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RESEARCH COMMUNICATIONS
CURRENT SCIEN CE, VOL. 106, NO. 10, 25 MAY 2014 1430
*For correspondence. (e-mail: jra jendhran@gmail.com)
Microbial diversity in termite nest
A. Manjula1, S. Sathyavathi1, M. Pushpanathan1,
P. Gunasekaran1 ,2 and J. Rajendhran1,*
1Department o f Genetics, School of Biol ogical Sc iences,
Madu rai Kamara j University, Madurai 625 021 , India
2Present address: Thir uvalluvar University, Vellore 6 32 106, India
In the present study, the microbial diversity of termite
nest was studied using bacterial tag encoded amplicon
pyrosequencing by both culture-dependent and
culture-independent approaches. A total of 10,793 and
4,777 high-quality reads were obtained in culture-
independent and culture-dependent approaches res-
pectively. The former approach revealed dominant
phyla Proteobacteria (32%) and Actinobacteria (20%),
whereas the latter approach revealed Firmicutes
(74%) and Proteobacteria (22%) as the most domi-
nant phyla. The significant variation in the microbial
diversity and composition of termitarium assessed by
the two approaches could be due to the fact that
culture-dependent approach explored only selected
groups of microbial population, whereas metagenomic
approach explored complete microbial diversity of
termitarium, which provides credence to the applica-
tion of metagenomic strategy to explore novel micro-
bial species.
Keywords: Metagenome, microbial diversity, pyro-
sequencing, termitarium.
TERMIT ES serve as the best model systems for studying
the symbiotic association between microbes and animals.
The microbial symbionts associated with the termite gut
play a pivotal role in lignocellulose digestion, methan o-
genesis, acetogenesis and nitrogen fixation. Termitarium
is the nest of termites comprised of partially digested
food materials and faecal matter of termites, enriched
with minerals and other organic constituents, which pro-
vides a suitable environment for the existence of a huge
diversity of microorganisms. The termitarium is highly
enriched with humic acids, which serve as terminal elec-
tron acceptors for respiration that supports microbial
growth1. The microbial population of dual origins from
both termites and neighbouring soil might result in
greater microbial diversity in the termitarium than termite
gut or termite-associated soil2. Earlier, microbial diver-
sity present in termite gut and soil environments had been
well characterized3. However, only a few reports are
available on the microbial diversity of termitarium2. The
major limitation associated with conventional cloning and
sequencing method is that it is highly time-consuming,
labour-intensive and may represent only th e predominant
microbial populations. Recently, high-throughput next-
generation sequencing technologies have bypassed the
limitations in traditional sequencing methods. Recent ad-
vancement in high-throughput metagenomic sequencing
technology had opened up the possibility to explore the
total microbial community associated with different envi-
ronmental niches. The culture-based methods are helpful
in understanding the physiological potential of the iso-
lated organisms and their potential applications. How-
ever, the existence of unculturable organisms limits their
access to the actual microbial diversity in culture-
dependent approach. Metagenomic appr oach can be used
to assess the entire microbial community with varying
complexity4. In the present study, we have investigated
the microbial diversity of termitarium by both culture-
dependent and culture-independent approaches using
bacterial tag-encoded FLX amplicon pyrosequencing
(bTEFAP) method.
The termitarium sample was collected from the
Madurai Kamaraj University campus, Madurai, India.
The sample was sieved using muslin cloth to remove
debris and solid wooden particles. For culture-dependent
analysis, 0.1 g of termitarium sample was dissolved in
10 ml of sterile phosphate buffered saline (PBS) and
serial ten-fold dilutions were prepared in PBS up to 10–7.
Aliquots of 0.1 ml were taken from the different dilutions
and plated onto each of the ten differ ent media (soil
extract medium5, AOM16, Luria Bertoni agar, nutrient
agar, Zobell marine agar, King’s B agar, brain heart infu-
sion agar, Trypticase soy agar (0.3%), R2A medium7 and
actinomycete isolation agar) and in cubated at 37C for 7
days. Then the colonies grown on 10–4 to 10–7 diluted
plates in each medium were scraped and homogenized by
vortexing. The pooled samples were stored in 10% glyc-
erol at –80C. From the pooled samples, approximately
1 109 CFUs were used for DNA extraction as described
earlier8. The cells were incubated in lysis buffer (20 mM
Tris-Cl, pH 8.0; 2 mM sodium EDTA; 1.2% Triton
X-100 and 20 mg/ml lysozyme) overnight at 37C and
DNA was extracted from the lysed cells using DNeasy kit
according to the manufactur er’s instructions (Qiagen,
Hilden, German y). For culture-independent analysis,
metagenomic DNA was extracted directly from the termi-
tarium sample and purified using the method described
earlier9.
