Communications Biology,
Journal Year:
2022,
Volume and Issue:
5(1)
Published: March 25, 2022
Genome-wide
association
studies
(GWAS)
are
increasingly
being
applied
to
investigate
the
genetic
basis
of
bacterial
traits.
However,
approaches
perform
power
calculations
for
GWAS
limited.
Here
we
implemented
two
alternative
conduct
using
existing
collections
genomes.
First,
a
sub-sampling
approach
was
undertaken
reduce
allele
frequency
and
effect
size
known
detectable
genotype-phenotype
relationship
by
modifying
phenotype
labels.
Second,
phenotype-simulation
conducted
simulate
phenotypes
from
variants.
We
both
into
computational
pipeline
(PowerBacGWAS)
that
supports
burden
testing,
pan-genome
variant
GWAS;
it
Enterococcus
faecium,
Klebsiella
pneumoniae
Mycobacterium
tuberculosis.
used
this
determine
sample
sizes
required
detect
causal
variants
different
minor
frequencies
(MAF),
heritability,
studied
homoplasy
population
diversity
on
Our
user
documentation
made
available
can
be
other
populations.
PowerBacGWAS
find
statistically
significant
associations,
or
associations
with
given
size.
recommend
genomes
species
study.
Nucleic Acids Research,
Journal Year:
2020,
Volume and Issue:
49(D1), P. D644 - D650
Published: Sept. 17, 2020
Abstract
An
increasing
prevalence
of
hospital
acquired
infections
and
foodborne
illnesses
caused
by
pathogenic
multidrug-resistant
bacteria
has
stimulated
a
pressing
need
for
benchtop
computational
techniques
to
rapidly
accurately
classify
from
genomic
sequence
data,
based
on
that,
trace
the
source
infection.
BacWGSTdb
(http://bacdb.org/BacWGSTdb)
is
free
publicly
accessible
database
we
have
developed
bacterial
whole-genome
typing
tracking.
This
incorporates
extensive
resources
genome
sequencing
data
corresponding
metadata,
combined
with
specialized
bioinformatics
tools
that
enable
systematic
characterization
isolates
recovered
infections.
Here,
present
2.0,
which
encompasses
several
major
updates,
including
(i)
integration
core
multi-locus
(cgMLST)
approach,
highly
scalable
appropriate
belonging
different
lineages;
(ii)
addition
multiple
analysis
module
can
process
dozens
user
uploaded
sequences
in
batch
mode;
(iii)
new
tracking
comparing
plasmid
those
deposited
public
databases;
(iv)
number
species
encompassed
2.0
increased
9
20,
represents
pathogens
medical
importance;
(v)
newly
designed,
user-friendly
interface
set
visualization
providing
convenient
platform
users
are
also
included.
Overall,
updated
bears
great
utility
continuing
provide
users,
epidemiologists,
clinicians
bench
scientists,
one-stop
solution
analysis.
Journal of Clinical Microbiology,
Journal Year:
2021,
Volume and Issue:
59(7)
Published: Jan. 29, 2021
Antimicrobial
resistance
(AMR)
remains
one
of
the
most
challenging
phenomena
modern
medicine.
Machine
learning
(ML)
is
a
subfield
artificial
intelligence
that
focuses
on
development
algorithms
learn
how
to
accurately
predict
outcome
variables
using
large
sets
predictor
are
typically
not
hand
selected
and
minimally
curated.
Frontiers in Microbiology,
Journal Year:
2021,
Volume and Issue:
12
Published: July 21, 2021
Rising
antibiotic
resistance
is
a
global
threat
that
projected
to
cause
more
deaths
than
all
cancers
combined
by
2050.
In
this
review,
we
set
summarize
the
current
state
of
resistance,
and
give
an
overview
emerging
technologies
aimed
escape
pre-antibiotic
era
recurrence.
