Glycative Stress Research
Online edition : ISSN 2188-3610
Print edition : ISSN 2188-3602
Received : December 13, 2021
Accepted : December 21, 2021
Published online : December 31, 2021
doi:10.24659/gsr.8.4_183

Original article

Postprandial induction of neutrophil extracellular trap formation in the blood
Yu Oshima *, Mariko Tanaka *, Nontaphat Leerach, Ai Harashima, Seiichi Munesue, Kumi Kimura,Hisanori Goto, Kenjiro Hayashi, Akane Niimura, Yasuhiko Yamamoto
Department of Biochemistry and Molecular Vascular Biology, Kanazawa University Graduate School of
Medical Sciences, Kanazawa, Japan.

*Oshima Y and Tanaka M equally contributed to this work.

Abstract

Aims: Neutrophils play a key role in infection control via two main mechanisms: phagocytosis and neutrophil extracellular
trap (NET) release. Despite their role in infection, NETs can also promote cancer growth and metastasis, inflammatory
diseases, and vascular thrombosis. However, the relationship between NET formation and the diet, which are critical factors
in the progression of metabolic syndrome, remains unclear. In this study, we examined whether blood NET formation isincreased after food intake and sought to identify the dietary components that trigger NET formation.
Methods: Using flow cytometry, we analysed NET formation in the blood of mice fed with four different nutritional diets:
normal moderate-fat diet (MF), high-fat diet (HF), high-fat and cholesterol diet (HFHC), and dietary fiber Bacto Agar (BA).
Results: The highest NET formation was found in HF-fed mice, while no increase was found in BA-fed mice. Moreover, weobserved peaks in NET formation ~ 2 h and 6 –24 h after meal consumption. NET formation was abolished after intestinalbacteria were depleted by antibiotic treatment, even when the mice were fed the HF meal. Furthermore, we observed NETformation in human peripheral blood 6 h after meal consumption.
Conclusions: These findings suggest that NET formation in peripheral blood may be induced after intake of a high-fat
diet, and that this phenomenon is closely associated with the gut microbiota. Further investigations are warranted to unveil
the involvement of food components, the gut microbiota, and blood NET formation in the pathogenesis of lifestyle-relateddiseases.

KEY WORDS: neutrophil extracellular traps, food intake, gut microbiota

Introduction

Neutrophils are a type of granulocyte and account for
45 –75 % of the total leukocytes in human peripheral blood.
They have a strong phagocytic capacity and protect the bodyagainst bacterial or fungal infections 1). Neutrophils migrate
to the infection site during an initial immune response andphagocytose pathogens. Then, the phagosomes are fusedwith lysosomes, forming mature phagolysosomes with fulldegradative and microbicidal capacity, and the pathogens
are killed. Other responses include the formation of reactive
oxygen species (ROS) and hydrogen peroxide, which areproduced by nicotinamide adenine dinucleotide phosphate(NADPH) oxidase and myeloperoxidase (MPO), respectively 2).
Moreover, neutrophils release DNA extracellularly in responseto stimuli to capture pathogens; the structures are called“neutrophil extracellular traps (NETs)” 3), and this uniqueand aggressive mechanism of cell death is known as“ NETosis,” which is neither apoptosis nor necrosis 4). NETs
contain histones, non-histone proteins, lysozyme, MPO, andneutrophil esterase, all of which contribute to host defense 5).
During the formation of NETs, the collapse of the nuclear
membrane occurs after citrullination of histone modification,

