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Impact of Wood Age on Termite Microbial Assemblages
Amrita Chakraborty,aJan Šobotník,bKate
rina Votýpková,aJaromír Hradecký,cPetr Stiblik,aJi
rí Synek,a
Thomas Bourguignon,b,d Petr Baldrian,eMichael S. Engel,f,g,h Vojt
ech Novotný,i,j Iñaki Odriozola,eTomášV
etrovskýa,e
a
EVA 4.0 Unit, Faculty of Forestry and Wood Sciences, Czech University of Life Sciences, Prague, Czech Republic
b
Faculty of Tropical AgriSciences, Czech University of Life Sciences, Prague, Czech Republic
c
Faculty of Forestry and Wood Sciences, Czech University of Life Sciences, Prague, Czech Republic
d
Okinawa Institute of Science & Technology Graduate University, Okinawa, Japan
e
Institute of Microbiology, Czech Academy of Sciences, Prague, Czech Republic
f
American Museum of Natural History, New York, New York, USA
g
Division of Entomology, Natural History Museum, University of Kansas, Lawrence, Kansas, USA
h
Department of Ecology & Evolutionary Biology, University of Kansas, Lawrence, Kansas, USA
i
Faculty of Science, University of South Bohemia, Ceske Budejovice, Czech Republic
j
Biology Centre of the Czech Academy of Sciences, Institute of Entomology, Ceske Budejovice, Czech Republic
ABSTRACT The decomposition of wood and detritus is challenging to most macro-
scopic organisms due to the recalcitrant nature of lignocellulose. Moreover, woody
plants often protect themselves by synthesizing toxic or nocent compounds which
infuse their tissues. Termites are essential wood decomposers in warmer terrestrial
ecosystems and, as such, they have to cope with high concentrations of plant toxins
in wood. In this paper, we evaluated the influence of wood age on the gut microbial
(bacterial and fungal) communities associated with the termites Reticulitermes fla-
vipes (Rhinotermitidae) (Kollar, 1837) and Microcerotermes biroi (Termitidae) (Desneux,
1905). We confirmed that the secondary metabolite concentration decreased with
wood age. We identified a core microbial consortium maintained in the gut of R. fla-
vipes and M. biroi and found that its diversity and composition were not altered by
the wood age. Therefore, the concentration of secondary metabolites had no effect
on the termite gut microbiome. We also found that both termite feeding activities
and wood age affect the wood microbiome. Whether the increasing relative abun-
dance of microbes with termite activities is beneficial to the termites is unknown
and remains to be investigated.
IMPORTANCE Termites can feed on wood thanks to their association with their gut
microbes. However, the current understanding of termites as holobiont is limited. To
our knowledge, no studies comprehensively reveal the influence of wood age on the
termite-associated microbial assemblage. The wood of many tree species contains
high concentrations of plant toxins that can vary with their age and may influence
microbes. Here, we studied the impact of Norway spruce wood of varying ages and
terpene concentrations on the microbial communities associated with the termites
Reticulitermes flavipes (Rhinotermitidae) and Microcerotermes biroi (Termitidae). We
performed a bacterial 16S rRNA and fungal ITS2 metabarcoding study to reveal the
microbial communities associated with R. flavipes and M. biroi and their impact on
shaping the wood microbiome. We noted that a stable core microbiome in the ter-
mites was unaltered by the feeding substrate, while termite activities influenced the
wood microbiome, suggesting that plant secondary metabolites have negligible
effects on the termite gut microbiome. Hence, our study shed new insights into the
termite-associated microbial assemblage under the influence of varying amounts of
terpene content in wood and provides a groundwork for future investigations for
developing symbiont-mediated termite control measures.
Editor Isaac Cann, University of Illinois Urbana-
Champaign
Copyright © 2023 American Society for
Microbiology. All Rights Reserved.
Address correspondence to Jan Šobotník,
sobotnik@ftz.czu.cz.
The authors declare no conflict of interest.
Received 3 March 2023
Accepted 25 March 2023
Month YYYY Volume XX Issue XX 10.1128/aem.00361-23 1
ENVIRONMENTAL MICROBIOLOGY
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KEYWORDS wood-feeding termites, Reticulitermes flavipes,Microcerotermes biroi, plant
defenses, terpenoids, core-microbiome, ectosymbionts, endosymbionts, bacteria, fungi
Termites (Isoptera) are one of the few animal lineages capable of feeding on lignocel-
lulose, the most common polymer on Earth. They play an important role in nutrient
recycling in tropical ecosystems, where they are among the most abundant animals (1–3).
Termites are traditionally divided into two informal groups based on their gut sym-
bionts which aid plant material digestion. The “lower”termites include 9 of the 10 ter-
mite families and primarily rely on hypermastigian protists (Parabasalia), bacteria, and
archaea to digest wood. In contrast, the “higher”termites, consisting only of the fam-
ily Termitidae, have lost their gut protists and are primarily associated with bacteria
and archaea (4) and, in the case of Macrotermitinae, with the symbiotic fungus
Termitomyces (5). While “lower”termites feed solely on wood or grasses, many line-
ages of termitids feed on other substrates, especially rotten wood and the organic
matter present in soil (6–9).
Termites thrive on wood, a nutritionally limiting substrate often rich in secondary
metabolites (10). Many host trees are chemically defended with various phenolic com-
pounds and terpenoids produced constitutively or upon attack by insects or patho-
gens (11). High concentrations of these defensive compounds, such as monoterpenes,
olefins, and diterpenes, are entomotoxic and contribute to the plant’s resistance to
insect infestation (12, 13). In response, insects have evolved strategies to overcome
toxic plant compounds (14, 15). In addition to aiding in the degradation of complex
dietary polymers (16, 17) and providing vitamins such as essential amino acids (18,
19), insect-associated microbes often manipulate and degrade toxic plant secondary
metabolites (20–24).
Over the past decade, the contribution of symbiotic microorganisms to insect
ecology has come to the forefront (25–27). Insect feeding habits play a vital role in shap-
ing gut microbiotas. For example, cockroaches feeding on a low-protein, high-fiber diet
exhibit reduced acetate and lactate production in their gut, resulting in low abundances
of streptococci and lactobacilli (28). Similarly, a high-cellulose diet increased the proto-
zoan population in the gut of Periplaneta americana (29). As noted above, “lower”ter-
mites harbor symbiotic protists which provide cellulolytic enzymes that help in wood
digestion. In contrast, “higher”termites lack symbiotic protists and solely depend on their
gut bacteria, archaea, and associated fungi to decompose cellulose (30, 31). Wood-feed-
ing Termitidae host bacterial communities distinct from those of soil-feeding Termitidae
(32, 33), producing larger amounts of lignocellulases (33, 34). The plant secondary metab-
olites content in wood is another factor which potentially influences gut microbial com-
munities, a factor that has been poorly investigated so far (32). Termite gut bacterial and
fungal symbionts may play an active role in detoxifying plant secondary metabolites, as is
the case in bark beetles (35–39).
The present study aims to determine the influence of tree secondary metabolites
(terpenes) on the gut microbial communities of wood-feeding termites. We studied two
termite species, the “lower”termite Reticulitermes flavipes (Rhinotermitidae) and the
“higher”termite Microcerotermes biroi (Termitidae), which we fed with Norway spruce
wood of various ages. As pieces of Norway spruce age, their secondary metabolite con-
tent dwindles (40), allowing the investigation of secondary metabolite impact on the
microbial assemblages associated with “lower”and “higher”termites. In this study, we
characterized microbial communities using high-throughput amplicon sequencing tar-
geting bacterial 16S rRNA and fungal ITS2. We compared the gut microbial commun-
ities of termite groups fed on woods of various ages with different concentrations of
secondary metabolites. We used the microbial assemblages of the wood used to feed
termites as wood controls and the unfed termites as termite controls. With this experi-
mental design, we determined the impact of tree secondary metabolites on termite gut
microbial communities.
Impact of Wood Age on Termite Microbial Assemblages Applied and Environmental Microbiology
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RESULTS
Plant secondary metabolites. The wood terpene content decreased as the wood
aged (Fig. 1). Fresh wood (FW_C) contained a larger amount of
a
-pinene (106.9 626.7
m
g/g),
b
-pinene 1
b
-myrcene (219.9 655
m
g/g), 3-carene (33 68.2
m
g/g), limonene
(19.6 64.9
m
g/g), and camphene (2.8 60.7
m
g/g) followed by standard timber (SW_C) that
contained
a
-pinene (69.5 617.4
m
g/g),
b
-pinene 1
b
-myrcene (38 69.5
m
g/g), 3-carene
(1.6 60.4
m
g/g), limonene (3.3 60.8
m
g/g), and camphene (2.8 60.7
m
g/g). Terpene con-
centration was the lowest in old wood (OW_C), with only
a
-pinene (0.46 60.12
m
g/g),
b
-pi-
nene 1
b
-myrcene (0.44 60.11
m
g/g), and camphene (0.32 60.08
m
g/g) being detectable
(Fig. 1). These values correspond to the average of two independent determinations in
dry weight form (DW) for each type of wood, expressed together with the 95% confi-
dence interval, based on the uncertainty of gas chromatography coupled with mass
spectrometry (GC-MS) determination, calculated for each analyte during validation.
Unfortunately, statistical significance could not be estimated due to the lack of sufficient
replications for each type of wood during the GC-MS determination of terpene content.
However, even with two replicates, the wood samples showed distinct differences in ter-
pene content.
Illumina sequencing. The Illumina pair-end sequencing performed on the MiSeq
platform yielded a total of 2,347,945 bacterial 16S sequences and 779,354 fungal inter-
nal transcribed spacer (ITS) sequences after the initial quality check and removal of chi-
meric sequences. The reads which passed quality assessment obtained from termites,
infested wood, and uninfested control wood samples were used for downstream bioin-
formatic analyses. The completeness of the sequencing is illustrated by the rarefaction
curves (Fig. S1in the Supplemental file 1).
Bacterial diversity. The operational taxonomic unit (OTU) clustering performed at
a 97% similarity cutoff documented the presence of 3,633 bacterial OTUs that were
assigned to 722 bacterial genera belonging to 30 phyla (Supplemental File 2, part 1).
