Biology subjects

Bedford, T.

Publications and source records attributed to Bedford, T..

At least 37 records · Page 2Linked to original sources

bioRxiv2020

Evaluating Specimen Quality and Results from a Community-Wide, Home-Based Respiratory Surveillance Study

IntroductionWhile influenza and other respiratory pathogens cause significant morbidity and mortality, the community-based burden of these infections remains incompletely understood. The development of novel methods to detect respiratory infections is essential for mitigating epidemics and developing pandemic-preparedness infrastructure. MethodsFrom October 2019 to March 2020, we conducted a home-based cross-sectional study in the greater Seattle area, utilizing electronic consent and data collection instruments. Participants received nasal swab collection kits via rapid delivery within 24 hours of self-reporting respiratory symptoms. Samples were returned to the laboratory and were screened for 26 respiratory pathogens and a human marker. Participant data were recorded via online survey at the time of sample collection and one week later. ResultsOf the 4,572 consented participants, 4,359 (95.3%) received a home swab kit, and 3,648 (83.7%) returned a nasal specimen for respiratory pathogen screening. The 3,638 testable samples had a mean RNase P CRT value of 19.0 (SD: 3.4) and 1,232 (33.9%) samples had positive results for one or more pathogens, including 645 (17.7%) influenza-positive specimens. Among the testable samples, the median time between shipment of the home swab kit and completion of laboratory testing was 8 days [IQR: 7.0-14.0]. DiscussionHome-based surveillance using online participant enrollment and specimen self-collection is a feasible method for community-level monitoring of influenza and other respiratory pathogens, which can readily be adapted for use during pandemics.

microbiology↗

bioRxiv2020

Evidence for adaptive evolution in the receptor-binding domain of seasonal coronaviruses

Seasonal coronaviruses (OC43, 229E, NL63 and HKU1) are endemic to the human population, regularly infecting and reinfecting humans while typically causing asymptomatic to mild respiratory infections. It is not known to what extent reinfection by these viruses is due to waning immune memory or antigenic drift of the viruses. Here, we address the influence of antigenic drift on immune evasion of seasonal coronaviruses. We provide evidence that at least two of these viruses, OC43 and 229E, are undergoing adaptive evolution in regions of the viral spike protein that are exposed to human humoral immunity. This suggests that reinfection may be due, in part, to positively-selected genetic changes in these viruses that enable them to escape recognition by the immune system. It is possible that, as with seasonal influenza, these adaptive changes in antigenic regions of the virus would necessitate continual reformulation of a vaccine made against them.

evolutionary biology↗

bioRxiv2020

Limited predictability of amino acid substitutions in seasonal influenza viruses

Seasonal influenza viruses repeatedly infect humans in part because they rapidly change their antigenic properties and evade host immune responses, necessitating frequent updates of the vaccine composition. Accurate predictions of strains circulating in the future could therefore improve the vaccine match. Here, we studied the predictability of frequency dynamics and fixation of amino acid substitutions. Current frequency was the strongest predictor of eventual fixation, as expected in neutral evolution. Other properties, such as occurrence in previously characterized epitopes or high Local Branching Index (LBI) had little predictive power. Parallel evolution was found to be moderately predictive of fixation. While the LBI had little power to predict frequency dynamics, it was still successful at picking strains representative of future populations. The latter is due to a tendency of the LBI to be high for consensus-like sequences that are closer to the future than the average sequence. Simulations of models of adapting populations, in contrast, show clear signals of predictability. This indicates that the evolution of influenza HA and NA, while driven by strong selection pressure to change, is poorly described by common models of directional selection such as travelling fitness waves.

evolutionary biology↗

bioRxiv2020

Integrating genotypes and phenotypes improves long-term forecasts of seasonal influenza A/H3N2 evolution

