Scientific Data,
Journal Year:
2024,
Volume and Issue:
11(1)
Published: April 22, 2024
Natural
products
exhibit
interesting
structural
features
and
significant
biological
activities.
The
discovery
of
new
bioactive
molecules
is
a
complex
process
that
requires
high-quality
metabolite
profiling
data
to
properly
target
the
isolation
compounds
interest
enable
their
complete
characterization.
same
can
also
be
used
better
understand
chemotaxonomic
links
between
species.
This
Data
Descriptor
details
dataset
resulting
from
untargeted
liquid
chromatography-mass
spectrometry
76
natural
extracts
Celastraceae
family.
spectral
annotation
results
related
chemical
taxonomic
metadata
are
shared,
along
with
proposed
examples
reuse.
further
studied
by
researchers
exploring
diversity
products.
serve
as
reference
sample
set
for
deep
metabolome
investigation
this
chemically
rich
plant
Analytical Chemistry,
Journal Year:
2024,
Volume and Issue:
96(8), P. 3409 - 3418
Published: Feb. 14, 2024
Untargeted
metabolomics
using
liquid
chromatography–electrospray
ionization–high-resolution
tandem
mass
spectrometry
(UPLC–ESI–MS/MS)
provides
comprehensive
insights
into
the
dynamic
changes
of
metabolites
in
biological
systems.
However,
numerous
unidentified
metabolic
features
limit
its
utilization.
In
this
study,
a
novel
approach,
Chemical
Classification-driven
Molecular
Network
(CCMN),
was
proposed
to
unveil
key
pathways
by
leveraging
hidden
information
within
features.
The
method
demonstrated
herbivore-induced
response
corn
silk
as
case
study.
analysis
UPLC–MS/MS
performed
on
wild
and
two
genetically
modified
lines
(pre-
postinsect
treatment).
Global
annotation
initially
identified
256
(ESI–)
327
(ESI+)
metabolites.
MS/MS-based
classifications
predicted
1939
1985
chemical
classes.
CCMNs
were
then
constructed
shared
classes,
which
facilitated
structure-
or
class
for
completely
unknown
Next,
844/713
significantly
decreased
1593/1378
increased
ESI–/ESI+
modes
defined
insect
herbivory,
respectively.
Method
validation
spiked
maize
sample
an
overall
prediction
accuracy
rate
95.7%.
Potential
prescreened
hypergeometric
test
both
class-annotated
differential
Subsequently,
CCMN
used
deeply
amend
uncover
pathway
deeply.
Finally,
8
defined,
including
phenylpropanoid
(C6–C3),
flavonoid,
octadecanoid,
diterpenoid,
lignan,
steroid,
amino
acid/small
peptide,
monoterpenoid.
This
study
highlights
effectiveness
CCMN-based
reduced
bias
conventional
enrichment
analysis.
It
valuable
complex
processes.
Scientific Data,
Journal Year:
2024,
Volume and Issue:
11(1)
Published: April 22, 2024
Natural
products
exhibit
interesting
structural
features
and
significant
biological
activities.
The
discovery
of
new
bioactive
molecules
is
a
complex
process
that
requires
high-quality
metabolite
profiling
data
to
properly
target
the
isolation
compounds
interest
enable
their
complete
characterization.
same
can
also
be
used
better
understand
chemotaxonomic
links
between
species.
This
Data
Descriptor
details
dataset
resulting
from
untargeted
liquid
chromatography-mass
spectrometry
76
natural
extracts
Celastraceae
family.
spectral
annotation
results
related
chemical
taxonomic
metadata
are
shared,
along
with
proposed
examples
reuse.
further
studied
by
researchers
exploring
diversity
products.
serve
as
reference
sample
set
for
deep
metabolome
investigation
this
chemically
rich
plant
