80
assessed separately (see also Levin et al. 2017; Brüwer and
Voolstra 2018; Brüwer and Voolstra within the abstracts
related to this chapter).
Human-induced catastrophes, such as oil spills, result in
immediate long-lasting changes of an ecosystem. In April
2010, the off-shore drilling platform Deepwater Horizon
sank in the Gulf of Mexico, which resulted in 650 million
liters of oil and gas being released into the deep sea (McNutt
et al. 2012). All of the emissions combined could cover the
Vatican state with an about 147 m thick layer. Kimes et al.
(2013) assessed the oil spill affected deep sea-sediments, as
commonly observed aerobic oil degradation may be hindered in anaerobic environments. Using a metabolomics
approach, they detected an increase of benzyl succinates, a
typical product of anaerobic oil biodegradation. An additional metagenomics analysis revealed an aggregation of
anaerobic bacteria, in particular Deltaproteobacteria, in the
respective sediments. This points towards an anoxic catabolism of hydrocarbons, thus suggesting a breakdown of oil
(Kimes et al. 2013).
Metabolomics are frequently applied for process optimization and yield increase in bioengineering. In the field of
algae-based biofuel production, nitrogen starvation of the
algae Chlamydomonas reinhardtii has been shown to
increase carbon assimilation, nitrogen metabolism, and triacylglycerol production (Park et al. 2015), triacylglycerol
being the targeted metabolite.
In conclusion, the omics-toolbox provides the possibility
to evaluate adaptation and acclimatization on a metaorganism scale. Due to its broad approach and the high throughput
methods, rather unexpected pathways may be revealed.
Complex Systems and Multi-meta-omics
The individual omic techniques can only display a fraction
of the biological complexity, as outlined above, since the
measurable appearance of life (i.e., an ome) varies greatly
depending on the layer accessed (e.g., genome, proteome,
etc.). This constitutes, for example, in the turn-over and
dynamic changes of the many intracellular components in
response to the environment. Single-cell studies aim to tackle
this complexity within individual cells by integrating multiomic data (Bock et al. 2016; see Kalita et al. within the
abstracts related to this chapter). On a larger scale, meta-data
from many co-existing organisms are valuable to study the
composition and interactions of communities.
Metagenomic and metatranscriptomic data may delineate
community compositions. This information combined with a
metabolic profile can reveal the ecological interactions exempli gratia in a microbial consortium (Freilich et al. 2011), or
depict the metabolites in an environment as a functional trait
of the respective community (Llewellyn et al. 2015). From
such insights, the contributions of species to an ecosystem’s
functioning and productivity can be deduced. Teeling et al.
(2012) collected samples of the North Sea twice a week over
the course of a year for multi-omics analysis. The succession
of different algal substrate degrading bacterial communities
responded to occurring phytoplankton blooms. They concluded that high bacterioplankton diversity in a relatively
homogeneous habitat as ‘the ocean’ may result from temporally distributed niches (Teeling et al. 2012).
Comparisons of species in a community, which are very
different for example in size, trophic level, or lifestyle, often
lack precision. Although two taxa may share an ecological
feature, their relative abundances may be very different in
the size of their impact on the environment (e.g., sea-weed
grazing of gastropoda and dugongs). And even though two
taxa may perform a comparable task, their ecological function can be entirely different (e.g., free-living and endosymbiotic dinoflagellates). Multi-omics can overcome these
discrepancies, as it can provide simultaneous information on
multiple layers (see Leary et al. 2014; Moran 2015; Thiele
et al. 2017 for marine microbiome).
Conclusion
The rapid development of new techniques, software, and
decreasing costs for high throughput methods allow unprecedented experimental designs. The rising field of omic studies provides a toolbox for a better understanding of the
complexity of life on earth. It is now possible to characterize
organisms on a genome-wide scale. Omics have revealed a
diversity of previously undetected species and simplify
quantitative and functional analyses. However, the transition
between different ome-layers is highly variable and requires
the integration of multiple omic approaches. This can
improve our understanding of the link between the genotype
and phenotype. With multi-omics, we could find out how
complex biological networks function.
Appendix
This article is related to the YOUMARES 8 conference session no. 2: “Reading the Book of Life – Omics as a Universal
Tool Across Disciplines”. The original Call for Abstracts and
the abstracts of the presentations within this session can be
found in the appendix “Conference Sessions and Abstracts”,
chapter “5 Reading the Book of Life – Omics as a Universal
Tool Across Disciplines”, of this book.