Seasonal influenza virus A/H3N2 is a major cause of death globally. Vaccination remains the most effective preventative. Rapid mutation of hemagglutinin allows viruses to escape adaptive immunity. This antigenic drift necessitates regular vaccine updates. Effective vaccine strains need to represent H3N2 populations circulating one year after strain selection. Experts select strains based on experimental measurements of antigenic drift and predictions made by models from hemagglutinin sequences. We developed a novel influenza forecasting framework that integrates phenotypic measures of antigenic drift and functional constraint with previously published sequence-only fitness estimates. Forecasts informed by phenotypic measures of antigenic drift consistently outperformed previous sequence-only estimates, while sequence-only estimates of functional constraint surpassed more comprehensive experimentally-informed estimates. Importantly, the best models integrated estimates of both functional constraint and either antigenic drift phenotypes or recent population growth.

evolutionary biology↗

bioRxiv2020

Helicobacter pylori diversification during chronic infection within a single host generates sub-populations with distinct phenotypes

Helicobacter pylori chronically infects the stomach of approximately half of the worlds population. Manifestation of clinical diseases associated with H. pylori infection, including cancer, is driven by strain properties and host responses; and as chronic infection persists, both are subject to change. Previous studies have documented frequent and extensive within-host bacterial genetic variation. To define how within-host diversity contributes to phenotypes related to H. pylori pathogenesis, this project leverages a collection of 39 clinical isolates acquired prospectively from a single subject at two time points and from multiple gastric sites. During the six years separating collection of these isolates, this individual, initially harboring a duodenal ulcer, progressed to gastric atrophy and concomitant loss of acid secretion. Whole genome sequence analysis identified 2,232 unique single nucleotide polymorphisms (SNPs) across isolates and a nucleotide substitution rate of 1.3x10-4 substitutions/site/year. Gene ontology analysis identified cell envelope genes among the genes with excess accumulation of nonsynonymous SNPs (nSNPs). A dendrogram based on genetic similarity, clusters isolates from each time point separately. Within time points, there is segregation of subgroups with phenotypic differences in bacterial morphology, ability to induce inflammatory cytokines, and mouse colonization. Higher inflammatory cytokine induction in recent isolates maps to shared polymorphisms in the Cag PAI protein, CagY, while rod morphology in a subgroup of recent isolates mapped to eight mutations in three distinct helical cell shape determining (csd) genes. The presence of subgroups with unique genetic and phenotypic properties suggest complex selective forces and multiple sub-niches within the stomach during chronic infection. Author SummaryHelicobacter pylori, one of the most common bacterial pathogens colonizing humans, is the main agent responsible for stomach ulcers and cancer. Certain strain types are associated with increased risk of disease, however many factors contributing to disease outcome remain unknown. Prior work has documented genetic diversity among bacterial populations within single individuals, but the impact of this diversity for continued bacterial infection or disease progression remains understudied. In our analysis we examined both genetic and functional features of many stomach isolates from a single individual infected over six years. During these six years the subject shifted from having excess acid production and a duodenal ulcer to lower acid production from gastric atrophy. The 39 isolates form sub-populations based on gene sequence changes that accumulated in the different isolates. In addition to having distinguishing genetic features, these sub-populations also have differences in several bacterial properties, including cell shape, ability to activate immune responses, and colonization in a mouse model of infection. This apparent functional specialization suggests that the bacterial sub-populations may have adapted to distinct sub-niches within the stomach during chronic infection.

microbiology↗

bioRxiv2020

dms-view: Interactive visualization tool for deep mutational scanning data

Summary and PurposeThe high-throughput technique of deep mutational scanning (DMS) has recently made it possible to experimentally measure the effects of all amino-acid mutations to a protein (Fowler and Fields 2014). Over the past five years, this technique has been used to study dozens of different proteins (Esposito et al. 2019) and answer a variety of research questions. For example, DMS has been used for protein engineering (Wrenbeck, Faber, and Whitehead 2017), understanding the human immune response to viruses (Lee et al. 2019), and interpreting human variation in a clinical setting (Starita et al. 2017; Gelman et al. 2019). Accompanying this proliferation of DMS studies has been the development of software tools (Bloom 2015; Rubin et al. 2017) and databases (Esposito et al. 2019) for data analysis and sharing. However, for many purposes it is important to also integrate and visualize the DMS data in the context of other information, such as the 3-D protein structure or natural sequence-variation data. Here we describe dms-view (https://dms-view.github.io/), a flexible, web-based, interactive visualization tool for DMS data. dms-view is written in JavaScript and D3, and links site-level and mutation-level DMS data to a 3-D protein structure. The user can interactively select sites of interest to examine the DMS measurements in the context of the protein structure. dms-view tracks the input data and user selections in the URL, making it possible to save specific views of interactively generated visualizations to share with collaborators or to support a published study. Importantly, dms-view takes a flexible input data file so users can easily visualize their own DMS data in the context of protein structures of their choosing, and also incorporate additional information such amino-acid frequencies in natural alignments.

