scCross: efficient search for rare subpopulations across multiple single-cell samples.

MOTIVATION: Identifying rare cell types is an important task to capture the heterogeneity of single-cell data, such as scRNA-seq. The widespread availability of such data enables to aggregate multiple samples, corresponding for example to different donors, into the same study. Yet, such aggregated data is often subject to batch effects between samples. Clustering it therefore generally requires the use of data integration methods, which can lead to overcorrection, making the identification of rare cells difficult. We present scCross, a biclustering method identifying rare subpopulations of cells present across multiple single-cell samples. It jointly identifies a group of cells with specific marker genes by relying on a global sum criterion, computed over entire subpopulation of cells, rather than pairwise comparisons between individual cells. This proves robust with respect to the high variability of scRNA-seq data, in particular batch effects. RESULTS: We show through several case studies that scCross is able to identify rare subpopulations across multiple samples without performing prior data integration. Namely, it identifies a cilium subpopulation with potential new ciliary genes from lung cancer cells, which is not detected by typical alternatives. It also highlights rare subpopulations in human pancreas samples sequenced with different protocols, despite visible shifts in expression levels between batches. We further show that scCross outperforms typical alternatives at identifying a target rare cell type in a controlled experiment with artificially created batch effects. This shows the ability of scCross to efficiently identify rare cell subpopulations characterized by specific genes despite the presence of batch effects. AVAILABILITY AND IMPLEMENTATION: The R and Scala implementation of scCross is freely available on GitHub, at https://github.com/agerniers/scCross/. A snapshot of the code and the data underlying this article are available on Zenodo, at https://zenodo.org/doi/10.5281/zenodo.10471063.

A multidisciplinary approach to estimating wolf population size for long-term conservation.

The wolf (Canis lupus) is among the most controversial of wildlife species. Abundance estimates are required to inform public debate and policy decisions, but obtaining them at biologically relevant scales is challenging. We developed a system for comprehensive population estimation across the Italian alpine region (100,000 km2 ), involving 1513 trained operators representing 160 institutions. This extensive network allowed for coordinated genetic sample collection and landscape-level spatial capture-recapture analyses that transcended administrative boundaries to produce the first estimates of key parameters for wolf population status assessment. Wolf abundance was estimated at 952 individuals (95% credible interval 816-1120) and 135 reproductive units (i.e., packs) (95% credible interval 112-165). We also estimated that mature individuals accounted for 33-45% of the entire population. The monitoring effort was spatially estimated thereby overcoming an important limitation of citizen science data. This is an important approach for promoting wolf-human coexistence based on wolf abundance monitoring and an endorsement of large-scale harmonized conservation practices.

Una estrategia multidisciplinaria para la estimación del tamaño poblacional de los lobos para la conservación a largo plazo Resumen El lobo (Canis lupus) está entre las especies de fauna más controversiales. Se requieren estimaciones de abundancia para informar al debate público y las decisiones políticas, pero es un reto obtenerlos en escalas con relevancia biológica. Desarrollamos un sistema para la estimación completa de la población en la región alpina de Italia (100,000 km2 ), con la participación de 1,513 operadores entrenados que representan a 160 instituciones. Esta red extensa permitió una colecta coordinada de muestras genéticas y análisis de captura-recaptura espacial que trascendieron las fronteras administrativas para así producir las primeras estimaciones de los parámetros clave para la evaluación del estado de la población de los lobos. Se estimó la abundancia en 952 individuos (95% intervalo de confianza 816-1120) y 135 unidades reproductivas (es decir, manadas) (95% intervalo de confianza 112-165). También estimamos que los individuos maduros representaban el 33-45% de toda la población. El esfuerzo de monitoreo se estimó espacialmente, por lo que sobrepasó una limitación importante de la ciencia ciudadana. Esta estrategia es importante para promover la coexistencia entre lobos y humanos con base en el monitoreo de la abundancia y el apoyo a las prácticas armonizadas de conservación a gran escala.

