The introduction of multilocus sequence typing (MLST) for the precise characterization of isolates of bacterial pathogens has had a marked impact on both routine epidemiological surveillance and microbial population biology. In both fields, a key prerequisite for exploiting this resource is the ability to discern the relatedness and patterns of evolutionary descent among isolates with similar genotypes. Traditional clustering techniques, such as dendrograms, provide a very poor representation of recent evolutionary events, as they attempt to reconstruct relationships in the absence of a realistic model of the way in which bacterial clones emerge and diversify to form clonal complexes. An increasingly popular approach, called BURST, has been used as an alternative, but present implementations are unable to cope with very large data sets and offer crude graphical outputs. Here we present a new implementation of this algorithm, eBURST, which divides an MLST data set of any size into groups of related isolates and clonal complexes, predicts the founding (ancestral) genotype of each clonal complex, and computes the bootstrap support for the assignment. The most parsimonious patterns of descent of all isolates in each clonal complex from the predicted founder(s) are then displayed. The advantages of eBURST for exploring patterns of evolutionary descent are demonstrated with a number of examples, including the simple Spain 23F -1 clonal complex of Streptococcus pneumoniae, "population snapshots" of the entire S. pneumoniae and Staphylococcus aureus MLST databases, and the more complicated clonal complexes observed for Campylobacter jejuni and Neisseria meningitidis.The ability to accurately determine the genetic relatedness of isolates of bacterial pathogens (or other disease agents) is fundamental to molecular epidemiological and evolutionary studies. In recent years, the use of nucleotide sequence variation at multiple housekeeping loci has become increasingly popular for strain characterization, as it has advantages for inferring levels of relatedness between strains and the reconstruction of evolutionary events (1, 2, 6-14, 18-23, 25, 28, 29).In many bacterial species, genetic variation at housekeeping loci accumulates as frequently or more frequently by homologous recombination (replacement of small chromosomal segments with those from related isolates) as by point mutation (15). Over the long term, recombination may prevent the true relationships between distantly related isolates of a species from being discerned. Epidemiological studies, however, are typically concerned with disease outbreaks or the spread of antibiotic-resistant or virulent strains between countries. Over these very short evolutionary timescales, of weeks to a few hundred years, recombination is unlikely to prevent the recognition of clones and clonal complexes within most bacterial populations. Thus, although the phylogenetic complexities introduced by homologous recombination may be problematic over long periods of evolutionary time (14, 15)...

Several major invasive bacterial pathogens are encapsulated. Expression of a polysaccharide capsule is essential for survival in the blood, and thus for virulence, but also is a target for host antibodies and the basis for effective vaccines. Encapsulated species typically exhibit antigenic variation and express one of a number of immunochemically distinct capsular polysaccharides that define serotypes. We provide the sequences of the capsular biosynthetic genes of all 90 serotypes of Streptococcus pneumoniae and relate these to the known polysaccharide structures and patterns of immunological reactivity of typing sera, thereby providing the most complete understanding of the genetics and origins of bacterial polysaccharide diversity, laying the foundations for molecular serotyping. This is the first time, to our knowledge, that a complete repertoire of capsular biosynthetic genes has been available, enabling a holistic analysis of a bacterial polysaccharide biosynthesis system. Remarkably, the total size of alternative coding DNA at this one locus exceeds 1.8 Mbp, almost equivalent to the entire S. pneumoniae chromosomal complement.

Summary SARS-CoV-2 Spike protein is critical for virus infection via engagement of ACE2 1 , and is a major antibody target. Here we report chronic SARS-CoV-2 with reduced sensitivity to neutralising antibodies in an immune suppressed individual treated with convalescent plasma, generating whole genome ultradeep sequences over 23 time points spanning 101 days. Little change was observed in the overall viral population structure following two courses of remdesivir over the first 57 days. However, following convalescent plasma therapy we observed large, dynamic virus population shifts, with the emergence of a dominant viral strain bearing D796H in S2 and ΔH69/ΔV70 in the S1 N-terminal domain NTD of the Spike protein. As passively transferred serum antibodies diminished, viruses with the escape genotype diminished in frequency, before returning during a final, unsuccessful course of convalescent plasma. In vitro , the Spike escape double mutant bearing ΔH69/ΔV70 and D796H conferred modestly decreased sensitivity to convalescent plasma, whilst maintaining infectivity similar to wild type. D796H appeared to be the main contributor to decreased susceptibility but incurred an infectivity defect. The ΔH69/ΔV70 single mutant had two-fold higher infectivity compared to wild type, possibly compensating for the reduced infectivity of D796H. These data reveal strong selection on SARS-CoV-2 during convalescent plasma therapy associated with emergence of viral variants with evidence of reduced susceptibility to neutralising antibodies.

