Metagenomics of microbial and viral life in terrestrial geothermal environments

Abstract

Geothermally heated regions of Earth, such as terrestrial volcanic areas (fumaroles, hot springs, and geysers) and deep-sea hydrothermal vents, represent a variety of different environments populated by extremophilic archaeal and bacterial microorganisms. Since most of these microbes thriving in such harsh biotopes, they are often recalcitrant to cultivation; therefore, ecological, physiological and phylogenetic studies of these microbial populations have been hampered for a long time. More recently, culture-independent methodologies coupled with the fast development of next generation sequencing technologies as well as with the continuous advances in computational biology, have allowed the production of large amounts of metagenomic data. Specifically, these approaches have assessed the phylogenetic composition and functional potential of microbial consortia thriving within these habitats, shedding light on how extreme physico-chemical conditions and biological interactions have shaped such microbial communities. Metagenomics allowed to better understand that the exposure to an extreme range of selective pressures in such severe environments, accounts for genomic flexibility and metabolic versatility of microbial and viral communities, and makes extreme- and hyper-thermophiles suitable for bioprospecting purposes, representing an interesting source for novel thermostable proteins that can be potentially used in several industrial processes.

Full text

REVIEW PAPER
Metagenomics of microbial and viral life in terrestrial
geothermal environments
Andrea Strazzulli .Salvatore Fusco .Beatrice Cobucci-Ponzano .
Marco Moracci .Patrizia Contursi
Published online: 5 June 2017
ÓThe Author(s) 2017. This article is an open access publication
Abstract Geothermally heated regions of Earth,
such as terrestrial volcanic areas (fumaroles, hot
springs, and geysers) and deep-sea hydrothermal
vents, represent a variety of different environments
populated by extremophilic archaeal and bacterial
microorganisms. Since most of these microbes thriv-
ing in such harsh biotopes, they are often recalcitrant
to cultivation; therefore, ecological, physiological and
phylogenetic studies of these microbial populations
have been hampered for a long time. More recently,
culture-independent methodologies coupled with the
fast development of next generation sequencing
technologies as well as with the continuous advances
in computational biology, have allowed the production
of large amounts of metagenomic data. Specifically,
these approaches have assessed the phylogenetic
composition and functional potential of microbial
consortia thriving within these habitats, shedding light
on how extreme physico-chemical conditions and
biological interactions have shaped such microbial
communities. Metagenomics allowed to better under-
stand that the exposure to an extreme range of
selective pressures in such severe environments,
accounts for genomic flexibility and metabolic versa-
tility of microbial and viral communities, and makes
extreme- and hyper-thermophiles suitable for bio-
prospecting purposes, representing an interesting
source for novel thermostable proteins that can be
potentially used in several industrial processes.
Keywords Hyperthermophiles Geothermal
environments Microbial and viral metagenomics 
CRISPR Enzyme discovery
1 Background
Hot springs populated by extreme thermophiles (T
opt
:
65–79 °C) and hyperthermophiles (T
opt
[80 °C)
(DeCastro et al. 2016) are very diverse and some of
them show combinations of extreme chemo-physical
conditions, such as temperature, acidic or alkaline
pHs, high pressure, and high concentrations of salts
and heavy metals (Lo
´pez-Lo
´pez et al. 2013). As with
all studies of environmental microbiology, our under-
standing of the composition, functional and physio-
logical dynamics, and evolution of extreme- and
hyper-thermophilic microbial consortia has lagged
A. Strazzulli M. Moracci P. Contursi (&)
Dipartimento di Biologia, Universita
`degli Studi di Napoli
Federico II, Complesso Universitario Monte S. Angelo,
Via Cinthia, 80126 Naples, Italy
e-mail: contursi@unina.it
A. Strazzulli B. Cobucci-Ponzano M. Moracci
Institute of Biosciences and Bioresources, National
Research Council of Italy, Via P. Castellino 111,
80131 Naples, Italy
S. Fusco
Division of Industrial Biotechnology, Department of
Biology and Biological Engineering, Chalmers University
of Technology, Gothenburg, Sweden
123
Rev Environ Sci Biotechnol (2017) 16:425–454
DOI 10.1007/s11157-017-9435-0
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substantially behind. However, recent advances in
‘omics’ technologies, particularly within a system
biology context, allowed significant progress in this
field. These include the prediction of microbial
consortia functionality in situ and the access to
enzymes with important potential applications in
biotechnology (Cowan et al. 2015). Metagenomics is
particularly relevant in geothermal environments
since most extremophilic microorganisms are recalci-
trant to cultivation-based approaches (Amann et al.
1995; Lorenz et al. 2002). The rapid and substantial
cost reduction in next-generation sequencing (NGS)
(Fig. 1) has dramatically accelerated the development
of sequence-based metagenomics as witnessed by the
explosion of metagenome shotgun sequence datasets
in the past few years. Metagenomics provides access
to the gene composition of microbial communities
offering a much deeper description than phylogenetic
surveys, which are often based only on the diversity of
the 16S rRNA gene. In addition, metagenomic
datasets can provide novel, and even unexpected
insights into community dynamics. For example,
surprisingly, it has been found that both extreme
thermophiles and hyperthermophiles showed a statis-
tically significant higher number of clustered regularly
interspaced short palindromic repeats (CRISPR)
sequences in their genomes than mesophiles, suggest-
ing that viruses/phages may play an important role in
shaping composition and function of thermophiles
communities as well as in driving their evolution
(Cowan et al. 2015). In addition, functional metage-
nomic strategies, exploiting expression libraries in
conventional microbes, are powerful alternatives to
conventional genomic approaches for producing novel
enzymes for industrial applications.
This review offers an overview on recent develop-
ments of metagenomics applied to terrestrial geother-
mal environments with temperature C65 °C. We
describe how recent progress in deep sequencing
technology led to the expansion of the studies on
Fig. 1 Evolution of technology sequencing in the past
10 years. The main characteristics of the different techniques,
including main pros and cons, are highlighted. NGS, producing
millions of shortreads (25–650 bp) is generally less expensive
than the Sanger sequencing and shows faster library construc-
tion without bias for toxic genes in the cloning host
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123
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microbial and phage/viral communities populating
these sites (Sect. 2) as well as to the use of CRISPR
loci as a metagenomic tool to identify specific hosts for
a viral assemblage (Sect. 2.2.1). Then, particular
emphasis is given to the most recent literature on the
distribution of microbiome and virome communities
populating terrestrial geothermal sites worldwide
(Sect. 4), and to the exploitation of functional
metagenomics for the discovery and production of
enzymes for biotechnology (Sect. 5).
2 Microbial and viral metagenomics of geothermal
environments
2.1 Microbial metagenomics
The microbiological study of geothermal environ-
ments officially started in the early 1970s with the
innovative work of Thomas Brock and followed, in the
1980s, by the early microbial studies by using 16S
rRNA analysis allowing the identification of Archaea
as a kingdom separated from Bacteria [Brock et al.
1971; Woese et al. 1990, which is reviewed in Brock
(2001)]. Since then, this approach, overcoming the
limitations of thermophilic microorganisms isolation,
has continuously revealed novel uncultivated micro-
bial lineages, proving that isolates represent less then
20% of the phylogenetic diversity in Archaea and
Bacteria (Reysenbach et al. 1994; Stahl et al. 1984;
Wu et al. 2009). Several microbiological surveys of
(hyper)thermophilic environments were performed in
the last 10 years by using 16S rRNA gene profiling.
This led to the first microbial characterization of
different geothermal areas, allowing the identification
of the dominant phyla/genera among the microbial
communities populating these environments and the
correlations with geophysical and climatic parameters
(Meyer-Dombard et al. 2005; Wang et al. 2014).
Despite the easiness of this approach, the assessment
of abundance estimation and of microbial diversity
from a single 16S rRNA gene is challenging for
several reasons (see the section below: Approaches
and tools for microbial and viral metagenomics)
(Fig. 2).
An alternative approach is the sequence-based
metagenomic (SBM) analysis, which has been
exploited successfully also on microbiomes
populating geothermal sites. This method provides
access to the gene composition of a microbial
community and to its encoded function, giving a
much broader and detailed phylogenetic description
than the 16S rRNA profiling (Wu et al. 2014). Indeed,
SBM, which is especially valuable for complex
communities requiring deeper sequencing, represents
the best approach in geothermal hot springs in which,
despite the low microbial complexity, the population
is not well characterized because of the difficulties in
isolating new strains through classical microbiology
approaches. As reported by Bahya and co-workers,
SBM led for the first time in 2007 to the identification
of two different Synechococcus populations inhabiting
the microbial mats of the Octopus Spring in the
Yellowstone National Park (YNP). This study
revealed extensive genome rearrangements and dif-
ferences related to the assimilation and storage of
several elements such as nitrogen, phosphorus and
iron suggesting that the two populations have adapted
differentially to the fluxes and gradients of chemical
elements (Bhaya et al. 2007). In addition, SBM
showed correlations between function and phylogeny
of unculturable microorganisms allowing the study of
evolutionary profiles and the identification of novel
candidate phyla (i.e. Geoarchaeota, Lokiarchaeota
and Aigarchaeota). These studies contributed to the
understanding of the archaea evolution and their
metabolic interactions that may not have been
addressed with the basic 16S rRNA gene profiling
(Kozubal et al. 2013; Spang et al. 2015). At the onset,
SBM was generally more expensive than 16S rRNA
sequencing, however, the constant reduction of the
NGS costs (Fig. 1) made this approach more and more
convenient thereby considerably increasing the num-
ber of metagenomic projects available and making it a
valid support, or even a direct alternative, to the 16S
rRNA profiling. In addition, the sequence data banks
resulting from SBM studies of geothermal environ-
ments are an important repository of genes encoding
for novel enzymes with potential biotechnological
interest. Therefore, in silico functional screening of
metagenomic data banks allows the identification of
genes that can be cloned and expressed in mesophilic
hosts to produce recombinant enzymes. Alternatively,
metagenomic expression libraries can be constructed
to perform direct functional screenings of the enzymes
of interest (see the section Enzyme discovery below).
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2.2 Viral metagenomics
Phages are generally the predominant biological entity
in every ecosystem and have the capability to greatly
influence the structure, composition and function of
their host population(s) (Snyder et al. 2015). This
holds true also in geothermal environments, although
their density is lower (typically 10–100-fold less
viruses than host cells) if compared to mesophilic
aquatic systems (Lo
´pez-Lo
´pez et al. 2013). Despite
their importance, the knowledge about the diversity
and biology of phages on the microbial communities
in these ecosystems is still limited (Schoenfeld et al.
2008). Since not obvious common genetic markers
exist, phages are still classified according to their host
range and morphology, thus making challenging the
discovery of genetic variants and novel subtypes. In
addition, the rate of lateral gene transfer events within
the geothermal environments is exceptionally high, a
fact that renders uncertain the resolution of evolution-
ary histories of the known major viral/phages groups
(Diemer and Stedman 2012).
