Graphical abstract
graphic file with name fx1.jpg
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Highlights
* •
Organotypic airway models can investigate EV-mediated intercellular
communication
* •
Increasing in vitro model complexity alters EV proteomic content
and diversity
* •
Different pulmonary cell types uniquely affect EV proteomic
composition
* •
Cellular composition of in vitro models is important to consider in
EV studies
__________________________________________________________________
Molecular physiology; Cell biology; Proteomics.
Introduction
Extracellular vesicles (EVs) are small, membrane-bound particles
released by a cell into the extracellular
space.[36]^1^,[37]^2^,[38]^3^,[39]^4 EVs can contain nucleic acids,
proteins, and lipids from their cell of origin and can release this
cargo into a recipient cell upon fusion with the cell
membrane.[40]^1^,[41]^2^,[42]^3^,[43]^4 This transfer of EV cargo can
significantly alter gene and protein expression in the recipient cell,
thereby altering biological signaling pathways and inducing functional
changes.[44]^5 Consequently, EVs are key mediators of intercellular
communication that can contribute to the physiological maintenance of a
tissue and disease
pathogenesis.[45]^1^,[46]^2^,[47]^3^,[48]^4^,[49]^5^,[50]^6^,[51]^7
EVs are of broad interest because of their association with a variety
of pathologies, including the progression of several pulmonary
diseases.[52]^4^,[53]^5^,[54]^8^,[55]^9^,[56]^10^,[57]^11 Indeed,
pulmonary EVs have pathophysiological roles in acute respiratory
distress syndrome (ARDS), chronic obstructive pulmonary disease (COPD),
interstitial pulmonary fibrosis (IPF), and multiple other lung
diseases.[58]^4^,[59]^8^,[60]^9^,[61]^10^,[62]^11^,[63]^12^,[64]^13^,[6
5]^14^,[66]^15^,[67]^16^,[68]^17 Pulmonary EVs are also of broad
interest because of their potential to serve as novel therapeutic
delivery vesicles to the pulmonary tissue.[69]^18 Despite the high
biological significance of pulmonary EVs, questions remain regarding EV
biogenesis, how EV cargo directs intercellular communication, and how
specific cell types of the airway modulate these processes.
Currently, there is a paucity of in vitro methods available to evaluate
these EV processes in the airway.[70]^12^,[71]^19 Recent studies
comparing in vitro monocultures to organotypic cultures of cancer cell
lines found EV composition from organotypic models more closely
corresponds with EV composition derived from patient plasma
samples.[72]^20^,[73]^21^,[74]^22 Thus, in vitro, organotypic models
may significantly improve our understanding of in vivo EV-mediated
intercellular signaling.
In terms of the pulmonary system, EVs secreted from the alveolar
capillary region (ACR) play significant roles in mediating pulmonary
homeostasis and disease pathogenesis.[75]^4^,[76]^10 The ACR is a
large, susceptible, and influential region of the lung, coincidently
involved in the pathogenesis of many respiratory diseases, such as
ARDS, COPD, and IPF.[77]^4^,[78]^16^,[79]^23^,[80]^24 The ACR
represents the interface of the respiratory and cardiovascular system
and is composed of multiple cell types. Notably, the resident alveolar
epithelial, interstitial fibroblasts, and microvascular endothelial
cells play key roles in maintaining homeostasis in the ACR and in
disease progression.[81]^4 The alveolar epithelium lines the alveolar
air sacs and provides an extensive surface area for gas exchange while
also forming a tight, physical barrier that prevents inhaled substances
from entering the cardiovascular system. In addition, the microvascular
endothelium lines the dense vascular network surrounding the alveoli.
The endothelium also contributes to gas exchange and, in conjunction
with the interstitial fibroblasts, the regulation of pulmonary immune
cell trafficking.[82]^25^,[83]^26 Consequently, alterations in
epithelial and endothelial signaling, as well as in the interstitial
fibroblasts that bridge these cell types in vivo, can have direct
impacts on both the respiratory and cardiovascular systems.
Here, we test the hypothesis that organotypic models of the ACR can be
leveraged to investigate how cells of the ACR mediate intercellular
communication through the EV proteome. Utilizing mass
spectrometry-based proteomics, we compared the EV proteome between two
organotypic models of the ACR: (1) a tri-culture model consisting of
alveolar epithelial, lung fibroblasts, and lung microvascular
endothelial cells and (2) a co-culture model consisting of alveolar
epithelial and lung fibroblasts to evaluate EVs in the absence of
endothelial cells. Proteomics analysis highlighted differences in EV
protein content between the models, as well as related biological
pathways. These model-specific differences in EV proteomic content
suggest that specific pulmonary cell types have unique effects on EV
composition and subsequent EV-mediated intercellular communication.
These differences highlight the utility of organotypic models in
investigating cell type-specific mechanisms to improve our
understanding of EV-mediated intercellular signaling and the
development of future EV-based therapeutic approaches.
Results
Overview of tri-culture and co-culture models
3D organotypic tri-culture and co-culture models of the ACR were used
in this study to evaluate culture model-specific contributions to EV
release and associated proteomic content ([84]Figure 1, [85]Table 1).
Here, the tri-culture model was implemented to evaluate EV-associated
communication mechanisms between alveolar epithelial cells (H441) and
lung fibroblasts (IMR90) seeded on opposite sides of a Transwell
insert, and microvascular endothelial cells (HULEC) seeded in the
basolateral compartment of a Transwell well. A simplified co-culture
model was also used to evaluate EVs in the absence of endothelial
cells.
Figure 1.
[86]Figure 1
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Overview of the in vitro organotypic models and EV isolation
(A) Representation of the alveolar capillary region in vivo.
(B) Schematics of the tri- and co-culture models of the airway are
shown.
(C) EVs were isolated from the basolateral conditioned medium from both
models to inform potential intercellular communication occurring
through EV proteomic expression signatures.
(D) A representative transmission electron micrograph of EVs isolated
from basolateral conditioned medium of the tri- and co-culture models
(an image from the tri-culture model is specifically shown here). EVs
are shown as white circles, with an example EV indicated by a black
arrow. A 200 nm scale bar is displayed in the bottom right corner.
Table 1.
