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September 2020

Microbes and Environments
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CONTENTS
MOST VALUABLE PAPER OF THE YEAR 2018
Nitric Oxide Production from Nitrite Reduction and Hydroxylamine Oxidation by Copper-containing
Dissimilatory Nitrite Reductase (NirK) from the Aerobic Ammonia-oxidizing Archaeon,
Nitrososphaera viennensis
Shun KobayaShi, DaiSuKe hira, Keitaro yoShiDa, MaSanori toyofuKu, yoSuKe ShiDa,
Wataru ogaSaWara, taKaShi yaMaguchi, nobuo araKi, and MaMoru oShiKi
33(4), 428–434, 2018

1

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*Times cited at the end of 2019

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Microbes Environ. Vol. 33, No. 4, 428-434, 2018https://www.jstage.jst.go.jp/browse/jsme2 doi:10.1264/jsme2.ME18058

MOST VALUABLE PAPER OF THE YEAR 2018

Short Communication
Nitric Oxide Production from Nitrite Reduction and Hydroxylamine Oxidation
by Copper-containing Dissimilatory Nitrite Reductase (NirK) from the Aerobic
Ammonia-oxidizing Archaeon, Nitrososphaera viennensis
Shun KobayaShi1, DaiSuKe hira2, Keitaro yoShiDa3, MaSanori toyofuKu3, yoSuKe ShiDa4, Wataru ogaSaWara4,
taKaShi yaMaguchi5, nobuo araKi1, and MaMoru oShiKi1*
1Department of Civil Engineering, National Institute of Technology, Nagaoka College, Nagaoka, Japan; 2Department of AppliedLife Science, Faculty of Biotechnology and Life Science, Sojo University, Ikeda, Kumamoto, Japan; 3Graduate School of Life andEnvironmental Sciences, University of Tsukuba, Tsukuba, Ibaraki, Japan; 4Department of Bioengineering, Nagaoka University ofTechnology, Nagaoka, Niigata, Japan; and 5Department of Science of Technology Innovation, Nagaoka University of Technology,
Nagaoka, Japan(Received April 21, 2018—Accepted July 17, 2018—Published online October 12, 2018)

Aerobic ammonia-oxidizing archaea (AOA) play a crucial role in the global nitrogen cycle by oxidizing ammonia to nitrite,
and nitric oxide (NO) is a key intermediate in AOA for sustaining aerobic ammonia oxidation activity. We herein heterologously
expressed the NO-forming, copper-containing, dissimilatory nitrite reductase (NirK) from Nitrososphaera viennensis andinvestigated its enzymatic properties. The recombinant protein catalyzed the reduction of 15NO2– to 15NO, the oxidation ofhydroxylamine (15NH2OH) to 15NO, and the production of 14-15N2O from 15NH2OH and 14NO2–. To the best of our knowledge,
the present study is the first to document the enzymatic properties of AOA NirK.
Key words: nitrite reduction, hydroxylamine oxidation, nitrous oxide production, ammonia oxidizing archaea, Nitrososphaera viennensis

possess nirK, which is transcribed and expressed during aerobic
ammonia oxidation (8, 15, 20, 37). These findings suggestthat NirK are involved in NO formation in AOA cells.
However, NO2– reduction to NO by AOA NirK has neverbeen demonstrated.
Bacterial NirK have been characterized as homotrimeric
enzymes, and each subunit has 2 Cu-binding sites (Type 1
and 2 Cu-binding sites). Type 1 Cu-binding sites receive anelectron from an electron donor, such as type 1 Cu proteins(single-domain cupredoxins) and/or cytochrome c, and theelectron is then further transferred to a type 2 Cu-binding sitethat is the catalytic center of NirK (14, 25). Bacterial NirK
have been classified into 2 phylogenetically distinct groups(class 1 and class 2 groups) based on sequence similarities,
and the NirK of the class 1 group contains linker loop andtower loop regions in the amino acid sequence (3). AOA
NirK, including Ns. viennensis NirK, are affiliated with adistinct clade of bacterial class 1 and 2 groups (Fig. 1A).
Lund et al. (20) reported that AOA NirK may be further
classified into several phylogenetic clades showing specificgeographic distributions. Ns. viennensis NirK has amino acidresidues consistent with those of type 1 and 2 Cu-bindingsites (His106, His140, and His316 for type 1 Cu-binding sites andHis101, Cys141, His152, and Met157 for type 2 Cu-binding sites)
as well as the linker and tower loop regions, whereas the C
terminus has unusual extensions of ~26 residues (Fig. 1B).
These phylogenetic affiliations of and structural variations in
Ns. viennensis NirK raise concerns regarding its enzymatic
properties, such as specific enzymatic activity, affinity for
NO2–, and products of NO2– reduction.
Based on its unique sequence and lack of biochemical
information, the purpose of the present study was to charac-

Aerobic ammonia oxidation, a rate-limiting step of nitrification, drives the global nitrogen cycle (24, 40), which involves
aerobic ammonia-oxidizing archaea and bacteria (AOA
and AOB, respectively) and complete ammonia oxidizers(comammox) (9, 44). Of these, AOA primarily contribute to
aerobic ammonia oxidation in natural environments including
soil and open ocean (19, 31, 46). AOA are affiliated with thephylum Thaumarchaeota, which includes phylogenetically andphysiologically diverse members (6) and the soil-inhabitingarchaeon Nitrososphaera viennensis (41). The biochemistryof aerobic ammonia oxidation by AOA has received a great
deal of interest because ammonia oxidation to nitrite (NO2–)
proceeds in a different manner to that of AOB. AOA oxidize
ammonia to hydroxylamine by ammonia monooxygenase(Amo) as well as AOB (43), while hydroxylamine is further
oxidized to NO2– by an unidentified enzyme (17). All known
AOA genomes lack the gene encoding hydroxylamine
dehydrogenase (Hao), and the involvement of a copper-protein
complex has been proposed (40, 45). In parallel with theoxidation of ammonia to NO2–, AOA produce nitric oxide(NO) (22). NO is a key intermediate in AOA cells because
this highly reactive molecule is essential for sustaining aerobic
ammonia oxidation activity (17, 33, 36, 47). To date, the following
2 pathways have been reported as a source of prokaryotic NO
formation: NO2– reduction to NO by copper-containing andcytochrome cd1-type dissimilatory nitrite reductases (NirK
and NirS, respectively) (38) and NH2OH oxidation to NO byhydroxylamine oxidoreductase (Hao) (4, 21). Although neither
nirS nor hao are found in AOA genomes (6), AOA commonly* Corresponding author. E-mail: oshiki@nagaoka-ct.ac.jp;
Tel: +81–258–34–9277; Fax: +81–258–34–9277/9284.

1

Copper-containing NO2– Reductase of AOA

429

Fig. 1. Phylogeny (A) and sequence alignments (B) of prokaryotic NirK. A) A phylogenetic tree of prokaryotic NirK was constructed by the
maximum likelihood method with the Jones-Taylor-Thornton model using the protein sequence of multicopper oxidase type 3 of Nitrososphaera
viennensis (accession number; AIC14243.1) as an outgroup. Branching points that support a probability >80% in bootstrap analyses (based on 500
replicates) are shown as filled circles. The scale bar represents 10% sequence divergence. Sequence accession numbers are indicated in parentheses.
B) Protein sequence alignment of nirK. NirK sequences were aligned using ClustalW software. Circles and triangles correspond to the amino acidresidues of type 1 and 2 Cu-binding sites, respectively. Linker, Tower loop (3), and C-terminal extension regions are underlined. Abbreviations of
microorganisms are as follows: Nitrosomonas europaea is N. europaea, A. xylosoxidans is Achromobacter xylosoxidans, A. faecalis is Alcaligenes
faecalis, N. gonorrhoeae is Neisseria gonorrhoeae, S. thermophilus is Sphaerobacter thermophilus, and Ns. viennensis is Nitrososphaera viennensis.

terize Ns. viennensis NirK. Prior to the present study, we
aimed to isolate Ns. viennensis NirK from a batch culture ofNs. viennensis as a native enzyme. However, the activity of
aerobic ammonia oxidation often disappeared when we scaledup the cultures (data not shown). Additionally, a slow growthrate (μmax 0.024 h–1) (41) and low biomass concentration in
the culture (ca. 107~8 cells mL–1) further precluded the preparation of the biomass required for protein purification. Since
2

Kobayashi et al.

430

recombinant NirK proteins have been successfully used topreviously examine several enzymatic properties (7, 16, 32),
the authors decided to heterologously express Ns. viennensis
NirK in Escherichia coli, and investigate its enzymatic
properties. The nirK gene located in the Ns. viennensis genome(accession number; CP007536.1) was cloned into the expression
vector pCold I (Takara Bio, Shiga, Japan) with the 6×His
tag using the Mighty cloning reagent set (Takara Bio), andtransformed into E. coli strain BL21(DE3) (Takara Bio). The
N-terminal region of Ns. viennensis NirK was predicted to be
the signal peptide sequence (Met1 to Ala24), and nirK without
the signal peptide sequence was amplified by PCR using
ExTaq polymerase (Takara Bio) and specific forward (5ʹGGCATATGGCCCCGACTGGTGTCACTAGACACTAT-3ʹ)and reverse (5ʹ-GGAAGCTTAACCAGAGGTGGTGTTGC
CACCGGAGG-3ʹ) oligonucleotide primers. The restriction
sites of NdeI and HindIII in the forward and reverse primers
above are underlined. Genomic DNA extracted from Ns.
viennensis cells (JCM19564) was used as the DNA templatefor PCR. The constructed plasmid was subjected to Sanger
sequencing, and no mutations were found in the sequence.
Regarding the expression of the recombinant protein in E. coli
cells, the expression culture was aerobically cultivated at 37°C
in Luria-Bertani media containing 100 ng μL–1 ampicillin.
When the OD600 of the culture increased to 0.4, the culture
was transferred to 15°C and held for 30 min, and protein
expression was then induced by adding isopropyl β-D-1thiogalactopyranoside (IPTG) at a final concentration of 0.1 mM.
After being incubated at 15°C for 24 h, cells were harvested
by centrifugation at 8,500×g at 4°C for 10 min. The harvested
cells were suspended in buffer containing 20 mM Tris HCl(pH 8), 200 mM NaCl, and 10% glycerol. The cells were
disrupted using a sonifier 250 (Branson) (output 20, duty 20%
for 60 s, 6 cycles), and centrifuged at 13,000×g at 4°C for 1 h.
The supernatant was recovered as a soluble protein fraction,and the recombinant protein was purified using His-tag affinity
chromatography. The recombinant protein was bound to His60
Ni Superflow resin (Takara Bio), and washed with washingbuffer containing 20 mM Tris HCl (pH 8), 200 mM NaCl,
10% glycerol, and 20 mM imidazole. The bound recombinant
protein was eluted with elution buffer containing 20 mM Tris
HCl (pH 8), 200 mM NaCl, 10% glycerol, and 300 mM
imidazole. Protein concentrations were measured using the
DC-protein assay kit (Bio-Rad, Hercules, CA, USA) withbovine serum albumin as previously described (26), and purity
was evaluated by sodium dodecyl sulfate-polyacrylamide gelelectrophoresis (SDS-PAGE) on a 10% polyacrylamide gel
as previously described (28). As shown in Fig. 2A, a single
protein band appeared at a molecular mass of 40 kDa, whichclosely matched the molecular mass deduced from aminoacid sequences of the recombinant protein (i.e., 39.7 kDa).
The protein band was excised from the gel, and subjected to amatrix-assisted laser desorption ionization-time of flight mass
spectrometry (MALDI-TOF MS) analysis after in-gel tryptic
digestion for protein identification (The detailed methodology
is described in the Supplementary text). The MALDI-TOF
MS analysis confirmed that the protein band corresponded toNs. viennensis NirK (Fig. S1). Regarding the reconstitutionof Cu-binding sites of the recombinant protein, the purified
recombinant protein was dialyzed against buffer containing

20 mM Tris HCl (pH 8), 300 mM NaCl, and 0.5 mM CuSO4
at 4°C for 57 h. The protein solution was dialyzed again using
the above Tris buffer without CuSO4 at 4°C for 6 h. The dialyzed
recombinant protein was concentrated using a Vivaspin column(MWCO; 30 kDa) (GE Healthcare Japan, Tokyo, Japan). The
recombinant protein was loaded onto a gel-filtration HiLoad
16/600 Superdex 200 pg column (GE Healthcare) to assess
the molecular mass of the recombinant protein, which was
105±1.3 kDa (Fig. 2B). Since the deduced molecular mass of
Ns. viennensis NirK was 39.7 kDa, the molecular mass obtainedby gel filtration indicated that the recombinant protein forms
a homotrimeric structure, similar to canonical NirK.
NirK have been characterized as metalloproteins showing
a blue or green color spectrum, and exhibit absorption peaks
at approximately 450 and/or 600 nm (3). Bacterial NirK,
which belong to the class 1 group, often show a maximum
absorption peak at approximately 450 nm, although an exception(Achromobacter xylosoxidans NirK) that shows a peak at 593 nm
has been previously reported (16). The purified recombinant
protein was pale blue in color, and showed an absorption
peak at 590 nm (Fig. 2C). This feature indicated that Ns.
viennensis NirK is affiliated with the subgroup of NirK showing
a blue color spectrum. The blue or green color spectrum of
NirK is derived from a copper atom in the type 1 Cu-bindingsite (14), while the type 2 Cu-binding site does not contributeto the UV or visible spectrum. The type 2 Cu-binding site
shows a characteristic electron spin resonance (ESR) spectrum(7, 16); therefore, an ESR analysis was performed using a
JES-FA200 spectrometer (JEOL, Tokyo, Japan) to test for thepresence of the type 2 Cu-binding site in the recombinant
protein. An axial type 2 Cu signal (g//=2.24, A//=18.31 mT,
and g⊥=2.06) was found in the ESR measurement (Fig. 2D),
indicating that the recombinant protein has a type 2 Cu-bindingsite coordinating with a copper atom. Additionally, we assessed
the copper content of the recombinant protein by inductively
coupled plasma mass spectrometry (ICP-MS). The copper
content was found to be 2.9 atoms per subunit of the recombinant protein, indicating that Cu was fully incorporated into
the recombinant protein. Overall, the recombinant protein shared
the structural and spectroscopic features of class 1 and 2
bacterial NirK, which is consistent with sequencing information.
The kinetics of NO2– reduction were examined by anoxically
incubating the recombinant protein at 25°C and pH 6.5 with
15NO – and artificial electron donors as previously described2(7). All of the buffers and stock solutions were preparedanoxically as previously described (27). Two milliliters of reaction
buffer (20 mM phosphate buffer, 0.1 to 1.6 mM Na15NO2–,
0.5 mM benzyl viologen (BV), and 0.24 mM sodium dithionite)
was dispensed into a 1-cm sealable quartz cuvette and placedin an anaerobic chamber in which the O2 concentration wasmaintained at lower than 1 ppm. BV was used as an artificial
electron donor because it has been employed to examine thekinetics of the NO2– reduction of bacterial NirK (7, 13). The
cuvette was set in a UV-VIS spectrometer UV-2700 (Shimadzu,
Kyoto, Japan), and the initial absorbance of the prepared reaction
mixture at a wavelength of 550 nm was approximately 2.0.
The reaction was initiated by adding the recombinant protein(50 μL containing 250 μg of protein) using a gastight syringe,
and the oxidation rate of reduced BV (molecular extinction
coefficient, 10.4 mM–1 cm–1) (13) was monitored at 550 nm.
3Copper-containing NO2– Reductase of AOA

431

Fig. 2. Characterization of recombinant Nitrososphaera viennensis NirK. A) SDS-PAGE of the recombinant protein purified by His-tag affinity
chromatography. B) Assessment of the molecular mass of the recombinant protein by gel filtration chromatography. Catalase from bovine liver (232 kDa),
lactate dehydrogenase (140 kDa), and bovine serum albumin (66 kDa) were used to prepare a standard calibration curve. C) UV-VIS absorption
spectra. The measurement was performed in a 20 mM Tris buffer (pH 8) containing 300 mM NaCl at 25°C. The solid line indicates the recombinant
protein (1 mL mL–1) oxidized with air. A 5×enlarged spectrum is also shown as a dashed line. D) ESR spectra. The measurement was performed
using the recombinant protein (4.9 mg mL–1) at –253°C.

The recombinant protein reduced NO2– by oxidizing BV,
whereas no significant BV oxidation was found in the cuvette
without the recombinant protein. The turnover number andKm value for NO2– reduction by the recombinant protein were
3.1 s–1 and 287 μM, respectively (Table 1), and the turnover

number and affinity constant were markedly lower and higher,
respectively, than those of other canonical NirK proteins,
including those from AOB. The product of NO2– reduction by
the recombinant protein was examined using phenazine
methosulfate (PMS) as the electron donor instead of BV.
4

Kobayashi et al.

432
Table 1.

Enzymatic properties of archaeal and bacterial copper-containing nitrite reductase (NirK). ND; not determined.

Organisms
Archaeal NirK
Nitrososphaera viennensis
NO2– reduction
NH2OH oxidation
Bacterial NirK (NO2– reduction)
Nitrosomonas europaea
Nitrosococcus oceani
Achromobacter xylosoxidans
Candidatus Jettenia caeni

MW*
(kDa)

Cu content†(atom per subunit)

Absorption(nm)105±1.5

2.9

590

96
114
110
101

ND
1.67
1.99
ND

450, 597
455, 575
595
449, 598

Activity‡
Turnover (s–1)

Km (μM)

Reference

3.1
0.039

287
97

This study
This study

288
1,600
172
319

ND
52
35
250

18
16
14, 32
7* Molecular weight (MW) of a trimeric NirK. The MW of Ca. Jettenia caeni NirK was calculated from amino acid sequences without a signal peptide
sequence. † Copper contents previously assessed by chemical analyses were shown. ‡ The following electron donors were used to evaluate the turnover number of NO2– reduction; methyl viologen for N. europaea and Nc. oceani, pseudoazurine for A. xylosoxidans, and benzyl viologen for Ns.
viennensis and Ca. Jettenia caeni NirK.

When BV was used as the electron donor, NO2– was reduced toNO, and further reduced to ammonia (approx. 60% of consumed
15NO –) as observed in a previous study in which the NO –2
2
reduction activity of A. xylosoxidans NirK was examinedusing methyl viologen (MV) as the electron donor (1). BV
and MV have low redox potentials (–350 and –440 mV,
respectively) (23), resulting in the reduction of NO to NH3;
therefore, PMS with a higher redox potential (+80 mV) wasused in the present study. The recombinant protein was incubatedas described above in a 1.8-mL gas-tight vial with the additionof 0.5 mM PMS and 5 mM ascorbic acid instead of BV anddithionite, and the production of 15N-labeled gaseous compounds(i.e., N2, NO, and N2O) in the headspace was examined by gas
chromatography mass spectrometry (GC/MS) as previously
described (27). The diluted gases of 15-15N2 (Cambridge Isotope
Laboratories, Tewksbury, MA, USA), 14NO, and 14-14N2O(GL Science, Tokyo, Japan) were also analyzed to prepare
standard curves for quantification. The recombinant protein
reduced 15NO2– with the oxidation of PMS, and 38 and 48%
of consumed 15NO2– were converted to 15NO and 15-15N2O,
respectively. This is direct evidence to show that the recombinant protein is a NO-forming nitrite reductase. We foundthat the production of 15-15N2O was equal to the production of
15NO, which likely results from the reduction of 15NO – to2
H15NO (i.e., NO2–+2e–+3H+ → HNO+H2O) and the chemical
formation of 15-15N2O from the formed H15NO (i.e., 2HNO →N2O+H2O) (35), as previously observed for a sulfide-linked
nitrite reductase (34).
Aside from NO2– reduction, NH2OH oxidation was also
investigated using the recombinant protein because NH2OH
is produced as an intermediate during aerobic ammonia
oxidation by AOA. The kinetics of NH2OH oxidation were
examined by aerobically incubating the recombinant protein(245 μg mL–1) at 30°C and pH 7.5 with 0.5 mM NH2OH, with
dissolved oxygen being available as an oxidant. The reaction
was initiated by the addition of NH2OH solution, and theconcentration of NH2OH was assessed colorimetrically (5).
The concentration of H2O2, which may be produced by theoxidase activity of NirK (12), was also evaluated colorimetricallyusing horseradish peroxidase (Wako, Osaka, Japan) and
3,3ʹ,5,5ʹ-tetramethylbenzidine (TMBZ) (Dojindo, Kumamoto,Japan) (2). As shown in Fig. S2, the recombinant proteinoxidized NH2OH with the production of H2O2. No NH2OH
oxidation or H2O2 production was observed when the incubation
was repeated without the addition of the recombinant protein.

