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William P Hanage

Publications and source records attributed to William P Hanage.

4 recordsLinked to original sources

SARS-CoV-2 intra-host variation shows evidence of transmission and convergent evolution in a university surveillance cohort.

Monitoring and understanding the transmission and evolution of SARS-CoV-2 remains a significant public health priority. Within-host genetic variation provides insight into viral evolution during infection and may help infer transmission events. In this study, we analysed intra-host variation in SARS-CoV-2 genome sequences from Boston University's testing mandate. Focusing on intra-host single nucleotide variants (iSNVs), we inferred transmission events and assessed the selective forces shaping within-host viral evolution. To minimize false-positive iSNVs resulting from systematic biases, we implemented stringent data filtering and developed a heuristic to exclude contamination-derived artefacts arising from batched sequencing. We find that intra-host variation is limited and infrequently transmitted during acute infections, suggesting that shared iSNVs serve as highly specific but insensitive markers of transmission. We also observed incomplete purifying selection shaping within-host diversity, with the loci most affected changing among variants of concern. Finally, we identified a highly recurrent iSNV (G11083T) which may represent a site of positive selection. Our results highlight that within-host variation provides insight into within-host pathogen evolution, in spite of its limited use in genomic epidemiology.

SARS-CoV-2

Characterisation of a persistent SARS-CoV-2 infection lasting more than 750 days in a person living with HIV: a genomic analysis.

BACKGROUND: People who are immunocompromised can develop persistent SARS-CoV-2 infections. Several viral mutations accumulated during the course of such persistent infections have also been observed in prominent variants of concern (VOCs). Here, we characterise persistent infection and viral evolution of SARS-CoV-2 lasting more than 750 days in a person with advanced HIV-1 infection. METHODS: Between March, 2021, and July, 2022, eight clinical specimens were collected from a person living with HIV, neither receiving antiretroviral therapy nor virally suppressed, and presumed to have been initially infected with SARS-CoV-2 in mid-May, 2020. Viral RNA was extracted from each swab and an amplicon-based sequencing approach was used for genomic analysis of SARS-CoV-2. Variable sites were characterised at the consensus and subconsensus levels, and phylogenetic tools were applied to analyse viral evolution. Publicly available SARS-CoV-2 sequences from GenBank were leveraged to contextualise our sequenced samples and identify any potential evidence of transmission. FINDINGS: Genomes formed a monophyletic cluster in the B.1 lineage. 68 consensus and 67 subconsensus single nucleotide variants were observed over the course of infection. The intrahost clock rate remained similar to that of the interhost rate in contemporaneous community sequences (6·74 × 10-4 [95% credible interval 5·05 × 10-4 to 8·54 × 10-4] substitutions per site per year vs 6·11 × 10-4 [5·54 × 10-5 to 6·66 × 10-4]). Mutations grouped into two distinct subpopulations present throughout infection. 10 non-synonymous mutations in the spike protein gene were at positions in common with those defining the omicron lineage (BA.1 or BA.2), of which nine were present before November, 2021. Nine of 18 substitutions present throughout infection were rare in online databases, suggesting a lack of long transmission chains descending from this individual. INTERPRETATION: Convergent SARS-CoV-2 evolution, both in and outside the spike protein, observed in this study suggests parallels with the evolutionary process leading to emergence of the omicron VOC. The inferred absence of onward infections might indicate a loss of transmissibility during adaptation to a single host. Our results underscore the importance of appropriate treatment to cure persistent SARS-CoV-2 infections and monitoring them to understand how mutations contribute to viral adaptation. FUNDING: National Institute of General Medical Sciences of the National Institutes of Health, Centers for Disease Control and Prevention, the National Institute of Allergy and Infectious Diseases, MassCPR, and Morris Singer Foundation.

Humans

Rapid inference of antibiotic susceptibility phenotype of uropathogens using metagenomic sequencing with neighbor typing.

