Bronchoalveolar lavage (BAL) culture is a standard, though time-consuming, approach for identifying microorganisms in patients with severe lower respiratory tract (LRT) infections. The sensitivity of BAL culture is relatively low, and prior antimicrobial therapy decreases the sensitivity further, leading to overuse of empirical antibiotics. The Unyvero LRT BAL Application (Curetis GmbH, Germany) is a multiplex molecular panel that detects 19 bacteria, 10 antibiotic resistance markers, and a fungus, Pneumocystis jirovecii, in BAL fluid in ∼4.5 h. Its performance was evaluated using 1,016 prospectively collected and 392 archived specimens from 11 clinical trial sites in the United States. Overall positive and negative percent agreements with culture results for identification of bacteria that grow in routine cultures were 93.4% and 98.3%, respectively, with additional potential pathogens identified by Unyvero in 21.7% of prospectively collected specimens. For detection of P. jirovecii, the positive percent agreement with standard testing was 87.5%. Antibiotic resistance marker results were compared to standard antibiotic susceptibility test results to determine positive predictive values (PPVs). PPVs ranged from 80 to 100%, based on the microorganism and specific resistance marker(s). The Unyvero LRT BAL Application provides accurate detection of common agents of bacterial pneumonia and of P. jirovecii The sensitivity and rapidity of this panel suggest significant clinical value for choosing appropriate antibiotics and for antibiotic stewardship.

Whole-genome sequencing (WGS) is now routinely performed in clinical microbiology laboratories to assess isolate relatedness. With appropriately developed analytics, the same data can be used for prediction of antimicrobial susceptibility. We assessed WGS data for identification using open-source tools and antibiotic susceptibility testing (AST) prediction using ARESdb compared to matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) identification and broth microdilution phenotypic susceptibility testing on clinical isolates from a multicenter clinical trial of the FDA-cleared Unyvero lower respiratory tract infection (LRTI) application (Curetis). For the trial, more than 2,000 patient samples were collected from intensive care units across nine hospitals and tested for LRTI. The isolate subset used in this study included 620 clinical isolates originating from 455 LRTI culture-positive patient samples. Isolates were sequenced using the Illumina Nextera XT protocol and FASTQ files with raw reads uploaded to the ARESdb cloud platform (ares-genetics.cloud; released for research use in 2020). The platform combines Ares Genetics' proprietary database ARESdb with state-of-the-art bioinformatics tools and curated public data. For identification, WGS showed 99 and 93% concordance with MALDI-TOF MS at the genus and species levels, respectively. WGS-predicted susceptibility showed 89% categorical agreement with phenotypic susceptibility across a total of 129 species-compound pairs analyzed, with categorical agreement exceeding 90% in 78 species-compound pairs and reaching 100% in 32. Results of this study add to the growing body of literature showing that, with improvement of analytics, WGS data could be used to predict antimicrobial susceptibility.

The emergence and spread of antimicrobial resistance is one of the major global issues currently threatening the health and wealth of nations, with effective guidelines and intervention strategies urgently required. Such guidelines and interventions should ideally be targeted at individuals, communities, and nations, requiring international coordination for maximum effect. In this respect, the European Joint Programming Initiative on Antimicrobial Resistance Transnational Working Group ‘Antimicrobial Resistance - Rapid Diagnostic Tests’ (JPIAMR AMR-RDT) is proposing to consider a ‘mix-and-match’ package for the implementation of point-of-care testing (PoCT), which is described in this publication. The working group was established with the remit of identifying barriers and solutions to the development and implementation of rapid infectious disease PoCT for combatting the global spread of antimicrobial resistance. It constitutes a multi-sectoral collaboration between medical, technological, and industrial opinion leaders involved in in vitro diagnostics development, medical microbiology, and clinical infectious diseases. The mix-and-match implementation package is designed to encourage the implementation of rapid infectious disease and antimicrobial resistance PoCT in transnational medical environments for use in the fight against increasing antimicrobial resistance.

