Annual Review of Animal Biosciences,
Год журнала:
2020,
Номер
8(1), С. 199 - 220
Опубликована: Фев. 15, 2020
Ruminant
production
systems
face
significant
challenges
currently,
driven
by
heightened
awareness
of
their
negative
environmental
impact
and
the
rapidly
rising
global
population.
Recent
findings
have
underscored
how
composition
function
rumen
microbiome
are
associated
with
economically
valuable
traits,
including
feed
efficiency
methane
emission.
Although
omics-based
technological
advances
in
last
decade
revolutionized
our
understanding
host-associated
microbial
communities,
there
remains
incongruence
over
correct
approach
for
analysis
large
omic
data
sets.
A
that
examines
host/microbiome
interactions
both
lower
digestive
tract
is
required
to
harness
full
potential
gastrointestinal
sustainable
ruminant
production.
This
review
highlights
animal
community
may
identify
exploit
causal
relationships
between
gut
host
traits
interest
a
practical
application
health
Frontiers in Microbiology,
Год журнала:
2017,
Номер
8
Опубликована: Ноя. 15, 2017
Datasets
collected
by
high-throughput
sequencing
(HTS)
of
16S
rRNA
gene
amplimers,
metagenomes
or
metatranscriptomes
are
commonplace
and
being
used
to
study
human
disease
states,
ecological
differences
between
sites,
the
built
environment.
There
is
increasing
awareness
that
microbiome
datasets
generated
HTS
compositional
because
they
have
an
arbitrary
total
imposed
instrument.
However,
many
investigators
either
unaware
this
assume
specific
properties
data.
The
purpose
review
alert
dangers
inherent
in
ignoring
nature
data,
point
out
derived
from
studies
can
should
be
treated
as
compositions
at
all
stages
analysis.
We
briefly
introduce
illustrate
pathologies
occur
when
data
analyzed
inappropriately,
finally
give
guidance
resources
examples
for
analysis
using
Data
from
16S
ribosomal
RNA
(rRNA)
amplicon
sequencing
present
challenges
to
ecological
and
statistical
interpretation.
In
particular,
library
sizes
often
vary
over
several
ranges
of
magnitude,
the
data
contains
many
zeros.
Although
we
are
typically
interested
in
comparing
relative
abundance
taxa
ecosystem
two
or
more
groups,
can
only
measure
taxon
specimens
obtained
ecosystems.
Because
comparison
specimen
is
not
equivalent
ecosystems,
this
presents
a
special
challenge.
Second,
because
(as
well
as
ecosystem)
sum
1,
these
compositional
data.
constrained
by
simplex
(sum
1)
unconstrained
Euclidean
space,
standard
methods
analysis
applicable.
Here,
evaluate
how
impact
performance
existing
normalization
differential
analyses.
Effects
on
normalization:
Most
enable
successful
clustering
samples
according
biological
origin
when
groups
differ
substantially
their
overall
microbial
composition.
Rarefying
clearly
clusters
than
other
techniques
do
for
ordination
metrics
based
presence
absence.
Alternate
measures
potentially
vulnerable
artifacts
due
size.
testing:
We
build
previous
work
seven
proposed
using
rarefied
raw
Our
simulation
studies
suggest
that
false
discovery
rates
abundance-testing
increased
rarefying
itself,
although
course
results
loss
sensitivity
elimination
portion
available
For
with
large
(~10×)
differences
average
size,
lowers
rate.
DESeq2,
without
addition
constant,
smaller
datasets
(<20
per
group)
but
tends
towards
higher
rate
samples,
very
uneven
sizes,
and/or
effects.
drawing
inferences
regarding
ecosystem,
composition
microbiomes
(ANCOM)
sensitive
(for
>20
also
critically
method
tested
has
good
control
These
findings
guide
which
use
characteristics
given
study.
Nature Communications,
Год журнала:
2019,
Номер
10(1)
Опубликована: Июнь 20, 2019
Abstract
Differential
abundance
analysis
is
controversial
throughout
microbiome
research.
Gold
standard
approaches
require
laborious
measurements
of
total
microbial
load,
or
absolute
number
microorganisms,
to
accurately
determine
taxonomic
shifts.
Therefore,
most
studies
rely
on
relative
data.
Here,
we
demonstrate
common
pitfalls
in
comparing
across
samples
and
identify
two
solutions
that
reveal
changes
without
the
need
estimate
load.
We
define
notion
“reference
frames”,
which
provide
deep
intuition
about
compositional
nature
In
an
oral
time
series
experiment,
reference
frames
alleviate
false
positives
produce
consistent
results
both
raw
cell-count
normalized
Furthermore,
consistent,
differentially
abundant
microbes
previously
undetected
independent
published
datasets
from
subjects
with
atopic
dermatitis.
These
methods
allow
reassessment
data
reproducible
sequencing
output
for
new
assays.
