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10 Pathophysiology ofMicrovascular Disease inDiabetes
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it is minimally invasive and can be performed quickly.
Introduced in the 1960s, this test compares systolic blood
pressure of the of the upper extremity (brachial artery) to the
lower extremity to create a ratio which is a strong predictor
of vascular disease [61]. Values of 0.9 are considered normal,
while lower values signify varying degrees of vascular dysfunction. However, the setting of highly calcied vessels and
ABI can be above 1.3 which is also suspicious for peripheral
vascular disease.
Due to the pathophysiology of diabetes, patients can often
develop calcied vessels, and therefore an ABI is not the
most appropriate test and can mask the effect of PAD in
patients with diabetes [62]. In this case, clinicians will use a
toe-brachial index (TBI) or toe pressure to assess perfusion.
Transcutaneous Oxygen Tension
Given that oxygen is vital to maintaining optimal tissue
health and promoting wound healing processes, assessing
the oxygenation in the cutaneous microcirculation may be
considered as an important index of skin blood perfusion.
Transcutaneous oxygen tension (TcPO2) is an established
technique that allows for a noninvasive evaluation of the
partial pressure of oxygen in cutaneous tissue. Correlating
well with peripheral arterial disease, TcPO2 may also have
value in predicting healing rates in those suffering from
DFU and amputation rates in those with peripheral arterial
disease or ischemic ulcers [63]. In brief, using a probe that
is applied to the surface of the skin and heated to 45°C in
order to induce vasodilation, TcPO2 measures the transfer of
oxygen molecules from the blood vessels to the skin surface
with a decreased TcPO2 reading indicating decreased oxygenation. Given that TcPO2 only assesses the area of the tissue directly under the probe, it may be more clinically
relevant to perform multiple measurements across varied
regions rather than conducting a single assessment. Indeed,
a regional perfusion index, calculated by dividing the foot
TcPO2 value by a baseline TcPO2 value measured at the
chest, may provide more reliable data [64]. It must be noted
that TcPO2 may be less reliable in warm ambient environments and in those who are active smokers; have autonomic
neuropathy or vascular calcication, with or without peripheral arterial disease; or in those who have an active infection, oedema, or callus, due to arteriolar shunting that causes
TcPO2 readings to be less representative of the true state of
the microvascular health [65]. The “oxygen challenge,” in
which patients are administered 100% oxygen during the
TcPO2 assessment, has been proposed as a strategy to more
accurately detect true values that represent peripheral artery
diseases in such conditions.
Hyperspectral Imaging
Hyperspectral imaging (HSI) is a technology that can noninvasively measure oxygenate hemoglobin and deoxygenated
hemoglobin concentrations in the subpapillary skin plexus.
This nonionizing and noncontact camera records twodimensional images of biological tissue and is effective in
measuring oxygenation levels of tissues. In brief, HSI is a
spectroscopic method that combines digital imaging with
conventional spectroscopy. HSI collects images as a function
of wavelength and provides an individualized reectance or
uorescence spectrum for each pixel in an image.
Wavelengths of visual light in the 500- to 660-nm range,
which includes the absorption peaks for oxyHb and deoxyHb,
are collected from each pixel in an image and broken down
by a spectral separator to generate a diffuse reectance spectrum. These spectra from each pixel are compared against
standard transmission solutions to determine the concentration of oxyHb and deoxyHb present in each visualized pixel
[66]. These wavelengths of light penetrate to 1–2mm below
the skin and thus obtain information from the subpapillary
plexus. The imager and hemoglobin calculation algorithm is
calibrated for different skin pigmentations.
Given its ability to easily quantify levels of oxygenated
hemoglobin within the wound, hyperspectral imaging has
been used for the last decade in the management of DFUs.
DFUs require normal, if not higher, level of cutaneous oxygen to heal and therefore HSI allows clinicians to quickly
assess whether there is satisfactory blood ow to sustain
such oxygen levels.