The values for the turnover number and affinity constant for
NH2OH oxidation were 0.039 s–1 and 97 μM (Table 1),
respectively, and the value for the turnover number was twoorders of magnitude lower than that observed for NO2–
reduction; therefore, the recombinant protein catalyzed NO2–
reduction more efficiently. The addition of cytochrome cfrom equine heart (1 mg mL–1) or BV (0.5 mM) did not resultin an increase in the reaction rate or affinity for NH2OH oxidation.
The product of NH2OH oxidation by the recombinant protein
was examined in a 15NH2OH tracer experiment (29). The
recombinant protein was incubated in a 1.8-mL gas-tight vialwith the addition of 0.5 mM 15NH2OH (Cambridge Isotope
Laboratories) instead of 14NH2OH. After a 2-h incubation, theconcentrations of the 15N-labeled gaseous products wereassessed by GC/MS. The recombinant protein oxidized
15NH OH and produced 15NO, 15-15N O, and 15-15N gases
2
2
2
quantitatively (Fig. 3), whereas the production of NO2– andNH3 was not detectable (detection limits: 50 and 100 μM,
respectively). The oxidation of NH2OH to NO has beenFig. 3. NH2OH oxidation by recombinant Nitrososphaera viennensis
NirK. The recombinant protein was incubated at 30°C and pH 7.5 in
1.8-mL vials (volume of the headspace: 1.5 mL), with i) 0.5 mM
15NH OH, ii) 15NH OH and 14NO – (each 0.5 mM), or iii) 14NH OH and2222
15NO –. The production of N , NO, and N O in the headspace was222
examined by gas chromatography mass spectrometry (GC/MS). NH3
and NO2– concentrations were also measured; however, they were notdetectable during the incubation. During a 2-h incubation, i) 63±35(mean±SD), ii) 149±1, and iii) 120±1 nmol N of NH2OH were consumed
in the liquid phase, resulting in 75–137% of the 15N-labeled nitrogenmass balance in the vials. Error bars represent the SD derived from
triplicate incubations, and the graph bars represent the mean values.
NH2OH oxidation was not found in the vials without the addition of therecombinant protein.

5

Copper-containing NO2– Reductase of AOA

433

cytochrome c was not. To date, the biochemistry of AOA
cupredoxin has not been investigated using natural enzymes
and recombinant proteins, and our study provides basic
information that furthers our understanding of the biochemistryof AOA.

described in bacterial Hao (21); however, to the best of ourknowledge, this is the first description of NH2OH oxidation
by NirK. We also observed 15-15N2O production from
15NH OH oxidation, which likely resulted from the oxidation2of 15NH2OH to H15NO and abiotic coupling of H15NO, aspreviously described. Notably, 15-15N2 was the major productof 15NH2OH oxidation by the recombinant protein.
Hydroxylamine disproportionation (30) may not be responsiblefor 15-15N2 production because NH3 production was not detectablein the liquid phase. The molecular mechanisms underlying
the oxidation of 15NH2OH to 15-15N2 by the recombinant protein
warrant further studies.
We repeated the above incubation with the addition of
NH2OH and NO2– because both compounds are available in
AOA cells during aerobic ammonia oxidation. Therefore, theabove incubation was repeated with the addition of 15NH2OH
and 14NO2– (each 0.5 mM) or 14NH2OH and 15NO2– (Cambridge
Isotope Laboratories) (each 0.5 mM). In both cases, 14-15N2O
was the major product (Fig. 3), indicating that the recombinant
protein produces N2O by oxidizing NH2OH using NO2– as anelectron acceptor. N2O production by the denitrifier NirKfrom NH2OH and NO2– has been previously described (10),and the N-nitrosation reaction is involved in N2O production(39). Notably, Ns. viennensis cells produce N2O when they
are incubated aerobically with NH3 and NO2– (42), although
the Ns. viennensis genome lacks the gene encoding nitricoxide reductase (nor) that is involved in N2O production from
nitrifier-denitrification. Stieglmeier et al. (42) suggested the
involvement of Ns. viennensis NirK in the production of N2O
in an Ns. viennensis culture, and our results support thishypothesis. Although the catalytic efficiency of Ns. viennensis
NirK for NH2OH oxidation was markedly lower than that ofNO2– reduction (Table 1), Ns. viennensis NirK may act as an
NH2OH oxidase in Ns. viennensis cells and produce N2O
under oxic growth conditions. Aside from 14-15N2O production,
the production of 15NO and 15-15N2O was also observed when
the recombinant protein was incubated with 14NH2OH and
15NO – (Fig. 3).
2
Although the recombinant protein catalyzes NO2– reduction
and NH2OH oxidation, the catalytic efficiency of both reactions
was low, as shown in Table 1. AOA nirK transcripts areabundant in the transcriptome (8, 11, 20, 37), suggesting thestrong expression of AOA NirK in cells. NirK was the 225th
most abundant protein of the 1,503 proteins detected in theproteome of the late exponential phase of Ns. viennensis cells
aerobically oxidizing ammonia (15). The strong expressionof NirK appears to support the activity of NO2– reduction toNO as well as NH2OH oxidation to NO by the low efficiency
catalytic enzyme. Ns. viennensis NirK may function as abifunctional enzyme that supplies NO molecules from 2
different sources (i.e., NH2OH and NO2–), which provides Ns.
viennensis cells with a competitive advantage. In the present
study, the enzymatic kinetics of recombinant Ns. viennensis
NirK for NO2– reduction were examined using artificial electron
donors; further studies are needed to identify physiologicalelectron donors in Ns. viennensis cells. Bacterial NirK may
accept electrons supplied from single-domain cupredoxin andcytochrome c (14, 25). A number of genes encoding singledomain cupredoxin were found in the Ns. viennensis genome(Table S1), whereas the ortholog of the gene encoding

Acknowledgements
This work was supported by JSPS KAKENHI Grant numbers
17K15305, 16H02371, and 16H04442 to M.O., T.Y., and N.A.,
respectively. The authors acknowledge Ko Furukawa, Akihiro Suzuki,
and Hisashi Satoh for their technical assistance with the ESR,UV-VIS, and ICP-MS measurements, respectively.
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Microbes Environ. Vol. 34, No. 2, 155-160, 2019https://www.jstage.jst.go.jp/browse/jsme2 doi:10.1264/jsme2.ME18148

MOST VALUABLE PAPER OF THE YEAR 2019

Antimicrobial Activities of Cysteine-rich Peptides Specific to Bacteriocytes of the
Pea Aphid Acyrthosiphon pisum
Nahoko Uchi1†, Mitsutaka Fukudome1, Narumi Nozaki1, Miyuzu Suzuki2, Ken-ichi Osuki1, Shuji Shigenobu2, andToshiki Uchiumi1*
1Graduate School of Science and Engineering, Kagoshima University, 1–21–35 Korimoto, Kagoshima, Kagoshima 890–0065,

Japan; and 2National Institute for Basic Biology, 38 Nishigonaka, Myodaiji, Okazaki, Aichi 444–8585, Japan(Received October 12, 2018—Accepted January 23, 2019—Published online March 21, 2019)

Aphids have a mutualistic relationship with the bacterial endosymbiont Buchnera aphidicola. We previously reported sevencysteine-rich peptides in the pea aphid Acyrthosiphon pisum and named them Bacteriocyte-specific Cysteine-Rich (BCR)
peptides; these peptides are exclusively expressed in bacteriocytes, special aphid cells that harbor symbionts. Similar symbioticorgan-specific cysteine-rich peptides identified in the root nodules of leguminous plants are named Nodule-specific Cysteine-Rich(NCR) peptides. NCR peptides target rhizobia in the nodules and are essential for symbiotic nitrogen fixation. A BacA (membraneprotein) mutant of Sinorhizobium is sensitive to NCR peptides and is unable to establish symbiosis. Based on the structural andexpressional similarities between BCR peptides and NCR peptides, we hypothesized that aphid BCR peptides exhibit antimicrobialactivity, similar to some NCR peptides. We herein synthesized BCR peptides and investigated their antimicrobial activities andeffects on the bacterial membrane of Escherichia coli. The peptides BCR1, BCR3, BCR5, and BCR8 exhibited antimicrobialactivities with increased membrane permeability. An sbmA mutant of E. coli, a homolog of bacA of S. meliloti, was moresensitive to BCR peptides than the wild type. Our results suggest that BCR peptides have properties that may be required tocontrol the endosymbiont, similar to NCR peptides in legumes.
Key words: symbiosis, aphid, Buchnera, cysteine-rich peptide, bacteriocyte

Endosymbiosis is often essential for the survival ofhosts and symbionts. A well-studied example is the mutualinterdependence between aphids and Buchnera (30). Aphids
harbor an endosymbiotic γ-proteobacterium, Buchnera
aphidicola, within specialized cells called bacteriocytes (27).
Buchnera provides the host with nutrients, such as essential
amino acids, that aphids cannot synthesize and that are deficientin plant phloem sap, aphids’ sole dietary component (13, 29).
The relationship between aphids and Buchnera is syntrophic
and obligate. Buchnera cells are vertically transmitted throughhost generations by transvariole transfer: they are exocytosed
from the maternal bacteriocyte, temporarily released into theextracellular space, and endocytosed by the posterior syncytial
cytoplasm of the blastula during early embryogenesis (stage
7) (4, 5, 17, 26). This symbiotic relationship is estimated tohave been established 200–250 Myr ago. This long-term
endosymbiotic relationship has shaped the characteristic
streamlined genome, from which Buchnera has lost many genes,
including those involved in the biosynthesis of lipopolysaccharides and phospholipids, gene regulation, and defense
responses, and has, thus, lost the ability to survive outside ofhost bacteriocytes (2, 29).
Seven cysteine-rich peptides (CRPs) that are exclusively
expressed in the bacteriocytes of the pea aphid Acyrthosiphon
pisum have been identified and designated as “BCRs”(Bacteriocyte-specific Cysteine-Rich [BCR] peptides) (31).

Each BCR peptide consists of a secretion signal peptide andmature peptide (44–84 amino acids) with 6 or 8 cysteine
residues (31). Their expression was initially detected in stage
7 embryos, with Buchnera cells being transported from maternal
bacteriocytes to the embryonic syncytium, and bacteriocytespecific expression is then maintained throughout the rest of
the aphid’s life. Although this expression pattern suggests theimportance of BCRs in the symbiosis with Buchnera, their
physiological activities and functions in symbiosis currently
remain unknown.
CRPs in symbiosis organs are found in other symbioses, suchas that between legumes and nitrogen-fixing α-Proteobacteria
called rhizobia (22), actinorhizal plants and nitrogen-fixing
Frankia (6), and bean bugs and β-Proteobacteria of the genus
Burkholderia (10). In the legume symbiosis, the host plant
forms a specific organ, the root nodule, in which rhizobia
live. Rhizobia penetrate the nodule cells and differentiate into
bacteroids, the symbiotic form. By metabolic adaptation,
bacteroids gain the ability to fix nitrogen (22, 33). In nodules
formed on the roots of legumes, such as Medicago, Pisum, andTrifolium, bacteroids show cell elongation, genome amplification, cell membrane modifications, and the loss of reproductive
activity (23). This terminal differentiation is mediated by
nodule-specific cysteine-rich (NCR) peptides that are producedby the host plants (34, 35).
Medicago truncatula produces more than 600 NCR peptides
in infected nodule cells only (28). NCR peptides are structurally
similar to defensins, i.e., they have signal peptides and mature
peptides that conserve 4 or 6 cysteine residues (22). Some NCR
peptides exhibit antimicrobial activity (34). Synthesized NCR
peptides have the ability to induce cell elongation, polyploidization, and cell membrane modifications in Sinorhizobium* Corresponding author. E-mail: uttan@sci.kagoshima-u.ac.jp;
Tel: +81–99–285–8164; Fax: +81–99–285–8163.
† Present address: Graduate School of Medical and Dental Science,
Kagoshima University, 8–35–1 Sakuragaoka, Kagoshima, Kagoshima
890–8544, Japan

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meliloti cultured in vitro (34). Signal peptides are cleaved bysignal peptidase, and mature NCR peptides are delivered tothe microsymbionts inside host plant cells. The DNF1 gene ofM. truncatula encodes a subunit of a nodule-specific signal
peptidase; dnf1 mutants cannot establish effective symbiosis(32, 35). In dnf1 mutant nodules, rhizobia remain undifferentiated, and NCR peptides localize within the endoplasmic
reticulum, and, thus, are not delivered to bacteroids. Thesefindings strongly support the view that NCR peptides are
essential for effective symbiosis (34, 35).
To survive exposure to NCR peptides, S. meliloti requires
BacA (14). The S. meliloti bacA mutant is hypersensitive to
NCR peptides: when S. meliloti bacA mutant cells are released
into nodule cells, they are rapidly killed (14). However, they
may survive in the nodule cells of the dnf1 mutant because
NCR peptides are not transported to these cells. These findings
show that BacA is essential for the chronic infection of nodules
as well as bacteroid development (12, 14).
We investigated whether the BCR peptides of A. pisum
exhibit antimicrobial activity and affect cell membrane
permeability, similar to the NCR peptides of legume plants.
We treated E. coli, a model γ-proteobacterium closely related
to Buchnera, with chemically synthesized BCRs. We foundthat 4 out of the 6 BCR peptides assayed exhibited antimicrobialactivities and induced cell elongation and higher intensities of
4ʹ,6-diamidino-2-phenylindole (DAPI) and propidium iodide(PI) fluorescence. The E. coli sbmA mutant, a homolog of
bacA of S. meliloti, was more sensitive to BCR peptides than
the wild type. Similarities in the in vitro activities of BCR
peptides to those of NCR peptides (14, 34) suggest that BCR
peptides are involved in the symbiosis with Buchnera in thepea aphid in a similar manner to NCR peptides in legume plants.

Treatment of bacterial strains with BCR or NCR peptides
All bacterial strains were cultured in liquid M9 medium. When
the OD600 of the culture reached 0.3, cells were harvested andwashed with 10 mM Tris·HCl buffer (pH 7.5) three times. Cells
were then suspended in 10 mM Tris·HCl buffer (pH 7.5) toOD600=0.1. Each test peptide was added to the bacterial suspension
at an appropriate concentration and the suspension was incubated at
30°C for 3 h. In the analysis of cell morphology and membrane
permeability, BCR peptides were added to a final concentration of
5 μM. As a control treatment, bovine serum albumin (BSA) wasused at the same concentration as BCR peptides.
Detection of antimicrobial activities of BCR and NCR peptides
To estimate antimicrobial activities, we diluted the bacterial suspension treated with each peptide and spread it on LB (E. coli) or TY(S. meliloti) agar plates. The relative number of cfus was assessed inrelation to the number that appeared on control (BSA-treated) plates
as 100%. To investigate changes in morphology and membrane
permeability, we analyzed the bacterial suspension according toprevious studies (15, 34) that analyzed the activities of NCR peptides.
Bacterial cells are detectable by staining with the fluorescent DNA
dye DAPI. PI, a fluorescent dye that stains nucleic acids, is excluded
from living cells, but enters dead cells or cells with the loss ofmembrane integrity. In brief, we added DAPI and PI together to thesuspension to a final concentration of 10 μg mL–1 each and analyzed
cells using a cell sorter (SH800, Sony, Tokyo, Japan) and confocal
microscopy (A1, Nikon Instech, Tokyo, Japan). The cfus of E. colisuspensions and morphology and membrane permeability of E. coli
cells were not affected by BSA under the experimental conditions
employed in the present study (data not shown).

Results
Antimicrobial activities of synthetic BCR peptides
BCR1, BCR3, BCR5, and BCR8 at 5 μM exhibited strong
antimicrobial activities against E. coli (MG1655) cells; thelatter three prevented colony formation (Fig. 1). When ca.
5×107 cells were treated with 5 μM of BCR1, ca. 1×102 cells

Materials and Methods
Bacterial strains and media
E. coli wild-type strains MG1655 and BW25113 and the sbmAdisrupted mutant JW0368 derived from BW25113 (1) were provided
by the National BioResource Project (https://shigen.nig.ac.jp/ecoli/
strain) and maintained on Luria-Bertani (LB) medium. S. meliloti
1021 and its bacA mutant (8) were maintained on TY medium (3). In
bioassays of the activities of BCR and NCR peptides, all strains were
cultured in M9 liquid medium (25) supplemented with 0.2% glucose.
In estimations of colony-forming units (cfus), E. coli strains wereplated on LB agar plates and Sinorhizobium strains on TY agar plates.
Refolding of BCR peptides
BCR1, BCR2, BCR4, BCR5, and BCR8 peptides were chemicallysynthesized through a custom peptide synthesis service by Medical& Biological Laboratories (Nagoya, Japan) and BCR3 was synthesized
by Biomatik Corporation (Cambridge, Canada). They were refoldedwith a Refolding CA Kit (Takara Bio, Kusatsu, Japan) according to
the manufacturer’s instructions. In brief, peptides were unfoldedusing guanidine hydrochloride with dithiothreitol, and were refoldedin cycloamylose/Tween 40 with d,l-cystine. They were then passed
through an Oasis HLB 3 cc column (Nihon Waters, Tokyo, Japan)
and eluted with 1 mL of elution buffer (4 vol. acetonitrile : 1 vol.
methanol : 5 vol. Milli-Q water containing 0.1% trifluoroacetic acid).
Eluates were dried and then dissolved in Milli-Q water to a final
concentration of 2 mg mL–1. The refolded peptide was verified by
HPLC, and the formation of disulfide bonds was confirmed by mass
spectrometry. BCR6 was not assayed in the present study because
BCR6 is too long (84 aa) to synthesize chemically. The NCR247
peptide was synthesized and used without refolding.

Fig. 1. Antimicrobial activities of BCR peptides. E. coli MG1655 wastreated with 5 μM BCR peptides for 3 h and colony-forming units were
estimated relative to the BSA control. Each value is the mean±SE ofthree independent experiments. Asterisks indicate a significant difference
between BCR4 and the control (P<0.05 by the Student’s t-test). N.C., nocolony appeared.

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survived (data not shown). No colony formed from the bacterial
suspension treated with BCR3, BCR5, or BCR8. BCR4
exhibited mild antimicrobial activity, whereas BCR2 showedno significant antimicrobial activity (Fig. 1).

and BCR1-treated cells increased the frequency at higher
intensities (Fig. 2B). Cells treated with BCR2, BCR5, andBCR8 fluoresced at higher intensities (Fig. 2B). BCR4-treatedcells produced slightly higher intensities (Fig. 2B). BCR1,
BCR2, BCR3, BCR5, and BCR8 clearly changed the profile
of PI staining, shifting it to higher intensities and a wider
distribution (Fig. 2C). BCR1 widened the distribution, shifting
the main frequency to a lower intensity and slightly increasing
the higher intensities (Fig. 2C). BCR4 slightly shifted the
distribution to a higher intensity (Fig. 2C). In summary, cell
sorter analyses revealed that some of the BCRs affected cellmorphology and membrane permeability, which increased
the intensities of DAPI and PI staining.
BCR-treated E. coli cells were also inspected by fluorescencemicroscopy. BCR1 and BCR3 significantly elongated cells
and increased the intensities of DAPI and PI fluorescence(Fig. 2D). BCR3 and BCR8 promoted cell aggregation (Fig.
2A, 2D, and S1). BCR4 had no significant effect on either

Effects of BCR peptides on E. coli cells
To reveal the effects of BCR peptides on cell morphology,
we used the cell sorter to measure the forward scatter parameter(FSC), which indicates cell size, and the side scatter parameter(SSC), which indicates the complexity of granularity and internal
complexity of cells, including cell formation. Histograms of
FSC and SSC measured by the cell sorter are shown in Fig.
2A. BCR2, BCR3, BCR5, and BCR8 increased FSC (Fig. 2A)
and SSC (Fig. S1). BCR1 and BCR4 slightly increased FSC(Fig. 2A), but not SSC (Fig. S1).
Most control cells stained with DAPI fluoresced at intensitiesof 20,000–30,000 (Fig. 2B). BCR1-treated and BCR3-treatedcells produced a wider range of the signal than control cells,

Fig. 2. Effects of BCR peptides on E. coli cells. E. coli MG1655 cells were treated for 3 h with 5 μM of the BCR peptide or BSA as the control.
Cells were stained with DAPI and PI and analyzed by a cell sorter. (A) Forward scatter (FSC), (B) DAPI, (C) PI. (D) Fluorescent microscopy of
MG1655 cells treated with BCR peptides and stained with DAPI and PI. Images are representative micrographs of cells treated with each peptide.
Scale bars, 5 μm. (E) Ratio of PI-positive cells to DAPI-stained cells. At least 4,000 cells were counted in each treatment. Each value is the mean±SE.
Means denoted by the same letter do not differ significantly (P<0.05, the Student’s t-test).

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morphology or fluorescence. BCR1, BCR3, and BCR8 significantly increased the fraction of PI-positive cells (Fig. 2E).

than those of BW25113 (Fig. 3A). BCR1, BCR3, and BCR8
also caused the elongation of BW25113 and JW0368 cells(Fig. S3).
S. meliloti ΔbacA was significantly more sensitive to 20 μM
NCR247 than wild-type S. meliloti 1021 (Fig. S4), as previously
reported (14). JW0368, an E. coli sbmA mutant, was moresensitive to NCR247 at 5 μM, but not at 20 μM, than BW25113(Fig. S4). Both E. coli strains were more resistant to NCR247
than S. meliloti (Fig. S4). No S. meliloti colonies formed at
5 μM BCR1, BCR3, or BCR8 (Fig. S5). Strain 1021 wasresistant to 3 μM BCR1, BCR3, and BCR8, whereas the ΔbacA
mutant was sensitive to them (Fig. 3B).
The effects of BCR1 and BCR8 on wild-type S. meliloti
cells was analyzed using the cell sorter. BCR1 and BCR8
markedly increased FSC (Fig. 4A), SSC (Fig. S6), DAPI, andPI fluorescence (Fig. 4B). Thus, BCR1 and BCR8 exerted
similar effects on S. meliloti as those on E. coli. BCR4 showedsimilar, but weaker effects.
The observed effects of BCR/NCR peptides on both E. coliand S. meliloti are summarized in Supplementary Tables S1and S2.

