Semantic Scholar Open Access 2022 52 sitasi

Engineering microbes for enhancing the degradation of environmental pollutants: A detailed review on synthetic biology.

P. R. Yaashikaa M. K. Devi P. Kumar

Abstrak

Anthropogenic activities resulted in the deposition of huge quantities of contaminants such as heavy metals, dyes, hydrocarbons, etc into an ecosystem. The serious ill effects caused by these pollutants to all living organisms forced in advancement of technology for degrading or removing these pollutants. This degrading activity is mostly depending on microorganisms owing to their ability to survive in harsh adverse conditions. Though native strains possess the capability to degrade these pollutants the development of genetic engineering and molecular biology resulted in engineering approaches that enhanced the efficiency of microbes in degrading pollutants at faster rate. Many bioinformatics tools have been developed for altering/modifying genetic content in microbes to increase their degrading potency. This review provides a detailed note on engineered microbes - their significant importance in degrading environmental contaminants and the approaches utilized for modifying microbes. The genes responsible for degrading the pollutants have been identified and modified fir increasing the potential for quick degradation. The methods for increasing the tolerance in engineered microbes have also been discussed. Thus engineered microbes prove to be effective alternate compared to native strains for degrading pollutants.

Topik & Kata Kunci

Penulis (3)

P

P. R. Yaashikaa

M

M. K. Devi

P

P. Kumar

Format Sitasi

Yaashikaa, P.R., Devi, M.K., Kumar, P. (2022). Engineering microbes for enhancing the degradation of environmental pollutants: A detailed review on synthetic biology.. https://doi.org/10.1016/j.envres.2022.113868

Akses Cepat

PDF tidak tersedia langsung

Cek di sumber asli →
Lihat di Sumber doi.org/10.1016/j.envres.2022.113868
Informasi Jurnal
Tahun Terbit
2022
Bahasa
en
Total Sitasi
52×
Sumber Database
Semantic Scholar
DOI
10.1016/j.envres.2022.113868
Akses
Open Access ✓