A first assessment of the genetic diversity of Mycobacterium tuberculosis complex in Cambodia

<p>Abstract</p> <p>Background</p> <p>Cambodia is among the 22 high-burden TB countries, and has one of the highest rates of TB in South-East Asia. This study aimed to describe the genetic diversity among clinical <it>Mycobacterium tuberculosis </it>complex (MTC) isolates collected in Cambodia and to relate these findings to genetic diversity data from neighboring countries.</p> <p>Methods</p> <p>We characterized by 24 VNTR loci genotyping and spoligotyping 105 <it>Mycobacterium tuberculosis </it>clinical isolates collected between 2007 and 2008 in the region of Phnom-Penh, Cambodia, enriched in multidrug-resistant (MDR) isolates (n = 33).</p> <p>Results</p> <p>Classical spoligotyping confirmed that the East-African Indian (EAI) lineage is highly prevalent in this area (60%-68% respectively in whole sample and among non-MDR isolates). Beijing lineage is also largely represented (30% in whole sample, 21% among non-MDR isolates, OR = 4.51, CI_95%[1.77, 11.51]) whereas CAS lineage was absent. The 24 loci MIRU-VNTR typing scheme distinguished 90 patterns with only 13 multi-isolates clusters covering 28 isolates. The clustering of EAI strains could be achieved with only 8 VNTR combined with spoligotyping, which could serve as a performing, easy and cheap genotyping standard for this family. Extended spoligotyping suggested relatedness of some unclassified "T1 ancestors" or "Manu" isolates with modern strains and provided finer resolution.</p> <p>Conclusions</p> <p>The genetic diversity of MTC in Cambodia is driven by the EAI and the Beijing families. We validate the usefulness of the extended spoligotyping format in combination with 8 VNTR for EAI isolates in this region.</p

Strongyloides stercoralis seroprevalence in Vietnam

Strongyloidiasis is a neglected tropical disease caused by the roundworm Strongyloides stercoralis affecting 30-100 million people worldwide. Many Southeast-Asian countries report a high prevalence of S. stercoralis infection but there is little data from Vietnam. Here, we evaluated the seroprevalence of S. stercoralis related to geography, sex and age in Vietnam through serological testing of anonymized sera. Sera (n = 1710, 1340 adults and 270 children) from an anonymized age stratified serum bank from 4 regions in Vietnam between 2012 and 2013 were tested using a commercial Strongyloides ratti IgG ELISA. Seroreactivity was found in 29.1% (390/1340) of adults and 5.5% (15/270) of children. Male adults were more frequently seroreactive than females (33.3% vs 24.9%, p=0.001). The rural central highlands had the highest seroprevalence (42.4% of adults). Seroreactivity in the other regions was 29.9% (Hue) and 26.0% and 18.2% in the large urban centres of Hanoi and Ho Chi Minh City, respectively. We conclude that seroprevalence of S. stercoralis was high in the Vietnamese adult population, especially in rural areas

Strongyloides stercoralis seroprevalence in Vietnam

Strongyloidiasis is a neglected tropical disease caused by the roundworm Strongyloides stercoralis affecting 30-100 million people worldwide. Many Southeast-Asian countries report a high prevalence of S. stercoralis infection but there is little data from Vietnam. Here, we evaluated the seroprevalence of S. stercoralis related to geography, sex and age in Vietnam through serological testing of anonymized sera. Sera (n = 1710, 1340 adults and 270 children) from an anonymized age stratified serum bank from 4 regions in Vietnam between 2012 and 2013 were tested using a commercial Strongyloides ratti IgG ELISA. Seroreactivity was found in 29.1% (390/1340) of adults and 5.5% (15/270) of children. Male adults were more frequently seroreactive than females (33.3% vs 24.9%, p=0.001). The rural central highlands had the highest seroprevalence (42.4% of adults). Seroreactivity in the other regions was 29.9% (Hue) and 26.0% and 18.2% in the large urban centres of Hanoi and Ho Chi Minh City, respectively. We conclude that seroprevalence of S. stercoralis was high in the Vietnamese adult population, especially in rural areas