Experimental design for the establishment and application of the tri-
and co-culture models
Components 6-well (24 mm insert)
Corning #3450 12-well (12 mm insert)
Corning #3460
Downstream Application EV Proteomics [6 biological replicates per
condition, 4 technical replicates combined due to sample yield
requirements] Cell Viability [3 biological replicates per condition],
Small Molecule Permeability Assays [6 biological replicates per
condition],
EV Microscopy [subset of 2 samples],
EV NTA [6 biological replicates per condition]
Insert (Apical Compartment) Growth Area 4.67 cm^2 1.12 cm^2
Well (Basolateral Compartment) Growth Area 9.5 cm^2 3.8 cm^2
Apical Media Volume 2000 μL 500 μL
Basolateral Media Volume 2000 μL 1000 μL
Inverted Plating Volume 1000 μL 250 μL
Diluted H441 Cell Suspension 1.75 × 10^5 cells/mL 16.8 × 10^4 cells/mL
H441 Cell Density 7.5 × 10^4 cells/cm^2 7.5 × 10^4 cells/cm^2
H441 Cell Count 3.5 × 10^5 cells/insert 8.4 × 10^4 cells/insert
Diluted IMR90 Cell Suspension 2.9 × 10^4 cells/mL 2.8 × 10^4 cells/mL
IMR90 Cell Density 6.25 × 10^3/cm^2 6.25 × 10^3/cm^2
IMR90 Cell Count 29,000 cells/insert 7,000 cells/insert
Diluted HULEC Cell Suspension 1.38 × 10^5 cells/mL 1.12 × 10^5 cells/mL
HULEC Cell Density 2.9 × 10^4 cells/cm^2 2.9 × 10^4 cells/cm^2
HULEC Cell Count 275,500 cells/B.C. 112,000 cells/B.C.
Downstream EV Sample Resuspension Volume in Filtered PBS 200 μL 50 μL
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Tri- and co-culture models were established using 6-well or 12-well
formats, depending on the indicated downstream application. The number
of experimental replicates conducted for each application is specified
in brackets. Basolateral compartment, B.C.
Cell viability and small molecule permeability measures
Cell viability and small molecule permeability were evaluated in the
tri- and co-culture models after 24 h. There were no significant
changes in cell viability across the tri- and co-culture models
([89]Figures S1A and S1B). In terms of small molecule permeability,
permeability of both the 0.4 kDa fluorescein isothiocyanate (FITC)
molecule and the 4 kDa tetramethylrhodamine isothiocyanate
(TRITC)-dextran molecule across the seeded Transwell insert of the tri-
and co-culture models spanned between an average of 1% and 4%
permeability, as compared to 100% permeability of the insert alone
([90]Figures S1C and S1D). Low permeability of small-molecular-weight
compounds across epithelial layers, such as that observed here, is
indicative of an established alveolar epithelial barrier.[91]^27
Physical characteristics of EVs isolated from conditioned media
Microscopy imaging and nanoparticle tracking analysis (NTA) were
carried out to assess the physical characteristics of EVs isolated from
the basolateral conditioned medium. Microscopy results showed that the
basolateral conditioned medium samples were enriched for EVs, indicated
by circular particles with diameters largely <100 nm ([92]Figures 1D
and [93]S4). NTA measured particle charges averaging −18.7 and −17.8 mV
for the tri- and co-culture models, respectively ([94]Figure 2A). These
charges are within range of previously reported values of EVs derived
from in vitro conditioned media samples.[95]^28^,[96]^29^,[97]^30
Particle counts indicated EV concentration averages of 9.75 x 10^6 and
6.52 x 10^6 particles/μL PBS in the tri- and co-culture model samples,
respectively ([98]Figure 2B). These concentrations equated to total
particle counts of 4.88 x 10^8 and 3.26 x 10^8 particles per well of
basolateral conditioned medium in the tri- and co-culture model,
respectively, plated in the 12-well format ([99]Figure 2C). Particle
sizes measured via NTA averaged across all samples were as follows: 10%
particle diameter of 78.8 nm, median particle diameter of 132.4 nm, and
90% particle diameter of 226.3 nm ([100]Figures 2D–2F). Size deviation
between NTA and microscopy methods have previously been characterized
and are hypothesized to be attributable to shrinkage resulting from
transmission electron microscopy sample preparation, as well as size
distortion due to resolution limits of NTA.[101]^31 While there are
notable differences between the average EV size illustrated in the
microscopy image, acquired from one part of a sample, and NTA measures,
acquired from larger subsets of many samples, both distributions
overlap with those typically reported for the EV subtype of small EVs
(largely <200nm).[102]^1 No particle characteristics were significantly
different between culture models ([103]Table S1).
Figure 2.
[104]Figure 2
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Physical characteristics of EV samples, as measured through
Nanoparticle Tracking Analysis (NTA)
EV physical measures included (A) particle charge; (B) particle count
converted into concentration values from the 12-well format in vitro
models’ conditioned media; (C) particle count within the analyzed
sample resuspended in PBS; (D) average 10% particle diameter;
(E) average 50% (i.e., median) particle diameter; and (F) average 90%
particle diameter. Data are displayed as bar charts, with the median
marked as a solid line in the middle, and the bars expanding across the
25% and 75% data distributions. Individual black dots represent the
actual measured values. Note that none of these physical measures
differed significantly between groups.
EV proteomic landscape in tri- and co-culture models
Proteomic analysis identified 1,336 unique proteins; 1,270 of which
were detected in the tri-culture model and 905 in the co-culture model
([106]Table S2). Of these, 431 proteins were only found in the
tri-culture and 66 proteins were only found in the co-culture EVs. The
remaining 839 proteins were detected in EVs isolated from both in vitro
models ([107]Figure 3A).
Figure 3.
[108]Figure 3
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Comparative proteomic landscape of EVs isolated from conditioned media
of 3D organotypic tri- and co-culture models of the airway epithelium
(A) Volcano plot of tri-culture and co-culture EV proteins and their
designation into summary-level protein lists. Proteins are colored and
shape dependent according to their detection across the culture models
and their level of significant, differential expression in tri-culture
vs. co-culture samples. Note that some proteins were only detected in
one of the models and did not reach the strict statistical threshold
for significance as a result of comparison against non-detected
proteins. These proteins are displayed with different shapes than
proteins meeting statistical significance (see legend).
(B) The top 10 most significant pathways associated with the EV
proteins increased in the tri-culture model (represented by the blue
proteins in panel A).
(C) The top 10 most significant pathways associated with EV proteins
increased in the co-culture model (represented by the purple proteins
in panel A). For all pathways, see [110]Table S3.
To investigate how the additional cell type in the tri-culture model,
the microvascular endothelial cells, affected EV proteomic content, we
statistically compared the abundances of EV proteins detected in the
tri-culture model to those in the co-culture model. Of the 839 proteins
detected in both models, 469 were identified as significantly,
differentially (p[adj] < 0.05 and log[2] fold change [FC]≥ +/− 0.585)
loaded into EVs when comparing the tri-culture model vs. co-culture
model samples, 431 of which were increased in the tri-culture model and
38 were increased in the co-culture model. The remaining 370 proteins
that were detected across both models were not significantly,
differentially loaded into EVs from either model ([111]Figures 3A and
3B). The 431 and 66 proteins detected in only the tri- and co-culture
models, respectively, did not reach statistical significance when
comparing abundance distributions between the tri- and co-culture
models, likely due to a strict multiple test corrected p value filter
requirement that could not be obtained when including values below
detection limits. However, 370 and 47 EV proteins found only in the
tri- and co-culture models, respectively, were considered
differentially loaded based on an FC criterion of ≥ ± 1.5
([112]Figures 3A and 3B). To generate summary-level protein lists to
carry forward in analyses and biological interpretations, we
established the following three groups of detected EV proteins: (1)
“Increased in tri-culture” (n = 801 proteins with log[2]FC ≥ 0.585
[tri-culture/co-culture], 431 of which reached p[adj] < 0.05); (2)
“Increased in co-culture” (n = 85 proteins with log[2]FC ≤ −0.585
[tri-culture/co-culture], 38 of which reached p[adj] < 0.05); and (3)
“No change” (n = 450 proteins).