The bacterial communities of wood pieces infested by R. flavipes revealed 12 dominant
FIG 1 Terpenic compounds content (
m
g/g DW) (DW, dry weight) present in Norway spruce wood
upon storage. FW_C represents freshly cut spruce wood, SW_C denotes commercially available spruce
timber felled 3 to 4 years ago, and OW_C represents old wood that was cut circa 120 years ago.
Values are the average of two independent analytical determinations of compound concentrations in
pooled homogenized (n= 6) samples of wood. Error bars represent the uncertainty (U) of the whole
analytical procedure, including extraction and GC-MS (gas chromatography coupled with mass
spectrometry) instrumental analysis. U is based on relative standard deviation (RSD) obtained from 9
independent determinations of compounds concentration in one homogenized wood sample. U is
calculated using the equation U = 2 RSD.
Impact of Wood Age on Termite Microbial Assemblages Applied and Environmental Microbiology
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phyla with relative abundance of $1% (Fig. 2a), while those infested by M. biroi
revealed 9 dominant phyla (Fig. 2b). Within the control wood, the relative abundance
of Proteobacteria (44.46%) was higher in old wood (OW_C) than in other types of wood
controls (SW_C, 27.58%; FW_C, 29.23%). FW_C had the highest relative abundance of
Planctomycetes (6.42%) and the lowest relative abundance of Actinobacteria (18.23%)
and Firmicutes (8.10%) among the wood controls. The termite-infested wood micro-
biome was characterized by a higher relative abundance of Proteobacteria than the
microbiomes of uninfested wood controls (Fig. 2). Proteobacteria and Actinobacteria
were the dominant phyla in both infested and uninfested wood, followed by Firmicutes
and Bacteroidetes.Elusimicrobia and Mycoplasmatota were only observed in infested
FIG 2 Relative abundance of bacterial communities. (a and b) Relative abundance of bacterial phyla (abundance of $1% in at least one sample) within
termites (Reticulitermes flavipes and Microcerotermes biroi) feeding on different substrates, termite-infested wood, and their controls. “Others”denotes the
total relative abundance of other phyla. (c and d) Heatmap illustrating the top 45 bacterial genera with relative abundance of $1% in at least one sample
documented in Reticulitermes and Microcerotermes before and after feeding on different substrates, termite-infested wood, and their controls. Color
gradient from red to green through black represents the relative abundance of bacterial operational taxonomic units (OTUs) present in each sample type.
Red color, low abundance; green color, high abundance. FW_C, fresh wood control; SW_C, standard wood control; OW_C, old wood control; FW_R_W,
Reticulitermes-infested fresh wood; SW_R_W, Reticulitermes-infested standard wood; OW_R_W, Reticulitermes-infested old wood; R_C_T, Reticulitermes control
termite before feeding; FW_R_T, Reticulitermes feeding on fresh wood; SW_R_T, Microcerotermes feeding on standard wood; OW_R_T, Reticulitermes feeding
on old wood; Cellu_R_T, Reticulitermes feeding on cellulose; FW_M_W, Microcerotermes-infested fresh wood; SW_M_W, Microcerotermes-infested standard
wood; OW_M_W, Microcerotermes-infested old wood; M_C_T, Microcerotermes control termite before feeding; FW_M_T, Microcerotermes feeding on fresh
wood; SW_M_T, Microcerotermes feeding on standard wood, OW_M_T, Microcerotermes feeding on old wood; Cellu_M_T, Microcerotermes feeding on
cellulose.
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wood samples and might have been introduced by termites during feeding activities
(Fig. 2; Supplemental File 2, part 1).
R. flavipes feeding on all substrates showed higher relative abundances of Proteobacteria,
Bacteroidetes,Actinobacteria, and Euryarchaeota than the control workers sampled before
the feeding experiment started (R_C_T). In contrast, Spirochaeta (34.14%), Elusimicrobia
(27.17%), and Mycoplasmatota (4.31%) were abundant in R_C_T (Fig. 2a; Supplemental
File 2, part 1). Similarly, feeding on wood substrates and cellulose increased the relative
abundance of Fibrobacteres,Bacteroidetes,andAcidobacteria in M. biroi compared to their
termite controls (M_C_T) (Fig. 2b). However, the relative abundance of Proteobacteria
and Firmicutes was the highest in M_C_T (Fig. 2b). Comparing the two termite species
the relative abundance of Elusimicrobia (27.17%), Bacteroidetes (12.2%), Euryarchaeota
(4.51%), and Mycoplasmatota (4.31%)werehigherinR. flavipes controls (R_C_T), while
the relative abundance of Spirochaeta (57.43%), Proteobacteria (27.58%), Firmicutes
(9.27%), and Fibrobacteres (2.21%) were higher in M. biroi (M_C_T) (Fig. 2, Supplemental
File 2). The relative abundances of the top 45 bacterial genera observed in the two ter-
mite species fed with different substrates, their infested wood, along with the controls,
are represented as heatmaps (Fig. 2c and d). These differentially abundant bacterial genera
include Spirochaeta,Endomicrobium,“Candidatus Armantifilum,”“Candidatus Symbiothrix,”
Dysgonomonas,Fibrobacter,Sphingomonas,Bacteroides,Ralstonia,Methylobacterium,
Roseburia,Methanobrevibacter,Ruminiclostridium,Propionibacterium,Burkholderia, etc.
(Supplemental File 2, parts 2 and 3).
The Shannon index revealed that the gut bacterial diversity of M. biroi controls
(M_C_T) was significantly lower than those of the R. flavipes controls (R_C_T) (Tukey’spost
hoc analysis; P,0.05); however, no significant differences were observed among termites
feeding on different substrates (Fig. S2a in the Supplemental file 1). M. biroi had higher
bacterial richness (Chao1 index) than R. flavipes (Fig. S2b in the Supplemental file 1).
Bacterial diversity was higher in the control wood samples than in wood samples infested
by termites. The highest bacterial diversity was found in the SW_C group. Interestingly,
termite feeding activities reduced the bacterial diversity (Shannon) and increased the bac-
terial richness (Chao1) in all types of wood samples (Fig. S3 in the Supplemental file 1).
The overall
b
-diversity represented by the nonmetric multidimensional scaling (NMDS)
plot showed distinct separation of the bacterial communities of both termite species (M.
biroi and R. flavipes) (Fig. 3) (permutational multivariate analysis of variance [PERMANOVA],
termite_species; df
num
=1,df
den
= 38, F= 133.18, P= 0.001). Moreover, the effect of
the substrate type depended on the termite species (PERMANOVA, termite_species:
substrate_type; df
num
=4,df
den
= 38, F= 2.47, P= 0.021). The bacterial community
composition associated with termites fed on spruce wood of different ages, cellulose,
and control termites differed between termite species (Tables S1, S5 and S6 in the
Supplemental file 3). No significant variation was observed among the gut bacterial
communities of M. biroi feeding on different types of wood. However, the bacterial com-
munities of M. biroi feeding on cellulose (Cellu_M_T) and control M. biroi samples
(M_C_T) significantly differed from that of M. biroi feeding on different types of spruce
wood substrates. A similar trend was observed in R. flavipes (Fig. 3a, Table S1 in the
Supplemental file 3).
Termite-feeding activities altered the wood microbiome. The control wood samples
clustered separately in the NMDS plot (Fig. 3b). Furthermore, the wood samples
infested by M. biroi and R. flavipes grouped in distinct clusters (PERMANOVA, termite_
species; df
num
=2,df
den
= 39, F= 15.04, P= 0.001). The effect of wood type on bacterial
community structure depended on the termite species (PERMANOVA, termite_species:
wood_type; df
num
=4,df
den
= 39, F= 2.44, P= 0.001). Therefore, the bacterial commun-
ities of wood samples infested with termites differed significantly from those of wood
samples free of termites (Fig. 3b; Table S2, S5 and S6 in the Supplemental file 3).
Fungal diversity. The fungal OTU clustering documented 1,499 OTUs assigned to
six phyla (Supplemental File 2, part 4). Among these, Ascomycota was prevalent in all
samples, followed by Basidiomycota, Mucoromycota, and Chytridiomycota. A lower
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relative abundance of Basidiomycota was observed in wood samples after R. flavipes
infestation. In contrast, standard (SW_M_W) and old wood (OW_M_W) samples
infested by M. biroi showed a high relative abundance of Basidiomycota compared to
control wood samples. Basidiomycota was proportionally more abundant in the guts
of both M. biroi and R. flavipes fed with all types of wood substrates than in their unfed
controls. In contrast, the relative abundance of Basidiomycota decreased in termites
fed with cellulose (Supplemental File 2, part 4).
The gut microbiome of R. flavipes contained a high proportion of Eurotiales (55.44%),
Onygenales (25.36%), and Agaricales (5.31%) before the feeding experiments started
(R_C_T) (Fig. 4a). The fungal order GS23 was absent in control wood samples but was
observed in termite-infested wood samples. Additionally, Hypocreales, Trichospornales,
and Ophiostomatales were proportionally more abundant in both the R. flavipes-infested
wood samples and in the guts of termites fed with all types of substrates than in the
controls (Fig. 4a). Similarly, the relative abundance of Sordariales was higher in M. biroi-
infested fresh wood (FW_M_W, 37.21%) and old wood (OW_M_W, 26.83%) samples than
in control wood samples (FW_C, 0.93%; OW_C, 0.96%) (Fig. 4b). However, the standard
wood control samples (SW_C) showed a higher relative abundance of Pleosporales (17.54%),
Capnodiales (12.14%), Diaporthales (16.46%), and Agaricales (11.43%) than the infested
wood samples (SW_M_W). Saccharomycetales (30.59%) were dominant in uninfested fresh
wood controls (FW_C), whereas Helotiales (19.11%) and Coniochaetales (22.48%) were prev-
alent in the old wood controls. The relative abundance of Trichosporonales increased in
M. biroi-infested wood samples (Fig. 4b). Furthermore, Eurotiales (45.26%) and Malasseziales
(2.44%) were predominant in the M. biroi controls (M_C_T) and decreased in relative abun-
dance in all types of wood substrates infested by M. biroi. In contrast, the relative abun-
dance of several fungal orders, such as Hypocreales, Sordariales, Saccharomycetales,
Botryosphaeriales, and Ustilaginales, was higher in wood samples infested by M. biroi (Fig.
