International Journal of Scientific & Engineering Research Volume 9, Issue 7, July-2018
ISSN 2229-5518

1,833

Wellness Fasting-induced Hyperketosis and Interaction
by Intestinal Microbiota
Shaw Watanabe, Izumi Utada, Takayoshi Hisada, Jun Mochizuki, Shoichi Mizuno, Satsuki Moriyama, Azusa
Hirakawa, Seichiro Aoe
Abstract—β-hydrobutyrate (BHB), one of representative ketone bodies, increases by fasting. Fasting endogenously produces ketone bodies in the liver, kidney andastrocytes in the brain. We reported the case in whom increased BHB would come from intestinal microbiota by Koda’s fasting diet. Relationship between plasma BHB
and intestinal microbiota has not well known. Sixty subjects were admitted in the ARSOA Wellness Fasting program. During a 4-day fasting period, they received a
combination of very low-energy vegetarian diet, physical exercise, meditation, and lectures about healthy lifestyles. Peripheral blood was collected on days 1 and 4 forroutine biochemical analyses and for the determination of serum levels of insulin, glucagon and other hormones. Glucose and BHB were measured every morning by
finger tip blood. The stools were collected pre-,mid- and post-fasting, and profiles of microbiota were analyzed by the metanalytic cytotechnicon. All data were collated
in an Excel file, and transferred to SPSS for statistical analysis. BHB in the blood increased from 0.3±0.2 mM at the day 1 to 2.0±1.2 mM at the day 4 of fasting, while
the glucose level decreased from 5.6±1.6 mM to 3.9±1.3 mM. Increases in plasma BHB were assigned to 4 groups (less than 1.0 mM, 1.0-1.99 mM, 2.0-2.99 mM andmore than 3.0 mM). Highest group of BHB showed significant association with family Enterobacteriaceae of prefasting microbiota profile. Further analysis of bacterial
profile at the species level clarified that 15 species were directly or indirectly related to BHB level, such as Providencia vermicola, P. rustigianii, P. sneebia, Morganella morganii, M. psychrotolerans, Proteus hauseri, Butyricimonas virosa,.etc. Five cases with very low Enterobacter presence showed lowest plasma BHB increase.
Only one case with high BHB level did not show any attributable bacteria. Plasma concentration of BHB was related to Enterobacteriaceae directly or indirectly. The
latter suggested syntrophic effects on Enterobacteriaceae. Known butyrate producing bacteria were suppressed by competitive interaction. It suggested that the metabolic pathway of butyrate synthesis and BHB production seemed to be done by different microbiota. Absorption of BHB from intestinal microbiota could be considered
like the BHB supplement use, so dietary effects should be clarified more. Four days of fasting induced hyperketonemia with some metabolic changes. The possible
absorption of BHB through intestinal wall could be accepted independent from butyrate production.

IJSER

Index Terms—β-hydroxybutyrate, Enterobacteriaceae, fasting, intestinal microbiota, ketone bodies, metabolism,

physiology

1.Introduction—————————— u ——————————The importance of ketone body metabolism in dia-

betic patients has been well known since 1970s, but recently,
β-hydroxybutyrate (BHB) has been identified as a key component of a metabolic signaling pathway. [1-3] However, manyquestions remain unanswered what determined individual
differences in the production and excretion of ketone bodies[4]. Recently, hyperketonemia induced by fasting or ketogenic
diet calls attention because of the possibilities for various clinical pharmaceutical effects [5,6].
We hypothesized that 3-β-hydroxybutyrate (BHB) could be
the fuel for the basic engine that produces energy in all terrestrial species [7]. However, ATP production from glucosepyruvic acid pathway seems to be later added as a dominantsystem in human. We hypothesize the establishment of TCA
cycle in mitochondria and enough oxygen supply since twobillion years ago would be the key events to promote thischange. The efficacy of ATP production from β-oxidation
product is 10 ATP molecules, while it is 12.5 molecules frompyruvic acid. So, evolution should select glucose burning system as a booster engine for energy production [7].
The liver and kidney are considered to be the major ketone body producing organs which contain abundant glycogen particles. So, a close relationship between ketone and glucose burning system may be present. This explains why cer-tain level of glucose burning system may be present. This explains why certain level of glucose is steadlily maintainedeven in the hyper ketogenic state.[8]BHB shows various pharmacological effects on disease
prevention, such as cardiovascular disease, Alzheimer’s disease, epilepsy, etc. [9-12] Inhibition of histone deacetylase,
stimulation of FOXO, resistance to oxidative stress, protectionof mitochondria, stimulation of adiponectin release, suppression of inflammasome, etc. are reported [10-16].
We found that a lady who had lived 18 years by only one
glass of vegetable juice a day could live by high BHB which
seemed to be produced by the intestinal bacteria.[17] However, individual differences in ketone production and the dynamics of ketogenesis are still unclear. Possibility of BHB absorption from intestinal lumen like butyrate is not known.
Therefore, we tried to clarify the occurrence of ketogenesis
during fasting by measuring concurrent changes in glucose,
ketone bodies, fatty metabolism and various hormonal changes in both blood and urine in relation to the intestinal
micarobiota. We recruited volunteer subjects among participants in a comprehensive fasting program, which included abalanced diet, physical activity, and mind exercises to achievea healthy spiritual life.

Author is currently the president of lifescience promoting association,
E-mail: watashaw@lifesceinee.or.jp, Co-Authors; IU & SM are working at AOB
Arsoa Group, TH & JM at Techno Suruga Co. Ltd. SM & AZ at Lifescience
Promoting Association. AZ & SA at Otsuma Women’s University
IJSER © 2018
http://www.ijser.org

International Journal of Scientific & Engineering Research Volume 9, Issue 7, July-2018
ISSN 2229-5518

2.Subjects and Mehods

Persons who wanted to participate in the program of
ARSOA wellness fasting were telephone-interviewed by theexpert staff about their health and willing to join the program.
All participants were requested to send 1 week dietary recordand health sheet, including past medical history, abnormal
laboratory data at a health check-up, habitual foods and/or
supplements, and any question to the counselor. [18] All participants signed the agreement sheet after precise explanationof the program.
Each participant took 50 ml fermented vegetable juice(ko-so), CellEnergy (multivitamins), and mineral tablet perday. Water and tea were freely available. On the last day, theattention to return to normal diet was taught, and the subjects ate half volume of boiled brown rice and vegetable soup
as a brunch. All participants were requested to report theirhealth condition after returning home (6th day and 1 month
later).
Every morning participants measured their body composition using the Body Composition Analyzer® (Tanita,
Tokyo, Japan), which determines body weight, fat volume,muscle volume, water contents, estimated bone weight, basal
metabolic rate and body mass index (BMI), based upon theelectric impedance.[19] Blood pressure and pulse rate were
measured with the Omron HEM-7021® monitor (Kyoto, Japan).
Blood glucose and BHB were measured every morningwith the Freestyle Precision Neo® meter (Abott, Chicago, IL,
USA). Daily first urine was checked for urinary pH, glucose,
BHB, urobilinogen, proteins, occult blood, bilirubin, nitrate,
and relative gravity using the Uropaper III® (Eiken, Tokyo,
Japan). A sample of about 10 ml of urine was stored in a frozen tube for quantitative analysis of creatinine, acetoacetate(AcAc), BHB and catecholamines by the Serum Research Laboratory (SRL).[20]On the 1st and 4th day morning, 7ml venous blood wascollected and the frozen sera were sent to the Serum ResearchLaboratory (SRL, Tokyo) for biological analysis, such as total
protein, triacylglyceride (TG) and free fatty acid, glucose andketone bodies, insulin, glucagon, creatinine, γGTP, asparatic
acid aminotransferase (AST) and alanine aminotransferase(ALT) .
Intestinal Bacteria
Fresh feces were collected 3 times; a few days before(pre-) fasting, during (mid-) fasting and about 1 week after(post-) fasting. Fecal samples (approximately 50-100 mg)
were sent to Techno Suruga Laboratory , Shizuoka, for thesequence amplicon analysis.[21-27] The stools were suspended in a solution containing100 mM Tris-HCI, pH 9.0, 40 mM
Tris-EDTA, pH8.0, and 4 M guanidine thiocyanate and0.001% bromothymol blue. An aliquot of 0.8 ml of the suspension was homogenized with zirconia beads in a 2.0 ml