Alignment of EV proteomic landscape with markers of EV presence and purity
A large number (n = 22) of detected proteins overlapped with the
International Society for Extracellular Vesicles (ISEV) Minimal
Information for Studies of Extracellular Vesicles (MISEV)’s list of
established protein markers of EV presence and purity
([113]Table S2).[114]^32 To detail, 14 proteins belonged to the “class
1” category spanning transmembrane or glycophospholipid (GPI)-anchored
proteins that inform the presence of an EV lipid bilayer, including the
following: Disintegrin and metalloproteinase domain-containing protein
10 (ADAM10), Amyloid-beta precursor protein (APP), Basigin (BSG),
several cluster of differentiation (CD) molecules (e.g., CD55, CD59,
CD63, CD81, and CD9), Epithelial cell adhesion molecule (EPCAM),
several human leukocyte antigen (HLA) class I histocompatibility
antigens (e.g., HLA-A, HLA-B, and HLA-C), 5′-nucleotidase (NT5E), and
Platelet endothelial cell adhesion molecule (PECAM1). Seven proteins
belonged to the “class 2” category of cytosolic proteins present in
eukaryotic cells that commonly incorporate into EVs, including
Glyceraldehyde-3-phosphate dehydrogenase (GAPDH), Heat shock protein
HSP 90-beta (HSP90AB1), and Heat shock cognate 71 kDa protein (HSPA8),
among others. One protein belonged to the “class 3” category of
proteins that often co-isolate with EVs and are thus considered
contaminants, namely Apolipoprotein B-100 (APOB). These findings
support the successful isolation and proteomic evaluation of EV
proteins from these in vitro models.
Pathway and cellular component-level changes between culture models
To better understand the potential biological functions and related
cellular locations of the detected EV proteomes, canonical pathway and
cellular component enrichment analyses were carried out. Analyses were
organized by separating the proteins into the following bins: (1)
“Increased in tri-culture” (n = 801 proteins); (2) “Increased in
co-culture” (n = 85 proteins); and (3) “No change” (n = 450 proteins),
as described in the aforementioned results and illustrated in
[115]Figure 3.
Pathway enrichment analyses found approximately 3x as many signaling
pathways enriched among the EV proteins in the “Increased in
tri-culture” compared to those in the “Increased in co-culture” groups
([116]Table S3A), paralleling the larger diversity of proteins detected
in the tri-culture model vs. co-culture model. Many of the most
significantly detected pathways in the “Increased in tri-culture” group
were associated with the regulation of mRNA translation. Notably, the
most significant pathway associated with the EVs within the “Increased
in tri-culture” group was the “eukaryotic initiation factor 2 (EIF2)
signaling” pathway (p = 6.31x10^−51) with 74 proteins involved in EIF2
signaling detected ([117]Figure 3C). The top canonical signaling
pathways associated with the EV proteins in the “Increased in
co-culture” group were related to axonal guidance signaling and
endocytosis ([118]Table S3B). The most significant pathway of this
group was the “axonal guidance signaling” pathway (p = 7.08x10^−8) with
13 proteins involved in signaling detected ([119]Figure 3C). The EIF2
signaling pathway was also the most significant pathway associated with
the EV proteins within the “No change” group, with 27 proteins involved
in EIF2 signaling detected (p = 2x10^−11) ([120]Table S3C).
Cellular component enrichment analysis results largely aligned with the
pathway analysis results for each group. The cellular component
analysis revealed EV proteins within the “Increased in tri-culture”
group were significantly enriched with proteins affiliated with mRNA
translation complexes such as the aminoacyl-tRNA synthetase multienzyme
complex (fold enrichment = 25.05, p = 1.89x10^−7) and the eukaryotic
translation initiation factor 3 (EIF3) complex (fold enrichment =
25.05, p = 5.14x10^−4), among others ([121]Table S4A). In addition, the
cellular component analysis revealed EV proteins within the “Increased
in co-culture” group were significantly enriched with proteins
affiliated with complexes such as the “protein complex involved in
cell-matrix adhesion” (fold enrichment = 66.1, p = 1.48x10^−3) and the
“basement membrane” (fold enrichment = 20.61, p = 1.72x10^−6), among
others ([122]Table S4B). EV proteins within the “No change” group were
significantly enriched with proteins associated with the beta-subunit
of the “proteasome complex” (fold enrichment = 24.36, p = 1.70x10^−3)
([123]Table S4C). EV proteomic enrichment similarities and differences
between culture models are additionally summarized in [124]Figure 4.
Figure 4.
[125]Figure 4
[126]Open in a new tab
Summary of EV proteomic similarities and differences across in vitro
culture models
Overall, the number and size distribution of EVs released across both
models were similar, but the diversity of protein molecules was
considerably increased in the tri-culture vs. co-culture model.
Furthermore, the tri-culture model showed greater enrichment for EIF2
and RNA translation pathway-level processes.
Protein-specific validation of EV isolates
The EV proteomics screen detected 59 EV proteins that overlap with the
MISEV category 1–3 proteins between both culture models
([127]Table S2). ALIX (PDCD6IP), ANXA5, CD63, CD81, and EpCAM are 6 of
these EV protein markers ([128]Figure S2). Two of these proteins (i.e.,
ALIX and ANXA5) also overlap with the MISEV category 1 proteins, as
previously described. EV protein markers were then validated among a
representative sample of EV isolates from the tri-culture model using a
pre-loaded antibody array of proteins commonly evaluated in EV studies.
The following proteins were measured within this sample: ANXA5, ICAM,
CD63, ALIX, CD81, TSG101, FLOT1, and GM130 ([129]Figure S3). Notably,
some additional proteins were detected via the exocheck antibody array,
which were not detected via proteomics (e.g., TSG101, FLOT1, and
GM130). Together, these findings support the successful isolation of
EVs and their associated protein content from cell culture media.
