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Page | 138 Before initiating a whole metagenomic study, an understanding of the potential microbial diversity and the relative abundance of species in the environmental sample is very important.
For example, the metagenome of soil samples will consist of a more complex microbial community, than human skin. Hence, for proper coverage, more data must be generated in case of soil than for human skin. A higher sequencing depth also allows the detection of rare taxa.
This makes shotgun metagenomic sequencing much more expensive than 16S sequencing, in order to achieve the coverage and depth needed for species identification.
Amplicon based sequencing: 16S sequencing is a widely used technique that relies on the variable regions (V1-V9) of the bacterial 16S rRNA gene to make community-wide taxonomic assignments. It is also used for microbial diversity analysis and has been used for various environmental samples, such as soil and gut microflora of animals and humans. Some degree of divergence is allowed during the sequence similarity assessment stage of the analysis;
typically, nearly identical sequences (497%) are clustered into Operational Taxonomical Units (OTU). The limitation of this method is that, if any two organisms have the same 16S rRNA gene sequence, they may be classified as the same species in a 16S analysis, even if they are from different species. Because 16S analysis is based on the 16S rRNA gene, with OTUs defined as taxa, it is generally not possible to distinguish strains, nor, in some cases, closely related species. The OTUs are analyzed at each taxonomic level, but are less precise at the species level.Amplicon based 18S/ITS is one of the basic components of fungal cells and comprises both conserved and hypervariable regions. The internal transcribed spacer region, ITS, is located between the 18S and 5.8S rRNA genes and has a high degree of sequence variation. The 18S rRNA is mainly used for high resolution taxonomic studies of fungi, while the ITS region is widely used for analyzing fungal diversity in environmental samples.
Taxonomic studies of fungi are often based on the nuclear ribosomal gene cluster, which includes the 18S or small subunit (SSU), 5.8S subunit, and 28S or large subunit (LSU) rRNA genes. ITS1 and ITS2 have been found to be the most suitable markers for fungal phylogenetic analysis due to their variable sequences, conserved primers and multicopy nature. Various pipelines, such as QIIME, MG-RAST and Mothur are used to perform taxonomic and functional analysis. In addition to rRNA genes, other amplicon-based studies are performed in order to focus on specific functions such as nitrogen fixation activity, and diversity analysis of nitrogenase reductase (nifH) genes.
B) Meta-transcriptomics and Meta-proteomics: RNA-Seq analysis of microbial communities in a complex ecosystem is known as Meta-transcriptomics (Zhang et al., 2017). Co-expression of gene clusters and transcript abundance, followed by functional annotation, can be studied in environmental samples (Oyserman et al., 2016). The quantitation of mRNA and pathway expression can be carried out using meta- transcriptomics. The challenge associated with meta-transcriptomic approaches is to get high quality RNA from environmental samples; given this, it is an efficient approach to elucidate gene expression, and to discover novel genes in the microbial community. The study of the proteome expressed in the microbial community is known as Meta-proteomics.
This has been used to investigate microbial activities along with complex metabolic
Page | 139 pathways in soil ecosystems. Community metaproteomics are emerging as complementary approaches to metagenomics and can provide large-scale characterization of proteins in the microbiota. Meta-genomics, along with meta-transcriptomics and meta-proteomics, provide insights into functional dynamics, prediction of the in situ microbial responses/activities, and the production capabilities of microbial communities.
Applications of metagenomics:
a) Metagenomics has a wide range of applications from clinical to environmental samples, from food safety to industrial waste, and also has the ability to identify pathogens.
b) Metagenomics provides information about the diversity of organisms in environmental samples and has provided insights in industrial research.
c) Functional metagenomics has been used for identification of several biocatalysts, which are available in the market. Novel cellulases with improved enzymatic characteristics have been identified.
d) The use of metagenomics, metatranscriptomics and metaproteomics approaches enhance enzyme discovery and can be used to efficiently screen for highly active enzymes.
e) Recent studies have stated that metagenomics can be used as a bioremediation tool; in comparison with other approaches of bioremediation, metagenomics gave better degrading ratios. Metagenomics study help in identifying different widespread microorganism and their respective functions in polluted environment; these microorganisms are the best tools in nature to degrade toxic pollutants.
f) Metagenomics has been used in clinical diagnostics
g) Viral metagenomics has the power to identify the root cause of novel epidemic diseases.
h) Metagenomics is also used in medical or forensic investigations, and to solve challenges in the field of medicine, agriculture and ecology.
i) Major applications of metaproteomics have included investigation of acid mine drainage biofilms, activated sludge, soil, human gut microbiota, and other environmental samples.
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