Hepatitis C virus (HCV) infection represents an important public health problem worldwide. Reduction of HCV morbidity and mortality is a current challenge owned to several viral and host factors. Virus molecular evolution plays an important role in HCV transmission, disease progression and therapy outcome. The high degree of genetic heterogeneity characteristic of HCV is a key element for the rapid adaptation of the intrahost viral population to different selection pressures (e.g., host immune responses and antiviral therapy). HCV molecular evolution is shaped by different mechanisms including a high mutation rate, genetic bottlenecks, genetic drift, recombination, temporal variations and compartmentalization. These evolutionary processes constantly rearrange the composition of the HCV intrahost population in a staging manner. Remarkable advances in the understanding of the molecular mechanism controlling HCV replication have facilitated the development of a plethora of direct-acting antiviral agents against HCV. As a result, superior sustained viral responses have been attained. The rapidly evolving field of anti-HCV therapy is expected to broad its landscape even further with newer, more potent antivirals, bringing us one step closer to the interferon-free era.

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Background Whole genome sequencing (WGS) has been proposed as a tool for diagnosing drug resistance in tuberculosis. However, reports of its effectiveness in endemic countries with important numbers of drug resistance are scarce. The goal of this study was to evaluate the effectiveness of this procedure in isolates from a tuberculosis endemic region in Mexico. Methods WGS analysis was performed in 81 tuberculosis positive clinical isolates with a known phenotypic profile of resistance against first-line drugs (isoniazid, rifampin, ethambutol, pyrazinamide and streptomycin). Mutations related to drug resistance were identified for each isolate; drug resistant genotypes were predicted and compared with the phenotypic profile. Genotypes and transmission clusters based on genetic distances were also characterized. Findings Prediction by WGS analysis of resistance against isoniazid, rifampicin, ethambutol, pyrazinamide and streptomycin showed sensitivity values of 84%, 96%, 71%, 75% and 29%, while specificity values were 100%, 94%, 90%, 90% and 98%, respectively. Prediction of multidrug resistance showed a sensitivity of 89% and specificity of 97%. Moreover, WGS analysis revealed polymorphisms related to second-line drug resistance, enabling classification of eight and two clinical isolates as pre- and extreme drug-resistant cases, respectively. Lastly, four lineages were identified in the population (L1, L2, L3 and L4). The most frequent of these was L4, which included 90% (77) of the isolates. Six transmission clusters were identified; the most frequent was TC6, which included 13 isolates with a L4.1.1 and a predominantly multidrug-resistant condition. Conclusions The results illustrate the utility of WGS for establishing the potential for prediction of resistance against first and second line drugs in isolates of tuberculosis from the region. They also demonstrate the feasibility of this procedure for use as a tool to support the epidemiological surveillance of drug- and multidrug-resistant tuberculosis.

Here, we analyze the viral divergence among hepatitis C virus (HCV) chronic cases infected with genotype 1. The intrahost viral evolution was assessed by deep sequencing using the 454 Genome Sequencer platform. The results showed a rapid nucleotide sequence divergence. This notorious short-term viral evolution is of the utmost importance for the study of HCV transmission, because direct links between related samples were virtually lost. Thus, rapid divergence of HCV significantly affects genetic relatedness studies and outbreak investigations.

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Globally, hepatitis C virus (HCV) infection affects approximately 130 million people and 3 million new infections occur annually. HCV is also recognized as an important cause of chronic liver disease in children. The absence of proofreading properties of the HCV RNA polymerase leads to a highly error prone replication process, allowing HCV to escape host immune response. The adaptive nature of HCV evolution dictates the outcome of the disease in many ways. Here, we investigated the molecular evolution of HCV in three unrelated children who acquired chronic HCV infection as a result of mother-to-child transmission, two of whom were also coinfected with HIV-1. The persistence of discrete HCV variants and their population structure were assessed using median joining network and Bayesian approaches. While patterns of viral evolution clearly differed between subjects, immune system dysfunction related to HIV coinfection or persistent HCV seronegativity stand as potential mechanisms to explain the lack of molecular evolution observed in these three cases. In contrast, treatment of HCV infection with PegIFN, which did not lead to sustained virologic responses in all 3 cases, was not associated with commensurate variations in the complexity of the variant spectrum. Finally, the differences in the degree of divergence suggest that the mode of transmission of the virus was not the main factor driving viral evolution.

Identifying the Mycobacterium tuberculosis resistance mutation patterns is of the utmost importance to assure proper patient’s management and devising of control programs aimed to limit spread of disease. Zoonotic Mycobacterium bovis infection still represents a threat to human health, particularly in dairy production regions. Routinary, molecular characterization of M. bovis is performed primarily by spoligotyping and mycobacterial interspersed repetitive units (MIRU) while next generation sequencing (NGS) approaches are often performed by reference laboratories. However, spoligotyping and MIRU methodologies lack the resolution required for the fine characterization of tuberculosis isolates, particularly in outbreak settings. In conjunction with sophisticated bioinformatic algorithms, whole genome sequencing (WGS) analysis is becoming the method of choice for advanced genetic characterization of tuberculosis isolates. WGS provides valuable information on drug resistance and compensatory mutations that other technologies cannot assess. Here, we performed an analysis of the most frequently identified mutations associated with tuberculosis drug resistance and their genetic relationship among 2,074 Mycobacterium bovis WGS recovered primarily from non-human hosts. Full-length gene sequences harboring drug resistant associated mutations and their phylogenetic relationships were analyzed. The results showed that M. bovis isolates harbor mutations conferring resistance to both first- and second-line antibiotics. Mutations conferring resistance for isoniazid, fluoroquinolones, streptomycin, and aminoglycosides were identified among animal strains. Our findings highlight the importance of molecular surveillance to monitor the emergence of mutations associated with multi and extensive drug resistance in livestock and other non-human mammals.