Discussion
This study aimed to leverage in vitro models of the airway,
specifically of the ACR, to further our understanding of EV-mediated
intercellular signaling mechanisms across specific combinations of
pulmonary cell types. Two different organotypic models of the ACR were
evaluated: a tri-culture model consisting of alveolar epithelial,
fibroblast, and lung microvascular endothelial cells, and a co-culture
model consisting of alveolar epithelial cells and lung fibroblasts
seeded in separate compartments across a Transwell insert. Notably, the
implemented alveolar epithelial and microvascular endothelial cell
lines reflect multiple important features of the ACR in vivo such as
alveolar epithelial barrier formation and surfactant protein
production[130]^33^,[131]^34 and are representative of the epithelial
and microvascular endothelial cells found in the human ACR. Comparing
EVs secreted from the tri- and co-culture in vitro airway model
revealed that EV physical characteristics, including particle number
and size distribution, remained consistent between the two models. When
evaluating EV proteomic signatures, however, the following differences
were apparent: (1) there was greater diversity in the proteins detected
in the tri-culture model (n = 1,270 proteins) vs. co-culture model (n =
905 proteins) and (2) the biological pathways associated with EV
proteins were differentially enriched in the tri-culture vs. co-culture
models. These model-specific differences in EV proteomic content
suggest that specific pulmonary cell types may have unique effects on
EV-mediated intercellular communication.
Proteins within EVs are becoming increasingly recognized as important
contributors of EV-mediated intercellular
communication.[132]^10^,[133]^19^,[134]^35^,[135]^36^,[136]^37^,[137]^3
8 Here we show an increased diversity of proteins in EVs isolated from
the tri-culture compared to the co-culture model of the airway
epithelium. Our observations demonstrate that increasing the biological
complexity (i.e., incorporating an additional in vivo-relevant cell
type) of an in vitro model can alter the EV proteome of the system,
thus, highlighting the importance of considering the cellular
composition of in vitro systems used in EV studies, especially in the
context of identifying potential biomarkers of exposure and/or disease.
Future studies are needed to identify the relative contributions of
different cell types and their potential to influence intercellular
communication.
Characterization of the proteins identified at increased levels in
tri-culture EVs (vs. co-culture EVs) revealed an enrichment in RNA
binding proteins such as multiple eukaryotic translation initiation
factors, ribosomal proteins, and protein chaperones. These proteins are
significantly associated with cellular components involved in protein
translation such as the Aminoacyl-tRNA Synthetase Multienzyme and the
EIF3 complexes.[138]^39 Accordingly, these proteins are also associated
with signaling pathways involved in the regulation of protein
translation, such as the EIF2 signaling pathways. Many of the
significantly enriched pathways associated with the altered tri-culture
EV proteins, including EIF2 signaling, can be activated by a diverse
array of stress-related signals that direct global and specific mRNA
translation.[139]^40^,[140]^41^,[141]^42^,[142]^43 However, findings
from the current analysis demonstrate increased detection of EIF2
signaling-related proteins in the absence of an applied exogenous
stressor or overt cell stress, as evidenced by a lack of cytotoxicity
in the culture models and maintenance of normal cellular morphology.
Our observations reported here parallel previous studies that have
identified a similar enrichment for proteins involved in EIF signaling
and translation across EV proteomes from various cell types, in the
absence of cellular stress.[143]^44^,[144]^45^,[145]^46 This persistent
detection of RNA binding proteins in EVs may suggest either an active
or passive role of these proteins in the RNA loading of EVs in the
donor cell. Future studies investigating this putative role may help
elucidate important mechanisms of EV biogenesis. Furthermore, as EV
content can be released into the recipient cell cytoplasm, the transfer
of translational machinery could also significantly enhance the
translation of transferred EV cargo that acts through RNA-to-protein
translational mechanisms and increase the efficacy of EV-mediated
intercellular signaling. Indeed, the investigation of EV proteins that
increase the delivery of EV therapeutic cargo into target cells and its
efficacy is of growing interest.[146]^30^,[147]^45^,[148]^47
Ovchinnikova et al.[149]^45 suggest the incorporation of protein
chaperones into EVs designed for drug delivery may help stabilize the
structure of therapeutic proteins within the EV and improve the
therapeutic efficacy upon delivery. With the recent advancement of mRNA
packaging into EVs,[150]^47^,[151]^48^,[152]^49^,[153]^50^,[154]^51 our
observations build upon those reported by Ovchinnikova et al.[155]^45
and support the value of future studies to investigate whether
co-packaging of translational machinery with mRNA therapeutic molecules
may enhance the mRNA translation and therapeutic effect upon delivery.
EV packaging of proteins involved in translational machinery increased
with the addition of the endothelial cells in the tri-culture model.
The airway has the highest vascular density in the human body;
therefore, it is plausible that endothelial EV signaling would have
influential effects on airway homeostasis and disease
development.[156]^52 Endothelial cells and endothelial-derived EVs and
microparticles are associated with the pathogenesis of a number of
pulmonary diseases.[157]^53^,[158]^54^,[159]^55 The tri-culture model
of the airway described herein may therefore be a useful tool to
identify causative mechanisms of endothelial EV-mediated intercellular
communication in airway disease development. Furthermore, this model
may also be a useful tool to identify candidate biomarkers of toxicant
exposure and/or pulmonary disease involving the pulmonary
microvasculature vasculature.[160]^56^,[161]^57
In the absence of endothelial cells, EV proteins at increased levels in
the co-culture model were associated with fewer biological pathways
compared to the tri-culture EV proteins. Of the pathways associated
with these EV proteins, the most significant pathway was the “Axonal
Guidance” signaling pathway. A large number of metalloproteases and
integrins contributed to the classification of this pathway as being
alternatively regulated. A growing number of studies have also detected
metalloproteases and integrins in
EVs.[162]^58^,[163]^59^,[164]^60^,[165]^61^,[166]^62^,[167]^63
Metalloproteases are thought to contribute to EV biogenesis,
modification, and EV uptake by recipient cells through the remodeling
of the extracellular matrix (ECM) and the modification of EV and cell
surface receptors.[168]^62^,[169]^63 Furthermore, EV-bound integrins
are involved in adhesion to the ECM and EV uptake by recipient
cells.[170]^60^,[171]^61 While studies have shown these proteins’
involvement in EV biogenesis, migration through the ECM, and the homing
of EVs to specific cell types in disease states such as cancer and
kidney disease, these mechanisms and/or resulting biological
consequences in the airway are still relatively
unclear.[172]^61^,[173]^64 The enrichment of these proteins and
associated signaling pathways in the co-culture EVs suggest
metalloproteases and integrins likely mediate these processes in the
airway as well. Thus, our results suggest the co-culture model
described herein may be a valuable tool to investigate the mechanisms
of EV biogenesis, migration, and recipient cell uptake in the airway.