Pyrosequencing was performed at Research and Test-
ing Laboratory (Lubbock, TX, USA) according to the
method described earlier10 . Initially, sequencing library
was generated with one-step PCR of 30 cycles using the
termitarium metagenomic DNA or genomic DNA isolated
from the pooled culture as template using universal bacte-
rial primers 926F (5AAACTYAAAKGAATTGRCGG3)
and 1392R (5ACGGGCGGTGTGTRC3) as described
earlier10 followed by pyrosequencing of the generated
sequence library. The bTEFAP procedure comprises of
one-step PCR using h ot start high-fidelity Taq poly-
merase, and sequencing of amplicons corresponding to
V6–V9 region of the 16S rRNA gene. The sequences
RESEARCH COMMUNICATIONS
CURRENT SCIEN CE, VOL. 106, NO. 10, 25 MAY 2014 1431
Figure 1. Relative abundance of different phyla observed in the termitariu m sample by culture-independ ent (a) and cultu re-
dependent (b) a pproa ches.
were deposited in MG-RAST metagenomic analysis
server (http://metagenomics.anl.gov) with accession
numbers 4478101.3 (culture-independent) and 4529406.3
(cultur e-dependent) respectively.
The pyrosequencing reads were screened and filtered
for quality and length using initial data-processing tool in
pyrosequencing pipeline available at ribosomal database
project (RDP) server (http://pyro.cme.msu.edu/init/form)
with minimum expected average quality score of 20 and
minimum sequence length of >150 bp. The high-quality
reads were then aligned using aligner tool available at the
RDP server. The operational taxonomic units (OTUs) and
rarefaction curves were created by aligning unique tag
sequences. The richness and diversity indices (Shannon–
Weaver and evenness) at each dissimilarity level were
calculated using pyrosequencing pipeline available at the
RDP ser ver. The ACE and Chao1 diversity indices were
determined using Estimate S software (http://viceroy.eeb.
uconn.edu/EstimateS). Taxonomic assignments were per-
formed using the RDP Classifier pr ogram (http://rdp.
cme.msu.edu/) with 80% bootstrap score. The taxonomic
composition and abundance of microbial species present
in termitarium samples were represented graphically
using the visualization tools for taxonomic composition
of microbial communities (VITCOMIC)11.
Microbial diversity of termitarium sample was investi-
gated by both culture-dependent and culture-independent
approaches through pyrosequencing of 16S rDNA hyper
variable regions (V6 to V9). A total of 10,793 reads and
4,777 reads with an average length of 366 and 411 bp
were obtained in culture-independent and culture-
dependent approaches respectively. The selected high-
quality reads were classified using RDP classifier, which
revealed the existence of a huge microbial diversity in the
culture-independent approach.
In culture-independent approach, more than 91.8% of
reads represented the bacteria domain and only 0.1% of
reads represented archeal group members. It was interest-
ing to note that 8.1% of r eads could not be assigned to
either bacteria or archaea. Sequencing of full-length 16S
rRNA genes (~1.5 kb) may reveal their taxonomic affilia-
tion. The microbial compositions at different phyla for
both culture-independent and culture-dependent approaches
are shown in Figure 1. A total of 20 different bacterial
phyla were observed in culture-independent appr oach,
which represented overall microbial diversity of the ter-
mitarium sample. The culture-independent approach
revealed dominant phyla Proteobacteria (32%), Actino-
bacteria (20%), Bacteroidetes (7%), Fibrobacteres/
Acidobacteria (6%) and few other less abundant phyla
like Gemmatimonadetes, Nitrospirae, Chlamydiae/Verru-
comicrobia, Chloroflexi, Firmicutes, Planctomycetes,
Tenericutes and Deinococcus. Sequence analysis also r e-
vealed the presence of some candidate sequences from
phyla OP10 (1%), TM7 (0.4%), WS3 (0.04%) and BRC1
(0.2%). The dominant phylum Proteobacteria includes
four major families – Bradyrhizobiaceae, Hyphomicro-
biaceae, Phyllobacteriaceae and Rhizobiaceae – which
play a major role in nitrogen fixation in termites. These
results are in consistent with the occurrence of N2-fixing
gamma pr oteobacteria in termite gut3.
The second most abundant phylum present in the
termitarium sample assessed by culture-independent
approach was Actinobacteria, which comprises of three
dominant families – Nocordioidaceae, Microbacteriaceae
and Solirubrobacteraceae – which were reported to play
major roles in degradation of cellulose, lignin and chitin2.
