| Title |
Survey of sulfur-oxidizing bacterial community in the Pearl River water using soxB, sqr, and dsrA as molecular biomarkers
|
|---|---|
| Published in |
3 Biotech, January 2018
|
| DOI | 10.1007/s13205-017-1077-y |
| Pubmed ID | |
| Authors |
Jianfei Luo, Xiaoqin Tan, Kexin Liu, Weitie Lin |
| Abstract |
In this study, we surveyed the abundance and diversity of three sulfur oxidation genes (sqr, soxB, and dsrA) using quantitative assays and Miseq high-throughput sequencing. The quantitative assays revealed that soxB is more abundant than sqr and dsrA and is the main contributor to sulfur oxidation. In the diversity analysis, the SOB community mainly comprised the classes Nitrospira, Alphaproteobacteria, Betaproteobacteria, and Gammaproteobacteria. The genera Gallionella, Hydrogenophaga, Limnohabitans, Methylomonas, Nitrospira, Rhodoferax, and Sulfuritalea were abundant in the communities for sqr; Dechloromonas, Limnohabitans, Paracoccus, Sulfuritalea, Sulfitobacter, and Thiobacillus were abundant in communities for soxB; Sulfuritalea, Sulfurisoma, and Thiobacillus were abundant in communities for dsrA. This study presented a high diversity of SOB species and functional sulfur-oxidizing genes in Pearl River via high-throughput sequencing, suggesting that the aquatic ecosystem has great potential to scavenge the sulfur pollutants by itself. |
Mendeley readers
The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 37 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 6 | 16% |
| Student > Ph. D. Student | 5 | 14% |
| Student > Master | 5 | 14% |
| Student > Doctoral Student | 2 | 5% |
| Student > Postgraduate | 2 | 5% |
| Other | 5 | 14% |
| Unknown | 12 | 32% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 8 | 22% |
| Environmental Science | 4 | 11% |
| Biochemistry, Genetics and Molecular Biology | 3 | 8% |
| Engineering | 2 | 5% |
| Social Sciences | 1 | 3% |
| Other | 3 | 8% |
| Unknown | 16 | 43% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 18 January 2018.
All research outputs
#5,808,024
of 23,016,919 outputs
Outputs from 3 Biotech
#122
of 1,248 outputs
Outputs of similar age
#116,114
of 442,996 outputs
Outputs of similar age from 3 Biotech
#5
of 71 outputs
Altmetric has tracked 23,016,919 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 1,248 research outputs from this source. They receive a mean Attention Score of 2.9. This one has done well, scoring higher than 89% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 442,996 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.
We're also able to compare this research output to 71 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 90% of its contemporaries.