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Scientific Articles #3

Critiques should be written in an appropriate scientific style such as APA format (1.5-spaced and 11-point Times New Roman or Arial font), and each should correctly cite at least three primary scientific references. Citations may be formatted in the style of any major scientific journal, and should indicate to the reader the source of data and observations and conclusions that are cited in the critique. The text of these critiques will be no longer than three pages excluding references. The idea of a critique is to go through the paper, figure by figure, and describe what was done, how it was done, suggest alternate explanations for the results as appropriate, and come up with ideas for additional tests that could have helped to confirm or refute the authors’ conclusions.

There are a total of five articles, but you only must choose one article to critique. Due date 05/07/2022.

Scientific Articles #3

ARTICLE

HPV infection alters vaginal microbiome through
down-regulating host mucosal innate peptides used
by Lactobacilli as amino acid sources
Alizee Lebeau1,14, Diane Bruyere1,14, Patrick Roncarati1, Paul Peixoto 2,3, Eric Hervouet 2,3, Gael Cobraiville4,

Bernard Taminiau 5, Murielle Masson 6, Carmen Gallego7, Gabriel Mazzucchelli8, Nicolas Smargiasso8,

Maximilien Fleron8,9, Dominique Baiwir 8,9, Elodie Hendrick1, Charlotte Pilard1, Thomas Lerho1,

Celia Reynders1, Marie Ancion1, Roland Greimers10, Jean-Claude Twizere 11, Georges Daube 5,

Geraldine Schlecht-Louf 7, Françoise Bachelerie7, Jean-Damien Combes12, Pierrette Melin 13,

Marianne Fillet4, Philippe Delvenne1,10, Pascale Hubert1 & Michael Herfs 1✉

Despite the high prevalence of both cervico-vaginal human papillomavirus (HPV) infection

and bacterial vaginosis (BV) worldwide, their causal relationship remains unclear. While BV

has been presumed to be a risk factor for HPV acquisition and related carcinogenesis for a

long time, here, supported by both a large retrospective follow-up study (n = 6,085) and
extensive in vivo data using the K14-HPV16 transgenic mouse model, we report a novel

blueprint in which the opposite association also exists. Mechanistically, by interacting with

several core members (NEMO, CK1 and β-TrCP) of both NF-κB and Wnt/β-catenin signaling
pathways, we show that HPV E7 oncoprotein greatly inhibits host defense peptide expres-

sion. Physiologically secreted by the squamous mucosa lining the lower female genital tract,

we demonstrate that some of these latter are fundamental factors governing host-microbial

interactions. More specifically, several innate molecules down-regulated in case of HPV

infection are hydrolyzed, internalized and used by the predominant Lactobacillus species as

amino acid source sustaining their growth/survival. Collectively, this study reveals a new viral

immune evasion strategy which, by its persistent/negative impact on lactic acid bacteria,

ultimately causes the dysbiosis of vaginal microbiota.

https://doi.org/10.1038/s41467-022-28724-8 OPEN

1 Laboratory of Experimental Pathology, GIGA-Cancer, University of Liege, Liege, Belgium. 2 INSERM, EFS BFC, UMR 1098, Interactions Hôte-Greffon-
Tumeur/Ingénierie Cellulaire et Génique, University of Bourgogne Franche-Comté, Besançon, France. 3 EPIGENEXP platform, University of Bourgogne
Franche-Comté, Besançon, France. 4 Laboratory for the Analysis of Medicines, Center for Interdisciplinary Research on Medicines (CIRM), University of Liege,
Liege, Belgium. 5 Department of Food Sciences-Microbiology, Fundamental and Applied Research for Animals and Health (FARAH), Faculty of Veterinary
Medicine, University of Liege, Liege, Belgium. 6 Ecole Supérieure de Biotechnologie Strasbourg, UMR 7242, CNRS, University of Strasbourg, Illkirch, France.
7 INSERM UMR 996, Inflammation Microbiome and Immunosurveillance, University of Paris-Saclay, Clamart, France. 8 Laboratory of Mass Spectrometry,
Department of Chemistry, University of Liege, Liege, Belgium. 9 GIGA Proteomic Facility, University of Liege, Liege, Belgium. 10 Department of Pathology,
University Hospital Center of Liege, Liege, Belgium. 11 Laboratory of Signaling and Protein Interactions, GIGA-Molecular Biology of Diseases, University of
Liege, Liege, Belgium. 12 Infections and Cancer Epidemiology Group, International Agency for Research on Cancer, World Health Organization, Lyon, France.
13 Department of Clinical Microbiology, University Hospital Center of Liege, Liege, Belgium. 14These authors contributed equally: Alizee Lebeau, Diane Bruyere.
✉email: M.Herfs@uliege.be

NATURE COMMUNICATIONS | (2022) 13:1076 | https://doi.org/10.1038/s41467-022-28724-8 | www.nature.com/naturecommunications 1

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A
ffecting at any point of time more than 300 million
individuals worldwide, human papillomavirus (HPV) is
the most common sexually transmitted infection1. To

date, over 225 genotypes have been fully characterized and about
one fifth, belonging to the alpha genus, can be detected in the
anogenital mucosa. Although most infections are cleared or
maintained in an asymptomatic or latent state by the immune
system, carcinogenic (high-risk) HPV strains (most notably
HPV16 and 18) cause virtually all squamous intraepithelial
lesions [low-grade (LSIL) and high-grade (HSIL)] and cell car-
cinoma (SCC) arising from the uterine cervix as well as a large
fraction (~50%) of vaginal/vulvar (pre)cancers. In total, HPV
infections account for ~5% of the worldwide cancer burden with
an estimated 550,000 new cases diagnosed annually in the lower
genital tract2,3. The persistence of an active infection for years or
decades indicates that these viruses have evolved a number of
mechanisms to escape both innate and adaptive immune
responses. Indeed, by directly interacting with some core proteins
or by indirectly altering their activity (post-translational mod-
ifications) or their gene expression pattern (promoter hyper-
methylation and histone modifications), viral E6 and E7
oncoproteins have been especially shown to antagonize the cGAS-
STING DNA sensing pathway4, to suppress the interferon
secretion and signaling5–7, to impair Toll-like receptor 9 and
major histocompatibility complex class I transcription8,9 and to
reduce chemotactic and proinflammatory gene expression10.

In contrast to the skin and the gut which are colonized by a
complex microbiome, the human vaginal ecosystem is associated
with a low microbial diversity largely dominated (>90%) by a few
Lactobacillus species (mainly L. crispatus, L. jensenii and L.
iners)11–13. Characterized by the replacement of the normally
dominant lactic acid bacteria by a more diverse bacterial mixture
predominated by Gardnerella vaginalis and other anaerobic
bacteria (e.g., Atopobium vaginae, Prevotella_ge, Mobiluncus_ge,
Sneathia_ge,…)14, bacterial vaginosis (BV) is a common vaginal
disorder among women of reproductive age. Although at least
50% of women with BV are asymptomatic, this microbial
imbalance (also called dysbiosis) can manifest clinically by a
vaginal discharge, the presence of clue cells (recognized by
cytologic review) and a “fishy” odor related to the production of
volatile amines by anaerobes15. Three decades of epidemiologic
studies reported the multiplicity of sexual partners, African des-
cent, vaginal douching and cigarette smoking as risk factors for
the acquisition of BV15. However, none of these latter on their
own can reliably explain the prevalence of this condition and the
etiopathogenesis of BV remains unclear15,16. Most likely, this
imbalance in the vaginal flora is multifactorial and involves
complex interactions between extrinsic factors, the different
species of bacteria constituting the endogenous vaginal micro-
biome and the host mucosa.

In addition to causing symptoms for some women, BV has
been shown to increase the risk of preterm delivery17 as well as
gynecologic complications such as endometritis, cervicitis and
postoperative pelvic infections18. Moreover, both the rise in the
vaginal pH and the reduced level of hydrogen peroxide (H2O2)
resulting from the low abundance of Lactobacilli is presumed to
promote the acquisition of both bacterial (e.g., Chlamydia tra-
chomatis and Neisseria gonorrhoeae) and viral (e.g., herpes sim-
plex virus type 2, HIV and HPV) sexually transmitted
pathogens19–22. The degradation of the protective mucus barrier
through the sialidase activity of anaerobic micro-organisms could
also contribute to this latter susceptibility for developing infec-
tions in the lower genital tract23. Regarding HPV infections,
besides favoring their acquisition, it is generally considered that
the oxidative stress resulting from microbial dysbiosis also pro-
motes the subsequent progression of HPV-positive (pre)

neoplastic lesions. In agreement, recent evidence has shown that
an anaerobic vaginal microbiome composition is associated with
a lower regression rate of HPV-related diseases24. Despite these
important findings, the interplay/association between BV and
HPV infection is still unclear. Indeed, while longitudinal studies
clearly reported increased rates of incident HPV among BV-
positive women (for a meta-analysis, see25), the risk of BV
occurrence following HPV infection has not been systematically
pursued/calculated. Overall, data related to the influence of HPV
on vaginal microbiome are limited and, as mentioned in several
review articles26,27, when BV and HPV coexist, we cannot exclude
that, in a significant proportion of women, the viral infection
preceded in time and, by altering the host mucosa secretome,
ultimately caused BV development.

The present multi-approach study shows a causal relationship
between HPV infection and BV. Mechanistically, the drastic
down-regulation of host defense peptides, related to the interac-
tions of HPV E7 oncoprotein with several key proteins (NEMO,
CK1, β-TrCP) involved in both NF-kB and Wnt/β-catenin sig-
naling pathways, has been shown to be instrumental in this
process. Indeed, we unexpectedly uncovered that the innate
molecules most secreted by the vaginal/cervical mucosa do not
display any antimicrobial activity on Lactobacillus species but
rather, are cleaved and used as amino acid source by these lactic
acid bacteria, sustaining their growth/survival. The accumulating
(retrospective clinical and in vitro) data have been finally con-
firmed in vivo using the K14-HPV16 transgenic mouse model in
which (pre)cancer development was associated with a vaginal
dysbiosis.

Results
A large retrospective follow-up analysis including over 6,000
patients identifies a two-way interaction between HPV infec-
tion and BV development. In the last decade, several systematic
reviews of the literature (and meta-analysis) clearly indicated that
HPV infection and BV are epidemiologically related25,26,28. How-
ever, some uncertainties still exist concerning the temporal sequence
between these two pathological conditions. Indeed, while BV has
been considered as a risk factor for HPV acquisition/persistence for
a long time, the inverse relationship remains unclear. To address this
important issue, a retrospective cohort study including women who
underwent at least 2 Pap smear screenings over an 8-year period was
performed. At each visit, complete data related to a potential
abnormal cytology result (Bethesda classification), the existence of
BV (Hay/Ison grading system) and high-risk HPV infection (Abbott
RealTime HPV assay) were available for all enrolled patients. At the
first visit, 3,481 out of 6,085 (57.2%) patients did not display any
evidence of HPV infection and/or BV. A mixed bacterial flora
(associated or not with the presence of clue cells) was reported in
about one third (2,053/6,085, 33.7%) of patients with normal
cytology (HPV negative). Single or multiple HPV infection was
detected in 262 (4.3%) patients with a morphologically normal
cervico-vaginal flora. At last, 289 (4.8%) patients were simulta-
neously positive for high-risk HPV and BV. The general char-
acteristics of the four defined groups and the geographic repartition
of patients are summarized in Fig. 1a and Supplementary Fig. 1,
respectively. Of note, patients’ age (distribution) was not significantly
different between the groups. No obvious difference in terms of
geographic distribution of patients was noticed either. Overall,
12,390 follow-up visits were completed by the selected women
(median follow-up time: 66.3 months) and, in order to precisely
determine the temporal relationship between BV and genital HPV
infection, the probability of acquiring one condition when the other
one was already present or not was estimated. During follow-up
visits, a positive HPV test (associated with cytological abnormalities)

ARTICLE NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-022-28724-8

2 NATURE COMMUNICATIONS | (2022) 13:1076 | https://doi.org/10.1038/s41467-022-28724-8 | www.nature.com/naturecommunications

and BV was observed in 117 (117/3,481, 3.4%) and 137 (137/3,481,
3.9%) control women (negative for HPV and BV at first visit),
respectively. Eight patients were positive for both HPV and BV at
the same follow-up visit. Importantly, the development of each
disorder was significantly more frequently diagnosed when the other
one was preceding in time [HPV: 123/2,053, 6% (OR: 1.83,
p < 0.0001); BV: 23/262, 8.8% (OR: 2.35, p < 0.001)] (Fig. 1b, c).
These latter results were not adjusted for age, race, or other potential
confounders [e.g., socioeconomic status of patients or number of sex
partners (due to the lack of available information)]. In parallel, the
median time for BV occurrence in HPV-infected and -uninfected
women was investigated and, interestingly, a significant difference
(34.53 months versus 59.44, p < 0.0001) was observed (Fig. 1d). To
further evaluate the interplay between HPV and BV, the persistence
of HPV infection according to the BV status (Fig. 1e) as well as the
inverse evaluation (Fig. 1f) were determined. Out of 791 HPV-
positive patients (diagnosed at first visit or during follow-up), 21
(2.7%) were excluded from the present longitudinal analysis because
they underwent examinations in a different hospital following HPV
diagnosis and, therefore, no data allowing to assess the persistence of
the viral infection were available in our records. For a similar reason,
0.8% (21/2,502) of BV-positive patients were not taken into con-
sideration either. As shown in Fig. 1e, the duration of HPV infec-
tions was significantly longer in BV-positive women compared to
their counterparts displaying a normal vaginal microbiome domi-
nated by Lactobacillus spp (persistent infections after 3 years: 43%
versus 32.4%, p < 0.0001). Remarkably, the opposite observation was
also made (Fig. 1f). Indeed, the 3-year BV persistence was 50.1% for
HPV-positive patients, as opposed to 41% for uninfected individuals
(p < 0.0001).

HPV oncoproteins impair innate (antimicrobial) peptide
expression in vaginal/cervical squamous mucosa. By the con-
stitutive or inducible production of soluble molecules (especially
innate peptides), the host mucosa actively participates to the
regulation of bacterial flora. These complex host-microbiota
interactions are still the subject of intense investigations and are
very likely specific for each organ as suggested by the important
disparities between each microbiome and mucosal surface (skin,
gut, oral, vaginal). According to the antimicrobial peptide data-
base (http://aps.unms.edu), the squamous epithelial cells (kerati-
nocytes) lining the lower part of the gynecologic tract secrete a
dozen of innate (antimicrobial) peptides29,30. By laser capture
microdissection, 44 independent frozen human tissue specimens
(11 normal squamous epithelia, 10 LSIL, 10 HSIL, and 13 SCC)
were sampled. In order to avoid bias related to HPV status, all
(pre)neoplastic lesions displayed diffuse (basal or full-thickness)
p16INK4a immunoreactivity in keeping with carcinogenic HPV
infection. To allow the comparison of the expression level of all
analyzed host defense peptides, the amplification efficiency of
each qPCR reaction was determined (Fig. 2a). As shown in
Fig. 2b, c, with the exception of HβD3, all antimicrobial peptides
were down-regulated in HPV-positive lesions compared to nor-
mal squamous vaginal/ectocervical epithelium. The inhibition of
“defensin-like” peptides (mainly S100A7 and elafin) was espe-
cially considered as essential given that, in normal/uninfected
conditions, these latter were up to 1000 fold (>10 Ct) more
expressed than the epithelial members of the defensin family.
Similar reduced expressions of both defensins and “defensin-like”
peptides in HPV-positive (pre)neoplastic lesions were also
observed at the protein level, as shown by immunohistochemical

Fig. 1 Retrospective clinical follow-up analysis evaluating the relationship between genital HPV infection and BV occurrence/persistence. a General
characteristics of the study population (n = 6,085). b Probability of high-risk HPV infection or BV development during the follow-up period according to the
status for the other gynecological disorder at first (enrollment) visit. c Forest plot showing the odds ratio (OR) and 95% confidence intervals (CI) for
developing one pathological condition when the other one was preceding in time [HPV infection (OR: 1.83, 95% CI: 1.41–2.37); BV development (OR: 2.35,
95% CI: 1.48–3.72)]. d Number of months for BV occurrence in HPV-positive and -negative patients. e Kaplan-Meier estimates for the persistence of HPV
infection according to the BV status (negative versus positive). The clearance of HPV infections was ascertained by both cytology (Bethesda system) and
PCR-based HPV test (Abbott High-risk HPV assay). f Kaplan–Meier curve for the persistence of BV according to the HPV status. Two consecutive negative
results (using Hay/Ison grading system) at least 12 months apart were required to consider a patient really/durably cured of BV. P values were determined
using two-sided Fisher’s exact test b, c, two-sided unpaired t-tests (d) and log-rank (Mantel-Cox) test e, f. Source data are provided as a Source Data file.

NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-022-28724-8 ARTICLE

NATURE COMMUNICATIONS | (2022) 13:1076 | https://doi.org/10.1038/s41467-022-28724-8 | www.nature.com/naturecommunications 3

experiments (Fig. 2e, f). Regarding LL-37, this cathelicidin-related
antimicrobial peptide was undetectable both at the mRNA and
protein levels (Fig. 2c and Supplementary Fig. 2). It is interesting
to notice that the morphologically normal (p16INK4a-negative)
squamous epithelium adjacent to HPV-positive (pre)neoplastic
lesions also displayed a significantly reduced expression of several

innate peptides (S100A7, elafin, HβD2, HβD4 and HD-5) (Sup-
plementary Fig. 3). In order to determine whether or not HPV
(and its viral oncoproteins) is directly responsible for the down-
regulation of defensin(-like) peptides observed in (pre)neoplastic
lesions, human keratinocytes were stably transduced with HPV16
E6E7 oncogenes and the expression level of each defense peptide

ARTICLE NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-022-28724-8

4 NATURE COMMUNICATIONS | (2022) 13:1076 | https://doi.org/10.1038/s41467-022-28724-8 | www.nature.com/naturecommunications

potentially expressed by the squamous mucosa and being part of
the innate immune barrier of the female lower genital tract was
investigated (Fig. 2d). HβD2-4 expression was shown to be highly
stimulated by TNFα whereas LPS was more efficient to induce
HD-5/6 expression. Significantly, not only did the presence of
viral oncoproteins greatly impair (up to 7 Ct, 128 fold) the
expression of so called “constitutive” peptides (SLPI, S100A7,
elafin and HβD1), but also the induction of HβD2-4 as well as
HD-5/6 following the exposure to TNFα/LPS was significantly
altered. A drastic reduced secretion of “constitutive” peptides in
case of HPV16 E6E7 transduction was also reported in cell
supernatants (ELISA) (Supplementary Fig. 4). In parallel, we
utilized a second in vitro model mimicking more closely the early
steps of the natural infection with carcinogenic HPV (Fig. 2g).
Using organotypic raft cultures, keratinocytes maintaining epi-
somal HPV18 genome displayed weaker immunoreactivities for
SLPI, S100A7, elafin, HβD2 and HβD4 compared to uninfected
cells. The other analyzed peptides were down-regulated at a lower
extent.