Laser Doppler
One of the most common methods adopted by researchers over
recent decades to quantify changes in cutaneous microvascular
function has been the laser Doppler owmetry (LDF). The
laser Doppler principle is based upon the phenomenon that
when a laser beam emitted by the imaging device hits moving
red blood cells in the cutaneous vessels, the light undergoes a
change in wavelength (Doppler shift) and the backscatter is
detected by the device [67]. The laser Doppler signal, quantied as the product of mean red blood cell velocity and concentration, provides an index of cutaneous perfusion referred to as
ux, rather than a direct measure of cutaneous blood ow.
Using a single-point laser probe and a high sampling frequency
of approximately 32Hz, LDF is capable of accurately quantifying rapid variations in cutaneous blood ow within a volume
of 1mm [3] or smaller. However, considering the anatomical
heterogeneity of the cutaneous microcirculation and the relatively small vascular region that can be assessed, LDF is sub-
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B. J. Sumpio and A. Veves
ject to increased spatial variability and thus presents relatively
poor reproducibility between measurements.
Laser Doppler imaging (LDI) is an alternative laser
Doppler-based imaging technology that scans a tissue bed of
interest (e.g., the volar surface of the forearm) to produce a
2D image and map cutaneous blood ux within that region,
with each pixel representing a separate perfusion value [68].
In contrast to LDF, where the laser unit is in direct contact
with the skin, LDI emits a laser beam at a set distance above
the skin surface. Therefore, given that LDI is capable of
assessing a large area of the cutaneous microvasculature in a
single scan, the spatial variability associated with LDF is
reduced. However, the image rate of LDI is much slower
than that of LDF, and therefore it is not possible to detect
rapid changes in cutaneous perfusion. Furthermore, research
commonly performs a single scan to acquire baseline and
post-intervention perfusion values, resulting in images that
correspond to a brief time point during the assessment of
microvascular function. Consequently, critical events (e.g.,
peak responses to tests of vascular reactivity) may be completely missed, introducing temporal variability and severely
limiting the reproducibility and interpretation of LDI data.
Complications fromVascular Dysfunction
Diabetic Foot Ulcers
The presence of PAD considerably decreases the levels of
oxygen and nutrients delivered to the extremities. Oxygen is
a critical component of wound healing and plays a role in
almost every step of the healing process [73]. In the earlier
stages of diabetes, there is only minimal disruption in oxygen delivery. However, as the disease progresses, there is
intimal thickening which consists of increased smooth muscle cell proliferation which eventually decreases the delivery
of oxygen to tissues [74]. In the setting of wounds, this local
hypoxia directly inhibits the cells’ ability to heal. Chronic
hypoxemia therefore decreases cell proliferation and impairs
neo-angiogenesis. As previously mentioned, for wound healing and tissue remodeling to take place, broblasts must differentiate in a process that requires TGF-B and PDGF via
oxygen-catalyzed reactions [75].
Diabetes also creates a plethora of systemic effects that
can impair wound healing, including hyperglycemia, a proinammatory state, neuropathy, and tissue hypoxia.
Hyperglycemia causes excessive glycosylation of proteins
and the ultimate formation of advanced glycation end products. These products in turn trigger the expression of proinammatory cytokines and are responsible for oxidative
damage and extracellular changes [18]. Fibroblast, keratinocyte, and endothelial cell proliferation becomes decreased or
inhibited in response to elevated plasma glucose levels. In
addition, the function of multiple inammatory cell types is
negatively impacted by diabetes [19–23].
Peripheral arterial disease is four to six times more prevalent
in patients with diabetes between the ages of 45 and 75years
than in those without diabetes with equal female and male
prevalence [69]. Diabetic foot ulcers are a common complication as a consequence of this. Approximately one quarter
of patients with diabetes develop a DFU throughout their
lifetime [70]. Unfortunately, DFU are notoriously difcult to
manage. Margolis et al., in their meta-analysis review,
showed that when using just the standard of care, a majority
of DFUs failed to heal in 12weeks [71]. Unfortunately, when
these wounds fail to heal, they affect patients’ quality of life
but can also led to more serious complications such as infection and sepsis. Ultimately over 15% will require an amputation [72].
