Characterization of Novel HIV Drug Resistance Mutations Using Clustering, Multidimensional Scaling and SVM-Based Feature Ranking

We present a case study on the discovery of clinically relevant domain knowledge in the field of HIV drug resistance. Novel mutations in the HIV genome associated with treatment failure were identified by mining a relational clinical database. Hierarchical cluster analysis suggests that two of these mutations form a novel mutational complex, while all others are involved in known resistance-conferring evolutionary pathways. The clustering is shown to be highly stable in a bootstrap procedure. Multidimensional scaling in mutation space indicates that certain mutations can occur within multiple pathways. Feature ranking based on support vector machines and matched genotype-phenotype pairs comprehensively reproduces current domain knowledge. Moreover, it indicates a prominent role of novel mutations in determining phenotypic resistance and in resensitization effects. These effects may be exploited deliberately to reopen lost treatment options. Together, these findings provide valuable insight into the interpretation of genotypic resistance tests

Genotypic tropism testing by massively parallel sequencing: qualitative and quantitative analysis

<p>Abstract</p> <p>Background</p> <p>Inferring viral tropism from genotype is a fast and inexpensive alternative to phenotypic testing. While being highly predictive when performed on clonal samples, sensitivity of predicting CXCR4-using (X4) variants drops substantially in clinical isolates. This is mainly attributed to minor variants not detected by standard bulk-sequencing. Massively parallel sequencing (MPS) detects single clones thereby being much more sensitive. Using this technology we wanted to improve genotypic prediction of coreceptor usage.</p> <p>Methods</p> <p>Plasma samples from 55 antiretroviral-treated patients tested for coreceptor usage with the Monogram Trofile Assay were sequenced with standard population-based approaches. Fourteen of these samples were selected for further analysis with MPS. Tropism was predicted from each sequence with geno2pheno_[coreceptor].</p> <p>Results</p> <p>Prediction based on bulk-sequencing yielded 59.1% sensitivity and 90.9% specificity compared to the trofile assay. With MPS, 7600 reads were generated on average per isolate. Minorities of sequences with high confidence in CXCR4-usage were found in all samples, irrespective of phenotype. When using the default false-positive-rate of geno2pheno_[coreceptor](10%), and defining a minority cutoff of 5%, the results were concordant in all but one isolate.</p> <p>Conclusions</p> <p>The combination of MPS and coreceptor usage prediction results in a fast and accurate alternative to phenotypic assays. The detection of X4-viruses in all isolates suggests that coreceptor usage as well as fitness of minorities is important for therapy outcome. The high sensitivity of this technology in combination with a quantitative description of the viral population may allow implementing meaningful cutoffs for predicting response to CCR5-antagonists in the presence of X4-minorities.</p

Characterization of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection clusters based on integrated genomic surveillance, outbreak analysis and contact tracing in an urban setting

BACKGROUND: Tracing of SARS-CoV-2 transmission chains is still a major challenge for public health authorities, when incidental contacts are not recalled or are not perceived as potential risk contacts. Viral sequencing can address key questions about SARS-CoV-2 evolution and may support reconstruction of viral transmission networks by integration of molecular epidemiology into classical contact tracing. METHODS: In collaboration with local public health authorities, we set up an integrated system of genomic surveillance in an urban setting, combining a) viral surveillance sequencing, b) genetically based identification of infection clusters in the population, c) integration of public health authority contact tracing data, and d) a user-friendly dashboard application as a central data analysis platform. RESULTS: Application of the integrated system from August to December 2020 enabled a characterization of viral population structure, analysis of four outbreaks at a maximum care hospital, and genetically based identification of five putative population infection clusters, all of which were confirmed by contact tracing. The system contributed to the development of improved hospital infection control and prevention measures and enabled the identification of previously unrecognized transmission chains, involving a martial arts gym and establishing a link between the hospital to the local population. CONCLUSIONS: Integrated systems of genomic surveillance could contribute to the monitoring and, potentially, improved management of SARS-CoV-2 transmission in the population

The XTrack system: application and advantage

XTrack, a rapid, cost-effective diagnostic HIV tropism system, yields predictive results and dissects virus mixtures. It is based on the duplexing of patient samples with selective DNA probes, combined with sequence-based analysis and replicative phenotyping for ambiguous samples

In-depth analysis of G-to-A hypermutation rate in HIV-1 env DNA induced by endogenous APOBEC3 proteins using massively parallel sequencing

Some APOBEC3 proteins cause G-to-A hypermutation in HIV-1 DNA when the accessory viral protein Vif is absent or non-functional. So far, cloning and sequencing has been performed to study G-to-A hypermutation. This is time-consuming and labour-intensive especially in the context of in vivo investigations where the number of hypermutated sequences can be very low. Thus, a massively parallel sequencing protocol has been developed for in-depth analysis of G-to-A hypermutation using the 454 pyrosequencing FLX system. Part of HIV-1 env was amplified and pyrosequenced after two rounds of infection in T cell lines and PBMCs using HIV-1 NL4-3Δvif. Specific criteria were applied to cope with major technical challenges: (1) the inclusion of hypermutated sequences, (2) the high genome diversity of HIV-1 env, and (3) the exclusion of sequences containing frameshift errors caused by pyrosequencing. In total, more than 140,000 sequences were obtained. 1.3-6.5% of guanines were mutated to adenine, most frequently in the GG dinucleotide context, the preferred deamination site of APOBEC3G. Non-G-to-A mutations occurred only in low frequencies (<0.6%). Single hypermutated sequences contained up to 24 G-to-A mutations. Overall, massively parallel sequencing is a very useful tool for in-depth analysis of G-to-A hypermutation in HIV-1 DNA induced by APOBEC3 proteins