Bacteroidetes, Treponema and Spirochaetes were most
frequently reported in termite gut, which play a major
role in symbiosis12– 14. In culture-independent approach,
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CURRENT SCIEN CE, VOL. 106, NO. 10, 25 MAY 2014 1432
Figure 2 . Ra refaction a nalysis o f termitar ium bacterial commu nity. Rarefaction curves were use d to esti mate richness in the sample and sampling
effort. The vertical axis shows the number of operational taxonomic units (OTUs) expected after sampling the number of sequences as shown in
horizontal axis at 0%, 3% and 5% dissimi larity level. The saturation of rarefaction curves at 3% and 5% dissimila rity level indicates the attainment
of ma ximum sampl ing effort of the sample. a, Culture-dependent. b, C ultu re-independ ent.
the relative abundance of Bacteroidetes, Firmicutes and
Spirochaetes was considerably low. The difference in the
abundance of these bacterial species might be due to the
difference in the physico-chemical properties that exist
between two different environments, i.e. termite gut and
termitarium. The steep increase in the pH between the
midgut and hindgut region of termite has been reported to
alter the microbial community13. Earlier, it was reported
that the abundance of Bacteroidetes was found to be 1.7%
at pH < 4 and 17% at pH > 8 (ref. 15). Another distinc-
tive feature of the termitarium sample was the presence
of Deinococcus-Thermus, a highly hazard-resistant group
of bacteria, which has not been reported to be associated
with the termite gut. Deinococcus sp. has been reported
from extreme environments such as hot springs and
radioactive waste-disposal sites16.
In recent years, termitarium has been used as a biofer-
tilizer to impr ove rice production in paddy fields17 . The
organic matter present in the termitarium is highly rich in
nitrogen, phosphorus and sulphur, which facilitates the
growth of microorganisms such as nitrogen fixers (Rhizo-
bium), decomposers (Pseudomonas) and sulphur oxidiz-
ers (Thiobacillus). The genera Rhizobium, Pseudomonas
and Thiobacillus were also observed in the termitarium
samples assessed by culture-independent approach. The
existence of genera Desulfovibrio, Clostridium and
Enterobacter indicated the pr esence of CO2-reducing ace-
togen bacteria in termitarium. It was also interesting to
note that Geobacter sp. represented 8% of the total bacte-
rial community whose occurrence in termitarium seems
to be unusual. The culture-independent approach also
revealed certain archael group members such as Crenar-
chaeota and Nitrososphaera, which play a major role in
nitrogen fixation. The occurrence of these soil beneficial
organisms in termitarium soil supported the use of this
soil as biofertilizer.
The culture-dependent approach has r evealed the pre-
sence of only three different phyla – Firmicutes (74%),
Proteobacteria (22%) and Actinobacteria (3%). Among
the members of Proteobacteria, Gammaproteobacteria
was found to be abundant in termitarium sample, whereas
the Alphaproteobacteria and Betapr oteobacteria were
poorly represented in culture-dependent approach. Acti-
nobacteria belongs to th e order Actinomycetales, which
includes seven genera – Streptomyces, Microbacterium,
Sinomonas, Kocuria, Micrococcus, Arthrobacter and
Rhodococcus. Of these, Firmicutes comprised of the fam-
ily Bacillaceae (68%) and Proteobacteria comprised of
Enterobacteriaceae (20%). Of the family Bacillaceae, th e
species Bacillus subtilis was found to be predominant,
which has been reported to be involved in lignin degrada-
tion.
Earlier studies on the microbial diversity associated
with termite gut using the conventional methods such as
denaturing gradient gel electrophoresis (DGGE) and 16S
rDNA sequencing have reported the presence of major
phyla Proteobacteria, Actinobacteria, Bacteroidetes/
chlorobi and Fibrobacteres/Acidobacteria16. Similar
results were also observed in termitarium sample by cul-
ture-dependent approach, implying that these phyla form
the major constituents of termite intestinal microflora,
involved in cellulose degradation, nitrogen acquisition
and acetogenesis in termites species. The culturing
method also favoured the growth of obligate aerobic
members that belonged to the phylum Firmicutes. Some
bacteria belonging to genera Klebsiella, Salmonella,
Sodalis and Staphylococcus were obtained only in cul-
ture-dependent approach and not found in culture-
independent appr oach. Not all bacterial genera identified
in culture-dependent approach were recovered by the cul-
ture-independent method. However, culture-independent
method provides more complete data of the bacterial
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CURRENT SCIEN CE, VOL. 106, NO. 10, 25 MAY 2014 1433
Table 1. Prediction of spe cies di versity by rich ness estimators at two dissimilari ty levels comparing cu lture-dependent and
metagenomic appr oaches.
