Nature Communications,
Год журнала:
2023,
Номер
14(1)
Опубликована: Сен. 22, 2023
Single-cell
resolution
analysis
of
complex
biological
tissues
is
fundamental
to
capture
cell-state
heterogeneity
and
distinct
cellular
signaling
patterns
that
remain
obscured
with
population-based
techniques.
The
limited
amount
material
encapsulated
in
a
single
cell
however,
raises
significant
technical
challenges
molecular
profiling.
Due
extensive
optimization
efforts,
single-cell
proteomics
by
Mass
Spectrometry
(scp-MS)
has
emerged
as
powerful
tool
facilitate
proteome
profiling
from
ultra-low
amounts
input,
although
further
development
needed
realize
its
full
potential.
To
this
end,
we
carry
out
comprehensive
orbitrap-based
data-independent
acquisition
(DIA)
for
proteomics.
Notably,
find
difference
between
optimal
DIA
methods
high-
low-load
samples.
We
improve
our
low-input
method
relying
on
high-resolution
MS1
quantification,
thus
enhancing
sensitivity
more
efficiently
utilizing
available
mass
analyzer
time.
With
input
tailored
method,
are
able
accommodate
long
injection
times
high
resolution,
while
keeping
the
scan
cycle
time
low
enough
ensure
robust
quantification.
Finally,
demonstrate
capability
approach
mouse
embryonic
stem
culture
conditions,
showcasing
global
proteomes
highlighting
differences
key
metabolic
enzyme
expression
subclusters.
Abstract
Background
Macrophages
are
innate
immune
cells
with
diverse
functional
and
molecular
phenotypes.
This
diversity
is
largely
unexplored
at
the
level
of
single-cell
proteomes
because
limitations
quantitative
protein
analysis.
Results
To
overcome
this
limitation,
we
develop
SCoPE2,
which
substantially
increases
accuracy
throughput
while
lowering
cost
hands-on
time
by
introducing
automated
miniaturized
sample
preparation.
These
advances
enable
us
to
analyze
emergence
cellular
heterogeneity
as
homogeneous
monocytes
differentiate
into
macrophage-like
in
absence
polarizing
cytokines.
SCoPE2
quantifies
over
3042
proteins
1490
single
macrophages
10
days
instrument
time,
quantified
allow
discern
cell
type.
Furthermore,
data
uncover
a
continuous
gradient
proteome
states
for
macrophages,
suggesting
that
macrophage
may
emerge
Parallel
measurements
transcripts
10×
Genomics
suggest
our
20-fold
more
copies
than
RNA
per
gene,
thus,
supports
quantification
improved
count
statistics.
allowed
exploring
regulatory
interactions,
such
interactions
between
tumor
suppressor
p53,
its
transcript,
genes
regulated
p53.
Conclusions
Even
environment,
heterogeneous.
correlates
inflammatory
axis
classically
alternatively
activated
macrophages.
Our
methodology
lays
foundation
analysis
mass
spectrometry
demonstrates
potential
inferring
transcriptional
post-transcriptional
regulation
from
variability
across
cells.
Nature Communications,
Год журнала:
2021,
Номер
12(1)
Опубликована: Июнь 7, 2021
Large-scale
single-cell
analyses
are
of
fundamental
importance
in
order
to
capture
biological
heterogeneity
within
complex
cell
systems,
but
have
largely
been
limited
RNA-based
technologies.
Here
we
present
a
comprehensive
benchmarked
experimental
and
computational
workflow,
which
establishes
global
mass
spectrometry-based
proteomics
as
tool
for
large-scale
analyses.
By
exploiting
primary
leukemia
model
system,
demonstrate
both
through
pre-enrichment
populations
non-enriched
unbiased
approach
that
our
workflow
enables
the
exploration
cellular
this
aberrant
developmental
hierarchy.
Our
is
capable
consistently
quantifying
~1000
proteins
per
across
thousands
individual
cells
using
instrument
time.
Furthermore,
develop
(SCeptre)
effectively
normalizes
data,
integrates
available
FACS
data
facilitates
downstream
analysis.