HPV impairs TNFα/LPS-induced innate peptide expression
through E7-dependent NEMO degradation and subsequent
suppression of NF-κB activation. Proinflammatory factors such
as TNFα, IL-1β and LPS have been previously shown to induce
the expression of elafin as well as several members of the defensin
family31–33. Given these results and the identification of putative
NF-κB/p65 binding sites within the promoters of DEFB2-4,
DEFA5-6 and PI3 (elafin) genes [estimations made using the
Eukaryotic promoter database34], we first evaluated the require-
ment of NF-κB signaling pathway activation in TNFα/LPS-
induced innate peptide expression. As expected, knockdown of
p65 with siRNA or indirectly via blockade of the degradation of
IκBα (BAY 11-7082) resulted in a significant decrease of defensin/
elafin mRNA levels in normal/uninfected keratinocytes (Fig. 3a,
b). To evaluate the potential alteration of NF-κB in case of HPV
infection as well as the role of each individual viral oncoprotein,
the occupancy of NF-κB binding sites on both PI3/elafin and
DEFB2 promoters was analyzed by ChIP in keratinocytes stably
transduced with HPV16 E6 or E7. As shown in Fig. 3c, upon
TNFα stimulation, a weaker occupancy of both gene promoters
by p65 was reported in E7-positive cells. E6 viral oncoprotein did
not seem to disrupt NF-κB signaling pathway. In order to
determine the mechanism underlying E7-dependent alteration of
NF-κB activation, the presence of both TNFα (TNFR1-2) and LPS
(CD14 and TLR4) receptors at the cell membrane was first ana-
lyzed by flow cytometry. No significant difference was observed
between cells transduced or not with HPV E6/E7 viral oncogenes

(Fig. 3d). IκBα degradation and p65 nuclear translocation upon
TNFα stimulation were then assessed. Interestingly, the presence
of E7 oncoproteins strongly reduced IκBα degradation (Fig. 3e),
explaining the cytoplasmic sequestration of p65 (Fig. 3f, g).
Further confirming these data, the percentage of epithelial cells
displaying nuclear p65 immunoreactivity was significantly lower
in HPV-positive cancers compared to their viral-unrelated
counterparts (Fig. 3h). Based on these clear-cut results, the
direct interaction of HPV16 E7 oncoprotein with each protein
members of the IKK kinase complex was evaluated using Gaussia
princeps luciferase complementation assay (GPCA). Strikingly, a
strong interaction between HPV16 E7 and NEMO was high-
lighted and confirmed by co-IP in both directions (Fig. 3i–j and
Supplementary Fig. 5). Similar results were obtained with HPV
E7 from several other genotypes (high-risk alpha: HPV18, 33 and
39; beta: HPV8, 38 and 49) (Supplementary Fig. 6). In order to
further characterize this interaction between E7 and IKK reg-
ulatory subunit (NEMO), three truncated/mutated forms of
HPV16 E7 were also tested: the CR1 + CR2 region (consisting of
1–36 amino acids), the C-terminal domain (37–98 amino acids)
and the C24G/E26G construct mutated within the LxCxE motif.
As shown in Fig. 3k, the GPCA signal was drastically reduced
with the CR1 + CR2 construct, supporting that NEMO interacts
with the C-terminal region of E7. Finally, protein stability/half-
life was measured in cultured cells after treatment with a protein
synthesis inhibitor (cycloheximide). In contrast to the high
NEMO stability observed in normal cells, HPV16 E7 oncoprotein
led to a marked degradation of this latter protein (Fig. 3l).

HPV E7 oncoprotein inhibits constitutive expression of both
elafin and S100A7 through promoting β-catenin stabilization/
signaling and subsequent up-regulation of c-myc. Based on data
collected by several approaches (e.g., microarray gene expression
profiling or ChIP-sequencing), it is estimated that ~15% of all
human genes are regulated (positively or negatively) by the onco-
genic protein c-myc35. Interestingly, both elafin and S100A7, which
are drastically down-regulated in HPV-infected tissues, are listed
within the high-affinity group of c-myc targets36. These latter results
obtained by high-throughput screening were, however, never con-
firmed/validated. Highlighting the involvement of this transcrip-
tional factor in elafin/S100A7 repression, by silencing c-myc (Fig

Scientific Articles #3

ARTICLE

HPV infection alters vaginal microbiome through
down-regulating host mucosal innate peptides used
by Lactobacilli as amino acid sources
Alizee Lebeau1,14, Diane Bruyere1,14, Patrick Roncarati1, Paul Peixoto 2,3, Eric Hervouet 2,3, Gael Cobraiville4,

Bernard Taminiau 5, Murielle Masson 6, Carmen Gallego7, Gabriel Mazzucchelli8, Nicolas Smargiasso8,

Maximilien Fleron8,9, Dominique Baiwir 8,9, Elodie Hendrick1, Charlotte Pilard1, Thomas Lerho1,

Celia Reynders1, Marie Ancion1, Roland Greimers10, Jean-Claude Twizere 11, Georges Daube 5,

Geraldine Schlecht-Louf 7, Françoise Bachelerie7, Jean-Damien Combes12, Pierrette Melin 13,

Marianne Fillet4, Philippe Delvenne1,10, Pascale Hubert1 & Michael Herfs 1✉

Despite the high prevalence of both cervico-vaginal human papillomavirus (HPV) infection

and bacterial vaginosis (BV) worldwide, their causal relationship remains unclear. While BV

has been presumed to be a risk factor for HPV acquisition and related carcinogenesis for a

long time, here, supported by both a large retrospective follow-up study (n = 6,085) and
extensive in vivo data using the K14-HPV16 transgenic mouse model, we report a novel

blueprint in which the opposite association also exists. Mechanistically, by interacting with

several core members (NEMO, CK1 and β-TrCP) of both NF-κB and Wnt/β-catenin signaling
pathways, we show that HPV E7 oncoprotein greatly inhibits host defense peptide expres-

sion. Physiologically secreted by the squamous mucosa lining the lower female genital tract,

we demonstrate that some of these latter are fundamental factors governing host-microbial

interactions. More specifically, several innate molecules down-regulated in case of HPV

infection are hydrolyzed, internalized and used by the predominant Lactobacillus species as

amino acid source sustaining their growth/survival. Collectively, this study reveals a new viral

immune evasion strategy which, by its persistent/negative impact on lactic acid bacteria,

ultimately causes the dysbiosis of vaginal microbiota.

https://doi.org/10.1038/s41467-022-28724-8 OPEN

1 Laboratory of Experimental Pathology, GIGA-Cancer, University of Liege, Liege, Belgium. 2 INSERM, EFS BFC, UMR 1098, Interactions Hôte-Greffon-
Tumeur/Ingénierie Cellulaire et Génique, University of Bourgogne Franche-Comté, Besançon, France. 3 EPIGENEXP platform, University of Bourgogne
Franche-Comté, Besançon, France. 4 Laboratory for the Analysis of Medicines, Center for Interdisciplinary Research on Medicines (CIRM), University of Liege,
Liege, Belgium. 5 Department of Food Sciences-Microbiology, Fundamental and Applied Research for Animals and Health (FARAH), Faculty of Veterinary
Medicine, University of Liege, Liege, Belgium. 6 Ecole Supérieure de Biotechnologie Strasbourg, UMR 7242, CNRS, University of Strasbourg, Illkirch, France.
7 INSERM UMR 996, Inflammation Microbiome and Immunosurveillance, University of Paris-Saclay, Clamart, France. 8 Laboratory of Mass Spectrometry,
Department of Chemistry, University of Liege, Liege, Belgium. 9 GIGA Proteomic Facility, University of Liege, Liege, Belgium. 10 Department of Pathology,
University Hospital Center of Liege, Liege, Belgium. 11 Laboratory of Signaling and Protein Interactions, GIGA-Molecular Biology of Diseases, University of
Liege, Liege, Belgium. 12 Infections and Cancer Epidemiology Group, International Agency for Research on Cancer, World Health Organization, Lyon, France.
13 Department of Clinical Microbiology, University Hospital Center of Liege, Liege, Belgium. 14These authors contributed equally: Alizee Lebeau, Diane Bruyere.
✉email: M.Herfs@uliege.be

NATURE COMMUNICATIONS | (2022) 13:1076 | https://doi.org/10.1038/s41467-022-28724-8 | www.nature.com/naturecommunications 1

12
3
4
5
6
7
8
9
0
()
:,;

A
ffecting at any point of time more than 300 million
individuals worldwide, human papillomavirus (HPV) is
the most common sexually transmitted infection1. To

date, over 225 genotypes have been fully characterized and about
one fifth, belonging to the alpha genus, can be detected in the
anogenital mucosa. Although most infections are cleared or
maintained in an asymptomatic or latent state by the immune
system, carcinogenic (high-risk) HPV strains (most notably
HPV16 and 18) cause virtually all squamous intraepithelial
lesions [low-grade (LSIL) and high-grade (HSIL)] and cell car-
cinoma (SCC) arising from the uterine cervix as well as a large
fraction (~50%) of vaginal/vulvar (pre)cancers. In total, HPV
infections account for ~5% of the worldwide cancer burden with
an estimated 550,000 new cases diagnosed annually in the lower
genital tract2,3. The persistence of an active infection for years or
decades indicates that these viruses have evolved a number of
mechanisms to escape both innate and adaptive immune
responses. Indeed, by directly interacting with some core proteins
or by indirectly altering their activity (post-translational mod-
ifications) or their gene expression pattern (promoter hyper-
methylation and histone modifications), viral E6 and E7
oncoproteins have been especially shown to antagonize the cGAS-
STING DNA sensing pathway4, to suppress the interferon
secretion and signaling5–7, to impair Toll-like receptor 9 and
major histocompatibility complex class I transcription8,9 and to
reduce chemotactic and proinflammatory gene expression10.

In contrast to the skin and the gut which are colonized by a
complex microbiome, the human vaginal ecosystem is associated
with a low microbial diversity largely dominated (>90%) by a few
Lactobacillus species (mainly L. crispatus, L. jensenii and L.
iners)11–13. Characterized by the replacement of the normally
dominant lactic acid bacteria by a more diverse bacterial mixture
predominated by Gardnerella vaginalis and other anaerobic
bacteria (e.g., Atopobium vaginae, Prevotella_ge, Mobiluncus_ge,
Sneathia_ge,…)14, bacterial vaginosis (BV) is a common vaginal
disorder among women of reproductive age. Although at least
50% of women with BV are asymptomatic, this microbial
imbalance (also called dysbiosis) can manifest clinically by a
vaginal discharge, the presence of clue cells (recognized by
cytologic review) and a “fishy” odor related to the production of
volatile amines by anaerobes15. Three decades of epidemiologic
studies reported the multiplicity of sexual partners, African des-
cent, vaginal douching and cigarette smoking as risk factors for
the acquisition of BV15. However, none of these latter on their
own can reliably explain the prevalence of this condition and the
etiopathogenesis of BV remains unclear15,16. Most likely, this
imbalance in the vaginal flora is multifactorial and involves
complex interactions between extrinsic factors, the different
species of bacteria constituting the endogenous vaginal micro-
biome and the host mucosa.

In addition to causing symptoms for some women, BV has
been shown to increase the risk of preterm delivery17 as well as
gynecologic complications such as endometritis, cervicitis and
postoperative pelvic infections18. Moreover, both the rise in the
vaginal pH and the reduced level of hydrogen peroxide (H2O2)
resulting from the low abundance of Lactobacilli is presumed to
promote the acquisition of both bacterial (e.g., Chlamydia tra-
chomatis and Neisseria gonorrhoeae) and viral (e.g., herpes sim-
plex virus type 2, HIV and HPV) sexually transmitted
pathogens19–22. The degradation of the protective mucus barrier
through the sialidase activity of anaerobic micro-organisms could
also contribute to this latter susceptibility for developing infec-
tions in the lower genital tract23. Regarding HPV infections,
besides favoring their acquisition, it is generally considered that
the oxidative stress resulting from microbial dysbiosis also pro-
motes the subsequent progression of HPV-positive (pre)

neoplastic lesions. In agreement, recent evidence has shown that
an anaerobic vaginal microbiome composition is associated with
a lower regression rate of HPV-related diseases24. Despite these
important findings, the interplay/association between BV and
HPV infection is still unclear. Indeed, while longitudinal studies
clearly reported increased rates of incident HPV among BV-
positive women (for a meta-analysis, see25), the risk of BV
occurrence following HPV infection has not been systematically
pursued/calculated. Overall, data related to the influence of HPV
on vaginal microbiome are limited and, as mentioned in several
review articles26,27, when BV and HPV coexist, we cannot exclude
that, in a significant proportion of women, the viral infection
preceded in time and, by altering the host mucosa secretome,
ultimately caused BV development.

The present multi-approach study shows a causal relationship
between HPV infection and BV. Mechanistically, the drastic
down-regulation of host defense peptides, related to the interac-
tions of HPV E7 oncoprotein with several key proteins (NEMO,
CK1, β-TrCP) involved in both NF-kB and Wnt/β-catenin sig-
naling pathways, has been shown to be instrumental in this
process. Indeed, we unexpectedly uncovered that the innate
molecules most secreted by the vaginal/cervical mucosa do not
display any antimicrobial activity on Lactobacillus species but
rather, are cleaved and used as amino acid source by these lactic
acid bacteria, sustaining their growth/survival. The accumulating
(retrospective clinical and in vitro) data have been finally con-
firmed in vivo using the K14-HPV16 transgenic mouse model in
which (pre)cancer development was associated with a vaginal
dysbiosis.

Results
A large retrospective follow-up analysis including over 6,000
patients identifies a two-way interaction between HPV infec-
tion and BV development. In the last decade, several systematic
reviews of the literature (and meta-analysis) clearly indicated that
HPV infection and BV are epidemiologically related25,26,28. How-
ever, some uncertainties still exist concerning the temporal sequence
between these two pathological conditions. Indeed, while BV has
been considered as a risk factor for HPV acquisition/persistence for
a long time, the inverse relationship remains unclear. To address this
important issue, a retrospective cohort study including women who
underwent at least 2 Pap smear screenings over an 8-year period was
performed. At each visit, complete data related to a potential
abnormal cytology result (Bethesda classification), the existence of
BV (Hay/Ison grading system) and high-risk HPV infection (Abbott
RealTime HPV assay) were available for all enrolled patients. At the
first visit, 3,481 out of 6,085 (57.2%) patients did not display any
evidence of HPV infection and/or BV. A mixed bacterial flora
(associated or not with the presence of clue cells) was reported in
about one third (2,053/6,085, 33.7%) of patients with normal
cytology (HPV negative). Single or multiple HPV infection was
detected in 262 (4.3%) patients with a morphologically normal
cervico-vaginal flora. At last, 289 (4.8%) patients were simulta-
neously positive for high-risk HPV and BV. The general char-
acteristics of the four defined groups and the geographic repartition
of patients are summarized in Fig. 1a and Supplementary Fig. 1,
respectively. Of note, patients’ age (distribution) was not significantly
different between the groups. No obvious difference in terms of
geographic distribution of patients was noticed either. Overall,
12,390 follow-up visits were completed by the selected women
(median follow-up time: 66.3 months) and, in order to precisely
determine the temporal relationship between BV and genital HPV
infection, the probability of acquiring one condition when the other
one was already present or not was estimated. During follow-up
visits, a positive HPV test (associated with cytological abnormalities)

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and BV was observed in 117 (117/3,481, 3.4%) and 137 (137/3,481,
3.9%) control women (negative for HPV and BV at first visit),
respectively. Eight patients were positive for both HPV and BV at
the same follow-up visit. Importantly, the development of each
disorder was significantly more frequently diagnosed when the other
one was preceding in time [HPV: 123/2,053, 6% (OR: 1.83,
p < 0.0001); BV: 23/262, 8.8% (OR: 2.35, p < 0.001)] (Fig. 1b, c).
These latter results were not adjusted for age, race, or other potential
confounders [e.g., socioeconomic status of patients or number of sex
partners (due to the lack of available information)]. In parallel, the
median time for BV occurrence in HPV-infected and -uninfected
women was investigated and, interestingly, a significant difference
(34.53 months versus 59.44, p < 0.0001) was observed (Fig. 1d). To
further evaluate the interplay between HPV and BV, the persistence
of HPV infection according to the BV status (Fig. 1e) as well as the
inverse evaluation (Fig. 1f) were determined. Out of 791 HPV-
positive patients (diagnosed at first visit or during follow-up), 21
(2.7%) were excluded from the present longitudinal analysis because
they underwent examinations in a different hospital following HPV
diagnosis and, therefore, no data allowing to assess the persistence of
the viral infection were available in our records. For a similar reason,
0.8% (21/2,502) of BV-positive patients were not taken into con-
sideration either. As shown in Fig. 1e, the duration of HPV infec-
tions was significantly longer in BV-positive women compared to
their counterparts displaying a normal vaginal microbiome domi-
nated by Lactobacillus spp (persistent infections after 3 years: 43%
versus 32.4%, p < 0.0001). Remarkably, the opposite observation was
also made (Fig. 1f). Indeed, the 3-year BV persistence was 50.1% for
HPV-positive patients, as opposed to 41% for uninfected individuals
(p < 0.0001).

HPV oncoproteins impair innate (antimicrobial) peptide
expression in vaginal/cervical squamous mucosa. By the con-
stitutive or inducible production of soluble molecules (especially
innate peptides), the host mucosa actively participates to the
regulation of bacterial flora. These complex host-microbiota
interactions are still the subject of intense investigations and are
very likely specific for each organ as suggested by the important
disparities between each microbiome and mucosal surface (skin,
gut, oral, vaginal). According to the antimicrobial peptide data-
base (http://aps.unms.edu), the squamous epithelial cells (kerati-
nocytes) lining the lower part of the gynecologic tract secrete a
dozen of innate (antimicrobial) peptides29,30. By laser capture
microdissection, 44 independent frozen human tissue specimens
(11 normal squamous epithelia, 10 LSIL, 10 HSIL, and 13 SCC)
were sampled. In order to avoid bias related to HPV status, all
(pre)neoplastic lesions displayed diffuse (basal or full-thickness)
p16INK4a immunoreactivity in keeping with carcinogenic HPV
infection. To allow the comparison of the expression level of all
analyzed host defense peptides, the amplification efficiency of
each qPCR reaction was determined (Fig. 2a). As shown in
Fig. 2b, c, with the exception of HβD3, all antimicrobial peptides
were down-regulated in HPV-positive lesions compared to nor-
mal squamous vaginal/ectocervical epithelium. The inhibition of
“defensin-like” peptides (mainly S100A7 and elafin) was espe-
cially considered as essential given that, in normal/uninfected
conditions, these latter were up to 1000 fold (>10 Ct) more
expressed than the epithelial members of the defensin family.
Similar reduced expressions of both defensins and “defensin-like”
peptides in HPV-positive (pre)neoplastic lesions were also
observed at the protein level, as shown by immunohistochemical

Fig. 1 Retrospective clinical follow-up analysis evaluating the relationship between genital HPV infection and BV occurrence/persistence. a General
characteristics of the study population (n = 6,085). b Probability of high-risk HPV infection or BV development during the follow-up period according to the
status for the other gynecological disorder at first (enrollment) visit. c Forest plot showing the odds ratio (OR) and 95% confidence intervals (CI) for
developing one pathological condition when the other one was preceding in time [HPV infection (OR: 1.83, 95% CI: 1.41–2.37); BV development (OR: 2.35,
95% CI: 1.48–3.72)]. d Number of months for BV occurrence in HPV-positive and -negative patients. e Kaplan-Meier estimates for the persistence of HPV
infection according to the BV status (negative versus positive). The clearance of HPV infections was ascertained by both cytology (Bethesda system) and
PCR-based HPV test (Abbott High-risk HPV assay). f Kaplan–Meier curve for the persistence of BV according to the HPV status. Two consecutive negative
results (using Hay/Ison grading system) at least 12 months apart were required to consider a patient really/durably cured of BV. P values were determined
using two-sided Fisher’s exact test b, c, two-sided unpaired t-tests (d) and log-rank (Mantel-Cox) test e, f. Source data are provided as a Source Data file.