4b). Nevertheless, among termite mycobiomes, the relative abundance of Eurotiomycetes
was the highest in both control termites (M_C_T and R_C_T) (Supplemental File 2, part 4).
Interestingly, the relative abundance of Eurotiomycetes in the gut of R. flavipes (80.82%)
was nearly double that found in M. biroi (45.3%). The heatmap represented the top 39 fun-
gal genera with a relative abundance of $1% in at least one sample (Fig. 4c and d). The
differentially abundant fungal genera included Trichoderma,Meyerozyma,Apiotrichum,
FIG 3 Nonmetric multidimensional scaling (NMDS) plot. The variation in the bacterial communities’present in (a) the two different termites
(Reticulitermes flavipes and Microcerotermes biroi) feeding on different substrates and their control. (b) Different wood substrates infested by
the termites and control uninfested wood. Samples are denoted by different shapes (square, control; circle, M. biroi; triangle, R. flavipes);
colors denote substrate types.
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Trichosporon,Fusarium,Alternaria,Sporothrix,Cadophora,Malassezia,andTalaromyces
(Supplemental File 2, parts 5 and 6).
The Shannon diversity index showed that the gut fungal communities of R. flavipes
and M. biroi did not significantly differ. In addition, no significant differences were
observed among termites feeding on different substrates (Tukey’spost hoc analysis; P.
0.05) (Fig. S4a in the Supplemental file 1). Similarly, none of the experimental factors sig-
nificantly affected the fungal richness (Chao1 index) in the guts of R. flavipes and M. biroi
(Fig. S4b in the Supplemental file 1). Fungal diversity was significantly higher in the unin-
fested control wood samples than in the samples infested by R. flavipes and M. biroi
(FW_C, SW_C, and OW_C) and decreased with wood age (Fig. S5a in the Supplemental
file 1). Fungal richness decreased with wood age across termite species and controls
(Fig. S5b in the Supplemental file 1).
FIG 4 Relative abundance of fungal communities. (a and b) Relative abundance of fungal order with relative abundance of $1% in at least one sample
within termites (R. flavipes and M. biroi) upon feeding on different substrates, termite-infested wood and their controls. “Others”denotes the total relative
abundance of rest of the fungal orders present. (c and d) Heatmap illustrating the top 39 fungal genera documented in Reticulitermes and Microcerotermes
before and after feeding on different substrates, termite-infested spruce wood, and control wood. Color gradient from red to green through black
represents the relative abundance of fungal OTUs present in each sample type. Red color denotes low abundance, green color signifies high abundance.
Group abbreviations are the same as in Fig. 2.
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Fungal community composition differed significantly between termite species (M. biroi
and R. flavipes); however, the difference was not as marked as for bacterial communities
(Fig. 5a) (PERMANOVA, termite_species; df
num
=1,df
den
= 38, F= 15.04, P=0.001).
Substrate type influenced fungal community composition in a species-specific manner
(PERMANOVA, termite_species: substrate_type; df
num
=4,df
den
= 38, F= 2.44, P=0.001).
The fungal community composition of M. biroi controls (M_C_T) significantly differed from
that of M. biroi fed on standard wood (SW_M_T), old wood (OW_M_T), and cellulose
(Cellu_M_T) (Table S3 in the Supplemental file 3). Similarly, the fungal community compo-
sition of R. flavipes controls was significantly different from those of other treatments
(Table S3 in the Supplemental file 3). The difference in fungal community composition
between controls and treatments was more prominent in M. biroi than in R. flavipes (Fig.
5a, Table S3 in the Supplemental file 3).
The fungal community composition of wood was strongly affected by termite activity.
Control wood samples clustered separately from infested wood samples, while wood
samples infested with R. flavipes and M. biroi largely overlapped in the NMDS plot
(PERMANOVA, termite_species; df
num
=2,df
den
=38,F=14.08,P= 0.001) (Fig. 5b).
Termite feeding activity strongly reduced the effect of wood age on fungal community
composition (PERMANOVA, termite_species: wood_type; df
num
=4,df
den
=38,F=2.62,
P= 0.001). Control wood samples showed a clear successional pattern with fungal com-
munities gradually changing from FW_C, through SW_C, to OW_C (Fig. 5b, Table S4 in
the Supplemental file 3). In contrast, the fungal community composition of wood sam-
ples on which termites fed did not markedly change with wood age (Fig. 5b, Table S4 in
the Supplemental file 3). Additionally, the fungal community composition significantly
varied between termite bodies and wood as estimated using Hellinger-transformed OTU
table based on Bray-Curtis dissimilarity distances (Table S6 in the Supplemental file 3).
Core gut microbiome in R. flavipes and M. biroi.We identified the core gut micro-
bial community consistently associated with termites feeding on all types of substrates.
The core gut bacterial community of R. flavipes included 452 OTUs belonging to 133 bac-
terial genera (Fig. 6a; Supplemental File 2, part 7), while the core gut fungal community
included 79 OTUs belonging to 31 fungal genera (Fig. 6b; Supplemental File 2, part 8).
Similarly, the core gut microbial community of M. biroi included 448 OTUs assigned to
120 bacterial genera (Fig. 6c; Supplemental File 2, part 9) and 92 OTUs belonging to 32
FIG 5 NMDS plot. The variation in the fungal communities present in (a) the two termites feeding on different substrates and their control,
and (b) different wood substrates either infested by the termites or control uninfested wood. Sample types are denoted by different
symbols as in Fig. 3.
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fungal genera (Fig. 6d; Supplemental File 2, part 10). In particular, the core gut bacterial
microbiome of both termite species included “Candidatus Armantifilum,”“Candidatus
Symbiothrix,”Clostridium,Desulfovibrio,Desulfosarcina,Dysgonomonas,Endomicrobium,
Fibrobacter,Massilia,Methanobrevibacter,Methylobacterium,Methanobacterium,Paludibacter,
Paraburkholderia,Parabacteroides,Pseudomonas,Ralstonia,Rickettsia,Roseospira,Ruminococcus,
Siphonobacter,Spirochaeta,Taibaiella,Tangfeifania,Tannerella,Treponema,Tyzzerella,and
Wolbachia (Supplemental File 2, parts 7 and 9). The core gut fungal microbiome of both ter-
mite species included Malassezia,Meyerozyma,Trichoderma,Fusarium,Aspergillus,Penicillium,
Debaryomyces,Hawksworthiomyces,Scytalidium,Trichosporon,Lasiodiplodia,andAlternaria
(Supplemental File 2, parts 8 and 10). In addition to the core OTUs shared by both termite spe-
cies, we also identified unique OTUs that may have been acquired during feeding (Fig. 6;
Supplemental File 2, parts 7 to 10).
DISCUSSION
The termite gut microbiome is not affected by wood age. The terpene content in
Norway spruce wood has decreased by more than 300 times over 120 years of timber
use. Our data showed that the terpene content influenced the gut microbial assem-
blage of both R. flavipes and M. biroi. The relative abundance of bacterial genera such
as Pseudomonas,Massilia, and Rhizobium was high in wood samples infested by ter-
mites (Fig. 1), suggesting they contribute to important functions, such as detoxification
of toxic plant secondary metabolites (35, 41–44). The high relative abundance of
Fibrobacteres in the gut of M. biroi is likely linked to their involvement in lignocellulose
degradation (45). Furthermore, our data documented the prevalence of spirochetes in
both R. flavipes and M. biroi, although the bacterial genera Spirochaeta and Treponema
FIG 6 Flower diagram representing the core and unique OTUs. (a and b) Core and unique bacterial
OTUs shared among R. flavipes and M. biroi upon feeding on different substrates. (c and d) Common
and unique fungal OTUs shared among Reticulitermes and Microcerotermes upon feeding on different
substrates. Group abbreviations are the same as in Fig. 2.
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showed significant differences in their relative abundance between these two species.
Overall, the relative abundance of Spirochaeta was higher in M. biroi than in R. flavipes.
Several studies have documented the importance of spirochetes in the termite gut for
their involvement in various metabolic processes such as nitrogen fixation, acetogene-
sis, and degradation of lignocellulose (46–51). The relatively lower abundance of spiro-
chetes in R. flavipes compared to M. biroi could reflect the presence of lignocellulolytic
protists in the guts of “lower”termites (52).
The bacterial lineages “Candidatus Azobacteroides”and Endomicrobium identified
in the present study are known as termite gut symbionts associated with gut protists
(53–55). Endomicrobium (phylum Elusimicrobia), identified as a predominant bacterial
genus in the guts of “lower”termites (R_C_T) (56), is mainly involved in amino acid syn-
thesis, glucose fermentation, nitrogen fixation, and recycling of nitrogenous wastes
(57–60). In contrast, “Candidatus Azobacteroides”is closely associated with gut protists
performing H
2
uptake and nitrogen fixation (59, 61). Furthermore, the ectosymbionts
“Candidatus Symbiothrix”and “Candidatus Armantifilum,”belonging to Bacteroidetes,
are known to colonize the cell surface of gut protists and perform lignocellulose diges-
tion and nitrogen fixation within the host termite (62, 63). Consequently, bacterial
communities associated with termites contribute to diverse metabolic functions com-
plementing the host metabolism.
The present study documented the fungal communities associated with termites
feeding on various wood substrates (Fig. 5). Members of fungal orders such as
Trichosporonales, Eurotiales, Saccharomycetales, and Malaseziales were observed in
both R. flavipes and M. biroi (64, 65). Many fungal genera documented in this study (Fig.
