Microbial populations vary between the upper and lower respiratory tract, but not within biogeographic regions of the lung of healthy horses.

Understanding normal microbial populations within areas of the respiratory tract is essential, as variable regional conditions create different niches for microbial flora, and proliferation of commensal microbes likely contributes to clinical respiratory disease. The objective was to describe microbial population variability between respiratory tract locations in healthy horses. Samples were collected from four healthy adult horses by nasopharyngeal lavage (NPL), transtracheal aspirate (TTA), and bronchoalveolar lavage (BAL) of six distinct regions within the lung. Full-length 16S ribosomal DNA sequencing and microbial profiling analysis was performed. There was a large amount of diversity, with over 1797 ASVs identified, reduced to 94 taxa after tip agglomeration and prevalence filtering. Number of taxa and diversity were highly variable across horses, sample types, and BAL locations. Firmicutes, proteobacteria, and actinobacteria were the predominant phyla. There was a significant difference in richness (Chao1, p = 0.02) and phylogenetic diversity (FaithPD, p = 0.01) between NPL, TTA, and BAL. Sample type (p = 0.03) and horse (p = 0.005) contributed significantly to Bray-Curtis compositional diversity, while Weighted Unifrac metric was only affected by simplified sample type (NPL and TTA vs BAL, p = 0.04). There was no significant effect of BAL locations within the lung with alpha or beta diversity statistical tests. Overall findings support diverse microbial populations that were variable between upper and lower respiratory tract locations, but with no apparent difference in microbial populations of the six biogeographic regions of the lung, suggesting that BAL fluid obtained blindly by standard clinical techniques may be sufficient for future studies in healthy horses.

A Gram-negative-selective antibiotic that spares the gut microbiome.

Infections caused by Gram-negative pathogens are increasingly prevalent and are typically treated with broad-spectrum antibiotics, resulting in disruption of the gut microbiome and susceptibility to secondary infections1-3. There is a critical need for antibiotics that are selective both for Gram-negative bacteria over Gram-positive bacteria, as well as for pathogenic bacteria over commensal bacteria. Here we report the design and discovery of lolamicin, a Gram-negative-specific antibiotic targeting the lipoprotein transport system. Lolamicin has activity against a panel of more than 130 multidrug-resistant clinical isolates, shows efficacy in multiple mouse models of acute pneumonia and septicaemia infection, and spares the gut microbiome in mice, preventing secondary infection with Clostridioides difficile. The selective killing of pathogenic Gram-negative bacteria by lolamicin is a consequence of low sequence homology for the target in pathogenic bacteria versus commensals; this doubly selective strategy can be a blueprint for the development of other microbiome-sparing antibiotics.

Differential gene expression in response to fungal pathogen exposure in the aquatic invertebrate, Daphnia dentifera.

While vertebrate immune systems are appreciated for their complexity and adaptability, invertebrate immunity is often considered to be less complex. However, immune responses in many invertebrates likely involve sophisticated processes. Interactions between the crustacean host Daphnia dentifera and its fungal pathogen Metschnikowia bicuspidata provide an excellent model for exploring the mechanisms underlying crustacean immunity. To explore the genomic basis of immunity in Daphnia, we used RNA-sequencing technology to quantify differential gene expression between individuals of a single host genotype exposed or unexposed to M. bicuspidata over 24 h. Transcriptomic analyses showed that the number of differentially expressed genes between the control (unexposed) and experimental (exposed) groups increased over time. Gene ontology enrichment analysis revealed that differentially expressed genes were enriched for immune-related molecules and processes, such as cuticle development, prostaglandin, and defense response processes. Our findings provide a suite of immunologically relevant genes and suggest the presence of a rapidly upregulated immune response involving the cuticle in Daphnia. Studies involving gene expression responses to pathogen exposure shine a light on the processes occurring during the course of infection. By leveraging knowledge on the genetic basis for immunity, immune mechanisms can be more thoroughly understood to refine our understanding of disease spread within invertebrate populations.

Using a multiple-delivery-mode training approach to develop local capacity and infrastructure for advanced bioinformatics in Africa.

With more microbiome studies being conducted by African-based research groups, there is an increasing demand for knowledge and skills in the design and analysis of microbiome studies and data. However, high-quality bioinformatics courses are often impeded by differences in computational environments, complicated software stacks, numerous dependencies, and versions of bioinformatics tools along with a lack of local computational infrastructure and expertise. To address this, H3ABioNet developed a 16S rRNA Microbiome Intermediate Bioinformatics Training course, extending its remote classroom model. The course was developed alongside experienced microbiome researchers, bioinformaticians, and systems administrators, who identified key topics to address. Development of containerised workflows has previously been undertaken by H3ABioNet, and Singularity containers were used here to enable the deployment of a standard replicable software stack across different hosting sites. The pilot ran successfully in 2019 across 23 sites registered in 11 African countries, with more than 200 participants formally enrolled and 106 volunteer staff for onsite support. The pulling, running, and testing of the containers, software, and analyses on various clusters were performed prior to the start of the course by hosting classrooms. The containers allowed the replication of analyses and results across all participating classrooms running a cluster and remained available posttraining ensuring analyses could be repeated on real data. Participants thus received the opportunity to analyse their own data, while local staff were trained and supported by experienced experts, increasing local capacity for ongoing research support. This provides a model for delivering topic-specific bioinformatics courses across Africa and other remote/low-resourced regions which overcomes barriers such as inadequate infrastructures, geographical distance, and access to expertise and educational materials.