The healing of DFUs relies on meticulous wound care as
well as adequate perfusion. There are multiple products
available that serve to supplement wound healing for DFUs,
but without adequate blood ow and oxygenation to the
wound bed, it is unlikely a wound will heal. Therefore, a
multidisciplinary approach is needed to care for this patient
demographic. This review will rst focus on current treatments for managing DFU and then discuss new advancements in DFU treatments to may improve outcomes in the
future.
Diabetic Neuropathy
Although diabetic neuropathy has been classically dened as
a microvascular complication, the relationship between skin
microvascular dysfunction and neuropathy in diabetes is
complex. From a mechanistic perspective, peripheral neuropathy and endothelial dysfunction share similar pathophysiological pathways. For example, increased intracellular
glucose increases the polyol pathway ux. In addition to
depleting the cellular NADPH reserve, increased aldosereductase transformation of glucose leads to sorbitol accumulation, which dedifferentiate Schwann cells into immature
cells [76]. Oxidative stress and AGEs also play an important
role in the pathophysiology of neuropathy.
The ability of the skin to adequately regulate blood ow
in response to temperature variations or to a variety of
mechanical and chemical stimuli is highly dependent on the
existence of intact neurovascular function. Patients with diabetes both with and without clinical neuropathy have demonstrated impaired thermoregulation [77]. In those with
uncomplicated type 2 diabetes (without any comorbidities),
vasodilation in response to whole-body heating is impaired,
suggesting abnormal cholinergic sympathetic function and/
10 Pathophysiology ofMicrovascular Disease inDiabetes
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or impaired cholinergic transmission (possibly involving
substance P) [78].
Unfortunately, when patients develop neuropathy, they
become more prone to develop cutaneous injuries. The loss
of proprioception and touch causes patients with diabetes to
become unaware of their peripheral surrounds. As a result,
injuries that include skin disruption by sharp objects, pressure sores related to inappropriate small shoe size and, even
more commonly, plantar sores associated with high foot
pressures during walking, do not receive timely treatment
and become chronic, non-healing wounds. Additionally, the
loss of temperature sensation can lead patients with diabetes
to walk on hot pathways without realizing as well as develop
frostbite in the cold. Together this neuronal loss increases the
propensity for patients to develop foot ulcers.
Conclusion
In conclusion, diabetes and hyperglycemia can lead to multiple systemic effects on both the structural and functional
impairment of the vascular system. In this chapter we have
shown the normal physiology of vascular endothelium and
the precision it must have to promote vascular tone, permeability, and proliferation. However, despite this complex
homeostasis, the consequences of diabetes leads to vascular
dysfunction via multiple pathways. Impaired NO synthesis
decreases vasodilation, hyperglycemia increases proinammatory cytokines, and thickened basement membrane works
to impair the body’s ability to react to vascular injury. This
ultimately leads to systemic effects on nearly all organ systems causing, neuropathy, nephropathy, retinopathy, and diabetic foot ulcers. By understanding the pathophysiology
behind how diabetes affects the vascular system, researchers
and clinicians can gain a better understanding on how to treat
and manage this disease in patients.
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High Content Single Cell andSpatial
https://t.me/med1917
Tissue Profiling Modalities
forDeciphering thePathogenesis
andTreatment ofWound Healing
YeredH.Pita-Juarez, NikolasKalavros,
DimitraKaragkouni, YulingMa, Xanthi-LidaKatopodi,
andIoannisS.Vlachos
11
Abstract
Recently developed -omics techniques have revolutionized
various areas of biology, vastly increasing both the throughput of experiments, as well as the insights that can be
acquired. The available repertoire of technologies keeps
expanding at an ever-increasing pace, with approaches such
as transcriptomics emerging as some of the most information-rich and benecial methods to address questions ranging from clinical phenotypes to mechanistic insights. In this
chapter, we examine wound healing through the prism of
transcriptome proling experiments, including bulk, singlecell as well as spatial transcriptomics. We aim to both highlight the signicance of these novel methods through
reviewing seminal studies that used them, as well as disentangle their workow, both experimental and computational,
demonstrating their ongoing democratization. We explore
the signicance and promise of single-cell and spatial transcriptomics in discovering the underlying mechanisms of
wound healing and identifying new therapeutic targets.
