Current data show no signal of Ebola virus adapting to humans

Current data show no signal of Ebola virus adapting to humans

Stephanie J. Spielman, Austin G. Meyer, Claus O. Wilke

Gire et al. (Science 345:1369–1372, 2014) analyzed 81 complete genomes sampled from the 2014 Zaire ebolavirus (EBOV) outbreak and claimed that the virus is evolving far more rapidly in the current outbreak than it has been between previous outbreaks. This assertion has received widespread attention, and many have perceived Gire et al. (2014)’s results as implying rapid adaptation of EBOV to humans during the current outbreak. Here, we show that, on the contrary, sequence divergence in EBOV is rather limited, and that the currently available data contain no signal of rapid evolution or adaptation to humans. Gire et al.’s findings resulted from an incorrect application of a molecular-clock model to a population of sequences with minimal divergence and segregating polymorphisms. Our results highlight how indiscriminate use of off-the-shelf analysis techniques may result in highly-publicized, misleading statements about an ongoing public health crisis.

E. coli populations in unpredictably fluctuating environments evolve to face novel stresses through enhanced efflux activity

E. coli populations in unpredictably fluctuating environments evolve to face novel stresses through enhanced efflux activity

Shraddha Madhav Karve, Sachit Daniel, Yashraj Chavhan, Abhishek Anand, Somendra Singh Kharola, Sutirth Dey

There is considerable understanding about how laboratory populations respond to predictable (constant or deteriorating-environment) selection for single environmental variables like temperature or pH. However, such insights may not apply when selection environments comprise multiple variables that fluctuate unpredictably, as is common in nature. To address this issue, we grew replicate laboratory populations of E. coli in nutrient broth whose pH and concentrations of salt (NaCl) and hydrogen peroxide (H2O2) were randomly changed daily. After ~170 generations, the fitness of the selected populations had not increased in any of the three selection environments. However, these selected populations had significantly greater fitness in four novel environments which have no known fitness-correlation with tolerance to pH, NaCl or H2O2. Interestingly, contrary to expectations, hypermutators did not evolve. Instead, the selected populations evolved an increased ability for energy dependent efflux activity that might enable them to throw out toxins, including antibiotics, from the cell at a faster rate. This provides an alternate mechanism for how evolvability can evolve in bacteria and potentially lead to broad-spectrum antibiotic resistance, even in the absence of prior antibiotic exposure. Given that environmental variability is increasing in nature, this might have serious consequences for public-health.

Counterinsurgency Doctrine Applied to Infectious Disease

Counterinsurgency Doctrine Applied to Infectious Disease
Benjamin C Kirkup ​

Recent scientific discoveries lead inexorably to the conclusion that the ‘total human’ incorporates a necessary body of numerous microbes, including bacteria. These bacteria play a very important role in immunity by actively resisting infections by outside bacteria; however, under certain conditions they can degrade their community. They can arrogate to themselves resources that normally flow through other metabolic pathways and form persistent biological structures. In this situation, these bacteria constitute an insurgency, with strategic ramifications.

Extensive capsule locus variation and large-scale genomic recombination within the Klebsiella pneumoniae clonal complex 258/11.

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

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

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

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.