Metagenomic is a promising technique that has many applications in different fields. In fact, metagenomics is the ideal culture-independent technique that unravels the microbial composition and biodiversity in the sample, which helps scientists to study and understand how this biodiversity is affected by continuously changing conditions in the environment and how this microbial community interacts with each other. In the past, the microbial composition in extreme environments was undiscovered due to the difficulty of isolation, culturing, and identification of microbes living there. However, nowadays after the development and combination of metagenomic and next-generation sequencing techniques, it became more easy to study the microbial composition in extreme environments without culturing. In this chapter, the use of metagenomic techniques to study the microbial biodiversity in different extreme environments are discussed. In addition, different NGS platforms are discussed in terms of principles, advantages, and limitations.

Since 1940s, microbial secondary metabolites (SMs) have attracted the attention of the scientific community. As a result, intensive researches have been conducted in order to discover and identify novel microbial secondary metabolites. Since, the discovery of novel secondary metabolites has been decreasing significantly due to many factors such as 1) unculturable microbes 2) traditional detection techniques 3) not all SMs expressed in the lab. As a result, searching for new techniques which can overcome the previous challenges was one of the most priority objectives. Therefore, the development of omics-based techniques such as genomics and metabolomic have revealed the potential of discovering novel SMs which were coded in the microorganisms’ DNA but not expressed in the lab or might be produced in undetectable amount by detecting the biosynthesis gene clusters (BGCs) that are associated with the biosynthesis of secondary metabolites. Nowadays, the integration of metabolomics and gene editing techniques such as CRISPR-Cas9 provide a successful platform for the detection and identification of known and unknown secondary metabolites also to increase secondary metabolites production.