| Literature DB >> 29692866 |
Xinyue Zhao1, Li Wang1, Fang Ma1, Jixian Yang1.
Abstract
BACKGROUND: The isolation of atrazine-degrading microorganisms with specific characteristics is fundamental for bioaugmenting the treatment of wastewater containing atrazine. However, studies describing the specific features of such microorganisms are limited, and further investigation is needed to improve our understanding of bioaugmentation. RESULTS ANDEntities:
Keywords: Arthrobacter sp. ZXY-2; Bioaugmentation; Degradation rate; Influential factors
Year: 2018 PMID: 29692866 PMCID: PMC5905105 DOI: 10.1186/s13068-018-1113-0
Source DB: PubMed Journal: Biotechnol Biofuels ISSN: 1754-6834 Impact factor: 6.040
Fig. 1The scheme of growth kinetics with (a) time course of the growth of strain ZXY-2 and (b) fitting of the specific growth rate of Arthrobacter sp. ZXY-2 under different atrazine concentrations. (White square) Experimental data; (blue line) the model-fitting regression curve
Fig. 2The metabolic products and pathway by strain ZXY-2. A HPLC-MS identification of metabolites; B the proposed metabolic pathway of atrazine. The analytical data for the detected ions included A (a) m/z 198, A (b) m/z 171, and A (c) m/z 128. Compounds A (a), A (b), and A (c) were identified as hydroxyatrazine, N-isopropylammelide, and cyanuric acid, respectively
Fig. 3Plot of atrazine degradation by strain ZXY-2 and the evolution of its metabolites
Fig. 4Kinetic relationships between the expression of three genes and atrazine degradation. Relative transcript levels were measured by RT-qPCR, using the 16S rRNA gene as a housekeeping gene, and are shown for (a) trzN, (b) atzB, and (c) atzC. At each kinetic sampling point, a Fisher’s test was performed to compare the relative transcript levels in atrazine-treated and control samples (n = 3, p < 0.05)
Numbers of genes associated with general COG functional categories
| Code | Functional category | Value | Proportiona |
|---|---|---|---|
| A | RNA processing and modification | 1 | 0.04 |
| B | Chromatin structure and dynamics | 1 | 0.04 |
| C | Energy production and conversion | 200 | 7.16 |
| D | Cell cycle control, cell division, chromosome partitioning | 24 | 0.86 |
| E | Amino acid transport and metabolism | 313 | 11.21 |
| F | Nucleotide transport and metabolism | 87 | 3.11 |
| G | Carbohydrate transport and metabolism | 319 | 11.42 |
| H | Coenzyme transport and metabolism | 103 | 3.69 |
| I | Lipid transport and metabolism | 121 | 4.33 |
| J | Translation, ribosomal structure, and biogenesis | 153 | 5.48 |
| K | Transcription | 232 | 8.31 |
| L | Replication, recombination, and repair | 278 | 9.95 |
| M | Cell wall/membrane/envelope biogenesis | 111 | 3.97 |
| N | Cell motility | 18 | 0.64 |
| O | Posttranslational modification, protein turnover, chaperones | 101 | 3.62 |
| P | Inorganic ion transport and metabolism | 171 | 6.12 |
| Q | Secondary metabolites biosynthesis, transport, and catabolism | 86 | 3.08 |
| R | General function prediction only | 223 | 7.98 |
| S | Function unknown | 196 | 7.02 |
| T | Signal transduction mechanisms | 88 | 3.15 |
| U | Intracellular trafficking, secretion, and vesicular transport | 24 | 0.86 |
| V | Defense mechanisms | 43 | 1.54 |
aThe total is based on the total number of protein-coding genes in the annotated genome