16S rRNA gene Next-Generation Sequencing (16SNGS) for bacterial pathogen identification: Pilot Study in a malaysian teaching hospital

Abstract

Background: Culture and biochemical testing (CBtest) have been routinely used for bacterial pathogen identification in many clinical microbiology laboratories. The process usually takes at least three days to obtain results. CBtest was found to be unideal for slow-growing or difficult-to-culture bacteria. With the advent of 16SNGS, infecting bacteria in clinical samples can be identified without culturing. In this pilot study, we evaluated and compared the usage of 16SNGS versus CBtest for bacterial pathogen identification in the clinical microbiology of our university teaching hospital. Methods and materials: Six bacteria samples identified as Escherichia coli, Staphylococcus aureus, Acinetobacter sp., Haemophilus influenzae, Burkholderia pseudomallei and Mycobacterium tuberculosis, respectively using CBtest were subjected to identification via 16SNGS targetting V3–V4 regions. B.E. Patho, a “plug-and-play” bioinformatics suite, was used for analysis of 16SNGS sequencing reads to identify bacteria samples. Turn-around time (TAT), cost and operator skills for both CBtest and 16SNGS workflows were determined. Results: Identification results for Acinetobacter sp., H. influenzae, B. pseudomallei, S. aureusand M. tuberculosis were similar at the genus level for both workflows. Interestingly, 16SNGS identified the E. coli sample as Klebsiella; this sample was later confirmed to be of mixed Enterobacteriaceae via further testing. S. aureus was accurately identified by both workflows at the species level. TAT for CBtest was 3 d for easy-to-culture bacteria such as E. coli and S. aureus, while it reached 60 d for M. tuberculosis. Of note, 16SNGS gave similar TAT of 5–6 d for all tested bacteria. CBtest incurred lower costs per identification (highest at 21.24 USD with API NH strip) compared to 416.74USD for 16SNGS. With the usage of the B.E. Patho bioinformatics suite, sequencing reads from 16SNGS were interpreted into bacteria identities with 6 touchscreen steps. Therefore, technicians trained in CBtest operated the 16SNGS workflow with no prior bioinformatics knowledge; nevertheless, training in DNA extraction, PCR and sequencing was a prerequisite for them. Conclusion: Alternative 16SNGS target regions or genes could be investigated, should identification of bacteria species be required for patient treatment. Notwithstanding its cost, 16SNGS could be a possible option for bacteria identification in clinical microbiology laboratories in the future.