Geothermal environments with temperature
[80 °C tend to be dominated by archaea over bacteria
and eukaryotes (Bolduc et al. 2015) and therefore,
the majority of viruses isolated from two types of
habitats are archeoviruses (Snyder et al. 2015). At
present, one order and 10 families (Fuselloviridae,
Bicaudaviridae, Ampullaviridae, Clavaviridae, Gut-
taviridae, Lipothrixviridae, Rudiviridae, Globuloviri-
dae, Myoviridae, Siphoviridae) of archaeal viruses
have been documented (Fusco et al. 2015a,b;
Prangishvili 2013; Snyder et al. 2015; Wang et al.
2015b). Until relatively recent times, the only
methodology available to study these viruses was
through the cultivation of their hosts (Lo
´pez-Lo
´pez
et al. 2013). By systematically applying this approach,
our knowledge on viruses populating (hyper)thermal
environments over the last 30 years has considerably
expanded thanks to the pioneer work of Wolfram
Zillig and, subsequently, of several groups in Europe
and USA (Bize et al. 2008; Dellas et al. 2013,2014;
Diemer and Stedman 2012; Haring et al. 2005; Peng
et al. 2012; Prangishvili et al. 2001,2006; Prangishvili
Fig. 2 Schematic flow chart of the analysis approaches of a
sample from geothermal sites. 16S rRNA profiling (purple),
microbial metagenomics (light blue), viral metagenomics
(orange), single-cell genomics (yellow) and functional metage-
nomics (green). Dashed arrows and box indicate optional steps.
(Color figure online)
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and Garrett 2004,2005; Rice et al. 2001,2004; Snyder
et al. 2011; Snyder and Young 2013; Zillig et al.
1996). While enrichment cultures have been invalu-
able in the study of thermophilic viruses, contextual
information, such as relative abundance, diversity, and
distribution, was mainly unknown.
Direct SBM analysis of environmental samples
together with the development of ad hoc bioinformat-
ics tools (Rampelli et al. 2016; Roux et al. 2014,2015)
had a revolutionary impact on virology of extremo-
philes providing a better understanding of viral specific
role in these environmental niches. In addition, viral
metagenomics and genomics of cultured viruses has
also revealed that a large proportion of predicted
archaeal viral genes are ‘unknown’ or ‘hypothetical’
(Contursi et al. 2014a; Prato et al. 2008) expanding the
content of genetic information referred as biological
‘dark matter’ (Martinez-Garcia et al. 2014). It is
expected that the annotation of additional sequenced
genomes as well as the exploitation of bioinformatics
tools based on structural protein homologies will help
to disclose this unexplored repository of viral genes
(Fig. 2). Interestingly, non-coding nucleic acid
sequences also play a critical role in archaeal virus
function, which is a virtually underestimated topic in
archaeal virology (Contursi et al. 2010).
Despite the promising scientific impact, only few
viral metagenomics on geothermal samples have been
reported so far (see also the paragraph: Geographical
distribution of microbiomes). Some studies were
pursued by deep sequencing of environmental samples
enriched for virus particles (Bolduc et al. 2012; Garrett
et al. 2010; Schoenfeld et al. 2008) whereas others
were performed by retrieving viral sequences from
whole SBM datasets (Gudbergsdottir et al. 2016;
Servı
´n-Garciduen
˜as et al. 2013a,b).
In addition, recently, the same approach allowed to
focus on the study of CRISPR that became one of the
most advanced fields in viral metagenomics and that is
reviewed below.
2.2.1 CRISPR
CRISPR is a mechanism of acquired immunity
playing a role in controlling the equilibrium between
prokaryotic populations and their parasites. This
system, which is found in the 80% of archaea and
40% of bacteria, recognizes and memorizes short
sequences from the genome of the viral or phage
invader (Barrangou et al. 2007; Brouns et al. 2008;
Fusco et al. 2015a; Marraffini and Sontheimer 2010;
van der Oost et al. 2009). The peculiar structure of
CRISPR loci (Fig. 3), with alternating spacer and
repeat units, results in a computationally identifiable
sequence signature. Several bioinformatics tools have
been developed to identify CRISPR spacers in bacte-
rial genomes (Biswas et al. 2013; Bland et al. 2007;
Edgar and Myers 2005; Grissa et al. 2007; Skennerton
et al. 2013), and spacer sequences have also been
collected in publicly accessible databases (Grissa et al.
2007; Rousseau et al. 2009).
A challenge in the field of archaeal virology is the
development of new approaches in order to move
rapidly from analysis of SBM to the identification and
isolation of the viral nucleic acids present in the
environmental samples as well as of their respective
hosts. In this regard, analyses of CRISPR spacers across
metagenomics data provide high-resolution genetic
markers that not only recapitulate the history of
infections in the host genomes, but also allow individ-
ual phage strains to be tracked by following their
presence in the very samehost genomes (Vale and Little
2010) (Fig. 2). This has been done either by extracting
spacers from sequenced host genomes or by PCR
identifying CRISPR spacers from the same sample
(Gudbergsdottir et al. 2016). An alternative approach
consists in exploiting a microarray platform built up
with CRISPR spacer sequences of host metagenomics
data to examine temporal changes in viral populations
within this environment (Snyder et al. 2010).
3 Approaches and tools for microbial and viral
metagenomics
3.1 Preparation of high-molecular weight DNA
and metagenomic libraries
The step of metagenomic DNA (mDNA) extraction
from samples collected in extreme environments plays
a critical role for the whole metagenomic analysis
workflow (Fig. 2). To be sure that the genetic infor-
mation obtained is representative of the whole micro-
biome, mDNA preparation requires specific protocols
to preserve, as much as possible, the quality and the
amount of the nucleic acids to guarantee best metage-
nomic library and the subsequent sequencing
approach. mDNA extraction from geothermal
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environments can be performed by following two
general strategies sharing the critical removal of
humic acid, a major soil component made of phenolic
moieties covalently bound to DNA (Lakay et al.
2007), which inhibits restriction enzymes and PCR
amplification (Tebbe and Vahjen 1993). The first
method is the ‘‘direct mDNA extraction’’ and consists
in cell lysis directly followed by the nucleic acids
separation from soil particles within the sample,
generally providing quickly high DNA amounts.
Fig. 3 Overview of the CRISPR-Cas system. Upon infection,
CRISPR immune system operates by recognizing foreign
genetic elements, such as plasmids and bacteriophages (blue
solid line) and cleaving them into short DNA fragments
(protospacers). In adaptation, these latter are then inserted, as
new spacers, into the sequence array of a CRISPR locus. Such a
locus consists of several short palindromic repeats, each
approximately 20–50 bp in length, interspersed by spacers
(Grissa et al. 2007). This array is typically located adjacent to a
leader sequence (black rectangle) and CRISPR-associated cas
genes (coloured arrows) (Rath et al. 2015). A newly acquired
spacer (blue box highlighted by a black arrow) is generally
inserted directionality into the CRISPR array region, which is
closest to the leader sequence, thus preserving the history of
viral infections. In transcription and processing, the repeats-
spacers array is transcribed into a pre-crRNA, which is cleaved
at each repeat to yield individual mature CRISPR RNAs
(crRNA). These guides a dedicated set of CRISPR-associated
(Cas) proteins to their targets during cellular surveillance
(Marraffini and Sontheimer 2010; van der Oost et al. 2009).
Indeed, upon reinfection, when the DNA or in some cases
mRNA of remembered invaders is identified, the CRISPR-Cas
system binds to invading phage DNA resulting in the
degradation of the phage genome sequence (Stern and Sorek
2011). (Color figure online)
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By contrast, in the second approach, named ‘‘indi-
rect mDNA extraction’’, the environmental samples
need to be physically and mechanically treated before
cell lysis. Although this method requires abundant
initial sample and is time-consuming if compared to
the ‘‘direct mDNA extraction’’, it is suitable for in-
depth sequencing and creation of fosmid libraries,
because of the reduced proportion of eukaryotic
sequences present in the sample and increased length
of the mDNA chunks (Delmont et al. 2011).
Library production for most sequencing technolo-
gies require not only high amounts of mDNA but in
some cases also amplification of nucleic acids gener-
ally performed by Multiple Displacement Amplifica-
tion (MDA). This method, used both in metagenomics
and single-cell genomics, can amplify femtograms to
up to micrograms of DNA (see below).
When only a specific part of the ecological
community is the target of analysis, as the viral
population, additional steps can be applied (Fig. 2).
Indeed, the relative abundance of viral particles in a
sample, compared to that of other organisms such as
bacteria or host cells (or their genomes), is a critical
factor for the discovery of viruses when using
metagenomic analysis. Enrichment methods applied
to the detection of viruses in hot springs are method-
ologically challenging mainly because extremophilic
viruses and their microbial hosts are rarely cultivable
(Edwards and Rohwer 2005). In addition, the majority
of the viral metagenomic reads (50–90%) show no
significant similarity to sequences from known organ-
isms. Current approaches for virus isolation and
concentration include filtration and/or adsorption to
and subsequent elution from positively or negatively
charged membrane filters (Katayama et al. 2002) and
pelletting of virus particles through ultracentrifugation
(Bolduc et al. 2012; Short and Short 2008). The
drawbacks include selective adsorption of viruses onto
treated filters, limited volume capacity and low or
variable recoveries of viruses. An efficient virus
purification and concentration method consisting in
the combination of tangential flow filtration (TFF)
with centrifugal ultrafiltration technology, has been
employed in order to obtain high density of viral
particles from high turbidity seawaters samples (Sun
et al. 2014). Such enrichment method has been applied
to recover hot springs viral particles for metagenomic
studies (Diemer and Stedman 2012; Schoenfeld et al.
2008). Finally, an efficient and reliable method to
concentrate viruses from ecological samples has been
developed by using FeCl
3
as a low-cost and non-toxic
agent that leads to nearly complete recovery (92–95%)
(John et al. 2011).
3.2 Next generation sequencing technology
Sanger sequencing, developed almost 40 years ago, is
still considered a good method for nucleic acid
sequencing, and is characterized by the use of sequenc-
ing library with large insert sizes ([30 Kb), long read
length (up to 1000 bp) with a relative low error rate.
However, over the past 10 years shotgun sequencing,
including metagenomic analysis, has gradually shifted
from this technology to NGS with faster library
construction, non associated to bias for toxic genes
for the cloning host (Sorek et al. 2007) and generally
less expensive. NGS platforms (Fig. 1) usually produce
millions of short sequence reads up to 800 bp. To date,
the most used sequencing techniques are Roche 454 and
Illumina that have now been extensively applied to
metagenomic from geothermal environments (Inskeep
et al. 2013b; Menzel et al. 2015) (Table 1).
