Part B | 11.3
316 Part B Tools and Methods in Marine Biotechnology
teractions in cells and fluxomics establishes dynamic
changes of molecules within a cell over time [11.99].
No single approach is sufficient to characterize the
complexity of biological systems [11.99]. In fact, it is
only through the integration of multiple layers or dimensions of information (provided by different omics
approaches) that a proper understanding of the whole
cell operation can be obtained [11.98]. The integration
of the overwhelming amount of information obtained
from multiple datasets can only be accomplished with
the use of mathematical modeling and computational
tools and results in a dynamic map of all cellular functions and regulatory circuits with spatiotemporal resolution [11.107]. The advances of the field of systems
biology are empowering the engineering of industrial
microorganisms, allowing the development of more
robust strategies and moving the field toward a designbased engineering of biological systems [11.108].
Single-Cell Analyses
The analysis of single cells is an approach with multiple biotechnological applications and presents both
unprecedented challenges and opportunities [11.83]. Individual cells can be physically separated from each
other and/or from the environmental matrix material before further analysis, through a technique called singlecell isolation [11.109]. In addition, targeted cells can be
individually recognized and distinguished from background populations through cell-sorting techniques, although some cell-sorting instrumentation also allows
cell isolation [11.109]. The fundamentals, advantages,
and drawbacks of the different devices used for cell
sorting and cell isolation were recently reviewed in detail [11.107, 109] and therefore they will not be covered
in this chapter.
One of the applications of single-cell analysis is
the study of cell-to-cell variations within an isogenic
cell population, delivering functional biological information beyond the statistical average of a microbial
population [11.107]. For example, through the use of
total transcript amplification, the heterogeneity of transcript levels among individual cells within a bacterial
population can now be studied [11.110]. A second
application of single-cell analysis is to individually
study yet-to-be cultured microorganisms using omics
approaches. Single-cell genomics (SCG) involves the
isolation of single cells from an environmental sample,
the purification of its DNA, followed by whole-genome
amplification and sequencing [11.26]. Methodological difficulties of SCG include background contamination during the amplification of single-cell DNA,
biases during amplification and sequencing, as well
as difficulties in sequence assembly [11.83, 111]. Different strategies have been tested in order to improve
SCG, such as reagent decontamination before amplification [11.112], artificially inducing polyploidy in single cells [11.113], improving the efficiency of genome
amplification [11.83], as well as using more efficient
assembly algorithms [11.111]. In spite of its limitations, it is currently possible to obtain a high percentage
of de novo genome sequences from yet-to-be cultured
microorganisms.
SCG is considered a powerful complement of both
cultivation and metagenomics, as it allows us to link
the metabolic potential of an uncultured microorganism with its taxonomic identity, as well as to define
possible strategies for the isolation of the microorganism [11.114]. In addition, SCG allows us to study
in situ interactions among organisms and is particularly suited for the analysis of symbiotic systems, for
example, the biotechnologically-relevant bacterial symbionts of marine sponges [11.115, 116]. In a recent
work, Bayer et al. [11.117] identified novel enzymes
involved in halogenation reactions in marine spongeassociated microbial consortia using a combination of
omics approaches, including SCG. In another study,
Martinez-Garcia and collaborators [11.118] sequenced
five Verrucomicrobia cells, identifying genes encoding
a wide spectrum of glycoside hydrolases, sulfatases,
peptidases, carbohydrate lyases, and esterases. In addition, the analysis of partially assembled genomes
of only ten cells of Prochlorococcus increased the
pan-genome of this genus by 4:6%, highlighting the
potential of this approach for bioprospecting [11.119].
Information concerning which proteins are being expressed in a particular environmental condition, their
abundance, as well as post-translational modifications
could be obtained through single-cell proteomics. However, further development of MS and micro/nanofluidic
based technologies is needed for the analysis of the
proteome from single cells. Although still not widely
used in biotechnological applications, the combination
of single-cell omics approaches has the potential to significantly contribute to this field [11.107, 114].
Metagenomic Approaches
Metagenomics, the direct analysis of the genomes contained in a microbial community, nowadays represents
a key tool for microbial marine bioprospecting, as it
allows access to the genetic potential of a microbial
community. Metagenomic analyses typically start with
the purification of DNA from an environmental sam-
316 Part B Tools and Methods in Marine Biotechnology
teractions in cells and fluxomics establishes dynamic
changes of molecules within a cell over time [11.99].
