Using 894 phylogenetically diverse genomes of the Mycobacterium tuberculosis complex (MTBC), we simulated in silico the ability of the Hain Lifescience GenoType MTBC to differentiate the causative agents of tuberculosis. We propose a revised interpretation of this assay to reflect its strengths (e.g. it can distinguish some strains of M. canettii and variants of M. bovis that are not intrinsically resistant to pyrazinamide) and limitations (e.g. M. orygis cannot be differentiated from M. africanum). This is a work of the U.S. Government and is not subject to copyright protection in the United States. Foreign copyrights may apply.
10 pages, 6 figures, 1 table, supplementary data https://doi.org/10.1016/j.scitotenv.2020.138118 ; Ecosystem-based management requires an assessment of the cumulative effects of human pressures and environmental change. The operationalization and integration of cumulative effects assessments (CEA) into decision-making processes often lacks a comprehensive and transparent framework. A risk-based CEA framework that divides a CEA in risk identification, risk analysis and risk evaluation, could structure such complex analyses and facilitate the establishment of direct science-policy links. Here, we examine carefully the operationalization of such a risk-based CEA framework with the help of eleven contrasting case studies located in Europe, French Polynesia, and Canada. We show that the CEA framework used at local, sub-regional, and regional scales allowed for a consistent, coherent, and transparent comparison of complex assessments. From our analysis, we pinpoint four emerging issues that, if accurately addressed, can improve the take up of CEA outcomes by management: 1) framing of the CEA context and defining risk criteria; 2) describing the roles of scientists and decision-makers; 3) reducing and structuring complexity; and 4) communicating uncertainty. Moreover, with a set of customized tools we describe and analyze for each case study the nature and location of uncertainty as well as trade-offs regarding available knowledge and data used for the CEA. Ultimately, these tools aid decision-makers to recognize potential caveats and repercussions of management decisions. One key recommendation is to differentiate CEA processes and their context in relation to governance advice, marine spatial planning or regulatory advice. We conclude that future research needs to evaluate how effective management measures are in reducing the risk of cumulative effects. Changing governance structures takes time and is often difficult, but we postulate that well-framed and structured CEA can function as a strategic tool to integrate ecosystem considerations across multiple sectorial policies. ; This article is a product of the working group on cumulative effects assessment under the framework of COST Action 15121 "Advancing marine conservation in the European and contiguous seas" (MarCons; http://www.marcons-cost.eu; (Katsanevakis et al., 2017)—supported by COST (European Cooperation in Science and Technology, CA15121)
Whole-genome sequencing allows rapid detection of drug-resistant Mycobacterium tuberculosis isolates. However, the availability of high-quality data linking quantitative phenotypic drug susceptibility testing (DST) and genomic data have thus far been limited. We determined drug resistance profiles of 176 genetically diverse clinical M. tuberculosis isolates from the Democratic Republic of the Congo, Ivory Coast, Peru, Thailand, and Switzerland by quantitative phenotypic DST for 11 antituberculous drugs using the BD Bactec MGIT 960 system and 7H10 agar dilution to generate a cross-validated phenotypic DST readout. We compared DST results with predicted drug resistance profiles inferred by whole-genome sequencing. Classification of strains by the two phenotypic DST methods into resistotype/wild-type populations was concordant in 73 to 99% of cases, depending on the drug. Our data suggest that the established critical concentration (5 mg/liter) for ethambutol resistance (MGIT 960 system) is too high and misclassifies strains as susceptible, unlike 7H10 agar dilution. Increased minimal inhibitory concentrations were explained by mutations identified by whole-genome sequencing. Using whole-genome sequences, we were able to predict quantitative drug resistance levels for the majority of drug resistance mutations. Predicting quantitative levels of drug resistance by whole-genome sequencing was partially limited due to incompletely understood drug resistance mechanisms. The overall sensitivity and specificity of whole-genome-based DST were 86.8% and 94.5%, respectively. Despite some limitations, whole-genome sequencing has the potential to infer resistance profiles without the need for time-consuming phenotypic methods.