The Roche 454 system produces an average read
length between 600 and 800 bp, reducing significantly
the number of reads that are too short to be annotated
without assembly (Wommack et al. 2008). The main
drawbacks of this method with respect to metage-
nomic applications are the production of artificial
replicate sequences (up to 15% of the resulting
sequences), which affect the estimation of both
microbial and gene abundances (Gomez-Alvarez
et al. 2009) and a high error rate in homopolymer
regions (Margulies et al. 2005). Despite these disad-
vantages, Roche 454 is much cheaper (up to 16,000$
per Gb) than the Sanger sequencing. In addition, also
the sample preparation has been optimized requiring
nanograms of mDNA for the sequencing of a single-
end library (Adey et al. 2010), although pair-end
sequencing might still require micrograms quantities.
If compared to the Roche 454 technology, Illumina,
being sensibly cheaper with a cost of *200$ per Gbp,
usually reads up to 300 bp (Fig. 1). In addition,
although more time consuming, Illumina has limited
systematic errors and the quality control allows to
detect and eliminate bad reads. Faster analysis can be
obtained with the Illumina MiSeq instrument. How-
ever, despite there is evidence that the MiSeq offers
valuable information for shotgun sequencing and can
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Table 1 State-of-the-art of the microbial metagenomics in geothermal environments worldwide
Number of site
(ref. Fig. 5)
Abbreviation
Location
Sequencing method
Survey
approach
Archaea
(% reads)
Bacteria
(% reads)
Main chemical features
Dominant microorganisms
References
1
ObP
Yellowstone
National
Park, USA
Aurora Genetic Analysis
System
16S
N.R.
N.R.
N.R.
Aquificales (Thermocrinis)
Uncultured Crenarchaeota
(Meyer-Dombard et al.
2005)
2
SSp
Aquificales (Hydrogenothermus )
Desulphurococcaceae - Thermoproteaceae
3
BP
Aquificales (Thermocrinis)
Uncultured Crenarchaeota
4
MRY
Roche/454 GS FLX
Low concentration of carbonates and bicarbonate,
high SO42−/Cl−ratio
Cyanobacteria
Chlorobi
Chloroflexi
(Jiang and Takacs-
Vesbach 2017)
5
MKL
Low concentration of carbonates and bicarbonate,
high SO42−/Cl−ratio
Aquificae
6
NOR
Low concentration of carbonates and bicarbonate,
Low SO42−/Cl−ratio
Cyanobacteria
Proteobacteria
Chloroflexi
7
DS
Roche/454 Titanium FLX
Metagenomics
Sulfur rich
Aquificales (Hydrogenobaculum)
(Inskeep et al. 2013b)
(Beam et al. 2014)
(Takacs-Vesbach et al.
2013)
8
OSP_14
FeIII-oxide rich
Aquificales (Hydrogenobaculum)
(Inskeep et al. 2013b)
(Takacs-Vesbach et al.
2013)
9
MHS
Low dissolved oxygen
concentration
Aquificales (Sulfurihydrogenibium)
(Inskeep et al. 2013b)
(Inskeep et al. 2010)
(Takacs-Vesbach et al.
2013)
10
CS
Aquificales (Sulfurihydrogenibium)
(Inskeep et al. 2010)
(Inskeep et al. 2013b)
(Takacs-Vesbach et al.
2013)
11
OS
Low-sulfide concentration
Aquificales (Thermocrinis)
(Inskeep et al. 2013a)
(Schoenfeld et al.
2008)
(Pride and Schoenfeld
2008)
(Takacs-Vesbach et al.
2013)
12
BCH
Aquificales (Thermocrinis)
(Inskeep et al. 2013b)
(Takacs-Vesbach et al.
2013)
13
CH
96.4
0.2
Low concentrations of dissolved
O2, H2S, H2and CH4.
Presence in suspention of S and SiO2
Crenarchaeota (Sulfolobales)
(Inskeep et al. 2010)
(Inskeep et al. 2013a)
(Inskeep et al. 2013b)
(Menzel et al. 2015)
14
NL
58
12.4
Low concentration of dissolved oxygen and sulfide
Presence of elemental sulfur and SiO2
Crenarchaeota (Sulfolobales)
(Inskeep et al. 2013a)
(Inskeep et al. 2013b)
(Menzel et al. 2015)
(Bolduc et al. 2012)
15
MG
N.R.
N.R.
Low dissolved oxygen concentration
Presence of sulfur sediments
Crenarchaeota (Desulfurococcales, Thermoproteales)
(Inskeep et al. 2013a)
(Inskeep et al. 2013b)
16
CIS
Crenarchaeota (Desulfurococcales, Thermoproteales)
(Inskeep et al. 2013a)
(Inskeep et al. 2013b)
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Table 1 continued
17 JCHS Crenarchaeota (Desulfurococcales, Thermoproteales)
(Inskeep et al. 2010)
(Inskeep et al. 2013a)
(Inskeep et al. 2013b)
18
WS
Low dissolved oxygen
concentration
Crenarchaeota
Aquificales
(Inskeep et al. 2013a)
(Inskeep et al. 2013b)
19
OSP_8
FeIII-oxide rich
Crenarchaeota
Mixed, Novel Archaeal
(Inskeep et al. 2013a)
(Inskeep et al. 2013b)
20
NGB
Crenarchaeota (Sulfolobales)
(Inskeep et al. 2010)
21
Is2-5S
Iceland
Illumina Hiseq
33
62.1
Rich in organic materials
Aquificales (Thermocrinis)
(Menzel et al. 2015)
22
Is3-13
19.7
79.0
Proteobacteria
23
Kam37
Kamchatka
Roche/454 Titanium FLX
Illumina MiSeq
16S
N.R.
N.R.
N.R.
Aquificales
Euryarchaeota
Crenarchaeota
Miscellaneous Crenarchaeotic Group
(Eme et al. 2013)
(Wemheuer et al. 2013)
24
Mutnovsky
Enterobacteriaceae
Miscellaneous Crenarchaeotic Group
(Wemheuer et al. 2013)
25
Bourlyashchy
Roche/454 GS FLX
Illumina MiSeq *
64*
30*
N.R.
Aquificales (Sulfurihydrogenibium and
Hydrogenobacter) in water
Thermodesulfobacteria (sediment)
Thermoproteales (Pyrobaculum) both water and
sediment
(Chernyh et al. 2015)
(Merkel et al. 2017)
26
Sery
Illumina MiSeq
16S
71
29
N.R.
Thermodesulfobacteria (Caldimicrobium)
(Merkel et al. 2017)
27
Thermofilny
99
1
N.R.
Aquificales (Sulfurihydrogenibium)
28
Izvilisty
76
23
N.R.
Aquificales (Sulfurihydrogenibium)
Dictyoglomus
29
3423
2
97
N.R.
Nanoarchaeota
30
3462
96
4
N.R.
Aquificales (Sulfurihydrogenibium)
31
3460
45
48
N.R.
Euryarchaeota
32
3401
14
86
N.R.
Nanoarchaeota
33
3404
99
1
N.R.
Aquificales (Sulfurihydrogenibium)
34
AI
Furnas Valley,
Azores
Roche/454 Titanium FLX
16S
and
metagenomics
N.R.
68
High dissolved organic carbon concentration in AIV
Proteobacteria
(Sahm et al. 2013)
-
AII
N.R.
not reported
-
AIII
not reported
35
AIV
35
40.0
Aquificae, Dictyoglomi
Crenarchaeota
-
BII
N.R.
N.R.
not reported
-
BIII
not reported
-
CII
not reported
36
SK
Perak, Malaysia
Illumina Hiseq
10.44
88.44
High degree of total organic carbon
Firmicutes
(Chan et al. 2015)
37
Dgg
Hot Springs of
Rehai region
in Tengchong,
China
Roche/454 Titanium FLX 16S ∼90
Aquificae
38
Drty-1
Crenarchaeota
39
GmqS
Aquificae
40
GmqC
Aquificae (water)
Crenarchaeota (sediment)
41
GmqP
Aquificae
Rev Environ Sci Biotechnol (2017) 16:425–454 433
123
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be used to test-run sequencing libraries before analysis
on HiSeq instruments, deeper sequencing is strictly
required in order to detect the majority of species in a
sample and to perform an high quality assembly with a
good abundance estimation of the microorganisms
(Clooney et al. 2016).
A detailed comparison about the advantages and
limitations of Roche 454 and Illumina platforms was
reviewed by Luo et al. (2012). The authors suggest that
both NGS technologies are reliable for quantitatively
assessing genetic diversity within environmental
communities. Moreover, considering the longer and
more accurate contigs obtained with Illumina by
assembly (despite the substantially shorter read
length) and the monetary savings by one fourth of
the cost relatively to Roche 454, Illumina method may
be a more favourable approach for metagenomic
studies (Luo et al. 2012).
3.3 16S rRNA PCR amplification
versus sequence-based metagenomics
and single cell genomics
Generally, 16S rRNA gene profiling is considered as a
first approach in a metagenomic survey and has been
applied to the analysis of the different microbial
populations since the middle 1990s with recent boosts
due to the advances of the NGS sequencing platforms
(Fig. 1). The comparison of 16S rRNA sequence
profiles across different samples, indeed, can explain
how microbial communities are related across differ-
ent environmental conditions. Typically, this
approach involves the amplification and the sequenc-
ing by NGS of short hypervariable regions (V1-V9) of
the 16S rRNA gene that demonstrate considerable and
differential sequence diversity in microorganisms.
Although a single hypervariable region is not suffi-
cient to phylogenetically classify microorganisms, the
hypervariable regions V2, V3 and V6 show the
maximal heterogeneity among the different lineages
providing the best discriminating power for the
analysis of microbial communities (Chakravorty
et al. 2007). Today, NGS can produce large 16S
rRNA datasets containing hundreds of thousands of
16S RNAs fragments allowing the survey of several
microbial communities simultaneously in different
hyperthermophilic environments (Hou et al. 2013;
Sahm et al. 2013). Despite the ease with which the 16S
rRNA profiling can be made, this approach is known to
Table 1 continued
42 JmqL Aquificae (water)
Crenarchaeota (sediment)
43
JmqR
Aquificae
44
Zzq
Crenarchaeota
45
HtjL
Crenarchaeota
46
HtjR
Crenarchaeota
Aquificae
47
SrbzU
N.R.
Aquificae
48
SrbzD
Aquificae
49
Gxs
Hot Springs of
Ruidian region
in Tengchong,
China
Large pools with neutral pH
Bacteria
50
Jz
Bacteria
Crenarchaeota
51
CPc
Taupo volcanic
zone
New Zeland
Illumina Miseq
Metagenomics
28
13
Presence of arsenic
Aquificales (Sulfurihydrogenibium)
(Hug et al. 2014)
52
CPp
12
19
53
CPr
21
54
AP
2
10
55
It6
Phlegrean Fields,
Italy
Illumina Hiseq
17.6
78.6
N.R.
Protobacteria (Acidithiobacillus)
(Menzel et al. 2015)
56
It3
Roche/454 Titanium FLX
96.6
N.R.
Crenarchaeota (Acidianus)
57
AM1
Los Azufres
National Park,
Mexico
N.R.