It is becoming increasingly evident that EVs and their cargo are
mediators of airway health and disease. Here, we observed that the
cellular complexity of organotypic models affects the proteomic cargo
of secreted EVs, which may have significant implications for future
investigation of mechanisms involved in intercellular communication
within the pulmonary airways. Thus, increasing the representation of
different in vivo-relevant cell types into in vitro organotypic models
can improve our ability to investigate the different aspects of
EV-mediated signaling mechanisms and to develop EV-based interventions
for respiratory disease. Further work using organotypic models of the
airway is needed to continue advancing our mechanistic understanding of
EV communication in the airway and its role in maintaining lung
homeostasis and disease development.
Limitations of the study
Our study has identified significantly enriched signaling pathways in
the tri- and co-culture EVs after 24 h in culture; however, we did not
investigate EV proteomics at other time points. Future studies are
needed to investigate if culture time modulates EV proteins and
affiliated signaling pathways. We also did not exclusively investigate
the cell type of origin of the EVs detected in the culture models, and
how this contributes to the diversity of the detected EV proteome.
Future investigations can build upon this work and provide further
insight into cell-specific roles in EV-mediated intercellular
communication in the lung. The cellular composition of our in vitro
models represents the ACR of the lung; therefore, our findings may more
closely reflect EV signaling from the respiratory region of the
respiratory system. Future studies using in vitro models of the
conducting (i.e., tracheobronchial) region are needed to investigate
how EV signaling may differ throughout the respiratory tract. Lastly,
while the incorporated human cell lines were all immortalized from
pulmonary tissue and, unlike other alveolar-like epithelial cell lines,
exhibit the crucial epithelial barrier function of the ACR, our models
do not incorporate primary cell types. Thus, future studies could
better address inter-individual response variability in EV signaling in
the airway through the incorporation of primary cells.
STAR★Methods
Key resources table
REAGENT or RESOURCE SOURCE IDENTIFIER
Chemicals, peptides, and recombinant proteins
__________________________________________________________________
Fluorescein isothiocyanate (FITC) Sigma Cat#F6377
Tetramethylrhodamine (TRITC) -labeled 4 kDa dextran Sigma Cat#T1037
__________________________________________________________________
Critical commercial assays
__________________________________________________________________
LIVE/DEAD™ Cell Imaging Kit (488/570) ThermoFisher Cat#[174]R37601
Exosome Isolation (from media) kit ThermoFisher Cat#4478359
Exo-Check antibody array System Biosciences Cat#EXORAY210B-8
Pierce™ BCA Protein Assay Kit Thermo Scientific Cat#23225
WesternBright Sirius HRP substrate Advansta Cat#K-12043-D10
__________________________________________________________________
Deposited data
__________________________________________________________________
EV isolation methods and study logistics This paper EV-Track
knowledgebase (EV-TRACK ID: [175]EV230971)
Cell viability, cell permeability, NTA, and proteomics data This paper
UNC Center for Environmental Medicine, Asthma and Lung Biology
(UNC-CEMALB)-Dataverse
([176]https://dataverse.unc.edu/dataverse/cemalb)
Script used to analyze NTA and proteomics data This paper UNC-CEMALB
Github website
([177]https://github.com/UNC-CEMALB/Characterizing-the-Extracellular-Ve
sicle-Proteomic-Landscape-of-the-Human-Airway-using-In-vitro-Orga)
full proteomics mass spectrometry data This paper PRoteomics
IDEntifications Database (PRIDE Project accession: [178]PXD040470)
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Experimental models: Cell lines
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NCI-H441 cells American Tissue Cell Collection [ATCC] Cat#CRM-HTB-174,
Batch #F-14929
IMR90 cells (human lung fibroblasts American Tissue Cell Collection
[ATCC] Cat#CCL-182, Batch #64155514
HULEC-5a cells American Tissue Cell Collection [ATCC] Cat#CRL-3244,
Batch #70025430
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Software and algorithms
__________________________________________________________________
Proteome Discoverer Thermo Scientific, version 2.5 N/A
Ingenuity Pathway Analysis Qiagen N/A
Gene Ontology (GO) analysis Protein ANalysis THrough Evolutionary
Relationships (PANTHER) 17.0 database [179]https://geneontology.org/
[180]Open in a new tab
Resource availability
Lead contact
Requests for further information, resources, and reagents should be
directed to and will be fulfilled by the lead contact, Julia Rager
(jrager@unc.edu).
Materials availability
This study did not generate new unique reagents.
Experimental model and study participant details
Cell culture
All cell types were maintained in a humidified cell culture incubator
at 37°C with 5% CO[2] and ambient O[2] levels (hereafter referred to as
a “tissue culture incubator”). All cells were passaged onto tissue
culture dishes (Techno Plastic Products, #93150 and 93100) coated with
bovine type I collagen solution (Advanced BioMatrix, San Diego, CA,
#5005).[181]^69 All cell types were authenticated by short tandem
repeat (STR) profiling using the ATCC Human Cell Authentication Service
(ATCC #135-XV; results included in [182]supplemental information) and
tested negative for Mycoplasma spp. contamination (Universal Mycoplasma
Detection Kit, ATCC #30-1012K).
The following three human cell types were selected to represent the
alveolar capillary region of the lung: (1) alveolar epithelial cells,
(2) fibroblasts, and (3) lung microvascular endothelial cells.
* Alveolar epithelial cells:
+ NCI-H441 cells (hereafter referred to as “H441”; human, male,
alveolar-like epithelial cells, American Tissue Cell
Collection [ATCC] #CRM-HTB-174, Batch #F-14929) represented
the alveolar epithelial cells and were obtained from the
University of North Carolina (UNC)-Chapel Hill Tissue Culture
Core Facility. This cell line was selected as it is the only
human alveolar-like epithelial cell line that forms a
functional, epithelial barrier (a critical function of the
alveolar epithelium in vivo). H441 were used for in vitro
airway culture model generation within an adjusted population
doubling (APD) range of 4–27. Detailed cell culture methods
for the H441 cell line is available through the online,
publicly available Nature Portfolio, Protocol
Exchange.[183]^69^,[184]^70^,[185]^71^,[186]^72 In brief,
IMR90 were maintained in Advanced-RPMI growth medium (A-RPMI;
ThermoFisher #12633020) supplemented with 5% FBS
(ThermoFisher, #16000044, certified), 0.5%
Penicillin/Streptomycin (P/S; ThermoFisher, #15140122) and
4 mM GlutaMAX (ThermoFisher #35050061)).
