Extensive capsule locus variation and large-scale genomic recombination within the Klebsiella pneumoniae clonal complex 258/11
Kelly L Wyres, Claire Gorrie, David J Edwards, Heiman FL Wertheim, Li Yang Hsu, Nguyen Van Kinh, Ruth Zadoks, Stephen Baker, Kathryn E Holt
Klebsiella pneumoniae clonal complex (CC) 258/11, comprising sequence types (STs) 258, 11 and closely related STs, is associated with dissemination of the K. pneumoniae carbapenemase (KPC). Hospital outbreaks of KPC CC258/11 infections have been observed globally and are very difficult to treat. As a consequence there is renewed interest in alternative infection control measures such as vaccines and phage or depolymerase treatments targeting the K pneumoniae polysaccharide capsule. To date, 78 immunologically distinct capsule variants have been described in K. pneumoniae. Previous investigations of ST258 and a small number of closely related strains suggested capsular variation was limited within this clone; only two distinct ST258 capsular synthesis (cps) loci have been identified, both acquired through large-scale recombination events (>50 kbp). Here we report comparative genomic analysis of the broader K. pneumoniae CC258/11. Our data indicate that several large-scale recombination events have shaped the genomes of CC258/11, and that definition of the complex should be broadened to include ST395 (also reported to harbour KPC). We identified 11 different cps loci within CC258/11, suggesting that capsular switching is actually common within the complex. We also observed several insertion sequences (IS) within the cps loci, and show further diversification of two loci through IS activity. These findings suggest the capsular loci of clinically important K. pneumoniae are under diversifying selection, which alters our understanding of the evolution of this important clone and has implications for the design of control measures targeting the capsule.
Coordinated Evolution of Influenza A Surface Proteins
Alexey D. Neverov, Sergey Kryazhimskiy, Joshua B. Plotkin, Georgii A. Bazykin
Surface proteins hemagglutinin (HA) and neuraminidase (NA) of the human influenza A virus evolve under selection pressure to escape the human adaptive immune response and antiviral drug treatments. In addition to these external selection pressures, some mutations in HA are known to affect the adaptive landscape of NA, and vice versa, because these two proteins are physiologically interlinked. However, the extent to which evolution of one protein affects the evolution of the other is unknown. Here we develop a novel phylogenetic method for detecting the signatures of such genetic interactions between mutations in different genes, that is, inter-gene epistasis. Using this method, we show that influenza surface proteins evolve in a coordinated way, with substitutions in HA affecting substitutions in NA and vice versa, at many sites. Of particular interest is our finding that the oseltamivir-resistance mutations in NA in subtype H1N1 were likely facilitated by prior mutations in HA. Our results illustrate that the adaptive landscape of a viral protein is remarkably sensitive to its genomic context and, more generally, imply that the evolution of any single protein must be understood within the context of the entire evolving genome.
Seasonality in the migration and establishment of H3N2 Influenza lineages with epidemic growth and decline
Daniel Zinder, Trevor Bedford, Edward B. Baskerville, Robert J. Woods, Manojit Roy, Mercedes Pascual
(Submitted on 15 Aug 2014)
Background: Influenza A/H3N2 has been circulating in humans since 1968, causing considerable morbidity and mortality. Although H3N2 incidence is highly seasonal, how such seasonality contributes to global phylogeographic migration dynamics has not yet been established. In this study, we incorporate time-varying migration rates in a Bayesian MCMC framework focusing initially on migration within China and, to and from North-America, as case studies, and later on global communities.
Results: Both global migration and migration between and within large geographic regions is clearly seasonal. On a global level, windows of immigration (in migration) map to the seasonal timing of epidemic spread, while windows of emigration (out migration) to epidemic decline. Seasonal patterns also affect the probability that local lineages go extinct and fail to contribute to long term viral evolution. The probability that a region will contribute to long term viral evolution as a part of the trunk of the phylogenetic tree increases in the absence of deep troughs and with reduced incidence variability.
Conclusions: Seasonal migration and rapid turnover within regions is sustained by the invasion of ‘fertile epidemic grounds’ at the end of older epidemics. Thus, the current emphasis on connectivity, including air-travel, should be complemented with a better understanding of the conditions and timing required for successful establishment. This will better our understanding of seasonal drivers, improve predictions, and improve vaccine updating by identifying strains that not only escape immunity but also have the seasonal opportunity to establish and spread. Further work is also needed on additional conditions that contribute to the persistence and long term evolution of influenza within the human population, such as spatial heterogeneity with respect to climate and seasonality.
Inferring the Clonal Structure of Viral Populations from Time Series Sequencing
Donatien Fotso-Chedom, Pablo R. Murcia, Chris D. Greenman
(Submitted on 30 Jul 2014)
RNA virus populations will undergo processes of mutation and selection resulting in a mixed population of viral particles. High throughput sequencing of a viral population subsequently contains a mixed signal of the underlying clones. We would like to identify the underlying evolutionary structures. We utilize two sources of information to attempt this; within segment linkage information, and mutation prevalence. We demonstrate that clone haplotypes, their prevalence, and maximum parsimony reticulate evolutionary structures can be identified, although the solutions may not be unique, even for complete sets of information. This is applied to a chain of influenza infection, where we infer evolutionary structures, including reassortment, and demonstrate some of the difficulties of interpretation that arise from deep sequencing due to artifacts such as template switching during PCR amplification.
Phylogenetics and the human microbiome
Frederick A Matsen IV
Comments: to appear in Systematic Biology
Subjects: Populations and Evolution (q-bio.PE); Genomics (q-bio.GN)
The human microbiome is the ensemble of genes in the microbes that live inside and on the surface of humans. Because microbial sequencing information is now much easier to come by than phenotypic information, there has been an explosion of sequencing and genetic analysis of microbiome samples. Much of the analytical work for these sequences involves phylogenetics, at least indirectly, but methodology has developed in a somewhat different direction than for other applications of phylogenetics. In this paper I review the field and its methods from the perspective of a phylogeneticist, as well as describing current challenges for phylogenetics coming from this type of work.
SRST2: Rapid genomic surveillance for public health and hospital microbiology labs
Michael Inouye, Harriet Dashnow, Lesley Raven, Mark B Schultz, Bernard J Pope, Takehiro Tomita, Justin Zobel, Kathryn E Holt
Rapid molecular typing of bacterial pathogens is critical for public health epidemiology, surveillance and infection control, yet routine use of whole genome sequencing (WGS) for these purposes poses significant challenges. Here we present SRST2, a tool for fast and accurate detection of genes, alleles and multi-locus sequence types from WGS data, which outperforms assembly-based methods. Using >900 genomes from common pathogens, we demonstrate SRST2’s utility for rapid genome surveillance in public health laboratory and hospital infection control settings.
Identifying the genetic basis of antigenic change in influenza A(H1N1)
William T. Harvey, Victoria Gregory, Donald J. Benton, James P. J. Hall, Rodney S. Daniels, Trevor Bedford, Daniel T. Haydon, Alan J. Hay, John W. McCauley, Richard Reeve
(Submitted on 16 Apr 2014)
Determining phenotype from genetic data is a fundamental challenge for virus research. Identification of emerging antigenic variants among circulating influenza viruses is critical to the vaccine virus selection process, with effectiveness maximized when vaccine constituents are antigenically matched to circulating viruses. Generally, antigenic similarity of viruses is assessed by the haemagglutination inhibition (HI) assay. We present models that define key antigenic determinants by identifying substitutions that significantly affect antigenic phenotype assessed using HI assay. Sequences of 506 haemagglutinin (HA) proteins from seasonal influenza A(H1N1) isolates and reference viruses, spanning over a decade, with complementary HI data and a crystallographic structure were analysed. We identified substitutions at fifteen surface-exposed positions as causing changes in antigenic phenotype of HA. At four positions the antigenic impact of substitutions was apparent at multiple points in the phylogeny, while eleven further sites were resolved by identifying branches containing antigenicity-changing events and determining the substitutions responsible by ancestral state reconstruction. Reverse genetics was used to demonstrate the causal effect on antigenicity of a subset of substitutions including one instance where multiple contemporaneous substitutions made a definitive identification impossible in silico. This technique quantifies the impact of specific amino acid substitutions allowing us to make predictions of antigenic distance, increasing the value of new genetic sequence data for monitoring antigenic drift and phenotypic evolution. It demonstrates the generality of an approach originally developed for foot-and-mouth disease virus that could be extended to other established and emerging influenza virus subtypes as well as other antigenically variable pathogens.
