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Full genome sequences are increasingly used to track the geographic spread and transmission dynamics of viral pathogens. Here, with a focus on Israel, we sequence 212 SARS-CoV-2 sequences and use them to perform a comprehensive analysis to trace the origins and spread of the virus. We find that travelers returning from the United States of America significantly contributed to viral spread in Israel, more than their proportion in incoming infected travelers. Using phylodynamic analysis, we estimate that the basic reproduction number of the virus was initially around 2.5, dropping by more than two-thirds following the implementation of social distancing measures. We further report high levels of transmission heterogeneity in SARS-CoV-2 spread, with between 2-10% of infected individuals resulting in 80% of secondary infections. Overall, our findings demonstrate the effectiveness of social distancing measures for reducing viral spread. In this study, Adi Stern and colleagues use full genome sequences of SARS-CoV-2 to look at the rate of infections in Israel. They report that social distancing had a significant effect on minimising the rate of transmission, and find evidence for transmission heterogeneity (superspreading events).

Abstract Cheater viruses cannot replicate on their own yet replicate faster than the wild type (WT) when the 2 viruses coinfect the same cell. Cheaters must possess dual genetic features: a defect, which leads to their inability to infect cells on their own, and a selective advantage over WT during coinfection. Previously, we have discovered 2 point-mutant cheaters of the MS2 bacteriophage. Here, we set out to discover the possible repertoire of cheater MS2 viruses by performing experimental evolution at a very high multiplicity of infection. Our results revealed a third point-mutant cheater that arose in 8 biological replicas. Each of the 3 primary cheaters disrupts the fine balance necessary for phage replication, in different ways that create a defect + advantage. We found that over time, the point-mutant cheaters accumulate additional secondary mutations, which alter other stages of the viral replication cycle, complementing the disruptions created by the original cheater. Intriguingly, cheater and secondary mutations almost always reside in very close proximity on the genome. This region encodes for multiple functions: overlapping reading frames as well as overlapping RNA structures critical for transitioning from one stage to another in the viral replication cycle. This region of overlap explains the dual functions of cheaters, as one mutation can have pleiotropic effects. Overall, these findings underscore how viruses, whose dense genomes often have overlapping functions, can easily evolve point-mutant cheaters, and how cheaters can evolve to alter the intricate balance of the viral replication cycle.

Abstract RNA viruses are particularly notorious for their high levels of genetic diversity, which is generated through the forces of mutation and natural selection. However, disentangling these two forces is a considerable challenge, and this may lead to widely divergent estimates of viral mutation rates, as well as difficulties in inferring the fitness effects of mutations. Here, we develop, test, and apply an approach aimed at inferring the mutation rate and key parameters that govern natural selection, from haplotype sequences covering full-length genomes of an evolving virus population. Our approach employs neural posterior estimation, a computational technique that applies simulation-based inference with neural networks to jointly infer multiple model parameters. We first tested our approach on synthetic data simulated using different mutation rates and selection parameters while accounting for sequencing errors. Reassuringly, the inferred parameter estimates were accurate and unbiased. We then applied our approach to haplotype sequencing data from a serial passaging experiment with the MS2 bacteriophage, a virus that parasites Escherichia coli. We estimated that the mutation rate of this phage is around 0.2 mutations per genome per replication cycle (95% highest density interval: 0.051–0.56). We validated this finding with two different approaches based on single-locus models that gave similar estimates but with much broader posterior distributions. Furthermore, we found evidence for reciprocal sign epistasis between four strongly beneficial mutations that all reside in an RNA stem loop that controls the expression of the viral lysis protein, responsible for lysing host cells and viral egress. We surmise that there is a fine balance between over- and underexpression of lysis that leads to this pattern of epistasis. To recap, we have developed an approach for joint inference of the mutation rate and selection parameters from full haplotype data with sequencing errors and used it to reveal features governing MS2 evolution.

