bioRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2024,
Номер
unknown
Опубликована: Апрель 26, 2024
Abstract
Recent
advances
have
allowed
for
the
detection
of
10,000
proteins
from
cultured
human
cell
samples,
such
as
HeLa
and
HEK293T
cells
in
a
single-shot
proteome
analysis.
However,
deeper
analysis
remains
challenging.
Therefore,
this
study,
we
aimed
to
perform
deep
proteomic
using
timsTOF
HT.
To
achieve
proteomics,
developed
Thin-diaPASEF,
parallel
accumulation-serial
fragmentation
(PASEF)
technology
featuring
thinly
divided
m/z
axis
only
regions
high
ion
density.
Furthermore,
60-cm
long
C18
column
with
particle
size
1.7
µm,
an
average
11,698,
11,615
11,019
unique
were
successfully
detected
500
ng
HEK293T,
K562
digests,
respectively,
100
min
active
gradient.
The
same
system
was
used
analyze
Lycopersicon
esculentum
lectin
(LEL)
enriched
plasma
serum.
LEL
method
identified
8,613
4,078
proteins,
serum,
respectively.
Our
ultra-deep
will
be
helpful
in-depth
comparison
medical
biological
research
because
it
enables
highly
coverage
single-shot.
Journal of Proteome Research,
Год журнала:
2023,
Номер
22(10), С. 3290 - 3300
Опубликована: Сен. 8, 2023
We
evaluate
the
quantitative
performance
of
newly
released
Asymmetric
Track
Lossless
(Astral)
analyzer.
Using
data-independent
acquisition,
Thermo
Scientific
Orbitrap
Astral
mass
spectrometer
quantifies
5
times
more
peptides
per
unit
time
than
state-of-the-art
spectrometers,
which
have
long
been
gold
standard
for
high-resolution
proteomics.
Our
results
demonstrate
that
can
produce
high-quality
measurements
across
a
wide
dynamic
range.
also
use
developed
extracellular
vesicle
enrichment
protocol
to
reach
new
depths
coverage
in
plasma
proteome,
quantifying
over
5000
proteins
60
min
gradient
with
spectrometer.
Nature Communications,
Год журнала:
2023,
Номер
14(1)
Опубликована: Июль 12, 2023
Abstract
Liquid
chromatography
(LC)
coupled
with
data-independent
acquisition
(DIA)
mass
spectrometry
(MS)
has
been
increasingly
used
in
quantitative
proteomics
studies.
Here,
we
present
a
fast
and
sensitive
approach
for
direct
peptide
identification
from
DIA
data,
MSFragger-DIA,
which
leverages
the
unmatched
speed
of
fragment
ion
indexing-based
search
engine
MSFragger.
Different
most
existing
methods,
MSFragger-DIA
conducts
database
tandem
(MS/MS)
spectra
prior
to
spectral
feature
detection
peak
tracing
across
LC
dimension.
To
streamline
analysis
data
enable
easy
reproducibility,
integrate
into
FragPipe
computational
platform
seamless
support
library
building
DIA,
data-dependent
(DDA),
or
both
types
combined.
We
compare
other
tools,
such
as
DIA-Umpire
based
workflow
FragPipe,
Spectronaut,
DIA-NN
library-free,
MaxDIA.
demonstrate
fast,
sensitive,
accurate
performance
variety
sample
schemes,
including
single-cell
proteomics,
phosphoproteomics,
large-scale
tumor
proteome
profiling
Nature Biotechnology,
Год журнала:
2024,
Номер
unknown
Опубликована: Фев. 1, 2024
Abstract
Mass
spectrometry
(MS)-based
proteomics
aims
to
characterize
comprehensive
proteomes
in
a
fast
and
reproducible
manner.
Here
we
present
the
narrow-window
data-independent
acquisition
(nDIA)
strategy
consisting
of
high-resolution
MS1
scans
with
parallel
tandem
MS
(MS/MS)
~200
Hz
using
2-Th
isolation
windows,
dissolving
differences
between
data-dependent
-independent
methods.