Pathogenic Escherichia coli possess elevated growth rates under exposure to sub-inhibitory concentrations of azithromycin

Antimicrobial resistance (AMR) has been identified by the World Health Organization (WHO) as one of the ten major threats to global health. Advances in technology, including whole-genome sequencing, have provided new insights into the origin and mechanisms of AMR. However, our understanding of the short-term impact of antimicrobial pressure and resistance on the physiology of bacterial populations is limited. We aimed to investigate morphological and physiological responses of clinical isolates of &lt;i&gt;E. coli&lt;/i&gt; under short-term exposure to key antimicrobials. We performed whole-genome sequencing on twenty-seven &lt;i&gt;E. coli&lt;/i&gt; isolates isolated from children with sepsis to evaluate their AMR gene content. We assessed their antimicrobial susceptibility profile and measured their growth dynamics and morphological characteristics under exposure to varying concentrations of ciprofloxacin, ceftriaxone, tetracycline, gentamicin, and azithromycin. AMR was common, with all organisms resistant to at least one antimicrobial; a total of 81.5% were multi-drug-resistant (MDR). We observed an association between resistance profile and morphological characteristics of the &lt;i&gt;E. coli&lt;/i&gt; over a three-hour exposure to antimicrobials. Growth dynamics experiments demonstrated that resistance to tetracycline promoted the growth of &lt;i&gt;E. coli&lt;/i&gt; under antimicrobial-free conditions, while resistance to the other antimicrobials incurred a fitness cost. Notably, antimicrobial exposure heterogeneously suppressed bacterial growth, but sub-MIC concentrations of azithromycin increased the maximum growth rate of the clinical isolates. Our results outline complex interactions between organism and antimicrobials and raise clinical concerns regarding exposure of sub-MIC concentrations of specific antimicrobials

Age-seroprevalence curves for the multi-strain structure of influenza A virus

The relationship between age and seroprevalence can be used to estimate the annual attack rate of an infectious disease. For pathogens with multiple serologically distinct strains, there is a need to describe composite exposure to an antigenically variable group of pathogens. In this study, we assay 24,402 general-population serum samples, collected in Vietnam between 2009 to 2015, for antibodies to eleven human influenza A strains. We report that a principal components decomposition of antibody titer data gives the first principal component as an appropriate surrogate for seroprevalence; this results in annual attack rate estimates of 25.6% (95% CI: 24.1% - 27.1%) for subtype H3 and 16.0% (95% CI: 14.7% - 17.3%) for subtype H1. The remaining principal components separate the strains by serological similarity and associate birth cohorts with their particular influenza histories. Our work shows that dimensionality reduction can be used on human antibody profiles to construct an age-seroprevalence relationship for antigenically variable pathogens

Structure of general-population antibody titer distributions to influenza A virus

Seroepidemiological studies aim to understand population-level exposure and immunity to infectious diseases. Their results are normally presented as binary outcomes describing the presence or absence of pathogen-specific antibody, despite the fact that many assays measure continuous quantities. A population's natural distribution of antibody titers to an endemic infectious disease may include information on multiple serological states - naiveté, recent infection, non-recent infection, childhood infection - depending on the disease in question and the acquisition and waning patterns of immunity. In this study, we investigate 20,152 general-population serum samples from southern Vietnam collected between 2009 and 2013 from which we report antibody titers to the influenza virus HA1 protein using a continuous titer measurement from a protein microarray assay. We describe the distributions of antibody titers to subtypes 2009 H1N1 and H3N2. Using a model selection approach to fit mixture distributions, we show that 2009 H1N1 antibody titers fall into four titer subgroups and that H3N2 titers fall into three subgroups. For H1N1, our interpretation is that the two highest-titer subgroups correspond to recent and historical infection, which is consistent with 2009 pandemic attack rates. Similar interpretations are available for H3N2, but right-censoring of titers makes these interpretations difficult to validate