Estimating and forecasting spatial population dynamics of apex predators using transnational genetic monitoring.

The ongoing recovery of terrestrial large carnivores in North America and Europe is accompanied by intense controversy. On the one hand, reestablishment of large carnivores entails a recovery of their most important ecological role, predation. On the other hand, societies are struggling to relearn how to live with apex predators that kill livestock, compete for game species, and occasionally injure or kill people. Those responsible for managing these species and mitigating conflict often lack fundamental information due to a long-standing challenge in ecology: How do we draw robust population-level inferences for elusive animals spread over immense areas? Here we showcase the application of an effective tool for spatially explicit tracking and forecasting of wildlife population dynamics at scales that are relevant to management and conservation. We analyzed the world's largest dataset on carnivores comprising more than 35,000 noninvasively obtained DNA samples from over 6,000 individual brown bears (Ursus arctos), gray wolves (Canis lupus), and wolverines (Gulo gulo). Our analyses took into account that not all individuals are detected and, even if detected, their fates are not always known. We show unequivocal quantitative evidence of large carnivore recovery in northern Europe, juxtaposed with the finding that humans are the single-most important factor driving the dynamics of these apex predators. We present maps and forecasts of the spatiotemporal dynamics of large carnivore populations, transcending national boundaries and management regimes.

MicroCellClust: mining rare and highly specific subpopulations from single-cell expression data.

MOTIVATION: Identifying rare subpopulations of cells is a critical step in order to extract knowledge from single-cell expression data, especially when the available data is limited and rare subpopulations only contain a few cells. In this paper, we present a data mining method to identify small subpopulations of cells that present highly specific expression profiles. This objective is formalized as a constrained optimization problem that jointly identifies a small group of cells and a corresponding subset of specific genes. The proposed method extends the max-sum submatrix problem to yield genes that are, for instance, highly expressed inside a small number of cells, but have a low expression in the remaining ones. RESULTS: We show through controlled experiments on scRNA-seq data that the MicroCellClust method achieves a high F1 score to identify rare subpopulations of artificially planted human T cells. The effectiveness of MicroCellClust is confirmed as it reveals a subpopulation of CD4 T cells with a specific phenotype from breast cancer samples, and a subpopulation linked to a specific stage in the cell cycle from breast cancer samples as well. Finally, three rare subpopulations in mouse embryonic stem cells are also identified with MicroCellClust. These results illustrate the proposed method outperforms typical alternatives at identifying small subsets of cells with highly specific expression profiles. AVAILABILITYAND IMPLEMENTATION: The R and Scala implementation of MicroCellClust is freely available on GitHub, at https://github.com/agerniers/MicroCellClust/ The data underlying this article are available on Zenodo, at https://dx.doi.org/10.5281/zenodo.4580332. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Efficient spatial multi-state capture-recapture model to study natal dispersal: An application to the Alpine marmot.

Studying natal dispersal in natural populations using capture-recapture data is challenging as an unknown proportion of individuals leaves the study area when dispersing and are never recaptured. Most dispersal (and survival) estimates from capture-recapture studies are thus biased and only reflect what happens within the study area, not the population. Here, we elaborate on recent methodological advances to build a spatially explicit multi-state capture-recapture model to study natal dispersal in a territorial mammal while accounting for imperfect detection and movement in and out of the study area. We validate our model using a simulation study where we compare it to a non-spatial multi-state capture-recapture model. We then apply it to a long-term individual-based dataset on Alpine marmot Marmota marmota. Our model was able to accurately estimate natal dispersal and survival probabilities, as well as mean dispersal distance for a large range of dispersal patterns. By contrast, the non-spatial multi-state estimates underestimated both survival and natal dispersal even for short dispersal distances relative to the study area size. We discuss the application of our approach to other species and monitoring setups. We estimated higher inheritance probabilities of female Alpine marmots, which suggests higher levels of philopatry, although the probability to become dominant after dispersal did not differ between sexes. Nonetheless, the lower survival of young adult males suggests higher costs of dispersal for males. We further discuss the implications of our findings in light of the life history of the species.

