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UNLABELLED: For 100 years, it has been obvious that Salmonella enterica strains sharing the serotype with the formula 1,4,[5],12:b:1,2-now known as Paratyphi B-can cause diseases ranging from serious systemic infections to self-limiting gastroenteritis. Despite considerable predicted diversity between strains carrying the common Paratyphi B serotype, there remain few methods that subdivide the group into groups that are congruent with their disease phenotypes. Paratyphi B therefore represents one of the canonical examples in Salmonella where serotyping combined with classical microbiological tests fails to provide clinically informative information. Here, we use genomics to provide the first high-resolution view of this serotype, placing it into a wider genomic context of the Salmonella enterica species. These analyses reveal why it has been impossible to subdivide this serotype based upon phenotypic and limited molecular approaches. By examining the genomic data in detail, we are able to identify common features that correlate with strains of clinical importance. The results presented here provide new diagnostic targets, as well as posing important new questions about the basis for the invasive disease phenotype observed in a subset of strains. IMPORTANCE: Salmonella enterica strains carrying the serotype Paratyphi B have long been known to possess Jekyll and Hyde characteristics; some cause gastroenteritis, while others cause serious invasive disease. Understanding what makes up the population of strains carrying this serotype, as well as the source of their invasive disease, is a 100-year-old puzzle that we address here using genomics. Our analysis provides the first high-resolution view of this serotype, placing strains carrying serotype Paratyphi B into the wider genomic context of the Salmonella enterica species. This work reveals a history of disease dating back to the middle ages, caused by a group of distinct lineages with various abilities to cause invasive disease. By quantifying the key genomic differences between the invasive and noninvasive populations, we are able to identify key virulence-related targets that can form the basis of simple, rapid, point-of-care tests. ; This work, including the efforts of Thomas R. Connor, Gemma Langridge, Theresa Feltwell, Julian Parkhill, and Nicholas Thomson, was funded by Wellcome Trust (098051). This work, including the efforts of Thomas R. Connor, was funded by Medical Research Council (MRC) (MR/L015080/1). F.-X.W. and S.L. are funded by the Institut Pasteur, the Institut de Veille Sanitaire, and the French Government's Investissement d'Avenir program Integrative Biology of Emerging Infectious Diseases Laboratory of Excellence (grant number ANR-10-LABX-62-IBEID). The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication ; Sí

Monitoring the spread of SARS-CoV-2 and reconstructing transmission chains has become a major public health focus for many governments around the world. The modest mutation rate and rapid transmission of SARS-CoV-2 prevents the reconstruction of transmission chains from consensus genome sequences, but within-host genetic diversity could theoretically help identify close contacts. Here we describe the patterns of within-host diversity in 1181 SARS-CoV-2 samples sequenced to high depth in duplicate. 95.1% of samples show within-host mutations at detectable allele frequencies. Analyses of the mutational spectra revealed strong strand asymmetries suggestive of damage or RNA editing of the plus strand, rather than replication errors, dominating the accumulation of mutations during the SARS-CoV-2 pandemic. Within- and between-host diversity show strong purifying selection, particularly against nonsense mutations. Recurrent within-host mutations, many of which coincide with known phylogenetic homoplasies, display a spectrum and patterns of purifying selection more suggestive of mutational hotspots than recombination or convergent evolution. While allele frequencies suggest that most samples result from infection by a single lineage, we identify multiple putative examples of co-infection. Integrating these results into an epidemiological inference framework, we find that while sharing of within-host variants between samples could help the reconstruction of transmission chains, mutational hotspots and rare cases of superinfection can confound these analyses.

Monitoring the spread of SARS-CoV-2 and reconstructing transmission chains has become a major public health focus for many governments around the world. The modest mutation rate and rapid transmission of SARS-CoV-2 prevents the reconstruction of transmission chains from consensus genome sequences, but within-host genetic diversity could theoretically help identify close contacts. Here we describe the patterns of within-host diversity in 1181 SARS-CoV-2 samples sequenced to high depth in duplicate. 95.1% of samples show within-host mutations at detectable allele frequencies. Analyses of the mutational spectra revealed strong strand asymmetries suggestive of damage or RNA editing of the plus strand, rather than replication errors, dominating the accumulation of mutations during the SARS-CoV-2 pandemic. Within- and between-host diversity show strong purifying selection, particularly against nonsense mutations. Recurrent within-host mutations, many of which coincide with known phylogenetic homoplasies, display a spectrum and patterns of purifying selection more suggestive of mutational hotspots than recombination or convergent evolution. While allele frequencies suggest that most samples result from infection by a single lineage, we identify multiple putative examples of co-infection. Integrating these results into an epidemiological inference framework, we find that while sharing of within-host variants between samples could help the reconstruction of transmission chains, mutational hotspots and rare cases of superinfection can confound these analyses. ; This work was funded by COG-UK, supported by funding from the Medical Research Council (MRC) part of UK Research & Innovation (UKRI), the National Institute of Health Research (NIHR) and Genome Research Limited, operating as the Wellcome Sanger Institute;

Monitoring the spread of SARS-CoV-2 and reconstructing transmission chains has become a major public health focus for many governments around the world. The modest mutation rate and rapid transmission of SARS-CoV-2 prevents the reconstruction of transmission chains from consensus genome sequences, but within-host genetic diversity could theoretically help identify close contacts. Here we describe the patterns of within-host diversity in 1181 SARS-CoV-2 samples sequenced to high depth in duplicate. 95.1% of samples show within-host mutations at detectable allele frequencies. Analyses of the mutational spectra revealed strong strand asymmetries suggestive of damage or RNA editing of the plus strand, rather than replication errors, dominating the accumulation of mutations during the SARS-CoV-2 pandemic. Within- and between-host diversity show strong purifying selection, particularly against nonsense mutations. Recurrent within-host mutations, many of which coincide with known phylogenetic homoplasies, display a spectrum and patterns of purifying selection more suggestive of mutational hotspots than recombination or convergent evolution. While allele frequencies suggest that most samples result from infection by a single lineage, we identify multiple putative examples of co-infection. Integrating these results into an epidemiological inference framework, we find that while sharing of within-host variants between samples could help the reconstruction of transmission chains, mutational hotspots and rare cases of superinfection can confound these analyses.