bioRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2024,
Номер
unknown
Опубликована: Ноя. 21, 2024
We
present
a
freely
available
diaPASEF
data
analysis
software,
Beta-DIA,
that
utilizes
deep
learning
methods
to
score
coelution
consistency
in
retention
time-ion
mobility
dimensions
and
spectrum
similarity.
Beta-DIA
integrates
these
learning-based
scores
with
traditional
function-based
scores,
enhancing
the
qualitative
performance.
In
some
low
detection
datasets,
identifies
twice
as
many
protein
groups
DIA-NN.
The
success
of
has
paved
another
way
for
application
fundamental
proteome
profiling.
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
Analytical Chemistry,
Год журнала:
2025,
Номер
unknown
Опубликована: Фев. 25, 2025
Mass
spectrometry-based
proteomics
is
about
35
years
old,
and
recent
progress
appears
to
be
speeding
up
across
all
subfields.
In
this
review,
we
focus
on
advances
over
the
last
two
in
select
areas
within
bottom-up
proteomics,
including
approaches
high-throughput
experiments,
data
analysis
using
machine
learning,
drug
discovery,
glycoproteomics,
extracellular
vesicle
structural
proteomics.
bioRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2023,
Номер
unknown
Опубликована: Июнь 24, 2023
Abstract
Mass
spectrometry-based
proteomics
has
been
rapidly
gaining
traction
as
a
powerful
analytical
method
both
in
basic
research
and
translation.
While
the
problem
of
error
control
peptide
protein
identification
addressed
extensively,
quality
resulting
quantities
remains
challenging
to
evaluate.
Here
we
introduce
QuantUMS
(
Quant
ification
using
an
U
ncertainty
M
inimising
S
olution),
machine
learning-based
which
minimises
errors
eliminates
bias
quantification
by
integrating
multiple
sources
quantitative
information.
In
combination
with
data-independent
acquisition
proteomics,
boosts
accuracy
precision
quantities,
well
reports
uncertainty
metric,
enabling
effective
filtering
data
for
downstream
analysis.
The
algorithm
linear
complexity
respect
number
mass
spectrometry
acquisitions
experiment
is
thus
scalable
infinitely
large
proteomic
experiments.
For
easy
implementation
laboratory,
integrate
our
automated
DIA-NN
software
suite.
medRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2023,
Номер
unknown
Опубликована: Окт. 15, 2023
Abstract
Background
Plasma
proteomics
offers
new
avenues
to
explore
non-genetic
associations,
such
as
biomarkers
for
lifestyle
and
environmental
exposure
in
population
studies.
To
date,
most
proteomic
investigations
studies
have
utilized
affinity-reagent
based
technologies,
which
are
ideal
quantify
the
low
abundant
fraction
of
circulating
proteome
but
may
omit
several
proteins
that
function
plasma.
Methods
Utilizing
high
throughput
mass
spectrometry,
we
quantified
148
highly
protein
groups
including
immunoglobulins,
coagulation
factors,
metabolic
proteins,
components
innate
immune
system,
plasma
3,632
participants
from
Cooperative
Health
Research
South
Tyrol
(CHRIS)
study.
Using
multiple
regression
analyses
then
investigated
associations
with
various
factors
common
medications.
Results
Beyond
age
sex,
is
predominantly
influenced
by
hormonal
contraceptives.
For
instance,
Angiotensinogen
(AGT)
levels
exhibit
significant
alteration
this
treatment,
suggesting
AGT
could
be
a
potential
biomarker
contraceptive
use.
The
effect
drug
class
more
pronounced
than
other
medications
or
covariates.
Furthermore,
our
analysis
does
not
reveal
any
enduring
signature
associated
use
these
Conclusion
In
contrast
used
drugs,
contraceptives
exert
on
proteome.
Given
its
prevalence
among
young
female
participants,
impact
might
misconstrued
sex-or
age-related
effects
One
should
thus
account
their
epidemiological
clinical
study
prevent
misleading
results.
bioRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2024,
Номер
unknown
Опубликована: Сен. 27, 2024
Rapid
and
comprehensive
analysis
of
complex
proteomes
across
large
sample
sets
is
vital
for
unlocking
the
potential
systems
biology.
We
present
UFP-MS,
an
ultra-fast
mass
spectrometry
(MS)
proteomics
method
that
integrates
narrow-window
data-independent
acquisition
(nDIA)
with
short-gradient
micro-flow
chromatography,
enabling
profiling
>240
samples
per
day.
This
optimized
MS
approach
identifies
6,201
7,466
human
proteins
1-
2-min
gradients,
respectively.
Our
streamlined
preparation
workflow
features
high-throughput
homogenization,
adaptive
focused
acoustics
(AFA)-assisted
proteolysis,
Evotip-accelerated
desalting,
allowing
processing
up
to
96
tissue
in
5
h.
As
a
practical
application,
we
analyzed
507
from
13
mouse
tissues
treated
enzyme-drug
L-asparaginase
(ASNase)
or
its
glutaminase-free
Q59L
mutant,
generating
quantitative
profile
11,472
following
drug
treatment.
The
results
confirmed
impact
ASNase
on
amino
acid
metabolism
solid
tissues.
Further
revealed
broad
suppression
anticoagulants
cholesterol
uncovered
numerous
tissue-specific
dysregulated
pathways.
In
summary,
UFP-MS
greatly
accelerates
generation
biological
insights
clinically
actionable
hypotheses
into
vulnerabilities
targeted
by
ASNase.
Expert Review of Proteomics,
Год журнала:
2024,
Номер
21(9-10), С. 367 - 376
Опубликована: Окт. 2, 2024
The
introduction
of
trapped
ion
mobility
spectrometry
(TIMS)
in
combination
with
fast
high-resolution
time-of-flight
(TOF)
mass
to
the
proteomics
field
led
a
jump
protein
identifications
and
quantifications,
as
well
lowering
limit
detection
for
proteins
from
biological
samples.
Parallel
Accumulation-Serial
Fragmentation
(PASEF)
is
driving
force
this
development
has
been
adapted
discovery
targeted
proteomics.
bioRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2024,
Номер
unknown
Опубликована: Ноя. 8, 2024
Abstract
RATIONALE
In
spatial
proteomics,
matrix-assisted
laser
desorption/ionization
(MALDI)
imaging
enables
rapid
and
cost-effective
peptide
measurement.
Yet,
in
situ
identification
remains
challenging.
Therefore,
this
study
aims
to
integrate
the
trapped
ion
mobility
spectrometry
(TIMS)-based
parallel
accumulation-serial
fragmentation
(PASEF)
into
MALDI
of
peptides
enable
multiplexed
MS/MS
imaging.
METHODS
An
initial
TIMS
MS1
survey
measurement
is
performed,
followed
by
a
manual
generation
precursor
list
containing
mass
over
charge
values
windows.
Inside
dual
system,
submitted
precursors
are
trapped,
separately
eluted
their
analyzed
quadrupole
time-of-flight
device,
thereby
enabling
Finally,
identified
spectrum
matching.
RESULTS
This
presents
first
(iprm-PASEF)
tryptic
peptides.
Its
applicability
showcased
on
two
histomorphologically
distinct
tissue
specimens
4-plex
5-plex
setup.
Precursors
were
successfully
search
engine
MASCOT
one
single
experiment
for
each
respective
tissue.
Peptide
identifications
corroborated
liquid-chromatography
tandem
experiments
fragment
colocalization
analyses.
CONCLUSIONS
present
study,
we
demonstrate
feasibility
TIMS-based
manner.
Hence,
it
represents
step
towards
integration
emerging
field
proteomics.