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experiments (Fig. 2e, f). Regarding LL-37, this cathelicidin-related
antimicrobial peptide was undetectable both at the mRNA and
protein levels (Fig. 2c and Supplementary Fig. 2). It is interesting
to notice that the morphologically normal (p16INK4a-negative)
squamous epithelium adjacent to HPV-positive (pre)neoplastic
lesions also displayed a significantly reduced expression of several

innate peptides (S100A7, elafin, HβD2, HβD4 and HD-5) (Sup-
plementary Fig. 3). In order to determine whether or not HPV
(and its viral oncoproteins) is directly responsible for the down-
regulation of defensin(-like) peptides observed in (pre)neoplastic
lesions, human keratinocytes were stably transduced with HPV16
E6E7 oncogenes and the expression level of each defense peptide

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potentially expressed by the squamous mucosa and being part of
the innate immune barrier of the female lower genital tract was
investigated (Fig. 2d). HβD2-4 expression was shown to be highly
stimulated by TNFα whereas LPS was more efficient to induce
HD-5/6 expression. Significantly, not only did the presence of
viral oncoproteins greatly impair (up to 7 Ct, 128 fold) the
expression of so called “constitutive” peptides (SLPI, S100A7,
elafin and HβD1), but also the induction of HβD2-4 as well as
HD-5/6 following the exposure to TNFα/LPS was significantly
altered. A drastic reduced secretion of “constitutive” peptides in
case of HPV16 E6E7 transduction was also reported in cell
supernatants (ELISA) (Supplementary Fig. 4). In parallel, we
utilized a second in vitro model mimicking more closely the early
steps of the natural infection with carcinogenic HPV (Fig. 2g).
Using organotypic raft cultures, keratinocytes maintaining epi-
somal HPV18 genome displayed weaker immunoreactivities for
SLPI, S100A7, elafin, HβD2 and HβD4 compared to uninfected
cells. The other analyzed peptides were down-regulated at a lower
extent.

HPV impairs TNFα/LPS-induced innate peptide expression
through E7-dependent NEMO degradation and subsequent
suppression of NF-κB activation. Proinflammatory factors such
as TNFα, IL-1β and LPS have been previously shown to induce
the expression of elafin as well as several members of the defensin
family31–33. Given these results and the identification of putative
NF-κB/p65 binding sites within the promoters of DEFB2-4,
DEFA5-6 and PI3 (elafin) genes [estimations made using the
Eukaryotic promoter database34], we first evaluated the require-
ment of NF-κB signaling pathway activation in TNFα/LPS-
induced innate peptide expression. As expected, knockdown of
p65 with siRNA or indirectly via blockade of the degradation of
IκBα (BAY 11-7082) resulted in a significant decrease of defensin/
elafin mRNA levels in normal/uninfected keratinocytes (Fig. 3a,
b). To evaluate the potential alteration of NF-κB in case of HPV
infection as well as the role of each individual viral oncoprotein,
the occupancy of NF-κB binding sites on both PI3/elafin and
DEFB2 promoters was analyzed by ChIP in keratinocytes stably
transduced with HPV16 E6 or E7. As shown in Fig. 3c, upon
TNFα stimulation, a weaker occupancy of both gene promoters
by p65 was reported in E7-positive cells. E6 viral oncoprotein did
not seem to disrupt NF-κB signaling pathway. In order to
determine the mechanism underlying E7-dependent alteration of
NF-κB activation, the presence of both TNFα (TNFR1-2) and LPS
(CD14 and TLR4) receptors at the cell membrane was first ana-
lyzed by flow cytometry. No significant difference was observed
between cells transduced or not with HPV E6/E7 viral oncogenes

(Fig. 3d). IκBα degradation and p65 nuclear translocation upon
TNFα stimulation were then assessed. Interestingly, the presence
of E7 oncoproteins strongly reduced IκBα degradation (Fig. 3e),
explaining the cytoplasmic sequestration of p65 (Fig. 3f, g).
Further confirming these data, the percentage of epithelial cells
displaying nuclear p65 immunoreactivity was significantly lower
in HPV-positive cancers compared to their viral-unrelated
counterparts (Fig. 3h). Based on these clear-cut results, the
direct interaction of HPV16 E7 oncoprotein with each protein
members of the IKK kinase complex was evaluated using Gaussia
princeps luciferase complementation assay (GPCA). Strikingly, a
strong interaction between HPV16 E7 and NEMO was high-
lighted and confirmed by co-IP in both directions (Fig. 3i–j and
Supplementary Fig. 5). Similar results were obtained with HPV
E7 from several other genotypes (high-risk alpha: HPV18, 33 and
39; beta: HPV8, 38 and 49) (Supplementary Fig. 6). In order to
further characterize this interaction between E7 and IKK reg-
ulatory subunit (NEMO), three truncated/mutated forms of
HPV16 E7 were also tested: the CR1 + CR2 region (consisting of
1–36 amino acids), the C-terminal domain (37–98 amino acids)
and the C24G/E26G construct mutated within the LxCxE motif.
As shown in Fig. 3k, the GPCA signal was drastically reduced
with the CR1 + CR2 construct, supporting that NEMO interacts
with the C-terminal region of E7. Finally, protein stability/half-
life was measured in cultured cells after treatment with a protein
synthesis inhibitor (cycloheximide). In contrast to the high
NEMO stability observed in normal cells, HPV16 E7 oncoprotein
led to a marked degradation of this latter protein (Fig. 3l).

HPV E7 oncoprotein inhibits constitutive expression of both
elafin and S100A7 through promoting β-catenin stabilization/
signaling and subsequent up-regulation of c-myc. Based on data
collected by several approaches (e.g., microarray gene expression
profiling or ChIP-sequencing), it is estimated that ~15% of all
human genes are regulated (positively or negatively) by the onco-
genic protein c-myc35. Interestingly, both elafin and S100A7, which
are drastically down-regulated in HPV-infected tissues, are listed
within the high-affinity group of c-myc targets36. These latter results
obtained by high-throughput screening were, however, never con-
firmed/validated. Highlighting the involvement of this transcrip-
tional factor in elafin/S100A7 repression, by silencing c-myc (Fig

Scientific Articles #3

ORIGINAL RESEARCH
published: 01 March 2021

doi: 10.3389/fimmu.2021.602067

Frontiers in Immunology | www.frontiersin.org 1 March 2021 | Volume 12 | Article 602067

Edited by:

Olivier Neyrolles,

Centre National de la Recherche

Scientifique (CNRS), France

Reviewed by:

Sandra J. Van Vliet,

Vrije Universiteit

Amsterdam, Netherlands

Salvador Iborra,

Universidad Complutense de

Madrid, Spain

Luisa Martinez-Pomares,

University of Nottingham,

United Kingdom

*Correspondence:

Mariano Prado Acosta

m.pradoacosta@gmail.com

Bernd Lepenies

bernd.lepenies@tiho-hannover.de

†Present address:

Mariano Prado Acosta,

Laboratorio de Bacterias Gram

Positivas, Departamento de Química

Biológica-IQUIBICEN, Facultad de

Ciencias Exactas y Naturales,

Universidad de Buenos

Aires-CONICET, Buenos Aires,

Argentina

Specialty section:

This article was submitted to

Molecular Innate Immunity,

a section of the journal

Frontiers in Immunology

Received: 02 September 2020

Accepted: 08 February 2021

Published: 01 March 2021

Citation:

Prado Acosta M,

Goyette-Desjardins G, Scheffel J,

Dudeck A, Ruland J and Lepenies B

(2021) S-Layer From Lactobacillus

brevis Modulates Antigen-Presenting

Cell Functions via the

Mincle-Syk-Card9 Axis.

Front. Immunol. 12:602067.

doi: 10.3389/fimmu.2021.602067

S-Layer From Lactobacillus brevis
Modulates Antigen-Presenting Cell
Functions via the Mincle-Syk-Card9
Axis
Mariano Prado Acosta1*†, Guillaume Goyette-Desjardins1, Jörg Scheffel2, Anne Dudeck3,

Jürgen Ruland4,5,6 and Bernd Lepenies1*

1 Research Center for Emerging Infections and Zoonoses, Institute for Immunology, University of Veterinary Medicine,

Hannover, Germany, 2 Dermatological Allergology, Allergie-Centrum-Charité, Department of Dermatology and Allergy, Charité

– Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of

Health, Berlin, Germany, 3 Medical Faculty, Institute for Molecular and Clinical Immunology, Otto-von-Guericke Universität

Magdeburg, Magdeburg, Germany, 4 School of Medicine, Institute of Clinical Chemistry and Pathobiochemistry, Technical

University of Munich, Munich, Germany, 5 German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany,
6 German Center for Infection Research (DZIF), Partner Site Munich, Munich, Germany

C-type lectin receptors (CLRs) are pattern recognition receptors that are crucial in

the innate immune response. The gastrointestinal tract contributes significantly to the

maintenance of immune homeostasis; it is the shelter for billions of microorganisms

including many genera of Lactobacillus sp. Previously, it was shown that host-CLR

interactions with gut microbiota play a crucial role in this context. The Macrophage-

inducible C-type lectin (Mincle) is a Syk-coupled CLR that contributes to sensing of

mucosa-associated commensals. In this study, we identified Mincle as a receptor for the

Surface (S)-layer of the probiotic bacteria Lactobacillus brevis modulating GM-CSF bone

marrow-derived cells (BMDCs) functions. We found that the S-layer/Mincle interaction

led to a balanced cytokine response in BMDCs by triggering the release of both pro- and

anti-inflammatory cytokines. In contrast, BMDCs derived from Mincle−/−, CARD9−/−

or conditional Syk−/− mice failed to maintain this balance, thus leading to an increased

production of the pro-inflammatory cytokines TNF and IL-6, whereas the levels of the anti-

inflammatory cytokines IL-10 and TGF-β were markedly decreased. Importantly, this was

accompanied by an altered CD4+ T cell priming capacity of Mincle−/− BMDCs resulting

in an increased CD4+ T cell IFN-γ production upon stimulation with L. brevis S-layer. Our

results contribute to the understanding of how commensal bacteria regulate antigen-

presenting cell (APC) functions and highlight the importance of the Mincle/Syk/Card9

axis in APCs as a key factor in host-microbiota interactions.

Keywords: Lactobacillus brevis, Mincle, Syk (spleen tyrosine kinase), CARD9, S-layer, antigen presenting cell

Prado Acosta et al. Lactobacillus brevis S-Layer Interaction With Mincle

INTRODUCTION

The intestinal tract of mammals is colonized by a large
number of microorganisms including trillions of bacteria that
are collectively referred to as the gut microbiota (1). These
indigenous microorganisms have co-evolved with their host in
a symbiotic relationship (2). In addition to metabolic benefits
for the host, these bacteria contribute to the maintenance
of immune homeostasis, modulate immune responses and
provide protection against pathogen colonization (3). The gut
microbiome impacts host immunity by influencing the release of
pro- and anti-inflammatory cytokines (4), release of metabolites
(5), and by modulating functions of antigen-presenting cells,
including dendritic cells (DCs) (6, 7). Recent studies show
that a disturbance of the gut microbiome is associated with
the progression of diseases such as inflammatory bowel disease
(IBD), obesity and cancer (8–11). Moreover, in addition to
local effects in the intestine, gut microbiota also influences host
immune responses at extra-intestinal distant sites such as the
brain, bone marrow, and lung (12–15).

There are numerous species of microorganisms present in
the gut microbiota, among them Lactobacillus being one of
the major bacterial genera found in the mammalian gut (16).
Lactobacillus sp. belongs to the lactic acid bacteria, a broadly
defined group characterized by the formation of lactic acid as the
sole or main end product of carbohydrate metabolism (17, 18).
In particular, Lactobacillus species found in the human gut have
received tremendous attention due to their health-promoting
properties (19). They are commonly used as probiotics, which are
defined by the FAO/WHO as live microorganisms that confer a
health benefit to the host, if administered in adequate amounts
(20). Lactobacillus sp. contributes to gut immune homeostasis in
many different ways; however, the mechanisms contributing to
immune regulation are still incompletely understood to date.

Many species of the genus Lactobacillus possess Surface
(S) layer proteins in their outermost envelope (21). S-layer
proteins are organized into arrays of a single polypeptide non-
covalently bound to the outermost envelope in the bacterial cell
surface. They play a crucial role in several biological functions,
such as initiation of immune responses. For instance, S-layer
proteins modulate DCs and T cell functions (22) and induce the
production of pro- as well as anti-inflammatory cytokines (23).

It has been previously shown that S-layer proteins interact
with host C-type lectin receptors (CLRs) (24, 25). Myeloid
CLRs are pattern recognition receptors (PRRs) that are crucial
for innate immunity and protection from invasive pathogens
by initiating innate sensing and early antimicrobial responses
(26, 27). Furthermore, CLRs play an important regulatory role
and maintain immune homeostasis in the gut (28). Previous
work by us and others indicate that the interaction of S-layer
from Lactobacillus acidophilus with the CLR DC-SIGN strongly
inhibits viral and bacterial infections (24, 29) and induces DC
effector functions (30). Moreover, the interaction between L.
acidophilus S-layer and the murine DC-SIGN ortholog SIGNR3
exerts regulatory signals resulting in the mitigation of colitis,
maintenance of gastrointestinal microbiota and gut mucosal
barrier function (31).

The Macrophage-inducible C-type lectin (Mincle) is a Syk-
coupled CLR. Sensing of mucosa-associated commensals by
the Mincle/Syk pathway in DCs contributes to IL-6 and IL-
23p19 production, thus promoting intestinal barrier function and
limiting inflammation and dysregulated metabolism in the liver
(3). In a recent study, it was shown that S-layer from Lactobacillus
kefiri provokes an immunostimulatory response and adjuvant
activity in vivo via Mincle engagement (32).

In this study, we purified S-layer from Lactobacillus brevis, a
microorganism known to exhibit a broad spectrum of probiotic
properties (33, 34). We determined the role of Mincle in S-layer
sensing of this Lactobacillus species and analyzed how Mincle-
mediated signaling affected GM-CSF bone marrow-derived cells
(BMDCs) effector functions upon L. brevis S-layer stimulation.
Interestingly, we found that Mincle significantly contributed to
the production of anti-inflammatory cytokines, particularly IL-
10, upon L. brevis stimulation in a Syk/Card9-dependent manner.
Our data provide insights into the interaction of microbiota with
host innate immunity and beneficial L. brevis contribution to
immune homeostasis.

MATERIALS AND METHODS

Isolation of S-Layer Proteins
S-layer proteins were extracted from overnight cultures of
Lactobacillus brevis (L. brevis) ATCC 14869 bacteria grown in
MRS broth at 32◦C and 5% CO2 by using a two-step LiCl
extraction; first, with 1 M LiCl to release S-layer associated
proteins (SLAP), and then with 6 M LiCl (35). The protein was
extensively dialyzed against distilled water overnight at 4◦C and
after centrifugation (10,000 × g 20 min), it was suspended in
sterile H2O and stored at 4

◦C. Purity was evaluated by SDS-
PAGE, which showed a single band after Coomassie blue and
silver staining (Supplementary Figure 1).

Mice
The source of the Mincle−/− mice (generated by the Consortium
for Functional Glycomics) and CARD9−/− mice was
described previously (36, 37). Inducible Syk-deficient mice
(RosaCreERT2/Sykfl/fl) were generated by crossing B6.129P2-
Syktm1.2Tara/J mice with B6.129-Gt(ROSA)26Sortm1(cre/ERT2)Tyj/J
(both from Jackson Laboratory). Mice were bred heterozygously
for the Syk allele to obtain RosaCreERT2/Sykwt/wt and
RosaCreERT2/Sykfl/fl. Mouse lines and the respective C57BL/6
wild type (WT) control mice and OT-II transgenic mice, were
housed in the animal facility of the University of Veterinary
Medicine Hannover under controlled temperature and
humidity and specific pathogen-free conditions. Mice were
sacrificed and tibia and femur from Mincle−/−, CARD9−/−,
RosaCreERT2/Sykfl/fl, RosaCreERT2/Sykwt/wt and WT mice
were prepared for the isolation of bone marrow cells.

Cell Culture
Bone marrow cells were isolated from tibia and femur of mice
as previously described (38). To obtain GM-CSF bone marrow-
derived cells (BMDCs), bone marrow cells were cultured in T-
125 flask with IMDM complete medium supplemented with 10%

Frontiers in Immunology | www.frontiersin.org 2 March 2021 | Volume 12 | Article 602067

Prado Acosta et al. Lactobacillus brevis S-Layer Interaction With Mincle

FBS and 5% of GM-CSF supernatant derived from X63 cells
(39). Medium was exchanged every 48 h and BMDCs were used
after 8–10 days of differentiation to ascertain that ≥80% of the
cell population expressed the DC marker CD11c. While the
majority of cells expressed the DC marker CD11c, it should be
noted that BMDC cultures are heterogeneous and also contain
a substantial portion of macrophages. Thus, here and in the
following, the abbreviation “BMDC” is used for “GM-CSF bone
marrow-derived cells.” All cells were grown at 37◦C in 5% CO2.

RosaCreERT2/Sykfl/fl and RosaCreERT2/Sykwt/wt-derived
BMDCs were cultured in T-125 flasks for suspension cell culture
with IMDM complete medium supplemented with 10% FBS
and 5% of GM-CSF supernatant. 4-hydroxytamoxifen (Sigma,
#H7904) was added to the cell culture at a final concentration
of 2 µM every 5 days with a complete media change leading
to a conditional Syk knockdown in RosaCreERT2/Sykfl/fl

(Syk−/−), while not affecting RosaCreERT2/Sykwt/wt cells
(Sykwt/wt). Cells were treated for 14 consecutive days and were
finally cultured in 4-hydroxytamoxifen-free medium for 5
days. Efficacy of Syk knockout was confirmed by PCR analysis
(Supplementary Figure 2).

HEK-BlueTM mMincle cells (InvivoGen #hkb-mmcl) were
cultured in T-75 flasks for adherent cell culture with DMEM
medium (4.5 g/l glucose), supplemented with 10% FBS,
penicillin-streptomycin (100 U/ml, 100 µg/ml), 100 µg/ml
NormocinTM and 2 mM L-glutamine until a confluency of ∼80%
was reached.

