Joint host-pathogen genomic analysis identifies hepatitis B virus mutations associated with human NTCP and HLA class I variation.

Evolutionary changes in the hepatitis B virus (HBV) genome could reflect its adaptation to host-induced selective pressure. Leveraging paired human exome and ultra-deep HBV genome-sequencing data from 567 affected individuals with chronic hepatitis B, we comprehensively searched for the signatures of this evolutionary process by conducting "genome-to-genome" association tests between all human genetic variants and viral mutations. We identified significant associations between an East Asian-specific missense variant in the gene encoding the HBV entry receptor NTCP (rs2296651, NTCP S267F) and mutations within the receptor-binding region of HBV preS1. Through in silico modeling and in vitro preS1-NTCP binding assays, we observed that the associated HBV mutations are in proximity to the NTCP variant when bound and together partially increase binding affinity to NTCP S267F. Furthermore, we identified significant associations between HLA-A variation and viral mutations in HLA-A-restricted T cell epitopes. We used in silico binding prediction tools to evaluate the impact of the associated HBV mutations on HLA presentation and observed that mutations that result in weaker binding affinities to their cognate HLA alleles were enriched. Overall, our results suggest the emergence of HBV escape mutations that might alter the interaction between HBV PreS1 and its cellular receptor NTCP during viral entry into hepatocytes and confirm the role of HLA class I restriction in inducing HBV epitope variations.

Ancient Genomes From Bronze Age Remains Reveal Deep Diversity and Recent Adaptive Episodes for Human Oral Pathobionts.

Ancient microbial genomes can illuminate pathobiont evolution across millenia, with teeth providing a rich substrate. However, the characterization of prehistoric oral pathobiont diversity is limited. In Europe, only preagricultural genomes have been subject to phylogenetic analysis, with none compared to more recent archaeological periods. Here, we report well-preserved microbiomes from two 4,000-year-old teeth from an Irish limestone cave. These contained bacteria implicated in periodontitis, as well as Streptococcus mutans, the major cause of caries and rare in the ancient genomic record. Despite deriving from the same individual, these teeth produced divergent Tannerella forsythia genomes, indicating higher levels of strain diversity in prehistoric populations. We find evidence of microbiome dysbiosis, with a disproportionate quantity of S. mutans sequences relative to other oral streptococci. This high abundance allowed for metagenomic assembly, resulting in its first reported ancient genome. Phylogenetic analysis indicates major postmedieval population expansions for both species, highlighting the inordinate impact of recent dietary changes. In T. forsythia, this expansion is associated with the replacement of older lineages, possibly reflecting a genome-wide selective sweep. Accordingly, we see dramatic changes in T. forsythia's virulence repertoire across this period. S. mutans shows a contrasting pattern, with deeply divergent lineages persisting in modern populations. This may be due to its highly recombining nature, allowing for maintenance of diversity through selective episodes. Nonetheless, an explosion in recent coalescences and significantly shorter branch lengths separating bacteriocin-carrying strains indicate major changes in S. mutans demography and function coinciding with sugar popularization during the industrial period.

Assessment of the pathogen genomics landscape highlights disparities and challenges for effective AMR Surveillance and outbreak response in the East African community.

The East African Community (EAC) grapples with many challenges in tackling infectious disease threats and antimicrobial resistance (AMR), underscoring the importance of regional and robust pathogen genomics capacities. However, a significant disparity exists among EAC Partner States in harnessing bacterial pathogen sequencing and data analysis capabilities for effective AMR surveillance and outbreak response. This study assesses the current landscape and challenges associated with pathogen next-generation sequencing (NGS) within EAC, explicitly focusing on World Health Organization (WHO) AMR-priority pathogens. The assessment adopts a comprehensive approach, integrating a questionnaire-based survey amongst National Public Health Laboratories (NPHLs) with an analysis of publicly available metadata on bacterial pathogens isolated in the EAC countries. In addition to the heavy reliance on third-party organizations for bacterial NGS, the findings reveal a significant disparity among EAC member States in leveraging bacterial pathogen sequencing and data analysis. Approximately 97% (n = 4,462) of publicly available high-quality bacterial genome assemblies of samples collected in the EAC were processed and analyzed by external organizations, mainly in Europe and North America. Tanzania led in-country sequencing efforts, followed by Kenya and Uganda. The other EAC countries had no publicly available samples or had all their samples sequenced and analyzed outside the region. Insufficient local NGS sequencing facilities, limited bioinformatics expertise, lack of adequate computing resources, and inadequate data-sharing mechanisms are among the most pressing challenges that hinder the EAC's NPHLs from effectively leveraging pathogen genomics data. These insights emphasized the need to strengthen microbial pathogen sequencing and data analysis capabilities within the EAC to empower these laboratories to conduct pathogen sequencing and data analysis independently. Substantial investments in equipment, technology, and capacity-building initiatives are crucial for supporting regional preparedness against infectious disease outbreaks and mitigating the impact of AMR burden. In addition, collaborative efforts should be developed to narrow the gap, remedy regional imbalances, and harmonize NGS data standards. Supporting regional collaboration, strengthening in-country genomics capabilities, and investing in long-term training programs will ultimately improve pathogen data generation and foster a robust NGS-driven AMR surveillance and outbreak response in the EAC, thereby supporting global health initiatives.

