Suchergebnisse

Analysis of pathogen genome data sequenced from clinical and historical samples has made it possible to perform phylogenetic analyses of sexually transmitted infections on a global scale, and to estimate the diversity, distribution, and coevolutionary host relationships of these pathogens, providing insights into pathogen emergence and disease prevention. Deep-sequenced pathogen genomes from clinical studies and ancient samples yield estimates of within-host and between-host evolutionary rates and provide data on changes in pathogen genomic stability and evolutionary responses. Here we examine three groups of pathogens transmitted mainly through sexual contact between modern humans to provide insight into ancient human behavior and history with their pathogens. Exploring ancient pathogen genomic divergence and the ancient viral-host parallel evolutionary histories will help us to reconstruct the origin of present-day geographical distribution and diversity of clinical pathogen infections, and will hopefully allow us to foresee possible environmentally induced pathogen evolutionary responses. Lastly, we emphasize that ancient pathogen DNA research should be combined with modern clinical pathogen data, and be equitable and provide advantages for all researchers worldwide, e.g., through shared data. ; V.N.P. was funded by the European Society of Clinical Microbiology and Infectious Diseases grant and the Ministry of Health, Government of Catalonia (grant SLT002/16/00496). C.J.H. was funded by the NIHR Cambridge Biomedical Research Centre Anti-Microbial Resistance theme. R.F.R. was funded by a National Geographic Society/Waitt Foundation Scientific Exploration Grant (Nr. W420–15) and the University of Pretoria. S.J.U was funded by Oxford Brookes University. ; http://www.mdpi.com/journal/genes ; am2018 ; Biochemistry ; Genetics ; Microbiology and Plant Pathology

Novel adenovirus genotypes are associated with outbreaks of disease, such as acute gastroenteritis, renal disease, upper respiratory tract infection and keratoconjunctivitis. Here, we identify novel and variant adenovirus genotypes in children coinfected with enterotoxigenic Escherichia coli, in Bangladesh. Metagenomic sequencing of stool was performed and whole adenovirus genomes were extracted. A novel species D virus, designated genotype 90 (P33H27F67) was identified, and the partial genome of a putative recombinant species B virus was recovered. Furthermore, the enteric types HAdV-A61 and HAdV-A40 were found in stool specimens. Knowledge of the diversity of adenovirus genomes circulating worldwide, especially in low-income countries where the burden of disease is high, will be required to ensure that future vaccination strategies cover the diversity of adenovirus strains associated with disease. ; This work was supported by NIHR Biomedical Research Centres in Cambridge (in particular the NIHR Cambridge BRC AMR Theme) and Wellcome Trust grant number 098051. This work was also supported by the International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b) which is grateful to the governments of Bangladesh, Canada, Sweden and the UK for providing core/unrestricted support. CJH is funded by the NIHR Cambridge Biomedical Research Centre (NHIR Cambridge, BRC) Antimicrobial Resistance theme. GD and MAB are supported by the Wellcome Trust. GD is supported by NIHR Cambridge, BRC. AM is funded by the DBT-Cambridge partnership.

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.