Stimulation of HEK-BlueTM mMincle
Reporter Cells
HEK-BlueTM mMincle reporter cell stimulation was done
according to the manufacturer’s instructions (InvivoGen #hkb-
mmcl). Briefly, after reaching confluence, the supernatant was
removed and the cells were rinsed with 3 ml of PBS and
afterwards resuspended in pre-warmed DMEM at 3 × 105

cells/ml. 180 µl cell suspension was seeded in a 96-well plate
and different concentrations of S-layer protein were added and
incubated for 24 h at 37◦C and 5% CO2. After the incubation,
180 µL of QUANTI-Blue solution (prepared by mixing 9,8 ml
ddH2O, 0,1 ml QB reagent, 0,1 ml QB buffer) was added to a
new flat-bottom 96-well plate and 20 µl of the supernatant of the
previously stimulated cells was added. The mix was incubated for
3 h at 37◦C and 5% CO2 and then the optical density (OD) was
measured at 620 nm.

Stimulation of BMDCs With S-Layer
Bone marrow cells were differentiated as described above.
BMDCs were seeded at a concentration of 1 × 105 cells/ml
in a 96-well plate and stimulated for 24 h with S-layer at
concentrations of 5 µg/ml and 10 µg/ml at 37◦C and 5% CO2.
Lipopolysaccharide (LPS) from Escherichia coli strain K-235
(Sigma-Aldrich) at a concentration of 1 µg/ml was added as a
positive control. On the next day, supernatants were harvested
and cytokine concentrations were measured by ELISA.

Production of Mincle-hFc Fusion Protein
Murine Mincle-hFc fusion protein was produced as described
previously (40). Briefly, the cDNA encoding the extracellular
part of murine Mincle was amplified by polymerase chain
reaction (PCR) and was then ligated into the pFuse-hIgG1-Fc2
expression vector (Invivogen #pfuse-hg1fc2) using the following
primers: Mincle-FW 5′-CCATGGGGCAGAACTTACAG
CCACAT-3′ and RV 5′-AGATCTGTCCAGAGGACTTA
TTTCTG-3′). CHO-S cells were transiently transfected with the
construct using MAX reagent (InvivoGen, San Diego, California,
United States). Mincle-hFc fusion protein was purified after 4
days of transfection from the cell supernatant using HiTrap
protein G HP columns (GE Healthcare, Piscataway, NJ,
United States). To confirm its presence and purity, the fusion
protein was analyzed by SDS-PAGE and subsequent Coomassie
blue staining and by Western blot using an anti-human IgG-
horseradish peroxidase (HRP) antibody. As a specificity control
for the binding assays, the hFc fragment was also expressed
and purified in the same fashion as murine Mincle-hFc, but
by using the pFuse-hIgG1-Fc2 expression vector without any
cloned CLR (“empty vector”). Recombinant human Mincle-hFc
(CLEC4E-Fc) was procured from R&D #8995-CL (R&D Systems,
Minneapolis, MN, USA).

ELISA-Based Binding Studies
A microplate with half-area wells (Greiner Bio-One GmbH,
Frickenhausen, Germany) was coated with 50 µl of 1 µg/ml
of S-layer protein overnight at RT. Non-adherent protein was
washed away, and the plate was blocked with buffer containing
1% BSA (Thermo Fisher Scientific, Darmstadt, Germany) in
PBS for 2 h at RT. After washing the wells, 200 ng of Mincle-
hFc fusion protein in lectin-binding buffer (50 mM HEPES,
5 mM MgCl2, and 5 mM CaCl2) was added per well and
incubated for 1 h at RT. Then, a 1:5,000-diluted HRP-conjugated
goat anti-human IgG antibody (Dianova, Geneva, Switzerland)
was added for 1 h at RT. Finally, the substrate solution [o-
phenylenediamine dihydrochloride substrate tablet (Thermo
Fisher Scientific, Massachusetts, United States), 24 mM citrate
buffer, 0.04% H2O2, 50 mM phosphate buffer in H2O] was
added to the samples, and the reaction was stopped with
2.0 M sulfuric acid. Data were collected using a Multiskan
Go microplate spectrophotometer (Thermo Fisher Scientific,
Waltham, United States) at a wavelength of 495 nm. When
competition assays were performed, different concentrations
of S-layer were incubated with Mincle-hFc protein and
subsequently added to the wells that had been pre-coated with
50 µg/ml of Trehalose-6,6-dimycolate (TDM) (Invivogen, San
Diego, United States).

Flow Cytometry-Based Binding Assay
Flow cytometry-based binding studies were performed to detect
L. brevis/Mincle interactions. 3 × 107 CFU/ml of L. brevis
were stained with 1 µM of the DNA-staining dye SYTO61
(Thermo Fisher Scientific) and incubated for 30 min at RT.
Subsequently, samples were incubated for 1 h with 200 ng of
Mincle-hFc fusion protein in lectin-binding buffer. After washing
once with lectin-binding buffer, the bacterial pellet was stained

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Prado Acosta et al. Lactobacillus brevis S-Layer Interaction With Mincle

with a PE-conjugated goat anti-human Fc antibody solution
(Dianova, 1:200 dilution) and incubated for 25 min at 4◦C.
Finally, flow-cytometric analysis was performed using an Attune
NxT Flow Cytometer (Thermo Fisher Scientific). Data analysis
was performed using the FlowJo Software (FlowJo, Ashland, OR,
USA). Additionally, L. brevis cells were treated with 6 M LiCl to
extract the S-layer from the cell wall. As control, hFc protein was
used for binding studies to exclude nonspecific binding.

Piceatannol Treatment
Piceatannol (PC), a Syk tyrosine kinase inhibitor (ab120722),
(#10083-24-6 abcam, Cambridge, UK) was diluted in DMSO
following manufacturer’s instructions. BMDCs were incubated
with PC at a concentration of 0.5 µM for 1 h at 37◦C and 5% CO2.

Dendritic Cell-T Cell Co-Culture Assay
Bone marrow cells were differentiated as described above.
BMDCs were seeded at a concentration of 2 × 105 cells/ml in a
96-well plate and were stimulated with EndoGrade R© ovalbumin
(OVA, 0.3 mg/ml, Hyglos, Bernried, Germany) in the presence
or absence of L. brevis S-layer (5 and 10 µg/ml) at 37◦C and 5%
CO2 for 24 h. T cells were isolated from spleens of 8–14 week old
OT-II transgenic mice via magnetic-activated cell sorting (Pan
T Cell Isolation Kit II mouse, Miltenyi Biotec). Purified T cells
were adjusted to a BMDC/T cell ratio of 1:5 and co-cultured with
BMDCs at 37◦C and 5% CO2 overnight.

qRT-PCR
To analyze Mincle mRNA expression, BMDCs from WT, Sykfl/fl,
Sykwt/wt and CARD9−/− mice were seeded in a 6-well plate at
1 × 106 cells/well and treated with S-layer at 10 µg/ml. Cells
were collected after 3, 6, and 24 h of incubation at 37◦C and
5% of CO2. To analyze cytokine mRNA expression, BMDCs
from WT and Mincle-deficient mice were used and the same
procedure was followed, except for treatment with S-layer for
12 h at final concentrations of 5 and 10 µg/ml. After stimulation,
cells were centrifugated at 300xg for 5 min and washed with PBS.
Next, 750 µl QIAzol was added and total RNA was isolated with
the RNeasy extraction kit (Qiagen, Hilden, Germany) according
to manufacturer’s instructions. For qRT-PCR the One-Step-RT-
PCR kit (Qiagen, Hilden, Germany) was used with an amount
of RNA template of 25 ng per sample. Expression levels were
measured using the AriaMx Real Time PCR system (Agilent
Technologies, Santa Cruz, CA, USA). For Mincle expression,
the housekeeping gene 18S rRNA was used for normalization,
whereas for cytokine expression, the GADPH housekeeping gene
was used.

PCR
To analyze Syk mRNA expression, unstimulated BMDCs
from WT mice, tamoxifen-treated Sykwt/wt and Sykfl/fl were
collected and total RNA was isolated as described above. To
perform the PCR, the OneStep-RT-PCR kit (Qiagen) was used
with 60 ng of RNA template per sample and the following
primer pair: forward 5′-TTTGGCAACATCACCCGGGAA-3′

and reverse 5′-CAGGCTTTGGGAAGGAGTAGG-3′ (Genbank
accession number U25685.1). To visualize the PCR products,

they were separated by agarose gel electrophoresis and visualized
using GelRed R© (Biotium, Fremont, CA, USA).

Cytokine ELISAs
Culture supernatants collected after S-layer stimulation of
BMDCs or the BMDC/T cell co-culture were analyzed for the
pro-inflammatory cytokines IL-6 and TNF (DuoSet ELISAkits,
R&D Systems, Minneapolis, MN, USA), the anti-inflammatory
cytokines IL-10 (ABTS ELISA Development Kit, PeproTech,
Hamburg, Germany) and TFG-β (DuoSet ELISAkits, R&D
Systems, Minneapolis, MN, USA) and the T cell secreted
cytokines IL-17 and IFN-γ (ABTS ELISA Development Kit,
PeproTech, Hamburg, Germany) according to the manufacturer’s
instructions. Plates were developed with the substrate 3,3′,5,5′-
Tetramethylbenzidine (TMB) and the color reaction was stopped
with 2 M sulfuric acid. Absorbance was measured at 450 nm
with a wavelength correction at 570 nm using a MultiskanGo
microplate spectrophotometer.

ELISpot
IFN-γ ELISpot was performed as indicated by the manufacturer
(Mabtech, Stockholm, Sweden). Briefly, activated PVDF ELISpot
plates (Mabtech, Stockholm, Sweden) were coated with the
anti-IFN-γ coating antibody (10 µg/ml in PBS) and incubated
overnight at 4◦C. Excess antibody was removed followed by
extensive washes with PBS. After blocking with culture medium
containing 10% FBS, BMDCs stimulated with S-layer for 24 h
were added to purified OT-II T cells at a ratio of 1:5 and the
plate was placed in a 37◦C humidified incubator with 5% CO2 for
24 h. After extensive washing, biotinylated anti-IFN-γ detection
antibody was added and incubated for 2 h at RT. Streptavidin-
HRP in PBS/0.5% FCS was added and incubated for 1 h at RT.
Spots were developed with substrate solution [1,25 mM 3,3′,5,5′-
Tetramethylbenzidine (TMB), 0.1 M citrate buffer, pH 6, 0.04%
H2O2]. Spots were counted with an ImmunoSpot

R© S6 Ultimate
reader (CTL) (Immunospot, Cleveland, USA) and the results
were analyzed by the ImmunoSpot R© SOFTWARE.

Statistical Analysis
Statistical analysis was performed using the GraphPad
Prism 7 software (GraphPad, San Diego, CA, USA).
Data are presented as mean ± SEM for all experiments.
Paired t-test was performed for Figures 1, 2 and two-
way ANOVA with a Tukey’s honest significance test was
used for the remaining figures. p < 0.05 was considered
statistically significant.

RESULTS

S-Layer From L. brevis Is Recognized by
Mincle
To analyze whether Mincle is involved in L. brevis S-layer
recognition, we performed an ELISA-based binding assay using
purified S-layer from L. brevis (Figure 1). The ELISA showed
a significant binding of murine Mincle-hFc to L. brevis S-
layer (Figure 1A) compared to the hFc control. Since it was

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Prado Acosta et al. Lactobacillus brevis S-Layer Interaction With Mincle

FIGURE 1 | Binding of S-layer to Mincle. (A) S-layer from L. brevis (5 µg per well, diluted in PBS) was immobilized on ELISA plates and incubated with murine

Mincle-hFc fusion protein (4 µg/mL) diluted either in lectin binding buffer or EDTA-containing buffer (10 mM EDTA) to analyze the Ca2+ dependency of the interaction.

Purified hFc was used as control. Binding was measured at O.D 495. (B) Mincle-hFc (4 µg/mL, diluted in lectin binding buffer) was pre-incubated with increasing

amounts of L. brevis S-layer (0–60 µg) and subsequently incubated with plate-bound TDM (50 µg/mL). Data shown are representative of three independent

experiments (triplicates each). Binding was measured at O.D 495 (C) Binding of Mincle-hFc to L. brevis was analyzed by flow cytometry. L. brevis was treated with

LiCl to remove the S-layer from the cell wall. Mincle-hFc fusion protein (4 µg/mL) was incubated with L. brevis (1 × 107 cells/mL) either in lectin binding buffer or

EDTA-containing buffer. A representative histogram plot of one binding experiment is shown. (D) Statistical analysis of the flow cytometry-based binding assay

showing the mean fluorescence intensity (MFI) of a representative experiment. Student’s t-test was performed to compare binding of the Mincle-hFc fusion to the hFc

control alone. Data are representative of four independent experiments (triplicates each) (***p < 0.001). Data depicted are the mean + SEM.

previously shown that Mincle recognizes ligands in a Ca2+-
dependent fashion (41), we determined whether the binding
of Mincle-hFc to the L. brevis S-layer was also mediated in
a Ca2+-dependent manner. Indeed, pre-incubation of Mincle-
hFc with the chelating agent EDTA resulted in a significantly
reduced binding of Mincle-hFc to S-layer (Figure 1A). To further
analyze the specificity of this interaction, we performed an
ELISA-based competition assay with increasing concentrations
of S-layer to compete with the known Mincle ligand trehalose-
6,6-dimycolate (TDM) (Figure 1B). As expected, Mincle-hFc
incubation in the presence of S-layer led to reduced binding
to TDM, thus confirming the specificity of the S-layer/Mincle
interaction. Additionally, human Mincle-hFc was shown to bind
in a Ca2+-dependent manner to the S-layer of L.brevis by
the ELISA binding assay (Supplementary Figure 3A), which

strengthens the results described above. We chose to focus
our characterization of the S-layer/Mincle interaction on the
murine model.

To prove that indeed the S-layer present in the cell wall
of L. brevis was the ligand for Mincle, we performed a flow
cytometric binding assay to L. brevis cells (Gating strategy
shown in Supplementary Figures 3B,C). We pre-treated the
bacteria with EDTA for Ca2+ complexation or alternatively
with LiCl, which strips the S-layer off the cell wall of L.
brevis (Figures 1C,D). In line with the ELISA-based binding
assay, flow cytometric analysis indicated substantial binding
of Mincle-hFc to L. brevis in a Ca2+-dependent manner.
In addition, pre-treatment of L. brevis with LiCl led to a
markedly reduced Mincle-hFc binding. These results confirm
and extend a previous study that demonstrated binding of

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Prado Acosta et al. Lactobacillus brevis S-Layer Interaction With Mincle

FIGURE 2 | Impact of L. brevis S-layer on Mincle engagement and expression. (A) HEK cells (5 × 104 cells) expressing murine Mincle (HEK-BlueTM -mMincle)

coupled to a NF-κB-inducible reporter system were stimulated with L. brevis S-layer for 24 h. SEAP activation was determined by photometric measurement at

620 nm. (B) Expression levels of Mincle mRNA at different time points after incubation of BMDCs with L. brevis S-layer, compared to untreated cells as control. Mean

+ SEM are from three independent experiments. Student’s t-test was performed to compare treatments (*p < 0.05, ***p < 0.001).

Mincle to S-layer protein from another Lactobacillus species, L.
kefiri (32).

Engagement of Mincle by S-Layer From L.
brevis
To analyze whether L. brevis S-layer acts as an agonistic
Mincle ligand, HEK cells expressing murine Mincle (HEK-
BlueTM-mMincle) were treated with L. brevis S-layer in different
concentrations. Upon engagement, Mincle activates the Fc
receptor γ-chain (FcRγ), which triggers signaling that finally
leads to NF-κB activation and the induction of the secreted
embryonic alkaline phosphatase (SEAP) reporter gene. SEAP
activity was then detected based on the conversion of the HEK-
Blue chromogenic substrate. Indeed, L. brevis S-layer activated
the Mincle reporter cells in a concentration-dependent manner
(Figure 2A). As a positive control, TDM was added to the
reporter cells, also triggering SEAP induction as expe

Scientific Articles #3

ORIGINAL RESEARCH
published: 09 October 2020

doi: 10.3389/fcimb.2020.564565

Frontiers in Cellular and Infection Microbiology | www.frontiersin.org 1 October 2020 | Volume 10 | Article 564565

Edited by:

Hridayesh Prakash,

Amity University, India

Reviewed by:

Gobardhan Das,

Jawaharlal Nehru University, India

Norbert Reiling,

Research Center Borstel

(LG), Germany

*Correspondence:

Nasreen Zafar Ehtesham

nzehtesham@gmail.com

Seyed Ehtesham Hasnain

seyedhasnain@gmail.com;

vc@jamiahamdard.ac.in

†These authors have contributed

equally to this work

‡Present address:

Javeed Ahmad,

Molecular Biology Section, Laboratory

of Immunology, National Institute of

Allergy and Infectious Diseases,

National Institute of Health, Bethesda,

MD, United States

Specialty section:

This article was submitted to

Microbes and Innate Immunity,

a section of the journal

Frontiers in Cellular and Infection

Microbiology

Received: 21 May 2020

Accepted: 28 August 2020

Published: 09 October 2020

Citation:

Arora SK, Naqvi N, Alam A, Ahmad J,

Alsati BS, Sheikh JA, Kumar P,

Mitra DK, Rahman SA, Hasnain SE

and Ehtesham NZ (2020)

Mycobacterium smegmatis Bacteria

Expressing Mycobacterium

tuberculosis-Specific Rv1954A Induce

Macrophage Activation and Modulate

the Immune Response.

Front. Cell. Infect. Microbiol.

10:564565.

doi: 10.3389/fcimb.2020.564565

Mycobacterium smegmatis Bacteria
Expressing Mycobacterium
tuberculosis-Specific Rv1954A
Induce Macrophage Activation and
Modulate the Immune Response
Simran Kaur Arora1,2†, Nilofer Naqvi1†, Anwar Alam1, Javeed Ahmad1‡,

Basma Saud Alsati1, Javaid Ahmad Sheikh3, Prabin Kumar4, Dipendra Kumar Mitra4,

Syed Asad Rahman5, Seyed Ehtesham Hasnain2,6* and Nasreen Zafar Ehtesham1*

1 Indian Council of Medical Research (ICMR)-National Institute of Pathology, Safdarjung Hospital Campus, New Delhi, India,
2 Institute of Molecular Medicine, Jamia Hamdard, New Delhi, India, 3 Department of Biotechnology, Jamia Hamdard, New

Delhi, India, 4 Department of Transplant Immunology and Immunogenetics, All India Institute of Medical Sciences, New Delhi,

India, 5 BioInception Pvt. Ltd., Chelmsford, United Kingdom, 6 Dr. Reddy’s Institute of Life Sciences, University of Hyderabad

Campus, Hyderabad, India

Mycobacterium tuberculosis (M. tb), the intracellular pathogen causing tuberculosis, has

developed mechanisms that endow infectivity and allow it to modulate host immune

response for its survival. Genomic and proteomic analyses of non-pathogenic and

pathogenic mycobacteria showed presence of genes and proteins that are specific to M.

tb. In silico studies predicted that M.tb Rv1954A is a hypothetical secretory protein that

exhibits intrinsically disordered regions and possess B cell/T cell epitopes. Treatment of

macrophages with Rv1954A led to TLR4-mediated activation with concomitant increase

in secretion of pro-inflammatory cytokines, IL-12 and TNF-α. In vitro studies showed

that rRv1954A protein or Rv1954A knock-in M. smegmatis (Ms_Rv1954A) activates

macrophages by enhancing the expression of CD80 and CD86. An upregulation in the

expression of CD40 and MHC I/II was noted in the presence of Rv1954A, pointing

to its role in enhancing the association of APCs with T cells and in the modulation of

antigen presentation, respectively. Ms_Rv1954A showed increased infectivity, induction

of ROS and RNS, and apoptosis in RAW264.7 macrophage cells. Rv1954A imparted

protection against oxidative and nitrosative stress, thereby enhancing the survival

of Ms_Rv1954A inside macrophages. Mice immunized with Ms_Rv1954A showed

that splenomegaly and primed splenocytes restimulated with Rv1954A elicited a Th1

response. Infection of Ms_Rv1954A in mice through intratracheal instillation leads to

enhanced infiltration of lymphocytes in the lungs without formation of granuloma. While

Rv1954A is immunogenic, it did not cause adverse pathology. Purified Rv1954A or

Rv1954A knock-in M. smegmatis (Ms_Rv1954A) elicited a nearly two-fold higher titer

of IgG response in mice, and PTB patients possess a higher IgG titer against Rv1954A,

also pointing to its utility as a diagnostic marker for TB. The observed modulation of

innate and adaptive immunity renders Rv1954A a vital protein in the pathophysiology of

this pathogen.