Yered H.Pita-Juarez and Nikolas Kalavros contributed equally to this
work.
Y. H. Pita-Juarez · D. Karagkouni · Y. Ma · X.-L. Katopodi
I. S. Vlachos (*)
Department of Pathology, Beth Israel Deaconess Medical Center,
Boston, MA, USA
Harvard Medical School, Boston, MA, USA
Broad Institute of MIT and Harvard, Cambridge, MA, USA
e-mail: ivlachos@bidmc.harvard.edu
N. Kalavros
Department of Pathology, Beth Israel Deaconess Medical Center,
Boston, MA, USA
Harvard Medical School, Boston, MA, USA
Broad Institute of MIT and Harvard, Cambridge, MA, USA
Spatial Technologies Unit, Harvard Initiative for RNA Medicine,
Beth Israel Deaconess Medical Center, Boston, MA, USA
Abbreviations
5ALA 5-aminolevulinic acid
ADK Adenosine kinase
Angptl4 Angiopoietin-like 4 protein
ATAC-seq Assay of transposase-accessible chromatin
with sequencing
Bu-HFSCs Bulge hair follicle stem cells
CCIs Cell-cell interactions
eAdo Extracellular adenosine
ECM Extracellular matrix
ENTs Equilibrative nucleoside transporters
FLIM Fluorescence lifetime imaging microscopy
GBM Glioblastoma
GBS Group B Streptococcus
GEM Gel beads in emulsion
GSEA Gene set enrichment analysis
HFN Hair follicle neogenesis
i202b Interferon-activated gene 202B
MDF Mouse dermal broblasts
MES Mesenchymal subtype
Nr-CWS Nocardia rubra cell wall skeleton
PBMCs Peripheral Blood Mononuclear Cells
PCA Principal component analysis
RNA-seq RNA sequencing
scRNA-seq Single cell RNA sequencing
SCs Stem cells
Shh signaling Sonic hedgehog signaling
ST Spatial transcriptomics
t-SNE t-distributed stochastic neighbor
embedding
UMAP Uniform Manifold Approximation and
Projection
WIHN Wound-induced hair follicle neogenesis
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024
A. Veves et al. (eds.), The Diabetic Foot, Contemporary Diabetes, https://doi.org/10.1007/978-3-031-55715-6_11
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Y. H. Pita-Juarez et al.
Introduction
The rapid developments of genomic, transcriptomic, and
proteomic techniques have resulted in radical changes in our
understanding of tissue alterations related to development,
homeostasis, and disease [1]. Bulk transcriptomic proling
methods, such as RNA-seq and microarrays, are powerful
methods to characterize the average gene expression across
an entire tissue, biouid, or cell population sample [2].
Genomics technologies have promised more precise disease
subgroupings and their optimal matched treatment with
novel targeted therapeutics [3]. Data acquisition and analy-
Genetics Environment
Inter-and Intra-Patient Heterogeneity
sis are central to such efforts, since the quantity, quality,
level of detail, and physiological relevance of patient information are the main tools utilized to stratify individuals into
relevant groups for prediction of events, such as treatment
response, disease progression rates, and likelihood of disease recurrence (Fig.11.1) [4]. Such analyses have enabled
us to characterize the diabetic wound immune microenvironment [5–7] and potential therapeutic avenues, including
treatment with primary cells, secretomes, compounds, or
whole devices [8–12].
