Segment self-repulsion is the major driving force of influenza genome packaging

The genome of influenza A virus consists of eight separate RNA segments, which are selectively packaged into virions prior to virus budding. The microscopic mechanism of highly selective packaging involves molecular interactions between packaging signals in the genome segments and remains poorly understood. We propose that the condition of proper packaging can be formulated as a large gap between RNA-RNA interaction energies in the viable virion with eight unique segments and in improperly packed assemblages lacking the complete genome. We then demonstrate that selective packaging of eight unique segments into an infective influenza virion can be achieved by self-repulsion of identical segments at the virion assembly stage, rather than by previously hypothesized intricate molecular recognition of particular segments. Using Monte Carlo simulations to maximize the energy gap, without any other assumptions, we generated model eight-segment virions, which all display specific packaging, strong self-repulsion of the segments, and reassortment patterns similar to natural influenza. The model provides a biophysical foundation of influenza genome packaging and reassortment and serves as an important step towards robust sequence-driven prediction of reassortment patterns of the influenza virus

Positive Selection Drives Preferred Segment Combinations during Influenza Virus Reassortment

Influenza A virus (IAV) has a segmented genome that allows for the exchange of genome segments between different strains. This reassortment accelerates evolution by breaking linkage, helping IAV cross species barriers to potentially create highly virulent strains. Challenges associated with monitoring the process of reassortment in molecular detail have limited our understanding of its evolutionary implications. We applied a novel deep sequencing approach with quantitative analysis to assess the in vitro temporal evolution of genomic reassortment in IAV. The combination of H1N1 and H3N2 strains reproducibly generated a new H1N2 strain with the hemagglutinin and nucleoprotein segments originating from H1N1 and the remaining six segments from H3N2. By deep sequencing the entire viral genome, we monitored the evolution of reassortment, quantifying the relative abundance of all IAV genome segments from the two parent strains over time and measuring the selection coefficients of the reassorting segments. Additionally, we observed several mutations coemerging with reassortment that were not found during passaging of pure parental IAV strains. Our results demonstrate how reassortment of the segmented genome can accelerate viral evolution in IAV, potentially enabled by the emergence of a small number of individual mutation

Positive Selection Drives Preferred Segment Combinations during Influenza Virus Reassortment

Influenza A virus (IAV) has a segmented genome that allows for the exchange of genome segments between different strains. This reassortment accelerates evolution by breaking linkage, helping IAV cross species barriers to potentially create highly virulent strains. Challenges associated with monitoring the process of reassortment in molecular detail have limited our understanding of its evolutionary implications. We applied a novel deep sequencing approach with quantitative analysis to assess the in vitro temporal evolution of genomic reassortment in IAV. The combination of H1N1 and H3N2 strains reproducibly generated a new H1N2 strain with the hemagglutinin and nucleoprotein segments originating from H1N1 and the remaining six segments from H3N2. By deep sequencing the entire viral genome, we monitored the evolution of reassortment, quantifying the relative abundance of all IAV genome segments from the two parent strains over time and measuring the selection coefficients of the reassorting segments. Additionally, we observed several mutations coemerging with reassortment that were not found during passaging of pure parental IAV strains. Our results demonstrate how reassortment of the segmented genome can accelerate viral evolution in IAV, potentially enabled by the emergence of a small number of individual mutation

Clustering of strong replicators associated with active promoters is sufficient to establish an early-replicating domain

Vertebrate genomes replicate according to a precise temporal program strongly correlated with their organization into A/B compartments. Until now, the molecular mechanisms underlying the establishment of early-replicating domains remain largely unknown. We defined two minimal cis-element modules containing a strong replication origin and chromatin modifier binding sites capable of shifting a targeted mid-late-replicating region for earlier replication. The two origins overlap with a constitutive or a silent tissue-specific promoter. When inserted side-by-side, these modules advance replication timing over a 250 kb region through the cooperation with one endogenous origin located 30 kb away. Moreover, when inserted at two chromosomal sites separated by 30 kb, these two modules come into close physical proximity and form an early-replicating domain establishing more contacts with active A compartments. The synergy depends on the presence of the active promoter/origin. Our results show that clustering of strong origins located at active promoters can establish early-replicating domains

Случай сочетанной инфекции оспы обезьян и вируса простого герпеса 1 типа

The first Russian clinical case of monkeypox in combination with herpes simplex type 1 infection in a 29-year-old man who returned from Portugal is described. The protocols for sequencing the virus genome are presented. Particular attention is paid to the difficulty of diagnosing vesicular rash in patients with a suspicious history.Описан первый в России клинический случай оспы обезьян в сочетании с инфекцией простого герпеса 1-го типа у мужчины 29 лет, вернувшегося из Испании. Представлены протоколы секвенирования генома вируса. Особое внимание уделено сложности диагностики везикулярной сыпи у пациентов с подозрительным анамнезом

Massively parallel sampling of lattice proteins reveals foundations of thermal adaptation

Evolution of proteins in bacteria and archaea living in different conditions leads to significant correlations between amino acid usage and environmental temperature. The origins of these correlations are poorly understood, and an important question of protein theory, physics-based prediction of types of amino acids overrepresented in highly thermostable proteins, remains largely unsolved. Here, we extend the random energy model of protein folding by weighting the interaction energies of amino acids by their frequencies in protein sequences and predict the energy gap of proteins designed to fold well at elevated temperatures. To test the model, we present a novel scalable algorithm for simultaneous energy calculation for many sequences in many structures, targeting massively parallel computing architectures such as graphics processing unit. The energy calculation is performed by multiplying two matrices, one representing the complete set of sequences, and the other describing the contact maps of all structural templates. An implementation of the algorithm for the CUDA platform is available at http://www.github.com/kzeldovich/galeprot and calculates protein folding energies over 250 times faster than a single central processing unit. Analysis of amino acid usage in 64-mer cubic lattice proteins designed to fold well at different temperatures demonstrates an excellent agreement between theoretical and simulated values of energy gap. The theoretical predictions of temperature trends of amino acid frequencies are significantly correlated with bioinformatics data on 191 bacteria and archaea, and highlight protein folding constraints as a fundamental selection pressure during thermal adaptation in biological evolution