1,834

screw cap tube by FastPrep24 Instrument (MP Biomedicals,
Santa Ana, CA) at 5 m/s for 2 min and placed on ice for 5
min. After centrifugation at 5000 × g for 1 min, DNA was extracted from 200 µL of the suspension using an automatic
nucleic acid extractor (Precision System Science, Chiba, Japan). MagDEA DNA 200 (GC) (Precision System Science)
was used as the reagent for automatic nucleic acid extraction,
as previously described.[21]NGS analysis of microbial community structure in feces
was performed using a MiSeq (Illumina, San Diego, CA), as
previously described. [25-27] The V3-V4 region of 16S rDNA
was amplified using the forward primer Pro341 F 5 ′ AATGATACGGCGACCACCGAGATCTACACXXXXXXXXACACTCTTTCCCTACACGACGCTCTTCCGATCTCCTACGGGNBGCASCAG-3 ′ , where
Xs represent the sample-specific 8-bp barcode sequences(CTCTCTAT, TATCCTCT, GTAAGGAG, ACTGCATA,AAGGAGTA, CTAAGCCT, CGTCTAAT, TCTCTCCG,
TCGACTAG, TTCTAGCT, CCTAGAGT, GCGTAAGA,CTATTAAG, AAGGCTAT, GAGCCTTA and TTATGCGA) )andthereverseprimer
Pro806R
5’CAAGCAGAAGACGGCATACGAGATZZZZZZZZGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCTGACTACNVGGGTATCTAATCC3’, where Zs represent the sample-specific 8-bp barcode sequences(TCGCCTTA,
CTAGTACG,
TTCTGCCT,GCTCAGGA, AGGAGTCC, CATGCCTA, GTAGAGAG,CAGCCTCG, TGCCTCTT, TCCTCTAC, TCATGAGC,
CCTGAGAT, TAGCGAGT and GTAGCTCC). The touchdown PCR method for thermal cycling was used with a GeneAmp PCR system 9700 (ABI, Foster City, CA). The PCR
reaction mixture (25 µL) contained 20 ng genomic DNA, 2
×MightyAmp Buffer Ver.2 (Takara, Otsu, Japan), 0.25 µM ofeach primer, and 1.25 units of MightyAmp DNA Polymerase(Takara). The PCR reaction and preparation of amplicon pool
were performed by the method of Takahashi et al. [27]Bioinformatics analysis
The determined 16S rDNA sequences were subjected tohomology searching using Metagenome@KIN software(World Fusion Co., Ltd., Tokyo, Japan) against the TechnoSuruga
Lab Microbial Identification Database DB-BA10.0 (TechnoSuruga Laboratory), which contains only bacteria with standing in the taxonomic nomenclature. [21]Statistical analysis
The information obtained from the questionnaire wasmade into the Excel database. Analysis was carried out as far
as possible on the point whether the microbiota influenced
ketone production in this study. The complete data of 57
people were provided for analysis
Four groups were categorized by the 4th day serum
BHB levels; less than 1 mM, 1.0-1.9 mM, 2.0-2.9 mM, more

IJSER
IJSER © 2018
http://www.ijser.org

International Journal of Scientific & Engineering Research Volume 9, Issue 7, July-2018
ISSN 2229-5518

than 3.0 mM. It roughly corresponded to the quartile value.
Laboratory data at the day 1 and 4 were compared by thepaired analysis. Data were checked using an unpaired t-test
with Welch’s correction for continuous variables or the
Mann-Whitney test (two-sided) and Fisher’s exact test for
categorical variables. Correlation analysis was carried out
between BHB level and each profile of microbiota at the phylum level, family level, and species level.
The IBM SPSS software Ver. 24 was used for calculation, andP values less than 0.05 were considered significant. The statistical significance of the decision was shown as * p < 0.05, * * p< 0.01, * * * p <0.001.

3.Results
The number of participants was 60, and 3 of them were
excluded from the analysis due to insufficient data. About 20
participants stayed in a mountaneous resort hotel in eachtime, and received a combination of low-energy vegetarian
diet (about 380 kcal intake by fermented vegetable juice perday), physical exercise (2-hour walking, slow training andstretch), meditation, and lectures about healthy life habits in
the 4-day program, as previously reported. [18]Average age of participants was 53.7±18.7 in 3 men and
47.8±11.8 in 54 women. Height and body weight were
116.7±3.2 cm and 64.3±4.1 kg in men and 158.1±5.6 cm and1,835

53.1±8.0 kg in women. Body weight decreased about 1.5±1.3kg（median 1.7kg）, and fat percent and muscle volume also
decreased during 4 day fasting.
The changes of basal metabolic rate (BMR), blood pressure, pulse rate and body temperature are shown in Table 1.
Most participants were women, who were working in cometic shops as a sales lady or owners. There were no current
smokers. Their lifestyle was healthy and about half of themwere ovo- and fish-vegetarians. Although headache, hungry,
GI tract distress, emesis, depressive and cold feeling occurred
toward the 2nd day, these symptoms dramatically disappeared at the 3rd day, and active and vivid feeling increasedon the 4th day and after. Skin condition also became good byfasting.
Glucose decreased, and BHB and acetoacetate (AcAc) increased toward 4th day. Systolic blood pressure decreased 8
mmHg in both males and females, and 4 mmHg in diastolicpressure, which continued at least one month later. On thecontrary, the pulse rate increased 9 at median. Body temperature and BMR decreased in both sex. (Table 1). However,
BHB difference only correlated to the body temperatureand pulse rate, and glucose decrease correlated with lowered
diastolic pressure.

IJSER

Table 1. Anthropometric, physiological, glucose and BHB change during 4 day-fasting
Day 1

Day 2

Day 3

Day 4

p

After 1 w

After 1 mos

54.9

±

8.3

54.4

±

8.2

53.6

±

8.1

53.5

±

8.1

***

53.5

±

8.1

53.1

±

7.6

21.5

±

4.2

21.5

±

3.1

21.5

±

3.2

21.3

±

3.2

0.502

21.5

±

3.4

21.4

±

3.2

29.6

±

6.8

30.3

±

6.7

30.0

±

6.6

29.4

±

6.8

0.454

28.1

±

6.5

28.2

±

5.9

84.9

±

8.3

84.2

±

8.2

83.1

±

8.4

82.1

±

8.7

***

82.2

±

8.6

81.3

±

7.9

BMR (kcal/day)

1107.0±101.91090.1±100.0

1087.4±

95.5

1092.4

±

117.2

***

body temp (℃）

36.5

±

0.4

36.3

±

0.4

36.4

±

0.3

36.3

±

0.3

*

36.3

±

0.4

36.3

±

0.4

puls (n/min)

74.5

±

12.0

79.4

±

11.7

81.1

±

13.6

83.5

±

11.5

***

70.6

±

8.6

70.7

±

9.8

121.5

±

19.2

117.5

±

17.9

113.0

±

16.6

110.9

±

14.4

***

117.1

±

15.7

117.6

±

24.1

80.4

±

12.7

79.1

±

12.0

76.7

±

11.8

75.9

±

10.9

***

76.9

±

12.7

75.3

±

9.1

b_glucose (mM)

5.0

±

1.6

4.6

±

1.1

4.1

±

1.2

3.9

±

1.3

***

na

na

b_bHB (mM)

0.3

±

0.2

0.4

±

0.3

1.2

±

0.7

2.0

±

1.2

***

na

na

body weight (kg)
BMI
fat %
waist circumference

systolic BP(mmHg)
diastolic BP(mmHg)

BHB in the plasma increased from 0.3±0.2 mM at the
day 1 to 2.0±1.2 mM at the day 4 of fasting, while the glucose
level decreased from 5.8±1.9 mM to 4.5±1.5 mM. Increases inplasma BHB were assigned to 4 groups (less than 1.0 mM,
1.0-1.9 mM, 2.0-2.9 mM, and more than 3 mM). The BHB/nana

AcAc ratio in the blood was 5.4±1.3, regardless of the BHB
concentration, but the range varied from 3.5 to 11.0. These
values returned to the normal range on the 14th day (10 days
after fasting).

IJSER © 2018
http://www.ijser.org

International Journal of Scientific & Engineering Research Volume 9, Issue 7, July-2018
ISSN 2229-5518

Changes of plasma biochemical markers
Changes of biochemical markers between Day 1 andDay 4 are shown in Table 2. Marked increase of free fatty
acids and decrease of triacylglycerol, decrease of glucose and1,836

insulin, increase of glucagon, slight increase of AST, ALT and
creatinine were observed. Increased AcAc and BHB negatively correlated to glucagon and glucose.

Table 2 Changes of serum biochemical markers on day 1 and 4th day of fasting
day 1

day 4

dif

n＝53

mean

sd

mean

sd

mean

sd

ｐ

TG (mg/dl)

99.8

±

60.2

56.0

± 20.9

-45.5

±

58.0

***

FFA (mg/dl)

736.2

±

344.8

1900.2± 535.