bioinformatics↗

bioRxiv2020

Characterising the epidemic spread of Influenza A/H3N2 within a city through phylogenetics

Infecting large portions of the global population, seasonal influenza is a major burden on societies around the globe. While the global source sink dynamics of the different seasonal influenza viruses have been studied intensively, its local spread remains less clear. In order to improve our understanding of how influenza is transmitted on a city scale, we collected an extremely densely sampled set of influenza sequences alongside patient metadata. To do so, we sequenced influenza viruses isolated from patients of two different hospitals, as well as private practitioners in Basel, Switzerland during the 2016/2017 influenza season. The genetic sequences reveal that repeated introductions into the city drove the influenza season. We then reconstruct how the effective reproduction number changed over the course of the season. We find trends in transmission dynamics correlated positively with trends in temperature, but not relative humidity nor school holidays. Alongside the genetic sequence data that allows us to see how individual cases are connected, we gathered patient information, such as the age or household status. Zooming into the local transmission outbreaks suggests that the elderly were to a large extent infected within their own transmission network, while school children likely drove the spread within the remaining transmission network. These patterns will be valuable to plan interventions combating the spread of respiratory diseases within cities given that similar patterns are observed for other influenza seasons and cities. Author summaryAs shown with the current SARS-CoV-2 pandemic, respiratory diseases can quickly spread around the globe. While it can be hugely important to understand how diseases spread around the globe, local spread is most often the main driver of novel infections of respiratory diseases such as SARS-CoV-2 or influenza. We here use genetic sequence data alongside patient information to better understand what the drives the local spread of influenza by looking at the 2016/2017 influenza season in Basel, Switzerland as an example. The genetic sequence data allows us to reconstruct the how the transmission dynamics changed over the course of the season, which we correlate to changes, but not humidity or school holidays. Additionally, the genetic sequence data allows us to see how individual cases are connected. Using patient information, such as age and household status our analyses suggest that the elderly mainly transmit within their own transmission network. Additionally, they suggest that school aged children, but not pre-school aged children are important drivers of the local spread of influenza.

evolutionary biology↗

bioRxiv2019

Seasonal influenza circulation patterns and projections for September 2019 to September 2020

