31
their denitrifying gene abundance genes to the greenhouse gas (nitrous oxide) emission from agriculture lands (Morales et al. 2010). The microbial community composition of Crenarchaeota in terrestrial as well as in aquatic ecosystems is also
identified through Q-PCR, which confirmed that Crenarchaeota is a stable community in the terrestrial ecosystem (Ochsenreiter et al. 2003). The relative abundance
of common groups of soil microorganisms was identified through taxa-specific
quantitative PCR (Fierer et al. 2005). However, in some cases the Q-PCR base analysed abundance of microorganism groups not truly representing their percentage in
environmental samples because of poor DNA isolation, improper rRNA sequence,
and a heterogeneous number of rRNA operons (Smith and Osborn 2009; Fierer
et al. 2005). Quantitative genotyping and single-nucleotide polymorphism (SNP)
detection, identification of alleles, can easily be performed through Q-PCR. It has
further implication in molecular diagnostics for rapid identification and enumeration of pathogens, which helps in controlling disease outbreaks in agriculture as
well as in medical sciences. Q-PCR has rapidly gained popularity because of its
robustness and higher responsiveness even for a low quantity of nucleic acids from
different samples (Smith and Osborn 2009). Some researchers such as Smets et al.
(2016), Props et al. (2017), and Wang et al. (2018) suggested that the Q-PCR can
also be utilized for identification and quantification of gene expression, analysing
the microbial abundance profiles in the soil and other complex environmental samples. Q-PCR-dependent detection tools based on species-specific primers are highly
useful for providing insight about host–microbe interactions in different domains of
the environment dealing with soil microbiology, ecology, etiology, and epidemiology of plant-pathogenic microorganisms.
3.9 DNA Microarray
Molecular-based methodologies have greatly increased our capability of microbial
identification from different environmental compartments. Still, it is difficult to
completely explore the vast microbial diversity of different environmental compartments as most of the methods can study only a small sample size with a limited set
of organisms. We therefore need more comprehensive and robust methods.
Microarrays with specifically designed microarray plates have unprecedented ability to quantify the microbial communities in a system. The method has been customized to access differences in gene expression between many cells and even in the
same cell grown in dissimilar conditions (Zhou and Thompson 2002; Bodrossy and
Sessitsch 2004; Schadt and Zhou 2005). DNA microarrays consist of probes composed of nucleic acids associated to a planar glass surface that is usually labelled
with chemically reactive groups (epoxy, poly-L-lysine, or aldehyde) for proper
binding of nucleotide probes. Samples are labelled chemically or by enzymatic
reaction to analyse the presence of targeted nucleic acid sequences. Further labelled
samples are hybridized on the array and washed with different-strength buffer solutions. The signal obtained through specific interactions among the probes and target
3.9 DNA Microarray
their denitrifying gene abundance genes to the greenhouse gas (nitrous oxide) emission from agriculture lands (Morales et al. 2010). The microbial community composition of Crenarchaeota in terrestrial as well as in aquatic ecosystems is also
identified through Q-PCR, which confirmed that Crenarchaeota is a stable community in the terrestrial ecosystem (Ochsenreiter et al. 2003). The relative abundance
of common groups of soil microorganisms was identified through taxa-specific
quantitative PCR (Fierer et al. 2005). However, in some cases the Q-PCR base analysed abundance of microorganism groups not truly representing their percentage in
environmental samples because of poor DNA isolation, improper rRNA sequence,
and a heterogeneous number of rRNA operons (Smith and Osborn 2009; Fierer
et al. 2005). Quantitative genotyping and single-nucleotide polymorphism (SNP)
detection, identification of alleles, can easily be performed through Q-PCR. It has
further implication in molecular diagnostics for rapid identification and enumeration of pathogens, which helps in controlling disease outbreaks in agriculture as
well as in medical sciences. Q-PCR has rapidly gained popularity because of its
robustness and higher responsiveness even for a low quantity of nucleic acids from
different samples (Smith and Osborn 2009). Some researchers such as Smets et al.
(2016), Props et al. (2017), and Wang et al. (2018) suggested that the Q-PCR can
also be utilized for identification and quantification of gene expression, analysing
the microbial abundance profiles in the soil and other complex environmental samples. Q-PCR-dependent detection tools based on species-specific primers are highly
useful for providing insight about host–microbe interactions in different domains of
the environment dealing with soil microbiology, ecology, etiology, and epidemiology of plant-pathogenic microorganisms.
3.9 DNA Microarray
Molecular-based methodologies have greatly increased our capability of microbial
identification from different environmental compartments. Still, it is difficult to
completely explore the vast microbial diversity of different environmental compartments as most of the methods can study only a small sample size with a limited set
of organisms. We therefore need more comprehensive and robust methods.
Microarrays with specifically designed microarray plates have unprecedented ability to quantify the microbial communities in a system. The method has been customized to access differences in gene expression between many cells and even in the
same cell grown in dissimilar conditions (Zhou and Thompson 2002; Bodrossy and
Sessitsch 2004; Schadt and Zhou 2005). DNA microarrays consist of probes composed of nucleic acids associated to a planar glass surface that is usually labelled
with chemically reactive groups (epoxy, poly-L-lysine, or aldehyde) for proper
binding of nucleotide probes. Samples are labelled chemically or by enzymatic
reaction to analyse the presence of targeted nucleic acid sequences. Further labelled
samples are hybridized on the array and washed with different-strength buffer solutions. The signal obtained through specific interactions among the probes and target
3.9 DNA Microarray