Viral infection outcomes are governed by the complex and dynamic interplay between the infecting virus population and the host response. It is increasingly clear that both viral and host cell populations are highly heterogeneous, but little is known about how this heterogeneity influences infection dynamics or viral pathogenicity. To dissect the interactions between influenza A virus (IAV) and host cell heterogeneity, we examined the combined host and viral transcriptomes of thousands of individual cells, each infected with a single IAV virion. We observed complex patterns of viral gene expression and the existence of multiple distinct host transcriptional responses to infection at the single cell level. We show that human H1N1 and H3N2 strains differ significantly in patterns of both viral and host anti-viral gene transcriptional heterogeneity at the single cell level. Our analyses also reveal that semi-infectious particles that fail to express the viral NS can play a dominant role in triggering the innate anti-viral response to infection. Altogether, these data reveal how patterns of viral population heterogeneity can serve as a major determinant of antiviral gene activation. The combination of the enormous diversity of viral populations, underlying heterogeneity within host cells, and random chance mean that no two infected cells look exactly the same. The role that single cell heterogeneity plays in determining infection outcomes remains very poorly understood. Here, we describe an approach that allowed us to quantify both viral and host gene expression in thousands of influenza A virus infected cells. We observed an enormous degree of heterogeneity in both viral and host gene expression between individual infected cells. We found that virions that fail to express the viral NS gene can be major drivers of host antiviral immune activation. Comparison of antiviral gene expression patterns between H1N1 and H3N2 infection revealed surprising differences in single cell patterns of innate immune activation. Altogether, these studies identify patterns of single cell heterogeneity in both host and viral gene expression as a significant driver of infection outcomes.

Background: Riverine ecosystems, highly sensitive to climate change and human activities, are characterized by rapid environmental change to fluctuating water levels and siltation, causing stress on their biological components. We have little understanding of mechanisms by which riverine plant species have developed adaptive strategies to cope with stress in dynamic environments while maintaining growth and development.Results: We report that poplar (Populusspp.) has evolved a systems level "stress proteome" in the leaf-stem-root apoplast continuum to counter biotic and abiotic factors. To obtain apoplast proteins fromP. deltoides, we developed pressure-chamber and water-displacement methods for leaves and stems, respectively. Analyses of 303 proteins and corresponding transcripts coupled with controlled experiments and bioinformatics demonstrate that poplar depends on constitutive and inducible factors to deal with water, pathogen, and oxidative stress. However, each apoplast possessed a unique set of proteins, indicating that response to stress is partly compartmentalized. Apoplast proteins that are involved in glycolysis, fermentation, and catabolism of sucrose and starch appear to enable poplar to grow normally under water stress. Pathogenesis-related proteins mediating water and pathogen stress in apoplast were particularly abundant and effective in suppressing growth of the most prevalent poplar pathogenMelampsora. Unexpectedly, we found diverse peroxidases that appear to be involved in stress-induced cell wall modification in apoplast, particularly during the growing season. Poplar developed a robust antioxidative system to buffer oxidation in stem apoplast.Conclusion: These findings suggest that multistress response in the apoplast constitutes an important adaptive trait for poplar to inhabit dynamic environments and is also a potential mechanism in other riverine plant species.

Tiny silicon microchip–based high-throughput hanging drop arrays allow drug screening and geometric control.