Keywords: host-pathogen interface, immune modulation, oxidative stress, signature protein, Th1 response

Arora et al. M. tb Rv1954A Drives Immune Response

INTRODUCTION

Mycobacterium tuberculosis (M. tb), the causative agent of
tuberculosis (TB), persists as a latent form in nearly 30% of
the global population who may not only serve as reservoir for
inadvertent transmission of disease but also develop active TB
during immunocompromised conditions. Recent reports have
suggested that nearly 10 million new cases of TB are diagnosed
annually with almost 1.45 million deaths being reported in
2018 alone (WHO., 2019). There is an exigent need to better
understand the pathomechanism of this disease, which advocates
an in-depth exploration of the mycobacterial interaction with the
host immune system.

Macrophages play a key role in the clearance of bacteria
through phagocytosis but paradoxically are the primary targets
of M. tb infection (Tundup et al., 2008). M. tb has evolved
mechanisms that enable it to not only avoid phago-lysosomal
fusion but also allow the pathogen to remain in a non-
replicating state within the macrophages, thereby dodging
immunosurveillance (Bussi and Gutierrez, 2019). This is
achieved by an arsenal of infectivity factors that modulate the
host defense strategies. M. tb modulates the activity of the
macrophage by dampening the secretion of pro-inflammatory
cytokines, which in turn suppress the antibacterial activity
of other immune cells. IFN-γ induces the activation of
macrophages, thereby leading to phagolysosome formation and
generating reactive oxygen species (ROS) that lead to clearance
of infection (Winau et al., 2006; Cavalcanti et al., 2012). TNF-
α supplements the activity of IFN-γ and generates ROS within
the macrophages that exert bacteriostatic effects on pathogens
(Delneste et al., 2003; Parameswaran and Patial, 2010). Knockout
mice deficient in IFN-γ and TNF-α acquire M. tb infections at
a higher rate as compared to control mice, pointing to the role
of IFN-γ/TNF-α in immunity against TB (Olsen et al., 2016). M.
tb employs various strategies to dampen this pro-inflammatory
cascade to override the host defense system (Hmama et al.,
2015). Apart from immune modulation, M. tb proteins impair the
activity of antigen-presenting cells (APCs) by either suppressing
the expression of co-stimulatory molecules or impairing the
activity of antigen-presenting molecules (Noss et al., 2000;
Hickman et al., 2002).

Studies to explore the immunomodulatory effect of M. tb
proteins have been at the forefront so as to decipher the role in
pathogenesis (Trajkovic, 2004; Hoffmann et al., 2018; Stylianou
et al., 2018). Comparative analysis of genome and proteome of
non-pathogenic and pathogenic mycobacterial species revealed
that M. tb evolved through reductive evolution from non-
pathogenic mycobacteria (Rahman et al., 2014). Despite the
reduction in the genome size, M. tb attained pathogenicity
by gene co-option whereby several functions were carried out
by individual proteins. Additionally, several genes responsible
for survival and infectivity expanded in numbers (Saini et al.,
2012; Rahman et al., 2014; Singh et al., 2014). In the current
study, we examined the function of gene Rv1954A that is
exclusively present in pathogenic mycobacteria and absent in
non-pathogenic mycobacteria. Rv1954A could have a role in M.
tb infectivity and thus provide insights into the pathomechanism

of TB disease. Our study showed the presence of the Rv1954A
gene in M. tb and BCG but absence in non-pathogenic bacteria.
The hypothetical protein Rv1954A was expressed in M. tb but
not in BCG and hence was termed as a “signature protein”
of M. tb. We elucidated the immunomodulatory role of M.
tb Rv1954 both in vitro and in vivo, delineating its role in
innate immune modulation and consequent effect on adaptive
immune responses.

MATERIALS AND METHODS

Reagents and Other Supplies
Gibco (Thermo Fisher Scientific India Pvt. Ltd., Mumbai,
India) supplied all cell culture reagents including DMEM.
Merck Limited, Mumbai, India, supplied sarkosyl,
imidazole, staurosporine, kanamycin, and isopropyl
β-D-1-thiogalactopyranoside (IPTG). BD Biosciences (San
Jose, CA, USA) supplied Middlebrook 7H11 agar, Middlebrook
7H9 media, and Middlebrook 7H10 media. ELISA kit, toxicity
removal kit, and enzymes were obtained from PeproTech (Rocky
Hill, NJ, USA), Norgen (Thorold, ON, Canada), and NEB
(Massachusetts, USA), respectively. Plastic wares for cell culture
were obtained from Corning (USA). All reagents used were of
analytical grade.

Computational Analyses and Molecular
Cloning of Rv1954A
ANCHOR software (https://iupred2a.elte.hu) was used to
predict the protein-binding sites in the disordered region, and
the IEDB (http://tools.immuneepitope.org/) tool was used to
predict T cell/B cell epitopes in the protein of interest. The
ORF encoding the M. tb Rv1954A gene was amplified by
polymerase chain reaction (PCR) using forward and reverse
primers (Supplementary Table 1). The gene was inserted in
EcoRI and XhoI restriction sites of pET28a to construct
a recombinant plasmid pET28a_Rv1954A. The recombinant
construct pET28a_Rv1954A was transformed into E. coli
BL21(DE3) expression strain, and the Rv1954A protein was
purified by the Ni-NTA affinity column and eluted with 200 mM
imidazole after inducing the culture for 3 h at 37◦C with 1 mM
IPTG. In order to concentrate the dialyzed protein, 3 kDa
cutoff Centricon was used. Contamination of bacterial endotoxin
was removed from the concentrated protein by treating with
polymyxin B beads followed by estimation of bacterial endotoxin
through LAL testing which estimated nil, and the protein was
further visualized through SDS-PAGE.

Generation of M. smegmatis Knock-In of
M. tb Rv1954A
M. smegmatis mc2155 was obtained from ATCC and maintained
as glycerol stocks. These bacterial strains were cultured in
Middlebrook 7H9 growth media supplemented with 10%
OADC. The pST_Ki_Rv1954A construct was generated using
the digested product from the pET28a_Rv1954A construct
(Parikh et al., 2013). To make M. smegmatis Rv1954A
knock-in, electroporation was employed. The positive colonies
were selected on Middlebrook 7H11 agar plates containing

Frontiers in Cellular and Infection Microbiology | www.frontiersin.org 2 October 2020 | Volume 10 | Article 564565

Arora et al. M. tb Rv1954A Drives Immune Response

kanamycin. PCR amplification was used to confirm the positive
clones as described previously (Pandey et al., 2017). A three
step sequential process was used to confirm the integration of
pST_Ki_Rv1954A into the genome of M. smegmatis. Firstly, 7H11
agar plates containing kanamycin were used to select the M.
smegmatis-positive colonies having Rv1954A (Ms_Rv1954A) and
vector pST-Ki (Ms_Vc). The positive colonies were then passaged
for seven generations on plates containing kanamycin. This was
followed by plating and passaging the positive colonies on a
kanamycin-negative plate for five generations. Lastly, plating and
passaging the colonies for seven generations on a kanamycin
plate confirmed the integration of the cassette. Colonies which
were confirmed were grown till the log phase and were harvested
followed by centrifuging and heating the pellet at 95◦C for
30 min and the pellet resuspended in an SDS-PAGE loading
dye. Centrifugation of the lysate fraction was done at 13,000
rpm for 10 min, and the supernatant obtained was loaded on
10% tricine gel. Western blotting was used for confirmation of
Rv1954A protein by anti-rabbit polyclonal Rv1954A antibody
generated in rabbit (described below). Visualization of the blots
was done after incubation with anti-rabbit IgG antibody, which
were HRP labeled.

Macrophage Culture and Cytokine
Estimation
Murine macrophage cell line RAW264.7 (ATCC) and
RAW-1TLR4 and RAW-1TLR2 were cultured in DMEM
supplemented with 10% fetal bovine serum (Gibco), 0.1
mg/mL streptomycin, 10 mM glutamine, and 1× Penta (Gibco)
with 5% CO2 at 37

◦C. RAW264.7 cells (5 × 104 cells/well)
were cultured with different concentrations of endotoxin-free
Rv1954A protein, and supernatant was collected after 24 h for
estimation of various cytokines (TNF-α and IL-12). A vial of
rRv1954A protein at 10 µg/ml was autoclaved at 121◦C, 15
psi of pressure for 30 min to denature/heat inactivate (HI) it,
which served as control. rRv1954A protein at 10 µg/ml was
treated with Proteinase K (Ambion) at 37◦C for 1 h followed
by heat inactivation at 95◦C for 10 min, which also served as
a negative control. 200 ng/ml LPS (Escherichia coli O111:B4)
obtained from Sigma (USA) was used as a positive control. In
another set of experiment, RAW264.7 (ATCC), RAW-1TLR4,
and RAW-1TLR2 (2 × 105) were infected with Ms_Vc or
Ms_Rv1954A in a 12-well plate in incomplete DMEM for 4 h at
MOI of 1:10 at 37◦C followed by three washes with PBS and kept
in a complete medium containing gentamicin to kill extracellular
bacteria. After 24 h of infection, the supernatant was collected
and levels of different cytokines were quantified using murine
standard ELISA Development Kit, as per the manufacturer’s
protocol. Briefly, 96-well ELISA plates were coated with 100 µl of
capture antibody and incubated at RT for overnight followed by
washing the plates three times with 300 µl PBST (1× PBS pH 7.2,
0.05% Tween 20) and blocking with 1% BSA for 1 h at RT. The
plates were then washed thrice with PBST, and addition of 100
µl of previously stimulated supernatant was done in each well
incubating at RT for 2 h. Hundred µl of the detection antibody
was added after washing five times with PBST followed by adding

an enzyme conjugate (100 µl/well), avidin HRP conjugate, for
2 h. The plates were incubated at RT for 2 h. Hundred µl of
TMB substrate was added to each well for color development
after washing seven times with PBST followed by stopping the
reaction with 2N H2SO4, and absorbance was taken at 450 nm
and reference wavelength at 570 nm. The cytokine levels were
determined by plotting the curve along with standards.

Immunofluorescence Staining
RAW264.7, RAW-1TLR4, RAW-1TLR2, and RAW-1TLR2/4
cells (0.5 × 106 cells/well) were seeded on coverslips in a 12-
well plate for overnight. In another set of experiment, RAW264.7
which were seeded on the coverslips were incubated with
50 µg/ml or without rat anti-mouse anti-TLR4 antibody for
90 min (Andresen et al., 2016). The cells were treated with
10 µg/ml Rv1954A protein for 6 h followed by washing and fixing
the cells with 4% PFA. These fixed cells were blocked with 3%
BSA followed by incubating with anti-Rv1954A raised in rabbit
(1:500) for 1 h. After washing with PBS, these cells were incubated
with Alexa Flour 594-labeled anti-rabbit IgG and DAPI followed
by mounting and visualization under a fluorescent microscope.

Measurement of Reactive Oxygen Species,
Nitric Oxide Levels, and Apoptosis
RAW 264.7 cells (2 × 105) infected with Ms_Vc or Ms_Rv1954A
in incomplete DMEM for 4 h at MOI of 1:10 at 37◦C followed
by three washes with PBS and kept in a complete medium
containing gentamicin to kill extracellular bacteria. After 12, 24,
and 48 h of infection, cells were harvested and washed with PBS.
These cells were further processed for determination of levels of
ROS or NO generated and apoptosis, as mentioned below. For the
determination of the generation of reactive oxygen species (ROS)
in RAW264.7 cells, CellROX Orange (Thermo Fisher Scientific
India Pvt Ltd, Mumbai, India) was added followed by incubation
at 37◦C for 30 min. Cells were acquired using a FACSCanto II
cytometer (BD Biosciences), and the data were analyzed using
FlowJo software (Becton, Dickinson and Company, New Jersey,
US). The generation of nitric oxide was determined using Griess
reagent as per the manufacturer’s protocol. Hundred µl of culture
supernatants was added to 100 µl of Griess reagent followed by
measuring the absorbance at 570 nm in a spectrophotometer.
Apoptosis was measured using Annexin-V-7AAD staining kit
(BioLegend, California, USA) as per the manufacturer’s protocol.
Cells cultured with Ms_Vc or Ms_Rv1954A were harvested,
washed with cold PBS, and resuspended in Annexin binding
buffer followed by staining with Annexin V-7AAD stain and
incubated for 15 min. Treatment of cells with staurosporine
(500 nM) served as the positive control. Cells were acquired using
FACSCanto II cytometer (BD Biosciences), and the data were
analyzed using FlowJo software.

Extracellular Staining of Surface Markers
RAW 264.7 cells (2 × 105) were infected with Ms_Vc or
Ms_Rv1954A in incomplete DMEM for 4 h at MOI of 1:10 at
37◦C followed by washing thrice with PBS and kept in complete
medium containing gentamicin to kill extracellular bacteria for
48 h. Cells were harvested and treated with fluorescently labeled

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Arora et al. M. tb Rv1954A Drives Immune Response

antibodies against various activation markers. Cells were fixed
and analyzed by flow cytometry.

Mycobacterial Survival Assay
M. smegmatis mc2155 were grown till the log phase and diluted
at 1:100 in 7H9 media followed by culturing till OD600 reached
0.05 and then were re-inoculated and allowed to grow in culture
for 30 h. OD600 was taken after every 3 h up to 30 h. RAW 264.7
cells (2 × 105) were infected with Ms_Vc or Ms_Rv1954A in
incomplete DMEM for 4 h at MOI of 1:10 at 37◦C followed
by washing thrice with PBS and kept in complete medium
containing gentamicin to kill extracellular bacteria. One ml of
0.025% SDS was used to lyse the cells after 4, 12, 24, and 48 h
of infection followed by plating the dilutions on 7H11 agar plates,
and colonies were counted and colony-forming units (CFU) were
calculated. In another experiment, log phase cultures (OD600 of
0.8–1.0) of Ms_Vc or Ms_Rv1954A were diluted 1:100 in 7H9
media and cultured till OD600 reached 0.2 and re-inoculated cells
were then treated with the indicated concentrations of H2O2 (5
and 10 mM) or 5 or 10 mM NaNO2 for 3, 6, and 9 h, and the cells
which survived were grown by plating appropriate dilutions on
7H10 media. The CFU was calculated.

Mycobacterial Phagocytosis Assay
A 45-min treatment of SYTO-9 (10 µM) (Thermo Scientific) was
used to stain the recombinant M. smegmatis (100 × 106) Ms_Vc
and Ms_Rv1954A. The excess dye was removed by washing the
stained cells with PBS, thrice. RAW 264.7 cells (2 × 105) were
infected with SYTO-9-stained Ms_Vc or Rv1954A in incomplete
DMEM for 4 h at MOI of 1:10 at 37◦C followed by washing
thrice with PBS and kept in complete medium containing
gentamicin in a 12-well plate. Cells were washed three times
with PBS, and the internalization of SYTO-9 stained Ms_Vc or
Ms_Rv1954A by RAW264.7 cells was analyzed through a flow
cytometer. For microscopic visualization of phagocytosis, 10-
mm-diameter coverslips were used and RAW 264.7 cells were
kept for adherence at 37◦C in a CO2 incubator. RAW 264.7
were co-cultured with SYTO-9-stained Ms_Vc or Ms_Rv1954A
at MOI of 1:10 in incomplete DMEM for 4 h at 37◦C. The cells
were washed and fixed with 4% PFA in PBS for 30 min, and
quenching was done using 50 mM NH4Cl in PBS followed by
visualizing the cells through a fluorescence microscope (Nikon
Carl Zeiss) (Naqvi et al., 2017).

Immunizations
All experiments using lab animals were performed according
to the guidelines of the Committee for the Purpose of
Control and Supervision on Experiments on Animals (CPCSEA),
Government of India (CPCSEA guidelines www.envfor.nic.in/
divisions/awd/cpcsea_laboratory.pdf), and Institutional Animal
Ethics Committee and Institutional Biosafety Committee,
National Institute of Pathology, New Delhi, India, approved
the protocols (Approval No. NIP/IAEC-1701). All animals
used in the experiments were kept in positive-pressure air-
conditioned units (25◦C, 50% relative humidity, 12-h light/dark
cycle). Generation of the polyclonal antibodies against purified
recombinant M. tb-Rv1954A was done in white New Zealand

rabbits by subcutaneous injection of 200 µg/ml of purified
recombinant protein emulsified with an equal volume of Freund’s
incomplete adjuvant followed by two booster immunizations
each after 15-days intervals. Two weeks after final immunization,
a dot-blot technique was used for quantitative estimation of the
antibody titer. For immunization, inbred BALB/c mice (female,
8–12 weeks, 20–25 g) were obtained from the National Institute
of Immunology (New Delhi, India). The test group (n = 5)
was injected subcutaneously with purified recombinant M. tb-
Rv1954A protein (10 µg/ml) in PBS buffer followed by booster
doses (10 µg/ml) after every tenth day till 1 month of primary
immunization. The control group (n = 5) was sham immunized
with PBS only. Use of adjuvant was avoided to minimize the
immunomodulatory bias obtained by use of adjuvants (Ciabattini
et al., 2016; Knudsen et al., 2016). In another experiment, BALB/c
mice (female, 8–12 weeks, 20–25 g) obtained from the National
Institute of Biologicals (NIB) Noida, India, were intraperitoneally
injected with Ms_Vc (n = 6) or Ms_Rv1954A (1 × 107) (n
= 6) for evaluation of the antigenicity and immunogenicity of
Rv1954A protein (Meng et al., 2017; Ruangkiattikul et al., 2017;
Dang et al., 2018). After 4 weeks of primary immunization,
mice were sacrificed and blood was collected from both sets of
mice either immunized with purified recombinant Rv1954A or
intraperitoneally injected with Ms_Vc/Ms_Rv1954A, and serum
was obtained and stored at −20◦C till further use. Another group
of mice was also given intratracheal instillation with Ms_Vc or
Ms_Rv1954A (1 × 106) followed by a booster dose after 15 days.
Mice were sacrificed after 1 month of primary immunization, and
lungs were recovered to observe any signs of pathology.