Antimicrobial susceptibility testing (AST) technologies help to accelerate the initiation of targeted antimicrobial therapy for patients with infections and could potentially extend the lifespan of current narrow-spectrum antimicrobials. Although conceptually new and rapid AST technologies have been described, including new phenotyping methods, digital imaging and genomic approaches, there is no single major, or broadly accepted, technological breakthrough that leads the field of rapid AST platform development. This might be owing to several barriers that prevent the timely development and implementation of novel and rapid AST platforms in health-care settings. In this Consensus Statement, we explore such barriers, which include the utility of new methods, the complex process of validating new technology against reference methods beyond the proof-of-concept phase, the legal and regulatory landscapes, costs, the uptake of new tools, reagent stability, optimization of target product profiles, difficulties conducting clinical trials and issues relating to quality and quality control, and present possible solutions.

Purpose Bloodstream infections remain an important cause of morbidity and mortality. Rapid diagnosis can reduce the time from empiric antimicrobial therapy to targeted therapy and improve patient outcomes.Methodology The fully automated Unyvero Blood Culture (BCU) Application (Curetis GmbH) can identify a broad panel of pathogens (36 analytes covering over 50 pathogens) and 16 antibiotic resistance gene markers simultaneously in about 5 h. The assay was evaluated in three clinical laboratories in comparison to routine microbiological procedures.Results A total of 207 blood cultures were included in the study, and 90.5 % of the species identified by culture were covered by the Unyvero BCU panel with an overall sensitivity of 96.8 % and specificity of 99.8 %. The time to result was reduced on average by about 34 h. The assay accurately identified 95 % of the species, including 158/164 monomicrobial and 7/9 polymicrobial cultures. The Unyvero BCU Cartridge detected a large number of resistance markers including mecA (n=57), aac(6′)aph(2′′) (n=40), one vanB resistance gene, and six instances of blaCTX-M.Conclusion The Unyvero BCU Application provided fast, reliable results, while significantly improving turnaround time in blood culture diagnostics.

High-throughput next-generation shotgun sequencing of pathogenic bacteria is growing in clinical relevance, especially for chromosomal DNA-based taxonomic identification and for antibiotic resistance prediction. Genetic exchange is facilitated for extrachromosomal DNA, e.g. plasmid-borne antibiotic resistance genes. Consequently, accurate identification of plasmids from whole-genome sequencing (WGS) data remains one of the major challenges for sequencing-based precision medicine in infectious diseases. Here, we assess the heterogeneity of four state-of-the-art tools (cBar, PlasmidFinder, plasmidSPAdes and Recycler) for the in silico prediction of plasmid-derived sequences from WGS data. Heterogeneity, sensitivity and precision were evaluated by reference-independent and reference-dependent benchmarking using 846 Gram-negative clinical isolates. Interestingly, the majority of predicted sequences were tool-specific, resulting in a pronounced heterogeneity across tools for the reference-independent assessment. In the reference-dependent assessment, sensitivity and precision values were found to substantially vary between tools and across taxa, with cBar exhibiting the highest median sensitivity (87.45%) but a low median precision (27.05%). Furthermore, integrating the individual tools into an ensemble approach showed increased sensitivity (95.55%) while reducing the precision (25.62%). CBar and plasmidSPAdes exhibited the strongest concordance with respect to identified antibiotic resistance factors. Moreover, false-positive plasmid predictions typically contained only few antibiotic resistance factors. In conclusion, while high degrees of heterogeneity and variation in sensitivity and precision were observed across the different tools and taxa, existing tools are valuable for investigating the plasmid-borne resistome. Nevertheless, additional studies on representative clinical data sets will be necessary to translate in silico plasmid prediction approaches from research to clinical application.