Sensitivity of the sbmA mutant to BCR peptides and NCR247
To reveal whether the SbmA protein is related to the antimicrobial activity of BCR peptides, BCR1, BCR3, and BCR8
were used because these BCRs exhibited strong antimicrobialactivity. We treated two strains of E. coli, BW25113 (wildtype) and JW0368 (sbmA mutant), with the BCR peptides atlower concentrations and calculated cfu values. Since nocolonies formed when BW25113 and JW0368 were treatedwith 5 μM BCR1, BCR3, or BCR8 (Fig. S2), we used a
sub-lethal concentration, 3 μM (Fig. 3A), in subsequent
assays. BCR1 and BCR3 reduced the cfus of JW0368 to less

Discussion
We investigated the antimicrobial activities of synthesized
BCR peptides found in the bacteriocytes of pea aphids. Seven
genes for BCR peptides (BCR1–6, 8) have been identified in
the genome of A. pisum (31). The mRNA expression of BCRs
in the embryo is initiated around the developmental stage
coincident with the infection of Buchnera into the embryo
from maternal bacteriocytes, and mRNA expression is maintained exclusively in bacteriocytes throughout the life of theaphid (31). Although expression patterns strongly suggest

Fig. 3. Sensitivity of the E. coli sbmA mutant and S. meliloti ΔbacA
mutant to BCR peptides. After a treatment with 3 μM BCRs for 3 h, thecolony-forming units of each strain were estimated relative to the BSA
control. The dataset shown is representative of three independent experiments. (A) E. coli BW25113 (wild type) and JW0368 (sbmA mutant).
(B) S. meliloti 1021 and ΔbacA mutant. Each value is the mean±SE ofthree independent experiments. Asterisks indicate a significant difference
between the wild type and mutant (P<0.01, the Student’s t-test).

Fig. 4. Effects of BCR peptides on S. meliloti. S. meliloti 1021 cells were treated for 3 h with 5 μM BCR peptides or 5 μM BSA. Cells stained withDAPI and PI were analyzed by flow cytometry. (A) Forward scatter (FSC), (B) DAPI and PI. Data are representative of at least three independent
experiments.

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Antimicrobial Peptides of the Pea Aphid

that BCR peptides control endosymbionts, their functions andactivities have not yet been investigated. We synthesized 6
out of 7 A. pisum BCR peptides and examined their effects onbacteria. All peptides exhibited antimicrobial activity or
permeabilized the membrane of E. coli cells: BCR1, BCR3,
BCR5, and BCR8 exhibited strong antimicrobial activity andpermeabilized the cell membrane, BCR2 only increased permeabilization, and BCR4 only showed mild antimicrobialactivity (Fig. 1 and 2). Thus, at least four aphid BCR peptides
were identified as antimicrobial peptides (AMPs). There wasno obvious correlation detectable among the amino acidsequences, isoelectric points, and antimicrobial activities of
BCR peptides. Since the sequence database search of BCR
peptides returned no significant hits outside of aphid species(31), these BCR peptides constitute a novel class of AMPs
specific to the aphid lineage.
We found that some BCRs exerted antimicrobial effects,
whereas other did not. We also noted that each BCR peptide
exerted antimicrobial effects at a different level and theireffects on bacterial morphology and membrane permeability
varied. In M. truncatula, the genes for NCR peptides are
expressed exclusively in the root nodules, whereas expression
patterns differ among genes (22). Each NCR peptide localizes
to a different zone of the nodule; e.g., NCR035 localizes tothe interzone and nitrogen-fixing zone, while NCR001 only
localizes to the nitrogen-fixing zone (34). NCR035 and NCR247
exhibit strong antimicrobial activities against S. meliloti,
while some NCR peptides, such as NCR057 or NCR224, donot. The genes for all six BCR peptides used in the present
study are exclusively expressed in the bacteriocyte of the pea
aphid (31). Among them, BCR2 and BCR4, similar to NCR057
and NCR224, did not exhibit strong antimicrobial activities;
BCR2 affected cell morphology and membrane permeability
without antimicrobial activity. These results suggest that each
BCR plays a different role in symbiosis, similar to NCR
peptides. Although the location and target of the peptides
within the bacteriocyte have not yet been reported, the pea
aphid also has a diverse line-up of CRPs that may function ina different context in symbiosis, as observed in M. truncatula.
Legumes, such as M. truncatula, of the Inverted-RepeatLacking Clade (IRLC) use several hundred NCR peptides tocontrol their microsymbionts. Aeschynomene spp. legumes,of the more ancient dalbergoid lineage, are expected to haveseveral tens to hundreds of NCR-like peptides (7). On theother hand, only seven genes for BCR peptides have been
identified on the genome of A. pisum. Although the reason forthe marked difference in the number of CRPs between aphid–
Buchnera and legume–rhizobia symbioses remains unclear,different systems of symbiosis may be responsible: Rhizobia
are soil bacteria that may survive independently of their hostplant; therefore, during symbiosis, the host plant may need totightly control them by using NCR peptides with diverse
functions. In contrast, Buchnera has lost the ability to survive
outside of the pea aphid and, thus, may be controlled by BCR
peptides with very restricted functions. Further studies are
required to understand the diverse evolutionary processes of
CRPs among symbiotic systems.
BacA, a membrane protein of S. meliloti, is essential forsymbiosis with M. sativa (12). BacA of S. meliloti is involvedin the modification of lipids with fatty acids (9); however, themolecular mechanisms employed by the BacA protein forresistance to AMPs remain unknown. The bacA mutant of S.
meliloti is sensitive to NCR peptides and is unable to differentiate into bacteroids in host nodule cells, resulting in theabortion of symbiosis (14). SbmA of E. coli is a homolog of
BacA of S. meliloti and may complement the symbiosis defectof the S. meliloti bacA mutant (16). Although differenceswere small, the significantly greater sensitivity of the E. colisbmA mutant and S. meliloti bacA mutant to BCR1, BCR3,
and NCR247 than their parent strains (Fig. 3 and S4) suggests
the involvement of bacterial SbmA and BacA proteins insensitivity to these cysteine-rich AMPs and the similar functionof these BCR peptides to NCR peptides. BacA and SbmA areboth transporters that import a number of structurally diverse
peptides into the cell (11, 18, 20, 21, 36). In S. meliloti, BacA
is essential for bacteroid differentiation and survival in thehost plant cell (12, 14). However, we did not find any homologsof bacA/sbmA in the Buchnera genome. BCR peptides may
function via a BacA/SbmA-independent mechanism andaffect the membrane permeability and survival of Buchnera.
AMPs are common peptides that function in the innate
immunity of eukaryotes (37). Besides BCR peptides and NCR
peptides, AMPs that are expressed and/or function in symbioticorgans have been reported in other symbiotic relationships:e.g., between bean bugs and Burkholderia (10) and between
actinorhizal plants and Frankia (6). The weevil antimicrobial
coleoptericin-A peptide regulates the growth of its symbiont
by inhibiting cell division (19). In the symbiosis between theactinorhizal plant Alnus and Frankia, Alnus provides defensinlike peptide Ag5 to Frankia. The present study revealed thatsome BCR peptides exhibited antibiotic activity and increased
the permeabilities of E. coli and S. meliloti cells. A possiblefunction of antimicrobial BCR peptides is to control thegrowth of Buchnera in bacteriocytes, similar to coleoptericin-A,
Ag5, and NCR, thereby controlling the size of the symbiont
population within the host. These antimicrobial BCRs may
also interact with secondary symbionts or invading microbes
in the aphids. Another possible function of BCRs is topromote metabolite exchange (24). In vitro, Ag5 exhibits
antimicrobial activity against Frankia and, at sublethal
concentrations, induces the permeabilization of the vesicle
membrane, resulting in the release of amino acids, particularly
glutamine and glutamate, from Frankia cells (6, 24), which
contributes to metabolic exchange between Frankia and nodule
cells. Since the pea aphid has lost many transporter genes in
its genome (24, 29), BCR peptides that permeabilize the cell
membrane may be used in the exchange of metabolites
between Buchnera and host cells. Animals and plants may
both use AMPs not only as a defense against microbial attack,but also for symbiosis with microbes, representing a parallel
evolution in symbiosis.
Acknowledgements
We would like to thank the National Institute of Genetics forproviding us with the E. coli strains. This study was supported by theJapan Society for the Promotion of Science KAKENHI Grant
Number 15K14899 to TU, 25291083 and 17H03717 to SS, and the
National Institute for Basic Biology (NIBB) Collaborative Research
Program (12-273, 13-325, 14-326, 15-321 and 16-317). We thank
Mr. Takahiro Bino (NIBB) for his technical support in cell sorting.
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Uchi et al.

SS thanks Dr. David L. Stern and Dr. Aishwarya Korgaonkar(Howard Hughes Medical Institute, Janelia Research Campus) for
discussions and Dr. Tatsuhiko Kondoh (Nagoya University) for his
support with biochemical experiments.

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Microbes Environ. Vol. 33, No. 2, 162-171, 2018https://www.jstage.jst.go.jp/browse/jsme2 doi:10.1264/jsme2.ME17203

MOST CITED ORIGINAL PAPER IN THIS
THREE YEARS [2017-2019] (21 citations)

Taxon Richness of “Megaviridae” Exceeds those of Bacteria and Archaea in the Ocean
Tomoko Mihara1, Hitoshi Koyano2, Pascal Hingamp3, Nigel Grimsley4, Susumu Goto5, and Hiroyuki Ogata1,*
1Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611–0011, Japan; 2School of Life Science andTechnology, Laboratory of Genome Informatics, Tokyo Institute of Technology, 2–12–1 Ookayama, Meguro-ku, Tokyo 152–8550,
Japan; 3Aix Marseille Université, Université de Toulon, CNRS, IRD, MIO UM 110, 13288, Marseille, France; 4Integrative Marine
Biology Laboratory (BIOM), CNRS UMR7232, Sorbonne Universities, 66650, Banyuls-sur-Mer, France; and 5Database Center forLife Science, Joint-Support Center for Data Science Research, Research Organization of Information and Systems, Wakashiba,
Kashiwa, Chiba 277–0871, Japan(Received December 28, 2017—Accepted February 25, 2018—Published online May 25, 2018)

Since the discovery of the giant mimivirus, evolutionarily related viruses have been isolated or identified from various
environments. Phylogenetic analyses of this group of viruses, tentatively referred to as the family “Megaviridae”, suggest thatit has an ancient origin that may predate the emergence of major eukaryotic lineages. Environmental genomics has sincerevealed that Megaviridae represents one of the most abundant and diverse groups of viruses in the ocean. In the present study,
we compared the taxon richness and phylogenetic diversity of Megaviridae, Bacteria, and Archaea using DNA-dependent
RNA polymerase as a common marker gene. By leveraging existing microbial metagenomic data, we found higher richness
and phylogenetic diversity in this single viral family than in the two prokaryotic domains. We also obtained results showingthat the evolutionary rate alone cannot account for the observed high diversity of Megaviridae lineages. These results suggestthat the Megaviridae family has a deep co-evolutionary history with diverse marine protists since the early “Big-Bang” radiationof the eukaryotic tree of life.
Key words: Mimiviridae, Megaviridae, species richness, RNA polymerase, ocean metagenome

Acanthamoeba polyphaga mimivirus (APMV), initiallymistaken as a Gram-positive bacterium when it was isolated
via amoeba co-culture in the 1990s (4), was recognized in2003 as a bone fide virus, indeed a ‘giant virus’ with a large
750-nm virion including a fibril-containing rigid surface layer(40). APMV possesses a 1.2-Mb linear dsDNA genome coding
for more than 1,000 genes (43, 65), which is more than those
encoded on the genomes of some small prokaryotes. It isclassified as a member of nucleocytoplasmic large DNA
viruses (NCLDVs), the proposed order “Megavirales” (17),together with various giant viruses discovered after APMV
(6, 45, 46, 63, 78). The unexpected dimensions and complexityof APMV and other exotic giant viruses triggered the reassessment of differences between cellular and viral life forms(66), fueled debates on the origin of viruses (14, 54, 56), andrevived interest in re-defining the concept of viruses (13, 15, 27).
Phylogenetic studies have indicated multiple origins of APMV
genes; some APMV genes appear to be of viral origin, whereas
others appear to originate from cellular organisms (23, 24, 55,71) or unknown sources (i.e., ORFans). Despite the apparent
mosaicity of its complex genome, one coherent finding thatemerges from these studies is that the origin of APMV lineage
is old, being as ancient as the emergence of the Eukarya
domain in the Tree of Life (65). In particular, the ancientorigin of APMV and related giant viruses has been supportedby phylogenies of replication- and transcription-related genes(1, 72, 77, 89). The antiquity of giant viruses further inspired
hypotheses of a putative “Fourth Domain of Life”, althoughthese are still highly controversial (7, 16, 44, 57, 59, 83, 90).
Since the discovery of APMV, numerous APMV relatives

have been isolated using amoeba co-culture from different
environments including marine sediment, river, soil, contact
lens liquid, and sewage water (2, 31, 41, 88). These viruses
are subdivided into lineage A, B and C mimiviruses (88). Theseamoebal mimiviruses, together with additional giant viruses
infecting microzooplankton, such as Cafeteria roenbergensis
virus (CroV) (25) and Bodo saltans virus (19) as well as
Klosneuviruses recently identified in metagenomes (71),
constitute the family Mimiviridae officially approved by theInternational Committee on Taxonomy of Viruses (ICTV).
Shortly after the discovery of APMV, algal viruses isolated in
the sea, such as Chrysochromulina ericina virus (CeV) andPyramimonas orientalis virus, were found to form a strongly
supported monophyletic group with APMV based on DNA
polymerase phylogenies (28, 51, 52). Since then, the monophyletic group has grown with the inclusion of Phaeocystis
globosa virus (PgV) (69), Aureococcus anophagefferens
virus (AaV) (53), Haptolina ericina virus (HeV RF02), andPrymnesium kappa viruses (PkV RF01 and PkV RF02) (34)
as well as metagenome-assembled Organic lake phycodnaviruses (OLPV1 and OLPV2) (86) and Yellowstone lake
mimivirus (YSLGV) (91). Some of these viruses are officially,
but inappropriately, classified in the Phycodnaviridae family.
Arslan et al. proposed to reassign the family “Megaviridae”
to the monophyletic group that combines the above mentioned
mimiviruses, zooplankton giant viruses, and algal giant viruses(2). Gallot-Lavallée et al. recently proposed to classify mimiviruses and microzooplankton giant viruses of the Megaviridae
family into the subfamily “Megamimivirinae” and the algal
viruses into the subfamily “Mesomimivirinae” (29). The tentative Megaviridae family is the focus of the present study
and it is this proposed Megaviridae nomenclature that we use
henceforth.

* Corresponding author. E-mail: ogata@kuicr.kyoto-u.ac.jp;
Tel: +81–774–38–3274; Fax: +81–774–38–3269.

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163

Taxon Richness of Megaviridae

Megaviridae constitutes approximately 36% of giant
viruses in epipelagic oceans, with their abundance being in
the order of 103 to 105 genomes mL–1 sea water (32). A recent
metatranscriptomic study also demonstrated that members of
Megaviridae are active everywhere in sunlit oceans and infecteukaryotic communities of various size ranges from piconanoplankton (0.8–5 μm) up to mesoplankton (180–2,000 μm) (9).
The hosts of isolated Megaviridae are still limited to a handfulof eukaryotic lineages, but already encompass an extremely
wide range of unicellular eukaryotes, including Amoebozoa,
Stramenopiles (Cafeteriaceae and Pelagophyceae), Euglenozoa(Kinetoplastida), Haptophyceae (Phaeocystales and Prymnesiales),and Viridiplantae (Chlorophyta). Sequence similarity searches
between metagenomic sequences and known Megaviridae
genomes also indicated the existence of many uncultured
Megaviridae lineages in marine environments (32). Taken
together with the inferred antiquity of Megaviridae, thesefindings suggest that the host range of Megaviridae is markedly
wider than currently recognized, and species richness inside
the family Megaviridae may consequently be comparablewith that of protists, which undoubtedly represent the majorpart of eukaryotic species’ diversity.
DNA-dependent RNA polymerases (RNAPs) of cellularorganisms are multisubunit protein complexes, the structuresof which have been elucidated for all three domains of life
(Bacteria, Archaea, and Eukarya) (82). The number of subunits constituting the machinery differs across the domains oflife (50, 82). Among them, the two largest subunits (hereafterreferred to as Rpb1 and Rpb2) are both highly conserved andmostly encoded as single copy genes in the three domains oflife, although eukaryotes commonly possess distant paralogs(33). Rpb1 and Rpb2 of eukaryotes correspond to the RNA
polymerase β’ and β subunits of bacteria, and to the RpoA
and RpoB of archaea, respectively (39, 80, 81). Archaeal
RpoA is composed of two subunits encoded by two small
genes. Rpb1 and Rpb2 have been selected as two of the 102
genes suitable for the assessment of phylogenetic relationships among prokaryotes (i.e., 102 Nearly Universal Trees)(38). Moreover, Rpb1 and Rpb2 are conserved in all known
members of Megaviridae (50). Transcriptomic and proteomic
studies have indicated that Rpb1 and Rpb2 are expressed
during infection and packed into mimivirus capsids (12, 42,
43, 67). Bacteriophages, such as T7 and SP6, encode singlesubunit RNAPs, which are phylogenetically unrelated tomultisubunit RNAPs (10, 74). Therefore, Rpb1 and Rpb2
possess the required characteristics to be used as phylogenetic markers for both Megaviridae and cellular organisms(65, 72). In the present study, we investigate the taxon richness (or lineage richness) and phylogenetic diversity (PD) of
Bacteria, Archaea, and Megaviridae based on Rpb1 and Rpb2
sequences found in marine microbial metagenomes derived
from prokaryotic size fractions.

and NCLDVs. We additionally used the GenomeNet/Virus-Host
Database (49) to retrieve the nucleotide sequences of Rpb1 and Rpb2.
Marine metagenomic sequence data were obtained from CAMERA(75) and the Tara Oceans project (32, 76) (Table S1). In addition, we
obtained metagenomic data for other non-marine environmentsfrom CAMERA and KEGG/MGENES (35). Collectively, we usedmetagenomic data derived from 58 projects (Table S1). Based on
metagenomic data, we initially prepared files for amino acidsequences for open reading frames (ORFs) that were longer than orequal to 150 codons. The total number of ORFs was 149,645,996:
marine metagenomes (101,856,227 ORFs, 68%), other aquatic
environmental metagenomes (8,385,210 ORFs, 5.6%), mammalassociated microbial metagenomes (38,341,510 ORFs, 26%), andother metagenomes (1,063,049 ORFs, 0.7%). Most of the analyses
presented in the present study focused on data from marine metagenomes, mainly derived from two large scale oceanic microbiome
projects: Tara Oceans and the Global Ocean Sampling project (68).
Data from other environments were used to confirm marine data.
Non-synonymous and synonymous substitution rate ratio
In order to estimate the level of functional constraint on Rpb1/
Rpb2 coding sequences, we computed the numbers of nonsynonymous (Ka) and synonymous (Ks) substitutions per site andtheir ratio (ω=Ka/Ks) using a maximum likelihood method implemented in the codeml program in the PAML package (85). We used
the Mann-Whitney U test to assess the significance of differences inω values between Megaviridae and bacterial sequences.
Reference sequence alignments and phylogenetic trees
We identified Rpb1 and Rpb2 homologs in the UniProt and
RefSeq databases using HMMER/HMMSEARCH (version 3.1;
E-value<1×10–5) (20) based on profile hidden Markov models that
we built from alignments of Rpb1 (COG0086) and Rpb2 homologs(COG0085) (30). We used CD-HIT version 4.6 to reduce the redundancy of the collected known Rpb1/2 sequences (47). The resulting
non-redundant sequences were aligned using MAFFT v7.215 (36)with default parameters and alignment columns containing gaps
were trimmed using trimAl v1.2rev59 (8). We referred to theresulting reference sequence alignments for Rpb1 and Rpb2 as
RAln-Rpb1 and RAln-Rpb2, respectively. We also generated reference sequence alignments solely composed of sequences from
Megaviridae, Bacteria, and Archaea, and referred to the alignments
as RAln-MBA-Rpb1 and RAln-MBA-Rpb2. Maximum likelihood
phylogenetic trees were constructed with the use of FastTree version
2.1.7 (64). The resulting reference trees for Rpb1 and Rpb2 werereferred to as RTree-Rpb1 and RTree-Rpb2, respectively. The
significance of the branches in the trees was assessed using the
Shimodaira-Hasegawa test (73) implemented in FastTree. Referencealignments and trees are available at the GenomeNet ftp site (ftp://
ftp.genome.jp/pub/db/community/RNAP_ref_tree).
Identification of RNAP homologs in metagenomes
In order to identify Rpb1 and Rpb2 homologs in metagenomic
sequence data, we used HMMER/HMMSEARCH (version 3.1) (20)with the default parameters and built 10 HMMs for Rpb1 and 10
HMMs for Rpb2, each of which represents a group of phylogenetically related sequences in our reference phylogenetic trees. Specifically,
these HMMs represent Megaviridae, other NCLDV groups 1 and 2(group 1: Asfarviridae, Poxviridae; 2: Ascoviridae, Iridoviridae,
Pandoravirus, Pithovirus), Bacteria, Archaea, Eukaryotes I to IV (I:RNAP I; II: RNAP II; III: RNAP III; IV: RNAP IV/V), and RNA
polymerases of plastids. We screened metagenomic data for the
Rpb1 and Rpb2 homologs (≥150 amino acid residues) using these
profile HMMs with HMMSEARCH (E-value<1×10–5).