This report details current seasonal influenza circulation patterns as of August 2019 and makes projections up to September 2020 to coincide with selection of the 2020 Southern Hemisphere vaccine strain. This is not meant as a comprehensive report, but is instead intended as particular observations that weve made that may be of relevance. Please also note that observed patterns reflect the GISAID database and may not be entirely representative of underlying dynamics. All analyses are based on the nextflu/nextstrain pipeline [1,2] with continual updates posted to nextstrain.org/flu. A/H3N2: A/H3N2 viruses continue to show substantial diversity in HA sequences with a deep split between 3c3.A and 3c2.A1b viruses. The most notable recent developments are the rapid rise of clade A1b/137F - a subclade of A1b/135K - in China and Bangladesh and clade A1b/197R - a subclade of A1b/131K - which dominates the ongoing season in Australia. Our models predict that A1b/137F and A1b/197R will be the dominant clades next year with A1b/197R accounting for most circulation. There is, however, large uncertainty in the true extent of A1b/137F circulation. A/H1N1pdm: The S183P substitution has risen to near fixation. The most successful subclade carrying this mutation is 183P-5 which has essentially replaced competing variants. A variant with substitutions 129D/185I is at 60% prevalence globally, while a second variant with substitution 130N is at 50% in North America and ~10% elsewhere. Substitutions at site 156 to D or K have arisen sporadically and result in loss of recognition by antisera raised against viruses with asparagine at position 156. Despite the large antigenic effect, viruses with mutations at site 156 dont seem to spread. Beyond variants at site 156, little to no antigenic evolution is evident in assays with ferret antisera. B/Vic: Antigenically drifted deletion variants at HA1 sites 162, 163 and 164 are now dominating global circulation and have all but taken over. The double deletion variant V1A.1 had previously been circulating at high frequency in the Americas. However, over the course of 2009, the triple deletion variant V1A.3 has increased in frequency globally and is now dominating in all geographic regions. Importantly, V1A.1 and V1A.3 variants appear antigenically distinct by HI assays with 4-8 fold reductions in log2 titer in both directions. B/Yam: B/Yam has not circulated in large numbers since the Northern Hemisphere season 2017/2018 and displays relatively little amino acid variation in HA or antigenic diversity. Amino acid variants at sites 229 and 232 have begun to circulate and population is now split between 229D/232D, 229N/232D and 229D/232N variants. These variants show little sign of antigenic difference in HI assays.

evolutionary biology↗

bioRxiv2019

Quantifying within-host evolution of H5N1 influenza in humans and poultry in Cambodia

Avian influenza viruses (AIVs) periodically cross species barriers and infect humans. The likelihood that an AIV will evolve mammalian transmissibility depends on acquiring and selecting mutations during spillover, but data from natural infection is limited. We analyze deep sequencing data from infected humans and domestic ducks in Cambodia to examine how H5N1 viruses evolve during spillover. Overall, viral populations in both species are predominated by low-frequency (<10%) variation shaped by purifying selection and genetic drift, and half of the variants detected within-host are never detected on the H5N1 virus phylogeny. However, we do detect a subset of mutations linked to human receptor binding and replication (PB2 E627K, HA A150V, and HA Q238L) that arose in multiple, independent humans. PB2 E627K and HA A150V were also enriched along phylogenetic branches leading to human infections, suggesting that they are likely human-adaptive. Our data show that H5N1 viruses generate putative human-adapting mutations during natural spillover infection, many of which are detected at >5% frequency within-host. However, short infection times, genetic drift, and purifying selection likely restrict their ability to evolve extensively during a single infection. Applying evolutionary methods to sequence data, we reveal a detailed view of H5N1 virus adaptive potential, and develop a foundation for studying host-adaptation in other zoonotic viruses. Author summaryH5N1 avian influenza viruses can cross species barriers and cause severe disease in humans. H5N1 viruses currently cannot replicate and transmit efficiently among humans, but animal infection studies and modeling experiments have suggested that human adaptation may require only a few mutations. However, data from natural spillover infection has been limited, posing a challenge for risk assessment. Here, we analyze a unique dataset of deep sequence data from H5N1 virus-infected humans and domestic ducks in Cambodia. We find that well-known markers of human receptor binding and replication arise in multiple, independent humans. We also find that 3 mutations detected within-host are enriched along phylogenetic branches leading to human infections, suggesting that they are likely human-adapting. However, we also show that within-host evolution in both humans and ducks are shaped heavily by purifying selection and genetic drift, and that a large fraction of within-host variation is never detected on the H5N1 phylogeny. Taken together, our data show that H5N1 viruses do generate human-adapting mutations during natural infection. However, short infection times, purifying selection, and genetic drift may severely limit how much H5N1 viruses can evolve during the course of a single infection.

microbiology↗

bioRxiv2019

Mapping person-to-person variation in viral mutations that escape polyclonal serum targeting influenza hemagglutinin

