Detection of bacterial pathogens from clinical specimens using conventional microbial culture and 16S metagenomics: a comparative study

Lalanika M. Abayasekara, Jennifer Perera, Vishvanath Chandrasekharan, Vaz S. Gnanam, Nisala A. Udunuwara, Dileepa S. Liyanage, Nuwani E. Bulathsinhala, Subhashanie Adikary, Janith V. S. Aluthmuhandiram, Chrishanthi S. Thanaseelan, D. Portia Tharmakulasingam, Tharaga Karunakaran, Janahan Ilango

Infectious disease is the leading cause of death worldwide, and diagnosis of polymicrobial and fungal infections is increasingly challenging in the clinical setting. Conventionally, molecular detection is still the best method of species identification in clinical samples. However, the limitations of Sanger sequencing make diagnosis of polymicrobial infections one of the biggest hurdles in treatment. The development of massively parallel sequencing or next generation sequencing (NGS) has revolutionized the field of metagenomics, with wide application of the technology in identification of microbial communities in environmental sources, human gut and others. However, to date there has been no commercial application of this technology in infectious disease diagnostic settings. Credence Genomics Rapid Infection Detection™ test, is a molecular based diagnostic test that uses next generation sequencing of bacterial 16S rRNA gene and fungal ITS1 gene region to provide accurate identification of species within a clinical sample. Here we present a study comparing 16S and ITS1 metagenomic identification against conventional culture for clinical samples. Using culture results as gold standard, a comparison was conducted using patient specimens from a clinical microbiology lab. Metagenomics based results show a 91.8% concordance rate for culture positive specimens and 52.8% concordance rate with culture negative samples. 10.3% of specimens were also positive for fungal species which was not investigated by culture. Specificity and sensitivity for metagenomics analysis is 91.8 and 52.7% respectively. 16S based metagenomic identification of bacterial species within a clinical specimen is on par with conventional culture based techniques and when coupled with clinical information can lead to an accurate diagnostic tool for infectious disease diagnosis.