Post on 05-Aug-2020
Article
Niche-Specific Reprogram
ming of EpigeneticLandscapes Drives Myeloid Cell Diversity inNonalcoholic SteatohepatitisGraphical Abstract
Highlights
d Myeloid cell diversity in NASH is associated with distinct
microanatomical niches
d Reprogramming of LXR activity leads to impaired Kupffer cell
identify and survival
d ATF3 collaborates with LXRs to promote a scar-associated
macrophage phenotype
d Altered enhancer landscapes enable inference of disease
mechanisms
Seidman et al., 2020, Immunity 52, 1057–1074June 16, 2020 ª 2020 Elsevier Inc.https://doi.org/10.1016/j.immuni.2020.04.001
Authors
Jason S. Seidman, Ty D. Troutman,
Mashito Sakai, ..., Joseph L. Witztum,
Ronald N. Germain,
Christopher K. Glass
Correspondencettroutman@health.ucsd.edu (T.D.T.),ckg@ucsd.edu (C.K.G.)
In Brief
Kupffer cells and recruited myeloid cells
contribute to the pathology of
nonalcoholic steatohepatitis (NASH), but
molecular mechanisms specifying their
distinct identities and functions are not
known. Seidman and colleagues address
this problem by defining cell- and
disease-specific enhancer landscapes
that enable inference of key transcription
factors that drive myeloid cell diversity
in NASH.
ll
mailto:ttroutman@health.ucsd.�edumailto:ckg@ucsd.�eduhttps://doi.org/10.1016/j.immuni.2020.04.001http://crossmark.crossref.org/dialog/?doi=10.1016/j.immuni.2020.04.001&domain=pdf
ll
Article
Niche-Specific Reprogramming of EpigeneticLandscapes Drives Myeloid Cell Diversityin Nonalcoholic SteatohepatitisJason S. Seidman,1,10 Ty D. Troutman,1,2,10,* Mashito Sakai,1,10 Anita Gola,3 Nathanael J. Spann,1 Hunter Bennett,1
Cassi M. Bruni,1 Zhengyu Ouyang,1 Rick Z. Li,1 Xiaoli Sun,2 BaoChau T. Vu,1 Martina P. Pasillas,1 Kaori M. Ego,1
David Gosselin,4 Verena M. Link,1,5 Ling-Wa Chong,6 Ronald M. Evans,6,7 Bonne M. Thompson,8 Jeffrey G. McDonald,8
Mojgan Hosseini,9 Joseph L. Witztum,2 Ronald N. Germain,3 and Christopher K. Glass1,2,11,*1Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA2Department of Medicine, University of California, San Diego, La Jolla, CA, USA3Lymphocyte Biology Section, Laboratory of Immune SystemBiology, National Institute of Allergy and Infectious Diseases, National Institutes
of Health, Bethesda, MD 201892, USA4Department of Molecular Medicine, Université Laval, Quebec City, QC, Canada5Faculty of Biology, Division of Evolutionary Biology, Ludwig-Maximilian University of Munich, Munich, Germany6Gene Expression Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA7Howard Hughes Medical Institute, The Salk Institute for Biological Studies, La Jolla, CA, USA8Center for Human Nutrition, UT Southwestern Medical Center, Dallas, TX, USA9Department of Pathology, University of California, San Diego, La Jolla, CA, USA10These authors contributed equally11Lead Contact*Correspondence: ttroutman@health.ucsd.edu (T.D.T.), ckg@ucsd.edu (C.K.G.)
https://doi.org/10.1016/j.immuni.2020.04.001
SUMMARY
Tissue-resident and recruited macrophages contribute to both host defense and pathology. Multiple macro-phage phenotypes are represented in diseased tissues, but we lack deep understanding ofmechanisms con-trolling diversification. Here, we investigate origins and epigenetic trajectories of hepatic macrophages dur-ing diet-induced non-alcoholic steatohepatitis (NASH). The NASH diet induced significant changes in Kupffercell enhancers and gene expression, resulting in partial loss of Kupffer cell identity, induction of Trem2 andCd9 expression, and cell death. Kupffer cell loss was compensated by gain of adjacent monocyte-derivedmacrophages that exhibited convergent epigenomes, transcriptomes, and functions. NASH-inducedchanges in Kupffer cell enhancers were driven by AP-1 and EGR that reprogrammed LXR functions requiredfor Kupffer cell identity and survival to instead drive a scar-associated macrophage phenotype. These find-ings reveal mechanisms by which disease-associated environmental signals instruct resident and recruitedmacrophages to acquire distinct gene expression programs and corresponding functions.
INTRODUCTION
Tissue-resident macrophages exhibit different transcriptomes in
response to environmental signals, enabling tissue-specific
functions (Gautier et al., 2012; Gosselin et al., 2014; Lavin
et al., 2014; Mass et al., 2016). Most tissues acquire resident
macrophage populations early in development from yolk sac or
fetal liver erythromyeloid progenitor (EMP) cells (Ginhoux et al.,
2010; Gomez Perdiguero et al., 2015; McGrath et al., 2015;
Schulz et al., 2012). In the brain and liver, EMP-derived microglia
and Kupffer cells (KCs) continue as exclusive, self-renewing
populations. In other tissues, EMP-derived macrophages are
partially or completely replaced over time by hematopoietic
stem cell (HSC)-derived cells (Bain et al., 2014; De Schepper
et al., 2018; Shaw et al., 2018; Yona et al., 2013).
Resident macrophages and infiltratingmonocyte-derived cells
contribute to a diverse array of human diseases (Holtman et al.,
2017; Kiss et al., 2018; Pirzgalska and Domingos, 2018). Nonal-
coholic steatohepatitis (NASH) is a form of nonalcoholic fatty
liver disease (NAFLD) and develops through combinatorial ac-
tions of steatosis and growing inflammation in response to
cellular stresses of the perturbed fatty liver environment (Haas
et al., 2016; Hardy et al., 2016; Machado and Diehl, 2016; Musso
et al., 2016; Rinella and Sanyal, 2016; Younossi et al., 2016). Dur-
ing NASH or acute liver injury, new macrophages are derived
from circulating monocytes (Karlmark et al., 2009; Seki et al.,
2009a, 2009b; Tacke and Zimmermann, 2014; Zigmond et al.,
2014). These recruited monocyte-derived cells can have both
detrimental and supportive roles, contributing to increases in pa-
thology during fibrosis onset, but hastening recovery when the
Immunity 52, 1057–1074, June 16, 2020 ª 2020 Elsevier Inc. 1057
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damage-evoking agent is removed (Ju and Tacke, 2016; Karl-
mark et al., 2009; Mitchell et al., 2009; Seki et al., 2009a,
2009b; Zigmond et al., 2014). These observations raise ques-
tions as to the mechanisms underlying the phenotypic diversity
of disease-associated macrophages.
Here, we define the identities, developmental origins, and mi-
cro-anatomic locations of the major myeloid populations in
response to a NASH-inducing diet. By sorting these cell popula-
tions and performing deep transcriptomic and epigenomic anal-
ysis, we provide evidence for combinatorial effects of diet and
anatomic location on regulatory pathways and transcription fac-
tors (TFs) that explain the emergence of disease-associated
macrophage phenotypes.
RESULTS
Single-Cell RNA-Seq Defines Myeloid Diversity DuringDietary NASHTo investigate immune cell heterogeneity during NASH, we per-
formed single-cell RNA sequencing (scRNA-seq) on liver non-
parenchymal cells from healthy mice fed a control diet or
NASH diet. As noted in previous studies (Hall et al., 2010; Pous-
sin et al., 2011), C57BL/6J mice exhibited rapid weight gain
when fed the NASH diet (Figure S1A) and developed steatosis,
inflammation, and a modest degree of fibrosis (Figure S1B).
Non-parenchymal cells from control mice and mice fed the
NASH diet for 30 weeks were purified using fluorescence-acti-
vated cell sorting (FACS) (Figure S1C). Over 6,000 scRNA-seq li-
braries that passed quality thresholds were created from these
isolated cells.
The NASH diet induced qualitative transcriptional differences
in cell clustering between cells from control livers and NASH
livers (Figure 1A left, Figure 1B; Table S1). Further, three of 17
clusters were primarily derived from cells from control diet
mice while eight clusters were primarily derived from NASH
diet mice (Figures 1A and S1D; Table S1). Interrogation of the
most abundant and most differentially expressed (DE) tran-
scripts in each cluster allowed a cell identity to be readily as-
signed to most clusters. Further studies were focused on the
five most abundant macrophage clusters. (Figure S1E;
Table S1).
The three most abundant clusters (KC-H, healthy KC;
KC-N, NASH KC; and KN-RM, named for being a recruited
macrophage occupying the KC niche, as described later)
had high expression of Adgre1, encoding the tissue macro-
phage marker F4/80, and high expression of putative KC
lineage-determining transcription factors (LDTFs) Mafb
and Maf, and KC-specific genes, as well as low expression
of Itgam, encoding CD11b (Figures 1C and S1E; Lavin et al.,
2014). KC-H consisted almost entirely of cells from controls,
while KC-N and KN-RM consisted of cells from the NASH
diet animals (Figures 1A and 1B; Table S1). The other two
major macrophage clusters were predominantly found in
NASH livers and had characteristic gene expression of
previously described monocyte-derived liver macrophages
(Figures 1C and S1E; Krenkel et al., 2018). Cluster 4 (hereafter
referred to as Ly6Chi-RM) expressed higher amounts of
transcripts typical of Ly6Chi monocytes such as Ly6c2,
Chil3, F13a1, and Fn1, while cluster 9 (hereafter referred to
1058 Immunity 52, 1057–1074, June 16, 2020
as Ly6Clo-RM) highly expressed Cd209a, Cd7, and Itgax
(Figure S1E).