Genome biology of the paleotetraploid perennial biomass crop Miscanthus.

Miscanthus is a perennial wild grass that is of global importance for paper production, roofing, horticultural plantings, and an emerging highly productive temperate biomass crop. We report a chromosome-scale assembly of the paleotetraploid M. sinensis genome, providing a resource for Miscanthus that links its chromosomes to the related diploid Sorghum and complex polyploid sugarcanes. The asymmetric distribution of transposons across the two homoeologous subgenomes proves Miscanthus paleo-allotetraploidy and identifies several balanced reciprocal homoeologous exchanges. Analysis of M. sinensis and M. sacchariflorus populations demonstrates extensive interspecific admixture and hybridization, and documents the origin of the highly productive triploid bioenergy crop M. × giganteus. Transcriptional profiling of leaves, stem, and rhizomes over growing seasons provides insight into rhizome development and nutrient recycling, processes critical for sustainable biomass accumulation in a perennial temperate grass. The Miscanthus genome expands the power of comparative genomics to understand traits of importance to Andropogoneae grasses.

Field pathogenomics of Fusarium head blight reveals pathogen transcriptome differences due to host resistance.

Fusarium head blight (FHB), caused by Fusarium graminearum and other Fusarium species, is a detrimental disease that affects small grains such as wheat around the world. Management of FHB is difficult, and surveillance as well as a better understanding of pathogen aggressiveness is needed for improved control. F. graminearum disease severity varies depending on the resistance of the host genotype. In this study, we used the field pathogenomics method to investigate gene expression and population structure of isolates collected from wheat lines of varying resistance levels (susceptible, intermediate, and resistant) as well as an axenic control. Differential gene expression was found among isolates collected from different host genotypes. Candidate gene sets were identified for both F. graminearum infection of specific host genotypes and general infection to wheat. Population structure of isolates from different resistance level sources was the same, with all isolates belonging to the NA1 population.

Sequencing Framework for the Sensitive Detection and Precise Mapping of Defective Interfering Particle-Associated Deletions across Influenza A and B Viruses.

The mechanisms and consequences of defective interfering particle (DIP) formation during influenza virus infection remain poorly understood. The development of next-generation sequencing (NGS) technologies has made it possible to identify large numbers of DIP-associated sequences, providing a powerful tool to better understand their biological relevance. However, NGS approaches pose numerous technical challenges, including the precise identification and mapping of deletion junctions in the presence of frequent mutation and base-calling errors, and the potential for numerous experimental and computational artifacts. Here, we detail an Illumina-based sequencing framework and bioinformatics pipeline capable of generating highly accurate and reproducible profiles of DIP-associated junction sequences. We use a combination of simulated and experimental control data sets to optimize pipeline performance and demonstrate the absence of significant artifacts. Finally, we use this optimized pipeline to reveal how the patterns of DIP-associated junction formation differ between different strains and subtypes of influenza A and B viruses and to demonstrate how these data can provide insight into mechanisms of DIP formation. Overall, this work provides a detailed roadmap for high-resolution profiling and analysis of DIP-associated sequences within influenza virus populations.IMPORTANCE Influenza virus defective interfering particles (DIPs) that harbor internal deletions within their genomes occur naturally during infection in humans and during cell culture. They have been hypothesized to influence the pathogenicity of the virus; however, their specific function remains elusive. The accurate detection of DIP-associated deletion junctions is crucial for understanding DIP biology but is complicated by an array of technical issues that can bias or confound results. Here, we demonstrate a combined experimental and computational framework for detecting DIP-associated deletion junctions using next-generation sequencing (NGS). We detail how to validate pipeline performance and provide the bioinformatics pipeline for groups interested in using it. Using this optimized pipeline, we detect hundreds of distinct deletion junctions generated during infection with a diverse panel of influenza viruses and use these data to test a long-standing hypothesis concerning the molecular details of DIP formation.

Do images of 'watching eyes' induce behaviour that is more pro-social or more normative? A field experiment on littering.

Displaying images of eyes causes people to behave more pro-socially in a variety of contexts. However, it is unclear whether eyes work by making people universally more pro-social, or by making them more likely to conform to local norms. If the latter, images of eyes could sometimes make people less pro-social if pro-social behaviour is not the local norm. To separate these hypotheses we conducted a field experiment in which we explored whether manipulating a local descriptive norm altered the eyes effect. We recorded litter dropping decisions on a university campus in a 2 x 2 design, comparing situations with and without litter already on the ground (a manipulation of the local descriptive norm) and with and without large signs displaying images of watching eyes. We additionally recorded the number of potential human observers in the vicinity at the time of each littering decision. We observed a norm effect: the presence of litter on the ground increased littering, replicating previous findings. We also found that images of watching eyes reduced littering, although contrary to previous findings this was only when there were larger numbers of people around. With regard to our central aim, we found no evidence that litter on the ground interacted non-additively with images of eyes to induce increased littering behaviour. Our data therefore support the hypothesis that images of eyes induce more pro-social behaviour, independent of local norms. This finding has positive implications for the application of eye images in combating anti-social behaviour.