Continuum Robots for Medical Interventions.

Continuum robots are not constructed with discrete joints but, instead, change shape and position their tip by flexing along their entire length. Their narrow curvilinear shape makes them well suited to passing through body lumens, natural orifices, or small surgical incisions to perform minimally invasive procedures. Modeling and controlling these robots are, however, substantially more complex than traditional robots comprised of rigid links connected by discrete joints. Furthermore, there are many approaches to achieving robot flexure. Each presents its own design and modeling challenges, and to date, each has been pursued largely independently of the others. This article attempts to provide a unified summary of the state of the art of continuum robot architectures with respect to design for specific clinical applications. It also describes a unifying framework for modeling and controlling these systems while additionally explaining the elements unique to each architecture. The major research accomplishments are described for each topic and directions for the future progress needed to achieve widespread clinical use are identified.

Estimating red fox density using non-invasive genetic sampling and spatial capture-recapture modelling.

Spatial capture-recapture modelling (SCR) is a powerful tool for estimating density, population size, and space use of elusive animals. Here, we applied SCR modelling to non-invasive genetic sampling (NGS) data to estimate red fox (Vulpes vulpes) densities in two areas of boreal forest in central (2016-2018) and southern Norway (2017-2018). Estimated densities were overall lower in the central study area (mean = 0.04 foxes per km2 in 2016, 0.10 in 2017, and 0.06 in 2018) compared to the southern study area (0.16 in 2017 and 0.09 in 2018). We found a positive effect of forest cover on density in the central, but not the southern study area. The absence of an effect in the southern area may reflect a paucity of evidence caused by low variation in forest cover. Estimated mean home-range size in the central study area was 45 km2 [95%CI 34-60] for females and 88 km2 [69-113] for males. Mean home-range sizes were smaller in the southern study area (26 km2 [16-42] for females and 56 km2 [35-91] for males). In both study areas, detection probability was session-dependent and affected by sampling effort. This study highlights how SCR modelling in combination with NGS can be used to efficiently monitor red fox populations, and simultaneously incorporate ecological factors and estimate their effects on population density and space use.

RNA stable isotope probing and high-throughput sequencing to identify active microbial community members in a methane-driven denitrifying biofilm.

AIMS: Aerobic methane oxidation coupled to denitrification (AME-D) is a promising process for removing nitrate from groundwater and yet its microbial mechanism and ecological implications are not fully understood. This study used RNA stable isotope probing (RNA-SIP) and high-throughput sequencing to identify the micro-organisms that are actively involved in aerobic methane oxidation within a denitrifying biofilm. METHODS AND RESULTS: Two RNA-SIP experiments were conducted to investigate labelling of RNA and methane monooxygenase (pmoA) transcripts when exposed to 13 C-labelled methane over a 96-hour time period and to determine active bacteria involved in methane oxidation in a denitrifying biofilm. A third experiment was performed to ascertain the extent of 13 C labelling of RNA using isotope ratio mass spectrometry (IRMS). All experiments used biofilm from an established packed bed reactor. IRMS confirmed 13 C enrichment of the RNA. The RNA-SIP experiments confirmed selective enrichment by the shift of pmoA transcripts into heavier fractions over time. Finally, high-throughput sequencing identified the active micro-organisms enriched with 13 C. CONCLUSIONS: Methanotrophs (Methylovulum spp. and Methylocystis spp.), methylotrophs (Methylotenera spp.) and denitrifiers (Hyphomicrobium spp.) were actively involved in AME-D. SIGNIFICANCE AND IMPACT OF THE STUDY: This is the first study to use RNA-SIP and high-throughput sequencing to determine the bacteria active within an AME-D community.

