34
4.1 Single-Cell Genomics (SCG)
Most of our present knowledge about the genome and its control is gained from
population-level studies involving thousands to millions of cells on average for
analysis. The resulting study, even though informative, quite frequently ignores any
heterogeneity within the population of cells (Macaulay and Voet 2014). Molecular
differences among individual single cells inside tissues and organ systems have led
to greater understanding. What is the dissimilarity between adjacent cells? How do
neighbouring cells affect each other? How do the cells influence the organization
and function of the organs and organisms? What is the difference at the genetic,
epigenetic, and gene expression levels? What is the phenomenon behind specific
development or diseases in individual cells? All these questions have remained
unexplored (Lovett 2013). Now, the ‘omics’ of single cells offers the chance for
exploring all these biological complexities that are currently a complex and challenging task (Lovett 2013). Development of the field of single-cell genomics signifies a turning point in cell biology. Through single-cell genomics, the expression
level of each gene per genome across thousands of individual cells can be accomplished within a single experiment. Single-cell genomics can assist the discovery of
new genes and pathways that regulate cell fate and transitions (Trapnell 2015).
Single-cell genomics and metagenomics correspond to two different sides of the
same coin, providing an understanding of the biology of organisms that cannot be
cultured (Perkel 2012). Metagenomics explores the genetic potential of a community but not the individuals. Single-cell approaches can cross that gap by endowing
scaffolds for the assembly of metagenomics data or reference genomes for variation
analyses. Therefore, for a large group of researchers these two approaches are complementary (Perkel 2012). The shift from 16S rRNA gene diversity analysis to
metagenomics, and just recently to single-cell genomics (SCG), is largely driven by
recent technological advances in sequencing approaches facilitating megabasescale to, ultimately, terabase-scale surveys (Woyke and Jarett 2015). In cultivationindependent genomics approaches, SCG can exclusively facilitate assessment of the
functional potential of totally unknown microbes without needing to rely on precise
assembly and binning approaches for metagenome data (Woyke and Jarett 2015).
One of the prime advantages of SCG is that it allows examination of samples at the
basic unit of life, the individual cells, and permits access to nucleic acids and the
relationship of features such as plasmids and cell-contained phages to the genome.
Single-cell genomes are now consistently sequenced and submitted to public databases, similar to metagenomes 10 years ago (Woyke and Jarett 2015). SCG has been
used in deciphering microbial entities and their communication behaviour in studying the interactions between two genes (Blainey 2012). The technique can provide
the structure of the microbial community and their functionality in various ecosystems (Lasken 2012). It can also give in-depth knowledge about inter-organism metabolic interaction and the evolutionary traits of uncultivable microbes (Stepanauskas
2012). Single-cell genomics uses unique synergy between the complex instrumentation, in which fluorescent in situ hybridization/fluorescence- activated cell sorting
(FISH/FACS) was used for separation of cells during the study of environmental
4 Single-Cell Genomics and Metagenomics for Microbial Diversity Analysis
4.1 Single-Cell Genomics (SCG)
Most of our present knowledge about the genome and its control is gained from
population-level studies involving thousands to millions of cells on average for
analysis. The resulting study, even though informative, quite frequently ignores any
heterogeneity within the population of cells (Macaulay and Voet 2014). Molecular
differences among individual single cells inside tissues and organ systems have led
to greater understanding. What is the dissimilarity between adjacent cells? How do
neighbouring cells affect each other? How do the cells influence the organization
and function of the organs and organisms? What is the difference at the genetic,
epigenetic, and gene expression levels? What is the phenomenon behind specific
development or diseases in individual cells? All these questions have remained
unexplored (Lovett 2013). Now, the ‘omics’ of single cells offers the chance for
exploring all these biological complexities that are currently a complex and challenging task (Lovett 2013). Development of the field of single-cell genomics signifies a turning point in cell biology. Through single-cell genomics, the expression
level of each gene per genome across thousands of individual cells can be accomplished within a single experiment. Single-cell genomics can assist the discovery of
new genes and pathways that regulate cell fate and transitions (Trapnell 2015).
Single-cell genomics and metagenomics correspond to two different sides of the
same coin, providing an understanding of the biology of organisms that cannot be
cultured (Perkel 2012). Metagenomics explores the genetic potential of a community but not the individuals. Single-cell approaches can cross that gap by endowing
scaffolds for the assembly of metagenomics data or reference genomes for variation
analyses. Therefore, for a large group of researchers these two approaches are complementary (Perkel 2012). The shift from 16S rRNA gene diversity analysis to
metagenomics, and just recently to single-cell genomics (SCG), is largely driven by
recent technological advances in sequencing approaches facilitating megabasescale to, ultimately, terabase-scale surveys (Woyke and Jarett 2015). In cultivationindependent genomics approaches, SCG can exclusively facilitate assessment of the
functional potential of totally unknown microbes without needing to rely on precise
assembly and binning approaches for metagenome data (Woyke and Jarett 2015).
One of the prime advantages of SCG is that it allows examination of samples at the
basic unit of life, the individual cells, and permits access to nucleic acids and the
relationship of features such as plasmids and cell-contained phages to the genome.
Single-cell genomes are now consistently sequenced and submitted to public databases, similar to metagenomes 10 years ago (Woyke and Jarett 2015). SCG has been
used in deciphering microbial entities and their communication behaviour in studying the interactions between two genes (Blainey 2012). The technique can provide
the structure of the microbial community and their functionality in various ecosystems (Lasken 2012). It can also give in-depth knowledge about inter-organism metabolic interaction and the evolutionary traits of uncultivable microbes (Stepanauskas
2012). Single-cell genomics uses unique synergy between the complex instrumentation, in which fluorescent in situ hybridization/fluorescence- activated cell sorting
(FISH/FACS) was used for separation of cells during the study of environmental
4 Single-Cell Genomics and Metagenomics for Microbial Diversity Analysis