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Microbes andEnvironments&

October 2023

Microbes and Environments
DIGEST 2023
CONTENTS
MOST VALUABLE PAPER OF THE YEAR 2022
Phenolic Acids Induce Nod Factor Production in Lotus japonicus–Mesorhizobium Symbiosis
Masayuki Shimamura, Takashi Kumaki, Shun Hashimoto, Kazuhiko Saeki, Shin-ichi Ayabe,
Atsushi Higashitani, Tomoyoshi Akashi, Shusei Sato, and Toshio Aoki
37(1), ME21094, 2022

22

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Tomonori Kindaichi, Noriatsu Ozaki, and Akiyoshi Ohashi
36(2), ME21007, 2021

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Raoudha Jabloune, Mario Khalil, Issam E. Ben Moussa, Anne-Marie Simao-Beaunoir, Sylvain Lerat,
Ryszard Brzezinski, and Carole Beaulieu
35(1), ME19086, 2020

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MOST CITED REVIEW PAPER PUBLISHED IN THIS THREE YEARS[2020-2022] (24 citations)
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35(2), ME20025, 2020

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Microbial Ecology along the Gastrointestinal Tract

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*Times cited at the end of 2022

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Microbes Environ. 37(1), 2022

https://www.jstage.jst.go.jp/browse/jsme2 doi:10.1264/jsme2.ME21094

MOST VALUABLE PAPER OF THE YEAR 2022

Phenolic Acids Induce Nod Factor Production in Lotus japonicus–
Mesorhizobium Symbiosis
Masayuki Shimamura1†, Takashi Kumaki2†, Shun Hashimoto2, Kazuhiko Saeki3, Shin-ichi Ayabe1,
Atsushi Higashitani2, Tomoyoshi Akashi1*, Shusei Sato2*, and Toshio Aoki1
Department of Applied Biological Sciences, Nihon University, Fujisawa, Kanagawa 252–0880, Japan; 2Graduate School of Life
Sciences, Tohoku University, Sendai, Miyagi 980–8577, Japan; and 3Department of Biological Sciences and Kyousei Science
Center for Life and Nature, Nara Women’s University, Nara 630–8506, Japan

1(Received December 28, 2021—Accepted January 22, 2022—Published online March 12, 2022)

In legume–rhizobia symbiosis, partner recognition and the initiation of symbiosis processes require the mutual exchangeof chemical signals. Chemicals, generally (iso)flavonoids, in the root exudates of the host plant induce the expressionof nod genes in rhizobia, and, thus, are called nod gene inducers. The expression of nod genes leads to the productionof lipochitooligosaccharides (LCOs) called Nod factors. Natural nod gene inducer(s) in Lotus japonicus–Mesorhizobium
symbiosis remain unknown. Therefore, we developed an LCO detection method based on ultra-high-performance liquid
chromatography–tandem-quadrupole mass spectrometry (UPLC-TQMS) to identify these inducers and used it hereinto screen 40 phenolic compounds and aldonic acids for their ability to induce LCOs in Mesorhizobium japonicum
MAFF303099. We identified five phenolic acids with LCO-inducing activities, including p-coumaric, caffeic, and ferulic
acids. The induced LCOs caused root hair deformation, and nodule numbers in L. japonicus inoculated with M. japonicum
were increased by these phenolic acids. The three phenolic acids listed above induced the expression of the nodA, nodB,
and ttsI genes in a strain harboring a multicopy plasmid encoding NodD1, but not that encoding NodD2. The presence of
p-coumaric and ferulic acids in the root exudates of L. japonicus was confirmed by UPLC-TQMS, and the induction of
ttsI::lacZ in the strain harboring the nodD1 plasmid was detected in the rhizosphere of L. japonicus. Based on these results,
we propose that phenolic acids are a novel type of nod gene inducer in L. japonicus–Mesorhizobium symbiosis.
Key words: nod gene inducer, Lotus japonicus–Mesorhizobium symbiosis, phenolic acids, lipochitooligosaccharides, ultra-high-performanceliquid chromatography–tandem-quadrupole mass spectrometry

Leguminous plants are characterized by their ability forsymbiosis with a number of Gram-negative bacteria, col‐lectively known as rhizobia. Rhizobia are free-living in
soil, but change into bacteroids in the cells of specifichost plants, in which they produce ammonium from atmos‐
pheric nitrogen and provide it to the host. Host–symbiont
recognition and the initiation of symbiosis require themutual exchange of chemical signals between leguminous
plants and rhizobia. In host plants, the processes leading
to root nodulation are triggered by rhizobial signal mole‐cules called nod factors (NFs). NFs are lipochitooligosac‐
charides (LCOs) consisting of the oligomeric backbone of
β-1,4-linked N-acetyl-d-glucosamine residues N-acylated at
the non-reducing end. Chemical groups such as sulfate,fucose, and acetate, which vary according to the rhizobial* Corresponding authors.
Tomoyoshi Akashi: E-mail: akashi.tomoyoshi@nihon-u.ac.jp;
Tel: +81–466–84–3353; Fax: +81–466–84–3353.
Shusei Sato: E-mail: shuseis@ige.tohoku.ac.jp;
Tel: +81–22–217–5688; Fax: +81–22–217–5691.
† These authors contributed equally to this work.
Toshio Aoki: deceased.
Citation: Shimamura, M., Kumaki, T., Hashimoto, S., Saeki, K.,
Ayabe, S., Higashitani, A., et al. (2022) Phenolic Acids Induce
Nod Factor Production in Lotus japonicus–Mesorhizobium Symbiosis.
Microbes Environ 37: ME21094.
https://doi.org/10.1264/jsme2.ME21094

2

strain, may substitute the oligosaccharide backbone (Lianget al., 2014). The transmembrane receptor kinases of thehost plant recognize specific NF structures and transmit asignal that triggers a series of symbiotic events, including
root hair deformation, the formation and elongation of infec‐
tion threads, and the induction of nodule primordia (Suzaki
et al., 2015). The induction of NF biosynthesis requires
specific low-molecular-weight compounds exuded from theroots of the host plant, which are recognized by the rhizobial
receptor NodD (Liu and Murray, 2016). When bound to thehost-derived ligand, NodD serves as a transcription factor;
it binds to cis elements called nod boxes and induces thetranscription of a series of flanking genes, including nod
genes, which encode enzymes involved in NF biosynthesis(Recourt et al., 1989; Begume et al., 2001; Liu and Murray,2016). Therefore, these plant factors are called nod geneinducers. They include flavonoids and related compounds,
such as flavanones, flavones, isoflavones, and chalcones,
and function at very low concentrations of 10–100 μM(Peters et al., 1986; Kosslak et al., 1987; Hungria et al.,1991). A nod box is also located upstream of the rhizobial
type III secretion system (T3SS) cluster containing the ttsI
gene (Okazaki et al., 2010). T3SS secretes effector proteinsthat affect symbiosis in host plant cells (Okazaki et al.,2013; Sugawara et al., 2018; Kusakabe et al., 2020).
Lotus japonicus, together with barrel medic (Medicago
truncatula) and soybean (Glycine max), is a legumi‐
nous model system for molecular genetics and genomics
Article ME21094

Shimamura et al.

(Handberg and Stougaard, 1992; Udvardi et al., 2005; Satoand Tabata, 2006). Data from whole-genome analyses ofthese species have provided insights into the origin andadaptive evolution of diverse leguminous plants (Cannon
et al., 2006; Hougaard et al., 2008; Sato et al., 2008;
Young and Bharti, 2012; O’Rourke et al., 2014). A moredetailed understanding of symbiotic nitrogen fixation may
be obtained by comparing the underlying molecular mech‐anisms among the three models. The reported nod geneinducers that act on Mesorhizobium strains, the symbionts of
L. japonicus, are aldonic acids and related compounds, suchas erythronic acid, tetronic acid, and succinic anhydride(Gagnon and Ibrahim, 1998). However, the induction of
NF production in Mesorhizobium strains requires 10 mM
tetronic acid or even higher concentrations of erythronic
acid and succinic anhydride, more than a thousand-foldhigher than those required for NF production in the sym‐
bionts of other legumes (Gagnon and Ibrahim, 1998). Fur‐thermore, aldonic acids have not been detected in the root
exudates or root tissues of L. japonicus. Therefore, thenatural nod gene inducers of L. japonicus–Mesorhizobium
symbiosis have not yet been identified.
Structural analyses using ultra-high-performance liq‐
uid chromatography coupled to quadrupole-time-of-flight(UPLC-QTOF) mass spectrometry (MS) and high-magneticfield nuclear magnetic resonance spectroscopy revealed that
Mesorhizobium NFs are a mixture of four major and fourminor LCOs that vary in the fatty acid type, the number ofcarbamoyl groups at the non-reducing end, and the numberof acetyl groups attached to fucose at the reducing end (Beket al., 2010). In the present study, we aimed to identify
natural substances that are exuded from L. japonicus roots
and act on Mesorhizobium strains as nod gene inducers bydirectly assaying NF production. We developed an assay
method in which LCOs were extracted from small-scalecultures of Mesorhizobium strains in the presence of thecandidate chemical compound and specifically detected by
UPLC–tandem-quadrupole MS (TQMS). UPLC-TQMS isa convenient method for routine assays; however, its resolu‐
tion is inferior to QTOF MS. We used this method to screen
authentic samples of aldonic acids, flavonoids, and related
phenolic compounds (instead of the fractionation of plant
extracts or root exudates), and then examined the presenceof the identified target compounds in the root exudates of L.
japonicus. We identified five phenolic acids that induce NF
production in Mesorhizobium strains.
NodD in Rhizobium leguminosarum is activated by naringe‐
nin, a nod gene inducer from Medicago sativa (Firmin et al.,1986). When the heterologous nodD of R. leguminosarum wasintroduced into Mesorhizobium japonicum MAFF303099(reclassified from M. loti based on genome sequence infor‐
mation; Martínez-Hidalgo et al., 2016) via a multicopy plas‐
mid, the application of naringenin induced NF production(López-Lara et al., 1995; Niwa et al., 2001; Bek et al., 2010)
and the expression of the ttsI gene, the regulator of T3SS
(Okazaki et al., 2010). Using a similar approach, namely,
the introduction of endogenous nodD genes encoded bymulticopy plasmids, we herein established which of the
two NodD receptors, NodD1 or NodD2, of M. japonicum
MAFF303099 interacted with the identified phenolic acids.

Materials and Methods
Chemicals
The following materials were purchased from the suppliers
indicated in parentheses: chlorogenic acid (MP Biomedicals);
gossypetin (Indofine Chemical Company); butein, eriodictyol, for‐mononetin, herbacetin, isorhamnetin, kaempferol, myricetin, andquercetin (Extrasynthèse); daidzein and genistein (LC Laborato‐ries); vestitol (Plantech); apigenin, biochanin A, coniferyl alcohol,
o-coumaric acid, m-coumaric acid, coumestrol, 5-hydroxyferulic
acid, luteolin, naringenin, phloretic acid, sinapic acid, and umbelli‐ferone (Merck); p-coumaric acid, erythronic acid, isoferulic acid,and succinic anhydride (TCI); caffeic acid, trans-cinnamic acid,
3,4-dimethoxycinnamic acid, ferulic acid, p-methoxycinnamic
acid, phenylalanine, tetronic acid, and L-tyrosine (FUJIFILM
Wako Pure Chemical). Umbellic acid was prepared from umbelli‐ferone by a treatment with 1 M NaOH at 90°C for 1 h. Isoliquir‐
itigenin was obtained from our laboratory stock (Shimamura etal., 2007).
NFs (LCOs) and Mesorhizobium strains
The plasmid pMP2112 encoding R. leguminosarum bv. trifolii
nodD (López-Lara et al., 1995) and a sample of the NF derived
from M. japonicum MAFF303099 harboring pMP2112 were pro‐vided by H. Kouchi of the International Christian University,
Japan. pMP2112 was transferred into M. japonicum MAFF303099(Kaneko et al., 2000; Saeki and Kouchi, 2000).
The bacterial strains and plasmids used in the present study aresummarized in Supplementary Table S1. The nodD1 and nodD2
deletion (ΔnodD1-nodD2) variant of M. japonicum MAFF303099
was generated by homologous recombination as described by
Hattori et al. (2002). The cosmid c243 was digested with BamHI
and ligated with a 1.9-kbp BamHI fragment of the kanamycin
resistance gene neo from pUCKM1 (Saeki et al., 1991). In
the resultant knockout plasmid pEMA49, the nodD1 (mll6179)–
nolL (mlr8757)–nodD2 (mlr6182)–mll6183–mlr6185 region was
replaced with the neo gene. The generated allele was homogeno‐
tized with the endogenous genomic locus in M. japonicum to pro‐
duce the ΔnodD variant. The construct was verified by Southernhybridization using c243 as a probe.
The nodA deletion (ΔnodA) variant was constructed essentiallyas described above, but with the precise in-frame deletion of the
NodA coding region. An allele in which nodA was replaced withthe spectinomycin resistance gene aadA was constructed by PCR
amplification from pKST001R (Hanyu et al., 2009) with primers
to add overhangs (wan_mlr8755_upper and wan_mlr8755_lower).
The amplified allele was then exchanged in Escherichia coli withthe endogenous mlr8755 allele in the cosmid c242.1 (Hattori
et al., 2002) in the presence of the phage lambda Red recom‐
binase (Datsenko and Wanner, 2000) to generate the knockout
plasmid pML8755DA. The correct construction of the ΔnodA var‐iant was verified by PCR with the primers KS_nodSJ_F01S and
KSnodC_Rev01 as well as by Southern hybridization using thewild-type PCR product as a probe.
In the functional analysis of nodD, the nodD1 and nodD2
genes were introduced separately into M. japonicum MAFF303099
and ML033 (Okazaki et al., 2010) as follows. The 1,272bp fragment containing the coding and promoter regionsof nodD1 (mlr6182) and the 1,365-bp fragment containing
those of nodD2 (mll6179) were amplified by PCR with theprimer pairs pBBR1_nodD1_Fw and pBBR1_nodD1_Rv, andpBBR1_nodD2_Fw and pBBR1_nodD2_Rv, respectively (Supple‐
mentary Table S2). PCR products were cloned into pBBR1MCS-2(Kovach et al., 1995) by In-Fusion HD cloning (Clontech). The
plasmids obtained (pMj-NodD1 and pMj-NodD2, respectively)
were introduced separately into E. coli DH5α and mobilized into
M. japonicum MAFF303099 using the previously described bacte‐rial conjugation system (Kusakabe et al., 2020). One day after

2 / 12

Article ME21094

3

nod Gene Inducers in L. japonicus–Mesorhizobium Symbiosis
conjugation, transformants containing pMj-NodD1 or pMj-NodD2
were selected on tryptone–yeast-extract plates containing 100 μg
mL–1 phosphomycin and 50 μg mL–1 kanamycin. Plasmid transfer
was confirmed by PCR.
Culture conditions for M. japonicum MAFF303099 and extractionof LCOs
M. japonicum MAFF303099 was pre-cultured in TY medium
at 28°C overnight. An aliquot of the culture was diluted withfresh TY medium (10 mL, OD660=0.001) and supplemented withthe antibiotics and phenolics shown in Table 1. Regarding M.
japonicum MAFF303099 carrying pMP2112, antibiotics and nar‐ingenin (final concentration, 1 μM) were added to the culture
medium. Diluted cultures were grown at 28°C for 24 h, centri‐
fuged (8,000×g, room temperature, 2 min), and LCOs were thenextracted from the supernatants with n-butanol.
Extraction of root exudates from legume seedlings
The seeds of alfalfa (M. sativa), red clover (Trifolium pratense),and L. japonicus B-129 Gifu were sterilized with solution
containing 2% (v/v) sodium hypochlorite and 0.02% (v/v)
Table 1.

Class

Flavanones
Flavones
Flavonols

Isoflavones

Isoflavans
Coumestans
Aldonic acids

UPLC-TQMS analysis
The butanol extracts of bacterial cultures and the ethanol
extracts of root exudates were concentrated by evaporation,
dissolved in 50% acetonitrile, and filtered through polytetra‐
fluoroethylene membrane filters (Merck). UPLC analyses wereconducted on Quattro Premier XE (Waters). Separation was per‐formed on an Acquity UPLC BEH C18 column (2.1×100 mm,
Waters) at 40°C and a flow rate of 0.38 mL min–1. Gradient elu‐tion was performed with 0.1% formic acid in water (A) and
0.1% formic acid in acetonitrile (B) as follows. LCOs: 44% B(0–4 min), 44–85% B (4–7 min), 85–99.5% B (7–7.1 min), 99.5%
B (7.1–7.2 min); root exudates: 5–15% B (0–7 min), 15–99% B(7–10 min).

NF (LCO)-inducing activities of compounds tested in the present study.
Compound
PubChem CID
Activity*

Phenylpropanoids

Chalcones

Tween-20 for 10 min, rinsed five times with sterilized distilledwater, and immersed in sterilized distilled water at room tem‐
perature overnight. They were then sown in a plastic container
containing B&D liquid medium (pH 6.8) and cultivated at 25°C
(16 h light/8 h dark) for 7 days. Media containing seedlingexudates were collected and loaded onto Oasis HLB cartridges(Waters), and exudate components were eluted with ethanol.

l-Phenylalanine (1)l-Tyrosine (2)trans-Cinnamic acid (3)p-Coumaric acid (4)Caffeic acid (5)Ferulic acid (6)5-Hydroxyferulic acid (7)Sinapic acid (8)Coniferyl alcohol (9)Umbellic acid (10)Umbelliferone (11)Chlorogenic acid (12)Phloretic acid (13)o-Coumaric acid (14)m-Coumaric acid (15)3,4-Dimethoxycinnamic acid (16)Isoferulic acid (17)p-Methoxycinnamic acid (18)
ButeinIsoliquiritigenin(2S)-Eriodictyol(2S)-Naringenin
Apigenin
Luteolin
Gossypetin
Herbacetin
Isorhamnetin
Kaempferol
Myricetin
Quercetin
Biochanin A
Daidzein
Formononetin
Genistein
Pseudobaptigenin(3R)-Vestitol
Coumestrol
Erythronic acid (lactonized)
Succinic anhydride
Tetronic acid (lactonized)

6140
6057
4445396375426890434458584468346377751549095
4466115281426
179442710394
63754063754171753173618669941452812226382784407354392465280443
5280445528064752805445281654528086352816725280343
52803735281708528037852809615281805
182259528170753259157922
521261

–
–
–
+
+
++
+
–
–
–
–
–
+
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–

*: ++ and + indicate LCO-inducing activity at 0.3 mg L–1 (++) and 15 mg L–1 (+); – no activity.

4

3 / 12

Article ME21094

Shimamura et al.
MS spectra were acquired with Quattro Premier v. 4.1 software(Waters) under the following conditions. Qualitative analyses: theselected ion recording (SIR) mode, electrospray ionization (ESI)
positive mode, capillary voltage 3.0 kV, cone voltage 30 V, desol‐
vation gas flow rate 800 L h–1 at 400°C, cone gas flow rate
50 L h–1, and source temperature 120°C. Quantitative analyses: theselected reaction monitoring (SRM) mode; conditions describedabove except that the capillary voltage was 3.5 kV and the cone
voltage was 50 V. SRM conditions for phenolic acids in root exu‐
dates are shown in Supplementary Table S3.
Isolation of rhizobia from root nodules of L. japonicus
Mature L. japonicus plants collected near the coast of
Kanagawa, Japan, were dubbed “Bishamon” (34°54'10.3"N
139°53'15.7"E) and “Nojimazaki” (35°08'26.5"N 139°39'36.0"E).
Nodules were harvested, and their surfaces were sterilized withsolution containing 2% (v/v) sodium hypochlorite and 0.02% (v/v)
Tween-20 for 10 min and then rinsed five times with sterilized
distilled water. Nodules were crushed individually with a pestle
in the presence of 40% glycerol, and the homogenates werespread on TY agar medium at 28°C for 10–14 days. A rhizobialcolony was isolated from each nodule and named Bishamon1-c2
or Nojimazaki1-a1. Nodule formation by the isolated rhizobia
in L. japonicus B-129 Gifu was examined according to Aoki
et al. (2021). The procedure for LCO extraction from rhizobia,
namely, Bishamon1-c2, Nojimazaki1-a1, and Tono (Kawaguchi etal., 2002), was the same as that for M. japonicum MAFF303099
described above.
Root hair deformation assay
The root hair deformation assay was performed with the nbutanol extract of M. japonicum MAFF303099 according to previ‐
ously described methods, except that B&D liquid and agar media
adjusted to pH 6.8 (Broughton and Dilworth, 1971) were usedinstead of half-strength nitrogen-free HM nutrients (ImaizumiAnraku et al., 1997). LCOs were extracted with n-butanol from
cultures of M. japonicum MAFF303099 treated with caffeic acidand purified on a solid-phase extraction column. An n-butanol
extract prepared from mock-treated M. japonicum was used as acontrol. Purified LCOs and the control sample were used to treat
7-day-old L. japonicus B-129 Gifu for 24 h, and the roots were
stained with toluidine blue and observed by light microscopy.
Expression analysis of ttsI, nodA, and nodB genes
To analyze the transcriptional regulation of the ttsI gene byphenolic acids, we used a chromosomally integrated translationallacZ fusion with the ML033 ttsI promoter (ML033) as previ‐
ously described (Okazaki et al., 2010). In the β-galactosidase
assay, approximately 50 μL of pre-cultured (stationary phase)
Mesorhizobium strains were inoculated into 5 mL of TY liquidmedium (OD660 0.01) in 50-mL tubes and grown for 21 h with orwithout phenolic acids at a final concentration of 10 μM.
β-Galactosidase activity was assessed in a microplate assay as
previously described (Griffith and Wolf, 2002). The expression of
the nodA and nodB genes was analyzed by qRT-PCR. Pre-cultured(mid-log phase) Mesorhizobium strains (1.5 mL) were inoculated
into 1.5 mL of TY liquid medium in 15-mL tubes with or without
phenolic acids at a final concentration of 10 μM and grown for
4 h. Bacterial RNA was stabilized by adding RNAprotect Bacteria
Reagent (Qiagen) and extracted with an RNeasy Mini kit (Qiagen),and purified total RNA was then treated with Recombinant DNase
I (Takara Bio). cDNA was synthesized from total RNA using an
ExScript RT Reagent Kit (Takara Bio). The primer pairs usedin the qRT-PCR analysis are listed in Supplementary Table S2.
All qRT-PCR measurements were performed in a C1000 Thermal
Cycler (Bio-Rad) with a Kapa SYBR Fast qPCR Kit (Kapa Biosys‐tems). The relative expression of the selected genes was calculated
as 2–ΔΔCt using the 16S rRNA gene as a reference. All experiments
were performed for three technical and three biological replicates.

The primers used to assess the expression levels of the various
target genes are listed in Supplementary Table S2.
Root X-Gal staining assay
L. japonicus MG-20 plants were grown for 10 days on 1/2 MS
medium agar plates, and ML033, ML033/pMj-nodD1, or ML033/
pMj-nodD2 suspensions containing approximately 108 cells were
inoculated onto the root surface with low melting point agar
containing 0.02% X-Gal. Low melting point agar containing
0.02% X-Gal without rhizobia cells was used as a mock control.
Blue staining was observed after a 2-days incubation at 25°C.

Results
Screening of compounds for LCO-inducing activity inrhizobia based on direct LCO detection by UPLC-TQMS
To detect NF production with high sensitivity and repro‐
ducibility, we established an analytical method to detect
LCOs in rhizobial culture media using UPLC-TQMS. Whenan authentic LCO sample was analyzed in the SIR mode by
UPLC-TQMS, a major peak appeared with a retention timeof 5–5.5 min and a minor peak appeared after 6 min (Fig.
1a). To monitor an authentic LCO, we set the m/z value to1502.7 based on the consecutive mass spectra of the major
peak (Fig. 1b), which we presumed to correspond to previ‐
ously reported NodMl-V (C18:1, Me, Cb, AcFuc) (LópezLara et al., 1995; Niwa et al., 2001; Bek et al., 2010).
The analysis of LCOs extracted from the culture mediumof M. japonicum MAFF303099 carrying the pMP2112 plas‐
mid, which harbored nodD from R. leguminosarum, in thepresence of 1 μM naringenin also revealed a major peak at
5–5.5 min (Fig. 1a).
The established analytical method was used to test
the LCO-inducing activities of 40 phenolic compounds,
including phenylpropanoids, chalcones, flavanones, fla‐vones, flavonols, isoflavones, an isoflavan, and a coume‐
stan, as well as aldonic acids that were previously reported
to exhibit nod gene-inducing activity (Table 1). LCO induc‐tion was analyzed by culturing M. japonicum MAFF303099
with 0.3 or 15 mg L–1 of the tested compounds, followedby n-butanol extraction of the culture medium and UPLCTQMS analyses using the SIR mode at m/z 1502.7 (Fig.
1b). LCO was produced in the presence of five phenolicacids at 15 mg L–1: p-coumaric acid (4), caffeic acid (5),ferulic acid (6), 5-hydroxyferulic acid (7), and phloretic
acid (13) (Fig. 1c and Table 1). Only ferulic acid (6) pro‐
moted LCO production at 0.3 mg L–1 (Table 1). Amongthe 40 compounds tested, the remaining 35 compounds,
including cinnamic acid, produced few or no LCOs (Table1). We evaluated the reproducibility of LCO-inducing activ‐
ities at various concentrations of these five phenolic acids
employing the SRM mode of UPLC-TQMS and found that
their activity increased in different concentration-dependent
manners up to 100 μM (Fig. 1d). At 1 μM, only ferulic
acid (6) was active, and its activity was the highest among
the five inducers at 10 μM. In contrast, caffeic acid (5)showed weak activity up to 10 μM, but was the most active
inducer at 100 μM. p-Coumaric acid (4), 5-hydroxyferulic
acid (7), and phloretic acid (13) were only active at 100 μM(Fig. 1d).
Using the deletion variants of M. japonicum
MAFF303099, we confirmed that the LCO-inducing activi‐

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nod Gene Inducers in L. japonicus–Mesorhizobium Symbiosis

ties of p-coumaric acid (4), caffeic acid (5), and ferulic acid(6) depended on the nodA and nodD genes (Supplementary
Fig. S1).
Phenolic acids induce LCO production in native
Mesorhizobium strains
To investigate whether the phenolic acids identified
by screening using M. japonicum MAFF303099 generally
induce LCOs in native L. japonicus rhizobia, we tested three
additional Mesorhizobium strains isolated from native L.
japonicus: Tono (Kawaguchi et al., 2002), Nojimazaki 1-a1,
and Bishamon 1-c2 (the present study). The phenolic acids
tested, namely, p-coumaric acid (4), caffeic acid (5), ferulic
acid (6), and 5-hydroxyferulic acid (7), produced LCOs withgood reproducibility and at levels that were significantly
higher (25- to 60-fold) in all native Mesorhizobium strains
than in M. japonicum MAFF303099 (Fig. 2a). No adverse
effects of these phenolic acids on the growth of rhizobia
were observed at the concentrations used (Fig. 2b).
Biological activities of phenolic acids toward the host plant
L. japonicus
To examine the abilities of the LCOs produced to func‐tion as NFs for L. japonicus, we assessed their root hair
deformation activities. The root hairs of L. japonicus treatedwith 1 nM LCOs, which were induced by 100 μM caffeic
acid, showed bending deformation, and some root hair tips
were curled (Supplementary Fig. S2a, b, and c). The con‐trol sample had no effect on root hairs (Supplementary
Fig. S2d).
Exogenous nod gene inducers have been shown toincrease the nodule number in pea and soybean (Novák
et al., 2002; Pan et al., 2008); therefore, we tested theeffects of phenolic acids on L. japonicus inoculated with
M. japonicum. The number of mature nodules significantly
increased after 4 weeks in the presence of 10 μM ferulic
acid (Fig. 3a and b) or 10 μM caffeic acid (Fig. 3c).

