A comprehensive study of conditions of the biodegradation of a plastic additive 2,6-di- tert -butylphenol and proteomic changes in the degrader Pseudomonas aeruginosa san ai.
Ana B MedićKsenija StojanovićLidija Izrael-ŽivkovićVladimir BeškoskiBranka LončarevićSaša KazazićIvanka M KaradžićPublished in: RSC advances (2019)
The Pseudomonas aeruginosa san ai strain was investigated for its capability to degrade the 2,6-di- tert -butylphenol (2,6-DTBP) plastic additive, a hazardous and toxic substance for aquatic life. This investigation was performed under different parameter values: 2,6-DTBP concentration, inoculum size, pH, and temperature. The GC-MS study showed that P. aeruginosa efficiently degraded 2,6-DTBP in the pH range of 5-8 at higher temperatures. Under exposure to 2,6-DTBP concentrations of 2, 10, and 100 mg L -1 , the strain degraded by 100, 100, and 85%, respectively, for 7 days. Crude enzyme preparation from the biomass of P. aeruginosa san ai showed higher efficiency in 2,6-DTBP removal than that shown by whole microbial cells. Gene encoding for the enzymes involved in the degradation of aromatic compounds in P. aeruginosa san ai was identified. To complement the genomic data, a comparative proteomic study of P. aeruginosa san ai grown on 2,6-DTBP or sunflower oil was conducted by means of nanoLC-MS/MS. The presence of aromatic substances resulted in the upregulation of aromatic ring cleavage enzymes, whose activity was confirmed by enzymatic tests; therefore, it could be concluded that 2,6-DTBP might be degraded by ortho -ring cleavage. A comparative proteomics study of P. aeruginosa san ai indicated that the core molecular responses to aromatic substances can be summarized as the upregulation of proteins responsible for amino acid metabolism with emphasized glutamate metabolism and energy production with upregulated enzymes of glyoxylate bypass. P. aeruginosa san ai has a high capacity to efficiently degrade aromatic compounds, and therefore its whole cells or enzymes could be used in the treatment of contaminated areas.
Keyphrases
- artificial intelligence
- amino acid
- pseudomonas aeruginosa
- induced apoptosis
- cystic fibrosis
- escherichia coli
- risk assessment
- big data
- cell proliferation
- nitric oxide
- biofilm formation
- poor prognosis
- endoplasmic reticulum stress
- fatty acid
- wastewater treatment
- long non coding rna
- label free
- combination therapy
- high performance liquid chromatography