Metabolites,
Год журнала:
2023,
Номер
13(3), С. 343 - 343
Опубликована: Фев. 24, 2023
Passengers
are
at
a
higher
risk
of
respiratory
infections
and
chronic
diseases
due
to
microbial
exposure
in
airline
cabins.
However,
the
presence
virulence
factors
(VFs),
antimicrobial
resistance
genes
(ARGs),
metabolites,
chemicals
yet
be
studied.
To
address
this
gap,
we
collected
dust
samples
from
cabins
two
airlines,
one
with
textile
seats
(TSC)
leather
(LSC),
analyzed
using
shotgun
metagenomics
LC/MS.
Results
showed
that
abundances
17
VFs
11
were
significantly
TSC
than
LSC
(
Frontiers in Microbiomes,
Год журнала:
2024,
Номер
3
Опубликована: Фев. 16, 2024
Introduction
Rhinitis
is
one
of
the
most
prevalent
chronic
respiratory
diseases
worldwide.
There
emerging
evidence
suggesting
that
indoor
microbiome
may
contribute
onset
and
exacerbation
rhinitis
symptoms,
but
comprehensive
studies
on
this
topic
remain
scarce.
Methods
In
study,
we
assessed
assemblage
settled
air
dust
collected
in
Petri
dishes
86
dormitory
rooms
Shanxi
University,
China
using
16s
rRNA
sequencing.
A
self-administered
questionnaire,
including
questions
about
symptoms
personal
information,
was
completed
by
357
students
residing
these
dormitories.
Logistic
linear
regression
model
applied
to
examine
associations
between
environmental
characteristics,
microbiome,
rhinitis.
Results
The
abundant
genera
dormitories
were
Ralstonia
(15.6%),
Pelomonas
(11.3%),
Anoxybacillus
(9.3%)
Ochrobactrum
(6.2%).
Taxa
richness
class
Actinobacteria
Fusobacteriia
negatively/protectively
associated
with
(p<0.05).
Six
bacterial
genera,
those
from
(
Actinomyces
),
Fusobacterium
Bacteroidetes
Prevotella
Capnocytophaga
Conversely,
seven
predominantly
Alphaproteobacteria
Betaproteobacteria
Sphingomonas,
Caulobacter
,
uncharacterized
Caulobacteraceae
Comamonadaceae
positively
Living
higher
floor
level
PM
2.5
concentrations
a
abundance
taxa
potentially
protective
against
lower
increasing
risk
(P<0.01).
However,
having
curtain
CO
2
Discussion
This
study
enhances
our
understanding
complex
interactions
microbiomes,
rhinitis,
shedding
light
potential
strategies
manipulate
for
disease
prevention
control.
Abstract
Background
Chronic
exposure
to
microorganisms
inside
homes
can
impact
respiratory
health.
Few
studies
have
used
advanced
sequencing
methods
examine
adult
outcomes,
especially
continuous
measures.
We
aimed
identify
metagenomic
profiles
in
house
dust
related
the
quantitative
traits
of
pulmonary
function
and
airway
inflammation
adults.
Microbial
communities,
1264
species
(389
genera),
vacuumed
bedroom
from
779
a
US
cohort
were
characterized
by
whole
metagenome
shotgun
sequencing.
examined
two
overall
microbial
diversity
measures:
richness
(the
number
individual
species)
Shannon
index
(reflecting
both
relative
abundance).
To
specific
differentially
abundant
genera,
we
applied
Lasso
estimator
with
high-dimensional
inference
methods,
novel
framework
for
analyzing
microbiome
data
relation
after
accounting
all
taxa
together.
Results
Pulmonary
measures
(forced
expiratory
volume
one
second
(FEV
1
),
forced
vital
capacity
(FVC),
FEV
/FVC
ratio)
not
associated
diversity.
However,
many
genera
(
p
-value
<
0.05
controlling
other
examined)
,
FVC,
or
/FVC.
Similarly,
fractional
exhaled
nitric
oxide
(FeNO),
marker
inflammation,
was
unrelated
but
differential
abundance
genera.
Several
including
Limosilactobacillus
measure
FeNO,
while
others,
Moraxella
Stenotrophomonas
single
trait.
Conclusions
Using
state-of-the-art
sequencing,
identified
indoor
inflammation.
Some
previously
conditions;
others
novel,
suggesting
environmental
components
contribute
various
outcomes.
The
are
applicable
studying
Metabolites,
Год журнала:
2023,
Номер
13(3), С. 343 - 343
Опубликована: Фев. 24, 2023
Passengers
are
at
a
higher
risk
of
respiratory
infections
and
chronic
diseases
due
to
microbial
exposure
in
airline
cabins.
However,
the
presence
virulence
factors
(VFs),
antimicrobial
resistance
genes
(ARGs),
metabolites,
chemicals
yet
be
studied.
To
address
this
gap,
we
collected
dust
samples
from
cabins
two
airlines,
one
with
textile
seats
(TSC)
leather
(LSC),
analyzed
using
shotgun
metagenomics
LC/MS.
Results
showed
that
abundances
17
VFs
11
were
significantly
TSC
than
LSC
(