* Fibroblasts:
+ IMR90 cells (human, female, lung fibroblasts; ATCC #CCL-182,
Batch #64155514) represented the fibroblasts and were obtained
from ATCC. This cell line was selected as it is a human lung
fibroblast line and grows well with the other cell types of
the organotypic models. IMR90 were used for in vitro airway
culture model generation within an adjusted population
doubling (APD) range of 3–15. Detailed cell culture methods
for the IMR90 cell line is available through the online,
publicly available Nature Portfolio, Protocol
Exchange.[187]^69^,[188]^70^,[189]^71^,[190]^72 In brief,
IMR90 were maintained in Advanced-RPMI growth medium (A-RPMI;
ThermoFisher #12633020) supplemented with 5% FBS
(ThermoFisher, #16000044, certified), 0.5%
Penicillin/Streptomycin (P/S; ThermoFisher, #15140122) and
4 mM GlutaMAX (ThermoFisher #35050061)).
* Lung microvascular endothelial cells:
+ HULEC-5a cells (hereafter referred to as “HULEC”; human, male,
lung microvascular endothelial cells, ATCC #CRL-3244, Batch
#70025430) represented the endothelial cells and were obtained
from ATCC. This cell line was selected as it is one of the
only human lung microvascular endothelial cell lines available
that can be expanded in culture similar to other immortalized
cell lines. HULEC were used for in vitro airway culture model
generation within an adjusted population doubling (APD) range
of 3–12. Detailed cell culture methods for the HULEC-5a cell
line is available through the online, publicly available
Nature Portfolio, Protocol
Exchange.[191]^69^,[192]^70^,[193]^71^,[194]^72 HULEC were
maintained in complete HULEC growth medium (MCDB-131 (Gibco
#10372019) supplemented with 10% FBS, 1% P/S, 10 mM GlutaMAX,
10 ng/mL human Epidermal Growth Factor (Fisher Scientific,
#PHG0311), and 1μg/mL hydrocortisone (MilliporeSigma,
#H0888)).
Method details
Tri- and co-culture model setup
The tri-culture and co-culture models were setup following the
“Alveolar Capillary Region Exposure (ACRE) Exposure Model” methodology,
detailed in full through the online, publicly available Nature
Portfolio, Protocol Exchange[195]^73 up to Day 3. On day 3 of the
tri-culture model setup, HULECs were seeded in separate
collagen-coated[196]^69 multi-well plates in complete HULEC growth
medium and incubated in a tissue culture incubator for 9 h to permit
the formation of a confluent monolayer. After the 9 h incubation
period, the medium was aspirated and replaced with HULEC Exposure
Medium (MCDB-131 supplemented with 1% exosome-depleted FBS (Gibco
#A2720803), 1% P/S, and 10mM GlutaMAX). In contrast, for the co-culture
model setup, cell-free HULEC Exposure Medium was plated in separate
multi-well plates to imitate a HULEC plating event. The apical and
basolateral media from the seeded Transwell inserts were aspirated from
the inserts and the seeded inserts were carefully transferred to
HULEC-seeded (tri-culture model) or HULEC-free (co-culture model)
wells. Polarization medium (A-RPMI growth medium supplemented with
0.5 μM dexamethasone (MilliporeSigma, #D4902)) was then added to the
apical side of the Transwell inserts prior to the cultures being placed
in a tissue culture incubator for 14 h. On day 4, the basolateral
medium of the cultures was replaced with fresh HULEC Exposure Medium
and the apical medium was replaced with Apical Exposure Medium (A-RPMI
supplemented with 0.5% P/S, 0.5 μM dexamethasone, and 4mM GlutaMAX).
The cultures were then incubated in a tissue culture incubator for 24
h. Following incubation, apical and basolateral compartments were
separated for cell-specific functional analysis. Cell seeding
densities, downstream applications, media volumes, and product numbers
for the tri- and co-culture setup are summarized ([197]Table 1).
Culture models are also depicted ([198]Figure 1).
Cell viability assay
Tri- and co-culture models were setup using the 12-well Transwell
insert format described in [199]Table 1. Cell viability of the tri- and
co-culture models was assessed 24 h after the final medium change on
day 4 of the model setups using the LIVE/DEAD™ Cell Imaging Kit
(488/570) (ThermoFisher, #[200]R37601). The apical medium of the
in vitro models was aspirated from the seeded Transwell inserts and the
basolateral medium was collected for downstream EV analysis. Following
media removal and collection, the inserts were transferred to new
multi-well plates. The seeded Transwell inserts and HULEC were rinsed
with pre-warmed DPBS. A 2X-stock solution of the LIVE/DEAD reagents,
0.75 μl/mL Calcein AM and 1.5 μL/mL Ethidium homodimer-1, was prepared
in DMEM-fluorobrite (DMEM-F; ThermoFisher, #A1896701) supplemented with
4mM GlutaMAX. This solution was then diluted two-fold in GlutaMAX
supplemented DMEM-F and added to the apical and basolateral
compartments of the seeded Transwell inserts and directly to the seeded
HULEC cells. All cells were incubated in these LIVE/DEAD reagents for
40-min at room temperature. Cells were then analyzed at
excitation/emission 488/515 nm (LIVE) and 570/602 nm (DEAD) on a
CLARIOstar Plus plate reader (BMG LabTech, Cary, NC). Extra tri-culture
model inserts were seeded for dead and live cell controls to obtain
maximum DEAD signal and maximum LIVE signal from the seeded inserts and
HULEC. Positive DEAD controls were generated according to the
manufacturer’s protocol. Positive LIVE controls were maintained in
appropriate exposure medium. Values represent the mean (± SD) from
three biological replicates (n = 3), which were each performed in
technical triplicate, and normalized to their respective maximum DEAD
and LIVE signal. Statistical analysis was conducted in GraphPad Prism
(version 9.3.1). An ordinary two-way ANOVA and Šidák’s multiple
comparisons post-hoc test was run to investigate significant
differences in cell viability between the seeded Transwell inserts of
the tri- and co-culture models. An unpaired, two-tailed t-test between
the LIVE and DEAD signal from the HULEC in the tri-culture was also run
to investigate HULEC viability in the tri-culture model.
Small molecule permeability assay
Similar to the cell viability assessment, additional replicates of the
tri- and co-culture models were setup using the 12-well Transwell
insert format described in [201]Table 1. Small molecule permeability
across the tri- and co-culture seeded Transwell inserts was
investigated 24 h after the final medium change on day 4 of the model
setups. The apical medium of the in vitro models was aspirated from the
seeded Transwell inserts and the basolateral medium was collected for
downstream EV analysis. Following the medium removal and collection,
the seeded inserts of the tri- and co-culture models were rinsed with
pre-warmed DPBS and transferred to new multi-well plates. Pre-warmed
basal DMEM-F was added to the basolateral compartment of each well. A
1 mg/mL suspension of fluorescein isothiocyanate (FITC, Sigma, #F6377)
and a 1 mg/mL suspension of Tetramethylrhodamine (TRITC) -labeled 4 kDa
dextran, (Sigma, #T1037) were mixed at a 1:1 ratio in basal DMEM-F and
were added to the apical compartment of the DPBS-washed seeded
Transwell inserts. These inserts were incubated in the presence of the
FITC/TRITC solution for 20 min in a tissue culture incubator and
protected from light. After incubation, the basolateral medium was
collected from each well, vortexed and 100 μL of each well’s
basolateral medium was transferred into wells of black 96-well plates
(Corning, #3603) in triplicate. Samples collected from unseeded,
non-collagen coated inserts were collected and plated in the same black
96-well plates to determine maximum small molecule permeability of the
Transwell inserts. Average fluorescence at 490/520 nm
(excitation/emission maxima) across all technical triplicate wells was
measured using a CLARIOstar Plus plate reader (BMG LabTech, Cary, NC).