Whole genome sequencing allows rapid detection of drug-resistant isolates. However, the availability of high-quality data linking quantitative phenotypic drug susceptibility testing (DST) and genomic data has thus far been limited.We determined drug resistance profiles of 176 genetically diverse clinical isolates from Democratic Republic of the Congo, Ivory Coast, Peru, Thailand and Switzerland by quantitative phenotypic DST for 11 antituberculous drugs using the BD BACTEC MGIT 960 system and 7H10 agar dilution to generate a cross-validated phenotypic DST readout. We compared DST results with predicted drug resistance profiles inferred by whole genome sequencing.Classification of strains by the two phenotypic DST methods into resistotype/wild type populations was concordant in 73-99 % of cases, depending on the drug. Our data suggests that the established critical concentration (5 mg/L) for ethambutol resistance (MGIT 960 system) is too high and may misclassify strains as susceptible, compared to 7H10 agar dilution. Increased minimal inhibitory concentrations were explained by mutations identified by whole genome sequencing. Using whole genome sequences, we were able to predict quantitative drug resistance levels for the majority of drug resistance mutations. Predicting quantitative levels of drug resistance by whole genome sequencing was partially limited due to incompletely understood drug resistance mechanisms. The overall sensitivity and specificity of whole genome-based DST were 86.8 % and 94.5 %, respectively.Despite some limitations, whole genome sequencing has the potential to infer resistance profiles without the need for time-consuming phenotypic methods.
Background Drug resistance threatens global tuberculosis control. We aimed to examine mortality in patients with tuberculosis from high-burden countries, according to concordance or discordance of results from drug susceptibility testing done locally and whole-genome sequencing (WGS). Methods In this multicentre cohort study, we collected pulmonary Mycobacterium tuberculosis isolates and clinical data from individuals with tuberculosis from antiretroviral therapy programmes and tuberculosis clinics in Côte d'Ivoire, Democratic Republic of the Congo, Kenya, Nigeria, Peru, South Africa, and Thailand, stratified by HIV status and drug resistance. Sites tested drug susceptibility using routinely available methods. WGS was done on Illumina HiSeq 2500 in the USA and Switzerland, and TBprofiler was used to analyse the genomes. We included individuals aged 16 years or older with pulmonary tuberculosis (bacteriologically confirmed or clinically diagnosed). We analysed mortality in multivariable logistic regression models adjusted for sex, age, HIV status, history of tuberculosis, and sputum positivity. Findings Between Sept 1, 2014, and July 4, 2016, of 634 patients included in our previous analysis, we included 582 patients with tuberculosis (median age 33 years [IQR 27–43], 225 [39%] women, and 247 [42%] HIV-positive). Based on WGS, 339 (58%) isolates were pan-susceptible, 35 (6%) monoresistant, 146 (25%) multidrug-resistant, and 24 (4%) pre-extensively drug-resistant (pre-XDR) or XDR. The analysis of mortality was based on 530 patients; 63 (12%) died and 77 (15%) patients received inappropriate treatment. Mortality ranged from 6% (18 of 310) in patients with pan-susceptible tuberculosis to 39% (nine of 23) in patients with pre-XDR or XDR tuberculosis. The adjusted odds ratio for mortality was 4·92 (95% CI 2·47–9·78) among undertreated patients, compared with appropriately treated patients. Interpretation In seven countries with a high burden of tuberculosis, we observed discrepancies between drug resistance patterns obtained locally and WGS. The underdiagnosis of drug resistance resulted in inappropriate treatment and higher mortality. WGS can provide accurate and detailed drug resistance information required to improve the outcomes of drug-resistant tuberculosis in high-burden settings. Our results support WHO's call for point-of-care tests based on WGS.
