Browsing by Subject "Drug resistance"
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- ItemOpen AccessIntegrating informatics tools and portable sequencing technology for rapid detection of resistance to anti-tuberculous drugs(2019-06-24) Phelan, Jody E.; O’Sullivan, Denise M; Machado, Diana; Ramos, Jorge; Oppong, Yaa E A; Campino, Susana; O’Grady, Justin; McNerney, Ruth; Hibberd, Martin L.; Viveiros, Miguel; Huggett, Jim F; Clark, Taane GAbstract Background Mycobacterium tuberculosis resistance to anti-tuberculosis drugs is a major threat to global public health. Whole genome sequencing (WGS) is rapidly gaining traction as a diagnostic tool for clinical tuberculosis settings. To support this informatically, previous work led to the development of the widely used TBProfiler webtool, which predicts resistance to 14 drugs from WGS data. However, for accurate and rapid high throughput of samples in clinical or epidemiological settings, there is a need for a stand-alone tool and the ability to analyse data across multiple WGS platforms, including Oxford Nanopore MinION. Results We present a new command line version of the TBProfiler webserver, which includes hetero-resistance calling and will facilitate the batch processing of samples. The TBProfiler database has been expanded to incorporate 178 new markers across 16 anti-tuberculosis drugs. The predictive performance of the mutation library has been assessed using > 17,000 clinical isolates with WGS and laboratory-based drug susceptibility testing (DST) data. An integrated MinION analysis pipeline was assessed by performing WGS on 34 replicates across 3 multi-drug resistant isolates with known resistance mutations. TBProfiler accuracy varied by individual drug. Assuming DST as the gold standard, sensitivities for detecting multi-drug-resistant TB (MDR-TB) and extensively drug-resistant TB (XDR-TB) were 94% (95%CI 93–95%) and 83% (95%CI 79–87%) with specificities of 98% (95%CI 98–99%) and 96% (95%CI 95–97%) respectively. Using MinION data, only one resistance mutation was missed by TBProfiler, involving an insertion in the tlyA gene coding for capreomycin resistance. When compared to alternative platforms (e.g. Mykrobe predictor TB, the CRyPTIC library), TBProfiler demonstrated superior predictive performance across first- and second-line drugs. Conclusions The new version of TBProfiler can rapidly and accurately predict anti-TB drug resistance profiles across large numbers of samples with WGS data. The computing architecture allows for the ability to modify the core bioinformatic pipelines and outputs, including the analysis of WGS data sourced from portable technologies. TBProfiler has the potential to be integrated into the point of care and WGS diagnostic environments, including in resource-poor settings.
- ItemOpen AccessNetwork-driven analysis of human–Plasmodium falciparum interactome: processes for malaria drug discovery and extracting in silico targets(2021-10-26) Agamah, Francis E.; Damena, Delesa; Skelton, Michelle; Ghansah, Anita; Mazandu, Gaston K.; Chimusa, Emile R.Background The emergence and spread of malaria drug resistance have resulted in the need to understand disease mechanisms and importantly identify essential targets and potential drug candidates. Malaria infection involves the complex interaction between the host and pathogen, thus, functional interactions between human and Plasmodium falciparum is essential to obtain a holistic view of the genetic architecture of malaria. Several functional interaction studies have extended the understanding of malaria disease and integrating such datasets would provide further insights towards understanding drug resistance and/or genetic resistance/susceptibility, disease pathogenesis, and drug discovery. Methods This study curated and analysed data including pathogen and host selective genes, host and pathogen protein sequence data, protein–protein interaction datasets, and drug data from literature and databases to perform human-host and P. falciparum network-based analysis. An integrative computational framework is presented that was developed and found to be reasonably accurate based on various evaluations, applications, and experimental evidence of outputs produced, from data-driven analysis. Results This approach revealed 8 hub protein targets essential for parasite and human host-directed malaria drug therapy. In a semantic similarity approach, 26 potential repurposable drugs involved in regulating host immune response to inflammatory-driven disorders and/or inhibiting residual malaria infection that can be appropriated for malaria treatment. Further analysis of host–pathogen network shortest paths enabled the prediction of immune-related biological processes and pathways subverted by P. falciparum to increase its within-host survival. Conclusions Host–pathogen network analysis reveals potential drug targets and biological processes and pathways subverted by P. falciparum to enhance its within malaria host survival. The results presented have implications for drug discovery and will inform experimental studies.