Phenolic acids induce the production of NFs (LCOs) inMesorhizobium japonicum MAFF303099. UPLC-TQMS analysis of anauthentic LCO sample and naringenin-induced LCOs in M. japonicum
harboring pMP2112. Chromatograms recorded by the SIR mode at
m/z 1502.7 (a) and the mass spectrum at a retention time of 5.41 min(b). (c) UPLC-TQMS analysis of LCOs produced in M. japonicum
MAFF303099 after the application of the indicated compounds at
15 mg L–1. (d) LCO production induced by different concentrationsof phenolic acids listed in (c). Error bars show S.E. (n=4).
Fig. 1.

6

NodD1 acts as a receptor for phenolic acids
Rhizobia perceive nod gene inducers, such as flavo‐
noids, through their binding to the transcriptional activator
NodD, which up-regulates the expression of nod genes
and the ttsI gene, a regulator of T3SS (Firmin et al.,
1986; Okazaki et al., 2010). To examine transcriptional
responses to the identified phenolic acids, we used M.
japonicum ML033, in which the translational fusion oflacZ with ttsI was integrated into the chromosome of M.
japonicum MAFF303099 (Okazaki et al., 2010). No signifi‐
cant increases in β-galactosidase activity were detected in
the presence of 1 μM p-coumaric acid (4), caffeic acid(5), or ferulic acid (6) (Fig. 4a). We then introduced oneof the endogenous nodD genes via a multicopy plasmid,
followed by an analysis using pMP2112 harboring nodD
from R. leguminosarum. We constructed separate multicopy
plasmids harboring nodD1 (pMj-NodD1) or nodD2 (pMjNodD2), and transferred them into M. japonicum ML033.
After a 21-h culture with 1 μM p-coumaric acid (4), caf‐
feic acid (5), or ferulic acid (6), β-galactosidase activity
significantly increased in ML033/pMj-NodD1, but not in
ML033/pMj-NodD2 (Fig. 4a). Induction levels were similar

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Production of LCOs and growth of Mesorhizobium strains isolated from different locations in the presence of phenolic acids. (a) LCO
production in M. japonicum MAFF303099, Tono, Nojimazaki 1-a1, and Bishamon 1-c2. (b) Growth of the strains tested in panel (a). Error bars
show S.E. (n=3 or 4).
Fig. 2.

to that with 1 μM naringenin in ML033/pMP2112 (Fig. 4a),which carries nodD from R. leguminosarum (López-Laraet al., 1995). In contrast, cinnamic acid (3), which did not
induce LCO production in the screening described above,
did not induce β-galactosidase activity in any of the strains(Fig. 4a).
The concentration dependence of β-galactosidase activity
in ML033/pMj-NodD1 induced by each phenolic acid (10nM to 10 μM) is shown in Fig. 4b. p-Coumaric acid (4)and ferulic acid (6) both significantly induced activity at thelowest concentration tested (10 nM), whereas caffeic acid(5) only induced it at 1 and 100 μM. This concentration
dependence was similar to that observed in the direct detec‐tion of LCO production (Fig. 1).
We then conducted qRT-PCR to investigate whether phe‐nolic acids induce the transcriptional activation of the NF
biosynthesis genes nodA and nodB using the ML033/pMjNodD1 strain. The nodA gene was significantly induced by
1 μM ferulic acid (6) and caffeic acid (5), while the nodB
gene was significantly induced at both 1 and 10 μM, similar
to the ttsI gene (Fig. 5). Caffeic acid (5) exerted similareffects to ferulic acid (6) (Fig. 5). As in the β-galactosidase
assay, cinnamic acid (3) did not induce nodA, nodB, or ttsI
expression (data not shown). The above results revealed
that the M. japonicum NodD1 receptor recognizes phenolicacids, such as ferulic and caffeic acids, and activates thetranscription of the nod genes.
Phenolic acids exuded from legume roots
To elucidate whether phenolic compounds were exuded

from the roots of L. japonicus, we used the SRM mode of
UPLC-TQMS to analyze the components of culture media
7 days after hydroponic cultures of L. japonicus, red clover,
and alfalfa. The levels of five phenolic acids that induce
the production of NFs (p-coumaric acid [4], caffeic acid [5],ferulic acid [6], 5-hydroxyferulic acid [7], and phloretic acid[13]) and those of phenolic acids that do not (cinnamic acid[3] and sinapic acid [8]) were quantified. p-Coumaric acid(4) and ferulic acid (6) were detected in hydroponic media
from all three plant species, with the levels of p-coumaricacid (4) being higher in exudates from L. japonicus (Table
2). Cinnamic acid (3) was only secreted by L. japonicus(Table 2). Trace levels (0.2 nmol g–1 FW plants or 0.6 nmol
mg–1 root exudate) of caffeic acid (5), sinapic acid (8), andphloretic acid (13) were detected, whereas 5-hydroxyferulic
acid (7) was undetectable (less than 0.2 nmol g–1 FW plantor 0.6 nmol mg–1 root exudate) in either legume.
To monitor the induction of the ttsI::lacZ fusion in
ML033 series strains in the rhizosphere of L. japonicus,
approximately 108 rhizobial cells were spread on the rootsof 10-day-old seedlings grown on agar medium with X-Gal.
The inoculation with the ML033/pMj-NodD1 strain resulted
in X-gal blue staining on and around the root surface (Sup‐plementary Fig. S3). The inoculation of the ML033/pMjNodD2 strain resulted in X-gal staining only on the root
surface. These results strongly suggest that phenolic acid(s)activating NodD1 were exuded not only on the root surface,but also into the rhizosphere of L. japonicus.

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nod Gene Inducers in L. japonicus–Mesorhizobium Symbiosis

Fig. 3. Promotion of nodulation by phenolic acids. (a) Typical images of 4-week-old Lotus japonicus MG-20 inoculated with Mesorhizobium
japonicum MAFF303099 in the absence or presence of ferulic acid. Scale bars: 1 cm. (b, c) Number of mature nodules in the absence or presenceof (b) ferulic acid or (c) caffeic acid. Error bars show S.E. (n=22–27). Significant differences between the absence (mock) and presence ofphenolic acids were assessed by the Student’s t-test (** P<0.01, * P<0.05, ns, not significant).

Discussion
The nod gene inducer in L. japonicus–Mesorhizobium
symbiosis has not been identified despite decades ofresearch. Therefore, we developed a highly sensitive method
to analyze LCOs using UPLC-TQMS. MS was previously
applied to the study of LCOs, mainly for a structural ana‐
lysis (Niwa et al., 2001; Bek et al., 2010). To use MS
for screening, we simplified purification and reduced therequired culture volume, which allowed us to evaluate 40
phenolic compounds. Among them, we identified five phe‐nolic acids that had the potential to induce LCO productionin M. japonicum MAFF303099. The production of LCOs
was enhanced by increases in the concentrations of eachof these phenolic acids. LCOs produced by M. japonicum
MAFF303099 in the presence of caffeic acid (5) induced
root hair deformation, and nodule numbers in L. japonicus
8

inoculated with M. japonicum were increased by the addi‐
tion of ferulic acid (6) and caffeic acid (5). These results
clearly identified phenolic compounds, but not flavonoids,
as nod gene inducers. Phenolic acids are produced via shiki‐
mic acid through the phenylpropanoid pathway, and also as
intermediates of the monolignol pathway in vascular plants.
A previous study reported that rhizobia utilized phenolicacids as carbon sources (Blum et al., 2000). A number of
nod gene inducers have been identified in legumes, andmost of them are (iso)flavonoids (Liu and Murray, 2016); tothe best of our knowledge, this is the first study to demon‐
strate that phenolic acids function as nod gene inducers.
The identified candidate nod gene inducers of L.
japonicus are phenylpropanoids with a carboxylic acidgroup, in contrast to coniferyl alcohol (9) and chlorogenic
acid (12) (Fig. 6). A comparison with phenolic acids that
did not induce LCOs (Table 2), i.e. l-phenylalanine (1),7 / 12

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Fig. 4. Effects of phenolic acids on the expression of lacZ-fused ttsI. (a) Effects of harboring pMj-NodD1, the pMj-NodD2 plasmid, or pMP2112
on β-galactosidase induction by the indicated phenolic acids (1 μM). (b) β-Galactosidase activity in Mesorhizobium japonicum MAFF303099
harboring pMj-NodD1 in the presence of different concentrations of the phenolic acids tested in the panel (a). Error bars show S.E. (n=3 or 4).
Significant differences between the absence (mock) and presence of phenolic acids were assessed by the Student’s t-test (** P<0.01).

trans-cinnamic acid (3), umbellic acid (10), o-coumaric acid(14), m-coumaric acid (15), 3,4-dimethoxycinnamic acid(16), isoferulic acid (17), and p-methoxycinnamic acid (18),suggested that a hydroxyl at C-4 and a hydrogen at C-2
or C-6 are important for the ability to induce NFs in M.
japonicum (Fig. 6). A single methoxy group did not pre‐clude LCO-inducing activity, whereas two methoxy groups,
as in sinapic acid (8), did. A double bond between α and βcarbons appears to be important for the induction of LCO
production, but is not essential because weak induction was
detected with phloretic acid (13). Therefore, the basic struc‐ture of a nod gene inducer appears to be that of p-coumaricacid (4) with at most a single methoxy group at C-3 orC-5 and hydrogens at C-2 and C-6. We suggest that the
carboxylic acid group and the C-3, C-4, and C-5 positions of
the phenyl ring were recognized by NodD.
Aldonic acids have been shown to promote LCO bio‐synthesis in Mesorhizobium strains (Gagnon and Ibrahim,
1998). In our experiments, none of the three aldonic acidcompounds tested induced LCO production at the concen‐
trations at which the five phenolic acids induced it. Gagnon
and Ibrahim (1998) identified aldonic acids in the root
exudates of Lupinus albus by screening based on measure‐ments of the β-galactosidase activities of Rhizobium lupinistrains harboring nodC::lacZ fusions, and 10 mM tetronic
acid was required to induce detectable LCO production in
M. japonicum R7A. We only tested concentrations up to

100 μM, which may explain why the aldonic acids tested
did not induce LCOs. Since tetronic acid was not detectedin the root exudates or seed metabolites of L. japonicus(Hashiguchi et al., 2018), aldonic acids cannot be endoge‐
nous nod gene inducers of L. japonicus.
In contrast to aldonic acids, the presence of p-coumaricacid (4), ferulic acid (6), and trans-cinnamic acid (3) was
confirmed in the root exudates of L japonicus (Table 2). In
addition, p-coumaric acid (4) and ferulic acid (6) are listed
as metabolites in the seeds of experimental and wild acces‐
sions of L. japonicus in LegumeBase, the resource databaseof National BioResource Project Lotus/Glycine (Hashiguchi
et al., 2018). Phenolic acids have also been reported in
the root exudates of other legume and non-legume plants(Mandal et al., 2010). We identified p-coumaric acid (4)and ferulic acid (6) in the root exudates of T. pratenseand M. sativa (Table 2), and, thus, these phenolic acids do
not appear to contribute to host specificity. Since phenolicacids are generally present in the rhizosphere, the responses
of Mesorhizobium strains to them may contribute to theirassociations with a broad range of plants, including nonhost plants. M. japonicum MAFF303099 associates with
non-host plants, such as Arabidopsis thaliana (Poitout et al.,2017), as a root epiphyte. T3SS may play a role in this rela‐tionship, as reported in Bradyrhizobium strains (Piromyou
et al., 2015). In the present study, the expression of ttsI, aregulator of the T3SS gene cluster, was induced by phenolic

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nod Gene Inducers in L. japonicus–Mesorhizobium Symbiosis

Fig. 5. qRT-PCR analysis of the expression of nodA, nodB, andttsI genes in Mesorhizobium japonicum MAFF303099 harboring pMjNodD1 in the absence or presence of (a) ferulic acid or (b) caffeic acid.
Error bars show S.E. (n=3 or 4). Significant differences between theabsence (mock) and presence of phenolic acids were assessed by theStudent’s t-test (** P<0.01, * P<0.05, ns, not significant).

acids at higher levels than that of nodA in M. japonicum
MAFF303099 carrying pMj-NodD1 (Fig. 5). Therefore,
phenolic acid recognition by Mesorhizobium strains may
have a function against non-host plants by inducing T3SS.
Regarding host specificity, differences in the concentrationsof phenolic acids in root exudates may affect host specific‐
ity in L. japonicus–Mesorhizobium symbiosis because theconcentration of p-coumaric acid (4) in the root exudatesof L. japonicus was more than ten-fold higher than thosein the root exudates of red clover and alfalfa (Table 2).
The NF receptors of host plants are important for recogni‐tion that affects the host range in plant–rhizobia symbiotic
interactions (Radutoiu et al., 2007; Bek et al., 2010). We
Table 2.

confirmed the function of LCOs induced by caffeic acid (5)as endogenous NFs for L. japonicus by demonstrating theirability to induce root hair deformation (Supplementary Fig.
S2). The number of mature nodules was increased by theaddition of phenolic acid-type nod gene inducers together
with an inoculation with M. japonicum (Fig. 3), as previ‐
ously reported in pea and soybean (Novák et al., 2002; Panet al., 2008). Therefore, the recognition of phenolic acids by
Mesorhizobium strains may function in two ways: the pro‐duction of T3SS may contribute to associations with a wide
range of plants, and, at the same time, the production of
LCOs may function in host recognition in symbiotic interac‐tions.
Although we confirmed LCO production after treatmentswith five phenolic acids, we failed to detect the induction of
nod genes by RT-PCR or ttsI expression using its promoter
fused to lacZ in the genome (Fig. 4a). The transcript levelsof genes regulated by NodD may be below the detectionlevel of normal RT-PCR and a single copy of lacZ in the
genome of M. japonicum MAFF303099; this may explain
our failure to identify nod gene inducers in L. japonicus–
Mesorhizobium symbiosis, even though it has been widelyused as a model of symbiosis in legume plants (Liu andMurray, 2016). The nodA promoter fused to lacZ in a
multicopy plasmid (pMP220) has been used to detect lacZ
expression in M. japonicum MAFF303099 (Kojima et al.,2012). We adopted this approach and attempted to increase
the copy number of nodD genes by introducing nodD1 or
nodD2 into a multicopy plasmid. This analysis revealed that
NodD1 was more sensitive to phenolic acids than NodD2,
indicating a functional differentiation between NodD1 andNodD2 with regards to the perception of phenolic acidsignals. In M. japonicum R7A, NodD1 and NodD2 arefunctionally redundant for nodulation, with nodD1 mutants
exhibiting only a slight delay in nodulation (Rodpothong
et al., 2009). Kelly et al. (2018) showed the preferential
activation of NodD1 and NodD2 by different compounds
produced at defined stages of symbiotic infection. NodD1
is primarily involved in the induction of downstream genes
within root hair infection threads. Since phenolic acids areintermediates in the biosynthesis of a number of phenolic
compounds, such as flavonoids and monolignols, it is rea‐
sonable that they act as nod gene inducers in root hair infec‐
tion threads. However, we detected p-coumaric acid (4) andferulic acid (6) in the root exudates of L. japonicus (Table2) and lacZ gene induction in the rhizosphere using an M.
japonicum strain with the nodD1 plasmid (Supplementary
Fig. S3). Therefore, the nod gene–inducing activities of phe‐nolic acids are not restricted to root hair infection threads,

Characteristics of hydroponic cultures and phenolic acid contents in root exudates of three leguminous plants. Values
are mean total contents±S.E. (n=4).
Contents
Contents
Seed germinated Plant FW Root exudates (nmol g–1 FW plant)(nmol mg–1 root exudate)(g DW)
(g)
(mg)
3
4
6
3
4
6

Lotus japonicus
red clover
alfalfa

0.82
0.69
2.07

1.44
3.38
10.21

2.7
2.7
8.2

4.0±0.1 11.9±0.3 2.0±0.0
n.d.
0.3±0.0 1.7±0.0
n.d.
0.4±0.0 0.6±0.0

21.1±0.6 63.2±1.3 10.5±0.1
n.d.
4.0±0.0 21.6±0.1
n.d.
5.0±0.0 8.0±0.1

FW, fresh weight. 3, trans-cinnamic acid; 4, p-coumaric acid; 6, ferulic acid; n.d., not detected.

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Fig. 6. Chemical structures of phenolic acids used in the present study. (a) Phenolic acids in the major phenylpropanoid pathway towards
coumarins, lignins, and lignans. (b) Other phenolic acids. See Table 1 for compound names.

they may also be involved in a wide range of associations in
the rhizosphere.
In the present study, we used the direct detection of
LCOs to screen for nod gene inducers in L. japonicus–
Mesorhizobium symbiosis. We identified five candidate
compounds in the group of phenolic acids, and detected twoin the root exudates of L. japonicus. By increasing the copy
number of one of the two nodD genes in M. japonicum,
we revealed that phenolic acids as nod gene inducers weremainly recognized by NodD1. Overall, we propose that phe‐nolic acids are a novel type of nod gene inducer in theL. japonicus–Mesorhizobium symbiosis system. Therefore,
substances that act as mutual symbiotic signals from bothsides, L. japonicus and M. japonicum, are now revealed.
The present results will accelerate the elucidation of theregulatory mechanisms in this symbiotic system.
Acknowledgements
We dedicate this report to the memory of the late Professor
Toshio Aoki (1961–2019), the last author and principle investiga‐

tor of this work. The late Professor Aoki designed and conducted
the central part of this research, including the establishment of
the LCO detection system using UPLC-TQMS, the screening ofphenolic compounds, the confirmation of the NF activity of LCO
induced by phenolic acids, and the detection of phenolic acids inroot exudates.
This work was supported by JSPS KAKENHI Grant Number
JP20250915, JST-Mirai Program Grant Number JPMJMI20E4, andJST CREST Grant Number JPMJCR16O1 Japan. We would liketo thank Ms. Chikako Mistuoka for her excellent technical assis‐
tance. We would also like to express our gratitude to Prof. Hiroshi
Kouchi for NF from M. japonicum and the plasmid pMP2112,
Prof. Hisayuki Mitsui for the plasmid pBBR1MCS-2, and Prof.
Shin Okazaki for the M. japonicum ML033 strain. The accessionsof the L. japonicus and Mesorhizobium strains were provided by
the National BioResource Project ‘Lotus/Glycine’.
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Microbes Environ. 36(2), 2021

https://www.jstage.jst.go.jp/browse/jsme2 doi:10.1264/jsme2.ME21007

MOST VALUABLE PAPER OF THE YEAR 2021

Bioelectrical Methane Production with an Ammonium Oxidative Reaction under
the No Organic Substance Condition
Ha T.T Dinh1,2, Hiromi Kambara1, Yoshiki Harada1, Shuji Matsushita1,3, Yoshiteru Aoi4, Tomonori Kindaichi1,
Noriatsu Ozaki1, and Akiyoshi Ohashi1*
Department of Civil and Environmental Engineering, Graduate School of Advanced Science and Engineering, Hiroshima
University, 1–4–1, Kagamiyama, Higashi-Hiroshima, Hiroshima 739–8527, Japan; 2Faculty of Environment, Ho Chi Minh City
University of Natural Resources and Environment, 236 Le Van Sy, 1 Ward, Tan Binh District, Ho Chi Minh City, Vietnam;
3Agricultural Technology Research Center, Hiroshima Prefectural Technology Research Institute, 6869, Hara, Hachihonmatsu,
Higashi-Hiroshima, Hiroshima 739–0151, Japan; and 4Program of Biotechnology, Graduate School of Integrated Sciences for
Life, Hiroshima University, 1–3–1, Kagamiyama, Higashi-Hiroshima, Hiroshima 739–8530, Japan
1(Received January 25, 2021—Accepted May 1, 2021—Published online June 17, 2021)

The present study investigated bioelectrical methane production from CO2 without organic substances. Even though
microbial methane production has been reported at relatively high electric voltages, the amount of voltage required and theorganisms contributing to the process currently remain unknown. Methane production using a biocathode was investigatedin a microbial electrolysis cell coupled with an NH4+ oxidative reaction at an anode coated with platinum powder under awide range of applied voltages and anaerobic conditions. A microbial community analysis revealed that methane production
simultaneously occurred with biological denitrification at the biocathode. During denitrification, NO3– was produced bychemical NH4+ oxidation at the anode and was provided to the biocathode chamber. H2 was produced at the biocathode by
the hydrogen-producing bacteria Petrimonas through the acceptance of electrons and protons. The H2 produced was
biologically consumed by hydrogenotrophic methanogens of Methanobacterium and Methanobrevibacter with CO2 uptake
and by hydrogenotrophic denitrifiers of Azonexus. This microbial community suggests that methane is indirectly produced
without the use of electrons by methanogens. Furthermore, bioelectrical methane production occurred under experimental
conditions even at a very low voltage of 0.05 V coupled with NH4+ oxidation, which was thermodynamically feasible.
Key words: ammonia oxidation, bio-electricity, denitrification, methane production, microbial community

Methane is the prime component of natural gas and is
widely utilized as an energy source worldwide. It is mainly
produced by biological and physical actions that collectively
contribute to 20–80% of natural gas reserves (Rice andClaypool, 1981). Methane is physically produced throughthe thermal decomposition of organic matter in association
with the formation of coal, gas, and oil (Schoell, 1988).
Conversely, biological methane formation is primarily per‐formed by methanogenic microbes (methanogens) in anae‐
robic environments (Whiticar et al., 1986; Whiticar, 1999).
Only methanogenic archaea are known to act as methano‐
gens and use substrates produced from organic matter
during fermentation, such as acetate, formate, and hydrogengas. This methane fermentation occurs in nature, but has
also been applied as an eco-friendly wastewater treatment
technology (Onodera, 2013; Townsend-Small et al., 2016).
Artificially produced biogas may be utilized as an energy
source after purification.
It is possible to generate electricity from organic substan‐ces. Microbial fuel cell (MFC) technology and its applica‐* Corresponding author. E-mail: ecoakiyo@hiroshima-u.ac.jp;
Tel: +81–82–424–7823; Fax: +81–82–424–7823.
Citation: Dinh, T. T H., Kambara, H., Harada, Y., Matsushita, S., Aoi,
Y., Kindaichi, T., et al. (2021) Bioelectrical Methane Production withan Ammonium Oxidative Reaction under the No Organic SubstanceCondition. Microbes Environ 36: ME21007.
https://doi.org/10.1264/jsme2.ME21007

14

tion to wastewater treatment have been extensively
examined (Logan et al., 2006; Sarmin et al., 2019; Wang etal., 2020). Conversely, in microbial electrosynthesis systems(MESs), methane is produced by providing electricity(Rabaey and Rozendal, 2010; Eerten‐Jansen et al., 2012).
High methane production is expected when MESs areapplied to wastewater treatment because of the combinationof methane fermentation using organic substances and theconversion of CO2 to methane by microbes through electric‐ity (Clauwaert et al., 2008; Clauwaert and Verstraete, 2009;
Zhao et al., 2016; Park et al., 2018; Peng et al., 2019). Ding
et al. (2016) identified 0.8 V as the optimal applied voltage
for appropriate wastewater treatment and maximum meth‐ane production using an MES.
In the MES, bioelectrical methane production is per‐formed without organic substrates (Cheng et al., 2009;
Villano et al., 2010; Zhen et al., 2015). Cheng et al. (2009)
reported that carbon dioxide was reduced to methane at abiocathode potential of <–0.7 V (vs. Ag/AgCl). At –1.0 V(vs. Ag/AgCl), the electron capture efficiency of methane
production was 96%. Two mechanisms have been proposed
for biological methane production using a biocathode. At
high applied voltages, methane may be produced by hydro‐
genotrophic methanogens using abiotic H2 formed in wateroxidation (Wagner et al., 2009; Eerten‐Jansen et al., 2012).
In this case, H2 is an important intermediate for methane
production. The second mechanism is direct electrotrophic
methane production. Cheng et al. (2009) reported that some
Article ME21007

Dinh et al.

methanogens must use electrons with CO2 to directly pro‐
duce methane, without hydrogen as an intermediary. Previ‐
ous studies on extracellular electron transfer demonstrated
that applied voltage may not be effective at promoting meth‐ane production, suggesting a pathway without H2 (Rotaru etal., 2013; Lohner et al., 2014; Holmes et al., 2017; Lee etal., 2017). However, there are insufficient experimental data
to prove direct electrotrophic methane production. It cur‐rently remains unclear whether bioelectrical methane pro‐duction occurs via direct and/or indirect reaction(s) in MESs.
The CO2 reduction potential to methane E0’cat at the bio‐
cathode is –0.24 V (vs. SHE) under the standard conditionat pH=7. When coupled with H2O oxidation (E0’an=0.81 V
vs SHE) at the anode, methane production in an MES occurs
thermodynamically by applying more than 1.05 V under the
standard condition. If the oxidation of inorganic compoundswith a lower potential (such as NH4+ oxidation to NO3– andN2: E0’an=0.36 V and –0.29 V vs. SHE, respectively) occurs
instead of H2O oxidation, methane may be produced at alower applied voltage. However, MES studies have not pro‐vided sufficient information on the oxidation reaction at theanode, with experiments being conducted at relatively highvoltages.
In the present study, we designed an MES experiment inwhich an organic substrate was not supplied, and NH4+ wasadded to the anode chamber to investigate whether methane
production is possible even at very low applied voltages.
Although the reaction of electrotrophic methane production
with NH4+ oxidation to N2 thermodynamically proceeded
even without a supply of electricity, this is the first study toreport coupling to the NH4+ oxidative reaction. In addition,
the microbial community was analyzed to identify theorganisms involved in bioelectrical methane production.
Materials and Methods
MES set-up
The MES used in the present study consisted of two glass cham‐bers, each with an effective volume of 70 mL, which were con‐nected by a 10-cm salt bridge containing 2% (w/w) agar (KF-30;
Fujirika) and 20% (w/w) KCl (Fig. S1). The top of each chamber
was connected to a 10-mL loss-of-resistance glass syringe torelease the pressure generated in the chamber by the gas produced
and also facilitate gas collection. A 9-cm2 electrode of carbon cloth(Toyobo) was installed in both chambers. The biocathode andanode electrodes were connected to a DC power supply (Array
3600 Series; T&C Technology) using a platinum wire. A 100-Ω
resistor was inserted between the power supply and biocathodeelectrode to estimate the electric current by measuring voltage
using a digital multimeter (FlePow; Levin Japan). Even if theexternal resister was inserted, the effect on the actual applied volt‐age was negligible when the internal resistance of the MES was
high. A small amount of anaerobic sludge taken from a laboratoryscale upflow anaerobic sludge blanket (UASB) reactor was inocu‐
lated on the surface of the cathode electrode. Platinum powder(10% by weight of platinum on carbon powder; E-TEK, C-1 10%
Pt on Vulcan XC-72) was coated on the surface of the anode, as
described in previous studies (Müller and Spitzer, 1905; Nutt andKapur, 1968; De Vooys et al., 2001; Bunce and Bejan, 2011; Li etal., 2017).

