Genome evolution of Salmonella enterica serovar Typhimurium

Salmonella enterica serovar Typhimurium (S. Typhimurium) is a food-borne pathogen which accounts for ~25 % of non-typhoidal Salmonella infections, usually through faecal-oral transmission. To maintain food safety and avoid unnecessary human and animal disease, understanding how pathogens such as S. Typhimurium evolve and their requirements for persistence is paramount. This study investigated genomic evolution of S. Typhimurium. First, a recently acquired novel genomic island was characterised that initiated successful clonal expansion of pandemic monophasic S. Typhimurium ST34, Salmonella genomic island 4 (SGI-4). SGI-4 was discovered to be self-transferable and enhance resistance to heavy metals. This was consistent with the epidemiology of monophasic S. Typhimurium ST34 strains as they are most frequently isolated from pigs and copper is used as a growth promoter in pig farming. Next, the phage sensitivity of S. Typhimurium lineages was investigated through associating phage sensitivity with whole genome sequence (WGS). DT193 that is characterised by resistance to all Anderson typing scheme phage preparations was the most frequent majority phage type, consistent with selection for phage resistance occurring many times throughout S. Typhimurium. The monophasic S. Typhimurium ST34 population was then investigated using large-scale WGS-based statistical analyses. A novel prophage termed mTmII was associated with continuation of the monophasic ST34 lineage and acquisition was accompanied by an increase in phage resistance. How phage predation shapes the evolution and persistence of S. Typhimurium pathovars in host animal niches was then investigated and a novel phenomenon enabling rapid resistance to phage predation through polymorphic gene variation discovered, including a base-specific deletion of serogroup B1 O-antigen polymerase encoding wzy, coupled with recombination mediated reversion of the locus in a mixed population of a single strain

Whole-genome epidemiology links phage-mediated acquisition of a virulence gene to the clonal expansion of a pandemic Salmonella enterica serovar Typhimurium clone

Epidemic and pandemic clones of bacterial pathogens with distinct characteristics continually emerge, replacing those previously dominant through mechanisms that remain poorly characterized. Here, whole-genome-sequencing-powered epidemiology linked horizontal transfer of a virulence gene, sopE, to the emergence and clonal expansion of a new epidemic Salmonella enterica serovar Typhimurium (S. Typhimurium) clone. The sopE gene is sporadically distributed within the genus Salmonella and rare in S. enterica Typhimurium lineages, but was acquired multiple times during clonal expansion of the currently dominant pandemic monophasic S. Typhimurium sequence type (ST) 34 clone. Ancestral state reconstruction and time-scaled phylogenetic analysis indicated that sopE was not present in the common ancestor of the epidemic clade, but later acquisition resulted in increased clonal expansion of sopE-containing clones that was temporally associated with emergence of the epidemic, consistent with increased fitness. The sopE gene was mainly associated with a temperate bacteriophage mTmV, but recombination with other bacteriophage and apparent horizontal gene transfer of the sopE gene cassette resulted in distribution among at least four mobile genetic elements within the monophasic S. enterica Typhimurium ST34 epidemic clade. The mTmV prophage lysogenic transfer to other S. enterica serovars in vitro was limited, but included the common pig-associated S. enterica Derby (S. Derby). This may explain mTmV in S. Derby co-circulating on farms with monophasic S. Typhimurium ST34, highlighting the potential for further transfer of the sopE virulence gene in nature. We conclude that whole-genome epidemiology pinpoints potential drivers of evolutionary and epidemiological dynamics during pathogen emergence, and identifies targets for subsequent research in epidemiology and bacterial pathogenesis

Increased phage resistance through lysogenic conversion accompanying emergence of monophasic Salmonella Typhimurium ST34 pandemic strain

Salmonella enterica serovar Typhimurium (S. Typhimurium) comprises a group of closely related human and animal pathogens that account for a large proportion of all Salmonella infections globally. The epidemiological record of S. Typhimurium in Europe is characterized by successive waves of dominant clones, each prevailing for approximately 10–15 years before replacement. Succession of epidemic clones may represent a moving target for interventions aimed at controlling the spread and impact of this pathogen on human and animal health. Here, we investigate the relationship of phage sensitivity and population structure of S. Typhimurium using data from the Anderson phage typing scheme. We observed greater resistance to phage predation of epidemic clones circulating in livestock over the past decades compared to variants with a restricted host range implicating increased resistance to phage in the emergence of epidemic clones of particular importance to human health. Emergence of monophasic S. Typhimurium ST34, the most recent dominant multidrug-resistant clone, was accompanied by increased resistance to phage predation during clonal expansion, in part by the acquisition of the mTmII prophage that may have contributed to the fitness of the strains that replaced ancestors lacking this prophage