T-RFLP and 16S
N.R.
N.R.
Acidic mud pool with high levels of Hg, Pb and Fe
Proteobacteria (Lysobacter enzymogenes)
(Brito et al. 2014)
N.R. not reported
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be limited by the short read lengths obtained,
sequencing errors (Quince et al. 2009), differences
arising from the different hypervariable regions cho-
sen (Youssef et al. 2009) and problems in the
Operational Taxonomic Units (OTUs) assignment
(Huse et al. 2010). Moreover, to assess abundance
estimation and microbial diversity from the single 16S
rRNA gene is challenging for several reasons, e.g.: (1)
it may fail to resolve a substantial fraction of the
diversity in a community given various biases asso-
ciated with PCR, (2) sequencing can produce widely
varying estimates of diversity because different
hypervariable regions have differential power at
resolving taxa, (3) sequencing provides just a survey
of the taxonomic composition of the microbial com-
munity without information about the biological
function of the taxa, and (4) sequencing is limited to
the analysis of known taxa while novel or highly
diverged microorganism or viruses, are difficult to
study using this approach. Moreover, given the
prevalence of horizontal gene transfer, the inherent
difficulties in defining microbial species, and the
limited resolution of the 16S rRNA gene among
closely related species, 16S rRNA profiling should be
evaluated carefully, in particular if applied to the
temporal microbial surveys. In this case, by using both
16S amplicon analysis and a metagenomic approach,
was observed 1.5- and *10-times more OTU assigned
to phyla and genera respectively with the metage-
nomic method than the 16S rRNA analysis. This
seems masking several levels of intra-genus differen-
tiation and heterogeneity of the microbial population
(Poretsky et al. 2014).
SBM is an alternative approach to the study of
microbial consortia that avoids the limitation of the
16S rRNA analysis. Reads obtained as described
above, align to various genomic locations of the
different genomes present in the sample, including
viruses. By assembling short reads (e.g. Illumina 100
paired-end) longer genomic contigs are obtained.
Then, the contigs can be clustered by ‘‘binning’’, on
the base of their nucleotide composition such as %GC
and tetranucleotide frequency (Wu et al. 2014),
allowing the taxonomic assignment of the resulting
bins by homology searches. The analysis of the contigs
provides access to the functional gene composition of
microbial communities giving a much broader and
detailed description than the phylogenetic surveys
based on 16S rRNA profiling. Moreover, by using
suitable sequence databases (nucleic and aminoaci-
dic), SBM is useful to obtain genetic information on
potentially novel biocatalysts, to reveal correlation
between function and phylogeny for uncultured
organisms, and to study evolutionary profiles of
microbial communities. However, the assembly pro-
cess is generally affected by the problem that single
reads have lower confidence in accuracy (low cover-
age) than the multiple reads that cover the same
segment of genetic information (high coverage). This
implies that in a complex microbial community with
low coverage, it is unlikely to get many reads covering
the same fragment of DNA and affecting the result of
the assembling. Nevertheless, without assembly, it is
impossible to analyse longer and more complex
genetic loci such as CRISPRs (Sun et al. 2016).
Despite the clear benefits, metagenomic sequence data
are not challenges-free since they are generally
complex and large, requiring specific hardware for
storing and elaboration to avoid computational issues.
In addition environmental metagenomic samples may
contain contaminating DNA such as from animals and
plants seizing useful reads from the microbial analysis.
To determine which reads were generated from a
detected contaminant’s genome, especially when the
contaminant is abundant or has a large genome, can be
problematic. SBM is generally more expensive than
16S rRNA sequencing, especially in complex com-
munities requiring a deepest sequencing. However, the
cost reduction of the NGS has dramatically increased
the number of metagenomic projects making these
approaches a direct substitute of the 16S rRNA
profiling. This expansion is reflected in the high
number of bioinformatics tools and data resources that
have been developed in the last six years and are
available for SBM analysis. Many of them work on a
command-line environment or are web-based tools,
which centralize metagenome data management and
analysis, providing an interface ready to use but
lacking in customization of the analysis. For a
complete and detailed overview of metagenomic tools
and strategies see the excellent review of Thomas et al.
(2012).
In contrast to the metagenomic approach, single-
cell genomics is addressed to the analysis of
genomes one cell at a time (Blainey and Quake
2014) (Fig. 2). This approach requires the separation
of individual cells from a complex environmental
sample (e.g. sediments or microbial mat), cell lysis
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123
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and the amplification and sequencing of genomic
DNA (gDNA). The first step is the isolation of
individual cells from the primary samples to obtain
a suspension of viable single cells. However, this
step can be challenging when the primary sample
requires mechanical or enzymatic dissociation (e.g.
sediments from a mud pool) keeping the cells viable
without biases for specific subpopulations. After
lysis of individual cells, the gDNA is amplified by
using MDA (Lasken 2012; Zong et al. 2012).
Generally, the resulting single amplified genomes
(SAG) are screened by 16S rRNA profiling for a
preliminary survey and identification of candidate
phyla or other taxa. SAGs of interest are then deep
sequenced by NGS platforms, assembled, and ana-
lyzed. By the analysis of the number of single-copy
conserved markers in the assembled sequences, it is
possible to evaluate how well a given SAG covers
the target microorganism’s genome (Rinke et al.
2013). Although single-cell genomics is a useful
tool for the study of unknown and uncultivable
microorganisms, in particular from extreme envi-
ronments such as geothermal areas, this shows
several critical issues. For instance, the amplification
protocols can introduce chimeric artefacts and a
severe bias in genomic coverage. To overcome these
problems during the assembling, specific methods
have been developed to analyse single-cell genomic
datasets combining data from closely related single
cells clustered by nucleotide percentage identity
(Rinke et al. 2013). The resulting assemblies can
often represent nearly complete pangenomes for a
given strain or species, allowing the detailed anal-
ysis of genes and pathways. Today, single-cell
genomics and metagenomics can be considered as
complementary approaches because the former is
not affected neither by amplification issues nor by
problems related to the separation of individual cells
from a complex primary sample, while the latter is
able to associate directly and unambiguously phy-
logeny and function (Walker 2014).
A combined approach of these methods, indeed,
was recently used to identify two novel candidate
phyla, Calescamantes and Candidatus kryptonia, by
the analysis of different SAGs and metagenomic
databases collected in different high-temperature
environments (Eloe-Fadrosh et al. 2016; Kim et al.
2015) proving that, although metagenomics and
single-cell genomics are informative of their own,
the results of the mixed approach could be greater
than the sum of their parts.
4 Geographical distribution of microbiomes
Terrestrial surface hot springs (T [65 °C), which are
spread all over the world, offer a remarkable source of
biodiversity. Hereinafter, we report on the state of the
art of the metagenomic survey of several hot springs
worldwide (Fig. 4). The microbial and viral metage-
nomic data are summarized in Tables 1and 2,
respectively.
4.1 Yellowstone National Park, USA
The Yellowstone geothermal complex includes more
then 10,000 thermal sites such as hot springs, vents,
geysers, and mud pools showing broad ranges of pH,
temperature and geochemical properties. One of the
first detailed environmental and microbiological sur-
vey has been reported in 2005 and included three
different hot springs in YNP, i.e. the Obsidian Pool
(ObP) (80 °C, pH 6.5), the Sylvan Spring (SSp)
(81 °C, pH *5.5), and the Bison Pool (BP) (83 °C,
pH *8.0) (Meyer-Dombard et al. 2005). The Obsid-
ian and Bison Pools are inhabited, among archaea,
mostly by different groups of uncultured crenar-
chaeota or by members of the family Desulphurococ-
caceae (in ObP and BP, respectively), while bacteria
belong to the genera Thermocrinis,Geothermobac-
terium and to the phylum Proteobacteria. On the other
hand, Hydrogenothermus was the most abundant
bacterial genus in SSp, together with a dominance of
families Desulphurococcaceae and Thermopro-
teaceae among archaea (Meyer-Dombard et al.
2005). More recently, Inskeep and co-workers, in an
extensive metagenomic survey of the microbial
species in the YNP, reported on the identification of
the predominant microbial populations, metabolic
features, and the relationship between geochemical
conditions and gene expression of five geochemically
dissimilar high-temperature environments, namely
Crater Hills (CH; 75 °C, pH 2.5), Norris Geyser Basin
(NGB; 65 °C, pH 3.0), Joseph’s Coat (JCHS; 80 °C,
pH 6.1), Calcite (CS; 75 °C, pH 7.8), and Mammoth
Hot Springs (MHS; 71 °C, pH 6.6) (Inskeep et al.
2010). Specifically, binning and fragment recruitment
approaches revealed that archaea, of the order
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Sulfolobales (in CH and NGB) and Thermoproteales
(in JCHS), mainly dwelt in high-temperature acidic
springs. Moreover, the results suggested that the
relative abundance of Thermoprotei was modulated
by differences in pH and/or concentration of dissolved
O
2
. By contrast, bacteria mainly belonging to the order
Aquificales, outnumbered archaea at pH values above
6.0 (CS and MHS). In particular, a predominance of
reads showed nucleotide identity with Sulfurihydro-
genibium sp. Y03AOP1 in MHS and with Thermus
aquaticus and Sulfurihydrogenibium yellowstonensis
in CS (Inskeep et al. 2010). To date, the widest
investigation of microbial communities in hyperther-
mophilic environments (known as the YNP metagen-
ome project) spans over 20 different geothermal sites
in the YNP, 13 of which showing temperatures above
65 °C. These sites have been pooled in two different
ecosystems based on features such as pH, temperature,
presence of dissolved sulfide and elemental sulfur that
are the main determinants shaping the microbiome
within (Inskeep et al. 2013b). The first ecosystem,
populated by Aquificales-rich ‘‘filamentous-streamer’’
communities, was identified in six sites: Dragon
Spring (DS; 68–72 °C, pH 3.1); 100 Spring Plan
(OSP_14; 72–74 °C, pH 3.5), Octopus Spring (OS;
74–76 °C, pH 7.9) and Bechler Spring (BCH;
80–82 °C, pH 7.8) together with MHS and CS
described above (Inskeep et al. 2013b; Takacs-
Vesbach et al. 2013). Whereas the second one is
represented in seven archaeal-dominated sediments:
Nymph Lake (NL; 88 °C, pH 4), Monarch Geyser
(MG; 78–80 °C, pH 4.0), Cistern Spring (CIS;
78–80 °C, pH 4.4), Washburn Spring (WS; 76 °C,
pH 6.4), 100 Spring Plan (OSP_8; 72 °C, pH 3.4), and
including CH and JCHS described above (Inskeep
et al. 2013a,b). The diversity detected among sites
with similar characteristics suggested that additional
geochemical and geophysical factors, such as the total
dissolved organic carbon (DOC) and the amount of
solid-phases of carbon, could play a role in the
consortia composition (Inskeep et al. 2013a,b;
Takacs-Vesbach et al. 2013). A similar observation
but mainly related to the different SO
42-
/Cl
-
ratio was
recently reported in the analysis of three thermal
springs sharing pH *4.0 of the YNP: Norris (NOR;
84 °C, pH 4.34), Mary Bay Area (MRY; 80 °C, pH
4.32) and Mud Kettles (MKL, 72 °C pH 4.35), which
resulted exclusively populated by bacteria and dom-
inated by microorganisms belonging to the phylum of
Cyanobacteria (NOR and MRY) and Aquificales
(MKL) (Jiang and Takacs-Vesbach 2017).