Using flow cytometry, we observed both Tim4+ and Tim4�
cells in the CD11bloF4/80hi KC gate during NASH in similar
proportions to KC-N and KN-RM and collected them for bulk
RNA-seq and epigenomic profiling (Figure 1D). We also
collected CD11bhiF4/80lo-Ly6Chi-RM and Ly6Clo-RM for RNA-
seq and assay for transposase-accessible chromatin (ATAC-
seq) (Figure 1E; Buenrostro et al., 2013). RNA-seq analysis of
these populations yielded concordant expression profiles to
scRNA-seq when comparing Seurat marker genes, indicating
that we isolated the corresponding macrophage populations
defined by scRNA-seq (Figure 1F).
We next compared these mouse macrophages to human
scRNA-seq populations of non-parenchymal liver cells from in-
dividuals with either advanced cirrhosis or without evident liver
disease (Ramachandran et al., 2019). Using orthogonal genes
to cluster the combined set of human and mouse cells under
control and disease conditions resulted in eight clusters (0–7,
Figures S1F and S1G). Human livers exhibited a greater diver-
sity of myeloid cells and, in contrast to the mouse model, all cell
populations were present to some extent in individuals with or
without cirrhosis. Importantly, mouse KC-H cells overlapped
with human KCs (clusters 0 and 1). A key finding of the human
studies was the increased presence of a ‘‘scar-associated
macrophage’’ (SAM) population in cirrhotic livers (Ramachan-
dran et al., 2019). These cells were found to reside in close
proximity to areas of fibrosis and were characterized by
increased expression of TREM2 and CD9. Importantly, the
cluster containing SAMs also contained substantial fractions
of the NASH-associated KC-N and KN-RM cells (cluster 3),
but not KC-H cells, consistent with the former cell type’s
increased expression of Trem2 and Cd9 (Figure 1F). Thus,
despite relatively sparse fibrosis, a SAM phenotype emerges
in this model.
Ontogeny and Environment Contribute to Diversity ofMyeloid Cells During NASHWe hypothesized that, similar to experimental KC ablation (Bon-
nardel et al., 2019; Sakai et al., 2019; Scott et al., 2016), Tim4�
KC-like macrophages that arise during NASH (KN-RM) may be
ontogenically distinct from the embryonically derived Tim4+
KCs (KC-N). To test this hypothesis, we performed lineage-
tracing experiments using Cx3cr1CreERT2; Rosa26tdTomato/+
mice (Figure S2A; Theurl et al., 2016; Yona et al., 2013). This
model labels tissue macrophages if tamoxifen is administered
perinatally, while only certain macrophages such as microglia,
but not KCs, are labeled if mice are pulsed during adulthood
(Dick et al., 2019; Theurl et al., 2016; Yona et al., 2013). In
contrast, during adulthood, tamoxifen labels peripheral mono-
cytes and thus monocyte-derived macrophages.
Tamoxifen administration on days 1 and 2 post-parturition re-
sulted in ~50% labeling of embryonic KCs (Figures S2B–S2D).
After 20 weeks on the NASH diet, nearly all tdTomato+ cells
were Tim4+ KCs (KC-N) (Figures S2B–S2D), indicating that
Tim4� KC-like macrophages (KN-RM) are not long-lived daugh-ters of embryonic KCs. Conversely, when adult mice fed the
NASH diet for 20 weeks were given tamoxifen 4 or 1 week prior
to sacrifice, ~90% of circulating monocytes were TdTomato+
A
B
F
C
D E
Figure 1. Transcriptional Diversity of Hepatic Macrophages during NASH
(A) tSNE projections of identified graph-based cell clusters from scRNA-seq data derived from hepatic CD45+CD146� cells from control mice ormice fed a NASHdiet for 30 weeks. (Left) cells are colored based on dietary condition. (Right) cells are colored based on cell identity of the five major myeloid cells identified. Data
represent two independent donor mice per group.
(B) Macrophage proportions from (A) for control mice (left) or mice with NASH (right).
(C) Gene expression of normalized scRNA-seq data of genes supporting cluster identities. Boxes denote quartiles, and whiskers denote data range excluding
outliers.
(D) Terminal FACS gates for purification of KCs from control mice (left), or CD11bloF4/80hiTim4+ and Tim4� cells from mice with NASH (right).(E) Terminal FACS gates for purification of Ly6Chi and Ly6Clo CD11bhiF4/80loLy6G�CX3CR1+ recruited hepatic macrophages (RM). ‘‘PMN’’ stands for poly-morphonuclear leukocyte.
(F) Comparison of myeloid clusters defined by scRNA-seq (left) and bulk RNA-seq (right) for the corresponding sorted populations. Left heatmap (100 cells per
column) depicts normalized and scaled expression values for marker genes identified using a Wilcoxon rank sum test through Seurat. Right heatmap shows z-
normalized row expression of each gene for RNA-seq from bulk purified cell populations from independent biological duplicates.
Please see also Figure S1.
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2 days after the final tamoxifen injection (data not shown), and
more than 10% of Tim4� KC-like macrophages (KN-RM) wereTdTomato+ (Figures S2C and S2D). We also observed a small
degree of labeling of Tim4+ KCs (Figures S2C and S2D), which
could be due to low expression of Cx3cr1 in Tim4+ KC-N cells
or to the gradual upregulation of Tim4 by recruited cells (Scott
et al., 2016). Overall, these results indicate that embryonic KCs
remain in the liver during development of NASH and are Tim4+,
Immunity 52, 1057–1074, June 16, 2020 1059
0.01
1
100
1
10
100
1000
KC−N KN−RM Ly6Chi&lo−RMTU
NE
L ne
ares
t nei
ghbo
rdi
stan
ce (
μm)
0
25
50
75
100
0 10 20 30
Weeks on AMLN NASH diet
Per
cent
KN
-RM
KC−HKN
−RM
Ly6C
hi&lo −R
MKC
−NKN
−RM
Ly6C
hi&lo −R
M
NASHControl
E
ANASH diet
nirehdac-Eota
moTdt+
08/4F+
ot amoTdt
F4/80
KC-N
KN-RM
B
Tim4
IFM
KC-NKN-RM
F4/80
2lgM
Mgl2+(Ly6Clo-RM)
Mgl2–(Ly6Chi-RM)
D
cv
PV
PV
PV
H
NAS
H d
iet
F4/80 TUNEL Tim4
KC-N
KC-N
KN-RM
KN-RM
KN-RM
F4/80 TUNEL Tim4
I J
6.94%
17%
75.3%
F
G
K
E-cadherin Mgl2+ Mgl2–
Tota
l TU
NE
L+ c
ell c
ount
per
area
1,0
00 μ
m2
0
250
500
750
1000
KN−R
M
Ly6C
hi −RM
Ly6C
lo −RM
KC
−N
nea
rest
neig
hbor
dis
tanc
e ( μ
m)
0
200
400
600
800
Dis
tanc
e to
nea
rest
CV
or
PV
(μm
)0
25
50
75
100
125
KC−NKN
−RM
Ly6C
hi&lo −R
M
Dis
tanc
e to
nea
rest
larg
e ve
ssel
(μ m
) *** ***
******
*****
***
***
******
***
***
***
CV PV
CV PVLy6Chi−RM
CV PVLy6Clo−RM
Ly6Chi&lo-RMLy6Chi&lo-RM
E-cadherin KN-RM KC-NLy6Chi&lo-RM
PV
PV
PV
cv
CV
PV
PV
C
(legend on next page)
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1060 Immunity 52, 1057–1074, June 16, 2020
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while most recruited CD11bloF4/80hi macrophages are Tim4�.These results also indicate that recruited KN-RM cells can
survive at least 4 weeks in the NASH liver while Ly6Chi&lo-RMs
are shorter lived.
To determine the localization of myeloid cells in the liver during
NASH, immunofluorescence (IF) microscopy was performed on
livers from Cx3cr1CreERT2; Rosa26tdTomato/+ mice pulsed with
tamoxifen 7 days prior to tissue collection (Figures 2A, 2B,
S2A, S2E, and S3A). As expected, tdTomato+ monocyte-derived
cells were abundant in NASH livers but nearly absent in control
livers (Figure S2E). Using multi-parameter imaging and histo-cy-
tometry (Gerner et al., 2012), we distinguished KC-H or KC-N,
KN-RM, and Ly6Chi&lo-RM in the control and NASH livers based
on Tim4, F4/80, and tdTomato expression. As Ly6C histological
staining could not be performed, Mgl2 was used as a surrogate
marker for Ly6Chi&lo-RM, with the Ly6Chi fraction being Mgl2�
and Ly6Clo being represented byMgl2+ (Figures 2A–2C, see Fig-
ure 3G for Ly6Clo-specific expression of Mgl2). Following in situ
confirmation of these myeloid cell subsets, we assessed their
spatial distribution using the positional data preserved in histo-
cytometry and nearest-neighbor distance analyses. The two
subsets (KN-RM and Ly6Chi&lo-RM) that were increased during
NASH displayed significant differences in their spatial distribu-
tions. By comparing nearest-neighbor distances from KC-N,
KN-RM cells were found to be distributed significantly closer
to KC-N cells than Ly6Chi&lo-RM cells (Figure 2D). In addition,
the small number KN-RM cells observed in control livers were
also in close proximity to KC-H cells (Figure S3B and data
not shown).