Correspondence to Yasuhiko Yamamoto, MD, PhD.
Department of Biochemistry and Molecular Vascular Biology,
Kanazawa University Graduate School of Medical Sciences.
13 -1 Takara-machi, Kanazawa 920 -8640, Japan
TEL: +81-76-265- 2181 FAX: +81-76 -234 - 4217 e-mail: yasuyama@med.kanazawa-u.ac.jp
Co-authors: Oshima Y, cantabile.6102@gmail.com; Tanaka M, plaplastichq@med.kanazawa-u.ac.jp;
Leerach N, nleerach@gmail.com; Harashima A, aharashima@staff.kanazawa-u.ac.jp;
Munesue S, smunesue@med.kanazawa-u.ac.jp; Kimura K, kukimura@staff.kanazawa-u.ac.jp;
Goto H, pitanori19890838@gmail.com; Hayashi K, ke. hayashi@po.nippon-shinyaku.co.jp;
Niimura A, imymemine@stu.kanazawa-u.ac.jp_ 18 3 _Glycative Stress Research 2021; 8 (4 ) : 183-189(c) Society for Glycative Stress ResearchPostprandial NET Formation in the Blood

which weakens the association between histones and DNA
and makes the chromatin filamentous through the action of
peptidylarginine deiminase (PAD), a deiminization enzymeof histone arginine residues, in the presence of Ca 2+ 6). NETformation is induced by phorbol myristate acetate (PMA),
lipopolysaccharide (LPS), and interleukin (IL)- 8 7).
NETs are also related to the development of various
diseases, including cancer growth and metastasis 8),
autoimmune diseases 9), and thrombosis 10). Nevertheless,reduced NET formation is linked to compromised conditions
and chronic granulomatosis 10). To date, it remains unclear
whether NET formation can be induced under physiologicaland healthy conditions in response to daily food intake,drinking, defecation, physical exercise, and mental stress.
In this study, we investigated whether NET formationin the blood is increased after food consumption, which
is closely associated with the development of metabolic
syndrome. If NET formation is indeed induced by mealintake, the dietary contents that trigger NET formation willneed to be identified. Here, we propose a novel concept forthe prevention and treatment of inflammatory responses inmetabolic syndrome, which consists in controlling the gut
microbiota and diet.

Materials and Methods
Animals

Male C57BL /6J mice (6 –18 -week- old; Charles River,
Yokohama, Japan) were used and kept individually (onemouse per cage) in usual stainless cages. The mice were fed
a normal moderate-fat diet (MF) (Oriental Yeast Co., Tokyo,
Japan) and provided water to drink ad libitum before theexperiments. The experimental diets used in the study wereas follows: MF (Oriental Yeast Co.; 359 kcal/100 g; protein
23.1%, fat 5.1%), high-fat diet (HF, D12492, Research Diets,
New Brunswick, NJ; 524 kcal/100 g; protein 26 %, fat 35 %gm %), dietary fiber Bacto Agar (BA, BD Sciences, Franklin
Lakes, NJ; 0 kcal/100 g, protein 0 %, fat 0 %), high-fat andhigh-cholesterol diet (HFHC, D09100301, Research Diets;
449 kcal/100 g; protein 22.5 %, fat 4 4.9 %, and 22.5 %cholesterol gm %). For gut microbiota disruption, the mice
were treated with ampicillin (1.0g/L, Nacalai Tesque, Kyoto,
Japan) and neomycin sulfate (1.0 g/L, Nacalai Tesque) for
2 weeks. Peripheral blood was collected from the tail veinof mice and mixed with 5 mM ethylenediaminetetraacetic
acid (EDTA). All animal experiments were approved by
the Committee on Animal Experimentation of Kanazawa
University and performed in accordance with the Fundamental
Guidelines for Proper Conduct of Animal Experiment andRelated Activities in Academic Research Institutions under
the jurisdiction of the Ministry of Education, Culture,
Sports, Science and Technology of Japan.

Human samples
Blood samples were collected from healthy volunteers(24 – 47 years old, two males and two females) using avacuum blood collection tube containing EDTA (Terumo
venoject II, Terumo, Tokyo). Blood was collected 12 h after
fasting; then, the volunteers were given a meal (one rice balland one fried chicken). The study complied with the ethicalprinciples set forth in the Helsinki Declaration and Japan's
Personal Information Protection Act, and was conducted inaccordance with the Ethical Guidelines for Medical Research
Involving Human Subjects (Public Notice of Ministry of
Education, Culture, Sports, Science and Technology/Ministryof Health, Labor and Welfare). The experimental plan wasapproved by the ethics committee of Kanazawa University.
Informed consent was obtained from subjects prior to thetests, and the subjects sufficiently understood the content of
the testing plan and voluntarily expressed their willingness
to participate in the test.