This series of rst -omic driven breakthroughs have led to
a much clearer understanding of the involved processes and
Stochasticity
Precision medicine
Pathogenesis
Mechanisms
Hypothesis
Fig. 11.1 Overview of bulk, single cell, and spatial transcriptomic
studies. An idealized workow for achieving precision medicine
through bulk RNA-sequencing (Bulk RNA-seq), single-cell RNA-
Disease
Models
Treatment
Development
Multi-omics Analyses
Bulk RNA
Genome
Epigenome
Transcriptome
Proteome
Metabolome
Decipher Heterogeneity, identity drivers,
construct microenvironment networks
sequencing (scRNA-seq), and spatial transcriptomics (ST), in addition
to other tissue proling techniques
scRNA
Spatial RNA
11 High Content Single Cell and Spatial Tissue Proling Modalities for Deciphering the Pathogenesis and Treatment of Wound…
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have empowered our ability to form a next generation of relevant questions, homing in the interactions between the different cellular components during wound healing, the effect
of therapeutics on diverse cell populations, as well as the role
of wound architecture or glucose homeostasis on the cellular
response to wounding. It has become increasingly apparent
that the homogenization of tissue and the averaging into a
single set of measurements, performed in assays, such as bulk
RNA-seq or microarrays, has often led to an inability to detect
rare cell types and subpopulations relevant to disease [3].
Single-Cell RNA Sequencing
The aforementioned shortcomings fueled a series of innovations focusing on capturing -omic proles at single cell resolution, or by keeping tissue architecture and structural
information intact. Single cell -omics and especially single
cell RNA sequencing (scRNA-seq) enable us to assess the
transcriptional proles of individual cells, providing an
unparallelled granularity and information density
(Table 11.1) [15]. In a single cell sequencing preparation,
instead of tissue homogenization, the samples are dissociated into single cell suspensions. Subsequently, by following
different strategies, most commonly encapsulation in microdroplets [16] or plating of each cell in single wells [17], they
are subjected to -omic interrogations independently.
In the context of wound healing process, the human skin
has a multilayer architecture dened by diverse cell populations, primarily keratinocytes and broblasts, as well as
immune cells, melanocytes, adipocytes, and endothelial cells
that orchestrate events leading to wound repair, as well as
response to pathogenic infection, exposure to ultraviolet
radiation, or toxic compounds (Fig.11.2) [17]. Dissociation
of skin samples into single cell suspensions can be challenging due to the different cell compositions and properties of
the skin's layers [18]. There are multiple single-cell dissociation techniques available depending on whether the dermis,
epidermis, or both are required to be represented in the cell
suspension for a given experiment [7].
In this regard, scRNA-seq has become a very powerful
tool to perform investigations that could not be addressed by
other methodologies, such as the assessment of cell-to-cell
variation, the identication of rare populations, and the
determination of heterogeneity within a cell population [3,
18]; insights are usually lost as background noise in bulk
RNA sequencing experiments [19, 20]. In addition, scRNAseq can be utilized to identify target cell populations for a
specic pathologic phenotype, as well as to capture cellular
response to treatment. In wound healing, scRNA-seq not
only provides a powerful means to investigate cellular heterogeneity and treatment responses but also offers a unique
window into the intricate cellular processes that drive the
wound healing cascade, enabling a more comprehensive
understanding of this critical biological phenomenon. All the
above are pivotal for new target identication and elucidating the mechanisms of action of therapeutics, playing a vital
role in precision medicine efforts. They aid in diagnosis,
prognosis, guide treatment selection, and support drug development [21–24].
