Project description:Application of next generation sequencing (NGS) for identification of prosthetic joint infection pathogens: a diagnostic evaluation study
Project description:Little is known about regulation of gene activity of the major pathogen Staphylococcus aureus during actual human infection. Here we characterize the transcriptome using deep RNA sequencing and the metabolome using NMR of S. aureus infected joint fluid derived from an acute human prosthetic joint infection, and compare them with the genome, transcriptome and metabolome of an isolate obtained from the sample grown in vitro (LB medium). The transcriptome indicated that the bacterial infection sustained on a versatile human-cell-based diet consisting of amino acids, glycans and nucleosides, since significant upregulation of genes involved in the catabolic degradation pathways of these compounds were observed in situ. This is consistent with metabolite analysis of the infected joint fluid and of S. aureus culture supernatants where the concentration of most amino acids and some amino sugars were found to be higher in the joint fluid, whereas the concentration of glucose was higher in culture supernatant. Furthermore, presumably because of oxygen limitations in the joint fluid, transcriptomic evidence for fermentation was observed, consistent with the presence of fermentation products (ethanol) in situ. Moreover, many, but not all, of the known virulence factor genes were upregulated in situ as well as the nine genes encoding the iron uptaking siderophore synthesis system.
Project description:BackgroundMetagenomic shotgun sequencing has the potential to change how many infections, particularly those caused by difficult-to-culture organisms, are diagnosed. Metagenomics was used to investigate prosthetic joint infections (PJIs), where pathogen detection can be challenging.MethodsFour hundred eight sonicate fluid samples generated from resected hip and knee arthroplasties were tested, including 213 from subjects with infections and 195 from subjects without infection. Samples were enriched for microbial DNA using the MolYsis basic kit, whole-genome amplified, and sequenced using Illumina HiSeq 2500 instruments. A pipeline was designed to screen out human reads and analyze remaining sequences for microbial content using the Livermore Metagenomics Analysis Toolkit and MetaPhlAn2 tools.ResultsWhen compared to sonicate fluid culture, metagenomics was able to identify known pathogens in 94.8% (109/115) of culture-positive PJIs, with additional potential pathogens detected in 9.6% (11/115). New potential pathogens were detected in 43.9% (43/98) of culture-negative PJIs, 21 of which had no other positive culture sources from which these microorganisms had been detected. Detection of microorganisms in samples from uninfected aseptic failure cases was conversely rare (7/195 [3.6%] cases). The presence of human and contaminant microbial DNA from reagents was a challenge, as previously reported.ConclusionsMetagenomic shotgun sequencing is a powerful tool to identify a wide range of PJI pathogens, including difficult-to-detect pathogens in culture-negative infections.
Project description:Typing and prediction of antibiotic resistance and virulence determinants in S. aureus using shotgun-metagenomics data from prosthetic joint tissue on blood culture bottles
Project description:Peri-prosthetic breast tissues were obtained from women with breast implants. Total RNA was extracted and cDNA library was prepared.