KCs reside within the hepatic sinusoids, but the sub-anatom-
ical organization of other liver macrophages during NASH is
less certain (Ju and Tacke, 2016). High-magnification imaging
using Collagen IV to visualize the endothelial basement mem-
brane demonstrated that KC-N and KN-RM cells resided within
hepatic sinusoids in this model (Figure S3C). In contrast, Ly6-
Chi&lo-RM cells were predominantly not found within the liver
Figure 2. Expanded Macrophage Diversity during NASH Is Supported
Niches
(A) Confocal image of NASH liver showing E-cadherin (to demark the peri-portal
white circles are the central veins (CV). Demarked at the periphery of the liver lobu
Scale: 50 microns.
(B) Histo-cytometry analysis of NASH liver sample. Statistical information of se
subsequently gated on F4/80 and tdTomato expression to quantify KC-N, KN-RM
population are shown in the middle panel, and Mgl2 expression on Ly6Chi&lo-R
(Mgl2+) cells.
(C) Confocal image of NASH liver showing distribution of rendered surfaces of
regions as in (A). Scale: 50 microns.
(D) Distance and phenotype (KN-RM, Mgl2lo-RM, or Mgl2hi-RM) of closest neighb
test; p < 0.001(***).
(E) Distance to nearest portal or central vein vasculature (large diameter vessels de
cells. Kruskal-Wallis with Dunn test; p < 0.001(***).
(F) Zoom-in representative confocal image of NASH liver showing distribution
demarks the peri-portal regions, and highlighted by white circles are CV and PV
(G) Distance to nearest center of CV or PV of Ly6Chi and Ly6Clo RM cells (mm). K
(H) Immunofluorescence (IF) image assessing in situ cell death via TUNEL staini
intensity projection (MIP) of a 20-mm z stack. Scale: 5 microns for the top row an
(I) Quantification of total TUNEL+ hepatic macrophages per area (1000 mm2) in C
(J) Nearest neighbor distance of all TUNEL+ cells to KN-RM, Ly6Chi or lo-RM, and K
test; p < 0.001(***).
(K) Temporal assessment of percentage of total CD11bloF4/80+CD146� cells thaPlease see also Figure S2 and Figure S3.
sinusoids, but were highly enriched around both portal and cen-
tral vein vasculature identifiable by the large vessel diameter
(15 mm or larger) (Figures 2D and 2E). Further, Ly6Chi-RM
(Mgl2�) cells were bi-modally distributed around portal andcentral veins, while Ly6Clo-RM (Mgl2+) cells were more uniformly
distributed in closer proximity to central veins (Figures 2F and
2G). Together, these findings further supported Ly6Chi&lo-RM
cells as being positionally separated from KC-N and KN-RM
cells based on measurements that were independent of
anatomical landmarks. These results provide evidence that
KC-N and KN-RM cells reside in a similar niche within the liver
sinusoids, which is spatially distinct from the anatomic positions
occupied by Ly6Chi&lo-RMs.
Previous work found that DLL4 expression by liver sinusoidal
endothelial cells (LSECs) is graded toward higher expression
patterns in periportal zones (Halpern et al., 2018). Further,
DLL4 mediated-activation of RBPJ participates in driving differ-
entiation of monocytes to Kupffer-like cells in a repopulation
model (Sakai et al., 2019). During NASH, we confirmed the
peri-portal (E-cadherin+) enrichment of DLL4 on LSECs (Figures
S3D and S3E). Further, KC-N and KN-RM cells were significantly
closer to DLL4+ CD138+ LSECs compared to Ly6Chi&lo-RMs
(Figures S3F and S3G). These results provide support for DLL4
as a factor that may support niche specialization of distinct
macrophage populations during NASH, consistent with its
known function in instructing a KC program in recruited
monocytes.
NASH Diet Induces KC Death and ReplacementKCs are considered a self-renewing population that is normally
closed to HSC-derived cells (Perdiguero and Geissmann,
2016). However, the observation that the NASH diet resulted in
recruitment of HSC-derived KN-RM cells raised the question of
whether the NASHdiet induces loss of embryonic KCs, providing
an open niche. TUNEL staining of NASH livers showed apoptosis
of Tim4+ KC-Ns during NASH diet, but not of KC-H cells from
by Monocyte Recruitment and Occupancy of Distinct Anatomical
regions) and tdTomato F4/80+ summed channel. Highlighted in the center by
le, portal-venous or arterial vessels (PV). Data from n = 3–4 mice per condition.
gmented objects (F4/80+tdTomato+ surfaces) was imported into FlowJo and
, and Ly6Chi&lo-RM cells. Tim4mean fluorescence intensity (MFI) for each gated
M cells macrophage is shown at right to distinguish Ly6Chi (Mgl2�) or Ly6Clo
KC-N, KN-RM, and Ly6Chi&lo-RM (Rec) cells. Dashed lines denote peri-portal
or to KC-N cells in NASH livers. Data pooled from n = 4 mice. Wilcox two-sided
fined to be greater than 15 mm in diameter) of KC-N, KN-RM, and Ly6Chi&lo-RM
of rendered surfaces of Mgl2lo (Ly6Chi) and Mgl2hi (Ly6Clo)-RMs. E-cadherin
blood vessels. Scale: 30 microns.
ruskal-Wallis with Dunn test; p < 0.01(**), p < 0.001(***).
ng in addition to Tim4 and F4/80 staining. Image from NASH mice; maximum
d 10 microns for the bottom row.
trl and NASH mouse livers.
C-N cells in NASH livers, data pooled from n = 4mice. Kruskal-Wallis with Dunn
t are Tim4� KN-RM from mice fed a NASH diet as indicated.
Immunity 52, 1057–1074, June 16, 2020 1061
Clu
ster
1C
lust
er 4
Clu
ster
2C
lust
er 3
0 5 10 15
0
5
10
15
685
1442
Blood Ly6Chi Mono
Ly6C
Hi -R
M
Blood Ly6Chi
KC-H KC-N KN-RMLy6Chi
-RMLy6Clo
-RM
0 5 10 15
0
5
10
15
521
316
KC
-H
KC-N
Mean expression (log2(TPM+1))
A
0 5 10 15
0
5
10
15
40
53
KN
-RM
Mean expression (log2(TPM+1))
KC-N
F
B
C D
E
−2 −1 0 1 2z-scaled (Log2(TPM+1))
0 5 10 15
0
5
10
15
1193
1046
Ly6Chi-RM
KN
-RM
2,21
0 ge
nes;
Log
2FC
> 2
; p.a
dj <
0.0
5;T
PM
> 4
EMP
Sinusoids Large vessels
Ctrl NASH
−20 0 20 40 60
−30
−20
−10
0
10
20
30
PC1 (57%)
PC2
(19%
)
Ly6Clo-RM
Ly6Chi-RM
KC-H
KC-N
KN-RM
RLM 14d
RLM 12h
RLM 1dBloodLy6Chi
Monocytes(Ctrl and NASH)
0
500
1000
1500
Mea
n E
xpre
ssio
n (T
PM
)
0
100
200
0
200
400
600
800
KC-H
KC-N
KN-R
M
Ly6C
hi -RM
Ly6C
lo -RM
Ly6C
hi -Mo
0
25
50
75Cd9
Trem2Clec10aMgl2
Arg2
Txnrd1
C6
Cd163
KC-H
KC-N
KN-R
M
Ly6C
hi -RM
Ly6C
lo -RM
Ly6C
hi -Mo
KC-H
KC-N
KN-R
M
Ly6C
hi -RM
Ly6C
lo -RM
Ly6C
hi -Mo
KC-H
KC-N
KN-R
M
Ly6C
hi -RM
Ly6C
lo -RM
Ly6C
hi -Mo
Kupffer cell signature
Response to wounding
ROS metab. signature
Scar-assoc. mac (SAM)
G
H
DTR–DTR+
Clec4f+Tim–
KC
0
1
2
3
Clec4f+Tim+
KC
0
2
4
6
Total KC
0
5
10
Per
cent
CD
45+
J K NASH CRN Score
0
2
4
6
DT
R–
DT
R+
DTR–DTR+
I
0 5 10 15
0
5
10
15
DTR–, n = 10
DT
R+, n
= 1
2
Mean expression (log2(TPM+1))
(legend on next page)
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1062 Immunity 52, 1057–1074, June 16, 2020
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mice fed a control diet (Figures 2H and 2I). In both control and
NASH livers, TUNEL+ KN-RM and Ly6Chi&lo-RM cells were rare
(Figure 2I). By nearest-neighbor analysis of TUNEL+ cells, KN-
RM cells were significantly enriched in nearby areas as
compared to Ly6Chi&lo-RM and KC-N cells (Figure 2J). Time
course experiments indicated that KN-RM cells were detected
by 10 weeks after initiation of the NASH diet and progressively
accumulated to account for more than 50%of the KC population
at 30 weeks (Figure 2K). These results indicate that Tim4+ KCs
undergo cell death during NASH, potentially resulting in partial
opening of the niche and enabling repopulation by HSC-derived
KN-RM cells.
Effect of NASH Diet on Resident and Recruited MyeloidCell TranscriptomesThe ability to sort distinct populations of hepatic myeloid cells
defined by scRNA-seq analysis enabled deep transcriptomic
profiling of each population (Table S2). Unsupervised hierar-
chical clustering of 2,210 DE genes among KC-H, KC-N,
KN-RM, Ly6Chi-RM, and Ly6Clo-RM tightly grouped KC-N
and KN-RM and distinguished KC-H, KC-N, and KN-RM cells
from Ly6Chi&lo-RMs (Figure 3A). With inclusion of DE genes in
blood monocytes, principal component analysis (PCA) also
indicated that KC-N and KN-RM cells from NASH mice group-
ed most closely with KC-H cells from healthy mice (Figure 3B).
