inner-banner-bg

Journal of Genetic Engineering and Biotechnology Research(JGEBR)

ISSN: 2690-912X | DOI: 10.33140/JGEBR

Impact Factor: 1.2

Characterization of Genetic Resources of Microorganism as Response of Climate Change

Abstract

Mostafa G. FadL

Identifying previously unknown genetic loci directing microbial adaptation holds great promise for using such discoveries to increase biomass yield Researchers are using genetic, genomic, and systems biology approaches to screen micro bialgenomes for genes and gene segments linked Such screens could reveal new insight into adaptation and nutrient use Metabolism. Novel pathways and master regulatory genes also may emerge from such investigations. Examples of screening techniques and associated approaches follow. Microbial communities can be analyzed using many techniques; microscopic, cultivation, immunological and nucleic-acid based molecular techniques. During the last years, nucleic-acid based molecular techniques have been used to identify and quantify microorganisms in the environment and technical applications. Most of these techniques are based on the extraction of DNA from cultures, bioreactors or environmental samples, followed by the amplification of extracted DNA using the Polymerase Chain Reaction, and finally analysis of the amplification products. In most of cases, the 16S ribosomal RNA gene of prokaryotic cells is analyzed for the PCR-based identification of bacteria. To address the biodiversity and to identify new species generating evident for Use Genetic Technology to Discover Genes Controlling Biomass with hypothesize that microbe that plays a biological role in adaptations to environmental factors. Where metabolic engineering has been defined as the direct improvement of product formation through the modification of specific biochemical reactions or the introduction of new ones, so it is implementation on microorganism and plant leading to drug discovery. Some critical steps enclose a well-organized and competent way and optimal metabolic engineering Moreover, the use genomics data for the activation of silent metabolic clusters can be incorporated.

PDF