5c and d) have been previously reported in different termite species (18, 66, 67), suggest-
ing that they are associated with termites in a stable fashion. They have also reported in
other insects, such as beetles (68, 69) and cockroaches (70). The high abundance of the
yeasts Debaryomyces,Meyerozyma,andMalassezia suggests that they are typical termite
gut inhabitants (64, 65, 71). Filamentous fungi and yeast communities inhabiting the
insect gut (72, 73) are known to play important roles in the decomposition of lignocellu-
loses, aiding in wood digestion (65, 74), detoxifying plant allelochemicals (38, 39), and
providing supplementary nutrients (75). The observed fungal genera Trichoderma,
Penicillium,Scytalidium,Lasiodiplodia,andHawksworthiomyces have been reported to ex-
hibit lignocellulolytic activities (76–79). Furthermore, Fusarium associated with termites
might participate in amino acid metabolism and the recycling of nitrogenous waste
products (80).
The overall microbial diversity of M. biroi and R. flavipes showed substantial varia-
tions (Fig. 4a). However, feeding on wood pieces of different ages did not significantly
alter the termite gut microbiome. These results indicate that the core gut microbial
community of termites is stable and remains unaffected by varying concentrations of
host tree allelochemicals.
Wood age and termite feeding activities affect the wood microbiome. The plant
terpenoid concentration decreased according to the following sequence: freshly cut
wood (FW_C), standard wood (SW_C), and old wood (OW_C), in which terpenoid com-
pounds were almost absent (Fig. S1). The bacterial communities present in wood mainly
comprised Proteobacteria, Actinobacteria, Firmicutes, and Bacteroidetes (81). However,
their relative abundance changed with the wood age. Furthermore, the overall microbial
community composition within the control and termite-infested wood samples differed,
reflecting the influence of termite-feeding activities (Fig. 1 and 5). The high abundance
of several bacterial genera such as Burkholderia,Erwinia,Massilia,Novosphingobium,
Paraburkholderia,Pseudomonas,Rhizobium,andSphingobium observed in termite-infested
fresh wood might reflect their ability to detoxify or tolerate toxic plant secondary metabo-
lites (35, 41–44). Furthermore, several bacterial genera such as Acetatifactor,Anaerostipes,
Atopobium,“Candidatus Azobacteroides,”Dysgonomonas,Endomicrobium,Mycoplasma,
Pasteuria,Parabacteroidetes,Paludibacter,Pseudohalocynthiibacter,Ralstonia,Roseospira,
Siphonobacter,andTangfeifania were absent in uninfested control wood samples but were
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introduced by termites during feeding. Most of these bacterial lineages were termite gut
symbionts, some of which were associated with their gut protists (53–55). The amplicon
DNA sequencing approach cannot differentiate between live bacteria and DNA originating
from dead cells. These termite gut symbiont DNA sequences likely originated from dead cells
or remnant DNA deposited by termites on their galleries. Furthermore, in termite-infested
wood, fungal communities belonging to the orders Eurotiales, Sordariales, Hypocreales,
Trichospornales, and Ophiostomatales were prevalent. The fungal genera Apiotrichum,
Fusarium,Hawksworthiomyces,Lasiodiplodia,Sporothrix,Trichosporon,andTrichoderma were
highly abundant in termite-infested wood, possibly contributing to lignocellulose degradation
and detoxification of secondary metabolites (76, 77, 79, 82). Additionally, our data document
the presence of the fungal orders Ustilaginales, Rhizophydiales, and GS23 in termite-
infested wood, which were absent from control wood samples, suggesting that they
were transferred from termites during feeding. Consequently, the control and termite-
infested wood samples formed distinct groups in the NMDS plot, showing significant dif-
ferences in overall microbial community composition (Fig. 4b). Although we interpreted
the effect of wood age on microbial communities as being driven by terpenoid concen-
tration, other factors such as temperature, moisture content, and nutrient availability
also vary with wood age and could affect the wood microbiome.
The core gut microbiome of termites. Our findings document that the core gut
microbiome of termites is unaffected by the feeding substrate. This was true for both bac-
terial and fungal communities and for both termite species investigated in this study. Many
of these observed core microbes, such as Clostridium,Fusarium,Malassezia,Penicillium,
Ruminococcus,Tyzzerella,andTrichoderma, have been reported as core members of the gut
microbiome in other wood-feeding insects, e.g., bark beetles, in which they perform vital
metabolic functions for their hosts (83, 84).
Conclusion. The present study revealed that the gut microbial community differed
significantly between the two termite species. A stable core gut microbiome was iden-
tified in both R. flavipes and M. biroi. This core microbiome was not altered by the feed-
ing substrate. The termite gut microbiome was not markedly influenced by the wood
age, which is characterized by varying concentrations of secondary metabolites.
Termite feeding activities considerably altered the wood microbiome, while wood age
and hence the concentration in plant allelochemicals had minor effects. Our results
also indicate that termite-feeding activities modified the wood microbiome, possibly
increasing the proportion of microbes beneficial to the termites, such as those partici-
pating in the initial detoxification of toxic plant metabolites, decomposition of ligno-
cellulose, and nitrogen assimilation.
MATERIALS AND METHODS
Termite sampling. The wood-feeding “lower”termite R. flavipes (R) was obtained from David Sillam-
Dussès (University Paris 13, France), while the “higher”wood-feeding termite, M. biroi (M), was brought
to Prague from the village of Wanang (Madang, Papua New Guinea; lat –5.22772°, long 145.07983°). We
made termite groups composed of 100 workers and 2 soldiers each (reflecting the soldier proportion in
both tested species [85]), which we placed into Petri dishes (85-mm diameter) containing 20 g fine sand,
5 mL tap water, and a piece of wood. The experiment was set at 27°C (60.5°C), and the Petri dishes
were placed into larger boxes lined with wet filter paper to maintain humidity at 100% for the 10 days
of the experiment. Termites were given a single piece of Norway spruce wood (20 33 mm). Three
types of wood were provided: freshly cut wood (FW_C; harvested within 24 h of tree logging), standard
timber (SW_C; 3 to 4 years of age), and old timber (OW_C; rafters 120 years old obtained during the uni-
versity building reconstruction). In addition, we established groups of termites provided with 2 g micro-
crystalline cellulose (Merck, product no. CAS 9004-34-6) instead of wood as positive feeding controls. We
also used uninfested wood fragments (six replicates) and unmanipulated termite samples (from stock
colonies, four replicates) as controls. A total of five replicates were performed for each wood type. All
samples were collected into RNAlater and stored at 280°C until DNA extraction.
Analyses of terpenoids. The content of selected secondary metabolites (terpenes) was measured
for the three types of wood using GC-MS. Two replicates were analyzed for each wood type. Wood sam-
ples were initially frozen in liquid nitrogen and homogenized into a fine powder using a Mixer Mill
Retsch MM 400 with a sterile steel bead (5 mm) for 15 min at 30 oscillations/sec. Next, 200 mg of wood
powder was placed into a 20 mL headspace vial, extracted with 2 mL N-hexane in an ultrasonic bath for
10 min, and then filtered into a 2-mL vial for GC analysis. One microliter of the extract was injected into
the gas chromatograph coupled to a time-of-flight mass spectrometer (GC-TOF-MS) (Leco Pegasus 4D,
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Leco, USA). The temperature-programmed injector was used in a split mode with a 1:10 split ratio. A 30-
m (0.25-mm internal diameter, 0.25-
m
mfilm thickness) Rxi-5MS (Restec, USA) column was used for sepa-
ration. The temperature program for the GC oven was as follows: 40°C for 1 min, then raised to 210°C at
a rate of 10°C/min, followed by an increase to 320°C at 20°C/min with a hold time of 2 min. The total GC
run time was 26 min. The mass spectrometer was operated at a mass range of 35 to 500 m/z with an ac-
quisition speed of 10 Hz. The similarity of the deconvoluted mass spectrum with spectra from the NIST
library was used for compound identification. The compounds of interest (
a
- and
b
-pinene,
b
-myrcene,
camphene, 3-carene, and limonene) were quantified using an external calibration curve based on com-
mercially available standards obtained from Sigma-Aldrich (USA). Since
b
-pinene and
b
-myrcene coe-
luted on the used column, these compounds were reported together. Results correspond to the average
values from two independent determinations for each type of wood in DW form, expressed together
with a 95% confidence interval, based on the uncertainty of GC-MS determination, calculated for each
analyte during validation (86).
DNA extraction, amplification, and sequencing. Total DNA was extracted from termites and wood
samples (either infested or uninfested). Termite samples were rinsed twice in 70% ethanol and washed
with sterile water for surface sterilization. Each termite sample consisted of a pool of 10 workers homog-
enized with a Mixer Mill Retsch MM 400 and two sterile steel beads (3 mm) for 2 min at 30 oscillations/
sec before DNA extraction. Similarly, the wood samples were freeze-dried in liquid nitrogen and homog-
enized with a Mixer Mill Retsch MM 400 using a 5-mm sterile steel bead for 15 min at 30 oscillations/sec
before DNA extraction. Total DNA was isolated using the Macherey-Nagel NucleoSpin Soil kit following
the manufacturer’s protocol and electrophoresed on 1% agarose gel with GelRed Nucleic Acid Stain
(Biotium, USA) to check DNA integrity. The DNA concentration was quantified on Nanodrop (Thermo
Fisher Scientific), and 10 ng of DNA was used as a template for downstream amplification reactions.
PCR amplification of the bacterial 16S rRNA gene targeting the V4 hypervariable region was per-
formed using the universal, uniquely barcoded primers 515F and 806R (87), while the fungal ITS2 do-
main was amplified using gITS7F and ITS4R uniquely barcoded primers (88, 89). PCR amplifications were
performed in triplicate using an Eppendorf Mastercycler (Eppendorf AG, Hamburg, Germany) nexus
cycler. The reaction mixture included 1PCR buffer with 1.5 mM MgCl
2
,10
m
M primers, 200
m
M each
dNTP, 10
m
g/mL of bovine serum albumin, 2 U Q5 High Fidelity DNA Polymerase (New England Biolabs),
and 10 ng of template DNA. PCRs were performed as follows: initial denaturation at 94°C for 5 min; fol-
lowed by 30 cycles of amplification at 94°C for 45 s, 50°C for 60 s, 72°C for 45 sec (bacterial amplification),
or 94°C for 45 s, 56°C for 30 s, 72°C for 30 s (fungal amplification); and a final extension step at 72°C for
10 min. A template control was also run to verify the absence of any contaminations. The amplicons
were purified using the MinElute PCR Purification kit (Qiagen GmbH, Hilden, Germany) according to the
manufacturer’s protocol and quantified with a Qubit 2.0 Fluorometer using the dsDNA HS Quantification
kit (Invitrogen). Sequencing libraries of purified amplicons adjusted at equimolar concentration were
prepared using the NEBNext Ultra DNA Library Pre-kit. Libraries were sequenced on the Illumina MiSeq
platform (Illumina Inc., USA) to yield 250-bp paired-end reads.