A longstanding question is how influenza evolves to escape human immunity, which is polyclonal and can target many distinct epitopes on the virus. Here we map how all amino-acid mutations to influenzas major surface protein affect viral neutralization by polyclonal human sera. The serum of some individuals is so focused that it selects single mutations that reduce viral neutralization by over an order of magnitude. However, different viral mutations escape the sera of different individuals. This individual-to-individual variation in viral escape mutations is not present among ferrets, which are frequently used as a model in influenza studies. Our results show how different single mutations help influenza escape the immunity of different members of the human population, a phenomenon that could shape viral evolution and disease susceptibility.

microbiology↗

bioRxiv2019

The ability of single genes vs full genomes to resolve time and space in outbreak analysis

Inexpensive pathogen genome sequencing has had a transformative effect on the field of phylodynamics, where ever increasing volumes of data have promised real-time insight into outbreaks of infectious disease. As well as the sheer volume of pathogen isolates being sequenced, the sequencing of whole pathogen genomes, rather than select loci, has allowed phylogenetic analyses to be carried out at finer time scales, often approaching serial intervals for infections caused by rapidly evolving RNA viruses. Despite its utility, whole genome sequencing of pathogens has not been adopted universally and targeted sequencing of loci is common in some pathogen-specific fields. In this study we aim to highlight the utility of sequencing whole genomes of pathogens by re-analysing a well-characterised collection of Ebola virus sequences in the form of complete viral genomes (~19kb long) or the rapidly evolving glycoprotein (GP, ~2kb long) gene. We quantify changes in phylogenetic, temporal, and spatial inference resolution as a result of this reduction in data and compare these to theoretical expectations. We propose a simple intuitive metric for quantifying temporal resolution, i.e. the time scale over which sequence data might be informative of various processes as a quick back-of-the-envelope calculation of statistical power available to molecular clock analyses.

epidemiology↗

bioRxiv2019

Early Prediction of Antigenic Transitions for Influenza A H3N2

Influenza A/H3N2 is a rapidly evolving virus which experiences major antigenic transitions every two to eight years. Anticipating the timing and outcome of transitions is critical to developing effective seasonal influenza vaccines. Using simulations from a published phylodynamic model of influenza transmission, we identified indicators of future evolutionary success for an emerging antigenic cluster. The eventual fate of a new cluster depends on its initial epidemiological growth rate--which is a function of mutational load and population susceptibility to the cluster--along with the variance in growth rate across co-circulating viruses. Logistic regression can predict whether a cluster at 5% relative frequency will eventually succeed with [~]80% sensitivity, providing up to eight months advance warning. As a cluster expands, the predictions improve while the lead-time for vaccine development and other interventions decreases. By focusing surveillance efforts on estimating population-wide susceptibility to emerging viruses, we can better anticipate major antigenic transitions.

epidemiology↗

bioRxiv2019

Evolution and rapid spread of a reassortant A(H3N2) virus that predominated the 2017-2018 influenza season

The 2017-2018 North American influenza season caused more hospitalizations and deaths than any year since the 2009 H1N1 pandemic. The majority of recorded influenza infections were caused by A(H3N2) viruses, with most of the viruss North American diversity falling into the A2 clade. Within A2, we observe a subclade which we call A2/re that rose to comprise almost 70% of A(H3N2) viruses circulating in North America by early 2018. Unlike most fast-growing clades, however, A2/re contains no amino acid substitutions in the hemagglutinin (HA) segment. Moreover, HI assays did not suggest substantial antigenic differences between A2/re viruses and viruses sampled during the 2016-2017 season. Rather, we observe that the A2/re clade was the result of a reassortment event that occurred in late 2016 or early 2017 and involved the combination of the HA and PB1 segments of an A2 virus with neuraminidase (NA) and other segments a virus from the clade A1b. The success of this clade shows the need for antigenic analysis that targets NA in addition to HA. Our results illustrate the potential for non-HA drivers of viral success and necessitate the need for more thorough tracking of full viral genomes to better understand the dynamics of influenza epidemics.