Materials and Methods
Sequence data
We used the UniProt database (Release 2016_03) (79) and the
National Center for Biotechnology Information (NCBI) Reference
Sequence (RefSeq) (61) Viral Section (Release 75) database tocollect Rpb1 and Rpb2 protein sequences from cellular organisms

Taxonomic classification
Phylogenetic placement is a bioinformatics technique that is used
to identify the most likely phylogenetic position for a given query
sequence on a reference phylogenetic tree. Pplacer is one of the
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phylogenetic placement tools that efficiently analyze large numbersof sequences, including short metagenomic sequences, within linear
computation time (48). Metagenomic Rpb1/Rpb2 sequence fragments
were aligned on the reference alignments (i.e., RAln-Rpb1 andRAln-Rpb2) using HMMALIGN and placed on the reference phylogenetic trees (RTree-Rpb1 and RTree-Rpb2) using Pplacer with theuse of the maximum likelihood mode. These Rpb1 and Rpb2 fragments were taxonomically classified into the above-mentioned 10
phylogenetic groups based on their phylogenetic placement.
Taxon richness and PD
Metagenomic Rpb1/Rpb2 fragments that were taxonomicallyassigned to Megaviridae, Bacteria, or Archaea were re-aligned on
the RAln-MBA-Rpb1 or RAln-MBA-Rpb2 reference sequencealignments using HMMALIGN. Since metagenomic sequenceswere often shorter than full-length sequences in the reference alignments, we examined taxon richness (i.e., the number of sequence
clusters) (3) and PD (22) along the alignment using a 100-residue
sliding window on the alignments (with a step size of 10 residues).
Metagenomic sequences exhibiting gaps at >10% of the sites in thealignment window were discarded.
Taxon richness was computed based on sequence clustering by
the ucluster_fast command of USEARCH v7.0 (21) with three cutoff values for amino acid sequence identities (i.e., 70%, 80%, and90%). The significance of differences between richness curves wasassessed using a Log-rank test (70).
PD was calculated using Phylogenetic Diversity Analyzer (PDA)
version 1.0 (11), based on FastTree phylogenetic trees of metagenomic sequences that were aligned inside the sliding window. In
order for PD scores to be comparable between Megaviridae,
Bacteria, and Archaea, we constructed a phylogenetic tree with1,000 randomly selected sequences for each organism group andcalculated the PD score.

Fig. 1. Functional constraints on Megaviridae Rpb2 and Rpb1. Nonsynonymous (Ka) and synonymous (Ks) substitution rate ratios (ω=Ka/Ks) are plotted for Megaviridae and bacterial Rpb2 (A) and Rpb1 (B).
We selected pairs of orthologs from Megaviridae (shown in red dots)based on the following criteria: Ka>0.01, Ks<5.0, and the percent standard
error of ω being below 25%. These closely related pairs of viral genes
were all from amoeba infecting mimiviruses. We selected pairs of orthologs
between genes from Escherichia coli K-12 MG1655 and genes fromother bacteria (shown in blue dots) based on the following criteria:
Ka>0.01, Ks<10.0, and the percent standard error of ω being below
25%. ω values were significantly lower for Megaviridae than for bacterial
homologs, indicating a higher level of evolutionary constraint on
Megaviridae homologs.

sample sizes for Megaviridae were small (n=7 for Rpb2, n=3
for Rpb1).
Reference trees and taxonomic classification of metagenomic
sequences
We identified 59,938 Rpb2 and 40,534 Rpb1 homologs in
the UniProt/RefSeq sequence databases using profile HMMs
derived from COG0085 (Rpb2) and COG0086 (Rpb1). Viral
Rpb2/Rpb1 sequences identified by this search all originatedfrom NCLDVs. Among these sequences, 511 Rpb2 and 575
Rpb1 sequences were selected as reference sequences after
reducing redundancy by clustering and discarding unusuallylong and short sequences. Based on the reference sequences,
we built reference phylogenetic trees for Rpb2 (Fig. 2A) and
Rpb1 (Fig. 2B). The reference trees were generally consistent
with the classification of prokaryotes and viruses as well as
eukaryotic paralogs.
Using profile HMMs built from these reference sequences,248,101 and 252,609 sequences were obtained from metagenomes as candidates of environmental Rpb2 and Rpb1,
respectively. These environmental sequences were phylogenetically classified using the reference trees described above,and specific phylogenetic groups were successfully assigned
to 195,195 Rpb2 and 214,521 Rpb1 sequences (Table 1). The
taxonomic assignments were dominated by Bacteria (80% for
Rpb2, 81% for Rpb1), Archaea (5.7% for Rpb2, 6.6% forRpb1), and Megaviridae (10.2% for Rpb2, 6.1% for Rpb1) as
expected from the microbial size fractions (enriched withprokaryotic size organisms and viruses, Table S1) targeted bymost of the analyzed metagenomes. Most of the sequencesthat were taxonomically assigned to Megaviridae were foundin marine metagenomes (Rpb2: 18,633 [93.3%]; Rpb1: 12,225[93.0%]), which is consistent with the previous finding of thehigh abundance of Megaviridae in the sea (32). The detectionof eukaryotic sequences was limited (1,824 for Rpb2 and
1,276 for Rpb1 for RNA polymerase II from marine metagenomes) and likely biased towards picoeukaryotes due to the

RNAP paralogs in Megaviridae
Some of the sequenced viruses of Megaviridae, such as PgV (69),
OLPV1, and OLPV2, encode two distantly related Rpb2 in theirgenomes. In order to eliminate the effect of the presence of theseparalogs on the richness assessment of Megaviridae Rpb2, we classified Megaviridae Rpb2 metagenomic sequences into two paralogous groups based on phylogenetic reconstructions and performed
additional rarefaction analyses for each of the paralogous groups.

Results
Functional constraints on Megaviridae Rpb2 and Rpb1 arehigher than those on bacterial homologs
The functional constraint on a protein sequence may be
estimated by the ratio (ω) of non-synonymous (Ka) andsynonymous (Ks) substitution rates. A small ω value indicates
an elevated level of functional constraint (i.e., slow pace ofamino acid sequence evolution), while a large ω value, which
is typically smaller than 1 for a functional protein coding
sequence, indicates a low level of functional constraint (i.e.,fast amino acid sequence evolution). We computed ω values
for Megaviridae Rpb2/Rpb1 by comparing close homologs.
We also computed ω values for bacterial Rpb2/Rpb1 bycomparing genes of Escherichia coli K-12 MG1655 withthose of other closely related bacteria (Fig. 1). The average ωvalue for Megaviridae Rpb2 was 0.0205, while it was 0.0582
for bacterial Rpb2. The average ω value for Megaviridae
Rpb1 was 0.0105, while it was 0.0811 for bacterial Rpb1.
These results suggest that functional constraints on Megaviridae
Rpb2/Rpb1 were higher than those on bacterial homologs(P=0.00003 for Rpb2, P=0.003 for Rpb1); however, the
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Taxon Richness of Megaviridae

Fig. 2. Maximum likelihood phylogenetic trees of Rpb2 and Rpb1. The Rpb2 tree (RTree-Rpb2) was constructed using 511 representative
sequences (A), and the Rpb1 tree (RTree-Rpb1) with 575 representative sequences (B). Branches are colored as follows: Eukaryotes I-IV (orange),
Bacteria (blue), Archaea (green), Megaviridae (red), plastid (purple), and other NCLDVs (pink).
Table 1.

Number of taxonomically assigned metagenome sequences.
Environment

MarineOther aquatic

Mammal associated

Other

Total

Operational clade name

Rpb2

Rpb1

Rpb2

Rpb1

Rpb2

Rpb1

Rpb2

Rpb1

Rpb2

Rpb1

Eukaryote I
Eukaryote II
Eukaryote III
Eukaryote IV/V
Bacteria
Archaea
Megaviridae
Chloroplast
NCLDVs 1
NCLDVs 2
Total

690
1,824
729
82
111,124
10,177
18,633
2,540
119
1,135
147,053

741
1,276
854
54
125,874
12,826
12,225
7,666
80
1,484
163,080

16
77
17
7
6,387
640
1,330
27
20
126
8,647

14
28
10
5
6,740
784
841
455
6
110
8,993

82
78
68
0
38,192
56
10
91
19
4
38,600

109
108
101
3
39,798
102
79
1,159
9
2
41,470

0
4
0
0
588
300
0
2
0
1
895

2
2
1
0
625
341
0
5
0
2
978

788
1,983
814
89
156,291
11,173
19,973
2,660
158
1,266
195,195

866
1,414
966
62
173,037
14,053
13,145
9,285
95
1,598
214,521

filter size range. Therefore, we excluded eukaryotic sequencesin subsequent analyses and focused on Megaviridae, Bacteria,and Archaea sequences identified in marine metagenomic
data unless otherwise specified.

along the reference alignments. In order to generate OTUs,
clustering was performed with three amino acid sequence
identity thresholds (i.e., 90%, 80%, and 70% identities). Rpb2
and Rpb1 of Megaviridae showed a higher number of OTUs
than those of Bacteria or Archaea at all resampling levels at
each of the three arbitrarily selected sequence rich regions(Fig. 3 and Fig. S2A and S2B). Similar results were obtained
when metagenomic sequences from other environments, suchas freshwater and the human gastrointestinal tract, were
included (Fig. S2C and S2D), and confirmed along the entire
length of the reference alignments; Megaviridae exhibited alarger number of OTUs than the two cellular domains whatever the regions of Rpb2 and Rpb1 considered (Fig. 4A and
B). Log-rank tests indicated that differences in the number of
OTUs between Megaviridae and the two cellular domains
were significant (Fig. 4C and D).

Taxon richness of Megaviridae RNAP is greater than thoseof Bacteria and Archaea
The average lengths of the Rpb2 and Rpb1 reference
sequences were as follows: Megaviridae Rpb2 (1,239 aa) and
Rpb1 (1,392 aa); bacterial Rpb2 (1,282 aa) and Rpb1 (1,346 aa);archaeal Rpb2 (1,132 aa) and Rpb1 (1,373 aa). In contrast,
most of the metagenomic Rpb2/Rpb1 sequences were foundto be partial: Megaviridae Rpb2 (314 aa) and Rpb1 (314 aa);bacterial Rpb2 (292 aa) and Rpb1 (285 aa); archaeal Rpb2
(313 aa) and Rpb1 (303 aa). These sequences were aligned onreference Rpb2 and Rpb1 alignments (RAln-MBA-Rpb2 andRAln-MBA-Rpb1) composed of complete sequences from
Megaviridae, Bacteria, and Archaea (Fig. S1). We assessedtaxon richness by generating operational taxonomic units(OTUs) from sequences aligned inside a 100-aa window

Effects of the existence of Megaviridae Rpb2 paralogs
Rpb2 and Rpb1 were encoded as a single copy in most of
the sequenced bacterial and archaeal genomes; only 1.96%
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Fig. 3. Rarefaction curves of richness for metagenomic Rpb2/Rpb1 sequences. The X-axis indicates the numbers of resampled sequences for eachorganism group and the Y-axis indicates the average number of OTUs over 10 resamplings. Sequence clustering was performed using an 80% aminoacid sequence identity cut-off. Regarding each Rpb2 (A, C) and Rpb1 (B), three positions of the reference alignment were selected for comparisonsof taxon richness between Megaviridae (red), Bacteria (blue), and Archaea (green). In (C), the taxon richness of two paralogous groups of
Megaviridae Rpb2 (pink/orange) were assessed separately.

(Rpb2) and 2.97% (Rpb1) of bacterial, and 1.00% (Rpb2) and
1.00% (Rpb1) of archaeal genomes presented paralogs.
However, during the reconstruction of RNAP reference trees,
we noted that some Megaviridae, such as PgV and OLPV1/2,
encoded two copies of Rpb2 genes. The existence of theseparalogs may contribute to increasing the richness of thehomologous group of sequences, hence inducing bias intaxon richness interpretations. In order to investigate theevolutionary relationships of these paralogs, we reconstructed
Rpb2 trees, including metagenomic sequences, based on thesame three sequence rich sub-alignment regions. The resultsof these analyses revealed that the Rpb2 paralogs were only
distantly related in the reconstructed phylogenetic trees (Fig.
S3). A set of Rpb2 from PgV, OLPV1, and OLPV2 grouped
together, whereas another set of Rpb2 from the same viruses
formed another group. This tree topology strongly suggested
a single duplication event of Rpb2 in the ancestor of theseviruses. Therefore, the existence of Megaviridae Rpb2 paralogs
may lead to an approximately two-fold increase in apparent
richness. In order to obtain a more reasonable estimate for thetaxon richness of Megaviridae based on Rpb2 sequences, weclassified metagenomic Rpb2 homologs into two groups by
taking putative ancient duplication into account (Fig. S3A,
S3B, and S3C). Richness estimates and rarefaction curves forindividually analyzed paralogous groups still indicated alarger number of OTUs for Megaviridae than for Bacteria andArchaea at any given number of resampled sequences (Fig.
3C). Paralogs were not found for Rpb1, except for a pair of
Rpb1 sequences in AaV. Sequence identity between the AaV
Rpb1 sequences was 33%. These sequences were found to beclosely located in phylogenetic trees when metagenomic
Rpb1 sequences were included (Fig. S3D). Therefore, we
considered the influence of the paralogous Rpb1 groups on
the taxon richness estimate to be negligible.
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Taxon Richness of Megaviridae

Fig. 4. Richness for 1,000 metagenomic Rpb2/Rpb1 sequences along the length of reference alignments. The numbers of OTUs after the resamplingof 1,000 metagenomic sequences were plotted at each sequence region of Rpb2 (A) and Rpb1 (B). The significance (p-value) of differences between
Megaviridae and prokaryotes was assessed using the Log-rank test at each sequence region of Rpb2 (C) and Rpb1 (D).

Comparison of PD between Megaviridae and Bacteria/Archaea
PD is a measure of the diversity of phylogenetically relatedsequences, defined as the sum of all branch lengths in thephylogenetic tree (60). We calculated PD scores for Rpb2 andRpb1 sequences obtained from marine metagenomes using asliding window on the Rpb alignment RAln-MBA-Rpb2 andRAln-MBA-Rpb1 (Fig. 5). Megaviridae showed higher PD
scores than Bacteria and Archaea along the entire length of
the alignments.
The phylogenetic distribution of Megaviridae Rpb2
sequences on the reference tree indicated that a larger numberof metagenomic sequences mapped to Mesomimivirinae
subfamily branches (95.1%) than to Megamimivirinae subfamilybranches (4.6%) (Fig. 6). Among the Megamimivirinae
branches, a larger number of environmental sequences (275
sequences) mapped to the branch leading to CroV than to thebranches leading to Klosneuviruses (52 sequences) or amoebal
mimiviruses (37 sequences). A notable feature of the Rpb2
phylogenetic distribution was that the deeper the branches(i.e., the closer to the root), the higher the number of environmental sequences they got assigned: e.g. 5,414 sequences
mapped to the root of one of the Mesomimivirinae Rpb2,
whereas only 234, 259, 1,247, and 438 sequences mapped to
the leaves representing OLPV1, OLPV2, PgV, and CeV reference genomes, respectively.

Fig. 5. Phylogenetic diversity of metagenomic Rpb2/Rpb1 sequences
along the length of reference alignments. Phylogenetic diversity (PD)scores were computed with phylogenetic trees constructed using 1,000
metagenomic sequences at each sequence region of Rpb2 (A) and Rpb1
(B).

Discussion

metagenomes (58 projects) and classified them into taxonomic
groups using a phylogenetic placement method. Taxonomic
assignments revealed a large representation of bacterial

In the present study, we extracted environmental Rpb1 and
Rpb2 sequence fragments from a large set of microbial
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Fig. 6. Numbers of metagenomic sequences assigned to branches of Megaviridae Rbp2. This phylogenetic tree is part of the full phylogenetic tree
in Fig. 2A. The numbers in red squares are the numbers of sequences in the Megamimivirinae subfamily and those in purple are the numbers of the
Mesomimivirinae subfamily. The dashed branch lines near the root of the tree represent the status of AaV sequence not forming a monophyletic
group with the other members of Megaviridae in the full reference tree in Fig. 2A.

Rpb1/2 sequences (~80%) and fewer archaeal and Megaviridae
sequences (5–10%). Megaviridae sequences were preferentiallydetected from metagenomes originating from aquatic
environments. This is consistent with previous findings, althoughmembers of Megaviridae have been isolated from various
environments including oceans, lakes, rivers, air conditioning
cooling systems, drainage, and soil (41). The over-representationof bacterial Rpb1/2 sequences in metagenomes is expected
given their known dominance in various environments (26,32). When the same sequence similarity thresholds wereapplied for taxon delineation for cellular organisms and viruses,
Megaviridae showed significantly higher taxon richness thanBacteria and Archaea. As a more general measure that does
not require sequence identity thresholds, we also examined
PD. The PD indices of Megaviridae were also systematicallyhigher than those of Bacteria and Archaea.
A possible reason for why apparent taxon richness in the
Megaviridae is so vast could be a fast evolutionary rate in
Megaviridae. However, our results indicated that functional
constraints are higher for Megaviridae Rpb1/2 than forbacterial homologs. This result suggests that the rate ofsequence evolution is lower for Megaviridae Rpb1/2 than forbacterial homologs if their mutation rates are similar. BlancMathieu and Ogata (5) previously indicated that the mutation
rate of giant viruses may be as low as prokaryotes based on
Drake’s rule, postulating that “the mutation rate per genome
has evolved towards a nearly invariant value across taxa”, aswell as the finding that giant viruses encode many DNA
repair enzymes. A recent study monitoring more than one
year of experimental evolution consistently demonstrated
that the mutation rates of a giant virus, Lausannevirus, and abacterium remained similar over the length of the experiment(58). Therefore, the average mutation rate of Megaviridae
may be similar to that of prokaryotes.
Even if a high mutation rate potentially contributed toaccelerated evolution, fast evolution is not sufficient to
explain the prominent radiation of evolutionarily deep lineages
because radiation requires niche expansion (62). As a matterof fact, the richness of prokaryotes, which evolve faster thaneukaryotes, is less than that of eukaryotes in marine environments.
Recent studies revealed the presence of ~110,000 OTUs atthe species level for eukaryotic plankton in the global sunlit
ocean (18), but only 36,000–45,000 OTUs for prokaryotes inthe same type of environment (76, 92). The markedly hightaxon richness of Megaviridae revealed by our study parallels
the high richness of eukaryotes, the potential hosts of
Megaviridae. Based on the ancient origin of Megaviridae thathas been inferred to antedate the emergence of major eukaryotic
lineages, our results strongly support the Megaviridae family
having a phylogenetically deep and wide co-evolutionary
history with diverse marine protists. This virus-host co-evolution
may have been at work from the early “Big-Bang” radiation
down to the more recent diversification of the tree of eukaryotes.
In other words, the long history of the diversification of
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eukaryotes may have played a key role in the successive
niche expansion of Megaviridae. A similar co-evolutionary
history was also proposed for a family of RNA viruses (37).
Many of the Megaviridae sequences were placed in the
branches leading to Mesomimivirinae (Fig. 6), which are
currently represented by algae-infecting viruses, such as PgV
and CeV. The host range of algal species of this clade spansfrom Haptophyceae (Phaeocystales and Prymnesiales) toPelagophyceae and Chlorophyta, which are deeply separated
from one another in the eukaryotic tree. It is also important tonote that even haptophytes alone constitute a very rich groupof unicellular eukaryotes (18). Among the Megamimivirinae
subfamily, one of the most abundant lineages observed inmarine metagenomes was the microzooplankton infecting
CroV; however, since the deeper branches also received many
sequence assignments, the inference of potential hosts forthese sequences are difficult. Overall, the phylogenetic positions of these marine Megaviridae marker genes point to diverse
protists, including unicellular algae and microflagellates, as
the potential host of these uncultured Megaviridae. Although
the amoebal co-culture method (41) has permitted many new
mimiviruses to be analyzed, further efforts to isolate viruses
from diverse eukaryotes are desirable in order to increase thegenome sampling coverage of this diverse clade.
In the present study, we showed that the taxon richness of
Megaviridae exceeded that of the prokaryotic domains in theocean. Investigations on the as yet uncovered diversity of
Megaviridae will require the development of experimental
alternatives to virus isolation by co-culture method, which isa labor-intensive process depending on the culturability ofeukaryotic hosts. These methods include single cell genomics(87), single virus genomics (84), the development of degenerate
PCR primers, and a co-occurrence network analysis (32).

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Acknowledgements
This work was supported by The Canon Foundation (No.
203143100025), JSPS/KAKENHI (Nos. 16KT0020, 17H03850,
and 26430184), Scientific Research on Innovative Areas from the
Ministry of Education, Culture, Science, Sports and Technology(MEXT) of Japan (Nos. 16H06429, 16K21723, and 16H06437), andthe Collaborative Research Program of the Institute for Chemical
Research, Kyoto University (No. 2016-28, 2017-25). PH was supported by the OCEANOMICS “Investissements d’Avenir” programof the French government (No. ANR-11-BTBR-0008). Computational
work was completed at the SuperComputer System, Institute for
Chemical Research, Kyoto University. We thank the Tara Oceans
consortium, staff, and sponsors who supported the Tara Oceans
Expedition (http://www.embl.de/tara-oceans/) for making data
accessible. This is contribution number 72 of the Tara Oceans
Expedition 2009–2013.
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Microbes Environ. Vol. 32, No. 4, 300-313, 2017https://www.jstage.jst.go.jp/browse/jsme2 doi:10.1264/jsme2.ME17017

MOST CITED REVIEW PAPER IN THIS
THREE YEARS [2017-2019] (44 citations)

Minireview
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) andother 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* Corresponding author. E-mail: cnakatsu@purdue.edu;
Tel: +1 (765) 496–2997; Fax: +1 (765) 496–2926.

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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.

