Bacterial pathogen identification in the diagnostic microbiology laboratory via standard method and 16S RRNA next-generation sequencing: A pilot study

Abstract

Culture and biochemical testing of infectious biospecimens (CBtest) is the standard for bacterial pathogen identification. However, CBtest is not ideal for identification of slow-growing or uncultivable, or poly-bacterial biospecimens. While the 16S rRNA next-generation sequencing (16SNGS) workflow has been used for pathogen identification, high sequencing cost and operator bioinformatics skill requirement are implementation barriers. In this study, turn-around time (TAT), diagnostic cost, and bioinformatics skill requirement for bacterial identification via CBtest and 16SNGS, together with the best workflow for identification of (i) easily-cultivable and (ii) slow growing pathogens were determined. A plug-and-play “sequence-to-pathogen-identity” bioinformatics suite, B.E. Patho, was used in 16SNGS workflow. In the first phase of study, six known bacteria were subjected to workflows of this study. TAT, diagnostic cost, bioinformatics skill requirement for pathogen identification were recorded. A score system was established to determine the best workflow for pathogen identification. In the second phase of the study, bacterial samples from 24 diagnostic samples (eight each from pus, sputum and urine specimens) together with their CBtest and 16SNGS identification workflows, were identified and scored according to the methodology of the first phase. Results from the first phase showed that both CBtest and 16SNGS provided similar identification of bacteria genera for all samples, except for Escherichia coli in which 16SNGS identified it as a mixture of Enterobacteriaceae and Klebsiella spp. In the second phase of the study, 16SNGS provided genera identification of bacterial communities in tested specimens compared to generic classification provided by CBtest; 16SNGS also provided identification that flagged as “no growth” via CBtest. 16SNGS TAT for slow-growing pathogen was shorter compared to CBtest; nonetheless, the cost of pathogen identification via 16SNGS was approximately 100 times higher compared to CBtest, making the CBtest a better workflow for identification of easily-cultivable bacteria, while 16SNGS a better workflow for identification of slow-growing pathogens. Interestingly, the B.E. Patho bioinformatics suite allowed pathogen identification to be carried out without bioinformatics skill. In summary, both workflows allowed bacterial identification in pure culture and diagnostic specimens. Reduction of sequencing costs and adoption of “sequence-to-pathogen-identity” bioinformatics suite may facilitate the adoption of 16SNGS in diagnostic microbiology.