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Povzetek: Rapid and accurate identification of bacterial pathogens is crucial for effective treatment and infection control, particularly in hospital settings. Conventional methods like culture techniques and MALDI-TOF mass spectrometry are often time-consuming and less sensitive. This study addresses the need for faster and more precise diagnostic methods by developing novel digital PCR (dPCR) assays for the rapid quantification of biomarkers from three Gram-negative bacteria: Acinetobacter baumannii, Klebsiella pneumoniae, and Pseudomonas aeruginosa. Utilizing publicly available genomes and the rapid identification of PCR primers for unique core sequences or RUCS algorithm, we designed highly specific dPCR assays. These assays were validated using synthetic DNA, bacterial genomic DNA, and DNA extracted from clinical samples. The developed dPCR methods demonstrated wide linearity, a low limit of detection (approx. 30 copies per reaction), and robust analytical performance with measurement uncertainty below 25 %. The assays showed high repeatability and intermediate precision, with no cross-reactivity observed. Comparison with MALDI-TOF mass spectrometry revealed substantial concordance, highlighting the methods’ suitability for clinical diagnostics. This study underscores the potential of dPCR for rapid and precise quantification of Gram-negative bacterial biomarkers. The developed methods offer significant improvements over existing techniques, providing faster, more accurate, and SI-traceable measurements. These advancements could enhance clinical diagnostics and infection control practices.
Ključne besede: digital PCR (dPCR), Gram-negative bacteria, pathogen detection, respiratory infections, biomarkers, RUCS algorithm
Objavljeno v DiRROS: 05.11.2024; Ogledov: 133; Prenosov: 332
Celotno besedilo (2,31 MB)
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Ključne besede: damping-off / Root Rot, parsley, pathogen detection, common bean, phatoggenecity
Objavljeno v DiRROS: 23.10.2024; Ogledov: 289; Prenosov: 53
Celotno besedilo (225,51 KB)

Povzetek: High-throughput sequencing (HTS), more specifically RNA sequencing of plant tissues, has become an indispensable tool for plant virologists to detect and identify plant viruses. During the data analysis step, plant virologists typically compare the obtained sequences to reference virus databases. In this way, they are neglecting sequences without homologies to viruses, which usually represent the majority of sequencing reads. We hypothesized that traces of other pathogens might be detected in this unused sequence data. In the present study, our goal was to investigate whether total RNA-seq data, as generated for plant virus detection, is also suitable for the detection of other plant pathogens and pests. As proof of concept, we first analyzed RNA-seq datasets of plant materials with confirmed infections by cellular pathogens in order to check whether these non-viral pathogens could be easily detected in the data. Next, we set up a community effort to re-analyze existing Illumina RNA-seq datasets used for virus detection to check for the potential presence of non-viral pathogens or pests. In total, 101 datasets from 15 participants derived from 51 different plant species were re-analyzed, of which 37 were selected for subsequent in-depth analyses. In 29 of the 37 selected samples (78%), we found convincing traces of non-viral plant pathogens or pests. The organisms most frequently detected in this way were fungi (15/37 datasets), followed by insects (13/37) and mites (9/37). The presence of some of the detected pathogens was confirmed by independent (q)PCRs analyses. After communicating the results, 6 out of the 15 participants indicated that they were unaware of the possible presence of these pathogens in their sample(s). All participants indicated that they would broaden the scope of their bioinformatic analyses in future studies and thus check for the presence of non-viral pathogens. In conclusion, we show that it is possible to detect non-viral pathogens or pests from total RNA-seq datasets, in this case primarily fungi, insects, and mites. With this study, we hope to raise awareness among plant virologists that their data might be useful for fellow plant pathologists in other disciplines (mycology, entomology, bacteriology) as well.
Ključne besede: plant viruses, plant virus detection, plant virology, high-throughput sequencing, RNA sequencing, plant tissues, plant pathogen, diagnostics, high-throughput sequencing, metagenomics, metatranscriptomics
Objavljeno v DiRROS: 12.07.2024; Ogledov: 424; Prenosov: 177
Celotno besedilo (1,70 MB)