| Literature DB >> 35096070 |
Gessesse Kebede Bekele1, Solomon Abera Gebrie1, Eshetu Mekonen2, Tekle Tafese Fida1, Adugna Abdi Woldesemayat1, Ebrahim M Abda1, Mesfin Tafesse1, Fasil Assefa3.
Abstract
Hydrocarbon-derived pollutants are becoming one of the most concerning ecological issues. Thus, there is a need to investigate and develop innovative, low-cost, eco-friendly, and fast techniques to reduce and/or eliminate pollutants using biological agents. The study was conducted to isolate, characterize, and identify potential diesel-degrading bacteria. Samples were collected from flower farms, lakeshores, old aged garages, asphalt, and bitumen soils and spread on selective medium (Bushnell Haas mineral salt agar) containing diesel as the growth substrate. The isolates were characterized based on their growth patterns using optical density measurement, biochemical tests, and gravimetric analysis and identified using the Biolog database and 16S rRNA gene sequencing techniques. Subsequently, six diesel degraders were identified and belong to Pseudomonas, Providencia, Roseomonas, Stenotrophomonas, Achromobacter, and Bacillus. Among these, based on gravimetric analysis, the three potent isolates AAUW23, AAUG11, and AAUG36 achieved 84%, 83.4%, and 83% diesel degradation efficiency, respectively, in 15 days. Consequently, the partial 16S rRNA gene sequences revealed that the two most potent bacterial strains (AAUW23 and AAUG11) were Pseudomonas aeruginosa, while AAUG36 was Bacillus subtilis. This study demonstrated that bacterial species isolated from hydrocarbon-contaminated and/or uncontaminated environments could be optimized to be used as potential bioremediation agents for diesel removal.Entities:
Year: 2022 PMID: 35096070 PMCID: PMC8799363 DOI: 10.1155/2022/5655767
Source DB: PubMed Journal: Int J Microbiol
Morphological and physiological characteristics of diesel-degrading bacteria isolated from different sampling sites.
| Isolates code | BioLog ID | Site | Gram's | Shape | Catalase | Urase | Casein | Starch |
|---|---|---|---|---|---|---|---|---|
| AAUG8 |
| Flower | − | Bacilli | + | + | − | − |
| AAUG9 |
| Flower | − | Bacilli | + | − | + | − |
| AAUG10 |
| Flower | − | Coccobacilli | − | + | + | − |
| AAUG11 |
| Flower | − | Bacilli | + | − | + | - |
| AAUA12 |
| Garages | + | Bacilli | + | + | + | + |
| AAUA13 |
| Garages | + | Bacilli | + | + | + | + |
| AAUA14 |
| Garages | − | Bacilli | + | + | − | − |
| AAUA15 |
| Garages | − | Bacilli | + | + | − | − |
| AAUAs16 |
| Asphalt | − | Bacilli | + | − | − | − |
| AAUAs17 |
| Asphalt | − | Bacilli | + | − | − | − |
| AAUC18 |
| Soda lake | − | Bacilli | + | + | + | - |
| AAUC19 |
| Soda lake | − | Bacilli | + | − | + | − |
| AAUC20 |
| Soda lake | − | Bacilli | + | − | − | − |
| AAUC21 |
| Soda lake | − | Bacilli | + | − | + | − |
| AAUW22 |
| Bitumen | − | Bacilli | + | − | + | − |
| AAUW23 |
| Bitumen | − | Bacilli | + | − | + | − |
| AAUW24 |
| Bitumen | − | Bacilli | + | − | + | − |
| AAUW25 |
| Bitumen | − | Bacilli | + | − | + | − |
| AAUG36 |
| Flower | + | Bacilli | + | − | + | + |
Diversity and community structure of isolates from hydrocarbon-contaminated sites and nonpolluted natural sites (Chitu Soda lake).
| Genus of the isolates | Distribution (%) | Species of the isolates | Distribution (%) | Species distribution (%) | |
|---|---|---|---|---|---|
| Contaminated Sites | Noncontaminated Sites | ||||
|
| 47 |
| 42 | 31.5 | 10.5 |
|
| 5 | 0 | 5 | ||
|
| 16 |
| 11 | 11 | 0 |
|
| 5 | 5 | 0 | ||
|
| 11 |
| 11 | 11 | 0 |
|
| 5 |
| 5 | 5 | 0 |
|
| 16 |
| 16 | 11 | 5 |
|
| 5 |
| 5 | 5 | 0 |
Figure 1Growth capacity of isolates on diesel (1% concentration at different growth periods).
Figure 2Growth capacity of isolates on diesel (3% concentration at different growth periods).
Figure 3Gravimetric analysis for diesel degradation.
Phylogenetic affiliation of 16S rRNA partial sequences of three bacterial isolates.
| Isolate code | Accession number | Top-hit Taxon | GenBank accession | Identity (%) | Taxonomy |
|---|---|---|---|---|---|
| AAUG11 | MT669831 |
| MT646431.1 MT636685.1 MT598024.1 MT626658.1 MT598019.1 | 99.69%, 99.69%, 99.69% 99.69% 99.69% | Bacteria; Proteobacteria; Gammaproteobacteria; Pseudomonadales; Pseudomonadaceae; |
| AAUG36 | MT669830 |
| MT645308.1 MT704510.1 MT706001.1 MT733943.1 MT677937.1 | 99.43%, 99.43%, 99.43% 99.43% 99.43% | Bacteria; Firmicutes; Bacilli; Bacillales; Bacillaceae; |
| AAUW23 | MT669825 |
| MT598024.1 KM216848.1 MK875780.1 MT626658.1 MT633047.1 | 99.23% 99.34% 93.34%, 99.23% 99.23% | Bacteria; Proteobacteria; Gammaproteobacteria; Pseudomonadales; Pseudomonadaceae; |
Figure 4Phylogenetic tree based on partial bacterial sequences of the 16S rRNA region for the two Pseudomonas isolates and one Bacillus subtilis (bold and coded with the initials “AAU”) and accession numbers of the 16S rRNA are followed by species names. Numbers at nodes indicated bootstrap values for each node out of 1,000 bootstrap resembling. The phylogenetic tree was constructed in MEGA X using the maximum likelihood method [48] and Kimura-2 parameter model [32]. The Escherichia coli partial sequence was used as an out-group.