A combined approach of metagenomics and single-cell
analysis conducted in CH and NL revealed the presence
of Nanoarchaeota that, indeed, represent Nanobsidianus
Fig. 4 Map of the geothermal sites described in this review and reported in Tables 1and 2
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123
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Table 2 State-of-the-art of the viral metagenomics in geothermal environments worldwide
Name
Abbreviation
Location
Sample type
Main inhabiting viruses
References
Octopus spring
OS
Yellowstone National Park, USA
Viral metagenomics from virus particles
samples
Lytic lifestyle
(Inskeep et al. 2013b)
(Schoenfeld et al. 2008)
(López-López et al. 2013)
Bear Paw
BP
Nymph Lake 10
NL10
Positive-strand RNA viruses
(Bolduc et al. 2012)
(Inskeep et al. 2013a)
Nymph Lake 17
NL17
Nymph Lake 18
NL18
Obsidian Pool
ObP
HAV1 (linear DNA) and HAV2 (circular DNA)
(Garrett et al. 2010)
Nymph Lake 10
NL10
Viral metagenomics from metagenomic
datasets
Lipothrixiviridae, Rudiviridae,
Ampullaviridae, PSV and TTV1
(Haring et al. 2004)
(Menzel et al. 2015)
Crater Hills CH1102 site
CH1102
Sulfolobus Monocaudavirus (SMV1)
(Gudbergsdottir et al. 2016)
Boiling Springs Lake
BSL
Lassen Volcanic National Park,
USA
Viral metagenomics from virus particles
samples
RNA-DNA hybrid virus (RDHV)
(Diemer and Stedman 2012)
Not named
Los Azufres National Park, Mexico
Viral metagenomics from metagenomic
datasets
Rudiviridae (SMR1) and Fuselloviridae (SMF1)
(Servín- Garcidueñas et al. 2013a,b)
Grensdalur
Is2-5S
Iceland
Caudovirales, Rudiviridae, PSV and TTV1
(Wang et al. 2015b)
(Menzel et al. 2015)
Krísuvík
Is3-13
Ampullaviridae, Rudiviridae,
Acidanius-bottle-shaped (ABV)-like, PSV and TTV1
Pisciarelli hot spring
It3
Phlegrean Fields, Italy
Lipothrixviridae and HAV2
(Wang et al. 2015b)
(Gudbergsdottir et al. 2016)
Solfatara volcano
It6
Lipothrixviridae, ATV-like, ARV-like
and Acidanius-bottle-shaped (ABV)-like
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stetter cells based on their high 16S rRNA similarity and
their overall genome homology.
This is in agreement with previous findings highlight-
ing the wide distribution of Nanobsidianus genus in this
kind of YNP geothermal environments (Clingenpeel
et al. 2013). Furthermore, single-cell and catalyzed
reporter deposition-fluorescence in situ hybridization
analysis performed on these environmental YNP samples
showed the occurrence of a symbiotic association
with extreme thermoacidophilic Crenarchaeota hosts,
such as Acidicryptum nanophilium, Acidolobus sp, Vul-
canisieta sp. (5%), and Sulfolobus spp.
Genome fragments of Nanobsidianus contain inte-
grated viral sequences. On the other hand, matching
viral DNA sequences were found in the viral fractions
isolated from the same hot springs, suggesting that
Nanobsidianus species can host viruses or support
viral replication (Munson-McGee et al. 2015).
Worth of note is also the abundance of archaeal
DNA-and RNA-viruses in these environments
(Table 2). The first viral metagenomics study
(Schoenfeld et al. 2008) lead to the identification of
double-stranded DNA viruses in the Octopus (93 °C)
and Bear Paw (74 °C) hot springs (Inskeep et al.
2013b). Operons and potentially complete genomes
were assembled, thus providing insight to the possibly
dominant viral populations within each hot-spring
(Lo
´pez-Lo
´pez et al. 2013; Schoenfeld et al. 2008).
Viral metagenomes indicated the predominance of a
lytic lifestyle as suggested by the significant propor-
tion of lys-like genes encoding for proteins involved in
host cell lysis (Lo
´pez-Lo
´pez et al. 2013; Schoenfeld
et al. 2008). This evidence is in contrast to the cultured
thermophilic crenarchaeal viruses, most of which are
non-lytic (Contursi et al. 2006; Prangishvili 2013;
Snyder et al. 2015; Wang et al. 2015b). The evidence
of the replacement of cellular genes by non-ortholo-
gous viral genes (i.e. helicases, DNA polymerases,
ribonucleotide reductase, and thymidylate synthase)
suggested that viruses might play a critical role in the
evolution of DNA and its replication mechanisms
(Schoenfeld et al. 2008).
In a further study, Inskeep and co-workers reported
the assembly of viral genomes from SBM data
collected in several YNP sites (Inskeep et al.
2013a,b). Based on phylogenetic analysis of known
viruses, 10 scaffolds from the archaeal-dominated
samples were classified as ‘‘viral’’ although the
similarity of the scaffolds to known viruses varied
considerably. CRISPR regions including both spacer
regions and direct repeats were predicted from these
assemblies and near perfect alignments were found
between CRISPR spacer regions and 8 of the 10 viral-
like scaffolds (Inskeep et al. 2010,2013a).
Novel positive-strand RNA viruses have been also
discovered in Nymph Lake hot springs (NL) charac-
terised by high temperature ([80 °C) and low pH \4
(Bolduc et al. 2012). Three sites (NL10, NL17 and
NL18) were selected as putative niches for archaeal
RNA viruses based on a viral-fraction-enrichment
approach followed by deep sequencing and two
genomic fragments of putative archaeal RNA viruses
were identified (Bolduc et al. 2012).
An attempt to link these RNA viral genomes to a
specific host type was carried out through the analysis
of the CRISPR direct repeat (DR) and spacer content
present in cellular metagenomics data sets from the
same sites (Bolduc et al. 2012). The majority of
matching spacer sequences of the RNA metagenome
was related to DRs Sulfolobus species (an organism-
commonly found in NL10) suggesting that this
crenarchaeon, might host not only DNA (Contursi
et al. 2014b; Lipps 2006) but also RNA viruses.
Intriguingly, the identification of these spacers might
indicate that not only DNA viruses but also archaeal
RNA viruses elicit CRISPR-mediated immunity.
The genetic diversity of these newly identified putative
archaeal RNA viruses was investigated by searching for
similarity throughout global metagenomics datasets
(Wang et al. 2015a). The authors were able to obtain
nine novel partial or nearly complete genomes of novel
genogroups or genotypes of the putative RNA viruses
previously identified by Bolduc et al. (2012).
Viral sequences were also retrieved from the
metagenomic dataset obtained in a recent study on
the NL10 (Menzel et al. 2015). Among the viral
families, Lipothrixiviridae, is the most abundant and
Rudiviridae and Ampullaviridae members were also
identified together with viral sequences assigned to
Pyrobaculum spherical virus (PSV) and Thermopro-
teus tenax virus 1 (TTV1) (Haring et al. 2004;
Neumann et al. 1989). The high representativeness
of archaeal viral families is in agreement with the
predominance of archaeal species (58.1% of reads
assigned to Archaea) in the NL10 site (Gudbergsdottir
et al. 2016).
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Despite the fact that the predominance of the
same archaeal species concerns the closely located
CH1102 site as well (Sulfur Spring, Temp: 79 °C,
pH 1.8), a different viral scenario has been detected
in this site. Indeed, the virus Sulfolobus Monocau-
davirus (SMV1) is the most abundant in CH1102
constituting more than 80% of the identified viral
reads (Uldahl et al. 2016). To link the viral genomes
and their potential host in the samples, CRISPR loci
were identified from the cellular part of the CH1102
metagenome where, interestingly, the number of
spacers matching to the novel SMV genomes was
generally very high.
By employing a network approach to a time series
of viral metagenomics data collected from high
temperature Nymph Lake acidic hot springs, Bolduc
and co-worker demonstrated the proof-of-concept that
the viral assemblage structure and its stability over a
5 year sampling period can be precisely defined
(Bolduc et al. 2015). Furthermore, this analysis
highlighted the high representativeness of completely
novel archaeal viruses, thus demonstrating that the
combination of metagenomics dataset with advanced
bioinformatics tools is essential to expand our knowl-
edge on the archaeal virosphere.
A metagenomic approach employed to obtain full
genome sequences from a hot basic enrichment
sample (85 °C and pH 6.0) collected from ObP
(Garrett et al. 2010) lead to the identification of two
novel genomes HAV1 (linear) and HAV2 (circular)
neither of which showing any clear similarity to other
known archaeal viruses (Garrett et al. 2010). Exten-
sive genomic differences were detected in multiple
variants of a virus HAV1, possibly resulting from
CRISPR-Cas-directed interference by unidentified
hosts.
4.2 Iceland
Given its location on a divergent tectonic plate
boundary (the mid-Atlantic Ridge), Iceland is studded
with active volcanic systems. Among these, metage-
nomics data are available for two distantly located
(about 45 km) sites, i.e. Krı
´suvı
´k (Is3-13) and Grens-
dalur (Is2-5S). Is3-13 (90 °C, pH 3.5–4.0), belonging
to a geothermal complex including solfataras, fumar-
oles, mud pots and hot springs, had very limited access
to organic materials. Instead, Is2-5S (85 °C and pH
5.0) is reached by the flow through streams from other
hot springs and is located on a hill plenty of organic
materials, such as moss and lichens (Menzel et al.
2015). Genomic DNA, extracted from both sediment
and water samples, was sequenced using the Illumina
Hiseq and analysed by MEGAN (Huson and Weber
2013). Mapped reads (several millions) were assigned
to archaeal microorganisms for 19.7 and 33% in Is3-13
and Is2-5S, respectively. The analysis showed a
predominance of Thermoproteales and Sulfolobales
in Is3-13 and of Crenarchaeota in Is2-5S, mainly of the
Pyrobaculum genus. On the other hand, bacteria were
overrepresented by Proteobacteria (in Is3-13), includ-
ing Gamma- and Beta-proteobacteria, and a large
population of Aquificales (Is2-5S) mostly belonging to
the species Thermocrinis albus and Sulfurihydrogen
ibiumazorense. By comparing their data with those
available for other geothermal locations worldwide,
authors concluded that the community structure is
strongly influenced by environmental parameters
rather than geographic distance (Menzel et al. 2015).