MES operation
The MES was operated in the batch-processing mode at 30°C ina thermostatic chamber. The anodic and biocathodic chambers
were filled with the same medium without organic substances anddeoxidized through a nitrogen purge. The medium was composedof NaHCO3 (200 mg L–1), NH4Cl (190 mg L–1), NaH2PO4(17 mg L–1), and Na2HPO4 (124 mg L–1), as well as trace elements,
including FeSO4·7H2O (7 mg L–1), CoCl2·6H2O (1.7 mg L–1),
ZnSO4·7H2O (1.5 mg L–1), HBO3 (0.6 mg L–1), MnCl2·4H2O(4.2 mg·L–1), NiCl2·4H2O (0.4 mg L–1), CuCl2·2H2O (0.27 mg L–1),
and Na2MoO2·2H2O (0.25 mg L–1), at a pH of 7.5. The medium
was completely replaced at intervals of 3, 5, 6, and 13 d, with thebatch experiment being repeated 20 times over 110 d of operation.
Each batch duration time was determined according to gas produc‐tion for gas sampling. Each batch experiment was performed at aconstant applied voltage in the range of 0.05–3.0 V to investigate
whether methane production is possible even at low voltages. Aftersetting up the MES, a voltage was immediately supplied toenhance microbial activity at the biocathode, and the anode wasunsterilized.
Sampling and analyses
The volume of gas production in the respective chambers wasmeasured using an airtight syringe. CH4, N2, CO2, and H2 concen‐
trations were then measured using a gas chromatograph equippedwith a thermal conductivity detector (GC-TCD; Shimadzu
GC-8A). NH4+, NO3–, and NO2– concentrations in the medium were
measured by ion chromatography (Shimadzu HPLC-20A) at thestart and end of each batch operation. Dissolved CH4 and N2 con‐centrations were estimated using Henry’s law.
Microbial community
The sludge sample at the biocathode was collected on day 110 of
the last MES operation and washed with phosphate buffer. DNA
was extracted using the FastDNA® SPIN Kit for Soil (MP Biomed‐
icals), according to the manufacturer’s instructions. PCR amplifi‐
cation of the 16S rRNA gene was performed using the primer
sets 341’F (5′-CCTAHGGGRBGCAGCAG-3′) and 805R (5′GACTACHVGGGTATCTAATCC-3′) with KAFA HiFi Hotstart
ReadyMix (Kapa Biosystems). PCR conditions were as follows:
the initial denaturation of DNA at 95°C for 3 min, followed by 25
cycles at 95°C for 30 s, at 55°C for 30 s, and at 72°C for 30 s, witha final extension at 72°C for 5 min. The PCR product was purified
and sequenced by the emulsion method using Illumina/Miseq (Illu‐
mina) at Hokkaido System Science. The sequences obtained wereanalyzed using QIIME (v1.8.0) (Caporaso et al., 2010). Opera‐
tional taxonomic units (OTUs) were grouped based on a thresholdvalue of 97% identity for DNA using the UCLUST algorithm(Edgar, 2010). These OTUs were classified using the Greengenes
database (McDonald et al., 2012; Werner et al., 2012).
Sequence data were deposited in the DDBJ database under
DDBJ/EMBL/GenBank accession number DRA011341.

Results
Performance of batch experiments
In MES batch operations, we initially attempted to apply
a relatively high voltage of 2.0 V over 3 d. Once a higher
current of approximately 0.18 mA was observed, it immedi‐
ately decreased to 0.09 mA and gradually declined overtime, as shown in Fig. 1. However, no gas bubbles werevisible in either the biocathode or anode chambers, despite
the sludge inoculation being expected to enable methane
production activity. The 3-d batch experiment was then

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Bioelectrical Methane Production

Fig. 1.

Time courses of applied voltage (a), current (b), and gases (CH4, N2, and CO2) produced (c) in batch experiments.

repeated with changes in bulk liquid, but at lower voltagesof 1.6 V and 1.4 V, resulting in current behaviors that were
the same as those at 2.0 V. Under these conditions, very few
bubbles were observed in the biocathode chamber. In thenext batch operation, bubbles were observed where theapplied voltage was returned to 2.0 V. However, it was notpossible to sample the gas produced because of its low vol‐ume.
Therefore, we changed the batch interval time from 3 to
5 d from day 12 onwards, except for some special batches.
More bubbles were produced in the biocathode chamber andcollected as a gas in the fifth batch operation at 2.0 V. The
gas produced was approximately 2.0 mL on days 12–17(Fig. 1). As expected, methane was detected, but its concen‐
tration was only 10.0%. The main component of the gas was
N2, with a very low concentration of CO2. The current wasmarkedly higher than that in the previous batch experimentat the same voltage. The current also decreased for approxi‐
mately 3 d, but increased thereafter. A significant difference
was observed in current behavior between the small andlarge gas production chambers. In control batch experiments
without the inoculation, methane was not detected in therange of 1.0–2.0 V; however, hydrogen production wasobserved at an applied voltage higher than 1.2 V in the cath‐ode chamber. Methane production is expected to be derived
16

from inorganic carbon in the presence of microbes on the
carbon cloth, the biological activity of which may beenhanced after 17 d of operation; however, no bubbles wereobserved in the anode chamber under any of the conditions
used.
To investigate the effects of voltage on methane produc‐tion, experiments were continuously performed while
decreasing the applied voltage step-by-step down to 0.1 V
until day 61 (Fig. 1). The current slightly decreased with
voltage reductions; however, its pattern of behavior was
similar in each batch period. Gas containing CH4 and N2
was produced at any voltage, except during days 22–27
when gas sampling failed.
Since high N2 concentrations of approximately 75 to 90%
were detected, we reconducted batch experiments underalmost identical conditions over a range of 0.05–3.0 V ondays 55–110 to reveal the source of N2 yield by measuring
ammonium, nitrate, and nitrite. In the last batch operation,
we also attempted methane production at a very low voltage
of 0.05 V. A small amount of gas containing 6.09% CH4 wascollected, even at the lowest voltage, particularly over a pro‐longed period of 13 d. NH4+ and NO3– concentrations
decreased in both the biocathode and anode chambers (Fig.
S2). Total nitrogen ions in the two chambers decreased in allbatches, suggesting that the yield of N2 was derived from

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Effects of voltage on gas production
Although a 100-Ω external resistor was inserted, the volt‐age supplied was nearly equal to the actual applied voltage
between the biocathode and anode because the current ver‐sus supplied voltage was small throughout the experiment,
as shown in Fig. 1. The gas production rate was signifi‐
cantly dependent on the applied voltage, as shown in Fig. 2.
CH4 production slightly increased in proportion to the volt‐age with 0.306 mL at 1.2 V, after which it decreased to
0.128 mL at 3.0 V. These results suggest that a very highvoltage does not always enhance methane production andmay have a negative effect on microbes. The N2 production
rate was similar to that of CH4 with respect to the effects ofvoltage; however, large fluctuations were observed. Thissuggests that microbes also play a role in N2 production.
The retained microbes were expected to grow and increase
with the operational time. However, they were slightly
detached when bulk liquid was replaced as a result ofchanges in batch conditions. Therefore, the number ofmicrobes was unstable, possibly contributing to fluctuations
in gas production.

Fig. 3.

0.4

Gas production rate (mL d-1 )inorganic nitrogen ions. Regarding the nitrogen balance, astrong relationship was observed between the amount ofconsumed NH4+ plus NO3– and produced N2 (Fig. S3).
Cecconet et al. (2019) reported the accumulation of NO2–
and N2O in a biocathodic denitrification process for ground‐water bioremediation. However, these intermediates in deni‐
trification were not detected in this MES experiment. The
lack of accumulation of intermediates may have beencaused by the slow reaction.

N2
N2
CH
CH44

0.3
0.2
0.1
0.0

0.0

0.5

1.0

1.5

2.0

2.5

3.0

Voltage (V)Fig. 2.

Gas production rates at different applied voltages.

Microbial community
In the 16S rRNA gene sequencing of the biomass sample
on day 110, more than 100,000 reads, including domain bac‐teria and archaea, were obtained, and the number of OTUs
exceeded 1,200. Sequencing results revealed the presence ofbacterial and archaeal communities (Fig. 3). Archaea com‐prised only 3.9% of the total reads.
The major families of bacteria were Porphyromonadaceae,
Rhodocyclaceae, and Geobacterceae, accounting for 26.8,
11.4, and 10.7%, respectively. The three families made up
approximately 45% of all microbes. Of the most dominantfamily Porphyromonadaceae, approximately 50% was theobligately anaerobic genus of Petrimonas, while 29.8%
uncultured genera were detected (Fig. 3). Petrimonas con‐sists of hydrogen-producing bacteria (Lu et al., 2012; Sun etal., 2015; Liu et al., 2016), suggesting that hydrogen is pro‐Microbial community of a biomass sample on day 110, based on the 16S rRNA gene.

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Bioelectrical Methane Production

Discussion
NH4+ oxidation was observed in the anode chamber,
although at insignificant amounts, indicating that NH4+ wasoxidized by donating electrons to the biocathode. Platinum
is commonly accepted as the most promising catalyst in theelectrochemical oxidation of ammonia (e.g., De Vooys etal., 2001; Li et al., 2017). Müller and Spitzer (1905)
reported that the anodic products of electrolyzing ammonia
at a platinum anode were mainly NO3– and N2 (25%–35%).
With over-oxidation, NO2– and NO3– products wereobserved at applied voltages of higher than +0.6 V (vs Ag/
AgCl) (Endo et al., 2005; Bunce and Bejan, 2011). NO3–
was also reportedly formed from NH4+ by catalytic oxida‐
tion with PtOx (Fóti and Comninellis, 2004; Panizza andCerisola, 2009). Since platinum powder was coated on thesurface of the anode with a carbon cloth electrode in thepresent study, similar reactions to the electrolysis of water
occurred; however, neither N2 nor NO2– production wasobserved.
The oxidation of NH4+ at the anode may be represented asfollows:
1/8 NH4 +3/8 H2O → 1/8 NO3 +5/4 H +e
+

–

+

–

(1)

The NO3– produced was transferred to the biocathodechamber through the salt bridge by diffusion, resulting in adecrease in the concentration of NO3– in the anode chamber
18(Fig. S3) because of N2 production in the biocathode cham‐ber.
CH4 and N2 production in the biocathode chamber sug‐gest that the reduction reactions of NO3– and CO2, respec‐tively, are represented as follows:
1/8 CO2+H++e– → 1/8 CH4+1/4 H2O (2)
1/5 NO3–+6/5 H++e– → 1/10 N2+3/5 H2O (3)Based on Faraday’s laws of electrolysis, the number ofdonated electrons, Ne [mol], may be calculated from themeasured current using the following equation:
Ne =

∫ Idt
F

(4)

where I is current (A), t is time (s), and F is Faraday’s con‐stant (C mol–1).
Assuming that all yield electrons Ne, calculated as per Eq.
(4), are used for the reduction of only CO2 or NO3–, theamounts of CH4 and N2 produced versus the electron yield
were calculated using Eqs. (2) and (3), respectively. Meas‐
ured CH4 production was markedly less than the calculated
value, while measured N2 production was also smaller than
the theoretical value under this assumption (Fig. S4). There‐
fore, the two reductions were simultaneously performed,
and Ne was distributed in both reductions. The required
electrons for measured CH4 production from CO2 reduction
were estimated using Eq. (2), with the ratio of required elec‐
trons to total measured electrons Ne shown in Fig. 4. The
electron ratio slightly decreased with the applied voltage,
rather than remaining constant. At very low voltages of 0.05
and 0.1 V, approximately 40% of the current was used forCO2 reduction to CH4, while only approximately 5% was
utilized at 3 V. Assuming that the current to electron ratio
was used for CO2 reduction and that the remaining electrons
were used for NO3– reduction to N2, as per Eq. (3), it is pos‐sible to estimate CH4 and N2 production from Ne. Fig. 5
compares measured and estimated CH4 and N2 production,with the curve showing the relationship between the elec‐tron ratio and voltage in Fig. 4 used in the calculation. A
good agreement was observed for both CH4 and N2 produc‐tion, meaning that the electron balance was almost main‐tained in this experiment, and the production of CH4 and N2
100
Ratio of required electrons forCH4 production to total
measured electrons (%)

duced in the biocathode chamber. Most bacteria belonging
to Rhodocyclaceae exhibit denitrification activity (Zhao etal., 2013; Wang et al., 2017). The predominant Azonexus
genus detected, which may grow on molecular hydrogen as
an electron donor (Zhao et al., 2011; Liang et al., 2021),
plays an important role in the denitrification process to pro‐
duce nitrogen gas. Only Geobacter was detected within the
Geobacterceae family. The presence of electrically conduc‐tive pili or flagella on Geobacter species is reportedly linked
to electron transfer in the MFC (Cabezas et al., 2015; Yan etal., 2020). In the present study, Geobacter appeared to be
responsible for electron transfer to yield biogas.
Regarding archaea, all OTUs were Euryarchaeota. The
majority of Euryarchaeota detected were methanogens, withthe dominant family (81.7%) being Methanobacteriaceae, ahydrogen-utilizing methanogen (Fig. 3). Two genera,
Methanobrevibacter and Methanobacterium, were detected
at concentrations of 63.8 and 36.3%, respectively (Fig. 3).
They played a major role in CH4 production in the bioca‐
thode chamber. In addition, Methanosaetaceae, an obligate
acetoclastic methanogen, was detected, albeit at a low con‐centration (7.1%); therefore, acetate may be produced andconverted to CH4. However, its contribution appears to havebeen insignificant.
The biological contributors to denitrification and methane
production were identified; the produced gas containing
CH4 and N2 may be explained by the presence of thesemicrobes. Therefore, we demonstrated the biological pro‐duction of CH4 through the provision of electricity, even atvery low voltages, and in the absence of organic substancesin the MES.

80
60

for N240
20
0

for CH4
0.0

1.0

2.0
Voltage (V)3.0

Fig. 4. Relationship between the ratio of required electrons for CH4
production to total measured electrons Ne and applied voltage.

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Measured gas production (mmol reactor-1)

Dinh et al.
0.15
N2
N2
CH4
CH4

0.1

0.05

0

0

0.05

0.1

0.15

Estimated gas production (mmol reactor-1)
Comparison between measured and estimated gas production.
An estimation of produced CH4 and N2 was performed assuming that
all electrons Ne were used for the reduction of both CO2 and NO3–,
while electrons from the ratio in Fig. 4 were used for CH4 production.

Fig. 5.

may theoretically be performed in the biocathode chamberaccording to the reduction reactions of Eqs. (2) and (3).
However, at a high voltage of 3.0 V, the calculated value of
produced N2 was markedly greater than the measured value(Fig. 5), indicating that some electrons were used for otherreductions by chemical and/or microbial reactions. If NO3–
reduction to NH4+ instead of N2, which is the reverse reac‐tion at the anode, is performed at the biocathode at high vol‐tages, the reversible reactions will lead to a waste ofelectrons yielded in the MES. A previous study reported thata high imposing voltage exerted a negative effect on metha‐nogens (Ding et al., 2016) and nitrate-reducing bacteria (Liet al., 2001; Ding et al., 2016), and excessive voltage not
only inhibited microbial activity, but also induced chemical
reactions.
Hydrogen was not detected. However, hydrogen was
expected to be produced in the biocathode chamber becauseof the presence of hydrogenotrophic methanogens, such as
Methanobacterium and Methanobrevibacter, and the hydro‐
genotrophic denitrifiers of Rhodocyclaceae (Azonexus). Fur‐thermore, the hydrogen-producing bacteria Petrimonas were
present. Previous studies on MESs also detected hydrogeno‐
trophic methanogens, such as Methanobrevibacter,
Methanocorpusculum, and Methanoculleus sp. (Sasaki etal., 2011; Van Eerten-Jansen et al., 2013; Jiang et al., 2014;
Siegert et al., 2015). Cheng et al. (2019) reported that
Methanobacterium palustre methanogens directly use elec‐
trons to produce methane without organic substances. How‐ever, this study did not provide sufficient evidence ofelectron utilization. Although Geobacter species are wellknown to have the ability to transfer electrons, it was sur‐prising that the dominant genus identified in this study was
Petrimonas due to the lack of available information on theelectron transfer ability of this genus. However, Petrimonas
may accept electrons to produce hydrogen, which may beprovided to the detected hydrogenotrophic methanogens anddenitrifiers in the absence of an organic substrate in thereactor. During the bio-electrochemical production of hydro‐gen, it is reasonable to assume that a very small amount ofhydrogen is electrochemically formed and biologically con‐sumed. However, this electrochemical pathway may only
negligibly contribute to production because hydrogenproducing Petrimonas was dominant in the microbial com‐munity.
Hydrogenotrophic methanogens and denitrifiers compete
for the shared substrate of H2 produced at the biocathode.
Denitrifiers are dominant in wastewater treatments underanoxic conditions in the presence of nitrate; this phenom‐
enon may be explained by Gibbs free energy. The energy
obtained in the denitrification reaction of Eq. (3) is mark‐edly larger than that in the methane production reaction of
Eq. (2). However, under hydrogenotrophic conditions,methanogens and denitrifiers were both enriched eventhough denitrification dominated throughout the experiment.
At the lowest applied voltage of 0.05 V, approximately 40%of the H2 produced was utilized for methane production by
the methanogens. However, with an increase in the applied
voltage, the utilization ratio decreased (Fig. 4), indicatingthat the applied voltage affected the utilization of H2 bymethanogens and denitrifiers. H2 production and concentra‐
tions are expected to increase at higher voltages. Microbeswith a high affinity for substrates generally consume sub‐strates faster than those with low affinity. The Monod con‐stant Km for H2 uptake was reportedly 1 and 2 μM for
Methanobacterium ruminatium (Lovley and Goodwin,1988) and Methanobrevibacter formicium (Schauer andFerry, 1980), respectively. In contrast, Smith et al. (1994)
reported that the Km of hydrogenotrophic denitrifiers ranged
between 0.3 and 3.32 μM. If methanogens had lower Km
than the denitrifiers at the biocathode, indicating a higher
affinity for H2 and lower maximum H2 uptake rate, the phe‐nomenon of a decreasing current ratio in methane produc‐tion with an increasing applied voltage, as shown in Fig. 4,
may be explained by this difference in Km between metha‐nogens and denitrifiers.
Based on the experimental results obtained, Fig. 6
proposes a scheme for the process of electronic methane
production used in the present study, without organic sub‐stances in the MES. Ammonium is oxidized to nitrate by aPt catalyst at the anode with electron release. The nitrateformed is transferred into the biocathode chamber throughthe salt bridge. At the biocathode, the hydrogen-producing
bacteria Petrimonas biochemically produce H2 by accepting
electrons and protons. The H2 produced is biologicallyconsumedbyhydrogenotrophic
methanogens
ofMethanobacterium and Methanobrevibacter coupled with
CO2 uptake, and by the hydrogenotrophic denitrifiers of
Rhodocyclaceae (Azonexus), with transferred nitrate reduc‐tion resulting in the production of methane and N2, respec‐tively. Consequently, the overall reaction at the anode andbiocathode in the MES is as follows:
1/8 CO2+1/3 NH4+ → 1/8 CH4+1/6 N2+1/3 H++1/4 H2O
ΔG0’=–3.134 kJ mol–1 e– (5)Thermodynamically, this reaction proceeds under the
standard condition even without the provision of external

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Article ME21007

19

Bioelectrical Methane Productione-

H2O
Geobacteraceae

N2

H2

e-

H+

Methanobacteriaceae

Porphyromonadaceae

Rhodocyclaceae

e-

H2

NO3-

NO3H+

NO3H+

e-

NH4+

CO2
CH4
H2O

Biocathode

Pt

Anode

Scheme of electronic methane and nitrogen production in
MES without organic substances.