Eccentric Tube Robots as Multiarmed Steerable Sheaths.

This paper presents a novel continuum robot sheath for use in single-port minimally invasive procedures such as neuroendoscopy in which the sheath is designed to deliver multiple robotic arms. Actuation of the sheath is achieved by using precurved superelastic tubes lining the working channels used for arm delivery. These tubes perform a similar role to push/pull tendons, but can accomplish shape change of the sheath via rotation. A kinematic model using Cosserat rod theory is derived which is based on modeling the system as a set of eccentrically aligned precurved tubes constrained along their length by an elastic backbone. The specific case of a two-arm sheath is considered in detail. Simulation and experiments are used to investigate the validate the concept and model.

In Vivo Molding of Airway Stents.

Like ready-to-wear clothing, medical devices come in a fixed set of sizes. While this may accommodate a large fraction of the patient population, others must either experience suboptimal results due to poor sizing or must do without the device. Although techniques have been proposed to fabricate patient-specific devices in advance of a procedure, this process is expensive and time consuming. An alternative solution that provides every patient with a tailored fit is to create devices that can be customized to the patient's anatomy as they are delivered. This paper reports an in vivo molding process in which a soft flexible photocurable stent is delivered into the trachea or bronchi over a UV-transparent balloon. The balloon is expanded such that the stent conforms to the varying cross-sectional shape of the airways. UV light is then delivered through the balloon curing the stent into its expanded conformal shape. The potential of this method is demonstrated using phantom, ex vivo and in vivo experiments. This approach can produce stents providing equivalent airway support to those made from standard materials while providing a customized fit.

Genome Typing and Epidemiology of Human Listeriosis in New Zealand, 1999 to 2018.

This study describes the epidemiology of listeriosis in New Zealand between 1999 and 2018 as well as the retrospective whole-genome sequencing (WGS) of 453 Listeria monocytogenes isolates corresponding to 95% of the human cases within this period. The average notified rate of listeriosis was 0.5 cases per 100,000 population, and non-pregnancy-associated cases were more prevalent than pregnancy-associated cases (averages of 19 and 5 cases per annum, respectively). WGS data was assessed using multilocus sequencing typing (MLST), including core-genome and whole-genome MLST (cgMLST and wgMLST, respectively) and single-nucleotide polymorphism (SNP) analysis. Thirty-nine sequence types (STs) were identified, with the most common being ST1 (21.9%), ST4 (13.2%), ST2 (11.3%), ST120 (6.1%), and ST155 (6.4%). A total of 291 different cgMLST types were identified, with the majority (n = 243) of types observed as a single isolate, consistent with the observation that listeriosis is predominately sporadic. Among the 49 cgMLST types containing two or more isolates, 18 cgMLST types were found with 2 to 4 isolates each (50 isolates in total, including three outbreak-associated isolates) that shared low genetic diversity (0 to 2 whole-genome alleles), some of which were dispersed in time or geographical regions. SNP analysis also produced results comparable to those from wgMLST. The low genetic diversity within these clusters suggests a potential common source, but incomplete epidemiological data impaired retrospective epidemiological investigations. Prospective use of WGS analysis together with thorough exposure information from cases could potentially identify future outbreaks more rapidly, including those that may have been undetected for some time over different geographical regions.

GPS collars have an apparent positive effect on the survival of a large carnivore.

Are instrumented animals representative of the population, given the potential bias caused by selective sampling and the influence of capture, handling and wearing bio-loggers? The answer is elusive owing to the challenges of obtaining comparable data from individuals with and without bio-loggers. Using non-invasive genetic data of a large carnivore, the wolverine (Gulo gulo) in Scandinavia, and an open-population spatial capture-recapture model, we found a 16 (credible interval: 4-30) percentage points lower mortality probability for GPS-collared individuals compared with individuals without GPS collars. While the risk of dying from legal culling was comparable for collared and non-collared wolverines, the former experienced lower probability of mortality due to causes other than legal culling. The aforementioned effect was pronounced despite a potentially lower age-and therefore likely higher natural mortality-of collared individuals. Reports of positive effects of bio-loggers on the survival of individuals are uncommon and we argue that GPS collars could shield animals from poaching. Our results highlight the challenges of drawing population-level inferences for populations subjected to poaching when using data from instrumented individuals.