Genomic Surveillance of Invasive Meningococcal Disease During a National MenW Outbreak in Australia, 2017-2018.

Background: In Australia, invasive meningococcal disease (IMD) incidence rapidly increased between 2014 and 2017 due to rising serogroup W (MenW) and MenY infections. We aimed to better understand the genetic diversity of IMD during 2017 and 2018 using whole genome sequencing data. Methods: Whole genome sequencing data from 440 Australian IMD isolates collected during 2017 and 2018 and 1737 international MenW:CC11 isolates collected in Europe, Africa, Asia, North America, and South America between 1974 and 2020 were used in phylogenetic analyses; genetic relatedness was determined from single-nucleotide polymorphisms. Results: Australian isolates were as follows: 181 MenW (41%), 144 MenB (33%), 88 MenY (20%), 16 MenC (4%), 1 MenW/Y (0.2%), and 10 nongenogroupable (2%). Eighteen clonal complexes (CCs) were identified, and 3 (CC11, CC23, CC41/44) accounted for 78% of isolates (343/440). These CCs were associated with specific serogroups: CC11 (n = 199) predominated among MenW (n = 181) and MenC (n = 15), CC23 (n = 80) among MenY (n = 78), and CC41/44 (n = 64) among MenB (n = 64). MenB isolates were highly diverse, MenY were intermediately diverse, and MenW and MenC isolates demonstrated the least genetic diversity. Thirty serogroup and CC-specific genomic clusters were identified. International CC11 comparison revealed diversification of MenW in Australia. Conclusions: Whole genome sequencing comprehensively characterized Australian IMD isolates, indexed their genetic variability, provided increased within-CC resolution, and elucidated the evolution of CC11 in Australia.

Ancient Mycobacterium leprae genome reveals medieval English red squirrels as animal leprosy host.

Leprosy, one of the oldest recorded diseases in human history, remains prevalent in Asia, Africa, and South America, with over 200,000 cases every year.1,2 Although ancient DNA (aDNA) approaches on the major causative agent, Mycobacterium leprae, have elucidated the disease's evolutionary history,3,4,5 the role of animal hosts and interspecies transmission in the past remains unexplored. Research has uncovered relationships between medieval strains isolated from archaeological human remains and modern animal hosts such as the red squirrel in England.6,7 However, the time frame, distribution, and direction of transmissions remains unknown. Here, we studied 25 human and 12 squirrel samples from two archaeological sites in Winchester, a medieval English city well known for its leprosarium and connections to the fur trade. We reconstructed four medieval M. leprae genomes, including one from a red squirrel, at a 2.2-fold average coverage. Our analysis revealed a phylogenetic placement of all strains on branch 3 as well as a close relationship between the squirrel strain and one newly reconstructed medieval human strain. In particular, the medieval squirrel strain is more closely related to some medieval human strains from Winchester than to modern red squirrel strains from England, indicating a yet-undetected circulation of M. leprae in non-human hosts in the Middle Ages. Our study represents the first One Health approach for M. leprae in archaeology, which is centered around a medieval animal host strain, and highlights the future capability of such approaches to understand the disease's zoonotic past and current potential.

Advancing pathogen genomics in resource-limited settings.

Genomic sequencing has emerged as a powerful tool to enhance early pathogen detection and characterization with implications for public health and clinical decision making. Although widely available in developed countries, the application of pathogen genomics among low-resource, high-disease burden settings remains at an early stage. In these contexts, tailored approaches for integrating pathogen genomics within infectious disease control programs will be essential to optimize cost efficiency and public health impact. We propose a framework for embedding pathogen genomics within national surveillance plans across a spectrum of surveillance and laboratory capacities. We adopt a public health approach to genomics and examine its application to high-priority diseases relevant in resource-limited settings. For each grouping, we assess the value proposition for genomics to inform public health and clinical decision-making, alongside its contribution toward research and development of novel diagnostics, therapeutics, and vaccines.