The viral community composition and the relative
abundance of viruses in IS2-5S and IS3-13 sites are
quite different. In both cases, the representativeness of
crenarchaeal viral sequences is high despite the
predominance of bacterial species. This apparent
discrepancy might be due to a compositional bias in
the reference database, since most of the thermophilic
viruses have been isolated from archaeal hosts (Gud-
bergsdottir et al. 2016).
The non-crenarchaeal viral order Caudovirales,
composed of head to tail viruses infecting members of
Bacteria and Euryarchaea is most abundant in Is2-5S
(Krupovic et al. 2011). Conversely, the IS3-13 site is
mostly populated by Ampullaviridae members and
constitutes only a small percentage of all the viral
sequences in the former sample. Furthermore,
sequences referable to Bicaudoviridae one of the most
widely represented crenarchaeal family in hot springs
(Wang et al. 2015b), are absent in IS2-5S metagenome
(Prangishvili 2013; Snyder et al. 2015). Interestingly,
the longest contig in Is3-13 metagenome was assigned
to a near complete Acidanius-bottle-shaped (ABV)-
like genome (Haring et al. 2005).
Common to both the sites are contigs assigned to
the Rudiviridae family (Prangishvili 2013; Snyder
et al. 2015; Wang et al. 2015b) and viral sequences
assigned to Pyrobaculum spherical virus (PSV) (Har-
ing et al. 2004) and Thermoproteus tenax virus 1
(TTV1) (Neumann et al. 1989) and accordingly the
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metagenomes also contain sequences assigned to their
archaeal Pyrobaculum and Thermoproteus tenax hosts
(Menzel et al. 2015).
Unique to IS2-5S site is a 20 kb contig representing
an novel incomplete viral genome that, as suggested
by CRISPR spacer analysis, is likely to infect
Hydrogenobaculum, an host for which no virus has
been reported before (Gudbergsdottir et al. 2016;
Romano et al. 2013). This is remarkable as a small but
significant percentage of cellular reads in the Is2-5S
metagenome were assigned to Hydrogenobaculum
supporting the CRISPR analysis (Menzel et al. 2015).
4.3 Kamchatka Peninsula, Russia
In the Kamchatka peninsula, also known as the land of
fire, an extended volcanic region of approximately
472,300 km
2
, three different areas, Uzon (81 °C, pH
7.2–7.4), Kam37 (85 °C, pH 5.5) and Mutnovsky
(70 °C, pH 3.5–4.0), were surveyed to study the
diversity of their microbial communities (Chernyh
et al. 2015; Eme et al. 2013; Merkel et al. 2017;
Wemheuer et al. 2013). This analysis, besides showing
that uncultivated members of the Aquificales,Eur-
yarchaeota,Crenarchaeota, and a Miscellaneous
Crenarchaeotic Group were dominating in Kam37,
led also to the discovery of two ancient (hyper)ther-
mophilic archaeal lineages, namely Hot Thaumar-
chaeota-related Clade 1 and Hot Thaumarchaeota-
related Clade 2. Thaumarcheota, along with Pro-
teobacteria and Thermotogae, thrive in the Uzon and
Mutnovsky sites as well. Interestingly enough, these
results further confirm the previous assumption that
comparable environmental conditions result in similar
microbial communities as in the case of the ObP in
YNP and the Uzon Caldera hot spring sharing
geochemical features as well as microbial community
structures (Meyer-Dombard et al. 2005; Simon et al.
2009). A recent microbial census by Merkel and co-
workers of several hot springs with temperature
[65 °C spread across Uzon and Mutnovsky (Sery:
80 °C, pH 6.1; Thermofilny: 67 °C, pH 6.1; Bour-
lyashchy 82 °C, pH 7.0; Izvilist: 77 °C pH 5.9; 3423:
72 °C pH 5.0; 3462: 72 °C, pH 5.1; 3460: 68 °C, pH
6.1; 3401: 90 °C pH 3.5; 3404: 70 °C pH 6.0) revealed
that as observed in other thermal habitat (i.e. YNP),
bacteria belonging to the genus Sulfurihydrogenibium
are the most abuntant and widely distributed group of
lithoautotrophic prokaryotes in these environments as
also previously reported for Bourlyashchy hot springs,
the hottest thermal pool of Uzon (Chernyh et al. 2015).
These microorganisms represent the only dominating
representatives of Aquificae in the springs analysed
together with other lithoautotrophic bacteria such as
Caldimicrobium and Thermocrinis. This indicates that
reduced sulfur compounds such as dissolved hydrogen
sulfide, are the primary energy source for lithoau-
totrophic carbon assimilation. Because of the simul-
taneous presence of both aerobic (i.e.
Sulfurihydrogenibium) and anaerobic (i.e. Caldimi-
crobium) microorganisms in these hot springs, the
authors suggest that the aerobic sulfur oxidation,
anaerobic hydrogen oxidation, and the reduction of the
sulfur compounds are the main energy-giving pro-
cesses in these sites (Merkel et al. 2017).
4.4 Furnas Valley, Azores
The Furnas Valley (Island of Sa
˜o Miguel) is the main
geothermal area of the Azores archipelago. Unlike
YNP and Iceland, here the largest spring is alkaline
and located on a height, whereas smaller ones are in
the valley and are more acidic (Brock and Brock
1967). Recently, nine sites showing a wide range of
physico-chemical characteristics (51–92 °C; pH
2.5–8.0) were explored, i.e. AI-AIV near Caldeira
Do Esgucho, BI-BIII near Caldeira
˜o and CI and CII
near Caldeira Asmodeu (Sahm et al. 2013). In this
study several approaches were used to assess the
prokaryotic diversity, i.e. fluorescence in situ
hybridization (FISH), analysis of 16S rRNA and
denaturing gradient gel electrophoresis (DGGE). The
AI site (51 °C, pH 3.0) was found to be populated by
few euryarchaeota, mainly belonging to the genus
Thermoplasma, whereas among bacteria dominated
Proteobacteria (80%), especially genera known for
their acidophilic (Acidicaldus) and chemolithoau-
totrophic (Acidithiobacillus) lifestyles. By contrast,
in the AIV site (92 °C, pH 8.0) an even distribution of
archaea (35%) and bacteria (40%) was detected. In
particular, phyla Thermotogales (genus Fervidobac-
terium), Firmicutes (genus Caldicellulosiruptor) and
Dictyoglomi (genus Dictyoglomus) were abundant
among bacteria, whereas the archaeal population was
almost exclusively composed by Crenarchaeota
belonging to the Desulfurococcaceae and Thermopro-
teaceae families (Sahm et al. 2013). A general
observations was that, once again, the pH was the
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predominant parameter, influencing microbial com-
plexity in different areas surveyed, with the highest
bacterial diversity detected at sites where temperatures
and pHs ranged 55–85 °C and 7.0–8.0, respectively.
Intriguingly, unlike other hot spring-environments
where Aquificales are dominant, here heterotrophic
bacteria prevail. To explain this, authors suggested
that a 20-400-fold higher DOC in the Furnas spring
could be a reason for the abundance of heterotrophic
bacteria (Sahm et al. 2013).
4.5 Sungai Klah, Malaysia
The Sungai Klah (SK) hot spring in Malaysia is
surrounded by a wooded area, which makes it
continuously fed by plant-derived material that results
in a higher degree of total organic carbon (TOC) if
compared with the other 60 geothermal sites present in
Malaysia. Moreover, three additional key factors were
found to be characteristic of SK: (1) temperature
exceeds 100 °C in many spring pools along the main
stream, (2) it fluctuates between 50 and 110 °C
throughout the stream and, (3) the pH is not uniform
and spans from 7.0 to 9.0 along the stream. In general,
SK is a shallow and fast-flowing stream with temper-
atures of 75–85 °C and pH 8.0. Samples retrieved
from this area were studied through 16S rRNA gene
profiling (Chan et al. 2015). This approach led to the
identification of 83 phyla among which the predom-
inant were Firmicutes,Proteobacteria,Chloroflexi,
Bacteroidetes,Euryarchaeota and Crenarchaeota.
Interestingly, by studying sequence affiliations the
authors could highlight a relationship between the
population diversity and the geochemical parameters
within the hot spring. Moreover, it was shown that
microbial communities were able to survive by
exploiting different symbiotic strategies to prosper
under multiple environmental stresses (Chan et al.
2015).
4.6 Tengchong, China
Located on the northeastern edge of Tibet–Yunnan
geothermal zone between the Eurasian and Indian
plates, Tengchong (China) is one of the most active
geothermal areas in the world with Rehai (Hot Sea)
and Ruidian geothermal fields characterized by the
most intense geothermal activity. While mainly large
pools with neutral pH (e.g. Gongxiaoshe and Jinze) are
located in Ruidian (Wang et al. 2014), Rehai hosts
several types of hot springs showing a wide range of
physico-chemical conditions, such as temperatures
from 58 to 97 °C and pH values between 1.8 and 9.3.
Examples are: (1) small source, high discharge springs
(Gumingquan and Jiemeiquan); (2) small, shallow
acidic mud pools featured by a decreasing temperature
gradient (Diretiyanqu); (3) shallow acidic pools like
Zhenzhuquan; and (4) shallow springs with multiple
geothermal sources such as Shuirebaozha (Hou et al.
2013). Besides few metagenomic studies mainly
focused on Crenarchaeota (Song et al. 2010)or
ammonia oxidizing archaea (Jiang et al. 2010), the
study by Hou et al. (2013) is the first report on a wide-
ranging survey of the microbial community in 16
different hot springs of Tengchong, aiming at shed-
ding light on the relationship between the diversity of
the thermophilic microbial communities and local
geochemical conditions. In particular, predicted num-
ber of OTU as well as Shannon and equitability
indexes based on 16S rRNA gene sequence data, were
used to highlight correlations between microbial
diversity and environmental geochemistry. Analysis
of these indexes using Mantel test revealed higher
microbial richness, equitability, and diversity in
Ruidian than in Rehai. Authors concluded that this is
mainly due to differences in the pH, temperatures and
TOC between the two springs (Hou et al. 2013). The
effect of seasonal changes on the microbial diversity in
Tengchong hot springs, which are located in a
subtropical area with heavy temporal monsoon rain
fall, has been studied by Briggs et al. (2014) and Wang
et al. (2014). Specifically, they compared the samples
collected between June and August (rainy season) with
those of Hou and colleagues sampled in January
during the dry season. By doing so, they revealed that
Ruidian sediments contained more diverse microbial
lineages than Rehai sediments thanks to the neutral pH
and moderate temperatures, and that neutral springs
contained similar microbial lineages in January and
June while in August a single dominant lineage of
Thermus emerged. Once again, the pH turned out to be
the primary factor influencing the microbial commu-
nity, followed by temperature and DOC (Wang et al.
2014). Overall, both studies indicated that tempera-
ture, pH, and other geochemical conditions play a key
role in shaping the microbial community structure in
Tengchong hot springs over the seasons.