genomics↗

bioRxiv2019

Comprehensive mapping of avian influenza polymerase adaptation to the human host

Viruses like influenza are infamous for their ability to adapt to new hosts. Retrospective studies of natural zoonoses and passaging in the lab have identified a modest number of host-adaptive mutations. However, it is unclear if these mutations represent all ways that influenza can adapt to a new host. Here we take a prospective approach to this question by completely mapping amino-acid mutations to the avian influenza virus polymerase protein PB2 that enhance growth in human cells. We identify numerous previously uncharacterized human-adaptive mutations. These mutations cluster on PB2s surface, highlighting potential interfaces with host factors. Some previously uncharacterized adaptive mutations occur in avian-to-human transmission of H7N9 influenza, showing their importance for natural virus evolution. But other adaptive mutations do not occur in nature because they are inaccessible via single-nucleotide mutations. Overall, our work shows how selection at key molecular surfaces combines with evolutionary accessibility to shape viral host adaptation.

microbiology↗

bioRxiv2018

Genomic epidemiology supports multiple introductions and cryptic transmission of Zika virus in Colombia

BackgroundColombia was the second most affected country during the American Zika virus (ZIKV) epidemic, with over 109,000 reported cases. Despite the scale of the outbreak, limited genomic sequence data were available from Colombia. We sought to sequence additional samples and use genomic epidemiology to describe ZIKV dynamics in Colombia.\n\nMethodsWe sequenced ZIKV genomes directly from clinical diagnostic specimens and infected Aedes ae-gypti samples selected to cover the temporal and geographic breadth of the Colombian outbreak. We performed phylogeographic analysis of these genomes, along with other publicly-available ZIKV genomes from the Americas, to estimate the frequency and timing of ZIKV introductions to Colombia.\n\nResultsWe attempted PCR amplification on 184 samples; 19 samples amplified sufficiently to perform sequencing. Of these, 8 samples yielded sequences with at least 50% coverage. Our phylogeo-graphic reconstruction indicates two separate introductions of ZIKV to Colombia, one of which was previously unrecognized. We find that ZIKV was first introduced to Colombia in February 2015 (95%CI: Jan 2015 - Apr 2015), corresponding to 5 to 8 months of cryptic ZIKV transmission prior to confirmation in September 2015. Despite the presence of multiple introductions, we find that the majority of Colombian ZIKV diversity descends from a single introduction. We find evidence for movement of ZIKV from Colombia into bordering countries, including Peru, Ecuador, Panama, and Venezuela.\n\nConclusionsSimilarly to genomic epidemiologic studies of ZIKV dynamics in other countries, we find that ZIKV circulated cryptically in Colombia. This more accurate dating of when ZIKV was circulating refines our definition of the population at risk. Additionally, our finding that the majority of ZIKV transmission within Colombia was attributable to transmission between individuals, rather than repeated travel-related importations, indicates that improved detection and control might have succeeded in limiting the scale of the outbreak within Colombia.

