Pleiotropy complicates a trade-off between phage resistance and antibiotic resistance.

Bacteria frequently encounter selection by both antibiotics and lytic bacteriophages. However, the evolutionary interactions between antibiotics and phages remain unclear, in particular, whether and when phages can drive evolutionary trade-offs with antibiotic resistance. Here, we describe Escherichia coli phage U136B, showing it relies on two host factors involved in different antibiotic resistance mechanisms: 1) the efflux pump protein TolC and 2) the structural barrier molecule lipopolysaccharide (LPS). Since TolC and LPS contribute to antibiotic resistance, phage U136B should select for their loss or modification, thereby driving a trade-off between phage resistance and either of the antibiotic resistance mechanisms. To test this hypothesis, we used fluctuation experiments and experimental evolution to obtain phage-resistant mutants. Using these mutants, we compared the accessibility of specific mutations (revealed in the fluctuation experiments) to their actual success during ecological competition and coevolution (revealed in the evolution experiments). Both tolC and LPS-related mutants arise readily during fluctuation assays, with tolC mutations becoming more common during the evolution experiments. In support of the trade-off hypothesis, phage resistance via tolC mutations occurs with a corresponding reduction in antibiotic resistance in many cases. However, contrary to the hypothesis, some phage resistance mutations pleiotropically confer increased antibiotic resistance. We discuss the molecular mechanisms underlying this surprising pleiotropic result, consideration for applied phage biology, and the importance of ecology in evolution of phage resistance. We envision that phages may be useful for the reversal of antibiotic resistance, but such applications will need to account for unexpected pleiotropy and evolutionary context.

Meningococcal A conjugate vaccine coverage in the meningitis belt of Africa from 2010 to 2021: a modelling study.

Background: As of the end of 2021, twenty-four countries in the African meningitis belt have rolled out mass campaigns of MenAfriVac®, a meningococcal A conjugate vaccine (MACV) first introduced in 2010. Twelve have completed introduction of MACV into routine immunisation (RI) schedules. Although select post-campaign coverage data are published, no study currently comprehensively estimates MACV coverage from both routine and campaign sources in the meningitis belt across age, country, and time. Methods: In this modelling study, we assembled campaign data from the twenty-four countries that had introduced any immunisation activity during or before the year 2021 (Benin, Burkina Faso, Burundi, Cameroon, Central African Republic, Chad, Côte d'Ivoire, Democratic Republic of the Congo, Ethiopia, Eritrea, the Gambia, Ghana, Guinea, Guinea Bissau, Kenya, Mali, Mauritania, Niger, Nigeria, Senegal, South Sudan, Sudan, Togo and Uganda) via WHO reports and RI data via systematic review. Next, we modelled RI coverage using Spatiotemporal Gaussian Process Regression. Then, we synthesized these estimates with campaign data into a cohort model, tracking coverage for each age cohort from age 1 to 29 years over time for each country. Findings: Coverage in high-risk locations amongst children aged 1-4 in 2021 was estimated to be highest in Togo with 96.0% (95% uncertainty interval [UI] 92.0-99.0), followed by Niger with 87.2% (95% UI 85.3-89.0) and Burkina Faso, with 86.4% (95% UI 85.1-87.6). These countries had high coverage values driven by an initial successful mass immunisation campaign, followed by a catch-up campaign, followed by introduction of RI. Due to the influence of older mass vaccination campaigns, coverage proportions skewed higher in the 1-29 age group than the 1-4 group, with a median coverage of 82.9% in 2021 in the broader age group compared to 45.6% in the narrower age group. Interpretation: These estimates highlight where gaps in immunisation remain and emphasise the need for broader efforts to strengthen RI systems. This methodological framework can be applied to estimate coverage for any vaccine that has been delivered in both routine and supplemental immunisation activities. Funding: Bill and Melinda Gates Foundation.

The Global Burden of Meningitis in Children: Challenges with Interpreting Global Health Estimates.

The World Health Organization (WHO) has developed a global roadmap to defeat meningitis by 2030. To advocate for and track progress of the roadmap, the burden of meningitis as a syndrome and by pathogen must be accurately defined. Three major global health models estimating meningitis mortality as a syndrome and/or by causative pathogen were identified and compared for the baseline year 2015. Two models, (1) the WHO and the Johns Hopkins Bloomberg School of Public Health's Maternal and Child Epidemiology Estimation (MCEE) group's Child Mortality Estimation (WHO-MCEE) and (2) the Institute for Health Metrics and Evaluation (IHME) Global Burden of Disease Study (GBD 2017), identified meningitis, encephalitis and neonatal sepsis, collectively, to be the second and third largest infectious killers of children under five years, respectively. Global meningitis/encephalitis and neonatal sepsis mortality estimates differed more substantially between models than mortality estimates for selected infectious causes of death and all causes of death combined. Estimates at national level and by pathogen also differed markedly between models. Aligning modelled estimates with additional data sources, such as national or sentinel surveillance, could more accurately define the global burden of meningitis and help track progress against the WHO roadmap.