Increased phage resistance through lysogenic conversion accompanying emergence of monophasic Salmonella Typhimurium ST34 pandemic strain

Salmonella enterica serovar Typhimurium ( S. Typhimurium) comprises a group of closely related human and animal pathogens that account for a large proportion of all Salmonella infections globally. The epidemiological record of S. Typhimurium in Europe is characterized by successive waves of dominant clones, each prevailing for approximately 10-15 years before replacement. Succession of epidemic clones may represent a moving target for interventions aimed at controlling the spread and impact of this pathogen on human and animal health. Here, we investigate the relationship of phage sensitivity and population structure of S. Typhimurium using data from the Anderson phage typing scheme. We observed greater resistance to phage predation of epidemic clones circulating in livestock over the past decades compared to variants with a restricted host range implicating increased resistance to phage in the emergence of epidemic clones of particular importance to human health. Emergence of monophasic S. Typhimurium ST34, the most recent dominant multidrug-resistant clone, was accompanied by increased resistance to phage predation during clonal expansion, in part by the acquisition of the mTmII prophage that may have contributed to the fitness of the strains that replaced ancestors lacking this prophage

Detection and characterization of ESBL-producing Escherichia coli from humans and poultry in Ghana

Introduction:; The increasing incidence of infections caused by extended-spectrum beta-lactamase (ESBL)-producing; Escherichia coli; in sub-Saharan Africa is of serious concern. Studies from countries with a highly industrialized poultry industry suggest the poultry production-food-consumer chain as a potential transmission route. In Africa, integrated studies at this human-animal interface are still missing.; Aim:; To determine the molecular epidemiology of ESBL-producing; E. coli; from the intestinal tract of humans and poultry in rural Ghana.; Methods:; During a 6-month period, fecal samples from all children admitted to the Agogo Hospital (Ghana) and broilers at eight poultry farms located within the hospital catchment area were collected. After screening on selective ESBL agar, whole genome sequencing (WGS) was performed on all ESBL isolates. The genomes were analyzed using multilocus sequence typing (MLST), ESBL genotyping and genome-based phylogenetic analyses.; Results:; Of 140 broilers and 54 children, 41 (29%) and 33 (61%) harbored ESBL; E. coli; , respectively, with prevalences on farms ranging between 0 and 85%. No predominant sequence type (ST) was detected among humans. ST10 was most prevalent among broilers (; n; = 31, 69%). The ESBL gene; bla; CTX-M-15; was predominant among broilers (; n; = 43, 96%) and humans (; n; = 32, 97%). Whole-genome-based phylogenetic analysis revealed three very closely related broiler/human isolate clusters (10% of ESBL isolates) with chromosomal and plasmid-mediated ESBL genes.; Conclusion:; The findings demonstrate a high frequency of intestinal ESBL-producing; E. coli; in rural Ghana. Considering that animal and human samples are independent specimens from the same geographic location, the number of closely related ESBL isolates circulating across these two reservoirs is substantial. Hence, poultry farms or meat products might be an important source for ESBL-producing bacteria in rural Ghana leading to difficult-to-treat infections in humans

Detection and Characterization of ESBL-Producing Escherichia coli From Humans and Poultry in Ghana

Introduction: The increasing incidence of infections caused by extended-spectrum beta-lactamase (ESBL)-producing Escherichia coli in sub-Saharan Africa is of serious concern. Studies from countries with a highly industrialized poultry industry suggest the poultry production-food-consumer chain as a potential transmission route. In Africa, integrated studies at this human–animal interface are still missing.Aim: To determine the molecular epidemiology of ESBL-producing E. coli from the intestinal tract of humans and poultry in rural Ghana.Methods: During a 6-month period, fecal samples from all children admitted to the Agogo Hospital (Ghana) and broilers at eight poultry farms located within the hospital catchment area were collected. After screening on selective ESBL agar, whole genome sequencing (WGS) was performed on all ESBL isolates. The genomes were analyzed using multilocus sequence typing (MLST), ESBL genotyping and genome-based phylogenetic analyses.Results: Of 140 broilers and 54 children, 41 (29%) and 33 (61%) harbored ESBL E. coli, respectively, with prevalences on farms ranging between 0 and 85%. No predominant sequence type (ST) was detected among humans. ST10 was most prevalent among broilers (n = 31, 69%). The ESBL gene blaCTX-M-15 was predominant among broilers (n = 43, 96%) and humans (n = 32, 97%). Whole-genome-based phylogenetic analysis revealed three very closely related broiler/human isolate clusters (10% of ESBL isolates) with chromosomal and plasmid-mediated ESBL genes.Conclusion: The findings demonstrate a high frequency of intestinal ESBL-producing E. coli in rural Ghana. Considering that animal and human samples are independent specimens from the same geographic location, the number of closely related ESBL isolates circulating across these two reservoirs is substantial. Hence, poultry farms or meat products might be an important source for ESBL-producing bacteria in rural Ghana leading to difficult-to-treat infections in humans