Repeat elements organise 3D genome structure and mediate transcription in the filamentous fungus Epichloë festucae.

Structural features of genomes, including the three-dimensional arrangement of DNA in the nucleus, are increasingly seen as key contributors to the regulation of gene expression. However, studies on how genome structure and nuclear organisation influence transcription have so far been limited to a handful of model species. This narrow focus limits our ability to draw general conclusions about the ways in which three-dimensional structures are encoded, and to integrate information from three-dimensional data to address a broader gamut of biological questions. Here, we generate a complete and gapless genome sequence for the filamentous fungus, Epichloë festucae. We use Hi-C data to examine the three-dimensional organisation of the genome, and RNA-seq data to investigate how Epichloë genome structure contributes to the suite of transcriptional changes needed to maintain symbiotic relationships with the grass host. Our results reveal a genome in which very repeat-rich blocks of DNA with discrete boundaries are interspersed by gene-rich sequences that are almost repeat-free. In contrast to other species reported to date, the three-dimensional structure of the genome is anchored by these repeat blocks, which act to isolate transcription in neighbouring gene-rich regions. Genes that are differentially expressed in planta are enriched near the boundaries of these repeat-rich blocks, suggesting that their three-dimensional orientation partly encodes and regulates the symbiotic relationship formed by this organism.

DsEcp2-1 is a polymorphic effector that restricts growth of Dothistroma septosporum in pine.

The detrimental effect of fungal pathogens on forest trees is an increasingly important problem that has implications for the health of our planet. Despite this, the study of molecular plant-microbe interactions in forest trees is in its infancy, and very little is known about the roles of effector molecules from forest pathogens. Dothistroma septosporum causes a devastating needle blight disease of pines, and intriguingly, is closely related to Cladosporium fulvum, a tomato pathogen in which pioneering effector biology studies have been carried out. Here, we studied D. septosporum effectors that are shared with C. fulvum, by comparing gene sequences from global isolates of D. septosporum and assessing effector function in both host and non-host plants. Many of the effectors were predicted to be non-functional in D. septosporum due to their pseudogenization or low expression in planta, suggesting adaptation to lifestyle and host. Effector sequences were polymorphic among a global collection of D. septosporum isolates, but there was no evidence for positive selection. The DsEcp2-1 effector elicited cell death in the non-host plant Nicotiana tabacum, whilst D. septosporum DsEcp2-1 mutants showed increased colonization of pine needles. Together these results suggest that DsEcp2-1 might be recognized by an immune receptor in both angiosperm and gymnosperm plants. This work may lead to the identification of plant targets for DsEcp2-1 that will provide much needed information on the molecular basis of gymnosperm-pathogen interactions in forests, and may also lead to novel methods of disease control.

Identifying gene-specific subgroups: an alternative to biclustering.