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 theMicrobiome 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 devel25

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Hillman et al.

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.

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.

Fungi
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

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
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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.

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

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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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

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
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Table 1.
StomachSmall intestine
Cecum
Appendix
Colon

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
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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)

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

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
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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).

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 that

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 in
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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.

Summary17.

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.

18.

19.
20.

21.
22.
23.

24.
25.

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3.
4.

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Microbes Environ. Vol. 28, No. 2, 244–250, 2013https://www.jstage.jst.go.jp/browse/jsme2 doi:10.1264/jsme2.ME12189

MOST CITED ORIGINAL PAPER IN THISTEN YEARS [2010-2019] (104 citations)

Candidatus Methanogranum caenicola: a Novel Methanogen from theAnaerobic Digested Sludge, and Proposal of Methanomassiliicoccaceae
fam. nov. and Methanomassiliicoccales ord. nov., for a Methanogenic
Lineage of the Class Thermoplasmata
TAKAO IINO1*, HIDEYUKI TAMAKI2, SATOSHI TAMAZAWA2,3, YOSHIYUKI UENO4, MORIYA OHKUMA1,
KEN-ICHIRO SUZUKI5, YASUO IGARASHI6, and SHIN HARUTA7
1Japan Collection of Microorganisms, RIKEN BioResource Center, 3–1–1 Koyadai, Tsukuba, Ibaraki 305–0074, Japan;
2Bioproduction Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Central

6, 1–1–1 Higashi, Tsukuba, Ibaraki 305–8566, Japan; 3Graduate School of Life and Environmental Sciences, Universityof Tsukuba, 1–1–1 Ten-noudai, Tsukuba, Ibaraki 305–8572, Japan; 4Kajima Technical Research Institute, 2–19–1
Tobitakyu, Chofu, Tokyo 182–0036, Japan; 5NITE Biological Resource Center (NBRC), National Institute of Technology
and Evaluation (NITE), 2–5–8 Kazusakamatari, Kisarazu, Chiba 292–0818, Japan; 6Department of Biotechnology,
Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1–1–1 Yayoi, Bunkyo-ku, Tokyo 113–8657,
Japan; and 7Graduate School of Science and Engineering, Tokyo Metropolitan University, 1–1 Minami-Osawa,
Hachioji-shi, Tokyo 192–0397, Japan(Received October 11, 2012—Accepted January 21, 2013—Published online March 23, 2013)

The class Thermoplasmata harbors huge uncultured archaeal lineages at the order level, so-called Groups E2 andE3. A novel archaeon Kjm51a affiliated with Group E2 was enriched from anaerobic sludge in the present study.
Clone library analysis of the archaeal 16S rRNA and mcrA genes confirmed a unique archaeal population in theenrichment culture. The 16S rRNA gene-based phylogeny revealed that the enriched archaeon Kjm51a formed a distinct
cluster within Group E2 in the class Thermoplasmata together with Methanomassiliicoccus luminyensis B10T andenvironmental clone sequences derived from anaerobic digesters, bovine rumen, and landfill leachate. Archaeon Kjm51ashowed 87.7% 16S rRNA gene sequence identity to the closest cultured species, M. luminyensis B10T, indicating thatarchaeon Kjm51a might be phylogenetically novel at least at the genus level. In fluorescence in situ hybridization
analysis, archaeon Kjm51a was observed as coccoid cells completely corresponding to the archaeal cells detected,
although bacterial rod cells still coexisted. The growth of archaeon Kjm51a was dependent on the presence of methanol
and yeast extract, and hydrogen and methane were produced in the enrichment culture. The addition of 2-bromo
ethanesulfonate to the enrichment culture completely inhibited methane production and increased hydrogenconcentration, which suggested that archaeon Kjm51a is a methanol-reducing hydrogenotrophic methanogen. Taken
together, we propose the provisional taxonomic assignment, named Candidatus Methanogranum caenicola, for theenriched archaeon Kjm51a belonging to Group E2. We also propose to place the methanogenic lineage of the class
Thermoplasmata in a novel order, Methanomassiliicoccales ord. nov.
Key words: Methanogranum caenicola, methanogen, Thermoplasmata, rice cluster III, anaerobic digested sludge

Until recently, the class Thermoplasmata had consistedof mainly acidophilic, aerobic, mesophilic to thermophilic,and sulfur-reducing archaea such as genera Acidiplasma(15), Ferroplasma (14), Picrophilus (47), Thermoplasma(4), Thermogymnomonas (28), and Candidatus Aciduliprofundum boonei (50). Archaeal members of those genera
mainly inhabit extreme environments such as acidic andsolfataric fields. On the other hand, culture-independent
approaches have retrieved a diverse array of environmentalclones belonging to the class Thermoplasmata from ordinary
environments, and many of these clones form huge uncultured
archaeal lineages at the order level, so-called Groups E2 andE3 (6, 33, 39). Groups E2 and E3 consist of sublineages
such as Marine group II, deep-sea hydrothermal ventEuryarchaeotic group 1 and 2 (DHVE1 and DHVE2), andrice cluster III (RC-III), which is derived from the alimentary
canal (12, 19, 54), anaerobic digester (13), contaminatedaquifer (8), deep-sea hydrothermal vent (40, 55), marine
plankton (5, 7), and rice field soil (3, 17, 30). More recently,
a uniformly shaped pure culture B10T, given the nameMethanomassiliicoccus luminyensis, was isolated fromhuman feces, and revealed to be a methanol-reducing,mesophilic, slightly alkaliphilic methanogen belonging to theclass Thermoplasmata (9). These findings suggest that theclass Thermoplasmata is a phenotypically versatile taxon;
however, very little is known about the phylogenetic diversity
and ecological distribution of methanogens in the class
Thermoplasmata.
In our previous study, members of RC-III within GroupE2 in the Thermoplasmata as well as Methanoculleus,
Methanosarcina, and Methanothermobacter species havebeen detected from methanogenic bioreactors (1, 21, 43, 44,46). To obtain cultures of those methanogens, we conducted* Corresponding author. E-mail: iino@jcm.riken.jp;
Tel: +81–48–467–9564; Fax: +81–48–462–4618.

38

Novel Methanogen in the Class Thermoplasmata

245with a pT7Blue T-vector kit (Novagen, Madison, WI, USA). The
clonal DNAs were amplified from randomly selected recombinantsby direct PCR with M13 primers, and then used as templates forsequencing. A universal primer 907r (56) and T7 promoter primers
were used for sequencing the cloned 16S rRNA and mcrA genes,
respectively. The obtained sequences of all the 16S rRNA geneclones (~690 bp) and the mcrA gene clones (~475 bp) were comparedwith those in the GenBank database using the BLAST program(NCBI-BLAST, www.ncbi.nlm.nih.gov/BLAST), and aligned using
the CLUSTAL_X program. Sequence identity of 99% was used as
the cut-off value for grouping the sequences into different
operational taxonomic units (OTUs).

enrichment cultures from methanogenic digester sludge andeventually succeeded in enriching a novel methanogenbelonging to Group E2 in class Thermoplasmata. Thus, thispaper deals with the phylogenetic characterization of theenriched methanogen in Thermoplasmata and the provisional
characterization of the phenotypes.
Materials and Methods
Sampling
The anaerobic sludge was collected from a methanogenic packedbed reactor at Kajima Technical Research Institute on 16th December
2004. The reactor, which was packed with carbon fiber textile assupporting media (43–45), had been properly operated at 55°C andwas stably producing methane gas from garbage slurry as feedstock.
The garbage slurry was prepared from kitchen waste from thecompany cafeteria. It was diluted with an equal amount of water
after removing non-biodegradable materials and then pulverizedusing a homogenizer. The physicochemical properties of the slurry
were as follows: pH 5.2; chemical oxygen demand (COD), approx.
203 g L−1; and volatile suspended solids (VSS), approx. 104 g L−1.

Phylogenetic analyses
Almost full-length 16S rRNA gene and partial mcrA genesequences were determined for phylogenetic analysis. The following
primers were used for sequencing the PCR product of the archaeal
16S rRNA gene: A10F, Kjm700F (5'-TGGGGTAGGGGTAAAATCCT-3'), Kjm1000F (5'-ACTCACCAGGGGAGACTGTT-3'),
A500R (5'-GTGTTACCGCGGCKGCTGG-3'), Kjm700R (5'-GTG
GTCCTTCTAGGATTACA-3'), and A1400R, that of the bacterial
16S rRNA gene: U520F (5'-GTGCCAGCAGCCGCGG-3') andU1492R, and that of mcrA gene: MR1mod and ME2mod. Sequenceswere compared using the BLAST program with those available in
the DDBJ/EMBL/GenBank databases. Phylogenetic analyses werecarried out using the 16S rRNA gene sequence and deduced aminoacid sequence of the mcrA gene. The 16S rRNA gene sequenceswere aligned with an ARB data set using ARB software (32).
According to the previously described method (27), thirty-fivereference sequences of the phylogenetically related archaea andenvironmental clones were selected as authentic sequences locatedin the class Thermoplasmata. The data set of deduced McrA aminoacid sequences was aligned using the CLUSTAL_X program.
Phylogenetic trees were constructed by the neighbor-joining (NJ)
method with the CLUSTAL_X program (42, 57) and the maximumlikelihood (ML) method with MORPHY software version 2.3b3(10, 20). In addition, the posterior probabilities of branching points
were estimated by Bayesian inference using MrBayes 3.1 (23, 41).

Enrichment from the sludge
The basal medium was used with or without 0.01% (w/v) yeast
extract (Becton Dickinson, Franklin Lakes, NJ, USA), designated
YB and B media, respectively, in this study. Basal medium wascomposed of (L−1): 0.54 g NH4Cl, 0.14 g KH2PO4, 0.20 g
MgCl2·6H2O, 0.15 g CaCl2·2H2O, 2.5 g NaHCO3, and 1.0 mL
trace element solution (58) containing 4.0 mg Na2WO4·H2O andeliminating NaCl. Prior to inoculation, the pH of the medium wasadjusted to 7.0 with 6 N HCl, dissolved oxygen was removed byflushing with N2:CO2 (4:1, v/v), and 10 mL vitamin solution (L−1)(60) and 10 mL sterile stock solution of Na2S/cysteine-HCl solution(each 50.0 g L−1) (26) were added. H2:CO2 (4:1, v/v; approx. 150kPa), formate, acetate, or methanol (all at 10 mM) was added tothe basal medium as the sole substrate. For enrichment, 0.5 mL
anaerobic sludge was inoculated into 20 mL of each medium andincubated at 30°C for a week. A stable enrichment culture wasobtained after three cultivations in MYB medium, YB medium
supplied with methanol. The enrichment culture was maintained in
MYB medium by consecutive transfer monthly.

Fluorescence in situ hybridization
The enriched archaeon Kjm51a grew on the aforementioned
MYB medium for 8 d. The harvested cells were fixed in 4%
paraformaldehyde at 4°C for 2 h and stored in 99% ethanol–
phosphate-buffered saline (1:1). The fixed cells were incubated in
hybridization buffer (0.9 M NaCl, 0.01% sodium dodecyl sulfate,
20 mM Tris-HCl, pH 7.2, and an appropriate amount of formamide)containing fluorescently labeled probes (0.5 pmol µL−1). Afterincubation at 46°C for 10 h, the buffer was replaced with washingsolution (378 mM NaCl, 0.01% sodium dodecyl sulfate, 20 mM
Tris-HCl, pH 7.2, and 5 mM EDTA). The sample was incubated at
46°C for 20 min. and then stained with 1 µg mL−1 of 4',6-diamidino2-phenylindole (DAPI). The sample obtained was observed undera confocal laser scanning microscope (LSM710; Carl Zeiss
Microscopy, Tokyo, Japan). A specific oligonucleotide probetargeting the 16S rRNA gene of the enriched archaeon Kjm51a(RC281r2, 5'-AAGGCCCATACCCGTCATC-3') was designed
using the Probe Design tool of the ARB software package (32). The
overall Gibbs free energy of this probe and target sequence calculatedwith the mathFISH web server was −9.2 kcal mol−1 (62). The probes
were labeled with fluorescent dye, Alexa Fluor 555 (Japan Bio
Services, Saitama, Japan). Two domain-specific probes were also
used: EUB338 labeled with Alexa Fluor 647 for detection of almost
all bacteria (2), and ARC915 labeled with Alexa Fluor 488 fordetection of almost all archaea (53). The stringency of hybridization
was adjusted by adding formamide to the hybridization buffer (15%[v/v] for all the probes used in this study). More than 8,000 DAPIstained cells were counted to determine the ratio of ARC915hybridized cells to EUB338-hybridized cells.

Preparation of DNA, PCR amplification, and DNA sequencing
The genomic DNA was extracted from the enrichment culture
and purified as described previously (49). The archaeal and bacterial
16S rRNA genes were amplified by PCR using the following
primers: A10F (5'-TCYGGTTGATCCYGCCRG-3') and A1400R(5'-ACGGGCGGTGTGTGCAAG-3') for the domain Archaea,
U27F and U1492R (25) for the domain Bacteria. The PCR mixture(50 µL) contained 1×PCR buffer, 3.5 mM MgCl2, 10 mM
deoxynucleoside triphosphates (dNTPs), 1.25 U AmpliTaq Gold(each from Applied Biosystems, Foster City, CA, USA), and 0.4µM of each forward and reverse primer. Approximately 100 ng
genomic DNA was used as a template under the following cycling
conditions: initial AmpliTaq Gold activation at 95°C for 9 min,followed by 30 cycles of denaturation at 95°C for 30 s, annealing
at 56°C for 30 s, extension at 72°C for 1.5 min, and a final extension
step at 72°C for 5 min. The mcrA gene encoding the alpha-subunitof methyl-coenzyme M reductase was also partially amplified by
PCR with primers MR1mod and ME2mod (35) under almost thesame PCR conditions except for its cycle number (40 cycles) andtime of extension step (1 min) in the cycle. The PCR product was
purified using the QIAquick PCR purification kit (Qiagen, Hilden,
Germany), and sequenced using the BigDye terminator v3.1 cycle
sequencing kit with a 3130xl genetic analyzer (both from Applied
Biosystems).
Clone library
The purified archaeal 16S rRNA and mcrA genes were cloned
39

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IINO et al.

Physiological characteristics
Growth conditions were determined using MYB medium. Aerobic
and microaerobic conditions were prepared by the substitution of
air and the addition of 2% (v/v) oxygen, respectively, with filtration
through a 0.2 µm-pore membrane filter. Prior to inoculation, acetate,lactate, or pyruvate (all at 10 mM) were added as carbon sources
instead of yeast extract. 2-Bromo ethanesulfonate (BES, final
concentration 20 mM) was added as the inhibitor of methane
production. Then, 0.2 mL of the preculture of the enrichment was
inoculated into 20 mL fresh medium containing each substrate. The
culture was incubated at 30°C for two weeks. After the transfer
twice, hydrogen and methane concentrations in the headspaces ofserum bottles were determined with a gas chromatograph (GC-14A;
Shimadzu, Kyoto, Japan) equipped with a thermal conductivity
detector and a porapack Type Q 80–100, mesh 80–100 (Waters,
Tokyo, Japan). The analysis conditions were as follows; column
temperature, 60°C; injector temperature, 80°C; and detector temperature, 100°C; current, 80 mA; carrier gas, N2.
Fig. 1. Phylogenetic affiliation of the enriched archaeon Kjm51a
within Group E2 in the class Thermoplasmata on the basis of the 16S
rRNA gene sequences. The tree was constructed using the neighborjoining method. Solid circles at branching nodes indicate supporting
probabilities above 95% by all the phylogenetic analysis methods(NJ, ML, and Bayesian), and open circles indicate probabilities above
85% by two or more analyses. Bar, 0.02 substitutions per nucleotide
position.

Accession numbers
The 16S rRNA gene and mcrA gene sequences of the enrichedarchaeon Kjm51a have been deposited in the DDBJ/EMBL/NCBI,
and GenBank nucleotide sequence databases under accession
numbers AB749767 and AB749768, respectively.

Results
Methanogenic enrichment cultures from anaerobic sludge
A methanogenic enrichment culture was obtained fromanaerobic digester using MYB medium containing methanol
and yeast extract. The archaeal population in the culture
was analyzed using archaeal 16S rRNA gene- and mcrA
gene-specific primers. A total of 113 and 61 clones wereobtained, respectively. A sole phylotype was obtained in bothclone libraries, i.e., all the cloned 16S rRNA gene and mcrA
gene sequences in the two libraries were almost identical to
the sequence identities of 99.4–100% and 99.5–100%,
respectively.
An almost full-length 16S rRNA gene sequence (1,309 bp)
was determined for a novel archaeon, designated phylotype
Kjm51a, in the enrichment culture. In the phylogenetic treesof the 16S rRNA gene sequences constructed using NJ, ML,
and Bayesian methods, the enriched archaeon Kjm51a wasplaced into an uncultured archaeal lineage, Group E2, in theclass Thermoplasmata (6) (Fig. 1). The topologies of thetrees generated by the three phylogenetic analysis methods
were almost identical, and were supported by high bootstrap
values (99–100%). Archaeon Kjm51a was a member of RCIII, a sublineage within Group E2, and showed the highest
sequence similarities (91.3–96.2%) to the environmentalclones derived from anaerobic digesters, bovine rumen, andlandfill leachate (13, 22, 54, 61). The nearest cultivatedneighbor of archaeon Kjm51a was Methanomassiliicoccus
luminyensis B10T with 87.7% sequence identity. A partial
mcrA gene sequence (1,109 bases) was also determined forthe enriched archaeon Kjm51a. The NJ tree constructedusing the McrA amino acid sequence deduced from the mcrA
gene sequence demonstrated that archaeon Kjm51a formeda monophyletic cluster together with M. luminyensis B10T
and environmental clone sequences derived from anaerobic
bioreactor and bovine rumen (Fig. 2), and that the cluster
was apparently distinct from the four known methanogenic
lineages, the classes Methanobacteria, ‘Methanomicrobia’,Fig. 2. Deduced McrA amino acid sequence-based phylogeny
showing the phylogenetic relationships among the enriched archaeon
Kjm51a, its related archaeon and environmental clones, and otherknown methanogens. Solid circles at branching nodes indicate
supporting probabilities above 95%, and open circles indicate probabilities above 80%. Bar, 0.02 substitutions per nucleotide position.

Methanococci, and Methanopyri. The McrA amino acidsequence of the enriched archaeon Kjm51a showed 76.0%
identity with that of the closest species, M. luminyensis B10T.
Coccoid- and rod-shaped cells were observed under the
microscope. The cocci and rods were identified as archaealand bacterial cells, respectively, by fluorescence in situ
hybridization with archaeal and bacterial probes (Fig. 3A and
B). A ratio of archaeal cells to total cells was at least 3.5±1.4%
in the enrichment culture. Cocci were hybridized with a
Kjm51a-specific probe, but rods were not (Fig. 3C). Cells
hybridized with the Kjm51a-specific probe completely corresponded to those with the archaeal probe (Fig. 3B and D).
The bacterial rods in the enrichment culture were provisionally identified as Clostridium celerecrescens (sequence40

Novel Methanogen in the Class Thermoplasmata

247

Discussion
The novel archaeon Kjm51a was successfully enrichedfrom anaerobic sludge using MYB medium containing
methanol and yeast extract. The archaeon was not yet purified
in this study because C. celerecrescens was dominantly
isolated in the presence of yeast extract, although we madea great effort to isolate the archaeon using agar plate culture
and dilution-extinction culture. Clone library analysis demonstrated that cloned 16S rRNA and mcrA gene sequences
obtained from the enrichment culture were almost identicalin each. Furthermore, FISH analysis also showed that coccal
cells hybridized with a Kjm51a-specific probe completely
corresponded to those with an archaeal probe. These findings
strongly support the archaeal purity of the enriched archaeon
Kjm51a in MYB medium, although bacterial cells still
coexisted.
The enriched archaeon Kjm51a was a strictly anaerobic
and chemoheterotrophic cocci showing growth and methane
production in the presence of methanol, the inhibition of
methane production by BES, a well-known inhibitor ofmethanogenesis (18). Hydrogen production was also
observed in the absence of methanol, which indicated thatthe coexisting bacterium, C. celerecrescens, produced hydrogen by its fermentation (38). Inhibition of methane production
by BES resulted in increased hydrogen production. Thesephysiological properties suggest that the enriched archaeon
Kjm51a might be a methanol-reducing hydrogenotrophic
methanogen.
As reported for Methanosphaera stadtmanae (34),
Methanomicrococcus blatticola (51), and Methanosarcina
barkeri strain Fusaro (36), the enriched archaeon Kjm51a
is likely to produce methane by the hydrogen-dependent reduction of methanol through the following reaction: H2+
CH3OH → CH4+H2O (11, 29, 52, 59). Methanomassiliicoccus
luminyensis, a recently isolated methanogen from humanfeces, belonging to Group E2, also produced methane frommethanol in the presence of hydrogen (9). The genome of
M. luminyensis likely encodes only a partial methanogenesis
pathway (16). Most recently, archaeon MpT1 in Group E2
was enriched from termite guts as a methanogen, whichconverted methanol to methane (39). Methanol may be acommon substrate for methanogenesis in Group E2. Schink
and Zeikus reported that heterotrophic microbes anaerobically
produced methanol as a major end product from pectin, which
is a component of plant tissue (48). Biodegradation of plants
occurs in a wide variety of environments, such as the rumen,
rice field soil and anaerobic digester treating garbage, andGroup E2 methanogens may contribute to carbon flux.
The enriched archaeon Kjm51a is the first culture representative derived from an anaerobic methanogenic digesterin Group E2. In the phylogenetic trees constructed using 16SrRNA gene sequences, the archaeon Kjm51a and M.
luminyensis B10T were completely separated in Group E2
with their low sequence identity (87.7%), which was
sufficiently low to classify them into different genera. The
enriched archaeon Kjm51a and M. luminyensis B10T wereaffiliated with RC-III, one of the sublineages in Group E2.
RC-III was clearly and completely separated from the validly
described order Thermoplasmatales. Its monophyletic lineage

Fig. 3. Epifluorescence micrographs of in situ hybridization of theenrichment archaeon Kjm51a grown on MYB medium for a week. The
same microscopic field is shown after hybridization with a Kjm51aspecific probe (red), an archaeal probe ARC915 (green), and a bacterial
probe EUB338 (blue). A, blue color; B, green color; C, merge of red,green and blue colors; D, red color. Bars, 10 µm.

