Biology subjects

Neher, R.

Publications and source records attributed to Neher, R..

6 recordsLinked to original sources

bioRxiv2018

Comprehensive analysis of intra- and interpatient evolution of enterovirus D68 by whole-genome deep sequencing

Worldwide outbreaks of enterovirus D68 (EV-D68) in 2014 and 2016 have caused widespread serious respiratory and neurological disease. To investigate diversity, spread, and evolution of EV-D68 we performed near full-length deep sequencing in 54 samples obtained in Sweden during the 2014 and 2016 outbreaks. In most samples, intrapatient variability was low and dominated by rare synonymous variants, but three patients showed evidence of dual infections with distinct EV-D68 variants from the same subclade. Interpatient evolution showed a very strong temporal signal, with an evolutionary rate of 0.0038{+/-}0.0001 substitutions per site and year. Phylogenetic trees reconstructed from the sequences suggest that EV-D68 was introduced into Stockholm several times during the 2016 outbreak and then spread locally. Putative neutralization targets in the BC- and DE-loops of the VP1 protein are slightly more diverse within-host and tend to undergo more frequent substitution than other genomic regions. However, evolution in these loops does not appear to have driven the emergence of the 2016 B3-subclade directly from the 2014 B1-subclade. Instead, the most recent ancestor of both clades was dated to 2009. The study provides a comprehensive description of the intra- and interpatient evolution of EV-D68, including the first report of intrapatient diversity and dual infections. The new data along with publicly available EV-D68 sequences are included in an interactive phylodynamic analysis on nextstrain.org/enterovirus/d68 to facilitate timely EV-D68 tracking in the future.xs

microbiology↗

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↗

bioRxiv2018

Seasonal influenza circulation patterns and projections for Feb 2018 to Feb 2019

This report details current seasonal influenza circulation patterns as of Feb 2018 and makes projections up to Feb 2019 to coincide with selection of the 2018-2019 Northern 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 pipeline [1] with continual updates posted to nextflu.org.\n\nA/H3N2: H3N2 diversity has largely been replaced by subclades A1b, A2 and A3 within 3c2.A. Subclades A1b and A2 predominate in the population and each shows increases in frequency, mutations at epitope sites and evidence for minor changes to antigenic phenotype. Clade A1b may be marginally fitter than clade A2, but we expect both clades to persist into the future without a clear immediate winner.\n\nA/H1N1pdm: A clade comprising mutations S74R, S164T and I295V has recently swept to fixation. The rapidity of this sweep suggests a selective origin. However, there is no evidence of antigenic change.\n\nB/Vic: Very little B/Vic activity has been observed in recent months. A clade with a two codon deletion at sites HA1:162/163 has gradually risen in frequency. HI measurements suggest an 8 to 16-fold titer drop relative to the vaccine strain, but this antigenic change has not yet resulted in a rapid rise of this variant.\n\nB/Yam: Europe experienced a strong and early B/Yam season in absence of amino acid variation in HA or antigenic diversity. However, several mutations in NA have rapidly swept or risen to intermediate frequencies.

evolutionary biology↗

bioRxiv2017

Seasonal influenza circulation patterns and projections for Sep 2017 to Sep 2018

This report details current seasonal influenza circulation patterns as of Sep 2017 and makes projections up to Sep 2018 to coincide with selection of the 2018 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 pipeline [1] with continual updates posted to nextflu.org.\n\nA/H3N2H3N2 continues to diversify with many coexisting clades, all of which carry several amino acid mutations at previously characterized epitope sites. The majority of viruses fall into the 3c2.a clade which has been dominating globally for >3 years, but 3c3.a viruses continue to persist. The common ancestor of circulating H3N2 viruses is now more than 5 years old, which is rare for H3N2. Despite extensive genetic diversity, serological assays suggest limited, but non-zero, antigenic evolution. We expect multiple competing clades within 3c2.a to persist into the future with no clear immediate winner.\n\nA/H1N1pdmA clade comprising mutations S74R and I295V has recently risen to >60% global frequency. Although it shows no antigenic distinction by ferret HI data, the rapidity of its rise suggests a selective origin.\n\nB/VicA clade with a two amino acid deletion 162-/163-has altered serological properties and is increasing in frequency, albeit slowly. Two other clades (carrying mutations K209N and V87A/I175V) have increased in frequency moderately.\n\nB/YamA clade comprising M251V within clade 3 viruses continues to dominate. The is little genetic differentiation within this clade and no evidence of antigenic evolution.

evolutionary biology↗

bioRxiv2017

TreeTime: maximum likelihood phylodynamic analysis

Mutations that accumulate in the genome of replicating biological organisms can be used to infer their evolutionary history. In the case of measurably evolving organisms genomes often reveal their detailed spatiotemporal spread. Such phylodynamic analyses are particularly useful to understand the epidemiology of rapidly evolving viral pathogens. The number of genome sequences available for different pathogens, however, has increased dramatically over the last couple of years and traditional methods for phylodynamic analysis scale poorly with growing data sets. Here, we present TreeTime, a Python based framework for phylodynamic analysis using an approximate Maximum Likelihood approach. TreeTime can estimate ancestral states, infer evolution models, reroot trees to maximize temporal signals, estimate molecular clock phylogenies and population size histories. The run time of TreeTime scales linearly with data set size.

evolutionary biology↗

bioRxiv2017

Estimating Time Of HIV-1 Infection From Next-Generation Sequence Diversity

Estimating the time since infection (TI) in newly diagnosed HIV-1 patients is challenging, but important to understand the epidemiology of the infection. Here we explore the utility of virus diversity estimated by next-generation sequencing (NGS) as novel biomarker by using a recent genome-wide longitudinal dataset obtained from 11 untreated HIV-1-infected patients with known dates of infection. The results were validated on a second dataset from 31 patients.\n\nVirus diversity increased linearly with time, particularly at 3rd codon positions, with little inter-patient variation. The precision of the TI estimate improved with increasing sequencing depth, showing that diversity in NGS data yields superior estimates to the number of ambiguous sites in Sanger sequences, which is one of the alternative biomarkers. The full advantage of deep NGS was utilized with continuous diversity measures such as average pairwise distance or site entropy, rather than the fraction of polymorphic sites. The precision depended on the genomic region and codon position and was highest when 3rd codon positions in the entire pol gene were used. For these data, TI estimates had a mean absolute error of around 1 year. The error increased only slightly from around 0.6 years at a TI of 6 months to around 1.1 years at 6 years.\n\nOur results show that virus diversity determined by NGS can be used to estimate time since HIV-1 infection many years after the infection, in contrast to most alternative biomarkers. We provide the regression coefficients as well as web tool for TI estimation.\n\nAuthor summaryHIV-1 establishes a chronic infection, which may last for many years before the infected person is diagnosed. The resulting uncertainty in the date of infection leads to difficulties in estimating the number of infected but undiagnosed persons as well as the number of new infections, which is necessary for developing appropriate public health policies and interventions. Such estimates would be much easier if the time since HIV-1 infection for newly diagnosed cases could be accurately estimated. Three types of biomarkers have been shown to contain information about the time since HIV-1 infection, but unfortunately, they only distinguish between recent and long-term infections (concentration of HIV-1-specific antibodies) or are imprecise (immune status as measured by levels of CD4+ T-lymphocytes and viral sequence diversity measured by polymorphisms in Sanger sequences).\n\nIn this paper, we show that recent advances in sequencing technologies, i.e. the development of next generation sequencing, enable significantly more precise determination of the time since HIV-1 infection, even many years after the infection event. This is a significant advance which could translate into more effective HIV-1 prevention.

epidemiology↗