172 research outputs found

    Analysis of a small outbreak of Shiga toxin-producing Escherichia coli O157:H7 using long-read sequencing

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    Compared to short-read sequencing data, long-read sequencing facilitates single contiguous de novo assemblies and characterization of the prophage region of the genome. Here, we describe our methodological approach to using Oxford Nanopore Technology (ONT) sequencing data to quantify genetic relatedness and to look for microevolutionary events in the core and accessory genomes to assess the within-outbreak variation of four genetically and epidemiologically linked isolates. Analysis of both Illumina and ONT sequencing data detected one SNP between the four sequences of the outbreak isolates. The variant calling procedure highlighted the importance of masking homologous sequences in the reference genome regardless of the sequencing technology used. Variant calling also highlighted the systemic errors in ONT base-calling and ambiguous mapping of Illumina reads that results in variations in the genetic distance when comparing one technology to the other. The prophage component of the outbreak strain was analysed, and nine of the 16 prophages showed some similarity to the prophage in the Sakai reference genome, including the stx2a-encoding phage. Prophage comparison between the outbreak isolates identified minor genome rearrangements in one of the isolates, including an inversion and a deletion event. The ability to characterize the accessory genome in this way is the first step to understanding the significance of these microevolutionary events and their impact on the evolutionary history, virulence and potentially the likely source and transmission of this zoonotic, foodborne pathogen

    Acquisition and loss of CTX-M plasmids in Shigella species associated with MSM transmission in the UK

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    Shigellosis in men who have sex with men (MSM) is caused by multidrug resistant Shigellae, exhibiting resistance to antimicrobials including azithromycin, ciprofloxacin and more recently the third-generation cephalosporins. We sequenced four bla (CTX-M-27)-positive MSM Shigella isolates (2018–20) using Oxford Nanopore Technologies; three S. sonnei (identified as two MSM clade 2, one MSM clade 5) and one S. flexneri 3a, to explore AMR context. All S. sonnei isolates harboured Tn7/Int2 chromosomal integrons, whereas S. flexneri 3a contained the Shigella Resistance Locus. All strains harboured IncFII pKSR100-like plasmids (67-83kbp); where present bla (CTX-M-27) was located on these plasmids flanked by IS26 and IS903B, however bla (CTX-M-27) was lost in S. flexneri 3a during storage between Illumina and Nanopore sequencing. IncFII AMR regions were mosaic and likely reorganised by IS26; three of the four plasmids contained azithromycin-resistance genes erm(B) and mph(A) and one harboured the pKSR100 integron. Additionally, all S. sonnei isolates possessed a large IncB/O/K/Z plasmid, two of which carried aph(3’)-Ib/aph(6)-Id/sul2 and tet(A). Monitoring the transmission of mobile genetic elements with co-located AMR determinants is necessary to inform empirical treatment guidance and clinical management of MSM-associated shigellosis

    Indoor bacterial and fungal aerosols as predictors of lower respiratory tract infections among under-five children in Ibadan, Nigeria

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    Background: This study aimed to investigate the association between exposure to diverse indoor microbial aerosols and lower respiratory tract infections (LRTI) among children aged 1 to 59 months in Ibadan, Nigeria. Methods: One hundred and seventy-eight (178) hospital-based LRTI cases among under-five children were matched for age (± 3 months), sex and geographical location with 180 community-based controls (under-five children without LRTI). Following consent from caregivers of eligible participants, a child’s health questionnaire, clinical proforma and standardized home-walkthrough checklist were used to collect data. Participant homes were visited and sampled for indoor microbial exposures using active sampling approach by Anderson sampler. Indoor microbial count (IMC), total bacterial count (TBC), and total fungal count (TFC) were estimated and dichotomized into high (> median) and low (≤ median) exposures. Alpha diversity measures including richness (R), Shannon (H) and Simpson (D) indices were also estimated. Conditional logistic regression models were used to test association between exposure to indoor microbial aerosols and LRTI risk among under-five children. Results: Significantly higher bacterial and fungal diversities were found in homes of cases (R = 3.00; H = 1.04; D = 2.67 and R = 2.56; H = 0.82; D = 2.33) than homes of controls (R = 2.00; H = 0.64; D = 1.80 and R = 1.89; H = 0.55; D = 1.88) p < 0.001, respectively. In the multivariate models, higher categories of exposure to IMC (aOR = 2.67, 95% CI 1.44–4.97), TBC (aOR = 2.51, 95% CI 1.36–4.65), TFC (aOR = 2.75, 95% CI 1.54–4.89), bacterial diversity (aOR = 1.87, 95% CI 1.08–3.24) and fungal diversity (aOR = 3.00, 95% CI 1.55–5.79) were independently associated with LRTI risk among under-five children. Conclusions: This study suggests an increased risk of LRTI when children under the age of five years are exposed to high levels of indoor microbial aerosols

