Antibiotic resistance prediction for Mycobacterium tuberculosis from genome sequence data with Mykrobe [version 1; peer review: 2 approved, 1 approved with reservations]

Two billion people are infected with Mycobacterium tuberculosis, leading to 10 million new cases of active tuberculosis and 1.5 million deaths annually. Universal access to drug susceptibility testing (DST) has become a World Health Organization priority. We previously developed a software tool, Mykrobe predictor, which provided offline species identification and drug resistance predictions for M. tuberculosis from whole genome sequencing (WGS) data. Performance was insufficient to support the use of WGS as an alternative to conventional phenotype-based DST, due to mutation catalogue limitations. Here we present a new tool, Mykrobe, which provides the same functionality based on a new software implementation. Improvements include i) an updated mutation catalogue giving greater sensitivity to detect pyrazinamide resistance, ii) support for user-defined resistance catalogues, iii) improved identification of non-tuberculous mycobacterial species, and iv) an updated statistical model for Oxford Nanopore Technologies sequencing data. Mykrobe is released under MIT license at https://github.com/mykrobe-tools/mykrobe. We incorporate mutation catalogues from the CRyPTIC consortium et al. (2018) and from Walker et al. (2015), and make improvements based on performance on an initial set of 3206 and an independent set of 5845 M. tuberculosis Illumina sequences. To give estimates of error rates, we use a prospectively collected dataset of 4362 M. tuberculosis isolates. Using culture based DST as the reference, we estimate Mykrobe to be 100%, 95%, 82%, 99% sensitive and 99%, 100%, 99%, 99% specific for rifampicin, isoniazid, pyrazinamide and ethambutol resistance prediction respectively. We benchmark against four other tools on 10207 (=5845+4362) samples, and also show that Mykrobe gives concordant results with nanopore data. We measure the ability of Mykrobe-based DST to guide personalized therapeutic regimen design in the context of complex drug susceptibility profiles, showing 94% concordance of implied regimen with that driven by phenotypic DST, higher than all other benchmarked tools

Impact of a silver layer on the membrane of tap water filters on the microbiological quality of filtered water

<p>Abstract</p> <p>Background</p> <p>Bacteria in the hospital's drinking water system represent a risk for the acquisition of a nosocomial infection in the severely immunocompromised host. Terminal tap water filters may be used to prevent nosocomial Legionnaires' disease. We present data from water samples using an improved kind of tap water filters.</p> <p>Methods</p> <p>In a blinded study on an intermediate care unit of the thoracic surgery department, a modified type of the Germlyser water filter (Aqua-Free Membrane Technology) with a newly-introduced silver layer on the filtration membrane was compared to its preceding type without such a layer on 15 water outlets. We determined growth of <it>Legionella</it>, other pathogenic bacteria, and the total heterotrophic plate count in unfiltered water and filtered water samples after filter usage intervals of 1 through 4 weeks.</p> <p>Results</p> <p>A total of 299 water samples were tested. Twenty-nine of the 60 unfiltered water samples contained <it>Legionella </it>of various serogroups (baseline value). In contrast, all samples filtered by the original water filter and all but one of the water samples filtered by the modified filter type remained <it>Legionella</it>-free. No other pathogenic bacteria were detected in any filtered sample. The total plate count in water samples increased during use of both kinds of filters over time. However, for the first 7 days of use, there were significantly fewer water samples containing >100 CFU per mL when using the new filter device compared with the older filters or taps with no filter. No advantage was seen thereafter.</p> <p>Conclusion</p> <p>The use of this type of terminal water filter is an appropriate method to protect immunocompromised patients from water-borne pathogens such as <it>Legionella</it>.</p

Multi-messenger observations of a binary neutron star merger

On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta

Prediction of Susceptibility to First-Line Tuberculosis Drugs by DNA Sequencing

Background: The World Health Organization recommends drug-susceptibility testing of Mycobacterium tuberculosis complex for all patients with tuberculosis to guide treatment decisions and improve outcomes. Whether DNA sequencing can be used to accurately predict profiles of susceptibility to first-line antituberculosis drugs has not been clear. Methods: We obtained whole-genome sequences and associated phenotypes of resistance or susceptibility to the first-line antituberculosis drugs isoniazid, rifampin, ethambutol, and pyrazinamide for isolates from 16 countries across six continents. For each isolate, mutations associated with drug resistance and drug susceptibility were identified across nine genes, and individual phenotypes were predicted unless mutations of unknown association were also present. To identify how whole-genome sequencing might direct first-line drug therapy, complete susceptibility profiles were predicted. These profiles were predicted to be susceptible to all four drugs (i.e., pansusceptible) if they were predicted to be susceptible to isoniazid and to the other drugs or if they contained mutations of unknown association in genes that affect susceptibility to the other drugs. We simulated the way in which the negative predictive value changed with the prevalence of drug resistance. Results: A total of 10,209 isolates were analyzed. The largest proportion of phenotypes was predicted for rifampin (9660 [95.4%] of 10,130) and the smallest was predicted for ethambutol (8794 [89.8%] of 9794). Resistance to isoniazid, rifampin, ethambutol, and pyrazinamide was correctly predicted with 97.1%, 97.5%, 94.6%, and 91.3% sensitivity, respectively, and susceptibility to these drugs was correctly predicted with 99.0%, 98.8%, 93.6%, and 96.8% specificity. Of the 7516 isolates with complete phenotypic drug-susceptibility profiles, 5865 (78.0%) had complete genotypic predictions, among which 5250 profiles (89.5%) were correctly predicted. Among the 4037 phenotypic profiles that were predicted to be pansusceptible, 3952 (97.9%) were correctly predicted. Conclusions: Genotypic predictions of the susceptibility of M. tuberculosis to first-line drugs were found to be correlated with phenotypic susceptibility to these drugs. (Funded by the Bill and Melinda Gates Foundation and others.