1181.4

±

607.3

***

glucose (mg/dl)

5.0

±

1.2

3.9

± 1.2

1.1

±

1.0

***

insulin (uUI/ml)

6.2

±

5.3

2.8

± 1.7

-3.5

±

5.2

***

glucagon (pg/ml)

153.7

±

33.6

183.1

± 60.0

26.0

±

63.7

***

AST (U/L)

21.4

±

5.2

31.5

± 8.9

10.0

±

6.5

***

ALT (U/L)

14.3

±

6.8

16.1

± 7.5

1.8

±

3.3

**

γ_GTP (U/L)

28.3

±

32.1

27.1

± 28.3

-1.6

±

5.4

0.113

Cre (mg/dl)

0.6

±

0.1

0.7

± 0.1

0.1

±

0.1

***

eGFR (ml/min/1.73m2)

84.4

±

14.8

74.0

± 15.0

-10.1

±

10.3

***

AcAc (mM)

0.0

±

0.0

0.3

± 0.2

-0.3

±

0.2

***

BHB (mM)

0.1

±

0.1

1.8

± 1.1

-1.7

±

1.1

***

total keton (mM)

0.0

±

0.0

2.2

± 1.3

-2.1

±

1.3

***

TG; tryglyceride, FFA; free fatty acids, AST; ALT γ_GTP, Cr; creatinine, eGFR; estimated glomelular filtration rae,
AcAc; acetoacetate, BHB; β-hydroxybutyrate

IJSER

further analysis. Most common bacteria in phylum was Fermicutes (36-40%), next Bacteroidetes (24%), Actinobacteria (1116%), and then Proteobacteria (0.7-1.9) and Verrucomicrobia(0.602%.). When compared bacterial profiles in 3 different
times, pre-, mid- and post-fasting, Actinobacteria, Proteobacteria and Verrucomicrobia showed significant changes by fasting(Table3).

Changes of microbiota profiles by fasting
Our analyzing system of microbiota profile recognized
600 species from about more than 24000 taxons. Number of
species more than 0.01% was 129 species. Rejected hits were
29.6% and undetermined rate was 9.4%. These were summarized to 60 genus, 29 families, 14 orders, 11 classes and 5 phylum. (Supplementary Table 1) We selected bacteria which
presented more than 0.01% or maximum value of 0.1% for

Table 3. Phylum profile of microbiota before, during and after fasting
time

Pre

Mid

Post

ANOVA

phylummean

sd

medianmean

sdmedianmean

sdmedianp

Firmicutes

40.31

8.12

40.57

36.88

11.03

38.61

41.09

9.38

40.71

0.057

Bacteroidetes

24.06

10.93

23.19

24.11

11.17

24.80

24.05

7.99

23.86

0.999

Actinobacteria

11.70

7.59

10.04

16.63

12.52

13.85

11.87

10.73

8.73

0.024*

Proteobacteria

6.65

6.51

3.94

3.90

4.77

1.58

7.04

7.74

3.61

0.026*

Verrucomicrobia

0.69

1.71

0.02

1.93

3.88

0.01

0.70

1.84

0.01

0.024*

Fusobacteria

0.38

1.46

0.00

0.31

1.16

0.00

0.18

0.69

0.00

0.68

Lentisphaerae

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

nd

Spirochaetes

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

nd

Synergistetes

0.00

0.01

0.00

0.01

0.03

0.00

0.00

0.02

0.00

nd

Rejected hit

16.20

7.76

15.80

16.24

9.70

14.36

15.06

6.69

15.43

0.699

IJSER © 2018
http://www.ijser.org

International Journal of Scientific & Engineering Research Volume 9, Issue 7, July-2018
ISSN 2229-5518

1,837

IJSER

Fig. 1. Changes of individual bacterial profiles in pre-, mid- and post-fasting. (left to right column). Upper 2 colums are high BHB level.
Phylum is shown from the bottom; Firmcutes (blue), Actinobacteria (brown), Bacteroidetes (grey), Proteobacteria (red), Verrucomicrobia (green),
Fusobacteria (violet), Spirochaetes (sky grey), Synergistetes (yellow), Lentisphaerae (pale grey) , and rejected (white).

Fig.2. Bacterial family profile of pre-, mid- and post-fasting by four BHB levels at 4th day. Enterobacteriaceae at prefasting profile showed significant association with high BHB group. Column shows Bacteroidaceaae (blue), Lachnospiraceae (brown), Ruminococcaceae (grey), Bifidobacteriaceae (yellow), Enterobacteriaceae (red), Eubacteriaceae (green), Prophyromonadaceae (dark blue), Coriobacteriaceae (moss green), Prevotellaceae (light blue), Streptococcaceae (dark brown), Veiolonellaceae (violet), Acidaminococcaceae (black), Rikenellaceae (cyan), Peptostreptococcaceae(right brown), Ersipelotrichaceae (grey), Verrucomicnobiaceae (yellaw), Sutterrelbaceae (sky blue), Desulfovibrionaceae (green grey), ge
Flovonifractorincetae sedis (blue), Clostridaceae (red brown), Fusobacteriaceae (violet grey), Bacillacieae (right brown), Enterococcaceae (skyblue), Lactobacillaceae (dark blue), Pasteurellaceae (light blue), Not determined (right brown), Actinomycetaceae (grey), Oscilospiracease (lightbrown), Brucellaceae (sky blue), ge intestinimonas incertage sedis (grey), Micrococcacease (dark blue), Peptoniphilaceae (brown), Pseudomanodaceae, Leuconostocaceae, ge Pseudoflavonifracter incertae sedis, ge Gemilla ircetae sedis, Synergistaceae, Succinivitrionaceae, and rejectd
hit (top: grey)

Comparison of profiles at the family level by BHB category showed significant correlation between prefasting proteobacteria and 4th day BHB level. Such difference was disappeared in the feces during fasting, and it became rather balanced after fasting. Individual response showed various typein high BHB producers but the presence of proteobacteria

was common (Fig. 2).
In comparison of profiles at the species level, significant
difference by BHB level was recognized in Morganella morganii, Proteus hauseri, and Providencia rustigianii (Table 4).
Bacterial profiles of individuals are listed in supplementarytable 2. (Suppl. Table 2)

IJSER © 2018
http://www.ijser.org

International Journal of Scientific & Engineering Research Volume 9, Issue 7, July-2018
ISSN 2229-5518

1,838

Table 4. Profile of microbiota by BHB level
BHB degree
Bacili ％<1.0 mM(n=16)

1.0-1.99(n=17)