Small molecule permeability of independent experiments was determined
by averaging the fluorescence intensity of the basolateral medium from
three inserts (technical triplicates within an independent experiment),
expressed as a percentage of the maximum small molecule permeability
observed in each experiment. The data shown represent the mean (± SD)
of five biological replicates (n = 5). Statistical analysis was
conducted in GraphPad Prism (version 9.3.1) using an unpaired,
two-tailed t-test between the tri- and co-culture samples.
Conditioned media processing and isolation of exosome-enriched EVs
To investigate EV characteristics and proteomic changes between the
tri- and co-culture models, the basolateral conditioned medium was
collected from each well of the 12-well Transwell inserts designated
for the cell viability and small molecular permeability assay as
described above. 24 h after the final media change on day 4 of the
model setup, basolateral conditioned medium was also collected from
additional tri- and co-culture models seeded using the 6-well Transwell
insert format described in [202]Table 1. For all conditioned medium
collected, cell debris were removed via centrifugation (13,000
[MATH: × :MATH]
g for 10 minutes at 4°C). Notably, it is possible that pre-processing
steps may have caused denser EVs such as apoptotic bodies or aggregates
to sediment out prior to EV isolation. This centrifugation step was
still carried out to meet the eventual goal of isolating smaller sized
EVs that overlap with the targeted exosome size ranges. EVs were
specifically isolated from conditioned medium using the Invitrogen
Total Exosome Isolation (from media) kit (ThermoFisher, #4478359). The
manufacturer’s protocol was implemented with one additional spin at
10,000
[MATH: × :MATH]
g for 30 min to enhance the removal of debris immediately prior to the
addition of precipitation reagent. Isolated EVs were resuspended in
filtered PBS (200 μL and 50 μL for samples collected from 6- and
12-well formats, respectively). EV samples were validated and
characterized using EV imaging, NTA, and proteomics analysis.
EV imaging
Two representative EV samples from the tri-culture model were imaged
via negative stain transmission electron microscopy on different days
during the study to ensure replicability. The sample was prepared by
floating glow-discharged formvar/carbon-coated 400 mesh copper grids
(Ted Pella, Inc, Redding, CA) onto droplets of sample aliquots (25 μL)
for 10 minutes. Two drops of deionized water and one droplet of 2%
aqueous uranyl acetate stain were then added to each grid for one
minute. Grids were blotted with filter paper, air dried, and then
visualized. Visualization was completed using a JEM-1230 transmission
electron microscope (JEOL USA, Inc., Peabody, MA) operating at 80kV,
and resulting images obtained using a Gatan Orius SC1000 CCD camera and
associated Microscopy Suite software, v3.10.1002.0 (Gatan, Inc.,
Pleasanton, CA).
EV particle charge, count, and size characterization
NTA was used to characterize EV particle charge, count, and size
distribution using a full set of n = 6 biological replicates per
culture model from the 12-well design ([203]Table 1). The
Multiple–Laser ZetaView® f-NTA Nanoparticle Tracking Analyzers System
(Particle Metrix, Mebane, NC) was run in scatter scanning mode to
measure particle count and size distribution. Particle charge was
measured via zeta-potential of particle mobility in an electric field.
EV samples were diluted in filtered PBS at 1:1000 for particle count
and size measures and 1:2000 for particle charge measures using 1.0 mL
sample volumes. NTA data were organized and analyzed in R Software
(v4.1.2), statistically evaluated for potential changes between culture
models via the Wilcoxon Rank Sum test and visualized using ggplot2.
EV proteomics analysis
A full set of n = 6 EV biological replicates per culture model were
analyzed for proteomic signatures through the UNC Proteomics Core
Facility. Due to limited protein yields, four technical replicates were
pooled using 1 mL aliquots from the 6-well design ([204]Table 1). This
approach ensured that technical replicates were prepared on the same
day (and cell passage number), and thus still represented unique
biological replicates once combined. Acetone (Thermo Scientific,
#A18-4) protein precipitation was performed and protein pellets were
reconstituted in 8M urea (Thermo Scientific, #29700). Samples were
reduced with 5mM DTT (Pierce™, Thermo Scientific, #20290) for 30 min at
56C, alkylated with 15mM iodoacetamide (Thermo Scientific, #122270050)
for 45 min at room temperature in the dark, then diluted to 1M urea
with 50mM ammonium bicarbonate pH 7.8 (Sigma, #1066-33-7). Samples were
digested with trypsin (Promega, #V5280) overnight at 37C. C18 desalting
spin columns (Pierce™, Thermo Fisher Scientific, #89870) were used to
clean resulting peptide samples, which were dried down via vacuum
centrifugation and stored at −80C until further analysis.
Samples were analyzed by liquid chromatography coupled to tandem mass
spectrometry (LC-MS/MS) using a Thermo Easy nLC 1200-QExactive HF.
Samples were injected onto an Easy Spray PepMap C18 column (75 μm
id × 25 cm, 2 μm particle size) (Thermo Scientific) and separated over
a 120 min method. The gradient for separation consisted of a step
gradient from 5 to 32 to 42% mobile phase B at a 250 nL/min flow rate,
where mobile phase A was 0.1% formic acid in water and mobile phase B
consisted of 0.1% formic acid in 80% ACN. The QExactive HF was operated
in data-dependent mode where the 15 most intense precursors were
selected for subsequent HCD fragmentation. Resolution for the precursor
scan (m/z 375–1700) was set to 60,000 with a target value of 3 × 10^6
ions, 100ms inject time. MS/MS scans resolution was set to 15,000 with
a target value of 1 × 10^5 ions, 100ms inject time. The normalized
collision energy was set to 27% for HCD, with an isolation window of
1.6 m/z. Peptide match was set to preferred, and precursors with
unknown charge or a charge state of 1 and ≥8 were excluded. Instrument
variability was checked by including pooled samples, combined from
equal volumes of all samples, and analyzing these before and after the
sample run. Samples were randomized prior to LC-MS/MS, and all samples
were analyzed consecutively minimizing the potential for batch effects.
