Special Issue: Genetics of Biodegradation and Bioremediation

Biodegradation of isoproturon by Escherichia coli expressing a Pseudomonas putida catechol 1,2-dioxygenase gene

The phenylurea herbicides are persistent in soil and water, necessitating the creation of methods for removing them from the environment. This study aimed to examine the soil microbial diversity, searching for local bacterial isolates able to efficiently degrade the phenylurea herbicide isoproturon, 3-(4-isopropylphenyl)-1, 1-dimethylurea (IPU). The best isolates able to effectively degrade IPU were selected, characterized, and identified as Pseudomonas putida and Acinetobacter johnsonii. The catechol 1, 2-dioxygenase enzyme's catA gene was amplified, cloned, and expressed in E. coli M15. The Expressed E. coli showed high degradation efficiency (44.80%) as analyzed by HPLC after 15 days of inoculation in comparison to P. putida (21.60%). The expression of the catA gene in P. putida and expressed E. coli was measured using quantitative polymerase chain reaction (qPCR). The results displayed a significant increase in the mRNA levels of the catA gene by increasing the incubation time with IPU. Hydrophilic interaction chromatography (HILIC) mass spectrometry analysis revealed that three intermediate metabolites, 1-(4-isopropylphenyl)-3-methylurea (MDIPU), 4-Isopropylaniline (4-IA) and 1-(4-isopropylphenyl) urea (DDIPU) were generated by both P. putida and expressed E. coli. In addition, IPU-induced catA activity was detected in both P. putida and expressed E. coli. The supernatant of both P. putida and expressed E. coli had a significant influence on weed growth. The study clearly exhibited that P. putida and expressed E. coli were capable of metabolizing IPU influentially and thus could be utilized for bioremediation and biodegradation technology development.

Current and emerging tools of computational biology to improve the detoxification of mycotoxins

Biological organisms carry a rich potential for removing toxins from our environment, but identifying suitable candidates and improving them remain challenging. We explore the use of computational tools to discover strains and enzymes that detoxify harmful compounds. In particular, we will focus on mycotoxins-fungi-produced toxins that contaminate food and feed-and biological enzymes that are capable of rendering them less harmful. We discuss the use of established and novel computational tools to complement existing empirical data in three directions: discovering the prospect of detoxification among underexplored organisms, finding important cellular processes that contribute to detoxification, and improving the performance of detoxifying enzymes. We hope to create a synergistic conversation between researchers in computational biology and those in the bioremediation field. We showcase open bioremediation questions where computational researchers can contribute and highlight relevant existing and emerging computational tools that could benefit bioremediation researchers.