Phage‐derived proteins: Advancing food safety through biocontrol and detection of foodborne pathogens
Comprehensive Reviews in Food Science and Food Safety,
Год журнала:
2025,
Номер
24(2)
Опубликована: Фев. 3, 2025
Abstract
The
emergence
of
antimicrobial‐resistant
foodborne
pathogens
poses
a
continuous
health
risk
and
economic
burden
as
they
can
easily
spread
through
contaminated
food.
Therefore,
the
demand
for
new
antimicrobial
agents
to
address
this
problem
is
steadily
increasing.
Similarly,
development
rapid,
sensitive,
accurate
pathogen
detection
tools
prerequisite
ensuring
food
safety.
Phage‐derived
proteins
have
become
innovative
combating
these
because
their
potent
activity
host
specificity.
Phage
are
relatively
free
from
regulation
compared
phages
per
se,
there
no
concerns
about
transduction
harmful
genes.
With
recent
progress
in
next‐generation
sequencing
technology,
analysis
phage
genomes
has
more
accessible,
numerous
with
potential
biocontrol
been
identified.
This
review
provides
comprehensive
overview
protein
research
on
safety
2006
present,
pivotal
period
marked
by
certification
Generally
Recognized
As
Safe
(GRAS).
Emphasizing
advancements,
we
investigated
diverse
applications
various
purposes.
While
highlighting
successful
implementation
proteins,
also
current
bottlenecks
propose
strategies
overcome
challenges.
By
summarizing
state
phage‐derived
contributes
deeper
understanding
effective
detecting
pathogens.
Язык: Английский
A practical approach to quantitative analytical surface-enhanced Raman spectroscopy
Chemical Society Reviews,
Год журнала:
2024,
Номер
unknown
Опубликована: Янв. 1, 2024
The
high
sensitivity,
molecular
specificity
and
speed
of
analysis
make
SERS
an
attractive
analytical
technique.
This
review
draws
out
the
underlying
principles
for
provides
practical
tips
tricks
quantitation.
Язык: Английский
Illuminating extracellular nanovesicles through the spectroscopic lens: a mini review of cutting-edge insights and emerging applications
Frontiers in Bioengineering and Biotechnology,
Год журнала:
2025,
Номер
13
Опубликована: Май 9, 2025
Extracellular
vesicles
(EVs)
are
cell-derived
particles
that
facilitate
intercellular
communication
by
carrying
bioactive
molecules
like
proteins
and
RNA,
impacting
both
health
disease.
Herein,
the
EVs'
significance
in
physiological
pathological
processes
is
reviewed,
emphasising
their
potential
as
biomarkers
for
diseases
including
instance,
cancer,
neurodegenerative
disorders
cardiovascular
conditions.
The
principles
applications
of
Raman
spectroscopy
(RS)
-
a
powerful
tool
offering
detailed
molecular
insights
into
EVs,
further
examined.
non-destructive
nature
this
spectroscopic
technique
renders
it
invaluable
studying
composition,
purity
concentration
EVs.
When
EVs
isolated
from
accessible
biofluids
such
blood,
urine
or
saliva,
overall
process
remains
minimally
invasive,
enhancing
its
clinical
applicability.
review
highlights
spectroscopy’s
role
identifying
disease-related
distinguishing
subpopulations
our
understanding
disease
mechanisms
therapeutic
applications.
Язык: Английский
Lighting the Path: Raman Spectroscopy’s Journey Through the Microbial Maze
Molecules,
Год журнала:
2024,
Номер
29(24), С. 5956 - 5956
Опубликована: Дек. 17, 2024
The
rapid
and
precise
identification
of
microorganisms
is
essential
in
environmental
science,
pharmaceuticals,
food
safety,
medical
diagnostics.
Raman
spectroscopy,
valued
for
its
ability
to
provide
detailed
chemical
structural
information,
has
gained
significant
traction
these
fields,
especially
with
the
adoption
various
excitation
wavelengths
tailored
optical
setups.
choice
wavelength
setup
spectroscopy
influenced
by
factors
such
as
applicability,
cost,
whether
bulk
or
single-cell
analysis
performed,
each
impacting
sensitivity
specificity
bacterial
detection.
In
this
study,
we
investigate
potential
different
identification,
utilizing
a
mock
culture
composed
six
species:
three
Gram-positive
(S.
warneri,
S.
cohnii,
E.
malodoratus)
Gram-negative
(P.
stutzeri,
K.
terrigena,
coli).
To
improve
classification,
applied
machine
learning
models
analyze
extract
unique
spectral
features
from
data.
results
indicate
that
significantly
influences
spectra
obtained,
thereby
accuracy
effectiveness
subsequent
classification
results.
Язык: Английский