Flow cytometry
To prevent non-specific signals, purified rat anti-mouse
CD16/CD32 (Mouse BD Fc Block) (1:100, BD Biosciences)
was added to 10 µL of EDTA-treated blood, and the mixture
was allowed to settle at room temperature (RT) for 15 min in
the dark. For the analysis of mouse samples, PE anti-mouse
Ly6G/ Ly6c (Gr -1) antibody (1:100, BioLegend, San Diego,CA), anti-histone H3 (citrulline R2 + R8 + R17 ) antibody(1: 50, Abcam), and FITC (fluorescein isothiocyanate) goatanti-rabbit IgG (1:100, BD Biosciences) were added andincubated at RT for 20 min. The samples were then treatedwith BD FACS Lysing Solution (BD Biosciences), washedwith phosphate buffered saline (PBS)/2 % fetal bovine serum(FBS), and analyzed using a flow cytometer (BD FACS
Aria Fusion), as described previously 11). For human samples,
CD45 monoclonal antibody (HI30) APC-eFluor 780 (1:100,
eBioscience, San Diego, CA), anti-histone H3 (citrulline
R2 + R8 + R17) antibody (1: 50, Abcam, Cambridge, UK),
and FITC goat anti-rabbit IgG (1:100, BD Biosciences)were used. The obtained data were re-analyzed using FlowJov 9. 9. 5 software (FlowJo, Ashland, OR) 11). Unstained, single
stains, and fluorescence minus one (FMO) controls wereused to set compensation and gates.

Giemsa Staining
The smear was covered with absolute methyl alcoholfor 5 min (ﬁxation). The alcohol was drained off, and theslide was covered with freshly diluted Giemsa stain solution( Wako Pure Chemical Industries, Osaka, Japan) for 20 min.
After washing with water and drying, the slides were enclosedwith Entellan ® new and observed under an optical microscope.

Stool DNA extraction and polymerase chain
reaction (PCR)

Fresh mouse stool samples were collected in 1. 5 ml
tubes. The samples were heated at 95 °C for 30 min in a 50
mM NaOH solution (300 µL). Then, 1.0 M Tris-HCl (pH7.0) (100 µL) was added, the tubes were centrifuged at
15,000 rpm for 10 min, and DNA was extracted. To semiquantify the number of intestinal bacteria, PCR targeting
16S rDNA was performed using 16S rDNA forward(5’- AGAGT T TGAT CCTG G C T CAG - 3’ ) and reverse(5’- G G T TAC C T T GT TAC GAC T T-3’) primers (35cycles; 98 °C for 10 s, 53 °C for 20 s, and 72 °C for 60 s). The
PCR products were separated by agarose gel electrophoresisand detected by ethidium bromide staining.

_ 18 4 _Glycative Stress Research

Statistical analysis
Results are presented as means ± SEM (standard errormean). Comparisons between groups were assessed using
Student’s t-test or one way analysis of variance (ANOVA)
combined with Scheffe’s multiple comparison test ( p < 0.05).

Results

Flow cytometric detection of NET formation inmouse blood

We performed flow cytometric analyses to detect NET
formation in mouse blood, as described previously 11). The
cluster of granulocytes was gated using forward versus side
scatter (FSC vs. SSC), and the single cell population was
fractioned for further analysis ( Fig. 1). Subsequently, Gr1-positive and citrullinated histone H3 (CitH3)- positive
neutrophils were determined to be NET-forming cells(Fig. 1). We first examined the appearance rates (%) of NET
cells in total Gr-1-positive neutrophils from mice fed astandard chow diet (MF). At fasting, the basal rate was 1.42
± 0.47 % ( Fig. 2-a ). Then, a first peak (6.41 ± 2.02 %) was
observed 2 h after consumption of the MF meal ( Fig. 2-a ).
In addition, a second peak and plateau were observed 6 – 24
h after the meal (14.41 ± 4.63 % at 24 h) ( Fig. 2-a). Next,
we examined the effect of different types of meals. The HF