BACKGROUND: Transcriptome analysis aims at gaining insight into cellular processes through discovering gene expression patterns across various experimental conditions. Biclustering is a standard approach to discover genes subsets with similar expression across subgroups of samples to be identified. The result is a set of biclusters, each forming a specific submatrix of rows (e.g. genes) and columns (e.g. samples). Relevant biclusters can, however, be missed when, due to the presence of a few outliers, they lack the assumed homogeneity of expression values among a few gene/sample combinations. The Max-Sum SubMatrix problem addresses this issue by looking at highly expressed subsets of genes and of samples, without enforcing such homogeneity. RESULTS: We present here the K-CPGC algorithm to identify K relevant submatrices. Our main contribution is to show that this approach outperforms biclustering algorithms to identify several gene subsets representative of specific subgroups of samples. Experiments are conducted on 35 gene expression datasets from human tissues and yeast samples. We report comparative results with those obtained by several biclustering algorithms, including CCA, xMOTIFs, ISA, QUBIC, Plaid and Spectral. Gene enrichment analysis demonstrates the benefits of the proposed approach to identify more statistically significant gene subsets. The most significant Gene Ontology terms identified with K-CPGC are shown consistent with the controlled conditions of each dataset. This analysis supports the biological relevance of the identified gene subsets. An additional contribution is the statistical validation protocol proposed here to assess the relative performances of biclustering algorithms and of the proposed method. It relies on a Friedman test and the Hochberg's sequential procedure to report critical differences of ranks among all algorithms. CONCLUSIONS: We propose here the K-CPGC method, a computationally efficient algorithm to identify K max-sum submatrices in a large gene expression matrix. Comparisons show that it identifies more significantly enriched subsets of genes and specific subgroups of samples which are easily interpretable by biologists. Experiments also show its ability to identify more reliable GO terms. These results illustrate the benefits of the proposed approach in terms of interpretability and of biological enrichment quality. Open implementation of this algorithm is available as an R package.

Chromatin-level regulation of the fragmented dothistromin gene cluster in the forest pathogen Dothistroma septosporum.

Genes required for fungal secondary metabolite production are usually clustered, co-regulated and expressed in stationary growth phase. Chromatin modification has an important role in co-regulation of secondary metabolite genes. The virulence factor dothistromin, a relative of aflatoxin, provided a unique opportunity to study chromatin level regulation in a highly fragmented gene cluster that is switched on during early exponential growth phase. We analysed three histone modification marks by ChIP-qPCR and gene deletion in the pine pathogen Dothistroma septosporum to determine their effects on dothistromin gene expression across a time course and at different loci of the dispersed gene cluster. Changes in gene expression and dothistromin production were associated with changes in histone marks, with higher acetylation (H3K9ac) and lower methylation (H3K9me3, H3K27me3) during early exponential phase at the onset of dothistromin production. But while H3K27me3 directly influenced dothistromin genes dispersed across chromosome 12, effects of H3K9 acetylation and methylation were orchestrated mainly through a centrally located pathway regulator gene DsAflR. These results revealed that secondary metabolite production can be controlled at the chromatin-level despite the genes being dispersed. They also suggest that patterns of chromatin modification are important in adaptation of a virulence factor for a specific role in planta.

Complex epigenetic regulation of alkaloid biosynthesis and host interaction by heterochromatin protein I in a fungal endophyte-plant symbiosis.

Epichloë festucae forms mutualistic symbiotic interactions with grasses of the Lolium and Festuca genera. Protection from insect and mammalian herbivory are the best-documented host benefits of these associations. The two main classes of anti-mammalian alkaloids synthesized by E. festucae are the ergot alkaloids and indole diterpenes, of which ergovaline and lolitrems are the principal terminal products. Synthesis of both metabolites require multiple gene products encoded by clusters of 11 genes located at the subtelomeric regions of chromosomes I and III respectively. These loci are essentially unexpressed in axenic culture but among the most highly expressed genes in planta. We show here that heterochromatin 1 protein (HepA) is an important component of the regulatory machinery that maintains these loci in a silent state in culture. Deletion of this gene led to derepression of eas and ltm gene expression under non-symbiotic culture conditions. Although there was no obvious culture phenotype, RNAseq analysis revealed that around 1000 genes were differentially expressed in the ΔhepA mutant compared to wild type with just one-third upregulated. Inoculation of the ΔhepA mutants into seedlings of Lolium perenne led to a severe host interaction phenotype characterized by a reduction in tiller length but an increase in tiller number. Hyphae within the leaves of these associations were much more abundant in the intercellular spaces of the leaves and aberrantly colonized the vascular bundles. This physiological change was accompanied by a dramatic change in the transcriptome with around 900 genes differentially expressed, with two thirds of these upregulated. This major physiological change was accompanied by a decrease in ltm gene expression and loss of the ability to synthesize lolitrems. These results show that HepA has an important role in controlling the chromatin state of these sub-telomeric secondary metabolite genes, including their symbiosis-specific regulation.

