Nanodiscs remain indispensable for Cryo-EM studies of membrane proteins
Current Opinion in Structural Biology,
Год журнала:
2025,
Номер
92, С. 103042 - 103042
Опубликована: Апрель 8, 2025
Язык: Английский
SynapseNet: Deep Learning for Automatic Synapse Reconstruction
Sarah Muth,
Frederieke Moschref,
Luca Freckmann
и другие.
bioRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2024,
Номер
unknown
Опубликована: Дек. 5, 2024
Abstract
Electron
microscopy
is
an
important
technique
for
the
study
of
synaptic
morphology
and
its
relation
to
function.
The
data
analysis
this
task
requires
segmentation
relevant
structures,
such
as
vesicles,
active
zones,
mitochondria,
presynaptic
densities,
ribbons,
compartments.
Previous
studies
were
predominantly
based
on
manual
segmentation,
which
very
time-consuming
prevented
systematic
large
datasets.
Here,
we
introduce
SynapseNet,
a
tool
automatic
synapses
in
electron
micrographs.
It
can
reliably
segment
vesicles
other
structures
wide
range
approaches,
thanks
annotated
dataset,
assembled,
domain
adaptation
functionality
developed.
We
demonstrated
capability
(semi-)automatic
biological
two
applications
made
it
available
easy-to-use
enable
novel
data-driven
insights
into
synapse
organization
Язык: Английский
CryoVIA: An image analysis toolkit for the quantification of membrane structures from cryo-EM micrographs
Structure,
Год журнала:
2025,
Номер
unknown
Опубликована: Фев. 1, 2025
Highlights•A
software
suite
for
automated
analysis
of
lipid
membranes
in
electron
micrographs•Includes
segmentation,
shape
identification,
and
membrane
properties•Applied
to
datasets
with
different
lipids
protein-induced
changes•Features
an
intuitive
GUI
batch
micrograph
analysisSummaryImaging
structures
associated
protein
complexes
using
cryoelectron
microscopy
(cryo-EM)
is
a
common
visualization
structure
determination
technique.
The
quantitative
the
structures,
however,
not
routine
time
consuming
particular
when
large
amounts
data
are
involved.
Here,
we
introduce
image-processing
cryo-vesicle
image
analyzer
(CryoVIA)
that
parametrizes
from
cryo-EM
images.
This
toolkit
combines
identification
methods
automatically
perform
large-scale
local
global
properties
such
as
bilayer
thickness,
size,
curvature
including
classifications.
We
included
analyses
exemplary
compositions
changes
through
endosomal
sorting
required
transport
III
(ESCRT-III)
remodeling
protein.
opens
new
possibilities
systematically
study
structural
their
modifications
images.Graphical
abstract
Язык: Английский