- ItemOpen AccessOptimised electronic patient records to improve clinical monitoring of HIV-positive patients in rural South Africa (MONART trial): study protocol for a cluster-randomised trial(2021-12-20) Iwuji, Collins; Osler, Meg; Mazibuko, Lusanda; Hounsome, Natalia; Ngwenya, Nothando; Chimukuche, Rujeko S; Khoza, Thandeka; Gareta, Dickman; Sunpath, Henry; Boulle, Andrew; Herbst, KobusBackground There is poor viral load monitoring (VLM) and inadequate management of virological failure in HIV-positive individuals on antiretroviral therapy in rural KwaZulu-Natal, South Africa. This could be contributing to increasing HIV drug resistance in the setting. This study aims to investigate the clinical and process impediments in VLM within the health system and to evaluate a quality improvement package (QIP) to address the identified gaps. The QIP comprises (i) a designated viral load champion responsible for administrative management and triaging of viral load results (ii) technological enhancement of the routine clinic-based Three Interlinked Electronic Register (TIER.Net) to facilitate daily automatic import of viral load results from the National Health Service Laboratory to TIER.Net (iii) development of a dashboard system to support VLM. Methods/design The study will evaluate the effectiveness of the QIP compared to current care for improving VLM and virological suppression using an effectiveness implementation hybrid type 3 design. This will use a cluster-randomised design with the primary healthcare clinics as the unit of randomisation with ten clinics randomised in a 1:1 ratio to either the intervention or control arm. We will enrol 150 HIV-positive individuals who had been on ART for ≥ 12 months from each of the ten clinics (750 in 5 intervention clinics vs. 750 in 5 control clinics) and follow them up for a period of 12 months. The primary outcome is the proportion of all patients who have a viral load (VL) measurement and are virally suppressed (composite outcome) after 12 months of follow up. Secondary outcomes during follow up include proportion of all patients with at least one documented VL in TIER.Net, proportion with VL ≥ 50 copies/mL, proportion with VL ≥ 1000 copies/mL (virological failure) and subsequent switch to second-line ART. Discussion We aim to provide evidence that a staff-centred quality improvement package, designated viral load monitoring champion, and augmentation of TIER.Net with a dashboard system will improve viral load monitoring and lead to improved virological suppression. Trial registration: This trial is registered on ClinicalTrials.gov on 8 Oct 2021. Identifier: NCT05071573; https://clinicaltrials.gov/ct2/show/NCT05071573?term=NCT05071573&draw=2&rank=1
- ItemOpen Access
- ItemOpen AccessSelf-medication and Anti-malarial Drug Resistance in the Democratic Republic of the Congo (DRC): A silent threat(BioMed Central, 2022-10-04) Akilimali, Aymar; Bisimwa, Charles; Aborode, Abdullahi T.; Biamba, Chrispin; Sironge, Leonard; Balume, Alain; Sayadi, Rahma; Ajibade, Samuel B.; Akintayo, Akintola A.; Oluwadairo, Tolulope O.; Fajemisin, Emmanuel A.Background Malaria is a global infectious (vector-borne: Anopheles mosquitoes) disease which is a leading cause of morbidity and mortality in Sub-Saharan Africa (SSA). Among all its parasitic (protozoan: Plasmodium sp.) variants, Plasmodium falciparum (PF) is the most virulent and responsible for above 90% of global malaria deaths hence making it a global public health threat. Main context Despite current front-line antimalarial treatments options especially allopathic medications and malaria prevention (and control) strategies especially governmental policies and community malaria intervention programs in SSA, PF infections remains prevalent due to increased antimicrobial/antimalarial drug resistance caused by several factors especially genetic mutations and auto(self)-medication practices in SSA. In this article, we focused on the Democratic Republic of Congo (DRC) as the largest SSA country by bringing perspective into the impact of self-medication and antimalarial drug resistance, and provided recommendation for long-term improvement and future analysis in malaria prevention and control in SSA. Conclusions Self-medication and anti-malarial drug resistance is a major challenge to malaria control in DRC and sub-Saharan Africa, and to achieve sustainable control, individual, community and governmental efforts must be aligned to stop self-medication, and strengthen the health systems against malaria.