Modeling Tube Clearance and Bounding the Effect of Friction in Concentric Tube Robot Kinematics.

The shape of a concentric tube robot depends not only on the relative rotations and translations of its constituent tubes, but also on the history of relative tube displacements. Existing mechanics-based models neglect all history-dependent phenomena with the result that when calibrated on experimental data collected over a robot's workspace, the maximum tip position error can exceed 8 mm for a 200-mm-long robot. In this paper, we develop a model that computes the bounding kinematic solutions in which Coulomb friction is acting either to maximize or minimize the relative twisting between each pair of contacting tubes. The path histories associated with these limiting cases correspond to first performing all tube translations and then performing relative tube rotations of sufficient angle so that the maximum Coulomb friction force is obtained along the interface of each contacting tube pair. The robot tip configurations produced by these path histories are shown experimentally to bound position error with respect to the estimated frictionless model compared to path histories comprised of translation or mixed translation and rotation. Intertube friction forces and torques are computed as proportional to the intertube contact forces. To compute these contact forces, the standard zero-clearance assumption that constrains the concentrically combined tubes to possess the same centerline is relaxed. The effects of clearance and friction are explored through numerical and physical experiments and it is shown that friction can explain much of the prediction error observed in existing models. This model is not intended for real-time control, but rather for path planning-to provide error bounds and to inform how the ordering of tube rotations and translations can be used to reduce the effect of friction.

Steering a Multi-armed Robotic Sheath Using Eccentric Precurved Tubes.

This paper presents a novel continuum robot sheath for use in single-port minimally invasive procedures such as neuroendoscopy in which the sheath is designed to deliver multiple robotic arms. Articulation of the sheath is achieved by using precurved superelastic tubes lining the working channels used for arm delivery. These tubes perform a similar role to push/pull tendons, but can accomplish shape change of the sheath via rotation as well as translation. A kinematic model using Cosserat rod theory is derived which is based on modeling the system as a set of eccentrically aligned precurved tubes constrained along their length by an elastic backbone. The specific case of a two-arm sheath is considered in detail and its relationship to a concentric tube balanced pair is described. Simulation and experiment are used to investigate the concept, map its workspace and to evaluate the kinematic model.

Host Tissue Environment Directs Activities of an Epichloë Endophyte, While It Induces Systemic Hormone and Defense Responses in Its Native Perennial Ryegrass Host.

Increased resilience of pasture grasses mediated by fungal Epichloë endophytes is crucial to pastoral industries. The underlying mechanisms are only partially understood and likely involve very different activities of the endophyte in different plant tissues and responses of the plant to these. We analyzed the transcriptomes of Epichloë festucae and its host, Lolium perenne, in host tissues of different function and developmental stages. The endophyte contributed approximately 10× more to the transcriptomes than to the biomass of infected tissues. Proliferating mycelium in growing host tissues highly expressed genes involved in hyphal growth. Nonproliferating mycelium in mature plant tissues, transcriptionally equally active, highly expressed genes involved in synthesizing antiherbivore compounds. Transcripts from the latter accounted for 4% of fungal transcripts. Endophyte infection systemically but moderately increased transcription of L. perenne genes with roles in hormone biosynthesis and perception as well as stress and pathogen resistance while reducing expression of genes involved in photosynthesis. There was a good correlation between transcriptome-based observations and physiological observations. Our data indicate that the fitness-enhancing effects of the endophyte are based both on its biosynthetic activities, predominantly in mature host tissues, and also on systemic alteration of the host's hormonal responses and induction of stress response genes. [Formula: see text] Copyright © 2017 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .