Biology subjects

McCrone, J. T.

Publications and source records attributed to McCrone, J. T..

10 recordsLinked to original sources

bioRxiv2026

Nextstrain automates real-time phylodynamic analysis of open data for endemic and emerging pathogens

MotivationGenome sequencing provides an exceptional window into the evolutionary and epidemiological dynamics of endemic and emerging pathogens, and thus allows for better, more targeted, public health interventions. Online genomic surveillance platforms can provide near real-time insight into these dynamics. ResultsNextstrain provides continually updated real-time genomic surveillance for 21 viruses and the bacterial pathogen Mycobacterium tuberculosis, with most analyses relying solely on open sequence data. Each pathogen includes steps to fetch and curate open data, classify sequences using established nomenclature systems, perform phylogenetic analyses, and share the results publicly. These analyses are automated, with most running daily to provide continually updated snapshots of pathogen evolution. Availability and ImplementationAll source code is available at https://github.com/nextstrain. Phylogenetic results can be visualized and downloaded at https://nextstrain.org/pathogens, and open sequence data and curated metadata are available at https://nextstrain.org/pathogens/files.

bioinformatics↗

bioRxiv2026

Recovery of an 18th Century Rhinovirus Genome through Ancient RNA Isolation of Human Lungs

RNA viruses cause substantial global morbidity, yet their impact prior to the twentieth century remains obscured. While ancient DNA studies have transformed our understanding of past pathogens, ancient RNA (aRNA) isolation is largely restricted to exceptionally preserved samples. Here, we simultaneously recover aDNA and aRNA from non-formalin-fixed human lung specimens and reconstructed an 18th-century Human Rhinovirus (HRV) A genome--the oldest human RNA virus identified to date. The RNA is highly fragmented, with distinctive terminal misincorporations and coverage patterns consistent with double-stranded RNA. Phylogenetic analyses indicate that this historical HRV genome is an extinct lineage related to contemporary genotypes, providing a unique perspective on rhinovirus evolution. These findings demonstrate that centuries-old medical specimens can retain informative aRNA, expanding the temporal scope of paleovirology.

genomics↗

bioRxiv2025

Evidence of latency reshapes our understanding of Ebola virus reservoir dynamics

The reservoir of Ebola virus (EBOV) has remained a mystery since the first recorded zoonotic epidemic in 1976. While recent outbreaks have revealed much about the epidemiological dynamics that sustain human-to-human transmission, the mechanisms by which the virus persists between epidemics are unknown. Observations of extreme EBOV evolutionary rate heterogeneity in humans suggest latency is an important, yet untested, factor in persistence between epidemics. We here explicitly model latency with a novel phylogenetic approach to characterise the natural history of EBOV and, by extension, its reservoir. We find evidence that EBOV undergoes extended periods (i.e., possibly decades) of quiescence in the reservoir. Accounting for these dynamics significantly changes our understanding of EBOVs evolutionary past and its geographic spread through Central Africa.

evolutionary biology↗

bioRxiv2024

HIPSTR: highest independent posterior subtree reconstruction in TreeAnnotator X

In Bayesian phylogenetic and phylodynamic studies it is common to summarise the posterior distribution of trees with a time-calibrated consensus phylogeny. While the maximum clade credibility (MCC) tree is often used for this purpose, we here show that a novel consensus tree method - the highest independent posterior subtree reconstruction, or HIPSTR - contains consistently higher supported clades over MCC. We also provide faster computational routines for estimating both consensus trees in an updated version of TreeAnnotator X, an open-source software program that summarizes the information from a sample of trees and returns many helpful statistics such as individual clade credibilities contained in the consensus tree. HIPSTR and MCC reconstructions on two Ebola virus and two SARS-CoV-2 data sets show that HIPSTR yields consensus trees that consistently contain clades with higher support compared to MCC trees. The MCC trees regularly fail to include several clades with very high posterior probability ([≥] 0.95) as well as a large number of clades with moderate to high posterior probability ([≥] 0.50), whereas HIPSTR achieves near-perfect performance in this respect. HIPSTR also exhibits favorable computational performance over MCC in TreeAnnotator X. Comparison to the recently developed CCD0-MAP algorithm yielded mixed results, and requires more in-depth exploration in follow-up studies. TreeAnnotator X - which is part of the BEAST X (v10.5.0) software package - is available at https://github.com/beast-dev/beast-mcmc/releases.

bioinformatics↗

bioRxiv2020

The effective population size and mutation rate of influenza A virus in acutely infected individuals

