Title |
Identification of low abundance microbiome in clinical samples using whole genome sequencing
|
---|---|
Published in |
Genome Biology, November 2015
|
DOI | 10.1186/s13059-015-0821-z |
Pubmed ID | |
Authors |
Chao Zhang, Kyle Cleveland, Felice Schnoll-Sussman, Bridget McClure, Michelle Bigg, Prashant Thakkar, Nikolaus Schultz, Manish A. Shah, Doron Betel |
Abstract |
Identifying the microbiome composition from primary tissues directly affords an opportunity to study the causative relationships between the host microbiome and disease. However, this is challenging due the low abundance of microbial DNA relative to the host. We present a systematic evaluation of microbiome profiling directly from endoscopic biopsies by whole genome sequencing. We compared our methods with other approaches on datasets with previously identified microbial composition. We applied this approach to identify the microbiome from 27 stomach biopsies, and validated the presence of Helicobacter pylori by quantitative PCR. Finally, we profiled the microbial composition in The Cancer Genome Atlas gastric adenocarcinoma cohort. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 17 | 40% |
United Kingdom | 3 | 7% |
Germany | 3 | 7% |
Canada | 2 | 5% |
Poland | 1 | 2% |
Chile | 1 | 2% |
France | 1 | 2% |
Spain | 1 | 2% |
Switzerland | 1 | 2% |
Other | 1 | 2% |
Unknown | 12 | 28% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 26 | 60% |
Members of the public | 16 | 37% |
Science communicators (journalists, bloggers, editors) | 1 | 2% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 4 | 2% |
Germany | 2 | <1% |
Czechia | 1 | <1% |
United Kingdom | 1 | <1% |
Ireland | 1 | <1% |
Thailand | 1 | <1% |
Estonia | 1 | <1% |
Japan | 1 | <1% |
Spain | 1 | <1% |
Other | 0 | 0% |
Unknown | 190 | 94% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 42 | 21% |
Researcher | 42 | 21% |
Student > Master | 23 | 11% |
Student > Bachelor | 22 | 11% |
Other | 12 | 6% |
Other | 32 | 16% |
Unknown | 30 | 15% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 56 | 28% |
Agricultural and Biological Sciences | 50 | 25% |
Medicine and Dentistry | 15 | 7% |
Immunology and Microbiology | 12 | 6% |
Computer Science | 9 | 4% |
Other | 23 | 11% |
Unknown | 38 | 19% |