Data processing. (i) Quality control and data filtering. Paired-end raw reads obtained from Illumina
sequencing were merged to generate single reads using the fastq-join command (90) of SEED 2 (version
2.1.05) (91). Merged sequences were demultiplexed and trimmed. Quality control tests were performed
for sequences with mean quality Phred scores Q ,30. Sequences with mismatches in barcodes were
discarded. Bacterial 16S sequences with read lengths of ,230 bp or .280 bp and fungal ITS sequences
with read lengths of ,40 bp were removed from the data set. All fungal sequences were extracted using
ITSx (version 1.0.11) (92) before the OTU clustering step to obtain the entire fungal ITS2 region.
(ii) OTU clustering. OTUs were clustered at 97% sequence similarity using the UPARSE algorithm
implemented in USEARCH version 8.1.1861 (93). Sequences identified as chimeric were excluded from
downstream analyses. OTUs with less than five reads were discarded to minimize the effect of contam-
inations (if any) and barcode hopping during sequencing (94). We used one representative sequence
for each OTU (i.e., the most abundant sequence) to perform taxonomic identification with RDP data-
base release 11 (95) to obtain the closest BLAST hit for each OTU. We used rrnDB version 5.4 (96) to
estimate the relative OTU abundance, a measure that corrects for the variation in 16S copy number
per genome among bacterial species (97). Simi larly, the fungal sequences were annotated using the
UNITE database version 7.2 (98).
(iii) Alpha (a-) and beta (b-) diversities. Bacterial and fungal species diversity (
a
-diversity) was esti-
mated using community richness (Chao1) and diversity (Shannon) indices (99). We estimated these indi-
ces for each termite species, termite-infested wood, and the controls using SEED v 2.1. The results were
displayed in R (100). We identified the microbial communities shared by termites fed with different
substrates.
The variability in the overall microbial community structure (
b
-diversity) among termites, termite-
infested wood, and their controls was visualized using nonmetric multidimensional scaling analysis (101)
with a Bray-Curtis distance matrix. The analyses were performed in R. The bacterial and fungal commun-
ities of termite guts and wood pieces were analyzed separately. For termite guts, a PERMANOVA analysis
(102) was performed using the adonis() function of the R package vegan (103) to test the null hypothesis
of no effect of the termite species and substrate type on the composition of the termite gut microbiome.
Bray-Curtis dissimilarity matrices were used as responses in the analyses. The relative abundance tables
were fourth-root-transformed prior to calculation of the dissimilarity matrix to reduce the influence of
the more abundant taxa relative to the less dominant taxa and allow community-wide assessment of
changes in taxon composition (104). Termite species (factor with two levels: M. biroi and R. flavipes), sub-
strate type (five levels: fresh wood, standard wood, old wood, cellulose, and control), and their interaction
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were included as explanatory variables. Post hoc pairwise comparisons of specificcombinationsoftermite
species and substrate types were performed using a pairwise PERMANOVA implemented in the
pairwiseAdonis R package (105). False-discovery rate (FDR) correction was used to adjust Pvalues to multiple
comparisons (106). Significance was assessed using 999 permutations.
Similarly, the null hypothesis of no effect of termite species and wood type on the wood microbiome
composition was tested using adonis(). Response matrices were again calculated using Bray-Curtis dis-
similarity of the fourth-root-transformed relative abundance tables. Termite species (factor with three
levels: M. biroi,R. flavipes, and wood control), wood type (three levels: fresh wood, standard wood, and
old wood), and their interaction were used as explanatory variables. Pairwise comparisons were per-
formed using the same procedure as for termite guts.
Additionally, to ensure the robustness of our results to the choice of dissimilarity index, these analy-
ses were repeated using a Hellinger-transformed OTU abundance table based on Bray-Curtis dissimilar-
ity, as well as phylogeny-based UniFrac (weighted and unweighted) dissimilarity (107). UniFrac-based
analysis was conducted only for bacteria since the ITS region shows higher variation than 16S and hence
does not allow the building of reliable phylogenetic trees for fungi, possibly leading to erroneous results
for this analysis (108).
Relative abundances of different taxa in specific experimental conditions were visualized usi ng bar-
plots and heatmaps. We used linear models to test the null hypothesis of no effect of termite species and
substrate type on termite gut and wood fungal and bacterial
a
-diversity (as measured by Chao1 commu-
nity richness estimator and Shannon-Wiener diversity index). Alpha diversity indices calculated for termite
and wood samples were used as response variables in the models, and termite species and substrate type
were used as explanatory variables, as explained previously for the multivariate PERMANOVA analyses. For
pairwise comparisons of specific combinations of termite species and substrate types, Tukey’spost hoc
tests were implemented using the R function TukeyHSD().
We performed a differential abundance analysis of bacterial and fungal genera in termite guts and
wood pieces between experimental groups using a quasi-likelihood negative binomial generalized log-
linear model to count data. This analysis was performed using the glmQLFit() function of the R package
edgeR (109). As for the previously described PERMANOVA analyses, termite species, substrate type, and
their interaction were included as explanatory variables for termite guts, whereas termite species, wood
type, and their interaction were included as explanatory variables for wood pieces. FDR correction was
used to adjust Pvalues to multiple comparisons (50). Because one of our main objectives was to deter-
mine the influence of wood age on the termite-associated microbiome, the following contrasts (inde-
pendently for Microcerotermes and Reticulitermes) were tested to identify differentially abundant taxa:
control termites versus termites fed with fresh wood, standard wood, old wood, and cellulose. Similarly,
we also studied differentially abundant microbial communities in termites fed with different wood sub-
strates. Furthermore, in the case of wood pieces, our objective was to determine how termite substrate
influences the termite microbiota. As such, the uninfested wood controls were compared with the
infested wood for the two termite species.
Data availability. The sequence data of the bacterial V4 hypervariable region of the 16S rRNA gene
and the fungal ITS2 gene amplified from two different wood-feeding termites (R. flavipes and M. biroi),
infested spruce wood, and their controls have been deposited in NCBI (SRA database) under BioProject
accession no. PRJNA792414.
SUPPLEMENTAL MATERIAL
Supplemental material is available online only.
SUPPLEMENTAL FILE 1, PDF file, 1.1 MB.
SUPPLEMENTAL FILE 2, XLSX file, 2.8 MB.
SUPPLEMENTAL FILE 3, DOCX file, 0.02 MB.
ACKNOWLEDGMENTS
We thank David Sillam-Dussès for providing R. flavipes material. We are grateful to
the New Guinea Binatang Research Centre (Madang, Papua New Guinea) for help with
the M. biroi material acquisition.
Financial support was provided by Czech Science Foundation projects no. 16-
05318S and 19-28126X; by the grant “EVA 4.0,”project no. CZ.02.1.01/0.0/0.0/16_019/
0000803, financed by the OP RDE; and by Faculty of Tropical AgriSciences project IGA
20223112.
REFERENCES
1. Brune A. 2014. Symbiotic digestion of lignocellulose in termite guts. Nat
Rev Microbiol 12:168–180. https://doi.org/10.1038/nrmicro3182.
2. Bar-On YM, Phillips R, Milo R. 2018. The biomass distribution on Earth.
Proc Natl Acad Sci U S A 115:6506–6511. https://doi.org/10.1073/pnas
.1711842115.
3. Griffiths HM, Ashton LA, Evans TA, Parr CL, Eggleton P. 2019. Termites
can decompose more than half of deadwood in tropical rainforest. Curr
Biol 29:R118–R119. https://doi.org/10.1016/j.cub.2019.01.012.
4. Inward DJ, Vogler AP, Eggleton P. 2007. A comprehensive phylogenetic
analysis of termites (Isoptera) illuminates key aspects of their evolutionary
Impact of Wood Age on Termite Microbial Assemblages Applied and Environmental Microbiology
Month YYYY Volume XX Issue XX 10.1128/aem.00361-23 13
Downloaded from https://journals.asm.org/journal/aem on 17 April 2023 by 37.48.60.75.
biology. Mol Phylogenet Evol 44:953–967. https://doi.org/10.1016/j.ympev
.2007.05.014.
5. Chouvenc T, Šobotník J, Engel MS, Bourguignon T. 2021. Termite evolution:
mutualistic associations, key innovations, and the rise of Termitidae. Cell
Mol Life Sci 78:2749–2769. https://doi.org/10.1007/s00018-020-03728-z.
6. Bourguignon T, Drouet T, Šobotník J, Hanus R, Roisin Y. 2015. Influence of
soil properties on soldierless termite distribution. PLoS One 10:e0135341.
https://doi.org/10.1371/journal.pone.0135341.
7. Bourguignon T, Šobotník J, Dahlsjö CA, Roisin Y. 2016. The soldierless
Apicotermitinae: insights into a poorly known and ecologically dominant
tropical taxon. Insect Soc 63:39–50. https://doi.org/10.1007/s00040-015
-0446-y.
8. Bourguignon T, Lo N, Šobotník J, Ho SY, Iqbal N, Coissac E, Lee M,
Jendryka MM, Sillam-Dusses D, K
rížková B. 2017. Mitochondrial phyloge-
nomics resolves the global spread of higher termites, ecosystem engi-
neers of the tropics. Mol Biol Evol 34:589–597. https://doi.org/10.1093/
molbev/msw253.