Fig. 6.

energy, such as electricity, because of the negative Gibbs
free energy ΔG0’ value. The actual condition, for example,
at an applied voltage of 0.1 V was as follows: pCH4=0.36
atm, pN2=0.65 atm, pCO2=0.03 atm, [H+]=15.1×10–5 M, and[NH4+]=5.38×10–3 M. In this case, the actual Gibbs freeenergy ΔG (=ΔG0’+RT ln[K]) was estimated to have a valueof –5.18 kJ mol–1 e–, suggesting that the production of meth‐ane and N2 is expected. Therefore, the present study
revealed that even in an inorganic environment, biologicalmethane production coupled with denitrification is possible
in combination with catalytic ammonium oxidation, even atvery low applied voltages <0.1 V, through the three key
players of hydrogenotrophic methanogens, denitrifiers, andhydrogen-producing bacteria.
Acknowledgements
This research was supported by the Japan Society for the Promo‐tion of Science (JSPS) as a Grant-in-Aid for scientific research(grant numbers 17H01300). We would like to thank Editage(www.editage.jp) for English language editing.
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Microbes Environ. Vol. 35, No. 1, 2020

https://www.jstage.jst.go.jp/browse/jsme2 doi:10.1264/jsme2.ME19086

MOST CITED ORIGINAL PAPER PUBLISHEDIN THIS THREE YEARS [2020-2022] (26 citations)

Enzymatic Degradation of p-Nitrophenyl Esters, Polyethylene Terephthalate,
Cutin, and Suberin by Sub1, a Suberinase Encoded by the Plant Pathogen
Streptomyces scabies
Raoudha Jabloune1, Mario Khalil1, Issam E. Ben Moussa1, Anne-Marie Simao-Beaunoir1, Sylvain Lerat1,
Ryszard Brzezinski1, and Carole Beaulieu1*
Département de Biologie, Université de Sherbrooke, Sherbrooke (QC), J1K 2R1, Canada

1(Received June 27, 2019—Accepted December 15, 2019—Published online February 27, 2020)

The genome of Streptomyces scabies, the predominant causal agent of potato common scab, encodes a potential cutinase,the protein Sub1, which was previously shown to be specifically induced in the presence of suberin. The sub1 gene wasexpressed in Escherichia coli and the recombinant protein Sub1 was purified and characterized. The enzyme was shown tobe versatile because it hydrolyzes a number of natural and synthetic substrates. Sub1 hydrolyzed p-nitrophenyl esters, withthe hydrolysis of those harboring short carbon chains being the most effective. The Vmax and Km values of Sub1 for pnitrophenyl butyrate were 2.36 mol g–1 min–1 and 5.7 10–4 M, respectively. Sub1 hydrolyzed the recalcitrant polymers cutinand suberin because the release of fatty acids from these substrates was observed following the incubation of the enzyme
with these polymers. Furthermore, the hydrolyzing activity of the esterase Sub1 on the synthetic polymer polyethylene
terephthalate (PET) was demonstrated by the release of terephthalic acid (TA). Sub1 activity on PET was markedly
enhanced by the addition of Triton and was shown to be stable at 37°C for at least 20 d.
Key words: actinobacteria, common scab, cutinase, esterase, potato

Streptomycetes are Gram-positive bacteria that are known
for their ability to produce a wide range of secondary
metabolites and for the complexity of their morphologicaldevelopment. Although most streptomycetes species aresaprophytic soil inhabitants, some are plant pathogens.
Among them, Streptomyces scabies is the predominantcausal agent of potato common scab and causes importanteconomic losses in Canada (Hill and Lazarovits, 2005), as
well as in most potato growing areas. Common scab is char‐acterized by corky lesions on the surface of potato tubers.
Similar to other soil-inhabiting streptomycetes, S. scabies
produces a large variety of extracellular enzymes, including
various glycosyl hydrolases and esterases (Komeil et al.,2013; Beaulieu et al., 2016). These enzymes may participate
in pathogenesis because the penetration of S. scabies into
host plants is considered to be facilitated by the secretion of
extracellular cell wall-degrading enzymes (Beauséjour etal., 1999).
The potato tuber is covered by a periderm that is com‐posed of three types of tissues: phellem, phellogen, andphelloderm (Tyner et al., 1997). The wall of phellem cells
impregnated with suberin, a plant polymer recalcitrant tobio-degradation, is composed of a polyaromatic domain
covalently linked to a polyaliphatic moiety (Bernards,
2002). The polyaromatic domain, a lignin-like structure,
consists of a hydroxycinnamic acid-derived polymericmatrix (Bernards and Lewis, 1998). The polyaliphatic
domain shares structural and chemical similarities withcutin, another polyester component of plant cuticles. Cutinand suberin both act as physical barriers against plant patho‐22* Corresponding author. E-mail: Carole.Beaulieu@USherbrooke.ca;
Tel: +1–819–821–7011; Fax: +1–819–821–7921.

gens (Khatri et al., 2011). Cutin and suberin are polymers offatty acid derivatives linked by ester bonds. Cutin is mostly
composed of C16 and C18 ω-hydroxyacids, polyhydroxya‐cids, epoxyacids, and α,ω-dicarboxylic acids. Suberin may
be distinguished from cutin by higher contents of hydroxy‐
cinnamic acids, fatty alcohols, and saturated aliphatics withlong chains (Beisson et al., 2012).
Cutinases hydrolyze the plant leaf cuticle by cleaving theester bounds of cutin (Dutta et al., 2009). Therefore, cuti‐nases belong to the esterase group, and more specifically toa class of serine esterases that contain the catalytic triad(serine, histidine and aspartate) with the active serine in theconsensus sequence Gly-His/Tyr-Ser-X-Gly (Martinez et al.,1994). Some fungal cutinases, such as the cutinase CcCUT1of the fungus Coprinopsis cinerea, also exhibit the ability todegrade suberin (Kontkanen et al., 2009). As lipolytic
enzymes, cutinases have interesting properties for applica‐
tions in various industrial processes (Carvalho et al., 1999).
For example, some cutinases exhibit the ability to degrade
synthetic polyesters, such as polycaprolactone (Murphy etal., 1996) and polyethylene terephthalate (PET)(Vertommen et al., 2005; Eberl et al., 2009; Ribitsch et al.,2015).
Previous studies suggested that the bacterium S. scabies
possesses the ability to degrade suberin. This pathogenic
bacterium exhibits strong esterase activity in the presence ofsuberized tissues (Beauséjour et al., 1999). Furthermore, asecretome analysis of S. scabies cultures grown in the pres‐ence of suberin revealed the presence of esterases, which are
predicted to play a role in lipid metabolism (Komeil et al.,2014; Beaulieu et al., 2016). Among them, the Sub1 protein
exhibits 33% identity with the cutinase CcCUT1 of the fun‐gus C. cinerea (Komeil et al., 2013). Interestingly, sub1

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gene expression was previously reported to be specificallyinduced in the presence of suberin (Komeil et al., 2013).
The cutinase from Aspergillus oryzae (PDB ID: 3GBS) ishallmarked by a central β-sheet of five parallel strands sur‐rounded by ten α-helices (Liu et al., 2009), as found for thepredicted three-dimensional structure of the protein Sub1
(Supplemental Fig. S1). The model of the Sub1 protein also
predicts the formation of two disulfide bonds (Cys31–Cys103;
Cys178–Cys185) and a catalytic triad including residues Ser
114, Asp 182, and His 195 (Komeil et al., 2013).
The main objectives of the present study were to produce
the Sub1 protein, purify and characterize its enzymatic prop‐
erties, and demonstrate that it functions as a polyesterasewith the ability to degrade biopolymers, such as cutin andsuberin, as well as the synthetic polyester PET.
Materials and Methods
Bacterial strains and culture conditions
An inoculum of S. scabies EF-35 (HER1481) was prepared intryptic soy broth (108 spores in 25 mL), as described previously(Komeil et al., 2013). Cultures of S. scabies EF-35 were incubatedwith shaking (250 rpm) at 30°C. Escherichia coli strains DH5α
(Invitrogen) and SHuffle T7 (New England Biolabs) were grown
in LB medium supplemented where necessary with kanamycin(30 μg mL–1) and were then incubated with shaking (250 rpm) at
37°C.
Suberin and cutin preparation
A suberin-enriched potato periderm was obtained as previously
described (Kolattukudy and Agrawal, 1974). The extracted mate‐rial was dried under a hood, ground using a coffee mill, and stored
at room temperature. To further remove residual polysaccharides in
the potato periderm, this material was exposed to microbial degra‐
dation in the presence of S. scabies EF-35, as described byBeaulieu et al. (2016). The S. scabies inoculum (1 mL) was added
to 50 mL of minimal medium consisting of a mineral solution(0.5 g L–1 [NH4]2SO4, 0.5 g L–1 K2HPO4, 0.2 g L–1 MgSO4-7H2O,
and 10 mg L–1 FeSO4-7H2O) and 1 g L–1 of the suberin-enriched
potato periderm. After a 30-d incubation, 10 mL of fresh mineralsolution and 200 μL of the S. scabies inoculum were both added tothe culture and the incubation was extended for an additional 30 d.
The culture was centrifuged at 3,450×g for 20 min, and the pellet
was resuspended in 100 mL of sterile water and then autoclavedfor 15 min. The suspension was washed with sterile water toremove bacterial cell debris. The resulting material (purified potato
suberin) was dried at 50°C for 24 h. Cutin was isolated from apples
following the protocol of Walton and Kolattukudy (1972).
DNA extraction
Genomic DNA was isolated from 48-h bacterial cultures of S.
scabies EF-35 using the GenElute Bacterial Genomic DNA Kit(Sigma-Aldrich) according to the manufacturer’s instructions.
Plasmid DNA was isolated from 12-h E. coli cultures using the
GenEluteTM Plasmid Miniprep Kit (Sigma-Aldrich) following the
manufacturer’s instructions.
Cloning of sub1 in E. coli
The sub1 coding sequence, deprived of its signal peptide (Gen‐Bank accession number MK689853), was amplified by PCR fromthe genomic DNA of S. scabies EF-35 using the primers F-pET(5′-ATATCCATGGCCGCCTGCACGGACATCG-3′) and R-pET(5′-ATATCTCGAGTTAGATCTTGGTCGCGGCGAAGG-3′). The
PCR mix contained 20 ng of DNA, 2.5 μL of Taq polymerase buf‐fer, 0.5 μL of dNTPs (10 mM), 0.5 μL (each) of forward andreverse primers (10 μM), and 0.125 μL of DNA Taq polymerase

Jabloune et al.
(New England Biolabs), in a total volume of 25 μL. PCR condi‐
tions consisted of 2 min at 95°C followed by 30 cycles at 95°C for
30 s, at 64°C for 1 min, and at 68°C for 1 min, with a final exten‐
sion at 68°C for 5 min. PCR was performed using the thermocycler
T100 (Bio-Rad). Amplification products were migrated on a 1%
agarose gel (Sambrook and Russell, 2001), purified from gelsusing the MinElute Gel Extraction Kit (Qiagen), and cloned into
the pET-30a(+) vector (Novagen). The amplification product andcloning vector pET-30a(+) were both digested using the restriction
enzymes NcoI and XhoI. Enzyme T4 DNA ligase (New England
Biolabs) was used to ligate plasmid ends to amplicons following
the manufacturer’s instructions. Ligation products were heatshock-transformed into competent cells of E. coli DH5α as per the
manufacturer’s instructions (New England Biolabs). Bacteria werethen incubated overnight on LB agar medium supplemented withkanamycin (30 μg mL–1). The plasmid insert was sequenced at asequencing and genome genotyping platform (CHUL, University
Laval, Quebec City, Canada). The plasmid pET-30a(+), with orwithout the sub1 insert, was transformed into the expression hostE. coli SHuffle T7, as previously described.
Protein extraction
Cultures of E. coli SHuffle T7 carrying pET without or with thesub1 gene insert (E. coli SHuffle T7-pET and E. coli SHuffle T7pET-sub1) were incubated on LB agar medium supplemented withkanamycin. When OD600 reached 0.6–0.8, isopropyl β-D-1thiogalactopyranoside (IPTG) was added to the culture (0 to
1.0 mM, final concentration) and bacteria were incubated at 25°C
for an additional 24 h. Cells were harvested by centrifugation(3,450×g) for 10 min, pellets were washed twice with saline (NaCl0.9%) and then resuspended in a buffer solution (50 mM NaH2PO4
and 300 mM NaCl, pH 8.0) supplemented with EDTA (2.5 mM).
The suspensions were sonicated on ice four times for 10 s and cen‐trifuged (3,450×g) at 4°C for 30 min to remove cell debris. The
supernatant was collected and successively passed through filterswith pore sizes of 0.45 and 0.2 μm. The resulting protein solution
was stored at 4°C.
Purification of the protein Sub1
An affinity column Ni-NT cOmplete His-Tag purification col‐umn (Roche) was used to purify the protein Sub1 from the cyto‐
plasmic fraction of E. coli SHuffle T7-pET-sub1, following the
manufacturer’s instructions. Elution buffer A (50 mM NaH2PO4,
300 mM NaCl, pH 8.0), supplemented with different concentra‐
tions of imidazole (5 to 250 mM), was used for column washingand His6-tagged protein elution. Protein fractions were subjected
to sodium dodecyl sulfate-polyacrylamide gel electrophoresis(SDS-PAGE) migration along with the marker PageRuler™ Pre‐
stained Protein Ladder (Thermo Scientific), as described by
Komeil et al. (2014). Proteins were stained with Coomassie bril‐liant blue R-250 (Bio-Rad; Lauzier et al., 2008) and fractions con‐taining purified Sub1 were pooled. This mixture was dialyzed inphosphate-buffered solution (PBS) to remove imidazole. Protein
concentrations were measured according to Bradford (Bradford,
1976).
Esterase activity of Sub1 on p-nitrophenyl esters
Esterase activity was assessed by spectrophotometrically meas‐
uring the absorbance of p-nitrophenol using the substrates pnitrophenyl butyrate (C4), p-nitrophenyl octanoate (C8), pnitrophenyl decanoate (C10), and p-nitrophenyl dodecanoate (C12)(Sigma-Aldrich). The molar extinction coefficient of p-nitrophenol
in Tris-HCl (20 mM, pH 7.5) at room temperature is
12,000 M–1 cm–1 at 420 nm. This enzymatic assay was performed
as described previously (Komeil et al., 2013) with slight modifica‐
tions. In a 1.5-mL plastic cuvette, 20 μL of 100×-diluted Sub1
(60 ng) was added to 970 μL of Tris-HCl (20 mM, pH 7.5), with orwithout Triton X-100 (0.5%), and 10 μL of a 20 mM p-nitrophenyl
ester substrate (0.2 mM final concentration). The absorbance at23

Sub1, a suberinase from Streptomyces scabies
420 nm of this reaction mix was measured at room temperature
every 10 s for 1 min. The increase in absorbance of each sample
was read against a blank without purified protein. One unit (U) was
the amount of enzyme liberating 1 μmol of p-nitrophenol min–1
under the assay conditions. The Vmax and Km values of the enzyme
Sub1 were assessed using the software GraphPad Prism7,
according to the Michaelis-Menten equation, with different con‐centrations of the C4 substrate.
Esterase activity of Sub1 on natural and synthetic polymers
Suberin and cutin were exposed to the enzyme Sub1 as follows.
Suberin or cutin (10 mg) was added to 350 μL of Tris-HCl(20 mM, pH 7.5) supplemented with 50 μL of the purified enzyme
Sub1 (15 μg). Control assays (blanks) were made of suberin andcutin without the addition of the enzyme Sub1. The mixture wasincubated at room temperature for 20 d. Colorimetric assays of freefatty acids released from the biopolymer were performed every 5 dusing a Free Fatty Acid Quantification Colorimetric/FluorometricKit (BioVision) according to the manufacturer’s instructions. A
standard curve was prepared with palmitic acid to convert absorb‐
ance at 570 nm into fatty acid concentrations.
The hydrolyzing activity of Sub1 was also estimated on poly‐
ethylene terephthalate (PET) by measuring the amount of tereph‐thalic acid (TA) released from PET according to Nimchua et al.
(2008) with slight modifications. Assays were conducted in 2-mL
tubes containing 10 mg of PET (ground granules, Sigma-Aldrich),
1 mL of Tris-HCl (20 mM, pH 7.5), and 3 μg of the enzyme Sub1.
In the first experiment, the effects of Triton on Sub1 performance
were tested. Tubes, with or without Triton X-100 (0.5%), wereincubated at 37°C and the concentrations of TA released in the
incubation media were recorded after 10 and 15 d. Blank assays, inwhich the enzyme Sub1 was omitted, were used as controls. Tubes
were then centrifuged (1 min) and 50 μL of the collected superna‐tant was added to 350 μL of Tris-HCl (20 mM, pH 7.5) into quartz
cuvettes. Absorbance at 240 nm was measured to assess TA con‐centrations (using a standard curve). In another experiment, thestability of Sub1, using PET as a substrate, was assessed at 37 and
50°C over a 20-d period. The incubation medium contained Triton
X-100 (0.5%) and the concentration of TA released in the reaction
mix was measured every 5 d, as described above.

Results
Heterologous production of Sub1
The S. scabies sub1 gene was cloned into a pET expres‐sion vector (data not shown) and expressed in E. coli strain

24

3/7

SHuffle T7. The cytoplasmic extract of E. coli SHuffle T7pET-sub1 was characterized by a thick and dense band of
approximatively 25 kDa, which was absent from the protein
profile of E. coli SHuffle T7-pET (Fig. 1). In E. coli SHuffle
T7-pET-sub1, Sub1 was produced even in the absence of
IPTG, while thicker protein bands were observed when sub1
gene expression was induced by this compound (Fig. 1).
The cytoplasmic fraction from cultures of E. coli Shuffle
T7-pET-sub1 showed, in the absence of the induction with
IPTG, that esterase activity on the C4 substrate (58.8 μmolmL–1) was significantly higher than that in control E. coli
SHuffle T7-pET (1.6 μmol mL–1) after 30 min of the incuba‐tion (Fig. 2). The esterase activity of E. coli SHuffle T7pET-sub1 was inducible with IPTG and was quickly
observable in the reaction mix. After 5 min of the incuba‐tion, the highest activity reached 32.2 μmol mL–1 when

Fig. 2. Esterase activity of cytoplasmic extracts from Escherichia coli
SHuffle T7 transformed with plasmid pET without (E. coli SHuffle
T7-pET) or with (E. coli SHuffle T7-pET-sub1) the sub1 insert andexposed to various concentrations of IPTG. Activity is expressed as theconcentration of p-nitrophenol released from p-nitrophenyl butyrate
substrate in 5- and 30-min reactions. These results are the means offive replicates±SD. Bar values accompanied by the same lower caseletter or upper case letter were not significantly different.

Fig. 1. SDS-PAGE gel of the cytoplasmic extract obtained from pET-transformed Escherichia coli strain SHuffle T7, without (E. coli SHuffle
T7-pET) or with (E. coli SHuffle T7-pET-sub1) the insert of the sub1 gene, after induction with different concentrations of IPTG.

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Jabloune et al.

0.8 mM IPTG was added to the culture, while activity was
6.3 μmol mL–1 in the absence of IPTG (Fig. 2).
Purification of the recombinant protein His-Sub1
An affinity column Ni-NT (cOmplete His-Tag) was used
to purify the recombinant protein Sub1 from the cytoplas‐
mic fraction of E. coli SHuffle T7-pET-sub1. By comparing
the migration profile of the cytoplasmic fraction and theflow-through (Fig. 3, lanes 2 and 3, respectively), the bandcorresponding to the recombinant protein His-Sub1(25 kDa) was present in the cytoplasmic fraction, while noband was present in the flow-through fraction, indicatingthat the Sub1 protein bound the column. The presence ofimidazole in the elution buffer allows the elution of His-tag
proteins from the column. At imidazole concentrations
ranging between 4 and 10 mM, the elution buffer released
the majority of the contaminant proteins, while a low quan‐tity of Sub1 was released with 10 mM imidazole (lane 7,
Fig. 3). A detectable quantity of Sub1 was eluted with nocontaminant proteins when 50 mM imidazole buffer wasused (lane 8, Fig. 3). However, at 200 mM imidazole, norecombinant protein was detected (lane 9, Fig. 3). A mass
spectrometry analysis confirmed that the purified protein
was Sub1 (data not shown). Purification efficacy was esti‐
mated by comparing the esterase activities (with 0.4 mM pnitrophenol butyrate as the substrate) of the cytoplasmic
fraction and the purified protein. The esterase activity of
Sub1 was 52-fold higher in the purified extract(23.0 U mL–1) than in the cytoplasmic crude extract(0.4 U mL–1).
Esterase activity of the Sub1 protein on p-nitrophenyl esters
The esterase activity of Sub1 on the p-nitrophenyl estersof varying carbon chain lengths was assessed in the presence
and absence of Triton X-100. Independent of the presence of
Triton X-100, Sub1 was more active on p-nitrophenyl buty‐rate (C4) and p-nitrophenyl octanoate (C8) than on pnitrophenyl esters with longer carbon chains (C10 and C12,
Fig. 4). The presence of Triton X-100 increased the esterase
activity of the enzyme on all of these substrates (Fig. 4). The
highest esterase activity (14.6 U nmol–1 or 616 U mg–1
Sub1) was obtained on the C4 substrate in the presence of
Triton X-100. Thus, Vmax and Km values for esterase Sub1
were calculated using the latter substrate. As shown in Fig.
5, the initial velocity (V0) of the hydrolysis reaction
increased when higher concentrations of the substrate pnitrophenol butyrate (p-NPB) were used. According to theMichaelis-Menten equation, Vmax was 55.8±2.0 U nmol–1
Sub1 (2,361±84.5 U mg–1 Sub1) and Km was 0.57±0.04 mM
p-NPB.
Effects of the Sub1 esterase on polymers
Sub1 was shown to hydrolyze suberin and cutin, releasing
1.22±0.06 and 2.65±0.18 nmol of fatty acids (palmitic acidequivalent) μg–1 Sub1 from these polymers, respectively,
after 20 d of the incubation. The ability of Sub1 to degrade
cutin and suberin appeared to be stable over the experimen‐
tal time course at room temperature because the amounts offatty acids released in the incubation medium correlatedwith time (P<0.0001; Fig. 6).

SDS–PAGE gel of cytoplasmic soluble proteins obtained from
Escherichia coli transformed with SHuffle T7-pET-sub1, after
fractionation on the affinity column (IMAC). Lane 1, molecular weightmarker; lane 2, cytoplasmic extract; lane 3, flow-through; lane 4,
proteins released after washing with buffer A; lanes 5 to 9, proteins
released after washing with buffer A supplemented with 4, 5, 10, 50, or
200 mM imidazole, respectively.

Fig. 3.

Esterase activity of the purified Sub1 enzyme using pnitrophenyl substrates of different carbon chain sizes (C4, C8, C10,
and C12) in the absence or presence of Triton X-100 (0.5%). Datashown are the mean±SD of three replicates. Bar values accompaniedby the same letter are not significantly different.

Fig. 4.

On the other hand, the release of TA showed that theSub1 esterase also had the ability to hydrolyze the synthetic
substrate PET. The addition of Triton X-100 to the reaction
mix enhanced the hydrolysis of PET by ca. 2.6-fold(P<0.0001, t-test; Fig. 7A) after 10 and 15 d of the incuba‐tion. The esterase activity of Sub1 on PET, in the presenceof Triton X-100, increased over the incubation time because
the amount of TA released during the degradation of PET
correlated with the incubation time (P<0.0001; Fig. 7B).
The enzyme Sub1 showed high stability at 37°C over thetest period (20 d) because the concentration of TA releasedin the incubation medium linearly correlated with time(r2=0.9874). However, the stability of Sub1 at 50°C fit a
non-linear curve (r2=0.9667).
25

5/7

Sub1, a suberinase from Streptomyces scabies

Degradation of cutin and suberin by enzyme Sub1 at room
temperature over a 20-d period, as expressed by the release of fatty
acids in the incubation medium. Data are the means±SD of four
replicates.

Fig. 6.

Effects of substrate (p-NPB) concentrations on the initial
speed (V0) of the hydrolysis reaction of the esterase Sub1. (A)Michaelis-Menten kinetic and (B) Lineweaver-Burk plot. Data are themeans±SD of three replicates.
Fig. 5.

Discussion
S. scabies may colonize potato tuber surfaces and is able
to directly penetrate potato cells (Loria et al., 2003). Previ‐
ous studies proposed that its entry into potato tuber tissues
may be facilitated by the production of esterases that26

degrade suberin present in the potato periderm (McQueenand Schottel, 1987; Beauséjour et al., 1999; Komeil et al.,2013). Although suberin degradation has not yet been exam‐
ined in detail, some fungal cutinases exhibit activity towards
suberin (Kontkanen et al., 2009). The protein Sub1 is part of
the S. scabies secretome when this bacterium is grown in thepresence of suberin (Beaulieu et al., 2016) and the sub1
gene is induced in the presence of suberin (Komeil et al.,2013). This study predicted that Sub1 was a cutinase due toits high sequence homology with other cutinases of fungal
origin. The present results confirm this prediction because
Sub1 exhibited the ability to hydrolyze both cutin and suberin.
In the present study, the heterologous production of the S.
scabies Sub1 protein was successfully achieved in E. coli.
Other studies also reported the heterologous expression ofbacterial esterases in E. coli (Chen et al., 2008; Su et al.,2013; Ribitsch et al., 2015). The molecular weight of Histagged Sub1 was estimated herein to be 25 kDa, which isconsistent with the predicted molecular weight of mature
Sub1 (18.7 kDa) plus the His-tag (4.9 kDa). Therefore, themolecular weight of Sub1 appears to be less than that ofmost bacterial cutinases, such as Tfu-0882 and Tfu-0883

Fig. 7. Concentrations of terephthalic acid (TA) released following the hydrolysis of ground particles of polyethylene terephthalate by 3 μg of theSub1 enzyme. (A) Effects of the presence of Triton X-100 (0.5%) on Sub1 performance after 10 and 15 d of incubation (at 37°C). (B) Sub1
enzymatic stability (in the presence of 0.5% Triton X-100) during 20 d of incubation at 37 and 50°C. TA concentrations were measured every 5 d.
Data are the means±SD of four replicates.

6/7

from Thermobifida fusca (29 kDa; Chen et al., 2008), but iscloser to those of fungal plant pathogen cutinases, such as
CcCUT1 from C. cinerea (18.8 kDa; Kontkanen et al.,2009) and CutA from Botrytis cinerea (18 kDa; van der
Vlugt-Bergmans et al., 1997).
As reported with other cutinases, purified Sub1 also has
the ability to hydrolyze p-nitrophenyl esters. Sub1 was more
active on p-nitrophenyl esters with short carbon chains, i.e.
p-nitrophenyl butyrate (p-NPB, C4) and p-nitrophenyl octa‐
noate (C8), than on those with longer carbon chains (C10and C12). Other microbial cutinases have also been reported
to be more active on p-nitrophenyl esters harboring shortfatty acid chains (Purdy and Kolattukudy, 1973; Kontkanen
et al., 2009). Using p-nitrophenyl butyrate as a substrate, theactivity of Sub1 followed a typical Michaelis-Menten curve.
The Sub1 enzyme showed affinity towards this substrate(Km=5.7 10–4 M), similar to two cutinases of Fusarium
solani pv. pisi with Km of 3.5 10–4 M and of 7.5 10–4 M,
respectively (Kolattukudy et al., 1981). Although strepto‐
mycetes such as S. scabies and filamentous fungi belong todifferent kingdoms, they exhibit similar lifestyles and often
share the same ecological niches (Wösten and Willey,2000). Their mycelia colonize various organic polymers andproduce large amounts of extracellular enzymes to retrieve
nutrients from these substrates. Therefore, similarities
between Sub1 and fungal cutinases may reflect an adapta‐
tion to a similar lifestyle. Other Streptomyces extracellularenzymes, e.g. chitosanases from the GH75 family, areencoded by genes that are also mainly represented in fungal
and actinobacterial genomes (Lacombe-Harvey et al., 2018).
Sub1 has high similarity, at the amino acid level, to thecutinase CUT1 from F. solani, which is able to degrade sub‐erin. Similar to CUT1, the present results indicated that
Sub1 exhibits hydrolysis activity on suberin. However, Sub1
and CUT1 showed higher activity on cutin than on suberin,
even though S. scabies and F. solani both infect and colo‐
nize potato tubers and are, thus, frequently in contact withpotato suberin (Fiers et al., 2012). This finding indicatesthat the presence of aromatic compounds in suberin also
contributes to its recalcitrant nature (Faber, 1979). However,difficulties are associated with comparing the efficacy ofSub1 with fungal cutinases because the methods used tomonitor cutinase activity differ between studies (van der
Vlugt-Bergmans et al., 1997; Kontkanen et al., 2009; Chenet al., 2013; the present results). To the best of our knowl‐edge, Sub1 represents the first bacterial cutinase for which
activity towards suberin has been demonstrated. Based on
the ecological niche of this pathogen, in which potato
tubers, but not the aerial part of the plant, are infected, sub‐erin most likely represents an important substrate for Sub1in the environment and, consequently, Sub1 may be desig‐
nated as a suberinase. While the ability to degrade cutin has
been shown to be important for the pathogenicity of various
fungal plant pathogens (Feng et al., 2011; Wang et al.,2017), there is no evidence to show that the ability todegrade suberin represents an asset in the infection processof plant pathogens. The Sub1 protein does not appear to bean essential pathogenicity factor for S. scabies because thesub1 gene has not been detected in other common scabinducing Streptomyces species, such as S. acidiscabies

Jabloune et al.