J. D. Brüwer and H. Buck-Wiese
assessed separately (see also Levin et al. 2017; Brüwer and
Voolstra 2018; Brüwer and Voolstra within the abstracts
related to this chapter).
Human-induced catastrophes, such as oil spills, result in
immediate long-lasting changes of an ecosystem. In April
2010, the off-shore drilling platform Deepwater Horizon
sank in the Gulf of Mexico, which resulted in 650 million
liters of oil and gas being released into the deep sea (McNutt
et al. 2012). All of the emissions combined could cover the
Vatican state with an about 147 m thick layer. Kimes et al.
(2013) assessed the oil spill affected deep sea-sediments, as
commonly observed aerobic oil degradation may be hindered in anaerobic environments. Using a metabolomics
approach, they detected an increase of benzyl succinates, a
typical product of anaerobic oil biodegradation. An additional metagenomics analysis revealed an aggregation of
anaerobic bacteria, in particular Deltaproteobacteria, in the
respective sediments. This points towards an anoxic catabolism of hydrocarbons, thus suggesting a breakdown of oil
(Kimes et al. 2013).
Metabolomics are frequently applied for process optimization and yield increase in bioengineering. In the field of
algae-based biofuel production, nitrogen starvation of the
algae Chlamydomonas reinhardtii has been shown to
increase carbon assimilation, nitrogen metabolism, and triacylglycerol production (Park et al. 2015), triacylglycerol
being the targeted metabolite.
In conclusion, the omics-toolbox provides the possibility
to evaluate adaptation and acclimatization on a metaorganism scale. Due to its broad approach and the high throughput
methods, rather unexpected pathways may be revealed.
Complex Systems and Multi-meta-omics
The individual omic techniques can only display a fraction
of the biological complexity, as outlined above, since the
measurable appearance of life (i.e., an ome) varies greatly
depending on the layer accessed (e.g., genome, proteome,
etc.). This constitutes, for example, in the turn-over and
dynamic changes of the many intracellular components in
response to the environment. Single-cell studies aim to tackle
this complexity within individual cells by integrating multiomic data (Bock et al. 2016; see Kalita et al. within the
abstracts related to this chapter). On a larger scale, meta-data
from many co-existing organisms are valuable to study the
composition and interactions of communities.
Metagenomic and metatranscriptomic data may delineate
community compositions. This information combined with a
metabolic profile can reveal the ecological interactions exempli gratia in a microbial consortium (Freilich et al. 2011), or
depict the metabolites in an environment as a functional trait
of the respective community (Llewellyn et al. 2015). From
such insights, the contributions of species to an ecosystem’s
functioning and productivity can be deduced. Teeling et al.
(2012) collected samples of the North Sea twice a week over
the course of a year for multi-omics analysis. The succession
of different algal substrate degrading bacterial communities
responded to occurring phytoplankton blooms. They concluded that high bacterioplankton diversity in a relatively
homogeneous habitat as ‘the ocean’ may result from temporally distributed niches (Teeling et al. 2012).
Comparisons of species in a community, which are very
different for example in size, trophic level, or lifestyle, often
lack precision. Although two taxa may share an ecological
feature, their relative abundances may be very different in
the size of their impact on the environment (e.g., sea-weed
grazing of gastropoda and dugongs). And even though two
taxa may perform a comparable task, their ecological function can be entirely different (e.g., free-living and endosymbiotic dinoflagellates). Multi-omics can overcome these
discrepancies, as it can provide simultaneous information on
multiple layers (see Leary et al. 2014; Moran 2015; Thiele
et al. 2017 for marine microbiome).
Conclusion
The rapid development of new techniques, software, and
decreasing costs for high throughput methods allow unprecedented experimental designs. The rising field of omic studies provides a toolbox for a better understanding of the
complexity of life on earth. It is now possible to characterize
organisms on a genome-wide scale. Omics have revealed a
diversity of previously undetected species and simplify
quantitative and functional analyses. However, the transition
between different ome-layers is highly variable and requires
the integration of multiple omic approaches. This can
improve our understanding of the link between the genotype
and phenotype. With multi-omics, we could find out how
complex biological networks function.
Appendix
This article is related to the YOUMARES 8 conference session no. 2: “Reading the Book of Life – Omics as a Universal
Tool Across Disciplines”. The original Call for Abstracts and
the abstracts of the presentations within this session can be
found in the appendix “Conference Sessions and Abstracts”,
chapter “5 Reading the Book of Life – Omics as a Universal
Tool Across Disciplines”, of this book.
J. D. Brüwer and H. Buck-Wiese