We
conducted
comprehensive
literature
survey
>150
original
research
review
articles
indexed
in
Web
Science
using
“antimicrobial
resistance,”
“diagnostics,”
“therapeutics,”
“disinfection,”
“nosocomial
infections,”
“ESKAPE
pathogens”
as
key
words.
discuss
impact
nosocomial
infections
on
spread
multi-drug
resistant
bacteria,
over
existing
developing
strategies
for
faster
diagnostics
infectious
diseases,
novel
approaches
therapy
finally
hospital
disinfection
prevent
MDR
bacteria
spread.
FEMS Microbiology Reviews,
Journal Year:
2022,
Volume and Issue:
46(6)
Published: June 24, 2022
Escherichia
coli
is
the
most
researched
microbial
organism
in
world.
Its
varied
impact
on
human
health,
consisting
of
commensalism,
gastrointestinal
disease,
or
extraintestinal
pathologies,
has
generated
a
separation
species
into
at
least
eleven
pathotypes
(also
known
as
pathovars).
These
are
broadly
split
two
groups,
intestinal
pathogenic
E.
(InPEC)
and
(ExPEC).
However,
components
coli's
infinite
open
accessory
genome
horizontally
transferred
with
substantial
frequency,
creating
hybrid
strains
that
defy
clear
pathotype
designation.
Here,
we
take
birds-eye
view
species,
characterizing
it
from
historical,
clinical,
genetic
perspectives.
We
examine
wide
spectrum
disease
caused
by
coli,
content
bacterium,
its
propensity
to
acquire,
exchange,
maintain
antibiotic
resistance
genes
virulence
traits.
Our
portrayal
also
discusses
elements
have
shaped
overall
population
structure
summarizes
current
state
vaccine
development
targeted
frequent
pathovars.
In
our
conclusions,
advocate
streamlining
efforts
for
clinical
reporting
ExPEC,
emphasize
potential
exists
throughout
entire
species.
Clinical Microbiology Reviews,
Journal Year:
2022,
Volume and Issue:
35(3)
Published: May 25, 2022
Antimicrobial
resistance
(AMR)
is
a
global
health
crisis
that
poses
great
threat
to
modern
medicine.
Effective
prevention
strategies
are
urgently
required
slow
the
emergence
and
further
dissemination
of
AMR.
Given
availability
data
sets
encompassing
hundreds
or
thousands
pathogen
genomes,
machine
learning
(ML)
increasingly
being
used
predict
different
antibiotics
in
pathogens
based
on
gene
content
genome
composition.
A
key
objective
this
work
advocate
for
incorporation
ML
into
front-line
settings
but
also
highlight
refinements
necessary
safely
confidently
incorporate
these
methods.
The
question
what
not
trivial
given
existence
quantitative
qualitative
laboratory
measures
models
typically
treat
genes
as
independent
predictors,
with
no
consideration
structural
functional
linkages;
they
may
be
accurate
when
new
mutational
variants
known
AMR
emerge.
Finally,
have
technology
trusted
by
end
users
public
settings,
need
transparent
explainable
ensure
basis
prediction
clear.
We
strongly
next
set
AMR-ML
studies
should
focus
refinement
limitations
able
bridge
gap
diagnostic
implementation.
Military Medical Research,
Journal Year:
2024,
Volume and Issue:
11(1)
Published: Jan. 23, 2024
Abstract
Antimicrobial
resistance
is
a
global
public
health
threat,
and
the
World
Health
Organization
(WHO)
has
announced
priority
list
of
most
threatening
pathogens
against
which
novel
antibiotics
need
to
be
developed.
The
discovery
introduction
are
time-consuming
expensive.
According
WHO’s
report
antibacterial
agents
in
clinical
development,
only
18
have
been
approved
since
2014.
Therefore,
critically
needed.
Artificial
intelligence
(AI)
rapidly
applied
drug
development
its
recent
technical
breakthrough
dramatically
improved
efficiency
antibiotics.
Here,
we
first
summarized
recently
marketed
antibiotics,
antibiotic
candidates
development.
In
addition,
systematically
reviewed
involvement
AI
utilization,
including
small
molecules,
antimicrobial
peptides,
phage
therapy,
essential
oils,
as
well
mechanism
prediction,
stewardship.
