Dysbiosis of Oral Microbiome: A Key Player in Oral Carcinogenesis? A Critical Review
Biomedicines,
Journal Year:
2025,
Volume and Issue:
13(2), P. 448 - 448
Published: Feb. 12, 2025
The
oral
cavity
is
known
to
harbor
hundreds
of
microorganisms,
belonging
various
genera,
constituting
a
peculiar
flora
called
the
microbiome.
change
in
relative
distribution
constituents
this
microbial
flora,
due
any
reason,
leads
dysbiosis.
For
centuries,
dysbiosis
has
been
linked
etiopathogenesis
several
medical
illnesses,
both
locally
and
systemically-.
However,
aided
by
recent
advent
bio-technological
capabilities,
reports
have
re-emerged
that
link
carcinogenesis,
numerous
studies
are
currently
exploring
their
association
plausible
mechanisms.
Some
proposed
mechanisms
dysbiosis-induced
carcinogenesis
(ODIC)
include—a
bacteria-induced
chronic
inflammatory
state
leading
direct
cellular
damage,
inflammatory-cytokine-mediated
promotion
proliferation
invasion,
release
bacterial
products
carcinogenic,
suppression
local
immunity
alteration
tumor
microenvironment.
actual
interactions
between
these
role
not
yet
fully
understood.
This
review
provides
comprehensive
overview
hypotheses
implicated
ODIC,
along
with
corresponding
molecular
aberrations.
Apart
from
discussing
usual
microbiome
profile,
also
summarizes
profiles
ODIC.
sheds
light
on
potential
clinical
implications
research
prevention
management
cancer.
Language: Английский
Imbalance in gut microbial interactions as a marker of health and disease
bioRxiv (Cold Spring Harbor Laboratory),
Journal Year:
2025,
Volume and Issue:
unknown
Published: April 30, 2025
Imbalances
in
the
human
gut
microbiome
(dysbioses)
are
linked
to
multiple
diseases
but
remain
poorly
understood.
Current
biomarkers
identify
dysbiosis
inconsistent
and
fail
capture
ecological
mechanisms
differentiating
healthy
from
diseased
microbiomes.
We
propose
a
general
biomarker,
inspired
by
phenomenology
observed
gut-microbiome
theoretical
model
introduced
here.
The
emergent
communities
show
complex
interaction
networks
two
distinct
collective
states,
corresponding
dysbiotic
Our
robust
metric
for
dysbiosis,
quantifying
balance
between
cooperation
competition,
differentiates
these
states
both
simulated
real
datasets
across
diverse
diseases.
Moreover,
it
reveals
that
results
shift
toward
greater
community.
further
correlates
with
disease
progression,
highlighting
its
potential
as
diagnostic
tool.
Language: Английский
Creating microbiome-model harmony between metaproteomics data and the ADM1da for a two-step anaerobic digester
bioRxiv (Cold Spring Harbor Laboratory),
Journal Year:
2024,
Volume and Issue:
unknown
Published: Dec. 22, 2024
Abstract
The
effective
operation,
planning,
and
optimization
of
renewable
energy
production
in
anaerobic
digestion
(AD)
plants
relies
on
advanced
process
models,
such
as
the
Anaerobic
Digestion
Model
No.
1
(ADM1).
This
study
applies
an
ADM1-based
model
(ADM1da)
to
simulate
a
two-step
digester
industrial
setting.
data
demonstrate
that
2.6%
methane
is
lost
result
open
hydrolysis.
Conversely,
incorporation
hydrolysis
fermenter
enhances
by
average
2.5%.
Although
ADM1-like
models
are
widely
recognized
for
accurately
representing
processes,
mechanistic
insights
into
microbiome
involved
have
been
limited
absence
tools
analyze
microbial
composition
functionality
at
time
these
were
developed.
To
overcome
this
limitation,
we
utilized
metaproteomics
approach
assess
abundance
biomass-correlated
activity
groups
defined
model,
aiming
bridge
gap
between
ecology
bioprocess
engineering
AD
systems.
We
also
developed
evaluated
series
rules
associating
particular
species
with
functional
model.
Our
analysis
demonstrates
while
supports
presence
stable
main
fermenter,
it
difficult
capture
dynamic
behavior
observed
fermenter.
Furthermore,
actual
displays
greater
versatility
than
assumes,
microorganisms
performing
multiple
functions
rather
being
restricted
single
roles.
In
conclusion,
identifies
options
improving
integrating
comprehensive
biological
knowledge
further
optimize
performance
digesters.
Highlights
Simulations
revealed
2.6
%
volume
loss
attributed
Implementation
increased
2.5%
Identification
map
ADM1da
depict
but
not
Microbial
perform
just
one
assumed
Language: Английский