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4.7 Taupo Volcanic Zone, New Zealand
In the central area of the New Zealand’s Northern
Island, a group of high temperature geothermal
systems take the name of the Taupo Volcanic Zone
(TVZ). Within this area, the Waiotapu region is
characterized by a large number of springs exhibiting
elevated arsenic concentrations (Mountain et al.
2003). With its 65-meter diameter, the Champagne
Pool (CP) represents the largest geothermal feature of
Waiotapu with arsenic concentrations ranging from
2.9 to 4.2 mg/L (Hedenquist and Henley 1985). The
inner rim of CP is characterized by subaqueous orange
amorphous As-S precipitate responsible of the char-
acteristic orange color (Jones et al. 2001). Whereas
convection stabilizes the water temperature around
75 °C, the surrounding silica terrace (Artist’s Palette)
shows lower temperatures (*45 °C). In order to
understand the evolution of arsenic resistance in
sulfidic geothermal systems, Hug and co-workers
studied the microbial contributions to coupled arsenic
and sulfur cycling at CP. To this aim, the authors
sampled four different CP areas with distinctive
physical and chemical features: (1) the inner pool
(CPp), (2) the inner rim (CPr), (3) the outflow channel
(CPc), and (4) the outer silica terrace (AP). The
concentration of the total dissolved arsenic was
measured and was found to be 3.0, 2.9, 3.6, and
4.2 mg/L at sites CPp, CPr, CPc and AP, respectively.
Moreover, total dissolved sulfur concentrations were
rather even in all the sites analysed, i.e. 91–105 mg/L
(Hug et al. 2014). It was previously reported that the
combination between dissolved toxic metal(loid)s and
high temperature in hot springs represents a strong
selective pressure on the inhabiting microbial com-
munities (Hirner et al. 1998). Indeed, sulfide ions
commonly used as electron donors/acceptors by
microorganisms under geothermal conditions, are
highly reactive with arsenic (Macur et al. 2013).
Therefore, microbially-mediated sulfur cycling could
exert an indirect, but profound, influence on arsenic
speciation, by affecting the concentration of thioarse-
nate species (Stauder et al. 2005). To shed light on the
potential microbial contributions to arsenic speciation
in CP, and to characterize the microbial diversity, total
genomic DNA was extracted from sediments and
analyzed by deep sequencing (Hug et al. 2014). This
analysis revealed that sequences assigned to the
Archaea domain were mostly belonging to genera
Sulfolobus,Thermofilum,Pyrobaculum,Desulfuro-
coccus,Thermococcus, and Staphylothermus, and that
the percentage of total Archaea was of 28, 21, 12 and
2% at CPp, CPc, CPr and AP, respectively. On the
other hand, most abundant sequences belonging to
Bacteria in all sites were closely related to the genus
Sulfurihydrogenibium. According to these authors, the
combination of sulfide dehydrogenase and sulfur
oxygenase–reductase encoding genes detected as
major sulfur oxidation genes at CPp, suggests a two-
step sulfide oxidation process to sulfite and thiosulfate,
also producing sulfide. Moreover, biogenic sulfide
produced would then be available to transform arsen-
ite to monothioarsenate. Interestingly enough, the
whole metagenomic analysis allowed to unravel the
impact on sulfur speciation by genes underpinning
sulfur redox transformations, thus highlighting a
microbial role in sulfur-dependent transformation of
arsenite to thioarsenate (Hug et al. 2014).
4.8 Phlegraean Fields, Italy
An extended area to the west of Naples, South Italy,
known as Phlegraean Fields, comprises 24 craters and
volcanic features, mostly lying underwater. In the
middle of this area is located the Solfatara volcano,
which is one of the youngest volcanoes formed within
this active volcanic field (Isaia et al. 2009; Orsi et al.
1996; Petrosino et al. 2012; Rosi and Santacroce
1984). The site with the most intense geothermal
activity is the Pisciarelli area that, despite its limited
extension (about 800 m
2
), is featured by over 20
physically and chemically different springs and mud
holes. Besides sulfide, arsenic is one of the most
prominent heavy metals detectable in this high-
temperature environment (Huber et al. 2000), thus
suggesting the presence of hyperthermophilic
microorganisms able to use these compounds for their
metabolism, similarly to what was shown by Hug et al.
(2014) in the Champagne Pool (New Zealand).
Recently, Solfatara volcano (It6) and Pisciarelli hot
spring (It3) were analysed by Menzel and colleagues
with the aim of defining the biodiversity, genome
contents and inferred functions of bacterial and
archaeal communities (Menzel et al. 2015). It6 sample
(76 °C, pH 3.0, water/sediment) is subjected to
IlluminaHiseq sequencing and whereas those from
the It3 site (86 °C, pH 5.5, water/sediment) is
sequenced using the Roche/454 Titanium (Menzel
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et al. 2015). This study showed that in It6 78.6% of the
mapped reads were assigned to Bacteria (phyla
Proteobacteria and Thermoprotei), while only
17.6% to Archaea (phyla Crenarchaeota and Eur-
yarchaeota). Conversely, It3 was mainly populated by
Archaea (96.6%), including species such as Acidianus,
Sulfolobus and Pyrobaculum (Menzel et al. 2015).
When these data were compared with those from
previous studies (Inskeep et al. 2013a; Sahm et al.
2013; Urbieta et al. 2014; Wemheuer et al. 2013) the
authors conclude that environmental chemico-physi-
cal parameters are the major determinants in shaping
the structure and composition of the microbial com-
munity (Menzel et al. 2015).
It3 and It6 metagenomes were screened for viral
sequences as well (Table 2). A common feature to
these two sites is the predominance of the
Lipothrixviridae (Prangishvili 2013; Snyder et al.
2015; Wang et al. 2015b) viral sequences, represent-
ing the 43.5 and 81.7%, respectively (Gudbergsdottir
et al. 2016). Despite the high abundance of contigs
assigned to this family, the absence of a complete
lipothrixviral genome in the metagenomes could
indicate the presence of multiple related but not
identical genomes of similar abundance.
Acidianus two-tailed virus (ATV)-like sequences
are also abundant in these two italian metagenomes in
agreement with the fact that ATV, the single member
of Bicaudaviridae, was originally isolated around
10 years ago from the It6 site (Prangishvili 2013;
Snyder et al. 2015; Wang et al. 2015b). However, no
full genome of an ATV-like virus was recovered
(Gudbergsdottir et al. 2016). Conversely, a long
Acidanius-bottle-shaped (ABV)-like contig was iden-
tified in the It6 metagenome indicating that this linear
genome, belonging to a novel representative of the
Ampullaviridae family, was complete as judged by the
presence of inverted terminal repeats. In addition,
another long ARV-like contig identified in the same
metagenome (Gudbergsdottir et al. 2016) was
assigned to a new member of the Rudiviridae family
(Prangishvili 2013; Snyder et al. 2015; Wang et al.
2015b).
The It3 metagenome contains also a &20 kbp
contig assigned to HAV2 (see above) (Garrett et al.
2010). However, since only one ORF showed simi-
larity (38% a.a. identity) to an HAV2 gene the authors
raised the possibility that this contig was part of a
novel viral genome (Gudbergsdottir et al. 2016). The
CRISPR analysis revealed that four spacers in the It3
metagenome matched to this novel genome originat-
ing from the hyperthermophilic crenarchaeon Py-
robaculum and indicating that the contig is an
extracellular sequence of either viral or plasmid origin
(Gudbergsdottir et al. 2016).
4.9 Lassen Volcanic National Park, USA
Viral metagenomic was carried out on samples from
the Boiling Springs Lake (BSL), an acidic, high
temperature lake (temperature ranging between 52
and 95 °C with a pH of approximately 2.5) located
in Lassen Volcanic National Park, USA (Table 2;
Diemer and Stedman 2012). The study revealed the
presence of a unique circular, putatively single-
stranded DNA virus, named RDHV (RNA-DNA
hybrid virus; Diemer and Stedman 2012). Indeed,
this viral genome harboured genes homologous to
both ssRNA and ssDNA viruses with the ORFs
arranged in an uncommon orientation. Intriguingly,
the hybrid nature of this virus was explained with
the occurrence of an interviral RNA-DNA recombi-
nation event in which a DNA circovirus-like
progenitor acquired a capsid protein gene from a
ssRNA virus via reverse transcription and recombi-
nation (Faurez et al. 2009). Mining environmental
sequence databases for genetic similar configura-
tions allowed the identification of three candidate
BSL RDHV-like genomes, thus indicating that BSL
RDHV is not endemic to Boiling Springs Lake.
Such recombination events, although occur infre-
quently, might constitute one of the driving force for
the evolution of novel viruses originating through
genetic exchange between distinct virus lineages
(Diemer and Stedman 2012).
4.10 Los Azufres National Park, Mexico
To date, the only microbial survey carried out in the
Los Azufres National Park (Mexico) was reported by
Brito and co-workers (Brito et al. 2014) analyzing five
different samples among which AM1 (87 °C; pH 3.4)
is the only one with temperature [65 °C. AM1,
collected from the main geyser present in the ‘‘Los
Azufres spa’’ showed high concentration of metals
such as Zn and Mn and of heavy metals (Hg, Pb and
Fe) up 1000 fold the EPA and WHO drinking water
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standards. The analysis by T-RFLP and 16S of the
sites revealed an overall low bacterial diversity and
that in particular AM1 was dominated exclusively by a
microorganism related to Lysobacter spp. before
identified in different extreme environments. This
result suggests that the bacterial community of this
site, if compared with the other in the area at lower
temperature, was mainly influenced by the concentra-
tion of Zn, Mn and temperature (Brito et al. 2014).
A study performed by Servı
´n-Garciduen
˜as et al.
(2013a,b) identified the consensus sequence of a novel
archaeal rudivirus (SMR1) as well as of a new member
of the family Fuselloviridae (SMF1) by metagenomic
reads assembly. Despite the large geographical dis-
tance from the locations of other sequenced rudi-
viruses and fuselloviruses, SMR1 and SMF1 retained a
core set of conserved genes specific to Rudiviridae and
Fuselloviridae, respectively. These genes were
inferred to be important for the viral life cycle and
their occurrence on the genomes of viruses geograph-
ically separated supported the hypothesis of exchange
of genetic material over intercontinental distances
(Servı
´n-Garciduen
˜as et al. 2013a,b).
5 Enzyme discovery
One of the driving interests toward metagenomic of
geothermal environments is the discovery and
exploitation of a rich pool of uncharacterised meta-
bolic pathways as well as of novel thermostable en-
zymes (thermozymes) with biochemical char-
acteristics evolved to accommodate the unique envi-
ronments that the microbes reside in Bartolucci et al.
(2013). Specifically, thermozymes exhibit an intrinsic
stability to common protein chemical–physical denat-
urants and therefore are of great interest in biotech-
nological applications representing a valuable
alternative to the available enzymes from mesophiles
(Cobucci-Ponzano et al. 2015; Sharma et al. 2012).