Nature Communications,
Год журнала:
2022,
Номер
13(1)
Опубликована: Янв. 17, 2022
Identifying
differentially
abundant
microbes
is
a
common
goal
of
microbiome
studies.
Multiple
methods
are
used
interchangeably
for
this
purpose
in
the
literature.
Yet,
there
few
large-scale
studies
systematically
exploring
appropriateness
using
these
tools
interchangeably,
and
scale
significance
differences
between
them.
Here,
we
compare
performance
14
differential
abundance
testing
on
38
16S
rRNA
gene
datasets
with
two
sample
groups.
We
test
amplicon
sequence
variants
operational
taxonomic
units
(ASVs)
Our
findings
confirm
that
identified
drastically
different
numbers
sets
significant
ASVs,
results
depend
data
pre-processing.
For
many
number
features
correlate
aspects
data,
such
as
size,
sequencing
depth,
effect
size
community
differences.
ALDEx2
ANCOM-II
produce
most
consistent
across
agree
best
intersect
from
approaches.
Nevertheless,
recommend
researchers
should
use
consensus
approach
based
multiple
to
help
ensure
robust
biological
interpretations.
Many
available,
but
it
lacks
systematic
comparison
among
authors
groups,
show
results.
Applied and Environmental Microbiology,
Год журнала:
2016,
Номер
82(16), С. 5039 - 5048
Опубликована: Июнь 26, 2016
ABSTRACT
In
the
United
States,
1
in
8
women
will
be
diagnosed
with
breast
cancer
her
lifetime.
Along
genetics,
environment
contributes
to
disease
development,
but
what
these
exact
environmental
factors
are
remains
unknown.
We
have
previously
shown
that
tissue
is
not
sterile
contains
a
diverse
population
of
bacteria.
thus
believe
host's
local
microbiome
could
modulating
risk
development.
Using
16S
rRNA
amplicon
sequencing,
we
show
bacterial
profiles
differ
between
normal
adjacent
from
and
healthy
controls.
Women
had
higher
relative
abundances
Bacillus
,
Enterobacteriaceae
Staphylococcus
.
Escherichia
coli
(a
member
family)
epidermidis
isolated
patients,
were
induce
DNA
double-stranded
breaks
HeLa
cells
using
histone-2AX
(H2AX)
phosphorylation
(γ-H2AX)
assay.
also
found
microbial
similar
sampled
directly
tumor.
This
study
raises
important
questions
as
role
plays
development
or
progression
how
can
manipulate
this
for
possible
therapeutics
prevention.
IMPORTANCE
shows
different
exist
those
cancer.
Higher
bacteria
ability
cause
damage
vitro
detected
was
decrease
some
lactic
acid
bacteria,
known
their
beneficial
health
effects,
including
anticarcinogenic
properties.
mammary
Human
milk
is
an
important
source
of
bacteria
for
the
developing
infant
and
has
been
shown
to
influence
bacterial
composition
neonate,
which
in
turn
can
affect
disease
risk
later
life.
Very
little
known
about
what
factors
shape
human
microbiome.
The
goal
present
study
was
examine
microbiota
from
a
range
women
who
delivered
vaginally
or
by
caesarean
(C)
section,
gave
birth
males
females,
at
term
preterm.Milk
collected
39
Caucasian
Canadian
women,
microbial
profiles
were
analyzed
16S
ribosomal
RNA
(rRNA)
sequencing
using
Illumina
platform.A
diverse
community
found
with
most
dominant
phyla
being
Proteobacteria
Firmicutes
genus
level,
Staphylococcus,
Pseudomonas,
Streptococcus
Lactobacillus.
Comparison
between
preterm
births,
C
section
(elective
non-elective)
vaginal
deliveries,
male
female
infants
showed
no
statistically
significant
differences.The
revealed
types
transferred
newborns.
We
postulate
that
there
may
be
fail-safe
mechanism
whereby
mother
"ready"
pass
along
her
imprint
irrespective
when
how
baby
born.
bioRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2019,
Номер
unknown
Опубликована: Июнь 15, 2019
One
major
limitation
of
microbial
community
marker
gene
sequencing
is
that
it
does
not
provide
direct
information
on
the
functional
composition
sampled
communities.
Here,
we
present
PICRUSt2
(
https://github.com/picrust/picrust2
),
which
expands
capabilities
original
PICRUSt
method
1
to
predict
potential
a
based
profiles.
This
updated
and
implementation
includes
several
improvements
over
previous
algorithm:
an
expanded
database
families
reference
genomes,
new
approach
now
compatible
with
any
OTU-picking
or
denoising
algorithm,
novel
phenotype
predictions.
Upon
evaluation,
was
more
accurate
than
PICRUSt1
other
current
approaches
overall.
also
flexible
allows
addition
custom
databases.
We
highlight
these
important
caveats
regarding
use
predicted
metagenomes,
are
related
inherent
challenges
analyzing
metagenome
data
in
general.