9. Bucek A, Šobotník J, He S, Shi M, McMahon DP, Holmes EC, Roisin Y, Lo
N, Bourguignon T. 2019. Evolution of termite symbiosis informed by
transcriptome-based phylogenies. Curr Biol 29:3728–3734.e4. https://doi
.org/10.1016/j.cub.2019.08.076.
10. Keeling CI, Bohlmann J. 2006. Diterpene resin acids in conifers. Phyto-
chemistry 67:2415–2423. https://doi.org/10.1016/j.phytochem.2006.08
.019.
11. Raffa KF, Aukema BH, Erbilgin N, Klepzig KD, Wallin KF. 2005. Interactions
among conifer terpenoids and bark beetles across multiple levels of
scale: an attempt to understand links between population patterns and
physiological processes. Recent Adv Phytochem 39:79–118. https://doi
.org/10.1016/S0079-9920(05)80005-X.
12. Werner RA. 1995. Toxicity and repellency of 4-allylanisole and monoter-
penes from white spruce and tamarack to the spruce beetle and eastern
larch beetle (Coleoptera: Scolytidae). Environ Entomol 24:372–379. https://
doi.org/10.1093/ee/24.2.372.
13. Raffa KF, Smalley EB. 1995. Interaction of pre-attack and induced monoter-
pene concentrations in host conifer defense against bark beetle-fungal
complexes. Oecologia 102:285–295. https://doi.org/10.1007/BF00329795.
14. Hammer TJ, Bowers MD. 2015. Gut microbes may facilitate insect herbi-
vory of chemically defended plants. Oecologia 179:1–14. https://doi.org/
10.1007/s00442-015-3327-1.
15. Ni J, Tokuda G. 2013. Lignocellulose-degrading enzymes from termites
and their symbiotic microbiota. Biotechnol Adv 31:838–850. https://doi
.org/10.1016/j.biotechadv.2013.04.005.
16. Douglas AE. 2009. The microbial dimension in insect nutritional ecology.
Funct Ecol 23:38–47. https://doi.org/10.1111/j.1365-2435.2008.01442.x.
17. Kirk TK, Cowling EB. 1984. Biological decomposition of solid wood, p
455–487. In Rogers R (ed), Advances in chemistry vol 207. ACS Publica-
tions, Washington, DC.
18. Varm A, Kolli BK, Paul J, Saxena S, König H. 1994. Lignocellulose degrada-
tion by microorganisms from termite hills and termite guts: a survey on
the present state of art. FEMS Microbiol Rev 15:9–28. https://doi.org/10
.1111/j.1574-6976.1994.tb00120.x.
19. Hyodo F, Tayasu I, Inoue T, Azuma JI, Kudo T, Abe T. 2003. Differential role
of symbiotic fungi in lignin degradation and food provision for fungus-
growing termites (Macrotermitinae: Isoptera). Funct Ecol 17:186–193.
https://doi.org/10.1046/j.1365-2435.2003.00718.x.
20. Chung SH, Rosa C, Scully ED, Peiffer M, Tooker JF, Hoover K, Luthe DS,
Felton GW. 2013. Herbivore exploits orally secreted bacteria to suppress
plant defenses. Proc Natl Acad Sci U S A 110:15728–15733. https://doi
.org/10.1073/pnas.1308867110.
21. Ceja-Navarro JA, Vega FE, Karaoz U, Hao Z, Jenkins S, Lim HC, Kosina P,
Infante F, Northen TR, Brodie EL. 2015. Gut microbiota mediate caffeine
detoxification in the primary insect pest of coffee. Nat Commun 6:7618.
https://doi.org/10.1038/ncomms8618.
22. Hammerbacher A, Schmidt A, Wadke N, Wright LP, Schneider B,
Bohlmann J, Brand WA, Fenning TM, Gershenzon J, Paetz C. 2013. A com-
mon fungal associate of the spruce bark beetle metabolizes the stilbene
defenses of Norway spruce. Plant Physiol 162:1324–1336. https://doi
.org/10.1104/pp.113.218610.
23. Welte CU, de Graaf RM, van den Bosch TJ, Op den Camp HJ, van Dam
NM, Jetten MS. 2016. Plasmids from the gut microbiome of cabbage
root fly larvae encode SaxA that catalyses the conversion of the plant
toxin 2-phenylethyl isothiocyanate. Environ Microbiol 18:1379–1390.
https://doi.org/10.1111/1462-2920.12997.
24. Gurung K, Wertheim B, Falcao Salles J. 2019. The microbiome of pest
insects: it is not just bacteria. Entomol Exp Appl 167:156–170. https://doi
.org/10.1111/eea.12768.
25. Six DL. 2012. Ecological and evolutionary determinants of bark beetle: fun-
gus symbioses. Insects 3:339–366. https://doi.org/10.3390/insects3010339.
26. Raffa KF. 2014. Terpenes tell different tales at different scales: glimpses
into the chemical ecology of conifer-bark beetle-microbial interactions. J
Chem Ecol 40:1–20. https://doi.org/10.1007/s10886-013-0368-y.
27. Douglas AE. 2015. Multiorganismal insects: diversity and function of resi-
dent microorganisms. Annu Rev Entomol 60:17–34. https://doi.org/10
.1146/annurev-ento-010814-020822.
28. Kane MD, Breznak JA. 1991. Effect of host diet on production of organic
acids and methane by cockroach gut bacteria. Appl Environ Microbiol
57:2628–2634. https://doi.org/10.1128/aem.57.9.2628-2634.1991.
29. Tinker KA, Ottesen EA. 2016. The core gut microbiome of the American
cockroach, Periplaneta americana, is stable and resilient to dietary shifts.
Appl Environ Microbiol 82:6603–6610. https://doi.org/10.1128/AEM
.01837-16.
30. Brune A, Dietrich C. 2015. The gut microbiota of termites: digesting the
diversity in the light of ecology and evolution. Annu Rev Microbiol 69:
145–166. https://doi.org/10.1146/annurev-micro-092412-155715.
31. Brune A, Ohkuma M. 2010. Role of the termite gut microbiota in symbi-
otic digestion, p 439–475. In Bignell D, Roisin Y, Lo N (ed), Biology of ter-
mites: a modern synthesis. Springer, Dordrecht, The Netherlands.
32. Dietrich C, Köhler T, Brune A. 2014. The cockroach origin of the termite
gut microbiota: patterns in bacterial community structure reflect major
evolutionary events. Appl Environ Microbiol 80:2261–2269. https://doi
.org/10.1128/AEM.04206-13.
33. Mikaelyan A, Dietrich C, Köhler T, Poulsen M, Sillam-Dussès D, Brune A.
2015. Diet is the primary determinant of bacterial community structure
in the guts of higher termites. Mol Ecol 24:5284–5295. https://doi.org/10
.1111/mec.13376.
34. Arora J, Kinjo Y, Šobotník J, Bu
cek A, Clitheroe C, Stiblik P, Roisin Y,
Žif
cáková L, Park YC, Kim KY, Sillam-Dussès D, Hervé V, Lo N, Tokuda G,
Brune A, Bourguignon T. 2022. The functional evolution of termite gut
microbiota. Microbiome 10:78. https://doi.org/10.1186/s40168-022
-01258-3.
35. Boone CK, Keefover-Ring K, Mapes AC, Adams AS, Bohlmann J, Raffa KF.
2013. Bacteria associated with a tree-killing insect reduce concentrations
of plant defense compounds. J Chem Ecol 39:1003–1006. https://doi
.org/10.1007/s10886-013-0313-0.
36. Skrodenytė-Arba
ciauskienėV, RadžiutėS, Stunžėnas V, B
uda V. 2012.
Erwinia typographi sp. nov., isolated from bark beetle (Ips typographus)
gut. Int J Syst Evol Microbiol 62:942–948. https://doi.org/10.1099/ijs.0
.030304-0.
37. Dowd PF, Shen SK. 1990. The contribution of symbiotic yeast to toxin re-
sistance of the cigarette beetle (Lasioderma serricorne). Entomol Exp
Appl 56:241–248. https://doi.org/10.1111/j.1570-7458.1990.tb01402.x.
38. Tsui CK-M, Farfan L, Roe AD, Rice AV, Cooke JE, El-Kassaby YA, Hamelin
RC. 2014. Population structure of mountain pine beetle symbiont Lep-
tographium longiclavatum and the implication on the multipartite bee-
tle-fungi relationships. PLoS One 9:e105455. https://doi.org/10.1371/
journal.pone.0105455.
39. Zhao T, Kandasamy D, Krokene P, Chen J, Gershenzon J, Hammerbacher
A. 2019. Fungal associates of the tree-killing bark beetle, Ips typographus,
vary in virulence, ability to degrade conifer phenolics and influence bark
beetle tunneling behavior. Fungal Ecol 38:71–79. https://doi.org/10
.1016/j.funeco.2018.06.003.
40. Bartnik C, Nawrot-Chorabik K, Woodward S. 2020. Phenolic compound
concentrations in Picea abies wood as an indicator of susceptibility towards
root pathogens. For Path 50:e12652. https://doi.org/10.1111/efp.12652.
41. Germida JJ. 1988. Growth of indigenous Rhizobium leguminosarum and
Rhizobium meliloti in soils amended with organic nutrients. Appl Environ
Microbiol 54:257–263. https://doi.org/10.1128/aem.54.1.257-263.1988.
42. Balkwill D, Fredrickson J, Romine M. 2006. Sphingomonas and related
genera, p 605–629. In Dworkin M, Falkow S, Rosenberg E, Schleifer KH,
Stackebrandt E (ed), The prokaryotes: a handbook on the biology of bac-
teria. Springer, New York, NY.
43. Chen W-M, Moulin L, Bontemps C, Vandamme P, Béna G, Boivin-Masson
C. 2003. Legume symbiotic nitrogen fixation by
b
-proteobacteria is wide-
spread in nature. J Bacteriol 185:7266–7272. https://doi.org/10.1128/JB
.185.24.7266-7272.2003.
Impact of Wood Age on Termite Microbial Assemblages Applied and Environmental Microbiology
Month YYYY Volume XX Issue XX 10.1128/aem.00361-23 14
Downloaded from https://journals.asm.org/journal/aem on 17 April 2023 by 37.48.60.75.