The
presented
here
lays
foundation
implementing
studies
world.
Proteomics
has
become
an
important
field
in
molecular
sciences,
as
it
provides
valuable
information
on
the
identity,
expression
levels,
and
modification
of
proteins.
For
example,
cancer
proteomics
unraveled
key
mechanistic
studies
tumor
growth
metastasis,
which
contributed
to
identification
clinically
applicable
biomarkers
well
therapeutic
targets.
Several
proteome
databases
have
been
established
are
being
shared
worldwide.
Importantly,
integration
with
other
omics
is
providing
extensive
data
related
mechanisms
target
modulators.
These
may
be
analyzed
processed
through
bioinformatic
pipelines
obtain
useful
information.
The
purpose
this
review
provide
overview
recent
advances
proteomic
techniques.
In
particular,
we
aim
offer
insights
into
current
brain
cancer,
applications
a
relatively
early
stage.
This
covers
from
discovery
characterization
technology.
Moreover,
addresses
global
trends
approaches
for
translational
research.
As
core
method
research,
continued
development
expected
at
scale
beyond
that
previously
seen.
Molecular Neurodegeneration,
Год журнала:
2021,
Номер
16(1)
Опубликована: Авг. 12, 2021
Mass
spectrometry-based
proteomics
empowers
deep
profiling
of
proteome
and
protein
posttranslational
modifications
(PTMs)
in
Alzheimer's
disease
(AD).
Here
we
review
the
advances
limitations
historic
recent
AD
proteomic
research.
Complementary
to
genetic
mapping,
studies
not
only
validate
canonical
amyloid
tau
pathways,
but
also
uncover
novel
components
broad
networks,
such
as
RNA
splicing,
development,
immunity,
membrane
transport,
lipid
metabolism,
synaptic
function,
mitochondrial
activity.
Meta-analysis
seven
datasets
reveals
2,698
differentially
expressed
(DE)
proteins
landscape
brain
(n
=
12,017
proteins/genes),
covering
35
reported
genes
risk
loci.
The
DE
contain
cellular
markers
enriched
neurons,
microglia,
astrocytes,
oligodendrocytes,
epithelial
cells,
supporting
involvement
diverse
cell
types
pathology.
We
discuss
hypothesized
protective
or
detrimental
roles
selected
proteins,
emphasizing
top
"amyloidome"
(all
biomolecules
plaques)
progression.
Comprehensive
PTM
analysis
represents
another
layer
molecular
events
AD.
In
particular,
PTMs
are
correlated
with
stages
indicate
heterogeneity
individual
patients.
Moreover,
unprecedented
coverage
biofluids,
cerebrospinal
fluid
serum,
procures
putative
biomarkers
through
meta-analysis.
Thus,
proteomics-driven
systems
biology
presents
a
new
frontier
link
genotype,
proteotype,
phenotype,
accelerating
development
improved
models
treatment
strategies.
Nature Communications,
Год журнала:
2022,
Номер
13(1)
Опубликована: Янв. 10, 2022
Abstract
Single-cell
proteomics
can
reveal
cellular
phenotypic
heterogeneity
and
cell-specific
functional
networks
underlying
biological
processes.
Here,
we
present
a
streamlined
workflow
combining
microfluidic
chips
for
all-in-one
proteomic
sample
preparation
data-independent
acquisition
(DIA)
mass
spectrometry
(MS)
analysis
down
to
the
single-cell
level.
The
enable
multiplexed
automated
cell
isolation/counting/imaging
processing
in
single
device.
Combining
chip-based
handling
with
DIA-MS
using
project-specific
spectral
libraries,
profile
on
average
~1,500
protein
groups
across
20
mammalian
cells.
Applying
chip-DIA
proteomes
of
adherent
non-adherent
malignant
cells,
cover
dynamic
range
5
orders
magnitude
good
reproducibility
<16%
missing
values
between
runs.
Taken
together,
offers
characterization,
analytical
sensitivity
robustness,
option
add
additional
functionalities
future,
thus
providing
basis
advanced
applications.