(Komeil et al., 2013), and its primary benefit may involvethe degradation of refractory polymers. However, Sub1 may
confer an advantage to S. scabies over other common scabinducing species by facilitating direct penetration, tuber col‐onization, and persistence in potato tuber debris.
While Sub1 is conserved in only a few streptomycetes, it
presents high homology not only with some fungal cuti‐nases, but also with cutinase-like enzymes from animal
pathogenic mycobacteria (Komeil et al., 2013). These bacte‐
ria do not encounter cutin or suberin in their environment;
however, cutinases were identified as multifunctional
enzymes that act on phospholipids, polysorbates, triacylgly‐
cerols, and triolein (Schué et al., 2010; Monu and Meena,2016). As multifunctional enzymes, cutinases have a num‐
ber of applications in industry (Carvalho et al., 1998). In thepresent study, the effects of Sub1 on PET, a synthetic poly‐
ester that is widely used in the production of textiles, were
tested. Sub1 was shown to degrade PET because the quan‐tity of terephthalic acid released from the synthetic polymer
depended on the enzyme concentration and increased overthe incubation time. The enzyme Sub1 maintained its activ‐
ity at 37°C for at least 20 d, showing that it is stable, as has
been demonstrated for other cutinases (Dutta et al., 2009).
Due to their functional properties, cutinases are considered
to be a link between esterases and lipases (Chahinian et al.,2002). The addition of a non-ionic surfactant, such as Tri‐
ton, into a reaction mix generally promotes the activity oflipases, but does not affect the activity of most cutinases.
For example, the presence of Triton in the reaction mix
increased the hydrolysis of polyester bis-(benzoyloxyethyl)
terephthalate (3PET) by a lipase secreted by Thermomyces
lanuginosus, whereas it did not exert any effect when thesame substrate was exposed to cutinases secreted by T. fusca
and F. solani (Eberl et al., 2009). Triton increases the activ‐
ity of lipases by promoting the opening of a peptide lid
located over the active site of the enzyme; such a lid is notpresent in cutinases (Eberl et al., 2009). As observed withmost cutinases, the addition of Triton X-100 did not affectcutin hydrolysis by Sub1 (data not shown). Nevertheless,the hydrolysis of p-nitrophenyl esters and of PET by Sub1
was enhanced in the presence of Triton.
The present study established that the sub1 gene of S.
scabies encodes a protein acting as a suberinase. The versa‐
tility of Sub1 may also be considered for adoption in indus‐
trial applications. A cutinase-like enzyme has recently
attracted global public attention. This enzyme, originallycharacterized in the bacterium Ideonella sakaiensis 201-F6,
is able to degrade PET and has been reclassified as a PETase(Yoshida et al., 2016). Thereafter, Austin et al. (2018) intro‐
duced modifications to the binding cleft of this enzyme andproduced an engineered PETase with better plasticdegrading properties than the native enzyme. The current
need for enzymes with the ability to degrade refractory pol‐ymers of anthropic origin makes further studies on the capa‐
bilities of Sub1 very relevant.
Acknowledgements
The authors thank Peter Moffett for the critical review of themanuscript. This work was funded by the Natural Sciences andEngineering Research Council of Canada (grant number 018602).

27

Sub1, a suberinase from Streptomyces scabies
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Microbes Environ. Vol. 29, No. 4, 427-430, 2014

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MOST CITED ORIGINAL PAPER PUBLISHEDIN THIS TEN YEARS [2013-2022] (252 citations)
MOST CITED ORIGINAL PAPER IN 2022 (38 citations)Short Communication
Intestinal Colonization by a Lachnospiraceae Bacterium Contributes
to the Development of Diabetes in Obese Mice
Keishi Kameyama1*, and KiKuji itoh2
1Institute for Innovation, Ajinomoto Co., Inc., Kawasaki 210–8681, Japan; and 2Department of Veterinary Public Health, Graduate

School of Agricultural and Life Sciences, The University of Tokyo, Tokyo 113–8657, Japan(Received April 4, 2014—Accepted July 17, 2014—Published online October 4, 2014)

The aim of the present study was to identify bacteria that may contribute to the onset of metabolic dysfunctions. We isolated
and identified a candidate bacterium belonging to Lachnospiraceae (strain AJ110941) in the feces of hyperglycemic obese
mice. The colonization of germ-free ob/ob mice by AJ110941 induced significant increases in fasting blood glucose levels aswell as liver and mesenteric adipose tissue weights, and decreases in plasma insulin levels and HOMA-β values. These results
indicated that the specific gut commensal bacterium AJ110941 influenced the development of obesity and diabetes in ob/ob
mice with genetic susceptibility for obesity.
Key words: gut microbiota, diabetes, T-RFLP, gnotobiotic mouse, Lachnospiraceae

The gut microbiota has been shown to influence hostenergy homeostasis, metabolism, and inflammation; thus,
microbial communities within the gut are now recognized as
an important environmental factor in the onset of obesity andtype 2 diabetes (T2D) (5, 7, 12, 14, 23). As a consequence,
interest in the development of methods to target gut microbiota
as a therapy for T2D is increasing (2, 12, 18, 21).
Several studies have conducted metagenomic analyses in
an attempt to identify members of the gut microbial community that contribute most significantly to the progression of
T2D. Qin et al. performed a metagenomic analysis on fecal
samples obtained from 345 Chinese men and women with orwithout T2D (19). Karlsson et al. also conducted a metagenomic analysis to compare microbial communities in fecal
samples collected from 145 European women who had either
T2D, impaired glucose metabolism, or were healthy (13).
Both of these studies reported that butyrate-producing
Roseburia species and Faecalibacterium prauznitzii wererarer in subjects with T2D; however, the identified bacteriathat existed in high population in T2D subjects differed between
these studies (8). Cani et al. proposed that lipopolysaccharide(LPS), a cell wall component of almost all Gram-negative
bacteria, may be a key substance responsible for metabolic
endotoxemia, low-grade systemic inflammation, and insulin
resistance in mouse models (1, 3). In support of this, aprevious study reported that experimental endotoxemia
induced adipose inflammation and insulin resistance inhuman subjects (17).
We herein searched for the specific gut commensal bacterium related to metabolic syndrome using the terminal
restriction fragment length polymorphism (T-RFLP) analysisof fecal samples from a mouse model of T2D. In this study, acomparison of homozygous db/db (diabetic) with heterozygous db/+ (non-diabetic) mice revealed that a specific* Corresponding author. E-mail: keishi_kameyama@ajinomoto.com

fragment of the T-RFLP analysis was present at significantly
higher levels in db/db mice than in db/+ mice. Even thoughob/ob obese mice gain weight rapidly and show the symptoms of insulin resistance, most of the obese mice do notdevelop severe hyperglycemia compared with db/db mice(22). However, one of the ob/ob mice in the present study
showed an abnormally high fasting blood glucose (FBG)
level similar to db/db mice. The specific fragment observed in
db/db mice was also the most prominent in the abnormally
hyperglycemic ob/ob mouse. We hypothesized that the specific bacterium harboring the fragment may have contributed
to the progression of T2D; therefore, we isolated and cultured
the bacterium (strain AJ110941). We then determined thatcolonization by the isolate with the LPS producer E. coli
induced hyperglycemia and the accumulation of adipose
tissue in the gnotobiotic ob/ob mouse model.
All experimental procedures were reviewed and approvedby the Animal Care Committee of Ajinomoto Co., Inc.
Male 5-week-old homozygous BKS.Cg-Dock7m +/+Leprdb/J(db/db, diabetic) mice, heterozygous control (db/+, nondiabetic) mice, and homozygous B6.V-Lepob/J (ob/ob, obese)
mice were obtained from Charles River Japan (Yokohama,Japan). Male 5-week-old germ-free ob/ob mice were obtained
from Sankyo Lab Service (Tokyo, Japan). These mice werehoused in a controlled environment (on a 12-h light/darkcycle with lights turning off at 19:00) with free access tostandard chow CRF-1 (Oriental Yeast, Tokyo, Japan) andwater and kept in specific pathogen-free (SPF) or germfree/gnotobiotic conditions throughout the experimental
period. Fresh feces and blood were collected from 5- and11-week-old mice after fasting for 16 h.
Blood glucose (FBG) levels were determined using
DRI-CHEM 7000V (Fujifilm, Tokyo, Japan). Plasma insulinlevels were determined using an ultrasensitive mouse insulinkit (Morinaga Institute of Biological Science, Yokohama,Japan). Plasma glucagon levels were determined using the

29

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Glucagon ELISA Kit Wako (Wako Pure Chemical Industries,
Osaka, Japan). Insulin resistance (HOMA-IR) and β-cellfunction (HOMA-β) were both calculated on the basis of thefasting levels of plasma glucose and insulin according to thehomeostasis model assessment (HOMA) method (16).
Fresh fecal samples were collected from mice, added to
99% ethanol, and stored at −30°C. Bacterial DNA wasextracted from the fecal samples using the FastDNA spin kit
for soil (MP Biomedicals, Santa Ana, CA) using the FastPrep
instrument (MP Biomedicals). T-RFLP analyses of the mouse
gut microbiota were performed as previously described (10).
Two universal primers, 27F labeled with 6-carboxyfluorescein(FAM): 5'-FAM-AGAGTTTGATCCTGGCTCAG-3' and
1492R: 5'-GGTTACCTTGTTACGACTT-3' were used in
PCR to amplify the 16S rRNA gene coding region. Purified
PCR products of the 16S rRNA gene were digested with MspI
(Takara Bio, Otsu, Japan).
To isolate and culture the bacterium, fresh feces werecollected and immediately weighed and transferred to ananaerobic chamber. The feces were homogenized with a
50-fold volume (v/w) of an anaerobic diluent, serially diluted,
and then plated on Eggerth-Gagnon (EG) agar plates (11).
The agar plates were incubated at 37°C for 4 d in theanaerobic chamber. All of the colonies were identified bytheir fragment size, and a target colony with a fragment sizeof 282 bp was then selected. The colony was passaged onto
new EG agar plates, and the bacterial purity of the isolate was
ensured by re-streaking and microscopic observations. The
16S rRNA gene sequence of the isolated bacterium wasdetermined as previously described (15). The sequence wasassembled using GENETYX version 7 (GENETYX, Tokyo,
Japan). The identification and phylogenic tree analysis of the
16S rRNA gene sequence were carried out using the
Ribosomal Database Project (RDP) (6).
When the mice were 8 weeks old, germ-free ob/ob mice
were separated into 3 groups for the germ-free/gnotobiotic
experiment: Group-1 (n=4), germ-free; Group-2 (n=4),
colonization by the non-pathogenic Escherichia coli strain
E-17, which had been isolated from SPF mice; Group-3(n=4), colonization by AJ110941 with E. coli E-17. Groups-2
and -3 were then orally inoculated with E. coli E-17 or
AJ110941 with E. coli E-17 (approximately 1×108 cells suspended in anaerobic PBS, respectively). Group-1 was orally
administered PBS only. These mice were maintained under
the germ-free or gnotobiotic conditions for 8 weeks.

30

Kameyama et al.

We compared differences in gut microbiota patterns
between db/+ and db/db mice. Hyperglycemia was observedin 11-week-old, but not in 5-week-old mice (Fig. S1). The
282 bp fragment was significantly higher in db/db than db/+
mice at both 5 and 11 weeks old (Fig. S2). We then evaluatedthe presence of the 282 bp fragment in another metabolic
syndrome model, the ob/ob mouse. The highest FBG level
observed among all ob/ob mice was in Mouse Number 4 (Fig.
S3). The 282 bp fragment was also more prominent in hyperglycemic Mouse Number 4 than in the normal glycemic
ob/ob mouse at both 5 and 11 weeks old (Fig. S4). Based onthese db/db and ob/ob mice results, we focused on this 282 bp
fragment bacteria.
We isolated a colony harboring the 282 bp fragment andestablished an axenic strain (strain AJ110941). The isolate
was determined to be closely related to the genus Anaerostipes
in the family Lachnospiraceae (Fig. 1).
We then generated gnotobiotic ob/ob mice colonized by
AJ110941 with E. coli. Eight weeks after the inoculation, thececum, liver, adipose tissue, and blood were collected after a
16-h fast. The gut microbiota of the cecal contents from thethree groups was determined by T-RFLP analysis. No PCR
amplicon was detected in Group-1. Only a single fragment(488 bp) that corresponded to E. coli was detected in Group2. Only two fragments (282 bp and 488 bp) were detected inGroup-3. These results clearly indicated that germ-free orgnotobiotic conditions were maintained during the experimental period. The weights of the liver and mesentericadipose tissue significantly increased in Group-3, whereas no
significant difference was observed in body weights between
the three groups. FBG and plasma glucagon levels weresignificantly higher in Group-3, while plasma insulin levels
were significantly lower. On the other hand, no significant
differences were observed in these parameters between
Groups-1 and -2. The homeostasis model assessment wascalculated from FBG and plasma insulin levels as an index of
insulin resistance (HOMA-IR) and pancreatic β cell function(HOMA-β). HOMA-β was significantly lower in Group-3,
whereas no significant differences were noted in HOMA-IR
between the three groups (Table 1). These results suggested
that colonization by AJ110941 may have promoted thedysfunction of pancreatic β-cells.
Therefore, AJ110941 should be regarded as one of theimportant causative gut bacteria for the induction of T2D. A
previous study reported that the relative abundance of theFig. 1. Phylogenetic tree based on the 16S rRNA gene constructed by Weighbor, the weighted neighbor-joining tree building algorithm, showing
AJ110941 and other strains of the family Lachnospiraceae. Clostridium perfringens ATCC13124T was used as an outgroup. The numbers close to
the nodes represent bootstrap values (n=100 replicates). The scale bar represents 0.05 substitutions per nucleotide position.

A Lachnospiraceae Bacterium Involved in Diabetes
Table 1.

429

Phenotypes of germ-free and gnotobiotic ob/ob mice

Body weight without the caecum (g)Cecum (% of body weight)
Liver (% of body weight without the cecum)
Mesenteric adipose tissue (% of body weight without the cecum)
Fasting blood glucose (mg dL−1)
Fasting plasma insulin (μU mL−1)
Fasting plasma glucagon (pg mL−1)
HOMA-IR
HOMA-βGroup-1

Group-2

Group-3

58.10 ± 5.98a
11.63 ± 4.89a
6.91 ± 0.66a
1.64 ± 0.46a
216.5 ± 113.6a
339.7 ± 46.44a
179.9 ± 43.0a
132.5 ± 23.3a
1350.4 ± 468.9a

61.75 ± 4.29a
12.88 ± 1.94a
7.29 ± 1.83a
1.81 ± 0.39a
286.5 ± 54.1ab
299.8 ± 105.0a
324.2 ± 42.4a
187.5 ± 70.6a
638.5 ± 411.9ab

63.48 ± 10.37a
4.47 ± 0.93b9.70 ± 0.46b
2.63 ± 0.30b
433.25 ± 65.4b
159.4 ± 50.9b
529.0 ± 18.3b
184.4 ± 64.1a
141.7 ± 40.7b

Group-1: germ-free, Group-2: colonization by E. coli, Group-3: colonization by AJ110941 with E. coli. Data are expressed asmeans±SD. Values not sharing a common letter are significantly different at p<0.05 by the Tukey–Kramer multiple comparisons test
(n=4 per group) using the JMP 10.0.0 statistical software package (SAS Institute, Cary, NC).

taxonomic family Lachnospiraceae was increased by earlylife subtherapeutic antibiotic treatments in an obese mousemodel (4). Additionally, a metagenomic study indicated thatthe taxonomic family Lachnospiraceae may be associatedwith T2D (19). However, it remains unclear whether bacteria
belonging to the family Lachnospiraceae actually affectobesity and FBG levels in vivo. Therefore, we generated
gnotobiotic ob/ob mice colonized by AJ110941 with E. coli
to reveal a possible causal relationship. In a preliminary
examination, we microscopically observed that AJ110941
did not singly colonize the intestinal tract of ob/ob germ-freemice. E. coli, which is a facultative anaerobe, may be needed
to maintain an oxygen-free environment in the intestinal tract
because AJ110941 needs strict anaerobic conditions for
growth. In our study, a mono-association with the LPS
producer E. coli induced neither hyperglycemia nor theaccumulation of adipose tissues. In contrast, LPS derived
from Gram-negative bacteria in the gastrointestinal tract waspreviously identified as one of the most important factors
inducing the development of T2D (1, 3). Our results indicatedthat the presence of LPS in the intestinal tract was necessary,
but not sufficient for the pathogenesis of diabetes. We speculated that AJ110941 may have assisted with the translocationof LPS into the blood from the intestinal tract. We are
currently investigating the effects of AJ110941 on LPS
translocation in in vitro/vivo models.
Regarding the particular gut bacterium involved in metabolic syndrome, Methanobrevibacter smithii and Bacteroides
thetaiotaomicron were previously shown to enhance hostenergy storage in di-associated mice (20). Furthermore, Fei
and Zhao reported that the strain Enterobacter cloacae B29,
which was isolated from an obese human subject, induced
obesity and insulin resistance accompanied by serum endotoxemia in mono-associated mice (9).
This is the first study to have successfully identified a
specific Lachnospiraceae bacterium involved in metabolic
disorders. Future studies are needed to elucidate the molecular mechanisms underlying the adverse effects of AJ110941
on glucose and lipid metabolism in mouse models. It remains
unclear whether AJ110941 or its closely-related species
inhabits the human intestinal tract. We intend to perform apreliminary epidemiological study on obese and diabetic
subjects to address this question.
The 16S rRNA gene sequence of the isolated bacterium(strain AJ110941) is available in the DDBJ/EMBL/GenBank
databases under the accession number AB861470.

Acknowledgements
We thank Ranko Nishi and Mizuki Kobayashi for their research
assistance.
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Microbes Environ. 35(2), 2020

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Minireview

MOST CITED REVIEW PAPER PUBLISHEDIN THIS THREE YEARS [2020-2022] (24 citations)

Size Matters: Ultra-small and Filterable Microorganisms in the Environment
Ryosuke Nakai1*†
Applied Molecular Microbiology Research Group, Bioproduction Research Institute, National Institute of Advanced Industrial
Science and Technology (AIST), 2–17–2–1, Tsukisamu-Higashi, Sapporo, 062–8517, Japan
1(Received February 29, 2020—Accepted April 17, 2020—Published online June 3, 2020)

Ultra-small microorganisms are ubiquitous in Earth’s environments. Ultramicrobacteria, which are defined as having acell volume of <0.1 μm3, are often numerically dominant in aqueous environments. Cultivated representatives among thesebacteria, such as members of the marine SAR11 clade (e.g., “Candidatus Pelagibacter ubique”) and freshwater
Actinobacteria and Betaproteobacteria, possess highly streamlined, small genomes and unique ecophysiological traits.
Many ultramicrobacteria may pass through a 0.2-μm-pore-sized filter, which is commonly used for filter sterilization invarious fields and processes. Cultivation efforts focusing on filterable small microorganisms revealed that filtered fractions
contained not only ultramicrocells (i.e., miniaturized cells because of external factors) and ultramicrobacteria, but also
slender filamentous bacteria sometimes with pleomorphic cells, including a special reference to members of Oligoflexia, theeighth class of the phylum Proteobacteria. Furthermore, the advent of culture-independent “omics” approaches to filterable
microorganisms yielded the existence of candidate phyla radiation (CPR) bacteria (also referred to as “Ca. Patescibacteria”)
and ultra-small members of DPANN (an acronym of the names of the first phyla included in this superphyla) archaea.
Notably, certain groups in CPR and DPANN are predicted to have minimal or few biosynthetic capacities, as reflected bytheir extremely small genome sizes, or possess no known function. Therefore, filtered fractions contain a greater variety andcomplexity of microorganisms than previously expected. This review summarizes the broad diversity of overlooked
filterable agents remaining in “sterile” (<0.2-μm filtered) environmental samples.
Key words: filterable microorganisms, ultramicrocells, ultramicrobacteria, candidate phyla radiation, minimal cell

How small may actual organisms be? This question has
long fascinated scientists in various fields. Prokaryotic
microorganisms (Archaea and Bacteria) constitute thesmallest life forms. Bacterial cells range in volume fromultramicrobacteria (UMB; <0.1 μm3; Duda et al., 2012) tothe typical bacterium Escherichia coli (1.6 μm3; Moore,1999) and the giant bacterium Epulopiscium fishelsoni(3.0×106 μm3; Schulz and Jørgensen, 2001; note that thecells of Thiomargarita namibiensis are larger [2.2×108 μm3],
but are occupied by a liquid vacuole, that is, they do nothave large cytoplasmic bodies; Schulz et al., 1999). Thus,
bacteria exhibit cell-size plasticity by varying cell volume
by more than seven orders of magnitude in different species.
UMB may pass through membrane filters down to 0.2-μmpore-size, which is commonly used for filter sterilization in
research laboratories as well as in medical, food, and indus‐
trial processes (Levy and Jornitz, 2006). In fact, efforts toculture microorganisms remaining in the 0.2-μm filtrate(hereafter called filterable microorganisms) of environmen‐
tal samples have yielded diverse UMB members. The sev‐
eral isolates were affiliated with unique lineages, such as* Corresponding author. E-mail: nakai-ryosuke@aist.go.jp;
Tel: +81–11–857–8408; Fax: +81–11–857–8980.
† Present address: Microbial Ecology and Technology ResearchGroup, Bioproduction Research Institute, National Institute ofAdvanced Industrial Science and Technology (AIST), 2–17–2–1,
Tsukisamu-Higashi, Sapporo, 062–8517, Japan.
Citation: Nakai, R. (2020) Size Matters: Ultra-small and Filterable
Microorganisms in the Environment. Microbes Environ 35: ME20025.
https://doi.org/10.1264/jsme2.ME20025

cosmopolitan
freshwater
Actinobacteria
andBetaproteobacteria (Hahn, 2003; Hahn et al., 2003) as wellas the candidate phylum termite group 1 (TG1) described as
Elusimicrobia (Geissinger et al., 2009). The existence of
UMB has expanded our knowledge of microbial life at thelower size limit.
In the last five years, filterable microorganisms have been
attracting increasing interest with the discovery of otherultra-small members: the candidate phyla radiation (CPR)
bacteria, also referred to as “Candidatus Patescibacteria”(hereafter described as CPR/Patescibacteria; Rinke et al.,2013; Brown et al., 2015), and some members of DPANN(an acronym of the names of the first phyla included in thissuperphyla, “Ca. Diapherotrites”, “Ca. Parvarchaeota”, “Ca.
Aenigmarchaeota”, Nanoarchaeota, and “Ca. Nanohalorch‐aeota”; Rinke et al., 2013; Dombrowski et al., 2019). Sev‐
eral CPR members have an extremely small cell volume(approximately 0.01 μm3) that was unveiled by cryotransmission electron microscopy imaging (Luef et al.,2015). Moreover, the emergence of these ultra-small prokar‐
yotes has re-opened debate on the tree of life (Hug et al.,2016; Parks et al., 2018; Zhu et al., 2019). These members
are ubiquitous in the environment and recent studies haveprovided insights into their contribution to the material
cycle (e.g., carbon and nitrogen cycles; Danczak et al.,2017; Lannes et al., 2019). This review focuses on the phy‐logenetic diversity and complexity of filterable microorgan‐
isms in natural systems, with specific references to UMB
and pleomorphic bacteria. Other reviews presented aspects
of ultra-small microorganisms including CPR/Patescibacte‐
ria and DPANN members (e.g., terminology, biogeography,
Article ME20025