After experimental KC ablation, blood Ly6Chi monocytes are
recruited to the liver and rapidly differentiate into KC-like liver
macrophages (Bonnardel et al., 2019; Sakai et al., 2019; Scott
et al., 2016). At 14 days after KC ablation, these repopulating
macrophages (GEO: GSE128662) also grouped closely with
KC-H, KC-N, and KN-RM (Figure 3B). Collectively, these re-
sults suggest that monocyte-derived KN-RMs follow a similar
developmental trajectory in the context of NASH to that of re-
populating liver macrophages (RLMs) in the KC abla-
tion model.
Pairwise comparisons of KC-H and KC-N cells indicated
that the NASH diet had a large impact on resident KC gene
expression (>800 DE genes), consistent with scRNA-seq
data (Figure 3C). Notably, fewer than 100 genes were identi-
fied as significantly altered when comparing KC-N and KN-
RM KCs from mice with NASH (Figure 3D), despite their
distinct origins (EMP versus HSC). In contrast, during NASH,
Figure 3. Highly Divergent Gene Expression Patterns across Myeloid P
(A) Unsupervised hierarchical clustering of DE genes in the indicated cell types i
(B) PCA of 2,000 most variable genes in RNA-seq data frommyeloid cells in liver a
from Sakai et al. (2019), n = 2–3 per group.
(C) Scatterplot of RNA-seq data in healthy (KC-H) or NASH (KC-N) Tim4+ KCs. D
(D) Comparison of NASH Tim4+ KCs (KC-N) and Tim4� Kupffer niche recruited m(E) Comparison of NASH Tim4� Kupffer niche recruited macrophages (KN-RM) a(F) Comparison of NASH blood Ly6Chi monocytes and Ly6Chi-RM.
(G) RNA-seq expression (mean TPM ± SD) of representative genes. TPM = trans
(H) Percentage of hepatic CD45+F4/80hiCD11bloLiveSinglets fromClec4f-cre R26
with DT, allowed to rest for 4 weeks, then fed the choline-deficient, L-amino acid
(I) RNA-seq from whole liver tissue from Clec4f-cre R26-iDTR�/� (n = 10) or Clec4quartiles, and whiskers denote data range.
(J) Representative (n > 5) H&E staining of liver tissue.
(K) NASH Clinical Research Network (CRN) scoring of stained liver sections. Scor
using Kruskal-Wallis rank sum test (p = 0.71). Boxes denote quartiles, and whisk
Please see also Figure S4.
KN-RM cells exhibited more than 2,200 DE genes in compar-
ison to Ly6Chi-RM, despite both cells originating from an HSC
precursor (Figure 3E). The divergent differentiation programs
of KN-RM and Ly6Chi-RM were further reinforced by pairwise
comparisons with gene expression in Ly6Chi circulating
monocytes, indicating more than 2,000 DE genes in each
case (Figures 3F and S4A).
Prior studies defined a set of KC identity genes that distinguish
the KC from other tissue-resident macrophages (Lavin et al.,
2014). Twenty-eight of the genes downregulated during the tran-
sition of KC-H cells to KC-N cells in the NASH model are among
this set, exemplified by Cd163 and C6 (Figures 3G and S4B).
However, many KC-specific genes maintained similar expres-
sion in cells from mice on the NASH diet, including C1qa, Cd5l,
Id3, and Il18bp, indicating that only a subset of the KC-specific
gene expression program is altered during NASH. Furthermore,
KC identity genes such as Clec4f, Vsig4, and Cdh5 were highly
expressed in KN-RM, but neither Ly6Chi&lo-RM population.
Considering the differential spatial distribution of these cell pop-
ulations, such findings suggest that the KC niche is necessary to
promote induction of these genes (Figure S4B).
Gene ontology analyses of genes whose expression distin-
guishes KC-H, KC-N, and KN-RM cells from Ly6Chi&lo-RM
(clusters 1 and 2, Figure 3A) were consistent with a stronger
pro-inflammatory and wound repair phenotype of the Ly6-
Chi&lo-RMs (Figure S4C), in agreement with prior studies (Hey-
mann and Tacke, 2016). Examples of DE genes associated
with the functional categories of ‘‘ROS metabolism’’ and
‘‘response to wounding’’ are illustrated in Figure 3G. Ly6Clo-
RM preferentially expressed Mgl2 (CD301b), a gene recently re-
ported to be expressed in skin macrophages that activates a
specific myofibroblast population implicated in tissue repair
and aging (Shook et al., 2018). In addition, we observed
increased expression of Trem2 and Cd9 in both KC-N and
KN-RM cells, consistent with recent observations identifying
these genes as markers for macrophages associated with
increased lipid burden and the presence of tissue scarring
(Hill et al., 2018; Jaitin et al., 2019; Ramachandran et al.,
2019; Xiong et al., 2019). Collectively, these results indicate
that the NASH diet acts to reprogram the endogenous KC pop-
ulation and induce divergent programs of differentiation of KN-
RM cells and Ly6Chi&lo-RMs.
opulations in NASH
n control and NASH liver.
nd blood from healthy and NASH-diet-fed mice, or recruited liver macrophages
E genes identified by DESeq2 (FC > 2, p-adj < 0.05) are colored in red.
acrophages (KN-RM).
nd Ly6Chi-RM.
cripts per kilobase million).
-iDTR�/� (n = 6) or Clec4f-cre R26i-DTR+ (n = 6)mouse livers. Mice were treated-defined, high-fat diet (CDAHFD) for 4 weeks.
f-cre R26-iDTR+ mice (n = 12) as in (H). Zero DE genes (DESeq2). Boxes denote
es > 5 are indicative of steatohepatitis. No significant difference was identified
ers denote data range.
Immunity 52, 1057–1074, June 16, 2020 1063
llArticle
Functional Convergence of Embryonic KCs and KN-RMsin NASHTo clarify the functional biological roles of embryonic KCs and
monocyte origin KN-RM cells, we used the Clec4f-cre R26-
iDTR system (Sakai et al., 2019). We treated DTR+ or DTR�
mice with diphtheria toxin (DT) to ablate embryonic KCs and
then allowed the KC niche to repopulate with monocyte precur-
sors. After a 4-week recovery period, the mice were subjected to
ad libitum feeding for 4weekswith a rapid NASH-inducingmodel
(Matsumoto et al., 2013). Ablation of embryonic (KC-H) KCs
before feeding mice the NASH diet led to increased proportions
of Tim4� KN-RM cells, as expected (Figure 3H). To assess theglobal molecular consequence of replacing embryonic KCs
with monocyte-derived KN-RMs, we performed RNA-seq on to-
tal liver tissue (Figure 3I). Notably, we found no DE genes be-
tween the two groups. We also found no differences in 23 circu-
lating inflammatory cytokines (Figure S4D). Finally, quantitative
histological assessment of liver sections indicated no effect of
replacing KCs with KN-RM. These results are consistent with
the largely convergent transcriptomes observed in comparison
of KC-N and KN-RM (Figures 3J and 3K).
Niche Occupancy Reprograms the EpigeneticLandscapesTo investigate mechanisms responsible for environment-spe-
cific programs of gene expression, we identified accessible
chromatin defined by ATAC-seq in five populations of cells
from mice with NASH: KC-N and KN-RM cells, Ly6Chi&lo-RMs,
and Ly6Chi blood monocytes. Examples of ATAC-seq peaks in
these five populations of cells from mice fed the NASH diet in
the vicinity of theClec4f and Itgam genes, which are highly differ-
entially expressed in KCs compared to Ly6Chi&lo-RMs, are illus-
trated in Figure 4A. Genome-wide comparisons of ATAC-seq
peak tag counts for Ly6Clo-RM versus Ly6Chi blood monocytes
are illustrated in Figure 4B, and the same comparison for KN-RM
and Ly6Chi blood monocytes is shown in Figure 4C. Differential
regions from the five myeloid populations in NASH mice, as
well as healthy KC-H cells and 24- and 48-h RLMs after KC abla-
tion (Sakai et al., 2019), were used for PCA illustrated as in
Figure 4D. PC1, accounting for ~65% of variance, primarily
distinguished KC-H, KC-N, and KN-RM populations from Ly6Chi
blood monocytes and Ly6Chi&lo-RM. RLMs 24 and 48 h after KC
ablation became incrementally closer to KCs along PC1, reflect-
ing chromatin remodeling after arriving at the KC niche. PC2, ac-
counting for ~13% of variance, primarily separated Ly6Chi blood
monocytes from Ly6Chi&lo-RM.
Hierarchical clustering of ATAC-seq data further support the
relationships suggested by PCA, with KC-N and KN-RMcells ex-
hibiting highly similar patterns of open chromatin that are distinct
from the transitional patterns observed in Ly6Chi&lo-RM (Fig-
ure S5A). Based on these findings and the results of lineage-
tracing experiments, we considered the open chromatin regions
of KN-RM and Ly6Clo-RM populations as divergent endpoints of
chromatin remodeling events following entry of Ly6Chi blood
monocytes into the NASH liver. ATAC-seq peaks specific for
KN-RM or Ly6Clo-RM in comparison to circulating Ly6Chi mono-
cytes (red data points in Figures 4B and 4C, respectively) indi-
cated that approximately 75% of these peaks were specific to
KN-RM or Ly6Clo-RM cells (Figure 4E). Peaks specific for KN-
1064 Immunity 52, 1057–1074, June 16, 2020
RM cells were highly enriched for motifs recognized by LXR
and members of the MAF and TFE families (Figure 4E). In
contrast, ATAC-seq peaks specific for Ly6Clo-RM cells were
highly enriched for NF-kB motifs and for motifs recognized by
RUNX, ZEB, and KLF TFs. Open chromatin regions lost from
blood monocytes during acquisition of either the KC or Ly6Chi&lo
-RM niche signatures (Figures 4B and 4C, blue points) were en-
riched for KLF and C/EBP motifs (Figures S5B and S5C). The
open chromatin regions lost during acquisition of the KC niche
additionally included motifs for RUNX and CTCF (Figure S5B).