    Green space, air pollution, traffic noise and mental wellbeing throughout adolescence: Findings from the PIAMA study

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    BACKGROUND: Green space, air pollution and traffic noise exposure may be associated with mental health in adolescents. We assessed the associations of long-term exposure to residential green space, ambient air pollution and traffic noise with mental wellbeing from age 11 to 20 years. METHODS: We included 3059 participants of the Dutch PIAMA birth cohort who completed the five-item Mental Health Inventory (MHI-5) at ages 11, 14, 17 and/or 20 years. We estimated exposure to green space (the average Normalized Difference Vegetation Index (NDVI) and percentages of green space in circular buffers of 300 m, 1000 m and 3000 m), ambient air pollution (particulate matter (PM10 and PM2.5), nitrogen dioxide, PM2.5 absorbance and the oxidative potential of PM2.5) and road traffic and railway noise (Lden) at the adolescents' home addresses at the times of completing the MHI-5. Associations with poor mental wellbeing (MHI-5 score ≤ 60) were assessed by generalized linear mixed models with a logit link, adjusting for covariates. RESULTS: The odds of poor mental wellbeing at age 11 to 20 years decreased with increasing exposure to green space in a 3000 m buffer (adjusted odds ratio (OR) 0.78 [95% CI 0.68-0.88] per IQR increase in the average NDVI; adjusted OR 0.77 [95% CI 0.67-0.88] per IQR increase in the total percentage of green space). These associations persisted after adjustment for air pollution and road traffic noise. Relationships between mental wellbeing and green space in buffers of 300 m and 1000 m were less consistent. Higher air pollution exposure was associated with higher odds of poor mental wellbeing, but these associations were strongly attenuated after adjustment for green space in a buffer of 3000 m, traffic noise and degree of urbanization. Traffic noise was not related to mental wellbeing throughout adolescence. CONCLUSIONS: Residential exposure to green space may be associated with a better mental wellbeing in adolescents

    Emergence of novel strains of Shigella flexneri associated with sexual transmission in adult men in England, 2019-2020.

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    National surveillance of shigellosis in England revealed an increase in sexually transmitted Shigella flexneri in adult males in 2019 that persisted throughout 2020. We observed a resurgence of azithromycin-resistant S. flexneri serotype 3a, and the emergence of two novel multidrug-resistant clades of S. flexneri 2a and S. flexneri 1b

    A statistical modelling approach for source attribution meta-analysis of sporadic infection with foodborne pathogens