5.1 Sequence-based function prediction
SBM enables the construction of data banks of all the
genes present in a geothermal sample. In silico
screening for sequence similarity or the presence of
conserved motifs followed by amplified through PCR-
approaches can allow the production of enzymes of
potential applicative interest. Some frequently used
databases for functional annotation are the SEED
annotation system, the KEGG orthology (KO) data-
base or the Pfam database (Finn et al. 2016; Kanehisa
et al. 2014; Overbeek et al. 2014). Then, identified
genes can be cloned and expressed in conventional
hosts from native or inducible promoters and recom-
binant enzymes can be purified and characterized in
detail. This approach increased enormously the num-
ber of genes to analyse if compared to genomic
screening requiring the isolation of microbial strains,
and it is especially convenient for extremophilic
microorganisms whose isolation is particularly chal-
lenging. On the other hand, also this approach shows
limitations. Firstly, the databases may be subjected to
phylogenetic biases, as some communities are more
accurately annotated than others; secondly, since
prediction of genes function is based on sequence
similarity to not many already characterized genes and
pathways in the public databases, currently, about
50% of genes in genomes are defined as ‘‘hypothet-
ical’’ or proteins of unknown function. Thirdly, the
presence of a gene on a metagenome does not mean
that it is expressed. To increase the probability of
finding active functional genes involved in a substrate
uptake and transformation, some studies use activity-
based screenings on expression libraries (functional
metagenomics) or a substrate-induced enrichment of
the community before the mDNA extraction (see
below).
5.2 Functional metagenomics
A powerful alternative or a complement, to SBM is
functional metagenomics that relies on the construc-
tion of metagenomic libraries by cloning environmen-
tal DNA into expression vectors and propagating them
in the appropriate hosts, followed by activity-based
screening (Fig. 2). Depending on the size of the insert,
functional metagenomics can be explored using vec-
tors carrying short (\
10 kb) or long size inserts
(200 kb). Bigger inserts have the potential to carry
entire gene-clusters as well as their own promoter
sequences, allowing the expression of more enzymes.
By using an appropriate screening method, genes
expressing a particular enzymatic activity can be
identified and their products characterized. Lambda
phage-based expression vectors offer the possibility of
screening for particular enzymatic activities directly
on phage plaques. Indeed E. coli cells are lysed at the
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end of the infection cycle and the translated metage-
nomic proteins are released into the extracellular
matrix. The main advantages of this approach are: (1)
isolation of entire genes, (2) direct identification of
enzymes fully active in recombinant form, and (3)
identification of novel enzymatic activities, whose
functions would not be predicted from the available
sequence databases (Lo
´pez-Lo
´pez et al. 2014).
The description of the thermozymes isolated
through functional metagenomics goes beyond the
aims of this manuscript. One of the main limitations of
this approach is the expression of heterologous genes
in E. coli (Gabor et al. 2004). Although the commonly
used E.coli strains have relaxed requirements for
promoter recognition and translation initiation, in this
host proteins may not fold correctly and many genes
from extremophilic environmental samples are not
translated efficiently, especially those belonging to
archaea, which might show a codon usage bias (Prato
et al. 2008). Alternative hosts and broad-host-range
vectors may be required to overcome these limitations
(Angelov et al. 2009; Cheng et al. 2014). Recently,
Leis and co-workers identified novel esterases from
hot springs in the Azores based by complementing the
growth of a custom, esterase-deficient strain of
Thermus thermophilus. By using this method, they
uncover several enzymes from underrepresented
species of archaeal origin leading to the identification
of new biocatalysts that do not share any known
sequence signatures at all (Leis et al. 2015).
5.3 Extremophilic microbiome enrichments
Direct selection of the enzymes by functional metage-
nomics is not always the best approach and adaptation
of entire extremophilic microbiomes on specific
substrates is an interesting alternative choice. Often,
complex substrates, recalcitrant to enzymatic conver-
sion, require the combined action of many catalytic
activities and accessory proteins that, in nature, are
provided by a complex microbiome. This is particu-
larly true for the conversion of plant lignocellulosic
material including cellulose and hemicelluloses (xy-
lans, xyloglucans, pectins, etc.) that are the two most
abundant polymers on Earth (global cellulose produc-
tion estimates range between 9 910
12
and
1.5 910
12
tons/year (Ha et al. 2011; Pinkert et al.
2009) and are remarkably stable to spontaneous
hydrolysis (half-life of the glycosidic bond is
4.7 910
6
years, Wolfenden et al. 1998). Thus, car-
bohydrate active enzymes (cazymes) from (hy-
per)thermophiles have interesting biotechnological
potential (Cobucci-Ponzano et al. 2006,2010a,b). In
fact, their impressive stability (Ausili et al. 2004)at
the conditions at which plant lignocellulose is pre-
treated in second generation biorefineries (steam-
explosion at extremes of temperatures and pHs), make
them the ideal catalysts for the hydrolysis of (hemi)-
cellulose into fermentable sugars for the production of
bioethanol and plastic precursors (Castiglia et al.
2016; Cobucci-Ponzano et al. 2013,2015; Iacono et al.
2016; Aulitto et al. 2017).
Functional metagenomics through selections at
high temperatures (60–75 °C) allowed the identifica-
tion of interesting thermophilic cazymes, including b-
glucosidase, cellulase, b-xylosidases/a-arabinofura-
nosidase, endoxylanase, a-fucosidase, and acetyl
xylan esterase from samples collected in environmen-
tal niches, like guts of animals and insects, and
compost, swine waste, and thermophilic methano-
genic digesters (Allgaier et al. 2010; Dougherty et al.
2012; Liang et al. 2010; Wang 2009; Wang et al.
2015c). However, direct selection of microbiomes
from extreme environments on plant biomass is a
useful alternative. Gladden and collaborators adapted
samples from composts to grow on switchgrass by
multiple passages at 60 °C. The enrichments produced
a reduction in microbiome diversity showing by 16S
rRNA the presence of thermophilic Gram-positive
bacteria Firmicutes,Bacteriodetes,Chloroflexi, and,
remarkably, an uncultivated lineage related to the
Gemmatimonadetes phylum (Gladden et al. 2011). In
addition, supernatants of the enriched cultures showed
endoglucanase and xylanase activities more
stable than those commercially available and
exploited in biorefineries. With a similar approach,
enrichments of a sample from a 94 °C geothermal pool
in Nevada (USA) on Miscanthus and cellulose Avicel
in strictly anaerobic conditions at 90 °C were per-
formed (Graham et al. 2011). Three 16S rRNA genes
were identified corresponding to the archaea Ignis-
phaera aggregans,Pyrobaculum islandicum, and
Thermophilum pendens, with the Ignisphaera-like
strain dominating the microbiome. In addition, CMC
active enzymes were detected in the enriched cultures
and the annotation analysis of the metagenomic data
bank allowed to identify and characterize a novel GH5
endoglucanase. This study showed the first
446 Rev Environ Sci Biotechnol (2017) 16:425–454
123
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microbiome of archaea able to deconstruct lignocel-
lulose at 90 °C and a novel uncommon cellulase
showing promising application in biorefineries.
Finally, a metagenomic analysis of an environmental
sample dominated by Firmicutes and collected in hot
springs (50-70 °C) in Xiamen-China has been
reported very recently. Upon enrichment on sugarcane
bagasse, a novel cellulase, XM70-Cel9, was identified
and biochemically characterized displaying relevant
biotechnological properties i.e. optimal temperature of
70 °C and good pH tolerance (Zhao et al. 2017).
6 Conclusions
The interest in the diversity, ecology, physiology and
biochemistry of extreme- and hyper-thermophilic
microorganisms has increased enormously during the
past few decades. An unanticipated phylogenetic and
physiological diversity of thermophiles has been
revealed through metagenomic studies conducted in
different thermophilic biotopes. Figure 5shows the
principal component analysis of the geothermal sites
herein described taking into account pH, temperature
and dominant phyla. The analysis clearly indicates a
direct correlation between the predominance of
archaeal phyla (i.e. Crenarchaeota) in higher temper-
ature (*75–90 °C) and low pH (2.6–5.5) sites and of
bacterial phyla (i.e. Aquificae) under lower tempera-
ture (*65 to 80 °C) and high pH (5.5–9.4) conditions.
This observation is in perfect agreement with the
studies reported by Inskeep et al. (2013b) in the YNP
metagenomic project.
It is expected that the combination of DNA
metagenomic studies together with metatranscrip-
tomic and metaproteomic approaches will allow us
to understand the functional dynamics of microbial
communities as well as to advance the prediction of
the in situ microbial activities and productivity of
microbial consortia.
Fig. 5 Principal
component representation of
the geothermal sites
described in this review (see
Table 1) considering
temperature, pH and
dominant phyla as clustering
parameters. The two main
clusters of geothermal sites,
Aand B, reflect the
correlation between the
dominant phyla and the
environmental parameters
(pH and T) confirming the
presence of dominant
archaeal and bacterial phyla
in high temperature/low pH
and low temperature/high
pH geothermal
environments, respectively.
1–20 Yellowstone National
Park (red), 21–22 Iceland
(light blue), 23–33
Kamchatka (orange), 34–35
Furnas Valley (purple), 36
Malasya (grey), 37–50
Rehai and Ruidia (pink); 51–
54 Taupo (green) and 55–56
Phlegraean fields (green);
57 Los Azufres (black).
(Color figure online)
Rev Environ Sci Biotechnol (2017) 16:425–454 447
123
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Besides the bacterial and archaeal communities,
viral metagenomic studies have provided information
concerning viral biogeography, diversity and commu-
nity structure of hot environments, and new viral types
contributing to the discovery of potential archaeal
RNA viruses. Viral metagenomics analysis has also
revealed the presence of high percentage of unknown
sequences demonstrating the vast novelty of genetic
information to be still obtained from viruses.
Microbial and viral metagenomics open up the
roads to analyze and screen the genetically and
metabolically rich microbial thermophilic communi-
ties in their entirety. By further developing high-
throughput screening methods and chromogenic sub-
strates-based tests for the detection of thermozymes it
is possible to foresee a quantum leap in the discovery
of novel biocatalysts to be successfully exploited in
sustainable processes for industrial applications.
Funding This work was supported by a Grant from
BIOPOLIS: PON03PE_00107_1 CUP: E48C14000030005
and by the project ‘‘Esobiologia e ambienti estremi: dalla
Chimica delle Molecole alla Biologia degli Estremofili—
ECMB’’ No. 2014-026-R.0 of the Italian Space Agency.
Authors’ contribution AS, SF, BCP, MM and PC wrote,
reviewed and edited the manuscript. All authors read and
approved the final manuscript.
Compliance with ethical standards
Conflict of interest The authors declare that they have no
conflict of interest.
Open Access This article is distributed under the terms of the
Creative Commons Attribution 4.0 International License (http://
creativecommons.org/licenses/by/4.0/), which permits unre-
stricted use, distribution, and reproduction in any medium,
provided you give appropriate credit to the original
author(s) and the source, provide a link to the Creative Com-
mons license, and indicate if changes were made.
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