The pattern of motif enrichment in KC-N and KN-RM cells im-
plies that liver niche signals increase the expression and/or activ-
ities of TFs that bind to LXR, MAF, and TFE motifs. Consistent
with this possibility, Nr1h3 (encoding LXRa), Mafb, Tfec, and
Id3 (Lavin et al., 2014; Mass et al., 2016) are among a set of
KC LDTFs higher expressed in KC-N and KN-RM cells than in
Ly6Chi&lo-RM cells (Figure 4F; Table S2). Importantly, these
TFs are highly induced in RLMs within 12 h of entry into the
open KC niche of the liver (Sakai et al., 2019). These findings
further support a model in which KN-RM cells largely follow the
developmental program taken by RLMs following KC depletion
upon adherence to LSECs. In contrast, the lack of induction of
KC LDTFs in Ly6Chi&lo-RM cells is consistent with their location
outside of the sinusoidal space. NF-kB motifs are enriched in
KC enhancers in comparison to other tissue-resident macro-
phages (Sakai et al., 2019), but the particularly strong enrichment
for this motif in Ly6Clo-RM cells implies that the niche occupied
by these cells provides additional signals that activate NF-kB. In
addition, while RUNX factors are lower in KC-N and KN-RM cells
in comparison to blood Ly6Chi monocytes, their expression is
maintained or increased in Ly6Chi&lo-RMs (Figure S5D). In con-
cert, analysis of open chromatin provides evidence that the
divergent patterns of gene expression observed in HSC-derived
KN-RM and Ly6Chi&lo-RM cells are in part determined by
whether or not they receive niche-specific signals necessary to
adequately induce KC LDTFs.
NASH Diet Reprograms the KC Enhancer LandscapeWe next sought to understand the basis for the altered expres-
sion of the more than 900 mRNAs during the transition of KC-H
cells in the healthy liver to KC-N cells in the NASH liver (Figures
3A and 3C). Corresponding changes in the regulatory land-
scapes during this transition would potentially enable inference
of TFs and upstream signaling pathways that mediate re-
sponses to the NASH diet. In contrast to changes in open chro-
matin observed in transition of Ly6Chi blood monocytes to KN-
RM cells (Figures 4C and 4D), relatively few differences in open
chromatin were observed comparing KC-H and KC-N cells
(Figure 5A, left). The enriched motifs associated with the
increased chromatin accessibility included sites for AP1 and
EGR factor binding, whereas sites of decreased chromatin
accessibility were enriched for PU.1 and SpiC motifs (Figure 5A
right).
To investigate potential changes in the transcriptional func-
tions of these regions, we performed chromatin immunoprecip-
itation sequencing (ChIP-seq) for acetylation of histone H3 lysine
27 (H3K27ac) in KC-H cells in the healthy liver and KC-N cells in
the NASH liver. H3K27ac is deposited by histone acetyltrans-
ferases (HATs) associated with transcriptional co-activators
0 2 4 6 8 10 12 14
0
2
4
6
8
10
12
14
Ly6C
lo-R
M
8507
3509
Ly6Chi Blood
KC-N
KN-RM
5 kb
01e32e33e3
01e32e33e3
01e32e33e3
01e32e33e3
01e32e33e3
Clec4f10 kb
02e24e2
02e24e2
02e24e2
02e24e2
02e24e2
Itgam
ATAC-seq ATAC-seqRNA RNAA B C
E
F
0 2 4 6 8 10 12 14
0
2
4
6
8
10
12
14
KN
-RM
6732
2458
Gained during niche acquisition versus Ly6Chi peripheral blood monocytes
P- value
%targ/%bkgd
BestMatch
NF-κBZEBRUNX
TFE/MITFLXREMAF
ATAC-seq peaks
4,500 only up in KN-RM
6,279 only up in Ly6Clo
-RM
2,226 upin both
Motif
1e-1011e-911e-79
30/175.1/0.933/21
1e-5221e-1481e-102
34/1037/2339/27
TCAGCTGACTGAGCTACGTAGACTGATCGTACTGACGATC
CGATTGAC
ACGT
GTACTCGAATCGATCGAGCTCTGACTAG
TGACCTGAGTCATCGA
AGTC
G TACGCTAG TACCGTACTAG
CATG
AC TGCTAGTCGACGTACGATAGCTGATCG TACG TACGTACCATGCTGATACGACTGC TGACGTAC TGACG TACGTAATGCCTAGGACTACTGC TAGCG TACG TACG TACG TAACGTGCATACTGCGTAAGTCTCAG
CGATGTACCGTAACGTAGTC
C CG T ACG ACG CG ACG G T CG T A ACG ACG ACG ACG AG T ACG ACG
NF-κBNFATJUN-CRE
1e-911e-791e-75
20/6.82.1/.0231/16
TCGACTGATCAGGCAT
AG TCCG TAAGCTCTAGCGATATCGCTGAAGTCCGAT
CTAGTGCATGAC
AGTCGACTGACTCAGT
CGATCTAG
ACGTTCAGCG TAG TACAG TCAGCTTAGC
TACG
CGATGATCC TGACATGAG TCCGTARBPJ1e-22 12/7.6
GATCCATG
AGCTCTAG
CTAGTCAG
CTGACTGATACGGATC
−100 −50 0 50 100
−80
−60
−40
−20
0
20
40
PC1 (65%)
PC
2 (1
3%)
KC-N
KN-RM
Ly6ChiBlood NASH
Ly6ChiBlood Control
Ly6Clo-RM
Ly6Chi-RM
KC-H
D
RLM 24hr
RLM 48hr
Nr1h3 Mafb Id3
KC
-HK
C-N
KN
−R
MLy
6Chi-R
M
0
100
200
300
400
0
20
40
60
0
100
200
300
400
0
200
400
600
800
Mea
n E
xpre
ssio
n (T
PM
) ATAC-seq (log2(norm. tags +1))
ATAC-seq (log2(norm. tags +1))
Ly6Chi Blood
Tfec
Ly6Chi -RM
Ly6Clo -RM
Ly6Chi Blood
Ly6C
lo-R
MLy
6Chi B
lood
KC
-HK
C-N
KN
−R
MLy
6Chi-R
MLy
6Clo-R
MLy
6Chi B
lood
KC
-HK
C-N
KN
−R
MLy
6Chi-R
MLy
6Clo-R
MLy
6Chi B
lood
KC
-HK
C-N
KN
−R
MLy
6Chi-R
MLy
6Clo-R
MLy
6Chi B
lood
Figure 4. Niche-Specific Reprogramming of Epigenetic Landscapes
(A) UCSC genome browser tracks of ATAC-seq signals in the vicinities of theClec4f and Itgam genes in the indicated cell types. Bar plots to the right of each track
represent the RNA-seq gene expression (mean TPM ± SD) in each population.
(B) Genome-wide comparison of normalized ATAC-seq peak tags at enhancer-like regions (>3 kb removed from transcription start site [TSS]) comparing Ly6Chi
blood monocytes and Ly6Clo-RM during NASH. Differential regions were identified using DESeq2 (FC > 2 and p-adj < 0.05 using independent biological du-
plicates).
(C) Genome-wide comparison of normalized ATAC-seq peak tags at enhancer-like regions (>3 kb removed from TSS) comparing open chromatin in Ly6Chi blood
monocytes and KN-RM.
(D) PCA of ATAC-seq datasets (n = 2–3) for the top 10,000most variable distal (>3 kb from TSS) regions in myeloid cell populations during NASH, or recruited liver
macrophages (RLM) from Sakai et al. (2019).
(E) De novo motifs enriched in distal open chromatin regions (>3 kb from TSS) enriched in KN-RM (top), Ly6Clo-RM (bottom), or enriched in both populations
(middle) compared to Ly6Chi blood monocytes during NASH. The background for motif enrichment analysis is the distal open chromatin from Ly6Chi blood
monocytes.
(F) Expression (mean TPM ± SD) of KC LDTFs in the indicated cell types.