A cluster of multidrug-resistant Mycobacterium tuberculosis among patients arriving in Europe from the Horn of Africa: A molecular epidemiological study

Background The risk of tuberculosis outbreaks among people fleeing hardship for refuge in Europe is heightened. We describe the cross-border European response to an outbreak of multidrug-resistant tuberculosis among patients from the Horn of Africa and Sudan. Methods On April 29 and May 30, 2016, the Swiss and German National Mycobacterial Reference Laboratories independently triggered an outbreak investigation after four patients were diagnosed with multidrug-resistant tuberculosis. In this molecular epidemiological study, we prospectively defined outbreak cases with 24-locus mycobacterial interspersed repetitive unit-variable number tandem repeat (MIRU-VNTR) profiles; phenotypic resistance to isoniazid, rifampicin, ethambutol, pyrazinamide, and capreomycin; and corresponding drug resistance mutations. We whole-genome sequenced all Mycobacterium tuberculosis isolates and clustered them using a threshold of five single nucleotide polymorphisms (SNPs). We collated epidemiological data from host countries from the European Centre for Disease Prevention and Control. Findings Between Feb 12, 2016, and April 19, 2017, 29 patients were diagnosed with multidrug-resistant tuberculosis in seven European countries. All originated from the Horn of Africa or Sudan, with all isolates two SNPs or fewer apart. 22 (76%) patients reported their travel routes, with clear spatiotemporal overlap between routes. We identified a further 29 MIRU-VNTR-linked cases from the Horn of Africa that predated the outbreak, but all were more than five SNPs from the outbreak. However all 58 isolates shared a capreomycin resistance-associated tlyA mutation. Interpretation Our data suggest that source cases are linked to an M tuberculosis clone circulating in northern Somalia or Djibouti and that transmission probably occurred en route before arrival in Europe. We hypothesise that the shared mutation of tlyA is a drug resistance mutation and phylogenetic marker, the first of its kind in M tuberculosis sensu stricto.</p

Antibiotic resistance prediction for Mycobacterium tuberculosis from genome sequence data with Mykrobe

Two billion people are infected with Mycobacterium tuberculosis, leading to 10 million new cases of active tuberculosis and 1.5 million deaths annually. Universal access to drug susceptibility testing (DST) has become a World Health Organization priority. We previously developed a software tool, Mykrobe predictor, which provided offline species identification and drug resistance predictions for M. tuberculosis from whole genome sequencing (WGS) data. Performance was insufficient to support the use of WGS as an alternative to conventional phenotype-based DST, due to mutation catalogue limitations. Here we present a new tool, Mykrobe, which provides the same functionality based on a new software implementation. Improvements include i) an updated mutation catalogue giving greater sensitivity to detect pyrazinamide resistance, ii) support for user-defined resistance catalogues, iii) improved identification of non-tuberculous mycobacterial species, and iv) an updated statistical model for Oxford Nanopore Technologies sequencing data. Mykrobe is released under MIT license at https://github.com/mykrobe-tools/mykrobe. We incorporate mutation catalogues from the CRyPTIC consortium et al. (2018) and from Walker et al. (2015), and make improvements based on performance on an initial set of 3206 and an independent set of 5845 M. tuberculosis Illumina sequences. To give estimates of error rates, we use a prospectively collected dataset of 4362 M. tuberculosis isolates. Using culture based DST as the reference, we estimate Mykrobe to be 100%, 95%, 82%, 99% sensitive and 99%, 100%, 99%, 99% specific for rifampicin, isoniazid, pyrazinamide and ethambutol resistance prediction respectively. We benchmark against four other tools on 10207 (=5845+4362) samples, and also show that Mykrobe gives concordant results with nanopore data. We measure the ability of Mykrobe-based DST to guide personalized therapeutic regimen design in the context of complex drug susceptibility profiles, showing 94% concordance of implied regimen with that driven by phenotypic DST, higher than all other benchmarked tools

The Cellular Thioredoxin-1/Thioredoxin Reductase-1 Driven Oxidoreduction Represents a Chemotherapeutic Target for HIV-1 Entry Inhibition

Background The entry of HIV into its host cell is an interesting target for chemotherapeutic intervention in the life-cycle of the virus. During entry, reduction of disulfide bridges in the viral envelope glycoprotein gp120 by cellular oxidoreductases is crucial. The cellular thioredoxin reductase-1 plays an important role in this oxidoreduction process by recycling electrons to thioredoxin-1. Therefore, thioredoxin reductase-1 inhibitors may inhibit gp120 reduction during HIV-1 entry. In this present study, tellurium-based thioredoxin reductase-1 inhibitors were investigated as potential inhibitors of HIV entry. Results The organotellurium compounds inhibited HIV-1 and HIV-2 replication in cell culture at low micromolar concentrations by targeting an early event in the viral infection cycle. Time-of-drug-addition studies pointed to virus entry as the drug target, more specifically: the organotellurium compound TE-2 showed a profile similar or close to that of the fusion inhibitor enfuvirtide (T-20). Surface plasmon resonance-based interaction studies revealed that the compounds do not directly interact with the HIV envelope glycoproteins gp120 and gp41, nor with soluble CD4, but instead, dose-dependently bind to thioredoxin reductase-1. By inhibiting the thioredoxin-1/thioredoxin reductase-1-directed oxidoreduction of gp120, the organotellurium compounds prevent conformational changes in the viral glycoprotein which are necessary during viral entry. Conclusion Our findings revealed that thioredoxin-1/thioredoxin reductase-1 acts as a cellular target for the inhibition of HIV entry