Spatial Transcriptomics: Biotechnologies, Computational Tools, and Neuroscience Applications
Small Methods,
Год журнала:
2025,
Номер
unknown
Опубликована: Янв. 6, 2025
Spatial
transcriptomics
(ST)
represents
a
revolutionary
approach
in
molecular
biology,
providing
unprecedented
insights
into
the
spatial
organization
of
gene
expression
within
tissues.
This
review
aims
to
elucidate
advancements
ST
technologies,
their
computational
tools,
and
pivotal
applications
neuroscience.
It
is
begun
with
historical
overview,
tracing
evolution
from
early
image-based
techniques
contemporary
sequence-based
methods.
Subsequently,
methods
essential
for
data
analysis,
including
preprocessing,
cell
type
annotation,
clustering,
detection
spatially
variable
genes,
cell-cell
interaction
3D
multi-slices
integration
are
discussed.
The
central
focus
this
application
neuroscience,
where
it
has
significantly
contributed
understanding
brain's
complexity.
Through
ST,
researchers
advance
brain
atlas
projects,
gain
development,
explore
neuroimmune
dysfunctions,
particularly
tumors.
Additionally,
enhances
neuronal
vulnerability
neurodegenerative
diseases
like
Alzheimer's
neuropsychiatric
disorders
such
as
schizophrenia.
In
conclusion,
while
already
profoundly
impacted
challenges
remain
issues
enhancing
sequencing
technologies
developing
robust
tools.
underscores
transformative
potential
paving
way
new
therapeutic
research.
Язык: Английский
Multiscale Dissection of Spatial Heterogeneity by Integrating Multi‐Slice Spatial and Single‐Cell Transcriptomics
Advanced Science,
Год журнала:
2025,
Номер
unknown
Опубликована: Фев. 25, 2025
Abstract
The
spatial
structure
of
cells
is
highly
organized
at
multiscale
levels
from
global
domains
to
local
cell
type
heterogeneity.
Existing
methods
for
analyzing
spatially
resolved
transcriptomics
(SRT)
are
separately
designed
either
domain
alignment
across
multiple
slices
or
deconvoluting
compositions
within
a
single
slice.
To
this
end,
novel
deep
learning
method,
SMILE,
proposed
which
combines
graph
contrastive
autoencoder
and
multilayer
perceptron
with
constraints
learn
informative
spot
representations.
By
comparing
SMILE
the
state‐of‐the‐art
on
simulation
real
datasets,
superior
performance
demonstrated
alignment,
identification,
deconvolution.
results
show
SMILE's
capability
not
only
in
simultaneously
dissecting
variations
different
scales
but
also
unraveling
altered
cellular
microenvironments
diseased
conditions.
Moreover,
can
utilize
prior
annotation
information
one
slice
further
enhance
performance.
Язык: Английский
Spatial transcriptomics in breast cancer: providing insight into tumor heterogeneity and promoting individualized therapy
Frontiers in Immunology,
Год журнала:
2024,
Номер
15
Опубликована: Дек. 19, 2024
A
comprehensive
understanding
of
tumor
heterogeneity,
microenvironment
and
the
mechanisms
drug
resistance
is
fundamental
to
advancing
breast
cancer
research.
While
single-cell
RNA
sequencing
has
resolved
issue
"temporal
dynamic
expression"
genes
at
level,
lack
spatial
information
still
prevents
us
from
gaining
a
cancer.
The
introduction
application
transcriptomics
addresses
this
limitation.
As
annual
technical
method
2020,
preserves
location
tissues
resolves
RNA-seq
data
help
localize
differentiate
active
expression
functional
within
specific
tissue
region,
enabling
study
attributes
gene
locations
cellular
environments.
In
context
cancer,
can
assist
in
identification
novel
subtypes
spatially
discriminative
features
that
show
promise
for
individualized
precise
treatment.
This
article
summarized
key
approaches,
recent
advances
its
applications
discusses
limitations
current
methods
prospects
future
development,
with
view
technology
clinical
practice.
Язык: Английский
Transcriptomic Approaches to Cardiomyocyte–Biomaterial Interactions: A Review
ACS Biomaterials Science & Engineering,
Год журнала:
2024,
Номер
10(7), С. 4175 - 4194
Опубликована: Июнь 27, 2024
Biomaterials,
essential
for
supporting,
enhancing,
and
repairing
damaged
tissues,
play
a
critical
role
in
various
medical
applications.
