Title | Transportation protocols for accurate assessment of microbial burden classification using molecular methods. |
Publication Type | Journal Article |
Year of Publication | 2021 |
Authors | Kung A, Chen J, Tomasek M, Liu D, Rodgers W, Gau V |
Journal | Sci Rep |
Volume | 11 |
Issue | 1 |
Pagination | 16069 |
Date Published | 2021 08 09 |
ISSN | 2045-2322 |
Abstract | Point-of-care testing is cost-effective, rapid, and could assist in avoiding hospital visits during a pandemic. However, they present some significant risks that current technologies cannot fully address. Skin flora contamination and insufficient specimen volume are two major limitations preventing self-collection microbiological testing outside of hospital settings. We are developing a hybrid testing procedure to bridge the laboratory test with patient-side specimen collection and transportation for molecular microbial classification of causative bacterial infection and early identification of microbial susceptibility profiles directly from whole blood or urine specimens collected patient-side by health care workers such as phlebotomists in nursing homes or family clinics. This feasibility study presents our initial development efforts, in which we tested various transportation conditions (tubes, temperature, duration) for direct-from-specimen viable pathogen detection to determine the ideal conditions that allowed for differentiation between contaminant and causative bacteria in urine specimens and optimal growth for low-concentration blood specimens after transportation. For direct-from-urine assays, the viable pathogen at the clinical cutoff of 10 CFU/mL was detected after transportation with molecular assays while contaminants (≤ 10 CFU/mL) were not. For direct-from-blood assays, contrived blood samples as low as 0.8 CFU/mL were reported positive after transportation without the need for blood culture. |
DOI | 10.1038/s41598-021-95619-x |
Alternate Journal | Sci Rep |
PubMed ID | 34373552 |
PubMed Central ID | PMC8352943 |
Grant List | R01 AI117059 / AI / NIAID NIH HHS / United States R44 HD084033 / HD / NICHD NIH HHS / United States |
Related Faculty:
William Rodgers, M.D., Ph.D.