Table 11.1 Overview of scRNA-seq assays
Platform Single-cell isolation Cell numbers Coverage UMI Amplication
Smart-seq FACS Hundreds of cells Full-length No PCR
Smart-seq2 FACS Hundreds of cells Full-length No PCR
Fluidigm C1 Micro-uidic Hundreds of cells Full-length No PCR
Drop-seq Microdroplets Large number of cells
10× Genomics Microdroplets Large number of cells
MATQ-seq FAC S Hundreds of cells Full-length Ye s PCR
Seq-well Micro-uidic Large number of cells
CEL-seq FACS Hundreds of cells
MARS-seq FACS Hundreds of cells
inDrop-seq Microdroplets Large number of cells
DNBelab C4 Microdroplets Large number of cells
SCRB-seq FAC S Large number of cells
Abbreviations: FAC S uorescence-activated cell sorting; IVT invitro transcription; PCR polymerase chain reaction; UMI unique molecular identier; MATQ-seq multiple annealing and dC-tailing-based quantitative single-cell RNA-seq; MARS-seq massively parallel single-cell RNAsequencing; DNB-seq DNA Nanoball Sequencing; SCRB-seq single cell RNA barcoding and sequencing [13, 14]
3′ end
3′ end, 5′ end
3′ end
3′ end
3′ end
3′ end
3′ end
3′ end
Yes PCR
Yes PCR
Yes PCR
Yes IVT
Yes IVT
Yes IVT
Yes PCR
Yes PCR
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Fig. 11.2 Sources of cells in the human skin. Diagram of the major features and anatomic organization of human skin. Cell-type composition of
the epidermis and dermis
Y. H. Pita-Juarez et al.
Spatial Tissue Proling andSpatial
Transcriptomics
Transcriptome profiling of tissues and single cells enables
the analysis of gene expression changes in a variety of
biological contexts at very high resolution. However, crucial information, such as tissue architecture or cell localization and co-localization, are lost during tissue
homogenization for bulk assays or dissociation into single cell suspensions for scRNA-seq [1, 3]. Recent
advances have enabled us to perform -omic assays in situ,
while keeping the tissue intact [25–27]. These assays,
collectively called spatial -omics, allow for the localization of cell types and their associated -omic profiles
within intact tissues [1]. Spatial transcriptomics (ST)
permits us to capture gene expression profiles in situ,
promising to revolutionize research and diagnostic procedures. For this, it was named “Method of the Year
2020” by Nature Methods [28].
ST can be used to uncover coordinated cellular behavior,
in the form of cellular phenotypes manifested within niches /
cellular neighborhoods, composed of multiple and diverse
cell types, which are lost in bulk or even single cell assays
[1], as well as the detailed characterization of cell-cell interactions (CCIs) [23]. ST is especially useful in capturing
complicated highly localized and topology-centric biological
processes, such as wound healing, by providing a precise
understanding of molecular and cellular events that occur in
specic locations of tissues and cell type contexts.
Under the broad ST term, we often include methods that
can be divided into ve principal approaches to resolve spa-
tial distribution of transcripts. They are (1) in situ sequencing,
(2) in situ capture protocols, (3) microdissection techniques,
(4) uorescent in situ hybridization methods, and (5) purely
in silico approaches (Table 11.2). We can also divide them
into two main categories, depending on the target space, targeted or unbiased. Targeted methods capture the expression
of a pre-selected group of genes, while unbiased methods
capture the entire transcriptome (Table11.2). Each methodology has its own set of strengths and limitations, and researchers choose the appropriate method on the basis of the
molecules of interest and the desired spatial resolution [1].
However, across all modalities, ST technologies suffer
from limitations in maximal transcript capture efciency,
throughput, or resolution of transcript locality (Table11.2).
To tackle current limitations, researchers often perform tandem scRNA-seq and ST, which are then integrated in silico,
maximizing the potential for high-resolution transcriptomic
proling in spatial contexts by leveraging the advantages of
each technology [23]. When applied to disease models or
distinct biological contexts, these data enable novel
hypothesis generation and mechanistic dissection. This
knowledge is particularly useful in clinical settings for the
identication of diagnostic biomarkers, the prioritizations of
novel therapeutic targets, and the improvement of prognostication efforts. The development of multi-omic tools, all of
which are steadily approaching single-cell resolution, and
their application to disease is analogous to acquiring a new
piece of an ever-changing puzzle. Assembling these pieces
will eventually broaden the prospects of precision medicine
by demonstrating the ability to robustly connect clinical phenomena to empirical measurements [23].