33

Nakaigenomic diversity, and metabolic variety; Duda et al., 2012;
Castelle et al., 2018; Ghuneim et al., 2018; Dombrowski etal., 2019). In this review, archaea with a cell volume of <0.1
μm3 are specifically referred to as ultramicroarchaea (UMA)
to distinguish them from UMB.
Filterable microorganisms
To date, many studies have reported the presence of filter‐
able microorganisms in various environments (mainly aque‐ous environments) including seawater (Haller et al., 2000;
Elsaied et al., 2001; Lannes et al., 2019; Obayashi and
Suzuki, 2019), lake water (Hahn, 2003; Hahn et al., 2003;
Watanabe et al., 2009; Fedotova et al., 2012; Maejima et al.,2018; Vigneron et al., 2019), terrestrial aquifers (Miyoshi etal., 2005; Luef et al., 2015), glacier ice and the ice cover oflakes (Miteva and Brenchley, 2005; Kuhn et al., 2014),
deep-sea hydrothermal fluids (Naganuma et al., 2007; Nakai
et al., 2011), and soil and sand (Nakai et al., 2013). How‐ever, the use of membrane filters with a small pore size
(approximately 0.2 μm) was traditionally recommended forthe retention of bacteria in the field of marine microbial
ecology in the 1960s (e.g., Anderson and Heffernan, 1965)
and is still widely practiced today in various fields. The
existence of very small microorganisms has been well rec‐ognized since the 1980s. The term “ultramicrobacteria” wasfirst used by Torrella and Morita (1981) to describe verysmall coccoid cell forms of <0.3 μm in diameter from sea‐water. MacDonell and Hood (1982) subsequently isolated
and characterized viable filterable microorganisms poten‐
tially belonging to the genera Vibrio, Aeromonas,
Pseudomonas, and Alcaligenes from estuarine waters. They
concluded that these filterable microorganisms represented astate of dormancy for adaptation to low nutrient conditions
and were not completely novel bacteria. Other studies also
reported that external factors reduced cell sizes, such as
Staphylococcus aureus and Pseudomonas syringae (~50%
reduction in size as described in Table 1; Watson et al.,
1998; Monier and Lindow, 2003). Therefore, the cells of
miniaturized microorganisms need to be distinguished fromtrue UMB and are described in this review as “ultramicro‐
cells”, which has the synonyms dwarf cells and midget cells,
according to Duda et al. (2012). Schut et al. (1997) andDuda et al. (2012) subsequently defined a cell volume index
of <0.1 μm3 as being characteristic of true UMB.
Based on previous studies, filterable microorganisms
have been classified into five groups (Fig. 1): (I) ultramicro‐
cells that are miniaturized microorganisms because of exter‐
nal factors (e.g., environmental stress) as described above;(II) obligate UMB that maintain small cell volumes(<0.1 μm3) regardless of their growth conditions; (III) facul‐
tative UMB that contain a small proportion of larger cellswith a cell volume >0.1 μm3 (note that the definitions of theterms “obligate” and “facultative” UMB follow those of
Duda et al. [2012]); (IV) slender filamentous bacteria; and(V) ultra-small members among CPR/Patescibacteria bacte‐
ria and DPANN archaea. In contrast to UMB strains, the cell
shapes and morphological characteristics of members ingroup V are largely unknown under different environmental
or culture conditions because all of the members of CPR
34

and DPANN are uncultivated, with a few exceptions ofmembers belonging to the phyla “Ca. Saccharibacteria”(former TM7) and Nanoarchaeota (e.g., Huber et al., 2002;
He et al., 2015). Incidentally, the groups presented in thisreview do not include filterable cell-wall-less mycoplasmas
as well as “nanobacteria” or “nannobacteria” as microfos‐sils, which are often referred to in geological literature(Folk, 1999), or as calcium carbonate nanoparticles in thehuman body, as reported in medical literature (Martel andYoung, 2008). Representative cases of groups II to V are
described below and Table 1 shows a summarized list.
Obligate UMB
Obligate UMB are often reported from aqueous environ‐ments. One of the most prominent representatives is“Candidatus Pelagibacter ubique” HTCC1062, which is a
SAR11 clade bacterium that is ubiquitous in marine envi‐
ronments. Previous studies found that SAR11 members con‐sistently dominated ribosomal RNA gene clone libraries
derived from seawater DNA and estimated their global pop‐
ulation size as 2.4×1028 cells—approximately 25% of all
prokaryotic cells—in oceans (Giovannoni et al., 1990;
Morris et al., 2002). Despite their ubiquitous and abundantpresence, it was not possible to isolate them. However, thefirst cultivated strain HTCC1062 was established in 2002
using a high-throughput dilution-to-extinction culturing(HTC) technique (Rappé et al., 2002). This HTC techniqueinvolves cultivation with serial dilutions of natural seawater
samples into very low nutrient media (Connon and
Giovannoni, 2002). The cell volume (approximately
0.01 μm3) of “Ca. P. ubique” was reported as one of thesmallest free-living cells known. Subsequent studies charac‐terized the SAR11 clade with the small, streamlined
genomes (<1.5 Mbp) described below, an unusual mode ofglycine auxotrophy, a light-dependent proton pump known
as proteorhodopsin, and the ability to utilize various onecarbon compounds (reviewed in Tripp, 2013; Giovannoni,2017). The SAR11 clade is highly divergent with multiple
ecotypes and has freshwater members known as LD12 clas‐sified in SAR11 subclade IIIb (Grote et al., 2012). An LD12
cultivated representative, “Ca. Fonsibacter ubiquis” strain
LSUCC0530, was subsequently established (Henson et al.,2018), and its genomic characteristics promoted the hypoth‐esis that gene losses for osmolyte uptake were related to theevolutionary transition, or metabolic tuning, of freshwater
SAR11 (LD12) from a salt to freshwater habitat.
Another marine ultramicrobacterium, Sphingopyxis
alaskensis (formerly known as Sphingomonas alaskensis)
RB2256 was intensively investigated before the study of the
SAR11 clade (e.g., Eguchi et al., 1996; Schut et al., 1997).
This strain was also characterized as an obligate UMB(Duda et al., 2012). When the cultivation of this strain tran‐
sitioned from low-carbon to highly-enriched media, the cellvolume of S. alaskensis remained at <0.1 μm3 in mostmedia; however, larger elongated cells, not UMB cells, wereobserved in trypticase soy agar medium (Vancanneyt et al.,2001). Furthermore, this strain possesses a larger genome of
3.3 Mb (DDBJ/ENA/GenBank accession no. CP000356)
than other UMB (Table 1).

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Diversity of Filterable Microorganisms
Table 1.

An overview of ultra-small and filterable microorganisms in the environment

Phylum (and classfor Proteobacteria)

Isolation source

Cell shape

Cell size (length×width Genome
and/or volume)
size (Mbp)

Physiological and ecologicaltrait(s) or its potential

Reference

Staphylococcus aureus 8325-4

Firmicutes

derivative of S.
aureus NCTC8325(patient’s strain)

coccicell size reduction
from 0.69±0.08
to 0.41±0.08 μm

n.d.

host cell invasion, starvationassociated cell size reduction

Watson et al. (1998)

Pseudomonas syringae pv. syringae
B728aProteobacteria(γ-proteobacteria)

snap bean leaflet

rods

cell length reduction
from ~2.5 to ~1.2 μm

6.09

host cell invasion, leaf
environment-induced cell size
reduction

Monier and Lindow (2003);
Feil et al. (2005)

Taxa
Ultramicrocells

Obligate ultramicrobacteria and related candidates“Candidatus Pelagibacter ubique”
HTCC1062

Proteobacteria(α-proteobacteria)

coastal sea

curved rods

0.01 μm3

1.31“Candidatus Fonsibacter ubiquis”
LSUCC0530

Proteobacteria(α-proteobacteria)

coastal lagoon

curved rods

1.0×0.1 μm

1.16

Sphingopyxis alaskensis RB2256

Proteobacteria(α-proteobacteria)

fjord estuary

short rods

0.05–0.09 μm3

3.35

Aurantimicrobium minutum KNCT

Actinobacteria

freshwater rivercurved rods

1.62

Rhodoluna lacicola MWH-Ta8T

Actinobacteria

freshwater lake

curved rods

0.7–0.8×0.3 μm;
0.04–0.05 μm3
0.85×0.30 μm;
0.053 μm3

Rhodoluna limnophila 27D-LEPIT

Actinobacteria

freshwater pond

short rods

0.49×0.28 μm

1.40

glycine auxotrophy, rhodopsinbased photometabolism,
utilization of one-carbon
compounds
glycine auxotrophy, rhodopsinbased photometabolism,
tetrahydrafolate metabolism**
utilization of various aminoacids, resistance to heat shock,
H2O2, and ethanol
rhodopsin-based
photometabolism**rhodopsin-based
photometabolism
nitrate uptake and nitrite
excretion system**Actinobacteria

freshwater lake

curved rods

0.041 μm3

1.35

catalase-dependent growth

Actinobacteria

freshwater lake

curved rods

0.061 μm3

1.46

catalase-dependent growth

Kim et al. (2019)

utilization of low-molecularweight substrates
utilization of sugars and sugar
polymers, strict fermentative
metabolism, oxygen tolerance

Hahn et al. (2012);
Meincke et al. (2012)

1.43

Rappé et al. (2002); Tripp(2013); Giovannoni (2017)
Henson et al. (2018)
Eguchi et al. (1996);
Schut et al. (1997)
Nakai et al. (2015, 2016b)
Hahn et al. (2014);
Keffer et al. (2015)
Pitt et al. (2019)“Candidatus Planktophila rubra”
IMCC25003“Candidatus Planktophila aquatilis”
IMCC26103
Polynucleobacter necessarius subsp.
asymbioticus QLW-P1DMWA-1T

Proteobacteria(β-proteobacteria)

freshwater pond

straight rods

0.7–1.2×0.4–0.5 μm

2.16

Opitutus sp. VeCb1

Verrucomicrobia

rice paddy soil

ellipsoids

0.49×0.33 μm;
0.030 μm3n.d.

Endomicrobium proavitum Rsa215

Elusimicrobia

gut homogenate of
Reticulitermes
santonensis

0.3–0.5 μm (for cocci);
0.5–3.5×0.15–0.30 μm 1.59
(for rods)

nitrogen fixation

Zheng and Brune (2015);
Zheng et al. (2016)

Chryseobacterium solincola NF4Bacteroidetes

lake sedimentcocci, rods
showing budding
cell division
cocci, rods
showing budding
cell division orcell septation

0.004–0.04 μm3 (forcocci); 0.1–0.3 μm3(for rods)~1.7

ectoparasite of Bacillus subtilis

Suzina et al. (2011);
Duda et al. (2012)

Proteobacteria(β-proteobacteria)

freshwater

0.12 μm3 (smallest
width=0.2 μm)

n.d.

n.d.

Wang et al. (2007, 2008)

Oligoflexus tunisiensis Shr3T

Proteobacteria(Oligoflexia)*

desert sandvarious lengths×0.4–
0.8 μm (for filaments)

7.57

multidrug resistance, incomplete Nakai et al. (2014, 2016a)
denitrification**

Silvanigrella aquatica MWH-NonnenW8redTProteobacteria(Oligoflexia)*

freshwater lake

3.6×0.6 μm (for rods)

3.51

antimicrobial peptides, plasmidencoded type IV secretion
Hahn et al. (2017)
systems**various lengths

3.94

utilization of limited substrates

Pitt et al. (2020)

various lengths

3.39

violacein-like production

Pitt et al. (2020)

cocci or ovalshaped

0.009±0.002 μm3

0.69–1.05

potential interaction with otherbacterial cells via pili-likestructures

Luef et al. (2015)

straight rods

1.6–1.9×0.5–0.6 μm

n.d.

endoplasmic symbiont of theciliate P. bursaria

Gong et al. (2014)

Facultative ultramicrobacteria

Slender filamentous bacteria
Hylemonella gracilis CB

Silvanigrella paludirubra SP-Ram-0.45- Proteobacteria
freshwater pond
(Oligoflexia)*
NSY-1T
Proteobacteria
Tfreshwater creek
Fluviispira multicolorata 33A1-SZDP (Oligoflexia)*
CPR/Patescibacteria bacteria
candidate division WWE3,“Candidatus
WWE3-OP11-OD1 bacteria
Microgenomates” (OP11), deep aquifer“Candidatus
Parcubacteria” (OD1)ciliated protist“Candidatus“Candidatus Sonnebornia yantaiensis” Parcubacteria” (OD1)
Paramecium
bursaria

spirals
pleomorphic (rods,
filaments, spirals,
and spherical [orcurled] cells)
pleomorphic (rods,
filaments, andspirals)
pleomorphic (rodsand filaments)
pleomorphic (rodsand filaments)

Kim et al. (2019)

Janssen et al. (1997);
Chin et al. (2001)“Candidatus
Saccharibacteria” (TM7)human oral cavity

cocci

0.2–0.3 μm

0.71ectosymbiont of Actinomycesodontolyticus

He et al. (2015)

Nanoarchaeum equitans

Nanoarchaeota

submarine hot ventcocci

0.4 μm~0.5

Huber et al. (2002)“Candidatus Nanopusillus acidilobi”

Nanoarchaeota

hot spring

cocci

0.1–0.3 μm

0.61“Candidatus Nanoclepta minutus”
Ncl-1

Nanoarchaeota

hot spring

flagellated cocci~0.2 μm

0.58

hypersaline lake

cocci-like

0.6 μm1.23

possible free-living lifestyle

Narasingarao et al. (2012)“Candidatus Nanosalinarum” sp.
J07AB56“Candidatus
Nanohaloarchaeota”“Candidatus
Nanohaloarchaeota”

ectosymbiont of Ignicoccus
hospitalis
ectosymbiont of Acidilobus
species
ectosymbiont of Zestosphaera
tikiterensis

hypersaline lake

cocci-like

0.6 μm1.22

possible free-living lifestyle

Narasingarao et al. (2012)

ARMAN-2, -4, and -5“Candidatus
Micrarchaeota”

acid mine drainage

cocci~0.5 μm~1.0“Candidatus Mancarchaeum
acidiphilum” Mia14“Candidatus
Micrarchaeota”

acid mine drainage

n.d.

n.d.

0.95

TM7x bacterium
DPANN archaea“Candidatus Nanosalina” sp. J07AB43

potential interaction with
Thermoplasmatales cells via
pili-like structuresectoparasite of Cuniculiplasma
divulgatum

Wurch et al. (2016)
John et al. (2019)

Baker et al. (2010)
Golyshina et al. (2017)

n.d.: no data.
* The proteobacterial class Oligoflexia is classified in the candidate phylum “Bdellovibrionota” in the Genome Taxonomy Database (GTDB).
** Putative physiological traits are inferred from their genomic and plasmid annotation.

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Article ME20025

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NakaiFig. 1. Diagram showing filterable microorganisms in the environment. (I) ultramicrocells; (II) obligate ultramicrobacteria; (III) facultative
ultramicrobacteria; (IV) slender filamentous bacteria; (V) ultra-small members of CPR bacteria (also referred to as “Candidatus Patescibacteria”)
and DPANN archaea indicated by the arrow in this Figure. See details in the text. This figure was created with BioRender (https://biorender.com/).

Other prominent representatives of obligate UMB are
freshwater actinobacterial strains. Typically, actinobacteria
are among the numerically dominant groups in freshwaterand their cells are found in smaller size fractions (Glöckner
et al., 2000; Sekar et al., 2003). Hahn et al. (2003) first iso‐lated nine filterable UMB of the class Actinobacteria from
freshwater habitats and newly described a novel phyloge‐
netic cluster (Luna cluster). This isolation was achieved by
the “filtration-acclimatization” method of filter separation
combined with an acclimatization procedure, which is a
stepwise transition from low substrate conditions to artifi‐
cial culture conditions. The important features of Luna clus‐
ter strains are their wide distribution in freshwater systems(Hahn and Pöckl, 2005) and their small cell sizes are stable
and maintained in nutrient-rich media (Hahn et al., 2003).
Our group also isolated an ultamicrosize actinobacterium
related to Luna strains from river water in Japan and named
it Aurantimicrobium minutum KNCT (Fig. 2; Nakai et al.,2015). This strain showed high 16S rRNA gene sequencesimilarity (>99%) to strains isolated from freshwater sys‐
tems in other places in Japan as well as in Austria, Australia,
China, Nicaragua, and Uganda (accession nos. AB278121,
AB599783, AJ507461, AJ507467, AJ565412, AJ565413,
and AJ630367), suggesting its cosmopolitan distribution in
freshwater.
36

Fig. 2. Scanning electron micrograph of c-shaped cells of
Aurantimicrobium minutum KNCT. Cells were cultured in organic
NSY (nutrient broth, soytone, and yeast extract; Hahn et al., 2004)
medium for two weeks. Scale bar: 200 nm. This micrograph is an
unpublished figure from the author; other micrographs of this species
are shown in Nakai et al. (2013, 2015).

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Diversity of Filterable Microorganisms

The other freshwater bacterium belonging to the Lunacluster, Rhodoluna lacicola MWH-Ta8T, was also described
as an obligate UMB (Hahn et al., 2014); an additional three
Rhodoluna strains smaller than R. lacicola were subse‐
quently reported (Pitt et al., 2019). From an ecophysiological point of view, the genomes of freshwater
actinobacteria
possess
rhodopsin
photosystems(Neuenschwander et al., 2018), while R. lacicola has an
unconventional proton-pumping rhodopsin that requires
external supplementation with the cofactor retinal (Keffer etal., 2015). The underlying cause is considered to be an
inability to biosynthesize the cofactor (Neuenschwander etal., 2018), suggesting that R. lacicola obtains retinal fromthe surrounding environment. One potential source in fresh‐water appears to be retinoids produced and released by cya‐nobacteria (Ruch et al., 2005; Wu et al., 2013).
Freshwater actinobacteria, including UMB strains, werepreviously shown to be phylogenetically diverse and subse‐
quent studies yielded nine lineages (acI, acTH1, acSTL,
Luna1, acIII, Luna3, acTH2, acIV, and acV; Newton et al.,2011). Among these lineages, acI containing multiple tribes
is considered to be the most successful and ubiquitous groupin the environment (Zwart et al., 2002; Warnecke et al.,
2004; Kang et al., 2017), although pure cultures had notbeen established despite various cultivation trials. However,Kim et al. (2019) recently reported the first two pure acI
cultures with very small sizes (volume, 0.04–0.06 μm3;
Table 1), which are assumed to be obligate UMB. A key
factor for their growth was the supplementation of a“helper” catalase, an enzyme that degrades hydrogen perox‐ide (H2O2), to the culture medium. Previous studies showedthat H2O2 generated in medium affected the culture effi‐
ciency of microorganisms sensitive to oxidative stress(Kawasaki and Kamagata, 2017) and that the growth of the
cyanobacterium Prochlorococcus was promoted by the pres‐ence of H2O2-scavenging microbes (Morris et al., 2011).
These findings demonstrated that a catalase-supplemented
cultivation strategy may facilitate the successful isolation ofpreviously uncultured freshwater UMB.
Freshwater habitats also harbor another obligate UMB
belonging to the genus Polynucleobacter in the class
Betaproteobacteria. Similar to some actinobacteria descri‐
bed earlier, UMB members of this genus also showed a cos‐
mopolitan distribution in freshwater systems (Hahn, 2003).
The relative abundance of the subspecies named PnecC was
high, ranging between <1% and 67% (average 14.5%) of
total bacterial numbers, in more than 130 lakes studied inCentral Europe, as assessed by fluorescent in situ hybridiza‐tion (Jezberová et al., 2010). Culture experiments andgenomic characterization suggested that PnecC bacteria innature can utilize low-molecular-weight products derived
from photooxidation and/or the direct enzymatic cleavage ofhigh-molecular-weight substrates, such as humic substances(Watanabe et al., 2009; Hahn et al., 2012). Certain PnecC
strains sharing ≥99% similarity in 16S rRNA gene sequen‐ces differed in their ecophysiological and genomic features(e.g., the presence/absence of iron transporter genes), sug‐gesting cryptic diversity among the abundant lineage notcovered by 16S rRNA gene-based typing (Hahn et al.,2016).

The obligate UMB inhabiting sea and freshwaters descri‐
bed above were characterized by minute cell sizes, but also
small genome sizes (<2 Mbp) with a low genomic guaninecytosine (GC) content: this genome “streamlining” is con‐sidered to reflect an adaptation to nutrient-limited conditions(e.g., SAR11 members; 1.16–1.46 Mb; Giovannoni et al.,2005; Grote et al., 2012; Henson et al., 2018) (Table 1).
This phenomenon of a reduced genome size with gene loss
also indicates metabolic dependencies on co-existing micro‐organisms in nature, as described by the “Black Queen
Hypothesis” (Morris et al., 2012). As another example, thereconstructed genomes of ultra-small and uncultivatedmarine actinobacteria (“Candidatus Actinomarinidae”) werevery small (<1 Mb) and had a very low GC content of
33% (Ghai et al., 2013). In addition, known obligate UMB
of different lineages, such as “Ca. P. ubique”(Alphaproteobacteria),
Polynucleobacterstrains(Betaproteobacteria), and A. minutum and R. lacicola(Actinobacteria), showed similar “c-shaped” (curved-rod)
cells (Table 1; A. minutum for Fig. 2; Hahn, 2003). This
unique shape may be advantageous for the efficient acquisi‐tion of substances because of their increased surface-tovolume ratio of cells or grazing resistance against
bacteriovorus protists for planktonic life in waters.
In contrast to aquatic environments, limited information
is currently available on UMB, including the obligate type,from soil habitats. Janssen et al. (1997) previously reported
anaerobic obligate UMB with very small ellipsoid to nearly
spherical shapes (e.g., Opitutus sp. VeCb1 with a cell vol‐ume of 0.030 μm3) belonging to the Verrucomicrobiales lin‐eage from rice paddy soil using dilution culture techniques.
Nakai et al. (2013) isolated and cultivated filterable strainsfrom soil and sand suspensions; however, obligate UMB
were not found among these strains. High-throughput
sequencing of the 16S rRNA gene revealed that the smaller
size fractions in soils were more likely to harbor rare or
poorly characterized bacterial and archaeal taxa, such as
Acidobacteria,
Gemmatimonadetes,
Elusimicrobia,
Verrucomicrobia, and Crenarchaeota (Portillo et al., 2013).
However, further studies are needed to clarify whether themembers detected in the small fractions contain UMB.
Facultative UMB
Facultative UMB that contain a small proportion of larger
cells with a cell volume >0.1 μm3 have not yet been charac‐terized in detail (Table 1) because morphological changes
throughout the growth cycle have only been examined in alimited number of UMB. Endomicrobium proavitum Rsa215(now deposited as DSM29378T=JCM32103T) belonging to
the phylum Elusimicrobia appears to be a well-studied
example of facultative UMB. The phylum Elusimicrobia(former termite group 1 candidate phylum) was initiallyestablished with the cultivated ultramicrobacterium of
Elusimicrobium minutum strain Pei191T from the 0.2 μmfiltered filtrate—originally prepared as a growth promoting
supplement for gut bacteria—of the gut homogenates of ascarab beetle larva (Geissinger et al., 2009; Herlemann etal., 2009). E. proavitum Rsa215 was isolated from the fil‐trate of the gut homogenate and was identified as a free-

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Nakailiving bacterium of a novel class-level lineage in
Elusimicrobia (Zheng et al., 2016). E. proavitum has an
unusual cell cycle that involves different cell forms, i.e.,
cocci, rods, and budding-like cells, during the cell cycle.
Under laboratory cultivation conditions, before growth com‐mences, the cell population is comprised of a large popula‐tion of UMB coccoid cells with a few rod-shaped cells(~3.5 μm in length); small cocci are formed from a bud-likeswelling at one pole of the rod-shaped cells during growth.
Although its morphological variation in the host gut cur‐rently remains unclear, cell characteristics as observed in thelaboratory result in the classification of facultative UMB.
Another important trait for E. proavitum is the ability to fix
nitrogen gas with a group IV nitrogenase, which was con‐sidered to harbor functions other than nitrogen fixation (DosSantos et al., 2012).
Slender filamentous bacteria
In addition to ultramicrocells and UMB, slender filamen‐
tous bacteria have frequently been found in 0.2 μm-filteredfractions of environmental samples. Slender spirillumshaped Hylemonella gracilis was isolated from filtrates offreshwater samples (e.g., Hahn et al., 2004; Nakai et al.,2013) and passes through membrane filters with small poresizes of not only 0.22–0.45 μm, but also 0.1 μm (Wang etal., 2007). The smallest widths of H. gracilis cells areapproximately 0.2 μm and close to filter pore sizes, which
may allow its slender cells to “squeeze” through these pores.
Regarding the quality control and assessment of filter sterili‐
zation, Wang et al. (2008) proposed that filterable slenderbacteria, such as H. gracilis with small cell widths, may be
used for the microbiological validation of membrane filters
instead of Brevundimonas diminuta, which is the current
standard strain tested.
During a screening of UMB, our group isolated a slenderfilamentous bacterium from the filtrate of a suspension ofdesert sands collected in Tunisia, and described Oligoflexus
tunisiensis Shr3T, which represents the eighth novel classnamed Oligoflexia within the phylum Proteobacteria (Nakai
et al., 2014; 2016a). The cell shape of this species is mainly
slender, filamentous, and of variable lengths, but shows apleomorphism with other shapes, such as a spiral, spherical(or curled), or curved rod morphology (Fig. 3; Nakai andNaganuma, 2015). This polymorphic flexibility of cells withsmall widths down to 0.4 μm appears to be related to theirability to pass through membrane filters; however, it has not
yet been clarified whether each morphological shape isassociated with a resting state or other states. Regarding fil‐amentous formation, this shape may be related to resistanceto protozoan grazing, as reported in previous studies (e.g.,
Jürgens et al., 1999; Suzuki et al., 2017a). The environmen‐
tal sequences closely related (>97%) to the 16S rRNA genesequence of O. tunisiensis were recovered from paddy soil,
cyanobacterial bloom in lake water, bioreactors, and humanskin using culture-independent approaches; however, theirdetection frequency was low, with at most ~0.6% (Nakai
and Naganuma, 2015). Thus, O. tunisiensis and its relatives
appear to be rare species, and their ecological roles are cur‐rently unclear; one possible role for O. tunisiensis may be
38

Fig. 3. Micrograph of pleomorphic cells of Oligoflexus tunisiensis
Shr3T. Cells were cultured in R2A medium for more than two weeks.
This micrograph is slightly modified from the figure originallypublished in Nakai and Naganuma (2015). Scale bar: 10 μm.

incomplete denitrification to nitrous oxide, as inferred fromits genome sequence (Nakai et al., 2016a).
Despite the potential rarity of its occurrence, the size fil‐tration method led to the isolation of an additional slenderfilamentous strain, Silvanigrella aquatica MWH-NonnenW8redT, with a pleomorphic morphology in the class (Hahn
et al., 2017). Hahn et al. (2017) reclassified the order
Bdellovibrionales, including Bdellovibrio spp. known as
small “bacteria-eating” bacteria (reviewed in Sockett, 2009),
from the class Deltaproteobacteria to the class Oligoflexia
based on in-depth phylogenetic analyses. Incidentally, 0.45μm filtrates of environmental samples are frequently used
for the enrichment culture of Bdellovibrio predatory bacte‐ria. In the Genome Taxonomy Database (GTDB) based on
genome phylogeny (https://gtdb.ecogenomic.org/; Parks etal., 2018), the class Oligoflexia belongs to the candidate
phylum “Bdellovibrionota”, named after the genus
Bdellovibrio, and not the phylum Proteobacteria; its taxo‐
nomic assignment will be discussed in future studies.
Oligoflexia very recently gained two more species,
Fluviispira multicolorata 33A1-SZDPT and Silvanigrella
paludirubra SP-Ram-0.45-NSY-1T, from freshwater habitats(Pitt et al., 2020). Silvanigrella spp. are phylogeneticallyclosely aligned with “Candidatus Spirobacillus cienkow‐skii” (Pitt et al., 2020), which is an uncultured pathogen ofwater fleas (Daphnia spp.) described morphologicallyalmost 130 years ago (Metchnikoff, 1889). Since
Silvanigrella spp. are isolated from the filtrates of micropore
filtration, size fractionation may be an effective method for
isolating the uncultivated pathogen as well as additionallyoverlooked agents in Oligoflexia. A detailed comparison
within members of this class will also be important for pur‐suing the evolutionary acquisition and divergence of preda‐
tory and pathogenic behaviors.
Diverse ultra-small members and their potentials
Metagenomic investigations on microbial communities
have generated genomes for an astounding diversity of bac‐

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teria and archaea; CPR/Patescibacteria inhabiting ground‐water has attracted increasing attention in recent years.
Traditionally, certain types of groundwater bacteria were
known to pass through a micropore filter (e.g., Shirey andBissonnette, 1991). Additionally, Miyoshi et al. (2005) phy‐logenetically characterized filterable microorganisms cap‐
tured by 0.1-μm-pore-sized filters from deep aquifers of the
Tono uranium mine, Japan and then discovered candidate
divisions OD1 and OP11 (now recognized as candidate
phyla “Ca. Parcubacteria” and “Ca. Microgenomates”,
respectively) enriched by approximately 44% in 16S rRNA
gene clones from the filtered fraction. The specific occur‐
rence of “Ca. Parcubacteria” (OD1) in the 0.2-μm filtrate
was also detected in deep-sea hydrothermal fluid(Naganuma et al., 2007). It was previously unclear whether
members of these candidate divisions were UMB. In subse‐
quent studies using cryo-imaging, ultra-small cells (approxi‐
mately 0.009±0.002 μm3) were reported in the filtrate of anaquifer water near Colorado, USA, which were enrichedwith the candidate divisions WWE3, OD1, and OP11, allrecently belonging to CPR/Patescibacteria (Luef et al.,2015).
Metagenomics was then used to reconstruct the genomesof filterable members in the aquifer system, representing>35 candidate phyla named CPR (Brown et al., 2015). Thishighly diversified group of uncultivated bacteria may subdi‐
vide the domain Bacteria (Hug et al., 2016); however, this
scenario remains controversial (e.g., Parks et al., 2018; Zhu
et al., 2019). Importantly, measurements of replication rates(Brown et al., 2016; Suzuki et al., 2017b) and cryotransmission electron microscopy images showing a divid‐
ing cell (Luef et al., 2015) indicated that the extremely
small cells of CPR/Patescibacteria are metabolically active
and not simply ultramicrocells during starvation. Moreover,
CPR/Patescibacteria genomes have been recovered fromother environments, such as highly alkaline groundwater(Suzuki et al., 2017b; Sato et al., 2019), lakes (Vigneron etal., 2019), soil (Starr et al., 2018), and marine sediment(Orsi et al., 2018) as well as the human microbiome (He etal., 2015) and dolphin mouse (Dudek et al., 2017), suggest‐
ing a wide distribution across environments. Besides
describing ultra-small life forms with high phylogenetic
novelty, genomic analyses of CPR/Patescibacteria members
have provided information on their small genomes, fermen‐
tative metabolism, and other unusual features (e.g., selfsplicing introns varying in length and proteins encodedwithin their 16S rRNA genes; Brown et al., 2015; Castelle
et al., 2018). Divergent 16S rRNA gene sequences prevent
many specific phyla (e.g., ~50% of “Ca. Microgenomates”[OP11] and 60% of candidate division WWE3) from being
detected by typical PCR surveys with the universal bacterial
primer set 515F and 806R (Brown et al., 2016). The small
genome sizes observed (often <1 Mb) appear to be a reflec‐tion of a symbiotic lifestyle and/or high in situ selection
pressure in a stable environment, rather than the genome
streamlining of free-living obligate UMB, as described ear‐lier, assuming streamlining characteristics (e.g., highly con‐served core genomes with few pseudogenes; Giovannoni etal., 2014). Although the CPR/Patescibacteria genomes stud‐
ied to date possess incomplete biosynthetic pathways fortheir cellular building blocks (e.g., nucleotides and fatty
acids; Castelle et al., 2018), the possibility of their ability tode novo synthesize them by unknown pathways cannot be
ruled out. Furthermore, their host-associated distribution
was reported: “Candidatus Sonnebornia yantaiensis” of“Ca. Parcubacteria” (OD1) as an endoplasmic symbiont of
the protist (Gong et al., 2014) and TM7x bacterium of “Ca.
Saccharibacteria” (TM7) attached to Actinomycesodontolyticus (He et al., 2015), as shown in Table 1.
The features of small cell sizes and small genomes
observed in CPR/Patescibacteria are shared by some mem‐bers of the DPANN archaea, particularly Nanoarchaeota(Huber et al., 2002), “Ca. Nanohalorchaeota” (Narasingarao
et al., 2012), and so-called ARMAN (archaeal RichmondMine acidophilic nano-organisms; Baker et al., 2010).
DPANN including these UMA has been expanded by theaddition of novel phylum-level groups, and, at the time ofwriting, encompasses at least ten different lineages(reviewed in Dombrowski et al., 2019). In several cases,
except for the members of “Ca. Nanohalorchaeota”, as with
CPR/Patescibacteria, DPANN-affiliated UMA showed an
ectosymbiotic localization: Nanoarchaeum equitans
attached to Ignicoccus hospitalis (Huber et al., 2002), “Ca.
Nanopusillus acidilobi” and its host Acidilobus species(Wurch et al., 2016), and “Ca. Mancarchaeum acidiphilum”
Mia14 (ARMAN-2-related organism) and its hostCuniculiplasma divulgatum (Golyshina et al., 2017) (otherdata in Table 1). Additionally, DPANN organisms lack theability to biosynthesize their building blocks (Castelle et al.,2018). Although it is still unclear whether these symbiotic
or parasitic lifestyles represent a way of life for the CPR/
Patescibacteria and DPANN groups, the cases describedabove indicate that several members of these groups appear
to be important in organism-organism interactions.
The characterization of ultra-small life forms may provide
a new perspective for minimal cells and synthetic cells. In
the field of synthetic biology, the top-down approach has
been employed to reduce and simplify the genomes of
microbial cells by genetic engineering, and then to identify
essential genes for living systems; the bottom-up approach,which is the opposite of the top-down approach, has beenused to examine what is sufficient for living systems byassembling non-living components, such as nucleic acids,
proteins, and lipids (e.g., Matsuura et al., 2011; Xu et al.,2016). In this context, DeWall and Cheng (2011) pointed outthat the small genomes of microorganisms in nature may bemodels for the identification of a minimal genome. Since
the ultra-small members described here as well as freeliving obligate UMB already harbor small and sometimes
streamlined genome structures (<2 Mb) through the loss of
unnecessary components, the “middle-out” approach, refer‐ring to the metabolic pathway of these members (Fig. 4),
which effectively combines traditional top-down andbottom-up approaches, will be useful for the rational designof artificial cells.
Conclusions
Numerous cultivation efforts have clearly shown thatsome previously uncultured members remain viable in

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39

NakaiFig. 4. A schematic diagram of the “middle-out” approach toward the development of minimal cells or synthetic cells. This approach, inspiredby the unusual biology of ultra-small life forms, may provide a new perspective to traditional top-down or bottom-up approaches. This figure wascreated with BioRender (https://biorender.com/).

small-size fractions. Some obligate UMB are ubiquitous anddominant in water systems and may play important roles innatural microbiome functions. In parallel, the advent ofhigh-throughput sequencing technology has greatly
expanded our knowledge of ultra-small microbial diversity.
Future studies are required to shed light on small microor‐ganisms hidden in various environmental samples (e.g.,soils and sediments) other than aqueous environments, andon the ecophysiological traits and biogeochemical roles ofthese members, including CPR/Patescibacteria and DPANN.
Further studies on “extreme” microorganisms at the lower
size limit will undoubtedly lead to new conundrums aboutlife on Earth.
Acknowledgement
I would like to thank Dr. K. Takai (JAMSTEC) and one anony‐mous reviewer for their helpful comments and suggestions on an
earlier draft of this review.
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Microbial Ecology along the Gastrointestinal Tract
Ethan t. hillman1, hang lu2, tianming Yao3, and CindY h. nakatsu4*
1Department of Agricultural and Biological Engineering, Purdue University, West Lafayette, Indiana 47907, USA; 2Department of

Animal Science, Purdue University, West Lafayette, Indiana 47907, USA; 3Department of Food Science, Purdue University, West
Lafayette, Indiana 47907, USA; and 4Department of Agronomy, Purdue University, West Lafayette, Indiana 47907, USA(Received January 31, 2017—Accepted August 19, 2017—Published online November 10, 2017)

The ecosystem of the human gastrointestinal (GI) tract traverses a number of environmental, chemical, and physical conditions
because it runs from the oral cavity to the anus. These differences in conditions along with food or other ingested substrates
affect the composition and density of the microbiota as well as their functional roles by selecting those that are the mostsuitable for that environment. Previous studies have mostly focused on Bacteria, with the number of studies conducted on
Archaea, Eukarya, and Viruses being limited despite their important roles in this ecosystem. Furthermore, due to the challenges
associated with collecting samples directly from the inside of humans, many studies are still exploratory, with a primary focus
on the composition of microbiomes. Thus, mechanistic studies to investigate functions are conducted using animal models.
However, differences in physiology and microbiomes need to be clarified in order to aid in the translation of animal model
findings into the context of humans. This review will highlight Bacteria, Archaea, Fungi, and Viruses, discuss differences
along the GI tract of healthy humans, and perform comparisons with three common animal models: rats, mice, and pigs.
Key words: Microbiome, mycobiome, virome, human gastrointestinal (GI) tract, animal models, diet

Researchers have been investigating the ecology of theintestinal microbiota for decades (120, 165) in order to identify,
characterize, and count their numbers. These extensive efforts
are due to the important roles the intestinal microbiota play indigestion, the production of essential vitamins, and protectionof the gastrointestinal (GI) tract from pathogen colonization(141). In the past few decades, molecular techniques targetingthe 16S rRNA gene and other genetic markers have beendeveloped to characterize and analyze bacterial communities.
These methods have been used to reveal the important roles
played by microbes in the GI tract (23, 180, 183, 184, 189,
212). In healthy individuals, the microbiome (microbialcommunity) and host have a mutualistic relationship in which
both partners benefit; however, pathogens may invade andcause disease under certain conditions. The initial aim of
most studies was to elucidate the role of the microbiome indisease. More recently, surveys have been performed onhealthy individuals in order to assess the contribution of the
microbiota to health, particularly in response to dietarychanges/supplementation with probiotics and/or prebiotics.
The human GI tract is a complex system that starts fromthe oral cavity, continues through the stomach and intestines,
and finally ends at the anus (Fig. 1). The density and compositionof the microbiome change along the GI tract, with major
populations being selected by the functions performed at thevarious locations. Bacteria along the GI tract have several
possible functions, many of which are beneficial for healthincluding vitamin production, the absorption of ions (Ca, Mg,
and Fe), protection against pathogens, histological development,enhancement of the immune system, and the fermentation of“non-digestible foods” to short chain fatty acids (SCFA) and44* Corresponding author. E-mail: cnakatsu@purdue.edu;
Tel: +1 (765) 496–2997; Fax: +1 (765) 496–2926.

other metabolites (19, 58, 63, 77, 138). The roles of fungi andviruses have not been examined in as much detail; however,they are known to play important roles in microbiota dynamics
and host physiology/immunity related to health and disease(45, 94, 133).
Food passes through the GI tract and the absorption rate ofnutrients is largely dependent on the activities of various
enzymes in the digestive system, such as amylase in saliva,
pepsin in the stomach, and pancreatic enzymes in the small
intestine. These mechanisms have been extensively examined(61, 62), particularly in the stomach. However, many foodcomponents cannot be digested in the upper GI tract and arepassed into the lower intestinal tract, in which they are fermented
by microbes. Functional studies commonly use animal models
in order to obtain a better understanding of the processes in
the GI tract that may lead to better health or decrease disease.
However, information from animal models may not be directlytranslatable to humans. Therefore, researchers need to consider
the limitations of the selected animal model when extrapolating
findings to humans.
Although microbiome studies often include an ecologicalcomponent, most of the research performed to date has
focused on Bacteria and not all of the biota. This represents alogical approach because Bacteria comprise most of the
microbiome. However, even biota representing a small proportion of the microbiome may play important roles in theecosystem (133). Therefore, researchers need to start shifting
their approach to include eukaryotic, prokaryotic, and viral(33, 133) interactions in efforts to elucidate the roles of allcomponents of the microbiome.
In recent years, a number of reviews have summarized
findings from the increasing number of studies being performedin this field (36, 73, 176, 188). While most studies have focusedon disease, the microbiome is also important for maintaining

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Fig. 1. Microbiome composition of Bacteria (1, 5, 20, 21, 43, 147, 156, 223), Eukarya (52, 85, 114, 126, 182, 197), and Viruses (45, 134, 151,
215) among the physiological niches of the human gastrointestinal (GI) tract. Phylum level compositional data are presented where available alongwith the most common genera in each GI tract location. The colors on the doughnut plots correspond to the legend in the lower left corner; the GI
tract is colored according to the pH scale shown at the bottom of Fig. 1. (* Malassezia was very abundant in one study and was not detected in anotherstudy. ** The abundance of Helicobacter may vary greatly between individuals. *** Proportions of these and other colon genera vary with age, diet,& geographical location.)

health. We herein highlight differences in the microbiome(Bacteria, Archaea, Fungi, and Viruses) along the GI tract ofhealthy humans, and how it compares to those of typical animalmodels used in research. One finding that is consistent tomost studies is that the microbiome of healthy individuals is
unique; however, there are still some generalities that will be
discussed in this review.
Microbiome diversity
Many factors contribute to the diversity of microbiomes,
and most studies have demonstrated the individuality of
microbiomes among subjects. Previous findings support microbial communities being more similar in subjects that are
genetically related (191), of a similar age (135, 213), or with
common diets (including the influences of ethnicity andgeography) (63). Diseases will also have an impact on microbiome diversity, including autoimmune and neoplastic diseases,
such as inflammatory bowel disease, diabetes, obesity, cardiovascular diseases, allergies, and cancer (37, 121). Treatments
for diseases may also affect a patient’s gut microbiota, andthe consequences of antibiotic use have been intensively
investigated (22, 95).
The host genotype has been shown to influence the devel-

opment of the gut microbiota, and the immune system has
been identified as a contributing factor (188). Crosstalk
between the microbiome and human immune system occurs
in response to a number of environmental factors, such as
diet, xenobiotics, and pathogens. Microbial host interactions
occur in the gut, mainly in the epithelial cell layer, myeloid
cells, and innate lymphoid cells, in which crosstalk and feedback loops contribute to the microbiome composition, hostphysiology, and disease susceptibility. These interactions
contribute not only to the bacterial community along the GI
tract, but also to the other microbiota (Fungi, Archaea, andViruses). Our understanding of the immunology associatedwith Fungi (150) and Archaea is currently limited. Transkingdom
commensal relationships among microbiota (including Viruses)
are considered to form from infancy (29, 30, 106, 200) andseveral co-occurring relationships have been identified (35,75, 76, 85, 214).
Bacteria. A more complete picture of human-associatedbacterial communities obtained using molecular techniques
has revealed that their diversity is greater than initiallyconsidered through cultivation (9, 20, 56, 90, 113). Using
almost full-length 16S rRNA gene sequences, predicted taxa
numbers range from 100–300 (20, 56), while pyrosequencing
suggests there are 1000s of phylotypes (38, 49). Most of the45

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gut bacteria identified by 16S rRNA gene sequencing belong
to the five phyla originally identified by cultivation, namely,
Bacteroidetes, Firmicutes, Actinobacteria, Proteobacteria, andVerrucomicrobia (90), and, at lower proportions, Fusobacteria,
Tenericutes, Spirochaetes, Cyanobacteria, and TM7 (189).
At lower levels of the taxonomic classification, microbiome
compositions vary with each individual. Attempts have been
made to identify a single core microbiome of Bacteria in the
GI tract. Although this has not been possible in the lower GI
tract (mainly using fecal samples) based on taxonomy, it
appears there are core microbial functions (152, 189, 191). It
is possible to identify some core microbiota in the oral cavity,esophagus, and stomach (148). Although extensive efforts
have been made to cultivate representative gut microbiota in
an attempt to gain a better understanding of the relationshipbetween taxa and function (156), there are still many undescribedtaxa with unknown functional roles in the gut.
As the price of sequencing decreases, it is becoming morecommon to use a metagenomic approach that provides information on all microbiota and potential functions (3, 70, 167,
189). This provides a means to go beyond Bacteria andobtain information on eukaryotic microbes (mainly fungi)
and viruses. Although Fungi, Archaea, and Viruses in the
microbiome are a part of the ‘rare biosphere’ (organisms thatcomprise <0.1% of the microbiome) (173), they still have asignificant impact on host health.
Fungi

46

Fungi are considered to comprise approximately 0.03% of
the fecal microbiome (143); making them approximately
3,300-fold less abundant than Bacteria. Fungal diversity inthe human gut is also lower than that of Bacteria (143, 166),
although more taxa are being found as the number of individuals
being studied using next generation sequencing is increasing(44, 126, 166, 182). In 2015, a review of 36 fungal gut microbiome studies revealed that there have been at least 267 distinct fungi identified in the human gut (181), while anotherstudy reported 221 (72). Despite the number of taxa that havebeen reported, most fungi are highly variable among individuals,
with few appearing to be common to all.
Cultivation-based analyses have typically identified Candidaas the most common fungal genus (166), and it is also frequently identified using non-cultivation-based methods, whereas
the other taxa identified have been variable, which may be
because of the analytical method used and/or subject variability.
For example, 66 genera of fungi were found using pyrosequencing when 98 individuals were examined, with the genera
Saccharomyces, Candida, and Cladosporium being the mostprevalent (85). Mucor was common in Spanish individuals(126) and the most common fungi in 16 vegetarians were
Fusarium, Malassezia, Penicillium, and Aspergillus (182).
These studies suggested that some taxa, e.g., Penicillium andAspergillus, are not resident in the gut and enter throughenvironmental sources, such as food and water, in which they
are commonly found. This may account for some of thevariability in taxa reported in various studies and for theincreasing number of fungi being identified as more studies
are being performed, even those based on cultivation (71).
Under certain conditions, some fungi may flourish and become

pathogenic including Candida, Aspergillus, Fusarium, andCryptococcus (44, 84, 140, 143). More information on fungalinteractions and diseases is available in a review by Wang etal. (204).
Despite their low abundance, fungi appear to have developed in mammalian guts along with the rest of the body from
infancy (106, 169). Although there is no consensus of a core
mycobiome, Candida, Saccharomyces, and Malassezia havebeen commonly reported (72). Most of the fungal species
detected appear to be either transient or environmental fungithat cannot colonize the gut and are often found in a single
study and/or one host only. A previous study indicated thatthe fungal community is unstable; only 20% of the initially
identified fungi were detected again 4 months later (78).
More studies on the stability of the mycobiome are needed inorder to establish the ecological roles of the components ofthe mycobiome. Many non-bacterial organisms have beenfound in numerous mammalian systems, which indicates thatthey play an important role that has been largely overlooked
and may lead to important discoveries and understanding in
the coming years.
Archaea
The most commonly reported genus of Archaea that has
been found in the GI tract is Methanobrevibacter (51, 55, 66,
85, 109). Other genera that have also been detected are
Methanosphaera (51), Nitrososphaera, Thermogynomonas,
and Thermoplasma (85) and the new candidate species,
Methanomethylophilus alvus (27, 131). Although Archaea
comprise a very small proportion of the microbiota,
Methanobrevibacter species are important contributors tomethanogenesis (66). Differences in Archaea in microbiome
samples may be due to the method used (51) and/or
complex relationships with other microbiota. For example,
Methanobrevibacter and Nitrososphaera were previously
shown to be mutually exclusive and potentially related tocarbohydrate intake (85). More studies are needed in order toclarify the interaction between Archaea and other microbiotagroups, which may contribute to our understanding of their fitness
and function (beyond methanogenesis) in the microbiome.
Viruses
Viruses in the human microbiome have also been understudied and available information is limited (161); the majorityof data are related primarily to disease and do not address thecommensal virome (34, 40). The majority of viral reads instudies that have been performed cannot be assigned to a
known group; this has contributed to the difficulties associatedwith assessing their roles in the GI tract (124, 160). A numberof teams have made extensive efforts in order to advancehuman virome studies (157, 161). In the last ten years, thenumber of identified polyomaviruses has increased from 4 to
13 species (some that cause disease and some that do not)(47), and the accuracy of identification techniques has been
improved to identify taxa at the genus level (199) and use
metagenomic information for viral taxonomy (172). Viral
communities are mainly comprised of bacteria-infecting
phage families (~90%), while eukaryotic viruses (~10%) areMicrobial Ecology of the GI Tractin lower abundance (157, 161). Metagenomic analyses havesuggested that the new bacteriophage, crAssphage associatedwith Bacteroides, is potentially common in humans (53). The
greatest diversity of phages is considered to occur in infantsand decreases with age, in contrast to increases in bacterial
diversity (116, 117, 162). With the availability of methods toenrich viruses in samples (41), and with more metagenomic
sequences and bioinformatics tools to identify viral sequences(53, 139), more information will be obtained on viral diversity and associated physiological factors in humans.
Similar to the microbiota, considerable variability appears
to exist in the viral taxa found among subjects (133). Limited
information is currently available on the functional roles ofmost viruses in the human GI tract. However, some possiblefunctions are: to increase bacterial fitness as sources of genetic
information (e.g., the source of antibiotic resistance genes), toincrease the immunity of bacteria or the human host, and toprotect against pathogens (40, 64, 157). The general consensus
is that the presence of bacteria is beneficial for viruses that are
increasingly trying to evade the immune system. This relationship may also be beneficial to bacteria as viruses may besources of potentially advantageous genes (resistance or tolerance to stress environments). Researchers are now examining
the ecological and evolutionary influences of phages on bacterial ecosystems (102), and the findings obtained may provide
insights into the important roles played by phages in the gut
microbiome.
The GI tract
Many challenges are associated with studying the microbial ecology of the GI tract because it is composed of chemically and physically diverse microhabitats stretching fromthe esophagus to the rectum, providing a surface area of
150–200 m2 for colonization or transient occupation by
microbes (16). The adult GI tract was initially estimated toharbor 1014 bacteria, 10 times more cells than the human body(16, 120); however, a more recent calculation estimates there
to be 1013 bacteria, which is equivalent to the number ofhuman cells (170). Lower bacterial numbers (103 to 104 bacteria mL–1 of intestinal content) are found in the upper end of
the GI tract, stomach, and small intestine, in which pH is low
and the transit time is short (16). The highest biodiversity(richness and evenness) of bacteria (1010–1011 bacteria g–1 ofintestinal content) is in the colon, in which cell turnover rate
is low, redox potential is low, and the transit time is long.
This section highlights the different functions and associatedmicrobiota along the human GI tract starting from the oralcavity, then the esophagus, stomach, and intestines (Fig. 1).
The oral cavity. Activity in the mouth may have a large
impact on the further digestion of food in the lower GI tract.
Food is mechanically ground into small particles, typically
0.1 mm, which increases the surface area. The oral microbiome
is composed of transient and commensal populations that
often form biofilms on soft and hard surfaces in the mouth(8). The most up-to-date information on taxa of the oral
microbiome may be found in the Human Oral Microbiome
Database (HOMD, http://www.homd.org/) (50). Informationin this database is limited to Bacteria and one Archaea.
Cultivation-independent analyses indicate that the most

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common genus is Streptococcus, while other genera include
Neisseria, Gemella, Granulicatella, and Veillonella, but notin all individuals examined (1, 91, 92, 107). The taxa present
appear to be dependent on interactions between microbes
within the community. For example, using a graph theorybased algorithm of an organism’s nutritional profile, the species
Streptococcus oralis and S. gordonii have low metabolic
complementarity and high metabolic competition, indicating
they are antagonistic to each other (110). In contrast,
Porphyromonas gingivalis was shown to have high metabolic
complementarity, indicating its ability to grow symbioticallywith diverse oral microbiota taxa. This computational method
was tested and confirmed with growth assays, making it aviable means to assess the ability of species to inhabit thesame environment. This has also been shown using an in situ
spectral analysis of microbiota in biofilm plaques. Biofilms
were shown to be composed of a number of taxa with
Corynebacterium at the foundation (209). The other taxa areconsidered to play complementary roles driven by the environmental and chemical gradients formed in biofilms that
control nutrient availability. These findings indicate that,
despite the large number of taxa identified in oral microbiome
studies, the core taxa of all microbiota may be identified in
the future based on spatial locations and functional roles (10).
Similar to Bacteria, large variations have been noted inviruses found in the oral cavity among subjects (151). Most
viruses are bacteriophages (approx. 99% of known sequences).
Viral communities are reproducible across time points withina subject, suggesting that they are stable; however, the humanand bacterial host significantly influence compositions (2,151, 163). In addition to interactions among oral bacteria,
many may associate with phages (57). Depending on the hostrange of the oral virome, this may make phages very common
inhabitants of the oral cavity. Furthermore, in addition tosurvival within bacterial hosts, phages may also survive in theoral mucosa and contribute to host immunity (11). These are
all new avenues of oral virome research that will likely be
investigated in greater depth in the future.
In addition to the bacterial microbiome, two cultivationindependent studies have been conducted on oral fungi.
Approximately 100 fungal species (20 genera) were detected
in one study of the oral mycobiome of healthy individuals(68). Among the fungi detected, Candida species were the mostcommon and abundant, while the other genera consisted of
Cladosporium, Aureobasidium, Saccharomycetales, Aspergillus,
Fusarium, and Cryptococcus. Most of these genera were also
detected in a recent study on three subjects; however,Malassezia, a skin pathogen, accounted for the most sequencereads (52). Most of the other studies conducted on the oral
mycobiome have focused on the role of fungi in disease (69,136). Since the oral microbial community is directly exposedto the environment, the presence of a dynamic and transientcommunity is expected, but warrants further study.
Esophagus. After swallowing, food is transported down
the esophagus by peristalsis to the stomach. Limited information is available on microbes inhabiting the esophagus (5, 91,147), and this may be due to the difficulties associated withobtaining samples because biopsies have typically been used.
However, a less invasive method using an esophageal string
has recently been demonstrated to be a feasible alternative