Whole-genome sequencing (WGS) is gaining importance in the analysis of bacterial cultures derived from patients with infectious diseases. Existing computational tools for WGS-based identification have, however, been evaluated on previously defined data relying thereby unwarily on the available taxonomic information.Here, we newly sequenced 846 clinical gram-negative bacterial isolates representing multiple distinct genera and compared the performance of five tools (CLARK, Kaiju, Kraken, DIAMOND/MEGAN and TUIT). To establish a faithful 'gold standard', the expert-driven taxonomy was compared with identifications based on matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) analysis. Additionally, the tools were also evaluated using a data set of 200 Staphylococcus aureus isolates.CLARK and Kraken (with k =31) performed best with 626 (100%) and 193 (99.5%) correct species classifications for the gram-negative and S. aureus isolates, respectively. Moreover, CLARK and Kraken demonstrated highest mean F-measure values (85.5/87.9% and 94.4/94.7% for the two data sets, respectively) in comparison with DIAMOND/MEGAN (71 and 85.3%), Kaiju (41.8 and 18.9%) and TUIT (34.5 and 86.5%). Finally, CLARK, Kaiju and Kraken outperformed the other tools by a factor of 30 to 170 fold in terms of runtime.We conclude that the application of nucleotide-based tools using k-mers-e.g. CLARK or Kraken-allows for accurate and fast taxonomic characterization of bacterial isolates from WGS data. Hence, our results suggest WGS-based genotyping to be a promising alternative to the MS-based biotyping in clinical settings. Moreover, we suggest that complementary information should be used for the evaluation of taxonomic classification tools, as public databases may suffer from suboptimal annotations.

The volumes of Waste Electrical and Electronic Equipment (WEEE) generated in some African countries can be compared to those of some Eastern European countries, but many of them do not have any WEEE legislation and/or collection and treatment system in place besides voluntary initiatives and the informal sector. The volumes of EEE placed on the market are expected to grow by >7% in the coming years, with a focus on ICT and photovoltaics. The paper takes a look at the existing and planned legislation on WEEE in the African countries, showing the major components of the various WEEE systems and their differences.

Prosthetic joint infections (PJI) are associated with high morbidity and costs. Various efforts have been made to improve the diagnosis of PJI over the past years, but only few studies have assessed the diagnostic utility of nucleic acid amplification test (NAAT) techniques in this context. Here, we report our experience with a commercial 16S rRNA gene PCR and an automated multiplex-PCR cartridge system in identifying pathogens causing PJI. A prospective single-centre study was performed including 54 patients with either septic or aseptic prosthetic joint replacement or surgical revision between February 2012 and April 2013. Conventional cultures of periprosthetic tissue samples were compared with the results of broad-range 16S rRNA gene real-time PCR (UMD-Universal Pathogen DNA Extraction and PCR Analysis, Molzym GmbH, Germany) and the multiplex-PCR Unyvero ITI(®) cartridge system (U-ITI; Curetis AG, Germany). Conventional culture and broad-range 16S rRNA gene real-time PCR were performed on all samples. U-ITI was used in a subgroup of 28 cases including all culture-positive cases. The agreement of the results from the methods was assessed. Of 54 cases, seven were culture-positive. Broad-range 16S rRNA gene real-time PCR gave 6, U-ITI 3 concordant positive results. Of the 47 culture-negative samples, 46 were also negative by broad-range 16S rRNA gene real-time PCR resulting in a 96% (52/54) agreement between 16S rRNA gene PCR and culture. Of the 21 culture-negative samples analysed with U-ITI, 20 gave negative results, including the single 16S rRNA gene PCR-positive/culture-negative specimen. The rate of agreement between U-ITI and culture results was 82% (23/28). This pilot study gave no indication of superiority of the used NAATs over conventional culture methods for the microbiological diagnosis of PJI. Drawbacks are susceptibility to contamination in the case of 16S rRNA gene real-time PCR, labour-intensive DNA extraction and limited pathogen panel in the case of the multiplex cartridge PCR system. More prospective trials are needed to evaluate the diagnostic performance of NAATs and their impact on the clinical management of PJI.