34 research outputs found
Gain-of-Function Experiments With Bacteriophage Lambda Uncover Residues Under Diversifying Selection in Nature
Viral gain-of-function mutations frequently evolve during laboratory experiments. Whether the specific mutations that evolve in the lab also evolve in nature and whether they have the same impact on evolution in the real world is unknown. We studied a model virus, bacteriophage 位, that repeatedly evolves to exploit a new host receptor under typical laboratory conditions. Here, we demonstrate that two residues of 位鈥檚 J protein are required for the new function. In natural 位 variants, these amino acid sites are highly diverse and evolve at high rates. Insertions and deletions at these locations are associated with phylogenetic patterns indicative of ecological diversification. Our results show that viral evolution in the laboratory mirrors that in nature and that laboratory experiments can be coupled with protein sequence analyses to identify the causes of viral evolution in the real world. Furthermore, our results provide evidence for widespread host-shift evolution in lambdoid viruses
Gain-of-Function Experiments With Bacteriophage Lambda Uncover Residues Under Diversifying Selection in Nature
Viral gain-of-function mutations frequently evolve during laboratory experiments. Whether the specific mutations that evolve in the lab also evolve in nature and whether they have the same impact on evolution in the real world is unknown. We studied a model virus, bacteriophage 位, that repeatedly evolves to exploit a new host receptor under typical laboratory conditions. Here, we demonstrate that two residues of 位鈥檚 J protein are required for the new function. In natural 位 variants, these amino acid sites are highly diverse and evolve at high rates. Insertions and deletions at these locations are associated with phylogenetic patterns indicative of ecological diversification. Our results show that viral evolution in the laboratory mirrors that in nature and that laboratory experiments can be coupled with protein sequence analyses to identify the causes of viral evolution in the real world. Furthermore, our results provide evidence for widespread host-shift evolution in lambdoid viruses
Exploiting Fast-Variables to Understand Population Dynamics and Evolution
We describe a continuous-time modelling framework for biological population
dynamics that accounts for demographic noise. In the spirit of the methodology
used by statistical physicists, transitions between the states of the system
are caused by individual events while the dynamics are described in terms of
the time-evolution of a probability density function. In general, the
application of the diffusion approximation still leaves a description that is
quite complex. However, in many biological applications one or more of the
processes happen slowly relative to the system's other processes, and the
dynamics can be approximated as occurring within a slow low-dimensional
subspace. We review these time-scale separation arguments and analyse the more
simple stochastic dynamics that result in a number of cases. We stress that it
is important to retain the demographic noise derived in this way, and emphasise
this point by showing that it can alter the direction of selection compared to
the prediction made from an analysis of the corresponding deterministic model.Comment: 33 pages, 9 figure
Large-scale discovery of protein interactions at residue resolution using co-evolution calculated from genomic sequences
ncreasing numbers of protein interactions have been identified in high-throughput experiments, but only a small proportion have solved structures. Recently, sequence coevolution-based approaches have led to a breakthrough in predicting monomer protein structures and protein interaction interfaces. Here, we address the challenges of large-scale interaction prediction at residue resolution with a fast alignment concatenation method and a probabilistic score for the interaction of residues. Importantly, this method (EVcomplex2) is able to assess the likelihood of a protein interaction, as we show here applied to large-scale experimental datasets where the pairwise interactions are unknown. We predict 504 interactions de novo in the E. coli membrane proteome, including 243 that are newly discovered. While EVcomplex2 does not require available structures, coevolving residue pairs can be used to produce structural models of protein interactions, as done here for membrane complexes including the Flagellar Hook-Filament Junction and the Tol/Pal complex
Data from: Gain-of-function experiments in bacteriophage lambda uncover residues under diversifying selection in nature
Viral gain-of-function mutations frequently evolve during laboratory experiments. Whether the specific mutations that evolve in the lab also evolve in nature and whether they have the same impact on evolution in the real world is unknown. We studied a model virus, bacteriophage 位, that repeatedly evolves to exploit a new host receptor under typical laboratory conditions. Here we demonstrate that two residues of 位鈥檚 J protein are required for the new function. In natural 位 variants, these amino acid sites are highly diverse and evolve at high rates. Insertions and deletions at these locations are associated with phylogenetic patterns indicative of ecological diversification. Our results show that viral evolution in the laboratory mirrors that in nature and that laboratory experiments can be coupled with protein sequence analyses to identify the causes of viral evolution in the real world. Furthermore, our results provide evidence for widespread host-shift evolution in lambdoid viruses
Analysis of bacterial genomes from an evolution experiment with horizontal gene transfer shows that recombination can sometimes overwhelm selection
Data from: Haplotype-phased synthetic long reads from short-read sequencing
Next-generation DNA sequencing has revolutionized the study of biology. However, the short read lengths of the dominant instruments complicate assembly of complex genomes and haplotype phasing of mixtures of similar sequences. Here we demonstrate a method to reconstruct the sequences of individual nucleic acid molecules up to 11.6 kilobases in length from short (150-bp) reads. We show that our method can construct 99.97%-accurate synthetic reads from bacterial, plant, and animal genomic samples, full-length mRNA sequences from human cancer cell lines, and individual HIV env gene variants from a mixture. The preparation of multiple samples can be multiplexed into a single tube, further reducing effort and cost relative to competing approaches. Our approach generates sequencing libraries in three days from less than one microgram of DNA in a single-tube format without custom equipment or specialized expertise
Haplotype-Phased Synthetic Long Reads from Short-Read Sequencing
<div><p>Next-generation DNA sequencing has revolutionized the study of biology. However, the short read lengths of the dominant instruments complicate assembly of complex genomes and haplotype phasing of mixtures of similar sequences. Here we demonstrate a method to reconstruct the sequences of individual nucleic acid molecules up to 11.6 kilobases in length from short (150-bp) reads. We show that our method can construct 99.97%-accurate synthetic reads from bacterial, plant, and animal genomic samples, full-length mRNA sequences from human cancer cell lines, and individual HIV <i>env</i> gene variants from a mixture. The preparation of multiple samples can be multiplexed into a single tube, further reducing effort and cost relative to competing approaches. Our approach generates sequencing libraries in three days from less than one microgram of DNA in a single-tube format without custom equipment or specialized expertise.</p></div