Marine Metagenome and Supporting Technology References 505
Part C | 19
ing of large metagenome libraries, technologies are
also required for the analysis of the huge amounts of
data generated by metagenomic studies. Already in the
post-genomic era, in the past few years many of us
have experienced the dramatic change from capillary
sequencing approaches to the recent next-generation
sequencing platforms. What was considered known already from capillary sequencing was the ability for
one to identify sequences of new genes from unknown
samples was completely changed with the introduction of deep sequencing platforms such as the 454
(Roche), Solexa (Illumina), SOLiD (Applied Biosystems), HeliScope (Helicos), PACBIO (Pacific Biosciences), and Ion torrent (Life technologies) [19.74,
75] systems. These platforms can generate giga or terabases of sequencing reads in an equal amount of
time to capillary sequencing, allowing not only genes
but genomes of organisms be sequenced in a matter
of days or weeks. In addition, software and techniques have also been developed to support the vast
amount of data generated by these sequencing platforms [19.76]. Even in metagenomics, several analytical and annotation tools such as the meta genome
analyzer (MEGAN) [19.77] and the metagenomics
RAST server (MG-RAST; RAST: rapid annotation using subsystem technology) [19.78], and databases such
as the Genomes OnLine Database (GOLD) [19.79]
and Genomic Encyclopedia of Bacteria and Archaea
(GEBA, http://genome.jgi.doe.gov) project have been
established to assist researchers in their respective
metagenomic analyses and studies.
In our group, we have taken approaches to analyze
the data attained from metagenome sequencing (approximately 110 Mbp) by conducting in silico screening for homologs to 45 enzymes that are of industrial
value. Using analysis of homologs at > 80%, 5080%,
and < 50% similarity against a total of 4075 genes, hits
rates were 1%, 29%, and 70%, respectively.
19.3 Summary
To summarize this chapter, it is clear that since the very
first introduction of metagenomic research for the analysis of various natural environments, not only have we
gained new insights or discovered numerous new and
novel genes that are of great use, we have also come to
realize that new technology and techniques are required
for the field to grow further. High-throughput analytical
systems, such as microfluidics and single-cell analysis
are just some examples of technology that have shown
its potential in supporting the rapidly growing metagenomic research field. With the rate at which the amounts
of data are being generated, it is almost certain that
in the very near future, and with the support of bioinformatics, methods or software for data processing and
analysis will also be required. Judging from the rate at
which the field is expanding and evolving, our perspective towards living organisms or natural ecosystems will
certainly change drastically.
References
19.1
P. Hugenholtz, B.M. Goebel, N.R. Pace: Impact
of culture-independent studies on the emerging
phylogenetic view of bacterial diversity, J. Bacteriol. 180(18), 4765–4774 (1998)
19.2
A. Lo Giudice, C. Caruso, S. Mangano, V. Bruni,
M. De Domenico, L. Michaud: Marine bacterioplankton diversity and community composition in
an antarctic coastal environment, Microb. Ecol.
63(1), 210–223 (2012)
19.3
M.G. van der Heijden, R.D. Bardgett, N.M. van
Straalen: The unseen majority: soil microbes as
drivers of plant diversity and productivity in terrestrial ecosystems, Ecol. Lett. 11(3), 296–310 (2008)
19.4
S. Humbert, S. Tarnawski, N. Fromin, M.P. Mallet, M. Aragno, J. Zopfi: Molecular detection of
anammox bacteria in terrestrial ecosystems: distribution and diversity, ISME J. 4(3), 450–454
(2010)
19.5
N. Fierer, R.B. Jackson: The diversity and biogeography of soil bacterial communities, Proc. Natl.
Acad. Sci. USA 103(3), 626–631 (2006)
19.6
L. Zhang, Z.H. Xu: Assessing bacterial diversity in
soil, J. Soils Sediments 8(6), 379–388 (2008)
19.7
F. Niehaus, C. Bertoldo, M. Kahler, G. Antranikian:
Extremophiles as a source of novel enzymes for industrial application, Appl. Microbiol. Biotechnol.