Method No. of sequ ences Dista nce OTUs ACE Chao1 Shannon Evenness
Metagenomic 10,793 0.03 3469 6924 .27 6504 .51 7.42914 0.9113 7
0.05 2527 4103 .64 3904 .94 6.9846 0.89149
Culture dependent 4,777 0.03 87 99.74 9 2.76 2.55298 0.57166
0.05 48 5 0.52 49.66 1.88139 0 .486
Figure 3. Comparative mapping of culture-indepe ndent and culture-dependent microbia l diver sity in the termitarium sampl e using VITCOMIC.
Blue dots indicate the relative abundance of the sequences in the culture-independent method and red dots indicate the relative abundance in the
cultured popu lation. Grey dots i ndicate the occu rrence of specific species in both cu lture-independent and culture-dependent appr oache s. The dots
in the innermost circle (i) represent 8 0–85% identity with the exi sting 16S rRNA gen e sequences in data bases; Similarly, other circles repre sent s
higher levels of identity with the existi ng sequenc es in the database a s follows: (ii) 85–90%; (iii) 90–95% and (iv) 95 –100 %.
community, including viable but not culturable bacteria
and also nonviable bacteria. In other cases, culturable
methods favour the growth of certain bacteria that are
less abundant in the environment, which could not be
detected in metagenome by culture-independent methods.
Recently, Shade et al.8 have reported that culturing cap-
tures the rar e bacterial community from th e soil samples,
which was poorly represented in whole metagenome-
based analysis.
The sampling effort and the richness of the microbial
diversity in the termitarium by both culture-dependent
and culture-independent approaches were estimated by
rarefaction analysis (Figure 2). In culture-dependent
approach, the rarefaction curves attained complete satura-
tion level, and required no further sampling, whereas the
rarefaction curves did not attained saturation level for
culture-independent approach. The clustering analysis has
revealed that the sequences were clustered into 3469 and
3537 OTUs for culture-independent and 87 and 48 OTUs
for culture-independent approaches at 3% and 5% dissimi-
larity levels respectively (Table 1). Diversity index is a
mathematical measure of species diversity in a community.
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CURRENT SCIEN CE, VOL. 106, NO. 10, 25 MAY 2014 1434
Diversity indices provide important in formation about
rarity and commonness of species in a community. The
ability to quantify diversity is important for biologists to
understand the community structure. The Shannon diver-
sity index (H) is commonly used to characterize species
diversity in a community. The index accounts for both
abundance and evenness of the species present. The di-
versity and evenness indices for culture-independent ap-
proach are much higher than those for the culture-
dependent approach, which indicated that the culture-
independent approach not only has a gr eater number of
species, but the individuals in the community are distri-
buted more equitably among these species.
VITCOMIC tool was used to classify th e bacterial
populations at species level using BLASTn analysis. The
results are represented in a circle map where each circle
is assigned to different similarity levels starting from
80% followed by 85%, 90%, 95% and 100%. Each dot
indicates the average similarity and the size of th e dots
represents the relative abundance of the sequences. The
overall taxonomic composition of the microbial commu-
nity of culture-independent and cultur e-dependent analy-
sis is shown in Figure 3. From the total reads obtain ed in
culture-independent approach, 57% of sequences showed
91–95% similarity level and only 19% of sequences
showed 96–100% similarity with existing rRNA gene
sequences in the database. A total of 23% of sequences
showed only 85–90% of similarity. Approximately 1% of
the reads showed less than 85% similarity with existing
sequences. In culture-dependent method, 96% of sequen-
ces showed 96–100% similarity level and only 4%
sequences were assigned at 91–95% similarity. No
sequences were obser ved in the range between 80% and
90% similarity levels. In Figure 3, each species in the
reference database was placed in circles with ordered
phylogenetic r elatedn ess. Physical distances between the
nearest species in the plot indicate the genetic distances
of 16S rRNA genes between them. The circle in the plot
indicates the boundaries of BLASTn average similarities.
Each dot represents average similarities of each sequence
against the nearest relative species in the r eference data-
set. The size of these dots indicates the relative abun-
dance of sequence in the sample.
To conclude, the microbial diversity associated with
termitarium habitat was assessed by both culture-
independent and culture-dependent approaches. Both the
approaches provided knowledge of a wide spectrum of
termitarium-associated microbial populations. Further
sequencing efforts with higher sequencing depth may
help in obtaining further insights into microbial diversity
of the habitat.
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ACKNOWLEDGEMENTS. A.M. thank s CSIR, New Delhi for pro-
viding fina ncial support in the form of Senior Research Fello wship. We
thank central facilities UGC-CAS, UGC-CEGS, UGC-NRCBS, and
DBT -IPLS and DST-PURSE programmes at the School of Biologica l
Sciences, M adurai Kamara j University, Ma durai.
Receiv ed 4 December 2 013 ; revised accepted 3 April 2014