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Table 11.2 Overview of ST assays
Capture
Platform Resolution
10× Genomics—Xenium Subcellular Targeted Fluorescence in situ
10× Genomics Visium (v1, v2)
Barcoded padlock probe ISS Subcellular Targeted In situ sequencing Up to 100
Bio-Techne—RNAscope HiPlex v2 Subcellular Targeted Fluorescence in situ
CODEX—PhenoCycler/PhenoCycler fusion Subcellular Targeted Fluorescence in situ
Curio biosciences—Curio seeker 1–2 cell resolution
FISSEQ Subcellular Unbiased In situ sequencing Whole transcriptome
NanoString—CosMx Subcellular Targeted Fluorescence in situ
nanoString—GeoMx DSP Areas of interest
Seq-scope
seqFISH Subcellular Targeted Fluorescence in situ
seqFISH+ Subcellular Targeted Fluorescence in situ
Slide-seq
Spatial Genomics—seqFish Subcellular Targeted Fluorescence in situ
STARmap Subcellular Targeted In situ sequencing Up to 1000
Vizgen—MERSCOPE/MERFISH Subcellular Targeted Fluorescence in situ
Overview of commercially available spatial transcriptomics platforms [1, 23, 29–33]
55-μm diameter
capture spots
(10μm spatially
indexed beads)
comprising 50+ cells
∼0.6-μm diameter
capture spots
(subcellular)
10-μm diameter
capture spots
method Methodology
hybridization
Unbiased In situ capture Whole transcriptome,
hybridization
hybridization
Unbiased In situ capture Whole transcriptome
hybridization
Targeted and
unbiased
Unbiased In situ capture Whole transcriptome
Unbiased In situ capture Whole transcriptome
In situ capture 96 targets with nCounter readout
hybridization
hybridization
hybridization
hybridization
Number of unique genes assayed
(multiplex capacity)
~400
RNA+protein
12 targets (FFPE) and 48 targets
(fresh or xed frozen)
~50+
1000
Or whole transcriptome via NGS
Up to 249
Up to 10,000
Up to 249
500
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In the following sections, we will highlight some of the
groundbreaking studies employing bulk, single-cell, and
spatial transcriptomics for wound healing in the skin, in both
animal and human models. For each study, we will point out
both their novelty as well as their future potential. We will
provide an overview of the methodology followed by the
authors and how it can assist in downstream investigations.
Finally, step-by-step approaches of the analysis of scRNA- seq
and spatial assays will be presented, discussing the widely
adopted tools and methodologies and highlighting those that
have been extensively used in wound healing studies.
Preclinical Animal andHuman Models
inWound Healing Bulk RNA Studies
Bulk RNA-seq, along with microarrays, are the rst and
most commonly used approaches to study gene expression
proles in wound healing research. These techniques allow
for the measurement of gene expression levels in whole populations of cells, delineating a prole of the overall gene
expression in the wound site [3, 34].
In this section, we aim to highlight bulk RNA-seq studies
which have contributed to our understanding of wound healing processes in both animal and human tissues (Table11.3).
These studies encompass three core axes in wound healing
research; the investigation of transcriptomic proles in the
diabetic wound versus the non-diabetic wound, the research
of the immune component implication in the wound healing,
as well as potential therapeutic approaches.
Focusing on the diabetic wound, Theocharidis etal. [5]
studied wound healing in diabetic foot ulcers (DFU) in
human samples, with the aim of revealing potential targets
for reinforcing DFU healing. The authors performed bulk
RNA-seq in three distinct cohorts, one control non-DFU
group and two distinct DFU groups classied as healer and
non-healer, respectively. Inammatory biomarkers were
shown to correlate with enhanced wound healing, including
angiogenesis regulators such as VEGF and sVCAM.
Similarly, Singh etal. [6] studied the impact of diabetes on
angiogenesis in the context of the diabetic wounds in humans
and mice. To underline the importance of endothelial cells
during wound healing, they co-cultured human umbilical
vein endothelial cells (HUVECs) with two different types of
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