Please see also Figure S5.
llArticle
Immunity 52, 1057–1074, June 16, 2020 1065
F
A
C
D
0 2 4 6 8 10 12 14
0
2
4
6
8
10
12
14
KC-H
KC
-N
402
90
Differential Kupffer ATAC-seq
MotifP- value
%targ/%bkgd
Bestmatch
1e-87 69/22 AP1/ATF1e-15 19/7 EGR2
1e-24 60/13 PU.1/SpiC
Up 10%
Down8%
All enhancers
Up 3.5%Down 24%
KC signature
B
1e-137 35/19 AP1/ATF
1e-20 11/7.3 RUNX1e-25 0.7/.04 NFAT
1e-19 16/11 EGR
Differential Kupffer H3K27ac ChIP-seq
MotifP- value
%targ/%bkgd
Bestmatch
1e-19 0.3/0.0
1e-33 49/39 NR half-site1e-25 0.4/0.0 MITF
MAF1e-17 0.3/0.0 IRF
CGATGTCA
C TAG
AC TGACTGACGTAG TCCG TACG TAAC TGCGATC TAGACTGCGATAGTCCG TAG TACCGTAAC TGATCGCG TAAGTC
AGCT
G TAC
ACGTATCGACGTATGCCG TAAC TGATGCG TACACGTC TGAACGTAG TCACGTATGCAC TGCG TACG TACG TAACTGGACTG TCACG TACG TACG TAATCGATGCCG TAAG TC
ACG AC CGT ACG G T CG TCTAGTCGATTGATAGCTACAAGCT
A
ACGTACGTACGTAGTCCGATG TCAG TCAC TGAAGCTAGCTAGCTACGTG TACAGTCACGTAC TGACGTAC TGAC TGAGCTCGATCGATTGAC
CTAG
ATGC
AGTCGATCCTGA
AGTCAGTC
0 2 4 6 8 10 12 14
0
2
4
6
8
10
12
1443352 total 10452 KC sig4201365 KC sig
35832553 KC sig
CTAG
CATG
CATG
AGCTGACTCGTAGATCAGCTGTCAATGCTCGACTAGCATGACGTAGTCCTGA 1e-15 3.5/1.6 LXRE
(known)
E H3K27ac ChIP-seq(log2(norm. tags +1))
−6 −4 −2 0 2 4 6
−5
0
5
10
log2(KC-N/KC-H) H3K27ac ChIP-seq
log2
(KC
-N/K
C-H
) R
NA
-seq
R = 0.70
RNA- vs H3K27ac ChIP-seq
***
SpicIrf1
TfecMafIrf5
Nr1h3Irf7Mitf
Nr1h2Mafb
Runx1Irf8Jun
Srebf1FosAtf3
Egr2
0 2 4log2(NASH/Ctrl)RNA-seq (TPM)
***
************
**
*******
TCGA
ACGTACTGG TCAATCGACGTG TACCG TA
TCGA
ATGC
ACGTACGTAGTCAGTCCGATAGTCGCATGCATGATCCTAG
ATGC
G TAC
AGTC
GTCAGTACCTAGTGACACGT
0
50
100
RN
A-s
eq (
TP
M)
Atf3Egr1Egr2Spic
0
400
800
0 1 4 10 20 30
Weeks on AMLN diet
RN
A-s
eq (
TP
M) C6
Cd163Cd9Trem2
G
Effect of NASH on H3K27ac
5 kb
10 kb 5 kb
20 kbCd9
Trem2Cd163
C6ATAC
H3K27ac
ATAC
H3K27ac
ATAC
H3K27ac H3K27ac
ATAC
KC-HKC-N
ATAC-seq (log2(norm. tags +1))
***
KC
-N
KC-H
Figure 5. The NASH Diet Alters the Activity States of Resident KC Enhancers(A) Left: Normalized ATAC-seq signal at all distal open chromatin regions (>3 kb from TSS) in Tim4+ KCs from healthy mice (KC-H) or Tim4+ KCs from mice on
NASH diet (KC-N). Regions with significantly more chromatin accessibility during NASH are colored in red, while regions with less accessibility during NASH are
colored blue. Right: De novo motif enrichment from differentially accessible chromatin region shown at right.
(B) Left: H3K27ac ChIP-seq signal around distal (>3 kb from TSS) ATAC-seq peaks in a 2,000 bp window. Differentially acetylated regions were determined using
DESeq2 (FC > 2, p-adj < 0.05). Regions overlapping with KC signature enhancers (Figure S6A) are colored green. Enhancers with more acetylation during NASH
are colored red, or orange if also a KC signature enhancer. Enhancers with less acetylation during NASH are colored blue, or purple if also a KC signature
enhancer. Right: Representative motif enrichment from differentially acetylated chromatin regions.
(legend continued on next page
llArticle
1066 Immunity 52, 1057–1074, June 16, 2020
)
llArticle
and is highly correlated with regulatory element activity
(Creyghton et al., 2010). Out of 43,352 total distal open chro-
matin regions defined by ATAC-seq, 4,201 putative enhancers
gained H3K27ac and 3,583 putative enhancers lost H3K27ac
in response to the NASH diet (Figure 5B), affecting 18% of the
enhancer-like regions overall (Figure 5C).
A comparison of H3K27ac associated with ATAC-seq peaks in
KC-H cells versus in other macrophage populations enabled
definition of a set of 10,452 putative KC-H signature enhancers
(Figure S6A; Sakai et al., 2019). A profound overlap was
observed between KC signature enhancers and enhancers
downregulated by the NASH diet, in total identifying 2,553 KC
signature downregulated enhancers (24% of KC signature en-
hancers, 71% of all downregulated enhancers, Fisher’s exact
test p value < 0.001) (Figures 5B and 5C). Conversely, only 365
KC signature enhancers were upregulated by NASH diet (3.5%
of KC signature enhancers, 8.7% of all upregulated enhancers,
Fisher’s exact test p value = 1) (Figures 5B and 5C). Changes
in H3K27ac were highly correlated with changes in expression
of the nearest gene (Figure 5D). These findings suggest a prefer-
ential suppressive effect of the NASH diet on gene regulatory
networks governing the function of KC enhancers, in line with
the corresponding downregulation of KC identity genes
(Figure S4B).
ATAC-seq and H3K27ac ChIP-seq tracks associated with the
downregulated KC identity genes C6 and Cd163 illustrated sub-
stantial loss of H3K27ac at their respective promoters and distal
regions of open chromatin (Figure 5F). The opposite pattern was
observed at the upregulated lipid-associatedmacrophage (LAM)
and SAM-defining genes Trem2 and Cd9 (Jaitin et al., 2019;
Ramachandran et al., 2019). In addition, Trem2 and Cd9 both
provided examples of genes in which new regions of open chro-
matin are established that are associated with H3K27ac (Fig-
ure 5F), representing putative NASH-dependent enhancers.
Both pre-existing and NASH-induced regions associated with
Trem2were shifted but conserved at the TREM2 locus in human
microglia (Figure S6C). Additional examples of NASH-induced
genes in KCs and associated gene ontologies are shown in
Figure S6B.
Motif enrichment analysis of regions of open chromatin
exhibiting loss of H3K27ac in response to the NASH diet
showed enrichment for binding sites recognized by LXR,
MAF, and IRF TFs (Figure 5B right). Each of these motifs are
recognized by TFs that are established or proposed to drive
KC identity (Lavin et al., 2014; Mass et al., 2016; Sakai
et al., 2019; Scott et al., 2018). In contrast, open chromatin
regions with gained H3K27ac were enriched for de novo
(C) Summaries of percent representation of (left) differentially activated enhancer
intersected with the KC signature enhancers.
(D) Ratio-ratio plot depicting fold change in H3K27acChIP-seq signal at enhancers
fold change inmRNA expression of closest gene annotated to enhancer region in T
in blue are significantly different (FC > 2, p-adj < 0.05) for both H3K27ac ChIP-se
relationship between the highlighted differential data points.
(E) Log2FC of candidate TFs known to bind DNA elements found enriched in (B) fo
0.01, and ***p-adj < 0.001 using DESeq2.
(F) UCSC genome browser tracks of ATAC-seq or H3K27ac ChIP-seq signals in
(G) Mean TPM (LOESS fit) of the indicated genes in Tim4+ KCs from mice fed the
week: n = 3; 20 week: n = 3; 30 week: n = 4).
Please see also Figure S6.
motifs matching AP1, NFAT, RUNX, and EGR TFs (Fig-
ure 5B right).
Comparison of KC-H to KC-N cells indicated significant induc-
tion of Atf3, Fos, Jun, Egr2, and Runx1 mRNAs (Figures 5E and
5G), suggesting that increased expression of these TFs during
NASH may contribute to activation of enhancers with corre-
sponding DNA binding elements (Figure 5B). Conversely,
mRNAs encoding a subset of KC LDTFs were downregulated
in response to the NASH diet, including Spic, Irf1, and Tfec.
Notably, SpiC (encoded by Spic) binds to a motif nearly identical
to that recognized by PU.1 that is enriched at genomic regions
exhibiting loss of open chromatin in NASH. In contrast, while
LXR motifs were highly enriched at genomic regions exhibiting
loss of open chromatin, expression of Nr1h3, encoding LXRa,
was not affected by the NASH diet, and expression ofNr1h2, en-
coding LXRb, was slightly increased (Figure 5E).
To relate changes in TF expression to global changes in gene
expression, we performed RNA-seq analysis of KCs following
1, 4, 10, 20, and 30 weeks of the NASH diet. Coordinated
changes in gene expression began to occur between 4 and
10 weeks of the NASH diet, with upregulation of Atf3 and
Egr2 associated with increases in Trem2 and Cd9 expression
and downregulation of Spic associated with decreases in
Cd163 and C6 expression (Figure 5G). These findings indicate
that acquisition of features corresponding to the LAM or SAM
phenotype characterized by high expression of Trem2 and
Cd9 requires prolonged exposure to the NASH diet, which ulti-
mately results in substantial reprogramming of the KC regula-
tory landscape.
NASH Diet Selectively Impairs LXR Regulation of KCIdentity GenesThe observation that LXR binding motifs were highly enriched in
genomic regions exhibiting diet-induced loss of H3K27ac led to
a focused analysis of LXR function. Comparison of effects of
LXR deletion with effects of the NASH diet on KC gene expres-
sion indicated that a subset of LXR target genes associated
with its role as a KC LDTF were strongly downregulated by
the NASH diet. For example, Cd5l, Timd4, Cd209l, Pcolce2,
and Plac8 require LXRa for expression (Sakai et al., 2019),
and all but Cd5l exhibited significantly reduced expression in
response to the NASH diet (Figure 6A). However, many canon-
ical LXR target genes such as Abca1, Abcg1, Mylip, and Srebf1
were significantly upregulated in response to the NASH diet
(Figure 6B; Table S3), arguing against a general loss of LXR
function. Targeted lipidomic analysis of known LXR ligands
(Peet et al., 1998) in liver indicated that the concentration of
s between control and NASH KCs, or (right) differentially acetylated enhancers
(2,000 bpwindow centered on ATAC-seq peaks >3 kb from TSS) compared to
im4+ KCs in NASH dietmice (KC-N) versus healthymice (KC-H). Points colored
q signal at enhancers and closest mRNA. Pearson correlation of 0.70 denotes
r KCs from healthy mice (KC-H) and NASHmice (KC-N). *p-adj < 0.05, **p-adj <
the vicinities of the indicated genes.