RNA viruses are particularly notorious for their high levels of genetic diversity, which is generated through the forces of mutation and natural selection. However, disentangling these two forces is a considerable challenge, and this may lead to widely divergent estimates of viral mutation rates, as well as difficulties in inferring fitness effects of mutations. Here, we develop, test, and apply an approach aimed at inferring the mutation rate and key parameters that govern natural selection, from haplotype sequences covering full length genomes of an evolving virus population. Our approach employs neural posterior estimation, a computational technique that applies simulation-based inference with neural networks to jointly infer multiple model parameters. We first tested our approach on synthetic data simulated using different mutation rates and selection parameters while accounting for sequencing errors. Reassuringly, the inferred parameter estimates were accurate and unbiased. We then applied our approach to haplotype sequencing data from a serial-passaging experiment with the MS2 bacteriophage. We estimated that the mutation rate of this phage is around 0.2 mutations per genome per replication cycle (95% highest density interval: 0.051-0.56). We validated this finding with two different approaches based on single-locus models that gave similar estimates but with much broader posterior distributions. Furthermore, we found evidence for reciprocal sign epistasis between four strongly beneficial mutations that all reside in an RNA stem-loop that controls the expression of the viral lysis protein, responsible for lysing host cells and viral egress. We surmise that there is a fine balance between over and under-expression of lysis that leads to this pattern of epistasis. To summarize, we have developed an approach for joint inference of the mutation rate and selection parameters from full haplotype data with sequencing errors, and used it to reveal features governing MS2 evolution.Competing Interest StatementThe authors have declared no competing interest.Footnotes* https://github.com/Stern-Lab/ms2-mutation-rate* https://www.ncbi.nlm.nih.gov/sra/PRJNA902661* https://zenodo.org/record/7486851

Ribonucleic acid (RNA) is a polymer with pivotal functions in many biological processes. RNA structure determination is thus a vital step towards understanding its function. The secondary structure of RNA is stabilized by hydrogen bonds formed between nucleotide base pairs and it defines the positions and shapes of functional stem-loops, internal loops, bulges, and other functional and structural elements. In this work we present a methodology for studying large intact RNA biomolecules using homonuclear 15N solid state nuclear magnetic resonance (NMR) spectroscopy. We show that Proton Driven Spin Diffusion (PDSD) experiments with long mixing times, up to 16s, improved by the incorporation of multiple rotor-synchronous 1H inversion pulses (termed Radiofrequency Dipolar Recoupling, RFDR, pulses), reveal key hydrogen-bond contacts. In the full-length RNA isolated from MS2 phage, we observed strong and dominant contributions of G-C Watson-Crick base pairs, and beyond these common interactions, we observe a significant contribution of the G-U wobble base pairs. Moreover, we can differentiate base-paired and non-base-paired nitrogen atoms. Using the improved technique facilitates characterization of hydrogen-bond types in intact large-scale RNA using solid-state NMR. It can be highly useful to guide secondary structure prediction techniques, and possibly structure determination methods. Competing Interest Statement The authors have declared no competing interest. Footnotes * Revised text and Supporting Information.

One of the key challenges in the field of genetics is the inference of haplotypes from next generation sequencing data. The MinION Oxford Nanopore sequencer allows sequencing long reads, with the potential of sequencing complete genes, and even complete genomes of viruses, in individual reads. However, MinION suffers from high error rates, rendering the detection of true variants difficult. Here we propose a new statistical approach named AssociVar, which differentiates between true mutations and sequencing errors from direct RNA/DNA sequencing using MinION. Our strategy relies on the assumption that sequencing errors will be dispersed randomly along sequencing reads, and hence will not be associated with each other, whereas real mutations will display a non-random pattern of association with other mutations. We demonstrate our approach using direct RNA sequencing data from evolved populations of the MS2 bacteriophage, whose small genome makes it ideal for MinION sequencing. AssociVar inferred several mutations in the phage genome, which were corroborated using parallel Illumina sequencing. This allowed us to reconstruct full genome viral haplotypes constituting different strains that were present in the sample. Our approach is applicable to long read sequencing data from any organism for accurate detection of bona fide mutations and inter-strain polymorphisms.

Cheater viruses, alternatively denoted as defective interfering viruses, cannot replicate on their own yet replicate faster than the wild type (WT) when the two viruses coinfect the same cell. Cheaters must possess dual genetic features: a defect, which leads to their inability to infect cells on their own, and a selective advantage over WT during co-infection. Previously, we have discovered two point-mutant cheaters of the MS2 bacteriophage. Here, we set out to discover the possible repertoire of cheater MS2 viruses by performing experimental evolution at a very high multiplicity of infection (MOI). Our results revealed a third point-mutant cheater that arose in eight biological replicas. Each of the three cheaters disrupts the fine balance necessary for phage replication, in different ways that create a defect + advantage. We found that over time, the point mutant cheaters accumulate additional “helper” mutations, which alter other stages of the viral replication cycle, complementing the disruptions created by the original cheater. Intriguingly, cheater and helper mutations almost always reside in very close proximity on the genome. This region encodes for multiple functions: overlapping reading frames as well as overlapping RNA structures critical for transitioning from one stage to another in the viral replication cycle. This region of overlap explains the dual functions of cheaters, as one mutation can have pleiotropic effects. Overall, these findings underscore how viruses, whose dense genomes often have overlapping functions, can easily evolve point-mutant cheaters, and how cheaters can evolve to alter the intricate balance of the viral replication cycle.