47

304

48

and yields similar findings to non-cultivation-based analysesof biopsies (60). Similar to the oral cavity, the most common
genus found in the esophagus is Streptococcus; however, an
overall comparison of the two communities has indicated thatthe number of taxa significantly differ between the two locations (15, 60). Among the few studies conducted on the viraland fungal microbiota of the esophagus, the focus has beenon association with disease (204) and none of the pathogenic
taxa inhabit healthy individuals.
Stomach. The stomach is the first digestive organ in the
body (89). It holds food and mechanically mixes it with proteolytic enzymes and gastric acids that aid in the breakdown
and subsequent absorption of nutrients. The growth of many
common bacteria is inhibited by these acidic conditions(pH<4), making this a unique community with the lowest
number of microbes, ranging between 101 and 103 CFU g–1.
In addition to digestion, the acidic conditions of the stomach
are considered to have evolved as a means of protection from
pathogens. This hypothesis is supported by the recent findingof a lower pH in the stomachs of scavengers and higher pH in
herbivores, which are less likely to encounter pathogens intheir food (13). Caution is needed when comparing the findingsof various studies throughout the GI tract because gastricjuice has a lower pH than the mucosal layer, resulting indifferences in the microbiota present (89).
Despite the low pH, non-cultivation-based analyses on
stomach biopsies revealed a more diverse microbiota than
expected (5, 20, 115). Regardless of variations among
subjects, there appears to be two major groups of individuals:
those with and without Helicobacter pylori (20). There is athird subset in which H. pylori is present in lower proportions
in some individuals that were negative using conventional
testing. Microbiomes dominated by H. pylori had significantly
greater proportions of the phylum Proteobacteria, of which it
is a member, and lower alpha diversity (5, 20). Other common genera are Streptococcus and Prevotella, both of which
are also found in the oral and esophageal communities;
however, the communities at these locations appear to differ(5). Limited information is available on fungi analyzed inbiopsy samples; although a cultivation study detected Candida
species, this appeared to be associated more with disease(224). The major interaction currently studied in the stomach
microbiota is with Helicobacter because of its association
with gastritis, peptic ulcers, and gastric cancer. However, thistaxon has been suggested to be beneficial for health, leadingsome to question whether the complete eradication of thismicrobe is the best option (67, 89).
In contrast, less information is available on the microbiomeof stomach fluids; it appears to harbor fewer Helicobacter
and an analysis of transcripts indicated that Actinobacteria
are the most active phylum; however, the other major phyla,
Firmicutes, Bacteroidetes, and Proteobacteria, are alsopresent (197). In the same study, it also appeared to harbornovel fungi; 77.5% of the ITS reads were not identified at thephylum level or lower. Candida and Phialemonium were theonly two identifiable fungal genera in all subjects tested,
whereas an additional 66 genera were present in at least oneof the nine subjects examined. Based on the infrequency andnumber of reads in this analysis, most of the taxa identified instomach fluids appear to be transient, and those playing an

Hillman et al.

active role are limited in this location.
Intestines. After mixing in the stomach, chime slowly
passes through the pyloric sphincter and enters the intestines,
in which the major digestion and absorption of nutrients
begin (12). Humans have a small and large intestine. The
small intestine, the main location in which food digestion andabsorption occurs, is further divided into three parts, theduodenum, jejunum, and ileum. The duodenum, in whichfood chime enters from the stomach, is directly associatedwith digestion and is linked to the pancreas and gallbladder.
Bile salts from the gallbladder and enzymes from the pancreas
enter the duodenum and mix with stomach chime in order tostart the digestion process. The epithelium in the jejunum andileum is responsible for glucose absorption into the bloodstream via glucose transporters and sodium ions. The small
intestine is followed by the large intestine (colon), which has
a larger diameter, but shorter length and is divided into four
sections: the ascending colon (cecum), transverse colon,
descending colon, and sigmoid colon (123). Water and minerals
are continuously absorbed along the colon before excretion.
Furthermore, complex foods that cannot be digested by thehost are used as growth substrates for the colonic microbiota(25, 178).
Spatial and temporal variabilities have been noted in the
microbial composition among the different intestinal structures
based on their functional roles and timing of food intake (18,129, 186). Although spatial variability exists along the intestinal
tract, the bacterial microbiome at the phylum level is considered
to remain fairly stable over time (43, 155); however, manyfactors may affect its stability (119). Undigested food andmost of the microbiota are found in the lumen, the central
space surrounded by the mucosal layer of the tubular intestinal
structure. The main absorption of growth substrates occurs
through the epithelial cells of the mucosa, which also prevents
the entry of the microbiota into host cells (174). A number ofimportant host-microbe interactions occur within the mucosa.
Energy from microbially produced metabolites, such as butyrate,
contributes to epithelial metabolism (97). Most of the gut isanaerobic, but there is an oxygen gradient in the mucosa thatprovides a competitive advantage for facultative anaerobes(174). Recent studies have also shown the importance of
metabolites produced by transkingdom microbiota to hostphysiology (185, 187, 188). Microbiota, such as Akkermansia
mucinophila, are commonly found residing in the mucus layer
and feed on mucin (39, 48). Therefore, the effects of hostinteractions with the gut microbiota, particularly those in thelarge intestine, have a prominent impact on overall human health,including energy reabsorption and immune system development.
Due to the difficulties associated with collecting multiple
samples along a healthy human GI tract in order to capture
the spatial heterogeneity of microbes in this environment,
most studies use fecal samples as a surrogate. However, thislimits the availability of regio-specific community information on the GI tract, resulting in portions, such as the small
intestine, remaining poorly characterized. The few studies
conducted on the small intestine have limited subject numbers
because they used biopsy samples (4, 201, 203) or ileotomy
patients (108, 195, 222). The bacterial genera most commonly
found among these studies were Clostridium, Streptococcus,
and Bacteroides. The number of studies that include fungi areMicrobial Ecology of the GI Tract
Table 1.
StomachSmall intestine
Cecum
Appendix
Colon

305
Comparison of the anatomy of the intestinal tract in humans and animal models

Human

Mouse

Rat

Pig

Four regions: cardia, fundus,
body, and pylorus
pH 1.5 to 3.5
5.5–6.4 m in length
pH 6.4 to 7.3
Smaller than the colon
No fermentation
pH 5.7
Present
Divided into the ascending,transcending, and descendingcolon
Main fermentation
Thick mucosa
pH 6.7

Three regions: forestomach,body, and pylorus
pH 3.0 to 4.0
350 mm in length
pH 4.7 to 5.2
Larger than the colon
Main fermentation
pH 4.4 to 4.6
AbsentNot divided

Three regions: forestomach,body, and pylorus
pH 3.0 to 4.0
1,485 mm in length
pH 5.0 to 6.1
Larger than the colon
Main fermentation
pH 5.9 to 6.6
AbsentNot divided

No fermentation
Thinner mucosa
pH 4.4 to 5.0

No fermentation
Thinner mucosa
pH 5.5 to 6.2

Four regions: esophagus, cardia,
fundus, and pylorus
pH 1.5 to 2.5
1.2–2.1 m in length
pH 6.1 to 6.7
Smaller than the colon
Some fermentation
pH 6.0 to 6.4
AbsentDivided into the ascending,transcending, and descendingcolon
Main fermentation
Thick mucosa
pH 6.1 to 6.6

Adapted from (59, 96, 128, 130, 137, 196)

even more limited, with the genera Candida and Saccharomyces
being the most frequently detected (108, 114). Caution is alsoneeded when extrapolating these findings to all individuals
because the health of some subjects was compromised whensamples were obtained.
Bacteria in the colon account for approximately 70% of all
bacteria in the human body because it is the main site for thebacterial fermentation of non-digestible food components
such as soluble fiber. The small number of studies that haveexamined microbial communities directly in the colon suggeststhat the bacterial composition is similar to that found in feces(86). However, fecal communities do not represent a single
colonic environment, such as the mucosa (223), but a mixtureof indigenous and transient microbes from the entire GI tract.
In studies in which a global view of the GI tract microbialcommunity is of interest, fecal material represents a good
surrogate and is easily obtained, allowing for multiple samples
to be obtained over short and long time periods from healthy
individuals. The majority of microbiome reviews have extensively covered colonic communities using feces (74, 92, 121,
148, 189); therefore, we will not describe its composition indetail. However, later in this review, the impact of diet on the
microbiome composition will be discussed. Furthermore, theabove sections on fungi and viruses provide information on
the taxa of these groups in the intestines.
Summary of the GI tract. The use of non-cultivationbased methods to investigate the microbiota in the GI tract
has increased our knowledge of their diversity. One groupthat we neglected to mention in this review was Protozoans/
Protists; however, recent reviews are available (79, 145).
Despite representing a smaller biomass than fungi, they also
appear to be important to the ecological structure of the gut
microbiome. The predator-prey relationship they have withother microbiota (145) may, in some cases, lead to disease
prevention (7). Difficulties are associated with elucidating thefunctional roles played by these various taxa at different points
along the GI tract. Therefore, it is still important to obtain
cultivated representatives to investigate their role and ecological significance along the GI tract. This consideration isimportant for all microbiota; however, it represents a larger
issue for low diversity groups, such as fungi, which may not
be numerically abundant, but still play a significant role (17).

Use of animal models
Animal models have been widely adopted in human gut
microbiome research (28, 98, 220) to reduce confounding
experimental factors such as genetics, age, and diet, which may
be more easily controlled in laboratory animals. Additionally,animal models with modified genetic backgrounds are available
for investigating potential mechanisms (137). Ideally, animalmodels with relatively similar genetic information (217), gut
structures, metabolism (142), and diets and behavior patterns(202) to humans need to be selected. Comprehensive comparisons of mice (137) and pigs (217) to humans were recently
conducted in order to aid in translating information fromanimal models to humans. In this section, we will highlightsome of their findings and compare GI tract structures andmicrobial community compositions. Furthermore, someadvantages and limitations associated with the use of animalmodels in human microbiome research will be discussed.
Similarities exist in the anatomy of the GI tract between
humans and most animal models (Table 1). However, differences in anatomical structures and pH at different locations
along the GI tract may contribute to differences in the microbiota found in humans versus animal models (26). The humancolon also has a thicker mucosal layer than those of mice andrats (137), which may have an effect on the diversity of the
microbiota colonizing the colon. Human gut bacteria aredominated by two phyla: Firmicutes and Bacteroidetes (189),
which also dominate the GI tract of commonly used model
animals (112). However, at lower taxonomic levels, somedifferences have been reported in microbiome compositionsin the gut between humans and animal models (Table 2). The
dominant taxa reported have varied as the number ofcomparisons performed has increased (137, 152); therefore,
the findings shown in Table 2 need to be used cautiously.
A pig gut gene catalogue of metabolic function wasrecently developed and compared to catalogues available forhumans and mice (217). They found that 96% of the KEGG
orthologs in humans were also present in pigs, whereas theoverlap at the gene level was markedly lower (9.46%).
However, there was a greater overlap between humans andpigs than between humans and mice. Microbial activity also
differs along the GI tract, with the most relevant being fermentation occurring in the ceca of most animal models, but

49Hillman et al.

306
Table 2.
Bacteria

Archaea
Viruses

Eukarya

Major taxa of the gut microbiota in humans and animal models

Human

Mouse

Rat

Pig

Firmicutes
Bacteroidetes
Actinobacteria
Proteobacteria
Methanobrevibacter
Nitrososphaera
Herpesviridae
Papillomaviridae
Polyomaviridae
Adenoviridae
CandidaMalassezia
Saccharomyces
Cladosporium

Firmicutes
Bacteroidetes

Firmicutes
Bacteroidetes

Firmicutes
Bacteroidetes

Methanobrevibacter

Methanobrevibacter

Variable

Variable

Ascomycota
Basidiomycota
Chytridiomycota
Zygomycota

Ascomycota
Basidiomycota
Chytridiomycota
Zygomycota

Methanomicrobia,
Methanosphaera
Picornaviridae
Astroviridae
Coronaviridae
Caliciviridae
Kazachstania
CandidaGalactomyces
Issatchenkia

Adapted from (85, 103, 105, 112, 125, 137, 153, 154, 171, 179, 193, 194, 215, 216, 221)50

not in humans (137). Strengths and weaknesses are associatedwith the major animal models being used, and these need tobe taken into consideration when conducting translational
research.
Rats. The use of rats as lab animals dates back to the1850s. They were considered to be a good candidate forhuman microbiome research because the rat contains thesame four dominant bacteria phyla in the GI tract (31), withFirmicutes (74%) and Bacteroidetes (23%) representing thelargest proportions (221). The advantages of using rats inhuman microbiome research include quick reproduction, afully sequenced genome, and easy handling and maintenancedue to their relatively small size. The limitation of this modelis that the diet used in rats differs from that for humans, andtheir behavior and living environment are also different,
which will affect the gut microbiota. The diet used in rat
studies is normal chow that is rich in fiber (205), and diet may
rapidly alter gut microbiota diversity (46). Although moststudies emphasize the impact of diet on the microbiota in thececum and/or colon (feces), the oral cavity of rats has beenused to clarify the impact of diet on the microbiome (93).
Mice. Many of the strengths and weaknesses associatedwith using rats are also applicable to mice. Similar to humans,
the microbiota in the GI tract of mice is dominated by
Firmicutes (74%) and Bacteroidetes (23%) at the phylum
level (217). However, there are differences at the genus level,
and this has led to the use of “humanized” mice. This isachieved by inoculating human gut microbiota into germ-free(GF) mice (192) or mice treated with antibiotics to eliminate
their gut microbiome (83). The microbiome of these mice
after fecal transplants may have a composition at the phyla
level that is 100% similar to humans and 88% at the genus
level (137). A recent study (175) used humanized mice to test
microbiome diversity after feeding with poorly accessible
carbohydrates, and found a similar reduction in OTU numbers to a human study (219). However, there are also some
limitations to using these animals, including the diet andenvironmental living conditions. Furthermore, gnotobiotic
mice may not reflect the human-microbe relationship due totheir weaker immune system (6).
Approximately 10 years ago, Scupham (168) showed that
all four major fungal phyla, Ascomycota, Basidiomycota,
Chytridiomycota, and Zygomycota, were present in the murine

gut. Additionally, many genera were identified, including
Acremonium, Monilinia, Fusarium, Cryptococcus, Filobasidium,
Scleroderma, Catenomyces, Spizellomyces, Neocallimastix,
Powellomyces, Entophlyctis, Mortierella, and Smittium. When
comparing these studies to the human gut, it is important tonote that this study indicated a more diverse fungal community
than those found in humans; the eukaryotic diversity of thehuman gut is low (143).
Pigs. Pigs have been used as surrogates for human microbiome research due to their highly similar genetics, physiological structures, behavior, metabolism, and immune functions to those of humans (81, 202). The greater similarities in
the omnivorous diet and GI tract structure between pigs andhumans are more advantageous than the murine model. The
microbiome of pigs is dominated by two phyla: Firmicutes
and Bacteroidetes (104); however, there are some notabledifferences at the genus level. The genus Prevotella wasfound to be common in two pig metagenomic studies (104,118). Since the number of pigs used in most studies is lessthan humans, the pig core microbiome at the genus level may
change as more pigs are studied. Another contributing factor
to shaping the microbiome composition is diet. Most studies
have found that the number of Bifidobacteria in pigs, eventhose on high fiber diets, is lower than that in humans (132,218), while that of Lactobacillus is higher (149). In nutrition
studies, humans and pigs are both dependent on the quality of
the nutrient load; however, the pig cecum has a larger capacity
to ferment indigestible compounds than the human cecum(54). The microbiota composition in pigs may differ from thatin humans due in part to differences in diet (81). Similar tomice, humanized GF pigs have been developed and themicrobiome after human fecal transplantation more closely
resembles that of the donor than conventional pigs (144).
However, the same disadvantages associated with using GF
mice are also true for GF pigs.
The genome of pigs may be mutated to study human diseases;
this is typically performed using miniature pigs such as thosefrom the Ossabaw and Gottingen islands (146). Genetic
mutations for metabolic syndrome and insulin resistance havesuccessfully been performed using Ossabaw pigs to study
human diseases such as type 2 diabetes (14, 177) and obesity(101). The ratio of Firmicutes to Bacteroidetes is higher inobese Ossabaw pigs than in lean pigs (146), similar to someMicrobial Ecology of the GI Tractobese humans (111, 190). This finding suggests that Ossabaw
pigs are a good model for researching the role of the microbiota
in human obesity. However, disadvantages are associatedwith using miniature pigs, mainly the higher cost for maintenance and longer reproductive period than rodents (146).
Although more extensive efforts have been made to investigate fungi in pigs than in other animal models, many ofthese studies were cultivation-based or for use as probiotics.
Fungi in pigs have been recently studied using a non-cultivation
approach and up to 17 species of yeast (belonging to thegenera Kazachstania, Galactomyces, Candida, Issatchenkia,
Pichia, Rhodotorula, and Trichosporon) were common in thegut (194). The number of studies on viruses is limited, but thecomposition appears to be highly variable among samples(164, 171) and affected by disease (24). These groups need to
be examined in more detail in order to establish whether pigs
are good models for use in understanding fungi and viruses inhumans.
Animal model summary. The convenience and cost ofusing animal models for human research are appealing.
However, researchers need be very careful when selecting
animal models appropriate for their objectives, particularly
when the objective is to directly extrapolate findings fromanimals to humans, due to the significant differences in GI
tract physiology and microbiome composition (65, 137, 217).
Diet in healthMany studies have found that diet is one of the main factors
shaping the composition of gut microbial populations. Dietary
approaches, such as the ingestion of non-digestible carbohydrates (prebiotics) and fermented food products containing
live cultures (probiotics), have been suggested to confer healthbenefits by enhancing the growth of beneficial intestinal bacteria(100, 158). As described earlier, the microbiota may break
down food components, such as non-digestible carbohydrates,
which are indigestible by the host in order to aid in maximizing
available nutrients (9) and produce metabolites that contributeto host health. Probiotics have been used as a means toreplenish the gut with “beneficial” microbiota after antibiotic
treatments or to treat diseases (82, 159). This section will
highlight some studies that demonstrated the health benefitsof prebiotics and probiotics and possible roles played by the
microbiota.
Dietary prebiotics and probiotics. Non-digestible andfermentable food components are often consumed as prebiotics
to selectively stimulate the growth and/or activity of endogenous colonic bacteria that may be beneficial to host health.
The increased consumption of prebiotics often correlates withenhancements in certain bacterial genera (a common example
is Bifidobacterium sp.); however, the reason they are beneficial remains unclear (208). Challenges are associated withelucidating the role being played by specific bacterial phylotypes because many of their processes are interactive (207).
For example, SCFA produced by bacterial fermentation may
lower intestinal pH, thereby increasing the solubility ofessential minerals, such as calcium, iron, and magnesium,and consequently enhancing their absorption and improving
health. Metabolites produced by microbes may also play animportant role in cellular differentiation and proliferation in307

the colonic mucosa by inducing apoptosis and may confer
protection against colitis and colorectal cancer by modulating
oncogene expression. These functions do not appear to be
performed by a single species; a number of different species
may be acting independently or in combination. Research isleading to an understanding of microbial community structure
and composition dynamics with respect to diet aids in establishing testable hypotheses for future research in health andbeneficial microbes (32). Most research has been performedon the influence of beneficial intestinal bacteria such as
Bifidobacterium spp. and Lactobacillus spp. on host healthmonitored using a cultivation approach. Cultivation-independent
approaches have now become more popular, leading to theidentification of new beneficial microbiota taxa and theirpotential functional roles in the gut as they relate to diet.
Dietary fibers and oligosaccharides are carbohydrate ingredients that vary in composition and structure, but are considered
to be non-digestible because of the lack of appropriate intestinal enzymes to hydrolyze them or structural hindrances thatprevent enzyme access in the gut. Although bacteria in thelower gut may ferment these carbohydrates, the rate anddegree of fermentation vary with the polysaccharide (80).
The range of fermentation in the colon for various fibers is
broad, from approximately 5% for cellulose to nearly 100%for pectin (42). The resulting SCFA, including butyrate andpropionate, are considered to reduce pH and solubilize minerals,
thereby improving their absorption and subsequent utilization.
Inulin, a long chain fructooligosaccharide (FOS) often
obtained from chicory root, and FOS from other sources are
the fibers that have been studied in the most detail (206).
Several novel fibers have been tested in an in vitro large
intestine model for their effects on the microbial stimulationand production of SCFA (122). All these novel fibers stimulated the growth of beneficial Bifidobacteria and some
Lactobacillus species along with increases in SCFA production. Only a few studies have examined the effects of fibers
and resistant starches on the human microbiome (87, 127,
198, 210, 211). A soluble corn fiber product has been demonstrated to increase Ca absorption in a number of different
studies (210, 211). More benefits to human health may be
attributed to the consumption of prebiotics and fermentationby the gut microbiome.
The number of studies that include diet effects on Archaea,
Fungi, and/or Viruses are limited; however, some examples
are included herein. Examinations of Archaea, Fungi, andBacteria correlations in response to diet revealed a syntrophic
model involving Candida, Prevotella, Ruminococcus, andMethanobrevibacter (85). Candida was considered to break
down carbohydrates into metabolites used by Prevotella andRuminococcus that produce CO2 for Methanobrevibacter(85). However, shifts in carbon sources or breaking down
starches via amylases from the human mouth may alter thisrelationship because Prevotella may no longer be dependent
on Candida. This is a good example of how Archaea, which
represent a very small portion of the microbiome, are a key
contributor to methanogenesis and waste decomposition. The
absence of Archaea may have severe effects on the surrounding
community as hydrogen, glucose metabolites, and other carbon
sources accumulate. Other organisms will eventually fill thisniche, but may diminish or accumulate new metabolites that51

Hillman et al.

308

ultimately shift the surrounding community based on theirfitness for using these substrates.
A recent study investigated rapid changes in the microbiome
composition when diets were either high in animal-based orplant-based fat and protein (46). The fungus Candida wasfound to increase in subjects placed on a plant-based diet,whereas Penicillium increased on animal-based diets. The
most commonly found fungi in vegetarians were Fusarium,
Malassezia, Penicillium, Aspergillus, and Candida (182).
Caution is needed when interpreting findings because someof these fungi may be found on food prior to ingestion (46,78, 182)
Phages assembled in the gut may also be modified by diet.
A recent study examined changes in the fecal viral community over an 8-d period in six subjects supplied different diets(134). Shotgun sequencing of virus-like particles revealed
that interpersonal differences in the virome were the largest
source of variations in this study. However, the virome ofsubjects whose diets were changed differed more than inthose who maintained their normal diet. Although this is only
one study with a few human subjects, studies using a mousemodel and different dietary fats support these findings (88,99). Collectively, these findings indicate that diet plays a keyrole in shaping the gut virome, and further research is neededin order to investigate interactions between diet and the virome.

5.
6.
7.

8.
9.
10.
11.
12.
13.
14.
15.
16.

Summary
Advances have been made in the last decade in our understanding of the role of the GI tract microbiome in humanhealth. This review has highlighted changes and differencesin the microbiome along the GI tract that are due to changes
in physical, chemical, and biological interactions. Althoughextensive research has been conducted on Bacteria in fecal
samples, the main kingdom inhabiting the gut, our knowledge
is still insufficient, particularly in other regions of the GI tract.
Furthermore, other groups (Archaea, Fungi, and Viruses) have
not yet been investigated in adequate detail, demonstrating areal void in knowledge. This highlights that the basic ecologyof microbiomes is important for gaining a greater understanding
to improve human health and decrease disease. In order toachieve this goal, it is important to include all microbiota instudies and remain cognizant of the limitations associatedwith understanding the entire GI tract of humans despite
challenges in sampling and cultivation. Furthermore, the useof appropriate animal models in mechanistic studies requires
careful consideration.
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Akinori Yabuki, Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokosuka, Japan
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JAPANESE SOCIETY OF PLANT MICROBE INTERACTIONS

Chair of Society: Kiwamu MINAMISAWA, Tohoku University
Secretary-General: Shusei SATO, Tohoku University
Treasurer: Hisayuki MITSUI, Tohoku University
General aﬀairs: Masayuki SUGAWARA, Obihiro University of Agriculture and Veterinary Medicine

JAPANESE SOCIETY FOR EXTREMOPHILES

President (2022–2023): Tairo OSHIMA, Kyowa-kako Co., Ltd
Vice President (2022–2023): Satoshi NAKAMURA, Tokyo Institute of Technology
Vice President (2022–2023): Yoshizumi ISHINO, Kyushu University

This journal is partly subsidized by the Grant-in-Aid for Publication of Scientific Research Results from the Japan Society for the
Promotion of Science (JSPS).

c/o NAKANISHI PRINTING CO.
Shimodachiuri Ogawa Higashi Kamikyoku, Kyoto 602-8048, Japan TEL: +81–75–441–3155, FAX: +81–75–417–2050