Rapid epidemic expansion of the SARS-CoV-2 Omicron variant in southern Africa

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic in southern Africa has been characterised by three distinct waves. The first was associated with a mix of SARS-CoV-2 lineages, whilst the second and third waves were driven by the Beta and Delta variants, respectively1-3. In November 2021, genomic surveillance teams in South Africa and Botswana detected a new SARS-CoV-2 variant associated with a rapid resurgence of infections in Gauteng Province, South Africa. Within three days of the first genome being uploaded, it was designated a variant of concern (Omicron) by the World Health Organization and, within three weeks, had been identified in 87 countries. The Omicron variant is exceptional for carrying over 30 mutations in the spike glycoprotein, predicted to influence antibody neutralization and spike function4. Here, we describe the genomic profile and early transmission dynamics of Omicron, highlighting the rapid spread in regions with high levels of population immunity

Comorbidity and dementia : a mixed method study on improving healthcare for people with dementia (CoDem)

© Queen’s Printer and Controller of HMSO 2016. This work was produced by Bunn et al. under the terms of a commissioning contract issued by the Secretary of State for Health. This issue may be freely reproduced for the purposes of private research and study and extracts (or indeed, the full report) may be included in professional journals provided that suitable acknowledgement is made and the reproduction is not associated with any form of advertising. Applications for commercial reproduction should be addressed to: NIHR Journals Library, National Institute for Health Research, Evaluation, Trials and Studies Coordinating Centre, Alpha House, University of Southampton Science Park, Southampton SO16 7NS, UKAmong people living with dementia (PLWD) there is a high prevalence of comorbid medical conditions but little is known about the effects of comorbidity on processes and quality of care and patient needs or how services are adapting to address the particular needs of this population. To explore the impact of dementia on access to non-dementia services and identify ways of improving the integration of services for this population

Burden of disease scenarios for 204 countries and territories, 2022–2050: a forecasting analysis for the Global Burden of Disease Study 2021