Mycobiome of the Bat White Nose Syndrome (WNS) Affected Caves and Mines reveals High Diversity of Fungi and Local Adaptation by the Fungal Pathogen Pseudogymnoascus (Geomyces) destructans
Tao Zhang, Tanya R. Victor, Sunanda S. Rajkumar, Xiaojiang Li, Joseph C. Okoniewski, Alan C. Hicks, April D. Davis, Kelly Broussard, Shannon L. LaDeau, Sudha Chaturvedi, Vishnu Chaturvedi
(Submitted on 3 Mar 2014)
The investigations of the bat White Nose Syndrome (WNS) have yet to provide answers as to how the causative fungus Pseudogymnoascus (Geomyces) destructans (Pd) first appeared in the Northeast and how a single clone has spread rapidly in the US and Canada. We aimed to catalogue Pd and all other fungi (mycobiome) by the culture-dependent (CD) and culture-independent (CI) methods in four Mines and two Caves from the epicenter of WNS zoonotic. Six hundred sixty-five fungal isolates were obtained by CD method including the live recovery of Pd. Seven hundred three nucleotide sequences that met the definition of operational taxonomic units (OTUs) were recovered by CI methods. Most OTUs belonged to unidentified clones deposited in the databases as environmental nucleic acid sequences (ENAS). The core mycobiome of WNS affected sites comprised of 46 species of fungi from 31 genera recovered in culture, and 17 fungal genera and 31 ENAS identified from clone libraries. Fungi such as Arthroderma spp., Geomyces spp., Kernia spp., Mortierella spp., Penicillium spp., and Verticillium spp. were predominant in culture while Ganoderma spp., Geomyces spp., Mortierella spp., Penicillium spp. and Trichosporon spp. were abundant is clone libraries. Alpha diversity analyses from CI data revealed that fungal community structure was highly diverse. However, the true species diversity remains undetermined due to under sampling. The frequent recovery of Pd indicated that the pathogen has adapted to WNS-afflicted habitats. Further, this study supports the hypothesis that Pd is an introduced species. These findings underscore the need for integrated WNS control measures that target both bats and the fungal pathogen.
Genetic drift suppresses bacterial conjugation in spatially structured populations
Peter D. Freese, Kirill S. Korolev, Jose I. Jimenez, Irene A. Chen
(Submitted on 24 Feb 2014)
Conjugation is the primary mechanism of horizontal gene transfer that spreads antibiotic resistance among bacteria. Although conjugation normally occurs in surface-associated growth (e.g., biofilms), it has been traditionally studied in well-mixed liquid cultures lacking spatial structure, which is known to affect many evolutionary and ecological processes. Here we visualize spatial patterns of gene transfer mediated by F plasmid conjugation in a colony of Escherichia coli growing on solid agar, and we develop a quantitative understanding by spatial extension of traditional mass-action models. We found that spatial structure suppresses conjugation in surface-associated growth because strong genetic drift leads to spatial isolation of donor and recipient cells, restricting conjugation to rare boundaries between donor and recipient strains. These results suggest that ecological strategies, such as enforcement of spatial structure and enhancement of genetic drift, could complement molecular strategies in slowing the spread of antibiotic resistance genes.
Genetic drift opposes mutualism during spatial population expansion
Melanie JI Muller, Beverly I Neugeboren, David R Nelson, Andrew W Murray
(Submitted on 24 Feb 2014)
Mutualistic interactions benefit both partners, promoting coexistence and genetic diversity. Spatial structure can promote cooperation, but spatial expansions may also make it hard for mutualistic partners to stay together, since genetic drift at the expansion front creates regions of low genetic and species diversity. To explore the antagonism between mutualism and genetic drift, we grew cross-feeding strains of the budding yeast S. cerevisiae on agar surfaces as a model for mutualists undergoing spatial expansions. By supplying varying amounts of the exchanged nutrients, we tuned strength and symmetry of the mutualistic interaction. Strong mutualism suppresses genetic demixing during spatial expansions and thereby maintains diversity, but weak or asymmetric mutualism is overwhelmed by genetic drift even when mutualism is still beneficial, slowing growth and reducing diversity. Theoretical modeling using experimentally measured parameters predicts the size of demixed regions and how strong mutualism must be to survive a spatial expansion.