Rutgers researchers have developed an analytical tool for spotting and omitting stray DNA and RNA that contaminate genetic analyses of single-celled organisms.
Their work, which appears in Nature Computational Science, also may help laboratories avoid mismatching sequenced gene fragments from different organisms in the same sample.
The free software, dubbed Single-cell Analysis of Host-Microbiome Interactions, or SAHMI, can improve the accuracy of medical research—particularly research into the microbiome’s effect on health—and may eventually drive clinical care that hinges upon genetic analyses of tissue samples.
“Sample contamination happens frequently because extraneous genetic material is everywhere: flecking off patient fingers, floating through the air, lurking inside the laboratory’s reagents,” said Bassel Ghaddar, a dual doctoral degree candidate at Rutgers Robert Wood Johnson Medical School and lead author of the study.
“There’s also a challenge arising from the algorithms we use to understand where sequenced gene segments come from,” Ghaddar added. “They need to figure out whether a bit of DNA or RNA belongs to the patient or a bacterium in the microbiome or an invading virus or something else. And these algorithms can make a lot of mistakes.”
2023-10-09 11:00:04
Post from phys.org