44. Xu LT, Lu M, Sun JH. 2016. Invasive bark beetle-associated microbes de-
grade a host defensive monoterpene. Insect Sci 23:183–190. https://doi
.org/10.1111/1744-7917.12255.
45. Calusinska M, Marynowska M, Bertucci M, Untereiner B, Klimek D, Goux
X, Sillam-Dussès D, Gawron P, Halder R, Wilmes P, Ferrer P, Gerin P,
Roisin Y, Delfosse P. 2020. Integrative omics analysis of the termite gut
system adaptation to Miscanthus diet identifies lignocellulose degrada-
tion enzymes. Commun Biol 3:275. https://doi.org/10.1038/s42003-020
-1004-3.
46. Su L, Yang L, Huang S, Su X, Li Y, Wang F, Wang E, Kang N, Xu J, Song A.
2016. Comparative gut microbiomes of four species representing the
higher and the lower termites. J Insect Sci 16:97. https://doi.org/10.1093/
jisesa/iew081.
47. Lilburn T, Kim K, Ostrom N, Byzek K, Leadbetter J, Breznak J. 2001. Nitrogen
fixation by symbiotic and free-living spirochetes. Science 292:2495–2498.
https://doi.org/10.1126/science.1060281.
48. Leadbetter JR, Schmidt TM, Graber JR, Breznak JA. 1999. Acetogenesis
from H
2
plus CO
2
by spirochetes from termite guts. Science 283:686–689.
https://doi.org/10.1126/science.283.5402.686.
49. Tokuda G, Mikaelyan A, Fukui C, Matsuura Y, Watanabe H, Fujishima M,
Brune A. 2018. Fiber-associated spirochetes are major agents of hemicel-
lulose degradation in the hindgut of wood-feeding higher termites. Proc
Natl Acad Sci U S A 115:E11996–E12004. https://doi.org/10.1073/pnas
.1810550115.
50. Breznak JA, Pankratz HS. 1977. In situ morphology of the gut microbiota
of wood-eating termites [Reticulitermes flavipes (Kollar) and Coptotermes
formosanus Shiraki]. Appl Environ Microbiol 33:406–426. https://doi.org/
10.1128/aem.33.2.406-426.1977.
51. Dröge S, Rachel R, Radek R, König H. 2008. Treponema isoptericolens sp.
nov., a novel spirochaete from the hindgut of the termite Incisitermes
tabogae. Int J Syst Evol Microbiol 58:1079–1083. https://doi.org/10.1099/
ijs.0.64699-0.
52. Sethi A, Kovaleva ES, Slack JM, Brown S, Buchman GW, Scharf ME. 2013. A
GHF7 cellulase from the protist symbiont community of Reticulitermes fla-
vipes enables more efficient lignocellulose processing by host enzymes.
Arch Insect Biochem Physiol 84:175–193. https://doi.org/10.1002/arch
.21135.
53. Desai MS, Strassert JF, Meuser K, Hertel H, Ikeda-Ohtsubo W, Radek R,
Brune A. 2010. Strict cospeciation of devescovinid flagellates and Bacter-
oidales ectosymbionts in the gut of dry-wood termites (Kalotermitidae).
Environ Microbiol 12:2120–2132. https://doi.org/10.1111/j.1462-2920
.2009.02080.x.
54. Noda S, Hongoh Y, Sato T, Ohkuma M. 2009. Complex coevolutionary his-
tory of symbiotic Bacteroidales bacteria of various protists in the gut of ter-
mites. BMC Evol Biol 9:158. https://doi.org/10.1186/1471-2148-9-158.
55. Hongoh Y, Sharma VK, Prakash T, Noda S, Taylor TD, Kudo T, Sakaki Y,
Toyoda A, Hattori M, Ohkuma M. 2008. Complete genome of the uncul-
tured Termite Group 1 bacteria in a single host protist cell. Proc Natl Acad
Sci U S A 105:5555–5560. https://doi.org/10.1073/pnas.0801389105.
56. Brune A. 2012. Endomicrobia: intracellular symbionts of termite gut flag-
ellates. Endocytobiosis Cell Res 23:11–15. https://zs.thulb.uni-jena.de/receive/
jportal_jparticle_00270371.
57. Stingl U, Radek R, Yang H, Brune A. 2005. “Endomicrobia”: cytoplasmic
symbionts of termite gut protozoa form a separate phylum of prokar-
yotes. Appl Environ Microbiol 71:1473–1479. https://doi.org/10.1128/
AEM.71.3.1473-1479.2005.
58. Zheng H, Dietrich C, Thompson CL, Meuser K, Brune A. 2015. Population
structure of Endomicrobia in single host cells of termite gut flagellates
(Trichonympha spp.). Microbes Environ 30:92–98. https://doi.org/10
.1264/jsme2.ME14169.
59. Hongoh Y, Sharma VK, Prakash T, Noda S, Toh H, Taylor TD, Kudo T, Sakaki
Y, Toyoda A, Hattori M, Ohkuma M. 2008. Genome of an endosymbiont
coupling N
2
fixation to cellulolysis within protist cells in termite gut. Sci-
ence 322:1108–1109. https://doi.org/10.1126/science.1165578.
60. Izawa K, Kuwahara H, Kihara K, Yuki M, Lo N, Itoh T, Ohkuma M, Hongoh
Y. 2016. Comparison of intracellular “Ca. Endomicrobium trichonym-
phae”genomovars illuminates the requirement and decay of defense
systems against foreign DNA. Genome Biol Evol 8:3099–3107. https://doi
.org/10.1093/gbe/evw227.
61. Inoue J-I, Saita K, Kudo T, Ui S, Ohkuma M. 2007. Hydrogen production
by termite gut protists: characterization of iron hydrogenases of paraba-
salian symbionts of the termite Coptotermes formosanus. Eukaryot Cell 6:
1925–1932. https://doi.org/10.1128/EC.00251-07.
62. Yuki M, Kuwahara H, Shintani M, Izawa K, Sato T, Starns D, Hongoh Y,
Ohkuma M. 2015. Dominant ectosymbiotic bacteria of cellulolytic protists
in the termite gut also have the potential to digest lignocellulose. Environ
Microbiol 17:4942–4953. https://doi.org/10.1111/1462-2920.12945.
63. Desai MS, Brune A. 2012. Bacteroidales ectosymbionts of gut flagellates
shape the nitrogen-fixing community in dry-wood termites. ISME J 6:
1302–1313. https://doi.org/10.1038/ismej.2011.194.
64. Prillinger H, Messner R, König H, Bauer R, Lopandic K, Molnar O, Dangel P,
Weigang F, Kirisits T, Nakase T, Sigler L. 1996. Yeasts associated with ter-
mites: a phenotypicand genotypic characterization and use of coevolution
for dating evolutionary radiations in asco- and basidiomycetes. Syst Appl
Microbiol 19:265–283. https://doi.org/10.1016/S0723-2020(96)80053-1.
65. Prillinger H, König H. 2006. The intestinal yeasts, p 319–334. In Prillinger
H, König H (ed), Intestinal microorganisms of termites and other inverte-
brates. Springer-Verlag Berlin, Berlin, Germany.
66. Rajgopal S, Rajyalakshmi Rao D, Varma A. 1979. Association of fungi in ter-
mite gut. Curr Sci 48:998–999. https://www.jstor.org/stable/24082324.
67. Rajgopal S, Rao DR, Varma A. 1981. Fungi of the worker termite-gut,
Odontotermes obesus (Rambur) from northern India. Nova Hedwigia 34:
97–100.
68. Rojas-Jiménez K, Hernández M. 2015. Isolation of fungi and bacteria
associated with the guts of tropical wood-feeding coleoptera and deter-
mination of their lignocellulolytic activities. Int J Microbiol 2015:285018.
https://doi.org/10.1155/2015/285018.
69. Ziganshina EE, Mohammed WS, Shagimardanova EI, Vankov PY, Gogoleva
NE, Ziganshin AM. 2018. Fungal, bacterial, and archaeal diversity in the di-
gestive tract of several beetle larvae (Coleoptera). Biomed Res Int 2018:
6765438. https://doi.org/10.1155/2018/6765438.
70. Salehzadeh A, Tavacol P, Mahjub H. 2007. Bacterial, fungal and parasitic
contamination of cockroaches in public hospitals of Hamadan, Iran. J
Vector Borne Dis 44:105–110.
71. Zhang N, Suh S-O, Blackwell M. 2003. Microorganisms in the gut of bee-
tles: evidence from molecular cloning. J Invertebr Pathol 84:226–233.
https://doi.org/10.1016/j.jip.2003.10.002.
72. Blackwell M. 2017. Yeasts in insects and other invertebrates, p 397–433.
In Buzzini P, Lachance M-A, Yurkov A (ed), Yeasts in natural ecosystems:
diversity. Springer Cham, Cham, Switzerland.
73. Stefanini I. 2018. Yeast-insect associations: it takes guts. Yeast 35:315–330.
https://doi.org/10.1002/yea.3309.
74. Schäfer A, Konrad R, Kuhnigk T, Kämpfer P, Hertel H, König H. 1996. Hemi-
cellulose-degrading bacteria and yeasts from the termite gut. J Appl Bac-
teriol 80:471–478. https://doi.org/10.1111/j.1365-2672.1996.tb03245.x.
75. Davis TS, Hofstetter RW, Foster JT, Foote NE, Keim P. 2011. Interactions
between the yeast Ogataea pini and filamentous fungi associated with
the western pine beetle. Microb Ecol 61:626–634. https://doi.org/10
.1007/s00248-010-9773-8.
76. de França Passos D, Pereira N Jr, de Castro AM. 2018. A comparative
review of recent advances in cellulases production by Aspergillus,Penicil-
lium and Trichoderma strains and their use for lignocellulose deconstruc-
tion. Curr Opin Green Sustain Chem 14:60–66. https://doi.org/10.1016/j
.cogsc.2018.06.003.
