Next-Generation Sequencing Reveals Frequent Opportunities for Exposure to Hepatitis C Virus in Ghana.

Globally, hepatitis C Virus (HCV) infection is responsible for a large proportion of persons with liver disease, including cancer. The infection is highly prevalent in sub-Saharan Africa. West Africa was identified as a geographic origin of two HCV genotypes. However, little is known about the genetic composition of HCV populations in many countries of the region. Using conventional and next-generation sequencing (NGS), we identified and genetically characterized 65 HCV strains circulating among HCV-positive blood donors in Kumasi, Ghana. Phylogenetic analysis using consensus sequences derived from 3 genomic regions of the HCV genome, 5'-untranslated region, hypervariable region 1 (HVR1) and NS5B gene, consistently classified the HCV variants (n = 65) into genotypes 1 (HCV-1, 15%) and genotype 2 (HCV-2, 85%). The Ghanaian and West African HCV-2 NS5B sequences were found completely intermixed in the phylogenetic tree, indicating a substantial genetic heterogeneity of HCV-2 in Ghana. Analysis of HVR1 sequences from intra-host HCV variants obtained by NGS showed that three donors were infected with >1 HCV strain, including infections with 2 genotypes. Two other donors share an HCV strain, indicating HCV transmission between them. The HCV-2 strain sampled from one donor was replaced with another HCV-2 strain after only 2 months of observation, indicating rapid strain switching. Bayesian analysis estimated that the HCV-2 strains in Ghana were expanding since the 16th century. The blood donors in Kumasi, Ghana, are infected with a very heterogeneous HCV population of HCV-1 and HCV-2, with HCV-2 being prevalent. The detection of three cases of co- or super-infections and transmission linkage between 2 cases suggests frequent opportunities for HCV exposure among the blood donors and is consistent with the reported high HCV prevalence. The conditions for effective HCV-2 transmission existed for ~ 3-4 centuries, indicating a long epidemic history of HCV-2 in Ghana

Maximum likelihood tree reconstructed with consensus NS5b, 5'UTR and consensus HVR1 gene sequences generated in this study.

<p>HCV-1 isolates are shown in black unfilled circles while HCV-2 are shown in black filled circles.</p

Maximum likelihood tree reconstructed with intra-host variants of HVR1 gene sequences of HCV genotype 1.

<p>Only unique haplotypes are shown. Individual samples are labeled with distinct identifiers beginning with letter ‘k’ and displayed with different colors.</p

Maximum likelihood tree reconstructed with NS5b gene sequences from West and Central Africa.

<p>Sequences from Ghana generated in this study are shown as red filled circles, those reported from West Africa as black filled triangles and those from Central Africa as black unfilled squares. Ghanaian sequences obtained from the GenBank are shown in blue filled circles.</p

Bayesian skyline plot, showing the epidemic history of HCV genotype 2.

<p>The thick black line in the middle represents the estimated mean effective number of infections through time in years. The two grey lines represent the 95% highest posterior density of this estimate.</p

PFnet of all sequences present in two patients at different time points.

<p>Each time point is shown with a different color. Sequences found on the first time point are shown in red and the second time point in blue. Each node represents a single sequence variant. The size of the node reflects frequency of the corresponding variant in the population. This network includes all of the links in any minimum spanning tree. The time interval between each time point is ~2 months.</p

Optimization of Next-Generation Sequencing Informatics Pipelines for Clinical Laboratory Practice

We direct your readers’ attention to the principles and guidelines (see Supplementary Guidelines) developed by the Next-generation Sequencing: Standardization of Clinical Testing II (Nex-StoCT II) informatics workgroup, which was convened by the Centers for Disease Control and Prevention (CDC). This work represents the first effort to systematically review current practices and present consensus recommendations for the design, optimization, and implementation of an informatics pipeline for clinical next-generation sequencing (NGS) in compliance with existing regulatory and professional quality standards1. Workgroup participants included informatics experts, clinical and research laboratory professionals, physicians with experience in NGS results interpretation, NGS test platform and software developers, and participants from US government agencies and professional organizations. The primary focus was the design, optimization, and implementation of an NGS informatics pipeline for the detection of germline sequence variants; however, the workgroup also discussed use of NGS for cancer and infectious disease testing. The typical NGS analytical process and selected workgroup recommendations are summarized in Table 1, Supplementary Fig. 1 and the Supplementary Guidelines