2.0-2.99(n=12)>3.0 mM

n=10

mean

sd

mean

sd

mean

sd

mean

sd

p

Faecalibacterium prausnitzii

5.37

4.46

5.45

3.18

5.05

3.62

4.54

3.35

0.932

Bacteroides vulgatus

3.72

8.24

3.67

5.57

3.78

4.21

4.57

6.37

0.985

Bacteroides dorei

3.75

6.37

2.81

3.82

2.20

3.67

3.62

5.57

0.508

Bacteroides uniformis

3.02

2.44

2.41

2.28

3.86

2.37

2.78

1.55

0.392

Blautia wexlerae

3.17

2.60

2.60

1.70

3.28

2.72

1.82

1.37

0.377

Bifidobacterium adolescentis

2.68

4.32

4.35

4.67

3.07

3.13

2.23

2.40

0.842

Eubacterium rectale

2.46

3.42

1.94

2.98

0.54

0.47

1.72

2.04

0.302

Bifidobacterium longum

2.41

2.34

1.55

1.25

0.79

0.67

1.41

0.93

0.057

Ruminococcus bromii

2.13

2.34

2.71

3.58

3.60

3.77

1.69

3.50

0.539

Collinsella aerofaciens

1.83

2.52

2.94

4.60

3.12

3.66

3.59

1.97

0.598

Subdoligranulum variabile

1.79

0.98

1.32

1.20

1.87

1.77

1.37

1.59

0.621

Fusicatenibacter saccharivorans

1.68

1.38

1.79

1.28

2.01

1.93

1.86

1.58

0.955

Bacteroides plebeius

1.42

2.56

2.40

4.77

0.40

0.91

1.96

4.70

0.522

Blautia luti

1.27

1.08

1.66

1.57

2.30

2.81

0.64

0.77

0.149

Morganella morganii

1.29

3.04

0.00

0.00

1.76

4.12

3.87

6.80

0.016

Ruminococcus obeum

0.90

0.79

1.76

1.77

1.21

1.01

0.55

0.62

0.072

Parabacteroides distasonis

0.78

0.73

1.24

2.00

1.48

1.45

2.55

2.40

0.089

Megamonas funiformis

0.77

1.58

0.55

1.56

1.84

4.30

3.09

6.65

0.306

Citrobacter freundii

0.60

1.47

0.32

0.72

0.13

0.38

0.60

1.13

0.591

Citrobacter werkmanii

0.40

0.68

0.58

1.22

0.00

0.00

1.23

3.64

0.412

Clostridium xylanolyticum

0.45

0.64

0.32

0.34

0.44

0.72

0.06

0.08

0.259

Bacteroides caccae

0.41

0.60

0.45

0.62

0.38

0.61

0.04

0.09

0.288

Ruminococcus lactaris

0.33

0.52

0.05

0.06

0.21

0.27

0.63

0.61

0.007

Megasphaera elsdenii

0.28

0.89

0.73

1.63

0.32

1.06

0.16

0.50

0.579

Streptococcus sinensis

0.27

0.48

0.06

0.09

0.04

0.07

0.08

0.11

0.083

IJSER

Eubacterium ventriosum

0.25

0.65

0.07

0.09

0.18

0.24

0.23

0.31

0.575

Roseburia inulinivorans

0.22

0.59

0.25

0.48

0.14

0.31

0.77

0.94

0.072

Flavonifractor plautii

0.16

0.18

0.18

0.20

0.20

0.20

0.37

0.46

0.216

Bacteroides finegoldii

0.11

0.34

0.02

0.07

0.07

0.15

0.41

1.27

0.372

Alistipes shahii

0.11

0.13

0.13

0.14

0.15

0.17

0.01

0.02

0.08

Clostridium bolteae

0.09

0.13

0.15

0.16

0.25

0.46

0.35

0.49

0.217

Bifidobacterium dentium

0.02

0.03

0.00

0.01

0.00

0.01

0.00

0.00

0.09

Proteus hauseri

0.00

0.00

0.00

0.00

0.00

0.00

1.91

4.02

0.023

Providencia vermicola

0.00

0.00

0.02

0.08

0.47

1.09

1.65

5.20

0.262

Providencia rustigianii

0.00

0.00

0.00

0.00

0.00

0.00

0.09

0.19

0.022

Veillonella tobetsuensis

0.00

0.01

0.00

0.01

0.00

0.00

0.02

0.03

0.035

Veillonella parvula

0.00

0.00

0.00

0.00

0.00

0.00

0.01

0.02

0.002

Solobacterium moorei

0.00

0.00

0.00

0.00

0.00

0.00

0.01

0.01

0.004

Corynebacterium argentoratense

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.01

0.081

Kluyvera georgiana

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.083

Pectobacterium aroidearum

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.01

0.023

Total % of bacili

44.17

44.46

45.15

52.48

more than 0.01% species

Syntrophic or competitive interaction of bacteria for BHB
production
Further analysis of bacterial profile at the species levelclarified that 7 species directly related to BHB level, such as
Providencia vermicola, Providencia rustigianii, Providencia
sneebia,

Morganella morganii, Morganella psychrotolerans, Proteus hauseri, and Butyricimonas virosa. (Table 5). They showed
syntrophic growth among them. Butyricimonas virosa coexisted with Providencia rustigianii (CC=1.000***) and Morganella
morganii (CC=0.763***).[28] Bacteroides finegoldii and Parabacteroides distasonis in Bacteroidaceae

IJSER © 2018
http://www.ijser.org

International Journal of Scientific & Engineering Research Volume 9, Issue 7, July-2018
ISSN 2229-5518

1,839

Table 5. Correlation of microbiota which show syntrophic and/or competitive interaction for BHB production
Bacteroides

Proteobacteria
相関

BHB at 4day
Providencia rustigianii
Providencia sneebia
Providencia vermicola

Butyricimonas virosa

Fermicutes

BHB

P

P

P

P

P

P

Porphylo

B

B

F

F

F

F

F

F

F

F

4thdayBHB

Providencia
rustigianii

P.sneebiaP.vermi
cola

Mor
gane
lla
mor
ganii

Morganella
psychrotoleransProteushauseri

Butyricimonas
virosaBacteroides
finegoldii

Parabacteroid
es
distasonis

Clostridium
bolteae

Clostridium
lavalense

Enterococcus
avium

Megam
onas
rupellensis

Allisonella
histaminiformans

Flavonifrac
torplautii

Roseburia
faecisBlautia
faecis1.400**.399**.418**.332*.399**.281*.400**.318*.360**.282*.399**.399**

.293*

.285*

.272*

-.288*-.350**.400**

1-0.026-0.035.753**-0.026-0.0381.000**-0.042.442**-0.011-0.026-0.026-0.026-0.0380.042-0.156-0.098.399**.418**.400**-0.026-0.0351.000**

1.972**-0.026.972**
1-0.035-0.0510.055.753**

1.000**.972**-0.026-0.026-0.035-0.038-0.026-0.0351.937**.907**-0.0420.045
0.013.442**

0.176
0.147-0.0111.000**.972**-0.0261.000**.972**-0.026-0.019-0.025-0.026-0.026-0.035-0.038

0.237
0.198
0.042

-0.109-0.142-0.156-0.114-0.125-0.098Morganella morganii.332*.753**-0.0510.055

1-0.0510.064.753**-0.0810.22-0.123-0.051-0.051-0.051

0.063

-0.05

-0.158-0.092

M. psychrotoleransProteus hauseri
Providencia rettgeri
Hafnia paralvei
Klebsiella variicola
Enterobacterasburiae
Enterobacterhormaechei
Enterobacter kobei
Kluyvera cryocrescens
Klebsiella oxytoca
Citrobacter freundii
Citrobacter sedlakii
Escherichia/Shigella
Bacteroides finegoldii
Parabacteroides
distasonis
Clostridium bolteae
Clostridium lavalenseEnterococcus avium
Megamonas
rupellensis
Allisonella histaminiformans
Flavonifractor plautii
Bacteroides faecichinchillae
Bacteroides stercoris
Bacteroides xylanisolvens.399**.281*-0.026-0.0381.000**-0.026.972**-0.035-0.0510.064

1-0.026-0.0261-0.026-0.038.937**-0.0420.045-0.1550.176-0.1011.000**-0.0261.000**-0.026-0.019-0.026-0.026.994**

0.237-0.136-0.1090.193-0.114-0.1260.043-0.047-0.033

0.161

.327*

-0.033-0.047-0.047-0.052-0.156-0.125-0.033-0.033-0.033-0.046-0.168-0.0750.145-0.048-0.034-0.0450.02-0.034.813**-0.048-0.054-0.169-0.129-0.034-0.034-0.034.813**-0.175

.317*

.272*

0.085

-0.054-0.038-0.051-0.031-0.038.359**-0.054-0.051-0.204-0.146-0.038-0.038-0.038.361**-0.1440.228-0.067-0.045-0.0730.05-0.065-0.045-0.06-0.044-0.045.319*-0.065-0.062-0.238-0.158-0.045-0.045-0.045.316*-0.1620.218-0.087-0.05-0.035-0.043-0.084-0.035

-0.05

-0.05

0.001

-0.17

-0.129-0.035-0.035-0.035-0.05-0.171.405**

0.058-0.074-0.054-0.038-0.046-0.104-0.038-0.054-0.054-0.041-0.152-0.129-0.038-0.038-0.038-0.054-0.177.339*-0.054-0.021-0.058-0.041-0.054-0.112-0.041-0.058-0.058-0.047-0.0720.071-0.041-0.041.390**-0.0580.01-0.107-0.144-0.007-0.019-0.121-0.008-0.033-0.078-0.026-0.036-0.0230.033-0.019-0.025-0.0310.016-0.025-0.039-0.064-0.144-0.051-0.09-0.0230.033-0.019-0.025-0.033-0.078-0.0260.014-0.033-0.078-0.026-0.0360.026
0.015-0.029-0.047-0.116-0.066-0.058-0.12-0.089-0.11-0.016.385**-0.0230.033-0.019-0.025-0.0230.033-0.019-0.025-0.023.380**-0.019-0.058-0.033-0.078-0.0260.015-0.12-0.073-0.0950.059.289*-0.081
0.008
0.054