AMLN NASH diet as indicated (0 week: n = 3; 1 week: n = 2; 4 week: n = 2; 10
Immunity 52, 1057–1074, June 16, 2020 1067
D
A B C
E
F
G
Figure 6. Genome-wide Occupancy of LXR Binding in KCs during NASH
(A) RNA-seq expression (mean TPM ± SD) of LXR-dependent KC signature genes. *p-adj < 0.05, **p-adj < 0.01, and ***p-adj < 0.001 using DESeq2.
(B) RNA-seq expression (mean TPM ± SD) of canonical LXR target genes.
(C) Quantification of desmosterol, 24-, 25-, and 27-OHC and 24,25-EC in livers from control or NASH mice. *** = p < 0.001.
(D) Mean LXR ChIP-seq signal at merged irreproducibility discovery rate (IDR) peaks from KC nuclei. Nuclei were sorted from Clec4f-Cre-NLS-TdTomato mice fed
either a control diet (n = 2) or the NASH diet for 20 weeks (n = 2). Peaks with significantly altered LXR binding were determined using DESeq2 (FC > 2, p-adj < 0.05).
(E) ATAC-seq, H3K27ac ChIP-seq, and LXR ChIP-seq signals in the vicinities of the indicated genes.
(F) Normalized distribution of LXR ChIP-seq density or H3K27ac ChIP-seq density at enhancers with either significantly altered LXR binding during NASH or all
LXR bound enhancers.
(G) Left: De novo motif enrichment for NASH-gained LXR peaks (right) or NASH-lost LXR peaks (right) shown in Figure 7D.
Please see also Figure S7.
llArticle
1068 Immunity 52, 1057–1074, June 16, 2020
A B
LXR gained LXR lost LXR total
G H
NASHControl
25,507
13,291
2,808
ATF3 ChIP-seqIDR peaks
01234567
Log2
(Tag
s+1)
1,000 bp
I
AP1/ATF3NR/LXREgr2PU1
0.000
0.002
0.004
0.006
0.008
−200−100 0 100 200
Mot
ifs p
er b
p pe
r pe
ak
0.000
0.001
0.002
0.003
0.004
−200−100 0 100 200
Distance from peak (bp)
0.000
0.001
0.002
0.003
−200−100 0 100 200
E
Control
NASH
ChIP-seq tag densities centered on genomic regions co-bound by LXRs and ATF3
ChI
P fr
agm
ent d
epth
per
bp p
er p
eak
ATF3 LXR P300 H3K27ac
−2000
−1000 0
1000
2000
−2000
−1000 0
1000
2000
−2000
−1000 0
1000
2000
−2000
−1000 0
1000
2000
2
4
6
8
3
6
9
12
2.5
5.0
7.5
10.0
0
5
10
15
20
Distance from enhancer (bp)
DC
P-value
Best match
1e-671 49.26/23.38 AP1/ATF3
1e-111 11.06/5.27 Egr2/Egr1
1e-69 42.57/33.94 MITF/USF1
NASH specific ATF3 vs all ATF3 peaks
Motif%targ/
%bkgd
NASH TF ocupancy atNASH gained enhancers
None 32%ATF3 10%LXR 3%
Both 54%
F
5 kb 10 kb
LXR
AT
F3
P30
0
Trem2 Cd9
Control NASH
Arhgap22
20 kb 10 kb
Kcnn4
0.0
2.5
5.0
7.5
10.0
0.0 2.5 5.0 7.5 10.0
Control − KC-H
NA
SH
− K
C-N
Mean expression(log2(TPM+1))
Gpnmb Mmp12Trem2
Cd9
ItgaxArhgap22
0.0
2.5
5.0
7.5
10.0
12.5
0.0 2.5 5.0 7.5 10.0 12.5
Clec4f-Cre- − KN-RM
Cle
c4f-
Cre
+ − K
N-R
M
Mean expression(log2(TPM+1))
43 significant
146
sign
ifica
nt
(LX
Rα/
β K
C-D
KO
)
(LXRα/β WT)
0
100
200
300
020406080
020406080
05
10152025
050
100150
0
10
20
30
Kcnn4 Tgfb3 Trem2
Arhgap22 Cd9 Itgax
Mea
n E
xpre
ssio
n (T
PM
)
Clec4f
-Cre-
Clec4f
-Cre+
Clec4f
-Cre-
Clec4f
-Cre+
Clec4f
-Cre-
Clec4f
-Cre+
**** ***
** n.s.***
Figure 7. Combinatorial Actions of LXR and ATF3 Coordinate NASH Responsive Gene Expression in KCs during NASH
(A) Motif frequency within 500 bp of LXR binding sites described in Figure 6F.
(B) Normalized ATF3 ChIP-seq signal at merged IDR peaks from KC nuclei. Nuclei were sorted from Clec4f-Cre-NLS-TdTomato mice fed either a control diet or
the NASH diet for 20 weeks (n = 2). Significant ATF3 peaks had Poisson enrichment p value < 0.0001 and FC > 4.
(legend continued on next page)
llArticle
Immunity 52, 1057–1074, June 16, 2020 1069
llArticle
desmosterol, which is by far the most abundant endogenous
LXR ligand in the liver (Sakai et al., 2019; Yang et al., 2006),
was significantly increased in the setting of the cholesterol-
rich NASH diet in comparison to the control diet (Figure 6C).
All other natural LXR agonists were present at much lower con-
centrations (data not shown). The increase in desmosterol is
consistent with the upregulation of general LXR target genes
involved in cholesterol homeostasis. A corresponding increase
in desmosterol was reported in livers of human subjects with
NASH and cirrhosis (Gorden et al., 2015).
To investigate whether changes in gene expression are asso-
ciated with corresponding changes in LXR binding, we per-
formed ChIP-seq for LXRa + LXRb in the combination of KC-
N and KN-RM cells marked by sorting nuclei prepared from
rapidly fixed control or NASH livers for nuclear Clec4f-tdTo-
mato expression (Figure S7A). These studies yielded high qual-
ity datasets that could not be obtained using conventionally
sorted cells and indicated that the NASH diet induced LXR
binding by more than 2-fold at more than 1,700 locations and
resulted in a loss of binding at more than 1,000 locations (Fig-
ure 6D). Notably, DNA binding was relatively unchanged at
most of the LXR binding sites associated with canonical LXR
activity (e.g., Abca1), which are highly LXR-dependent but not
affected at the mRNA level by the NASH diet (Figure 6E). In
contrast, LXR binding in the vicinity of Timd4, Pcolce2, and
Plac8 was markedly reduced. Overall, LXR ChIP-seq peaks
were preferentially depleted from KC signature enhancers
(405/1046, or ~39% of total downregulated LXR peaks in en-
hancers, blue points, Fisher’s exact test p value < 0.001)
compared to LXR signal gained at KC signature enhancers
(128/1795, or ~7% of total upregulated LXR peaks in en-
hancers, red points, Fisher’s exact test p value = 1) (Figures
6D and S7B). Sites at which LXR binding was gained were
associated with increased H3K27ac, whereas the opposite
pattern was observed at sites at which LXR binding was lost,
consistent with a positive regulatory function of LXR at these lo-
cations (Figure 6F).
NASH-Induced Collaborative Binding PartnersRepurpose LXRsMotif analysis of genomic regions exhibiting gain or loss of LXR
binding in response to the NASH diet indicated enrichment for
AP-1 or ATF, EGR, and MITF motifs at gained sites, and PU.1
or SPIC, GLIS3, and nuclear receptor half site motifs at lost sites
(Figure 6G). The distance relationships of thesemotifs to the cen-
ter of the LXR peak were consistent with collaborative binding in-
teractions observed for other LDTFs (Figure 7A; Heinz et al.,
2015). These findings suggested the possibility that NASH-
(C) De novo motif enrichment for NASH-specific ATF3 peaks as in (B).
(D) Intersection of ATF3 and/or LXR IDR ChIP-seq peaks from KC nuclei isolated
(from Figure 5B).
(E) Normalized distribution of ChIP-seq tag density at sites co-bound by LXRs an
(F) UCSC genome browser tracks of LXR, ATF3, and P300 ChIP-seq signals in the
both LXR and ATF3 are shaded yellow, and peaks with only gained ATF3 are sh
(G) Mean expression (TPM) for genes nearest to NASH-specific LXR peaks co-b
(H) RNA-seq (n = 2 per group) of KN-RM from control mice or Clec4fCre-LXRafl/
(I) As in (H) for selected genes. **p-adj < 0.01; ***p-adj < 0.001.
Please see also Figure S7.
