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Background: Torque teno viruses (TTV) are small DNA viruses whose replication is closely linked to immune status. A growing number of publications underlined the potential of TTV viral load as an indicator of immunosuppression., Objectives: To demonstrate the analytical performance of the first standardized RUO (Research Use Only) assay to detect and quantify human TTV DNA in whole blood and plasma., Study Design: We established analytical performances for TTV load measurement in various populations. The TTV kinetics were followed in kidney recipients. TTV viral load was analyzed on whole blood samples from 42 kidney recipients follow-up, 53 kidney deceased donors and 31 healthy volunteers., Results: The qPCR TTV assay detects the most prevalent human TTV genotypes and does not cross react with other viruses. Limit of detection was 2.2 log 10 copies/mL in whole blood and plasma, linearity and precision were demonstrated over the range 1.61 to 10.61 log 10 copies/mL in whole blood. Prevalence of TTV DNA in blood differed significantly among groups: 45% in healthy volunteers, 74% in donors and 83% in kidney recipients. In kidney recipients, early TTV kinetics were comparable to those previously observed with in-house assays in other transplant settings: viral load increased from an average of 4.3 log 10 to 7.9 log 10 copies/mL within the first 75 days post transplantation., Conclusion: This TTV assay showed high analytical sensitivity, specificity, linearity and precision. It is a useful standardized tool to further evaluate TTV load as a biomarker of immune status that could improve individual treatment strategy., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Motivation: Alignment-based taxonomic binning for metagenome characterization proceeds in two steps: reads mapping against a reference database (RDB) and taxonomic assignment according to the best hits. Beyond the sequencing technology and the completeness of the RDB, selecting the optimal configuration of the workflow, in particular the mapper parameters and the best hit selection threshold, to get the highest binning performance remains quite empirical., Results: We developed a statistical framework to perform such optimization at a minimal computational cost. Using an optimization experimental design and simulated datasets for three sequencing technologies, we built accurate prediction models for five performance indicators and then derived the parameter configuration providing the optimal performance. Whatever the mapper and the dataset, we observed that the optimal configuration yielded better performance than the default configuration and that the best hit selection threshold had a large impact on performance. Finally, on a reference dataset from the Human Microbiome Project, we confirmed that the optimized configuration increased the performance compared with the default configuration., Availability and Implementation: Not applicable., Contact: magali.dancette@biomerieux.com, Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)