Prediction of Antibiotic Susceptibility Profiles of Vibrio cholerae Isolates From Whole Genome Illumina and Nanopore Sequencing Data: CholerAegon

During the last decades, antimicrobial resistance (AMR) has become a global public health concern. Nowadays multi-drug resistance is commonly observed in strains of Vibrio cholerae, the etiological agent of cholera. In order to limit the spread of pathogenic drug-resistant bacteria and to maintain treatment options the analysis of clinical samples and their AMR profiles are essential. Particularly, in low-resource settings a timely analysis of AMR profiles is often impaired due to lengthy culturing procedures for antibiotic susceptibility testing or lack of laboratory capacity. In this study, we explore the applicability of whole genome sequencing for the prediction of AMR profiles of V. cholerae. We developed the pipeline CholerAegon for the in silico prediction of AMR profiles of 82 V. cholerae genomes assembled from long and short sequencing reads. By correlating the predicted profiles with results from phenotypic antibiotic susceptibility testing we show that the prediction can replace in vitro susceptibility testing for five of seven antibiotics. Because of the relatively low costs, possibility for real-time data analyses, and portability, the Oxford Nanopore Technologies MinION sequencing platform-especially in light of an upcoming less error-prone technology for the platform-appears to be well suited for pathogen genomic analyses such as the one described here. Together with CholerAegon, it can leverage pathogen genomics to improve disease surveillance and to control further spread of antimicrobial resistance.

Analysis of Diagnostic Findings From the European Mobile Laboratory in Guéckédou, Guinea, March 2014 Through March 2015

Background. A unit of the European Mobile Laboratory (EMLab) consortium was deployed to the Ebola virus disease (EVD) treatment unit in Guéckédou, Guinea, from March 2014 through March 2015.

Methods. The unit diagnosed EVD and malaria, using the RealStar Filovirus Screen reverse transcription–polymerase chain reaction (RT-PCR) kit and a malaria rapid diagnostic test, respectively.

Results. The cleaned EMLab database comprised 4719 samples from 2741 cases of suspected EVD from Guinea. EVD was diagnosed in 1231 of 2178 hospitalized patients (57%) and in 281 of 563 who died in the community (50%). Children aged <15 years had the highest proportion of Ebola virus–malaria parasite coinfections. The case-fatality ratio was high in patients aged <5 years (80%) and those aged >74 years (90%) and low in patients aged 10–19 years (40%). On admission, RT-PCR analysis of blood specimens from patients who died in the hospital yielded a lower median cycle threshold (Ct) than analysis of blood specimens from survivors (18.1 vs 23.2). Individuals who died in the community had a median Ct of 21.5 for throat swabs. Multivariate logistic regression on 1047 data sets revealed that low Ct values, ages of <5 and ≥45 years, and, among children aged 5–14 years, malaria parasite coinfection were independent determinants of a poor EVD outcome.

Conclusions. Virus load, age, and malaria parasite coinfection play a role in the outcome of EVD.

Correction: Experimental Treatment with Favipiravir for Ebola Virus Disease (the JIKI Trial): A Historically Controlled, Single-Arm Proof-of-Concept Trial in Guinea

[This corrects the article DOI: 10.1371/journal.pmed.1001967.].

Temporal and spatial analysis of the 2014-2015 Ebola virus outbreak in West Africa

West Africa is currently witnessing the most extensive Ebola virus (EBOV) outbreak so far recorded. Until now, there have been 27,013 reported cases and 11,134 deaths. The origin of the virus is thought to have been a zoonotic transmission from a bat to a two-year-old boy in December 2013 (ref. 2). From this index case the virus was spread by human-to-human contact throughout Guinea, Sierra Leone and Liberia. However, the origin of the particular virus in each country and time of transmission is not known and currently relies on epidemiological analysis, which may be unreliable owing to the difficulties of obtaining patient information. Here we trace the genetic evolution of EBOV in the current outbreak that has resulted in multiple lineages. Deep sequencing of 179 patient samples processed by the European Mobile Laboratory, the first diagnostics unit to be deployed to the epicentre of the outbreak in Guinea, reveals an epidemiological and evolutionary history of the epidemic from March 2014 to January 2015. Analysis of EBOV genome evolution has also benefited from a similar sequencing effort of patient samples from Sierra Leone. Our results confirm that the EBOV from Guinea moved into Sierra Leone, most likely in April or early May. The viruses of the Guinea/Sierra Leone lineage mixed around June/July 2014. Viral sequences covering August, September and October 2014 indicate that this lineage evolved independently within Guinea. These data can be used in conjunction with epidemiological information to test retrospectively the effectiveness of control measures, and provides an unprecedented window into the evolution of an ongoing viral haemorrhagic fever outbreak.

Ultrasensitive monitoring of HIV-1 viral load by a low-cost real-time reverse transcription-PCR assay with internal control for the 5' long terminal repeat domain

BACKGROUND

Current HIV-1 viral-load assays are too expensive for resource-limited settings. In some countries, monitoring of antiretroviral therapy is now more expensive than treatment itself. In addition, some commercial assays have shown shortcomings in quantifying rare genotypes.

METHODS

We evaluated real-time reverse transcription-PCR with internal control targeting the conserved long terminal repeat (LTR) domain of HIV-1 on reference panels and patient samples from Brazil (n = 1186), South Africa (n = 130), India (n = 44), and Germany (n = 127).

RESULTS

The detection limit was 31.9 IU of HIV-1 RNA/mL of plasma (> 95% probability of detection, Probit analysis). The internal control showed inhibition in 3.7% of samples (95% confidence interval, 2.32%-5.9%; n = 454; 40 different runs). Comparative qualitative testing yielded the following: Roche Amplicor vs LTR assay (n = 431 samples), 51.7% vs 65% positives; Amplicor Ultrasensitive vs LTR (n = 133), 81.2% vs 82.7%; BioMerieux NucliSens HIV-1 QT (n = 453), 60.5% vs 65.1%; Bayer Versant 3.0 (n = 433), 57.7% vs 55.4%; total (n = 1450), 59.0% vs 63.8% positives. Intra-/interassay variability at medium and near-negative concentrations was 18%-51%. The quantification range was 50-10,000,000 IU/mL. Viral loads for subtypes A-D, F-J, AE, and AG yielded mean differences of 0.31 log(10) compared with Amplicor in the 10(3)-10(4) IU/mL range. HIV-1 N and O were not detected by Amplicor, but yielded up to 180 180.00 IU/mL in the LTR assay. Viral loads in stored samples from all countries, compared with Amplicor, NucliSens, or Versant, yielded regression line slopes (SD) of 0.9 (0.13) (P < 0.001 for all).

CONCLUSIONS

This method offers all features of commercial assays and covers all relevant genotypes. It could allow general monitoring of antiretroviral therapy in resource-limited settings.