The gut microbiota is associated with NET
formation in the blood
To examine the association of diet-induced NETformation with the gut microbiota, we treated mice with
ampicillin natrium (1.0 g/L) and neomycin sulfate (1.0 g/L)
orally for 2 weeks to disturb their gut microbiota. Afterconfirming the effects of the antibiotics by PCR analysisof the 16S rDNA in stools, we selected mice with reduced
numbers of gut bacteria and fed them with HF (Fig. 3-a).
FACS analysis clearly demonstrated that the NET appearance
rates in the blood were dramatically reduced in the mice
during the observation period, including at the 0 h baseline(Fig. 3-b).
1000

18.1

800

800

600

600

FSC-W

SSC-A

1000

meal (35 % fat, containing lard) increased the rate of NET
formation to 10. 55 ± 4.13 % and 29.01 ± 5.30 % at 2 and12 h postmeal, respectively (Fig. 2-b). The HFHC meal (44.9 %
fat, containing cocoa butter and 22.5% cholesterol) induced
two peaks of NET formation, 6.75 ± 2.66 % and 8.80 ±4.60 % at 2 and 6 h postmeal, respectively (Fig. 2-c). The
group fed the BA meal (0 kcal /100 g, protein 0 %, fat 0 %),which was used as a dietary control meal, showed a slightincrease in the rate of NET cells 2 h after meal ingestion.
However, the increase was not statistically significant and
NET formation decreased thereafter (Fig. 2-d ). The largest
increase was observed in the HF group (Fig. 2).

400

400
200

200
0

99.5

0

200

400

600

800

0

1000

0

200

FSC-A
1000

68

800

800

600

600

SSC-A

SSC-A

600

800

1000

FSC-A

1000

400
200
0
10 0

400

NETs

400
200

10 1

10 2

10 3

0
10 0

10 4

Gr -1

10 1

10 2

10 3

10 4

CitH3

Fig. 1. Flow cytometry.

NETs were detected in mouse peripheral blood using PE anti-mouse Ly6G/ Ly6c (Gr-1) antibody, anti-histone H3 (citrulline
R2 + R8 + R17) antibody, and FITC goat anti-rabbit IgG by flow cytometry. CitH3, citrullinated histone H3; NETs, neutrophil
extracellular traps; FITC, fluorescein isothiocyanate; SSC, side scatter; FSC, forward scatter.

_ 18 5 _Postprandial NET Formation in the Blood

40

25
20
15

30
25
20
15
10

5

5
0 1 2 3

6

40

12

0

24 ( h)d)

HFHC

0 1 2 3612

24 ( h)612Antibiotics

24 ( h)

40

BA

35
30

NETs (%)

25
20
15

25
20
15

10

10

5

5
6

12

0

100 bp ladder0 1 2 324 ( h)0 1 2 3−

1 diets.
2 1 2 3 4 5 6 7 8 9 10
Fig. 2. The formation of NETs in the blood from mice fed different chow

E.coli

30

0

HF

35

10

35

NETs (%)

40

NETs (%)

30

0

c)

b)

MF

35

1 kbp ladder

NETs (%)a)

The appearance rates (%) of NET cells in total Gr-1-positive neutrophils from mice fed a standard chow diet (MF, n = 14)(a), high fat diet (HF, n = 14) (b), high fat and high cholesterol diet (HFHC, n = 13) (c), dietary fiber Bacto Agar (BA, n =9) (d). We observed the NET formation from 0 (fasting) to 24 hours after feeding. Data represent mean ± SEM. * p < 0.05 vsbasal level (0 hour). NETs, neutrophil extracellular traps; SEM, standard error mean.

b)

1 2 1 2 3 4 5 6 7 8 9 10

HF

35

NETs (%)−

40

Antibiotics

E.coli1 kbp ladder

100 bp laddera)← 16s rDNA

30

Antibiotics（ - ）

25

20
15

10
5
0

Antibiotics（ + ）0 1 2 3

6

12

24

(h)