This
is
achieved
by
pairing
quadrupole
Orbitrap
mass
spectrometer
asymmetric
track
lossless
(Astral)
analyzer
which
provides
>200-Hz
MS/MS
scanning
speed,
high
resolving
power
sensitivity,
low-ppm
accuracy.
The
nDIA
enables
profiling
>100
full
yeast
per
day,
or
48
human
day
at
depth
~10,000
protein
groups
half-an-hour
~7,000
proteins
5
min,
representing
3×
higher
coverage
compared
current
state-of-the-art
MS.
Multi-shot
offline
fractionated
samples
~3
h.
High
quantitative
precision
accuracy
are
demonstrated
three-species
proteome
mixture,
quantifying
14,000+
single
run.
Molecular & Cellular Proteomics,
Год журнала:
2023,
Номер
22(7), С. 100577 - 100577
Опубликована: Май 19, 2023
Accurate
biomarkers
are
a
crucial
and
necessary
precondition
for
precision
medicine,
yet
existing
ones
often
unspecific
new
have
been
very
slow
to
enter
the
clinic.
Mass
spectrometry
(MS)-based
proteomics
excels
by
its
untargeted
nature,
specificity
of
identification,
quantification,
making
it
an
ideal
technology
biomarker
discovery
routine
measurement.
It
has
unique
attributes
compared
affinity
binder
technologies,
such
as
OLINK
Proximity
Extension
Assay
SOMAscan.
In
in
previous
review
2017,
we
described
technological
conceptual
limitations
that
had
held
back
success.
We
proposed
'rectangular
strategy'
better
separate
true
minimizing
cohort-specific
effects.
Today,
this
converged
with
advances
MS-based
technology,
increased
sample
throughput,
depth
quantification.
As
result,
studies
become
more
successful,
producing
candidates
withstand
independent
verification
and,
some
cases,
already
outperform
state-of-the-art
clinical
assays.
summarize
developments
over
last
years,
including
benefits
large
cohorts,
which
acceptance.
Shorter
gradients,
scan
modes,
multiplexing
about
drastically
increase
cross-study
integration,
proxies
absolute
levels.
found
multiprotein
panels
inherently
robust
than
current
single
analyte
tests
capture
complexity
human
phenotypes.
Routine
MS
measurement
clinic
is
fast
becoming
viable
option.
The
full
set
proteins
body
fluid
(global
proteome)
most
important
reference
best
process
control.
Additionally,
increasingly
all
information
could
be
obtained
from
targeted
analysis
although
latter
may
straightforward
way
regular
use.
Many
challenges
remain,
not
least
regulatory
ethical
but
outlook
applications
never
brighter.
Molecular Systems Biology,
Год журнала:
2023,
Номер
19(9)
Опубликована: Авг. 21, 2023
Single-cell
proteomics
aims
to
characterize
biological
function
and
heterogeneity
at
the
level
of
proteins
in
an
unbiased
manner.
It
is
currently
limited
proteomic
depth,
throughput,
robustness,
which
we
address
here
by
a
streamlined
multiplexed
workflow
using
data-independent
acquisition
(mDIA).
We
demonstrate
automated
complete
dimethyl
labeling
bulk
or
single-cell
samples,
without
losing
depth.
Lys-N
digestion
enables
five-plex
quantification
MS1
MS2
level.
Because
channels
are
quantitatively
isolated
from
each
other,
mDIA
accommodates
reference
channel
that
does
not
interfere
with
target
channels.
Our
algorithm
RefQuant
takes
advantage
this
confidently
quantifies
twice
as
many
per
single
cell
compared
our
previous
work
(Brunner
et
al,
PMID
35226415),
while
allows
routine
analysis
80
cells
day.
Finally,
combined
spatial
increase
throughput
Deep
Visual
Proteomics
seven-fold
for
microdissection
four-fold
MS
analysis.
Applying
primary
cutaneous
melanoma,
discovered
signatures
within
distinct
tumor
microenvironments,
showcasing
its
potential
precision
oncology.
