| Title |
Genetic Characteristics of Coronaviruses from Korean Bats in 2016
|
|---|---|
| Published in |
Microbial Ecology, July 2017
|
| DOI | 10.1007/s00248-017-1033-8 |
| Pubmed ID | |
| Authors |
Saemi Lee, Seong-Deok Jo, Kidong Son, Injung An, Jipseol Jeong, Seung-Jun Wang, Yongkwan Kim, Weonhwa Jheong, Jae-Ku Oem |
| Abstract |
Bats have increasingly been recognized as the natural reservoir of severe acute respiratory syndrome (SARS), coronavirus, and other coronaviruses found in mammals. However, little research has been conducted on bat coronaviruses in South Korea. In this study, bat samples (332 oral swabs, 245 fecal samples, 38 urine samples, and 57 bat carcasses) were collected at 33 natural bat habitat sites in South Korea. RT-PCR and sequencing were performed for specific coronavirus genes to identify the bat coronaviruses in different bat samples. Coronaviruses were detected in 2.7% (18/672) of the samples: 13 oral swabs from one species of the family Rhinolophidae, and four fecal samples and one carcass (intestine) from three species of the family Vespertiliodae. To determine the genetic relationships of the 18 sequences obtained in this study and previously known coronaviruses, the nucleotide sequences of a 392-nt region of the RNA-dependent RNA polymerase (RdRp) gene were analyzed phylogenetically. Thirteen sequences belonging to SARS-like betacoronaviruses showed the highest nucleotide identity (97.1-99.7%) with Bat-CoV-JTMC15 reported in China. The other five sequences were most similar to MERS-like betacoronaviruses. Four nucleotide sequences displayed the highest identity (94.1-95.1%) with Bat-CoV-HKU5 from Hong Kong. The one sequence from a carcass showed the highest nucleotide identity (99%) with Bat-CoV-SC2013 from China. These results suggest that careful surveillance of coronaviruses from bats should be continued, because animal and human infections may result from the genetic variants present in bat coronavirus reservoirs. |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Australia | 1 | 25% |
| Unknown | 3 | 75% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 54 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 54 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 10 | 19% |
| Student > Ph. D. Student | 10 | 19% |
| Student > Bachelor | 7 | 13% |
| Student > Master | 7 | 13% |
| Other | 3 | 6% |
| Other | 6 | 11% |
| Unknown | 11 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 10 | 19% |
| Agricultural and Biological Sciences | 7 | 13% |
| Veterinary Science and Veterinary Medicine | 5 | 9% |
| Nursing and Health Professions | 3 | 6% |
| Medicine and Dentistry | 2 | 4% |
| Other | 8 | 15% |
| Unknown | 19 | 35% |
Attention Score in Context
This research output has an Altmetric Attention Score of 12. 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 09 February 2024.
All research outputs
#2,735,263
of 23,956,119 outputs
Outputs from Microbial Ecology
#172
of 2,115 outputs
Outputs of similar age
#50,891
of 317,553 outputs
Outputs of similar age from Microbial Ecology
#3
of 51 outputs
Altmetric has tracked 23,956,119 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,115 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done particularly well, scoring higher than 91% 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 317,553 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 83% of its contemporaries.
We're also able to compare this research output to 51 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 96% of its contemporaries.