0.052
-0.129-0.085-0.062-0.088.318*-0.042.937**.907**-0.081.937**-0.042-0.042

1

0.018

0.142

.937**.937**-0.029-0.0420.231-0.106.360**.442**

0.045

0.013

0.22

0.045

-0.155.442**

0.018

1

.289*

0.045

0.045

0.25

-0.155.483**-0.191

-0.11

.282*

-0.011

0.176

0.147

-0.1230.176-0.101-0.011

0.142

.289*

1

0.176

0.176

0.068

-0.101.705**-0.243-.272*.399**-0.0261.000**.972**-0.0511.000**-0.026-0.026.937**

0.045

0.176

1

1.000**-0.019-0.0260.237-0.109-0.114.399**-0.0261.000**.972**-0.0511.000**-0.026-0.026.937**

0.045

0.176

1.000**

1-0.019-0.0260.237-0.109-0.114-0.0260.073-0.109-0.114

.293*
.285*
.272*
0.226

IJSER
-0.026-0.019-0.025-0.051-0.019-0.026-0.026-0.029

0.25

0.068

-0.019-0.0191-0.038-0.026-0.035

0.063

0.042

0.237

0.198

-0.05

-0.026.994**-0.038-0.042-0.155-0.101-0.026-0.026-0.0261-0.136

0.184

-0.13

0.237

-0.136

0.042

0.231

.483**.705**

0.237

0.237

0.073

-0.1361-.292*-0.211-0.0570.098.676**.633**

0.13.676**-0.0430.098.683**

0.103

0.134

.676**.676**-0.081-0.043

.323*

0.021

-0.106

.315*

.292*

-0.156.315*-0.106-0.106.286*.374**

0.235

.315*

.315*

-0.074-0.105.400**-0.1640.028.448**-0.048-0.064.285*-0.048-0.069.448**-0.076.362**

0.205-0.048-0.0480.071-0.0690.139-0.098-0.064-0.059.415**.392**-0.114.415**-0.059-0.059.367**.354**

0.179.415**.415**-0.041-0.059.322*-0.1420.09-0.091-0.056.453**.272*.426**
0.245-0.091-0.139.453**.272*-0.035-0.084-0.091-0.056.391**
0.232-0.1650.042.342*.574**.453**.272*.453**.272*-0.064-0.059-0.034-0.084

0.193
.268*

-0.102-.267*-0.237-.310*

0.03-0.128.452**-0.038-0.083-0.048-0.102-0.064.327*-0.107-0.083-0.048-0.118-0.068.452**-0.038-0.123-0.0760.25.427**

-0.03
0.065

-0.083-0.048-0.083-0.048-0.0440.013-0.118-0.068

0.058
0.214

0.053
-0.154-0.124-0.074-0.026-0.085

.325*

.297*

-0.141.325*-0.085-0.085.272*-0.089

0.119

.325*

.325*

-0.011-0.0840.091-0.247-.278*

0.068-0.026-0.019

0.144

.331*

-0.019-0.026-0.026-0.029-0.088-0.071-0.019-0.019-0.019-0.026-0.095-0.109-0.048

0.184
0.157

Hungatella hathewayi

0.179

Blautia stercoris
Blautia glucerasea
Clostridium leptum
Clostridium nexile
Clostridium ramosum
Odoribacter laneus
Parabacteroides
goldsteinii
Parabacteroides
merdaeParasutterella
excrementihominis
Ruminococcus
bromiiRuminococcus
torquesAnaerostipes
butyraticus
Anaerotruncus
colihominis
Odoribacter
splanchnicus
Faecalibacteriumprausnitzii
Acidaminococcus
intestini
Adlercreutzia
equolifaciens
Alistipes shahii
Asaccharobactercelatus
Roseburia faecis
Blautia faecis
Bifidobacterium
longumBacteroides faecis
Bacteroides fragilis
Bacteroides vulgatus
Bacteroides nordii
Blautia luti
B.coprocola
Bacteroides dorei
B. eggerthii
B. ovatus
Barnesiella intestinihominis
Bifidobacterium
adolescentis
B.bifidum

0.207
0.075

-0.06

.320*

.298*

-0.115

.320*

-0.06

-0.06

.392**-0.016

0.265

.320*

.320*

-0.042

-0.06

0.027

-0.129-0.166-0.001

0.053

0.255

-0.077-0.101.325*-0.077

-0.11

0.255

-0.11

0.055

0.119

-0.077-0.077-0.077-0.11.444**-0.063-0.016

0.207

.290*

-0.07

-0.093

0.235

-0.07

-0.1

.290*

-0.111.390**

.274*

-0.07

-0.07

-0.07

-0.1

.267*

-0.011

-0.09

0.022

.346**-0.107-0.1080.243-0.107-0.153.346**-0.139

0.064

0.028

-0.107-0.107-0.107-0.152-0.173-0.221

0.087

0.24

-0.084.363**.322*-0.198.363**-0.134-0.084

.298*

0.222

.666**.363**.363**-0.067-0.134.602**-0.021-0.125

0.068

-0.01

-0.029-0.039-0.056-0.029-0.042-0.01-0.047-0.057.569**-0.029-0.029-0.029-0.0420.03-0.152-0.145
0.043

0.079

-0.054-0.038-0.05-0.104-0.038-0.054-0.054

-0.06

0.111

.315*

-0.038-0.038-0.038-0.054.412**-0.162-0.218-0.061-0.154-0.159-0.158-0.154-0.22-0.061-0.147-0.117-0.16-0.154-0.154-0.154-0.219-0.099

0.137

.277*

-0.137-0.083-0.178-0.149-0.01-0.178-0.028-0.083-0.168-0.098-.410**-0.178-0.178-0.049-0.029-.394**.421**.415**-0.137-0.076-0.053-0.071-0.088-0.053-0.076-0.076-0.075-0.1380.047-0.053-0.0530.046-0.0760.115-0.075-0.028-0.121-0.026-0.019-0.025-0.051-0.019-0.026-0.026-0.029-0.058-0.016-0.019-0.019-0.019-0.026-0.0950.008-0.085-0.262-0.143-0.1-0.076-0.029-0.1-0.143-0.143-0.088-0.134-.275*

-0.1

-0.1

-0.1

-0.143-0.194-0.068-0.02-0.156-0.066-0.046-0.062-0.128-0.046-0.066-0.066-0.009-0.102-0.079-0.046-0.046-0.046-0.066-0.101-0.035-0.155.402**-.288*-0.156-0.109-0.142-0.158-0.1090.193-0.156-0.106-0.191-0.243-0.109-0.109-0.1090.184-.292*

1-.350**-0.098-0.114-0.125-0.092-0.114-0.126-0.098-0.088-0.11-.272*-0.114-0.114-0.114-0.13-0.211.402**

1-0.2590.146-0.137-0.169-0.001-0.137

0.032

0.146

-0.0130.083-0.105-0.137-0.137-0.0610.034-0.013

0.039

0.004

0.15
0.244
0.078
0.021
-0.181-0.02-0.046-0.208-0.079-0.069-0.009-0.122-0.03-0.166-0.0690.037-0.051
0.013-0.0480.158
0.246-0.021-0.117-0.049-0.087-0.036-0.089-0.0640.136
0.229-0.028-0.085-0.064-0.111-0.048-0.113-0.132-0.092-0.12-0.059-0.108-0.08-0.038-0.0990.002-0.0480.158
0.246-0.021-0.117-0.049-0.087-0.036-0.089-0.069-0.0750.113-0.03-0.002-0.069-0.124-0.051-0.098-0.069-0.009-0.122-0.03-0.166-0.0690.037-0.051
0.013-0.0510.116
0.205-0.034-0.072-0.054-0.1190.224-0.1160.104.343*.361**.356**-.315*-0.031-0.024-0.067-0.038

0.236
0.215
0.107
0.004
-0.216-0.074.401**-0.087.424**-0.0480.158
0.246-0.021-0.117-0.049-0.087-0.036-0.089-0.0480.158
0.246-0.021-0.117-0.049-0.087-0.036-0.089.651**.371**-0.0860.141-0.117.447**
0.092-0.0360.02-0.068-0.0750.113-0.03-0.002-0.069-0.124-0.051-0.0980.142.348**
0.231
0.223-0.223
0.001
.327*
-0.04
.289*

-0.159-0.252-0.107-0.126
0.032
0.007-0.099-0.053-0.232-0.1540.065-0.194-0.131
0.107
0.045-0.065-0.007-0.218-0.21-0.133-0.093-0.076-0.075-0.093-0.133-0.133-0.066-0.1180.18-0.093-0.093-0.093-0.133

0.094

0.051

0.168

-0.1170.037-0.113-0.125-0.032-0.113-0.1330.037-0.1270.009-0.155-0.113-0.113-0.113-0.133-0.114