The global evolutionary dynamics of influenza viruses ultimately derive from processes that take place within and between infected individuals. Recent work suggests that within-host populations are dynamic, but an in vivo estimate of mutation rate and population size in naturally infected individuals remains elusive. Here we model the within-host dynamics of influenza A viruses using high depth of coverage sequence data from 200 acute infections in an outpatient, community setting. Using a Wright-Fisher model, we estimate a within-host effective population size of 32-72 and an in vivo mutation rate of 3.4x10-6 per nucleotide per generation.

microbiology↗

bioRxiv2020

Accommodating individual travel history, global mobility, and unsampled diversity in phylogeography: a SARS-CoV-2 case study.

Spatiotemporal bias in genome sequence sampling can severely confound phylogeographic inference based on discrete trait ancestral reconstruction. This has impeded our ability to accurately track the emergence and spread of SARS-CoV-2, the virus responsible for the COVID-19 pandemic. Despite the availability of unprecedented numbers of SARS-CoV-2 genomes on a global scale, evolutionary reconstructions are hindered by the slow accumulation of sequence divergence over its relatively short transmission history. When confronted with these issues, incorporating additional contextual data may critically inform phylodynamic reconstructions. Here, we present a new approach to integrate individual travel history data in Bayesian phylogeographic inference and apply it to the early spread of SARS-CoV-2, while also including global air transportation data. We demonstrate that including travel history data for each SARS-CoV-2 genome yields more realistic reconstructions of virus spread, particularly when travelers from undersampled locations are included to mitigate sampling bias. We further explore methods to ameliorate the impact of sampling bias by augmenting the phylogeographic analysis with lineages from undersampled locations in the analyses. Our reconstructions reinforce specific transmission hypotheses suggested by the inclusion of travel history data, but also suggest alternative routes of virus migration that are plausible within the epidemiological context but are not apparent with current sampling efforts. Although further research is needed to fully examine the performance of our travel-aware phylogeographic analyses with unsampled diversity and to further improve them, they represent multiple new avenues for directly addressing the colossal issue of sample bias in phylogeographic inference.

evolutionary biology↗

bioRxiv2019

Influenza B viruses exhibit lower within-host diversity than influenza A viruses in human hosts

Influenza B virus undergoes seasonal antigenic drift more slowly than influenza A, but the reasons for this difference are unclear. While the evolutionary dynamics of influenza viruses play out globally, they are fundamentally driven by mutation, reassortment, drift, and selection within individual hosts. These processes have recently been described for influenza A virus, but little is known about the evolutionary dynamics of influenza B virus (IBV) at the level of individual infections and transmission events. Here we define the within-host evolutionary dynamics of influenza B virus by sequencing virus populations from naturally-infected individuals enrolled in a prospective, community-based cohort over 8176 person-seasons of observation. Through analysis of high depth-of-coverage sequencing data from samples from 91 individuals with influenza B, we find that influenza B virus accumulates lower genetic diversity than previously observed for influenza A virus during acute infections. Consistent with studies of influenza A viruses, the within-host evolution of influenza B viruses is characterized by purifying selection and the general absence of widespread positive selection of within-host variants. Analysis of shared genetic diversity across 15 sequence-validated transmission pairs suggests that IBV experiences a tight transmission bottleneck similar to that of influenza A virus. These patterns of local-scale evolution are consistent with influenza B virus slower global evolutionary rate.\n\nImportanceThe evolution of influenza virus is a significant public health problem and necessitates the annual evaluation of influenza vaccine formulation to keep pace with viral escape from herd immunity. Influenza B virus is a serious health concern for children, in particular, yet remains understudied compared to influenza A virus. Influenza B virus evolves more slowly than influenza A, but the factors underlying this are not completely understood. We studied how the within-host diversity of influenza B virus relates to its global evolution by sequencing viruses from a community-based cohort. We found that influenza B virus populations have lower within-host genetic diversity than influenza A virus and experience a tight genetic bottleneck during transmission. Our work provides insights into the varying dynamics of influenza viruses in human infection.

microbiology↗

bioRxiv2018

A speed-fidelity trade-off determines the mutation rate and virulence of an RNA virus

