.; Guevorkian, K.; Pourquie, O. A Gradient of Glycolytic Activity
Coordinates FGF and Wnt Signaling during Elongation of the Body Axis in Amniote Embryos. Dev. Cell. 2017, 40, 342–353.
[CrossRef] [PubMed]
Oginuma, M.; Harima, Y.; Tarazona, O.A.; Diaz-Cuadros, M.; Michaut, A.; Ishitani, T.; Xiong, F.; Pourquie, O. Intracellular pH
controls WNT downstream of glycolysis in amniote embryos. Nature 2020, 584, 98–101. [CrossRef]
Ferreira, C.R.; Pirro, V.; Eberlin, L.S.; Hallett, J.E.; Cooks, R.G. Developmental phases of individual mouse preimplantationembryos characterized by lipid signatures using desorption electrospray ionization mass spectrometry. Anal. Bioanal. Chem.
2012, 404, 2915–2926. [CrossRef]
Pirro, V.; Guffey, S.C.; Sepulveda, M.S.; Mahapatra, C.T.; Ferreira, C.R.; Jarmusch, A.K.; Cooks, R.G. Lipid dynamics in zebrafish
embryonic development observed by DESI-MS imaging and nanoelectrospray-MS. Mol. Biosyst. 2016, 12, 2069–2079. [CrossRef]
Tata, A.; Sudano, M.J.; Santos, V.G.; Landim-Alvarenga, F.D.; Ferreira, C.R.; Eberlin, M.N. Optimal single-embryo mass
spectrometry fingerprinting. J. Mass Spectrom. 2013, 48, 844–849. [CrossRef]
Goto-Inoue, N.; Kashiwagi, A.; Kashiwagi, K.; Mori, T. Metabolomic approach for identifying and visualizing molecular tissue
markers in tadpoles of Xenopus tropicalis by mass spectrometry imaging. Biol. Open 2016, 5, 1252–1259. [CrossRef]
Tian, H.; Fletcher, J.S.; Thuret, R.; Henderson, A.; Papalopulu, N.; Vickerman, J.C.; Lockyer, N.P. Spatiotemporal lipid profiling
during early embryo development of Xenopus laevis using dynamic ToF-SIMS imaging. J. Lipid Res. 2014, 55, 1970–1980.
[CrossRef]
Wang, M.; Dubiak, K.; Zhang, Z.; Huber, P.W.; Chen, D.D.Y.; Dovichi, N.J. MALDI-imaging of early stage Xenopus laevis embryos.
Talanta 2019, 204, 138–144. [CrossRef] [PubMed]
Ohata, Y.; Matsukawa, S.; Moriyama, Y.; Michiue, T.; Morimoto, K.; Sato, Y.; Kuroda, H. Sirtuin inhibitor Ex-527 causes neuraltube defects, ventral edema formations, and gastrointestinal malformations in Xenopus laevis embryos. Dev. Growth Differ.
2014, 56, 460–468. [CrossRef] [PubMed]
Hayasaka, R.; Tabata, S.; Hasebe, M.; Ikeda, S.; Ohnuma, S.; Mori, M.; Soga, T.; Tomita, M.; Hirayama, A. Metabolomic Analysis of
Small Extracellular Vesicles Derived from Pancreatic Cancer Cells Cultured under Normoxia and Hypoxia. Metabolites 2021, 11, 215.
[CrossRef] [PubMed]
Hirayama, A.; Tabata, S.; Kudo, R.; Hasebe, M.; Suzuki, K.; Tomita, M.; Soga, T. The use of a double coaxial electrospray ionization
sprayer improves the peak resolutions of anionic metabolites in capillary ion chromatography-mass spectrometry. J. Chromatogr. A
2020, 1619, 460914. [CrossRef]
Tadokoro, H.; Hirayama, A.; Kudo, R.; Hasebe, M.; Yoshioka, Y.; Matsuzaki, J.; Yamamoto, Y.; Sugimoto, M.; Soga, T.; Ochiya, T.
Adenosine leakage from perforin-burst extracellular vesicles inhibits perforin secretion by cytotoxic T-lymphocytes. PLoS ONE
2020, 15, e0231430. [CrossRef]
Takeda, H.; Izumi, Y.; Takahashi, M.; Paxton, T.; Tamura, S.; Koike, T.; Yu, Y.; Kato, N.; Nagase, K.; Shiomi, M.; et al. Widelytargeted quantitative lipidomics method by supercritical fluid chromatography triple quadrupole mass spectrometry. J. Lipid Res.
2018, 59, 1283–1293. [CrossRef]