Fig. 4. Methane and hydrogen production in the enrichment culture
obtained from anaerobic sludge. Filled bars, methane; open squares,hydrogen. Data points and bars are the means and standard deviations,
respectively (n=3). Abbreviations: MYB, MYB medium supplied withmethanol in YB medium; YB, YB medium; MYB+BES, MYB
medium supplied with BES; ND, not detected.

identity: 99.9%, X71848) by bacterial 16S rRNA genesequence analysis.
Physiological property of the enriched archaeon Kjm51a
The enriched archaeon Kjm51a was strictly anaerobic andwas capable of growing in MYB medium under a N2/CO2(4:1 [v/v]) atmosphere, but could not grow under microaerobic or aerobic conditions. Both methanol and yeast extract
were required for the growth of archaeon Kjm51a. Acetate,lactate, and pyruvate were not utilized as carbon sources
instead of yeast extract. Metabolic products of the enrichment
culture with methanol and yeast extract were hydrogen andmethane, and that with yeast extract and without methanol
was hydrogen (Fig. 4). Growth of the enriched archaeon
Kjm51a in the presence of methanol and its methane
production were completely inhibited by the addition of BES.
The amount of hydrogen in the presence of BES wasapproximately three times higher than that in the absence of
BES.
41

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IINO et al.

pl. n. Methanomassiliicoccaceae family of the genus
Methanomassiliicoccus).
The family Methanomassiliicoccaceae is defined on thebasis of a phylogenetic tree constructed by phylogenetic
analysis of the 16S rRNA gene sequence of a single cultivatedrepresentative, of the enriched culture, and of environmentalclone sequences derived mainly from the alimentary canal,
anaerobic digester, landfill leachate, and rice field soil. The
type genus is Methanomassiliicoccus.

was strongly supported by the probability scores (>99%)
calculated using all the phylogenetic analysis methods. The
16S rRNA gene sequence of the enriched archaeon Kjm51aand M. luminyensis B10T had similarities of only 77.1 to80.3% with those of the known archaeal species in the order
Thermoplasmatales. These similarities are lower than the
85% similarity that is generally used as a cut-off value
for distinguishing lineages at the phylum, as suggested by
Hugenholtz et al. (24). Therefore, RC-III composed ofthe enriched culture Kjm51a and M. luminyensis B10T is adistinct order level lineage in the class Thermoplasmata.
Previously, Kemnitz et al. (30) reported that the RC-III
archaea might heterotrophically grow using peptides, basedon their enrichment culture experiment; however, taken
together with the recent study (6), our findings clearly
indicated that RC-III is a novel methanogenic lineage.
In conclusion, an archaeal representative enriched fromthe anaerobic methanogenic digester is a novel methanogenbelonging to RC-III within Group E2 in the class Thermoplasmata. According to the recommendations of Murray andStackebrandt (37), we propose the provisional taxonomic
assignment of Candidatus Methanogranum caenicola forthe enriched archaeon Kjm51a. Most recently, the order
Methanoplasmatales was provisionally proposed for the
deep-branching lineage accommodating M. luminyensis andthe enriched archaea MpT1 and MpM2 (39); however, thislineage should be proposed as the Methanomassiliicoccales
on the basis of Rule 47a of the Bacteriological Code to
avoid bacteriological confusion (31). Consequently, we
propose to rename the order ‘Methanoplasmatales’ as
Methanomassiliicoccales for the sublineage accommodating
M. luminyensis B10T and the enriched archaeon Kjm51a as
described below. The proposal of this novel order follows
the description of the new family Methanomassiliicoccaceae.
To purify the enriched archaeon Kjm51a and understand its
ecological role in the methanogenic environment, further
study via enrichment culture will be necessary.

Description of Methanomassiliicoccales ord. nov.
Methanomassiliicoccales (Me.tha.no.mas.si.li.i.coc.cal’es.
N.L. neut. n. Methanomassiliicoccus type genus of the order;-ales ending to denote an order; N.L. fem. pl. n. Methanomassiliicoccales order of the genus Methanomassiliicoccus).
The description is the same as that for the family
Methanomassiliicoccaceae. The type genus is Methanomassiliicoccus.
Acknowledgements
The authors thank Dr. Hiroyuki Imachi (Japan Agency for MarineEarth Science & Technology) for helpful discussions on several
aspects of the paper.
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44

MOST CITED REVIEW PAPER IN
THIS TEN YEARS [2010-2019] (120 citations)

Microbes Environ. Vol. 26, No. 2, 101–112, 2011

http://wwwsoc.nii.ac.jp/jsme2/ doi:10.1264/jsme2.ME10179

Minireview
The Ecology, Biology and Pathogenesis of Acinetobacter spp.: An Overview
HAMUEL JAMES DOUGHARI1*, PATRICK ALOIS NDAKIDEMI1, IZANNE SUSAN HUMAN1, and SPINNEY BENADE1
1Applied Sciences Faculty, Cape Peninsula University of Technology, P.O. Box 652 Cape Town 8000, South Africa(Received October 9, 2010—Accepted February 16, 2011—Published online March 18, 2011)

Acinetobacter are a major concern because of their rapid development of resistance to a wide range of antimicrobials, and rapid profundity in transformation, surviving desiccation and persistinge in the environment for a very longtime. The organisms are associated with bacteraemia, pulmonary infections, meningitis, diarrhea and notorious nosocomial infections with mortality rates of 20 to 60%. Transmission is via person-to-person contact, water and foodcontamination, and contaminated hospital equipment. The increasing virulence and rapid development of multidrug
resistance by these organisms highlights the need to search for alternatives for chemotherapy. A poor understandingof the organisms and dearth of information about their occurrence especially in developing countries informed theneed for this review paper.
Key words: Acinetobacter, acinetobactins, biofilms, coccobacilli, ecology, taxonomy

Introduction

Recent taxonomy

The name “Acinetobacter” originates from the Greek word
“akinetos” meaning “unable to move”, as these bacteria
are not motile yet they display a twitching kind of motility.
Bacteria of the genus Acinetobacter have gained increasing
attention in recent years first, as a result of their potential
to cause severe nosocomial (Greek nosos disease, andkomeion to take care of) infections (6, 7, 62, 63, 85, 108, 112,117), second, for their profundity in developing multidrug(MDR) and extreme drug resistance (XDR) (5, 56, 86, 91,115) third, for the ability of some strains to produce
verotoxins (VA) (48), and fourth, for the role members of thegenus play in enhanced biological phosphorus removal in
wastewater (16, 43, 80). Recently, Acinetobacter spp. havedemonstrated a hydrocarbon-degrading capability (74, 75,122), that is of interest for soil bioremediation and a specificstrain Acinetobacter baylyi ADP1 has shown remarkablecompetence for natural transformation irrespective of DNA
source, thus making it a potentially important tool for biotechnology (2, 19, 111, 112). Possible suggested applicationsof Acinetobacter spp. are summarized in Table 1.
In addition, since the environment, soil, and animals are
their natural habitats, food and water contamination exposes
humans to infections. The ability of these bacteria to colonize almost any surface and to acquire antibiotic resistancedistinguishes them from other infectious bacteria. Despite
the huge increase in the frequency of infections caused by
MDR Acinetobacter, there is still a lack of awareness of theimportance of these microorganisms (30). This review therefore gives an overview of the biology, ecology and medicalsignificance of the entire genus Acinetobacter in a broad
sense with a view to providing basic general information on
this group of bacteria for a better understanding and the possible adoption of proactive and effective control measuresagainst infections associated with some of the bacteria.

The first strain of Acinetobacter spp. was isolated
from soil and identified as Micrococcus calcoaceticus byBeijerinck in 1911 (2, 13). Acinetobacter group werepreviously insufficiently defined for a very long time andconfusedly classified into more than a dozen different genera(Achromobacter, Alcaligens, Cytophaga, Diplococcus,
Bacterium, Herellea, Lingelsheimia, Mima, Micrococcus,
Moraxella and Neisseria) (2, 15, 27, 90, 97).
The genus Acinetobacter was first created in 1954 by
Brisou and Prevot to separate the non motile from the
motile members of the tribe “Achromobactereae” and wascomposed of non-pigmented Gram-negative saprophytic bacteria comprising both oxidase-negative and oxidase-positive
species. In 1957, Brisou identified a typical species named
Acinetobacter anitratum (15). Baumann et al. (3) using
distinct nutritional properties later characterized the organisms as oxidase-negative and proposed to classify themunder the genus Acinetobacter. In 1971, the subcommittee on
Moraxella and allied bacteria accepted this proposal andthe genus was limited to oxidase-negative strains (71).
Three species were initially included in this genus but
because of difficulties in distinguishing them based on
differences in physiological characteristics, all the species
were named A. calcoaceticus (2). In fact, Bergy’s Manualof Bacteriology placed these bacteria in the family
Neisseriaceae with only A. calcoaceticus as a species andthe two subspecies A. anitratum and Acinetobacter lwofii(59). Several years later, Bouvet and Grimont (12) identified
more than fifteen genomic species, including Acinetobacterbaumannii (formerly A. calcoaceticus var anitratum and A.
glucidolytica non liquefaciens), Acinetobacter haemolyticus,
Acinetobacter junii, Acinetobacter johnsonii and Acinetobacter radioresistens (12, 13, 27).
The species’ names have undergone considerable taxonomic changes over the years as molecular methods haveadvanced understanding of the genetic make-up of this groupof organisms (109). Recent classifications which seem

* Corresponding author. E-mail: jameshamuel@yahoo.com;
Tel: +27–7–3355–0274, Fax: +234–703–559–9712.

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DOUGHARI et al.
Table 1. Possible applications for Acinetobacter spp. and their products

Bioremediation ofwaste waters andeffluents

Bioremediation of soils andeffluents contaminatedwith heavy metalsi) Phosphate removali) Textile or tannery industrial
effluent containing heavy
metalsii) Lead from digested
sewage sludgeiii) Chromium-contaminatedactivated sludge or
wastewateriv) Silver contaminatedphotographic wastewaterii) Degradation of
petrochemicalsiii) Breakdown oforganic pollutants

Production of biopolymers
and biosurfactanti) For prevention of dental
plaqueBiomass productioni) Protein productionii) For use in paper-makingii) Manganese leachingand other industries
from oresiii) For efficient emulsification iii) Production of immuneof oil waste pollutants
adjuvants

Clinical usesi) Production of
glutaminase-sparaginaseii) Production of L(−)
carnitineiv) For incorporation incosmetics, detergents andshampoos(82, 107)

to have gained wide acceptance among bacterial taxonomists have recognized this group of heterogeneousbacteria as gamma proteobacteria classified in the order
Pseudomonadales and the family Moraxellaceae (13). Thus
the taxonomical classification is given as; Domain—Bacteria,
Phylum—Proteobacteria, Class—Gammaproteobacteria,
Order—Pseudomonadales, Family—Moraxellaceae, Genus—Acinetobacter (DNA G+C content 39–47%) and species(with A. baumannii, A. haemolyticus and A. calcoaceticus
as species of clinical importance). Recent classifications
using cell shape, absence of flagella, G+C content of
DNA and nutritional properties, placed these organisms (A.
baumannii, A. haemolyticus and A. calcoaceticus as well asother Acinetobacters) in the genus Moraxella, now known
as Acinetobacter (2). Based on DNA-DNA hybridization
studies, 32 species of Acinetobacter have now been recognized, with 22 assigned valid names and the rest assigned
numbers and referred to as a ‘genomic group’ (42, 91).
Among the named species, A. baumannii is the main species
associated with clinical infections followed by the non-A.
baumannii species A. haemolyticus, A. junii, A. johnsonii and
A. lwofii (2, 49). Recently, the emergence of other speciesof clinical importance such as A. ursingii and A. schindleri
has been reported (95).
Another difficulty associated with classification is theclose resemblance between species such that phenotypic
differentiation becomes very difficult. For instance, there is a
close relationship between A. baumannii and A. calcoaceticus,
and genomospecies 3 and 13. As a result of the difficulties indistinguishing isolates phenotypically in the former pair, theterm A. baumannii-A. calcoaceticus complex or Abc complex has been used. Furthermore, some authors still reportthese isolates as A. calcoaceticus subspecies anitratum.
This situation led to contributors to the Manual of ClinicalMicrobiology to conclude that the majority of species of thisgroup of bacteria cannot be reliably distinguished based on
phenotypic tests (13, 37, 94, 102).
To avoid confusion therefore, a more reliable classification based on combination of the results of DNA-DNA
hybridization and on phenotypic characteristics was adopted(2). In clinical practice however, these taxonomic complications have led to the under-recognition and misclassificationof the species.

Biology, cultural and biochemical characteristics of the
Acinetobacter group
The genus Acinetobacter consists of strictly aerobic, nonmotile, catalase-positive, indole-negative, oxidase-negative,
Gram-negative, non-fermentative encapsulated coccobacillirods (13, 111). Many strains are unable to reduce nitrates tonitrites (9). The bacteria are strictly aerobic and although
they flourish on most laboratory media at temperatures of
20–30°C with the clinical isolates growing at 37 to 42°C, formost strains the optimum temperature is 33–35°C. In the
exponential phase of growth, they are bacilli 0.9 to 1.6 μm in
diameter and 1.5 to 2.5 μm in length, often in pairs or assembled into longer chains of varying length. Acinetobacter spp.
are non-fastidious and can be grown on standard laboratory
media (64). On blood agar (BA), colonies show typical morphology and size: Non-pigmented, white or cream colored,smooth or mucoid (when capsule is present), opaque, 1–2
mm in diameter (after 18–24 h incubation at 37°C) (9), on
eosin methylene blue agar (EMB), colonies are bluish tobluish gray, on Herellea agar (HA) they are pale lavender incolor (9), while on Leeds Acinetobacter Medium (LAM) the
bacteria are pink on a purple background. In aged cultures
the bacteria may be spherical or filamentous. The organisms
can be recovered after enrichment culture from virtually all
samples obtained from soil or surface water (85). The members of the Acinetobacter group are nutritionally versatile
chemoheterotrophs and the range of substrates they use assole carbon and energy sources parallels that of the aerobic
pseudomonads.
The cell wall of Acinetobacter is typical of that of Gramnegative bacteria, however de-staining is difficult due to atendency to retain crystal violet and this can lead to incorrect
identification as Gram-positive cocci (1). The cells of
Acinetobacter vary in size and arrangement. Acinetobacter
generally form smooth and sometimes mucoid colonies onsolid media, ranging in color from white to pale yellow orgrayish white. Some environmental strains have beenreported to produce a diffusible brown pigment (1, 85).
Several clinical isolates show hemolysis on sheep blood agar
plates (85).
Pathogenesis, virulence factors and resistance
Pathogenesis. In the past, Acinetobacter spp. were con46

Ecology of Acinetobacter spp.

103

wounds or surgical trauma, and purulent lesions of the eye.
The organisms are ranked 9th after S. aureus, E. coli,
Klebsiella spp. P. aerugenosa, C. albicans, Enterococci,
Serratia and Enterobacter as agents of nosocomial BIs, andaccount for 34% of the mortality and 43% of deaths due tohospital-acquired infections (29). They are the second mostcommonly isolated nonfermenters in human specimens (81),after Pseudomonas aeruginosa and their incidence is on theincrease and mortality rates are quite high (56, 111, 119). A.
baumannii was found to be associated with a series of fatal
cases of community pneumonia (29) and A. haemolyticus,
with endocarditis and verotoxin production, and hence
bloody diarrhea (11, 17, 47).
Pathogenic mechanisms. The pathogenic mechanisms ofAcinetobacter spp. are little understood or studied (84).
Though the infective doses of Acinetobacter in human infections have yet to be determined, intraperitoneal injections inmice with 40 clinical isolates of Acinetobacter showed theLD50 to range from 103 to 106 viable cells per mouse(82). Though A. baumannii is the most studied species,
the precise mechanisms involved in the establishment andprogression of infections by this species are unclear. The
organism is not known to produce either diffusible toxins
or cytolysins, and few virulence factors have been identified (45). However, comparative genomic studies with A.
baumannii and the environmental A. baylyi have identified genes involved in pilus biogenesis, iron uptake andmetabolism, quorum sensing and a type IV secretion system
as making up part of the organism’s ‘virulome’ (106, 111).
Other authors have also reported common virulence factors among the Acinetobacters which are discussed below.
There is a need for microbiologists to further investigate
these virulence mechanisms for possible discovery of more
effective control measures.
Virulence factors. i) Cell surface hydrophobicity andenzymes: Acinetobacter spp. have been demonstrated to
exhibit cell surface hydrophobicity, an important determinant bacterial adhesion. For a successful infection to occur,bacteria must successfully adhere to host cells (24). The
hydrophobicity of a microorganism protects it from being
phagocytosed and appears to play an important role in its
attachment to various polymers. Hydrophobicity also confers
the ability to adhere to plastic surfaces, such as cathetersand prostheses. Through this hydrophobicity, Acinetobacter
spp. coaggregate into flocs in sludge. Non-flocculating A.
johnsonii S35 displays significant coaggregation with threeother bacterial species, Oligotropha carboxidovorans,
Microbacterium esteraromaticum, and Xanthomonas
axonopodis (76). The degree and mechanism of coaggregation were found to be pair-dependent; and cell surfacehydrophobicity was an important factor controlling thecoaggregation of A. johnsonii S35 and its partner strains (76,89). The hydrophobic properties of bacterial strains dependon their surface structure, which in turn determines thedegree of hydrophobicity: the rougher the cell surface, thegreater the hydrophobicity and vice versa. In Acinetobacter,the presence of protein protrusions on the cell surface confershydrophobicity. A recent study using scanning electron
microscopy showed the presence of blister-like protein protrusions on A. johnsonii S35 and A. junii S33, these bacterial

sidered saprophytes of little clinical significance (7), but with
the introduction of powerful new antibiotics in clinical practice and agriculture and the use of invasive procedures in
hospital intensive care units (ICUs), drug resistant-related
community and hospital-acquired Acinetobacter infections
have emerged with increasing frequency (49). A. baumannii
is an important emerging nosocomial pathogen worldwide,
followed by A. lwofii and A. haemolyticus. Conditions attributable to Acinetobacter spp. include blood stream infections(BIs), ventilator-associated pneumonia (VAP), bacteremia,
meningitis, urinary tract infections, cholangitis, peritonitis,skin and wound infections, ventriculitis, and infective
endocarditis (10, 56, 117). The bacteria can also colonize theskin and respiratory tract without causing an infection. An
infection results if the host first line of defence is compromised. Studies have however, revealed that colonization
increased with hospital stays (82). In gastroentistenal infections with A. lwoffıi and H. pylori infections for example, thenormal tissue architecture of the gastric epithelium is alteredleading to chronic gastritis (Fig. 1). Infections with A.
lwoffıi induce production of pro-inflammatory cytokines
which increase gastrin levels that in turn promote proliferation of the gastric epithelium. Persistent inflammation
including the activation of antigen-presenting cells (APCs),
release of pro-inflammatory cytokines such as macrophage
chemotactic protein (MCP), macrophage inflammatory protein (MIP), Toll-like receptor (TLR), somatostatin (SOM),
reactive oxygen species (ROS) involved in acid secretion(Fig. 1) and changes in the number of gastric epithelial cells
can lead to gastritis, peptic ulcers, and more rarely, gastriccancer (94). Though colonization occurs more frequently
than infections, studies have also shown that lethal infections
result from pathogenic strains in immunosuppressed animals
with mortality rates of 75 to 100% (96). The bacteria havealso been associated with bacteremia, sepsis in neonatal
intensive care units and pediatric oncology units, as well as
community acquired meningitis and endophthalmitis (25,106, 110). Other conditions include suppuration; abscessesof the brain, lung, and the thyroid, secondary infections ofFig. 1. Schematic model of bacterial colonization of the gastricmucosa, activation of antigen presenting cells (APC), release of proinflammatory cytokines and alteration in the number of gastricepithelial cells involved in acid secretion. MCP, macrophage chemotactic protein; MIP, macrophage inflammatory protein; TLR, Toll-likereceptor; SOM, somatostatin; ROS, reactive oxygen species (92).
(Reproduced with permission, copyright Elsevier).