Isolation of Splenocytes and Estimation of
Cytokines
Mice were sacrificed after 30 days of primary immunization,
and spleens were recovered. Splenocytes were obtained using
standard protocols (Ahmad et al., 2018) for in vitro assays.
Spleens were recovered and perfused using a 26-gauge needle,
and cell suspension obtained using a cell strainer devoid of
debris was centrifuged and suspended in RBC lysis buffer (0.84%
NH4Cl solution). The splenocytes obtained were devoid of
erythrocytes and were centrifuged and resuspended in complete
media. Splenocytes (1 × 106 cells) were then re-stimulated
with recombinant protein (10 µg/ml) for various time points.
The supernatants were collected and levels of IFN-γ quantified
using the murine standard ELISA Development Kit, as per the
manufacturer’s protocol described earlier.

In another experiment, splenocytes from mice infected with
Ms_Vc or Ms_Rv1954A (0.1 × 106 cells/well) were also seeded in
a 96-well plate, stimulated with recombinant protein Rv1954A,
and incubated at 37◦C for 12, 24, and 48 h. The levels of secreted
cytokines TNF-α, IL-6, and IL-12 were quantified using a murine
standard ELISA Development Kit (PeproTech, Rocky Hill, NJ,
USA) as per the manufacturer’s protocol.

Histological Analysis of Lungs
BALB/c mice (n = 6) were given intratracheal infection with PBS,
Ms_Vc (1 × 106), or Ms_Rv1954A (1 × 106) in 50 µl PBS. A
booster dose of intratracheal infection was also given after 15

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Arora et al. M. tb Rv1954A Drives Immune Response

FIGURE 1 | Rv1954A enhances TLR4-mediated production of pro-inflammatory cytokines in macrophages. RAW264.7, RAW-1TLR4, and RAW-1TLR2 cells were

treated with purified Rv1954A protein (2, 5, 10 µg/ml). Autoclaved (AC) protein and proteinase K (PK)-treated protein served as negative controls. LPS treatment

served as a positive control. Levels of IL-12 and TNF-α were estimated using ELISA (A). Representative data from three experiments show the concentration of IL-12

(Continued)

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Arora et al. M. tb Rv1954A Drives Immune Response

FIGURE 1 | and TNF-α as mean ± SEM. Statistical significance was determined with the student t-test. (B) RAW264.7, RAW-1TLR4, and RAW-1TLR2 were

infected with Ms_Vc and Ms_Rv1954A at an MOI of 1:10. Supernatants were collected after 24 h of infection, and secretion of cytokine levels was estimated through

ELISA. Representative data from three experiments show the concentration of IL-12 and TNF-α as mean ± SEM. Statistical significance was determined with the

student t-test. RAW264.7, RAW-1TLR4, RAW-1TLR2, and RAW-1TLR21TLR4 cells were cultured on coverslips followed by incubation with Rv1954A protein

10 µg/ml for 6 h. The cells were fixed and incubated with anti-Rv1954A followed by staining with Alexa Flour 594 nm and DAPI and visualized by a fluorescent

microscope (magnification is 40×, scale bar represents 20 µm) (C). RAW 264.7 cultured on the coverslips were pretreated with or without rat anti-mouse anti-TLR4

for 90 min. Cells were stimulated with 10 µg/ml rRv1954A protein for 6 h followed by fixing and treatment with anti-Rv1954A antibody raised in rabbit tagged with

Alexa Flour 594 and DAPI followed by mounting and visualization under a fluorescent microscope (magnification is 40×, scale bar represents 20 µm) (D).

days. Mice were sacrificed after 1 month of primary infection.
The lungs from the mice were fixed in 4% formalin and were
processed for hematoxylin and eosin staining.

Human Subjects
All the protocols involving the use of samples from human
subjects conformed to the Declaration of Helsinki. Approval
was granted for all related experiments by the Insti

Scientific Articles #3

Frontiers in Cellular and Infection Microbiolo

Edited by:
Manisha Yadav,

University of Delhi, India

Reviewed by:
Rishein Gupta,

University of Texas at San Antonio,
United States

Murugesan V. S. Rajaram,
The Ohio State University,

United States

*Correspondence:
Himanshu Kumar

hkumar@iiserb.ac.in

Specialty section:
This article was submitted to

Microbes and Innate Immunity,
a section of the journal

Frontiers in Cellular and Infection
Microbiology

Received: 09 September 2020
Accepted: 10 December 2020
Published: 27 January 2021

Citation:
Mishra R, Krishnamoorthy P and
Kumar H (2021) MicroRNA-30e-

5p Regulates SOCS1 and SOCS3
During Bacterial Infection.

Front. Cell. Infect. Microbiol. 10:604016.
doi: 10.3389/fcimb.2020.604016

BRIEF RESEARCH REPORT
published: 27 January 2021

doi: 10.3389/fcimb.2020.604016

MicroRNA-30e-5p Regulates SOCS1
and SOCS3 During Bacterial Infection
Richa Mishra1, Pandikannan Krishnamoorthy1 and Himanshu Kumar1,2*

1 Laboratory of Immunology and Infectious Disease Biology, Department of Biological Sciences, Indian Institute of Science
Education and Research (IISER) Bhopal, Bhopal, India, 2 WPI Immunology, Frontier Research Centre, Osaka University,
Osaka, Japan

Host innate immunity is the major player against continuous microbial infection. Various
pathogenic bacteria adopt the strategies to evade the immunity and show resistance
toward the various established therapies. Despite the advent of many antibiotics
for bacterial infections, there is a substantial need for the host-directed therapies
(HDTs) to combat the infection. HDTs are recently being adopted to be useful in
eradicating intracellular bacterial infection. Changing the innate immune responses of
the host cells alters pathogen’s ability to reside inside the cell. MicroRNAs are the small
non-coding endogenous molecules and post-transcriptional regulators to target the
3’UTR of the messenger RNA. They are reported to modulate the host’s immune
responses during bacterial infections. Exploiting microRNAs as a therapeutic candidate
in HDTs upon bacterial infection is still in its infancy. Here, initially, we re-analyzed the
publicly available transcriptomic dataset of macrophages, infected with different
pathogenic bacteria and identified significant genes and microRNAs common to the
differential infections. We thus identified and miR-30e-5p, to be upregulated in different
bacterial infections which enhances innate immunity to combat bacterial replication by
targeting key negative regulators such as SOCS1 and SOCS3 of innate immune signaling
pathways. Therefore, we propose miR-30e-5p as one of the potential candidates to be
considered for additional clinical validation toward HDTs.

Keywords: innate immunity, microRNA, host-pathogen interaction, bacterial infection, host-directed therapy

INTRODUCTION

Variety of commensal bacteria were considered beneficial to human host and their role is crucial for
the host survival. In contrast, several bacteria qualify the category of potential pathogens to cause
serious health ailments in humans ranging from the food-borne illnesses caused by species such as
Listeria monocytogenes and Salmonella typhi, as well as tuberculosis caused by Mycobacterium
tuberculosis and also associated with oncogenesis. Additionally, bacterial infections are associated as
a secondary infection to many infectious and non-infectious diseases, which further enhance the
severity of primary disease, for example influenza virus and HIV infection. Furthermore, the
alarming elevation of the antibacterial resistance against any bacterial disease possess biggest global
threat and is a critical cause for the millions of human deaths annually around the world
(Laxminarayan et al., 2013). Like viruses, bacteria can also cause outbreak, leading to sever

gy | www.frontiersin.org January 2021 | Volume 10 | Article 6040161

Mishra et al. miR-30e Regulates Bacterial Infection

health damage and lives. Recently, a food-borne- bacteria Listeria
monocytogenes caused an outbreak in South Africa leading to
severe illness and deaths among the population (de Noordhout
et al., 2014; Allam et al., 2018; Desai et al., 2019; Thomas et al.,
2020). Therefore, re-exploring the host factors against bacterial
infections might is needed.

Innate immunity is the first line of defense accelerates when a
pathogen encounters the host. Host cells express pattern
recognizing receptors (PRRs) which sense a diverse range of
invading pathogens including bacteria through PAMPs
(pathogen associated molecular patterns) and triggers the
immune responses which subsequently eliminate the infection
(Kawai and Akira, 2010; Kumar et al., 2011). Macrophages are
one of the major innate immune cells also termed as professional
phagocytes which helps in binding and clearance of the invading
bacterial pathogens (Nau et al., 2002). Additionally, non-
immune epithelial cells aid in immune activation to challenge
the bacterial infection (Francis and Thomas, 1996). However,
almost all pathogenic bacteria develop certain mechanisms to
manipulate the host immune system for their survival by various
immune evasion strategies (Diacovich and Gorvel, 2010; Reddick
and Alto, 2014).

The activated immune system may lead to excessive secretion
of inflammatory molecules like interferons and pro-
inflammatory cytokines. Hence, immune actions are tightly
regulated at various levels. One important regulatory factors
and fine tuners of immune system were the microRNAs
(miRNAs). miRNAs are small non-coding RNAs of length
ranging from 18-22 nucleotides in their mature form. They
bind to the partially complementary sequences of the
3’untranslated regions (3’-UTR) in mRNA transcript of the
gene to inhibit the expression of the corresponding gene at
post-transcriptional level. The miRNAs have been previously
shown to be involved in the regulation of bacterial infections and
also employed by the bacteria for their survival (Izar et al., 2012;
Maudet et al., 2014; Das et al., 2016; Zhou et al., 2018). Host
directed therapy (HDT) is one of the recently emerging approach
against infectious diseases which majorly aims to directly affects
the host factors and machineries which play crucial role in the
encroachment and survival of the pathogens (Kaufmann et al.,
2018). In previous studies, miRNAs recommended for HDT in
bacterial infections (Iannaccone et al., 2014; Sabir et al., 2018) but
still the approach of considering miRNAs for HDT lies in
its infancy.

In present work, we aimed to identify the miRNA-mediated
regulation common to wide range of bacterial infection. We
initially re-analyzed the RNA-sequencing dataset GSE73502, in
which peripheral blood mononuclear cells (PBMCs) of healthy
volunteers were differentiated to macrophages then infected with
Listeria monocytogenes and Salmonella typhimurium respectively
(Haraga et al., 2008; Pai et al., 2016). Both the bacteria have
different genetic composition and varied immune activation
mechanisms associated with them to be used as the model
bacteria for understanding the host-bacterial interactions (Corr
and O’Neill, 2009). We determine high confidence genes (HCGs)
using robust rank aggregation method. Then after applied

Frontiers in Cellular and Infection Microbiology | www.frontiersin.org 2

miRNAs-seed enrichment analysis to HCGs, which identified
miR-30-5p family as the highly enriched family of miRNAs
within the host. Our study proposed the role of miR-30e-5p
(miR-30e) in modulating innate immunity during bacterial
infections, due to its significant upregulation during
pathogenic infections and PAMPs stimulation. Altogether, our
finding concludes that miR-30e targets the 3’-UTR of SOCS1 and
SOCS3, crucial negative regulators of innate immunity which
enhances the innate immune responses and reduces the bacterial
replication of Listeria monocytogenes and Uropathogenic E. coli –
representative of both gram-positive and gram-negative
bacterium respectively, causing severe diseases like listeriosis
and urinary tract infections. This further proposes that miR-
30e might considered as the potential candidate for HDTs during
infectious diseases caused by intracellular bacteria.

MATERIALS AND METHODS

Cell Lines, Bacteria, and Reagents
HEK293 human embryonic kidney cells (ATCC CRL-3216), Raw
264.7 (Cell Repository, NCCS, India), HeLa cervical cancer cells
(Cell Repository, NCCS, India), were cultured in Dulbecco’s
modified Eagle’s medium (DMEM) supplemented with 10%
fetal bovine serum (FBS) and 1% Antibiotic-Antimycotic
solution. DMEM, FBS and Antibiotic-Antimycotic solution
were purchased from Invitrogen. Human PBMCs were isolated
from whole blood as reported previously (Ingle et al., 2015). The
seeded cells were washed with phosphate-buffered saline (PBS)
prior to infection. Then cells were infected in serum-free
DMEM/RPMI with L. mono. for 2 h and UPEC for 1 h with
50 MOI after attaining optical density (OD 600) of 0.4 to 0.8.
After infection cells were washed twice with serum free DMEM/
RPMI and supplemented with complete DMEM/RPMI and
gentamicin (75ug/ml, Sigma) for 24 h at 37°C, 5% CO2. Cells
were harvested after 24 h in BHI media containing 1X Triton
(Thermo Scientific) and/or Trizol (Ambion Life Tech.) for CFU
assay and mRNA quantification. For electroporation of human
PBMCs, 1 X 106 cells were suspended in Opti-MEM (Invitrogen)
containing 50 nM mirVana miRNA mimics (Ambion). The cells
were pulsed twice with 1000 V for 0.5 ms with a pulse interval of
5 s with the Gene Pulser Xcell electroporation system. The cells
were then transferred to RPMI supplemented with 10% FBS.
Then infected with L. mono. with 50 MOI. Transfection of HeLa
cells with miRNA mimics, inhibitors and control mimics/
inhibitors and/or plasmids was performed with Lipofectamine
2000 or 3000 (Invitrogen) according to the manufacturer’s
protocol. Stimulation of cells was carried out using LPS and
CpG from Sigma and Invivogen. DMEM, FBS, Opti-MEM,
RPMI, and Lipofectamine 2000/3000 were purchased from
Invitrogen. The miR-30e mimic (miR-30e) (Invitrogen: Catalog
number#4464066) or a nonspecific miRNA negative control#1
(miR-NC1) (Invitrogen: Catalog number#4464058) was used
according to the manufacturer’s instructions (Applied
Biosystems). The miR-30e inhibitor (AmiR-30e) (Invitrogen:

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Mishra et al. miR-30e Regulates Bacterial Infection

Catalog number#4464066) was used to inhibit miR-30e
expression in transfected cells.

Bacterial Infection
Listeria monocytogenes (L. mono.), a gram-positive bacterium
was used for infection (MTCC-1143). Bacteria were grown to the
logarithmic growth phase in brain heart infusion BHI (HiVeg™

Media, HIMEDIA) at 37°C with continuous shaking at 200 rpm
overnight. Secondary culture was established until desired OD.
Bacteria were subsequently washed with fresh BHI and PBS by
two steps of centrifugation at (4,000 rpm, 5 min) and diluted in
serum free DMEM/RPMI at 50 MOI for infection. Secondly,
Uropathogenic E. coli (UPEC), a gram-negative bacterium was
used for infection, UPEC bacteria used in the study was GFP-
tagged, GFP was induced by using inducing agent IPTG
(Isopropyl ß-D-1-thiogalactopyranoside) at a secondary culture
without shaking the inoculated tube/s. After obtaining optimal
OD, respective bacterial cultures were used to infect the
mammalian HeLa cells and PBMCs accordingly. Cell were
then harvested to quantify the bacterial population by
performing colony forming unit assay and counting the
bacterial colonies at different dilutions on BHI plates incubated
overnight at 37°C.

Quantitative Real-Time Reverse
Transcription PCR
Total RNA was extracted with the Trizol reagent (Ambion/
Invitrogen) and used to synthesize cDNA with the iScript
cDNA Synthesis Kit (BioRad, Hercules, CA, USA) according to
the manufacturer’s protocol. Gene expression was measured by
quantitative real-time PCR using gene-specific primers both for
humans and bacteria as analyzed in the results and SYBR Green
(Biorad, Hercules, CA, USA) and additionally using 18S and
NPM1 (for AGO2-RNA immunoprecipitation experiment)
primers for normalization. For quantification of the
abundances of miR-30e, real-time PCR analysis was performed
with the TaqMan Universal PCR Master Mix (Applied
Biosystems) and the miR-30e-5p specific TaqMan miRNA
assays. The Taqman U6 assay was used as a reference control.
Real time quantification was done using StepOne Plus Real time
PCR Systems by Applied BioSystems (Foster City, CA, USA).

Luciferase Reporter Assays
HEK 293T and HeLa cells (5 X 104) were seeded into a 24-well
plate and transiently transfected with 25 nM of mimics (miR-30e
and miR-NC1), 50 ng of the transfection control pRL-TK
plasmid (Renilla luciferase containing plasmid) and 300 ng of
the various expression plasmids (containing 3’-UTR of specific
genes and Firefly luciferase containing plasmid) according to the
respective experiments. In another experiment, 300 ng of miR-
30e promoter Firefly luciferase containing plasmid together with
50 ng of the transfection control pRL-TK plasmid were
transfected together and finally infected with L. mono. The
cells were lysed at 24 h after transfection and/or infection, and
finally the luciferase activity in total cell lysates was measured
using Glomax machine (Promega, Madison, WI, USA).

Frontiers in Cellular and Infection Microbiology | www.frontiersin.org 3

Enzyme-Linked Immunosorbent Assay
(ELISA)
HeLa cells were transiently transfected with miR-30e and miR-
NC1 and then were infected L. mono. bacterial infection then
treated with gentamycin. The culture media were harvested 24 h
after infection and were analyzed by specific ELISA kits (Becton
Dickinson) according to the manufacturer’s instructions to
determine the amounts of IL6 that were secreted by the cells.

RNA Immunoprecipitations
RNA immunoprecipitations were performed as described previously
(Meister et al., 2004; Beitzinger and Meister, 2011). The pIRESneo-
Flag/HA Ago2 plasmid was a gift from Professor T. Tuschl (Addgene
plasmid #10822). Briefly, HeLa cells transfected with miRNA and
infected with L. mono. then treated with gentamycin were lysed in
0.5% NP-40, 150 mM KCl, 25 mM tris-glycine (pH 7.5) and
incubated with M2 Flag affinity beads (Sigma) overnight. The lysate
was then washed with 300 mM NaCl, 50 mM tris-glycine (pH 7.5), 5
mM MgCl2, and 0.05% NP-40. The extraction of RNA from the
immunoprecipitated RNPs was performed with the Trizol reagent
(Ambion, Invitrogen) according to the manufacturer’s protocol.

Microscopy
HeLa cells were seeded along with cover slips in low confluency
and next day transfected with miRNA mimic for 24 h prior to
bacterial infection then infected with UPEC-GFP for 4 h and
treated with gentamycin for 1 h. Afterwards kept in incubator
(37°C, 5% CO2) for 24 h. Then cells were fixed with 4% PFA for
15 min at room temperature; permeabilized with 0.05% Triton
X-100 in 1 x PBS for 10 min at room temperature; blocked with
bovine serum albumin (5 mg/ml) in PBS, 0.04% Tween-20 for
30 min and incubated for 1 h with the relevant primary
antibodies diluted in blocking buffer. The cells were then
washed three times with PBS and incubated for 1 h with the
appropriate secondary antibodies at room temperature. Nuclei
were stained with DAPI, phalloidin red was used to stain the
actin filaments of the cells. Cover slips then containing cells were
carefully mounted on to the glass slides using Fluoroshield
(Sigma) as mounting media. Slide was then kept for few hours
for drying before imaging. Images were visualized at 40X with
Apotome – AXIO fluorescence microscope by Zeiss.