77. De Beer ZW, Marincowitz S, Duong TA, Kim J-J, Rodrigues A, Wingfield MJ.
2016. Hawksworthiomyces gen. nov.(Ophiostomatales), illustrates the ur-
gency for a decision on how to name novel taxa known only from envi-
ronmental nucleic acid sequences (ENAS). Fungal Biol 120:1323–1340.
https://doi.org/10.1016/j.funbio.2016.07.004.
78. Eriksson K-EL, Blanchette RA, Ander P. 2012. Microbial and enzymatic
degradation of wood and wood components. Springer Science & Busi-
ness Media, Berlin, Germany.
79. Félix C, Libório S, Nunes M, Félix R, Duarte AS, Alves A, Esteves AC. 2018.
Lasiodiplodia theobromae as a producer of biotechnologically relevant
enzymes. Int J Mol Sci 19:29. https://doi.org/10.3390/ijms19020029.
80. Scully ED, Geib SM, Carlson JE, Tien M, McKenna D, Hoover K. 2014. Func-
tional genomics and microbiome profiling of the Asian longhorned beetle
(Anoplophora glabripennis) reveal insights into the digestive physiology
and nutritional ecology of wood feeding beetles. BMC Genomics 15:1096.
https://doi.org/10.1186/1471-2164-15-1096.
81. Bulgarelli D, Schlaeppi K, Spaepen S, Van Themaat EVL, Schulze-Lefert
P. 2013. Structure and functions of the bacterial microbiota of plants.
Annu Rev Plant Biol 64:807–838. https://doi.org/10.1146/annurev
-arplant-050312-120106.
82. Molnar O, Schatzmayr G, Fuchs E, Prillinger H. 2004. Trichosporon mycotoxi-
nivorans sp. nov., a new yeast species useful in biological detoxification of
Impact of Wood Age on Termite Microbial Assemblages Applied and Environmental Microbiology
Month YYYY Volume XX Issue XX 10.1128/aem.00361-23 15
Downloaded from https://journals.asm.org/journal/aem on 17 April 2023 by 37.48.60.75.
various mycotoxins. Syst Appl Microbiol 27:661–671. https://doi.org/10
.1078/0723202042369947.
83. Chakraborty A, Modlinger R, Ashraf MZ, Synek J, Schlyter F, Roy A. 2020.
Core mycobiome and their ecological relevance in the gut of five Ips
bark beetles (Coleoptera: Curculionidae: Scolytinae). Front Microbiol 11:
568853. https://doi.org/10.3389/fmicb.2020.568853.
84. Chakraborty A, Ashraf MZ, Modlinger R, Synek J, Schlyter F, Roy A. 2020.
Unravelling the gut bacteriome of Ips (Coleoptera: Curculionidae: Scoly-
tinae): identifying core bacterial assemblage and their ecological rele-
vance. Sci Rep 10:18572. https://doi.org/10.1038/s41598-020-75203-5.
85. Haverty MI. 1977. The proportion of soldiers in termite colonies: a list
and a bibliography. Sociobiology 2:199–216.
86. Št
epán R, Hajšlová J, Kocourek V, Tichá J. 2004. Uncertainties of gas chro-
matographic measurement of troublesome pesticide residues in apples
employing conventional and mass spectrometric detectors. Anal Chim
Acta 520:245–255. https://doi.org/10.1016/j.aca.2004.05.045.
87. Caporaso JG, Lauber CL, Walters WA, Berg-Lyons D, Lozupone CA,
Turnbaugh PJ, Fierer N, Knight R. 2011. Global patterns of 16S rRNA di-
versity at a depth of millions of sequences per sample. Proc Natl Acad
Sci U S A 108:4516–4522. https://doi.org/10.1073/pnas.1000080107.
88. Ihrmark K, Bödeker ITM, Cruz-Martinez K, Friberg H, Kubartova A, Schenck
J, Strid Y, Stenlid J, Brandström-Durling M, Clemmensen KE, Lindahl BD.
2012. New primers to amplify the fungal ITS2 region: evaluation by 454-
sequencing of artificial and natural communities. FEMS Microbiol Ecol 82:
666–677. https://doi.org/10.1111/j.1574-6941.2012.01437.x.
89. Tedersoo L, Anslan S, Bahram M, Põlme S, Riit T, Liiv I, Kõljalg U, Kisand V,
Nilsson H, Hildebrand F, Bork P, Abarenkov K. 2015. Shotgun metage-
nomes and multiple primer pair-barcode combinations of amplicons reveal
biases in metabarcoding analyses of fungi. MycoKeys 10:1–43. https://doi
.org/10.3897/mycokeys.10.4852.
90. Aronesty E. 2011. ea-utils: Command-line tools for processing biological
sequencing data. Available from https://github.com/ExpressionAnalysis/
ea-utils.
91. Vetrovský T, Baldrian P, Morais D. 2018. SEED 2: a user-friendly platform
for amplicon high-throughput sequencing data analyses. Bioinformatics
34:2292–2294. https://doi.org/10.1093/bioinformatics/bty071.
92. Bengtsson-Palme J, Ryberg M, Hartmann M, Branco S, Wang Z, Godhe A,
De Wit P, Sánchez-García M, Ebersberger I, de Sousa F. 2013. Improved
software detection and extraction of ITS1 and ITS 2 from ribosomal ITS
sequences of fungi and other eukaryotes for analysis of environmental
sequencing data. Methods Ecol Evol 4:914–919. https://doi.org/10.1111/
2041-210X.12073.
93. Edgar R. 2013. UPARSE: highly accurate OTU sequences from microbial
amplicon reads. Nat Methods 10:996–998. https://doi.org/10.1038/nmeth
.2604.
94. Thomas D, Vandegrift R, Bailes G, Roy B. 2017. Understanding and miti-
gating some limitations of Illumina MiSeq for environmental sequencing
of fungi. bioRxiv. https://doi.org/10.1101/184960.
95. Cole JR, Wang Q, Fish JA, Chai B, McGarrell DM, Sun Y, Brown CT, Porras-
Alfaro A, Kuske CR, Tiedje JM. 2014. Ribosomal Database Project: data and
tools for high throughput rRNA analysis. Nucleic Acids Res 42:D633–D642.
https://doi.org/10.1093/nar/gkt1244.
96. Stoddard SF, Smith BJ, Hein R, Roller BR, Schmidt TM. 2015. rrnDB:
improved tools for interpreting rRNA gene abundance in bacteria and
archaea and a new foundation for future development. Nucleic Acids
Res 43:D593–D598. https://doi.org/10.1093/nar/gku1201.
97. V
etrovský T, Baldrian P. 2013. The variability of the 16S rRNA gene in bac-
terial genomes and its consequences for bacterial community analyses.
PLoS One 8:e57923. https://doi.org/10.1371/journal.pone.0057923.
98. Kõljalg U, Nilsson RH, Abarenkov K, Tedersoo L, Taylor AFS, Bahram M,
Bates ST, Bruns TD, Bengtsson-Palme J, Callaghan TM, Douglas B,
Drenkhan T, Eberhardt U, Dueñas M, Grebenc T, Griffith GW, Hartmann
M, Kirk PM, Kohout P, Larsson E, Lindahl BD, Lücking R, Martín MP,
Matheny PB, Nguyen NH, Niskanen T, Oja J, Peay KG, Peintner U,
Peterson M, Põldmaa K, Saag L, Saar I, Schüßler A, Scott JA, Senés C,
Smith ME, Suija A, Taylor DL, Telleria MT, Weiss M, Larsson K-H. 2013.
Towards a unified paradigm for sequence-based identification of fungi.
Mol Ecol 22:5271–5277. https://doi.org/10.1111/mec.12481.
99. Magurran AE. 1988. Ecological diversity and its measurement. Princeton
University Press, Princeton, NJ.
100. R Core Team. 2013. R: a language and environment for statistical com-
puting. R Foundation for Statistical Computing, Vienna, Austria.
101. Oksanen J. 2011. vegan: Community ecology package. R package ver-
sion 1.17–9. Available from http://cran.r-project.org/package=vegan.
102. Anderson MJ. 2001. A new method for non-parametric multivariate analy-
sis of variance. Austral Ecol 26:32–46. https://doi.org/10.1111/j.1442-9993
.2001.01070.pp.x.
103. Oksanen J, Blanchet F, Friendly M, Kindt R, Legendre P, McGlinn D,
Minchin P, O’Hara R, Simpson G, Solymos P. 2018. vegan: Community
ecology package. R package version 2.5–2. https://cran.r-project.org/web/
packages/vegan/index.html.
104. Clarke KR, Gorley RN, Somerfield PJ, Warwick RM. 2014. Change in marine
communities: an approach to statistical analysis and interpretation.
https://updates.primer-e.com/primer7/manuals/Methods_manual_v7.pdf.
105. Martinez Arbizu P. 2017. pairwiseAdonis: Pairwise multilevel comparison
using adonis. R package version 00 1. https://github.com/pmartinezarbizu/
pairwiseAdonis.
106. Benjamini Y, Hochberg Y. 1995. Controlling thefalse discovery rate: a prac-
tical and powerful approach to multiple testing. J R Stat Soc Ser B Meth-
odol 57:289–300. https://doi.org/10.1111/j.2517-6161.1995.tb02031.x.
107. Lozupone C, Knight R. 2005. UniFrac: a new phylogenetic method for
comparing microbial communities. Appl Environ Microbiol 71:8228–8235.
https://doi.org/10.1128/AEM.71.12.8228-8235.2005.
108. Halwachs B, Madhusudhan N, Krause R, Nilsson RH, Moissl-Eichinger C,
Högenauer C, Thallinger GG, Gorkiewicz G. 2017. Critical issues in myco-
biota analysis. Front Microbiol 8:180. https://doi.org/10.3389/fmicb.2017
.00180.
109. Robinson MD, McCarthy DJ, Smyth GK. 2010. edgeR: a Bioconductor pack-
age for differential expression analysis of digital gene expression data. Bio-
informatics 26:139–140. https://doi.org/10.1093/bioinformatics/btp616.
Impact of Wood Age on Termite Microbial Assemblages Applied and Environmental Microbiology
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