Background: In an important model for neuroscience, songbirds learn to discriminate songs they hear during tape-recorded playbacks, as demonstrated by song-specific habituation of both behavioral and neurogenomic responses in the auditory forebrain. We hypothesized that microRNAs (miRNAs or miRs) may participate in the changing pattern of gene expression induced by song exposure. To test this, we used massively parallel Illumina sequencing to analyse small RNAs from auditory forebrain of adult zebra finches exposed to tape-recorded birdsong or silence.Results: In the auditory forebrain, we identified 121 known miRNAs conserved in other vertebrates. We also identified 34 novel miRNAs that do not align to human or chicken genomes. Five conserved miRNAs showed significant and consistent changes in copy number after song exposure across three biological replications of the song-silence comparison, with two increasing (tgu-miR-25, tgu-miR-192) and three decreasing (tgu-miR-92, tgu-miR-124, tgu-miR-129-5p). We also detected a locus on the Z sex chromosome that produces three different novel miRNAs, with supporting evidence from Northern blot and TaqMan qPCR assays for differential expression in males and females and in response to song playbacks. One of these, tgu-miR-2954-3p, is predicted (by TargetScan) to regulate eight song-responsive mRNAs that all have functions in cellular proliferation and neuronal differentiation.Conclusions: The experience of hearing another bird singing alters the profile of miRNAs in the auditory forebrain of zebra finches. The response involves both known conserved miRNAs and novel miRNAs described so far only in the zebra finch, including a novel sex-linked, song-responsive miRNA. These results indicate that miRNAs are likely to contribute to the unique behavioural biology of learned song communication in songbirds.

Moloney leukemia virus 10 (Mov10) is an RNA helicase that mediates access of the RNA-induced silencing complex to messenger RNAs (mRNAs). Until now, its role as an RNA helicase and as a regulator of retrotransposons has been characterized exclusively in cell lines. We investigated the role of Mov10 in the mouse brain by examining its expression over development and attempting to create a Mov10 knockout mouse. Loss of both Mov10 copies led to early embryonic lethality. Mov10 was significantly elevated in postnatal murine brain, where it bound retroelement RNAs and mRNAs. Mov10 suppressed retroelements in the nucleus by directly inhibiting complementary DNA synthesis, while cytosolic Mov10 regulated cytoskeletal mRNAs to influence neurite outgrowth. We verified this important function by observing reduced dendritic arborization in hippocampal neurons from the Mov10 heterozygote mouse and shortened neurites in the Mov10 knockout Neuro2A cells. Knockdown of Fmrp also resulted in shortened neurites. Mov10, Fmrp, and Ago2 bound a common set of mRNAs in the brain. Reduced Mov10 in murine brain resulted in anxiety and increased activity in a novel environment, supporting its important role in the development of normal brain circuitry. Mov10 is essential for normal neuronal development and brain function. Mov10 preferentially binds RNAs involved in actin binding, neuronal projection, and cytoskeleton. This is a completely new and critically important function for Mov10 in neuronal development and establishes a precedent for Mov10 being an important candidate in neurological disorders that have underlying cytoarchitectural causes like autism and Alzheimer’s disease.

The H3ABioNet pan-African bioinformatics network, which is funded to support the Human Heredity and Health in Africa (H3Africa) program, has developed node-assessment exercises to gauge the ability of its participating research and service groups to analyze typical genome-wide datasets being generated by H3Africa research groups. We describe a framework for the assessment of computational genomics analysis skills, which includes standard operating procedures, training and test datasets, and a process for administering the exercise. We present the experiences of 3 research groups that have taken the exercise and the impact on their ability to manage complex projects. Finally, we discuss the reasons why many H3ABioNet nodes have declined so far to participate and potential strategies to encourage them to do so. Many programs have been developed to boost the technical and computational skills of scientists working in low to medium income countries (LMIC), who often struggle to remain competitive with their peers in more developed parts of the world. Typically, these programs rely on intensive workshops where students acquire and exercise these skills under the supervision of experienced trainers. However, when trainees return to their home institutions, even after extensive exposure to state of the art techniques, they often find it difficult to put the skills they have acquired into practice and to establish themselves as fully independent practitioners. We have attempted to build a framework through which teams of scientists in African research groups can demonstrate that they have acquired the necessary skills to analyze different types of genomic datasets. Three teams of scientists who have successfully submitted to this assessment exercise report their positive experiences. Many potential participants have so far declined the opportunity, and we discuss the reasons for their reluctance as well as possible ways to facilitate their engagement and provide them with incentives. We argue that assessments such as this could be part of any program aiming to develop technical skills in scientists wishing to support genomic research programs.