Re-analysis of the RNA-Seq Dataset
The raw read counts were obtained from GSE73502 (Pai et al.,
2016) through GREP2 R package (Mahi et al., 2019) and were
TMM (Trimmed mean of M-values) normalized. Differential
expression analysis was performed using EdgeR (Robinson et al.,
2010) package with a significance cutoff – logFC >1.5 and
adjusted p-value <0.05. The differential expression analysis was
performed for each time point (2hr and 24 hr) and both the
bacterial infections separately. In case of robust rank aggregation
(RRA) approach (Kolde et al., 2012), the significant differentially
expressed genes (DEGs) obtained from each case were ranked
using robust rank aggregation R package, which basically ranks
and aggregate the high confidence genes across each list. The
high confidence genes were calculated based on the p-value

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Mishra et al. miR-30e Regulates Bacterial Infection

adjusted using Bonferroni correction and 30 genes were obtained
below the cutoff less than 0.05. In next approach, miRNA seed
enrichment analysis was performed using the tool Mienturnet
(Licursi et al., 2019). In this, the high confidence genes were used
as input for the miRNA enrichment analysis. The number of

Frontiers in Cellular and Infection Microbiology | www.frontiersin.org 4

miRNAs which were predicted to be binding with the high
confidence genes were represented using the bar plot (Figure
1D). All the analysis was performed in R 3.6 environment and
the tool Networkanalyst (Zhou et al., 2019) was used for the
generation of PCA plot and Venn diagram.

A B

D

E F G IH

C

FIGURE 1 | Bioinformatic identification of crucial host genes and microRNAs (miRNAs) associated with bacterial infection in Macrophages. (A) Schematic of the
bioinformatics pipeline used to identify the high confidence genes and the potential miRNAs that target them, upon infection with two different bacteria at different
time points. (B) PCA plot shows the segregation of samples between three experimental groups – Control, Listeria and Salmonella infection. (C) Venn diagram
shows the overlap of differentially expressed genes at 2 h and 24 h of Listeria and Salmonella infection compared to the corresponding uninfected samples giving 30
high confidence host factors obtained through robust rank aggregation (RRA) method. (D) Bar plot showing miRNA seed enrichment analysis for significant high
confidence genes obtained through robust rank aggregation method. (E–H) Quantification (as determined by qRT-PCR analysis) of the fold changes in the
abundances of miR-30e as indicated in hPBMCs, HeLa and Raw264.7 cells in presence of respective bacterial pathogens and PAMPs stimulation. (I) Quantification
of miR-30e promoter activity by luciferase assay as indicated in HeLa cells. Data are mean +/- SEM of triplicate samples from single experiment and are
representative of two independent experiments. ***P < 0.001, **P < 0.01 and *P < 0.05 by one-way ANOVA Tukey test and student t-test.

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Mishra et al. miR-30e Regulates Bacterial Infection

Statistical Analysis
All experiments were carried out along with the appropriate
controls, indicated as control cells (Ctrl) or uninfected/non-
infected cells. Experiments were performed in duplicates or
triplicates for at least two or three times independently.
GraphPad Prism 8.0 (GraphPad Software, La Jolla, CA, USA)
was used for statistical analysis. The differences between two
groups were compared by using an unpaired two-tailed Student’s
t-test. While the differences between three groups or more were
compared by using analysis of variance (ANOVA) with Tukey
test. Differences were considered to be statistically significant
when P < 0.05. Statistical significance in the figures is indicated as
follows: ***P < 0.001, **P < 0.01, *P < 0.05; ns, not significant.

RESULTS

Bioinformatic Prediction of Host Genes
and Their Regulatory MicroRNAs During
Bacterial Infection
To investigate the microRNAs (miRNAs) and their target(s)
involved in bacterial infection, we robustly re-analyzed the
publicly available transcriptomic dataset GSE73502 in Gene
Expression Omnibus (GEO) database. The dataset comprises
of human macrophages infected with live gram-positive Listeria
or gram-negative Salmonella bacteria, respectively (Pai et al.,
2016). We first identified high confidence genes (HGCs) or the
host factors from the dataset which were significantly
dysregulated upon bacterial infection. Next, we identified the
miRNAs targeting these HCGs. The schematic of in-silico
unbiased pipeline used to perform the analysis is explained in
Figure 1A. The dataset includes samples of human macrophages
infected with bacteria both at early (2 h) and late (24 h) time
points that were taken for analysis to cover the maximum
number of infected samples during the unbiased analysis as
well as to find the wide range host factors involved in crucial
cellular machineries both at early and late stages of infection.
After normalization, the segregation of different samples was
visualized through PCA plot (Figure 1B). Differential expression
analysis for genes was performed between the non-infected
(control) and infected (Listeria and Salmonella) groups. The
963 and 3857 differentially expressed genes (DEGs) were obtain
upon Listeria infection at 2 h and 24 h respectively. Similarly,
2040 and 2669 DEGs were obtain upon infection with Salmonella
at 2 h and 24 h respectively. To determine the significantly
dysregulated genes crucial for different cellular responses and
common to both bacterial infections at early and late time points,
we employed a popular rank aggregation method known as
robust rank aggregation (RRA) (Kolde et al., 2012). The
overlap of the DEGs were depicted in Venn diagram (Figure
1C). Robust rank aggregation method narrowed 30 genes to be
significantly dysregulated in all the cases with the adjusted
p-value of 0.05. These 30 genes or host factors were
predominantly related to immune pathways and studied during
bacterial infections. In addition, this analysis holds valid

Frontiers in Cellular and Infection Microbiology | www.frontiersin.org 5

presumptions to be taken into consideration as the target cells
used here were macrophages from healthy volunteers infected
with bacteria (Listeria and Salmonella), are the crucial innate
immune cells to play an important role in defense during bacterial
infections. Through this approach we have found 30 HCGs
crucial for both the infections. In this connection, we predicted
the microRNAs which can modulate these HCGs as the host
regulatory molecules proposing their utility in host-directed
therapy (HDT). Furthermore, we performed miRNA seed-
target enrichment analysis using a tool called Mienturnet
(Licursi et al., 2019). This analysis provides the miRNA seed
enrichment result from the given query of HCGs. We found the
miRNA-seed of miR-30-5p family to be significantly enriched
which targets seven of these 30 HCGs as shown in Figure 1D. This
family consists offive members (miR-30a to miR-30e) with minor
sequence difference and major phylogenetic difference as
regulated at different chromosomal location. miR-30a/b/c/d has
been extensively studied in relation to bacterial infections and
immune evasion strategies as discussed later. However, role of
miRNA-30e during bacterial infection is poorly understood.
Hence, we further focused on miRNA-30e characterization as
the host regulatory microRNA and concluded that miR-30e-5p
induced upon different bacterial infections and stimulation
with bacterial PAMPs in hPBMCs, HeLa and Raw264.7 cells
respectively (Figures 1E–H). In addition, we estimated the miR-
30e promoter activity in presence of Listeria monocytogenes
(L. mono.) infection (Figure 1I) and found that bacterial
infection controls miR-30e transcriptional regulation to regulate
its expression.

The miRNA-30e-5p Targets Innate
Immunity Regulators SOCS1 and SOCS3
To demonstrate the post-transcriptional regulation by miR-
30e-5p, out of seven enriched host genes, SOCS1 and SOCS3
were selected to be analyzed in-vitro as shown schematic
representation (Figure 2A). Because SOCS1 and SOCS3, a key
immune negative regulator of PRR-mediated innate immune
signaling pathways were obtained after the unbiased miRNA-
seed enrichment analysis to demonstrate the role of miR-30e in
immune regulation. Notably, they were also observed to be
highly conserved targets of miR-30e throughout all
the different class of species (Figure 2B). Next, to validate the
regulation of 3’UTR of mRNA targets, the 3’UTR of the SOCS1
and SOCS3 gene were cloned downstream of luciferase gene
under the CMV promoter to perform the luciferase assay. It was
found that miR-30e significantly reduced the luciferase activity
compared to control miR-NC1 (Figure 2C). In contrast,
introduction of mutation (3’UTR_MUT) in cloned 3’UTR/
3’UTR_WT by site directed mutagenesis (SDM) did not
change the luciferase activity in presence of miR-30e and it
was comparable with 3’UTR_WT (wild type) as shown in Figure
2D. miR-NC1 was used as a control for the experiment.
Furthermore, we scanned the 3’UTRs of SOCS1 and SOCS3 for
RNA binding site for AGO2 protein, in CLIP database, which is a
key component of the miRNA-mediated silencing known as
RNA-induced silencing complex (RISC) and found that the miR-

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Mishra et al. miR-30e Regulates Bacterial Infection

30e make stable complexes with the target genes (Mishra et al.,
2020). To validate, miR-30e and negative regulators transcripts
(SOCS1 and SOCS3) interaction, AGO2 pull-down assay was
performed as shown in schematic (Figure 2E) and found that
introduction of miR-30e significantly enriches the transcript of
SOCS1 and SOCS3 during L. mono. infection compared to the L.
mono. infection alone or L. mono. infection along with control
miR-NC1 treated cells, suggesting that miRNA-30e directly
interact with the transcript through the formation of RISC.
Next, the ectopic expression of miR-30e reduced the

Frontiers in Cellular and Infection Microbiology | www.frontiersin.org 6

expression level of SOCS1 and SOCS3 in HeLa cells compared
to the control after L. mono. infection (Figure 2F) and UPEC
infection (Figure 2G). Taken together, miR-30e targets SOCS1
and SOCS3 significantly which might regulate innate immunity
during bacterial infection.

The MiRNA-30e-5p Curtails Bacterial
Infection by Enhancing Innate Immunity
To understand the physiological implication of miR-30e-
mediated targeting of SOCS1 and SOCS3, we investigated

A B

D

E F G

C

FIGURE 2 | miR-30e-5p targets SOCS1 and SOCS3. (A) Schematic of miR-30e-5p targeting of innate immune regulators. (B) miR-30-5p binding 3’ UTR site
conservation of SOCS1 and SOCS3 among wide range of species. (C, D) HEK293 cells were transfected with 50 ng of pRL-TK and 300 ng of 3’UTR_WT or 300 ng
of 3’UTR_MUT (of indicated genes) together with 25 nM miR-30e or miR-NC1 mimics, 24 h after transfection, the cell was lysed and subjected to luciferase assay.
(E) Schematic for RNA-immunoprecipitation assay. HeLa cells were transfected with plasmid encoding Flag-AGO2 in presence of miR-30e (50 nM) and miR-NC1
(50 nM) and then infected with L. mono. (50 MOI). Serum-free media of cells were replaced after 2 h with complete media containing gentamicin. After 24 h cells
were subjected to RNA immunoprecipitation and quantified for SOCS1 and SOCS3 transcripts. (F, G) Quantification of the fold changes by qRT-PCR analysis in the
relative abundances of SOCS1 and SOCS3 after infection of (F) L. mono. (50 MOI) and (G) UPEC (50 MOI) for 24 h in HeLa cells prior to transfected with miR-30e
or miR-NC1 as indicated. Data are mean +/- SEM of triplicate samples from single experiment and

Scientific Articles #3

Frontiers in Immunology | www.frontiersin.

Edited by:
Michael R. Yeaman,

University of California, Los Angeles,
United States

Reviewed by:
Liana Chan,

Lundquist Institute for Biomedical
Innovation, United States

N. Alejandra Saavedra-Avila,
Albert Einstein College of Medicine,

United States

*Correspondence:
Chyung-Ru Wang

chyung-ru-wang@northwestern.edu

Specialty section:
This article was submitted to

Microbial Immunology,
a section of the journal

Frontiers in Immunology

Received: 24 September 2020
Accepted: 22 October 2020

Published: 18 November 2020

Citation:
Genardi S, Visvabharathy L, Cao L,
Morgun E, Cui Y, Qi C, Chen Y-H,

Gapin L, Berdyshev E and Wang C-R
(2020) Type II Natural Killer T Cells
Contribute to Protection Against

Systemic Methicillin-Resistant
Staphylococcus aureus Infection.

Front. Immunol. 11:610010.
doi: 10.3389/fimmu.2020.610010

ORIGINAL RESEARCH
published: 18 November 2020

doi: 10.3389/fimmu.2020.610010

Type II Natural Killer T Cells
Contribute to Protection Against
Systemic Methicillin-Resistant
Staphylococcus aureus Infection
Samantha Genardi1, Lavanya Visvabharathy1, Liang Cao1, Eva Morgun1, Yongyong Cui1,
Chao Qi2, Yi-Hua Chen2, Laurent Gapin3, Evgeny Berdyshev4 and Chyung-Ru Wang1*

1 Department of Microbiology and Immunology, Northwestern University Feinberg School of Medicine, Chicago, IL, United
States, 2 Department of Pathology, Northwestern University Feinberg School of Medicine, Chicago, IL, United States,
3 Department of Immunology and Microbiology, University of Colorado School of Medicine, Aurora, CO, United States,
4 Department of Medicine, National Jewish Health, Denver, CO, United States

Methicillin-resistant Staphylococcus aureus (SA) bacteremia is responsible for over
10,000 deaths in the hospital setting each year. Both conventional CD4+ T cells and gd
T cells play protective roles in SA infection through secretion of IFN-g and IL-17. However,
the role of other unconventional T cells in SA infection is largely unknown. Natural killer T
(NKT) cells, a subset of innate-like T cells, are activated rapidly in response to a wide range
of self and microbial lipid antigens presented by MHC I-like molecule CD1d. NKT cells are
divided into two groups, invariant NKT (iNKT) and type II NKT cells, based on TCR usage.
Using mice lacking either iNKT cells or both types of NKT cells, we show that both NKT cell
subsets are activated after systemic SA infection and produce IFN-g in response to SA
antigen, however type II NKT cells are sufficient to control bacterial burden and
inflammatory infiltrate in infected organs. This protective capacity was specific for NKT
cells, as mice lacking mucosal associated invariant T (MAIT) cells, another innate-like T cell
subset, had no increased susceptibility to SA systemic infection. We identify polar lipid
species from SA that induce IFN-g production from type II NKT cells, which requires both
CD1d-TCR engagement and IL-12 production by antigen presenting cells. We also
demonstrate that a population of T cells enriched for type II NKT cells are increased in
PBMC of SA bacteremic patients compared to healthy controls. Therefore, type II NKT
cells perform effector functions that enhance control of SA infection prior to conventional T
cell activation and recognize SA-derived lipid antigens. As CD1d is highly conserved in
humans, these CD1d-restricted SA lipid antigens could be used in the design of next
generation SA vaccines targeting cell-mediated immunity.

Keywords: Staphylococcus aureus, natural killer T cells, CD1, lipid antigens, cytokine, knockout mice

org November 2020 | Volume 11 | Article 6100101

Genardi et al. CD1d-Restricted NKT Cells Protects From Infection

INTRODUCTION

Staphylococcus aureus (SA) is a leading cause of healthcare-
associated and community-acquired infection in the United
States. SA causes a range of infections in humans, including
skin and soft tissue infection (SSTI), pneumonia, endocarditis,
and bacteremia, which if left untreated, can lead to sepsis and
high levels of mortality (1). Despite the traditional thinking that
humoral immunity is the main driver of immune defense against
extracellular pathogens, T cells are now recognized as critical
players in protection against SA in multiple routes of infection, as
shown in humans and preclinical animal models. HIV patients
with decreased CD4+ T cell counts have increased susceptibility
to SA bacteremia (2, 3). Additionally, patients with hyper IgE
syndrome who have a STAT3 mutation resulting in an inability
to develop Th17 cells have increased susceptibility to SA skin and
pulmonary infections (4). In mouse models of infection, both
CD4+ T cells and gd T cells produce cytokines and protect against
SA. CD4+ memory T cells produce IFN-g upon secondary
peritonitis challenge and promote recruitment of macrophages
and clearance of SA (5). In the skin, gd T cell production of IL-
17A is necessary for neutrophil recruitment to sites of infection
and decreased bacterial burden (6). A recent study demonstrates
that clonotypic Vg6+Vd4+ T cells are the primary source of IL-
17-producing T cells which drive protection in mouse SA skin
infection (7).

While conventional CD4+ T cells and gd T cells have been
studied in SA infection, the role of other non-conventional T cell
subsets in SA infection is less explored. Natural killer T (NKT)
cells are innate resident T lymphocytes that are activated early in
response to infection, and rapidly secrete a wide range of
cytokines, depending on the nature of the stimuli (8). NKT
cells are restricted by the MHC class I-like molecule CD1d,
which presents lipid antigens rather than peptide antigens, and
can be divided into two groups based on TCR usage and lipid
antigen recognition (9, 10). Invariant (iNKT) cells recognize the
lipid agonist a-galactosylceramide (a-GalCer), which, when
loaded onto a CD1d tetramer, can be used to identify this
population in vivo (11–13). iNKT cells also recognize
glycosphingolipids from Sphingomonas species (14) and
glycoglycerol lipids from Streptococcus pneumoniae (S.
pneumoniae) and Borrelia burgdorferi (15). In mouse models
of S. pneumoniae and Borrelia burgdorferi infection, rapid
cytokine production by iNKT cells recruited innate immune
cells to the site of infection and contributed to bacterial clearance
(16, 17). While iNKT cells are the dominant NKT cell subset in
mice, they make up a minority of the NKT cell pool in humans,
with type II NKT cells being the dominant NKT cell subset (18).
Type II NKT cells express a more diverse TCR repertoire and
recognize a wide range of self and microbial lipid antigens. Due
to the lack of specific tools to identify this polyclonal population
in vivo, type II NKT cells have been understudied compared to
iNKT cells, though some studies have demonstrated an active
role for type II NKT cells during infection (19). In a mouse model
of SA sepsis, Cardell and colleagues showed that administration
of sulfatide, a self-lipid known to stimulate a subset of type II
NKT cells, protected mice from lethal SA systemic challenge (20).

Frontiers in Immunology | www.frontiersin.org 2

Type II NKT cells also recognize phosphatidylglycerol (PG),
cardiolipin, and phosphatidylinositol from Corynebacterium
glutamicum (C. glutamicum) and Mycobacterium tuberculosis
(Mtb), and PG from Listeria monocytogenes (L. monocytogenes)
(21, 22). Both subsets of NKT cells can have synergistic or
opposing actions in models of infection. In Trypanosoma cruzi
infection, type II NKT cells drove a proinflammatory phenotype
that increased parasite-induced mortality and decreased
generation of pathogen-specific antibodies, whereas iNKT cells
were anti-inflammatory and contributed to lowered mortality
(23). In contrast, both iNKT and type II NKT cells protected
mice from hepatitis B virus (HBV) infection, but their
mechanisms of action were different; type II NKT cells were
activated by CD1d-presented HBV modified lysophospholipids
while iNKT cells were activated indirectly by secreted IL-12 (24).
These studies highlight the differential role of NKT cell subsets in
response to various pathogens. However, the relative
contribution of NKT cell subsets to protective immunity
against SA infection has not been explored.