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those of verotoxins from E. coli and other bacteria (65). The
emergence of verotoxin-producing A. haemolyticus strains isworrisome given the high transformability of Acinetobacter
spp. This therefore calls for intensive surveillance of theseorganisms especially in the environment for the developmentof proactive control measures. The current work therefore
focuses on isolation and identification of A. haemolyticus
from environmental samples and the determination of theirverotoxin production and antimicrobial resistance profiles aswell as the effect of phytochemical extracts on verotoxin
production by the isolates.
iv) Siderophores: Siderophores are host iron-binding protein structures responsible for iron up take in bacteria.
One possible defense mechanism against bacterial infections
is the reduction of free extracellular iron concentrations via
iron-binding proteins such as lactoferrin or by transfer (14,121). The normal concentration of free iron in the body is10−8 M, and the concentration required for bacteria to survive
in the human body is 10−6 M. Bacteria meet their iron
requirement by binding exogenous iron using siderophores
or hemophores (61, 72, 121). Bacterial siderophores arecalled aerobactins. Acinetobacter siderophores are called
acinetobactins and are chiefly made up of the amine histamine which results from histidin decarboxylation (78). Iron
import into the bacterial cell is however regulated by a ferric
regulator uptake protein serving as a transcription repressor
to induce siderophore synthesis or degradation (111).
v) Outer membrane proteins (OMPs): Outer membraneproteins (OMPs) in some Gram-negative bacteria are known
to have essential roles in pathogenesis and adaptation inhost cells as well as in antibiotic resistance. Several OMPsof the OmpA family have been characterized in various
Acinetobacter strains (28, 45). Vila et al. (115) reported
homology between the genome sequence of OmpA of A.
radioresistens, A. baumannii and A. junii. The OmpA proteins induce apoptosis of epithelial cells (21), stimulating
gastrin and interlukin B gene expression (55). In a recent
study, Vallenet et al. (111) showed that A. baylyi OmpA
has emulsifying activity and that only one gene in each
Acinetobacter strain encodes an OmpA protein. In otherwords, these proteins share more than 89% of their aminoacids and thus have the same chromosomal context. The cellsof Acinetobacter spp. are surrounded by OmpA, a protein tokill host cells (20). During an infection, OmpA binds toeukaryotic cells and gets translocated into the nucleus where
it causes cell death (20, 28, 99).
Resistance to antibiotics and mechanisms of resistance.
The major problem with Acinetobacter spp. is their resistance to antibiotics (66, 67). Savov et al. (101) reported thatthese organisms are most commonly resistant to ampicillin,
cephalothin, carbenicillin, gentamicin, amikacin, chloramphenicol, tetracycline, co-trimoxazole, ciprofloxacin andcefoperazone. Previously ampicillin, second generation
cephalosporins, quinolones, minocyline, colistin, amynoglycosides, impenim, sulbactam and gentamicin were used totreat Acinetobacter infections. Resistance to these antibiotics
has hindered therapeutic management, causing growing concern the world over (32, 47, 87, 91, 115). A. baumannii has
been developing resistance to all antibiotics used in treating
infections. Currently, most A. baumannii strains are resistantcells were able to coaggregate efficiently with other bacterial
cells compared to a mutant strain A. johnsonii IAM1517
with smooth cell surfaces (89) which was unable to form
aggregates (89).
Surface hydrophobicity is also mediated by colonization
factors, complimentary cell surface receptors, fimbriae andother cell wall components (14, 60) and cell surface enzymes
that facilitate the adhesion of bacterial cells to host cells.
For example, the urease activity of Acinetobacter promotes
colonization of the mouse stomach (24). Urease also helps
Acinetobacter spp. colonize the hypochlorhydric or achlorhydric human stomach inducing inflammation (100). Polysaccharide slimes on the bacterial cell surface are reported toconfer hydrophobicity (53, 61 93, 97). Other virulenceconferring enzymes secreted by the bacteria include esterases,
certain amino-peptidases, and acid phosphatases (93, 108).
Esterases have strong hydrolyzing activity against shortchain fatty acids, thereby causing damage to lipid tissues.
Hydrolytic enzymes usually confer the bacterium with verystrong hemolytic activity. The most extensively studiedhydrolytic enzymes in Ps. aerugenosa are phospholipases C(PLC)-H, which is encoded by plcS, is acidic and has strong
hemolytic activity, and PLC-N, which is encoded by plcN, isbasic, and has no hemolytic activity (93). Recent studies
revealed that two copies of the phospholipase C (plc) genewith 50% identity to that of Pseudomonas are found in A.
baumannii. It is therefore assumed that these lipases serve asimilar function, although this is yet to be elucidated (111).
Hoštacká and Klokočníková also reported the secretion ofphosphotidylethanolamine and sphingomyelin which are allcytotoxic to leucocytes (53).
ii) Toxic slime polysaccharides: Toxic slime polysaccharides have also been reported among Acinetobacter spp. (53).
They are usually produced during the exponential phase of
growth and are made up of the glucose building blocks Dglucuronic acid, D-mannose, L-ramnose and D-glucose. The
slime polysaccharides are toxic to neutroplils, and inhibit
their migration as well as inhibit phagocytosis, but without
disrupting the host immune system (50, 53). It is importantto understand these structures in order to develop effective
control measures. Currently, the authors are focusing on
determining the hydrophobicity of A. haemolyticus isolates
from water and wastewater samples and the effect of stressand phytochemical extracts on this hydrophobicity.
iii) Verotoxins: Grotiuz et al. (47) first reported the
production of verotoxins in Acinetobacter (from A.
haemolyticus). Verotoxins are associated with bloody diarrheas and produced by many enteric bacteria including E.
coli and Shigella dysenteriae (31). The toxins belong to aparticular protein subfamily, the RNA N-glycosidases which
directly target the cell ribosome machinery, inhibiting protein synthesis. Verotoxins can be classified into 2 antigenic
groups, vtx-1 and vtx-2, which include (especially vtx-2) an
important number of genotypic variants. The mechanism bywhich A. haemolyticus produces this toxin is, however, notwell understood. Lambert et al. (65) speculated that A.
haemolyticus acquires vtx2-producing activity via horizontal
gene transfer in the gut lumen, since it can be rapidlytransformed. In any case, the pathogenicity, basic structure,and chemical components of the toxins are the same as48

Ecology of Acinetobacter spp.

105

sides via aminoglycoside-modifying enzymes; quinolones byaltering the target enzymes DNA gyrase and topoisomerase
IV through chromosomal mutations, a decrease in permeability and increase in the active efflux of the drug by the microbial cell (67). Several efflux pumps acting against antibiotics
have been described for Acinetobacter spp. grouped as (i)major facilitator superfamilies (MFSs) comprising the Tet(A)-efflux system for tetracycline, Tet (B)-efflux system fortetracycline and minocycline and Caml A-efflux system forchloramphenicol, (ii) resistance-nodulation division (RND)
comprising Ade ABC (ATP binding cassettes)—efflux systems against aminoglycosides, β-lactams, chloramphenicol,
erythromycin, tetracyclines, ethidium bromide, and reduced
susceptibility to fluoroquinolones and (iii) multi drug andtoxic compounds extrusion systems (MATEs) comprising of
Abe M—efflux system against norfloxacin, ofloxacin, ciprofloxacin, gentamicin, 4,6-diamino-2-phenylindole (DAPI),
triclosan, acriflavin, doxocrubicin, rhodamin 6G and ethidium bromide (114). Major mechanisms of resistance to dif-to aminoglycosides, tetracyclines, cephalosporins, ampicillins,
cefotaximes, chloramphenicols, gentamicins and tobramycins (91). The activity of carbapenems is further jeopardized by the emergence of enzymatic and membrane-based
mechanisms of resistance (85).
Antimicrobial resistance among Acinetobacter is either
intrinsic or acquired via transformation. Several mechanismsof resistance including altered penicillin-binding proteins,
low/decrease permeability of the outer membrane to antibiotics or increase in the active efflux of the antibiotics, target site mutations, and inactivation via modifying enzymes
have been reported (56, 115). Mechanisms of resistance toantibiotics by Acinetobacter spp. vary with species, the typeof antibiotic, and geographical location (56). Thus β-lactam
antibiotics are inactivated by the production of β-lactamases
or alterations of penicillin-binding proteins and decreased
permeability of the outer membrane to β-lactams (92); cephalosporins by chromosomally encoded cephalosporinases
and occasionally, by cell impermeability and aminoglyco-

Table 2. Major mechanisms of resistance identified for the different classes of antibiotics
Antimicrobial class/resistancemechanismβ-Lactamβ-Lactamases

Carbapenemases

OMP loss
Efflux pump
Altered PBP expression
Tetracyclines
Efflux pump
Ribosomal protection
Glycylcyclines
Efflux pump
Aminoglycosides
Enzymatic degradation

16S rDNA methyltransferases
Quinolones
DNA gyrase/topoisomerase mutations
Efflux pumps
Chloramphenicol
Efflux pumps

Trimethoprim/sulfamethoxazole
Efflux pumpDihydropteroate synthase
Dihydrofolate reductase
Macrolides
Efflux pumps
Polymyxins

Class/family

Intrinsic cephalosporinase
Class A/high-prevalence ESBLAClass A/low-prevalence ESBLAClass D OXA enzymes/ESBLM–D
Class D OXA enzymes/ESBLCARBA-D,
MBLs/ESBLCARBA-B,
Class A carbapenemase/ESBLCARBA-A
CarO, HMP-AB, 33–36 kDa protein, 43 kDa protein
AdeABC

Variants

AmpC (ADC1–7)
VEB-1, -2, PER-1, -2, TEM-92, -116,
SHV-12, -5, CTX-M-2, -3
SCO-1
OXA-51-like
OXA-23–27, -37, -40, -58like, VIM, IMP, SIM
GES-11

PBP2 downregulation
MFS, RND

A, TetB, AdeABC
TetM

RND

AdeABC

Acetyltransferases
Nucleotidyltransferases
Phosphotransferases

AacC1/2, AadA, AadB
Ant1
AphA1, AphA6,
ArmA

RND, MATE, BIMP

GyrA/ParC
AdeABC, AdeM, AbeS

RND
MFS
BIMP

AdeABC, AdeIJK
CmlA, CraA
AbeS

RND

AdeABC, AdeIJK
SulI/II
FolA

MATE, BIMP
PmrAB two-component mutation

AbeM, AbeS

MBL—metallo-β-lactamase; OMP—outer membrane protein; HMP—heat modifiable protein; PBP—penicillin-binding protein; MFS—major
facilitator superfamily; RND—resistance–nodulation–cell division; MATE—multidrug and toxic compound extrusion; BIMP—bacterial integral
membrane proteins (46).

49

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DOUGHARI et al.

compliments is however yet to be discovered.

ferent classes of antibiotics are listed in Table 2.
Owing to this escalation of multidrug resistance, deliberate efforts should be made towards investigating othersources of antibiotics with novel mechanisms of action,with a view to developing effective control measures against
the recalcitrant bacteria. Investigations of phytochemicals
should be considered since they form a very rich source ofantibiotic substances (32) with potential activity against
microbial pathogens.
Resistance to environmental and host factors. The emergence of nosocomial or community-acquired infections ofAcinetobacter is a result of high adaptability to adverse
environmental conditions, an ability to persist for several
days in dry and harsh environments such as the hospitalenvironment, the increased use of broad spectrum antibiotics, the vulnerability of individuals or patients, andthe rapid transformation of organisms that results in increased multidrug resistance. To survive and multiply inthe host, many bacteria produce a variety of substancesthat allow them avoid the defense mechanisms of the host(58). Acinetobacter spp. are found as natural inhabitantsof human skin and repeated isolation may suggest thatthey are potential pathogens. Acinetobacter spp. are able tosurvive on moist and dry surfaces (118) and some strains
have been found to be tolerant of soap (9, 56). The abilityof Acinetobacter to persist in dry conditions, on inanimate
objects, and in dust for several days and weeks has been reported. Recent isolates of A. lwoffii compared to the isolates
from the 1970s are relatively resistant to irradiation. This
raises concerns about the persistence of A. lwoffii on
medical devices that are sterilized by gamma irradiation,
especially in intensive care units (ICU) (93).
Acinetobacter species also survive exposure to the commonly used disinfectants like chlorhexidine, gluconate andphenols, particularly those not used in the appropriate concentrations (40). Compared with other genera of Gramnegative bacilli, Acinetobacter is able to survive much betteron fingertips or on dry surfaces when tested under simulated
environmental conditions (118). Apart from being able togrow at a very broad range of temperatures, they are alsoable to resist drying. The presence of more electron dense
cell walls and nucleic acids are thought to be responsible
for the heat (50–75°C) resistance (56). In fact, while Ps.
aerugenosa and E. coli can only survive heat for a maximumof 24 h, A. baumannii can survive for up to 25 days (58).
Survival for 157 days (A. radioresistens), over 30 days (A.
baumannii) and 21 days (A. lwoffii) has been reported (54,57, 88). A. baumannii has also demonstrated resistance tothe killing action of normal human serum (NHS) and thepossession of a lipopolysaccharide was thought to be partly
responsible (42). King et al. (61) also suggested modulationof pathogen interaction with serum by a complement regulator. The complement system is the host innate immune
defense comprising a series of serum proteins that initiates
the death of the bacterium through either lysis or opsonization. One of the mechanisms by which bacterial cells resist
killing by serum compliments is by producing surface proteins that bind human factor H (FH), and thereby inhibit thedeposition of complements on the bacterial surface (41, 63).
The mechanism by which Acinetobacter spp. resist serum

Transfer of resistance among Acinetobacter spp.
Resistance to antibiotics is transferred among Acinetobacter spp. via plasmids and transposons. While plasmids
are DNA elements that carry antibiotic and heavy metal
resistance conferring genes capable of autonomous replication, transposons are sequences of DNA that can move (ortranspose) themselves to new positions within the genome ofa bacterium (or any other prokaryotic cell). These elements
are often present in resistant bacteria and have been reported
in clinical isolates of Acinetobacter spp. (40). Plasmids andtransposons are easily transferred between bacteria via theprocess of genetic transformation. Transformation occurs
between Acinetobacter spp. Due to the high frequency anddegree of adaptability and transformability among somestrains of Acinetobacter spp., species capable of colonizing
multiple settings can mediate the transfer of novel antibiotic
resistance genes from antibiotic-producing environmental
species to clinical isolates. For example, an intermediategroup including spp. 7, 8, and 9 is capable of adapting tohuman tissues as well as remaining in the environment thus
serving as effective vehicles for conveying resistance genes
between species (93). Gene transfers in Acinetobacter spp.
also occur via conjugation and transduction. Conjugation in
Acinetobacter involves a wide host range and chromosomaltransfer, while transduction involves a large number ofbacteriophages with a restricted host range (93). Owing to
the high transformation ability of Acinetobacters, the role ofgenetic elements in the virulence of this group needs to bethoroughly investigated and adequately understood as in thecase of E. coli. This will no doubt open up more frontiers
for more effective control measures and the application of
the organisms in biotechnology.
Epidemiology and ecology
Several studies have reported the epidemiology of A.
baumannii infections in different parts of the world including
Europe, the United States and South America (64, 104).
Although these organisms are often associated with nosocomial (117) infections, community acquired diarrhea
outbreaks and pneumonia have been reported with somefrequency in tropical regions of the world especiallyduring warm (summer) and humid months (18, 56). An infrequent manifestation of Acinetobacter is nosocomial meningitis and these cases have been reported after neurosurgicalprocedures (18, 56, 58). The morbidity and mortality
rates of Acinetobacter infections are comparable to those ofmethicillin-resistant Staphylococcus aureus (MRSA), andthe organisms have been termed ‘Gram-negative MRSA’,
manifesting similar epidemiological behavior to MRSA. The
impact in terms of morbidity and mortality is probably closer to that of coagulase-negative staphylococci and available
data suggest that the mortality rate ranges from 20% to60% (58). Thus several reports have alerted clinicians to theemergence of a potentially difficult and dangerous organism that is responsible for outbreaks of infection and cancause severe problems (58). Owing to the morphological50

Ecology of Acinetobacter spp.

107

Food contamination. Acinetobacter spp. have been associated with food contamination. Several foods including
vegetables have long been known to be an important sourceof contamination with Gram-negative bacteria such as
Escherichia coli and Klebsiella spp. (85). Acinetobacter spp.
have been recovered from vegetables, apples, melons, cabbages, cauliflowers, lettuce, cucumbers, peppers, mushrooms, radishes, carrots as well as tubers such as potatoes
and cereals such as sweet corn (10, 85). Acinetobacter spp.
have also been implicated in the spoilage of bacon, chicken,
meat, fish and eggs even when stored under refrigeration orafter adequate gamma irradiation (84, 108). Hospital food
could also be a potential source of A. baumannii (10, 108).
Many strains isolated from foods have lipolytic activity andsome strains produce diffusible pigments.
Soil and wastewaters. Water and soil also provide a home
to various microorganisms. Acinetobacter genomospecies
3, A. baumannii, A. calcoaceticus acinetobacters, and A.
calcoaceticus, A. johnsonii, A. haemolyticus, and Acinetobacter genomic species 11 have been reported to inhabit soil
and aquatic environments (86). The organisms have also
been isolated from freshwater ecosystems; raw sewage andwastewater treatment plants (10) and activated sludge (16,83, 85). A. baylyi, A. bouvetii, A. grimontii, A. tjernbergiae,
A. towneri, and A. tandoii are commonly found in naturalenvironments but occasionally isolated in activated sludge
and have not been found associated with humans (19, 85).
They are able to store phosphate as polyphosphates and may
have potential applications in the biological removal ofphosphates (2).
Biofilms. Biofilms are composed of microorganisms attached to surfaces and encased in a hydrated polymericmatrix made of polysaccharides, proteins and nucleic acids(100, 113). Biofilms function in a manner similar to tissues,
using a primitive circulatory system to pump fluids andnutrients through channels in the matrix by changing theionic strength of the extracellular milieu, causing periodic
contraction of matrix polymers.
Pilus mediated biofilms (PMBs) are formed by Acinetobacter spp. especially A. baumannii, A. haemolyticus, A.
lwoffii and A. calcoaceticus thus forming thin layers of
microorganisms on glass, medical devises, metals, ceramics
and other inanimate objects (28, 39). The biofilm thus constitutes a colonial niche for the bacteria from where contact
with humans will result in infection. The hydrophobic
surface polysaccharide and pili on the bacterial cell surface
initiates adherence to human epithelial cells thus initiating
the infection process (28).
Life in biofilms provides microbes with protection against
assault from the outside world with barriers against penetration by antimicrobial agents, oxygen and nutrients, alongwith depressed growth rates and an activated adaptive stressresponse (99). It also enables the organisms to resist theimmune host response. Vidal et al. (90) and Lee et al.
(113) reported the readiness of A. baumannii to adhere toboth biological and abiotic surfaces, on which it is able toform biofilms thus ensuring its survival (69, 112).
Unlike in other bacteria where the formation of biofilms
is facilitated by intrinsic factors such as the presence of typeIV pili, flagella, curli and fimbriae, in Acinetobacter spp.,

similarity between Acinetobacter and Neisseriaceae (bothbeing Gram-negative diplococci), care should be taken while
examining the Gram stain. Neisseria meningitidis is, however,
far more common as an agent of meningitis. Uncommon
conditions involving Acinetobacter are contiguous osteomyelitis, peritonitis associated with continuous ambulatory
peritoneal dialysis, ophthalmic infection, skin and wound
infections, abscesses, sepsis, endocarditis and burn infections. Despite the increasing significance of Acinetobacter,there are no significant epidemiological reports on the incidence of infections from many parts of the world particularly, developing countries. Epidemiologic investigations
on Acinetobacter spp. of clinical significance other thanA. baumannii as well as on the epidemiology of acinetobacteriosis in developing countries are essential.
Acinetobacters are mostly free living saprophytes foundubiquitously in nature (111). However, different species of
the genus are generally associated with different habitats.
Acinetobacter genomospecies 3 is found in water and soil, on
vegetables, and on human skin; A. johnsonii and A.
haemolyticus are found in water, wastewater, soil, on humanskin, and in human feces; A. lwoffii and A. radioresistens arefound on human skin; and Acinetobacter genomic species 11
is found in water, in soil, and on vegetables as well as thehuman intestinal tract (10, 26).
Human and animal body. Acinetobacter spp. are generally considered part of the normal flora of the skin andmucous membranes or the pharynx, human respiratory
secretions, urine, rectum (116) and other human clinicalsamples (101). They are the only group of Gram-negative
bacteria that may be natural residents of human skin, withcarriage rates of 42.5% in healthy individuals and as highas 75% in hospitalized patients (101). In a study conductedby Seifert et al. (103) Acinetobacter spp. were isolated fromvarious parts of the human body including the forehead,nose, ear, throat, trachea, conjunctiva axilla, hand, groin,
vagina, perineum and toe web. The organisms are also foundin the distal urethra of healthy people (63). Generally
the species most frequently isolated are A. johnsonii, A.
lwoffii, A. radioresistens, A. baumannii, A. calcoaceticus,
A. haemolyticus and Acinetobacter genomospecies 3 and13. Colonization of the intestinal tract by Acinetobacter
spp. however, is controversial. While some authors suggestthat it is an unusual event (46), others report that the gastrointestinal tract is the most important reservoir of resistantstrains (23). The difference is probably due to the epidemiological situation i.e. whether there is an epidemic outbreakor not.
Acinetobacter spp. have been isolated from different
animal sources including birds; fish and rainbow trout (10,49). On several occasions, chicken septicemia (15% deathrate), septicemia in turkeys and calves, mastitis and metrititis
in cows, abortions in cattle, pigs and horses, keratoconjunctivitis in cattle, omphalitis in calves, ear infections in cats,and respiratory infections and Balanoposthitis in horses havebeen reported (38). A. beijerinkii and A. baumannii areamong the species of Acinetobacter implicated in animal
diseases (38). The organisms have also been isolated fromlice collected from homeless people (68).
51

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DOUGHARI et al.