No single approach is sufficient to characterize the
complexity of biological systems [11.99]. In fact, it is
only through the integration of multiple layers or dimensions of information (provided by different omics
approaches) that a proper understanding of the whole
cell operation can be obtained [11.98]. The integration
of the overwhelming amount of information obtained
from multiple datasets can only be accomplished with
the use of mathematical modeling and computational
tools and results in a dynamic map of all cellular functions and regulatory circuits with spatiotemporal resolution [11.107]. The advances of the field of systems
biology are empowering the engineering of industrial
microorganisms, allowing the development of more
robust strategies and moving the field toward a designbased engineering of biological systems [11.108].
Single-Cell Analyses
The analysis of single cells is an approach with multiple biotechnological applications and presents both
unprecedented challenges and opportunities [11.83]. Individual cells can be physically separated from each
other and/or from the environmental matrix material before further analysis, through a technique called singlecell isolation [11.109]. In addition, targeted cells can be
individually recognized and distinguished from background populations through cell-sorting techniques, although some cell-sorting instrumentation also allows
cell isolation [11.109]. The fundamentals, advantages,
and drawbacks of the different devices used for cell
sorting and cell isolation were recently reviewed in detail [11.107, 109] and therefore they will not be covered
in this chapter.
One of the applications of single-cell analysis is
the study of cell-to-cell variations within an isogenic
cell population, delivering functional biological information beyond the statistical average of a microbial
population [11.107]. For example, through the use of
total transcript amplification, the heterogeneity of transcript levels among individual cells within a bacterial
population can now be studied [11.110]. A second
application of single-cell analysis is to individually
study yet-to-be cultured microorganisms using omics
approaches. Single-cell genomics (SCG) involves the
isolation of single cells from an environmental sample,
the purification of its DNA, followed by whole-genome
amplification and sequencing [11.26]. Methodological difficulties of SCG include background contamination during the amplification of single-cell DNA,
biases during amplification and sequencing, as well
as difficulties in sequence assembly [11.83, 111]. Different strategies have been tested in order to improve
SCG, such as reagent decontamination before amplification [11.112], artificially inducing polyploidy in single cells [11.113], improving the efficiency of genome
amplification [11.83], as well as using more efficient
assembly algorithms [11.111]. In spite of its limitations, it is currently possible to obtain a high percentage
of de novo genome sequences from yet-to-be cultured
microorganisms.
SCG is considered a powerful complement of both
cultivation and metagenomics, as it allows us to link
the metabolic potential of an uncultured microorganism with its taxonomic identity, as well as to define
possible strategies for the isolation of the microorganism [11.114]. In addition, SCG allows us to study
in situ interactions among organisms and is particularly suited for the analysis of symbiotic systems, for
example, the biotechnologically-relevant bacterial symbionts of marine sponges [11.115, 116]. In a recent
work, Bayer et al. [11.117] identified novel enzymes
involved in halogenation reactions in marine spongeassociated microbial consortia using a combination of
omics approaches, including SCG. In another study,
Martinez-Garcia and collaborators [11.118] sequenced
five Verrucomicrobia cells, identifying genes encoding
a wide spectrum of glycoside hydrolases, sulfatases,
peptidases, carbohydrate lyases, and esterases. In addition, the analysis of partially assembled genomes
of only ten cells of Prochlorococcus increased the
pan-genome of this genus by 4:6%, highlighting the
potential of this approach for bioprospecting [11.119].
Information concerning which proteins are being expressed in a particular environmental condition, their
abundance, as well as post-translational modifications
could be obtained through single-cell proteomics. However, further development of MS and micro/nanofluidic
based technologies is needed for the analysis of the
proteome from single cells. Although still not widely
used in biotechnological applications, the combination
of single-cell omics approaches has the potential to significantly contribute to this field [11.107, 114].
Metagenomic Approaches
Metagenomics, the direct analysis of the genomes contained in a microbial community, nowadays represents
a key tool for microbial marine bioprospecting, as it
allows access to the genetic potential of a microbial
community. Metagenomic analyses typically start with
the purification of DNA from an environmental sam-