Background: Future trends in disease burden and drivers of health are of great interest to policy makers and the public at large. This information can be used for policy and long-term health investment, planning, and prioritisation. We have expanded and improved upon previous forecasts produced as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) and provide a reference forecast (the most likely future), and alternative scenarios assessing disease burden trajectories if selected sets of risk factors were eliminated from current levels by 2050. Methods: Using forecasts of major drivers of health such as the Socio-demographic Index (SDI; a composite measure of lag-distributed income per capita, mean years of education, and total fertility under 25 years of age) and the full set of risk factor exposures captured by GBD, we provide cause-specific forecasts of mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) by age and sex from 2022 to 2050 for 204 countries and territories, 21 GBD regions, seven super-regions, and the world. All analyses were done at the cause-specific level so that only risk factors deemed causal by the GBD comparative risk assessment influenced future trajectories of mortality for each disease. Cause-specific mortality was modelled using mixed-effects models with SDI and time as the main covariates, and the combined impact of causal risk factors as an offset in the model. At the all-cause mortality level, we captured unexplained variation by modelling residuals with an autoregressive integrated moving average model with drift attenuation. These all-cause forecasts constrained the cause-specific forecasts at successively deeper levels of the GBD cause hierarchy using cascading mortality models, thus ensuring a robust estimate of cause-specific mortality. For non-fatal measures (eg, low back pain), incidence and prevalence were forecasted from mixed-effects models with SDI as the main covariate, and YLDs were computed from the resulting prevalence forecasts and average disability weights from GBD. Alternative future scenarios were constructed by replacing appropriate reference trajectories for risk factors with hypothetical trajectories of gradual elimination of risk factor exposure from current levels to 2050. The scenarios were constructed from various sets of risk factors: environmental risks (Safer Environment scenario), risks associated with communicable, maternal, neonatal, and nutritional diseases (CMNNs; Improved Childhood Nutrition and Vaccination scenario), risks associated with major non-communicable diseases (NCDs; Improved Behavioural and Metabolic Risks scenario), and the combined effects of these three scenarios. Using the Shared Socioeconomic Pathways climate scenarios SSP2-4.5 as reference and SSP1-1.9 as an optimistic alternative in the Safer Environment scenario, we accounted for climate change impact on health by using the most recent Intergovernmental Panel on Climate Change temperature forecasts and published trajectories of ambient air pollution for the same two scenarios. Life expectancy and healthy life expectancy were computed using standard methods. The forecasting framework includes computing the age-sex-specific future population for each location and separately for each scenario. 95% uncertainty intervals (UIs) for each individual future estimate were derived from the 2·5th and 97·5th percentiles of distributions generated from propagating 500 draws through the multistage computational pipeline. Findings: In the reference scenario forecast, global and super-regional life expectancy increased from 2022 to 2050, but improvement was at a slower pace than in the three decades preceding the COVID-19 pandemic (beginning in 2020). Gains in future life expectancy were forecasted to be greatest in super-regions with comparatively low life expectancies (such as sub-Saharan Africa) compared with super-regions with higher life expectancies (such as the high-income super-region), leading to a trend towards convergence in life expectancy across locations between now and 2050. At the super-region level, forecasted healthy life expectancy patterns were similar to those of life expectancies. Forecasts for the reference scenario found that health will improve in the coming decades, with all-cause age-standardised DALY rates decreasing in every GBD super-region. The total DALY burden measured in counts, however, will increase in every super-region, largely a function of population ageing and growth. We also forecasted that both DALY counts and age-standardised DALY rates will continue to shift from CMNNs to NCDs, with the most pronounced shifts occurring in sub-Saharan Africa (60·1% [95% UI 56·8–63·1] of DALYs were from CMNNs in 2022 compared with 35·8% [31·0–45·0] in 2050) and south Asia (31·7% [29·2–34·1] to 15·5% [13·7–17·5]). This shift is reflected in the leading global causes of DALYs, with the top four causes in 2050 being ischaemic heart disease, stroke, diabetes, and chronic obstructive pulmonary disease, compared with 2022, with ischaemic heart disease, neonatal disorders, stroke, and lower respiratory infections at the top. The global proportion of DALYs due to YLDs likewise increased from 33·8% (27·4–40·3) to 41·1% (33·9–48·1) from 2022 to 2050, demonstrating an important shift in overall disease burden towards morbidity and away from premature death. The largest shift of this kind was forecasted for sub-Saharan Africa, from 20·1% (15·6–25·3) of DALYs due to YLDs in 2022 to 35·6% (26·5–43·0) in 2050. In the assessment of alternative future scenarios, the combined effects of the scenarios (Safer Environment, Improved Childhood Nutrition and Vaccination, and Improved Behavioural and Metabolic Risks scenarios) demonstrated an important decrease in the global burden of DALYs in 2050 of 15·4% (13·5–17·5) compared with the reference scenario, with decreases across super-regions ranging from 10·4% (9·7–11·3) in the high-income super-region to 23·9% (20·7–27·3) in north Africa and the Middle East. The Safer Environment scenario had its largest decrease in sub-Saharan Africa (5·2% [3·5–6·8]), the Improved Behavioural and Metabolic Risks scenario in north Africa and the Middle East (23·2% [20·2–26·5]), and the Improved Nutrition and Vaccination scenario in sub-Saharan Africa (2·0% [–0·6 to 3·6]). Interpretation: Globally, life expectancy and age-standardised disease burden were forecasted to improve between 2022 and 2050, with the majority of the burden continuing to shift from CMNNs to NCDs. That said, continued progress on reducing the CMNN disease burden will be dependent on maintaining investment in and policy emphasis on CMNN disease prevention and treatment. Mostly due to growth and ageing of populations, the number of deaths and DALYs due to all causes combined will generally increase. By constructing alternative future scenarios wherein certain risk exposures are eliminated by 2050, we have shown that opportunities exist to substantially improve health outcomes in the future through concerted efforts to prevent exposure to well established risk factors and to expand access to key health interventions

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Background: Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. Methods: 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. Findings: Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. Interpretation: Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic