56
metabolic machinery used by microbes under diverse habitats as proteins are considered as signature molecules of the cellular processes (Hettich et al. 2013).
Proteomics is stated as a wide-scale study of proteins synthesized by any living
entity (Wilkins et al. 1995). It emerged through 2-D gel electrophoresis-mediated
mapping of protein expression (O’Farrell 1975). The application of 2-D gel electrophoresis made isolation of protein and peptides feasible from a cellular mix of
diverse complexity (Pedersen et al. 1978). Identification of protein is a tedious process because of the limited availability of responsive and high-throughput sequencing tools (Maron et al. 2007). After the 1990s, proteomics emerged as an advanced
tool because of the availability of highly effective mass spectrometry (MS) for peptide ionization, permitting quick and extremely robust identification and characterization of proteins (Pandey and Mann 2000; Yates et al. 1993). Along with this, there
was parallel progress in the field of bioinformatics tools for the analysis of 2D gels
and mass spectra, allowing (1) quick detection of proteins through database matching with available mass spectra (Pandey and Lewitter 1999), (2) further reverse
genetics-based identification of corresponding genes (Mann and Pandey 2001), and
(3) the assessment of protein posttranslational modifications (Anderson et al. 2002).
Apart from these technological advancements, most of the proteomics studies were
conducted under laboratory conditions and do not account for the diverse interactions occurring among the microbial communities. Thus, modified approaches are
required for the in situ identification and evaluation of the wide-scale protein expression at the level of population or community (Maron et al. 2007).
On the basis of the DNA extraction from a specific environment, development of
microbial community genomics represents a path forward (Martin et al. 2006;
Venter et al. 2004; Tyson et al. 2004; Lacerda et al. 2007), although apart from the
discovery of new genes, not much information was related to function and system
dynamics. In contrast, proteomics studies facilitate information about rapid physiological responses as proteins are synthesized and folded within seconds (Lehninger
1965; Lacerda et al. 2007). Limitations of the DNA- or RNA-based approaches
were recognized at the later stages of the postgenomic era by the production of
structural rather than functional information from these approaches (Maron et al.
2007). Large-scale proteomics studies of indigenous microbial communities, that is,
metaproteomics, have emerged as a valuable approach to know the functionality of
the microorganisms in the ecosystem. It is expected that thorough metaproteome
characterization can help in exploring the structural-functional diversity of microbes
from different environmental components (Maron et al. 2007).
5.2.1 Metaproteomics: Benefits and Challenges
Metaproteomics is the characterization of the whole protein component of environmental microbial samples (Wilmes and Bond 2004; Tanca et al. 2014). Analysis of
metaproteome datasets reveals the community structure-function and dynamics of
the microorganisms in a particular environment. It further improves our
5 Metatranscriptomics and Metaproteomics for Microbial Communities Profiling
metabolic machinery used by microbes under diverse habitats as proteins are considered as signature molecules of the cellular processes (Hettich et al. 2013).
Proteomics is stated as a wide-scale study of proteins synthesized by any living
entity (Wilkins et al. 1995). It emerged through 2-D gel electrophoresis-mediated
mapping of protein expression (O’Farrell 1975). The application of 2-D gel electrophoresis made isolation of protein and peptides feasible from a cellular mix of
diverse complexity (Pedersen et al. 1978). Identification of protein is a tedious process because of the limited availability of responsive and high-throughput sequencing tools (Maron et al. 2007). After the 1990s, proteomics emerged as an advanced
tool because of the availability of highly effective mass spectrometry (MS) for peptide ionization, permitting quick and extremely robust identification and characterization of proteins (Pandey and Mann 2000; Yates et al. 1993). Along with this, there
was parallel progress in the field of bioinformatics tools for the analysis of 2D gels
and mass spectra, allowing (1) quick detection of proteins through database matching with available mass spectra (Pandey and Lewitter 1999), (2) further reverse
genetics-based identification of corresponding genes (Mann and Pandey 2001), and
(3) the assessment of protein posttranslational modifications (Anderson et al. 2002).
Apart from these technological advancements, most of the proteomics studies were
conducted under laboratory conditions and do not account for the diverse interactions occurring among the microbial communities. Thus, modified approaches are
required for the in situ identification and evaluation of the wide-scale protein expression at the level of population or community (Maron et al. 2007).
On the basis of the DNA extraction from a specific environment, development of
microbial community genomics represents a path forward (Martin et al. 2006;
Venter et al. 2004; Tyson et al. 2004; Lacerda et al. 2007), although apart from the
discovery of new genes, not much information was related to function and system
dynamics. In contrast, proteomics studies facilitate information about rapid physiological responses as proteins are synthesized and folded within seconds (Lehninger
1965; Lacerda et al. 2007). Limitations of the DNA- or RNA-based approaches
were recognized at the later stages of the postgenomic era by the production of
structural rather than functional information from these approaches (Maron et al.
2007). Large-scale proteomics studies of indigenous microbial communities, that is,
metaproteomics, have emerged as a valuable approach to know the functionality of
the microorganisms in the ecosystem. It is expected that thorough metaproteome
characterization can help in exploring the structural-functional diversity of microbes
from different environmental components (Maron et al. 2007).
5.2.1 Metaproteomics: Benefits and Challenges
Metaproteomics is the characterization of the whole protein component of environmental microbial samples (Wilmes and Bond 2004; Tanca et al. 2014). Analysis of
metaproteome datasets reveals the community structure-function and dynamics of
the microorganisms in a particular environment. It further improves our
5 Metatranscriptomics and Metaproteomics for Microbial Communities Profiling