0.164

0.029

-0.0940.043-0.131-0.071-0.071-0.0020.258-0.071

0.112-0.071-0.101

0.258-0.095-0.071-0.101-0.095-0.0550.09

Bilophila wadsworthia

0.206

0.189

0.117

0.11

0.076

0.117

-0.165

0.189

0.123

0.265

.304*

0.117

0.117

0.022

-0.164.328*-0.234-0.121

Blautia hansenii
Blautia schinkii
Blautia wexlerae

00.07-0.224-0.06-0.03-0.161

0.186-0.021-0.1730.167-0.028-0.2-0.116-0.057-0.1450.186-0.021-0.173

-0.06
-0.03
0.048

-0.06
-0.03
-0.1610.15-0.033-0.076-0.057-0.064-0.08.520**.584**-.303*

0.186-0.021-0.1730.186-0.021-0.173-0.042-0.021
0.035

-0.06
-0.03
0.049

.292*
0.039
0.011

-0.248-0.1230.193-0.207-0.128.459**and some Fermicutes, such as Clostridium bolteae, C. lavense,

Enterococcus avium, Megamonas repellensis, Allisonella histamini-

IJSER © 2018
http://www.ijser.org

International Journal of Scientific & Engineering Research Volume 9, Issue 7, July-2018
ISSN 2229-5518

formans and Flavonifractor plautii were indirectly associatedwith Enterobacter families, except for Flavonifractor plauti. (Table 5)

1,840

These association was confirmed by individual level(Suppl. Table 2). Enterobactereciae species were recognized in
20/22 high bHB producers, 13/17 moderate bHB producers
and 15/16 low producers. Two in high BHB, 4 in middle BHB,
and 1 in low BHB did not have enterobacteriacea species, andin these cases, Clostridium bolteae, C. lavalense, Enterococcus
avium, Hunatella hathewayi, Megamonas rupellensis and Ruminococcus bromii seemed to be related to BHB production.

Roseburia faecis and Blautia faecis were negatively associated with BHB concentration, but they showed syntrophic
correlation with Providencia rettgeri, Hafnia paralvei, and otherenterobacters. Five cases with very low Enterobacter profile
showed lowest BHB level. Only one case with high BHB level
showed no positive association to proteobacteriae, but broad
association was present, such as Megamonas funiformis, Prevotella copri and P. stercorea, Bifidobacterium adolescentis, Faecalibacterium prausnizii,
etc. (Table 5)

Cooperation (syntrophic) or suppression (competitive)of bacilli was suggested by correlation network among individual species (Table 5). Generally BHB producing bacteria
suppressed butyrate producing bacteria．Sumary relationship between BHB level and network of microbiota is shownin Table 6.

Table 6. Microbiota with direct and indirect correlation with serum BHB level
Primary correlation
Directcorrelation

CC withBHB

phylumProvidencia vermicola.418**P

Providencia rustigianii.400**

P

Secondary relationshipCC with name1

IJSER
Providencia sneebia.399**P

Morganella morganii

.332*

P

Morganella psychrotolerans.399**

P

Proteus hauseri

.281*

P

Butyricimonas virosa.400**

B

Providencia rustigianii

1.000***

Clostridium lavalense.399**

F

E.coli/shigela.385**

Enterococcus avium.399**F

Parabacteroides distasonis.360**

B

providencia.990***

Bacteroides finegoldii

.318*

B

providencia, butyricomonas.442***

Megamonas rupellensis

.293*

F

Kluyvera, citrobacter.390***

Allisonella histaminiformans

.285*

F

proteus, hafnia.994**

Clostridium bolteae

.282*

F

E.coli/shigela.385**

Flavonifractor plautii

.272*

F

many

.600***

Negative

Roseburia faecis-.288*

F

enterobacter, hafnia, krebsiella.405***

correlation

Blautia faecis-.350**

F

many

Rejected hit-.285*

Indirectcorrelation

Effects of Dietary habit on bacterial profile
From semiquantitative food frequency questionnaire before participation in the wellness fasting, water soluble andinsoluble dietary fiber intake, fat and protein intake were individually calculated. Protein intake showed significant correlation with Acidaminococcus intestinalis (CC=0.24*), fat intake
with Blautia faecis (CC=0.326*), Dialister inivisis (CC=0.394**),and Hafnia paraluei (CC=0.343*). Dietary fibers positively correexcept for Hafnia arluei. Competitive and trophic interaction

P. sneebia, P.vermicola, Morganella

1.000***.400-.500***

lated with Fusobacterium mortiferum (CC=0.343**), Lactonifactor
longoviformis (CC=0.269*), Eubacterium eligens (CC=0.262*) andnegatively correlated Bifidobacterium adolescence (CC=-0.288*),
B. breve (CC=-0.284*), Citrobacter sedlakii (CC=-0.274*), andBlautia luti (CC=-0.247*). Both protein intake and dietary fiber
intake did not show significant correlation with Enterobacterfamily,seemed to be present.

IJSER © 2018
http://www.ijser.org

International Journal of Scientific & Engineering Research Volume 9, Issue 7, July-2018
ISSN 2229-5518

4.Discussion

In the fasted state, acetyl CoA is provided from βoxidation of fatty acids and overflowed acetyl CoA makes

1,841

acetoacetyl CoA, and ketone bodies are produced via 3’hydroxy-3 methyl glutaryl CoA. [27] In bacteria, synthesis anddegaradation of ketone bodies is similar, but relationship between butyrate metabolism is obscure. (Fig. 3)

IJSER
Fig. 3. Synthesis and degradation of ketone bodies
Reference pathyway and bacteria with key enzyme.

Cahill [29] studied the glucose metabolism of people
who let themselves fast for 40 days, and he found that in the
starving human adult, BHB and aceto-acetate were producedin the liver from long-chain fatty acids and BHB could be theenergy source in the brain and other tissues. A rise of BHB
blood concentration to approximately 6 mM was characteristic. Approximately all of the lactate, pyruvate, glycerol, andamino acid carbons which are removed by the liver and kidney are converted into glucose, as evidenced by substratebalances across these organs to keep the basic level. [30]Cahill’s research was integrative rather than reductionism, but he opened the unique insight on the metabolic adaptation of humans to starvation. During starvation, extremely
low insulin levels facilitate acyl-CoA entry into mitochondria,
producing excess amounts of acetyl-CoA that cannot be metabolized in the Krebs cycle and are diverted towards thesynthesis of ketone bodies. ｖBHB is considered to be produced in the liver, kidney and astrocytes in the brain, but ourcase report suggested the involvement of intestinal microbiota. Fasting caused hyperketonemia, but the degree was different by individuals. [4] We tried to clarify the involvementof microbiota for production of ketone bodies in this study.
Mitsuo Koda [31] developed fasting dietary therapy andconfirmed beneficial effects for many patients with intractable diseases. About 900-1000 kcal/day by unpolished brown
rice, green vegetable paste and tofu constitute the basic regi-

men of Koda’s therapy. We found the successful patient who
had recovered from spino-cerebellar degeneration at a young
age by Koda’s dietary therapy.[17] She had been living on
only one glass of fresh vegetable juice per day for 18 years
since her acute episode at age 20. Her ketone bodies, especially BHB in the blood, were more than 3 mM, so the main energy should come from ketone bodies. Her biochemicalchanges coincided with the metabolic adaptation to yield
BHB, as shown by elevated aspartate aminotransferase(AST), alanine aminotransferase (ALT) and creatine kinase(CK). High aspartate was a reflection of above metabolicchange. Increased BHB was observed in two participants
among five, and both of them had Bifidobacteriacae in the fecal
bacteria. [17] Some Bacteroides had xylanase or cellulose activities, so these species may play an important role in fiber
degradation in a strict vegetarian. Hayashi, et al. [32] had
previously analyzed the fecal bacteria of Mori 15 years ago.
They found that Clostridium and Bacteroides were the dominant groups. They also found many Bifidobacterium by direct
culture.
Our previous study in wellness fasting and BHB production by Pass analysis showed that the decreased BMR andinsulin significantly contributed to the increase in BHB and
AcAc. [4,5] From our experience of Mori’s case, we considered the different gut microbiome should influence the production of BHB.

