Potential utility of the Genedrive point-of-care test for HCV RNA detection

Quality Assurance for Hepatitis C Virus Point-of-Care Diagnostics in Sub-Saharan Africa

As part of a multinational study to evaluate the Bioline Hepatitis C virus (HCV) point-of-care (POC) testing in sub-Saharan Africa (SSA), this narrative review summarises regulatory standards and quality indicators for validating and approving HCV clinical diagnostics. In addition, this review also provides a summary of their diagnostic evaluations using the REASSURED criteria as the benchmark and its implications on the WHO HCV elimination goals 2030.

Rapid Visual Detection of Hepatitis C Virus Using Reverse Transcription Recombinase-Aided Amplification–Lateral Flow Dipstick

Hepatitis C virus (HCV) infection is a global public health threat. Reaching the World Health Organization’s objective for eliminating viral hepatitis by 2030 will require a precise disease diagnosis. While immunoassays and qPCR play a significant role in detecting HCV, rapid and accurate point-of-care testing is important for pathogen identification. This study establishes a reverse transcription recombinase-aided amplification–lateral flow dipstick (RT-RAA-LFD) assay to detect HCV. The intact workflow was completed within 30 min, and the detection limit for synthesized C/E1 plasmid gene-containing plasmid was 10 copies/μl. In addition, the test showed good specificity, with no cross-reactivity observed for hepatitis A virus, hepatitis B virus, HIV, syphilis, and human papillomavirus virus. Using extracted RNAs from 46 anti-HCV antibody-positive samples, RT-RAA-LFD showed 100% positive and negative concordance rates with qPCR. In summary, the RT-RAA-LFD assay established in this study is suitable for the rapid clinical detection of HCV at the community level and in remote areas.

Diagnostic Performance and Usability of the Genedrive® HCV ID Kit in Two Decentralized Settings in Cameroon and Georgia

Point-of-care diagnostics have the potential to increase diagnosis and linkage to care and help reach the WHO targets to eliminate hepatitis C virus (HCV) by 2030. Here, we evaluated the diagnostic accuracy of Genedrive HCV ID assay for the qualitative detection of HCV RNA in decentralized settings in two low- and middle-income countries using fresh plasma specimens from 426 participants. The Abbott RealTime HCV assay was used as the gold standard. Genedrive HCV ID assay was conducted by different users. Users also completed questionnaires to assess the usability of Genedrive. At detection thresholds of 12 IU/mL or 30 IU/mL, 1000 IU/mL, and 2362 IU/mL, the sensitivity was 96.2% (95% CI: 92.7-98.4), 100% (98.2-100), and 100% (98.2-100), respectively; the specificity was 99.5% (95% CI: 97.4-100), 99.5% (97.5-100), and 98.7% (96.1-100), respectively. All genotypes detected using the gold-standard assay were also detected with Genedrive. Users found Genedrive easy to use. Genedrive is a simple and accurate test to confirm chronic HCV infection in decentralized, real-life, resource-limited settings. This novel diagnostic tool could contribute to closing the current gap in HCV diagnosis.

Offline Next Generation Metagenomics Sequence Analysis Using MinION Detection Software (MINDS)

Field laboratories interested in using the MinION often need the internet to perform sample analysis. Thus, the lack of internet connectivity in resource-limited or remote locations renders downstream analysis problematic, resulting in a lack of sample identification in the field. Due to this dependency, field samples are generally transported back to the lab for analysis where internet availability for downstream analysis is available. These logistics problems and the time lost in sample characterization and identification, pose a significant problem for field scientists. To address this limitation, we have developed a stand-alone data analysis packet using open source tools developed by the Nanopore community that does not depend on internet availability. Like Oxford Nanopore Technologies’ (ONT) cloud-based What’s In My Pot (WIMP) software, we developed the offline MinION Detection Software (MINDS) based on the Centrifuge classification engine for rapid species identification. Several online bioinformatics applications have been developed surrounding ONT’s framework for analysis of long reads. We have developed and evaluated an offline real time classification application pipeline using open source tools developed by the Nanopore community that does not depend on internet availability. Our application has been tested on ATCC’s 20 strain even mix whole cell (ATCC MSA-2002) sample. Using the Rapid Sequencing Kit (SQK-RAD004), we were able to identify all 20 organisms at species level. The analysis was performed in 15 min using a Dell Precision 7720 laptop. Our offline downstream bioinformatics application provides a cost-effective option as well as quick turn-around time when analyzing samples in the field, thus enabling researchers to fully utilize ONT’s MinION portability, ease-of-use, and identification capability in remote locations.