51(6), 711–729 (1999)
19.8
W. Fenical, P.R. Jensen: Developing a new resource
for drug discovery: marine actinomycete bacteria,
Nat. Chem. Biol. 2(12), 666–673 (2006)
Part C | 19
ing of large metagenome libraries, technologies are
also required for the analysis of the huge amounts of
data generated by metagenomic studies. Already in the
post-genomic era, in the past few years many of us
have experienced the dramatic change from capillary
sequencing approaches to the recent next-generation
sequencing platforms. What was considered known already from capillary sequencing was the ability for
one to identify sequences of new genes from unknown
samples was completely changed with the introduction of deep sequencing platforms such as the 454
(Roche), Solexa (Illumina), SOLiD (Applied Biosystems), HeliScope (Helicos), PACBIO (Pacific Biosciences), and Ion torrent (Life technologies) [19.74,
75] systems. These platforms can generate giga or terabases of sequencing reads in an equal amount of
time to capillary sequencing, allowing not only genes
but genomes of organisms be sequenced in a matter
of days or weeks. In addition, software and techniques have also been developed to support the vast
amount of data generated by these sequencing platforms [19.76]. Even in metagenomics, several analytical and annotation tools such as the meta genome
analyzer (MEGAN) [19.77] and the metagenomics
RAST server (MG-RAST; RAST: rapid annotation using subsystem technology) [19.78], and databases such
as the Genomes OnLine Database (GOLD) [19.79]
and Genomic Encyclopedia of Bacteria and Archaea
(GEBA, http://genome.jgi.doe.gov) project have been
established to assist researchers in their respective
metagenomic analyses and studies.
In our group, we have taken approaches to analyze
the data attained from metagenome sequencing (approximately 110 Mbp) by conducting in silico screening for homologs to 45 enzymes that are of industrial
value. Using analysis of homologs at > 80%, 5080%,
and < 50% similarity against a total of 4075 genes, hits
rates were 1%, 29%, and 70%, respectively.
19.3 Summary
To summarize this chapter, it is clear that since the very
first introduction of metagenomic research for the analysis of various natural environments, not only have we
gained new insights or discovered numerous new and
novel genes that are of great use, we have also come to
realize that new technology and techniques are required
for the field to grow further. High-throughput analytical
systems, such as microfluidics and single-cell analysis
are just some examples of technology that have shown
its potential in supporting the rapidly growing metagenomic research field. With the rate at which the amounts
of data are being generated, it is almost certain that
in the very near future, and with the support of bioinformatics, methods or software for data processing and
analysis will also be required. Judging from the rate at
which the field is expanding and evolving, our perspective towards living organisms or natural ecosystems will
certainly change drastically.
References
19.1
P. Hugenholtz, B.M. Goebel, N.R. Pace: Impact
of culture-independent studies on the emerging
phylogenetic view of bacterial diversity, J. Bacteriol. 180(18), 4765–4774 (1998)
19.2
A. Lo Giudice, C. Caruso, S. Mangano, V. Bruni,
M. De Domenico, L. Michaud: Marine bacterioplankton diversity and community composition in
an antarctic coastal environment, Microb. Ecol.
63(1), 210–223 (2012)
19.3
M.G. van der Heijden, R.D. Bardgett, N.M. van
Straalen: The unseen majority: soil microbes as
drivers of plant diversity and productivity in terrestrial ecosystems, Ecol. Lett. 11(3), 296–310 (2008)
19.4
S. Humbert, S. Tarnawski, N. Fromin, M.P. Mallet, M. Aragno, J. Zopfi: Molecular detection of
anammox bacteria in terrestrial ecosystems: distribution and diversity, ISME J. 4(3), 450–454
(2010)
19.5
N. Fierer, R.B. Jackson: The diversity and biogeography of soil bacterial communities, Proc. Natl.
Acad. Sci. USA 103(3), 626–631 (2006)
19.6
L. Zhang, Z.H. Xu: Assessing bacterial diversity in
soil, J. Soils Sediments 8(6), 379–388 (2008)
19.7
F. Niehaus, C. Bertoldo, M. Kahler, G. Antranikian:
Extremophiles as a source of novel enzymes for industrial application, Appl. Microbiol. Biotechnol.
51(6), 711–729 (1999)
19.8
W. Fenical, P.R. Jensen: Developing a new resource
for drug discovery: marine actinomycete bacteria,
Nat. Chem. Biol. 2(12), 666–673 (2006)