Love the one you're with: replicate viral adaptations converge on the same phenotypic change

Bacteriophage-Host Interactions and Coevolution

Bacteriophages are the most abundant entity on the planet and play very relevant roles in the diversity and abundance of their bacterial hosts. These interactions are subject to several factors, such as the first encounter of the phage with its host bacterium, in which molecular interactions are fundamental. Along with this, these interactions depend on the environment and other communities present. This chapter focuses on these phage-bacteria interactions, reviewing the knowledge of the early stage (receptor-binding proteins), host responses (resistance and counter-resistance), and ecological and evolutionary models described to date. In general, knowledge has focused on a few phage-bacteria models and has been deepened by sequencing and metagenomics. The study of phage-bacteria interactions is an essential step for the development of therapies and other applications of phages in the clinical and productive environment.

Transcript degradation and codon usage regulate gene expression in a lytic phage

Many viral genomes are small, containing only single- or double-digit numbers of genes and relatively few regulatory elements. Yet viruses successfully execute complex regulatory programs as they take over their host cells. Here, we propose that some viruses regulate gene expression via a carefully balanced interplay between transcription, translation, and transcript degradation. As our model system, we employ bacteriophage T7, whose genome of approximately sixty genes is well annotated and for which there is a long history of computational models of gene regulation. We expand upon prior modeling work by implementing a stochastic gene expression simulator that tracks individual transcripts, polymerases, ribosomes, and ribonucleases participating in the transcription, translation, and transcript-degradation processes occurring during a T7 infection. By combining this detailed mechanistic modeling of a phage infection with high-throughput gene expression measurements of several strains of bacteriophage T7, evolved and engineered, we can show that both the dynamic interplay between transcription and transcript degradation, and between these two processes and translation, appear to be critical components of T7 gene regulation. Our results point to targeted degradation as a generic gene regulation strategy that may have evolved in many other viruses. Further, our results suggest that detailed mechanistic modeling may uncover the biological mechanisms at work in both evolved and engineered virus variants.

Parallel evolution of HIV-1 in a long-term experiment

One of the most intriguing puzzles in biology is the degree to which evolution is repeatable. The repeatability of evolution, or parallel evolution, has been studied in a variety of model systems, but has rarely been investigated with clinically relevant viruses. To investigate parallel evolution of HIV-1, we passaged two replicate HIV-1 populations for almost 1 year in each of two human T-cell lines. For each of the four evolution lines, we determined the genetic composition of the viral population at nine time points by deep sequencing the entire genome. Mutations that were carried by the majority of the viral population accumulated continuously over 1 year in each evolution line. Many majority mutations appeared in more than one evolution line, that is, our experiments showed an extreme degree of parallel evolution. In one of the evolution lines, 62% of the majority mutations also occur in another line. The parallelism impairs our ability to reconstruct the evolutionary history by phylogenetic methods. We show that one can infer the correct phylogenetic topology by including minority mutations in our analysis. We also find that mutation diversity at the beginning of the experiment is predictive of the frequency of majority mutations at the end of the experiment.

Experimental Evolution of Extreme Resistance to Ionizing Radiation in Escherichia coli after 50 Cycles of Selection