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    Numerous source attribution studies for foodborne pathogens based on epidemiological and microbiological methods are available. These studies provide empirical data for modelling frameworks that synthetize the quantitative evidence at our disposal and reduce reliance on expert elicitations. Here, we develop a statistical model within a Bayesian estimation framework to integrate attribution estimates from expert elicitations with estimates from microbial subtyping and case-control studies for sporadic infections with four major bacterial zoonotic pathogens in the Netherlands (Campylobacter, Salmonella, Shiga toxin-producing E. coli [STEC] O157 and Listeria). For each pathogen, we pooled the published fractions of human cases attributable to each animal reservoir from the microbial subtyping studies, accounting for the uncertainty arising from the different typing methods, attribution models, and year(s) of data collection. We then combined the population attributable fractions (PAFs) from the case-control studies according to five transmission pathways (domestic food, environment, direct animal contact, human-human transmission and travel) and 11 groups within the foodborne pathway (beef/lamb, pork, poultry meat, eggs, dairy, fish/shellfish, fruit/vegetables, beverages, grains, composite foods and food handlers/vermin). The attribution estimates were biologically plausible, allowing the human cases to be attributed in several ways according to reservoirs, transmission pathways and food groups. All pathogens were predominantly foodborne, with Campylobacter being mostly attributable to the chicken reservoir, Salmonella to pigs (albeit closely followed by layers), and Listeria and STEC O157 to cattle. Food-wise, the attributions reflected those at the reservoir level in terms of ranking. We provided a modelling solution to reach consensus attribution estimates reflecting the empirical evidence in the literature that is particularly useful for policy-making and is extensible to other pathogens and domains

    Optimization of bacterial DNA and endotoxin extraction from settled airborne dust

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    Collecting and obtaining sufficient amount of airborne particles for multiple microbial component assessments can be challenging. A passive dust sampling device, the electrostatic dust fall collector (EDC) has been established for assessing airborne exposures including endotoxin and glucans. Recently, with advances in next-generation sequencing techniques, EDCs were used to collect microbial cells for DNA sequencing analysis to promote the study of airborne bacterial and fungal communities. However, low DNA yields have been problematic when employing passive sampling with EDC. To address this challenge, we attempted to increase the efficiency of extraction. We compared DNA extraction efficiency of bacterial components from EDCs captured on filters through filtration using five extraction techniques. By measuring the abundance, diversity and structure of bacterial communities using qPCR and amplicon sequencing targeting 16S rRNA genes, we found that two techniques outperformed the rest. Furthermore, we developed protocols to simultaneously extract both DNA and endotoxin from a single EDC cloth. Our technique promotes a high quality to price ratio and may be employed in large epidemiological studies addressing airborne bacterial exposure where a large number of samples is needed

    Accessory Genome Dynamics and Structural Variation of Shigella from Persistent Infections

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    Shigellosis is a diarrheal disease caused mainly by Shigella flexneri and Shigella sonnei Infection is thought to be largely self-limiting, with short- to medium-term and serotype-specific immunity provided following clearance. However, cases of men who have sex with men (MSM)-associated shigellosis have been reported where Shigella of the same serotype were serially sampled from individuals between 1 and 1,862 days apart, possibly due to persistent carriage or reinfection with the same serotype. Here, we investigate the accessory genome dynamics of MSM-associated S. flexneri and S. sonnei isolates serially sampled from individual patients at various days apart to shed light on the adaptation of these important pathogens during infection. We find that pairs likely associated with persistent infection/carriage and with a smaller single nucleotide polymorphism (SNP) distance, demonstrated significantly less variation in accessory genome content than pairs likely associated with reinfection, and with a greater SNP distance. We observed antimicrobial resistance acquisition during Shigella carriage, including the gain of an extended-spectrum beta-lactamase gene during carriage. Finally, we explored large chromosomal structural variations and rearrangements in seven (five chronic and two reinfection associated) pairs of S. flexneri 3a isolates from an MSM-associated epidemic sublineage, which revealed variations at several common regions across isolate pairs, mediated by insertion sequence elements and comprising a distinct predicted functional profile. This study provides insight on the variation of accessory genome dynamics and large structural genomic changes in Shigella during persistent infection/carriage. In addition, we have also created a complete reference genome and biobanked isolate of the globally important pathogen, S. flexneri 3a.IMPORTANCE Shigella spp. are Gram-negative bacteria that are the etiological agent of shigellosis, the second most common cause of diarrheal illness among children under the age of five in low-income countries. In high-income countries, shigellosis is also a sexually transmissible disease among men who have sex with men. Within the latter setting, we have captured prolonged and/or recurrent infection with shigellae of the same serotype, challenging the belief that Shigella infection is short lived and providing an early opportunity to study the evolution of the pathogen over the course of infection. Using this recently emerged transmission scenario, we comprehensively characterize the genomic changes that occur over the course of individual infection with Shigella and uncover a distinct functional profile of variable genomic regions, findings that have relevance for other Enterobacteriaceae