Fig. 3. The gut microbiota and NET formation in the mouse blood.
(a) PCR analyses for 16S rDNA. Mice were treated with or without antibiotics (1.0 g/L ampicillin sodium and 1.0 g/L neomycin sulfate in
the drinking water) for 2 weeks. Without antibiotics, Antibiotic (−); with antibiotics, Antibiotic (+). (b) The appearance rates (%) of NET
40

HF

cells in total Gr-1-positive neutrophils from mice fed a high fat diet (HF) with or without antibiotics in the drinking water. Antibiotic (+), nNETs (%)

35 = 10; Antibiotic (−), n = 14. Data represent mean ± SEM. * p < 0.05 between Antibiotic (+) and Antibiotic (−). NET, neutrophil extracellular

30 trap; PCR, polymerase chain reaction; SEM, standard error mean.

Antibiotics（ - ）

25

20
15

10
5
0

Antibiotics（ + ）0 1 2 3

6

12

24

(h)

_ 18 6 _← 16s rDGlycative Stress Research

Flow cytometric detection of NET formation inhuman blood
We next investigated the formation of postprandial
NETs in human blood. NETs were defined as CD45and CitH3-positive granulocytes in the peripheral blood( Fig. 4-a). After fasting for 12 h, a meal (fried chicken
and rice with tuna mayonnaise) was given to four healthy
volunteers (24 – 47 years old, two males and two females).

a)

250K

Flow cytometry analyses revealed that the NET appearance
rate in the blood was higher 6 h after meal intake ( 2.48 ±0.98 %) than at fasting (0.78 ± 0.05 % at 0 h); however, thedifference was not statistically significant (Fig. 4-b). Next,
we conducted morphological observations of NET formationin human peripheral blood. We used blood smear samples
collected 6 h after meal ingestion and performed Giemsa
staining. As seen in Fig. 5-b, we detected neutrophils with
nuclei released outside the cell membrane in the blood.

250K

29.1

150K
100K

FSC-W

200K

FSC-W

SSC-A

SSC-A

200K

50K
0

98.8

150K
100K
50K

0

50K

100K

150K

200K

0

250K

0

50K

FSC-A

200K

250K

250K

95.4

200K

150K

150K

100K
50K

SSC-A

200K

SSC

SSC-A

SSC-A

150K

FSC-A

250K

NETs

100K
50K

0

0 10 2

10 3

10 4

0

10 5

CD45

b)

100K

4.0

0 10 2

10 3

10 4

10 5

CitH3

p = 0.0671

3.5

NETs (%)

3.0
2.5
2.0
1.5
1.0
0.5
0

0

3

6 (h)

Fig. 4. The formation of NETs in the human blood.
(a) Gating strategy. NETs were detected in human peripheral blood using CD45 monoclonal antibody APC-eFluor780, anti-histone
H 3 (citrulline R2+R8+R17) antibody, and FITC goat anti-rabbit IgG by flow cytometry. (b) The appearance rates (%) of NET cells
in CD45-positive granulocytes from healthy subjects (n = 4). Data represent mean ± SEM. CitH3, citrullinated histone H3; NETs,
neutrophil extracellular traps; FITC, fluorescein isothiocyanate; SSC, side scatter; FSC, forward scatter; SEM, standard error mean.

_ 18 7 _Postprandial NET Formation in the Bloodb)a)Fig. 5. Morphological observation of NETs in human blood.
Giemsa staining. (a) Normal neutrophils and (b) neutrophils showing neutrophil extracellular traps (NETs).