genomics↗

bioRxiv2018

Dengue antigenic relationships predict evolutionary dynamics

Dengue virus (DENV) exists as four genetically distinct serotypes, each of which is historically assumed to be antigenically uniform. However, recent analyses suggest that antigenic heterogeneity may exist within each serotype, but its source, extent and impact remain unclear. Here, we construct a sequence-based model to directly map antigenic change to underlying genetic divergence. We identify 49 specific substitutions and four colinear substitution clusters that contribute to dengue antigenic diversity. We report moderate antigenic diversity within each serotype, resulting in variation in genotype-specific patterns of heterotypic cross-neutralization. We also quantify the impact of this antigenic heterogeneity on real-world DENV population dynamics. We find that antigenic fitness mediates fluctuations in DENV clade frequencies, although this appears to be primarily explained by coarser serotype-level antigenic differences. These results provide a more nuanced understanding of dengue antigenic evolution, with important ramifications for vaccine design and epidemic preparedness.\n\nAuthor SummaryDengue virus (DENV), the causative agent of dengue hemorrhagic fever, exists as four genetically distinct serotypes, DENV1 to DENV4. These serotypes are antigenically distinct: symptomatic reinfection with a homotypic virus is very rare, while reinfection with a heterotypic virus is sometimes associated with severe disease. Until recently, it has been assumed that viruses within each serotype are antigenically uniform. However, specific genotypes within each serotype have been anecdotally associated with varying severity of patient outcomes and epidemic magnitude. One hypothesis is that each serotype contains overlooked, meaningful antigenic diversity. While antigenic cartography conducted on neutralization titers suggests that heterogeneity may exist within each serotype, its source, extent and impact is unclear. Here, we analyze a previously published titer dataset to quantify and characterize the extent of DENV intraserotype antigenic diversity. We map antigenic changes to specific mutations in E, the dengue envelope protein, and interpolate across the alignment to estimate the antigenic distance between pairs of viruses based on their genetic differences. We identify 49 specific substitutions and four colinear substitution clusters that contribute to dengue antigenic evolution. We find that DENV antigenic divergence is tightly coupled to DENV genetic divergence, and is likely a gradual, ongoing process. We report modest but significant antigenic diversity within each serotype of DENV, which may have important ramifications for vaccine design. To understand the impact of this antigenic heterogeneity on real-world DENV population dynamics, we also quantify the extent to which population immunity--accumulated through recent circulation of antigenically similar genotypes--determines the success and decline of DENV clades in a hyperendemic population. We find that antigenic fitness is a key determinant of DENV population turnover, although this appears to be driven by coarser serotype-level antigenic differences. By leveraging both molecular data and real-world population dynamics, these results provide a more nuanced understanding of dengue antigenic evolution, with important ramifications for improving vaccine design and epidemic preparedness.

evolutionary biology↗

bioRxiv2018

Deep mutational scanning of hemagglutinin helps predict evolutionary fates of human H3N2 influenza variants

Human influenza virus rapidly accumulates mutations in its major surface protein hemagglutinin (HA). The evolutionary success of influenza virus lineages depends on how these mutations affect HAs functionality and antigenicity. Here we experimentally measure the effects on viral growth in cell culture of all single amino-acid mutations to the HA from a recent human H3N2 influenza virus strain. We show that mutations that are measured to be more favorable for viral growth are enriched in evolutionarily successful H3N2 viral lineages relative to mutations that are measured to be less favorable for viral growth. Therefore, despite the well-known caveats about cell-culture measurements of viral fitness, such measurements can still be informative for understanding evolution in nature. We also compare our measurements for H3 HA to similar data previously generated for a distantly related H1 HA, and find substantial differences in which amino acids are preferred at many sites. For instance, the H3 HA has less disparity in mutational tolerance between the head and stalk domains than the H1 HA. Overall, our work suggests that experimental measurements of mutational effects can be leveraged to help understand the evolutionary fates of viral lineages in nature -- but only when the measurements are made on a viral strain similar to the ones being studied in nature.\n\nSignificance StatementA key goal in the study of influenza virus evolution is to forecast which viral strains will persist and which ones will die out. Here we experimentally measure the effects of all amino-acid mutations to the hemagglutinin protein from a human H3N2 influenza strain on viral growth in cell culture. We show that these measurements have utility for distinguishing among viral strains that do and do not succeed in nature. Overall, our work suggests that new high-throughput experimental approaches may be useful for understanding virus evolution in nature.

evolutionary biology↗

bioRxiv2018

Real-time analysis and visualization of pathogen sequence data

The rapid development of sequencing technologies has to led to an explosion of pathogen sequence data that are increasingly collected as part of routine surveillance or clinical diagnostics. In public health, sequence data is used to reconstruct the evolution of pathogens, anticipate future spread, and target interventions. In clinical settings whole genome sequences identify pathogens at the strain level, can be used to predict phenotypes such as drug resistance and virulence, and inform treatment by linking to closely related cases. However, the vast majority of sequence data are only used for specific narrow applications such as typing. Comprehensive analysis of these data could provide detailed insight into outbreak dynamics, but is not routinely done since fast, robust, and interpretable analysis work-flows are not in place. Here, we review recent developments in real-time analysis of pathogen sequence data with a particular focus on visualization and integration of sequence and phenotypic data.

microbiology↗