Mutation rates can evolve through genetic drift, indirect selection due to genetic hitchhiking, or direct selection on the physicochemical cost of high fidelity. However, for many systems, it has been difficult to disentangle the relative impact of these forces empirically. In RNA viruses, an observed correlation between mutation rate and virulence has led many to argue that their extremely high mutation rates are advantageous, because they may allow for increased adaptability. This argument has profound implications, as it suggests that pathogenesis in many viral infections depends on rare or de novo mutations. Here we present data for an alternative model whereby RNA viruses evolve high mutation rates as a byproduct of selection for increased replicative speed. We find that a poliovirus antimutator, 3DG64S, has a significant replication defect and that wild type and 3DG64S populations have similar adaptability in two distinct cellular environments. Experimental evolution of 3DG64S under r-selection led to reversion and compensation of the fidelity phenotype. Mice infected with 3DG64S exhibited delayed morbidity at doses well above the LD50, consistent with attenuation by slower growth as opposed to reduced mutational supply. Furthermore, compensation of the 3DG64S growth defect restored virulence, while compensation of the fidelity phenotype did not. Our data are consistent with the kinetic proofreading model for biosynthetic reactions and suggest that speed is more important than accuracy. In contrast to what has been suggested for many RNA viruses, we find that within host spread is associated with viral replicative speed and not standing genetic diversity.\n\nAuthor SummaryMutation rate evolution has long been a fundamental problem in evolutionary biology. The polymerases of RNA viruses generally lack proofreading activity and exhibit extremely high mutation rates. Since most mutations are deleterious and mutation rates are tuned by natural selection, we asked why hasnt the virus evolved to have a lower mutation rate? We used experimental evolution and a murine infection model to show that RNA virus mutation rates may actually be too high and are not necessarily adaptive. Rather, our data indicate that viral mutation rates are driven higher as a result of selection for viruses with faster replication kinetics. We suggest that viruses have high mutation rates, not because they facilitate adaption, but because it is hard to be both fast and accurate.

microbiology↗

bioRxiv2017

The evolutionary dynamics of influenza A virus within and between human hosts

The global evolutionary dynamics of influenza virus ultimately derive from processes that take place within and between infected individuals. Here we define the dynamics of influenza A virus populations in human hosts through next generation sequencing of 249 specimens from 200 individuals collected over 6290 person-seasons of observation. Because these viruses were collected over 5 seasons from individuals in a prospective community-based cohort, they are broadly representative of natural human infections with seasonal viruses. We used viral sequence data from 35 serially sampled individuals to estimate a within host effective population size of 30-70 and an in vivo mutation rate of 4x10-5 per nucleotide per cellular infectious cycle. These estimates are consistent across several models and robust to the models' underlying assumptions. We also identified 43 epidemiologically linked and genetically validated transmission pairs. Maximum likelihood optimization of multiple transmission models estimates an effective transmission bottleneck of 1-2 distinct genomes. Our data suggest that positive selection of novel viral variants is inefficient at the level of the individual host and that genetic drift and other stochastic processes dominate the within and between host evolution of influenza A viruses.

microbiology↗

bioRxiv2016

Vaccination has minimal impact on the intrahost diversity of H3N2 influenza viruses

While influenza virus diversity and antigenic drift have been well characterized on a global scale, the factors that influence the virus rapid evolution within and between human hosts are less clear. Given the modest effectiveness of seasonal vaccination, vaccine-induced antibody responses could serve as a potent selective pressure for novel influenza variants at the individual or community level. We used next generation sequencing of patient-derived viruses from a randomized, placebo-controlled trial of vaccine efficacy to characterize the diversity of influenza A virus and to define the impact of vaccine-induced immunity on within-host populations. Importantly, this study design allowed us to isolate the impact of vaccination while still studying natural infection. We used pre-season hemagglutination inhibition and neuraminidase inhibition titers to quantify vaccine-induced immunity directly and to assess its impact on intrahost populations. We identified 166 cases of H3N2 influenza over 3 seasons and 5119 person-years. We obtained whole genome sequence data for 119 samples and used a stringent and empirically validated analysis pipeline to identify intrahost single nucleotide variants at [≥]1% frequency. Phylogenetic analysis of consensus hemagglutinin and neuraminidase sequences showed no stratification by pre-season HAI and NAI titer, respectively. In our study population, we found that the vast majority of intrahost single nucleotide variants were rare and that very few were found in more than one individual. Most samples had fewer than 15 single nucleotide variants across the entire genome, and the level of diversity did not significantly vary with day of sampling, vaccination status, or pre-season antibody titer. Contrary to what has been suggested in experimental systems, our data indicate that seasonal influenza vaccination has little impact on intrahost diversity in natural infection and that vaccine-induced immunity may be only a minor contributor to antigenic drift at local scales.

microbiology↗