EV proteomics data processing and statistical analysis
Proteins were identified and quantified using Proteome Discoverer
(Thermo Scientific, version 2.5) with the UniProt Human database,
containing ∼20,000 proteins, appended with a common lab contaminants
database used in general proteomic studies.[205]^74 Further data
processing and analysis was carried out in R Software (v4.1.2), where a
series of pre-processing steps were applied to the initial set of 2,167
protein observations. Proteins abundances were normalized based on
total peptide amount.[206]^75 Non-detect proteins were treated as
missing data and retained values of “NA” in this step. Second, a
detection filter required that proteins were identified from at least
two peptides. Third, a background filter was applied requiring that a
protein be measured in at least 50% of the samples within either
culture model (i.e., either detected in three of the six biological
replicates of the co-culture and tri-culture groups). These filters
yielded a list of 1,427 proteins (represented by 1,542 observed
features) carried forward in the analysis.
Data were log[2]-transformed to allow for subsequent imputation and
normalization algorithms. Missing data were imputed via quantile
regression imputation of left-censored data (QRILC) through the
imputeLCMD package, which replaces missing data with left-censored data
from a Gaussian distribution.[207]^76 This method was selected based on
the assumption that data were missing not at random (MNAR) and likely
represented proteins that were not present and/or below detection.
Notably, QRILC has been shown to out-perform other imputation methods
under conditions of MNAR.[208]^77 Potential sample outliers were
evaluated using principal component analysis (stats package).[209]^78
Resulting dimensionally reduced value distribution plots did not
indicate samples with outlying distributions, and thus all biological
samples were retained.
Statistical analyses then compared protein distributions in tri-culture
vs. co-culture model samples using a t-test followed by a false
discovery rate (FDR) adjustment for multiple testing, resulting in
adjusted p values (P[adj]). Fold change (FC) in expression was
calculated as the ratio of the average abundance levels across
tri-culture samples divided by the average abundance levels across
co-culture samples, per protein. Following statistical analysis,
contaminant proteins were excluded as identified through the UniProt
contaminants database. 91 proteins (represented by 91 observations)
were considered common lab contaminants (e.g., Bovine serum albumin).
Following this exclusion, 1,336 proteins of biological interest
remained (represented by 1,451 observations) and were detected in EVs
in at least one culture model ([210]Table S2). Global statistical
results were visualized via volcano plots using GraphPad Prism (version
9.3.1).
After statistical analyses were completed, proteins were binned into
the following categories based upon their distribution of expression
changes[211]^1: ‘Increased in tri-culture’ – EV proteins that were
loaded at increased levels in EVs from the tri-culture model (based off
a log[2]FC (tri-culture/co-culture) ≥ 0.585), and that were
significantly increased in the tri-culture/co-culture comparison (based
off a log[2]FC ≥ 0.585 and p[adj] < 0.05)[212]^2; ‘Increased in
co-culture’ – EV proteins that were loaded at increased levels in EVs
from the co-culture model (based off a log[2]FC
(tri-culture/co-culture) ≤ −0.585, and that were significantly
increased in the co-culture/tri-culture comparison (based off a
log[2]FC ≤ −0.585 and p[adj] < 0.05)[213]^3; ‘No change’ – the
remaining proteins that were detected in either model but not increased
in either model in comparison to the other.
Comparing detected EV proteins with markers of presence and purity
The International Society for Extracellular Vesicles (ISEV)’s
Guidelines for Minimal Information for Studies of Extracellular
Vesicles (MISEV) advocates for the measurement and reporting of certain
proteins to characterize EVs used in research studies.[214]^32
Important proteins highlighted by the ISEV include those that inform EV
presence and purity, spanning the following categories[215]^1
transmembrane or GPI-anchored proteins that inform the presence of an
EV lipid bilayer[216]^2; cytosolic proteins present in eukaryotic cells
that commonly incorporate into EVs[217]^3; proteins that often
co-isolate with EVs and are thus considered contaminants. EV proteins
detected in this study were compared against the MISEV’s list of
proteins in categories 1–3 that inform EV presence and purity.
Pathway and cellular compartment enrichment of EV proteins
To understand the biological implications of the measured EV proteins,
pathway and cellular compartment enrichment analyses were carried out.
For the pathway enrichment analysis, protein lists were evaluated using
the Ingenuity Knowledge Database within Ingenuity Pathway Analysis
(IPA; Qiagen).[218]^79 Pathways that were considered significantly
enriched were defined as pathways that were over-represented,
containing more proteins than expected by random chance. For the
compartment enrichment analysis, Gene Ontology (GO) analysis was
carried out using the Protein ANalysis THrough Evolutionary
Relationships (PANTHER) 17.0 database.[219]^80 Cellular compartments or
stable macromolecular complexes that were considered significantly
enriched within each respective list of EV proteins were defined as
over-represented cellular locations, with more proteins at these sites
than expected by random chance ([220]Table S4). The statistical filter
applied for identification of over-represented pathways and cellular
locations was p < 0.01, based off a Fisher’s Exact Test with a
Bonferroni multiple tests correction, paralleling methods and filters
previously implemented in toxicological response
comparisons.[221]^81^,[222]^82
Protein-specific validation of EV isolates
Specific proteins were validated leveraging the System Bioscience
Exo-Check antibody array (System Biosciences, #EXORAY210B-8), a
semi-quantitative assay with pre-loaded antibodies printed on a
membrane. This assay includes nine proteins commonly used in EV
evaluations, including programmed cell death 6 interacting protein
(ALIX), annexin A5 (ANXA5), tetraspanin 63 (CD63), tetraspanin 81
(CD81), epithelial cell adhesion molecule (EPCAM), flotillin 1 (FLOT1),
cis-golgi matrix protein (GM130), intercellular adhesion molecule 1
(ICAM1), and tumor susceptibility gene 101 (TSG101). Protein was
quantified for a subset of EV samples to estimate total EV protein
using the Pierce™ BCA Protein Assay Kit (Thermo Scientific, #23225)
with absorbance values read at 562 nm on a Molecular Devices SpectraMax
iD5 Multi-Mode Microplate Reader. This assay required slightly higher
amounts of protein in comparison to the proteomics screen, requiring
the aggregation of EV samples isolated across five 1mL biological
replicates from the 12-well tri-culture samples, resulting in the
analysis of one collective EV sample from the tri-culture design.
Antibody array measures were then collected according to manufacturer’s
protocol. A resulting membrane was developed using the WesternBright
Sirius HRP substrate (Advansta, #K-12043-D10) and imaged using LI-COR
Biosciences C-DiGit Blot Scanner and Image Studio software.
Additionally, these nine proteins were evaluated within the EV
proteomics data to verify their presence in or on EVs and visualized
via GraphPad Prism (version 9.3.1).
Quantification and statistical analysis
Statistical analyses, as well as strategies for the randomization of
samples for each experiment can be found in the [223]STAR Methods
section that describes the experiment. Significance was defined as
p < 0.05.
Acknowledgments