IJSER © 2018
http://www.ijser.org

International Journal of Scientific & Engineering Research Volume 9, Issue 7, July-2018
ISSN 2229-5518

Comparison of our cases with other Japanese microbiota
Nishijima et al. [33] analyzed gut microbiota of the Japanese by comparing the metagenomic data obtained from 106
Japanese individuals with those from 11 other nations. They
found that the composition of the Japanese gut microbiome
showed more abundant in the phylum Actinobacteria, in particular in the genus Bifidobacterium, than other nations. Hisada et al. [22] reported predominance of Fermicutes and ourcase showed the similar proportion. However, Proteobacteria
and Verrucobacteria may be influenced by fasting and theirdietary habit as vegetalian.
Numerous animal models and human studies consistently demonstrated that gut microbiota can modulate hostenergy homeostasis and adiposity through different mechanisms. [34-39] Dietary change or fasting could change microbiota quickly within a short period [40,41]. Some people
could not raise ketone concentration in the blood as expectedeven by the ketogenic diet. A metabolic homeostasis would
be different in these people, and need further study.
Relationship with butyrate producing bacteria:
Butyrate-producing bacteria may represent a functionalgroup, rather than a coherent phylogenetic group, within the
microbial community of the human large intestine. Butyrate
formation can play a special role in bacterial energy metabolism [42-46] and this implies that certain features of energy
metabolism and microbial ecology may be shared between
phylogenetically distinct groups of butyrate-producing bacteria. Numerically, two of the most important groups appear
to be Faecalibacterium prausnitzii, which belongs to the Clostridium leptum cluster, and Eubacterium rectale/Roseburia spp.,
which belong to the Clostridium coccoides cluster of firmicutebacteria. After reduction to butyryl-CoA, butyrate can beformed either with the enzymes phosphotransbutyrylase andbutyrate-kinase via butyry-l-phosphate or with the enzyme
butyryl-CoA : acetate CoA-transferase, which utilizes acetate
as a co-substrate and generates acetyl-CoA. (Fig. 4)
Butyrate-producing human gut isolates, covering aphylogenetically wide range of representatives of clostridial
cluster XIVa and some cluster IV and XVI strains, indicatedthat the butyryl-CoA : acetate CoA-transferase route is far
more prevalent in this ecosystem than the butyrate kinase

1,842

route.[44]Could synthesis of BHB come from butyrate? The current data suggested Enterobactericeae mainly correlated to the
BHB production, but several other species in Clostridium andBacteroides that had correlation with BHB were indirectly related to Enterobactericeae. Enterobacter seemed to suppress
Fermicutes, so butyrate producing bacteria would be suppressed in the colon. Possibility of metabolism by intestinal
microbiota from butyrate to BHB in the body seemed to be
independent.
In addition, there are many bacteria that can synthesizepoly(3-hydroxy butyrate-co-3 hydroxyvalerate) oly-beta hydroxyl butyrate.[47-50] These bacteria are capable of using abroad range of carbon sources for their growth and for the
production of polyhydroxyalkanoates (PHAs). They can use
monosaccharides (glucose and fructose), disaccharides (sucrose), pentoses (xylose and arabinose), various organic acids(acetic acid, propionic acid and octanoic acid) for growth andthe production of polyhydroxyalkanoates (PHAs). PHAs and
BHB could be hydrolyzed inside and outside of the bacilli.
One case who did not show the direct or indirect correlation with Enterobacteriaceae could be related to such unknown bacteria.

4 . Conclusion

IJSER
1.
2.
3.

4.

Wellness fasting caused metabolic and physiologicalchanges , and induced hyperketonemia which showedcorrelation with prefasting microbiota profile.
High BHB level showed association with family Enterobacteriaceae directly or indirectly.
The dominance of Enterobacteriaceae seemed to suppress
butyrate producing bacteria. So, the BHB production
seemed to be independent from butyrate pathway in thegut.
The rout of BHB synthesis would be multiple bysyntrophic and/or competitive growth of bacteria.

Acknowledgment

The authors appreciate the participants in this study.
The authors appreciate Dr. Teruyuki Kobayashi, Chiba Science University, for review and discussion on this paper, and
Dr. Philippe Calain, MSF, for his kind English revision anddiscussion.
COI: This research was supported by the Life Science Promoting Association, AOB Keio Group and TechnoSuruga
Laboratory.

IJSER © 2018
http://www.ijser.org

International Journal of Scientific & Engineering Research Volume 9, Issue 7, July-2018
ISSN 2229-5518

References[1] A.M.Robinson and D.H.Williamson, “Physiological role ofketone bodies as substrates and signals in mammalian tissues.” Physiol Rev. 1980; 60(1): 143-187. Web site.
http://physrev.physiology. org/content/60/1/143.long.
[2] J.C.Newman and E.Verdin, “β-hydroxybutyrate: Much
more than a metabolite.” Diabetes Res Clin Prac. 2014;
106(2): 173-181.doi: 10.1016/j.diabres.2014.08.009[3] R.L.Veech, “The therapeutic implications of ketone bodies:
the effects of ketone bodies in pathological conditions: Ketosis, ketogenic diet, redox states, insulin resistance, andmitochondirial metabolism.” Prostaglandins Leukot Essent
Fatty
Acids.
2004;
70(3):
309-319.
doi:
10.1016/j.plefa.2003.09.007[4] S.Watanabe, “Wellness fasting and hyperketosis.” Diabetes Res Open J. 2016; 2(2): e10-e13. doi: 10.17140/DROJ-2e007[5] S.Watanabe, A. Hirakawa, I.Utada, S.Aoe, S.Moriyama,
and R.Takiguchi, “Ketone body production and excretion
during wellness fasting,” Diabetes Res Open J 2017; 3(1):18. doi: 10.17140/DROJ-3-129[6] P.J.Cox, T.Kirk, T.Ashmore, K.Willerton and R.Evans,“Nutritional ketosis alters fuel preference and thereby endurance performance in athlete.” Cell Metabolism. 2016;24(2): 1-13. doi: 10.1016/j.cmet.2016.07.010[7] S.Watanabe, A.Hirakawa, S.Aoe, K.Fukuda and
T.Muneta,”Basic ketone engine and booster glucose engine
for energy production.“”Diabetes Res Open J. 2016: 2(1):14-23. doi: 10.17140/DROJ2-125[8] R.N.Heitmann, D.J.Dawes and S.C.Sensenig, “Hepatic
ketogenesis and peripheral ketone body utilization in the
nutrient.” J Nutr.1987; 117(6): 1174-1180. Web site.
http://europepmc.org/
abstract/med/3298582. Accessed December 29, 2016.
[9]
S.Phinney
andJ.Volek,
https://nutritionalketosisforhealth.com/what-is[10] J.Zhang, Q.Cao and S.Li,” 3-Hydroxybutyrate methyl
ester as a potential drug against Alzheimer’s disease via
mitochondria protection mechanism.” Biomaterials. 2013;34(30): 7552-7562. doi: 10.1016/j.biomaterials.2013.06.043[11] H.C.Kang, D.E.Chung, D.W.Kim and H,D.Kim,”Earlyand late- onset complications of the ketogenic diet for intractable epilepsy.” Epilepsia 2004; 45(9): 1116-1123. doi:
10.1111/j.0013-9580.2004.10004.
[12] G.P.Delcuve, D.H.Khan and J.R.Davi. ”Roles of histone
deacetylases in epigenetic regulation: Emerging paradigms from studies with inhibitors.” Clin Epigenetics.
2012; 4(1): 5. doi: 10.1186/1868-7083-4-5[13] T.Shimazu, M.D.Hirschey, J.Newman et al. “Suppressionof oxidative stress by β-hydroxybutyrate, an endogenous
histone deacetylase inhibitor.” Science. 2013; 339(6116):
211-214. doi: 10.1126/science.1227166[14] J.M.Miles, M.W.Haymond and J.E.Gerich. “Effects of freefatty acids, insulin, glucagon and adrenaline on ketone
body production in humans.” Ciba Found Symp. 1982; 87:
192-213. doi: 10.1002/9780470720691.ch11[15] R.Felty and E.O. Balasse,” Ketone body production anddisposal in diabetic ketosis. A comparison with fasting ke-

