Correction: Individual-based model highlights the importance of trade-offs for virus-host population dynamics and long-term co-existence.

[This corrects the article DOI: 10.1371/journal.pcbi.1010228.].

Molecular evidence of parallel evolution in a cyanophage.

Antagonistic interactions between bacteriophage (phage) and its bacterial host drives the continual selection for resistance and counter-defence. To date, much remains unknown about the genomic evolution that occurs as part of the underlying mechanisms. Such is the case for the marine cyanobacteria Synechococcus and viruses (cyanophages) that infect them. Here, we monitored host and phage abundances, alongside genomic changes to the phage populations, in a 500-day (~55 bacterial generations) infection experiment between Synechococcus sp. WH7803 and the T4-type cyanophage S-PM2d, run parallel in three replicate chemostats (plus one control chemostat). Flow cytometric count of total abundances revealed relatively similar host-phage population dynamics across the chemostats, starting with a cycle of host population collapse and recovery that led to phases of host-phage coexistence. Whole-genome analysis of the S-PM2d populations detected an assemblage of strongly selected and repeatable genomic changes, and therefore parallel evolution in the phage populations, early in the experiment (sampled on day 39). These consisted mostly of non-synonymous single-nucleotide-polymorphisms and a few instances of indel, altogether affecting 18 open-reading-frames, the majority of which were predicted to encode virion structures including those involved in phage adsorption onto host (i.e., baseplate wedge, short tail fibre, adhesin component). Mutations that emerged later (sampled on day 500), on the other hand, were found at a larger range of frequencies, with many lacking repeatability across the chemostats. This is indicative of some degree of between-population divergence in the phage evolutionary trajectory over time. A few of the early and late mutations were detected within putative auxiliary metabolic genes, but these generally occurred in only one or two of the chemostats. Less repeatable mutations may have higher fitness costs, thus drawing our attention onto the role of trade-offs in modulating the trajectory of a host-phage coevolution.

Differential toxicity of bioorthogonal non-canonical amino acids (BONCAT) in Escherichia coli.

Single-cell methods allow studying the activity of single bacterial cells, potentially shedding light on regulatory mechanisms involved in services like biochemical cycling. Bioorthogonal non-canonical amino acid tagging (BONCAT) is a promising method for studying bacterial activity in natural communities, using the methionine analogues L-azidohomoalanine (AHA) and L-homopropargylglycine (HPG) to track protein production in single cells. Both AHA and HPG have been deemed non-toxic, but recent findings suggest that HPG affects bacterial metabolism. In this study we examined the effect of AHA and HPG on Escherichia coli with respect to acute toxicity and growth. E. coli exposed to 5.6-90 µM HPG showed no growth, and the growth rate was significantly reduced at >0.35 µM HPG, compared to the HPG-free control. In contrast, E. coli showed growth at concentrations up to 9 mM AHA. In assays where AHA or HPG were added during the exponential growth phase, the growth sustained but the growth rate was immediately reduced at the highest concentrations (90 µM HPG and 10 mM AHA). Prolonged incubations (20h) with apparently non-toxic concentrations suggest that the cells incorporating NCAAs fail to divide and do not contribute to the next generation resulting in the relative abundance of labelled cells to decrease over time. These results show that HPG and AHA have different impact on the growth of E. coli. Both concentration and incubation time affect the results and need to be considered when designing BONCAT experiments and evaluating results. Time course incubations are suggested as a possible way to obtain more reliable results.

Individual-based model highlights the importance of trade-offs for virus-host population dynamics and long-term co-existence.

Viruses play diverse and important roles in ecosystems. In recent years, trade-offs between host and virus traits have gained increasing attention in viral ecology and evolution. However, microbial organism traits, and viral population parameters in particular, are challenging to monitor. Mathematical and individual-based models are useful tools for predicting virus-host dynamics. We have developed an individual-based evolutionary model to study ecological interactions and evolution between bacteria and viruses, with emphasis on the impacts of trade-offs between competitive and defensive host traits on bacteria-phage population dynamics and trait diversification. Host dynamics are validated with lab results for different initial virus to host ratios (VHR). We show that trade-off based, as opposed to random bacteria-virus interactions, result in biologically plausible evolutionary outcomes, thus highlighting the importance of trade-offs in shaping biodiversity. The effects of nutrient concentration and other environmental and organismal parameters on the virus-host dynamics are also investigated. Despite its simplicity, our model serves as a powerful tool to study bacteria-phage interactions and mechanisms for evolutionary diversification under various environmental conditions.

Plant traits and vegetation data from climate warming experiments along an 1100 m elevation gradient in Gongga Mountains, China.

Functional trait data enhance climate change research by linking climate change, biodiversity response, and ecosystem functioning, and by enabling comparison between systems sharing few taxa. Across four sites along a 3000-4130 m a.s.l. gradient spanning 5.3 °C in growing season temperature in Mt. Gongga, Sichuan, China, we collected plant functional trait and vegetation data from control plots, open top chambers (OTCs), and reciprocally transplanted vegetation turfs. Over five years, we recorded vascular plant composition in 140 experimental treatment and control plots. We collected trait data associated with plant resource use, growth, and life history strategies (leaf area, leaf thickness, specific leaf area, leaf dry matter content, leaf C, N and P content and C and N isotopes) from local populations and from experimental treatments. The database consists of 6,671 plant records and 36,743 trait measurements (increasing the trait data coverage of the regional flora by 500%) covering 11 traits and 193 plant taxa (ca. 50% of which have no previous published trait data) across 37 families.