In previous work (D. R. Harris et al., J Bacteriol 191:5240-5252, 2009, https://doi.org/10.1128/JB.00502-09; B. T. Byrne et al., Elife 3:e01322, 2014, https://doi.org/10.7554/eLife.01322), we demonstrated that Escherichia coli could acquire substantial levels of resistance to ionizing radiation (IR) via directed evolution. Major phenotypic contributions involved adaptation of organic systems for DNA repair. We have now undertaken an extended effort to generate E. coli populations that are as resistant to IR as Deinococcus radiodurans After an initial 50 cycles of selection using high-energy electron beam IR, four replicate populations exhibit major increases in IR resistance but have not yet reached IR resistance equivalent to D. radiodurans Regular deep sequencing reveals complex evolutionary patterns with abundant clonal interference. Prominent IR resistance mechanisms involve novel adaptations to DNA repair systems and alterations in RNA polymerase. Adaptation is highly specialized to resist IR exposure, since isolates from the evolved populations exhibit highly variable patterns of resistance to other forms of DNA damage. Sequenced isolates from the populations possess between 184 and 280 mutations. IR resistance in one isolate, IR9-50-1, is derived largely from four novel mutations affecting DNA and RNA metabolism: RecD A90E, RecN K429Q, and RpoB S72N/RpoC K1172I. Additional mechanisms of IR resistance are evident.IMPORTANCE Some bacterial species exhibit astonishing resistance to ionizing radiation, with Deinococcus radiodurans being the archetype. As natural IR sources rarely exceed mGy levels, the capacity of Deinococcus to survive 5,000 Gy has been attributed to desiccation resistance. To understand the molecular basis of true extreme IR resistance, we are using experimental evolution to generate strains of Escherichia coli with IR resistance levels comparable to Deinococcus Experimental evolution has previously generated moderate radioresistance for multiple bacterial species. However, these efforts could not take advantage of modern genomic sequencing technologies. In this report, we examine four replicate bacterial populations after 50 selection cycles. Genomic sequencing allows us to follow the genesis of mutations in populations throughout selection. Novel mutations affecting genes encoding DNA repair proteins and RNA polymerase enhance radioresistance. However, more contributors are apparent.

Mutation-Driven Parallel Evolution during Viral Adaptation

Convergent evolution has been demonstrated across all levels of biological organization, from parallel nucleotide substitutions to convergent evolution of complex phenotypes, but whether instances of convergence are the result of selection repeatedly finding the same optimal solution to a recurring problem or are the product of mutational biases remains unsettled. We generated 20 replicate lineages allowed to fix a single mutation from each of four bacteriophage genotypes under identical selective regimes to test for parallel changes within and across genotypes at the levels of mutational effect distributions and gene, protein, amino acid, and nucleotide changes. All four genotypes shared a distribution of beneficial mutational effects best approximated by a distribution with a finite upper bound. Parallel adaptation was high at the protein, gene, amino acid, and nucleotide levels, both within and among phage genotypes, with the most common first-step mutation in each background fixing on an average in 7 of 20 replicates and half of the substitutions in two of the four genotypes occurring at shared sites. Remarkably, the mutation of largest beneficial effect that fixed for each genotype was never the most common, as would be expected if parallelism were driven by selection. In fact, the mutation of smallest benefit for each genotype fixed in a total of 7 of 80 lineages, equally as often as the mutation of largest benefit, leading us to conclude that adaptation was largely mutation-driven, such that mutational biases led to frequent parallel fixation of mutations of suboptimal effect.

Hidden Complexity of Yeast Adaptation under Simple Evolutionary Conditions

Few studies have "quantitatively" probed how adaptive mutations result in increased fitness. Even in simple microbial evolution experiments, with full knowledge of the underlying mutations and specific growth conditions, it is challenging to determine where within a growth-saturation cycle those fitness gains occur. A common implicit assumption is that most benefits derive from an increased exponential growth rate. Here, we instead show that, in batch serial transfer experiments, adaptive mutants' fitness gains can be dominated by benefits that are accrued in one growth cycle, but not realized until the next growth cycle. For thousands of evolved clones (most with only a single mutation), we systematically varied the lengths of fermentation, respiration, and stationary phases to assess how their fitness, as measured by barcode sequencing, depends on these phases of the growth-saturation-dilution cycles. These data revealed that, whereas all adaptive lineages gained similar and modest benefits from fermentation, most of the benefits for the highest fitness mutants came instead from the time spent in respiration. From monoculture and high-resolution pairwise fitness competition experiments for a dozen of these clones, we determined that the benefits "accrued" during respiration are only largely "realized" later as a shorter duration of lag phase in the following growth cycle. These results reveal hidden complexities of the adaptive process even under ostensibly simple evolutionary conditions, in which fitness gains can accrue during time spent in a growth phase with little cell division, and reveal that the memory of those gains can be realized in the subsequent growth cycle.