Discussion
NETosis is a newly discovered type of aggressive
neutrophil cell death that is different from apoptosis andnecrosis. NET formation during NETosis allows the releaseof nuclear substances outside the cells 12, 13). NETs, which arecomposed of a network of fibers assembled from chromatin
DNA, histones, non-histones, and neutrophil granule proteins,can kill pathogens; however, they can also exhibit toxic
actions in the host. For example, activated neutrophils with
NET formation enhance autoimmune responses related toa wide range of inflammatory autoimmune diseases by
exposing autoantigens in susceptible individuals. Several
studies have recently shown that NETs play a pivotal rolein the development of sterile inflammation under several
chronic inflammatory conditions 14). Sterile inflammation
occurs in the absence of microorganisms and is induced byphysical, chemical, metabolic, or antigenic stimuli. When
non-infectious stimuli persist and cannot be eliminated,
NETs can promote sterile inflammation, becoming a partof the pathophysiology of a variety of diseases, including
vascular and immune-related diseases, metabolic disorders,and cancer. Neutrophils can be activated by various stimuli
such as bacteria, fungi, viruses, and platelets 14). In addition
to these physiological stimuli, non-physiological small
compounds, including PMA and calcium ionophores (CaI),
are known to activate neutrophils 14). However, the types ofphysiological components, including diet, that can induce
NET formation remain unknown.
In this study, we have revealed for the first time thatfood intake, even with a standard chow diet (MF), caninduce NET formation in mouse peripheral blood ( Fig. 2).
The lipid content in the diet, especially lard, significantly
enhanced NET formation, as evidenced by the fact that
HF-fed mice showed higher NET formation than HFHCfed mice (Fig. 2). In addition, cholesterol did not appear toaccelerate blood NET formation ( Fig. 2-c). Furthermore, we
found that diet-induced NET formation consisted of two
peaks in blood NET formation, occurring approximately 2 h
and 6 – 24 h after meal consumption (Fig. 2). Since the firstpeak was observed even in calorie-free and lipid-free agar
BA (Fig. 2-d ), we suspect that this may not be caused by the
dietary content, but by physical irritation to the intestinal
tract or intestinal peristalsis triggered by the entrance of thesubstance into the intestinal tract. In contrast, the second
peak may be induced by the lipid contained in the diet. The
experiments with antibiotic treatment suggested that bothpeaks in blood NET formation may be due to the presence ofgut microbiota (Fig. 3 ). Furthermore, we found that dietaryintake induces blood NET formation in humans ( Figs. 4 and
5 ). Vitamin C suppresses inflammation and NET formation,and minerals such as copper and zinc are involved in human
NET formation 15). Moreover, vitamin D supplementation
has been shown to inhibit NET formation in patients withsystemic lupus erythematosus 16).
In addition to NETosis, which is a lytic pathway of
NET formation, nonlytic NET formation has been reported
very recently; this nonlytic pathway may occur in the absenceof neutrophil death, maintaining the ability of neutrophils
to phagocytose and release NETs without plasma membrane
disruption 17). In this study, we used flow cytometry to detect
cell surface CitH3-positive granulocytes as NETs; thus, theNET appearance rate (%) obtained in our system included
both lytic and nonlytic NETs.
Based on our findings, we propose a novel concept
for the prevention and treatment of vascular and immunerelated diseases, metabolic disorders, and cancer by focusing
on the gut microbiota and diet. Further investigations are
required to unveil the molecular and cellular involvement of
the gut microbiota and food components such as lipids in thepathogenesis of lifestyle-related diseases through blood NETformation.

_ 18 8 _Glycative Stress Research

Conclusion

Acknowledgments

Diet-induced NET formation was observed in the
peripheral blood of mice and humans. The dietary lipid
content and gut microbiota of the host may affect NET
formation. This phenomenon may be a biomarker for the
progression of lifestyle-related diseases and may open a
new avenue for the prevention and treatment of vascular andimmune-related diseases, metabolic disorders, and cancer.

We thank Y. Niimura for her secretary assistance.
The document was edited by Editage, a division of Cactus
Communications. We wish to thank our collaborators, Dr.
Tomoharu Miyashita (Kanazawa Medical University) andProf. Tetsuo Ohta (Kanazawa University Hospital).

Conflict of interest statement
The authors declare no conflict of interest in this study.

Funding
We acknowledge the financial support from the
Kanazawa University SAKIGAKE project 2020, Takeda
Science Foundation, and Grants-in-Aid for Scientific
Research (21H02695, 21K09317, 20K07323, and 18K06889).

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