UNLABELLED: Timely diagnostic tools are needed to improve antibiotic treatment. Pairing metagenomic sequencing with genomic neighbor typing algorithms may support rapid clinically actionable results. We created resistance-associated sequence elements (RASE) databases for Escherichia coli and Klebsiella spp. and used them to predict antibiotic susceptibility in directly sequenced (Oxford Nanopore) urine specimens from critically ill patients. RASE analysis was performed on pathogen-specific reads from metagenomic sequencing. We evaluated the ability to predict (i) multi-locus sequence type (MLST) and (ii) susceptibility profiles. We used neighbor typing to predict MLST and susceptibility phenotype of E. coli (64/80) and Klebsiella spp. (16/80) from urine samples. When optimized by lineage score, MLST predictions were concordant for 73% of samples. Similarly, a RASE-susceptible prediction for a given isolate was associated with a specificity and a positive likelihood ratio (LR+) for susceptibility of 0.65 (95% CI, 0.54-0.76) and 2.26 (95% CI, 1.75-2.92), respectively, with an increase in the probability of susceptibility of 10%. A RASE-non-susceptible prediction was associated with a sensitivity and a negative likelihood ratio (LR-) for susceptibility of 0.79 (95% CI, 0.74-0.84) and 0.32 (95% CI, 0.24-0.43) respectively, with a decrease in the probability of susceptibility of 20%. Numerous antibiotic classes could reasonably be reconsidered empiric therapy by shifting empiric probabilities of susceptibility across relevant treatment thresholds. Moreover, these predictions can be available within 6 h. Metagenomic sequencing of urine specimens with neighbor typing provides rapid and informative predictions of lineage and antibiotic susceptibility with the potential to impact clinical decision-making. IMPORTANCE: Urinary tract infections (UTIs) are a common diagnosis in hospitals and are often treated empirically with broad-spectrum antibiotics. These broad-spectrum agents can select for resistance in these bacteria and co-colonizing organisms. The use of narrow-spectrum agents is desirable as an antibiotic stewardship measure; however, it is counterbalanced by the need for adequate therapy. Identification of causative organisms and their antibiotic susceptibility can help direct treatment; however, conventional testing requires days to produce actionable results. Methods to quickly and accurately predict susceptibility phenotypes for pathogens causing UTI could thus improve both patient outcomes and antibiotic stewardship. Here, expanding on previous work showing accurate prediction for certain Gram-positive pathogens, we demonstrate how the use of RASE from metagenomic sequencing can provide informative and rapid phenotype prediction results for common Gram-negative pathogens in UTI, highlighting the future potential of this method to be used in clinical settings to guide empiric antibiotic selection.

Humans

Fuzzy species among recombinogenic bacteria.

BACKGROUND: It is a matter of ongoing debate whether a universal species concept is possible for bacteria. Indeed, it is not clear whether closely related isolates of bacteria typically form discrete genotypic clusters that can be assigned as species. The most challenging test of whether species can be clearly delineated is provided by analysis of large populations of closely-related, highly recombinogenic, bacteria that colonise the same body site. We have used concatenated sequences of seven house-keeping loci from 770 strains of 11 named Neisseria species, and phylogenetic trees, to investigate whether genotypic clusters can be resolved among these recombinogenic bacteria and, if so, the extent to which they correspond to named species. RESULTS: Alleles at individual loci were widely distributed among the named species but this distorting effect of recombination was largely buffered by using concatenated sequences, which resolved clusters corresponding to the three species most numerous in the sample, N. meningitidis, N. lactamica and N. gonorrhoeae. A few isolates arose from the branch that separated N. meningitidis from N. lactamica leading us to describe these species as 'fuzzy'. CONCLUSION: A multilocus approach using large samples of closely related isolates delineates species even in the highly recombinogenic human Neisseria where individual loci are inadequate for the task. This approach should be applied by taxonomists to large samples of other groups of closely-related bacteria, and especially to those where species delineation has historically been difficult, to determine whether genotypic clusters can be delineated, and to guide the definition of species.

Cluster Analysis