Starkey, Jordan C.

ABSTRACT Nosocomial outbreaks impact patient safety and place an economic burden on healthcare facilities. Laboratory testing plays a crucial role in outbreak investigation and guides containment efforts. In recent years, whole genome sequencing (WGS) methods have replaced traditional typing methods due to higher resolution and simplified workflows. Though an improvement from previous methods, bacterial WGS is time-consuming with manual DNA extraction and library preparation and long sequencing times for paired-end sequence data. Here, a fully automated library preparation and sequencing solution, the Clear Dx TM WGS platform (Clear Labs, San Carlos, CA), was compared to a more manual library preparation and sequencing approach using 226 isolates representing 18 bacterial species. Sequence data were analyzed using SeqSphere+ (Ridom, Münster, Germany), and the results of the two methods were compared. Of the 224 isolate sequences analyzed, 222 (99%) showed concordant isolate groupings, and, overall, the results of the two approaches were statistically similar by comparison of distance matrices. The automated workflow reduced turnaround time by 16–19 h and eliminated 3 h of manual labor while decreasing costs by an estimated 34%–57% depending on the number of isolates run. This study demonstrates the advantages of integrating automation into bacterial WGS workflows. IMPORTANCE An automated platform for bacterial nucleic acid extraction and whole genome sequencing was compared to a manual method for bacterial strain typing. The two approaches yielded nearly equivalent results, with the automated approach providing improvement in turnaround time and cost, with less manual pipetting.

ABSTRACT The definition of the microbiology of pleural space infection has been challenging due to the poor yield of conventional culture. Here, the results of a 16S ribosomal RNA gene PCR/sequencing assay performed on pleural fluid in routine clinical practice between August 2020 and January 2023 were evaluated. Amplified 16S rRNA gene DNA was submitted to Sanger sequencing and/or next-generation sequencing or results were reported as negative, depending on PCR crossing threshold value. In all, 496 pleural fluids were tested at Mayo Clinic Laboratories, with 227 positive results, including 57 from Mayo Clinic patients. Among the 57 Mayo Clinic patients, pleural space infection was community acquired in 48 (84%); Fusobacterium nucleatum group and/or Streptococcus intermedius were detected in 31/57 (54%) cases [including 28/48 (58%) community-acquired cases], with additional facultative and/or anaerobic species also found in various combinations in 17/31 (55%). Results of this study suggest that the most frequent microorganism profile involved in community-acquired pleural space infection may be a combination of F. nucleatum group and/or S. intermedius , with or without other normal microbiota. IMPORTANCE We describe here the most frequent microorganisms detected in community-acquired pleural space infection using a clinically performed sequencing-based assay. We found that the most common detection was the Fusobacterium nucleatum group and/or Streptococcus intermedius , with or without other normal microbiota. We propose the term e-FuSion (effusion with Fusobacterium nucleatum group, Streptococcus intermedius , and other oral normal microbiota) for this entity.

The diagnosis of periprosthetic joint infection (PJI) is challenging, often requiring multiple clinical specimens and diagnostic techniques, some with prolonged result turnaround times. Here, the diagnostic performance of the Investigational Use Only (IUO) BioFire Joint Infection (JI) Panel was compared to 16S rRNA gene-based targeted metagenomic sequencing (tMGS) applied to synovial fluid for PJI diagnosis.