1070 Immunity 52, 1057–1074, June 16, 2020
induced changes in the binding and function of LXRs were the
consequence of altered collaborative binding interactions with
AP-1 factors, EGRs, and members of the ETS TF family PU.1
and/or SpiC. To examine this possibility, we focused on ATF3,
as it was the most highly induced AP-1 factor in response to
the NASH diet (Figure 5E) and recognized the AP-1 motif en-
riched in NASH-specific enhancers (Figure 5B). Similar to
expression amounts of Atf3, we detected ~2.5 times as many
peaks in nuclei from mice with NASH (data not shown). This
observation correlated with an overall increased magnitude of
ATF3 ChIP-seq signal during NASH (Figures 7B and S7D). En-
hancers with gained ATF3 binding during NASH were enriched
for de novo motifs corresponding to AP-1, EGR, and MITF2
TFs (Figures 7C and S7C).
Intersection of the LXR and ATF3 ChIP-seq datasets indicated
~28,000 instances of overlapping peaks (Figure S7E). Of the
1,793 LXR binding sites increased by >2-fold in NASH, ~80%
overlapped with ATF3 peaks, consistent with a collaborative
binding relationship. Notably, the combination of LXR and
ATF3 was observed at 54% of NASH-induced enhancers (Fig-
ure 7D). Themajority of these sites were occupied by LXRs under
control conditions, but exhibited substantial increases in
H3K27ac in the context of NASH (Figure 7E). This result sug-
gested that diet-induced binding of ATF3 to these sites resulted
in the subsequent recruitment of HATs. We therefore performed
ChIP-seq for the HAT P300 and found its recruitment to the LXR
and ATF3 peaks in response to the NASH diet, indicating a likely
role in contribution to acetylation of H3K27 and subsequent
enhancer function (Figures 7E and S7F–S7H). Representative
examples of NASH-induced co-binding of LXRs and ATF3 or
for NASH-induced binding of ATF3 at pre-existing LXR binding
sites are illustrated for Trem2, Cd9, Arhgap22, and Kcnn4 in
Figure 7F.
Analysis of the genes nearest to enhancers bound by ATF3
and LXR in the context of the NASH diet revealed a shift in
expression distribution toward a higher mean during NASH (Fig-
ure 7G). To directly evaluate NASH-specific functions of LXRs re-
sulting from these induced binding sites, we crossed
LXRafl/flLXRbfl/fl mice to the Clec4f-cre-TdTomato mouse to
generate KC-N and KN-RM-specific LXRa�/�LXRb�/� mice.The progeny were then fed either a control diet or the NASH
diet for 20 weeks. Due to the near complete absence of KC-N
cells in theClec4f-cre-TdTomato LXRafl/flLXRbfl/fl mice, compar-
isons were made of control and Clec4f-cre-TdTomato
LXRafl/flLXRbfl/fl KN-RMs. By comparing LXR-dependent gene
expression in KN-RMs under these two conditions, we identified
a set of 146 NASH-specific LXR-dependent genes (Figures 7H
and 7I), 33 of which were part of the set defined in Figure 7G.
from NASH-diet-fed mice with enhancers with increased activity during NASH
d ATF3 indicated in (D).
vicinities of the indicated genes. Peakswith NASH-gained (HOMER) binding for
aded green.
ound by ATF3. DE genes identified using p-adj < 0.05 and FC > 2.flLXRbfl/fl mice fed the NASH diet for 20 weeks. DE genes identified as in (G).
llArticle
Notably, LXR dependency was observed both at genes
exhibiting NASH-induced binding of LXR (e.g., the SAM-associ-
ated gene Cd9) and genes exhibiting recruitment of ATF3 to pre-
existing LXR binding sites (e.g., Arhgap22 and Kcnn4). Trem2
expression was reduced in LXRa�/�LXRb�/� KN-RMs, but didnot retain statistical significance after correction for multiple
testing. Collectively, these findings provide evidence that
NASH-induced changes in collaborative TFs result in altered
binding and function of LXRs, contributing to the NASH-specific
program of KC gene expression.
DISCUSSION
Here, investigation of genomic and anatomic relationships
among phenotypically distinct macrophage populations in a
mouse model of NASH revealed a strong association of niche
occupancy with the transcriptional and phenotypic states of
different EMP- and HSC-derived myeloid cells. HSC-derived
macrophages observed in this model of NASH reside in at least
two distinct niches associated with divergent pathways of dif-
ferentiation. One pathway corresponds to the development of
Ly6Chi&lo-RMs, which reside proximal to large portal and cen-
tral vein vessels in contact with conventional (but most likely in-
flamed) vascular endothelium. An alternative pathway results in
the accumulation of KN-RM cells, which colocalized with KC-N
in contact with the LSECs and adopted a similar pattern of
gene expression. This process occurred concordantly with pro-
gressive loss of resident KC-Ns, most likely due to apoptosis.
These findings provide strong evidence for instructive roles of
the LSECs and the NASH diet in determining the molecular
phenotypes of both KN-RM and KC-N cells. Of particular inter-
est, we observed that a subset of KC-N and KN-RM cells ac-
quire similarities to the recently identified SAM that resides in
areas of fibrosis in human cirrhotic livers (Ramachandran
et al., 2019).
The transitions of open chromatin, H3K27ac and genome-
wide locations of LXRs and ATF3 provide evidence for
NASH-induced alterations in expression and activities of
ATF3, resulting in reprogramming KC-specific functions of
LXRs. In the context of relatively constant LXR expression,
increased ATF3 and likely other AP-1 TFs are suggested to
drive redistribution of LXR to NASH-specific enhancers as
well as activate poised enhancers bound by LXRs under control
conditions. The decreased expression of Spic in the context of
the NASH diet may also contribute to loss of collaborative LXR
binding at a subset of KC-specific enhancers. The delineation
of NASH-induced regulatory elements associated with the
Cd9 and Trem2 genes that are occupied by LXRs and ATF3
suggest roles of these TFs in establishing the SAM and/or
LAM phenotypes. A key remaining question is to determine
whether the altered functions of LXRs in KCs are pathogenic
or represent an adaptive response to the NASH diet.
Overall, these studies are consistent with a model in which
distinct microenvironments within the NASH liver drive diver-
gent patterns of differentiation of resident and infiltrating cells
by remodeling the open chromatin landscapes of recruited
monocytes and altering the activities of pre-existing enhancers
of the resident KC population. The inference of TFs and up-
stream signaling pathways associated with these distinct cell
populations provides a basis for understanding how disease-
promoting environmental signals instruct resident and recruited
macrophages to acquire distinct pathogenic programs of gene
expression. Application of the methods utilized in this study
should prove valuable in gaining a better understanding of
how distinct myeloid phenotypes are established in other dis-
ease contexts.
STAR+METHODS
Detailed methods are provided in the online version of this paper
and include the following:
d KEY RESOURCES TABLE
d RESOURCE AVAILABILITY
B Lead Contact
B Materials Availability
B Data and Code Availability
d EXPERIMENTAL MODEL AND SUBJECT DETAILS
B Mice
B NASH-Model Diets
B Diphtheria toxin (DT)-mediated depletion of
Kupffer cells
d METHOD DETAILS
B Microscopy and Histo-Cytometry
B Nuclei Sorting
B Cell Sorting and Flow Cytometry
B Single-Cell RNA-Seq
B ATAC-Seq
B Poly A RNA-Seq
B Chromatin Immunoprecipitation
B ChIP-Seq Library Preparation
B Lipid Measurements
d QUANTIFICATION AND STATISTICAL ANALYSIS
B Sequencing Data Analysis
SUPPLEMENTAL INFORMATION
Supplemental Information can be found online at https://doi.org/10.1016/j.
immuni.2020.04.001.
ACKNOWLEDGMENTS
These studies were supported by NIH grants DK091183, HL088083,
DK063491, and GM085764 and Fondation Leducq grant 16CVD01. J.S.S.
was supported by American Heart Association Fellowship 16PRE30980030
and NIH Predoctoral Training grant 5T32DK007541. T.D.T. was supported
by P30 DK063491, T32DK007044, and NRSA T32CA009523. M.S. was sup-
ported by the Manpei Suzuki Diabetes Foundation of Tokyo, Japan and the
Osamu Hayaishi Memorial Scholarship for Study Abroad, Japan. X.S. was
supported by the American Heart Association grant 18POST34060088.
This work was also supported in part by the Intramural Research program
of NIAID, NIH.
AUTHOR CONTRIBUTIONS
Conceptualization, J.S.S., T.D.T., M.S., A.G., R.N.G, and C.K.G.; Methodol-
ogy, J.S.S., T.D.T., M.S., A.G. and N.J.S.; Formal Analysis, J.S.S, T.D.T.,
A.G., Z.O., R.Z.L., and M.H.; Investigation, J.S.S., T.D.T., M.S., A.G.,
C.M.B., N.J.S., H.B., B.T.V., M.P.P., K.M.E., D.G., and L.-W.C.; Data Curation,
J.S.S., T.D.T, and Z.O; Writing – Original Draft, J.S.S., T.D.T, A.G., R.N.G, and
C.K.G.; Writing – Review & Editing, J.S.S, T.D.T., M.S., A.G., V.M.L., R.N.G.,
Immunity 52, 1057–1074, June 16, 2020 1071
https://doi.org/10.1016/j.immuni.2020.04.001https://doi.org/10.1016/j.immuni.2020.04.001
llArticle
and C.K.G.; Funding Acquisition, J.S.S., T.D.T., R.N.G, and C.K.G.; Visualiza-
tion, J.S.S., T.D.T., A.G., and Z.O.
DECLARATION OF INTERESTS
J.L.W. and X.S. are named inventors on patent applications or patents
related to the use of oxidation-specific antibodies that are held by UCSD.
J.L.W. is a consultant to Ionis Pharm and is a scientific founder of Oxi-
tope, Inc.
Received: February 3, 2020
Revised: April 1, 2020
Accepted: April 8, 2020
Published: May 1, 2020
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