Through the 16S rRNA gene, the following traditional molecular fingerprinting
methods can be applied to characterize the microflora in the anaerobic digesters
(Talbot et al. 2008):
– Denaturing/temperature gradient electrophoresis;
– Single-strand-conformation polymorphism,
– (Terminal) restriction fragment length polymorphism
– Sanger sequencing of clone libraries.
New applications in research are represented by the use of high-throughput
sequencing technologies as the Roche 454 and the Illumina platforms for sequencing
and the 16S rRNA gene amplicon sequencing. These have increased the resolution
which is available for the analysis of the microbial populations (Werner et al. 2010;
Lee et al. 2012). The results of these analyses have to be correlated with the operative
parameters of the digester to understand really how those can influence the microbial
community structure and metabolic paths (Sundberg et al. 2013; Ziganshin et al.
2013; Zhang et al. 2009).
Metagenomics is the random sequencing of genomic DNA, which has been
extracted directly from the microbial community populating the biogas reactor.
Metagenomics gives different information with respect to the 16S rRNA genebased analysis because it provides data on the physiology of the anaerobic digestion
microbia and their single components (Su et al. 2012; Shakya et al. 2013) (Fig. 10.9).
Metagenomes also can be sequenced and provide information about microbial
genomic diversity and their physiological complexity (Temperton and Giovannoni
2012). The metagenomics has the final goal to reconstruct large genome parts or
complete genomes of all the community members (Tyson et al. 2004; Wrighton et al.
2012).
10.7.2 Metatranscriptomics
Metatranscriptomics is used to sequence the reverse transcribed mRNA which has
been extracted from the bacteria (Su et al. 2012). This can enable the measurement of
the expression of genes in situ (Fig. 10.9). This method can reduce the complexity
level which has been detected with the metagenomics so that only the members of
the community which are metabolically active can be analyzed (Su et al. 2012;
Carvalhais et al. 2012).
10.7.3 Metaproteonomics
This is the analysis of the protein complement of a microbial community at a specific
time (Su et al. 2012) (Fig. 10.9). Basically, the metaproteonomics integrates the data
provided by the metatranscriptomics, because genes expression and activity, have to
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PietroBartocci et al.
methods can be applied to characterize the microflora in the anaerobic digesters
(Talbot et al. 2008):
– Denaturing/temperature gradient electrophoresis;
– Single-strand-conformation polymorphism,
– (Terminal) restriction fragment length polymorphism
– Sanger sequencing of clone libraries.
New applications in research are represented by the use of high-throughput
sequencing technologies as the Roche 454 and the Illumina platforms for sequencing
and the 16S rRNA gene amplicon sequencing. These have increased the resolution
which is available for the analysis of the microbial populations (Werner et al. 2010;
Lee et al. 2012). The results of these analyses have to be correlated with the operative
parameters of the digester to understand really how those can influence the microbial
community structure and metabolic paths (Sundberg et al. 2013; Ziganshin et al.
2013; Zhang et al. 2009).
Metagenomics is the random sequencing of genomic DNA, which has been
extracted directly from the microbial community populating the biogas reactor.
Metagenomics gives different information with respect to the 16S rRNA genebased analysis because it provides data on the physiology of the anaerobic digestion
microbia and their single components (Su et al. 2012; Shakya et al. 2013) (Fig. 10.9).
Metagenomes also can be sequenced and provide information about microbial
genomic diversity and their physiological complexity (Temperton and Giovannoni
2012). The metagenomics has the final goal to reconstruct large genome parts or
complete genomes of all the community members (Tyson et al. 2004; Wrighton et al.
2012).
10.7.2 Metatranscriptomics
Metatranscriptomics is used to sequence the reverse transcribed mRNA which has
been extracted from the bacteria (Su et al. 2012). This can enable the measurement of
the expression of genes in situ (Fig. 10.9). This method can reduce the complexity
level which has been detected with the metagenomics so that only the members of
the community which are metabolically active can be analyzed (Su et al. 2012;
Carvalhais et al. 2012).
10.7.3 Metaproteonomics
This is the analysis of the protein complement of a microbial community at a specific
time (Su et al. 2012) (Fig. 10.9). Basically, the metaproteonomics integrates the data
provided by the metatranscriptomics, because genes expression and activity, have to
334
PietroBartocci et al.