Molecular & Cellular Proteomics,
Год журнала:
2024,
Номер
23(2), С. 100712 - 100712
Опубликована: Янв. 4, 2024
Data-independent
acquisition
(DIA)
mass
spectrometry
(MS)
has
emerged
as
a
powerful
technology
for
high-throughput,
accurate
and
reproducible
quantitative
proteomics.
This
review
provides
comprehensive
overview
of
recent
advances
in
both
the
experimental
computational
methods
DIA
proteomics,
from
data
schemes
to
analysis
strategies
software
tools.
are
categorized
based
on
design
precursor
isolation
windows,
highlighting
wide-window,
overlapping-window,
narrow-window,
scanning
quadrupole-based,
parallel
accumulation-serial
fragmentation
(PASEF)-enhanced
methods.
For
analysis,
major
classified
into
spectrum
reconstruction,
sequence-based
search,
library-based
de
novo
sequencing
sequencing-independent
approaches.
A
wide
array
tools
implementing
these
reviewed,
with
details
their
overall
workflows
scoring
approaches
at
different
steps.
The
generation
optimization
spectral
libraries,
which
critical
resources
also
discussed.
Publicly
available
benchmark
datasets
covering
global
proteomics
phosphoproteomics
summarized
facilitate
performance
evaluation
various
workflows.
Continued
synergistic
developments
versatile
components
expected
further
enhance
power
DIA-based
Nature Communications,
Год журнала:
2024,
Номер
15(1)
Опубликована: Март 9, 2024
Abstract
In
common
with
other
omics
technologies,
mass
spectrometry
(MS)-based
proteomics
produces
ever-increasing
amounts
of
raw
data,
making
efficient
analysis
a
principal
challenge.
A
plethora
different
computational
tools
can
process
the
MS
data
to
derive
peptide
and
protein
identification
quantification.
However,
during
last
years
there
has
been
dramatic
progress
in
computer
science,
including
collaboration
that
have
transformed
research
industry.
To
leverage
these
advances,
we
develop
AlphaPept,
Python-based
open-source
framework
for
processing
large
high-resolution
sets.
Numba
just-in-time
compilation
on
CPU
GPU
achieves
hundred-fold
speed
improvements.
AlphaPept
uses
Python
scientific
stack
highly
optimized
packages,
reducing
code
base
domain-specific
tasks
while
accessing
latest
advances.
We
provide
an
easy
on-ramp
community
contributions
through
concept
literate
programming,
implemented
Jupyter
Notebooks.
Large
datasets
rapidly
be
processed
as
shown
by
hundreds
proteomes
minutes
per
file,
many-fold
faster
than
acquisition.
used
build
automated
pipelines
web-serving
functionality
compatibility
downstream
tools.
It
provides
access
via
one-click
installation,
modular
library
advanced
users,
open
GitHub
repository
developers.
Nature Communications,
Год журнала:
2025,
Номер
16(1)
Опубликована: Янв. 2, 2025
Abstract
Data-independent
acquisition
has
become
a
widely
used
strategy
for
peptide
and
protein
quantification
in
liquid
chromatography-tandem
mass
spectrometry-based
proteomics
studies.
The
integration
of
ion
mobility
separation
into
data-independent
analysis,
such
as
the
diaPASEF
technology
available
on
Bruker’s
timsTOF
platform,
further
improves
accuracy
depth
achievable
using
acquisition.
We
introduce
diaTracer,
spectrum-centric
computational
tool
optimized
data.
diaTracer
performs
three-dimensional
(mass
to
charge
ratio,
retention
time,
mobility)
peak
tracing
feature
detection
generate
precursor-resolved
“pseudo-tandem
spectra”,
facilitating
direct
(“spectral-library
free”)
identification
from
is
stand-alone
fully
integrated
FragPipe
platform.
demonstrate
performance
data
triple-negative
breast
cancer,
cerebrospinal
fluid,
plasma
samples,
phosphoproteomics
human
leukocyte
antigens
immunopeptidomics
experiments,
low-input
spatial
study.
also
show
that
enables
unrestricted
post-translational
modifications
open/mass-offset
searches.
