Cell Systems,
Journal Year:
2021,
Volume and Issue:
12(8), P. 780 - 794.e7
Published: June 14, 2021
COVID-19
is
highly
variable
in
its
clinical
presentation,
ranging
from
asymptomatic
infection
to
severe
organ
damage
and
death.
We
characterized
the
time-dependent
progression
of
disease
139
inpatients
by
measuring
86
accredited
diagnostic
parameters,
such
as
blood
cell
counts
enzyme
activities,
well
untargeted
plasma
proteomes
at
687
sampling
points.
report
an
initial
spike
a
systemic
inflammatory
response,
which
gradually
alleviated
followed
protein
signature
indicative
tissue
repair,
metabolic
reconstitution,
immunomodulation.
identify
prognostic
marker
signatures
for
devising
risk-adapted
treatment
strategies
use
machine
learning
classify
therapeutic
needs.
show
that
models
based
on
proteome
are
transferable
independent
cohort.
Our
study
presents
map
linking
routinely
used
parameters
their
dynamics
infectious
disease.
Cell Systems,
Journal Year:
2020,
Volume and Issue:
12(1), P. 23 - 40.e7
Published: Oct. 8, 2020
We
performed
RNA-seq
and
high-resolution
mass
spectrometry
on
128
blood
samples
from
COVID-19-positive
COVID-19-negative
patients
with
diverse
disease
severities
outcomes.
Quantified
transcripts,
proteins,
metabolites,
lipids
were
associated
clinical
outcomes
in
a
curated
relational
database,
uniquely
enabling
systems
analysis
cross-ome
correlations
to
molecules
patient
prognoses.
mapped
219
molecular
features
high
significance
COVID-19
status
severity,
many
of
which
involved
complement
activation,
dysregulated
lipid
transport,
neutrophil
activation.
identified
sets
covarying
molecules,
e.g.,
protein
gelsolin
metabolite
citrate
or
plasmalogens
apolipoproteins,
offering
pathophysiological
insights
therapeutic
suggestions.
The
observed
dysregulation
platelet
function,
coagulation,
acute
phase
response,
endotheliopathy
further
illuminated
the
unique
phenotype.
present
web-based
tool
(covid-omics.app)
interactive
exploration
our
compendium
illustrate
its
utility
through
machine
learning
approach
for
prediction
severity.
Nature Communications,
Journal Year:
2022,
Volume and Issue:
13(1)
Published: July 8, 2022
The
dia-PASEF
technology
uses
ion
mobility
separation
to
reduce
signal
interferences
and
increase
sensitivity
in
proteomic
experiments.
Here
we
present
a
two-dimensional
peak-picking
algorithm
generation
of
optimized
spectral
libraries,
as
well
take
advantage
neural
network-based
processing
data.
Our
computational
platform
boosts
depth
by
up
83%
compared
previous
work,
is
specifically
beneficial
for
fast
experiments
those
with
low
sample
amounts.
It
quantifies
over
5300
proteins
single
injections
recorded
at
200
samples
per
day
throughput
using
Evosep
One
chromatography
system
on
timsTOF
Pro
mass
spectrometer
almost
9000
93-min
nanoflow
gradient
2,
from
ng
HeLa
peptides.
A
user-friendly
implementation
provided
through
the
incorporation
algorithms
DIA-NN
software
FragPipe
workflow
library
generation.
