Hemorrhagic fever outbreaks are difficult to diagnose and control in part because of a lack of low-cost and easily accessible diagnostic structures in countries where etiologic agents are present. Furthermore, initial clinical symptoms are common and shared with other endemic diseases such as malaria or typhoid fever. Current molecular diagnostic methods such as polymerase chain reaction require trained personnel and laboratory infrastructure, hindering diagnostics at the point of need, particularly in outbreak settings. Therefore, rapid diagnostic tests such as lateral flow can be broadly deployed and are typically well-suited to rapidly diagnose hemorrhagic fever viruses, such as Ebola virus. Early detection and control of Ebola outbreaks require simple, easy-to-use assays that can detect very low amount of virus in blood. Here, we developed and characterized an immunoassay test based on immunochromatography coupled to silver amplification technology to detect the secreted glycoprotein of EBOV. The glycoprotein is among the first viral proteins to be detected in blood. This strategy aims at identifying infected patients early following onset of symptoms by detecting low amount of sGP protein in blood samples. The limit of detection achieved by this sGP-targeted kit is 2.2 x 10 4 genome copies/ml in plasma as assayed in a monkey analytical cohort. Clinical performance evaluation showed a specificity of 100% and a sensitivity of 85.7% when evaluated with plasma samples from healthy controls and patients infected with Zaire Ebola virus from Macenta, Guinea. This rapid and accurate diagnostic test could therefore be used in endemic countries for early detection of infected individuals in point of care settings. Moreover, it could also support efficient clinical triage in hospitals or clinical
Background: Shortening the time-to-result for pathogen detection and identification and antibiotic susceptibility testing for patients with Hospital-Acquired and Ventilator-Associated pneumonia (HAP-VAP) is of great interest. For this purpose, clinical metagenomics is a promising non-hypothesis driven alternative to traditional culture-based solutions: when mature, it would allow direct sequencing all microbial genomes present in a BronchoAlveolar Lavage (BAL) sample with the purpose of simultaneously identifying pathogens and Antibiotic Resistance Genes (ARG). In this study, we describe a new bioinformatics method to detect pathogens and their ARG with good accuracy, both in mono-and polymicrobial samples.Methods: The standard approach (hereafter called TBo), that consists in taxonomic binning of metagenomic reads followed by an assembly step, suffers from lack of sensitivity for ARG detection. Thus, we propose a new bioinformatics approach (called TBwDM) with both models and databases optimized for HAP-VAP, that performs reads mapping against ARG reference database in parallel to taxonomic binning, and joint reads assembly.Results: In in-silico simulated monomicrobial samples, the recall for ARG detection increased from 51% with TBo to 97.3% with TBwDM ; in simulated polymicrobial infections, it increased from 41.8% to 82%. In real sequenced BAL samples (mono and polymicrobial), detected pathogens were also confirmed by traditional culture approaches. Moreover, both recall and precision for ARG detection were higher with TBwDM than with TBo (35 points difference for recall, and 7 points difference for precision).Conclusions: We present a new bioinformatics pipeline to identify pathogens and ARG in BAL samples from patients with HAP-VAP, with higher sensitivity for ARG recovery than standard approaches and the ability to link ARG to their host pathogens.
The gut microbiome is widely analyzed using high-throughput sequencing, such as 16S rRNA gene amplicon sequencing and shotgun metagenomic sequencing (SMS). DNA extraction is known to have a large impact on the metagenomic analyses. The aim of this study was to compare DNA extraction protocols for 16S sequencing. In that context, four commonly used DNA extraction methods were compared for the analysis of the gut microbiota. Commercial versions were evaluated against modified protocols using a stool preprocessing device (SPD, bioMérieux) upstream DNA extraction. Stool samples from nine healthy volunteers and nine patients with a Clostridium difficile infection were extracted with all protocols and 16S sequenced. Protocols were ranked using wet- and dry-lab criteria, including quality controls of the extracted genomic DNA, alpha-diversity, accuracy using a mock community of known composition and repeatability across technical replicates. SPD improved overall efficiency of three of the four tested protocols compared with their commercial version, in terms of DNA extraction yield, sample alpha-diversity, and recovery of Gram-positive bacteria. The best overall performance was obtained for the S-DQ protocol, SPD combined with the DNeasy PowerLyser PowerSoil protocol from QIAGEN. Based on this evaluation, we strongly believe that the use of such stool preprocessing device improves both the standardization and the quality of the DNA extraction in the human gut microbiome studies.
Background: The gut microbiome is widely analyzed using high-throughput sequencing, such as 16S rRNA gene amplicon sequencing and shotgun metagenomic sequencing (SMS). DNA extraction is known to have a large impact on the metagenomic analyses. The aim of this study was to select a unique and best performing DNA extraction protocol for both metagenomic sequencing methods. In that context, four commonly used DNA extraction methods were compared for the analysis of the gut microbiota. Commercial versions were evaluated against modified protocols using a stool preprocessing device (SPD, bioMérieux) in order to facilitate DNA extraction. Stool samples from nine healthy volunteers and nine patients with a Clostridium difficile infection were extracted with all protocols and sequenced with both metagenomic methods. Protocols were ranked using wet- and dry-lab criteria, including quality controls of the extracted genomic DNA, alpha-diversity, accuracy using a mock community of known composition and repeatability across technical replicates.Results: Independently of the sequencing methods used, SPD significantly improved efficiency of the four tested protocols compared with their commercial version, in terms of extracted DNA quality, accuracy of the predicted composition of the microbiota (notably for Gram-positive bacteria), sample alpha-diversity, and experimental repeatability. The best overall performance was obtained for the S-DQ protocol, SPD combined to the DNeasy PowerLyser PowerSoil protocol from QIAGEN.Conclusion: Based on this evaluation, we recommend to use the S-DQ protocol, to obtain standardized and high quality extracted DNA in the human gut microbiome studies.
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