    Residential exposure to livestock farms and lung function in adolescence - The PIAMA birth cohort study

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    Background: There is a growing interest in the impact of air pollution from livestock farming on respiratory health. Studies in adults suggest adverse effects of livestock farm emissions on lung function, but so far, studies involving children and adolescents are lacking. Objectives: To study the association of residential proximity to livestock farms and modelled particulate matter ≤10 μm (PM10) from livestock farms with lung function in adolescence. Methods: We performed a cross-sectional study among 715 participants of the Dutch prospective PIAMA (Prevention and Incidence of Asthma and Mite Allergy) birth cohort study. Relationships of different indicators of residential livestock farming exposure (distance to farms, distance-weighted number of farms, cattle, pigs, poultry, horses and goats within 3 km; modelled atmospheric PM10 concentrations from livestock farms) with forced expiratory volume in 1 s (FEV1) and forced vital capacity (FVC) at age 16 were assessed by linear regression taking into account potential confounders. Associations were expressed per interquartile range increase in exposure. Results: Higher exposure to livestock farming was consistently associated with a lower FEV1, but not with FVC among participants living in less urbanized municipalities (<1500 addresses/km2, N = 402). Shorter distances of homes to livestock farms were associated with a 1.4% (0.2%; 2.7%) lower FEV1. Larger numbers of farms within 3 km and higher concentrations of PM10 from livestock farming were associated with a 1.8% (0.8%, 2.9%) and 0.9% (0.4%,1.5%) lower FEV1, respectively. Conclusions: Our findings suggest that higher exposure to livestock farming is associated with a lower FEV1 in adolescents. Replication and more research on the etiologic agents involved in these associations and the underlying mechanisms is needed

    Phylodynamics of Highly Pathogenic Avian Influenza A(H5N1) Virus Circulating in Indonesian Poultry

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    After its first detection in 1996, the highly pathogenic avian influenza A(H5Nx) virus has spread extensively worldwide. HPAIv A(H5N1) was first detected in Indonesia in 2003 and has been endemic in poultry in this country ever since. However, Indonesia has limited information related to the phylodynamics of HPAIv A(H5N1) in poultry. The present study aimed to increase the understanding of the evolution and temporal dynamics of HPAIv H5N1 in Indonesian poultry between 2003 and 2016. To this end, HPAIv A(H5N1) hemagglutinin sequences of viruses collected from 2003 to 2016 were analyzed using Bayesian evolutionary analysis sampling trees. Results indicated that the common ancestor of Indonesian poultry HPAIv H5N1 arose approximately five years after the common ancestor worldwide of HPAI A(H5Nx). In addition, this study indicated that only two introductions of HPAIv A(H5N1) occurred, after which these viruses continued to evolve due to extensive spread among poultry. Furthermore, this study revealed the divergence of H5N1 clade 2.3.2.1c from H5N1 clade 2.3.2.1b. Both clades 2.3.2.1c and 2.3.2.1b share a common ancestor, clade 1, suggesting that clade 2.3.2.1 originated and diverged from China and other Asian countries. Since there was limited sequence and surveillance data for the HPAIv A(H5N1) from wild birds in Indonesia, the exact role of wild birds in the spread of HPAIv in Indonesia is currently unknown. The evolutionary dynamics of the Indonesian HPAIv A(H5N1) highlight the importance of continuing and improved genomic surveillance and adequate control measures in the different regions of both the poultry and wild birds. Spatial genomic surveillance is useful to take adequate control measures. Therefore, it will help to prevent the future evolution of HPAI A(H5N1) and pandemic threats
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