This
Review
focuses
on
the
interaction
of
biomaterials
cardiomyocytes,
emphasizing
unique
significance
transcriptomic
approaches
understanding
their
interactions,
which
are
pivotal
cardiac
bioengineering
regenerative
medicine.
Transcriptomic
serve
as
powerful
tools
to
investigate
how
cardiomyocytes
respond
biomaterials,
shedding
light
gene
expression
patterns,
regulatory
pathways,
cellular
processes
involved
these
interactions.
Emerging
technologies
such
bulk
RNA-seq,
single-cell
single-nucleus
spatial
transcriptomics
offer
promising
avenues
more
precise
in-depth
investigations.
Longitudinal
studies,
pathway
analyses,
machine
learning
techniques
further
improve
ability
explore
complex
mechanisms
involved.
review
also
discusses
challenges
opportunities
utilizing
cardiomyocyte-biomaterial
research.
Although
there
ongoing
costs,
cell
size
limitation,
sample
differences,
analytical
process,
exist
exciting
prospects
comprehensive
biomaterial
design,
disease
treatment,
drug
testing.
These
multimodal
methodologies
have
capacity
deepen
our
intricate
network
between
potentially
revolutionizing
research
with
aim
promoting
heart
health,
they
studying
interactions
other
types.
Язык: Английский
Transcriptomics in the Study of Antiviral Innate Immunity
Methods in molecular biology,
Год журнала:
2024,
Номер
unknown, С. 83 - 91
Опубликована: Авг. 27, 2024
Язык: Английский
Single Cell RNA Sequencing and Data Analysis
Elsevier eBooks,
Год журнала:
2024,
Номер
unknown
Опубликована: Янв. 1, 2024
Язык: Английский
Trends and Challenges of the Modern Pathology Laboratory for Biopharmaceutical Research Excellence
Toxicologic Pathology,
Год журнала:
2024,
Номер
unknown
Опубликована: Дек. 13, 2024
Pathology,
a
fundamental
discipline
that
bridges
basic
scientific
discovery
to
the
clinic,
is
integral
successful
drug
development.
Intrinsically
multimodal
and
multidimensional,
anatomic
pathology
continues
be
empowered
by
advancements
in
molecular
digital
technologies
enabling
spatial
tissue
detection
of
biomolecules
such
as
genes,
transcripts,
proteins.
Over
past
two
decades,
breakthroughs
biology
automation
digitization
laboratory
processes
have
enabled
implementation
higher
throughput
assays
generation
extensive
data
sets
from
sections
biopharmaceutical
research
development
units.
It
our
goal
provide
readers
with
some
rationale,
advice,
ideas
help
establish
modern
meet
emerging
needs
research.
This
manuscript
provides
(1)
high-level
overview
current
state
future
vision
for
excellence
practice
(2)
shared
perspectives
on
how
optimally
leverage
expertise
discovery,
toxicologic,
translational
pathologists
effective
spatial,
molecular,
support
discovery.
captures
insights
experiences,
challenges,
solutions
laboratories
various
organizations,
including
their
approaches
troubleshooting
adopting
new
technologies.
Язык: Английский
Spatially Variable Genes
Shantagoud Biradar,
Chaaya Suresh,
Nagashri Nanjundeshwara
и другие.
Advances in medical diagnosis, treatment, and care (AMDTC) book series,
Год журнала:
2024,
Номер
unknown, С. 1 - 28
Опубликована: Дек. 17, 2024
The
clinical
translation
of
spatial
transcriptomics
represents
cancer
diagnosis
and
therapy
based
on
the
role
heterogeneity
cancer-associated
fibroblasts
(CAFs)
within
tumor
microenvironment
(TME).
Recent
developments
in
have
enabled
a
detailed
characterization
organization
cellular
interactions
tumors.
data
integration,
multi-omics
approaches,
along
with
developing
standardized
protocols
is
essential
for
effective
translation.
experimental
selection
regimes
factorial
designs
reveals
novel
insights
into
biomarkers
prognostic
value
CAFs.
incorporation
optogenetics
advancements
bio-engineered
gene
circuits,
therapeutics
tissue
engineering
further
underscores
potential
to
refine
patient
stratification
improve
treatment
responsiveness.
By
integrating
workflows,
this
work
aims
advance
personalized
therapies
biology.
Язык: Английский