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Development of droplet digital PCR-based detection of bacterial pathogens in prosthetic joint infection: a preliminary study using a synthesized model plasmid.

ABSTRACT: Periprosthetic joint infection (PJI) can be diagnosed to characterize the microorganisms constituting a biofilm, which is an essential procedure for proper treatment. The gold standard method for detecting and identifying the causative microorganism is culture of microorganisms from patients-derived sample.; however, this method takes a long time and has low sensitivity. To compensate for these limitations, identification methods based on real-time PCR (RT-PCR) have been widely used. However, RT-PCR also has limitations, including low sensitivity and the requirement of a standard curve for quantification. Therefore, to prevent significant proliferation of pathogenic bacteria, it is important to detect a limited number of infectious bacteria during early stages of PJI. In the present study, we developed droplet digital PCR-based detection of bacterial pathogens in PJI. And we evaluated the analytical performance of the assay using a model plasmid, based on the 16S ribosomal DNA sequence of target bacteria commonly found in PJI. We also prepared genomic DNA extracted from E. coli, S. aureus, and S. epidermidis to test whether ddPCR provides better sensitivity and quantification of the target sequences. ddPCR detected 400 attograms of target DNA, which was more than 10 times less than that detected by real-time PCR using synthesized plasmid. In addition, ddPCR detected target regions from genomic DNA of 50 femtograms for E. coli, 70 femtograms for S. epidermidis, and 90 femtograms for S. aureus. The results indicate that ddPCR has the potential to decrease the microbial detection limit and provide precise detection, signifying its effectiveness for early PJI.

SUBMITTER: Tak LJ

PROVIDER: S-EPMC10651726 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

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Development of droplet digital PCR-based detection of bacterial pathogens in prosthetic joint infection: a preliminary study using a synthesized model plasmid.

Tak Lee-Jung LJ Shin Min-Kyoung MK Yoo Jun-Il JI Cho Min-Chul MC Kim Wanil W

Frontiers in cellular and infection microbiology 20231102

Periprosthetic joint infection (PJI) can be diagnosed to characterize the microorganisms constituting a biofilm, which is an essential procedure for proper treatment. The gold standard method for detecting and identifying the causative microorganism is culture of microorganisms from patients-derived sample.; however, this method takes a long time and has low sensitivity. To compensate for these limitations, identification methods based on real-time PCR (RT-PCR) have been widely used. However, RT ...[more]

PMID: 38029245

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Project description:Bacteria can be considered as biological nanofactories that manufacture a cornucopia of bioproducts most notably recombinant proteins. As such, they must perfectly match with appropriate plasmid vectors to ensure successful overexpression of target genes. Among many parameters that correlate positively with protein productivity plasmid copy number plays pivotal role. Therefore, development of new and more accurate methods to assess this critical parameter will result in optimization of expression of plasmid-encoded genes. In this study, we present a simple and highly accurate method for quantifying plasmid copy number utilizing an EvaGreen single colour, droplet digital PCR. We demonstrate the effectiveness of this method by examining the copy number of the pBR322 vector within Escherichia coli DH5α cells. The obtained results were successfully validated by real-time PCR. However, we observed a strong dependency of the plasmid copy number on the method chosen for isolation of the total DNA. We found that application of silica-membrane-based columns for DNA purification or DNA isolation with use of bead-beating, a mechanical cell disruption lead to determination of an average of 20.5 or 7.3 plasmid copies per chromosome, respectively. We found that recovery of the chromosomal DNA from purification columns was less efficient than plasmid DNA (46.5 ± 1.9% and 87.4 ± 5.5%, respectively) which may lead to observed differences in plasmid copy number. Besides, the plasmid copy number variations dependent on DNA template isolation method, we found that droplet digital PCR is a very convenient method for measuring bacterial plasmid content. Careful determination of plasmid copy number is essential for better understanding and optimization of recombinant proteins production process. Droplet digital PCR is a very precise method that allows performing thousands of individual PCR reactions in a single tube. The ddPCR does not depend on running standard curves and is a straightforward and reliable method to quantify the plasmid copy number. Therefore we believe that the ddPCR designed in this study will be widely used for any plasmid copy number calculation in the future.

Project description:ObjectiveBacterial DNA (bactDNA) detection can be used to quickly identify pathogenic bacteria and has been studied on ascitic fluid. We aimed to retrospectively analyze the diagnostic value and applicational prospect of the bactDNA load in spontaneous bacterial peritonitis (SBP).MethodWe extracted viable bactDNA from ascitic samples of 250 patients with decompensated cirrhosis collected from October 2019 to April 2021 and detected the bactDNA by droplet digital polymerase chain reaction (ddPCR). We used ascitic samples of a baseline cohort of 191 patients to establish diagnostic thresholds for SBP and analyze the patients' diagnostic performance based on ascites polymorphonuclear (PMN) and clinical manifestation. We performed bactDNA quantification analysis on 13 patients with a PMN less than 250 cells/mm3 but with clinical symptoms. The dynamic changes of the bactDNA load from eight patients (before, during, and after SBP) were analyzed.ResultsAfter the removal of free DNA, the bactDNA detected by ddPCR was generally decreased (1.75 vs. 1.5 log copies/µl, P < 0.001). Compared with the traditional culture and PMN count in the SBP diagnosis, the bactDNA showed that the ddPCR sensitivity was 80.5%, specificity was 95.3%, positive predictive value was 82.5%, and negative predictive value was 94.7%, based on clinical composite criteria. In patients with a PMN less than 250 cells/mm3, the bactDNA load of 13 patients with symptoms was significantly higher than those without symptoms (2.7 vs. 1.7 log copies/µl, P < 0.001). The bactDNA in eight patients had SBP that decreased by 1.6 log copies/µl after 48 h of antibiotic treatment and by 1.0 log copies/µl after 3 days of continued treatment.ConclusionBactDNA detection can be used to further enhance the diagnostic efficiency of SBP. Therefore, the application of ddPCR assay not only can be used to discriminate and quantify bacteria but also can be used in the clinical assessment for antibiotics treatment.

Dataset Information

Development of droplet digital PCR-based detection of bacterial pathogens in prosthetic joint infection: a preliminary study using a synthesized model plasmid.

Publications

Development of droplet digital PCR-based detection of bacterial pathogens in prosthetic joint infection: a preliminary study using a synthesized model plasmid.

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