Background Interventions using split belt treadmills (SBTM) aim to improve gait symmetry (GA) in Parkinson's disease (PD). Comparative effects in conjugated SBTM conditions were not studied systematically despite potentially affecting intervention outcomes. We compared gait adaptation effects instigated by SBTM walking with respect to the type (increased\\decreased speed) and the side (more/less affected) of the manipulated belt in PD. Methods Eight individuals with PD performed four trials of SBTM walking, each consisted of baseline tied belt configuration, followed by split belt setting – either WS or BS belt's speed increased or decreased by 50% from baseline, and final tied belt configuration. Based on the disease's motor symptoms, a 'worst' side (WS) and a 'best' side (BS) were defined for each participant. Results SB initial change in GA was significant regardless of condition ( p  ≤ 0.02). This change was however more pronounced for BS-decrease compared with its matching condition WS-increase ( p  = 0.016). Similarly, the same was observed for WS-decrease compared to BS-increase ( p  = 0.013). Upon returning to tied belt condition, both BS-decrease and WS-increased resulted in a significant change in GA ( p  = 0.04). Upper limb asymmetry followed a similar trend of GA reversal, although non-significant. Conclusions Stronger effects on GA were obtained by decreasing the BS belt’s speed of the best side, rather than increasing the speed of the worst side. Albeit a small sample size, which limits the generalisability of these results, we propose that future clinical studies would benefit from considering such methodological planning of SBTM intervention, for maximising of intervention outcomes. Larger samples may reveal arm swinging asymmetries alterations to match SBTM adaptation patterns. Finally, further research is warranted to study post-adaption effects in order to define optimal adaptation schemes to maximise the therapeutic effect of SBTM based interventions.

There is a lot of evidence that early developmental therapy achieves impressive therapeutic results for those who require it. Therefore, developmental follow-up, which includes the process of monitoring the child’s development over time, makes it possible to identify possible developmental problems and treat them from a young age. This assumption is true in relation to all children with developmental difficulties but is mainly true in the context of children with a diagnosis of autism. However, despite the abundance of developmental scales for the neurotypical population, there are currently no valid scales for assessing motor function for children with autism. The current article focuses on the presentation of the motor delay, identified according to the literature, in many of the children with autism and requires the provision of professional and compatible treatment for these children. This motor delay and the lack of a motor assessment tool for children with autism raises the need for an adapted motor developmental assessment tool, which will produce measurable results, to enable the monitoring of the aforementioned disability and the receiving of tailored treatment from the physiotherapists who deal with the development of children with autism at an early age. The article reviews common existing assessment tools for use in assessing normal development in children with autism, presents the limitations and the challenges that arise when using these assessment tools with children on the autism spectrum and presents the need for a new developmental assessment tool that will be built and validated specifically for children with autism.

Background: Gross motor function in Rett syndrome (RTT) is always limited. The complex clinical picture typical of most people with RTT requires intensive and specific rehabilitation programs. Previous reports on remotely supervised motor activity programs suggested positive outcomes for this population. The current article describes the impact of a remote-supervised motor activity program carried out by family members of individuals with RTT on achieving rehabilitation goals and improving gross and fine motor functioning and daily physical activity. Methods: Forty subjects with RTT followed a three-month remotely supervised motor activity program carried out by their family members at home after a three-month baseline period. After the end of the intervention, a three-month wash-out period was implemented. Rehabilitation goal achievement, motor functioning, and level of daily physical activity were measured. Results: 82.4% of rehabilitation goals were achieved or overachieved. Participants’ motor functioning and physical activity significantly increased after the intervention (p ˂ 0.001). Improvements were maintained after the wash-out phase. Conclusions: The proposed intervention was effective for people with RTT of various ages and severity levels. The results highlight the need for lifelong, individualized, daily based, and professionally supervised rehabilitation possibilities for individuals with RTT.