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The response of the global virus genomics community to the SARS-CoV-2 pandemic has been unprecedented, with significant advances made towards the ‘real-time’ generation and sharing of SARS-CoV-2 genomic data. The rapid growth in virus genome data production has necessitated the development of new analytical methods that can deal with orders of magnitude more genomes than previously available. Here we present and describe pangolin (Phylogenetic Assignment of Named Global Outbreak Lineages), a computational tool that has been developed to assign the most likely lineage to a given SARS-CoV-2 genome sequence according to the Pango dynamic nomenclature scheme described in Rambaut et al. (2020). To date, nearly two million virus genomes have been submitted to the web-application implementation of pangolin, which has facilitated the SARS-CoV-2 genomic epidemiology and provided researchers with access to actionable information about the pandemic’s transmission lineages.

Visualization is frequently used to aid our interpretation of complex datasets. Within microbial genomics, visualizing the relationships between multiple genomes as a tree provides a framework onto which associated data (geographical, temporal, phenotypic and epidemiological) are added to generate hypotheses and to explore the dynamics of the system under investigation. Selected static images are then used within publications to highlight the key findings to a wider audience. However, these images are a very inadequate way of exploring and interpreting the richness of the data. There is, therefore, a need for flexible, interactive software that presents the population genomic outputs and associated data in a user-friendly manner for a wide range of end users, from trained bioinformaticians to front-line epidemiologists and health workers. Here, we present Microreact, a web application for the easy visualization of datasets consisting of any combination of trees, geographical, temporal and associated metadata. Data files can be uploaded to Microreact directly via the web browser or by linking to their location (e.g. from Google Drive/Dropbox or via API), and an integrated visualization via trees, maps, timelines and tables provides interactive querying of the data. The visualization can be shared as a permanent web link among collaborators, or embedded within publications to enable readers to explore and download the data. Microreact can act as an end point for any tool or bioinformatic pipeline that ultimately generates a tree, and provides a simple, yet powerful, visualization method that will aid research and discovery and the open sharing of datasets.

Globalized infectious diseases are causing species declines worldwide, but their source often remains elusive. We used whole-genome sequencing to solve the spatiotemporal origins of the most devastating panzootic to date, caused by the fungus Batrachochytrium dendrobatidis, a proximate driver of global amphibian declines. We traced the source of B. dendrobatidis to the Korean peninsula, where one lineage, BdASIA-1, exhibits the genetic hallmarks of an ancestral population that seeded the panzootic. We date the emergence of this pathogen to the early 20th century, coinciding with the global expansion of commercial trade in amphibians, and we show that intercontinental transmission is ongoing. Our findings point to East Asia as a geographic hotspot for B. dendrobatidis biodiversity and the original source of these lineages that now parasitize amphibians worldwide.

Evasion of clinical interventions by Streptococcus pneumoniae occurs through selection of non-susceptible genomic variants. Here we use genome sequencing of 3,085 pneumococcal carriage isolates from a 2.4 km2 refugee camp to enable unprecedented resolution of the process of recombination, and highlight its impact on population evolution. Genomic recombination hotspots show remarkable consistency between lineages, indicating common selective pressures acting at certain loci, particularly those associated with antibiotic resistance. Temporal changes in antibiotic consumption are reflected in changes in recombination trends demonstrating rapid spread of resistance when selective pressure is high. The highest frequencies of receipt and donation of recombined DNA fragments were observed in non-encapsulated lineages, implying that this largely overlooked pneumococcal group, which is beyond the reach of current vaccines, may play a major role in genetic exchange and adaptation of the species as a whole. These findings advance our understanding of pneumococcal population dynamics and provide important information for the design of future intervention strategies.