1,843

tosis.” Diabetes.1985; 34(4): 326-332. doi:
10.2337/diab.34.4.326[16] U.Keller, M.Lustenberger, J.Müller-Brand, P.P.Gerber and
W.Stauffacher,”Human ketone body production and utilization studied using tracer techniques: Regulation by freefatty acids, insulin, catecholamines, and thyroid hormones.” Diabetes Metab Rev. 1989; 5(3): 285-298. doi:
10.1002/dmr.5610050306[17] A.Hirakawa, S.Watanabe and H.Tanaka,” Koda’s fasting
therapy: Energy balance and intestinal bacteria flora.”
Adv Food Technol Nutr Sci Open J. 2015; 1(5): 112-123.
doi: 10.17140/AFTNSOJ-1-120[18] I.Utada, S.Moriyama, S.Hitomi, H.Honda, R.Takiguchi
and S.Watamabe, “Wellness fasting for healthy longevity.”
Adv Food Technol Nutr Sci Open J. 2016;2(3):103-109. doi:
10.17140/AFTNSOJ-2-136[19] Y.Sakamoto, M.Nishizawa, T.Sato, M/Ohno and
Y.Ikeda,”Availability of body composition instrument by
bio-inpedance method.” Proc Japan Obesity Society. 1992;
12: 244-246.
[20] S.Watanabe, M.Noboru, M.Yasunari, T.Ideura, “A crosssectional study on the effects of long term very low protein diets in patients with chronic kidney disease: Serumand urine, DEXA and amino acid profiles”. Anti Aging
Med. 2010; 7(2):7-13. doi: 10.3793/jaam.7.7[21] T.Hisada, K.Endoh and K.Kuriki, “Inter- and intra-individual variations in seasonal and daily stabilitiesof the human gut microbiota in Japanese.” Arch Microbiol(2015) 197:919–934 DOI 10.1007/s00203-015-1125-020[22] M.A.Quail, M.Smith, P.Coupland, T.D.Otto and
S.R.Harris,”A tale of three next generation sequencing
platforms: comparison of Ion Torrent, Pacific Biosciences
and Illumina MiSeq sequencers.” BMC Genom 2012;
13:341. doi:10.1186/1471-2164-13-341[23] J.Qin, R.Li, J.RaesJ, M.Arumugam, K.S.Burgdorf and
C.Manichanh, “A human gut microbial gene catalogue established by metagenomic sequencing.” Nature
2012;464:59–65. doi:10.1038/nature08821[24] L.A.David, C.F.Maurice, R.N.Carmody, D.B.Gootenberg
and J.E.Button,” Diet rapidly and reproducibly alters thehuman gut microbiome.” Nature 2014; 505:559-563.
Doi:10.1038/nature12820[25] P.Gillevet, M.Sikaroodi, A.Keshavarzian and E.A.Mutlu.”
Quantitative assessment of the human gut microbiome
using multitag pyrosequencing.” Chem Biodivers
2010;7:1065–1075. doi:10.1002/cbdv.200900322[26] Y.D.Nam, M.J. Jung, S.W.Roh, M.S.Kim and J.W.Bae JW, “
Comparative analysis of Korean human gut microbiota bybarcoded pyrosequencing. ” PLoS One 2011; 6:e22109.
doi:10.1371/journal.pone.0022109[27] S.Takahashi, J.Tomita, K.Nishioka, T.Hisada andN.Nishijima, “Development of a Prokaryotic Universal
Primer for Simultaneous Analysis of Bacteria and Archaea
Using Next-Generation Sequencing.” PLoS ONE 2014;
9(8): e105592. doi:10.1371/journal.pone.0105592[28] M.Sakamoto, A.Takagaki, K.Matsumoto, Y.Kato and
K.Goto, “ Butyricimonas synergistica gen. nov., sp. nov.
and Butyricimonas virosa sp. nov., butyric acid-producing
bacteria in the family ‘Porphyromonadaceae’ isolated

IJSER
IJSER © 2018
http://www.ijser.org

International Journal of Scientific & Engineering Research Volume 9, Issue 7, July-2018
ISSN 2229-5518

from rat faeces.” Int J Systemat Evolut Microbiol 2009;59:1748–1753 DOI 10.1099/ijs.0.007674-0[29] G.F.Cahill Jr,” Starvation in man.” New Engl J Med. 1970;
282:668-675. doi: 10.1056/NEJM197003192821209[30] E.O.Blasse,” Kinetics of ketone body metabolism in fasting humans.” Metabolism. 1979; 28(1): 41-50. doi:
10.1016/0026-0495(79)90166-5[31] M.Koda, “Science of the Fasting Therapy,” Shunju-sha,
Tokyo, Japan ISBN4-393-71301-X[32] H.Hayashi, M.Sakamoto and Y.Benno,” Fecal microbial
diversity in a strict vegetarian as detemined by molecular analysis and cultivation.” Microbiol Immunol. 2002;
46: 819-831. doi: 10.1111/j.1348-0421.2002.tb02769.
[33] S.Nishijima, W.Suda, K.Oshima, S.W.Kim and Y.Hirose,“The gut microbiome of healthy Japanese and its microbial and functional uniqueness.” DNA Research, 2016;23(2),125-133. DOI: 10.1093/dnares/dsw002[34] The Human Microbiome Project Consortium Structure,function and diversity of the healthy human microbiome.
Nature 2012; 486:207–214. doi:10.1038/nature11234[35] M.Arumugam, J.Raes, E.Pelletier, D.L.Paslier and
T.Yamada, “Enterotypes of the human gut microbiome.”
Nature 2011; 473:174–180. doi:10.1038/nature09944[36] J.J.Faith, J.L.Guruge, M.Charbonneau, S.Subramanianand H.Seedorf, “The long-term stability of the human gut
microbiota.”
Science2013;
341:1237439.
doi:10.1126/science.1237439[37] I.Martınez, C.E.Muller and J.Walter,” Long-term temporal analysis of the human fecal microbiota revealed astable core of dominant bacterial species.” PLoS One
2013;8:e69621. doi:10.1371/journal. pone.0069621[38] A.Schwiertz, D.Taras, K.Schafer, S.Beijer and N.A.Bos,”
Microbiota and SCFA in lean and overweight healthy subjects.” Obesity. 2010;18(1):190–5.
https://doi.org/10.1038/oby.2009.167[39]
S.H.Duncan,
G.E.Lobley,
G.Holtrop,
J.Ince,A.M.Johnstone and P.Louis,” Human colonic microbiota
associated with diet, obesity and weight loss.” Int J Obes
(Lond). 2008;32(11):1720–4.
[40] M.Remely, E.Aumueller, C.Merold, S.Dworzak, B.Hippe
and J.Zanner,” Effects of short chain fatty acid producing
bacteria on epigenetic regulation of FFAR3 in type 2 diabetes and obesity.” Gene. 2014;537(1):85–92.
[41] I.Marlinez, J.M.Lattimer, K.L.Hubach, J.A.Case and
J.Yang,” Gut microbiome composition is linked to wholegrain-induced immunological improvements.” The ISME
Journal 2003; 7:269-280. Doi=10.1038/ismej 2012.104[42] P.Louis and H.J.Flint,”Diversity, metabolism and microbial ecology of butyrate-producing bacteria from the human large intestine.” FEMS Microbiology Letters, Volume294, Issue 1, 1 May 2009, Pages 1–8,
https://doi.org/10.1111/j.1574-6968.2009.01514.
[43] S.H.Duncan, G.Holtrop, G.E.Lobley, A.G.Calder,
C.S.Stewart and H.J.Flint, “Contribution of acetate to butyrate formation by human faecal bacteria.” Brit J Nutr
2004;91: 915–923.
[44] P.Louis, S.H.Duncan, S.I.McCrae, J.Millar, M.S.Jackson
and H.J.Flint HJ,” Restricted distribution of the butyratekinase pathway among butyrate-producing bacteria fromthe human colon.” J Bacteriol 2004; 186: 2099-2106.

1,844[45] P.Louis, H.J.Flint, “Diversity, metabolism and microbial
ecology of butyrate-producing bacteria from the humanlarge intestine”. FEMS Microbiol Lett 2009; 294:1-8.
[46] G.Herrmann, E.Jayamani, G.Mai and W.Buckel, “Energy
conservation via electron-transferring flavoprotein in anaerobic bacteria.” J Bacteriol. 2008;190: 784–791.
[47] K.Uchino, M.Shiraki and T.Saito,”Metabolism of Poly-3Hydroxybutyrate.” Sci J Kanagawa Univ 2009; 20（2）:283-286[48] K.Uchino, T.Saito, B.Gebauer and D.Jendrossek, “Isolatedpoly(3-hydroxybutyrate) (PHB) granules are complex bacterial organelles catalyzing formation of PHB from acetylcoenzyme A (CoA) and degradation of PHB to acetylCoA.” J. Bacteriol. 2007;189:8250-6.
[49] A.Sugiyama, T.Kobayashi, M.Shiraki and T.Saito,”Rolesof poly(3-hydroxybutyrate) de- polymerase and 3HBoligomer hydrolase in bacterial PHB metabolism.”Curr.
Microbiol. 2004; 48: 424-7.
[50] T.Hisano, K.Kasuya, Y.Tezuka, N.Ishii and T.Kobayashi,”
The crystal structure of polyhydroxybutyrate depolymerase from Penicillium funiculosum provides insights into
the recognition and degradation of biopolyesters.” J. Mol.
Biol. 2006; 356: 993-1004

IJSER
IJSER © 2018
http://www.ijser.org