ABSTRACT
Clinical infection by hepatitis A virus (HAV) is generally self-limited but in some cases can progress to liver failure. Here, an HAV outbreak investigation among children with acute liver failure in a highly endemic country is presented. In addition, a sensitive method for HAV whole genome amplification and sequencing suitable for analysis of clinical samples is described. In this setting, two fatal cases attributed to acute liver failure and two asymptomatic cases living in the same household were identified. In a second household, one HAV case was observed with jaundice which resolved spontaneously. Partial molecular characterization showed that both households were infected by HAV subtype IA; however, the infecting strains in the two households were different. The HAV outbreak strains recovered from all cases grouped together within cluster IA1, which contains closely related HAV strains from the United States commonly associated with international travelers. Full-genome HAV sequences obtained from the household with the acute liver failure cases were related (genetic distances ranging from 0.01% to 0.04%), indicating a common-source infection. Interestingly, the strain recovered from the asymptomatic household contact was nearly identical to the strain causing acute liver failure. The whole genome sequence from the case in the second household was distinctly different from the strains associated with acute liver failure. Thus, infection with almost identical HAV strains resulted in drastically different clinical outcomes.
Subject(s)
Disease Outbreaks , Genome, Viral , Hepatitis A virus/genetics , Hepatitis A/complications , Hepatitis A/epidemiology , Liver Failure, Acute/epidemiology , Adolescent , Child , Cluster Analysis , Female , Hepatitis A/pathology , Hepatitis A/virology , Hepatitis A virus/isolation & purification , Humans , Liver Failure, Acute/pathology , Liver Failure, Acute/virology , Male , Molecular Sequence Data , Phylogeny , RNA, Viral/genetics , Sequence Analysis, DNA , United StatesABSTRACT
Hepatitis C virus (HCV) is a major public health problem that affects more than 180 million people worldwide. Identification of HCV transmission networks is of critical importance for disease control. HCV related cases are often difficult to identify due to the characteristic long incubation period and lack of symptoms during the acute phase of the disease, making it challenging to link related cases to a common source of infection. Additionally, HCV transmission chains are difficult to trace back since viral variants from epidemiologically linked cases are genetically related but rarely identical. Genetic relatedness studies primarily rely on information obtained from the rapidly evolving HCV hypervariable region 1 (HVR1). However, in some instances, the rapid divergence of this region can lead to loss of genetic links between related isolates, which represents an important challenge for outbreak investigations and genetic relatedness studies. Sequencing of multiple and longer sub-genomic regions has been proposed as an alternative to overcome the limitations imposed by the rapid molecular evolution of the HCV HVR1. Additionally, conventional molecular approaches required to characterize the HCV intra-host genetic variation are laborious, time-consuming, and expensive while providing limited information about the composition of the viral population. Next generation sequencing (NGS) approaches enormously facilitate the characterization of the HCV intra-host population by detecting rare variants at much lower frequencies. Thus, NGS approaches using multiple sub-genomic regions should improve the characterization of the HCV intra-host population. Here, we explore the usefulness of multiregion sequencing using a NGS platform for genetic relatedness studies among HCV cases.
Subject(s)
Hepacivirus/genetics , Hepatitis C/virology , High-Throughput Nucleotide Sequencing , Multilocus Sequence Typing , Adult , Evolution, Molecular , Female , Genotype , Hepacivirus/classification , Hepatitis C/epidemiology , Humans , Male , Middle Aged , Phylogeny , Viral Load , Viral Nonstructural Proteins/geneticsABSTRACT
Here, we describe the molecular characterization of six human Mycobacterium bovis clinical isolates, including three multidrug resistant (MDR) strains, collected in Mexico through the National Survey on Tuberculosis Drug Resistance (ENTB-2008), a nationally representative survey conducted during 2008-2009 in nine states with a stratified cluster sampling design. The genetic background of bovine M. bovis strains identified in three different states of Mexico was studied in parallel to assess molecular relatedness of bovine and human strains. Additionally, resistance to first and second line anti-tuberculosis (TB) drugs and molecular identification of mutations conferring drug resistance was also performed. All strains were characterized by spoligotyping and 24-loci MIRU-VNTRs, and analyzed using the SITVIT2 (n = 112,000 strains) and SITVITBovis (n = 25,000 strains) proprietary databases of Institut Pasteur de la Guadeloupe. Furthermore, data from this study (n = 55 isolates), were also compared with genotypes recorded for M. bovis from USA (n = 203), Argentina (n = 726), as well as other isolates from Mexico (independent from the present study; n = 147), to determine any evidence for genetic relatedness between circulating M. bovis strains. The results showed that all human M. bovis cases were not genetically related between them or to any bovine strain. Interestingly, a high degree of genetic variability was observed among bovine strains. Several autochthonous and presumably imported strains were identified. The emergence of drug-resistant M. bovis is an important public health problem that jeopardizes the success of TB control programs in the region.
Subject(s)
Drug Resistance, Multiple, Bacterial/genetics , Mutation , Mycobacterium bovis/genetics , Tuberculosis, Multidrug-Resistant/microbiology , Tuberculosis, Pulmonary/microbiology , Antitubercular Agents/therapeutic use , Databases, Genetic , Genotype , Humans , Mexico/epidemiology , Microbial Sensitivity Tests , Minisatellite Repeats , Molecular Diagnostic Techniques , Mycobacterium bovis/drug effects , Mycobacterium bovis/isolation & purification , Phenotype , Phylogeny , Predictive Value of Tests , Sputum/microbiology , Tuberculosis, Multidrug-Resistant/diagnosis , Tuberculosis, Multidrug-Resistant/drug therapy , Tuberculosis, Multidrug-Resistant/epidemiology , Tuberculosis, Multidrug-Resistant/transmission , Tuberculosis, Pulmonary/diagnosis , Tuberculosis, Pulmonary/drug therapy , Tuberculosis, Pulmonary/epidemiology , Tuberculosis, Pulmonary/transmissionABSTRACT
Infection with hepatitis A virus (HAV) is the commonest viral cause of liver disease and presents an important public health problem worldwide. Several unique HAV properties and molecular mechanisms of its interaction with host were recently discovered and should aid in clarifying the pathogenesis of hepatitis A. Genetic characterization of HAV strains have resulted in the identification of different genotypes and subtypes, which exhibit a characteristic worldwide distribution. Shifts in HAV endemicity occurring in different parts of the world, introduction of genetically diverse strains from geographically distant regions, genotype displacement observed in some countries and population expansion detected in the last decades of the 20th century using phylogenetic analysis are important factors contributing to the complex dynamics of HAV infections worldwide. Strong selection pressures, some of which, like usage of deoptimized codons, are unique to HAV, limit genetic variability of the virus. Analysis of subgenomic regions has been proven useful for outbreak investigations. However, sharing short sequences among epidemiologically unrelated strains indicates that specific identification of HAV strains for molecular surveillance can be achieved only using whole-genome sequences. Here, we present up-to-date information on the HAV molecular epidemiology and evolution, and highlight the most relevant features of the HAV-host interactions.