In this study, we determined whether iNKT or type II NKT
cells play dominant or synergistic roles during systemic
methicillin-resistant SA infection and whether these T cells
subsets can recognize antigens derived from SA that could be
used in the design of a subunit vaccine. Our data shows that both
NKT cell subsets are activated and expanded after SA infection.
However, only type II NKT cells are necessary for lowering
bacterial burden in SA infected liver and kidneys at early times
post-infection, mediated by IFN-g production to polar lipid
species derived from SA. This protective effect was unique for
type II NKT cells, as mice lacking MAIT cells, another innate-
like T cell subset that recognizes microbially derived vitamin B-
related metabolites (25, 26), had no significant increase in SA
bacterial burden. We also demonstrate that NKT-like cells, but
not MAIT cells, are elevated in the PBMC of patients with
systemic SA infection, demonstrating the relevance of our
findings to the human setting.

MATERIALS AND METHODS

Ethics Statement
This study was carried out in strict accordance with the
recommendations in the Guide for the Care and Use of
Laboratory Animals of the National Institutes of Health. The
protocol was approved by the Animal Care and Use Committee of
the Northwestern University (Protocol number: IS00001659). For
human blood collection, the protocol was approved by the
Northwestern Institutional Review Board (IRB #STU0001210512).

Mice
Wildtype C57BL/6 (B6) mice and MHC class II deficient (MHC-
II-/-) mice were obtained from The Jackson Laboratory (Bar
Harbor, ME). MyD88-/- mice were obtained from Mutant Mouse
Resource and Research Centers. Ja18(-10)-/- mice (hereafter
referred to as Ja18-/- mice) were generated on the B6
background in Dr. Laurent Gapin’s lab (University of

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Genardi et al. CD1d-Restricted NKT Cells Protects From Infection

Colorado) (27). We backcrossed these Ja18-/- mice to B6 mice in
our mouse colony to generate wild-type littermate controls.
CD1d-/- mice were generated in house and have been
backcrossed onto B6 background for at least 12 generations
(28). MR1-/- mice were provided by Dr. Ted Hansen
(Washington University) and backcrossed to B6 mice to
generate MR1+/+ littermate controls. Va3.2+Vb9+ CD1d-
autoreactive transgenic mice (24ab) were provided by Dr.
Suzanna Cardell (University of Gothenburg) (29). MHC-II-/-

CD1d-/- mice were generated by crossing CD1d-/- mice and
MHC-II-/- mice. Naïve mice were housed in a specific
pathogen-free facility.

S. aureus Bacteremia Model and Bacterial
Quantification
All data were obtained using the USA300 methicillin-resistant
SA clinical isolate strain, generously provided by Dr. Nancy
Freitag (University of Illinois at Chicago). Briefly, SA was grown
up overnight in tryptic soy broth (MP Biomedicals, Solon, OH)
at 37°C, 220 rpm, diluted 1:100 the next day, and grown to mid-
log phase. Bacteria were wash, resuspended, and inoculated via
tail vein with 2×106 or 1×107 CFU USA300 in PBS. For colony
forming unit (CFU) quantification, whole liver, kidney, or spleen
were homogenized in PBS by sonication, raised to a volume of
10 ml with PBS, and plated in serial dilutions on tryptic soy agar
containing 5 µg/ml erythromycin.

Histology Imaging
Hematoxylin and Eosin (H&E) staining of SA-infected kidneys
were performed by the Northwestern mouse histology and
phenotyping core. H&E slides were imaged using the
TissueGnostics Imaging System and inflammatory foci were
quantified using Tissue/HistoQuest software. Two sections
from each kidney of each mouse were quantified and the
average inflammatory foci for each mouse was calculated and
recorded as one data point.

S. aureus Lipid Isolation and Fractionation
SA lipid isolation and fractionation were performed as described
previously (30). Briefly, bacterial pellet from the overnight
culture of USA300 was treated with lysostaphin to lyse the
peptidoglycan cell wall and release protoplasts. Total lipid was
extracted from protoplasts using a modified Bligh-Dyer
extraction method (31) and was fractionated using silica gel
column chromatography and a chloroform-methanol gradient.
Dominant lipid fractions were identified using thin layer
chromatography, as previously described (30), and listed in
Figure 6A.

Mouse Cell Preparation and Lipid Pulsing
Mouse leukocyte single cell suspensions were isolated from
lymph node (LN), liver, spleen, and kidney of naïve and
infected mice. Lymphocytes were isolated from kidneys and
livers using a 37.5% Percoll gradient centrifugation. For
ELISPOT total fraction screening experiments (Figure 5B)
single cell suspensions of Ja18-/- liver were enriched for CD8-

T cells (as type II NKT cells are either CD4+ of DN) by magnetic-

Frontiers in Immunology | www.frontiersin.org 3

activated cell sorting (MACS) negative selection (Miltenyi
Biotec), using biotinylated CD8a/b, B220, MHCII, ter119,
Ly6G, and anti-biotin beads. For FR-8 ELISPOT and adoptive
transfer experiments, we included additional mAb specific to
TCRgd and CD11b in the negative selection cocktail to further
enriched for type II NKT cells. BMDCs were derived from mouse
bone marrow progenitors in complete RPMI (cRPMI)
supplemented with 10 ng/ml GM-CSF (PeproTech, 315–03)
and 2 ng/ml IL-4 (PeproTech, 214–14). Mature BMDCs were
pulsed with 10 µg/ml of total SA lipids (SAlip) or lipid fractions
overnight. Total SA lipids and lipid fractions were prepared by
drying down eluent buffer and resuspending at the appropriate
concentration in cRPMI. All lipids were sonicated for 15 min in a
water bath sonicator before pulsing.

Human Sample Acquisition and Processing
PBMC were acquired through the Northwestern Memorial
Hospital. The inclusion criteria for infected patients was as
follows: patients with confirmed SA bacteremia (by at least one
blood culture where blood has been collected by use of aseptic
technique), patients who were inpatients at NMH at the time of
study collection, patients over the age of 18, and patients able to
give consent for blood collection. The exclusion criteria were as
follows: pregnant individuals, mixed bacteremic patients, patients
with known active infections with blood-borne viruses (including
human immunodeficiency virus Ab/Ag positive, hepatitis C RNA
positive, hepatitis B sAg positive, and SARS-CoV-2 RNA positive
individuals), patients with active malignancies (including
hematologic and solid organ malignancies), solid organ transplant
recipients, patients with steroid treatment for at least 1 month (>30
mg/day), and patients on cytotoxic immunosuppressive therapy
(including calcineurin inhibitors, e.g. cyclosporine, tacrolimus,
antiproliferative agents, e.g. azathioprine, cyclophosphamide,
methotrexate, chlorambucil, mycophenylate mofetil, and immune-
active monoclonal antibodies, e.g. adalimumab, alemtuzumab,
belimumab, golimumab, infliximab, muromonab-CD3,
natalizumab, ofatumumab, rituximab, tocilizumab, tocitumomab).
Patient demographics for consented individuals is as follows: N=9
healthy controls (21) (5 males, 4 females), N=7 SA bacteremic
patients (SA) (four males, three females). The median age of HC
was 31 ± 3.46 and the median age of SA was 60 ± 16.21. Of the SA
patients, 1 had MRSA and 6 had MSSA. Each infected sample
collected was paired with healthy donor blood for side by side
processing and downstream assays. PBMC were isolated from
whole blood within 48 h of original blood draw using
Histopaque-1077 (Sigma-Aldrich). Leukocytes were collected at
the serum, cell interface and washed 3x before counting cells with
a hemocytometer and performing surface staining.

Reagents and Antibodies
Mouse and human CD1d tetramer (TET+) unloaded or loaded
with a-galactosylceramide (a-GalCer) analog PBS57 and human
MR1 tetramer (TET+) loaded with 6-FP (control) or 5-OP-RU
were provided by NIH tetramer facility. Fluorochrome-
conjugated antibodies against mouse CD3, CD4, CD8a, CD69,
NK1.1, TCRb, Ly6G, CD11b, B220, CD11c, Ly6C, F4-80, IFN-g,

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Genardi et al. CD1d-Restricted NKT Cells Protects From Infection

IL-17A, Vb2, Vb7, and Vb12 and human CD3, CD4, CD8a,
Va7.2, CD161, CD14, and CD19 were purchased from
BioLegend. Vb4, Vb5.1/5.2, Vb6, Vb8.1/8.2, Vb9, Vb11, and
Vb13 were purchased from BD. Anti-Vb10 was purchased from
eBioscience. Live dead eFlour506 was purchased from Thermo
Fischer Scientific.

Flow Cytometry
Single cell suspensions were incubated with purified 2.4G2 mAb
or human Fc block (BD Biosciences) then stained with specific
antibodies. For intracellular staining experiments, cells were
stimulated with 50 ng/ml phorbol 12-myristate 13-acetate (32)
(Enzo Life Sciences, BML-PE160-0005) and 0.5 µg/ml
Ionomycin (Sigma, I9657-5MG) for 2 h followed by 4 h of
brefeldin A (BioLegend, 420601) stimulation. Following
stimulation, cells were surface stained, then fixed overnight
with 0.5% paraformaldehyde (Sigma, 158127-3KG). The next
day, cells were permeabilized with 0.05% saponin (Sigma,
S7900), then intracellularly stained with anti-cytokine
antibodies. Flow cytometry was performed on a FACSCanto II
(BD Biosciences) and data analysis was performed with FlowJo
Software version 10 (Tree Star, Inc.).

Cytokine Secretion Assays
Enzyme-linked immunosorbant assay (ELISA) was performed to
detect IFN-g or IL-17A cytokine secretion. Cytometric bead
assay (CBA) was performed to detect IL-4, IL-6, IL-10, IL-13,
IL-23, TNF-a, and GM-CSF cytokine secretion. Single cell
suspensions of liver or spleen were incubated with a-GalCer
(200 ng/ml) or heat-killed SA (HKSA) (106 CFU) for 48 h, then
supernatant was collected for ELISA or CBA. For ELISPOT
assay, Multiscreen-IP plates (Millipore) were coated with 10 µg/
ml mouse anti-IFN-g or anti-IL-17A overnight in PBS, then
blocked with cRPMI. Total liver lymphocytes or T cell enriched
liver lymphocytes were cultured with total SA lipid or SA lipid
fraction-pulsed BMDCs for 18-20 h before assay development,
detailed assay protocol published previously (33). Developed
ELISPOT plates were imaged using an ImmunoSpot reader
(Cellular Technology Ltd.).

RNA Isolation and Real-Time PCR
T cells were enriched from Ja18-/- mouse liver or spleen
lymphocytes using MACS negative selection as previously
described. Type II NKT cells were sorted from pooled enriched
T cells using a BD FacsAria. RNA was extracted from sorted cells
using RNA-easy kit (QIAGEN) and cDNA was generated using
Superscript II reverse transcriptase (Invitrogen). RT-PCR was
performed using SYBR Green PCR master mix with cytokine
primers (listed in Supplementary Table 1) and MyiQ real-time
detection system (Bio-Rad). PCR were run in duplicate and
cytokine values were normalized to b-actin as housekeeping gene.

Adoptive Transfer of Type II NKT Cells
Recipient mice (CD45.1+ mice) were irradiated with 900 rads of
cesium 1 day prior to adoptive transfer. Splenocytes from
CD45.2+24ab Tg mice were enriched for T cells as previously

Frontiers in Immunology | www.frontiersin.org 4

described above. 5×106 cells were transferred to recipient
mice. 1 day after adoptive transfer, recipient mice were infected
via tail vein with 2×106 CFU of SA. Mice were euthanized at
2 dpi and organs were isolated for CFU quantification and
intracellular staining.

Statistical Analysis
All statistical analyses were performed using GraphPad Prism
software. Unpaired Student’s t test was used for comparison of
two groups, one-way ANOVA was used for comparison of
more than two groups, and two-way ANOVA was used for
comparison of more than two groups and two variables. For CFU
quantification statistics, Mann-Whitney test was used. Values are
represented as mean + SEM. Statistical significance is denoted by
the annotation: *p<0.05; **p<0.01; ***p<0.001; ****p<0.0001.

RESULTS

Mice Lacking NKT Cells but Not MAIT
Cells Had Increased Bacterial Burden and
Neutrophil Infiltration in Infected Liver and
Kidneys Following Systemic SA Infection
Given that NKT cells have been shown to play a protective role in
the early response to many bacterial infections, we sought to
determine whether NKT cells were important for controlling
bacterial growth in infected organs after bloodstream challenge
with MRSA strain USA300 LAC, an isolate that frequently causes
community-acquired skin and soft-tissue infections as well as
systemic infections (34). To investigate this, we used C57BL/6
mice (B6) and CD1d-/- mice in the B6 background; CD1d-/- mice
do not develop NKT cells due to absence of CD1d expression on
double-positive thymocytes, which is required for NKT cell
positive selection in vivo (28). Once SA enters the bloodstream
of mice after infection, its characteristic route of progression
through the body is to first be absorbed by liver Kupffer cells
within 24 h post infection, then over a period of 2–5 days lyse
Kupffer cells and migrate to the kidneys, where it establishes
abscesses (35, 36). We thus quantified bacteria in the liver and
kidney of SA-infected mice at various times post infection.
CD1d-/- mice had increased bacterial burden in the liver and
kidney compared to B6 mice at 4 days post infection (dpi),
though both groups had equivalent burdens by 8 dpi (Figures
1A, B), which suggested that NKT cells were necessary for early
control of bacterial growth. This effect was more profound in the
liver, where NKT cells were enriched, compared to the kidney.
We also compared control of SA systemic infection by NKT cells
to another subset of innate-like T cells, mucosal associated
invariant T (MAIT) cells, which were activated by vitamin B
metabolites present in various bacteria, including SA (37). In
contrast to NKT cells, mice lacking MAIT cells (MR1-/-) had no
discernable difference in bacterial burden in the liver or kidney
compared to wild-type littermate controls (MR1+/+) at various
timepoints (Figures 1C, D), highlighting a unique role of NKT
cells in the early control of SA infection. In addition, we

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Genardi et al. CD1d-Restricted NKT Cells Protects From Infection

characterized immune infiltrates in infected kidneys and liver by
flow cytometry and identified that neutrophils were increased in
the kidneys and liver of CD1d-/- mice relative to B6 mice
(Figures 1E, F). No significant difference in total number of B
cells, macrophages, dendritic cells, and conventional T cells
(CD4+ and CD8+) in the infected liver and kidney were
detected between these two groups (Supplementary Figures 1
and 2). This data suggested that NKT cells, but not MAIT cells,
were critical at early stages of infection to control SA growth and
neutrophil infiltration in infected liver and kidneys.

Type II NKT Cells Were Sufficient to
Reduce Bacterial Burden in Infected Liver
and Kidneys of Mice Challenged With
Sublethal Dose of SA
To determine whether type II NKT cells were sufficient to reduce
SA bacterial burden, we added the Ja18-/- mouse strain which
contains a 10 base pair deletion in the Traj18 gene and therefore
do not develop Va14-Ja18 expressing iNKT cells, but retained
the ability to develop type II NKT cells (27). These mice are an
improved version of the original Ja18-/- mice, which have lower
TCR diversity due to suppressed transcription of TRAJ gene
segments upstream of Traj18 (38). To date, a mouse model
lacking type II NKT cells but retaining iNKT cells does not exist,

Frontiers in Immunology | www.frontiersin.org 5

therefore we could not test the efficacy of iNKT cells alone in
control of bacterial burdens. B6 (expressing iNKT and II NKT
cells) and Ja18-/- mice (expressing only type II NKT cells) had
similar bacterial burdens in the liver and kidney at all timepoints
tested post infection, while CD1d-/- mice (lacking both NKT cell
subsets) again had significantly increased bacterial burdens in the
liver and kidney at 4 dpi (Figures 2A, B), which suggested that
type II NKT cells were sufficient to control SA growth in the
absence of iNKT cells at this early timepoint. We also assessed
pathology of inflammatory foci and abscess formation in the
kidney at 4 dpi by H&E staining (Figures 2C, D). Compared to
B6 and Ja18-/- mice, where inflammatory foci (marked with
arrow heads) were predominantly found in the renal pelvis,
CD1d-/- mice had significantly larger inflammatory foci found in
all areas of the kidneys (Figures 2C, D, and Supplementary
Figure 3). We then determined what cytokines were being
induced after SA infection and whether this pattern was
altered in mice lacking NKT cells, focusing on the liver and
spleen where NKT cells are readily detectable. Liver and spleen
lymphocytes from SA-infected CD1d-/- mice produced less IFN-
g in response to in vitro restimulation with heat-killed SA
(HKSA) compared to infected B6 and Ja18-/- mice at 4 dpi
(Figures 2E, F). In the liver, iNKT cells were partially responsible
for the CD1d-dependent IFN-g response to HKSA, as Ja18-/-

liver lymphocytes exhibited intermediate levels of IFN-g

A B

D

E F

C

FIGURE 1 | Mice lacking NKT cells have increased bacterial burdens and neutrophilic infiltrate in SA infected organs. (A, B) Colony forming units (CFU) quantified in
liver (A) and kidneys (B) of B6 and CD1d-/- mice at various times post infection (N=6–8 mice/genotype/timepoint). (C, D) CFU quantified in liver (C) and kidneys (D) of
MR1+/+ and MR1-/- mice at various times post infection (N=4-7 mice/genotype/timepoint). (E, F) Total number of neutrophils in the liver (E) and kidney (F) of infected
mice (liver: N=3 naïve, N=14 4 dpi/genotype, kidney: N=4 naïve, N=11-12 4 dpi/genotype). Statistical analysis: (A–D) Mann-Whitney test; (E, F) 2-way ANOVA.

November 2020 | Volume 11 | Article 610010

Genardi et al. CD1d-Restricted NKT Cells Protects From Infection

production between B6 and CD1d-/- mice (Figure 2E). However,
type II NKT cells were sufficient for CD1d-dependent IFN-g
production in the absence of iNKT cells in the spleen (Figure
2F). Together, this data suggested that type II NKT cells were
sufficient to reduce bacterial burden and kidney inflammatory
infiltrate while enhancing IFN-g production in the early stages of
SA infection.

NKT Cells Were Activated and Underwent
Expansion and Proliferation After SA
Infection
After showing that mice lacking NKT cells had elevated SA
bacterial burden in liver and kidneys, we then determined
whether type II NKT cells became activated and expanded
during SA infection compared to iNKT cells. We used a CD1d
tetramer loaded with PBS57, an a-GalCer analog, to identify

Frontiers in Immunology | www.frontiersin.org 6

iNKT cells in vivo (Supplementary Figure 4A). Since we did not
have specific tetramers to identify type II NKT cells in vivo, we
used a negative gating strategy to remove iNKT cells and CD8+ T
cells, then gated on CD4+NK1.1+TCRb+ cells, which allowed us
to look at polyclonal type II NKT cells (Supplementary Figure
4B). Both iNKT and type II NKT cells expanded in the liver of
SA-infected B6 and Ja18-/- mice (Figures 3A, B) at 4 dpi, then
contracted by 8 dpi. An increased number of iNKT cells was also
detected in the kidney, but not pooled peripheral and kidney
draining LN, at 4 dpi (Supplementary Figures 5B, E). We
confirmed our gating strategy for type II NKT cells using
CD1d-/- mice; most of the TET-CD8a-CD4+NK1.1+TCRb+

cells were CD1d-restricted as the

Scientific Articles #3

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There are a total of five articles, but you only must choose one article to critique. Due date 05/07/2022.