and versatile Acinetobacters are in terms of growth on
media. A wide range of media has been employed incultivating organisms from different sources. For routine
clinical and laboratory investigations, traditional methods
have used agar (34), brain heart infusion agar (108), nutrient
agar, tryptic soy agar (9), Simon’s Citrate agar (29) Violet
red bile agar, Luria Bertani agar (49) Eosin-methylene
blue, MacConkey agar and Holton medium (34). For
environmental screening, especially where Acinetobactermay be in very low numbers, Bauman’s’ Enrichment
Medium has been employed (13, 49) and broths including
MacConkey broth, trypton soy broth, Brain Heart Infusion
broth (49) and Luria broth (29, 63). Highly contaminated samples are inoculated in a liquid mineral medium containing asingle carbon source and ammonium or nitrate salt as the nitrogen source with the final pH of the medium being 5.5 to 5.6(63). Shaking during the incubation is employed in order forthe strictly aerobic acinetobacters to outgrow pseudomonads.
The broths can later be transferred onto Eosin-methylene
blue, MacConkey agar or a selective medium such as Herellea
agar or Leeds Acinetobacter Medium in which antibiotics
have been added to suppress the growth of other bacteria(51, 108).
Biochemical typing methods include the use of colorimetric based GN card ID 32 GN, API 20NE, RapID NF Plus andVitek 2 systems (19) all of which are antibody-based agglutination tests. Serological identification has been attemptedwith the analysis of capsular type and lipopolysaccharide(98) molecules as well as protein profiles for taxonomy andepidemiological investigations.
Because of the widespread nature of Acinetobacter spp.,
typing methods are required for genomic characterization(49). The differences in antimicrobial efficacy against different species, and the need to select effective chemotherapeutic
agents, require the accurate identification of Acinetobacter
spp. to the species level. Thus several molecular diagnostic
methods including the polymerase chain reaction (PCR)(47), PFGE, RAPD-PCR DNA fingerprinting (16, 86), fluorescent in situ hybridization (FISH) (112), 16S rRNA gene
restriction analysis (ARDRA) (79), and 16S rRNA gene
PCR-DGGE fingerprinting for genetic characterization ofAcinetobacter spp. from environmental samples Vanbroekhoven et al. have been employed (112). A recent diagnostic method which was reported to have high specificity
and can discriminate between Acinetobacter species is the
microsphere-based array technique that combines an allelespecific primer extension assay and microsphere hybridization (73). The method was reported to be so efficient that 13
different species of Acinetobacter were discriminated inless than 9 h with 90% accuracy and precision (73). The
use of DNA-DNA hybridization and sequence analysis (19,49) is considered the gold standard, but the method is laborintensive and impractical in most clinical laboratories.
Other methods that have been employed in the epidemiological investigation of outbreaks caused by Acinetobacter
spp. include biotyping, phage typing, cell envelope protein
typing, plasmid typing, ribotyping, restriction fragment
length polymorphisms and arbitrarily primed PCR (AP-PCR)(4). These methods are however too expensive and too technical for use in unequipped laboratories. Exploration of sim-

putative chaperon secretion membrane systems (csms) andputative surface adherence protein regions (sapr) have beenreported to be responsible (39, 110). The process generally,
involves reversible attachment, irreversible attachment, maturation and dispersion. A. baumannii-associated infections
are often contracted via biofilms on Foley catheters, venous
catheters, or cerebrospinal shunts.
Hospital environment. A. baumannii is the most important bacterial species associated with nosocomial or hospitalacquired infections. These infections are caused by organisms present in hospitals or other clinical facilities. Most ofthese infections emerge while the patient is in the hospitalbut others are not detected until the patient has been discharged. In the early 70s, nosocomial pathogens were predominantly Gram-negative bacilli especially Ps. aeruginosa,
and Enterobacteriaceae, while the 90s saw the emergence ofGram-positive methicillin-resistant S. aureus (MRSA) andvancomycin-resistant enterococci (VRE) (111, 115). In
recent times however, in addition to MRSA and VRE(mainly in the USA), the introduction of broad spectrum
antibiotics in hospitals has resulted in the emergence of multidrug resistant strictly Gram-negative nosocomial bacterial
pathogens including Ps. aeruginosa, Klebsiella pneumonia
and A. baumannii (33). In a hospital environment, they havebeen isolated from reusable medical equipments such as ventilator tubings, arterial pressure monitoring devices, humidifiers, washbasins, plastic urinals and respirometers (26, 52,
112, 118). The organisms have also been isolated from theskin of healthcare personnel, mattresses, pillows and in all
types of ventilator equipment and moist situations such as
sinks and tap water (8, 56). The presence of MDR and nosocomial Acinetobacter in the hospital environment complicates treatment since such infected patients often need to beisolated (70, 77). This underlies the need to fully study theseorganisms and proffer alternative chemotherapeutic solutions.
Though many Acinetobacter spp. are only found incertain habitats, some are distributed widely in nature. A.
calcoaceticus is found in water and soil and on vegetables(2, 10).
Diagnosis
Infection or colonization with Acinetobacter is usuallydiagnosed by the culture of environmental and clinical samples. The environmental samples include wastewater, activated sludge, sewage, aquaculture freshwater habitats, frozen
shrimps (49) soil (16, 112), vegetables (10), fresh andspoiled meat (34) animal droppings and river water while theclinical samples include blood, cerebrospinal fluid, endoctracheal aspirate, pus (91), sputum, urine, respiratory secretions(115), Catheter tips (24), wound, stool or sterile body fluid,skin, cordon of newborns, nasal swabs, hand swabs of hospital workers and hospital environments (swabs on surfaces ofmachines, wash-hand basins, floors, tables, UV lamps) (22).
Microbiologic cultures can be processed by standard methods on routine media. Antimicrobial susceptibility can be
determined by various means, with the agar-dilution method
being the gold-standard.
A glance at the literature shows just how non fastidious52

Ecology of Acinetobacter spp.

109

found to be synergistic in vivo. Quinolone and amikacinsynergy was also observed. The treatment of a serious
infection with Acinetobacter should be combination therapy
based on laboratory antimicrobial susceptibility results.
Local antimicrobial prescribing habits should be criticallyguided by the susceptibility results. Suspected hospitaloutbreaks involving multidrug-resistant Acinetobacter
infections should not be regarded with akinesis but betackled ferociously and promptly. The prompt revisionof infection control procedures such as hand-washing, patientisolation, ventilator care and good housekeeping is also pertinent. Chemotherapeutic approaches for most antimicrobialresistant Gram-negative infections, include the use of
carbapenems (imipenem and meropenem), but carbapenemresistant Acinetobacter is increasingly reported (56, 101).
Resistance to the carbapenem class of antibiotics complicates
the treatment of multidrug-resistant Acinetobacter infections. However, colistin and polymyxin B have been used totreat highly resistant Acinetobacter infections; unfortunately
renal toxicity of colistin has made its choice unattractive.
Acinetobacter isolates resistant to colistin and polymyxin B
have also been reported (44). The best approach is combination therapy where studies have demonstrated in vitro
susceptibility of multidrug-resistant Acinetobacter to various
synergistic combinations of antimicrobials including
carbapenems, colistin, rifampin, and ampicillin-sulbactam(67, 101, 121). The clinical utility of these combinations
against pan-resistant Acinetobacter remains to be determined(44, 56, 120).
The costs associated with controlling an outbreak of
Acinetobacter infections can be staggering, and some institutions have even been forced to close entire units in order
to interrupt the transmission of Acinetobacter (64, 104, 109).
Therefore, there is a very compelling need to prevent transmission in the healthcare setting and keep the organism frombecoming endemic in an institution. It is also importantthat contamination of the environment, water or food should
be guarded against especially by MDR strains. Careful personal and hand-hygiene should be observed. The disinfectionof hands with-alcohol based disinfectants and observationof standard hospital practices cannot be overemphasized.
Laboratories should embark on active surveillance to detect
cultures and patients who are colonized with multidrugresistant Acinetobacter as well as a community-based
surveillance to determine carriage rates. Other measures
successful in the control of outbreaks include isolation
precautions for infected or colonized patients, cohorting ofpatients, patients’ relatives and staff, environmental disinfection, antimicrobial control, and unit closure (105, 118).
Investigations for novel antibiotic substances with possible
activity against Acinetobacter spp. from plants and othernatural sources with a view to sourcing alternative treatment
should be seriously considered by both research institutions
and pharmaceutical companies.

ple laboratory culture procedures will enhance isolation ofthese organisms especially in developing countries where
electricity and sophisticated diagnostic procedures, andtrained manpower are lacking.
Factors predisposing individuals to acinetobacterioses
Though it is generally agreed that A. baumannii is themost medically significant Acinetobacter spp., there is an
ongoing debate on the clinical impact of the Acinetobacterswith controversial views on whether these organisms
increase morbidity or mortality. While some researchers areof the opinion that A. baumannii infections are responsible
for an increase in patient mortality, others are of the opinion
that infections occur in critically ill patients and mortality
is as a result of other underlying diseases (28, 35, 36).
Whatever the case may be, virtually every study has concluded that there is a detrimental effect (45). The lack of aconsensus on the degree of mortality may be due in partto the difficulty in distinguishing between colonization andinfection, which is compounded by limited information on
the pathogenesis. There is also extensive methodologicalheterogeneity between studies (prospective versus retrospective), and variation in the definitions of cases versus controls(A. baumannii infection versus other infection, polymicrobial
versus monomicrobial) (48, 70). There are also problems
with the accurate identification of organisms to the species
level as well as assessment of the impact of specific clones,
which may differ in virulence potential (45). In addition, theability of organisms to rapidly develop multidrug resistanceand to persist in harsh environmental conditions calls for theneed to take Acinetobacter infections seriously.
Individuals vulnerable to Acinetobacter infections include
those who have recently undergone major surgery, thosewith malignant diseases or burns, and immunosuppressed
patients such as the elderly, neonates with low birth weights,
and patients with prolonged illnesses (84, 107, 108). Nosocomial pneumonia occur in intensive care units (ICUs) with afrequency of 3 to 5% (even higher in patients with mechanical ventilation) and with crude mortality rates of 30 to 75%
have been reported (107, 108). Bacteremia is very common
in elderly immunocompromised patients. The main source ofbacteremia in these patients is bacterial pneumonia, and themost important predisposing factors are malignant diseases,
trauma, prolonged antibiotic treatment, prolonged intravenous lines, post operations, urinary catheterization, renaltransplants chest tubes, mechanical ventilation, parenteralnutrition and long hospitalization (64, 82). Poor hygienic
conditions, and contaminated food and water are common
sources of infection. In addition, it’s been reported that lower
temperatures and an acidic pH may enhance the ability of
Acinetobacter spp. to invade dead tissues (58).
Treatment, prevention and control
Treatment of Acinetobacter infections should be individualized according to susceptibility patterns as the
carbapenems, some fluoroquinolones and doxycycline may
retain activity. Impenim with an aminoglycoside andβ-lactam/β-lactamase inhibitor with an aminoglycoside wasConclusion
Acinetobacter previously ignored as low-grade pathogens
have suddenly generated interest. The emergence of multiresistant strains, some of which are pan-resistant to antibiot53

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11. Blanco, M., J.E. Blanco, A. Mora, et al. 2003. Serotypes, virulence
genes, and intimin types of shiga toxin (verotoxin)-producing
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12. Bouvet, P., and P. Grimont. 1986. Taxonomy of the genus
Acinetobacter with the recognition of Acinetobacter baumanni sp.
nov., Acinetobacter haemolyticus sp. nov., Aninetobacter johnsonii
sp. nov., and amended description of Acinetobacter calcoaceticus andAcinetobacter lwofii. Int. J. Syst. Bacteriol. 36:228–240.
13. Bouvet, P.J.M., and M.L. Joly-Guillou. 2000. Acinetobacter spp.
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ics, that suddenly cause an outbreak of infection, and theability of the organism to resist desiccation and its rapidtransformation potential has overwhelmed scientists worldwide. Despite an exponential rise in A. baumannii infections
over the past decade, many questions remain unanswered(45). While knowledge of the virulence and particularly theresistance mechanisms is increasing, the populations at risk
and the pathogenesis of severe infection are still poorly
understood. The association of the organisms with conditions
such as bacteraemia or pulmonary infections, diarrhea andnosocomial infections further highlights a major concern.
Most available reports are on A. baumannii as the mostimportant clinical species, while investigations are concentrated more on clinical samples. Other samples including
environmental and food samples should be investigated forboth A. baumannii and other species with a view to investigating their health implications. Control measures should
not be limited to investigations of the environment (food,water etc.) for microbial characterization and studies ofAcinetobacter virulence and resistance mechanisms alone
but the use of animal models should also be considered. The
dearth of available treatments remains a major concern andalthough further work on the use and efficacy of combination
therapies is warranted, a more urgent priority must be thedevelopment of novel therapeutic agents (45) including
studies on the effect of phytochemicals from plant sources(32).
Acknowledgements
This study was supported by Cape Peninsula University ofTechnology, Cape Town South Africa (research fund RP03).
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MICROBES AND ENVIRONMENTSEDITORIAL BOARD (2020)

Editor-in-Chief

Ken Takai, Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokosuka, Japan

Senior Editors

Koki Toyota, Tokyo University of Agriculture and Technology, Koganei, Japan
Shin Haruta, Tokyo Metropolitan University, Hachioji, Japan
Satoshi Hanada, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Japan
Hiroyuki Futamata, Shizuoka University, Hamamatsu, Japan
Kazuhiko Narisawa, Ibaraki University, Ami, Japan
Kiwamu Minamisawa, Tohoku University, Sendai, Japan
Nobuhiko Nomura, University of Tsukuba, Tsukuba, Japan
Takuro Nunoura, Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokosuka, Japan
Satoshi Ishii, University of Minnesota, St. Paul, MN, USA
Sen-Lin Tang, Academia Sinica, Taipei, Taiwan

Managing Editors

Yoshihiro Takaki (Online Submission System), Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokosuka, Japan
Satoshi Nakagawa (Online Submission System), Kyoto University, Kyoto, Japan
Shigeto Otsuka (Online Submission System), The University of Tokyo, Tokyo, Japan
Takuro Nunoura (Treasurer), Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokosuka, Japan
Hiroyuki Imachi (Business aﬀairs/Manuscript Reception), Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokosuka, Japan
Yuki Morono (Manuscript Reception), Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Nankoku, Japan
Michinari Sunamura (Manuscript Reception), The University of Tokyo, Tokyo, Japan
Takashi Narihiro (Manuscript Edition), National Institute of Advanced Industrial Science and Technology (AIST), Sapporo,Japan
Satoko Shinozaki-Yabana (Manuscript Edition/Manuscript Reception), National Institutes for Cultural Heritage, Tokyo, Japan

Associate Editors

Yoshiteru Aoi, Hiroshima University, Higashi-Hiroshima, Japan
Chih-Yu Chiu, Academia Sinica, Taipei, Taiwan
Jang-Cheon Cho, Inha University, Incheon, Korea
Peter Dunﬁeld, University of Calgary, Calgary, Canada
Craig Everroad, NASA Ames Research Center, Moﬀett Field, CA, USA
Manabu Fukui, Hokkaido University, Sapporo, Japan
Natsuko Hamamura, Kyushu University, Fukuoka, Japan
Yasufumi Hikichi, Kochi University, Nankoku, Japan
Shir-Ly Huang, National Central University, Jhongli City, Taiwan
Yuichi Hongoh, Tokyo Institute of Technology, Tokyo, Japan
Hiroyuki Imachi, Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokosuka, Japan
Shun’ichi Ishii, Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Nankoku, Japan
Tsukasa Ito, Gunma University, Kiryu, Japan
Elena P. Ivanova, Swinburne University of Technology, Melbourne, Australia
Wataru Iwasaki, The University of Tokyo, Tokyo, Japan
Yasuhiro Kasahara, Hokkaido University, Sapporo, Japan
Takafumi Kataoka, Fukui Prefectural University, Obama, Japan
Junichi Kato, Hiroshima University, Higashi-Hiroshima, Japan
Yoshitomo Kikuchi, National Institute of Advanced Industrial Science and Technology (AIST), Sapporo, Japan
Hiroyuki Kimura, Shizuoka University, Shizuoka, Japan
Tomonori Kindaichi, Hiroshima University, Higashi-Hiroshima, Japan
Staﬀan Kjelleberg, The University of New South Wales, Sydney, Australia
Ken-ichi Kucho, Kagoshima University, Kagoshima, JapanKen Kurokawa, National Institute of Genetics, Mishima, Japan
Mei-Chin Lai, National Chung Hsing University, Taichung, Taiwan
Shuang-Jiang Liu, Institute of Microbiology Chinese Academy of Sciences (IMCAS), Beijing, China
Wen-Tso Liu, University of Illinois at Urbana-Champaign, Champaign, IL, USA
Fumito Maruyama, Hiroshima University, Higashi-Hiroshima, Japan
Shawn McGlynn, Tokyo Institute of Technology, Tokyo, Japan
Keisuke Miyauchi, Tohoku Gakuin University, Tagajo, Japan
Ryo Miyazaki, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Japan
Keizo Nagasaki, Kochi University, Kochi, Japan
Yuji Nagata, Tohoku University, Sendai, Japan
Atsushi Nakabachi, Toyohashi University of Technology, Toyohashi, Japan
Satoshi Nakagawa, Kyoto University, Kyoto, Japan
Tatsunori Nakagawa, Nihon University, Kanagawa, Japan
This journal is partly subsidized by the Grant-in-Aid for Publication of Scientific Research Results from the Japan Society for the
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Shin-ichi Nakano, Kyoto University, Otsu, Japan
Naohiro Noda, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Japan
Satoko Noda, University of Yamanashi, Kofu, Japan
Hideaki Nojiri, The University of Tokyo, Tokyo, Japan
Ryo Ohtomo, Hokkaido Agricultural Research Center (NARO), Sapporo, Hokkaido
Shigeto Otsuka, The University of Tokyo, Tokyo, Japan
Joonhong Park, Yonsei University, Seoul, Korea
Michael J. Sadowsky, University of Minnesota, St. Paul, MN, USA
Keishi Senoo, The University of Tokyo, Tokyo, Japan
Toru Shigematsu, Niigata University of Pharmacy and Applied Sciences, Niigata, Japan
Masaki Shintani, Shizuoka University, Hamamatsu, Japan
Satoru Suzuki, Ehime University, Matsuyama, Japan
Shino Suzuki, Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Nankoku, Japan
Mio Takeuchi, National Institute of Advanced Industrial Science and Technology (AIST), Osaka, Japan
Hideyuki Tamaki, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Japan
Akinori Yabuki, Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokosuka, Japan
Naoko Yoshida, Nagoya Institute of Technology, Nagoya, Japan
Takashi Yoshida, Kyoto University, Kyoto, Japan
Susumu Yoshizawa, The University of Tokyo, Tokyo, Japan
Lian-Hui Zhang, Institute of Molecular and Cell Biology, Proteos, Singapore
Kazuhiko Saeki, Nara Womenʼs University, Nara, Japan
Shusei Sato, Tohoku University, Sendai, Japan
Masaru Usui, Rakuno Gakuen University, Ebetsu, Japan
Torahiko Okubo, Hokkaido University, Sapporo, Japan
Takayuki Wada, Osaka City University, Osaka, Japan
Masafumi Shimizu, Gifu University, Gifu, Japan
Tomoyasu Nishizawa, Ibaraki University, Ami, Japan
Rie Yatsunami, Tokyo Institute of Technology, Yokohama, Japan
Masaaki Konishi, Kitami Institute of Technology, Kitami, Japan
Satoshi Wakai, Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokosuka, Japan

JAPANESE SOCIETY OF MICROBIAL ECOLOGY

President (2019–2020): Yoichi KAMAGATA, National Institute of Advanced Industrial Science and Technology (AIST)
Secretary (2019–2020): Seigo AMACHI, Chiba University
Business affairs (2019–2020): Hideyuki TAMAKI, National Institute of Advanced Industrial Science and Technology (AIST)
Business affairs (2019–2020): Shigeki YAMAMURA, National Institute for Environmental Studies
Business affairs (2019–2020): Wataru KITAGAWA, National Institute of Advanced Industrial Science and Technology (AIST)
Treasurer (2019–2020): Manabu KANNO, National Institute of Advanced Industrial Science and Technology (AIST)
Treasurer (2019–2020): Yuya SATO, National Institute of Advanced Industrial Science and Technology (AIST)
Treasurer (2019–2020): Taiki KATAYAMA, National Institute of Advanced Industrial Science and Technology (AIST)JAPANESE SOCIETY OF SOIL MICROBIOLOGY

President (2019–2020): Hiroyuki OHTA, Ibaraki University
Secretary (2019–2020): Kazuhiko NARISAWA, Ibaraki University
Treasurer (2019–2020): Shigenobu YOSHIDA, Central Region Agricultural Research Center, NARO

TAIWAN SOCIETY OF MICROBIAL ECOLOGY

President (2018–2020): Pi-Han WANG, Tunghai University
Vice President (2018–2020): Chang-Ping YU, National Taiwan University
International Business Affairs (2018–2020): Shiu-Mei LIU, National Taiwan Ocean University
International Business Affairs (2018–2020): Shir-Ly HUANG, National Yang-Ming University
Secretary-General (2018–2020): Chien-Sen LIAO, I-Shou University

JAPANESE SOCIETY OF PLANT MICROBE INTERACTIONS

Chair of Society: Kiwamu MINAMISAWA, Tohoku University
Secretary-General: Shusei SATO, Tohoku University
Treasurer: Hisayuki MITSUI, Tohoku University

JAPANESE SOCIETY FOR EXTREMOPHILES

President (2020-2021): Tairo OSHIMA, Kyowa-kako Co., Ltd
Vice President (2020-2021): Akira INOUE, Toyo University
Vice President (2020-2021): Toshihiro ITOH, Kitasato Research Center for Environmental Science